Sample records for als point clouds
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Object-Based Coregistration of Terrestrial Photogrammetric and ALS Point Clouds in Forested Areas
NASA Astrophysics Data System (ADS)
Polewski, P.; Erickson, A.; Yao, W.; Coops, N.; Krzystek, P.; Stilla, U.
2016-06-01
Airborne Laser Scanning (ALS) and terrestrial photogrammetry are methods applicable for mapping forested environments. While ground-based techniques provide valuable information about the forest understory, the measured point clouds are normally expressed in a local coordinate system, whose transformation into a georeferenced system requires additional effort. In contrast, ALS point clouds are usually georeferenced, yet the point density near the ground may be poor under dense overstory conditions. In this work, we propose to combine the strengths of the two data sources by co-registering the respective point clouds, thus enriching the georeferenced ALS point cloud with detailed understory information in a fully automatic manner. Due to markedly different sensor characteristics, coregistration methods which expect a high geometric similarity between keypoints are not suitable in this setting. Instead, our method focuses on the object (tree stem) level. We first calculate approximate stem positions in the terrestrial and ALS point clouds and construct, for each stem, a descriptor which quantifies the 2D and vertical distances to other stem centers (at ground height). Then, the similarities between all descriptor pairs from the two point clouds are calculated, and standard graph maximum matching techniques are employed to compute corresponding stem pairs (tiepoints). Finally, the tiepoint subset yielding the optimal rigid transformation between the terrestrial and ALS coordinate systems is determined. We test our method on simulated tree positions and a plot situated in the northern interior of the Coast Range in western Oregon, USA, using ALS data (76 x 121 m2) and a photogrammetric point cloud (33 x 35 m2) derived from terrestrial photographs taken with a handheld camera. Results on both simulated and real data show that the proposed stem descriptors are discriminative enough to derive good correspondences. Specifically, for the real plot data, 24 corresponding stems were coregistered with an average 2D position deviation of 66 cm.
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NASA Astrophysics Data System (ADS)
Tomljenovic, Ivan; Tiede, Dirk; Blaschke, Thomas
2016-10-01
In the past two decades Object-Based Image Analysis (OBIA) established itself as an efficient approach for the classification and extraction of information from remote sensing imagery and, increasingly, from non-image based sources such as Airborne Laser Scanner (ALS) point clouds. ALS data is represented in the form of a point cloud with recorded multiple returns and intensities. In our work, we combined OBIA with ALS point cloud data in order to identify and extract buildings as 2D polygons representing roof outlines in a top down mapping approach. We performed rasterization of the ALS data into a height raster for the purpose of the generation of a Digital Surface Model (DSM) and a derived Digital Elevation Model (DEM). Further objects were generated in conjunction with point statistics from the linked point cloud. With the use of class modelling methods, we generated the final target class of objects representing buildings. The approach was developed for a test area in Biberach an der Riß (Germany). In order to point out the possibilities of the adaptation-free transferability to another data set, the algorithm has been applied ;as is; to the ISPRS Benchmarking data set of Toronto (Canada). The obtained results show high accuracies for the initial study area (thematic accuracies of around 98%, geometric accuracy of above 80%). The very high performance within the ISPRS Benchmark without any modification of the algorithm and without any adaptation of parameters is particularly noteworthy.
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NASA Astrophysics Data System (ADS)
Lague, D.
2014-12-01
High Resolution Topographic (HRT) datasets are predominantly stored and analyzed as 2D raster grids of elevations (i.e., Digital Elevation Models). Raster grid processing is common in GIS software and benefits from a large library of fast algorithms dedicated to geometrical analysis, drainage network computation and topographic change measurement. Yet, all instruments or methods currently generating HRT datasets (e.g., ALS, TLS, SFM, stereo satellite imagery) output natively 3D unstructured point clouds that are (i) non-regularly sampled, (ii) incomplete (e.g., submerged parts of river channels are rarely measured), and (iii) include 3D elements (e.g., vegetation, vertical features such as river banks or cliffs) that cannot be accurately described in a DEM. Interpolating the raw point cloud onto a 2D grid generally results in a loss of position accuracy, spatial resolution and in more or less controlled interpolation. Here I demonstrate how studying earth surface topography and processes directly on native 3D point cloud datasets offers several advantages over raster based methods: point cloud methods preserve the accuracy of the original data, can better handle the evaluation of uncertainty associated to topographic change measurements and are more suitable to study vegetation characteristics and steep features of the landscape. In this presentation, I will illustrate and compare Point Cloud based and Raster based workflows with various examples involving ALS, TLS and SFM for the analysis of bank erosion processes in bedrock and alluvial rivers, rockfall statistics (including rockfall volume estimate directly from point clouds) and the interaction of vegetation/hydraulics and sedimentation in salt marshes. These workflows use 2 recently published algorithms for point cloud classification (CANUPO) and point cloud comparison (M3C2) now implemented in the open source software CloudCompare.
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Automatic Generation of Building Models with Levels of Detail 1-3
NASA Astrophysics Data System (ADS)
Nguatem, W.; Drauschke, M.; Mayer, H.
2016-06-01
We present a workflow for the automatic generation of building models with levels of detail (LOD) 1 to 3 according to the CityGML standard (Gröger et al., 2012). We start with orienting unsorted image sets employing (Mayer et al., 2012), we compute depth maps using semi-global matching (SGM) (Hirschmüller, 2008), and fuse these depth maps to reconstruct dense 3D point clouds (Kuhn et al., 2014). Based on planes segmented from these point clouds, we have developed a stochastic method for roof model selection (Nguatem et al., 2013) and window model selection (Nguatem et al., 2014). We demonstrate our workflow up to the export into CityGML.
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NASA Astrophysics Data System (ADS)
Possner, A.; Wang, H.; Caldeira, K.; Wood, R.; Ackerman, T. P.
2017-12-01
Aerosol-cloud interactions (ACIs) in marine stratocumulus remain a significant source of uncertainty in constraining the cloud-radiative effect in a changing climate. Ship tracks are undoubted manifestations of ACIs embedded within stratocumulus cloud decks and have proven to be a useful framework to study the effect of aerosol perturbations on cloud morphology, macrophysical, microphyiscal and cloud-radiative properties. However, so far most observational (Christensen et al. 2012, Chen et al. 2015) and numerical studies (Wang et al. 2011, Possner et al. 2015, Berner et al. 2015) have concentrated on ship tracks in shallow boundary layers of depths between 300 - 800 m, while most stratocumulus decks form in significantly deeper boundary layers (Muhlbauer et al. 2014). In this study we investigate the efficacy of aerosol perturbations in deep open and closed cell stratocumulus. Multi-day idealised cloud-resolving simulations are performed for the RF06 flight of the VOCALS-Rex field campaign (Wood et al. 2011). During this flight pockets of deep open and closed cells were observed in a 1410 m deep boundary layer. The efficacy of aerosol perturbations of varied concentration and spatial gradients in altering the cloud micro- and macrophysical state and cloud-radiative effect is determined in both cloud regimes. Our simulations show that a continued point source emission flux of 1.16*1011 particles m-2 s-1 applied within a 300x300 m2 gridbox induces pronounced cloud cover changes in approximately a third of the simulated 80x80 km2 domain, a weakening of the diurnal cycle in the open-cell regime and a resulting increase in domain-mean cloud albedo of 0.2. Furthermore, we contrast the efficacy of equal strength near-surface or above-cloud aerosol perturbations in altering the cloud state.
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NASA Astrophysics Data System (ADS)
Lee, Yeon Joo; Imamura, Takeshi; Maejima, Yasumitsu; Sugiyama, Ko-ichiro
The thick cloud layer of Venus reflects solar radiation effectively, resulting in a Bond albedo of 76% (Moroz et al., 1985). Most of the incoming solar flux is absorbed in the upper cloud layer at 60-70 km altitude. An unknown UV absorber is a major sink of the solar energy at the cloud top level. It produces about 40-60% of the total solar heating near the cloud tops, depending on its vertical structure (Crisp et al., 1986; Lee et al., in preparation). UV images of Venus show a clear difference in morphology between laminar flow shaped clouds on the morning side and convective-like cells on the afternoon side of the planet in the equatorial region (Titov et al., 2012). This difference is probably related to strong solar heating at the cloud tops at the sub-solar point, rather than the influence from deeper level convection in the low and middle cloud layers (Imamura et al., 2014). Also, small difference in cloud top structures may trigger horizontal convection at this altitude, because various cloud top structures can significantly alter the solar heating and thermal cooling rates at the cloud tops (Lee et al., in preparation). Performing radiative forcing calculations for various cloud top structures using a radiative transfer model (SHDOM), we investigate the effect of solar heating at the cloud tops on atmospheric dynamics. We use CReSS (Cloud Resolving Storm Simulator), and consider the altitude range from 35 km to 90 km, covering a full cloud deck.
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Rutzinger, Martin; Höfle, Bernhard; Hollaus, Markus; Pfeifer, Norbert
2008-01-01
Airborne laser scanning (ALS) is a remote sensing technique well-suited for 3D vegetation mapping and structure characterization because the emitted laser pulses are able to penetrate small gaps in the vegetation canopy. The backscattered echoes from the foliage, woody vegetation, the terrain, and other objects are detected, leading to a cloud of points. Higher echo densities (>20 echoes/m2) and additional classification variables from full-waveform (FWF) ALS data, namely echo amplitude, echo width and information on multiple echoes from one shot, offer new possibilities in classifying the ALS point cloud. Currently FWF sensor information is hardly used for classification purposes. This contribution presents an object-based point cloud analysis (OBPA) approach, combining segmentation and classification of the 3D FWF ALS points designed to detect tall vegetation in urban environments. The definition tall vegetation includes trees and shrubs, but excludes grassland and herbage. In the applied procedure FWF ALS echoes are segmented by a seeded region growing procedure. All echoes sorted descending by their surface roughness are used as seed points. Segments are grown based on echo width homogeneity. Next, segment statistics (mean, standard deviation, and coefficient of variation) are calculated by aggregating echo features such as amplitude and surface roughness. For classification a rule base is derived automatically from a training area using a statistical classification tree. To demonstrate our method we present data of three sites with around 500,000 echoes each. The accuracy of the classified vegetation segments is evaluated for two independent validation sites. In a point-wise error assessment, where the classification is compared with manually classified 3D points, completeness and correctness better than 90% are reached for the validation sites. In comparison to many other algorithms the proposed 3D point classification works on the original measurements directly, i.e. the acquired points. Gridding of the data is not necessary, a process which is inherently coupled to loss of data and precision. The 3D properties provide especially a good separability of buildings and terrain points respectively, if they are occluded by vegetation. PMID:27873771
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Six Martian years of CO2 clouds survey by OMEGA/MEx.
NASA Astrophysics Data System (ADS)
Gondet, Brigitte; bibring, Jean-Pierre; Vincendon, Mathieu
2014-05-01
Mesospheric clouds have been detected first from Earth (Bell et al 1996 [1]), then from Mars orbit (MGS/TES and MOC, Clancy et al 1998 [2]). Their composition (CO2) was inferred from temperature. Similar detection and temperature-inferred composition was then performed by Spicam and PFS on board Mars Express (Monmessin et al [3], Formisano et al [4]., 2006). The first direct detection and characterization (altitude, composition, velocity) was performed by OMEGA/ Mars Express (then coupled to HRSC/ Mars Express, and confirmed by CRISM/MRO (Montmessin et al. [5], 2007, Maattanen et al [6]., Scholten et al. [7], 2010, Vincendon et al [8]., 2011). Omega is a very powerful tool for the study of CO2 clouds as it is able to unambiguously identify the CO2 composition of a cloud based on a near-IR spectral feature located at 4.26 μm [5],. Therefore since the beginning of the Mars Express mission (2004) OMEGA as done a systematic survey of these mesospheric clouds. Thanks to the orbit of Mars Express, we can observe this clouds from different altitudes (from apocenter to pericenter) and at different local times. We will present the result of 6 Martians years of observations and point out a correlation with the dust activity. We also observe that their time of appearance/disappearance varies slightly from year to year. We will mention also the existence of mesospheric H2O clouds. References [1] JF Bell. et al. JGR 1996; [2] RT Clancy et al., GRL 1998 [3] F. Montmessin et al. JGR 2006; [4] V. Formisano et al., Icarus 2006; [5] F. Montmessin et al JGR 2007 [6] A. Määttänen et al. Icarus 2010; [7] F. Scholten et al. PSS 2010; [8] M. Viencendon et al. JGR 2011
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Mesospheric CO2 Clouds at Mars: Seven Martian Years Survey by OMEGA/MEX
NASA Astrophysics Data System (ADS)
Gondet, Brigitte; Bibring, Jean-Pierre
2016-04-01
Mesospheric clouds have been detected first from Earth (Bell et al 1996 [1]), then from Mars orbit (MGS/TES and MOC, Clancy et al 1998 [2]). Their composition (CO2) was inferred from temperature. Similar detection and temperature-inferred composition was then performed by Spicam and PFS on board Mars Express (Monmessin et al [3], Formisano et al [4]. 2006). The first direct detection and characterization (altitude, composition, velocity) was performed by OMEGA/ Mars Express (then coupled to HRSC/ Mars Express, and confirmed by CRISM/MRO (Montmessin et al. [5], 2007, Maattanen et al [6]. Scholten et al. [7], 2010, Vincendon et al [8], 2011). Omega is a very powerful tool for the study of CO2 clouds as it is able to unambiguously identify the CO2 composition of a cloud based on a near-IR spectral feature located at 4.26 μm [5] Therefore since the beginning of the Mars Express mission (2004) OMEGA as done a systematic survey of these mesospheric clouds. Thanks to the orbit of Mars Express, we can observe this clouds from different altitudes (from apocenter to pericenter) and at different local times. We will present the result of 7 Martians years of observations, point out a correlation with the dust activity and an irregular concentration of clouds from years to years. References [1] JF Bell. et al. JGR 1996; [2] RT Clancy et al., GRL 1998 [3] F. Montmessin et al. JGR 2006; [4] V. Formisano et al., Icarus 2006; [5] F. Montmessin et al JGR 2007 [6] A. Määttänen et al. Icarus 2010; [7] F. Scholten et al. PSS 2010; [8] M. Viencendon et al. JGR 2011
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NASA Astrophysics Data System (ADS)
Amiri, N.; Polewski, P.; Yao, W.; Krzystek, P.; Skidmore, A. K.
2017-09-01
Airborne Laser Scanning (ALS) is a widespread method for forest mapping and management purposes. While common ALS techniques provide valuable information about the forest canopy and intermediate layers, the point density near the ground may be poor due to dense overstory conditions. The current study highlights a new method for detecting stems of single trees in 3D point clouds obtained from high density ALS with a density of 300 points/m2. Compared to standard ALS data, due to lower flight height (150-200 m) this elevated point density leads to more laser reflections from tree stems. In this work, we propose a three-tiered method which works on the point, segment and object levels. First, for each point we calculate the likelihood that it belongs to a tree stem, derived from the radiometric and geometric features of its neighboring points. In the next step, we construct short stem segments based on high-probability stem points, and classify the segments by considering the distribution of points around them as well as their spatial orientation, which encodes the prior knowledge that trees are mainly vertically aligned due to gravity. Finally, we apply hierarchical clustering on the positively classified segments to obtain point sets corresponding to single stems, and perform ℓ1-based orthogonal distance regression to robustly fit lines through each stem point set. The ℓ1-based method is less sensitive to outliers compared to the least square approaches. From the fitted lines, the planimetric tree positions can then be derived. Experiments were performed on two plots from the Hochficht forest in Oberösterreich region located in Austria.We marked a total of 196 reference stems in the point clouds of both plots by visual interpretation. The evaluation of the automatically detected stems showed a classification precision of 0.86 and 0.85, respectively for Plot 1 and 2, with recall values of 0.7 and 0.67.
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NASA Astrophysics Data System (ADS)
Pilarska, M.
2018-05-01
Airborne laser scanning (ALS) is a well-known and willingly used technology. One of the advantages of this technology is primarily its fast and accurate data registration. In recent years ALS is continuously developed. One of the latest achievements is multispectral ALS, which consists in obtaining simultaneously the data in more than one laser wavelength. In this article the results of the dual-wavelength ALS data classification are presented. The data were acquired with RIEGL VQ-1560i sensor, which is equipped with two laser scanners operating in different wavelengths: 532 nm and 1064 nm. Two classification approaches are presented in the article: classification, which is based on geometric relationships between points and classification, which mostly relies on the radiometric properties of registered objects. The overall accuracy of the geometric classification was 86 %, whereas for the radiometric classification it was 81 %. As a result, it can be assumed that the radiometric features which are provided by the multispectral ALS have potential to be successfully used in ALS point cloud classification.
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Sun, Mei; Wu, Qianghua
2010-04-15
A cloud point extraction (CPE) method for the preconcentration of ultra-trace aluminum in human albumin prior to its determination by graphite furnace atomic absorption spectrometry (GFAAS) had been developed in this paper. The CPE method was based on the complex of Al(III) with 1-(2-pyridylazo)-2-naphthol (PAN) and Triton X-114 was used as non-ionic surfactant. The main factors affecting cloud point extraction efficiency, such as pH of solution, concentration and kind of complexing agent, concentration of non-ionic surfactant, equilibration temperature and time, were investigated in detail. An enrichment factor of 34.8 was obtained for the preconcentration of Al(III) with 10 mL solution. Under the optimal conditions, the detection limit of Al(III) was 0.06 ng mL(-1). The relative standard deviation (n=7) of sample was 3.6%, values of recovery of aluminum were changed from 92.3% to 94.7% for three samples. This method is simple, accurate, sensitive and can be applied to the determination of ultra-trace aluminum in human albumin. 2009 Elsevier B.V. All rights reserved.
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Analysis of 3d Building Models Accuracy Based on the Airborne Laser Scanning Point Clouds
NASA Astrophysics Data System (ADS)
Ostrowski, W.; Pilarska, M.; Charyton, J.; Bakuła, K.
2018-05-01
Creating 3D building models in large scale is becoming more popular and finds many applications. Nowadays, a wide term "3D building models" can be applied to several types of products: well-known CityGML solid models (available on few Levels of Detail), which are mainly generated from Airborne Laser Scanning (ALS) data, as well as 3D mesh models that can be created from both nadir and oblique aerial images. City authorities and national mapping agencies are interested in obtaining the 3D building models. Apart from the completeness of the models, the accuracy aspect is also important. Final accuracy of a building model depends on various factors (accuracy of the source data, complexity of the roof shapes, etc.). In this paper the methodology of inspection of dataset containing 3D models is presented. The proposed approach check all building in dataset with comparison to ALS point clouds testing both: accuracy and level of details. Using analysis of statistical parameters for normal heights for reference point cloud and tested planes and segmentation of point cloud provides the tool that can indicate which building and which roof plane in do not fulfill requirement of model accuracy and detail correctness. Proposed method was tested on two datasets: solid and mesh model.
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Filtering Photogrammetric Point Clouds Using Standard LIDAR Filters Towards DTM Generation
NASA Astrophysics Data System (ADS)
Zhang, Z.; Gerke, M.; Vosselman, G.; Yang, M. Y.
2018-05-01
Digital Terrain Models (DTMs) can be generated from point clouds acquired by laser scanning or photogrammetric dense matching. During the last two decades, much effort has been paid to developing robust filtering algorithms for the airborne laser scanning (ALS) data. With the point cloud quality from dense image matching (DIM) getting better and better, the research question that arises is whether those standard Lidar filters can be used to filter photogrammetric point clouds as well. Experiments are implemented to filter two dense matching point clouds with different noise levels. Results show that the standard Lidar filter is robust to random noise. However, artefacts and blunders in the DIM points often appear due to low contrast or poor texture in the images. Filtering will be erroneous in these locations. Filtering the DIM points pre-processed by a ranking filter will bring higher Type II error (i.e. non-ground points actually labelled as ground points) but much lower Type I error (i.e. bare ground points labelled as non-ground points). Finally, the potential DTM accuracy that can be achieved by DIM points is evaluated. Two DIM point clouds derived by Pix4Dmapper and SURE are compared. On grassland dense matching generates points higher than the true terrain surface, which will result in incorrectly elevated DTMs. The application of the ranking filter leads to a reduced bias in the DTM height, but a slightly increased noise level.
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The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.
Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the conceptmore » of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are difficult for the CloudSat radar to detect due to surface contamination (Mace et al. 2007; Marchand et al. 2008). Therefore, the ARM ground-based cloud observations can provide important observations of clouds that complement measurements from space.« less
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Landscape monitoring of post-industrial areas using LiDAR and GIS technology
NASA Astrophysics Data System (ADS)
Wężyk, Piotr; Szostak, Marta; Krzaklewski, Wojciech; Pająk, Marek; Pierzchalski, Marcin; Szwed, Piotr; Hawryło, Paweł; Ratajczak, Michał
2015-06-01
The quarrying industry is changing the local landscape, forming deep open pits and spoil heaps in close proximity to them, especially lignite mines. The impact can include toxic soil material (low pH, heavy metals, oxidations etc.) which is the basis for further reclamation and afforestation. Forests that stand on spoil heaps have very different growth conditions because of the relief (slope, aspect, wind and rainfall shadows, supply of solar energy, etc.) and type of soil that is deposited. Airborne laser scanning (ALS) technology deliver point clouds (XYZ) and derivatives as raster height models (DTM, DSM, nDSM=CHM) which allow the reception of selected 2D and 3D forest parameters (e.g. height, base of the crown, cover, density, volume, biomass, etc). The automation of ALS point cloud processing and integrating the results into GIS helps forest managers to take appropriate decisions on silvicultural treatments in areas with failed plantations (toxic soil, droughts on south-facing slopes; landslides, etc.) or as regular maintenance. The ISOK country-wide project ongoing in Poland will soon deliver ALS point cloud data which can be successfully used for the monitoring and management of many thousands of hectares of destroyed post-industrial areas which according to the law, have to be afforested and transferred back to the State Forest.
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Applications of 3D-EDGE Detection for ALS Point Cloud
NASA Astrophysics Data System (ADS)
Ni, H.; Lin, X. G.; Zhang, J. X.
2017-09-01
Edge detection has been one of the major issues in the field of remote sensing and photogrammetry. With the fast development of sensor technology of laser scanning system, dense point clouds have become increasingly common. Precious 3D-edges are able to be detected from these point clouds and a great deal of edge or feature line extraction methods have been proposed. Among these methods, an easy-to-use 3D-edge detection method, AGPN (Analyzing Geometric Properties of Neighborhoods), has been proposed. The AGPN method detects edges based on the analysis of geometric properties of a query point's neighbourhood. The AGPN method detects two kinds of 3D-edges, including boundary elements and fold edges, and it has many applications. This paper presents three applications of AGPN, i.e., 3D line segment extraction, ground points filtering, and ground breakline extraction. Experiments show that the utilization of AGPN method gives a straightforward solution to these applications.
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NASA Astrophysics Data System (ADS)
Zlinszky, András; Schroiff, Anke; Otepka, Johannes; Mandlburger, Gottfried; Pfeifer, Norbert
2014-05-01
LIDAR point clouds hold valuable information for land cover and vegetation analysis, not only in the spatial distribution of the points but also in their various attributes. However, LIDAR point clouds are rarely used for visual interpretation, since for most users, the point cloud is difficult to interpret compared to passive optical imagery. Meanwhile, point cloud viewing software is available allowing interactive 3D interpretation, but typically only one attribute at a time. This results in a large number of points with the same colour, crowding the scene and often obscuring detail. We developed a scheme for mapping information from multiple LIDAR point attributes to the Red, Green, and Blue channels of a widely used LIDAR data format, which are otherwise mostly used to add information from imagery to create "photorealistic" point clouds. The possible combinations of parameters are therefore represented in a wide range of colours, but relative differences in individual parameter values of points can be well understood. The visualization was implemented in OPALS software, using a simple and robust batch script, and is viewer independent since the information is stored in the point cloud data file itself. In our case, the following colour channel assignment delivered best results: Echo amplitude in the Red, echo width in the Green and normalized height above a Digital Terrain Model in the Blue channel. With correct parameter scaling (but completely without point classification), points belonging to asphalt and bare soil are dark red, low grassland and crop vegetation are bright red to yellow, shrubs and low trees are green and high trees are blue. Depending on roof material and DTM quality, buildings are shown from red through purple to dark blue. Erroneously high or low points, or points with incorrect amplitude or echo width usually have colours contrasting from terrain or vegetation. This allows efficient visual interpretation of the point cloud in planar, profile and 3D views since it reduces crowding of the scene and delivers intuitive contextual information. The resulting visualization has proved useful for vegetation analysis for habitat mapping, and can also be applied as a first step for point cloud level classification. An interactive demonstration of the visualization script is shown during poster attendance, including the opportunity to view your own point cloud sample files.
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Long-term observations of aerosol and cloud condensation nuclei concentrations in Barbados
NASA Astrophysics Data System (ADS)
Pöhlker, Mira L.; Klimach, Thomas; Krüger, Ovid O.; Hrabe de Angelis, Isabella; Ditas, Florian; Praß, Maria; Holanda, Bruna; Su, Hang; Weber, Bettina; Pöhlker, Christopher; Farrell, David A.; Stevens, Bjorn; Prospero, Joseph M.; Andreae, Meinrat O.; Pöschl, Ulrich
2017-04-01
Long-term observation of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations has been conducted at the Ragged Point site in Barbados since August 2016. Ragged Point is a well-established station to monitor the transatlantic transport of Saharan dust outbreaks [1]. In the absence of dust plumes, it represents an ideal site to analyze the maritime boundary layer aerosol that is transported with the trade winds over the Atlantic towards Barbados [2,3]. Broad aerosol size distribution (10 nm to 10 µm) as well as size-resolved CCN measurements at 10 different supersaturations from 0.05 % to 0.84 % have been conducted. The continuous online analyses are supplemented by intensive sampling periods to probe specific aerosol properties with various offline techniques (i.e., microscopy and spectroscopy). Aerosol key properties from our measurements are compared with the continuous and in depth observation of cloud properties at Deebles Point, which is in close neighborhood to the Ragged Point site [2]. Moreover, our activities have been synchronized with the HALO-NARVAL-2 aircraft campaign in August 2016 that added further detailed information on shallow cumulus clouds, which are characteristic for the Atlantic trade winds and represent a crucial factor in the Earth climate system. Our measurements have the following two focal points: (i) We aim to obtain a detailed CCN climatology for the alternation of maritime and dust-impacted episodes at this unique coastal location. This study will complement our recent in-depth analysis for the long-term CCN variability at a remote rain forest location [4]. (ii) Furthermore, we aim to collect detailed information on the role of different aerosol populations on the properties of the climatically important shallow cumulus clouds. References: [1] Prospero, J. M., Collard, F. X., Molinie, J., Jeannot, A. (2014), Global Biogeochemical Cycles, 28, 757-773. [2] Stevens, B., et al. (2016), Bulletin of the American Meteorological Society, 97, 787-801. [3] Wex, H., et al., (2016), Atmos. Chem. Phys., 16, 14107-14130. [4] Pöhlker, M. L.., et al. (2016), Atmos. Chem. Phys., 16, 15709-15740.
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D Model of AL Zubarah Fortress in Qatar - Terrestrial Laser Scanning VS. Dense Image Matching
NASA Astrophysics Data System (ADS)
Kersten, T.; Mechelke, K.; Maziull, L.
2015-02-01
In September 2011 the fortress Al Zubarah, built in 1938 as a typical Arabic fortress and restored in 1987 as a museum, was recorded by the HafenCity University Hamburg using terrestrial laser scanning with the IMAGER 5006h and digital photogrammetry for the Qatar Museum Authority within the framework of the Qatar Islamic Archaeology and Heritage Project. One goal of the object recording was to provide detailed 2D/3D documentation of the fortress. This was used to complete specific detailed restoration work in the recent years. From the registered laser scanning point clouds several cuttings and 2D plans were generated as well as a 3D surface model by triangle meshing. Additionally, point clouds and surface models were automatically generated from digital imagery from a Nikon D70 using the open-source software Bundler/PMVS2, free software VisualSFM, Autodesk Web Service 123D Catch beta, and low-cost software Agisoft PhotoScan. These outputs were compared with the results from terrestrial laser scanning. The point clouds and surface models derived from imagery could not achieve the same quality of geometrical accuracy as laser scanning (i.e. 1-2 cm).
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ARM Cloud Radar Simulator Package for Global Climate Models Value-Added Product
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Yuying; Xie, Shaocheng
It has been challenging to directly compare U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility ground-based cloud radar measurements with climate model output because of limitations or features of the observing processes and the spatial gap between model and the single-point measurements. To facilitate the use of ARM radar data in numerical models, an ARM cloud radar simulator was developed to converts model data into pseudo-ARM cloud radar observations that mimic the instrument view of a narrow atmospheric column (as compared to a large global climate model [GCM] grid-cell), thus allowing meaningful comparison between model outputmore » and ARM cloud observations. The ARM cloud radar simulator value-added product (VAP) was developed based on the CloudSat simulator contained in the community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) (Bodas-Salcedo et al., 2011), which has been widely used in climate model evaluation with satellite data (Klein et al., 2013, Zhang et al., 2010). The essential part of the CloudSat simulator is the QuickBeam radar simulator that is used to produce CloudSat-like radar reflectivity, but is capable of simulating reflectivity for other radars (Marchand et al., 2009; Haynes et al., 2007). Adapting QuickBeam to the ARM cloud radar simulator within COSP required two primary changes: one was to set the frequency to 35 GHz for the ARM Ka-band cloud radar, as opposed to 94 GHz used for the CloudSat W-band radar, and the second was to invert the view from the ground to space so as to attenuate the beam correctly. In addition, the ARM cloud radar simulator uses a finer vertical resolution (100 m compared to 500 m for CloudSat) to resolve the more detailed structure of clouds captured by the ARM radars. The ARM simulator has been developed following the COSP workflow (Figure 1) and using the capabilities available in COSP wherever possible. The ARM simulator is written in Fortran 90, just as is the COSP. It is incorporated into COSP to facilitate use by the climate modeling community. In order to evaluate simulator output, the observational counterpart of the simulator output, radar reflectivity-height histograms (CFAD) is also generated from the ARM observations. This report includes an overview of the ARM cloud radar simulator VAP and the required simulator-oriented ARM radar data product (radarCFAD) for validating simulator output, as well as a user guide for operating the ARM radar simulator VAP.« less
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Inverted Polarity Thunderstorms Linked with Elevated Cloud Base Height
NASA Astrophysics Data System (ADS)
Cummins, K. L.; Williams, E.
2016-12-01
The great majority of thunderstorms worldwide exhibit gross positive dipole structure, produce intracloud lightning that reduces this positive dipole (positive intracloud flashes), and produce negative cloud-to-ground lightning from the lower negative end of this dipole. During the STEPS experiment in 2000 much new evidence for thunderstorms (or cells within multi-cellular storms) with inverted polarity came to light, both from balloon soundings of electric field and from LMA analysis. Many of the storms with inverted polarity cells developed in eastern Colorado. Fleenor et al. (2009) followed up after STEPS to document a dominance of positive polarity CG lightning in many of these cases. In the present study, surface thermodynamic observations (temperature and dew point temperature) have been used to estimate the cloud base heights and temperatures at the time of the Fleenor et al. lightning observations. It was found that when more than 90% of the observed CG lightning polarity within a storm is negative, the cloud base heights were low (2000 m AGL or lower, and warmer, with T>10 C), and when more than 90% of the observed CG lightning within a storm was positive, the cloud base heights were high (3000 m AGL or higher, and colder, with T< 2 C). Multi-cellular storms or temporally-evolving storms with mixed polarity were generally associated with intermediate cloud base heights. These findings on inverted polarity thunderstorms are remarkably consistent with results in other parts of the world where strong instability prevails in the presence of high cloud base height: the plateau regions of China (Liu et al., 1989; Qie et al., 2005), and in pre-monsoon India (Pawar et al., 2016), particularly when mixed polarity cases are excluded. Calculations of adiabatic cloud water content for lifting from near 0 oC cast some doubt on earlier speculation (Williams et al., 2005) that the graupel particles in these inverted polarity storms attain a wet growth condition, and so exhibit positive charging following laboratory experiments. This mechanism will be contrasted with the possibility of positive graupel charging associated with small droplet sizes (consistent with high cloud base) or through involvement of ice nuclei (Pawar et al., 2016) in the semiarid environments that frequently accompany inverted polarity storms.
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NASA Astrophysics Data System (ADS)
Melin, M.; Korhonen, L.; Kukkonen, M.; Packalen, P.
2017-07-01
Canopy cover (CC) is a variable used to describe the status of forests and forested habitats, but also the variable used primarily to define what counts as a forest. The estimation of CC has relied heavily on remote sensing with past studies focusing on satellite imagery as well as Airborne Laser Scanning (ALS) using light detection and ranging (lidar). Of these, ALS has been proven highly accurate, because the fraction of pulses penetrating the canopy represents a direct measurement of canopy gap percentage. However, the methods of photogrammetry can be applied to produce point clouds fairly similar to airborne lidar data from aerial images. Currently there is little information about how well such point clouds measure canopy density and gaps. The aim of this study was to assess the suitability of aerial image point clouds for CC estimation and compare the results with those obtained using spectral data from aerial images and Landsat 5. First, we modeled CC for n = 1149 lidar plots using field-measured CCs and lidar data. Next, this data was split into five subsets in north-south direction (y-coordinate). Finally, four CC models (AerialSpectral, AerialPointcloud, AerialCombi (spectral + pointcloud) and Landsat) were created and they were used to predict new CC values to the lidar plots, subset by subset, using five-fold cross validation. The Landsat and AerialSpectral models performed with RMSEs of 13.8% and 12.4%, respectively. AerialPointcloud model reached an RMSE of 10.3%, which was further improved by the inclusion of spectral data; RMSE of the AerialCombi model was 9.3%. We noticed that the aerial image point clouds managed to describe only the outermost layer of the canopy and missed the details in lower canopy, which was resulted in weak characterization of the total CC variation, especially in the tails of the data.
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NASA Astrophysics Data System (ADS)
Tokuyama, Sekito; Oka, Tomoharu; Takekawa, Shunya; Yamada, Masaya; Iwata, Yuhei; Tsujimoto, Shiho
2017-01-01
High-velocity compact clouds (HVCCs) is one of the populations of peculiar clouds detected in the Central Molecular Zone (CMZ) of our Galaxy. They have compact appearances (< 5 pc) and large velocity widths (> 50 km s-1). Several explanations for the origin of HVCC were proposed; e.g., a series of supernovae (SN) explosions (Oka et al. 1999) or a gravitational kick by a point-like gravitational source (Oka et al. 2016). To investigate the statistical property of HVCCs, a complete list of them is acutely necessary. However, the previous list is not complete since the identification procedure included automated processes and manual selection (Nagai 2008). Here we developed an automated procedure to identify HVCCs in a spectral line data.
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Automatic extraction of discontinuity orientation from rock mass surface 3D point cloud
NASA Astrophysics Data System (ADS)
Chen, Jianqin; Zhu, Hehua; Li, Xiaojun
2016-10-01
This paper presents a new method for extracting discontinuity orientation automatically from rock mass surface 3D point cloud. The proposed method consists of four steps: (1) automatic grouping of discontinuity sets using an improved K-means clustering method, (2) discontinuity segmentation and optimization, (3) discontinuity plane fitting using Random Sample Consensus (RANSAC) method, and (4) coordinate transformation of discontinuity plane. The method is first validated by the point cloud of a small piece of a rock slope acquired by photogrammetry. The extracted discontinuity orientations are compared with measured ones in the field. Then it is applied to a publicly available LiDAR data of a road cut rock slope at Rockbench repository. The extracted discontinuity orientations are compared with the method proposed by Riquelme et al. (2014). The results show that the presented method is reliable and of high accuracy, and can meet the engineering needs.
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Point-based and model-based geolocation analysis of airborne laser scanning data
NASA Astrophysics Data System (ADS)
Sefercik, Umut Gunes; Buyuksalih, Gurcan; Jacobsen, Karsten; Alkan, Mehmet
2017-01-01
Airborne laser scanning (ALS) is one of the most effective remote sensing technologies providing precise three-dimensional (3-D) dense point clouds. A large-size ALS digital surface model (DSM) covering the whole Istanbul province was analyzed by point-based and model-based comprehensive statistical approaches. Point-based analysis was performed using checkpoints on flat areas. Model-based approaches were implemented in two steps as strip to strip comparing overlapping ALS DSMs individually in three subareas and comparing the merged ALS DSMs with terrestrial laser scanning (TLS) DSMs in four other subareas. In the model-based approach, the standard deviation of height and normalized median absolute deviation were used as the accuracy indicators combined with the dependency of terrain inclination. The results demonstrate that terrain roughness has a strong impact on the vertical accuracy of ALS DSMs. From the relative horizontal shifts determined and partially improved by merging the overlapping strips and comparison of the ALS, and the TLS, data were found not to be negligible. The analysis of ALS DSM in relation to TLS DSM allowed us to determine the characteristics of the DSM in detail.
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NASA Astrophysics Data System (ADS)
Ferraz, A.; Painter, T. H.; Saatchi, S.; Bormann, K. J.
2016-12-01
Fusion of multi-temporal Airborne Snow Observatory (ASO) lidar data for mountainous vegetation ecosystems studies The NASA Jet Propulsion Laboratory developed the Airborne Snow Observatory (ASO), a coupled scanning lidar system and imaging spectrometer, to quantify the spatial distribution of snow volume and dynamics over mountains watersheds (Painter et al., 2015). To do this, ASO weekly over-flights mountainous areas during snowfall and snowmelt seasons. In addition, there are additional flights in snow-off conditions to calculate Digital Terrain Models (DTM). In this study, we focus on the reliability of ASO lidar data to characterize the 3D forest vegetation structure. The density of a single point cloud acquisition is of nearly 1 pt/m2, which is not optimal to properly characterize vegetation. However, ASO covers a given study site up to 14 times a year that enables computing a high-resolution point cloud by merging single acquisitions. In this study, we present a method to automatically register ASO multi-temporal lidar 3D point clouds. Although flight specifications do not change between acquisition dates, lidar datasets might have significant planimetric shifts due to inaccuracies in platform trajectory estimation introduced by the GPS system and drifts of the IMU. There are a large number of methodologies that address the problem of 3D data registration (Gressin et al., 2013). Briefly, they look for common primitive features in both datasets such as buildings corners, structures like electric poles, DTM breaklines or deformations. However, they are not suited for our experiment. First, single acquisition point clouds have low density that makes the extraction of primitive features difficult. Second, the landscape significantly changes between flights due to snowfall and snowmelt. Therefore, we developed a method to automatically register point clouds using tree apexes as keypoints because they are features that are supposed to experience little change during winter season. We applied the method to 14 lidar datasets (12 snow-on and 2 snow-off) acquired over the Tuolumne River Basin (California) in the year of 2014. To assess the reliability of the merged point cloud, we analyze the quality of vegetation related products such as canopy height models (CHM) and vertical vegetation profiles.
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Modelling ice microphysics of mixed-phase clouds
NASA Astrophysics Data System (ADS)
Ahola, J.; Raatikainen, T.; Tonttila, J.; Romakkaniemi, S.; Kokkola, H.; Korhonen, H.
2017-12-01
The low-level Arctic mixed-phase clouds have a significant role for the Arctic climate due to their ability to absorb and reflect radiation. Since the climate change is amplified in polar areas, it is vital to apprehend the mixed-phase cloud processes. From a modelling point of view, this requires a high spatiotemporal resolution to capture turbulence and the relevant microphysical processes, which has shown to be difficult.In order to solve this problem about modelling mixed-phase clouds, a new ice microphysics description has been developed. The recently published large-eddy simulation cloud model UCLALES-SALSA offers a good base for a feasible solution (Tonttila et al., Geosci. Mod. Dev., 10:169-188, 2017). The model includes aerosol-cloud interactions described with a sectional SALSA module (Kokkola et al., Atmos. Chem. Phys., 8, 2469-2483, 2008), which represents a good compromise between detail and computational expense.Newly, the SALSA module has been upgraded to include also ice microphysics. The dynamical part of the model is based on well-known UCLA-LES model (Stevens et al., J. Atmos. Sci., 56, 3963-3984, 1999) which can be used to study cloud dynamics on a fine grid.The microphysical description of ice is sectional and the included processes consist of formation, growth and removal of ice and snow particles. Ice cloud particles are formed by parameterized homo- or heterogeneous nucleation. The growth mechanisms of ice particles and snow include coagulation and condensation of water vapor. Autoconversion from cloud ice particles to snow is parameterized. The removal of ice particles and snow happens by sedimentation and melting.The implementation of ice microphysics is tested by initializing the cloud simulation with atmospheric observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC). The results are compared to the model results shown in the paper of Ovchinnikov et al. (J. Adv. Model. Earth Syst., 6, 223-248, 2014) and they show a good match. One of the advantages of UCLALES-SALSA is that it can be used to quantify the effect of aerosol scavenging on cloud properties in a precise way.
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Comments on "Failures in detecting volcanic ash from a satellite-based technique"
Prata, F.; Bluth, G.; Rose, B.; Schneider, D.; Tupper, A.
2001-01-01
The recent paper by Simpson et al. [Remote Sens. Environ. 72 (2000) 191.] on failures to detect volcanic ash using the 'reverse' absorption technique provides a timely reminder of the danger that volcanic ash presents to aviation and the urgent need for some form of effective remote detection. The paper unfortunately suffers from a fundamental flaw in its methodology and numerous errors of fact and interpretation. For the moment, the 'reverse' absorption technique provides the best means for discriminating volcanic ash clouds from meteorological clouds. The purpose of our comment is not to defend any particular algorithm; rather, we point out some problems with Simpson et al.'s analysis and re-state the conditions under which the 'reverse' absorption algorithm is likely to succeed. ?? 2001 Elsevier Science Inc. All rights reserved.
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Impact of Albedo Contrast Between Cirrus and Boundary-Layer Clouds on Climate Sensitivity
NASA Technical Reports Server (NTRS)
Chou, Ming-Dah; Lindzen, R. S.; Hou, A. Y.; Lau, William K. M. (Technical Monitor)
2001-01-01
In assessing the iris effect suggested by Lindzen et al. (2001), Fu et al. (2001) found that the response of high-level clouds to the sea surface temperature had an effect of reducing the climate sensitivity to external radiative forcing, but the effect was not as strong as LCH found. This weaker reduction in climate sensitivity was due to the smaller contrasts in albedos and effective emitting temperatures between cirrus clouds and the neighboring regions. FBH specified the albedos and the outgoing longwave radiation (OLR) in the LCH 3.5-box radiative-convective model by requiring that the model radiation budgets at the top of the atmosphere be consistent with that inferred from the Earth Radiation Budget Experiment (ERBE). In point of fact, the constraint by radiation budgets alone is not sufficient for deriving the correct contrast in radiation properties between cirrus clouds and the neighboring regions, and the approach of FBH to specifying those properties is, we feel inappropriate for assessing the iris effect.
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AMF3 CloudSat Overpasses Field Campaign Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matrosov, Sergey; Hardin, Joseph; De Boer, Gijs
Synergy between ground-based and satellite radar observations of clouds and precipitation is important for refining the algorithms to retrieve hydrometeor microphysical parameters, improvements in the retrieval accuracy, and better understanding the advantages and limitations of different retrieval approaches. The new dual-frequency (Ka- and W-band, 35 GHz and 94 GHz) fully polarimetric scanning U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Research Facility cloud radars (SACRs-2) are advanced sensors aimed to significantly enhance remote sensing capabilities (Kollias et al. 2016). One of these radars was deployed as part of the third ARM Mobile Facility (AMF3) at Oliktok Point, Alaska (70.495omore » N, 149.886oW). The National Aeronautics and Space Administration (NASA) CloudSat satellite, which is part of the polar-orbiting A-train satellite constellation, passes over the vicinity of the AMF3 location (typically within 0-7 km depending on a particular overpass) on a descending orbit every 16 days at approximately 13:21 UTC. The nadir pointing W-band CloudSat cloud profiling radar (CPR) provides vertical profiles of reflectivity that are then used for retrievals of hydrometeor parameters (Tanelli et al. 2008). The main objective of the AMF3 CloudSat overpasses intensive operating period (IOP) campaign was to collect approximately collocated in space and time radar data from the SACR-2 and the CloudSat CPR measurements for subsequent joint analysis of radar variables and microphysical retrievals of cloud and precipitation parameters. Providing the reference for the SACR-2 absolute calibration from the well-calibrated CloudSat CPR was another objective of this IOP. The IOP objectives were achieved by conducting seven special SACR-2 scans during the 10.5-min period centered at the exact time of the CloudSat overpass over the AMF3 (~1321 UTC) on six dates of the CloudSat overpasses during the three-month period allocated to this IOP. These six days were March 5 and 21, April 6 and 22, and May 8 and 24.« less
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NASA Astrophysics Data System (ADS)
Kauffmann, Jens; Thushara Pillai, G. S.; Zhang, Qizhou; Lu, Xing; Immer, Katharina
2015-08-01
The Central Molecular Zone of the Milky Way (CMZ; innermost ~100pc) hosts a number of remarkably dense and massive clouds. These are subject to extreme environmental conditions, including very high cosmic ray fluxes and strong magnetic fields. Exploring star formation under such exceptional circumstances is essential for several of reasons. First, the CMZ permits to probe an extreme point in the star formation parameter space, which helps to test theoretical models. Second, CMZ clouds might help to understand the star formation under extreme conditions in more distant environments, such as in starbursts and the early universe.One particularly striking aspect is that — compared to the solar neighborhood — CMZ star formation in dense gas is suppressed by more than an order of magnitude (Longmore et al. 2012, Kauffmann et al. 2013). This questions current explanations for relations between the dense gas and the star formation rate (e.g., Gao & Solomon 2004, Lada et al. 2012). In other words, the unusually dense and massive CMZ molecular clouds form only very few stars, if any at all. Why is this so?Based on data from ALMA, CARMA, and SMA interferometers, we present results from the Galactic Center Molecular Cloud Survey (GCMS), the first study of a comprehensive sample of molecular clouds in the CMZ. This research yields a curious result: most of the major CMZ clouds are essentially devoid of significant substructure of the sort usually found in regions of high-mass star formation (Kauffmann et al. 2013). Preliminary analysis indicates that some clouds rather resemble homogeneous balls of gas. This suggests a highly dynamic picture of cloud evolution in the CMZ where clouds form, disperse, and re-assemble constantly. This concept is benchmarked against a new ALMA survey and first results from a legacy survey on the SMA.It is plausible that dense clouds in other galaxies have a similar internal structure. Instruments like ALMA and the JWST will soon permit to resolve such regions in nearby galaxies.
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NASA Technical Reports Server (NTRS)
Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu
2016-01-01
Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in MODIS retrievals caused by sub-pixel reflectance inhomogeneity. (Zhang et al. 2016). How cloud vertical structure influences MODIS LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed MODIS cloud property retrievals. (Cho et al. 2015). Cloud property retrievals from 15m resolution ASTER observations. (Werner et al. 2016). Modeling: LES-Satellite observation simulator (Zhang et al. 2012, Miller et al. 2016).
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NASA Astrophysics Data System (ADS)
Hu, Han; Ding, Yulin; Zhu, Qing; Wu, Bo; Lin, Hui; Du, Zhiqiang; Zhang, Yeting; Zhang, Yunsheng
2014-06-01
The filtering of point clouds is a ubiquitous task in the processing of airborne laser scanning (ALS) data; however, such filtering processes are difficult because of the complex configuration of the terrain features. The classical filtering algorithms rely on the cautious tuning of parameters to handle various landforms. To address the challenge posed by the bundling of different terrain features into a single dataset and to surmount the sensitivity of the parameters, in this study, we propose an adaptive surface filter (ASF) for the classification of ALS point clouds. Based on the principle that the threshold should vary in accordance to the terrain smoothness, the ASF embeds bending energy, which quantitatively depicts the local terrain structure to self-adapt the filter threshold automatically. The ASF employs a step factor to control the data pyramid scheme in which the processing window sizes are reduced progressively, and the ASF gradually interpolates thin plate spline surfaces toward the ground with regularization to handle noise. Using the progressive densification strategy, regularization and self-adaption, both performance improvement and resilience to parameter tuning are achieved. When tested against the benchmark datasets provided by ISPRS, the ASF performs the best in comparison with all other filtering methods, yielding an average total error of 2.85% when optimized and 3.67% when using the same parameter set.
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NASA Astrophysics Data System (ADS)
Corlies, Paul; Hayes, Alexander; Adamkovics, Mate; Rodriguez, Sebastien; Kelland, John; Turtle, Elizabeth P.; Mitchell, Jonathan; Lora, Juan M.; Rojo, Patricio; Lunine, Jonathan I.
2017-10-01
We present in this work a detailed analysis of many of the clouds in the Cassini Visual and Infrared Mapping Spectrometer (VIMS) dataset in order to understand their global and seasonal properties. Clouds are one of the few direct observables in Titan’s atmosphere (Griffith et al 2009, Rodriguez et al 2009, Adamkovics et al 2010), and so determining their characteristics allows for a better understanding of surface atmosphere interactions, winds, transport of volatile material, and general circulation. We find the clouds on Titan generally reside in at 5-15km altitude, which agrees with previous modelling efforts (Rafkin et al. 2015), as well as a power law distribution for cloud optical depth. We assume an average cloud droplet size of 100um. No seasonal dependence is observed with either cloud altitude or optical depth, suggesting there is no preferred seasonal formation mechanisms. Combining these characteristics with cloud size (Kelland et al 2017) can trace the transport of volatiles in Titan’s atmosphere, which can be compared against general circulation models (GCMs) (Lora et al 2015). We also present some specific analysis of interesting cloud systems including hypothesized surface fogs (Brown et al 2009) and orographic cloud formation (Barth et al 2010, Corlies et al 2017). In this analysis we use a correlation between Cassini VIMS and RADAR observations as well as an updated topographic map of Titan’s southern hemisphere to better understand the role that topography plays in influencing and driving atmospheric phenomena.Finally, with the end of the Cassini mission, ground based observing now acts as the only means with which to observe clouds on Titan. We present an update of an ongoing cloud campaign to search for clouds on Titan and to understand their seasonal evolution.References:Adamkovics et al. 2010, Icarus 208:868Barth et al. 2010, Planet. Space Sci. 58:1740Corlies et al. 2017, 48th LPSC, 2870CGriffith et al. 2009, ApJ 702:L105Kelland et al. 2017, 48th LPSC, 2748KLora et al. 2015, Icarus 250:516Rafkin et al. 2015, J. Geophys. Res. 120:739Rodriguez et al. 2009, Nature 459:678
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Why is the Magellanic Stream so Turbulent? - A Simulational Study
NASA Astrophysics Data System (ADS)
Williams, Elliott; Shelton, Robin L.
2018-06-01
As the Large and Small Magellanic Clouds travel through the Milky Way (MW) halo, gas is tidally and ram pressure stripped from them, forming the Leading Arm (LA) and Magellanic Stream (MS). The evolution of the LA and MS are an interest to astronomers because there is evidence that the diffuse gas that has been stripped off is able to fall onto the galactic disk and cool enough to fuel star formation in the MW. For et al, 2014 published a catalog of 251 high velocity clouds (HVCs) in the MS, many of which have head-tail morphologies, suggesting interaction with the Milky Way’s halo or other gas in the MS. For et al noticed that the pointing direction of the HVCs are random, which they interpreted as an indication of strong turbulence. They suggested the shock cascade scenario as a contributing process, where ablated cloud material generates turbulence (and H-alpha emission). We take a closer look at this process via simulations. We ran numerical simulations of clouds in the MS using the University of Chicago’s FLASH software. We simulated cases that had two clouds, where one trailed behind the other, and we simulated cases that had one cloud in order to examine the effects of drafting on cloud dynamics and velocity dispersion. Initial cloud temperatures ranged from 100 K to 20,000 K. We have created velocity dispersion maps from the FLASH simulation data to visualize turbulence. We compare these generated maps with 21 cm observations (most recently Westmeier, 2017), in order to search for signatures similar to the small scale turbulence seen in the simulations. We find that if the clouds are initially near to each other, then drafting allows the trailing cloud to catch the leading cloud and mix together. For greater separations, Kelvin-Helmholtz instabilities disrupt the clouds enough before impact that drafting has a minimal role. Our velocity dispersion maps of the warmer clouds closely match values published in For et al, 2014; although, thermal broadening accounts for a large fraction of the velocity dispersion found in the generated maps.
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Solichin Manuri; Hans-Erik Andersen; Robert J. McGaughey; Cris Brack
2017-01-01
The airborne lidar system (ALS) provides a means to efficiently monitor the status of remote tropical forests and continues to be the subject of intense evaluation. However, the cost of ALS acquisition canvary significantly depending on the acquisition parameters, particularly the return density (i.e., spatial resolution) of the lidar point cloud. This study assessed...
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NASA Astrophysics Data System (ADS)
Matsui, T. N.; Suzuki, K.; Nakajima, T. Y.; Matsumae, Y.
2011-12-01
Clouds play an import role in energy balance and climate changes of the Earth. IPCC AR4, however, pointed out that cloud feedback is still the large source of uncertainty in climate estimates. In the recent decade, the new satellites with the active instruments (e.g. Cloudsat) represented a new epoch in earth observations. The active remote sensing is powerful for illustrating the vertical structures of clouds, but the passive remote sensing from satellite images also contribute to better understating of cloud system. For instance, Nakajima et al. (2010a) and Suzuki et al. (2010) illustrated transition of cloud growth, from cloud droplet to drizzle to rain, using the combine analysis of the cloud droplet size retrieved from passive images (MODIS) and the reflectivity profiles from Cloudsat. Furthermore, EarthCARE that is a new satellite launched years later is composed of not only the active but also passive instruments for the combined analysis. On the other hands, the methods to retrieve the advanced information of cloud properties are also required because many imagers have been operated and are now planned (e.g. GCOM-C/SGLI), and have the advantages such as wide observation width and more observation channels. Cloud droplet effective radius (CDR) and cloud optical thickness (COT) can be retrieved using a non-water-absorbing band (e.g. 0.86μm) and a water-absorbing band (1.6, 2.1, 3.7μm) of imagers under the assumptions such as the log-normal droplet size distribution and the plane-parallel cloud structure. However, the differences between three retrieved CDRs using 1.6, 2.1 or 3.7μm (R16, R21 and R37) are found in the satellite observations. Several studies pointed out that vertical/horizontal inhomogeneity of cloud structure, difference of penetration depth of water-absorbing bands, multi-modal droplet distribution and/or 3-D radiative transfer effect cause the CDR differences. In other words, the advanced information of clouds may lie hidden in the differences. Nakajima et al. (2010b) investigated the impact of the differences sensitivities to particle size and the penetration depth in an attempt to explain the CDR differences found in by using a simple two-layer cloud model with the bi-modal size distribution functions. Their results showed the sensitivity differences between 1.6, 2.1 and 3.7μm bands to droplet sizes and their vertical stratification. In this study, we further investigate the impact of the vertical inhomogeneity structure including the drizzle by using a spectral-bin microphysics cloud model. We apply the 1-D radiative transfer computation to the numerical cloud fields generated by the cloud model, and retrieve the CDRs from the reflectances thus simulated at each band. We then compare the statistics of these retrieved CDRs with the CDRs obtained from MODIS observations and derive the sensitivity functions of the retrieved CDRs to the particle size and the optical depth from the sets of the droplet distribution functions predicted by the model and the retrieved CDRs. This study is an attempt to interpret the CDR differences in terms of the cloud vertical structure and the cloud particle growth processes.
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Ohashi, Akira; Tsuguchi, Akira; Imura, Hisanori; Ohashi, Kousaburo
2004-07-01
The cloud point extraction behavior of aluminum(III) with 8-quinolinol (HQ) or 2-methyl-8-quinolinol (HMQ) and Triton X-100 was investigated in the absence and presence of 3,5-dichlorophenol (Hdcp). Aluminum(III) was almost extracted with HQ and 4(v/v)% Triton X-100 above pH 5.0, but was not extracted with HMQ-Triton X-100. However, in the presence of Hdcp, it was almost quantitatively extracted with HMQ-Triton X-100. The synergistic effect of Hdcp on the extraction of aluminum(III) with HMQ and Triton X-100 may be caused by the formation of a mixed-ligand complex, Al(dcp)(MQ)2.
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Lidar Penetration Depth Observations for Constraining Cloud Longwave Feedbacks
NASA Astrophysics Data System (ADS)
Vaillant de Guelis, T.; Chepfer, H.; Noel, V.; Guzman, R.; Winker, D. M.; Kay, J. E.; Bonazzola, M.
2017-12-01
Satellite-borne active remote sensing Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations [CALIPSO; Winker et al., 2010] and CloudSat [Stephens et al., 2002] provide direct measurements of the cloud vertical distribution, with a very high vertical resolution. The penetration depth of the laser of the lidar Z_Opaque is directly linked to the LongWave (LW) Cloud Radiative Effect (CRE) at Top Of Atmosphere (TOA) [Vaillant de Guélis et al., in review]. In addition, this measurement is extremely stable in time making it an excellent observational candidate to verify and constrain the cloud LW feedback mechanism [Chepfer et al., 2014]. In this work, we present a method to decompose the variations of the LW CRE at TOA using cloud properties observed by lidar [GOCCP v3.0; Guzman et al., 2017]. We decompose these variations into contributions due to changes in five cloud properties: opaque cloud cover, opaque cloud altitude, thin cloud cover, thin cloud altitude, and thin cloud emissivity [Vaillant de Guélis et al., in review]. We apply this method, in the real world, to the CRE variations of CALIPSO 2008-2015 record, and, in climate model, to LMDZ6 and CESM simulations of the CRE variations of 2008-2015 period and of the CRE difference between a warm climate and the current climate. In climate model simulations, the same cloud properties as those observed by CALIOP are extracted from the CFMIP Observation Simulator Package (COSP) [Bodas-Salcedo et al., 2011] lidar simulator [Chepfer et al., 2008], which mimics the observations that would be performed by the lidar on board CALIPSO satellite. This method, when applied on multi-model simulations of current and future climate, could reveal the altitude of cloud opacity level observed by lidar as a strong constrain for cloud LW feedback, since the altitude feedback mechanism is physically explainable and the altitude of cloud opacity accurately observed by lidar.
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More on the lambda 2800 A 'interstellar extinction' feature
NASA Astrophysics Data System (ADS)
McLachlan, A.; Nandy, K.
1985-02-01
In a response made to a recent letter by Karim et al. (1984), it is shown that the examples of interstellar absorption at 2800 A that they attribute to proteinaceous material can all be attributed to overexposure of IUE detectors. It is pointed out that stars in the Large Magellanic Cloud show pronounced absorption at 2800 A which cannot be due to interstellar protein since there is no associated absorption at 2200 A; this lack of absorption cannot be due to presence of graphite, whose absorption is weak in the Cloud. The claim by Karim et al. that the spectra of eight stars show 2800 A absorption and that these spectra are saturation-free is considered, and it is shown that data processing problems at IUE ground stations make these spectra unreliable.
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NASA Astrophysics Data System (ADS)
Cantrell, W. H.; Chandrakar, K. K.; Karki, S.; Kinney, G.; Shaw, R.
2017-12-01
Many of the climate impacts of boundary layer clouds are modulated by aerosol particles. As two examples, their interactions with incoming solar and upwelling terrestrial radiation and their propensity for precipitation are both governed by the population of aerosol particles upon which the cloud droplets formed. In turn, clouds are the primary removal mechanism for aerosol particles smaller than a few micrometers and larger than a few nanometers. Aspects of these interconnected phenomena are known in exquisite detail (e.g. Köhler theory), but other parts have not been as amenable to study in the laboratory (e.g. scavenging of aerosol particles by cloud droplets). As a complicating factor, boundary layer clouds are ubiquitously turbulent, which introduces fluctuations in the water vapor concentration and temperature, which govern the saturation ratio which mediates aerosol-cloud interactions. We have performed laboratory measurements of aerosol-cloud coupling and feedbacks, using Michigan Tech's Pi Chamber (Chang et al., 2016). In conditions representative of boundary layer clouds, our data suggest that the lifetime of most interstitial particles in the accumulation mode is governed by cloud activation - particles are removed from the Pi Chamber when they activate and settle out of the chamber as cloud droplets. As cloud droplets are removed, these interstitial particles activate until the initially polluted cloud cleans itself and all particulates are removed from the chamber. At that point, the cloud collapses. Our data also indicate that smaller particles, Dp < ˜ 20 nm are not activated, but are instead removed through diffusion, enhanced by the fact that droplets are moving relative to the suspended aerosol. I will discuss results from both warm (i.e. liquid water only) and mixed phase clouds, showing that cloud and aerosol properties are coupled through fluctuations in the supersaturation, and that threshold behaviors can be defined through the use of the Dämkohler number, the ratio of the characteristic turbulence timescale to the cloud's microphysical response time. Chang, K., et al., 2016. A laboratory facility to study gas-aerosol-cloud interactions in a turbulent environment: The Π Chamber. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-15-00203.1
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NASA Astrophysics Data System (ADS)
Azahari Razak, Khamarrul; Straatsma, Menno; van Westen, Cees; Malet, Jean-Philippe; de Jong, Steven M.
2010-05-01
Airborne Laser Scanning (ALS) is the state of the art technology for topographic mapping over a wide variety of spatial and temporal scales. It is also a promising technique for identification and mapping of landslides in a forested mountainous landscape. This technology demonstrates the ability to pass through the gaps between forest foliage and record the terrain height under vegetation cover. To date, most of the images either derived from satellite imagery, aerial-photograph or synthetic aperture radar are not appropriate for visual interpretation of landslide features that are covered by dense vegetation. However, it is a necessity to carefully map the landslides in order to understand its processes. This is essential for landslide hazard and risk assessment. This research demonstrates the capabilities of high resolution ALS data to recognize and identify different types of landslides in mixed forest in Barcelonnette, France and tropical rainforest in Cameron Highlands, Malaysia. ALS measurements over the 100-years old forest in Bois Noir catchment were carried out in 2007 and 2009. Both ALS dataset were captured using a Riegl laser scanner. First and last pulse with density of one point per meter square was derived from 2007 ALS dataset, whereas multiple return (of up to five returns) pulse was derived from July 2009 ALS dataset, which consists of 60 points per meter square over forested terrain. Generally, this catchment is highly affected by shallow landslides which mostly occur beneath dense vegetation. It is located in the dry intra-Alpine zone and represented by the climatic of the South French Alps. In the Cameron Highlands, first and last pulse data was captured in 2004 which covers an area of up to 300 kilometres square. Here, the Optech laser scanner was used under the Malaysian national pilot study which has slightly low point density. With precipitation intensity of up to 3000 mm per year over rugged topography and elevations up to 2800 m a.s.l., mapping the landslides under tropical rainforest which are highly vegetated and rapidly re-vegetated still remains a challenge. With the advancement of point clouds processing algorithm, high resolution Digital Terrain Models (DTMs) are becoming a very valuable data source for the production of landslide related maps. In this study, two filtering algorithms, which are based on least square interpolation and progressive TIN densification, are used to extract the bare earth surface. Quantitative and qualitative assessment that was carried out under ISPRS Working Group III/3 shown that those algorithms performed well in terms of discontinuity preservation, vegetation on the slope and high outlier influence in the point clouds. Hence, they are capable to extract ground points under difficult scenarios, especially for application under rugged forested terrain. The optimal terrain information has been exploited from ALS point clouds, particularly to preserve important landslide characteristics and to filter out unnecessary features. Morphological characteristics and geometric signatures of landslides are taken into consideration for the derivation of high-quality digital terrain model. Furthermore, ALS-derived DTMs are investigated at different spatial scales for suitable hillslopes morphology representation. Hence, appropriate 2D and 3D visualization methods are presented in such a way to help the image interpreters to detect landslides and classify them according to type, movement mechanism and activity status in forested mountainous terrain.
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NASA Technical Reports Server (NTRS)
Ni, Wenjian; Ranson, Kenneth Jon; Zhang, Zhiyu; Sun, Guoqing
2014-01-01
LiDAR waveform data from airborne LiDAR scanners (ALS) e.g. the Land Vegetation and Ice Sensor (LVIS) havebeen successfully used for estimation of forest height and biomass at local scales and have become the preferredremote sensing dataset. However, regional and global applications are limited by the cost of the airborne LiDARdata acquisition and there are no available spaceborne LiDAR systems. Some researchers have demonstrated thepotential for mapping forest height using aerial or spaceborne stereo imagery with very high spatial resolutions.For stereo imageswith global coverage but coarse resolution newanalysis methods need to be used. Unlike mostresearch based on digital surface models, this study concentrated on analyzing the features of point cloud datagenerated from stereo imagery. The synthesizing of point cloud data from multi-view stereo imagery increasedthe point density of the data. The point cloud data over forested areas were analyzed and compared to small footprintLiDAR data and large-footprint LiDAR waveform data. The results showed that the synthesized point clouddata from ALOSPRISM triplets produce vertical distributions similar to LiDAR data and detected the verticalstructure of sparse and non-closed forests at 30mresolution. For dense forest canopies, the canopy could be capturedbut the ground surface could not be seen, so surface elevations from other sourceswould be needed to calculatethe height of the canopy. A canopy height map with 30 m pixels was produced by subtracting nationalelevation dataset (NED) fromthe averaged elevation of synthesized point clouds,which exhibited spatial featuresof roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlationwith RH50 of LVIS data with a slope of 1.04 and R2 of 0.74 indicating that the canopy height derived fromPRISM triplets can be used to estimate forest biomass at 30 m resolution.
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The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Li, Xiaowen; Khain, Alexander; Matsui, Toshihisa; Lang, Stephen; Simpson, Joanne
2008-01-01
Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 2001]. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds [NRC, 2001]." The aerosol effect on clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path [Twomey, 1977] and the "semi-direct" effect on cloud coverage [e.g., Ackerman et al ., 2001]." Enhanced aerosol concentrations can also suppress warm rain processes by producing a narrow droplet spectrum that inhibits collision and coalescence processes [e.g., Squires and Twomey, 1961; Warner and Twomey, 1967; Warner, 1968; Rosenfeld, 19991. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect [Albrecht, 1989], is even more complex, especially for mixed-phase convective clouds. Table 1 summarizes the key observational studies identifying the microphysical properties, cloud characteristics, thermodynamics and dynamics associated with cloud systems from high-aerosol continental environments. For example, atmospheric aerosol concentrations can influence cloud droplet size distributions, warm-rain process, cold-rain process, cloud-top height, the depth of the mixed phase region, and occurrence of lightning. In addition, high aerosol concentrations in urban environments could affect precipitation variability by providing an enhanced source of cloud condensation nuclei (CCN). Hypotheses have been developed to explain the effect of urban regions on convection and precipitation [van den Heever and Cotton, 2007 and Shepherd, 2005]. Please see Tao et al. (2007) for more detailed description on aerosol impact on precipitation. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.
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Optimal Exploitation of the Temporal and Spatial Resolution of SEVIRI for the Nowcasting of Clouds
NASA Astrophysics Data System (ADS)
Sirch, Tobias; Bugliaro, Luca
2015-04-01
Optimal Exploitation of the Temporal and Spatial Resolution of SEVIRI for the Nowcasting of Clouds An algorithm was developed to forecast the development of water and ice clouds for the successive 5-120 minutes separately using satellite data from SEVIRI (Spinning Enhanced Visible and Infrared Imager) aboard Meteosat Second Generation (MSG). In order to derive cloud cover, optical thickness and cloud top height of high ice clouds "The Cirrus Optical properties derived from CALIOP and SEVIRI during day and night" (COCS, Kox et al. [2014]) algorithm is applied. For the determination of the liquid water clouds the APICS ("Algorithm for the Physical Investigation of Clouds with SEVIRI", Bugliaro e al. [2011]) cloud algorithm is used, which provides cloud cover, optical thickness and effective radius. The forecast rests upon an optical flow method determining a motion vector field from two satellite images [Zinner et al., 2008.] With the aim of determining the ideal time separation of the satellite images that are used for the determination of the cloud motion vector field for every forecast horizon time the potential of the better temporal resolution of the Meteosat Rapid Scan Service (5 instead of 15 minutes repetition rate) has been investigated. Therefore for the period from March to June 2013 forecasts up to 4 hours in time steps of 5 min based on images separated by a time interval of 5 min, 10 min, 15 min, 30 min have been created. The results show that Rapid Scan data produces a small reduction of errors for a forecast horizon up to 30 minutes. For the following time steps forecasts generated with a time interval of 15 min should be used and for forecasts up to several hours computations with a time interval of 30 min provide the best results. For a better spatial resolution the HRV channel (High Resolution Visible, 1km instead of 3km maximum spatial resolution at the subsatellite point) has been integrated into the forecast. To detect clouds the difference of the measured albedo from SEVIRI and the clear-sky albedo provided by MODIS has been used and additionally the temporal development of this quantity. A pre-requisite for this work was an adjustment of the geolocation accuracy for MSG and MODIS by shifting the MODIS data and quantifying the correlation between both data sets.
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A High Resolution Hydrometer Phase Classifier Based on Analysis of Cloud Radar Doppler Spectra.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luke,E.; Kollias, P.
2007-08-06
The lifecycle and radiative properties of clouds are highly sensitive to the phase of their hydrometeors (i.e., liquid or ice). Knowledge of cloud phase is essential for specifying the optical properties of clouds, or else, large errors can be introduced in the calculation of the cloud radiative fluxes. Current parameterizations of cloud water partition in liquid and ice based on temperature are characterized by large uncertainty (Curry et al., 1996; Hobbs and Rangno, 1998; Intriery et al., 2002). This is particularly important in high geographical latitudes and temperature ranges where both liquid droplets and ice crystal phases can exist (mixed-phasemore » cloud). The mixture of phases has a large effect on cloud radiative properties, and the parameterization of mixed-phase clouds has a large impact on climate simulations (e.g., Gregory and Morris, 1996). Furthermore, the presence of both ice and liquid affects the macroscopic properties of clouds, including their propensity to precipitate. Despite their importance, mixed-phase clouds are severely understudied compared to the arguably simpler single-phase clouds. In-situ measurements in mixed-phase clouds are hindered due to aircraft icing, difficulties distinguishing hydrometeor phase, and discrepancies in methods for deriving physical quantities (Wendisch et al. 1996, Lawson et al. 2001). Satellite-based retrievals of cloud phase in high latitudes are often hindered by the highly reflecting ice-covered ground and persistent temperature inversions. From the ground, the retrieval of mixed-phase cloud properties has been the subject of extensive research over the past 20 years using polarization lidars (e.g., Sassen et al. 1990), dual radar wavelengths (e.g., Gosset and Sauvageot 1992; Sekelsky and McIntosh, 1996), and recently radar Doppler spectra (Shupe et al. 2004). Millimeter-wavelength radars have substantially improved our ability to observe non-precipitating clouds (Kollias et al., 2007) due to their excellent sensitivity that enables the detection of thin cloud layers and their ability to penetrate several non-precipitating cloud layers. However, in mixed-phase clouds conditions, the observed Doppler moments are dominated by the highly reflecting ice crystals and thus can not be used to identify the cloud phase. This limits our ability to identify the spatial distribution of cloud phase and our ability to identify the conditions under which mixed-phase clouds form.« less
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Clustering, randomness, and regularity in cloud fields: 2. Cumulus cloud fields
NASA Astrophysics Data System (ADS)
Zhu, T.; Lee, J.; Weger, R. C.; Welch, R. M.
1992-12-01
During the last decade a major controversy has been brewing concerning the proper characterization of cumulus convection. The prevailing view has been that cumulus clouds form in clusters, in which cloud spacing is closer than that found for the overall cloud field and which maintains its identity over many cloud lifetimes. This "mutual protection hypothesis" of Randall and Huffman (1980) has been challenged by the "inhibition hypothesis" of Ramirez et al. (1990) which strongly suggests that the spatial distribution of cumuli must tend toward a regular distribution. A dilemma has resulted because observations have been reported to support both hypotheses. The present work reports a detailed analysis of cumulus cloud field spatial distributions based upon Landsat, Advanced Very High Resolution Radiometer, and Skylab data. Both nearest-neighbor and point-to-cloud cumulative distribution function statistics are investigated. The results show unequivocally that when both large and small clouds are included in the cloud field distribution, the cloud field always has a strong clustering signal. The strength of clustering is largest at cloud diameters of about 200-300 m, diminishing with increasing cloud diameter. In many cases, clusters of small clouds are found which are not closely associated with large clouds. As the small clouds are eliminated from consideration, the cloud field typically tends towards regularity. Thus it would appear that the "inhibition hypothesis" of Ramirez and Bras (1990) has been verified for the large clouds. However, these results are based upon the analysis of point processes. A more exact analysis also is made which takes into account the cloud size distributions. Since distinct clouds are by definition nonoverlapping, cloud size effects place a restriction upon the possible locations of clouds in the cloud field. The net effect of this analysis is that the large clouds appear to be randomly distributed, with only weak tendencies towards regularity. For clouds less than 1 km in diameter, the average nearest-neighbor distance is equal to 3-7 cloud diameters. For larger clouds, the ratio of cloud nearest-neighbor distance to cloud diameter increases sharply with increasing cloud diameter. This demonstrates that large clouds inhibit the growth of other large clouds in their vicinity. Nevertheless, this leads to random distributions of large clouds, not regularity.
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Orographic Condensation at the South Pole of Titan
NASA Astrophysics Data System (ADS)
Corlies, Paul; Hayes, Alexander; Adamkovics, Mate
2016-10-01
Although many clouds have been observed on Titan over the past two decades (Griffith et al. 1998, Rodriquez et al 2009, Brown et al. 2010), only a handful of clouds have been analyzed in detail (Griffith et al 2005, Brown et al 2009, Adamkovics et al 2010). In light of new data and better radiative transfer (RT) modelling, we present here a reexamination of one of these cloud systems observed in March 2007, formerly identified as ground fog (Brown et al 2009), using the Cassini VIMS instrument. Combining our analysis with RADAR observations we attempt to understand the connection and correlation between this low altitude atmospheric phenomenon and the local topography, suggesting instead, a topographically driven (orographic) cloud formation mechanism. This analysis would present the first links between cloud formation and topography on Titan, and has valuable implications in understanding additional cloud formation mechanisms, allowing for a better understanding of Titan's atmospheric dynamics.We will also present an update on an ongoing ground based observation campaign looking for clouds on Titan. This campaign, begun back in April 2014, has been (nearly) continuously monitoring Titan for ongoing cloud activity. Although a variety of telescope and instruments have been used in an effort to best capture the onset of cloud activity expected at Titan's North Pole, no cloud outbursts have yet been observed from the ground (though frequent observations have been made with Cassini ISS/VIMS). This is interesting because it further suggests a developing dichotomy between Titan's seasons, since clouds were observable from the ground during southern summer. Thus, monitoring the onset of large scale cloud activity at Titan's North Pole will be crucial to understanding Titan's hydrologic cycle on seasonal timescales.
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NASA Astrophysics Data System (ADS)
Viudez-Mora, A.; Kato, S.; Smith, W. L., Jr.; Chang, F. L.
2016-12-01
Knowledge of the vertical cloud distribution is important for a variety of climate and weather applications. The cloud overlapping variations greatly influence the atmospheric heating/cooling rates, with implications for the surface-troposphere radiative balance, global circulation and precipitation. Additionally, an accurate knowledge of the multi-layer cloud distribution in real-time can be used in applications such safety condition for aviation through storms and adverse weather conditions. In this study, we evaluate a multi-layered cloud algorithm (Chang et al. 2005) based on MODIS measurements aboard Aqua satellite (MCF). This algorithm uses the CO2-slicing technique combined with cloud properties determined from VIS, IR and NIR channels to locate high thin clouds over low-level clouds, and retrieve the τ of each layer. We use CALIPSO (Winker et. al, 2010) and CloudSat (Stephens et. al, 2002) (CLCS) derived cloud vertical profiles included in the C3M data product (Kato et al. 2010) to evaluate MCF derived multi-layer cloud properties. We focus on 2 layer overlapping and 1-layer clouds identified by the active sensors and investigate how well these systems are identified by the MODIS multi-layer technique. The results show that for these multi-layered clouds identified by CLCS, the MCF correctly identifies about 83% of the cases as multi-layer. However, it is found that the upper CTH is underestimated by about 2.6±0.4 km, because the CO2-slicing technique is not as sensitive to the cloud physical top as the CLCS. The lower CTH agree better with differences found to be about 1.2±0.5 km. Another outstanding issue for the MCF approach is the large number of multi-layer false alarms that occur in single-layer conditions. References: Chang, F.-L., and Z. Li, 2005: A new method for detection of cirrus overlapping water clouds and determination of their optical properties. J. Atmos. Sci., 62. Kato, S., et al. (2010), Relationships among cloud occurrence frequency, overlap, and effective thickness derived from CALIPSO and CloudSat merged cloud vertical profiles, J. Geophys. Res., 115. Stephens, G. L., et al. (2002), The CloudSat mission and A-Train, Bull. Am. Meteorol. Soc., 83. Winker, D. M., et al., 2010: The CALIPSO Mission: A global 3D view of aerosols and clouds. Bull. Amer. Meteor. Soc., 91.
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Modeling CO 2 ice clouds with a Mars Global Climate Model
NASA Astrophysics Data System (ADS)
Audouard, Joachim; Määttänen, Anni; Listowski, Constantino; Millour, Ehouarn; Forget, Francois; Spiga, Aymeric
2016-10-01
Since the first claimed detection of CO2 ice clouds by the Mariner campaign (Herr and Pimentel, 1970), more recent observations and modelling works have put new constraints concerning their altitude, region, time and mechanisms of formation (Clancy and Sandor, 1998; Montmessin et al., 2007; Colaprete et al., 2008; Määttänen et al., 2010; Vincendon et al., 2011; Spiga et al. 2012; Listowski et al. 2014). CO2 clouds are observed at the poles at low altitudes (< 20 km) during the winter and at high altitudes (60-110 km) in the equatorial regions during the first half of the year. However, Martian CO2 clouds's variability and dynamics remain somehow elusive.Towards an understanding of Martian CO2 clouds and especially of their precise radiative impact on the climate throughout the history of the planet, including their formation and evolution in a Global Climate Model (GCM) is necessary.Adapting the CO2 clouds microphysics modeling work of Listowski et al. (2013; 2014), we aim at implementing a complete CO2 clouds scheme in the GCM of the Laboratoire de Météorologie Dynamique (LMD, Forget et al., 1999). It covers CO2 microphysics, growth, evolution and dynamics with a methodology inspired from the water ice clouds scheme recently included in the LMD GCM (Navarro et al., 2014).Two main factors control the formation and evolution of CO2 clouds in the Martian atmosphere: sufficient supersaturation of CO2 is needed and condensation nuclei must be available. Topography-induced gravity-waves (GW) are expected to propagate to the upper atmosphere where they produce cold pockets of supersaturated CO2 (Spiga et al., 2012), thus allowing the formation of clouds provided enough condensation nuclei are present. Such supersaturations have been observed by various instruments, in situ (Schofield et al., 1997) and from orbit (Montmessin et al., 2006, 2011; Forget et al., 2009).Using a GW-induced temperature profile and the 1-D version of the GCM, we simulate the formation of CO2 clouds in the mesosphere and investigate the sensitivity of our microphysics scheme. First results and steps towards the integration in the 3-D GCM will be presented and discussed at the conference.This work is funded by the Laboratory of Excellence ESEP.
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Wave-clouds coupling in the Jovian troposphere.
NASA Astrophysics Data System (ADS)
Gaulme, P.; Mosser, B.
2003-05-01
First studies about Jovian oscillations are due to Vorontsov et al. (1976). Attempts to observe them started in the late 1980's (Deming et al. 1989, Mosser et al. 1991). The micro-satellite Jovis and ground-based observations campaign such as SŸMPA (e.g Baglin et al. 1999) account for an accurate analysis of the cloud response to an acoustic wave. Therefore, the propagation of sound or gravity waves in the Jovian troposphere is revisited, in order to estimate their effect on the highest clouds layer. From basic thermodynamics, the troposphere should be stratified in three major ice clouds layers: water-ammonia, ammonium-hydrosulfide and ammonia ice for the highest. The presence of ammonia ice clouds has been inferred from Kuiper in 1952, and was predicted to dominate the Jovian skies. However, they had been observed spectroscopically over less than one percent of the surface. This absence of spectral proof could come from a coating of ammonia particles from other substances (Baines et al. 2002). In this work, we study the behaviour of a cloud submitted to a periodic pressure perturbation. We suppose a vertical wave propagating in a plane parallel atmosphere including an ammonia ice cloud layer. We determine the relation between the Lagrangian pressure perturbation and the variation of the fraction of solid ammonia. The linearized equations governing the evolution of the Eulerian pressure and density perturbed terms allows us to study how the propagation is altered by the clouds and how the clouds move with the wave. Finally, because a pressure perturbation modifies the fraction of solid ammonia, we estimate how much an ammonia crystal should grow or decrease and how the clouds albedo could change with the wave. Baglin et al. 1999. BAAS 31, 813. Baines et al. 2002. Icarus 159, 74. Deming et al. 1989. Icarus 21, 943. Kuiper 1952.The atmospheres of the Earth and Planets pp. 306-405. Univ. of Chicago Press, Chicago. Mosser et al. 1991. A&A 251, 356. Vorontsov et al. 1976. Icarus 27, 109.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Dong; Schwartz, Stephen E.; Yu, Dantong
Clouds are a central focus of the U.S. Department of Energy (DOE)’s Atmospheric System Research (ASR) program and Atmospheric Radiation Measurement (ARM) Climate Research Facility, and more broadly are the subject of much investigation because of their important effects on atmospheric radiation and, through feedbacks, on climate sensitivity. Significant progress has been made by moving from a vertically pointing (“soda-straw”) to a three-dimensional (3D) view of clouds by investing in scanning cloud radars through the American Recovery and Reinvestment Act of 2009. Yet, because of the physical nature of radars, there are key gaps in ARM's cloud observational capabilities. Formore » example, cloud radars often fail to detect small shallow cumulus and thin cirrus clouds that are nonetheless radiatively important. Furthermore, it takes five to twenty minutes for a cloud radar to complete a 3D volume scan and clouds can evolve substantially during this period. Ground-based stereo-imaging is a promising technique to complement existing ARM cloud observation capabilities. It enables the estimation of cloud coverage, height, horizontal motion, morphology, and spatial arrangement over an extended area of up to 30 by 30 km at refresh rates greater than 1 Hz (Peng et al. 2015). With fine spatial and temporal resolution of modern sky cameras, the stereo-imaging technique allows for the tracking of a small cumulus cloud or a thin cirrus cloud that cannot be detected by a cloud radar. With support from the DOE SunShot Initiative, the Principal Investigator (PI)’s team at Brookhaven National Laboratory (BNL) has developed some initial capability for cloud tracking using multiple distinctly located hemispheric cameras (Peng et al. 2015). To validate the ground-based cloud stereo-imaging technique, the cloud stereo-imaging field campaign was conducted at the ARM Facility’s Southern Great Plains (SGP) site in Oklahoma from July 15 to December 24. As shown in Figure 1, the cloud stereo-imaging system consisted of two inexpensive high-definition (HD) hemispheric cameras (each cost less than $1,500) and ARM’s Total Sky Imager (TSI). Together with other co-located ARM instrumentation, the campaign provides a promising opportunity to validate stereo-imaging-based cloud base height and, more importantly, to examine the feasibility of cloud thickness retrieval for low-view-angle clouds.« less
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Classification of forest land attributes using multi-source remotely sensed data
NASA Astrophysics Data System (ADS)
Pippuri, Inka; Suvanto, Aki; Maltamo, Matti; Korhonen, Kari T.; Pitkänen, Juho; Packalen, Petteri
2016-02-01
The aim of the study was to (1) examine the classification of forest land using airborne laser scanning (ALS) data, satellite images and sample plots of the Finnish National Forest Inventory (NFI) as training data and to (2) identify best performing metrics for classifying forest land attributes. Six different schemes of forest land classification were studied: land use/land cover (LU/LC) classification using both national classes and FAO (Food and Agricultural Organization of the United Nations) classes, main type, site type, peat land type and drainage status. Special interest was to test different ALS-based surface metrics in classification of forest land attributes. Field data consisted of 828 NFI plots collected in 2008-2012 in southern Finland and remotely sensed data was from summer 2010. Multinomial logistic regression was used as the classification method. Classification of LU/LC classes were highly accurate (kappa-values 0.90 and 0.91) but also the classification of site type, peat land type and drainage status succeeded moderately well (kappa-values 0.51, 0.69 and 0.52). ALS-based surface metrics were found to be the most important predictor variables in classification of LU/LC class, main type and drainage status. In best classification models of forest site types both spectral metrics from satellite data and point cloud metrics from ALS were used. In turn, in the classification of peat land types ALS point cloud metrics played the most important role. Results indicated that the prediction of site type and forest land category could be incorporated into stand level forest management inventory system in Finland.
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NASA Astrophysics Data System (ADS)
Howle, J. F.; Bawden, G. W.; Hunter, L. E.; Rose, R. S.
2009-12-01
High resolution (centimeter level) three-dimensional point-cloud imagery of offset glacial outwash deposits were collected by using ground based tripod LiDAR (T-LiDAR) to characterize the cumulative fault slip across the recently identified Polaris fault (Hunter et al., 2009) near Truckee, California. The type-section site for the Polaris fault is located 6.5 km east of Truckee where progressive right-lateral displacement of middle to late Pleistocene deposits is evident. Glacial outwash deposits, aggraded during the Tioga glaciation, form a flat lying ‘fill’ terrace on both the north and south sides of the modern Truckee River. During the Tioga deglaciation melt water incised into the terrace producing fluvial scarps or terrace risers (Birkeland, 1964). Subsequently, the terrace risers on both banks have been right-laterally offset by the Polaris fault. By using T-LiDAR on an elevated tripod (4.25 m high), we collected 3D high-resolution (thousands of points per square meter; ± 4 mm) point-cloud imagery of the offset terrace risers. Vegetation was removed from the data using commercial software, and large protruding boulders were manually deleted to generate a bare-earth point-cloud dataset with an average data density of over 240 points per square meter. From the bare-earth point cloud we mathematically reconstructed a pristine terrace/scarp morphology on both sides of the fault, defined coupled sets of piercing points, and extracted a corresponding displacement vector. First, the Polaris fault was approximated as a vertical plane that bisects the offset terrace risers, as well as bisecting linear swales and tectonic depressions in the outwash terrace. Then, piercing points to the vertical fault plane were constructed from the geometry of the geomorphic elements on either side of the fault. On each side of the fault, the best-fit modeled outwash plane is projected laterally and the best-fit modeled terrace riser projected upward to a virtual intersection in space, creating a vector. These constructed vectors were projected to intersection with the fault plane, defining statistically significant piercing points. The distance between the coupled set of piercing points, within the plane of the fault, is the cumulative displacement vector. To assess the variability of the modeled geomorphic surfaces, including surface roughness and nonlinearity, we generated a suite of displacement models by systematically incorporating larger areas of the model domain symmetrically about the fault. Preliminary results of 10 models yield an average cumulative displacement of 5.6 m (1 Std Dev = 0.31 m). As previously described, Tioga deglaciation melt water incised into the outwash terrace leaving terrace risers that were subsequently offset by the Polaris fault. Therefore, the age of the Tioga outwash terrace represents a maximum limiting age of the tectonic displacement. Using regional age constraints of 15 to 13 kya for the Tioga outwash terrace (Benson et al., 1990; Clark and Gillespie, 1997; James et al., 2002) and the above model results, we estimate a preliminary minimum fault slip rate of 0.40 ± 0.05 mm/yr for the Polaris type-section site.
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NASA Technical Reports Server (NTRS)
Dye, James E.; Krider, E. Phillip; Merceret, Francis J.; Willett, John C.; Bateman, Monte G.; Mach, Douglas M.; Walterscheid, Richard; O'Brien, T. Paul; Christian, Hugh J.
2008-01-01
Ascending space vehicles are vulnerable to both natural and triggered lightning. Launches under the jurisdiction of the United States are generally subject to a set of rules called the Lightning Launch Commit Criteria (LLCC) (Krider etal., 1999; Krider etal., 2006). The LLCC protect both the vehicle and the public by assuring that the launch does not take place in conditions posing a significant risk of a lightning strike to the ascending vehicle. Such a strike could destroy the vehicle and its payload, thus causing failure of the mission while releasing both toxic materials and debris. To assure safety, the LLCC are conservative and sometimes they may seriously limit the ability of the launch operator to fly as scheduled even when conditions are benign. In order to safely reduce the number of launch scrubs and delays attributable to the LLCC, the Airborne Field Mill (ABFM II) program was undertaken in 2000 - 2001. The effort was directed to collecting detailed high-quality data on the electrical, microphysical, radar and meteorological properties of thunderstorm-associated clouds. Details may be found in Dye et al., 2007. The expectation was that this additional knowledge would provide a better physical basis for the LLCC and allow them to be revised to be less restrictive while remaining at least as safe. That expectation was fulfilled, leading to significant revisions to the LLCC in 2003 and 2005. The 2005 revisions included the application of a new radar-derived quantity called the Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) in the rules governing flight through anvil clouds. VAHIRR is the product of the volume averaged radar reflectivity times the radardetermined cloud thickness. The reflectivity average extends horizontally 5 km west, east, south and north of a point along the flight track and vertically from the 0 C isotherm to the top of the radar cloud. This region is defined as the "Specified Volume". See Dye et al., 2006 and Merceret et al., 2006 for a more thorough description of VAHIRR. The units are dBZ km (not dBZ per kilometer) and the threshold is 10 dBZ km. It is safe to fly through an anvil cloud for which VAHIRR is below this threshold everywhere along the flight track as long as (1) the entire cloud within 5 nmi. (9.26 km) of the flight track is colder than 0 C, (2) the points at which VAHIRR must be evaluated are at least 20 km from any active convective cores and recent lightning, and (3) the radar return is not being attenuated within the Specified Volume around those points.
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VizieR Online Data Catalog: OGLE Magellanic Clouds anomalous Cepheids (Soszynski+, 2015)
NASA Astrophysics Data System (ADS)
Soszynski, I.; Udalski, A.; Szymanski, M. K.; Pietrzynski, G.; Wyrzykowski, L.; Ulaczyk, K.; Poleski, R.; Pietrukowicz, P.; Kozlowski, S.; Skowron, J.; Mroz, P.; Pawlak, M.
2016-06-01
Time-series I and V-band photometry of the Magellanic Clouds was obtained in the years 2010-2015 using the 32-chip mosaic CCD camera mounted at the focus of the 1.3-m Warsaw Telescope located at Las Campanas Observatory in Chile. The observatory is operated by the Carnegie Institution for Science. The OGLE- IV camera has a total field of view of 1.4 square degrees and pixel scale of 0.26". The OGLE-IV fields cover approximately 650 square degrees in both Clouds and a region between both galaxies, the so-called Magellanic Bridge. For each field we obtained from 90 (in sparse regions far from the centers of the Magellanic Clouds) to over 750 observing points (in the densest fields) in the Cousins I-band and from several to over 260 points in the Johnson V-band. Data reduction of the OGLE images was performed using the Difference Image Analysis technique (Alard and Lupton 1998ApJ...503..325A, Wozniak 2000). Detailed descriptions of the instrumentation, photometric reductions and astrometric calibrations of the OGLE-IV data are provided by Udalski et al. (2015, Cat. J/AcA/50/421). (8 data files).
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First Prismatic Building Model Reconstruction from Tomosar Point Clouds
NASA Astrophysics Data System (ADS)
Sun, Y.; Shahzad, M.; Zhu, X.
2016-06-01
This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR) point clouds. The proposed approach is modular and works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007) and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon complexity constrained merging is employed to refine (i.e., to reduce) the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated and validated over a large building (convention center) in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR.
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NASA Astrophysics Data System (ADS)
Letu, H.; Nagao, T. M.; Nakajima, T. Y.; Ishimoto, H.; Riedi, J.; Shang, H.
2017-12-01
Ice cloud property product from satellite measurements is applicable in climate change study, numerical weather prediction, as well as atmospheric study. Ishimoto et al., (2010) and Letu et al., (2016) developed a single scattering property of the highly irregular ice particle model, called the Voronoi model for developing ice cloud product of the GCOM-C satellite program. It is investigated that Voronoi model has a good performance on retrieval of the ice cloud properties by comparing it with other well-known scattering models. Cloud property algorithm (Nakajima et al., 1995, Ishida and Nakajima., 2009, Ishimoto et al., 2009, Letu et al., 2012, 2014, 2016) of the GCOM-C satellite program is improved to produce the Himawari-8/AHI cloud products based on the variation of the solar zenith angle. Himawari-8 is the new-generational geostationary meteorological satellite, which is successfully launched by the Japan Meteorological Agency (JMA) on 7 October 2014. In this study, ice cloud optical and microphysical properties are simulated from RSTAR radiative transfer code by using various model. Scattering property of the Voronoi model is investigated for developing the AHI ice cloud products. Furthermore, optical and microphysical properties of the ice clouds are retrieved from Himawari-8/AHI satellite measurements. Finally, retrieval results from Himawari-8/AHI are compared to MODIS-C6 cloud property products for validation of the AHI cloud products.
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Topobathymetric LiDAR point cloud processing and landform classification in a tidal environment
NASA Astrophysics Data System (ADS)
Skovgaard Andersen, Mikkel; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Brandbyge Ernstsen, Verner
2017-04-01
Historically it has been difficult to create high resolution Digital Elevation Models (DEMs) in land-water transition zones due to shallow water depth and often challenging environmental conditions. This gap of information has been reflected as a "white ribbon" with no data in the land-water transition zone. In recent years, the technology of airborne topobathymetric Light Detection and Ranging (LiDAR) has proven capable of filling out the gap by simultaneously capturing topographic and bathymetric elevation information, using only a single green laser. We collected green LiDAR point cloud data in the Knudedyb tidal inlet system in the Danish Wadden Sea in spring 2014. Creating a DEM from a point cloud requires the general processing steps of data filtering, water surface detection and refraction correction. However, there is no transparent and reproducible method for processing green LiDAR data into a DEM, specifically regarding the procedure of water surface detection and modelling. We developed a step-by-step procedure for creating a DEM from raw green LiDAR point cloud data, including a procedure for making a Digital Water Surface Model (DWSM) (see Andersen et al., 2017). Two different classification analyses were applied to the high resolution DEM: A geomorphometric and a morphological classification, respectively. The classification methods were originally developed for a small test area; but in this work, we have used the classification methods to classify the complete Knudedyb tidal inlet system. References Andersen MS, Gergely Á, Al-Hamdani Z, Steinbacher F, Larsen LR, Ernstsen VB (2017). Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment. Hydrol. Earth Syst. Sci., 21: 43-63, doi:10.5194/hess-21-43-2017. Acknowledgements This work was funded by the Danish Council for Independent Research | Natural Sciences through the project "Process-based understanding and prediction of morphodynamics in a natural coastal system in response to climate change" (Steno Grant no. 10-081102) and by the Geocenter Denmark through the project "Closing the gap! - Coherent land-water environmental mapping (LAWA)" (Grant no. 4-2015).
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NASA Astrophysics Data System (ADS)
Hoose, C.; Lohmann, U.; Stier, P.; Verheggen, B.; Weingartner, E.; Herich, H.
2007-12-01
The global aerosol-climate model ECHAM5-HAM (Stier et al., 2005) has been extended by an explicit treatment of cloud-borne particles. Two additional modes for in-droplet and in-crystal particles are introduced, which are coupled to the number of cloud droplet and ice crystal concentrations simulated by the ECHAM5 double-moment cloud microphysics scheme (Lohmann et al., 2007). Transfer, production and removal of cloud-borne aerosol number and mass by cloud droplet activation, collision scavenging, aqueous-phase sulfate production, freezing, melting, evaporation, sublimation and precipitation formation are taken into account. The model performance is demonstrated and validated with observations of the evolution of total and interstitial aerosol concentrations and size distributions during three different mixed-phase cloud events at the alpine high-altitude research station Jungfraujoch (Switzerland) (Verheggen et al, 2007). Although the single-column simulations can not be compared one-to-one with the observations, the governing processes in the evolution of the cloud and aerosol parameters are captured qualitatively well. High scavenged fractions are found during the presence of liquid water, while the release of particles during the Bergeron-Findeisen process results in low scavenged fractions after cloud glaciation. The observed coexistence of liquid and ice, which might be related to cloud heterogeneity at subgrid scales, can only be simulated in the model when forcing non-equilibrium conditions. References: U. Lohmann et al., Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM, Atmos. Chem. Phys. 7, 3425-3446 (2007) P. Stier et al., The aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys. 5, 1125-1156 (2005) B. Verheggen et al., Aerosol partitioning between the interstitial and the condensed phase in mixed-phase clouds, Accepted for publication in J. Geophys. Res. (2007)
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Gravity, turbulence and the scaling ``laws'' in molecular clouds
NASA Astrophysics Data System (ADS)
Ballesteros-Paredes, Javier
The so-called Larson (1981) scaling laws found empirically in molecular clouds have been generally interpreted as evidence that the clouds are turbulent and fractal. In the present contribution we discussed how recent observations and models of cloud formation suggest that: (a) these relations are the result of strong observational biases due to the cloud definition itself: since the filling factor of the dense structures is small, by thresholding the column density the computed mean density between clouds is nearly constant, and nearly the same as the threshold (Ballesteros-Paredes et al. 2012). (b) When accounting for column density variations, the velocity dispersion-size relation does not appears anymore. Instead, dense cores populate the upper-left corner of the δ v-R diagram (Ballesteros-Paredes et al. 2011a). (c) Instead of a δ v-R relation, a more appropriate relation seems to be δ v 2 / R = 2 GMΣ, which suggest that clouds are in collapse, rather than supported by turbulence (Ballesteros-Paredes et al. 2011a). (d) These results, along with the shapes of the star formation histories (Hartmann, Ballesteros-Paredes & Heitsch 2012), line profiles of collapsing clouds in numerical simulations (Heitsch, Ballesteros-Paredes & Hartmann 2009), core-to-core velocity dispersions (Heitsch, Ballesteros-Paredes & Hartmann 2009), time-evolution of the column density PDFs (Ballesteros-Paredes et al. 2011b), etc., strongly suggest that the actual source of the non-thermal motions is gravitational collapse of the clouds, so that the turbulent, chaotic component of the motions is only a by-product of the collapse, with no significant ``support" role for the clouds. This result calls into question if the scale-free nature of the motions has a turbulent, origin (Ballesteros-Paredes et al. 2011a; Ballesteros-Paredes et al. 2011b, Ballesteros-Paredes et al. 2012).
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Multiple-Primitives Hierarchical Classification of Airborne Laser Scanning Data in Urban Areas
NASA Astrophysics Data System (ADS)
Ni, H.; Lin, X. G.; Zhang, J. X.
2017-09-01
A hierarchical classification method for Airborne Laser Scanning (ALS) data of urban areas is proposed in this paper. This method is composed of three stages among which three types of primitives are utilized, i.e., smooth surface, rough surface, and individual point. In the first stage, the input ALS data is divided into smooth surfaces and rough surfaces by employing a step-wise point cloud segmentation method. In the second stage, classification based on smooth surfaces and rough surfaces is performed. Points in the smooth surfaces are first classified into ground and buildings based on semantic rules. Next, features of rough surfaces are extracted. Then, points in rough surfaces are classified into vegetation and vehicles based on the derived features and Random Forests (RF). In the third stage, point-based features are extracted for the ground points, and then, an individual point classification procedure is performed to classify the ground points into bare land, artificial ground and greenbelt. Moreover, the shortages of the existing studies are analyzed, and experiments show that the proposed method overcomes these shortages and handles more types of objects.
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Biological aerosol particles in the atmosphere and their impact on clouds (BIOCLOUDS)
NASA Astrophysics Data System (ADS)
Amato, Pierre; Attard, Eleonore; Deguillaume, Laurent; Delort, Anne-Marie; Flossmann, Andrea; Good, Nicholas; Joly, Muriel; Koop, Thomas; Möhler, Ottmar; Monier, Marie; Morris, Cindy; Oehm, Caroline; Pöschl, Ulrich; Sancelme, Martine
2015-04-01
The project BIOCLOUDS aimed at investigating and quantifying the role of bioaerosols in tropospheric clouds. We focused on the studies on microorganisms, mainly bacteria. To reach our objective we (1) isolated and identified INA bacterial strains in cloud waters, (2) studied in more details IN properties of bacteria isolated from cloud waters in laboratories and cloud chamber, (3) used new data as input to cloud models. 1. Isolation and Identification of INA bacterial strains in cloud waters Cloud water samples were collected at the puy de Dôme station under sterile conditions, microorganisms were cultured on agar plates and further identified by DNA sequencing coding for16SrRNA. 257 bacterial strains isolated from 25 cloud events were screened and 44 isolates were selected as they belonged to Pseudomonas, Xanthomonas and Erwinia genera which are potential INA candidates. Using the classical "Droplet Freezing method" as ice nucleation test, 7 strains were shown INA+. Their cumulative IN frequency profiles were established and showed that some of them are very efficient, for example the strain Pseudomonas syringae 13b74 started to nucleate a t-3°C and 4% of the cells were active at- 5°C. 2. Further laboratory investigations of IN properties of cloud bacterial strains All the experiments presented in this section were carried out with 3 Pseudomonas syringae strains. We tested the influence of O3, NO, UV and pH, which are atmospheric markers of anthropogenic activity, on the IN activity of the Pseudomonas strains. It was clearly shown that pH had a main influence, acidic pHs decreased the IN activity of the strains. This suggests a negative impact of human emissions on the natural capacity of bacteria to precipitate with rain. The 3 Pseudomas strains were sprayed in the AIDA cloud chamber. The survival of these strains with time before cloud formation was measured and will be used in the future to parameterize models for bacterial transport. After cloud formation, IN activity of bacteria was followed with time, our results suggest that bacteria are precipitated in the cloud chamber as a result of their IN activity. Also the coating of bacteria with sulfates decreased their IN activity, pointing out the negative potential anthropogenic influence on IN bacteria activity. 3. Modeling study to see if any impact of bacteria on cloud development and/or precipitation is realistic. Modeling studies were performed with DESCAM (Detailed SCAvenging Model) using as an input the new data from the different campaigns in AIDA. M. VAÏTILINGOM et al. Atmospheric Environment, 2012, 56, 88-100. E. ATTARD et al. Atmospheric Chemistry and Physics, 2012, 12, 10667-10677. M. JOLY et al. Atmospheric Environment, 2013, 70, 392-400.
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Equatorial cloud level convection on Venus
NASA Astrophysics Data System (ADS)
Lee, Yeon Joo; Imamura, Takeshi; Sugiyama, Koichiro; Sato, Takao M.; Maejima, Yasumitsu
2016-10-01
In the equatorial region on Venus, a clear cloud top morphology difference depending on solar local time has been observed through UV images. Laminar flow shaped clouds are shown on the morning side, and convective-like cells on the afternoon side (Titov et al. 2012). Baker et al. (1998) suggested that deep convective motions in the low-to-middle cloud layers at the 40-60 km range can explain cellular shapes. Imamura et al. (2014), however argued that this cannot be a reason, as convection in the low-to-middle cloud layers can be suppressed near sub solar regions due to a stabilizing effect by strong solar heating. We suggest that the observed feature may be related to strong solar heating at local noon time (Lee et al. 2015). Horizontal uneven distribution of an unknown UV absorber and/or cloud top structure may trigger horizontal convection (Toigo et al. 1994). In order to examine these possibilities, we processed 1-D radiative transfer model calculations from surface to 100 km altitude (SHDOM, Evans 1998), which includes clouds at 48-71 km altitudes (Crisp et al. 1986). The results on the equatorial thermal cooling and solar heating profiles were employed in a 2D fluid dynamic model calculation (CReSS, Tsuboki and Sakakibara 2007). The calculation covered an altitude range of 40-80 km and a 100-km horizontal distance. We compared three conditions; an 'effective' global circulation condition that cancels out unbalanced net radiative energy at equator, a condition without such global circulation effect, and the last condition assumed horizontally inhomogeneous unknown UV absorber distribution. Our results show that the local time dependence of lower level cloud convection is consistent with Imamura et al.'s result, and suggest a possible cloud top level convection caused by locally unbalanced net energy and/or horizontally uneven solar heating. This may be related to the observed cloud morphology in UV images. The effective global circulation condition, however, can "remove" such cloud top level convection. The later one consists with measured high static stability at the cloud top level from radio occultation measurement.
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Microphysical Model Studies of Venus Clouds
NASA Astrophysics Data System (ADS)
Meade, P. E.; Bullock, M. A.; Grinspoon, D. H.
2004-11-01
We have adapted a standard cloud microphysics model to construct a self-consistent microphysical model of Venus' cloud layer which reproduces and extends previous studies (e.g. James et al. 1997). Our model is based on the Community Aerosol and Radiation Model Atmosphere (CARMA), which is a widely used computer code for terrestrial cloud microphysics, derived from the work of Toon et al. (1988). The standard code has been adapted to treat H2O and H2SO4 as co-condensing vapor species onto aqueous H2SO4 cloud droplets, as well as the nucleation of condensation nuclei to droplets. Vapor condensation and evaporation follows the method of James et al. (1997). Microphysical processes included in this model include nucleation of condensation nuclei, condensation and evaporation of H2O and H2SO4 vapor, and droplet coagulation. Vertical transport occurs though advection, eddy diffusion, sedimentation for both droplets and condensation nuclei. The cloud model is used to explore the sensitivity of Venus' cloud layer to environmental changes. Observations of the Venus' lower cloud from the Pioneer Venus, Venera, and Galileo spacecraft have suggested that the properties of the lower cloud may be time-variable, and at times may be entirely absent (Carlson et al. 1993, Grinspoon et al. 1993, Esposito et al. 1997). Our model explores the dependence of such behavior on environment factors such as variations in water or SO2 abundance. We have also calculated the optical properties of the model atmosphere using both the conventional optical constants for H2SO4 (Palmer and Williams, 1975), and the new data of Tisdale et al. (1998). This work has been supported by NASA's Exobiology Program. References Carlson, R.W., et al., 1993. Planetary and Space Science, 41, 477-486. Esposito, L.W., et al., 1997. In Venus II, eds. S.W. Bougher et al., pp. 415-458, University of Arizona Press, Tucson. Grinspoon, D.H., et al., 1993. Planetary and Space Science, 41 (July 1993), 515-542. James, E. P., et al., 1997. Icarus, 129, 147-171. Palmer, K.F., and D. Williams, 1975. Applied Optics, 14, 208-219. Tisdale, R.T., et al., 1998. Journal of Geophysical Research, 103, 25,353-25,370. Toon , O. B., et al., 1988. J. Atmos. Sci., 45, 2123-2143.
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SCUBA and HIRES Results for Protostellar Cores in the MON OB1 Dark Cloud
NASA Astrophysics Data System (ADS)
Wolf-Chase, G.; Moriarty-Schieven, G.; Fich, M.; Barsony, M.
1999-05-01
We have used HIRES-processing of IRAS data and point-source modelling techniques (Hurt & Barsony 1996; O'Linger 1997; Barsony et al. 1998), together with submillimeter continuum imaging using the Submillimeter Common-User Bolometer Array (SCUBA) on the 15-meter James Clerk Maxwell Telescope (JCMT), to search CS cores in the Mon OB1 dark cloud (Wolf-Chase, Walker, & Lada 1995; Wolf-Chase & Walker 1995) for deeply embedded sources. These observations, as well as follow-up millimeter photometry at the National Radio Astronomy Observatory (NRAO) 12-meter telescope on Kitt Peak, have lead to the identification of two Class 0 protostellar candidates, which were previously unresolved from two brighter IRAS point sources (IRAS 06382+0939 & IRAS 06381+1039) in this cloud. Until now, only one Class 0 object had been confirmed in Mon OB1; the driving source of the highly-collimated outflow NGC 2264 G (Ward-Thompson, Eiroa, & Casali 1995; Margulis et al. 1990; Lada & Fich 1996), which lies well outside the extended CS cores. One of the new Class 0 candidates may be an intermediate-mass source associated with an H_2O maser, and the other object is a low-mass source which may be associated with a near-infrared jet, and possibly with a molecular outflow. We report accurate positions for the new Class 0 candidates, based on the SCUBA images, and present new SEDs for these sources, as well as for the brighter IRAS point sources. A portion of this work was performed while GWC held a President's Fellowship from the University of California. MB and GWC gratefully acknowledge financial support from MB's NSF CAREER Grant, AST97-9753229.
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Point-Cloud Compression for Vehicle-Based Mobile Mapping Systems Using Portable Network Graphics
NASA Astrophysics Data System (ADS)
Kohira, K.; Masuda, H.
2017-09-01
A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds, and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.
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Response to "The Iris Hypothesis: A Negative or Positive Cloud Feedback?"
NASA Technical Reports Server (NTRS)
Chou, Ming-Dah; Lindzen, Richard S.; Hou, Arthur Y.; Lau, William K. M. (Technical Monitor)
2001-01-01
Based on radiance measurements of Japan's Geostationary Meteorological Satellite, Lindzen et al. found that the high-level cloud cover averaged over the tropical western Pacific decreases with increasing sea surface temperature. They further found that the response of high-level clouds to the sea surface temperature had an effect of reducing the magnitude of climate change, which is referred as a negative climate feedback. Lin et al. reassessed the results found by Lindzen et al. by analyzing the radiation and clouds derived from the Tropical Rainfall Measuring Mission Clouds and the Earth's Radiant Energy System measurements. They found a weak positive feedback between high-level clouds and the surface temperature. We have found that the approach taken by Lin et al. to estimating the albedo and the outgoing longwave radiation is incorrect and that the inferred climate sensitivity is unreliable.
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The registration of non-cooperative moving targets laser point cloud in different view point
NASA Astrophysics Data System (ADS)
Wang, Shuai; Sun, Huayan; Guo, Huichao
2018-01-01
Non-cooperative moving target multi-view cloud registration is the key technology of 3D reconstruction of laser threedimension imaging. The main problem is that the density changes greatly and noise exists under different acquisition conditions of point cloud. In this paper, firstly, the feature descriptor is used to find the most similar point cloud, and then based on the registration algorithm of region segmentation, the geometric structure of the point is extracted by the geometric similarity between point and point, The point cloud is divided into regions based on spectral clustering, feature descriptors are created for each region, searching to find the most similar regions in the most similar point of view cloud, and then aligning the pair of point clouds by aligning their minimum bounding boxes. Repeat the above steps again until registration of all point clouds is completed. Experiments show that this method is insensitive to the density of point clouds and performs well on the noise of laser three-dimension imaging.
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NASA Astrophysics Data System (ADS)
Chimot, Julien; Vlemmix, Tim; Veefkind, Pepijn; Levelt, Pieternel
2016-04-01
Numerous studies have drawn attention to the complexities related to the retrievals of tropospheric NO2 columns derived from satellite UltraViolet-Visible (UV-Vis) measurements in the presence of aerosols. Correction for aerosol effects will remain a challenge for the next generation of air quality satellite instruments such as TROPOMI on Sentinel-5 Precursor, Sentinel-4 and Sentinel-5. The Ozone Monitoring Instrument (OMI) instrument has provided daily global measurements of tropospheric NO2 for more than a decade. However, aerosols are not explicitly taken into account in the current operational OMI tropospheric NO2 retrieval chain (DOMINO v2 [Boersma et al., 2011]). Our study analyses 2 approaches for an operational aerosol correction, based on the use of the O2-O2 477 nm band. The 1st approach is the cloud-model based aerosol correction, also named "implicit aerosol correction", and already used in the operational chain. The OMI O2-O2 cloud retrieval algorithm, based on the Differential Optical Absorption Spectroscopy (DOAS) approach, is applied both to cloudy and to cloud-free scenes with aerosols present. Perturbation of the OMI cloud retrievals over scenes dominated by aerosols has been observed in recent studies led by [Castellanos et al., 2015; Lin et al., 2015; Lin et al., 2014]. We investigated the causes of these perturbations by: (1) confronting the OMI tropospheric NO2, clouds and MODIS AQUA aerosol products; (2) characterizing the key drivers of the aerosol net effects, compared to a signal from clouds, in the UV-Vis spectra. This study has focused on large industrialised areas like East-China, over cloud-free scenes. One of the key findings is the limitation due to the coarse sampling of the employed cloud Look-Up Table (LUT) to convert the results of the applied DOAS fit into effective cloud fraction and pressure. This leads to an underestimation of tropospheric NO2 amount in cases of particles located at elevated altitude. A higher sampling of the variation of O2-O2 SCD and continuum reflectance as a function of effective cloud parameters in case of low effective cloud fraction values is requested for applying an aerosol correction. The updates of the OMI O2-O2 cloud algorithm, based on the scheduled new OMI cloud LUT, will be presented in terms of impacts of the effective cloud retrievals and reduced biases of tropospheric NO2 columns over cloud-free scenes dominated by aerosols in China. A 2nd approach is investigated, assuming a more explicit aerosol correction. Previous analyses pointed out that the O2-O2 spectra contain information about aerosols: the continuum reflectance is primarily constrained by the Aerosol Optical thickness (AOT) while the O2-O2 Slant Column Density (SCD) mostly results from the combination of AOT and aerosols altitude. We have developed a first prototype algorithm allowing to retrieve information about AOT and aerosol altitude from the O2-O2 DOAS fit. We will discuss preliminary sensitivities and the potential accuracy of the associated explicit aerosol correction, without the use of effective cloud parameters.
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He, Ying; Liang, Bin; Yang, Jun; Li, Shunzhi; He, Jin
2017-08-11
The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this requirement. In this paper, we proposed the ICP algorithm based on point cloud features (GF-ICP). This method uses the geometrical features of the point cloud to be registered, such as curvature, surface normal and point cloud density, to search for the correspondence relationships between two point clouds and introduces the geometric features into the error function to realize the accurate registration of two point clouds. The experimental results showed that the algorithm can improve the convergence speed and the interval of convergence without setting a proper initial value.
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Liang, Bin; Yang, Jun; Li, Shunzhi; He, Jin
2017-01-01
The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this requirement. In this paper, we proposed the ICP algorithm based on point cloud features (GF-ICP). This method uses the geometrical features of the point cloud to be registered, such as curvature, surface normal and point cloud density, to search for the correspondence relationships between two point clouds and introduces the geometric features into the error function to realize the accurate registration of two point clouds. The experimental results showed that the algorithm can improve the convergence speed and the interval of convergence without setting a proper initial value. PMID:28800096
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Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.; ...
2017-08-11
Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept ofmore » instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.
Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept ofmore » instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Xiaoqing Wu; Xin-Zhong Liang; Sunwook Park
2007-01-23
The works supported by this ARM project lay the solid foundation for improving the parameterization of subgrid cloud-radiation interactions in the NCAR CCSM and the climate simulations. We have made a significant use of CRM simulations and concurrent ARM observations to produce long-term, consistent cloud and radiative property datasets at the cloud scale (Wu et al. 2006, 2007). With these datasets, we have investigated the mesoscale enhancement of cloud systems on surface heat fluxes (Wu and Guimond 2006), quantified the effects of cloud horizontal inhomogeneity and vertical overlap on the domain-averaged radiative fluxes (Wu and Liang 2005), and subsequently validatedmore » and improved the physically-based mosaic treatment of subgrid cloud-radiation interactions (Liang and Wu 2005). We have implemented the mosaic treatment into the CCM3. The 5-year (1979-1983) AMIP-type simulation showed significant impacts of subgrid cloud-radiation interaction on the climate simulations (Wu and Liang 2005). We have actively participated in CRM intercomparisons that foster the identification and physical understanding of common errors in cloud-scale modeling (Xie et al. 2005; Xu et al. 2005, Grabowski et al. 2005).« less
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Ionisation in ultra-cool, cloud forming extrasolar planetary atmospheres
NASA Astrophysics Data System (ADS)
Helling, Christiane; the LEAP Team
2015-04-01
Transit spectroscopy provides evidence that extrasolare planets are covered in clouds, a finding that has been forecast by cloud model simulations 15 years ago. Atmospheres are strongly affected by clouds through their large opacity and their chemical activity. Cloud formation models allow to predict cloud particle sizes, their chemical composition and the composition of the remaining atmospheric gas (Woitke & Helling 2004, A&A 414; Helling & Woitke 2006, A&A 455), for example, as input for radiative transfer codes like Drift-Phoenix (Witte et al. 2009; A&A 506). These cloud particles are charged and can discharge, for example in form of lighting (Helling et al. 2013, ApJ 767; Bailey et al. 2014, ApJ 784). Earth observations demonstrate that lighting effects not only the local chemistry but also the electron budget of the atmosphere. This talk will present our work on cloud formation modelling and ionisation processes in cloud forming atmospheres. An hierarchy of ionisation processes leads to a vertically inhomogenously ionised atmosphere which has implications for planetary mass loss and global circulation pattern of planetary atmospheres. Processes involved, like Cosmic Ray ionisation, do also activate the local chemistry such that large hydrocarbon molecules form (Rimmer et al. 2014, IJAsB 13).
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Titan's atmosphere (clouds and composition): new results
NASA Astrophysics Data System (ADS)
Griffith, C. A.
Titan's atmosphere potentially sports a cycle similar to the hydrologic one on Earth with clouds, rain and seas, but with methane playing the terrestrial role of water. Over the past ten years many independent efforts indicated no strong evidence for cloudiness until some unique spectra were analyzed in 1998 (Griffith et al.). These surprising observations displayed enhanced fluxes of 14-200 % on two nights at precisely the wavelengths (windows) that sense Titan's lower altitude where clouds might reside. The morphology of these enhancements in all 4 windows observed indicate that clouds covered ~6-9 % of Titan's surface and existed at ~15 km altitude. Here I discuss new observations recorded in 1999 aimed to further characterize Titan's clouds. While we find no evidence for a massive cloud system similar to the one observed previously, 1%-4% fluctuations in flux occur daily. These modulations, similar in wavelength and morphology to the more pronounced ones observed earlier, suggest the presence of clouds covering ≤1% of Titan's disk. The variations are too small to have been detected by most prior measurements. Repeated observations, spaced 30 minutes apart, indicate a temporal variability observable in the time scale of a couple of hours. The cloud heights hint that convection might govern their evolution. Their short lives point to the presence of rain.
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Automatic derivation of natural and artificial lineaments from ALS point clouds in floodplains
NASA Astrophysics Data System (ADS)
Mandlburger, G.; Briese, C.
2009-04-01
Water flow is one of the most important driving forces in geomorphology and river systems have ever since formed our landscapes. With increasing urbanisation fertile flood plains were more and more cultivated and the defence of valuable settlement areas by dikes and dams became an important issue. Today, we are dealing with landscapes built up by natural as well as man-made artificial forces. In either case the general shape of the terrain can be portrayed by lineaments representing discontinuities of the terrain slope. Our contribution, therefore, presents an automatic method for delineating natural and artificial structure lines based on randomly distributed point data with high density of more than one point/m2. Preferably, the last echoes of airborne laser scanning (ALS) point clouds are used, since the laser signal is able to penetrate vegetation through small gaps in the foliage. Alternatively, point clouds from (multi) image matching can be employed, but poor ground point coverage in vegetated areas is often the limiting factor. Our approach is divided into three main steps: First, potential 2D start segments are detected by analyzing the surface curvature in the vicinity of each data point, second, the detailed 3D progression of each structure line is modelled patch-wise by intersecting surface pairs (e.g. planar patch pairs) based on the detected start segments and by performing line growing and, finally, post-processing like line cleaning, smoothing and networking is carried out in a last step. For the initial detection of start segments a best fitting two dimensional polynomial surface (quadric) is computed in each data point based on a set of neighbouring points, from which the minimum and maximum curvature is derived. Patches showing high maximum and low minimum curvatures indicate linear discontinuities in the surface slope and serve as start segments for the subsequent 3D modelling. Based on the 2D location and orientation of the start segments, surface patches can be identified as to the left or the right of the structure line. For each patch pair the intersection line is determined by least squares adjustment. The stochastic model considers the planimetric accuracy of the start segments, and the vertical measurement errors in the data points. A robust estimation approach is embedded in the patch adjustment for elimination of off-terrain ALS last echo points. Starting from an initial patch pair, structure line modelling is continued in forward and backward direction as long as certain thresholds (e.g. minimum surface intersection angles) are fulfilled. In the final post-processing step the resulting line set is cleaned by connecting corresponding line parts, by removing short line strings of minor relevance, and by thinning the resulting line set with respect to a certain approximation tolerance in order to reduce the amount of line data. Thus, interactive human verification and editing is limited to a minimum. In a real-world example structure lines were computed for a section of the river Main (ALS, last echoes, 4 points/m2) demonstrating the high potential of the proposed method with respect to accuracy and completeness. Terrestrial control measurements have confirmed the high accuracy expectations both in planimetry (<0.4m) and height (<0.2m).
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Multilayered Clouds Identification and Retrieval for CERES Using MODIS
NASA Technical Reports Server (NTRS)
Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung
2006-01-01
Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.
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Wang, Feng; Tzanakis, Iakovos; Eskin, Dmitry; Mi, Jiawei; Connolley, Thomas
2017-11-01
The cavitation-induced fragmentation of primary crystals formed in Al alloys were investigated for the first time by high-speed imaging using a novel experimental approach. Three representative primary crystal types, Al 3 Ti, Si and Al 3 V with different morphologies and mechanical properties were first extracted by deep etching of the corresponding Al alloys and then subjected to ultrasonic cavitation processing in distilled water. The dynamic interaction between the cavitation bubbles and primary crystals was imaged in situ and in real time. Based on the recorded image sequences, the fragmentation mechanisms of primary crystals were studied. It was found that there are three major mechanisms by which the primary crystals were fragmented by cavitation bubbles. The first one was a slow process via fatigue-type failure. A cyclic pressure exerted by stationary pulsating bubbles caused the propagation of a crack pre-existing in the primary crystal to a critical length which led to fragmentation. The second mechanism was a sudden process due to the collapse of bubbles in a passing cavitation cloud. The pressure produced upon the collapse of the cloud promoted rapid monotonic crack growth and fast fracture in the primary crystals. The third observed mechanism was normal bending fracture as a result of the high pressure arising from the collapse of a bubble cloud and the crack formation at the branch connection points of dendritic primary crystals. The fragmentation of dendrite branches due to the interaction between two freely moving dendritic primary crystals was also observed. A simplified fracture analysis of the observed phenomena was performed. The specific fragmentation mechanism for the primary crystals depended on their morphology and mechanical properties. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Barkhatov, N. A.; Revunov, S. E.; Vorobjev, V. G.; Yagodkina, O. I.
2018-03-01
The cause-and-effect relations of the dynamics of high-latitude geomagnetic activity (in terms of the AL index) and the type of the magnetic cloud of the solar wind are studied with the use of artificial neural networks. A recurrent neural network model has been created based on the search for the optimal physically coupled input and output parameters characterizing the action of a plasma flux belonging to a certain magnetic cloud type on the magnetosphere. It has been shown that, with IMF components as input parameters of neural networks with allowance for a 90-min prehistory, it is possible to retrieve the AL sequence with an accuracy to 80%. The successful retrieval of the AL dynamics by the used data indicates the presence of a close nonlinear connection of the AL index with cloud parameters. The created neural network models can be applied with high efficiency to retrieve the AL index, both in periods of isolated magnetospheric substorms and in periods of the interaction between the Earth's magnetosphere and magnetic clouds of different types. The developed model of AL index retrieval can be used to detect magnetic clouds.
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Speeding Clouds May Reveal Invisible Black Holes
NASA Astrophysics Data System (ADS)
Kohler, Susanna
2017-07-01
Several small, speeding clouds have been discovered at the center of our galaxy. A new study suggests that these unusual objects may reveal the lurking presence of inactive black holes.Peculiar Cloudsa) Velocity-integrated intensity map showing the location of the two high-velocity compact clouds, HCN0.0090.044 and HCN0.0850.094, in the context of larger molecular clouds. b) and c) Latitude-velocity and longitude-velocity maps for HCN0.0090.044 and HCN0.0850.094, respectively. d) and e) spectra for the two compacts clouds, respectively. Click for a closer look. [Takekawa et al. 2017]Sgr A*, the supermassive black hole marking the center of our galaxy, is surrounded by a region roughly 650 light-years across known as the Central Molecular Zone. This area at the heart of our galaxy is filled with large amounts of warm, dense molecular gas that has a complex distribution and turbulent kinematics.Several peculiar gas clouds have been discovered within the Central Molecular Zone within the past two decades. These clouds, dubbed high-velocity compact clouds, are characterized by their compact sizes and extremely broad velocity widths.What created this mysterious population of energetic clouds? The recent discovery of two new high-velocity compact clouds, reported on in a paper led by Shunya Takekawa (Keio University, Japan), may help us to answer this question.Two More to the CountUsing the James Clerk Maxwell Telescope in Hawaii, Takekawa and collaborators detected the small clouds near the circumnuclear disk at the centermost part of our galaxy. These two clouds have velocity spreads of -80 to -20 km/s and -80 to 0 km/s and compact sizes of just over 1 light-year. The clouds similar appearances and physical properties suggest that they may both have been formed by the same process.Takekawa and collaborators explore and discard several possible origins for these clouds, such as outflows from massive protostars (no massive, luminous stars have been detected affiliated with these clouds), interaction with supernova remnants (no supernova remnants have been detected toward the clouds), and cloudcloud collisions (such collisions leave other signs, like cavities in the parent cloud, which are not detected here).Masses and velocities of black holes that could create the two high-velocity compact clouds fall above the red and blue lines here. [Takekawa et al. 2017]Revealed on the PlungeAs an alternative explanation, Takekawa and collaborators propose that these two small,speeding cloudswere each created when a massive compact object plunged into a nearby molecular cloud. Since we dont seeany luminous stellar counterparts to the high-velocity compact clouds, this suggests that the responsibleobjects were invisible black holes. As each black hole tore through a molecular cloud, it dragged some of the clouds gas along behind it to form the high-velocity compact cloud.Does this explanation make sense statistically? The authors point out that the number of black holes predicted to silently lurk in the central 30 light-years of the Milky Way is around 10,000. This makes it entirely plausible that we could have caught sight of two of them as they revealed their presence while plunging through molecular clouds.If the authors interpretation is correct, then high-velocity compact clouds provide an excellent opportunity: we can search for these speeding bodiesto potentially discover inactive black holes that would otherwise go undetected.CitationShunya Takekawa et al 2017 ApJL 843 L11. doi:10.3847/2041-8213/aa79ee
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Kedzierski, Michal; Fryskowska, Anna
2014-01-01
Visualization techniques have been greatly developed in the past few years. Three-dimensional models based on satellite and aerial imagery are now being enhanced by models generated using Aerial Laser Scanning (ALS) data. The most modern of such scanning systems have the ability to acquire over 50 points per square meter and to register a multiple echo, which allows the reconstruction of the terrain together with the terrain cover. However, ALS data accuracy is less than 10 cm and the data is often incomplete: there is no information about ground level (in most scanning systems), and often around the facade or structures which have been covered by other structures. However, Terrestrial Laser Scanning (TLS) not only acquires higher accuracy data (1–5 cm) but is also capable of registering those elements which are incomplete or not visible using ALS methods (facades, complicated structures, interiors, etc.). Therefore, to generate a complete 3D model of a building in high Level of Details, integration of TLS and ALS data is necessary. This paper presents the wavelet-based method of processing and integrating data from ALS and TLS. Methods of choosing tie points to combine point clouds in different datum will be analyzed. PMID:25004157
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Kedzierski, Michal; Fryskowska, Anna
2014-07-07
Visualization techniques have been greatly developed in the past few years. Three-dimensional models based on satellite and aerial imagery are now being enhanced by models generated using Aerial Laser Scanning (ALS) data. The most modern of such scanning systems have the ability to acquire over 50 points per square meter and to register a multiple echo, which allows the reconstruction of the terrain together with the terrain cover. However, ALS data accuracy is less than 10 cm and the data is often incomplete: there is no information about ground level (in most scanning systems), and often around the facade or structures which have been covered by other structures. However, Terrestrial Laser Scanning (TLS) not only acquires higher accuracy data (1-5 cm) but is also capable of registering those elements which are incomplete or not visible using ALS methods (facades, complicated structures, interiors, etc.). Therefore, to generate a complete 3D model of a building in high Level of Details, integration of TLS and ALS data is necessary. This paper presents the wavelet-based method of processing and integrating data from ALS and TLS. Methods of choosing tie points to combine point clouds in different datum will be analyzed.
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NASA Technical Reports Server (NTRS)
Marley, Mark Scott
2016-01-01
Over the past several years a number of high cadence photometric observations of solar system giant planets have been acquired by various platforms. Such observations are of interest as they provide points of comparison to the already expansive set of brown dwarf variability observations and the small, but growing, set of exoplanet variability observations. By measuring how rapidly the integrated light from solar system giant planets can evolve, variability observations of substellar objects that are unlikely to ever be resolved can be placed in a fuller context. Examples of brown dwarf variability observations include extensive work from the ground (e.g., Radigen et al. 2014), Spitzer (e.g., Metchev et al. 2015), Kepler (Gizis et al. 2015), and HST (Yang et al. 2015).Variability has been measured on the planetary mass companion to the brown dwarf 2MASS 1207b (Zhou et al. 2016) and further searches are planned in thermal emission for the known directly imaged planets with ground based telescopes (Apai et al. 2016) and in reflected light with future space based telescopes. Recent solar system variability observations include Kepler monitoring of Neptune (Simon et al. 2016) and Uranus, Spitzer observations of Neptune (Stauffer et al. 2016), and Cassini observations of Jupiter (West et al. in prep). The Cassini observations are of particular interest as they measured the variability of Jupiter at a phase angle of approximately 60 deg, comparable to the viewing geometry expected for space based direct imaging of cool extrasolar Jupiters in reflected light. These solar system analog observations capture many of the characteristics seen in brown dwarf variability, including large amplitudes and rapid light curve evolution on timescales as short as a few rotation periods. Simon et al. (2016) attribute such variations at Neptune to a combination of large scale, stable cloud structures along with smaller, more rapidly varying, cloud patches. The observed brown dwarf and exoplanet variability may well arise from comparable cloud structures. In my presentation I will compare and contrast the nature of the variability observed for the various solar system and other substelar objects and present a wish list for future observations.
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NASA Astrophysics Data System (ADS)
Marley, Mark S.; Kepler Giant Planet Variability Team, Spitzer Ice Giant Variability Team
2016-10-01
Over the past several years a number of of high cadence photometric observations of solar system giant planets have been acquired by various platforms. Such observations are of interest as they provide points of comparison to the already expansive set of brown dwarf variability observations and the small, but growing, set of exoplanet variability observations. By measuring how rapidly the integrated light from solar system giant planets can evolve, variability observations of substellar objects that are unlikely to ever be resolved can be placed in a fuller context. Examples of brown dwarf variability observations include extensive work from the ground (e.g., Radigan et al. 2014), Spitzer (e.g., Metchev et al. 2015), Kepler (Gizis et al. 2015), and HST (Yang et al. 2015). Variability has been measured on the planetary mass companion to the brown dwarf 2MASS 1207b (Zhou et al. 2016) and further searches are planned in thermal emission for the known directly imaged planets with ground based telescopes (Apai et al. 2016) and in reflected light with future space based telescopes. Recent solar system variability observations include Kepler monitoring of Neptune (Simon et al. 2016) and Uranus, Spitzer observations of Neptune (Stauffer et al. 2016), and Cassini observations of Jupiter (West et al. in prep). The Cassini observations are of particular interest as they measured the variability of Jupiter at a phase angle of ˜60○, comparable to the viewing geometry expected for space based direct imaging of cool extrasolar Jupiters in reflected light. These solar system analog observations capture many of the characteristics seen in brown dwarf variability, including large amplitudes and rapid light curve evolution on timescales as short as a few rotation periods. Simon et al. (2016) attribute such variations at Neptune to a combination of large scale, stable cloud structures along with smaller, more rapidly varying, cloud patches. The observed brown dwarf and exoplanet variability may well arise from comparable cloud structures. In my presentation I will compare and contrast the nature of the variability observed for the various solar system and other substellar objects and present a wish list for future observations.
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Registration algorithm of point clouds based on multiscale normal features
NASA Astrophysics Data System (ADS)
Lu, Jun; Peng, Zhongtao; Su, Hang; Xia, GuiHua
2015-01-01
The point cloud registration technology for obtaining a three-dimensional digital model is widely applied in many areas. To improve the accuracy and speed of point cloud registration, a registration method based on multiscale normal vectors is proposed. The proposed registration method mainly includes three parts: the selection of key points, the calculation of feature descriptors, and the determining and optimization of correspondences. First, key points are selected from the point cloud based on the changes of magnitude of multiscale curvatures obtained by using principal components analysis. Then the feature descriptor of each key point is proposed, which consists of 21 elements based on multiscale normal vectors and curvatures. The correspondences in a pair of two point clouds are determined according to the descriptor's similarity of key points in the source point cloud and target point cloud. Correspondences are optimized by using a random sampling consistency algorithm and clustering technology. Finally, singular value decomposition is applied to optimized correspondences so that the rigid transformation matrix between two point clouds is obtained. Experimental results show that the proposed point cloud registration algorithm has a faster calculation speed, higher registration accuracy, and better antinoise performance.
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Accuracy assessment of building point clouds automatically generated from iphone images
NASA Astrophysics Data System (ADS)
Sirmacek, B.; Lindenbergh, R.
2014-06-01
Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable. In this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone video file as an input. We register such automatically generated point cloud on a TLS point cloud of the same object to discuss accuracy, advantages and limitations of the iPhone generated point clouds. For the chosen example showcase, we have classified 1.23% of the iPhone point cloud points as outliers, and calculated the mean of the point to point distances to the TLS point cloud as 0.11 m. Since a TLS point cloud might also include measurement errors and noise, we computed local noise values for the point clouds from both sources. Mean (μ) and standard deviation (σ) of roughness histograms are calculated as (μ1 = 0.44 m., σ1 = 0.071 m.) and (μ2 = 0.025 m., σ2 = 0.037 m.) for the iPhone and TLS point clouds respectively. Our experimental results indicate possible usage of the proposed automatic 3D model generation framework for 3D urban map updating, fusion and detail enhancing, quick and real-time change detection purposes. However, further insights should be obtained first on the circumstances that are needed to guarantee a successful point cloud generation from smartphone images.
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NASA Astrophysics Data System (ADS)
Sims-Waterhouse, D.; Bointon, P.; Piano, S.; Leach, R. K.
2017-06-01
In this paper we show that, by using a photogrammetry system with and without laser speckle, a large range of additive manufacturing (AM) parts with different geometries, materials and post-processing textures can be measured to high accuracy. AM test artefacts have been produced in three materials: polymer powder bed fusion (nylon-12), metal powder bed fusion (Ti-6Al-4V) and polymer material extrusion (ABS plastic). Each test artefact was then measured with the photogrammetry system in both normal and laser speckle projection modes and the resulting point clouds compared with the artefact CAD model. The results show that laser speckle projection can result in a reduction of the point cloud standard deviation from the CAD data of up to 101 μm. A complex relationship with surface texture, artefact geometry and the laser speckle projection is also observed and discussed.
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The Dependence of Cloud-SST Feedback on Circulation Regime and Timescale
NASA Astrophysics Data System (ADS)
Middlemas, E.; Clement, A. C.; Medeiros, B.
2017-12-01
Studies suggest cloud radiative feedback amplifies internal variability of Pacific sea surface temperature (SST) on interannual-and-longer timescales, though only a few modeling studies have tested the quantitative importance of this feedback (Bellomo et al. 2014b, Brown et al. 2016, Radel et al. 2016 Burgman et al. 2017). We prescribe clouds from a previous control run in the radiation module in Community Atmospheric Model (CAM5-slab), a method called "cloud-locking". By comparing this run to a control run, in which cloud radiative forcing can feedback on the climate system, we isolate the effect of cloud radiative forcing on SST variability. Cloud-locking prevents clouds from radiatively interacting with atmospheric circulation, water vapor, and SST, while maintaining a similar mean state to the control. On all timescales, cloud radiative forcing's influence on SST variance is modulated by the circulation regime. Cloud radiative forcing amplifies SST variance in subsiding regimes and dampens SST variance in convecting regimes. In this particular model, a tug of war between latent heat flux and cloud radiative forcing determines the variance of SST, and the winner depends on the timescale. On decadal-and-longer timescales, cloud radiative forcing plays a relatively larger role than on interannual-and-shorter timescales, while latent heat flux plays a smaller role. On longer timescales, the absence of cloud radiative feedback changes SST variance in a zonally asymmetric pattern in the Pacific Ocean that resembles an IPO-like pattern. We also present an analysis of cloud feedback's role on Pacific SST variability among preindustrial control CMIP5 models to test the model robustness of our results. Our results suggest that circulation plays a crucial role in cloud-SST feedbacks across the globe and cloud radiative feedbacks cannot be ignored when studying SST variability on decadal-and-longer timescales.
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NASA Astrophysics Data System (ADS)
Earlie, C. S.; Masselink, G.; Russell, P.; Shail, R.; Kingston, K.
2013-12-01
Our understanding of the evolution of hard rock coastlines is limited due to the episodic nature and ';slow' rate at which changes occur. High-resolution surveying techniques, such as Terrestrial Laser Scanning (TLS), have just begun to be adopted as a method of obtaining detailed point cloud data to monitor topographical changes over short periods of time (weeks to months). However, the difficulties involved in comparing consecutive point cloud data sets in a complex three-dimensional plane, such as occlusion due to surface roughness and positioning of data capture point as a result of a consistently changing environment (a beach profile), mean that comparing data sets can lead to errors in the region of 10 - 20 cm. Meshing techniques are often used for point cloud data analysis for simple surfaces, but in surfaces such as rocky cliff faces, this technique has been found to be ineffective. Recession rates of hard rock coastlines in the UK are typically determined using aerial photography or airborne LiDAR data, yet the detail of the important changes occurring to the cliff face and toe are missed using such techniques. In this study we apply an algorithm (M3C2 - Multiscale Model to Model Cloud Comparison), initially developed for analysing fluvial morphological change, that directly compares point to point cloud data using surface normals that are consistent with surface roughness and measure the change that occurs along the normal direction (Lague et al., 2013). The surfaces changes are analysed using a set of user defined scales based on surface roughness and registration error. Once the correct parameters are defined, the volumetric cliff face changes are calculated by integrating the mean distance between the point clouds. The analysis has been undertaken at two hard rock sites identified for their active erosion located on the UK's south west peninsular at Porthleven in south west Cornwall and Godrevy in north Cornwall. Alongside TLS point cloud data, in-situ measurements of the nearshore wave climate, using a pressure transducer, offshore wave climate from a directional wavebuoy, and rainfall records from nearby weather stations were collected. Combining beach elevation information from the georeferenced point clouds with a continuous time series of wave climate provides an indication of the variation in wave energy delivered to the cliff face. The rates of retreat were found to agree with the existing rates that are currently used in shoreline management. The additional geotechnical detail afforded by applying the M3C2 method to a hard rock environment provides not only a means of obtaining volumetric changes with confidence, but also a clear illustration of the locations of failure on the cliff face. Monthly cliff scans help to narrow down the timings of failure under energetic wave conditions or periods of heavy rainfall. Volumetric changes and sensitive regions to failure established using this method allows us to capture episodic changes to the cliff face at a high resolution (1 - 2 cm) that are otherwise missed using lower resolution techniques typically used for shoreline management, and to understand in greater detail the geotechnical behaviour of hard rock cliffs and determine rates of erosion with greater accuracy.
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Performance Evaluation of sUAS Equipped with Velodyne HDL-32E LiDAR Sensor
NASA Astrophysics Data System (ADS)
Jozkow, G.; Wieczorek, P.; Karpina, M.; Walicka, A.; Borkowski, A.
2017-08-01
The Velodyne HDL-32E laser scanner is used more frequently as main mapping sensor in small commercial UASs. However, there is still little information about the actual accuracy of point clouds collected with such UASs. This work evaluates empirically the accuracy of the point cloud collected with such UAS. Accuracy assessment was conducted in four aspects: impact of sensors on theoretical point cloud accuracy, trajectory reconstruction quality, and internal and absolute point cloud accuracies. Theoretical point cloud accuracy was evaluated by calculating 3D position error knowing errors of used sensors. The quality of trajectory reconstruction was assessed by comparing position and attitude differences from forward and reverse EKF solution. Internal and absolute accuracies were evaluated by fitting planes to 8 point cloud samples extracted for planar surfaces. In addition, the absolute accuracy was also determined by calculating point 3D distances between LiDAR UAS and reference TLS point clouds. Test data consisted of point clouds collected in two separate flights performed over the same area. Executed experiments showed that in tested UAS, the trajectory reconstruction, especially attitude, has significant impact on point cloud accuracy. Estimated absolute accuracy of point clouds collected during both test flights was better than 10 cm, thus investigated UAS fits mapping-grade category.
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A shape-based segmentation method for mobile laser scanning point clouds
NASA Astrophysics Data System (ADS)
Yang, Bisheng; Dong, Zhen
2013-07-01
Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well.
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NASA Astrophysics Data System (ADS)
Giorio, Chiara; Brégonzio-Rozier, Lola; Siekmann, Frank; Cazaunau, Mathieu; Temime-Roussel, Brice; Langley DeWitt, Helen; Gratien, Aline; Michoud, Vincent; Pangui, Edouard; Morales, Sébastien; Ravier, Sylvain; Zielinski, Arthur T.; Tapparo, Andrea; Vermeylen, Reinhilde; Claeys, Magda; Voisin, Didier; Salque-Moreton, Guillaume; Kalberer, Markus; Doussin, Jean-François; Monod, Anne
2017-04-01
Biogenic volatile organic compounds (BVOCs) undergo atmospheric processing and form a wide range of oxidised and water-soluble compounds. These compounds could partition into atmospheric water droplets, and react within the aqueous phase producing higher molecular weight and less volatile compounds which could remain in the particle phase after water evaporation (Ervens et al., 2011). The aim of this work was the molecular characterisation of secondary organic aerosol (SOA) formed from the photooxidation of isoprene and methacrolein during cloud evapo-condensation cycles. The experiments were performed within the CUMULUS project (CloUd MULtiphase chemistry of organic compoUndS in the troposphere), at the 4.2 m3 stainless steel CESAM chamber at LISA (Brégonzio-Rozier et al., 2016). In each experiment, isoprene or methacrolein was photooxidised with HONO and clouds have been produced to study oxidation processes in a multiphase environment that well simulates the interactions between VOCs, SOA particles and cloud droplets. During all the experiments, SOA was characterised online with a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and offline with gas chromatography mass spectrometry (GC-MS) and direct infusion nanoelectrospray ionisation high resolution mass spectrometry (nanoESI-HRMS). We observed that the main SOA compound in all experiments was 2-methylglyceric acid which undergoes oligomerisation reactions. A large number of long homologous series of oligomers were detected in all experiments, together with a complex co-oligomerised system made of monomers with a large variety of different structures. Comparison of SOA from multiphasic (smog chamber) experiments and samples from aqueous phase oxidation of methacrolein with •OH radical pointed out different types of oligomerisation reactions dominating the two different systems. Ervens et al. (2011) Atmos. Chem. Phys. 11, 11069 11102. Brégonzio-Rozier et al. (2016) Atmos. Chem. Phys. 16, 1747 1760.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Leaitch, W.R.; Isaac, G.A.
Comparisons are drawn between the aerosol cloud microphysical theory implicit in the modeling of Kaufman et al. and the cloud droplet and cloud water sulfate concentrations of Leaitch et al. for the purpose of helping to understand the effect of sulfate particle son climate through cloud modification. In terms of the range of possibilities and prospects for future climate given by Kaufman et al. for the effect of sulfur on cloud albedo, the data favor the possibility of stronger cooling. Scatter in the data makes it impossible to constrain model parameters; however, the comparisons suggest that there may not bemore » a universal relationship, and that the uncertainties involved in trying to model this process are large.« less
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Potential New Lidar Observations for Cloud Studies
NASA Technical Reports Server (NTRS)
Winker, Dave; Hu, Yong; Narir, Amin; Cai, Xia
2015-01-01
The response of clouds to global warming represents a major uncertainty in estimating climate sensitivity. These uncertainties have been tracked to shallow marine clouds in the tropics and subtropics. CALIOP observations have already been used extensively to evaluate model predictions of shallow cloud fraction and top height (Leahy et al. 2013; Nam et al 2012). Tools are needed to probe the lowest levels of the troposphere. The large footprint of satellite lidars gives large multiple scattering from clouds which presents new possibilities for cloud retrievals to constrain model predictions.
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NASA Astrophysics Data System (ADS)
Mitchell, Jonathan
2012-04-01
Titan’s methane clouds have received much attention since they were first discovered spectroscopically (Griffith et al. 1998). Titan's seasons evolve slowly, and there is growing evidence of a seasonal response in the regions of methane cloud formation (e.g. Rodriguez et al. 2009). A complete, three-dimensional view of Titan’s clouds is possible through the determination of cloud-top heights from Cassini images (e.g., Ádámkovics et al. 2010). Even though Titan’s surface is warmed by very little sunlight, we now know Titan’s methane clouds are convective, evolving through tens of kilometers of altitude on timescales of hours to days with dynamics similar to clouds that appear on Earth (Porco et al. 2005). Cassini ISS has also shown evidence of rain storms on Titan that produce surface accumulation of methane (Turtle et al. 2009). Most recently, Cassini has revealed a 1000-km-scale, arrow-shaped cloud at the equator followed by changes that appear to be evidence of surface precipitation (Turtle et al. 2011b). Individual convective towers simulated with high fidelity indicate that surface convergence of methane humidity and dynamic lifting are required to trigger deep, precipitating convection (e.g. Barth & Rafkin 2010). The global expanses of these cloud outbursts, the evidence for surface precipitation, and the requirement of dynamic convergence and lifting at the surface to trigger deep convection motivate an analysis of storm formation in the context of Titan’s global circulation. I will review our current understanding of Titan’s methane meteorology using Cassini and ground-based observations and, in particular, global circulation model simulations of Titan’s methane cycle. When compared with cloud observations, our simulations indicate an essential role for planetary-scale atmospheric waves in organizing convective storms on large scales (Mitchell et al. 2011). I will end with predictions of Titan’s weather during the upcoming northern hemisphere summer.
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NASA Astrophysics Data System (ADS)
Dupont, J. C.; Haeffelin, M.; Morille, Y.; Noel, V.; Keckhut, P.; Comstock, J.; Winker, D.; Chervet, P.; Roblin, A.
2009-04-01
Cirrus clouds not only play a major role in the energy budget of the Earth-Atmosphere system, but are also important in the hydrological cycle [Stephens et al., 1990; Webster, 1994]. According to satellite passive remote sensing, high-altitude clouds cover as much as 40% of the earth's surface on average (Liou 1986; Stubenrauch et al., 2006) and can reach 70% of cloud cover over the Tropics (Wang et al., 1996; Nazaryan et al., 2008). Hence, given their very large cloud cover, they have a major role in the climate system (Lynch et al. 2001). Cirrus clouds can be classified into three distinct families according to their optical thickness, namely subvisible clouds (OD<0.03), semi-transparent clouds (0.03
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LSAH: a fast and efficient local surface feature for point cloud registration
NASA Astrophysics Data System (ADS)
Lu, Rongrong; Zhu, Feng; Wu, Qingxiao; Kong, Yanzi
2018-04-01
Point cloud registration is a fundamental task in high level three dimensional applications. Noise, uneven point density and varying point cloud resolutions are the three main challenges for point cloud registration. In this paper, we design a robust and compact local surface descriptor called Local Surface Angles Histogram (LSAH) and propose an effectively coarse to fine algorithm for point cloud registration. The LSAH descriptor is formed by concatenating five normalized sub-histograms into one histogram. The five sub-histograms are created by accumulating a different type of angle from a local surface patch respectively. The experimental results show that our LSAH is more robust to uneven point density and point cloud resolutions than four state-of-the-art local descriptors in terms of feature matching. Moreover, we tested our LSAH based coarse to fine algorithm for point cloud registration. The experimental results demonstrate that our algorithm is robust and efficient as well.
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NASA Astrophysics Data System (ADS)
Buratti, B. J.; Pitman, K. M.; Baines, K.; Sotin, C.; Brown, R. H.; Clark, R. N.; Nicholson, P. D.; Griffith, C. A.; Le Mouelic, S.; Momary, T.
2007-12-01
Mid-latitude clouds on Titan have been monitored by the Cassini spacecraft since they were reported by ground- based observers (Roe et al. 2005, Ap. J. 618, L49). The Cassini Visual Infrared Mapping Spectrometer (VIMS) is especially suited to detecting and mapping these clouds because its wavelength range of 0.4-5.1 microns covers several key methane cloud filters. These clouds may be the result of atmospheric upwelling on Titan (Griffith et al. 2000 Science 290, p. 509; Rannou et al. 2006 Science 311, p. 201), or they may start as plumes coming from active geologic features on Titan (Roe et al. 2005, Science 310, p. 477). Mid-latitude clouds were observed in the early part of the nominal mission (Dec. 2004 and early 2005), but they had disappeared until a large cloud system was observed in summer 2006, in the 0-90 degrees W longitude mid-latitude regions of Titan. A new group of clouds was observed during the two flybys of July 2007, which dwarfs the previous mid-latitude system. These clouds originate in a region centered on ~200 W longitude and ~48 S latitude. Monitoring of mid-latitude clouds will show whether their timescales for formation are compatible with climate models for Titan's atmosphere. If mid-latitude clouds are the result of active geologic processes, there appears to be more than one source on Titan's surface. Work funded by NASA.
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NASA Astrophysics Data System (ADS)
Widemann, T.; Marcq, E.; Tsang, C.; Mueller, N. T.; Kappel, D.; Helbert, J.; Dyar, M. D.; Smrekar, S. E.
2017-12-01
Venus' climate evolution is driven by the energy balance of its global cloud layers. Venus displays the best-known case of polar vortices evolving in a fast-rotating atmosphere. Polar vortices are pervasive in the Solar System and may also be present in atmosphere-bearing exoplanets. While much progress has been made since the early suggestion that the Venus clouds are H2O-H2SO4 liquid droplets (Young 1973), several cloud parameters are still poorly constrained, particularly in the lower cloud layer and optically thicker polar regions. The average particle size is constant over most of the planet but increases toward the poles. This indicates that cloud formation processes are different at latitudes greater than 60°, possibly as a result of the different dynamical regimes that exist in the polar vortices (Carlson et al. 1993, Wilson et al. 2008, Barstow et al. 2012). Few wind measurements exist in the polar region due to unfavorable viewing geometry of currently available observations. Cloud-tracking data indicate circumpolar circulation close to solid-body rotation. E-W winds decrease to zero velocity close to the pole. N-S circulation is marginal, with extremely variable morphology and complex vorticity patterns (Sanchez-Lavega et al. 2008, Luz et al. 2011, Garate-Lopez et al. 2013). The Venus Emissivity Mapper (VEM; Helbert et al., 2016) proposed for NASA's Venus Origins Explorer (VOX) and the ESA M5/EnVision orbiters has the capability to better constrain the microphysics (vertical, horizontal, time dependence of particle size distribution, or/and composition) of the lower cloud particles in three spectral bands at 1.195, 1.310 and 1.510 μm at a spatial resolution of 10 km. Circular polar orbit geometry would provide an unprecedented study of both polar regions within the same mission. In addition, VEM's pushbroom method will allow short timescale cloud dynamics to be assessed, as well as local wind speeds, using repeated imagery at 90 minute intervals. Tracking lower cloud motions as proxies for wind measurements at high spatial resolutions will greatly benefit modeling of the vortice's physics, as well as wave-generating dynamical instabilities (Garate-Lopez et al. 2015).
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Dependence of marine stratocumulus reflectivities on liquid water paths
NASA Technical Reports Server (NTRS)
Coakley, James A., Jr.; Snider, Jack B.
1990-01-01
Simple parameterizations that relate cloud liquid water content to cloud reflectivity are often used in general circulation climate models to calculate the effect of clouds in the earth's energy budget. Such parameterizations have been developed by Stephens (1978) and by Slingo and Schrecker (1982) and others. Here researchers seek to verify the parametric relationship through the use of simultaneous observations of cloud liquid water content and cloud reflectivity. The column amount of cloud liquid was measured using a microwave radiometer on San Nicolas Island following techniques described by Hogg et al., (1983). Cloud reflectivity was obtained through spatial coherence analysis of Advanced Very High Resolution Radiometer (AVHRR) imagery data (Coakley and Beckner, 1988). They present the dependence of the observed reflectivity on the observed liquid water path. They also compare this empirical relationship with that proposed by Stephens (1978). Researchers found that by taking clouds to be isotropic reflectors, the observed reflectivities and observed column amounts of cloud liquid water are related in a manner that is consistent with simple parameterizations often used in general circulation climate models to determine the effect of clouds on the earth's radiation budget. Attempts to use the results of radiative transfer calculations to correct for the anisotropy of the AVHRR derived reflectivities resulted in a greater scatter of the points about the relationship expected between liquid water path and reflectivity. The anisotropy of the observed reflectivities proved to be small, much smaller than indicated by theory. To critically assess parameterizations, more simultaneous observations of cloud liquid water and cloud reflectivities and better calibration of the AVHRR sensors are needed.
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"Analysis of the multi-layered cloud radiative effects at the surface using A-train data"
NASA Astrophysics Data System (ADS)
Viudez-Mora, A.; Smith, W. L., Jr.; Kato, S.
2017-12-01
Clouds cover about 74% of the planet and they are an important part of the climate system and strongly influence the surface energy budget. The cloud vertical distribution has important implications in the atmospheric heating and cooling rates. Based on observations by active sensors in the A-train satellite constellation, CALIPSO [Winker et. al, 2010] and CloudSat [Stephens et. al, 2002], more than 1/3 of all clouds are multi-layered. Detection and retrieval of multi-layer cloud physical properties are needed in understanding their effects on the surface radiation budget. This study examines the sensitivity of surface irradiances to cloud properties derived from satellite sensors. Surface irradiances were computed in two different ways, one using cloud properties solely from MODerate resolution Imaging Spectroradiometer (MODIS), and the other using MODIS data supplemented with CALIPSO and CloudSat (hereafter CLCS) cloud vertical structure information [Kato et. al, 2010]. Results reveal that incorporating more precise and realistic cloud properties from CLCS into radiative transfer calculations yields improved estimates of cloud radiative effects (CRE) at the surface (CREsfc). The calculations using only MODIS cloud properties, comparisons of the computed CREsfc for 2-layer (2L) overcast CERES footprints, CLCS reduces the SW CRE by 1.5±26.7 Wm-2, increases the LW CRE by 4.1±12.7 Wm-2, and increases the net CREsfc by 0.9±46.7 Wm-2. In a subsequent analysis, we classified up to 6 different combinations of multi-layered clouds depending on the cloud top height as: High-high (HH), high-middle (HM), high-low (HL), middle-middle (MM), middle-low (ML) and low-low (LL). The 3 most frequent 2L cloud systems were: HL (56.1%), HM (22.3%) and HH (12.1%). For these cases, the computed CREsfc estimated using CLCS data presented the most significant differences when compared using only MODIS data. For example, the differences for the SW and Net CRE in the case HH was 12.3±47.3 Wm-2 and 16.0±48.45 Wm-2, respectively. For the case of HM, the LW CRE difference was -9.9±14.0 Wm-2. Kato, S., et al. (2010), J. Geophys. Res., 115. Stephens, G. L., et al. (2002), Bull. Am. Meteorol. Soc., 83. Winker, D. M., et al., (2010),Bull. Amer. Meteor. Soc., 91.
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Aerosol processing in stratiform clouds in ECHAM6-HAM
NASA Astrophysics Data System (ADS)
Neubauer, David; Lohmann, Ulrike; Hoose, Corinna
2013-04-01
Aerosol processing in stratiform clouds by uptake into cloud particles, collision-coalescence, chemical processing inside the cloud particles and release back into the atmosphere has important effects on aerosol concentration, size distribution, chemical composition and mixing state. Aerosol particles can act as cloud condensation nuclei. Cloud droplets can take up further aerosol particles by collisions. Atmospheric gases may also be transferred into the cloud droplets and undergo chemical reactions, e.g. the production of atmospheric sulphate. Aerosol particles are also processed in ice crystals. They may be taken up by homogeneous freezing of cloud droplets below -38° C or by heterogeneous freezing above -38° C. This includes immersion freezing of already immersed aerosol particles in the droplets and contact freezing of particles colliding with a droplet. Many clouds do not form precipitation and also much of the precipitation evaporates before it reaches the ground. The water soluble part of the aerosol particles concentrates in the hydrometeors and together with the insoluble part forms a single, mixed, larger particle, which is released. We have implemented aerosol processing into the current version of the general circulation model ECHAM6 (Stevens et al., 2013) coupled to the aerosol module HAM (Stier et al., 2005). ECHAM6-HAM solves prognostic equations for the cloud droplet number and ice crystal number concentrations. In the standard version of HAM, seven modes are used to describe the total aerosol. The modes are divided into soluble/mixed and insoluble modes and the number concentrations and masses of different chemical components (sulphate, black carbon, organic carbon, sea salt and mineral dust) are prognostic variables. We extended this by an explicit representation of aerosol particles in cloud droplets and ice crystals in stratiform clouds similar to Hoose et al. (2008a,b). Aerosol particles in cloud droplets are represented by 5 tracers for the chemical components as well as 5 tracers for aerosol particles in ice crystals. This allows simulations of aerosol processing in warm, mixed-phase (e.g. through the Bergeron-Findeisen process) and ice clouds. The fixed scavenging ratios used for wet deposition in clouds in standard HAM are replaced by an explicit treatment of collision of cloud droplets/ice crystals with interstitial aerosol particles. Nucleation scavenging of aerosol particles by acting as cloud condensation nuclei or ice nuclei, freezing and evaporation of cloud droplets and melting and sublimation of ice crystals are treated explicitly. In extension to previous studies, aerosol particles from evaporating precipitation are released to modes which correspond to their size. Cloud processing of aerosol particles changes their size distribution and hence influences cloud droplet and ice crystal number concentrations as well as precipitation rate, which in turn affects aerosol concentrations. Results will be presented at the conference. Hoose et al., JGR, 2008a, doi: 10.1029/2007JD009251 Hoose et al., ACP, 2008b, doi: 10.5194/acp-8-6939-2008 Stevens et al., 2013, submitted Stier et al., ACP, 2005, doi: 10.5194/acp-5-1125-2005
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Green Bank Telescope Observations of HI in the circumgalactic medium of M31
NASA Astrophysics Data System (ADS)
Denny, Lucas; Early, Laura; Berg, Michelle; Howk, Chris; Lehner, Nicolas; Lockman, Felix; wotta, Christopher
2018-01-01
The nearby spiral galaxy M31 contains an extensive gaseous circumgalactic medium (CGM) that is being studied in project AMIGA, a large HST program to obtain UV spectroscopy of the CGM in absorption against background AGN. As part of this project, sensitive HI 21cm emission observations were made using the Robert C. Byrd Green Bank Telescope (GBT) toward 48 AGN at impact parameters between 25 kpc and 340 kpc. No emission was detected to a 5-sigma limit on log(NHI) of 17.6 cm-2 (Howk et al 2017, ApJ, 846, 141). We now report on a search for HI emission in 1x1 degree fields around 8 of the AGN to 5-sigma limits on log(NHI) of 17.9 cm-2. The new observations cover ~10 times the area of the M31 CGM covered by the Howk et al pointings, though at somewhat reduced sensitivity. Again, no HI emission was detected with the exception of the "Davies Cloud", a high-velocity cloud of M31 that has been known for some time. We will discuss the absence of significant HI emission in the context of the COS-Halos study of 44 galaxies at z~0.2, and how this finding may relate to the existence of HI clouds between M31 and M33 (Wolfe et al. 2016, ApJ, 816, 81).The GBT is a facility of the National Science Foundation, operated under a cooperative agreement by Associated Universities, Inc.
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Isotopic evidence for primordial molecular cloud material in metal-rich carbonaceous chondrites.
Van Kooten, Elishevah M M E; Wielandt, Daniel; Schiller, Martin; Nagashima, Kazuhide; Thomen, Aurélien; Larsen, Kirsten K; Olsen, Mia B; Nordlund, Åke; Krot, Alexander N; Bizzarro, Martin
2016-02-23
The short-lived (26)Al radionuclide is thought to have been admixed into the initially (26)Al-poor protosolar molecular cloud before or contemporaneously with its collapse. Bulk inner Solar System reservoirs record positively correlated variability in mass-independent (54)Cr and (26)Mg*, the decay product of (26)Al. This correlation is interpreted as reflecting progressive thermal processing of in-falling (26)Al-rich molecular cloud material in the inner Solar System. The thermally unprocessed molecular cloud matter reflecting the nucleosynthetic makeup of the molecular cloud before the last addition of stellar-derived (26)Al has not been identified yet but may be preserved in planetesimals that accreted in the outer Solar System. We show that metal-rich carbonaceous chondrites and their components have a unique isotopic signature extending from an inner Solar System composition toward a (26)Mg*-depleted and (54)Cr-enriched component. This composition is consistent with that expected for thermally unprocessed primordial molecular cloud material before its pollution by stellar-derived (26)Al. The (26)Mg* and (54)Cr compositions of bulk metal-rich chondrites require significant amounts (25-50%) of primordial molecular cloud matter in their precursor material. Given that such high fractions of primordial molecular cloud material are expected to survive only in the outer Solar System, we infer that, similarly to cometary bodies, metal-rich carbonaceous chondrites are samples of planetesimals that accreted beyond the orbits of the gas giants. The lack of evidence for this material in other chondrite groups requires isolation from the outer Solar System, possibly by the opening of disk gaps from the early formation of gas giants.
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Isotopic evidence for primordial molecular cloud material in metal-rich carbonaceous chondrites
Van Kooten, Elishevah M. M. E.; Wielandt, Daniel; Schiller, Martin; Nagashima, Kazuhide; Thomen, Aurélien; Olsen, Mia B.; Nordlund, Åke; Krot, Alexander N.; Bizzarro, Martin
2016-01-01
The short-lived 26Al radionuclide is thought to have been admixed into the initially 26Al-poor protosolar molecular cloud before or contemporaneously with its collapse. Bulk inner Solar System reservoirs record positively correlated variability in mass-independent 54Cr and 26Mg*, the decay product of 26Al. This correlation is interpreted as reflecting progressive thermal processing of in-falling 26Al-rich molecular cloud material in the inner Solar System. The thermally unprocessed molecular cloud matter reflecting the nucleosynthetic makeup of the molecular cloud before the last addition of stellar-derived 26Al has not been identified yet but may be preserved in planetesimals that accreted in the outer Solar System. We show that metal-rich carbonaceous chondrites and their components have a unique isotopic signature extending from an inner Solar System composition toward a 26Mg*-depleted and 54Cr-enriched component. This composition is consistent with that expected for thermally unprocessed primordial molecular cloud material before its pollution by stellar-derived 26Al. The 26Mg* and 54Cr compositions of bulk metal-rich chondrites require significant amounts (25–50%) of primordial molecular cloud matter in their precursor material. Given that such high fractions of primordial molecular cloud material are expected to survive only in the outer Solar System, we infer that, similarly to cometary bodies, metal-rich carbonaceous chondrites are samples of planetesimals that accreted beyond the orbits of the gas giants. The lack of evidence for this material in other chondrite groups requires isolation from the outer Solar System, possibly by the opening of disk gaps from the early formation of gas giants. PMID:26858438
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NASA Astrophysics Data System (ADS)
Stanfield, R. E.; Dong, X.; Xi, B.; Kennedy, A. D.; Del Genio, A. D.; Minnis, P.; Loeb, N. G.; Doelling, D.
2013-05-01
Marine Boundary Layer (MBL) Clouds are an extremely important part of the climate system. Their treatment in climate models is a large source of uncertainty that will harm future projection of the Earth's climate. Zhang et al. (2005, CMIP3) compared the GCMs simulated cloud fractions (CF) with NASA CERES and ISCCP results and found that most GCMs underestimated mid-latitude MBL clouds but overestimated their optical depth. The underestimated CF and overestimated cloud optical thickness in the models offset each other when calculating TOA radiation budgets. Recent studies (Jiang et al. 2012; Stanfield et al. 2013; and Dolinar et al. 2013) have found there has not been much improvement from CMIP3 to CMIP5 for MBL clouds. Most GCMs still simulate fewer mid-latitude MBL clouds. In this study, we compare the NASA GISS CMIP5 and Post-CMIP5 results with NASA CERES cloud properties (SYN1deg) and TOA radiation budgets (EBAF), as well as CloudSat-CALIPSO cloud products. Special attention has been paid over the Southern mid-latitudes (~ 30-60 °S) where the total cloud fractions can reach up to 80-90% with MBL clouds being the dominant cloud type. Comparisons have shown that the globally averaged total CFs and TOA radiation budgets from CMIP5 agreed well with satellite observations, however, there are significant regional differences. For example, most CMIP5 models underestimated MBL clouds over the Southern mid-latitudes, including the GISS GCM, resulting in less reflected (or more absorbed) shortwave flux at TOA. The preliminary results from NASA GISS post-CMIP5 have made many improvements, and agree much better with satellite observations. These improvements are attributed to a new PBL parameterization, where more/less clouds can be simulated when the PBL gets deeper/shallower. This update has a large effect on radiation and clouds.
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Generating DEM from LIDAR data - comparison of available software tools
NASA Astrophysics Data System (ADS)
Korzeniowska, K.; Lacka, M.
2011-12-01
In recent years many software tools and applications have appeared that offer procedures, scripts and algorithms to process and visualize ALS data. This variety of software tools and of "point cloud" processing methods contributed to the aim of this study: to assess algorithms available in various software tools that are used to classify LIDAR "point cloud" data, through a careful examination of Digital Elevation Models (DEMs) generated from LIDAR data on a base of these algorithms. The works focused on the most important available software tools: both commercial and open source ones. Two sites in a mountain area were selected for the study. The area of each site is 0.645 sq km. DEMs generated with analysed software tools ware compared with a reference dataset, generated using manual methods to eliminate non ground points. Surfaces were analysed using raster analysis. Minimum, maximum and mean differences between reference DEM and DEMs generated with analysed software tools were calculated, together with Root Mean Square Error. Differences between DEMs were also examined visually using transects along the grid axes in the test sites.
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A Wing Pod-based Millimeter Wave Cloud Radar on HIAPER
NASA Astrophysics Data System (ADS)
Vivekanandan, Jothiram; Tsai, Peisang; Ellis, Scott; Loew, Eric; Lee, Wen-Chau; Emmett, Joanthan
2014-05-01
One of the attractive features of a millimeter wave radar system is its ability to detect micron-sized particles that constitute clouds with lower than 0.1 g m-3 liquid or ice water content. Scanning or vertically-pointing ground-based millimeter wavelength radars are used to study stratocumulus (Vali et al. 1998; Kollias and Albrecht 2000) and fair-weather cumulus (Kollias et al. 2001). Airborne millimeter wavelength radars have been used for atmospheric remote sensing since the early 1990s (Pazmany et al. 1995). Airborne millimeter wavelength radar systems, such as the University of Wyoming King Air Cloud Radar (WCR) and the NASA ER-2 Cloud Radar System (CRS), have added mobility to observe clouds in remote regions and over oceans. Scientific requirements of millimeter wavelength radar are mainly driven by climate and cloud initiation studies. Survey results from the cloud radar user community indicated a common preference for a narrow beam W-band radar with polarimetric and Doppler capabilities for airborne remote sensing of clouds. For detecting small amounts of liquid and ice, it is desired to have -30 dBZ sensitivity at a 10 km range. Additional desired capabilities included a second wavelength and/or dual-Doppler winds. Modern radar technology offers various options (e.g., dual-polarization and dual-wavelength). Even though a basic fixed beam Doppler radar system with a sensitivity of -30 dBZ at 10 km is capable of satisfying cloud detection requirements, the above-mentioned additional options, namely dual-wavelength, and dual-polarization, significantly extend the measurement capabilities to further reduce any uncertainty in radar-based retrievals of cloud properties. This paper describes a novel, airborne pod-based millimeter wave radar, preliminary radar measurements and corresponding derived scientific products. Since some of the primary engineering requirements of this millimeter wave radar are that it should be deployable on an airborne platform, occupy minimum cabin space and maximize scan coverage, a pod-based configuration was adopted. Currently, the radar system is capable of collecting observations between zenith and nadir in a fixed scanning mode. Measurements are corrected for aircraft attitude changes. The near-nadir and zenith pointing observations minimize the cross-track Doppler contamination in the radial velocity measurements. An extensive engineering monitoring mechanism is built into the recording system status such as temperature, pressure, various electronic components' status and receiver characteristics. Status parameters are used for real-time system stability estimates and correcting radar system parameters. The pod based radar system is mounted on a modified Gulfstream V aircraft, which is operated and maintained by the National Center for Atmospheric Research (NCAR) on behalf of the National Science Foundation (NSF). The aircraft is called the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) (Laursen et al., 2006). It is also instrumented with high spectral resolution lidar (HSRL) and an array of in situ and remote sensors for atmospheric research. As part of the instrument suite for HIAPER, the NSF funded the development of the HIAPER Cloud Radar (HCR). The HCR is an airborne, millimeter-wavelength, dual-polarization, Doppler radar that serves the atmospheric science community by providing cloud remote sensing capabilities for the NSF/NCAR G-V (HIAPER) aircraft. An optimal radar configuration that is capable of maximizing the accuracy of both qualitative and quantitative estimated cloud microphysical and dynamical properties is the most attractive option to the research community. The Technical specifications of cloud radar are optimized for realizing the desired scientific performance for the pod-based configuration. The radar was both ground and flight tested and preliminary measurements of Doppler and polarization measurements were collected. HCR observed sensitivity as low as -37 dBZ at 1 km range and resolved linear depolarization ratio (LDR) signature better than -29 dB during its latest test flights. References: Kollias, P., and B. A. Albrecht, 2000: The turbulence structure in a continental stratocumulus cloud from millimeter wavelength radar observation. J. Atmos. Sci., 57, 2417-2434. Kollias, P., B.A. Albrecht, R. Lhermitte, and A. Savtchenko, 2001: Radar observations of updrafts, downdrafts, and turbulence in fair weather cumuli. J. Atmos. Sci. 58, 1750-1766. Laursen, K. K., D. P. Jorgensen, G. P. Brasseur, S. L. Ustin, and J. Hunning, 2006: HIAPER: The next generation NSF/NCAR research aircraft. Bulletin of the American Meteorological Society, 87, 896-909. Pazmany, A. L., R. E. McIntosh, R. Kelly, and V. G., 1994: An airborne 95-GHz dual-polarized radar for cloud studies. IEEE Trans. Geosci. Remote Sens., 32, 731-739. Vali, G., Kelly, R.D., French, J., Haimov, S., Leon, D., McIntosh, R., Pazmany, A., 1998. Fine-scale structure and microphysics of coastal stratus. J. Atmos. Sci. 55, 3540-3564.
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Solid propellant exhausted aluminum oxide and hydrogen chloride - Environmental considerations
NASA Technical Reports Server (NTRS)
Cofer, W. R., III; Winstead, E. L.; Purgold, G. C.; Edahl, R. A.
1993-01-01
Measurements of gaseous hydrogen chloride (HCl) and particulate aluminum oxide (Al2O3) were made during penetrations of five Space Shuttle exhaust clouds and one static ground test firing of a shuttle booster. Instrumented aircraft were used to penetrate exhaust clouds and to measure and/or collect samples of exhaust for subsequent analyses. The focus was on the primary solid rocket motor exhaust products, HCl and Al2O3, from the Space Shuttle's solid boosters. Time-dependent behavior of HCl was determined for the exhaust clouds. Composition, morphology, surface chemistry, and particle size distributions were determined for the exhausted Al2O3. Results determined for the exhaust cloud from the static test firing were complicated by having large amounts of entrained alkaline ground debris (soil) in the lofted cloud. The entrained debris may have contributed to neutralization of in-cloud HCl.
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The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)
NASA Astrophysics Data System (ADS)
Kuçak, R. A.; Özdemir, E.; Erol, S.
2017-05-01
Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.
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Optical properties of aerosol contaminated cloud derived from MODIS instrument
NASA Astrophysics Data System (ADS)
Mei, Linlu; Rozanov, Vladimir; Lelli, Luca; Vountas, Marco; Burrows, John P.
2016-04-01
The presence of absorbing aerosols above/within cloud can reduce the amount of up-welling radiation in visible (VIS) and short-wave infrared and darken the spectral reflectance when compared with a spectrum of a clean cloud observed by satellite instruments (Jethva et al., 2013). Cloud properties retrieval for aerosol contaminated cases is a great challenge. Even small additional injection of aerosol particles into clouds in the cleanest regions of Earth's atmosphere will cause significant effect on those clouds and on climate forcing (Koren et al., 2014; Rosenfeld et al., 2014) because the micro-physical cloud process are non-linear with respect to the aerosol loading. The current cloud products like Moderate Resolution Imaging Spectroradiometer (MODIS) ignoring the aerosol effect for the retrieval, which may cause significant error in the satellite-derived cloud properties. In this paper, a new cloud properties retrieval method, considering aerosol effect, based on the weighting-function (WF) method, is presented. The retrieval results shows that the WF retrieved cloud properties (e.g COT) agrees quite well with MODIS COT product for relative clear atmosphere (AOT ≤ 0.4) while there is a large difference for large aerosol loading. The MODIS COT product is underestimated for at least 2 - 3 times for AOT>0.4, and this underestimation increases with the increase of AOT.
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DACCIWA Cloud-Aerosol Observations in West Africa Field Campaign Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chiu, J Christine; Blanchard, Yann; Hill, Peter
Interactions between aerosols and clouds, and their effects on radiation, precipitation, and regional circulations, are one of the largest uncertainties in understanding climate. With reducing uncertainties in predictions of weather, climate, and climate impacts in mind, the Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) project, funded by the European Commission, set out to improve our understanding of cloud-aerosol interactions in southern West Africa. This region is ideal for studying cloud-aerosol interactions because of its rich mix of natural and anthropogenic aerosols and diverse clouds, and because of the strong dependence on the regional and global climate of the sensitive West Africanmore » monsoon. The overview of DACCIWA is described in Knippertz et al. 2015. The interdisciplinary DACCIWA team includes not only several European and African universities, but also Met Centres in the UK, France, Germany, Switzerland, Benin, Ghana, and Nigeria. One of the crucial research activities in DACCIWA is the major field campaign in southern West Africa from June to July 2016, comprising a benchmark data set for assessing detailed processes on natural and anthropogenic emissions; atmospheric composition; air pollution and its impacts on human and ecosystem health; boundary layer processes; couplings between aerosols, clouds, and rainfall; weather systems; radiation; and the monsoon circulation. Details and highlights of the campaign can be found in Flamant et al. 2017. To provide aerosol/cloud microphysical and optical properties that are essential for model evaluations and for the linkage between ground-based, airborne, and spaceborne observations, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility loaned two sun photometers to the DACCWIA team for the campaign from June 8 to July 29, 2016. The first sun photometer was deployed at Kumasi, Ghana (6.67962°N, 1.56019°W) by the University of Leeds (UK). The instrument was supposed to operate in normal aerosol mode in clear-sky conditions for aerosol monitoring, and operate in cloud mode for measuring cloud properties when clouds block the sun. Unfortunately, the robot of the sun photometer did not work properly from the beginning of the deployment, and remained problematic throughout the campaign. No useful data was recovered. The second sun photometer was deployed at Savé, Benin (8.000842°N, 2.413115°E), set up and maintained by the Karlsruher Institut fuer Technologie, Germany. Unlike most sun photometers that are designed to monitor aerosol properties and thus operated in normal aerosol mode, this sun photometer at Savé was operated in a special cloud mode, pointing vertically and measuring zenith radiance continuously at wavelengths of 440, 500, 675, 870, 1020, and 1640 nm with 10-sec temporal resolution. Zenith radiances at 440, 870, and 1640 nm alone can be used to retrieve cloud optical depth and column-mean effective radius (Chiu et al. 2010, 2012). The following section takes 6 and 7 July as an example to highlight a typical diurnal cycle of clouds observed during the campaign. Cloud properties retrieved from zenith radiance are compared against those retrieved from microwave radiometer (MWR) measurements, and against in situ measurements collected from the Twin Otter aircraft.« less
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Comparative exoplanetology with consistent retrieval methods
NASA Astrophysics Data System (ADS)
Barstow, Joanna Katy; Aigrain, Suzanne; Irwin, Patrick Gerard Joseph; Sing, David
2016-10-01
The number of hot Jupiters with broad wavelength spectroscopic data has finally become large enough to make comparative planetology a reasonable proposition. New results presented by Sing et al. (2016) showcase ten hot Jupiters with spectra from the Hubble Space Telescope and photometry from Spitzer, providing insights into the presence of clouds and hazes.Spectral retrieval methods allow interpretation of exoplanet spectra using simple models, with minimal prior assumptions. This is particularly useful for exotic exoplanets, for which we may not yet fully understand the physical processes responsible for their atmospheric characteristics. Consistent spectral retrieval of a range of exoplanets can allow robust comparisons of their derived atmospheric properties.I will present a retrieval analysis using the NEMESIS code (Irwin et al. 2008) of the ten hot Jupiter spectra presented by Sing et al. (2016). The only distinctive aspects of the model for each planet are the mass and radius, and the temperature range explored. All other a priori model parameters are common to all ten objects. We test a range of cloud and haze scenarios, which include: Rayleigh-dominated and grey clouds; different cloud top pressures; and both vertically extended and vertically confined clouds.All ten planets, with the exception of WASP-39b, can be well represented by models with at least some haze or cloud. Our analysis of cloud properties has uncovered trends in cloud top pressure, vertical extent and particle size with planet equilibrium temperature. Taken together, we suggest that these trends indicate condensation and sedimentation of at least two different cloud species across planets of different temperatures, with condensates forming higher up in hotter atmospheres and moving progressively further down in cooler planets.Sing, D. et al. (2016), Nature, 529, 59Irwin, P. G. J. et al. (2008), JQSRT, 109, 1136
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Applicability Analysis of Cloth Simulation Filtering Algorithm for Mobile LIDAR Point Cloud
NASA Astrophysics Data System (ADS)
Cai, S.; Zhang, W.; Qi, J.; Wan, P.; Shao, J.; Shen, A.
2018-04-01
Classifying the original point clouds into ground and non-ground points is a key step in LiDAR (light detection and ranging) data post-processing. Cloth simulation filtering (CSF) algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS) has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM), 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature) for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44 %, 0.77 % and1.20 %. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.
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Investigating the Accuracy of Point Clouds Generated for Rock Surfaces
NASA Astrophysics Data System (ADS)
Seker, D. Z.; Incekara, A. H.
2016-12-01
Point clouds which are produced by means of different techniques are widely used to model the rocks and obtain the properties of rock surfaces like roughness, volume and area. These point clouds can be generated by applying laser scanning and close range photogrammetry techniques. Laser scanning is the most common method to produce point cloud. In this method, laser scanner device produces 3D point cloud at regular intervals. In close range photogrammetry, point cloud can be produced with the help of photographs taken in appropriate conditions depending on developing hardware and software technology. Many photogrammetric software which is open source or not currently provide the generation of point cloud support. Both methods are close to each other in terms of accuracy. Sufficient accuracy in the mm and cm range can be obtained with the help of a qualified digital camera and laser scanner. In both methods, field work is completed in less time than conventional techniques. In close range photogrammetry, any part of rock surfaces can be completely represented owing to overlapping oblique photographs. In contrast to the proximity of the data, these two methods are quite different in terms of cost. In this study, whether or not point cloud produced by photographs can be used instead of point cloud produced by laser scanner device is investigated. In accordance with this purpose, rock surfaces which have complex and irregular shape located in İstanbul Technical University Ayazaga Campus were selected as study object. Selected object is mixture of different rock types and consists of both partly weathered and fresh parts. Study was performed on a part of 30m x 10m rock surface. 2D and 3D analysis were performed for several regions selected from the point clouds of the surface models. 2D analysis is area-based and 3D analysis is volume-based. Analysis conclusions showed that point clouds in both are similar and can be used as alternative to each other. This proved that point cloud produced using photographs which are both economical and enables to produce data in less time can be used in several studies instead of point cloud produced by laser scanner.
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Bibliography on Cold Regions Science and Technology. Volume 52. Part 2,
1998-12-01
eng] 52-5087 spheric gases from antarctic ice cores. Gillaik, T., et al, in sediments and biota from four US arctic lakes. Allen-Gil, Study of the...1996,eng] 52-2678 52-690 Solomon , S., et at, [1997,eng] 52-879 Studies of cloud ice water path and optical thickness during Homogeneous ice...of clouds: a wave ota, D., et al, [1995,eng] 52-5364 flash rate. Solomon , R.C., [1997,eng] 52-1070 cloud case study . Ackerman, S.A., et al, [1998,eng
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NASA Astrophysics Data System (ADS)
Liu, X.; Shi, Y.; Wu, M.; Zhang, K.
2017-12-01
Mixed-phase clouds frequently observed in the Arctic and mid-latitude storm tracks have the substantial impacts on the surface energy budget, precipitation and climate. In this study, we first implement the two empirical parameterizations (Niemand et al. 2012 and DeMott et al. 2015) of heterogeneous ice nucleation for mixed-phase clouds in the NCAR Community Atmosphere Model Version 5 (CAM5) and DOE Accelerated Climate Model for Energy Version 1 (ACME1). Model simulated ice nucleating particle (INP) concentrations based on Niemand et al. and DeMott et al. are compared with those from the default ice nucleation parameterization based on the classical nucleation theory (CNT) in CAM5 and ACME, and with in situ observations. Significantly higher INP concentrations (by up to a factor of 5) are simulated from Niemand et al. than DeMott et al. and CNT especially over the dust source regions in both CAM5 and ACME. Interestingly the ACME model simulates higher INP concentrations than CAM5, especially in the Polar regions. This is also the case when we nudge the two models' winds and temperature towards the same reanalysis, indicating more efficient transport of aerosols (dust) to the Polar regions in ACME. Next, we examine the responses of model simulated cloud liquid water and ice water contents to different INP concentrations from three ice nucleation parameterizations (Niemand et al., DeMott et al., and CNT) in CAM5 and ACME. Changes in liquid water path (LWP) reach as much as 20% in the Arctic regions in ACME between the three parameterizations while the LWP changes are smaller and limited in the Northern Hemispheric mid-latitudes in CAM5. Finally, the impacts on cloud radiative forcing and dust indirect effects on mixed-phase clouds are quantified with the three ice nucleation parameterizations in CAM5 and ACME.
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NASA Astrophysics Data System (ADS)
Widemann, Thomas; Marcq, Emmanuel; Tsang, Constantine; Mueller, Nils; Kappel, David; Helbert, Joern; Dyar, Melinda; Smrekar, Suzanne
2017-10-01
Venus displays the best-known case of polar vortices evolving in a fast-rotating atmosphere. Polar vortices are pervasive in the Solar System and may also be present in atmosphere-bearing exoplanets. While much progress has been made since the early suggestion that the Venus clouds are H2O-H2SO4 liquid droplets (Young 1973), several cloud parameters are still poorly constrained, particularly in the lower cloud layer and optically thicker polar regions. The average particle size is constant over most of the planet but increases toward the poles. This indicates that cloud formation processes are different at latitudes greater than 60°, possibly as a result of the different dynamical regimes that exist in the polar vortices (Carlson et al. 1993, Wilson et al. 2008, Barstow et al. 2012).Few wind measurements exist in the polar region due to unfavorable viewing geometry of currently available observations. Cloud-tracking data indicate circumpolar circulation close to solid-body rotation. E-W winds decrease to zero velocity close to the pole. N-S circulation is marginal, with extremely variable morphology and complex vorticity patterns (Sanchez-Lavega et al. 2008, Luz et al. 2011, Garate-Lopez et al. 2013).The Venus Emissivity Mapper (VEM; Helbert et al., 2016) proposed for NASA’s Venus Origins Explorer (VOX) and the ESA M5/EnVision orbiters has the capability to better constrain the microphysics (vertical, horizontal, time dependence of particle size distribution, or/and composition) of the lower cloud particles in three spectral bands at 1.195, 1.310 and 1.510 μm at a spatial resolution of ~10 km. Circular polar orbit geometry would provide an unprecedented simultaneous study of both polar regions within the same mission. In addition, VEM’s pushbroom method will allow short timescale cloud dynamics to be assessed, as well as local wind speeds, using repeated imagery at 90 minute intervals. Tracking lower cloud motions as proxies for wind measurements at high spatial resolutions will greatly benefit modeling of the vortice’s physics, as well as wave-generating dynamical instabilities (Garate-Lopez et al. 2015).
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LiDAR Point Cloud and Stereo Image Point Cloud Fusion
2013-09-01
LiDAR point cloud (right) highlighting linear edge features ideal for automatic registration...point cloud (right) highlighting linear edge features ideal for automatic registration. Areas where topography is being derived, unfortunately, do...with the least amount of automatic correlation errors was used. The following graphic (Figure 12) shows the coverage of the WV1 stereo triplet as
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LIDAR Point Cloud Data Extraction and Establishment of 3D Modeling of Buildings
NASA Astrophysics Data System (ADS)
Zhang, Yujuan; Li, Xiuhai; Wang, Qiang; Liu, Jiang; Liang, Xin; Li, Dan; Ni, Chundi; Liu, Yan
2018-01-01
This paper takes the method of Shepard’s to deal with the original LIDAR point clouds data, and generate regular grid data DSM, filters the ground point cloud and non ground point cloud through double least square method, and obtains the rules of DSM. By using region growing method for the segmentation of DSM rules, the removal of non building point cloud, obtaining the building point cloud information. Uses the Canny operator to extract the image segmentation is needed after the edges of the building, uses Hough transform line detection to extract the edges of buildings rules of operation based on the smooth and uniform. At last, uses E3De3 software to establish the 3D model of buildings.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Wenyang; Cheung, Yam; Sawant, Amit
2016-05-15
Purpose: To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. Methods: The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparsemore » regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. Results: On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. Conclusions: The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications.« less
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Liu, Wenyang; Cheung, Yam; Sawant, Amit; Ruan, Dan
2016-05-01
To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications.
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Liu, Wenyang; Cheung, Yam; Sawant, Amit; Ruan, Dan
2016-01-01
Purpose: To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. Methods: The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. Results: On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. Conclusions: The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications. PMID:27147347
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Automatic Registration of TLS-TLS and TLS-MLS Point Clouds Using a Genetic Algorithm
Yan, Li; Xie, Hong; Chen, Changjun
2017-01-01
Registration of point clouds is a fundamental issue in Light Detection and Ranging (LiDAR) remote sensing because point clouds scanned from multiple scan stations or by different platforms need to be transformed to a uniform coordinate reference frame. This paper proposes an efficient registration method based on genetic algorithm (GA) for automatic alignment of two terrestrial LiDAR scanning (TLS) point clouds (TLS-TLS point clouds) and alignment between TLS and mobile LiDAR scanning (MLS) point clouds (TLS-MLS point clouds). The scanning station position acquired by the TLS built-in GPS and the quasi-horizontal orientation of the LiDAR sensor in data acquisition are used as constraints to narrow the search space in GA. A new fitness function to evaluate the solutions for GA, named as Normalized Sum of Matching Scores, is proposed for accurate registration. Our method is divided into five steps: selection of matching points, initialization of population, transformation of matching points, calculation of fitness values, and genetic operation. The method is verified using a TLS-TLS data set and a TLS-MLS data set. The experimental results indicate that the RMSE of registration of TLS-TLS point clouds is 3~5 mm, and that of TLS-MLS point clouds is 2~4 cm. The registration integrating the existing well-known ICP with GA is further proposed to accelerate the optimization and its optimizing time decreases by about 50%. PMID:28850100
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Automatic Registration of TLS-TLS and TLS-MLS Point Clouds Using a Genetic Algorithm.
Yan, Li; Tan, Junxiang; Liu, Hua; Xie, Hong; Chen, Changjun
2017-08-29
Registration of point clouds is a fundamental issue in Light Detection and Ranging (LiDAR) remote sensing because point clouds scanned from multiple scan stations or by different platforms need to be transformed to a uniform coordinate reference frame. This paper proposes an efficient registration method based on genetic algorithm (GA) for automatic alignment of two terrestrial LiDAR scanning (TLS) point clouds (TLS-TLS point clouds) and alignment between TLS and mobile LiDAR scanning (MLS) point clouds (TLS-MLS point clouds). The scanning station position acquired by the TLS built-in GPS and the quasi-horizontal orientation of the LiDAR sensor in data acquisition are used as constraints to narrow the search space in GA. A new fitness function to evaluate the solutions for GA, named as Normalized Sum of Matching Scores, is proposed for accurate registration. Our method is divided into five steps: selection of matching points, initialization of population, transformation of matching points, calculation of fitness values, and genetic operation. The method is verified using a TLS-TLS data set and a TLS-MLS data set. The experimental results indicate that the RMSE of registration of TLS-TLS point clouds is 3~5 mm, and that of TLS-MLS point clouds is 2~4 cm. The registration integrating the existing well-known ICP with GA is further proposed to accelerate the optimization and its optimizing time decreases by about 50%.
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Low altitude cloud height and methane humidity retrievals on Titan in the near-IR
NASA Astrophysics Data System (ADS)
Adamkovics, M.; Hayes, A.; Mitchell, J.; De Pater, I.; Young, E.
2013-12-01
The formation of low altitude clouds on Titan, with cloud-top altitudes below ~10km, likely occurs by a fundamentally different mechanism than for the clouds commonly observed to have cloud-tops in the upper troposphere, above ~15km [1]. Near-infrared spectroscopy of clouds has been the method of choice for determining cloud altitudes [2], however, uncertainties in aerosols scattering properties and opacities, together with limitations in laboratory measurements of gas opacities (in particular for methane), lead to uncertainties in how accurately the altitude of low clouds can be retrieved [3]. Here we revisit near-IR spectra obtained with Keck and Cassini using new laboratory methane line data in the HITRAN 2012 database [4] to address the problem of measuring the altitudes of low clouds. We discuss the role of topography in relation to the formation of low clouds and other diagnostics of conditions near the surface, such as the tropospheric methane humidity. We reanalyze measurements the tropospheric humidity variation [5] and describe observational strategies for improved diagnostics of the tropospheric humidity on Titan . Acknowledgements: Funding for this work is provided by the NSF grant AST-1008788 and NASA OPR grant NNX12AM81G. References: [1] Brown, et al. (2009) ApJ, 706, L110-L113. [2] Ádámkovics et al. (2010) Icarus, 208, 868-877. [3] Griffith et al. (2012) Icarus, 218, 975-988. [4] Rothman et al. (2013) AIP Conf. Proc., 1545, 223-231. [5] Penteado & Griffith (2010) Icarus, 206, 345-351.
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NASA Astrophysics Data System (ADS)
Griffith, C. A.; Hall, J. L.; Geballe, T. R.
2000-10-01
Titan's atmosphere potentially sports a cycle similar to the hydrologic one on Earth with clouds, rain and seas, but with methane playing the terrestrial role of water. Over the past ten years many independent efforts indicated no strong evidence for cloudiness until some unique spectra were analyzed in 1998 (Griffith et al.). These surprising observations displayed enhanced fluxes of 14-200% on two nights at precisely the wavelengths (windows) that sense Titan's lower altitude where clouds might reside. The morphology of these enhancements in all 4 windows observed indicate that clouds covered ~6-9% of Titan's surface and existed at ~15 km altitude. Here I discuss new observations recorded in 1999 aimed to further characterize Titan's clouds. While we find no evidence for a massive cloud system similar to the one observed previously, 1%-4% fluctuations in flux occur daily. These modulations, similar in wavelength and morphology to the more pronounced ones observed earlier, suggest the presence of clouds covering <=1% of Titan's disk. The variations are too small to have been detected by most prior measurements. Repeated observations, spaced 30 minutes apart, indicate a temporal variability observable in the time scale of a couple of hours. The cloud heights hint that convection governs their evolutions. Their short lives point to the presence of rain. C. A. Griffith and J. L. Hall are supported by the NASA Planetary Astronomy Program NAG5-6790.
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Automatic Classification of Trees from Laser Scanning Point Clouds
NASA Astrophysics Data System (ADS)
Sirmacek, B.; Lindenbergh, R.
2015-08-01
Development of laser scanning technologies has promoted tree monitoring studies to a new level, as the laser scanning point clouds enable accurate 3D measurements in a fast and environmental friendly manner. In this paper, we introduce a probability matrix computation based algorithm for automatically classifying laser scanning point clouds into 'tree' and 'non-tree' classes. Our method uses the 3D coordinates of the laser scanning points as input and generates a new point cloud which holds a label for each point indicating if it belongs to the 'tree' or 'non-tree' class. To do so, a grid surface is assigned to the lowest height level of the point cloud. The grids are filled with probability values which are calculated by checking the point density above the grid. Since the tree trunk locations appear with very high values in the probability matrix, selecting the local maxima of the grid surface help to detect the tree trunks. Further points are assigned to tree trunks if they appear in the close proximity of trunks. Since heavy mathematical computations (such as point cloud organization, detailed shape 3D detection methods, graph network generation) are not required, the proposed algorithm works very fast compared to the existing methods. The tree classification results are found reliable even on point clouds of cities containing many different objects. As the most significant weakness, false detection of light poles, traffic signs and other objects close to trees cannot be prevented. Nevertheless, the experimental results on mobile and airborne laser scanning point clouds indicate the possible usage of the algorithm as an important step for tree growth observation, tree counting and similar applications. While the laser scanning point cloud is giving opportunity to classify even very small trees, accuracy of the results is reduced in the low point density areas further away than the scanning location. These advantages and disadvantages of two laser scanning point cloud sources are discussed in detail.
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Georeferencing UAS Derivatives Through Point Cloud Registration with Archived Lidar Datasets
NASA Astrophysics Data System (ADS)
Magtalas, M. S. L. Y.; Aves, J. C. L.; Blanco, A. C.
2016-10-01
Georeferencing gathered images is a common step before performing spatial analysis and other processes on acquired datasets using unmanned aerial systems (UAS). Methods of applying spatial information to aerial images or their derivatives is through onboard GPS (Global Positioning Systems) geotagging, or through tying of models through GCPs (Ground Control Points) acquired in the field. Currently, UAS (Unmanned Aerial System) derivatives are limited to meter-levels of accuracy when their generation is unaided with points of known position on the ground. The use of ground control points established using survey-grade GPS or GNSS receivers can greatly reduce model errors to centimeter levels. However, this comes with additional costs not only with instrument acquisition and survey operations, but also in actual time spent in the field. This study uses a workflow for cloud-based post-processing of UAS data in combination with already existing LiDAR data. The georeferencing of the UAV point cloud is executed using the Iterative Closest Point algorithm (ICP). It is applied through the open-source CloudCompare software (Girardeau-Montaut, 2006) on a `skeleton point cloud'. This skeleton point cloud consists of manually extracted features consistent on both LiDAR and UAV data. For this cloud, roads and buildings with minimal deviations given their differing dates of acquisition are considered consistent. Transformation parameters are computed for the skeleton cloud which could then be applied to the whole UAS dataset. In addition, a separate cloud consisting of non-vegetation features automatically derived using CANUPO classification algorithm (Brodu and Lague, 2012) was used to generate a separate set of parameters. Ground survey is done to validate the transformed cloud. An RMSE value of around 16 centimeters was found when comparing validation data to the models georeferenced using the CANUPO cloud and the manual skeleton cloud. Cloud-to-cloud distance computations of CANUPO and manual skeleton clouds were obtained with values for both equal to around 0.67 meters at 1.73 standard deviation.
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NASA Technical Reports Server (NTRS)
Feofilov, A. G.; Petelina, S V.; Kutepov, A. A.; Pesnell, W. D.; Goldberg, R. A.; Llewellyn, E. J.; Russell, J. M.
2006-01-01
The Optical Spectrograph and Infrared Imaging System (OSIRIS) instrument on board the Odin satellite detects Polar Mesospheric Clouds (PMCs) through the enhancement in the limb scattered solar radiance. The Sounding of the Atmosphere using the Broadband Emission Radiometry (SABER) instrument on board the TIMED satellite is a limb scanning infrared radiometer that measures temperature and vertical profiles and energetic parameters for minor constituents in the mesosphere and lower thermosphere. The combination of OSIRIS and SABER data has been previously used to statistically derive thermal conditions for PMC existence [Petelina et al., 2005]. In this work, we employ the simultaneous common volume measurements of PMCs by OSIRIS and temperature profiles measured by SABER for the Northern Hemisphere summers of 2002-2005 and corrected in the polar region by accounting for the vibrational-vibrational energy exchange among the CO2 isotopes [Kutepov et al., 2006]. For each of 20 coincidences identified within plus or minus 1 degree latitude, plus or minus 2 degrees longitude and less than 1 hour time the frost point temperatures were calculated using the corresponding SABER temperature profile and water vapor densities of 1,3, and 10 ppmv. We found that the PMC presence and brightness correlated only with the temperature threshold that corresponds to the frost point. The absolute value of the temperature below the frost point, however, didn't play a significant role in the intensity of PMC signal for the majority of selected coincidences. The presence of several bright clouds at temperatures above the frost point is obviously related to the limitation of the limb geometry when some near- or far-field PMCs located at higher (and warmer) altitudes appear to be at lower altitudes.
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NASA Technical Reports Server (NTRS)
Feofilov, A. G.; Petelina, S. V.; Kutepov, A. A.; Pesnell, W. D.; Goldberg, R. A.; Llewellyn, E. J.; Russell, J. M.
2006-01-01
The Optical Spectrograph and Infrared Imaging System (OSIRIS) instrument on board the Odin satellite detects Polar Mesospheric Clouds (PMCs) through the enhancement in the limb-scattered solar radiance. The Sounding of the Atmosphere using the Broadband Emission Radiometry (SABER) instrument on board the TIMED satellite is a limb scanning infrared radiometer that measures temperature and vertical profiles and energetic parameters for minor constituents in the mesosphere and lower thermosphere. The combination of OSIRIS and SABER data has been previously used to statistically derive thermal conditions for PMC existence [Petelina et al., 2005]. a, A.A. Kutepov, W.D. Pesnell, In this work, we employ the simultaneous common volume measurements of PMCs by OSIRIS and temperature profiles measured by SABER for the Northern Hemisphere summers of 2002-2005 and corrected in the polar region by accounting for the vibrational-vibrational energy exchange among the CO2 isotopes [Kutepov et al., 2006]. For each of 20 coincidences identified within plus or minus 1 degree latitude, plus or minus 2 degrees longitude and less than 1 hour time the frost point temperatures were calculated using the corresponding SABER temperature profile and water vapor densities of 1,3, and 10 ppmv. We found that the PMC presence and brightness correlated only with the temperature threshold that corresponds to the frost point. The absolute value of the temperature below the frost point, however, didn't play a significant role in the intensity of PMC signal for the majority of selected coincidences. The presence of several bright clouds at temperatures above the frost point is obviously related to the limitation of the limb geometry when some near- or far-field PMCs located at higher (and warmer) altitudes appear to be at lower altitudes.
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NASA Astrophysics Data System (ADS)
Wężyk, P.; Gęca, T.
2013-12-01
Dynamic economic and social changes taking place for the past 20 years in Poland, effects often of such loss of extensive agriculture and abandonment of agricultural activities particularly on small and narrow plots , usually on the soils of poor grading. Even before the Polish accession to the EU, set - aside and fallow areas cover approx. 2.3 million ha (in 2002), but in subsequent years the area drastically decreased from 1.3 million ha (in 2004) , by 1.0 million ha ( 2 005 ) to 0.4 million hectares (2011). As a result of cessation of mowing meadows, grazing pastures and agricultural measures , we can observed the phenomenon of secondary forest succession ( plant communities of a forest properties ) leading to changes in land use and land cover classes structure . Recording changes in the agro - forestry space, update reference registers of the land and building (EGiB) and control granted to farmers subsidies ( direct EU payments) requires an efficient and automated technology acquisition, processing and analysis of spatial data. In addition to the used by ARiMR (in the LPIS system) vector data and aerial orthophotomaps , there is still a need to strengthen the decision - making process such as update of current ranges of land - use cla sses. One of the GI technologies that could be a real breakthrough is the Airborne Laser Scanning (ALS) . The study area cover 137.17 ha in the village Tuklęcz (commune Rytwiany, Staszów County , ?więtokrzyskie Voivodeship ). The EGiB geo data came from PODGiK in Staszów. They were two ALS point cloud data sets: one provided by the RZGW in Krakow (from airborne campaign Nov. 2009; density ~ 2 pts / m2) and the second from ISOK project (Nov. 2012; density ~ 4 pts / m2 ). The Terrasolid and FUSION (USDA Forest Service) and ArcGIS Esri software were used in the study . Detection of vegetation was carried out in 4 variants differ in the "height above ground" of the class "succession" (thresholds: from 0.4m , 1m, 2m and 3m ). The results indicate that in each scenario (variant), in the area of arable land ("R") - class (covering 60.55 % of the analyzed area) were over 70 % of all detected secondary forest succession polygons, covering more than 50% of agricultural land. Secondary succession occupied from 31.38 % to 61.05 % the land - use "R" and from 34.93 % to 67.03 % of the land - use Pastures' ("Ps"), which shows the high economic transformations taking place in the area. The use of wide - scale ALS data in Poland, has been made possible by the ISOK project assuming execution to the end of 2013 for an area of about 191000 km2 of classified ALS point cloud (cloud density: 4 pts/ m 2 - Standard I for agricultural areas; 12 pts/ m 2 - Standard II for urban areas ), digital terrain model (DTM ) and the digitals (topographic) surface model ( DSM ). In addition, the aerial photographs are obtained in the ISOK project for coloring of ALS point clouds or for orthophoto generation purpose. Observed in the years 2002 - 2010 decrease by 26% the number of farms in Poland (up to 1 ha area) is some indication that the problem of abandonment of agricultural land has not yet been closed. Regular ALS campaigns or the use of alternative technologies such as stereo - matching of aerial photographs or radar technologies, it gives a good chance to manage and monitor the changes in rural areas. This retrieved data can be used in the construction of development plans of communes or management plans of Natura2000, which largely depend on properly conducted agricultural economy (Special Protection Areas - SPA) means eg. mowing overgrown meadows and pastures . On the other hand, since 1995, the National Afforestation Programme (KPZL) exist, which implies achieving 30% forest cover in Poland in year 2020 and 33% in year 2050
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NASA Astrophysics Data System (ADS)
Cura, Rémi; Perret, Julien; Paparoditis, Nicolas
2017-05-01
In addition to more traditional geographical data such as images (rasters) and vectors, point cloud data are becoming increasingly available. Such data are appreciated for their precision and true three-Dimensional (3D) nature. However, managing point clouds can be difficult due to scaling problems and specificities of this data type. Several methods exist but are usually fairly specialised and solve only one aspect of the management problem. In this work, we propose a comprehensive and efficient point cloud management system based on a database server that works on groups of points (patches) rather than individual points. This system is specifically designed to cover the basic needs of point cloud users: fast loading, compressed storage, powerful patch and point filtering, easy data access and exporting, and integrated processing. Moreover, the proposed system fully integrates metadata (like sensor position) and can conjointly use point clouds with other geospatial data, such as images, vectors, topology and other point clouds. Point cloud (parallel) processing can be done in-base with fast prototyping capabilities. Lastly, the system is built on open source technologies; therefore it can be easily extended and customised. We test the proposed system with several billion points obtained from Lidar (aerial and terrestrial) and stereo-vision. We demonstrate loading speeds in the ˜50 million pts/h per process range, transparent-for-user and greater than 2 to 4:1 compression ratio, patch filtering in the 0.1 to 1 s range, and output in the 0.1 million pts/s per process range, along with classical processing methods, such as object detection.
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NASA Astrophysics Data System (ADS)
Gajda, Agnieszka; Wójtowicz-Nowakowska, Anna
2013-04-01
A comparison of the accuracy of pixel based and object based classifications of integrated optical and LiDAR data Land cover maps are generally produced on the basis of high resolution imagery. Recently, LiDAR (Light Detection and Ranging) data have been brought into use in diverse applications including land cover mapping. In this study we attempted to assess the accuracy of land cover classification using both high resolution aerial imagery and LiDAR data (airborne laser scanning, ALS), testing two classification approaches: a pixel-based classification and object-oriented image analysis (OBIA). The study was conducted on three test areas (3 km2 each) in the administrative area of Kraków, Poland, along the course of the Vistula River. They represent three different dominating land cover types of the Vistula River valley. Test site 1 had a semi-natural vegetation, with riparian forests and shrubs, test site 2 represented a densely built-up area, and test site 3 was an industrial site. Point clouds from ALS and ortophotomaps were both captured in November 2007. Point cloud density was on average 16 pt/m2 and it contained additional information about intensity and encoded RGB values. Ortophotomaps had a spatial resolution of 10 cm. From point clouds two raster maps were generated: intensity (1) and (2) normalised Digital Surface Model (nDSM), both with the spatial resolution of 50 cm. To classify the aerial data, a supervised classification approach was selected. Pixel based classification was carried out in ERDAS Imagine software. Ortophotomaps and intensity and nDSM rasters were used in classification. 15 homogenous training areas representing each cover class were chosen. Classified pixels were clumped to avoid salt and pepper effect. Object oriented image object classification was carried out in eCognition software, which implements both the optical and ALS data. Elevation layers (intensity, firs/last reflection, etc.) were used at segmentation stage due to proper wages usage. Thus a more precise and unambiguous boundaries of segments (objects) were received. As a results of the classification 5 classes of land cover (buildings, water, high and low vegetation and others) were extracted. Both pixel-based image analysis and OBIA were conducted with a minimum mapping unit of 10m2. Results were validated on the basis on manual classification and random points (80 per test area), reference data set was manually interpreted using ortophotomaps and expert knowledge of the test site areas.
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New evidence for chemical depletion of ammonia in the 1 to 2 bar region of Jupiter's atmosphere
NASA Astrophysics Data System (ADS)
Wong, M. H.; Atreya, S. K.; Romani, P. N.; De Pater, I.; Kuhn, W. R.; Kalogerakis, K. S.
2014-12-01
It has long been known that the vertical profile of ammonia within Jupiter's cloud layers is not well-described by a simple equilibrium profile, with saturated vapor above the cloud base and the well-mixed deep abundance below the cloud base. An additional depletion of ammonia by a factor of 4-10 is required by global microwave spectra at p < 6 bar [e.g., 1]. Dynamical effects, ranging from cloud layer circulation between belts and zones [2] to molecular differentiation following convective activity [3] might be sufficient to explain the global microwave data. However, in situ cloud density measurements by the Galileo Probe [4] suggest a large gap in our understanding of cloud chemistry in Jupiter, especially when combined with other tracers such as volatile mixing ratios [5] and static stability [6]. Using the "fresh clouds" method of modeling cloud density [7], and assuming that cloud-forming advection was weak at all levels in the probe site, we find that NH4SH formation cannot explain cloud densities between 1 and 1.4 bar in situ. The composition of additional chemical species, or adsorption of ammonia on other ices, are candidate processes that strongly require further laboratory study of the H2O-NH3-H2S volatile system at temperatures of 150 to 300 K [1]. Spectral features near 3 microns suggest widespread NH4SH in the visible cloud decks of Jupiter [8], but additional species may also contribute to absorption at these wavelengths. Infrared spectroscopy at high angular resolution in the future---performed by Juno, JWST, or 30-m class ground-based telescopes---may be able to observe ammonia depletion mechanisms in action. References:[1] de Pater et al. (2001), Icarus 149, 66-78.[2] Showman and de Pater (2005), Icarus 174, 192-204.[3] Sugiyama et al. (2011), GRL 38, L13201.[4] Ragent et al. (1998), JGR 103, 22891-22909.[5] Wong et al. (2004), Icarus 171, 153-170.[6] Magalhães, Seiff, and Young (2002), Icarus 158, 410-433.[7] Wong et al. (2014), Icarus, submitted.[8] Sromovsky et al. (2010), Icarus 210, 211-229 and 230-257. [This material is supported by the NASA Juno Project through a SWRI subcontract (SKA), and by NASA Grant No. NNX11AM55G issued through the Outer Planets Research Program (MHW).
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NASA Technical Reports Server (NTRS)
Ginger, Kathryn M.
1993-01-01
Since clouds are the largest variable in Earth's radiation budget, it is critical to determine both the spatial and temporal characteristics of their radiative properties. The relationships between cloud properties and cloud fraction are studied in order to supplement grid scale parameterizations. The satellite data used is from three hourly ISCCP (International Satellite Cloud Climatology Project) and monthly ERBE (Earth Radiation Budget Experiment) data on a 2.5 deg x 2.5 deg latitude-longitude grid. Mean cloud spherical albedo, the mean optical depth distribution, and cloud fraction are examined and compared off the coast of California and the mid-tropical Atlantic for July 1987 and 1988. Individual grid boxes and spatial averages over several grid boxes are correlated to Coakley's theory of reflection for uniform and broken layered cloud and to Kedem, et al.'s findings that rainfall volume and fractional area of rain in convective systems is linear. Kedem's hypothesis can be expressed in terms of cloud properties. That is, the total volume of liquid in a box is a linear function of cloud fraction. Results for the marine stratocumulus regime indicate that albedo is often invariant for cloud fractions of 20% to 80%. Coakley's satellite model of small and large clouds with cores (1 km) and edges (100 m) is consistent with this observation. The cores maintain high liquid water concentrations and large droplets while the edges contain low liquid water concentrations and small droplets. Large clouds are just a collection of cores. The mean optical depth (TAU) distributions support the above observation with TAU values of 3.55 to 9.38 favored across all cloud fractions. From these results, a method based upon Kedem, et al's theory is proposed to separate the cloud fraction and liquid water path (LWP) calculations in a general circulation model (GCM). In terms of spatial averaging, a linear relationship between albedo and cloud fraction is observed. For tropical locations outside the Intertropical Convergence Zone (ITCZ), results of cloud fraction and albedo spatial averaging followed that of the stratus boxes containing few overcast scenes. Both the ideas of Coakley and Kedem, et al. apply. Within the ITCZ, the grid boxes tended to have the same statistical properties as stratus boxes containing many overcast scenes. Because different dynamical forcing mechanisms are present, it is difficult to devise a method for determining subgrid scale variations. Neither of the theories proposed by Kedem, et al. or Coakley works well for the boxes with numerous overcast scenes.
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On the Spatial Power Spectrum of the E x B Gradient Drift Instability in Ionospheric Plasma Clouds.
1981-04-14
Perkins et al., 1973]. In reality, an artificially injected plasma cloud will, initially, be two- dimensional in the plane perpendicular to the magnetic...Motion of Artificial Ion Clouds in the Upper Atmosphere, Planet. Space Sci., 15, 1, 1967. Kelley, M.C., K.D. Baker, and J.C. Ulwick, Late Time Barium...42960 COMiANDER WORLOA’AY POS’AL CENTER J.S. ARMY MISSILE INTELLIGENCE AGENCY "’OS ANGELES, CA. 90009 REDSTONE ARSENAL, AL 35809 OICY ATTN CODE 52 0ICY
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NASA Astrophysics Data System (ADS)
Ku, N. W.; Popescu, S. C.
2015-12-01
In the past few years, three global forest canopy height maps have been released. Lefsky (2010) first utilized the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate a global forest canopy height map in 2010. Simard et al. (2011) integrated GLAS data and other ancillary variables, such as MODIS, Shuttle Radar Topography Mission (STRM), and climatic data, to generate another global forest canopy height map in 2011. Los et al. (2012) also used GLAS data to create a vegetation height map in 2012.Several studies attempted to compare these global height maps to other sources of data., Bolton et al. (2013) concluded that Simard's forest canopy height map has strong agreement with airborne lidar derived heights. Los map is a coarse spatial resolution vegetation height map with a 0.5 decimal degrees horizontal resolution, around 50 km in the US, which is not feasible for the purpose of our research. Thus, Simard's global forest canopy height map is the primary map for this research study. The main objectives of this research were to validate and calibrate Simard's map with airborne lidar data and other ancillary variables in the southern United States. The airborne lidar data was collected between 2010 and 2012 from: (1) NASA LiDAR, Hyperspectral & Thermal Image (G-LiHT) program; (2) National Ecological Observatory Network's (NEON) prototype data sharing program; (3) NSF Open Topography Facility; and (4) the Department of Ecosystem Science and Management at Texas A&M University. The airborne lidar study areas also cover a wide variety of vegetation types across the southern US. The airborne lidar data is post-processed to generate lidar-derived metrics and assigned to four different classes of point cloud data. The four classes of point cloud data are the data with ground points, above 1 m, above 3 m, and above 5 m. The root mean square error (RMSE) and coefficient of determination (R2) are used for examining the discrepancies of the canopy heights between the airborne lidar-derived metrics and global forest canopy height map, and the regression and random forest approaches are used to calibrate the global forest canopy height map. In summary, the research shows a calibrated forest canopy height map of the southern US.
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NASA Astrophysics Data System (ADS)
Zhao, Yu; Shi, Chen-Xiao; Kwon, Ki-Chul; Piao, Yan-Ling; Piao, Mei-Lan; Kim, Nam
2018-03-01
We propose a fast calculation method for a computer-generated hologram (CGH) of real objects that uses a point cloud gridding method. The depth information of the scene is acquired using a depth camera and the point cloud model is reconstructed virtually. Because each point of the point cloud is distributed precisely to the exact coordinates of each layer, each point of the point cloud can be classified into grids according to its depth. A diffraction calculation is performed on the grids using a fast Fourier transform (FFT) to obtain a CGH. The computational complexity is reduced dramatically in comparison with conventional methods. The feasibility of the proposed method was confirmed by numerical and optical experiments.
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Carbon Dioxide Clouds at High Altitude in the Tropics and in an Early Dense Martian Atmosphere
NASA Technical Reports Server (NTRS)
Colaprete, Anthony; Toon, Owen B.
2001-01-01
We use a time dependent, microphysical cloud model to study the formation of carbon dioxide clouds in the Martian atmosphere. Laboratory studies by Glandor et al. show that high critical supersaturations are required for cloud particle nucleation and that surface kinetic growth is not limited. These conditions, which are similar to those for cirrus clouds on Earth, lead to the formation of carbon dioxide ice particles with radii greater than 500 micrometers and concentrations of less than 0.1 cm(exp -3) for typical atmospheric conditions. Within the current Martian atmosphere, CO2 cloud formation is possible at the poles during winter and at high altitudes in the tropics during periods of increased atmospheric dust loading. In both cases, temperature perturbations of several degrees below the CO2 saturation temperature are required to nucleate new cloud particles suggesting that dynamical processes are the most common initiators of carbon dioxide clouds rather than diabatic cooling. The microphysical cloud model, coupled to a two-stream radiative transfer model, is used to reexamine the impact of CO2 clouds on the surface temperature within a dense CO2 atmosphere. The formation of carbon dioxide clouds leads to a warmer surface than what would be expected for clear sky conditions. The amount of warming is sensitive to the presence of dust and water vapor in the atmosphere, both of which act to dampen cloud effects. The radiative warming associated with cloud formation, as well as latent heating, work to dissipate the clouds when present. Thus, clouds never last for periods much longer than several days, limiting their overall effectiveness for warming the surface. The time average cloud optical depth is approximately unity leading to a 5-10 K warming, depending on the surface pressure. However, the surface temperature does not rise about the freezing point of liquid water even for pressures as high as 5 bars, at a solar luminosity of 75% the current value.
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VizieR Online Data Catalog: LMC PNe multiwavelength photometry (Reid, 2014)
NASA Astrophysics Data System (ADS)
Reid, W. A.
2017-07-01
Using the 2MASS 6x catalogue for the LMC (Cutri et al. 2003, Cat. II/246; 2012, Cat. VII/233), magnitudes were obtained for 274 PNe in J, 269 in H and 263 in Ks. To increase the number of detections available for comparison, magnitudes were also obtained from the InfraRed Survey Facility (IRSF) Magellanic Clouds Point Source Catalogue (Kato et al., 2007, Cat. II/288). The 3.6, 4.5, 5.8 and 8um bands were obtained with the IRAC on board Spitzer. This study used the archival data from the Spitzer legacy programme SAGE (Meixner et al., 2006, Cat. J/AJ/132/2268) which mapped the central 7x7deg2 area of the LMC. The MIPS data were also obtained from both the Hora et al. (2008, Cat. J/AJ/135/726) and Gruendl & Chu (2009, Cat. J/ApJS/184/172) studies. (3 data files).
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NASA Astrophysics Data System (ADS)
Patterson, V. M.; Bormann, K.; Deems, J. S.; Painter, T. H.
2017-12-01
The NASA SnowEx campaign conducted in 2016 and 2017 provides a rich source of high-resolution Lidar data from JPL's Airborne Snow Observatory (ASO - http://aso.jpl.nasa.gov) combined with extensive in-situ measurements in two key areas in Colorado: Grand Mesa and Senator Beck. While the uncertainty in the 50m snow depth retrievals from NASA's ASO been estimated at 1-2cm in non-vegetated exposed areas (Painter et al., 2016), the impact of forest cover and point-cloud density on ASO snow lidar depth retrievals is relatively unknown. Dense forest canopies are known to reduce lidar penetration and ground strikes thus affecting the elevation surface retrieved from in the forest. Using high-resolution lidar point cloud data from the ASO SnowEx campaigns (26pt/m2) we applied a series of data decimations (up to 90% point reduction) to the point cloud data to quantify the relationship between vegetation, ground point density, resulting snow-off and snow-on surface elevations and finally snow depth. We observed non-linear reductions in lidar ground point density in forested areas that were strongly correlated to structural forest cover metrics. Previously, the impacts of these data decimations on a small study area in Grand Mesa showed a sharp increase in under-canopy surface elevation errors of -0.18m when ground point densities were reduced to 1.5pt/m2. In this study, we expanded the evaluation to the more topographically challenging Senator Beck basin, have conducted analysis along a vegetation gradient and are considering snow the impacts of snow depth rather than snow-off surface elevation. Preliminary analysis suggest that snow depth retrievals inferred from airborne lidar elevation differentials may systematically underestimate snow depth in forests where canopy density exceeds 1.75 and where tree heights exceed 5m. These results provide a basis from which to identify areas that may suffer from vegetation-induced biases in surface elevation models and snow depths derived from airborne lidar data, and help quantify expected spatial distributions of errors in the snow depth that can be used to improve the accuracy of ASO basin-scale depth and water equivalent products.
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Processing Uav and LIDAR Point Clouds in Grass GIS
NASA Astrophysics Data System (ADS)
Petras, V.; Petrasova, A.; Jeziorska, J.; Mitasova, H.
2016-06-01
Today's methods of acquiring Earth surface data, namely lidar and unmanned aerial vehicle (UAV) imagery, non-selectively collect or generate large amounts of points. Point clouds from different sources vary in their properties such as number of returns, density, or quality. We present a set of tools with applications for different types of points clouds obtained by a lidar scanner, structure from motion technique (SfM), and a low-cost 3D scanner. To take advantage of the vertical structure of multiple return lidar point clouds, we demonstrate tools to process them using 3D raster techniques which allow, for example, the development of custom vegetation classification methods. Dense point clouds obtained from UAV imagery, often containing redundant points, can be decimated using various techniques before further processing. We implemented and compared several decimation techniques in regard to their performance and the final digital surface model (DSM). Finally, we will describe the processing of a point cloud from a low-cost 3D scanner, namely Microsoft Kinect, and its application for interaction with physical models. All the presented tools are open source and integrated in GRASS GIS, a multi-purpose open source GIS with remote sensing capabilities. The tools integrate with other open source projects, specifically Point Data Abstraction Library (PDAL), Point Cloud Library (PCL), and OpenKinect libfreenect2 library to benefit from the open source point cloud ecosystem. The implementation in GRASS GIS ensures long term maintenance and reproducibility by the scientific community but also by the original authors themselves.
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The size-line width relation and the mass of molecular hydrogen
DOE Office of Scientific and Technical Information (OSTI.GOV)
Issa, M.; Maclaren, I.; Wolfendale, A. W.
Some difficulties associated with the problem of cloud definition are considered, with particular regard to the crowded distribution of clouds and the difficulty of choosing an appropriate boundary in such circumstances. A number of tests carried out on the original data suggest that the delta(v) - S relation found by Solomon et al. (1987) is not a genuine reflection of the dynamical state of Giant Molecular Clouds. The Solomon et al. parameters, are insensitive to the actual cloud properties and are unable to distinguish true clouds from the consequences of sampling any crowded region of emission down to a lowmore » threshold temperature. The overall effect of such problems is to overestimate both the masses of Giant Molecular Clouds and the number of very large clouds. 24 refs.« less
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Studies of Dark Spots and Their Companion Clouds on the Ice Giant Planets
NASA Astrophysics Data System (ADS)
Bhure, Sakhee; Sankar, Ramanakumar; Hadland, Nathan; Palotai, Csaba J.; Le Beau, Raymond P.; Koutas, Nikko
2017-10-01
Observations of ice giant planets in our Solar System have shown several large-scale dark spots with varying lifespans. Some of these features were directly observed, others were diagnosed from their orographic companion clouds. Historically, numerical simulations have been able to model certain characteristics of these storms such as the shape variability of the Neptune Great Dark Spot (GDS-89) (Deng and Le Beau, 2006), but have not been able to match observed drift rates and lifespans using the standard zonal wind profiles (Hammel et al. 2009). Common amongst these studies has been the lack of condensable species in the atmosphere and an explicit treatment of cloud microphysics. Yet, observations show that dark spots can affect neighboring cloud features, such as in the case of bright companion clouds or the “Berg” on Uranus. An analysis of the cloud structure is therefore required to gain a better understanding of the underlying atmospheric physics and dynamics of these vortices.For our simulations, we use the Explicit Planetary Isentropic Coordinate (EPIC) general circulation model (Dowling et al. 1998, 2006) and adapt its jovian cloud microphysics module which successfully reproduced the cloud structure of jovian storms, such as the Great Red Spot and the Oval BA (Palotai and Dowling 2008, Palotai et al. 2014). EPIC was recently updated to account for the condensation of methane and hydrogen sulfide (Palotai et al. 2016), which allows us to account for both the high-altitude methane ice-cloud and the deep atmosphere hydrogen sulfide ice-cloud layers.In this work, we simulate large-scale vortices on Uranus and Neptune with varying cloud microphysical parameters such as the deep abundance and the ambient supersaturation. We examine the effect of cloud formation on their lifespan and drift rates to better understand the underlying processes which drive these storms.
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NASA Astrophysics Data System (ADS)
Coddington, O.; Pilewskie, P.; Schmidt, S.
2013-12-01
The upwelling shortwave irradiance measured by the airborne Solar Spectral Flux Radiometer (SSFR) flying above a cloud and aerosol layer is influenced by the properties of the cloud and aerosol particles below, just as would the radiance measured from satellite. Unlike satellite measurements, those from aircraft provide the unique capability to fly a lower-level leg above the cloud, yet below the aerosol layer, to characterize the extinction of the aerosol layer and account for its impact on the measured cloud albedo. Previous work [Coddington et al., 2010] capitalized on this opportunity to test the effects of aerosol particles (or more appropriately, the effects of neglecting aerosols in forward modeling calculations) on cloud retrievals using data obtained during the Intercontinental Chemical Transport Experiment/Intercontinental Transport and Chemical Transformation of anthropogenic pollution (INTEX-A/ITCT) study. This work showed aerosols can cause a systematic bias in the cloud retrieval and that such a bias would need to be distinguished from a true aerosol indirect effect (i.e. the brightening of a cloud due to aerosol effects on cloud microphysics) as theorized by Haywood et al., [2004]. The effects of aerosols on clouds are typically neglected in forward modeling calculations because their pervasiveness, variable microphysical properties, loading, and lifetimes makes forward modeling calculations under all possible combinations completely impractical. Using a general inverse theory technique, which propagates separate contributions from measurement and forward modeling errors into probability distributions of retrieved cloud optical thickness and droplet effective radius, we have demonstrated how the aerosol presence can be introduced as a spectral systematic error in the distributions of the forward modeling solutions. The resultant uncertainty and bias in cloud properties induced by the aerosols is identified by the shape and peak of the posteriori retrieval distributions. In this work, we apply this general inverse theory approach to extend our analysis of the spectrally-dependent impacts of overlying aerosols on cloud properties over a broad range in cloud optical thickness and droplet effective radius. We investigate the relative impacts of this error source and compare and contrast results to biases and uncertainties in cloud properties induced by varying surface conditions (ocean, land, snow). We perform the analysis for two different measurement accuracies (3% and 0.3%) that are typical of current passive imagers, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) [Platnick et al., 2003], and that are expected for future passive imagers, such as the HyperSpectral Imager for Climate Science (HySICS) [Kopp et al., 2010]. Coddington, O., P. Pilewskie, et al., 2010, J. Geophys. Res., 115, doi: 10.1029/2009JD012829. Haywood, J. M., S. R. Osborne, and S. J. Abel, 2004, Q. J. R. Meteorol. Soc., 130, 779-800. Kopp, G., et al., 2010, Hyperspectral Imagery Radiometry Improvements for Visible and Near-Infrared Climate Studies, paper presented at 2010 Earth Science Technology Forum, Arlington, VA, USA. Platnick, S., et al., 2003, IEEE Trans. Geosci. Remote Sens., 41(2), 459- 473.
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a Global Registration Algorithm of the Single-Closed Ring Multi-Stations Point Cloud
NASA Astrophysics Data System (ADS)
Yang, R.; Pan, L.; Xiang, Z.; Zeng, H.
2018-04-01
Aimed at the global registration problem of the single-closed ring multi-stations point cloud, a formula in order to calculate the error of rotation matrix was constructed according to the definition of error. The global registration algorithm of multi-station point cloud was derived to minimize the error of rotation matrix. And fast-computing formulas of transformation matrix with whose implementation steps and simulation experiment scheme was given. Compared three different processing schemes of multi-station point cloud, the experimental results showed that the effectiveness of the new global registration method was verified, and it could effectively complete the global registration of point cloud.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Berg, Larry K.; Kassianov, Evgueni I.; Long, Charles N.
2006-03-30
In previous work, Berg and Stull (2005) developed a new parameterization for Fair-Weather Cumuli (FWC). Preliminary testing of the new scheme used data collected during a field experiment conducted during the summer of 1996. This campaign included a few research flights conducted over three locations within the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site. A more comprehensive verification of the new scheme requires a detailed climatology of FWC. Several cloud climatologies have been completed for the ACRF SGP, but these efforts have focused on either broad categories of clouds grouped by height and seasonmore » (e.g., Lazarus et al. 1999) or height and time of day (e.g., Dong et al. 2005). In these two examples, the low clouds were not separated by the type of cloud, either stratiform or cumuliform, nor were the horizontal chord length (the length of the cloud slice that passed directly overhead) or cloud aspect ratio (defined as the ratio of the cloud thickness to the cloud chord length) reported. Lane et al. (2002) presented distributions of cloud chord length, but only for one year. The work presented here addresses these shortcomings by looking explicitly at cases with FWC over five summers. Specifically, we will address the following questions: •Does the cloud fraction (CF), cloud-base height (CBH), and cloud-top height (CTH) of FWC change with the time of day or the year? •What is the distribution of FWC chord lengths? •Is there a relationship between the cloud chord length and the cloud thickness?« less
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NASA Astrophysics Data System (ADS)
Xu, Y.; Sun, Z.; Boerner, R.; Koch, T.; Hoegner, L.; Stilla, U.
2018-04-01
In this work, we report a novel way of generating ground truth dataset for analyzing point cloud from different sensors and the validation of algorithms. Instead of directly labeling large amount of 3D points requiring time consuming manual work, a multi-resolution 3D voxel grid for the testing site is generated. Then, with the help of a set of basic labeled points from the reference dataset, we can generate a 3D labeled space of the entire testing site with different resolutions. Specifically, an octree-based voxel structure is applied to voxelize the annotated reference point cloud, by which all the points are organized by 3D grids of multi-resolutions. When automatically annotating the new testing point clouds, a voting based approach is adopted to the labeled points within multiple resolution voxels, in order to assign a semantic label to the 3D space represented by the voxel. Lastly, robust line- and plane-based fast registration methods are developed for aligning point clouds obtained via various sensors. Benefiting from the labeled 3D spatial information, we can easily create new annotated 3D point clouds of different sensors of the same scene directly by considering the corresponding labels of 3D space the points located, which would be convenient for the validation and evaluation of algorithms related to point cloud interpretation and semantic segmentation.
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The One to Multiple Automatic High Accuracy Registration of Terrestrial LIDAR and Optical Images
NASA Astrophysics Data System (ADS)
Wang, Y.; Hu, C.; Xia, G.; Xue, H.
2018-04-01
The registration of ground laser point cloud and close-range image is the key content of high-precision 3D reconstruction of cultural relic object. In view of the requirement of high texture resolution in the field of cultural relic at present, The registration of point cloud and image data in object reconstruction will result in the problem of point cloud to multiple images. In the current commercial software, the two pairs of registration of the two kinds of data are realized by manually dividing point cloud data, manual matching point cloud and image data, manually selecting a two - dimensional point of the same name of the image and the point cloud, and the process not only greatly reduces the working efficiency, but also affects the precision of the registration of the two, and causes the problem of the color point cloud texture joint. In order to solve the above problems, this paper takes the whole object image as the intermediate data, and uses the matching technology to realize the automatic one-to-one correspondence between the point cloud and multiple images. The matching of point cloud center projection reflection intensity image and optical image is applied to realize the automatic matching of the same name feature points, and the Rodrigo matrix spatial similarity transformation model and weight selection iteration are used to realize the automatic registration of the two kinds of data with high accuracy. This method is expected to serve for the high precision and high efficiency automatic 3D reconstruction of cultural relic objects, which has certain scientific research value and practical significance.
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Global Single and Multiple Cloud Classification with a Fuzzy Logic Expert System
NASA Technical Reports Server (NTRS)
Welch, Ronald M.; Tovinkere, Vasanth; Titlow, James; Baum, Bryan A.
1996-01-01
An unresolved problem in remote sensing concerns the analysis of satellite imagery containing both single and multiple cloud layers. While cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget, most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. Coakley (1983) used a spatial coherence method to determine whether a region contained more than one cloud layer. Baum et al. (1995) developed a scheme for detection and analysis of daytime multiple cloud layers using merged AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High-resolution Infrared Radiometer Sounder) data collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign. Baum et al. (1995) explored the use of a cloud classification technique based on AVHRR data. This study examines the feasibility of applying the cloud classifier to global satellite imagery.
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Brute Force Matching Between Camera Shots and Synthetic Images from Point Clouds
NASA Astrophysics Data System (ADS)
Boerner, R.; Kröhnert, M.
2016-06-01
3D point clouds, acquired by state-of-the-art terrestrial laser scanning techniques (TLS), provide spatial information about accuracies up to several millimetres. Unfortunately, common TLS data has no spectral information about the covered scene. However, the matching of TLS data with images is important for monoplotting purposes and point cloud colouration. Well-established methods solve this issue by matching of close range images and point cloud data by fitting optical camera systems on top of laser scanners or rather using ground control points. The approach addressed in this paper aims for the matching of 2D image and 3D point cloud data from a freely moving camera within an environment covered by a large 3D point cloud, e.g. a 3D city model. The key advantage of the free movement affects augmented reality applications or real time measurements. Therefore, a so-called real image, captured by a smartphone camera, has to be matched with a so-called synthetic image which consists of reverse projected 3D point cloud data to a synthetic projection centre whose exterior orientation parameters match the parameters of the image, assuming an ideal distortion free camera.
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An Approach of Web-based Point Cloud Visualization without Plug-in
NASA Astrophysics Data System (ADS)
Ye, Mengxuan; Wei, Shuangfeng; Zhang, Dongmei
2016-11-01
With the advances in three-dimensional laser scanning technology, the demand for visualization of massive point cloud is increasingly urgent, but a few years ago point cloud visualization was limited to desktop-based solutions until the introduction of WebGL, several web renderers are available. This paper addressed the current issues in web-based point cloud visualization, and proposed a method of web-based point cloud visualization without plug-in. The method combines ASP.NET and WebGL technologies, using the spatial database PostgreSQL to store data and the open web technologies HTML5 and CSS3 to implement the user interface, a visualization system online for 3D point cloud is developed by Javascript with the web interactions. Finally, the method is applied to the real case. Experiment proves that the new model is of great practical value which avoids the shortcoming of the existing WebGIS solutions.
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Model for Semantically Rich Point Cloud Data
NASA Astrophysics Data System (ADS)
Poux, F.; Neuville, R.; Hallot, P.; Billen, R.
2017-10-01
This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.
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1984-07-01
aerosols and sub pixel-sized clouds all tend to increase Channel 1 with respect to Channel 2 and reduce the computed VIN. Further, the Guide states that... computation of the VIN. Large scale cloud contamination of pixels, while diffi- cult to correct for, can at least be monitored and affected pixels...techniques have been developed for computer cloud screening. See, for example, Horvath et al. (1982), Gray and McCrary (1981a) and Nixon et al. (1983
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Formation of massive clouds and dwarf galaxies during tidal encounters
NASA Technical Reports Server (NTRS)
Kaufman, Michele; Elmegreen, Bruce G.; Thomasson, Magnus; Elmegreen, Debra M.
1993-01-01
Gerola et al. (1983) propose that isolated dwarf galaxies can form during galaxy interactions. As evidence of this process, Mirabel et al. (1991) find 10(exp 9) solar mass clouds and star formation complexes at the outer ends of the tidal arms in the Antennae and Superantennae galaxies. We describe observations of HI clouds with mass greater than 10(exp 8) solar mass in the interacting galaxy pair IC 2163/NGC 2207. This pair is important because we believe it represents an early stage in the formation of giant clouds during an encounter. We use a gravitational instability model to explain why the observed clouds are so massive and discuss a two-dimensional N-body simulation of an encounter that produces giant clouds.
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Reevaluation of lunar and Martian spectra in the mid-IR region.
Plendl, J N; Plendl, H S
1982-12-15
A reference point method has been developed to correct infrared spectra from the moon and other celestial objects for selective absorption in the earth's atmosphere. The method is applied to lunar spectra that were obtained 2.3 km above sea level within the two atmospheric IR windows. The results indicate that SiO(2) and Al(2)O(3) are major mineral constituents in the four large surface areas analyzed in agreement with the localized probings at spacecraft landing sites. In addition, IR spectra from Martian dust clouds that were observed from the Mariner 9 spacecraft are examined. The principal sources of radiation in this case appear to be Al(2)O(3) and sulfur.
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Self-Similar Spin Images for Point Cloud Matching
NASA Astrophysics Data System (ADS)
Pulido, Daniel
The rapid growth of Light Detection And Ranging (Lidar) technologies that collect, process, and disseminate 3D point clouds have allowed for increasingly accurate spatial modeling and analysis of the real world. Lidar sensors can generate massive 3D point clouds of a collection area that provide highly detailed spatial and radiometric information. However, a Lidar collection can be expensive and time consuming. Simultaneously, the growth of crowdsourced Web 2.0 data (e.g., Flickr, OpenStreetMap) have provided researchers with a wealth of freely available data sources that cover a variety of geographic areas. Crowdsourced data can be of varying quality and density. In addition, since it is typically not collected as part of a dedicated experiment but rather volunteered, when and where the data is collected is arbitrary. The integration of these two sources of geoinformation can provide researchers the ability to generate products and derive intelligence that mitigate their respective disadvantages and combine their advantages. Therefore, this research will address the problem of fusing two point clouds from potentially different sources. Specifically, we will consider two problems: scale matching and feature matching. Scale matching consists of computing feature metrics of each point cloud and analyzing their distributions to determine scale differences. Feature matching consists of defining local descriptors that are invariant to common dataset distortions (e.g., rotation and translation). Additionally, after matching the point clouds they can be registered and processed further (e.g., change detection). The objective of this research is to develop novel methods to fuse and enhance two point clouds from potentially disparate sources (e.g., Lidar and crowdsourced Web 2.0 datasets). The scope of this research is to investigate both scale and feature matching between two point clouds. The specific focus of this research will be in developing a novel local descriptor based on the concept of self-similarity to aid in the scale and feature matching steps. An open problem in fusion is how best to extract features from two point clouds and then perform feature-based matching. The proposed approach for this matching step is the use of local self-similarity as an invariant measure to match features. In particular, the proposed approach is to combine the concept of local self-similarity with a well-known feature descriptor, Spin Images, and thereby define "Self-Similar Spin Images". This approach is then extended to the case of matching two points clouds in very different coordinate systems (e.g., a geo-referenced Lidar point cloud and stereo-image derived point cloud without geo-referencing). The use of Self-Similar Spin Images is again applied to address this problem by introducing a "Self-Similar Keyscale" that matches the spatial scales of two point clouds. Another open problem is how best to detect changes in content between two point clouds. A method is proposed to find changes between two point clouds by analyzing the order statistics of the nearest neighbors between the two clouds, and thereby define the "Nearest Neighbor Order Statistic" method. Note that the well-known Hausdorff distance is a special case as being just the maximum order statistic. Therefore, by studying the entire histogram of these nearest neighbors it is expected to yield a more robust method to detect points that are present in one cloud but not the other. This approach is applied at multiple resolutions. Therefore, changes detected at the coarsest level will yield large missing targets and at finer levels will yield smaller targets.
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Rosnell, Tomi; Honkavaara, Eija
2012-01-01
The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479
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Rosnell, Tomi; Honkavaara, Eija
2012-01-01
The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation.
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Stereoscopic observations from meteorological satellites
NASA Astrophysics Data System (ADS)
Hasler, A. F.; Mack, R.; Negri, A.
The capability of making stereoscopic observations of clouds from meteorological satellites is a new basic analysis tool with a broad spectrum of applications. Stereoscopic observations from satellites were first made using the early vidicon tube weather satellites (e.g., Ondrejka and Conover [1]). However, the only high quality meteorological stereoscopy from low orbit has been done from Apollo and Skylab, (e.g., Shenk et al. [2] and Black [3], [4]). Stereoscopy from geosynchronous satellites was proposed by Shenk [5] and Bristor and Pichel [6] in 1974 which allowed Minzner et al. [7] to demonstrate the first quantitative cloud height analysis. In 1978 Bryson [8] and desJardins [9] independently developed digital processing techniques to remap stereo images which made possible precision height measurement and spectacular display of stereograms (Hasler et al. [10], and Hasler [11]). In 1980 the Japanese Geosynchronous Satellite (GMS) and the U.S. GOES-West satellite were synchronized to obtain stereo over the central Pacific as described by Fujita and Dodge [12] and in this paper. Recently the authors have remapped images from a Low Earth Orbiter (LEO) to the coordinate system of a Geosynchronous Earth Orbiter (GEO) and obtained stereoscopic cloud height measurements which promise to have quality comparable to previous all GEO stereo. It has also been determined that the north-south imaging scan rate of some GEOs can be slowed or reversed. Therefore the feasibility of obtaining stereoscopic observations world wide from combinations of operational GEO and LEO satellites has been demonstrated. Stereoscopy from satellites has many advantages over infrared techniques for the observation of cloud structure because it depends only on basic geometric relationships. Digital remapping of GEO and LEO satellite images is imperative for precision stereo height measurement and high quality displays because of the curvature of the earth and the large angular separation of the two satellites. A general solution for accurate height computation depends on precise navigation of the two satellites. Validation of the geosynchronous satellite stereo using high altitude mountain lakes and vertically pointing aircraft lidar leads to a height accuracy estimate of +/- 500 m for typical clouds which have been studied. Applications of the satellite stereo include: 1) cloud top and base height measurements, 2) cloud-wind height assignment, 3) vertical motion estimates for convective clouds (Mack et al. [13], [14]), 4) temperature vs. height measurements when stereo is used together with infrared observations and 5) cloud emissivity measurements when stereo, infrared and temperature sounding are used together (see Szejwach et al. [15]). When true satellite stereo image pairs are not available, synthetic stereo may be generated. The combination of multispectral satellite data using computer produced stereo image pairs is a dramatic example of synthetic stereoscopic display. The classic case uses the combination of infrared and visible data as first demonstrated by Pichel et al. [16]. Hasler et at. [17], Mosher and Young [18] and Lorenz [19], have expanded this concept to display many channels of data from various radiometers as well as real and simulated data fields. A future system of stereoscopic satellites would be comprised of both low orbiters (as suggested by Lorenz and Schmidt [20], [19]) and a global system of geosynchronous satellites. The low earth orbiters would provide stereo coverage day and night and include the poles. An optimum global system of stereoscopic geosynchronous satellites would require international standarization of scan rate and direction, and scan times (synchronization) and resolution of at least 1 km in all imaging channels. A stereoscopic satellite system as suggested here would make an extremely important contribution to the understanding and prediction of the atmosphere.
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Photoionisation modelling of the broad line region
NASA Astrophysics Data System (ADS)
King, Anthea
2016-08-01
Two of the most fundamental questions regarding the broad line region (BLR) are "what is its structure?" and "how is it moving?" Baldwin et al. (1995) showed that by summing over an ensemble of clouds at differing densities and distances from the ionising source we can easily and naturally produce a spectrum similar to what is observed for AGN. This approach is called the `locally optimally emitting clouds' (LOC) model. This approach can also explain the well-observed stratification of emission lines in the BLR (e.g. Clavel et al. 1991, Peterson et al. 1991, Kollatschny et al. 2001) and `breathing' of BLR with changes in the continuum luminosity (Netzer & Mor 1990, Peterson et al. 2014) and is therefore a generally accepted model of the BLR. However, LOC predictions require some assumptions to be made about the distribution of the clouds within the BLR. By comparing photoionization predictions, for a distribution of cloud properties, with observed spectra we can infer something about the structure of the BLR and distribution of clouds. I use existing reverberation mapping data to constrain the structure of the BLR by observing how individual line strengths and ratios of different lines change in high and low luminosity states. I will present my initial constraints and discuss the challenges associated with the method.
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NASA Technical Reports Server (NTRS)
Kawamoto, Kazuaki; Minnis, Patrick; Smith, William L., Jr.
2001-01-01
One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a 1-layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum el al. (1995) used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow (1997) also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. (1999) used a combination infrared, visible, and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne (2000) proposed 1.6 and 11 microns. bispectral threshold method. While all of these methods have made progress in solving this stubborn problem, none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the ARM domains (e.g., Minnis et al 1998) and hence should identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the NOAA Advanced Very High Resolution Radiometer (AVHRR) used over the ARM SGP and NSA sites to study the capability of detecting overlapping clouds
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a Fast Method for Measuring the Similarity Between 3d Model and 3d Point Cloud
NASA Astrophysics Data System (ADS)
Zhang, Zongliang; Li, Jonathan; Li, Xin; Lin, Yangbin; Zhang, Shanxin; Wang, Cheng
2016-06-01
This paper proposes a fast method for measuring the partial Similarity between 3D Model and 3D point Cloud (SimMC). It is crucial to measure SimMC for many point cloud-related applications such as 3D object retrieval and inverse procedural modelling. In our proposed method, the surface area of model and the Distance from Model to point Cloud (DistMC) are exploited as measurements to calculate SimMC. Here, DistMC is defined as the weighted distance of the distances between points sampled from model and point cloud. Similarly, Distance from point Cloud to Model (DistCM) is defined as the average distance of the distances between points in point cloud and model. In order to reduce huge computational burdens brought by calculation of DistCM in some traditional methods, we define SimMC as the ratio of weighted surface area of model to DistMC. Compared to those traditional SimMC measuring methods that are only able to measure global similarity, our method is capable of measuring partial similarity by employing distance-weighted strategy. Moreover, our method is able to be faster than other partial similarity assessment methods. We demonstrate the superiority of our method both on synthetic data and laser scanning data.
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Motion Estimation System Utilizing Point Cloud Registration
NASA Technical Reports Server (NTRS)
Chen, Qi (Inventor)
2016-01-01
A system and method of estimation motion of a machine is disclosed. The method may include determining a first point cloud and a second point cloud corresponding to an environment in a vicinity of the machine. The method may further include generating a first extended gaussian image (EGI) for the first point cloud and a second EGI for the second point cloud. The method may further include determining a first EGI segment based on the first EGI and a second EGI segment based on the second EGI. The method may further include determining a first two dimensional distribution for points in the first EGI segment and a second two dimensional distribution for points in the second EGI segment. The method may further include estimating motion of the machine based on the first and second two dimensional distributions.
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Pointo - a Low Cost Solution to Point Cloud Processing
NASA Astrophysics Data System (ADS)
Houshiar, H.; Winkler, S.
2017-11-01
With advance in technology access to data especially 3D point cloud data becomes more and more an everyday task. 3D point clouds are usually captured with very expensive tools such as 3D laser scanners or very time consuming methods such as photogrammetry. Most of the available softwares for 3D point cloud processing are designed for experts and specialists in this field and are usually very large software packages containing variety of methods and tools. This results in softwares that are usually very expensive to acquire and also very difficult to use. Difficulty of use is caused by complicated user interfaces that is required to accommodate a large list of features. The aim of these complex softwares is to provide a powerful tool for a specific group of specialist. However they are not necessary required by the majority of the up coming average users of point clouds. In addition to complexity and high costs of these softwares they generally rely on expensive and modern hardware and only compatible with one specific operating system. Many point cloud customers are not point cloud processing experts or willing to spend the high acquisition costs of these expensive softwares and hardwares. In this paper we introduce a solution for low cost point cloud processing. Our approach is designed to accommodate the needs of the average point cloud user. To reduce the cost and complexity of software our approach focuses on one functionality at a time in contrast with most available softwares and tools that aim to solve as many problems as possible at the same time. Our simple and user oriented design improve the user experience and empower us to optimize our methods for creation of an efficient software. In this paper we introduce Pointo family as a series of connected softwares to provide easy to use tools with simple design for different point cloud processing requirements. PointoVIEWER and PointoCAD are introduced as the first components of the Pointo family to provide a fast and efficient visualization with the ability to add annotation and documentation to the point clouds.
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Study of Huizhou architecture component point cloud in surface reconstruction
NASA Astrophysics Data System (ADS)
Zhang, Runmei; Wang, Guangyin; Ma, Jixiang; Wu, Yulu; Zhang, Guangbin
2017-06-01
Surface reconfiguration softwares have many problems such as complicated operation on point cloud data, too many interaction definitions, and too stringent requirements for inputing data. Thus, it has not been widely popularized so far. This paper selects the unique Huizhou Architecture chuandou wooden beam framework as the research object, and presents a complete set of implementation in data acquisition from point, point cloud preprocessing and finally implemented surface reconstruction. Firstly, preprocessing the acquired point cloud data, including segmentation and filtering. Secondly, the surface’s normals are deduced directly from the point cloud dataset. Finally, the surface reconstruction is studied by using Greedy Projection Triangulation Algorithm. Comparing the reconstructed model with the three-dimensional surface reconstruction softwares, the results show that the proposed scheme is more smooth, time efficient and portable.
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Compression of 3D Point Clouds Using a Region-Adaptive Hierarchical Transform.
De Queiroz, Ricardo; Chou, Philip A
2016-06-01
In free-viewpoint video, there is a recent trend to represent scene objects as solids rather than using multiple depth maps. Point clouds have been used in computer graphics for a long time and with the recent possibility of real time capturing and rendering, point clouds have been favored over meshes in order to save computation. Each point in the cloud is associated with its 3D position and its color. We devise a method to compress the colors in point clouds which is based on a hierarchical transform and arithmetic coding. The transform is a hierarchical sub-band transform that resembles an adaptive variation of a Haar wavelet. The arithmetic encoding of the coefficients assumes Laplace distributions, one per sub-band. The Laplace parameter for each distribution is transmitted to the decoder using a custom method. The geometry of the point cloud is encoded using the well-established octtree scanning. Results show that the proposed solution performs comparably to the current state-of-the-art, in many occasions outperforming it, while being much more computationally efficient. We believe this work represents the state-of-the-art in intra-frame compression of point clouds for real-time 3D video.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, W; Sawant, A; Ruan, D
2016-06-15
Purpose: Surface photogrammetry (e.g. VisionRT, C-Rad) provides a noninvasive way to obtain high-frequency measurement for patient motion monitoring in radiotherapy. This work aims to develop a real-time surface reconstruction method on the acquired point clouds, whose acquisitions are subject to noise and missing measurements. In contrast to existing surface reconstruction methods that are usually computationally expensive, the proposed method reconstructs continuous surfaces with comparable accuracy in real-time. Methods: The key idea in our method is to solve and propagate a sparse linear relationship from the point cloud (measurement) manifold to the surface (reconstruction) manifold, taking advantage of the similarity inmore » local geometric topology in both manifolds. With consistent point cloud acquisition, we propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, building the point correspondences by the iterative closest point (ICP) method. To accommodate changing noise levels and/or presence of inconsistent occlusions, we further propose a modified sparse regression (MSR) model to account for the large and sparse error built by ICP, with a Laplacian prior. We evaluated our method on both clinical acquired point clouds under consistent conditions and simulated point clouds with inconsistent occlusions. The reconstruction accuracy was evaluated w.r.t. root-mean-squared-error, by comparing the reconstructed surfaces against those from the variational reconstruction method. Results: On clinical point clouds, both the SR and MSR models achieved sub-millimeter accuracy, with mean reconstruction time reduced from 82.23 seconds to 0.52 seconds and 0.94 seconds, respectively. On simulated point cloud with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent performance despite the introduced occlusions. Conclusion: We have developed a real-time and robust surface reconstruction method on point clouds acquired by photogrammetry systems. It serves an important enabling step for real-time motion tracking in radiotherapy. This work is supported in part by NIH grant R01 CA169102-02.« less
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The global impact of mineral dust on cloud droplet number concentration
NASA Astrophysics Data System (ADS)
Karydis, V.; Tsimpidi, A.; Bacer, S.; Pozzer, A.; Nenes, A.; Lelieveld, J.
2016-12-01
This study assesses the importance of mineral dust for cloud droplet formation by taking into account i) the adsorption of water on the surface of insoluble dust particles, ii) the coating of soluble material on the surface of mineral particles which augments their cloud condensation nuclei activity, and iii) the effect of dust on the inorganic aerosol concentrations through thermodynamic interactions with mineral cations. Simulations are carried out with the EMAC chemistry climate model that calculates the global atmospheric aerosol composition using the ISORROPIA-II thermodynamic equilibrium model and considers the gas phase interactions with K+-Ca2+-Mg2+-NH4+-Na+-SO42-NO3-Cl-H2O particle components. Emissions of the inert mineral dust and the reactive dust aerosol components are calculated online by taking into account the soil particle size distribution and chemical composition of different deserts worldwide (Karydis et al., 2016). We have implemented the "unified dust activation parameterization" (Kumar et al., 2011; Karydis et al., 2011) to calculate the droplet number concentration by taking into account the inherent hydrophilicity from adsorption and the acquired hygroscopicity from soluble salts by dust particles. Our simulations suggest that mineral dust significantly increases the cloud droplet number concentration (CDNC) over the main deserts and the adjacent oceans. However, over polluted areas the CDNC decreases significantly in the presence of dust. Furthermore, we investigate the role of adsorption activation of insoluble aerosols and the mineral dust thermodynamic interactions with inorganic anions on the cloud droplet formation. The CDNC sensitivity to the emission load, chemical composition, and inherent hydrophilicity of mineral dust is also tested. ReferencesKarydis, et al. (2011). "On the effect of dust particles on global cloud condensation nuclei and cloud droplet number." J. Geophys. Res. Atmos. 116. Karydis, et al. (2016). "Effects of mineral dust on global atmospheric nitrate concentrations." Atmos. Chem. Phys. 16(3): 1491-1509. Kumar, et al. (2011). "Measurements of cloud condensation nuclei activity and droplet activation kinetics of wet processed regional dust samples and minerals." Atmos. Chem. Phys. Discuss. 11(4): 12561-12605.
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FPFH-based graph matching for 3D point cloud registration
NASA Astrophysics Data System (ADS)
Zhao, Jiapeng; Li, Chen; Tian, Lihua; Zhu, Jihua
2018-04-01
Correspondence detection is a vital step in point cloud registration and it can help getting a reliable initial alignment. In this paper, we put forward an advanced point feature-based graph matching algorithm to solve the initial alignment problem of rigid 3D point cloud registration with partial overlap. Specifically, Fast Point Feature Histograms are used to determine the initial possible correspondences firstly. Next, a new objective function is provided to make the graph matching more suitable for partially overlapping point cloud. The objective function is optimized by the simulated annealing algorithm for final group of correct correspondences. Finally, we present a novel set partitioning method which can transform the NP-hard optimization problem into a O(n3)-solvable one. Experiments on the Stanford and UWA public data sets indicates that our method can obtain better result in terms of both accuracy and time cost compared with other point cloud registration methods.
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CLaMS-Ice: Large-scale cirrus cloud simulations in comparison with observations
NASA Astrophysics Data System (ADS)
Costa, Anja; Rolf, Christian; Grooß, Jens-Uwe; Spichtinger, Peter; Afchine, Armin; Spelten, Nicole; Dreiling, Volker; Zöger, Martin; Krämer, Martina
2016-04-01
Cirrus clouds are an element of uncertainty in the climate system and have received increasing attention since the last IPCC reports. The interactions of different freezing mechanisms, sedimentation rates, updraft velocity fluctuations and other factors that determine the formation and evolution of those clouds is still not fully understood. Thus, a reliable representation of cirrus clouds in models representing real atmospheric conditions is still a challenging task. At last year's EGU, Rolf et al. (2015) introduced the new large-scale microphysical cirrus cloud model CLaMS-Ice: based on trajectories calculated with CLaMS (McKenna et al., 2002 and Konopka et al. 2007), it simulates the development of cirrus clouds relying on the cirrus bulk model by Spichtinger and Gierens (2009). The qualitative agreement between CLaMS-Ice simulations and observations could be demonstrated at that time. Now we present a detailed quantitative comparison between standard ECMWF products, CLaMS-Ice simulations, and in-situ measurements obtained during the ML-Cirrus campaign 2014. We discuss the agreement of the parameters temperature (observational data: BAHAMAS), relative humidity (SHARC), cloud occurrence, cloud particle concentration, ice water content and cloud particle radii (all NIXE-CAPS). Due to the precise trajectories based on ECMWF wind and temperature fields, CLaMS-Ice represents the cirrus cloud vertical and horizontal coverage more accurately than the ECMWF ice water content (IWC) fields. We demonstrate how CLaMS-Ice can be used to evaluate different input settings (e.g. amount of ice nuclei, freezing thresholds, sedimentation settings) that lead to cirrus clouds with the microphysical properties observed during ML-Cirrus (2014).
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Smart Point Cloud: Definition and Remaining Challenges
NASA Astrophysics Data System (ADS)
Poux, F.; Hallot, P.; Neuville, R.; Billen, R.
2016-10-01
Dealing with coloured point cloud acquired from terrestrial laser scanner, this paper identifies remaining challenges for a new data structure: the smart point cloud. This concept arises with the statement that massive and discretized spatial information from active remote sensing technology is often underused due to data mining limitations. The generalisation of point cloud data associated with the heterogeneity and temporality of such datasets is the main issue regarding structure, segmentation, classification, and interaction for an immediate understanding. We propose to use both point cloud properties and human knowledge through machine learning to rapidly extract pertinent information, using user-centered information (smart data) rather than raw data. A review of feature detection, machine learning frameworks and database systems indexed both for mining queries and data visualisation is studied. Based on existing approaches, we propose a new 3-block flexible framework around device expertise, analytic expertise and domain base reflexion. This contribution serves as the first step for the realisation of a comprehensive smart point cloud data structure.
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Motion-Compensated Compression of Dynamic Voxelized Point Clouds.
De Queiroz, Ricardo L; Chou, Philip A
2017-05-24
Dynamic point clouds are a potential new frontier in visual communication systems. A few articles have addressed the compression of point clouds, but very few references exist on exploring temporal redundancies. This paper presents a novel motion-compensated approach to encoding dynamic voxelized point clouds at low bit rates. A simple coder breaks the voxelized point cloud at each frame into blocks of voxels. Each block is either encoded in intra-frame mode or is replaced by a motion-compensated version of a block in the previous frame. The decision is optimized in a rate-distortion sense. In this way, both the geometry and the color are encoded with distortion, allowing for reduced bit-rates. In-loop filtering is employed to minimize compression artifacts caused by distortion in the geometry information. Simulations reveal that this simple motion compensated coder can efficiently extend the compression range of dynamic voxelized point clouds to rates below what intra-frame coding alone can accommodate, trading rate for geometry accuracy.
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Solubilization of phenanthrene above cloud point of Brij 30: a new application in biodegradation.
Pantsyrnaya, T; Delaunay, S; Goergen, J L; Guseva, E; Boudrant, J
2013-06-01
In the present study a new application of solubilization of phenanthrene above cloud point of Brij 30 in biodegradation was developed. It was shown that a temporal solubilization of phenanthrene above cloud point of Brij 30 (5wt%) permitted to obtain a stable increase of the solubility of phenanthrene even when the temperature was decreased to culture conditions of used microorganism Pseudomonas putida (28°C). A higher initial concentration of soluble phenanthrene was obtained after the cloud point treatment: 200 against 120μM without treatment. All soluble phenanthrene was metabolized and a higher final concentration of its major metabolite - 1-hydroxy-2-naphthoic acid - (160 against 85μM) was measured in the culture medium in the case of a preliminary cloud point treatment. Therefore a temporary solubilization at cloud point might have a perspective application in the enhancement of biodegradation of polycyclic aromatic hydrocarbons. Copyright © 2013 Elsevier Ltd. All rights reserved.
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A portable low-cost 3D point cloud acquiring method based on structure light
NASA Astrophysics Data System (ADS)
Gui, Li; Zheng, Shunyi; Huang, Xia; Zhao, Like; Ma, Hao; Ge, Chao; Tang, Qiuxia
2018-03-01
A fast and low-cost method of acquiring 3D point cloud data is proposed in this paper, which can solve the problems of lack of texture information and low efficiency of acquiring point cloud data with only one pair of cheap cameras and projector. Firstly, we put forward a scene adaptive design method of random encoding pattern, that is, a coding pattern is projected onto the target surface in order to form texture information, which is favorable for image matching. Subsequently, we design an efficient dense matching algorithm that fits the projected texture. After the optimization of global algorithm and multi-kernel parallel development with the fusion of hardware and software, a fast acquisition system of point-cloud data is accomplished. Through the evaluation of point cloud accuracy, the results show that point cloud acquired by the method proposed in this paper has higher precision. What`s more, the scanning speed meets the demand of dynamic occasion and has better practical application value.
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Joint classification and contour extraction of large 3D point clouds
NASA Astrophysics Data System (ADS)
Hackel, Timo; Wegner, Jan D.; Schindler, Konrad
2017-08-01
We present an effective and efficient method for point-wise semantic classification and extraction of object contours of large-scale 3D point clouds. What makes point cloud interpretation challenging is the sheer size of several millions of points per scan and the non-grid, sparse, and uneven distribution of points. Standard image processing tools like texture filters, for example, cannot handle such data efficiently, which calls for dedicated point cloud labeling methods. It turns out that one of the major drivers for efficient computation and handling of strong variations in point density, is a careful formulation of per-point neighborhoods at multiple scales. This allows, both, to define an expressive feature set and to extract topologically meaningful object contours. Semantic classification and contour extraction are interlaced problems. Point-wise semantic classification enables extracting a meaningful candidate set of contour points while contours help generating a rich feature representation that benefits point-wise classification. These methods are tailored to have fast run time and small memory footprint for processing large-scale, unstructured, and inhomogeneous point clouds, while still achieving high classification accuracy. We evaluate our methods on the semantic3d.net benchmark for terrestrial laser scans with >109 points.
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Point clouds segmentation as base for as-built BIM creation
NASA Astrophysics Data System (ADS)
Macher, H.; Landes, T.; Grussenmeyer, P.
2015-08-01
In this paper, a three steps segmentation approach is proposed in order to create 3D models from point clouds acquired by TLS inside buildings. The three scales of segmentation are floors, rooms and planes composing the rooms. First, floor segmentation is performed based on analysis of point distribution along Z axis. Then, for each floor, room segmentation is achieved considering a slice of point cloud at ceiling level. Finally, planes are segmented for each room, and planes corresponding to ceilings and floors are identified. Results of each step are analysed and potential improvements are proposed. Based on segmented point clouds, the creation of as-built BIM is considered in a future work section. Not only the classification of planes into several categories is proposed, but the potential use of point clouds acquired outside buildings is also considered.
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High-Precision Registration of Point Clouds Based on Sphere Feature Constraints.
Huang, Junhui; Wang, Zhao; Gao, Jianmin; Huang, Youping; Towers, David Peter
2016-12-30
Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method.
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High-Precision Registration of Point Clouds Based on Sphere Feature Constraints
Huang, Junhui; Wang, Zhao; Gao, Jianmin; Huang, Youping; Towers, David Peter
2016-01-01
Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method. PMID:28042846
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NASA Astrophysics Data System (ADS)
Garate-Lopez, Itziar; Lebonnois, Sébastien
2017-04-01
A new simulation of Venus atmospheric circulation obtained with the LMD Venus GCM is described and the impact of cloud's latitudinal structure on the general circulation is analyzed. The model used here is based on that presented in Lebonnois et al. (2016). However, in the present simulation we consider the latitudinal variation of the cloud structure (Haus et al., 2014) both for the solar heating and to compute the infrared net-exchange rate matrix used in the radiative transfer module. The new cloud treatment affects mainly the balance in the angular momentum and the zonal wind distribution. Consequently, the agreement between the vertical profile of the modeled mean zonal wind and the profiles measured by different probes, is clearly improved from previous simulations in which zonal winds below the clouds were weak (roughly half the observed values). Moreover, the equatorial jet obtained at the base of the cloud deck is now more consistent with the observations. In Lebonnois et al. (2016) it was too strong compared to mid-latitudes, but in the present simulation the equatorial jet is less intense than the mid-latitude jets, in concordance with cloud-tracking measurements (Hueso et al., 2015). Since the atmospheric waves play a crucial role in the angular momentum budget of the Venus's atmospheric circulation, we analyze the wave activity by means of the Fast Fourier Transform technique studying the frequency spectrum of temperature, zonal and meridional wind fields. Modifications in the activity of the different types of waves present in the Venusian atmosphere compared to Lebonnois et al. (2016) are discussed, in terms of horizontal and vertical transport of the angular momentum by diurnal and semi-diurnal tides, barotropic and baroclinic waves, and Rossby and Kelvin type waves. Haus R., Kappel D. and Arnold G., 2014. Atmospheric thermal structure and cloud features in the southern hemisphere of Venus as retrieved from VIRTIS/VEX radiation measurements. Icarus 232, 232-248. Hueso R., Peralta J., Garate-Lopez I., et al., 2015. Six years of Venus winds at the upper cloud level from UV, visible and near infrared observations from VIRTIS on Venus express. Planet. Space Sci. 113-114, 78-99. Lebonnois S., Sugimoto N., and Gilli G., 2016. Wave analysis in the atmosphere of Venus below 100km altitude, simulated by the LMD Venus GCM. Icarus 278, 38-51.
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Pan, Tao; Liu, Chunyan; Zeng, Xinying; Xin, Qiao; Xu, Meiying; Deng, Yangwu; Dong, Wei
2017-06-01
A recent work has shown that hydrophobic organic compounds solubilized in the micelle phase of some nonionic surfactants present substrate toxicity to microorganisms with increasing bioavailability. However, in cloud point systems, biotoxicity is prevented, because the compounds are solubilized into a coacervate phase, thereby leaving a fraction of compounds with cells in a dilute phase. This study extends the understanding of the relationship between substrate toxicity and bioavailability of hydrophobic organic compounds solubilized in nonionic surfactant micelle phase and cloud point system. Biotoxicity experiments were conducted with naphthalene and phenanthrene in the presence of mixed nonionic surfactants Brij30 and TMN-3, which formed a micelle phase or cloud point system at different concentrations. Saccharomyces cerevisiae, unable to degrade these compounds, was used for the biotoxicity experiments. Glucose in the cloud point system was consumed faster than in the nonionic surfactant micelle phase, indicating that the solubilized compounds had increased toxicity to cells in the nonionic surfactant micelle phase. The results were verified by subsequent biodegradation experiments. The compounds were degraded faster by PAH-degrading bacterium in the cloud point system than in the micelle phase. All these results showed that biotoxicity of the hydrophobic organic compounds increases with bioavailability in the surfactant micelle phase but remains at a low level in the cloud point system. These results provide a guideline for the application of cloud point systems as novel media for microbial transformation or biodegradation.
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Impact of Aerosol Processing on Orographic Clouds
NASA Astrophysics Data System (ADS)
Pousse-Nottelmann, Sara; Zubler, Elias M.; Lohmann, Ulrike
2010-05-01
Aerosol particles undergo significant modifications during their residence time in the atmosphere. Physical processes like coagulation, coating and water uptake, and aqueous surface chemistry alter the aerosol size distribution and composition. At this, clouds play a primary role as physical and chemical processing inside cloud droplets contributes considerably to the changes in aerosol particles. A previous study estimates that on global average atmospheric particles are cycled three times through a cloud before being removed from the atmosphere [1]. An explicit and detailed treatment of cloud-borne particles has been implemented in the regional weather forecast and climate model COSMO-CLM. The employed model version includes a two-moment cloud microphysical scheme [2] that has been coupled to the aerosol microphysical scheme M7 [3] as described by Muhlbauer and Lohmann, 2008 [4]. So far, the formation, transfer and removal of cloud-borne aerosol number and mass were not considered in the model. Following the parameterization for cloud-borne particles developed by Hoose et al., 2008 [5], distinction between in-droplet and in-crystal particles is made to more physically account for processes in mixed-phase clouds, such as the Wegener-Bergeron-Findeisen process and contact and immersion freezing. In our model, this approach has been extended to allow for aerosol particles in five different hydrometeors: cloud droplets, rain drops, ice crystals, snow flakes and graupel. We account for nucleation scavenging, freezing and melting processes, autoconversion, accretion, aggregation, riming and selfcollection, collisions between interstitial aerosol particles and hydrometeors, ice multiplication, sedimentation, evaporation and sublimation. The new scheme allows an evaluation of the cloud cycling of aerosol particles by tracking the particles even when scavenged into hydrometeors. Global simulations of aerosol processing in clouds have recently been conducted by Hoose et al. [6]. Our investigation regarding the influence of aerosol processing will focus on the regional scale using a cloud-system resolving model with a much higher resolution. Emphasis will be placed on orographic mixed-phase precipitation. Different two-dimensional simulations of idealized orographic clouds will be conducted to estimate the effect of aerosol processing on orographic cloud formation and precipitation. Here, cloud lifetime, location and extent as well as the cloud type will be of particular interest. In a supplementary study, the new parameterization will be compared to observations of total and interstitial aerosol concentrations and size distribution at the remote high alpine research station Jungfraujoch in Switzerland. In addition, our simulations will be compared to recent simulations of aerosol processing in warm, mixed-phase and cold clouds, which have been carried out at the location of Jungfraujoch station [5]. References: [1] Pruppacher & Jaenicke (1995), The processing of water vapor and aerosols by atmospheric clouds, a global estimate, Atmos. Res., 38, 283295. [2] Seifert & Beheng (2006), A two-moment microphysics parameterization for mixed-phase clouds. Part 1: Model description, Meteorol. Atmos. Phys., 92, 4566. [3] Vignati et al. (2004), An efficient size-resolved aerosol microphysics module for large-scale transport models, J. Geophys. Res., 109, D22202 [4] Muhlbauer & Lohmann (2008), Sensitivity studies of the role of aerosols in warm-phase orographic precipitation in different flow regimes, J. Atmos. Sci., 65, 25222542. [5] Hoose et al. (2008), Aerosol processing in mixed-phase clouds in ECHAM5HAM: Model description and comparison to observations, J. Geophys. Res., 113, D071210. [6] Hoose et al. (2008), Global simulations of aerosol processing in clouds, Atmos. Chem. Phys., 8, 69396963.
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Study of the thermodynamic phase of hydrometeors in convective clouds in the Amazon Basin
NASA Astrophysics Data System (ADS)
Ferreira, W. C.; Correia, A. L.; Martins, J.
2012-12-01
Aerosol-cloud interactions are responsible for large uncertainties in climatic models. One key fator when studying clouds perturbed by aerosols is determining the thermodynamic phase of hydrometeors as a function of temperature or height in the cloud. Conventional remote sensing can provide information on the thermodynamic phase of clouds over large areas, but it lacks the precision needed to understand how a single, real cloud evolves. Here we present mappings of the thermodynamic phase of droplets and ice particles in individual convective clouds in the Amazon Basin, by analyzing the emerging infrared radiance on cloud sides (Martins et al., 2011). In flights over the Amazon Basin with a research aircraft Martins et al. (2011) used imaging radiometers with spectral filters to record the emerging radiance on cloud sides at the wavelengths of 2.10 and 2.25 μm. Due to differential absorption and scattering of these wavelengths by hydrometeors in liquid or solid phases, the intensity ratio between images recorded at the two wavelengths can be used as proxy to the thermodynamic phase of these hydrometeors. In order to analyze the acquired dataset we used the MATLAB tools package, developing scripts to handle data files and derive the thermodynamic phase. In some cases parallax effects due to aircraft movement required additional data processing before calculating ratios. Only well illuminated scenes were considered, i.e. images acquired as close as possible to the backscatter vector from the incident solar radiation. It's important to notice that the intensity ratio values corresponding to a given thermodynamic phase can vary from cloud to cloud (Martins et al., 2011), however inside the same cloud the distinction between ice, water and mixed-phase is clear. Analyzing histograms of reflectance ratios 2.10/2.25 μm in selected cases, we found averages typically between 0.3 and 0.4 for ice phase hydrometeors, and between 0.5 and 0.7 for water phase droplets, consistent with the findings in Martins et al., (2011). Figure 1 shows an example of thermodynamic phase classification obtained with this technique. These experimental results can potentially be used in fast derivations of thermodynamic phase mappings in deep convective clouds, providing useful information for studies regarding aerosol-cloud interactions. Image of the ratio of reflectances at 2.10/2.25μm
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Relating Line Width and Optical Depth for CO Emission in the Large Mgellanic Cloud
NASA Astrophysics Data System (ADS)
Wojciechowski, Evan; Wong, Tony; Bandurski, Jeffrey; MC3 (Mapping CO in Molecular Clouds in the Magellanic Clouds) Team
2018-01-01
We investigate data produced from ALMA observations of giant molecular clouds (GMCs) located in the Large Magellanic Cloud (LMC), using 12CO(2–1) and 13CO(2–1) emission. The spectral line width is generally interpreted as tracing turbulent rather than thermal motions in the cloud, but could also be affected by optical depth, especially for the 12CO line (Hacar et al. 2016). We compare the spectral line widths of both lines with their optical depths, estimated from an LTE analysis, to evaluate the importance of optical depth effects. Our cloud sample includes two regions recently published by Wong et al. (2017, submitted): the Tarantula Nebula or 30 Dor, an HII region rife with turbulence, and the Planck cold cloud (PCC), located in a much calmer environment near the fringes of the LMC. We also include four additional LMC clouds, which span intermediate levels of star formation relative to these two clouds, and for which we have recently obtained ALMA data in Cycle 4.
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A LiDAR Survey of an Exposed Magma Plumbing System in the San Rafael Desert, Utah
NASA Astrophysics Data System (ADS)
Richardson, J. A.; Kinman, S.; Connor, L.; Connor, C.; Wetmore, P. H.
2013-12-01
Fields of dozens to hundreds of volcanoes are a common occurrence on Earth and are created due to distributed-style volcanism often referred to as "monogenetic." These volcanic fields represent a significant hazard on both local and regional scales. While it is important to understand the physical states of active volcanic fields, it is difficult or impossible to directly observe active magma emplacement. Because of this, observing an exposed magmatic plumbing system may enable further efforts to describe active volcanic fields. The magmatic plumbing system of a Pliocene-aged monogenetic volcanic field is currently exposed as a sill and dike swarm in the San Rafael Desert of Central Utah. Alkali diabase and shonkinitic sills and dikes in this region intruded into Mesozoic sedimentary units of the Colorado Plateau and now make up the most erosion resistant units, forming mesas, ridges, and small peaks associated with sills, dikes, and plug-like bodies respectively. Diez et al. (Lithosphere, 2009) and Kiyosugi et al. (Geology, 2012) provide evidence that each cylindrical plug-like body represents a conduit that once fed one volcano. The approximate original depth of the currently exposed swarm is estimated to be 0.8 km. Volcanic and sedimentary materials may be discriminated at very high resolution with the use of Light Detection and Ranging (LiDAR). LiDAR produces a three dimensional point cloud, where each point has an associated return intensity. High resolution, bare earth digital elevation models (DEMs) can be produced after vegetation is identified and removed from the dataset. The return intensity at each point can enable classification as either sedimentary or volcanic rock. A Terrestrial LiDAR Survey (TLS) has been carried out to map a large hill with at least one volcanic conduit at its core. This survey implements a RIEGL VZ-400 3D Laser Scanner, which successfully maps solid objects in line-of-sight and within 600 meters. The laser used has a near infrared wavelength. The scanner is set up at 11 scan positions around the conduit edifice, enabling the creation of a 3D point cloud for the edifice and surrounding surface geology. Vegetation is then removed and the point cloud is georeferenced to create a bare earth DEM. Points are assigned RGB color values using calibrated photographs taken coincident to the laser scanning. With the processed LiDAR point cloud, volcanic and sedimentary materials may be discriminated by return intensity and RGB color values. We find that intrusive material returns a demonstrably lower intensity signal than the lighter sedimentary units. Along with field mapping during the TLS, this information can provide high resolution detail of the local magma plumbing system. Exposed dikes, sills, and conduits mapped by this survey are extrapolated into a 3D space from the top of the edifice the base election of the survey to provide a first-order estimate of the final intrusive volume of the now eroded volcanic field in this location.
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NASA Astrophysics Data System (ADS)
Santos, E. G.; Jorge, A.; Shimabukuro, Y. E.; Gasparini, K.
2017-12-01
The State of Mato Grosso - MT has the second largest area with degraded forest among the states of the Brazilian Legal Amazon. Land use and land cover change processes that occur in this region cause the loss of forest biomass, releasing greenhouse gases that contribute to the increase of temperature on earth. These degraded forest areas lose biomass according to the intensity and magnitude of the degradation type. The estimate of forest biomass, commonly performed by forest inventory through sample plots, shows high variance in degraded forest areas. Due to this variance and complexity of tropical forests, the aim of this work was to estimate forest biomass using LiDAR point clouds in three distinct forest areas: one degraded by fire, another by selective logging and one area of intact forest. The approach applied in these areas was the Individual Tree Detection (ITD). To isolate the trees, we generated Canopy Height Models (CHM) images, which are obtained by subtracting the Digital Elevation Model (MDE) and the Digital Terrain Model (MDT), created by the cloud of LiDAR points. The trees in the CHM images are isolated by an algorithm provided by the Quantitative Ecology research group at the School of Forestry at Northern Arizona University (SILVA, 2015). With these points, metrics were calculated for some areas, which were used in the model of biomass estimation. The methodology used in this work was expected to reduce the error in biomass estimate in the study area. The cloud points of the most representative trees were analyzed, and thus field data was correlated with the individual trees found by the proposed algorithm. In a pilot study, the proposed methodology was applied generating the individual tree metrics: total height and area of the crown. When correlating 339 isolated trees, an unsatisfactory R² was obtained, as heights found by the algorithm were lower than those obtained in the field, with an average difference of 2.43 m. This shows that the algorithm used to isolate trees in temperate areas did not obtained satisfactory results in the tropical forest of Mato Grosso State. Due to this, in future works two algorithms, one developed by Dalponte et al. (2015) and another by Li et al. (2012) will be used.
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Vicente, Filipa A; Cardoso, Inês S; Sintra, Tânia E; Lemus, Jesus; Marques, Eduardo F; Ventura, Sónia P M; Coutinho, João A P
2017-09-21
Aqueous micellar two-phase systems (AMTPS) hold a large potential for cloud point extraction of biomolecules but are yet poorly studied and characterized, with few phase diagrams reported for these systems, hence limiting their use in extraction processes. This work reports a systematic investigation of the effect of different surface-active ionic liquids (SAILs)-covering a wide range of molecular properties-upon the clouding behavior of three nonionic Tergitol surfactants. Two different effects of the SAILs on the cloud points and mixed micelle size have been observed: ILs with a more hydrophilic character and lower critical packing parameter (CPP < 1 / 2 ) lead to the formation of smaller micelles and concomitantly increase the cloud points; in contrast, ILs with a more hydrophobic character and higher CPP (CPP ≥ 1) induce significant micellar growth and a decrease in the cloud points. The latter effect is particularly interesting and unusual for it was accepted that cloud point reduction is only induced by inorganic salts. The effects of nonionic surfactant concentration, SAIL concentration, pH, and micelle ζ potential are also studied and rationalized.
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Point Cloud Management Through the Realization of the Intelligent Cloud Viewer Software
NASA Astrophysics Data System (ADS)
Costantino, D.; Angelini, M. G.; Settembrini, F.
2017-05-01
The paper presents a software dedicated to the elaboration of point clouds, called Intelligent Cloud Viewer (ICV), made in-house by AESEI software (Spin-Off of Politecnico di Bari), allowing to view point cloud of several tens of millions of points, also on of "no" very high performance systems. The elaborations are carried out on the whole point cloud and managed by means of the display only part of it in order to speed up rendering. It is designed for 64-bit Windows and is fully written in C ++ and integrates different specialized modules for computer graphics (Open Inventor by SGI, Silicon Graphics Inc), maths (BLAS, EIGEN), computational geometry (CGAL, Computational Geometry Algorithms Library), registration and advanced algorithms for point clouds (PCL, Point Cloud Library), advanced data structures (BOOST, Basic Object Oriented Supporting Tools), etc. ICV incorporates a number of features such as, for example, cropping, transformation and georeferencing, matching, registration, decimation, sections, distances calculation between clouds, etc. It has been tested on photographic and TLS (Terrestrial Laser Scanner) data, obtaining satisfactory results. The potentialities of the software have been tested by carrying out the photogrammetric survey of the Castel del Monte which was already available in previous laser scanner survey made from the ground by the same authors. For the aerophotogrammetric survey has been adopted a flight height of approximately 1000ft AGL (Above Ground Level) and, overall, have been acquired over 800 photos in just over 15 minutes, with a covering not less than 80%, the planned speed of about 90 knots.
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Fast ground filtering for TLS data via Scanline Density Analysis
NASA Astrophysics Data System (ADS)
Che, Erzhuo; Olsen, Michael J.
2017-07-01
Terrestrial Laser Scanning (TLS) efficiently collects 3D information based on lidar (light detection and ranging) technology. TLS has been widely used in topographic mapping, engineering surveying, forestry, industrial facilities, cultural heritage, and so on. Ground filtering is a common procedure in lidar data processing, which separates the point cloud data into ground points and non-ground points. Effective ground filtering is helpful for subsequent procedures such as segmentation, classification, and modeling. Numerous ground filtering algorithms have been developed for Airborne Laser Scanning (ALS) data. However, many of these are error prone in application to TLS data because of its different angle of view and highly variable resolution. Further, many ground filtering techniques are limited in application within challenging topography and experience difficulty coping with some objects such as short vegetation, steep slopes, and so forth. Lastly, due to the large size of point cloud data, operations such as data traversing, multiple iterations, and neighbor searching significantly affect the computation efficiency. In order to overcome these challenges, we present an efficient ground filtering method for TLS data via a Scanline Density Analysis, which is very fast because it exploits the grid structure storing TLS data. The process first separates the ground candidates, density features, and unidentified points based on an analysis of point density within each scanline. Second, a region growth using the scan pattern is performed to cluster the ground candidates and further refine the ground points (clusters). In the experiment, the effectiveness, parameter robustness, and efficiency of the proposed method is demonstrated with datasets collected from an urban scene and a natural scene, respectively.
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NASA Astrophysics Data System (ADS)
Nayak, M.; Beck, J.; Udrea, B.
This paper focuses on the aerospace application of a single beam laser rangefinder (LRF) for 3D imaging, shape detection, and reconstruction in the context of a space-based space situational awareness (SSA) mission scenario. The primary limitation to 3D imaging from LRF point clouds is the one-dimensional nature of the single beam measurements. A method that combines relative orbital motion and scanning attitude motion to generate point clouds has been developed and the design and characterization of multiple relative motion and attitude maneuver profiles are presented. The target resident space object (RSO) has the shape of a generic telecommunications satellite. The shape and attitude of the RSO are unknown to the chaser satellite however, it is assumed that the RSO is un-cooperative and has fixed inertial pointing. All sensors in the metrology chain are assumed ideal. A previous study by the authors used pure Keplerian motion to perform a similar 3D imaging mission at an asteroid. A new baseline for proximity operations maneuvers for LRF scanning, based on a waypoint adaptation of the Hill-Clohessy-Wiltshire (HCW) equations is examined. Propellant expenditure for each waypoint profile is discussed and combinations of relative motion and attitude maneuvers that minimize the propellant used to achieve a minimum required point cloud density are studied. Both LRF strike-point coverage and point cloud density are maximized; the capability for 3D shape registration and reconstruction from point clouds generated with a single beam LRF without catalog comparison is proven. Next, a method of using edge detection algorithms to process a point cloud into a 3D modeled image containing reconstructed shapes is presented. Weighted accuracy of edge reconstruction with respect to the true model is used to calculate a qualitative “ metric” that evaluates effectiveness of coverage. Both edge recognition algorithms and the metric are independent of point cloud densit- , therefore they are utilized to compare the quality of point clouds generated by various attitude and waypoint command profiles. The RSO model incorporates diverse irregular protruding shapes, such as open sensor covers, instrument pods and solar arrays, to test the limits of the algorithms. This analysis is used to mathematically prove that point clouds generated by a single-beam LRF can achieve sufficient edge recognition accuracy for SSA applications, with meaningful shape information extractable even from sparse point clouds. For all command profiles, reconstruction of RSO shapes from the point clouds generated with the proposed method are compared to the truth model and conclusions are drawn regarding their fidelity.
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NASA Astrophysics Data System (ADS)
Gézero, L.; Antunes, C.
2017-05-01
The digital terrain models (DTM) assume an essential role in all types of road maintenance, water supply and sanitation projects. The demand of such information is more significant in developing countries, where the lack of infrastructures is higher. In recent years, the use of Mobile LiDAR Systems (MLS) proved to be a very efficient technique in the acquisition of precise and dense point clouds. These point clouds can be a solution to obtain the data for the production of DTM in remote areas, due mainly to the safety, precision, speed of acquisition and the detail of the information gathered. However, the point clouds filtering and algorithms to separate "terrain points" from "no terrain points", quickly and consistently, remain a challenge that has caught the interest of researchers. This work presents a method to create the DTM from point clouds collected by MLS. The method is based in two interactive steps. The first step of the process allows reducing the cloud point to a set of points that represent the terrain's shape, being the distance between points inversely proportional to the terrain variation. The second step is based on the Delaunay triangulation of the points resulting from the first step. The achieved results encourage a wider use of this technology as a solution for large scale DTM production in remote areas.
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Evaluation of terrestrial photogrammetric point clouds derived from thermal imagery
NASA Astrophysics Data System (ADS)
Metcalf, Jeremy P.; Olsen, Richard C.
2016-05-01
Computer vision and photogrammetric techniques have been widely applied to digital imagery producing high density 3D point clouds. Using thermal imagery as input, the same techniques can be applied to infrared data to produce point clouds in 3D space, providing surface temperature information. The work presented here is an evaluation of the accuracy of 3D reconstruction of point clouds produced using thermal imagery. An urban scene was imaged over an area at the Naval Postgraduate School, Monterey, CA, viewing from above as with an airborne system. Terrestrial thermal and RGB imagery were collected from a rooftop overlooking the site using a FLIR SC8200 MWIR camera and a Canon T1i DSLR. In order to spatially align each dataset, ground control points were placed throughout the study area using Trimble R10 GNSS receivers operating in RTK mode. Each image dataset is processed to produce a dense point cloud for 3D evaluation.
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Green Bank Telescope OH Observations of Smith's Cloud: Evidence Of A Lack Of Chemistry
NASA Astrophysics Data System (ADS)
Minter, Anthony
2017-03-01
Smith's Cloud is a large few × 106 Solar Mass cloud which will impact the Milk Way disk in about 35 Million Years (Lockman et al., 2008). Green Bank Telescope OH observations indicate that there are no molecules present in Smith's Cloud, and thus there is no active ongoing chemistry in Smith's Cloud.
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NASA Technical Reports Server (NTRS)
Ginger, Kathryn M.
1993-01-01
Since clouds are the largest variable in Earth's radiation budget, it is critical to determine both the spatial and temporal characteristics of their radiative properties. This study examines the relationships between cloud properties and cloud fraction in order to supplement grid scale parameterizations. The satellite data used in this study is from three hourly ISCCP (International Satellite Cloud Climatology Project) and monthly ERBE (Earth Radiation Budget Experiment) data on a 2.50 x 2.50 latitude-longitude grid. Mean cloud spherical albedo, the mean optical depth distribution and cloud fraction are examined and compared off the coast of California and the mid-tropical Atlantic for July 1987 and 1988. Individual grid boxes and spatial averages over several grid boxes are correlated to Coakleys (1991) theory of reflection for uniform and broken layered cloud and to Kedem, et al.(1990) findings that rainfall volume and fractional area of rain in convective systems is linear. Kedem's hypothesis can be expressed in terms of cloud properties. That is, the total volume of liquid in a box is a linear function of cloud fraction. Results for the marine stratocumulus regime indicate that albedo is often invariant for cloud fractions of 20% to 80%. Coakley's satellite model of small and large clouds with cores (1 km) and edges (100 in) is consistent with this observation. The cores maintain high liquid water concentrations and large droplets while the edges contain low liquid water concentrations and small droplets. Large clouds are just a collection of cores. The mean optical depth (TAU) distributions support the above observation with TAU values of 3.55 to 9.38 favored across all cloud fractions. From these results, a method based upon Kedem, et al. theory is proposed to separate the cloud fraction and liquid water path (LWP) calculations in a general circulation model (GCM). In terms of spatial averaging, a linear relationship between albedo and cloud fraction is observed. For tropical locations outside the Intertropical Convergence Zone (ITCZ), results of cloud fraction and albedo spatial averaging followed that of the stratus boxes containing few overcast scenes. Both the ideas of Coakley and Kedem, et al. apply. Within the ITCZ, the grid boxes tended to have the same statistical properties as stratus boxes containing many overcast scenes. Because different dynamical forcing mechanisms are present, it is difficult to devise a method for determining subgrid scale variations. Neither of the theories proposed by Kedem, et al. or Coakley works well for the boxes with numerous overcast scenes.
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NASA Astrophysics Data System (ADS)
Li, Tao; Wang, Yan; Zhou, Jie; Wang, Tao; Ding, Aijun; Nie, Wei; Xue, Likun; Wang, Xinfeng; Wang, Wenxing
2017-03-01
Aerosols and cloud water were analyzed at a mountaintop in the planetary boundary layer in southern China during March-May 2009, when two Asian dust storms occurred, to investigate the effects of aerosol-cloud interactions (ACIs) on chemical evolution of atmospheric trace elements. Fe, Al, and Zn predominated in both coarse and fine aerosols, followed by high concentrations of toxic Pb, As, and Cd. Most of these aerosol trace elements, which were affected by dust storms, exhibited various increases in concentrations but consistent decreases in solubility. Zn, Fe, Al, and Pb were the most abundant trace elements in cloud water. The trace element concentrations exhibited logarithmic inverse relationships with the cloud liquid water content and were found highly pH dependent with minimum concentrations at the threshold of pH 5.0. The calculation of Visual MINTEQ model showed that 80.7-96.3% of Fe(II), Zn(II), Pb(II), and Cu(II) existed in divalent free ions, while 71.7% of Fe(III) and 71.5% of Al(III) were complexed by oxalate and fluoride, respectively. ACIs could markedly change the speciation distributions of trace elements in cloud water by pH modification. The in-cloud scavenging of aerosol trace elements likely reached a peak after the first 2-3 h of cloud processing, with scavenging ratios between 0.12 for Cr and 0.57 for Pb. The increases of the trace element solubility (4-33%) were determined in both in-cloud aerosols and postcloud aerosols. These results indicated the significant importance of aerosol-cloud interactions to the evolution of trace elements during the first several cloud condensation/evaporation cycles.
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Polar cloud observatory at Ny-Ålesund in GRENE Arctic Climate Change Research Project
NASA Astrophysics Data System (ADS)
Yamanouchi, Takashi; Takano, Toshiaki; Shiobara, Masataka; Okamoto, Hajime; Koike, Makoto; Ukita, Jinro
2016-04-01
Cloud is one of the main processes in the climate system and especially a large feed back agent for Arctic warming amplification (Yoshimori et al., 2014). From this reason, observation of polar cloud has been emphasized and 95 GHz cloud profiling radar in high precision was established at Ny-Ålesund, Svalbard in 2013 as one of the basic infrastructure in the GRENE (Green Network of Excellence Program) Arctic Climate Change Research Project. The radar, "FALCON-A", is a FM-CW (frequency modulated continuous wave) Doppler radar, developed for Arctic use by Chiba University (PI: T. Takano) in 2012, following its prototype, "FALCON-1" which was developed in 2006 (Takano et al., 2010). The specifications of the radar are, central frequency: 94.84 GHz; antenna power: 1 W; observation height: up to 15 km; range resolution: 48 m; beam width: 0.2 degree (15 m at 5 km); Doppler width: 3.2 m/s; time interval: 10 sec, and capable of archiving high sensitivity and high spatial and time resolution. An FM-CW type radar realizes similar sensitivity with much smaller parabolic antennas separated 1.4 m from each other used for transmitting and receiving the wave. Polarized Micro-Pulse Lidar (PMPL, Sigma Space MPL-4B-IDS), which is capable to measure the backscatter and depolarization ratio, has also been deployed to Ny-Ålesund in March 2012, and now operated to perform collocated measurements with FALCON-A. Simultaneous measurement data from collocated PMPL and FALCON-A are available for synergetic analyses of cloud microphysics. Cloud mycrophysics, such as effective radius of ice particles and ice water content, are obtained from the analysis based on algorithm, which is modified for ground-based measurements from Okamoto's retrieval algorithm for satellite based cloud profiling radar and lidar (CloudSat and CALIPSO; Okamoto et al., 2010). Results of two years will be shown in the presentation. Calibration is a point to derive radar reflectivity (dBZ) from original intensity data. Degradation of transmission power was monitored and sensitivity of receiving system was derived with estimating antenna gain by using radio wave absorber and considering antenna geometry of two antenna system. In order to estimate final results, altitude dependent detection limit curve was also calculated. Original intensity data in real time and calibrated radar reflectivity data are archived on "Arctic Data archive System (ADS)". Other collocated observations were made with fog monitor (particle size distribution), MPS (particle image) for continuous measurements at Zeppelin Mountain, 450 m height a. s. l., and tethered balloon for intense observing period. From these measurements together with aerosol and meteorological monitoring made by collaborating institutes (Stockholm University, University of Florence, AWI, NILU, NCAR and NPI) microphysics of low level cloud and aerosol-cloud interactions are discussed. Ground based remote sensors provide a powerful validation for satellite cloud observations. Radar reflectivity (dBZ) by FALCON-A was compared with that by CPR on CloudSAT during several overpasses around Ny-Ålesund, and though some difference due to the different vertical resolution was seen, overall agreement was confirmed. We are planning to establish Ny-Ålesund observatory as the super site for validation for EarthCARE (JAXA-ESA) mission.
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NASA Astrophysics Data System (ADS)
Bolkas, Dimitrios; Martinez, Aaron
2018-01-01
Point-cloud coordinate information derived from terrestrial Light Detection And Ranging (LiDAR) is important for several applications in surveying and civil engineering. Plane fitting and segmentation of target-surfaces is an important step in several applications such as in the monitoring of structures. Reliable parametric modeling and segmentation relies on the underlying quality of the point-cloud. Therefore, understanding how point-cloud errors affect fitting of planes and segmentation is important. Point-cloud intensity, which accompanies the point-cloud data, often goes hand-in-hand with point-cloud noise. This study uses industrial particle boards painted with eight different colors (black, white, grey, red, green, blue, brown, and yellow) and two different sheens (flat and semi-gloss) to explore how noise and plane residuals vary with scanning geometry (i.e., distance and incidence angle) and target-color. Results show that darker colors, such as black and brown, can produce point clouds that are several times noisier than bright targets, such as white. In addition, semi-gloss targets manage to reduce noise in dark targets by about 2-3 times. The study of plane residuals with scanning geometry reveals that, in many of the cases tested, residuals decrease with increasing incidence angles, which can assist in understanding the distribution of plane residuals in a dataset. Finally, a scheme is developed to derive survey guidelines based on the data collected in this experiment. Three examples demonstrate that users should consider instrument specification, required precision of plane residuals, required point-spacing, target-color, and target-sheen, when selecting scanning locations. Outcomes of this study can aid users to select appropriate instrumentation and improve planning of terrestrial LiDAR data-acquisition.
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Reactions of N(+) (3P) ions with normal, para, and deuterated hydrogens at low temperatures
NASA Astrophysics Data System (ADS)
Marquette, J. B.; Rebrion, C.; Rowe, B. R.
1988-08-01
The method of reaction kinetics in uniform supersonic flow (French designation CRESU; Dupeyrat et al., 1985) is used to study the reactions of N(+) (3P) with n-H2, p-H2, HD, and D2 at temperatures 8, 20, 27, 45, 68, 163, and 300 K. Results obtained using either He or N2 as the buffer gas are presented in tables and graphs and discussed in detail. The reaction with p-H2 is shown to be significantly slower than that with n-H2, a finding attributed to rotational-energy and spin-orbit-energy driving of these processes. It is pointed out that these results are in agreement with those of Barlow et al. (1986) and Herbst et al. (1987), apparently ruling out these reactions as the source of the NH3 observed in dense interstellar cloud cores.
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NASA Astrophysics Data System (ADS)
Poux, F.; Neuville, R.; Billen, R.
2017-08-01
Reasoning from information extraction given by point cloud data mining allows contextual adaptation and fast decision making. However, to achieve this perceptive level, a point cloud must be semantically rich, retaining relevant information for the end user. This paper presents an automatic knowledge-based method for pre-processing multi-sensory data and classifying a hybrid point cloud from both terrestrial laser scanning and dense image matching. Using 18 features including sensor's biased data, each tessera in the high-density point cloud from the 3D captured complex mosaics of Germigny-des-prés (France) is segmented via a colour multi-scale abstraction-based featuring extracting connectivity. A 2D surface and outline polygon of each tessera is generated by a RANSAC plane extraction and convex hull fitting. Knowledge is then used to classify every tesserae based on their size, surface, shape, material properties and their neighbour's class. The detection and semantic enrichment method shows promising results of 94% correct semantization, a first step toward the creation of an archaeological smart point cloud.
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NASA Astrophysics Data System (ADS)
Liu, X.; Wang, Y.; Zhang, D.; Wang, Z.
2016-12-01
Mixed-phase clouds consisting of both liquid and ice water occur frequently at high-latitudes and in mid-latitude storm track regions. This type of clouds has been shown to play a critical role in the surface energy balance, surface air temperature, and sea ice melting in the Arctic. Cloud phase partitioning between liquid and ice water determines the cloud optical depth of mixed-phase clouds because of distinct optical properties of liquid and ice hydrometeors. The representation and simulation of cloud phase partitioning in state-of-the-art global climate models (GCMs) are associated with large biases. In this study, the cloud phase partition in mixed-phase clouds simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against satellite observations. Observation-based supercooled liquid fraction (SLF) is calculated from CloudSat, MODIS and CPR radar detected liquid and ice water paths for clouds with cloud-top temperatures between -40 and 0°C. Sensitivity tests with CAM5 are conducted for different heterogeneous ice nucleation parameterizations with respect to aerosol influence (Wang et al., 2014), different phase transition temperatures for detrained cloud water from shallow convection (Kay et al., 2016), and different CAM5 model configurations (free-run versus nudged winds and temperature, Zhang et al., 2015). A classical nucleation theory-based ice nucleation parameterization in mixed-phase clouds increases the SLF especially at temperatures colder than -20°C, and significantly improves the model agreement with observations in the Arctic. The change of transition temperature for detrained cloud water increases the SLF at higher temperatures and improves the SLF mostly over the Southern Ocean. Even with the improved SLF from the ice nucleation and shallow cumulus detrainment, the low SLF biases in some regions can only be improved through the improved circulation with the nudging technique. Our study highlights the challenges of representations of large-scale moisture transport, cloud microphysics, ice nucleation, and cumulus detrainment in order to improve the mixed-phase transition in GCMs.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
de Szoeke, Simon P.
The investigator and DOE-supported student [1] retrieved vertical air velocity and microphysical fall velocity retrieval for VOCALS and CAP-MBL homogeneous clouds. [2] Calculated in-cloud and cloud top dissipation calculation and diurnal cycle computed for VOCALS. [3] Compared CAP-MBL Doppler cloud radar scenes with (Remillard et al. 2012) automated classification.
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Temporally consistent segmentation of point clouds
NASA Astrophysics Data System (ADS)
Owens, Jason L.; Osteen, Philip R.; Daniilidis, Kostas
2014-06-01
We consider the problem of generating temporally consistent point cloud segmentations from streaming RGB-D data, where every incoming frame extends existing labels to new points or contributes new labels while maintaining the labels for pre-existing segments. Our approach generates an over-segmentation based on voxel cloud connectivity, where a modified k-means algorithm selects supervoxel seeds and associates similar neighboring voxels to form segments. Given the data stream from a potentially mobile sensor, we solve for the camera transformation between consecutive frames using a joint optimization over point correspondences and image appearance. The aligned point cloud may then be integrated into a consistent model coordinate frame. Previously labeled points are used to mask incoming points from the new frame, while new and previous boundary points extend the existing segmentation. We evaluate the algorithm on newly-generated RGB-D datasets.
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Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory
NASA Astrophysics Data System (ADS)
Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro
2016-04-01
Nowadays, mobile laser scanning has become a valid technology for infrastructure inspection. This technology permits collecting accurate 3D point clouds of urban and road environments and the geometric and semantic analysis of data became an active research topic in the last years. This paper focuses on the detection of vertical traffic signs in 3D point clouds acquired by a LYNX Mobile Mapper system, comprised of laser scanning and RGB cameras. Each traffic sign is automatically detected in the LiDAR point cloud, and its main geometric parameters can be automatically extracted, therefore aiding the inventory process. Furthermore, the 3D position of traffic signs are reprojected on the 2D images, which are spatially and temporally synced with the point cloud. Image analysis allows for recognizing the traffic sign semantics using machine learning approaches. The presented method was tested in road and urban scenarios in Galicia (Spain). The recall results for traffic sign detection are close to 98%, and existing false positives can be easily filtered after point cloud projection. Finally, the lack of a large, publicly available Spanish traffic sign database is pointed out.
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Structure and covariance of cloud and rain water in marine stratocumulus
NASA Astrophysics Data System (ADS)
Witte, Mikael; Morrison, Hugh; Gettelman, Andrew
2017-04-01
Many state of the art cloud microphysics parameterizations in large-scale models use assumed probability density functions (pdfs) to represent subgrid scale variability of relevant resolved scale variables such as vertical velocity and cloud liquid water content (LWC). Integration over the assumed pdfs of small scale variability results in physically consistent prediction of nonlinear microphysical process rates and obviates the need to apply arbitrary tuning parameters to the calculated rates. In such parameterizations, the covariance of cloud and rain LWC is an important quantity for parameterizing the accretion process by which rain drops grow via collection of cloud droplets. This covariance has been diagnosed by other workers from a variety of observational and model datasets (Boutle et al., 2013; Larson and Griffin, 2013; Lebsock et al., 2013), but there is poor agreement in findings across the studies. Two key assumptions that may explain some of the discrepancies among past studies are 1) LWC (both cloud and rain) distributions are statistically stationary and 2) spatial structure may be neglected. Given the highly intermittent nature of precipitation and the fact that cloud LWC has been found to be poorly represented by stationary pdfs (e.g. Marshak et al., 1997), neither of the aforementioned assumptions are valid. Therefore covariance must be evaluated as a function of spatial scale without the assumption of stationary statistics (i.e. variability cannot be expressed as a fractional standard deviation, which necessitates well-defined first and second moments of the LWC distribution). The present study presents multifractal analyses of both rain and cloud LWC using aircraft data from the VOCALS-REx field campaign to illustrate the importance of spatial structure in microphysical parameterizations and extends the results of Boutle et al. (2013) to provide a parameterization of rain-cloud water covariance as a function of spatial scale without the assumption of statistical stationarity.
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Model Intercomparison of CCN-Limited Arctic Clouds During ASCOS
NASA Astrophysics Data System (ADS)
Stevens, Robin; Dearden, Chris; Dimetrelos, Antonios; Eirund, Gesa; Possner, Anna; Raatikainen, Tomi; Loewe, Katharina; Hill, Adrian; Shipway, Ben; Connolly, Paul; Ekman, Annica; Hoose, Corinna; Laaksonen, Ari; de Leeuw, Gerrit; Kolmonen, Pekka; Saponaro, Giulia; Field, Paul; Carlsaw, Ken
2017-04-01
Future decreases in Arctic sea ice are expected to increase fluxes of aerosol and precursor gases from the open ocean surface within the Arctic. The resulting increase in cloud condensation nuclei (CCN) concentrations would be expected to result in increased cloud albedo (Struthers et al, 2011), leading to potentially large changes in radiative forcings. However, Browse et al. (2014) have shown that these increases in condensable material could also result in the growth of existing particles to sizes where they are more efficiently removed by wet deposition in drizzling stratocumulus clouds, ultimately decreasing CCN concentrations in the high Arctic. Their study was limited in that it did not simulate alterations of dynamics or cloud properties due to either changes in heat and moisture fluxes following sea-ice loss or changing aerosol concentrations. Taken together, these results show that significant uncertainties remain in trying to quantify aerosol-cloud processes in the Arctic system. The current representation of these processes in global climate models is most likely insufficient to realistically simulate long-term changes. In order to better understand the microphysical processes currently governing Arctic clouds, we perform a model intercomparison of summertime high Arctic (>80N) clouds observed during the 2008 ASCOS campaign. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). The results of these experiments will be used as a basis for sensitivity studies on the impact of sea-ice loss on Arctic clouds through changes in aerosol and precursor emissions as well as changes in latent and sensible heat fluxes. Browse, J., et al., Atmos. Chem. Phys., 14(14), 7543-7557, doi:10.5194/acp-14-7543-2014, 2014. Struthers, H., et al., Atmos. Chem. Phys., 11(7), 3459-3477, doi:10.5194/acp-11-3459-2011, 2011.
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NASA Astrophysics Data System (ADS)
Kastner, Joel H.; Myers, P. C.
1994-02-01
One hypothesis for the elevated abundance of Al-26 present during the formation of the solar system is that an asymptotic giant branch (AGB) star expired within the molecular cloud (MC) containing the protosolar nebula. To test this hypothesis for star-forming clouds at the present epoch, we compared nearly complete lists of rapidly mass-losing AGB stars and MCs in the solar neighborhood and identified those stars which are most likely to encounter a nearby cloud. Roughly 10 stars satisfy our selection criteria. We estimated probabilities of encounter for these stars from the position of each star relative to cloud CO emission and the likely star-cloud distance along the line of sight. Typical encounter probabilities are approximately 1%. The number of potential encounters and the probability for each star-cloud pair to result in an encounter suggests that within 1 kpc of the Sun, there is a approximately 1% chance that a given cloud will be visited by a mass-losing AGB star over the next million years. The estimate is dominated by the possibility of encounters involving the stars IRC +60041 and S Cep. Over a MC lifetime, the probability for AGB encounter may be as high as approximately 70%. We discuss the implications of these results for theories of AL-26 enrichment of processed and unprocessed meteoritic inclusions. If the Al-26 in either type of inclusion arose from AGB-MC interaction, the low probability estimated here seems to require that AGB-MC encounters trigger multiple star formation and/or that the production rate of AGB stars was higher during the epoch of solar system formation than at present. Various lines of evidence suggest only the more massive (5-8 solar mass) AGB stars can produce significant AL-26 enrichment of star-forming clouds.
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Hahn, C. J. [University of Arizona; Warren, S. G. [University of Washington; Eastman, R.
1999-08-01
This database contains surface synoptic weather reports for the entire globe, gathered from various available data sets. The reports were processed, edited, and rewritten to provide a single dataset of individual observations of clouds, spanning the 57 years 1952-2008 for ship data and the 39 years 1971-2009 for land station data. In addition to the cloud portion of the synoptic report, each edited report also includes the associated pressure, present weather, wind, air temperature, and dew point (and sea surface temperature over oceans). This data set is called the "Extended Edited Cloud Report Archive" (EECRA). The EECRA is based solely on visual cloud observations from weather stations, reported in the WMO synoptic code (WMO, 1974). Reports must contain cloud-type information to be included in the archive. Past data sources include those from the Fleet Numerical Oceanographic Center (FNOC, 1971-1976) and the National Centers for Environmental Prediction (NCEP, 1977-1996). This update uses data from a new source, the 'Integrated Surface Database' (ISD, 1997-2009; Smith et al., 2011). Our past analyses of the EECRA identified a subset of 5388 weather stations that were determined to produce reliable day and night observations of cloud amount and type. The update contains observations only from this subset of stations. Details concerning processing, previous problems, contents, and comments are available in the archive's original documentation . The EECRA contains about 81 million cloud observations from ships and 380 million from land stations. The data files have been compressed using unix. Unix/linux users can "uncompress" or "gunzip" the files after downloading. If you're interested in the NDP-026C database, then you'll also want to explore its related data products, NDP-026D and NDP-026E.
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a Gross Error Elimination Method for Point Cloud Data Based on Kd-Tree
NASA Astrophysics Data System (ADS)
Kang, Q.; Huang, G.; Yang, S.
2018-04-01
Point cloud data has been one type of widely used data sources in the field of remote sensing. Key steps of point cloud data's pro-processing focus on gross error elimination and quality control. Owing to the volume feature of point could data, existed gross error elimination methods need spend massive memory both in space and time. This paper employed a new method which based on Kd-tree algorithm to construct, k-nearest neighbor algorithm to search, settled appropriate threshold to determine with result turns out a judgement that whether target point is or not an outlier. Experimental results show that, our proposed algorithm will help to delete gross error in point cloud data and facilitate to decrease memory consumption, improve efficiency.
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Isolating signatures of major cloud-cloud collisions using position-velocity diagrams
NASA Astrophysics Data System (ADS)
Haworth, T. J.; Tasker, E. J.; Fukui, Y.; Torii, K.; Dale, J. E.; Shima, K.; Takahira, K.; Habe, A.; Hasegawa, K.
2015-06-01
Collisions between giant molecular clouds are a potential mechanism for triggering the formation of massive stars, or even super star clusters. The trouble is identifying this process observationally and distinguishing it from other mechanisms. We produce synthetic position-velocity diagrams from models of cloud-cloud collisions, non-interacting clouds along the line of sight, clouds with internal radiative feedback and a more complex cloud evolving in a galactic disc, to try and identify unique signatures of collision. We find that a broad bridge feature connecting two intensity peaks, spatially correlated but separated in velocity, is a signature of a high-velocity cloud-cloud collision. We show that the broad bridge feature is resilient to the effects of radiative feedback, at least to around 2.5 Myr after the formation of the first massive (ionizing) star. However for a head-on 10 km s-1 collision, we find that this will only be observable from 20 to 30 per cent of viewing angles. Such broad-bridge features have been identified towards M20, a very young region of massive star formation that was concluded to be a site of cloud-cloud collision by Torii et al., and also towards star formation in the outer Milky Way by Izumi et al.
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2012-09-30
package developed by the Cloud Feedback Model Intercomparison Project (CFMIP), COSP (BODAS- SALCEDO et al. 2011). COSP will convert the model hydrometers ...and infrared data at high spatial and temporal resolution. J. Hydromet ., 5, 487-503. Kay, J. E. et al., 2012: Exposing global cloud biases in the
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Interaction of a supernova shock with two interstellar clouds
NASA Astrophysics Data System (ADS)
Hansen, J. F.; McKee, C. F.
2005-10-01
The interaction of supernova shocks and interstellar clouds is an important astrophysical phenomenon since it can result in stellar and planetary formation. Our experiments attempt to simulate this mass-loading as it occurs when a shock passes through interstellar clouds. We drive a strong shock using a 5 kJ laser into a foam-filled cylinder with embedded Al spheres (diameter D=120 μm) simulating interstellar clouds. The density ratio between Al and foam is ˜9. We have previously reported on the interaction between shock and a single cloud, and the ensuing Kelvin-Helmholtz and Widnall instabilities. We now report on experiments under way in which two clouds are placed side by side. Cloud separation (center to center) is either 1.2xD or 1.5xD. Initial results for 1.2xD show that cloud material merges and travels further downstream than in the single cloud case. For 1.5xD, material does not merge, but the clouds tilt toward each other. Work performed under the auspices of the Department of Energy by the Lawrence Livermore National Laboratory under contract number W-7405-ENG-48.
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EDITORIAL: Focus on Cloud Physics FOCUS ON CLOUD PHYSICS
NASA Astrophysics Data System (ADS)
Falkovich, Gregory; Malinowski, Szymon P.
2008-07-01
Cloud physics has for a long time been an important segment of atmospheric science. It is common knowledge that clouds are crucial for our understanding of weather and climate. Clouds are also interesting by themselves (not to mention that they are beautiful). Complexity is hidden behind the common picture of these beautiful and interesting objects. The typical school textbook definition that a cloud is 'a set of droplets or particles suspended in the atmosphere' is not adequate. Clouds are complicated phenomena in which dynamics, turbulence, microphysics, thermodynamics and radiative transfer interact on a wide range of scales, from sub-micron to kilometres. Some of these interactions are subtle and others are more straightforward. Large and small-scale motions lead to activation of cloud condensation nuclei, condensational growth and collisions; small changes in composition and concentration of atmospheric aerosol lead to significant differences in radiative properties of the clouds and influence rainfall formation. It is justified to look at a cloud as a composite, nonlinear system which involves many interactions and feedback. This system is actively linked into a web of atmospheric, oceanic and even cosmic interactions. Due to the complexity of the cloud system, present-day descriptions of clouds suffer from simplifications, inadequate parameterizations, and omissions. Sometimes the most fundamental physics hidden behind these simplifications and parameterizations is not known, and a wide scope of view can sometimes prevent a 'microscopic', deep insight into the detail. Only the expertise offered by scientists focused on particular elementary processes involved in this complicated pattern of interactions allows us to shape elements of the puzzle from which a general picture of clouds can be created. To be useful, every element of the puzzle must be shaped precisely. This often creates problems in communication between the sciences responsible for shaping elements of the puzzle, and those which combine them. Scales, assumptions and the conditions used in order to describe a particular single process of interest must be consistent with the conditions in clouds. The papers in this focus issue of New Journal of Physics collectively demonstrate (i) the variation in scientific approaches towards investigating cloud processes, (ii) the various stages of shaping elements of the puzzle, and (iii) some attempts to put the pieces together. These papers present just a small subset of loosely arranged elements in an initial stage of puzzle creation. Addressed by this issue is one of the important problems in our understanding of cloud processes—the interaction between cloud particles and turbulence. There is currently a gap between the cloud physics community and scientists working in wind tunnels, on turbulence theory and particle interactions. This collection is intended to narrow this gap by bringing together work by theoreticians, modelers, laboratory experimentalists and those who measure and observe actual processes in clouds. It forms a collage of contributions showing various approaches to cloud processes including: • theoretical works with possible applications to clouds (Bistagnino and Boffetta, Gustavsson et al), • an attempt to construct a phenomenological description of clouds and rain (Lovejoy and Schertzer), • simplified models designed to parameterize turbulence micro- and macro-effects (Celani et al, Derevyanko et al), • focused theoretical research aimed at particular cloud processes (Ayala et al, parts I and II, Wang et al), • laboratory and modeling studies of complex cloud processes (Malinowski et al). This collage is far from being complete but, hopefully, should give the reader a representative impression of the current state of knowledge in the field. We hope it will be useful to all scientists whose work is inspired by cloud processes. Focus on Cloud Physics Contents The equivalent size of cloud condensation nuclei Antonio Celani, Andrea Mazzino and Marco Tizzi Laboratory and modeling studies of cloud-clear air interfacial mixing: anisotropy of small-scale turbulence due to evaporative cooling Szymon P Malinowski, Miroslaw Andrejczuk, Wojciech W Grabowski, Piotr Korczyk, Tomasz A Kowalewski and Piotr K Smolarkiewicz Evolution of non-uniformly seeded warm clouds in idealized turbulent conditions Stanislav Derevyanko, Gregory Falkovich and Sergei Turitsyn Lagrangian statistics in two-dimensional free turbulent convection A Bistagnino and G Boffetta Turbulence, raindrops and the l1/2 number density law S Lovejoy and D Schertzer Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 2. Theory and parameterization Orlando Ayala, Bogdan Rosa and Lian-Ping Wang Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 1. Results from direct numerical simulation Orlando Ayala, Bogdan Rosa, Lian-Ping Wang and Wojciech W Grabowski Collisions of particles advected in random flows K Gustavsson, B Mehlig and M Wilkinson Turbulent collision efficiency of heavy particles relevant to cloud droplets Lian-Ping Wang, Orlando Ayala, Bogdan Rosa and Wojciech W Grabowski
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Object Detection using the Kinect
2012-03-01
Kinect camera and point cloud data from the Kinect’s structured light stereo system (figure 1). We obtain reasonable results using a single prototype...same manner we present in this report. For example, at Willow Garage , Steder uses a 3-D feature he developed to classify objects directly from point...detecting backpacks using the data available from the Kinect sensor. 4 3.1 Point Cloud Filtering Dense point clouds derived from stereo are notoriously
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Effects of Aerosol Pollution on Clouds over Megacities
NASA Astrophysics Data System (ADS)
Sechrist, B.; Jacobson, M. Z.
2013-12-01
The correlation between aerosol optical depth (AOD) and cloud properties - principally cloud fraction and cloud optical depth (COD) - is examined using satellite retrievals from the MODIS satellites over Los Angeles and Beijing. Ten Hoeve et al. (2011, Atmos. Chem. Phys, 11(7), 3021-3036) used satellite data to examine the impact of aerosols on warm clouds around Rondonia, Brazil, during the biomass burning season. They found that the COD-AOD relationship exhibits a 'boomerang' shape in which COD initially increases with increasing AOD but then decreases as AOD continues to increase beyond some critical level. This result is thought to reflect the balance between the microphysical and radiative components of a cloud's response to aerosols. The microphysical process dominates at low AOD, while the radiative process dominates at high AOD. This study is analogous to Ten Hoeve et al., but for aerosols derived primarily from fossil fuel combustion rather than biomass burning. Preliminary results will be presented.
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Tunnel Point Cloud Filtering Method Based on Elliptic Cylindrical Model
NASA Astrophysics Data System (ADS)
Zhua, Ningning; Jiaa, Yonghong; Luo, Lun
2016-06-01
The large number of bolts and screws that attached to the subway shield ring plates, along with the great amount of accessories of metal stents and electrical equipments mounted on the tunnel walls, make the laser point cloud data include lots of non-tunnel section points (hereinafter referred to as non-points), therefore affecting the accuracy for modeling and deformation monitoring. This paper proposed a filtering method for the point cloud based on the elliptic cylindrical model. The original laser point cloud data was firstly projected onto a horizontal plane, and a searching algorithm was given to extract the edging points of both sides, which were used further to fit the tunnel central axis. Along the axis the point cloud was segmented regionally, and then fitted as smooth elliptic cylindrical surface by means of iteration. This processing enabled the automatic filtering of those inner wall non-points. Experiments of two groups showed coincident results, that the elliptic cylindrical model based method could effectively filter out the non-points, and meet the accuracy requirements for subway deformation monitoring. The method provides a new mode for the periodic monitoring of tunnel sections all-around deformation in subways routine operation and maintenance.
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NASA Astrophysics Data System (ADS)
Grussenmeyer, P.; Alby, E.; Landes, T.; Koehl, M.; Guillemin, S.; Hullo, J. F.; Assali, P.; Smigiel, E.
2012-07-01
Different approaches and tools are required in Cultural Heritage Documentation to deal with the complexity of monuments and sites. The documentation process has strongly changed in the last few years, always driven by technology. Accurate documentation is closely relied to advances of technology (imaging sensors, high speed scanning, automation in recording and processing data) for the purposes of conservation works, management, appraisal, assessment of the structural condition, archiving, publication and research (Patias et al., 2008). We want to focus in this paper on the recording aspects of cultural heritage documentation, especially the generation of geometric and photorealistic 3D models for accurate reconstruction and visualization purposes. The selected approaches are based on the combination of photogrammetric dense matching and Terrestrial Laser Scanning (TLS) techniques. Both techniques have pros and cons and recent advances have changed the way of the recording approach. The choice of the best workflow relies on the site configuration, the performances of the sensors, and criteria as geometry, accuracy, resolution, georeferencing, texture, and of course processing time. TLS techniques (time of flight or phase shift systems) are widely used for recording large and complex objects and sites. Point cloud generation from images by dense stereo or multi-view matching can be used as an alternative or as a complementary method to TLS. Compared to TLS, the photogrammetric solution is a low cost one, as the acquisition system is limited to a high-performance digital camera and a few accessories only. Indeed, the stereo or multi-view matching process offers a cheap, flexible and accurate solution to get 3D point clouds. Moreover, the captured images might also be used for models texturing. Several software packages are available, whether web-based, open source or commercial. The main advantage of this photogrammetric or computer vision based technology is to get at the same time a point cloud (the resolution depends on the size of the pixel on the object), and therefore an accurate meshed object with its texture. After matching and processing steps, we can use the resulting data in much the same way as a TLS point cloud, but in addition with radiometric information for textures. The discussion in this paper reviews recording and important processing steps as geo-referencing and data merging, the essential assessment of the results, and examples of deliverables from projects of the Photogrammetry and Geomatics Group (INSA Strasbourg, France).
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Simulations of Polar Stratospheric Clouds and Denitrification Using Laboratory Freezing Rates
NASA Technical Reports Server (NTRS)
Drdla, Katja; Tabazadeh, Azadeh; Gore, Warren J. (Technical Monitor)
2001-01-01
During the 1999-2000 Arctic winter, the SAGE (Stratospheric Aerosol and Gas Experiment) III Ozone Loss and Validation Experiment (SOLVE) provided evidence of widespread solid-phase polar stratospheric clouds (PSCs) accompanied by severe nitrification. Previous simulations have shown that a freezing process occurring at temperatures above the ice frost point is necessary to explain these observations. In this work, the nitric acid freezing rates measured by Salcedo et al. and discussed by Tabazadeh et al. have been examined. These freezing rates have been tested in winter-long microphysical simulations of the 1999-2000 Arctic vortex evolution in order to determine whether they can explain the observations. A range of cases have been explored, including whether the PSC particles are composed of nitric acid dihydrate or trihydrate, whether the freezing process is a bulk process or occurs only on the particle surfaces, and uncertainties in the derived freezing rates. Finally, the possibility that meteoritic debris enhances the freezing rate has also been examined. The results of these simulations have been compared with key PSC and denitrification measurements made by the SOLVE campaign. The cases that best reproduce the measurements will he highlighted, with a discussion of the implications for our understanding of PSCs.
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NASA Astrophysics Data System (ADS)
Hu, J.; Rosenfeld, D.; Zhang, P.; Snyder, J.; Orville, R. E.; Ryzhkov, A.; Zrnic, D.; Williams, E. R.; Zhang, R.
2017-12-01
Here we apply the cell tracking methodology, shown in our companion poster, to quantifying factors affecting the vigor and the time-height evolution of hydrometeors and electrification properties of convective cells. Benefitting from the Dual-polarimetric NEXRAD radar network, we composite more than 5000 well-tracked cells among three radars (at Houston, Lubbock and Oklahoma City), stratified by CCN, CAPE and land/sea locations. The analyzed cell properties include Z, ZDR, Kdp, and ρhv, Dm (raindrop diameter) and Nw (raindrop concentration) by the algorithm of Bringi et al. (2003). Lightning Mapping Array (LMA) data is also included in the analysis, which provides a 3D structure of lightning occurrence and RF power. The contrasting CCN conditions over marine, land, pristine and polluted areas are identified based on the satellite retrieval technique described in Rosenfeld et al. (2016). The results show that more CCN are associated with: Increased echo top height, manifesting the invigoration effect. Enhanced reflectivities, especially above the freezing level at around 4.5 km. Raindrop sizes at the initial stage increase at the expense of their concentrations, due to the smaller cloud droplets and suppressed coalescence. Larger propensity for hail. Lightning sources increase with greater CCN concentration and is likely due to the delayed warm rain process and enhanced mixed phase process under more CCN condition, when activated CCN into cloud droplets is too high (> 1000 cm-3) the glaciation is delayed too much and leave little ice at lower levels and thus decrease lightning activity. Land pristine clouds have fewer lightning sources than polluted clouds. Marine pristine clouds seldom have lightning Increased CAPE had a similar effect to the effect of added CCN. The cloud tracking and properties are obtained by a new methodology of Multi-Cell Identification and Tracking (MCIT) algorithm (Hu et al, 2017), with details about the algorithm to be found in the author's accompanying poster session. References [1] Bringi, V. et al., J. Atmos. Sci., 60, 354-365. (2003) [2] Rosenfeld, D. et al., Proc. Natl. Acad. Sci., 113, 5828-5834. (2016) [3] Hu, J. et al., in preparation.
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NASA Astrophysics Data System (ADS)
Maahn, M.; Acquistapace, C.; de Boer, G.; Cox, C.; Feingold, G.; Marke, T.; Williams, C. R.
2017-12-01
When acting as cloud condensation nuclei (CCN) or ice nucleating particles (INPs), aerosols have a strong potential to influence cloud properties. In particular, they can impact the number, size, and phase of cloud particles and potentially cloud lifetime through aerosol indirect and semi-direct effects. In polar regions, these effects are of great importance for the radiation budget due to the shortwave albedo and longwave emissivity of mixed-phase clouds. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program operates two super sites equipped with state of the art ground-based remote sensing instruments in northern Alaska. The sites are both coastal and are highly correlated with respect to large scale synoptic patterns. While the site at Utqiaġvik (formerly known as Barrow) generally represents a relatively pristine Arctic environment lacking significant anthropogenic sources, the site at Oliktok Point, approximately 250 km to the east, is surrounded by the Prudhoe Bay Oil Field, which is the largest oil field in North America. Based on aircraft measurement, the authors recently showed that differences in the properties of liquid clouds properties between the sites can be attributed to local emissions associated with the industrial activities in the Prudhoe Bay region (Maahn et al. 2017, ACPD). However, aircraft measurements do not provide a representative sample of cloud properties due to temporal limitations in the amount of data. In order to investigate how frequently and to what extent liquid cloud properties and processes are modified, we use ground based remote sensing observations such as e.g., cloud radar, Doppler lidar, and microwave radiometer obtained continuously at the two sites. In this way, we are able to quantify inter-site differences with respect to cloud drizzle production, liquid water path, frequency of cloud occurrence, and cloud radiative properties. Turbulence and the coupling of clouds to the boundary layer is investigated in order to infer the potential role of locally emitted aerosols in modulating the observed differences.
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A Modular Approach to Video Designation of Manipulation Targets for Manipulators
2014-05-12
side view of a ray going through a point cloud of a water bottle sitting on the ground. The bottom left image shows the same point cloud after it has...System (ROS), Point Cloud Library (PCL), and OpenRAVE were used to a great extent to help promote reusability of the code developed during this
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Automatic Matching of Large Scale Images and Terrestrial LIDAR Based on App Synergy of Mobile Phone
NASA Astrophysics Data System (ADS)
Xia, G.; Hu, C.
2018-04-01
The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.
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Cloud microphysics modification with an online coupled COSMO-MUSCAT regional model
NASA Astrophysics Data System (ADS)
Sudhakar, D.; Quaas, J.; Wolke, R.; Stoll, J.; Muehlbauer, A. D.; Tegen, I.
2015-12-01
Abstract: The quantification of clouds, aerosols, and aerosol-cloud interactions in models, continues to be a challenge (IPCC, 2013). In this scenario two-moment bulk microphysical scheme is used to understand the aerosol-cloud interactions in the regional model COSMO (Consortium for Small Scale Modeling). The two-moment scheme in COSMO has been especially designed to represent aerosol effects on the microphysics of mixed-phase clouds (Seifert et al., 2006). To improve the model predictability, the radiation scheme has been coupled with two-moment microphysical scheme. Further, the cloud microphysics parameterization has been modified via coupling COSMO with MUSCAT (MultiScale Chemistry Aerosol Transport model, Wolke et al., 2004). In this study, we will be discussing the initial result from the online-coupled COSMO-MUSCAT model system with modified two-moment parameterization scheme along with COSP (CFMIP Observational Simulator Package) satellite simulator. This online coupled model system aims to improve the sub-grid scale process in the regional weather prediction scenario. The constant aerosol concentration used in the Seifert and Beheng, (2006) parameterizations in COSMO model has been replaced by aerosol concentration derived from MUSCAT model. The cloud microphysical process from the modified two-moment scheme is compared with stand-alone COSMO model. To validate the robustness of the model simulation, the coupled model system is integrated with COSP satellite simulator (Muhlbauer et al., 2012). Further, the simulations are compared with MODIS (Moderate Resolution Imaging Spectroradiometer) and ISCCP (International Satellite Cloud Climatology Project) satellite products.
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NASA Astrophysics Data System (ADS)
Vázquez Tarrío, Daniel; Borgniet, Laurent; Recking, Alain; Liebault, Frédéric; Vivier, Marie
2016-04-01
The present research is focused on the Vénéon river at Plan du Lac (Massif des Ecrins, France), an alpine braided gravel bed stream with a glacio-nival hydrological regime. It drains a catchment area of 316 km2. The present research is focused in a 2.5 km braided reach placed immediately upstream of a small hydropower dam. An airbone LIDAR survey was accomplished in October, 2014 by EDF (the company managing the small hydropower dam), and data coming from this LIDAR survey were available for the present research. Point density of the LIDAR-derived 3D-point cloud was between 20-50 points/m2, with a vertical precision of 2-3 cm over flat surfaces. Moreover, between April and Juin, 2015, we carried out a photogrammetrical campaign based in aerial images taken with an UAV-drone. The UAV-derived point-cloud has a point density of 200-300 points/m2, and a vertical precision over flat control surfaces comparable to that of the LIDAR point cloud (2-3 cm). Simultaneously to the UAV campaign, we took several Wolman samples with the aim of characterizing the grain size distribution of bed sediment. Wolman samples were taken following a geomorphological criterion (unit bars, head/tail of compound bars). Furthermore, some of the Wolman samples were repeated with the aim of defining the uncertainty of our sampling protocol. LIDAR and UAV-derived point clouds were treated in order to check whether both point-clouds were correctly co-aligned. After that, we estimated bed roughness using the detrended standard deviation of heights, in a 40-cm window. For all this data treatment we used CloudCompare. Then, we measured the distribution of roughness in the same geomorphological units where we took the Wolman samples, and we compared with the grain size distributions measured in the field: differences between UAV-point cloud roughness distributions and measured-grain size distribution (~1-2 cm) are in the same order of magnitude of the differences found between the repeated Wolman samples (~0.5-1.5 cm). Differences with LIDAR-derived roughness distributions are only slightly higher, which could be due to the lower point density of the LIDAR point clouds.
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Gyroscopic effects in interference of matter waves
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tolstikhin, Oleg I.; Morishita, Toru; Watanabe, Shinichi
2005-11-15
A new gyroscopic interference effect stemming from the Galilean translational factor in the matter wave function is pointed out. In contrast to the well-known Sagnac effect that stems from the geometric phase and leads to a shift of interference fringes, this effect causes slanting of the fringes. We illustrate it by calculations for two split cigar-shaped Bose-Einstein condensates under the conditions of a recent experiment, see Y. Shin et al., Phys. Rev. Lett. 92, 050405 (2004). Importantly, the measurement of slanting obviates the need of a third reference cloud.
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NASA Astrophysics Data System (ADS)
Wielicki, B. A.; Cooke, R. M.; Golub, A. A.; Mlynczak, M. G.; Young, D. F.; Baize, R. R.
2016-12-01
Several previous studies have been published on the economic value of narrowing the uncertainty in climate sensitivity (Cooke et al. 2015, Cooke et al. 2016, Hope, 2015). All three of these studies estimated roughly 10 Trillion U.S. dollars for the Net Present Value and Real Option Value at a discount rate of 3%. This discount rate is the nominal discount rate used in the U.S. Social Cost of Carbon Memo (2010). The Cooke et al studies approached this problem by examining advances in accuracy of global temperature measurements, while the Hope 2015 study did not address the type of observations required. While temperature change is related to climate sensitivity, large uncertainties of a factor of 3 in current anthropogenic radiative forcing (IPCC, 2013) would need to be solved for advanced decadal temperature change observations to assist the challenge of narrowing climate sensitivity. The present study takes a new approach by extending the Cooke et al. 2015,2016 papers to replace observations of temperature change to observations of decadal change in the effects of changing clouds on the Earths radiative energy balance, a measurement known as Cloud Radiative Forcing, or Cloud Radiative Effect. Decadal change in this observation is direclty related to the largest uncertainty in climate sensitivity which is cloud feedback from changing amount of low clouds, primarily low clouds over the world's oceans. As a result, decadal changes in shortwave cloud radiative forcing are more directly related to cloud feedback uncertainty which is the dominant uncertainty in climate sensitivity. This paper will show results for the new approach, and allow an examination of the sensitivity of economic value results to different observations used as a constraint on uncertainty in climate sensitivity. The analysis suggests roughly a doubling of economic value to 20 Trillion Net Present Value or Real Option Value at 3% discount rate. The higher economic value results from two changes: a larger increase in accuracy for SW cloud radiative forcing vs temperature, and from a lower confounding noise from natural variability in the cloud radiative forcing variable compared to temperature. In particular, global average temperature is much more sensitive to the climate noise of ENSO cycles.
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Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction
Berveglieri, Adilson; Liang, Xinlian; Honkavaara, Eija
2017-01-01
This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras. PMID:29207468
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Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction.
Berveglieri, Adilson; Tommaselli, Antonio M G; Liang, Xinlian; Honkavaara, Eija
2017-12-02
This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Chitra Sivaraman, PNNL
Cloud droplet number concentration is an important factor in understanding aerosol-cloud interactions. As aerosol concentration increases, it is expected that droplet number concentration (Nd) will increase and droplet size will decrease, for a given liquid water path. This will greatly affect cloud albedo as smaller droplets reflect more shortwave radiation; however, the magnitude and variability of these processes under different environmental conditions is still uncertain.McComiskey et al. (2009) have implemented a method, based onBoers and Mitchell (1994), for calculating Nd from ground-based remote sensing measurements of optical depth and liquid water path. They show that the magnitude of the aerosol-cloudmore » interactions (ACI) varies with a range of factors, including the relative value of the cloud liquid water path (LWP), the aerosol size distribution, and the cloud updraft velocity. Estimates of Nd under a range of cloud types and conditions and at a variety of sites are needed to further quantify the impacts of aerosol cloud interactions. In order to provide data sets for studying aerosol-cloud interactions, the McComiskey et al. (2009) method was implemented as the Droplet Number Concentration (NDROP) value-added product (VAP).« less
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Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds
NASA Astrophysics Data System (ADS)
Zeng, L.; Kang, Z.
2017-09-01
This paper realizes automatically the navigating elements defined by indoorGML data standard - door, stairway and wall. The data used is indoor 3D point cloud collected by Kinect v2 launched in 2011 through the means of ORB-SLAM. By contrast, it is cheaper and more convenient than lidar, but the point clouds also have the problem of noise, registration error and large data volume. Hence, we adopt a shape descriptor - histogram of distances between two randomly chosen points, proposed by Osada and merges with other descriptor - in conjunction with random forest classifier to recognize the navigation elements (door, stairway and wall) from Kinect point clouds. This research acquires navigation elements and their 3-d location information from each single data frame through segmentation of point clouds, boundary extraction, feature calculation and classification. Finally, this paper utilizes the acquired navigation elements and their information to generate the state data of the indoor navigation module automatically. The experimental results demonstrate a high recognition accuracy of the proposed method.
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NASA Astrophysics Data System (ADS)
Ghanti, R.; Ghosh, S.
2010-03-01
The Indian subcontinent is undergoing a phase of rapid urbanisation. Inevitable fallout of this process is a concomitant increase in air pollution much of which can be attributed to the infamous great Indian haze phenomena. One observes that the aerosol size distributions vary considerably along the Bay of Bengal (BOB), Arabian Sea (AS) and the Indian Ocean (IO), although, the dynamical attributes are very similar, particularly over the BOB and the AS during this season. Unlike major European studies (e.g. Aerosol Characterization Experiment-2, Ghosh et al., 2005), there are no cloud microphysical modelling studies to complement these observational results for the Indian sub-continent. Ours is the first modelling study over this important region where a time-tested model (O'Dowd et al., 1999a; Ghosh et al., 2007; Rap et al., 2009) is used to obtain cloud microphysical and optical properties from observed aerosol size distributions. Un-activated aerosol particles and very small cloud droplets have to be treated specially to account for non-ideal effects-our model does this effectively yielding realistic estimate of cloud droplet number concentrations (Nc). Empirical relationships linking aerosol concentration to (Nc) yield a disproportionately higher Nc suggesting that such empirical formulations should be used with caution. Our modelling study reveals that the cloud's microphysical and optical properties are very similar along the AS and the BOB despite them having disparate dry aerosol spectral distributions. This is non-intuitive, as one would expect changes in microphysical development with widely different aerosol distributions. There is some increase in cloud droplet numbers with increased haze concentrations but much less than a simple proportion would indicate.
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Towards 3D Matching of Point Clouds Derived from Oblique and Nadir Airborne Imagery
NASA Astrophysics Data System (ADS)
Zhang, Ming
Because of the low-expense high-efficient image collection process and the rich 3D and texture information presented in the images, a combined use of 2D airborne nadir and oblique images to reconstruct 3D geometric scene has a promising market for future commercial usage like urban planning or first responders. The methodology introduced in this thesis provides a feasible way towards fully automated 3D city modeling from oblique and nadir airborne imagery. In this thesis, the difficulty of matching 2D images with large disparity is avoided by grouping the images first and applying the 3D registration afterward. The procedure starts with the extraction of point clouds using a modified version of the RIT 3D Extraction Workflow. Then the point clouds are refined by noise removal and surface smoothing processes. Since the point clouds extracted from different image groups use independent coordinate systems, there are translation, rotation and scale differences existing. To figure out these differences, 3D keypoints and their features are extracted. For each pair of point clouds, an initial alignment and a more accurate registration are applied in succession. The final transform matrix presents the parameters describing the translation, rotation and scale requirements. The methodology presented in the thesis has been shown to behave well for test data. The robustness of this method is discussed by adding artificial noise to the test data. For Pictometry oblique aerial imagery, the initial alignment provides a rough alignment result, which contains a larger offset compared to that of test data because of the low quality of the point clouds themselves, but it can be further refined through the final optimization. The accuracy of the final registration result is evaluated by comparing it to the result obtained from manual selection of matched points. Using the method introduced, point clouds extracted from different image groups could be combined with each other to build a more complete point cloud, or be used as a complement to existing point clouds extracted from other sources. This research will both improve the state of the art of 3D city modeling and inspire new ideas in related fields.
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SeReNA Project: studying aerosol interactions with cloud microphysics in the Amazon Basin
NASA Astrophysics Data System (ADS)
Correia, A. L.; Catandi, P. B.; Frigeri, F. F.; Ferreira, W. C.; Martins, J.; Artaxo, P.
2012-12-01
Cloud microphysics and its interaction with aerosols is a key atmospheric process for weather and climate. Interactions between clouds and aerosols can impact Earth's radiative balance, its hydrological and energetic cycles, and are responsible for a large fraction of the uncertainty in climatic models. On a planetary scale, the Amazon Basin is one of the most significant land sources of moisture and latent heat energy. Moreover, every year this region undergoes mearked seasonal shifts in its atmospheric state, transitioning from clean to heavily polluted conditions due to the occurrence of seasonal biomass burning fires, that emit large amounts of smoke to the atmosphere. These conditions make the Amazon Basin a special place to study aerosol-cloud interactions. The SeReNA Project ("Remote sensing of clouds and their interaction with aerosols", from the acronym in Portuguese, @SerenaProject on Twitter) is an ongoing effort to experimentally investigate the impact of aerosols upon cloud microphysics in Amazonia. Vertical profiles of droplet effective radius of water and ice particles, in single convective clouds, can be derived from measurements of the emerging radiation on cloud sides. Aerosol optical depth, cloud top properties, and meteorological parameters retrieved from satellites will be correlated with microphysical properties derived for single clouds. Maps of cloud brightness temperature will allow building temperature vs. effective radius profiles for hydrometeors in single clouds. Figure 1 shows an example extracted from Martins et al. (2011), illustrating a proof-of-concept for the kind of result expected within the framework for the SeReNA Project. The results to be obtained will help foster the quantitative knowledge about interactions between aerosols and clouds in a microphysical level. These interactions are a fundamental process in the context of global climatic changes, they are key to understanding basic processes within clouds and how aerosols can influence them. Reference: Martins et al. (2011) ACP, v.11, p.9485-9501. Available at: http://bit.ly/martinspaper Figure 1. Brightness temperature (left panel) and thermodynamic phase (right) of hydrometeors in the convective cloud shown in the middle panel. Extracted from Martins et al. (2011).
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Fast Semantic Segmentation of 3d Point Clouds with Strongly Varying Density
NASA Astrophysics Data System (ADS)
Hackel, Timo; Wegner, Jan D.; Schindler, Konrad
2016-06-01
We describe an effective and efficient method for point-wise semantic classification of 3D point clouds. The method can handle unstructured and inhomogeneous point clouds such as those derived from static terrestrial LiDAR or photogammetric reconstruction; and it is computationally efficient, making it possible to process point clouds with many millions of points in a matter of minutes. The key issue, both to cope with strong variations in point density and to bring down computation time, turns out to be careful handling of neighborhood relations. By choosing appropriate definitions of a point's (multi-scale) neighborhood, we obtain a feature set that is both expressive and fast to compute. We evaluate our classification method both on benchmark data from a mobile mapping platform and on a variety of large, terrestrial laser scans with greatly varying point density. The proposed feature set outperforms the state of the art with respect to per-point classification accuracy, while at the same time being much faster to compute.
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Catching the Drift: Simulating Dark Spots and Bright Companions on the Ice Giants
NASA Astrophysics Data System (ADS)
LeBeau, R. P., Jr.; Koutas, N.; Palotai, C. J.; Bhure, S.; Hadland, N.; Sankar, R.
2017-12-01
Starting with the original Great Dark Spot (GDS-89) observed by Voyager 2, roughly a half-dozen large geophysical vortices have been observed on the Ice Giants, the most recent in 2015 on Neptune (Wong et al., 2016). While the presumption is that these Dark Spots are similar in structure to the large vortices on Jupiter, in some cases the Dark Spots exhibit dynamical motions such as the shape oscillations and latitudinal drift of GDS-89 (Smith et al., 1989) or the possible vortex drift underlying the "Berg" cloud feature on Uranus (de Pater et al., 2011). Others, like NGDS-1998, have remained largely stable across years of observation (Sromovsky et al., 2002). In addition, several of the vortices are linked with Bright Companion clouds which are presumed to be orographic features formed as the atmosphere rises over the vortex. The numerical simulation of these features has evolved with each new observation. Prior simulations have captured the forms if not all the specifics of observed Dark Spot dynamics (LeBeau and Dowling, 1998; LeBeau and Deng, 2006); likewise, numerical models have demonstrated the potential for orographic companion clouds (Stratman et al., 2001). However, as more knowledge of the Ice Giant atmospheres has been obtained, it has proven challenging to generate consistent dynamical models that capture the details of the Dark Spot variations and are physically consistent with known observations. In particular, current simulations indicate that the addition of a companion cloud can alter the vortex dynamics, both in terms of drift and oscillations. Given the impact of these clouds, a new parametric simulation study uses an updated microphysics model, implemented in the Explicit Planetary Isentropic Coordinate (EPIC) general circulation model (Dowling et al., 1998, 2006), to account for the condensation of methane and hydrogen sulfide (Palotai et al., 2016). Simulations of dark spots with varying sizes, strengths, and locations are conducted with different microphysical parameters such as the deep abundance and ambient supersaturation. Simulations are evaluated in terms of vortex stability and drift rate along with companion cloud formation with the goal of improving our understanding of the underlying physics driving the varying behaviors of the observed Dark Spots.
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A Voxel-Based Approach for Imaging Voids in Three-Dimensional Point Clouds
NASA Astrophysics Data System (ADS)
Salvaggio, Katie N.
Geographically accurate scene models have enormous potential beyond that of just simple visualizations in regard to automated scene generation. In recent years, thanks to ever increasing computational efficiencies, there has been significant growth in both the computer vision and photogrammetry communities pertaining to automatic scene reconstruction from multiple-view imagery. The result of these algorithms is a three-dimensional (3D) point cloud which can be used to derive a final model using surface reconstruction techniques. However, the fidelity of these point clouds has not been well studied, and voids often exist within the point cloud. Voids exist in texturally difficult areas, as well as areas where multiple views were not obtained during collection, constant occlusion existed due to collection angles or overlapping scene geometry, or in regions that failed to triangulate accurately. It may be possible to fill in small voids in the scene using surface reconstruction or hole-filling techniques, but this is not the case with larger more complex voids, and attempting to reconstruct them using only the knowledge of the incomplete point cloud is neither accurate nor aesthetically pleasing. A method is presented for identifying voids in point clouds by using a voxel-based approach to partition the 3D space. By using collection geometry and information derived from the point cloud, it is possible to detect unsampled voxels such that voids can be identified. This analysis takes into account the location of the camera and the 3D points themselves to capitalize on the idea of free space, such that voxels that lie on the ray between the camera and point are devoid of obstruction, as a clear line of sight is a necessary requirement for reconstruction. Using this approach, voxels are classified into three categories: occupied (contains points from the point cloud), free (rays from the camera to the point passed through the voxel), and unsampled (does not contain points and no rays passed through the area). Voids in the voxel space are manifested as unsampled voxels. A similar line-of-sight analysis can then be used to pinpoint locations at aircraft altitude at which the voids in the point clouds could theoretically be imaged. This work is based on the assumption that inclusion of more images of the void areas in the 3D reconstruction process will reduce the number of voids in the point cloud that were a result of lack of coverage. Voids resulting from texturally difficult areas will not benefit from more imagery in the reconstruction process, and thus are identified and removed prior to the determination of future potential imaging locations.
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Classification by Using Multispectral Point Cloud Data
NASA Astrophysics Data System (ADS)
Liao, C. T.; Huang, H. H.
2012-07-01
Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.
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Validation of the large-scale Lagrangian cirrus model CLaMS-Ice by in-situ measurements
NASA Astrophysics Data System (ADS)
Costa, Anja; Rolf, Christian; Grooß, Jens-Uwe; Afchine, Armin; Spelten, Nicole; Dreiling, Volker; Zöger, Martin; Krämer, Martina
2015-04-01
Cirrus clouds are an element of uncertainty in the climate system and have received increasing attention since the last IPCC reports. The interaction of varying freezing meachanisms, sedimentation rates, temperature and updraft velocity fluctuations and other factors that lead to the formation of those clouds is still not fully understood. During the ML-Cirrus campaign 2014 (Germany), the new cirrus cloud model CLaMS-Ice (see Rolf et al., EGU 2015) has been used for flight planning to direct the research aircraft HALO into interesting cirrus cloud regions. Now, after the campaign, we use our in-situ aircraft measurements to validate and improve this model - with the long-term goal to enable it to simulate cirrus cloud cover globally, with reasonable computing times and sufficient accuracy. CLaMS-Ice consists of a two-moment bulk model established by Spichtinger and Gierens (2009a, 2009b), which simulates cirrus clouds along trajectories that the Lagrangian model CLaMS (McKenna et al., 2002 and Konopka et al. 2007) derived from ECMWF data. The model output covers temperature, pressure, relative humidity, ice water content (IWC), and ice crystal numbers (Nice). These parameters were measured on board of HALO by the following instruments: temperature and pressure by BAHAMAS, total and gas phase water by the hygrometers FISH and SHARC (see Meyer et al 2014, submitted to ACP), and Nice as well as ice crystal size distributions by the cloud spectrometer NIXE-CAPS (see also Krämer et al., EGU 2015). Comparisons of the model results with the measurements yield that cirrus clouds can be successfully simulated by CLaMS-Ice. However, there are sections in which the model's relative humidity and Nice deviate considerably from the measured values. This can be traced back to e.g. the initialization of total water from ECMWF data. The simulations are therefore reinitiated with the total water content measured by FISH. Other possible sources of uncertainties are investigated, as imposed temperature fluctuations, numbers and efficencies of heterogeneous ice nuclei or assumptions concerning the sedimentation rates. This contribution sums up the results of these investigations and outlines future work on CLaMS-Ice, that will lead to a tool helping to understand the cirrus clouds under the different environmental conditions during ML-Cirrus.
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Line segment extraction for large scale unorganized point clouds
NASA Astrophysics Data System (ADS)
Lin, Yangbin; Wang, Cheng; Cheng, Jun; Chen, Bili; Jia, Fukai; Chen, Zhonggui; Li, Jonathan
2015-04-01
Line segment detection in images is already a well-investigated topic, although it has received considerably less attention in 3D point clouds. Benefiting from current LiDAR devices, large-scale point clouds are becoming increasingly common. Most human-made objects have flat surfaces. Line segments that occur where pairs of planes intersect give important information regarding the geometric content of point clouds, which is especially useful for automatic building reconstruction and segmentation. This paper proposes a novel method that is capable of accurately extracting plane intersection line segments from large-scale raw scan points. The 3D line-support region, namely, a point set near a straight linear structure, is extracted simultaneously. The 3D line-support region is fitted by our Line-Segment-Half-Planes (LSHP) structure, which provides a geometric constraint for a line segment, making the line segment more reliable and accurate. We demonstrate our method on the point clouds of large-scale, complex, real-world scenes acquired by LiDAR devices. We also demonstrate the application of 3D line-support regions and their LSHP structures on urban scene abstraction.
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Characterizing Sorghum Panicles using 3D Point Clouds
NASA Astrophysics Data System (ADS)
Lonesome, M.; Popescu, S. C.; Horne, D. W.; Pugh, N. A.; Rooney, W.
2017-12-01
To address demands of population growth and impacts of global climate change, plant breeders must increase crop yield through genetic improvement. However, plant phenotyping, the characterization of a plant's physical attributes, remains a primary bottleneck in modern crop improvement programs. 3D point clouds generated from terrestrial laser scanning (TLS) and unmanned aerial systems (UAS) based structure from motion (SfM) are a promising data source to increase the efficiency of screening plant material in breeding programs. This study develops and evaluates methods for characterizing sorghum (Sorghum bicolor) panicles (heads) in field plots from both TLS and UAS-based SfM point clouds. The TLS point cloud over experimental sorghum field at Texas A&M farm in Burleston County TX were collected using a FARO Focus X330 3D laser scanner. SfM point cloud was generated from UAS imagery captured using a Phantom 3 Professional UAS at 10m altitude and 85% image overlap. The panicle detection method applies point cloud reflectance, height and point density attributes characteristic of sorghum panicles to detect them and estimate their dimensions (panicle length and width) through image classification and clustering procedures. We compare the derived panicle counts and panicle sizes with field-based and manually digitized measurements in selected plots and study the strengths and limitations of each data source for sorghum panicle characterization.
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How Models Simulate the Radiative Effect in the Transition Zone of the Aerosol-Cloud Continuum
NASA Astrophysics Data System (ADS)
Calbo Angrill, J.; González, J. A.; Long, C. N.; McComiskey, A. C.
2017-12-01
Several studies have pointed towards dealing with clouds and aerosols as two manifestations of what is essentially the same physical phenomenon: a suspension of tiny particles in the air. Although the two extreme cases (i.e., pure aerosol and well-defined cloud) are easily distinguished, and obviously produce different radiative effects, there are many situations in the transition (or "twilight") zone. In a recent paper [Calbó et al., Atmos. Res. 2017, j.atmosres.2017.06.010], the authors of the current communication estimated that about 10% of time there might be a suspension of particles in the air that is difficult to distinguish as either cloud or aerosol. Radiative transfer models, however, simulate the effect of clouds and aerosols with different modules, routines, or parameterizations. In this study, we apply a sensitivity analysis approach to assess the ability of two radiative transfer models (SBDART and RRTM) in simulating the radiative effect of a suspension of particles with characteristics in the boundary between cloud and aerosol. We simulate this kind of suspension either in "cloud mode" or in "aerosol mode" and setting different values of optical depth, droplet size, water path, aerosol type, cloud height, etc. Irradiances both for solar and infrared bands are studied, both at ground level and at the top of the atmosphere, and all analyses are repeated for different solar zenith angles. We obtain that (a) water clouds and ice clouds have similar radiative effects if they have the same optical depth; (b) the spread of effects regarding different aerosol type/aerosol characteristics is remarkable; (c) radiative effects of an aerosol layer and of a cloud layer are different, even if they have similar optical depth; (d) for a given effect on the diffuse component, the effect on the direct component is usually greater (more extinction of direct beam) by aerosols than by clouds; (e) radiative transfer models are somewhat limited when simulating the effects of a suspension of particles in the transition zone, as the approach to this zone as an aerosol or as a cloud produces different results.
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Measurements of carbon monoxide above Venus' cloud top from IRTF/CSHELL observations
NASA Astrophysics Data System (ADS)
Marcq, Emmanuel; Encrenaz, Thérèse; Lellouch, Emmanuel; Bertaux, Jean-Loup; Widemann, Thomas; Birlan, Mirel
2014-05-01
Venus' cloud top region exhibits a higher level of variability both in space and time than previously thought. The interplay between photochemistry, dynamics and cloud microphysics requires more observational constraints in order to be fully grasped. Recent observations of sulfur dioxide (SO2) variability have evidenced both short-term, long-term and latitudinal variability whose origin remains mysterious (volcanogenic emissions? dynamic variability?). A better knowledge of the variability of other minor species would be highly welcome in this context. Carbon monoxide (CO), whose pattern of sinks and sources is opposite to SO2, is a prime candidate. CO was detected above the clouds of Venus for the first time by Connes et al. near 2.3μm, with a mixing ratio of about 45 ppmv. More recently, Irwin et al. used VIRTIS-M near 4.7μm on the nightside, and evidenced no spatial variations, with 40 ± 10 ppmv in the 65 - 70 km range. Iwagami et al. found 58 ± 17 ppmv near 2.3μm on the dayside, whereas Krasnopolski in the same spectral range found evidence of a CO decrease with increasing local time (52 ± 4 ppmv at 08:00 compared to 40 ± 4 ppmv at 16:30). Following a methodology inspired from previous SO2 observations, we have observed Venus using the high-resolution (R = 41500) spectrometer CSHELL between 4.53 to 4.54μmat the IRTF (Mauna Kea, Hawaii) from 2012-08-25 until 2012-08-28 and 2013-10-31 to 2013-11-03, around the greatest western and eastern elongations of Venus. Our main results (Marcq et al., submitted) are: (1) Strong limb darkening is observed, that can be translated into an altitude of emission for the CO2 lines (whose mixing ratio is known and constant with height in the lower mesosphere). We are able to probe in an altitude range from 65 km (center of the disk) up to 78 km (limb). (2) It then appears that CO is increasing with increasing height, with a scale height of about 4 ± 1 km on the night side and 9 ± 0.5 km on the day side. This is consistent with a source of photochemical source of CO located at a higher altitude than the thermochemical sink of CO. (3) Our measurements indicate an increase with increasing latitude on the northern hemisphere day side, as well as with a steady decrease from local noon to local midnight. Both are consistent with previously identified trends, although our mean mixing ratio appears on the lower end of previous estimates. (4) Some high-altitude (~ 140 km) fluorescence of CO is also observed, especially near the subsolar point. References [1] Connes, P., et al. (1968) [2] Irwin, P.G.J. et al. (2008) [3] Iwagami, N. et al. (2010) [4] Krasnoploski, V.A. (2010) [5] Encrenaz, T. et al. (2012) [6] Marcq, E. et al., submitted to Plan. and Space Sci. (2014)
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Powerful model for the point source sky: Far-ultraviolet and enhanced midinfrared performance
NASA Technical Reports Server (NTRS)
Cohen, Martin
1994-01-01
I report further developments of the Wainscoat et al. (1992) model originally created for the point source infrared sky. The already detailed and realistic representation of the Galaxy (disk, spiral arms and local spur, molecular ring, bulge, spheroid) has been improved, guided by CO surveys of local molecular clouds, and by the inclusion of a component to represent Gould's Belt. The newest version of the model is very well validated by Infrared Astronomy Satellite (IRAS) source counts. A major new aspect is the extension of the same model down to the far ultraviolet. I compare predicted and observed far-utraviolet source counts from the Apollo 16 'S201' experiment (1400 A) and the TD1 satellite (for the 1565 A band).
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Efficient terrestrial laser scan segmentation exploiting data structure
NASA Astrophysics Data System (ADS)
Mahmoudabadi, Hamid; Olsen, Michael J.; Todorovic, Sinisa
2016-09-01
New technologies such as lidar enable the rapid collection of massive datasets to model a 3D scene as a point cloud. However, while hardware technology continues to advance, processing 3D point clouds into informative models remains complex and time consuming. A common approach to increase processing efficiently is to segment the point cloud into smaller sections. This paper proposes a novel approach for point cloud segmentation using computer vision algorithms to analyze panoramic representations of individual laser scans. These panoramas can be quickly created using an inherent neighborhood structure that is established during the scanning process, which scans at fixed angular increments in a cylindrical or spherical coordinate system. In the proposed approach, a selected image segmentation algorithm is applied on several input layers exploiting this angular structure including laser intensity, range, normal vectors, and color information. These segments are then mapped back to the 3D point cloud so that modeling can be completed more efficiently. This approach does not depend on pre-defined mathematical models and consequently setting parameters for them. Unlike common geometrical point cloud segmentation methods, the proposed method employs the colorimetric and intensity data as another source of information. The proposed algorithm is demonstrated on several datasets encompassing variety of scenes and objects. Results show a very high perceptual (visual) level of segmentation and thereby the feasibility of the proposed algorithm. The proposed method is also more efficient compared to Random Sample Consensus (RANSAC), which is a common approach for point cloud segmentation.
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Three-dimensional reconstruction of indoor whole elements based on mobile LiDAR point cloud data
NASA Astrophysics Data System (ADS)
Gong, Yuejian; Mao, Wenbo; Bi, Jiantao; Ji, Wei; He, Zhanjun
2014-11-01
Ground-based LiDAR is one of the most effective city modeling tools at present, which has been widely used for three-dimensional reconstruction of outdoor objects. However, as for indoor objects, there are some technical bottlenecks due to lack of GPS signal. In this paper, based on the high-precision indoor point cloud data which was obtained by LiDAR, an international advanced indoor mobile measuring equipment, high -precision model was fulfilled for all indoor ancillary facilities. The point cloud data we employed also contain color feature, which is extracted by fusion with CCD images. Thus, it has both space geometric feature and spectral information which can be used for constructing objects' surface and restoring color and texture of the geometric model. Based on Autodesk CAD platform and with help of PointSence plug, three-dimensional reconstruction of indoor whole elements was realized. Specifically, Pointools Edit Pro was adopted to edit the point cloud, then different types of indoor point cloud data was processed, including data format conversion, outline extracting and texture mapping of the point cloud model. Finally, three-dimensional visualization of the real-world indoor was completed. Experiment results showed that high-precision 3D point cloud data obtained by indoor mobile measuring equipment can be used for indoor whole elements' 3-d reconstruction and that methods proposed in this paper can efficiently realize the 3 -d construction of indoor whole elements. Moreover, the modeling precision could be controlled within 5 cm, which was proved to be a satisfactory result.
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NASA Astrophysics Data System (ADS)
Gupta, Shaurya; Guha, Daipayan; Jakubovic, Raphael; Yang, Victor X. D.
2017-02-01
Computer-assisted navigation is used by surgeons in spine procedures to guide pedicle screws to improve placement accuracy and in some cases, to better visualize patient's underlying anatomy. Intraoperative registration is performed to establish a correlation between patient's anatomy and the pre/intra-operative image. Current algorithms rely on seeding points obtained directly from the exposed spinal surface to achieve clinically acceptable registration accuracy. Registration of these three dimensional surface point-clouds are prone to various systematic errors. The goal of this study was to evaluate the robustness of surgical navigation systems by looking at the relationship between the optical density of an acquired 3D point-cloud and the corresponding surgical navigation error. A retrospective review of a total of 48 registrations performed using an experimental structured light navigation system developed within our lab was conducted. For each registration, the number of points in the acquired point cloud was evaluated relative to whether the registration was acceptable, the corresponding system reported error and target registration error. It was demonstrated that the number of points in the point cloud neither correlates with the acceptance/rejection of a registration or the system reported error. However, a negative correlation was observed between the number of the points in the point-cloud and the corresponding sagittal angular error. Thus, system reported total registration points and accuracy are insufficient to gauge the accuracy of a navigation system and the operating surgeon must verify and validate registration based on anatomical landmarks prior to commencing surgery.
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Study on Huizhou architecture of point cloud registration based on optimized ICP algorithm
NASA Astrophysics Data System (ADS)
Zhang, Runmei; Wu, Yulu; Zhang, Guangbin; Zhou, Wei; Tao, Yuqian
2018-03-01
In view of the current point cloud registration software has high hardware requirements, heavy workload and moltiple interactive definition, the source of software with better processing effect is not open, a two--step registration method based on normal vector distribution feature and coarse feature based iterative closest point (ICP) algorithm is proposed in this paper. This method combines fast point feature histogram (FPFH) algorithm, define the adjacency region of point cloud and the calculation model of the distribution of normal vectors, setting up the local coordinate system for each key point, and obtaining the transformation matrix to finish rough registration, the rough registration results of two stations are accurately registered by using the ICP algorithm. Experimental results show that, compared with the traditional ICP algorithm, the method used in this paper has obvious time and precision advantages for large amount of point clouds.
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The Effect of Carbon Dioxide (CO 2) Ice Cloud Condensation on the Habitable Zone
NASA Astrophysics Data System (ADS)
Lincowski, Andrew; Meadows, Victoria; Robinson, Tyler D.; Crisp, David
2016-10-01
The currently accepted outer limit of the habitable zone (OHZ) is defined by the "maximum greenhouse" limit, where Rayleigh scattering from additional CO2 gas overwhelms greenhouse warming. However, this long-standing definition neglects the radiative effects of CO2 clouds (Kopparapu, 2013); this omission was justified based on studies using the two-stream approximation, which found CO2 clouds to be highly likely to produce a net warming. However, recent comparisons of the radiative effect of CO2 clouds using both a two-stream and multi-stream radiative transfer model (Kitzmann et al, 2013; Kitzmann, 2016) found that the warming effect was reduced when the more sophisticated multi-stream models were used. In many cases CO2 clouds caused a cooling effect, meaning that their impact on climate could not be neglected when calculating the outer edge of the habitable zone. To better understand the impact of CO2 ice clouds on the OHZ, we have integrated CO2 cloud condensation into a versatile 1-D climate model for terrestrial planets (Robinson et al, 2012) that uses the validated multi-stream SMART radiative transfer code (Meadows & Crisp, 1996; Crisp, 1997) with a simple microphysical model. We present preliminary results on the habitable zone with self-consistent CO2 clouds for a range of atmospheric masses, compositions and host star spectra, and the subsequent effect on surface temperature. In particular, we evaluate the habitable zone for TRAPPIST-1d (Gillon et al, 2016) with a variety of atmospheric compositions and masses. We present reflectance and transit spectra of these cold terrestrial planets. We identify any consequences for the OHZ in general and TRAPPIST-1d in particular. This more comprehensive treatment of the OHZ could impact our understanding of the distribution of habitable planets in the universe, and provide better constraints for statistical target selection techniques, such as the habitability index (Barnes et al, 2015), for missions like JWST, WFIRST-AFTA and the LUVOIR mission concept.
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Li, Chun-Ta; Shih, Dong-Her; Wang, Chun-Cheng
2018-04-01
With the rapid development of wireless communication technologies and the growing prevalence of smart devices, telecare medical information system (TMIS) allows patients to receive medical treatments from the doctors via Internet technology without visiting hospitals in person. By adopting mobile device, cloud-assisted platform and wireless body area network, the patients can collect their physiological conditions and upload them to medical cloud via their mobile devices, enabling caregivers or doctors to provide patients with appropriate treatments at anytime and anywhere. In order to protect the medical privacy of the patient and guarantee reliability of the system, before accessing the TMIS, all system participants must be authenticated. Mohit et al. recently suggested a lightweight authentication protocol for cloud-based health care system. They claimed their protocol ensures resilience of all well-known security attacks and has several important features such as mutual authentication and patient anonymity. In this paper, we demonstrate that Mohit et al.'s authentication protocol has various security flaws and we further introduce an enhanced version of their protocol for cloud-assisted TMIS, which can ensure patient anonymity and patient unlinkability and prevent the security threats of report revelation and report forgery attacks. The security analysis proves that our enhanced protocol is secure against various known attacks as well as found in Mohit et al.'s protocol. Compared with existing related protocols, our enhanced protocol keeps the merits of all desirable security requirements and also maintains the efficiency in terms of computation costs for cloud-assisted TMIS. We propose a more secure mutual authentication and privacy preservation protocol for cloud-assisted TMIS, which fixes the mentioned security weaknesses found in Mohit et al.'s protocol. According to our analysis, our authentication protocol satisfies most functionality features for privacy preservation and effectively cope with cloud-assisted TMIS with better efficiency. Copyright © 2018 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Ge, Xuming
2017-08-01
The coarse registration of point clouds from urban building scenes has become a key topic in applications of terrestrial laser scanning technology. Sampling-based algorithms in the random sample consensus (RANSAC) model have emerged as mainstream solutions to address coarse registration problems. In this paper, we propose a novel combined solution to automatically align two markerless point clouds from building scenes. Firstly, the method segments non-ground points from ground points. Secondly, the proposed method detects feature points from each cross section and then obtains semantic keypoints by connecting feature points with specific rules. Finally, the detected semantic keypoints from two point clouds act as inputs to a modified 4PCS algorithm. Examples are presented and the results compared with those of K-4PCS to demonstrate the main contributions of the proposed method, which are the extension of the original 4PCS to handle heavy datasets and the use of semantic keypoints to improve K-4PCS in relation to registration accuracy and computational efficiency.
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Insights on TTL Dehydration Mechanisms from Microphysical Modelling of Aircraft Observations
NASA Technical Reports Server (NTRS)
Ueyama, R.; Pfister, L.; Jensen, E.
2014-01-01
The Tropical Tropopause Layer (TTL), a transition layer between the upper troposphere and lower stratosphere in the tropics, serves as the entryway of various trace gases into the stratosphere. Of particular interest is the transport of water vapor through the TTL, as WV is an important greenhouse gas and also plays a significant role in stratospheric chemistry by affecting polar stratospheric cloud formation and the ozone budget. While the dominant control of stratospheric water vapor by tropical cold point temperatures via the "freeze-drying" process is generally well understood, the details of the TTL dehydration mechanisms, including the relative roles of deep convection, atmospheric waves and cloud microphysical processes, remain an active area of research. The dynamical and microphysical processes that influence TTL water vapor concentrations are investigated in simulations of cloud formation and dehydration along air parcel trajectories. We first confirm the validity of our Lagrangian models in a case study involving measurements from the Airborne Tropical TRopopause EXperiment (ATTREX) flights over the central and eastern tropical Pacific in Oct-Nov 2011 and Jan-Feb 2013. ERA-Interim winds and seasonal mean heating rates from Yang et al. (2010) are used to advance parcels back in time from the flight tracks, and time-varying vertical profiles of water vapor along the diabatic trajectories are calculated in a one-dimensional cloud model as in Jensen and Pfister (2004) but with more reliable temperature field, wave and convection schemes. The simulated water vapor profiles demonstrate a significant improvement over estimates based on the Lagrangian Dry Point, agreeing well with aircraft observations when the effects of cloud microphysics, subgrid-scale gravity waves and convection are included. Following this approach, we examine the dynamical and microphysical control of TTL water vapor in the 30ºS-30ºN latitudinal belt and elucidate the dominant processes in the winter and summer seasons. Implications of the TTL dehydration processes for the regulation of global stratospheric humidity will be discussed.
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Annual Cycle of Cloud Forcing of Surface Radiation Budget
NASA Technical Reports Server (NTRS)
Wilber, Anne C.; Smith, G. Louis; Stackhouse, Paul W., Jr.; Gupta, Shashi K.
2006-01-01
The climate of the Earth is determined by its balance of radiation. The incoming and outgoing radiation fluxes are strongly modulated by clouds, which are not well understood. The Earth Radiation Budget Experiment (Barkstrom and Smith, 1986) provided data from which the effects of clouds on radiation at the top of the atmosphere (TOA) could be computed (Ramanathan, 1987). At TOA, clouds increase the reflected solar radiation, tending to cool the planet, and decrease the OLR, causing the planet to retain its heat (Ramanathan et al., 1989; Harrison et al., 1990). The effects of clouds on radiation fluxes are denoted cloud forcing. These shortwave and longwave forcings counter each other to various degrees, so that in the tropics the result is a near balance. Over mid and polar latitude oceans, cloud forcing at TOA results in large net loss of radiation. Here, there are large areas of stratus clouds and cloud systems associated with storms. These systems are sensitive to surface temperatures and vary strongly with the annual cycle. During winter, anticyclones form over the continents and move to the oceans during summer. This movement of major cloud systems causes large changes of surface radiation, which in turn drives the surface temperature and sensible and latent heat released to the atmosphere.
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Large-scale urban point cloud labeling and reconstruction
NASA Astrophysics Data System (ADS)
Zhang, Liqiang; Li, Zhuqiang; Li, Anjian; Liu, Fangyu
2018-04-01
The large number of object categories and many overlapping or closely neighboring objects in large-scale urban scenes pose great challenges in point cloud classification. In this paper, a novel framework is proposed for classification and reconstruction of airborne laser scanning point cloud data. To label point clouds, we present a rectified linear units neural network named ReLu-NN where the rectified linear units (ReLu) instead of the traditional sigmoid are taken as the activation function in order to speed up the convergence. Since the features of the point cloud are sparse, we reduce the number of neurons by the dropout to avoid over-fitting of the training process. The set of feature descriptors for each 3D point is encoded through self-taught learning, and forms a discriminative feature representation which is taken as the input of the ReLu-NN. The segmented building points are consolidated through an edge-aware point set resampling algorithm, and then they are reconstructed into 3D lightweight models using the 2.5D contouring method (Zhou and Neumann, 2010). Compared with deep learning approaches, the ReLu-NN introduced can easily classify unorganized point clouds without rasterizing the data, and it does not need a large number of training samples. Most of the parameters in the network are learned, and thus the intensive parameter tuning cost is significantly reduced. Experimental results on various datasets demonstrate that the proposed framework achieves better performance than other related algorithms in terms of classification accuracy and reconstruction quality.
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NASA Astrophysics Data System (ADS)
Ge, Huazhi; Zhang, Xi; Fletcher, Leigh; Orton, Glenn S.; Sinclair, James Andrew; Fernandes,, Joshua; Momary, Thomas W.; Warren, Ari; Kasaba, Yasumasa; Sato, Takao M.; Fujiyoshi, Takuya
2017-10-01
Many brown dwarfs exhibit infrared rotational light curves with amplitude varying from a fewpercent to twenty percent (Artigau et al. 2009, ApJ, 701, 1534; Radigan et al. 2012, ApJ, 750,105). Recently, it was claimed that weather patterns, especially planetary-scale waves in thebelts and cloud spots, are responsible for the light curves and their evolutions on brown dwarfs(Apai et al. 2017, Science, 357, 683). Here we present a clear relationship between the direct IRemission maps and light curves of Jupiter at multiple wavelengths, which might be similar withthat on cold brown dwarfs. Based on infrared disk maps from Subaru/COMICS and VLT/VISIR,we constructed full maps of Jupiter and rotational light curves at different wavelengths in thethermal infrared. We discovered a strong relationship between the light curves and weatherpatterns on Jupiter. The light curves also exhibit strong multi-bands phase shifts and temporalvariations, similar to that detected on brown dwarfs. Together with the spectra fromTEXES/IRTF, our observations further provide detailed information of the spatial variations oftemperature, ammonia clouds and aerosols in the troposphere of Jupiter (Fletcher et al. 2016,Icarus, 2016 128) and their influences on the shapes of the light curves. We conclude that waveactivities in Jupiter’s belts (Fletcher et al. 2017, GRL, 44, 7140), cloud holes, and long-livedvortices such as the Great Red Spot and ovals control the shapes of IR light curves and multi-wavelength phase shifts on Jupiter. Our finding supports the hypothesis that observed lightcurves on brown dwarfs are induced by planetary-scale waves and cloud spots.
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Superposition and alignment of labeled point clouds.
Fober, Thomas; Glinca, Serghei; Klebe, Gerhard; Hüllermeier, Eyke
2011-01-01
Geometric objects are often represented approximately in terms of a finite set of points in three-dimensional euclidean space. In this paper, we extend this representation to what we call labeled point clouds. A labeled point cloud is a finite set of points, where each point is not only associated with a position in three-dimensional space, but also with a discrete class label that represents a specific property. This type of model is especially suitable for modeling biomolecules such as proteins and protein binding sites, where a label may represent an atom type or a physico-chemical property. Proceeding from this representation, we address the question of how to compare two labeled points clouds in terms of their similarity. Using fuzzy modeling techniques, we develop a suitable similarity measure as well as an efficient evolutionary algorithm to compute it. Moreover, we consider the problem of establishing an alignment of the structures in the sense of a one-to-one correspondence between their basic constituents. From a biological point of view, alignments of this kind are of great interest, since mutually corresponding molecular constituents offer important information about evolution and heredity, and can also serve as a means to explain a degree of similarity. In this paper, we therefore develop a method for computing pairwise or multiple alignments of labeled point clouds. To this end, we proceed from an optimal superposition of the corresponding point clouds and construct an alignment which is as much as possible in agreement with the neighborhood structure established by this superposition. We apply our methods to the structural analysis of protein binding sites.
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Cloud Radiative Effect in dependence on Cloud Type
NASA Astrophysics Data System (ADS)
Aebi, Christine; Gröbner, Julian; Kämpfer, Niklaus; Vuilleumier, Laurent
2015-04-01
Radiative transfer of energy in the atmosphere and the influence of clouds on the radiation budget remain the greatest sources of uncertainty in the simulation of climate change. Small changes in cloudiness and radiation can have large impacts on the Earth's climate. In order to assess the opposing effects of clouds on the radiation budget and the corresponding changes, frequent and more precise radiation and cloud observations are necessary. The role of clouds on the surface radiation budget is studied in order to quantify the longwave, shortwave and the total cloud radiative forcing in dependence on the atmospheric composition and cloud type. The study is performed for three different sites in Switzerland at three different altitude levels: Payerne (490 m asl), Davos (1'560 m asl) and Jungfraujoch (3'580 m asl). On the basis of data of visible all-sky camera systems at the three aforementioned stations in Switzerland, up to six different cloud types are distinguished (Cirrus-Cirrostratus, Cirrocumulus-Altocumulus, Stratus-Altostratus, Cumulus, Stratocumulus and Cumulonimbus-Nimbostratus). These cloud types are classified with a modified algorithm of Heinle et al. (2010). This cloud type classifying algorithm is based on a set of statistical features describing the color (spectral features) and the texture of an image (textural features) (Wacker et al. (2015)). The calculation of the fractional cloud cover information is based on spectral information of the all-sky camera data. The radiation data are taken from measurements with pyranometers and pyrgeometers at the different stations. A climatology of a whole year of the shortwave, longwave and total cloud radiative effect and its sensitivity to integrated water vapor, cloud cover and cloud type will be calculated for the three above-mentioned stations in Switzerland. For the calculation of the shortwave and longwave cloud radiative effect the corresponding cloud-free reference models developed at PMOD/WRC will be used (Wacker et al. (2013)). References: Heinle, A., A. Macke and A. Srivastav (2010) Automatic cloud classification of whole sky images, Atmospheric Measurement Techniques. Wacker, S., J. Gröbner and L. Vuilleumier (2013) A method to calculate cloud-free long-wave irradiance at the surface based on radiative transfer modeling and temperature lapse rate estimates, Theoretical and Applied Climatology. Wacker, S., J. Gröbner, C. Zysset, L. Diener, P. Tzoumanikis, A. Kazantzidis, L. Vuilleumier, R. Stöckli, S. Nyeki, and N. Kämpfer (2015) Cloud observations in Switzerland using hemispherical sky cameras, Journal of Geophysical Research.
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NASA Astrophysics Data System (ADS)
Kang, Zhizhong
2013-10-01
This paper presents a new approach to automatic registration of terrestrial laser scanning (TLS) point clouds utilizing a novel robust estimation method by an efficient BaySAC (BAYes SAmpling Consensus). The proposed method directly generates reflectance images from 3D point clouds, and then using SIFT algorithm extracts keypoints to identify corresponding image points. The 3D corresponding points, from which transformation parameters between point clouds are computed, are acquired by mapping the 2D ones onto the point cloud. To remove false accepted correspondences, we implement a conditional sampling method to select the n data points with the highest inlier probabilities as a hypothesis set and update the inlier probabilities of each data point using simplified Bayes' rule for the purpose of improving the computation efficiency. The prior probability is estimated by the verification of the distance invariance between correspondences. The proposed approach is tested on four data sets acquired by three different scanners. The results show that, comparing with the performance of RANSAC, BaySAC leads to less iterations and cheaper computation cost when the hypothesis set is contaminated with more outliers. The registration results also indicate that, the proposed algorithm can achieve high registration accuracy on all experimental datasets.
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A Catalog of Molecular Clouds in the Milky Way Galaxy
NASA Astrophysics Data System (ADS)
Wahl, Matthew; Koda, J.
2010-01-01
We have created a complete catalog of molecular clouds in the Milky Way Galaxy. This is an extension of our previous study (Koda et al. 2006) which used a preliminary data set from The Boston University Five College Radio Astronomy Observatory Galactic Ring Survey (BUFCRAO GRS). This work is of the complete data set from this GRS. The data covers the inner part of the northern Galactic disk between galactic longitudes 15 to 56 degrees, galactic latitudes -1.1 to 1.1 degrees, and the entire Galactic velocities. We used the standard cloud identification method. This method searches the data cube for a peak in temperature above a specified value, and then searches around that peak in all directions until the extents of the cloud are found. This method is iterated until all clouds are found. We prefer this method over other methods, because of its simplicity. The properties of our molecular clouds are very similar to those based on a more evolved method (Rathborne et al. 2009).
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Microphysics of Pyrocumulonimbus Clouds
NASA Technical Reports Server (NTRS)
Jensen, Eric; Ackerman, Andrew S.; Fridlind, Ann
2004-01-01
The intense heat from forest fires can generate explosive deep convective cloud systems that inject pollutants to high altitudes. Both satellite and high-altitude aircraft measurements have documented cases in which these pyrocumulonimbus clouds inject large amounts of smoke well into the stratosphere (Fromm and Servranckx 2003; Jost et al. 2004). This smoke can remain in the stratosphere, be transported large distances, and affect lower stratospheric chemistry. In addition recent in situ measurements in pyrocumulus updrafts have shown that the high concentrations of smoke particles have significant impacts on cloud microphysical properties. Very high droplet number densities result in delayed precipitation and may enhance lightning (Andrew et al. 2004). Presumably, the smoke particles will also lead to changes in the properties of anvil cirrus produces by the deep convection, with resulting influences on cloud radiative forcing. In situ sampling near the tops of mature pyrocumulonimbus is difficult due to the high altitude and violence of the storms. In this study, we use large eddy simulations (LES) with size-resolved microphysics to elucidate physical processes in pyrocumulonimbus clouds.
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Fine-scale Horizontal Structure of Arctic Mixed-Phase Clouds.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rambukkange,M.; Verlinde, J.; Elorante, E.
2006-07-10
Recent in situ observations in stratiform clouds suggest that mixed phase regimes, here defined as limited cloud volumes containing both liquid and solid water, are constrained to narrow layers (order 100 m) separating all-liquid and fully glaciated volumes (Hallett and Viddaurre, 2005). The Department of Energy Atmospheric Radiation Measurement Program's (DOE-ARM, Ackerman and Stokes, 2003) North Slope of Alaska (NSA) ARM Climate Research Facility (ACRF) recently started collecting routine measurement of radar Doppler velocity power spectra from the Millimeter Cloud Radar (MMCR). Shupe et al. (2004) showed that Doppler spectra has potential to separate the contributions to the total reflectivitymore » of the liquid and solid water in the radar volume, and thus to investigate further Hallett and Viddaurre's findings. The Mixed-Phase Arctic Cloud Experiment (MPACE) was conducted along the NSA to investigate the properties of Arctic mixed phase clouds (Verlinde et al., 2006). We present surface based remote sensing data from MPACE to discuss the fine-scale structure of the mixed-phase clouds observed during this experiment.« less
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Continuum Limit of Total Variation on Point Clouds
NASA Astrophysics Data System (ADS)
García Trillos, Nicolás; Slepčev, Dejan
2016-04-01
We consider point clouds obtained as random samples of a measure on a Euclidean domain. A graph representing the point cloud is obtained by assigning weights to edges based on the distance between the points they connect. Our goal is to develop mathematical tools needed to study the consistency, as the number of available data points increases, of graph-based machine learning algorithms for tasks such as clustering. In particular, we study when the cut capacity, and more generally total variation, on these graphs is a good approximation of the perimeter (total variation) in the continuum setting. We address this question in the setting of Γ-convergence. We obtain almost optimal conditions on the scaling, as the number of points increases, of the size of the neighborhood over which the points are connected by an edge for the Γ-convergence to hold. Taking of the limit is enabled by a transportation based metric which allows us to suitably compare functionals defined on different point clouds.
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Point cloud registration from local feature correspondences-Evaluation on challenging datasets.
Petricek, Tomas; Svoboda, Tomas
2017-01-01
Registration of laser scans, or point clouds in general, is a crucial step of localization and mapping with mobile robots or in object modeling pipelines. A coarse alignment of the point clouds is generally needed before applying local methods such as the Iterative Closest Point (ICP) algorithm. We propose a feature-based approach to point cloud registration and evaluate the proposed method and its individual components on challenging real-world datasets. For a moderate overlap between the laser scans, the method provides a superior registration accuracy compared to state-of-the-art methods including Generalized ICP, 3D Normal-Distribution Transform, Fast Point-Feature Histograms, and 4-Points Congruent Sets. Compared to the surface normals, the points as the underlying features yield higher performance in both keypoint detection and establishing local reference frames. Moreover, sign disambiguation of the basis vectors proves to be an important aspect in creating repeatable local reference frames. A novel method for sign disambiguation is proposed which yields highly repeatable reference frames.
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Hubble's Role in Studies of Venus' Clouds, Climate and Habitability
NASA Astrophysics Data System (ADS)
Jessup, Kandis-Lea; Marcq, Emmanuel; Mills, Franklin; Bertaux, Jean-Loup; Lee, Yeon Joo; Limaye, Sanjay; Roman, Anthony; Yung, Yuk
2018-06-01
Venus’ slow rotation fosters thick cloud formation, via long solar days, low Coriolis forces and strong subsolar convection. Thus, Venus and other slow rotators may maintain an Earth-like climate at ~ 2x the stellar flux as rapid rotators – if the cloud albedo is high, buffering climate change (Yang et al. 2014). However, Venus’ dense H2SO4 clouds host an absorbing source that drives solar heating, fostering rather than buffering climate change. As such, the response of an atmosphere to the available stellar flux and its impact on habitability will be quite different for a slow rotator planet with Venus-like vs. Earth-like buffering clouds.2010/2011 HST/STIS observations of Venus have provided data relevant for studying several of the mechanisms that determine Venus’ climate. These observations showed unambiguously that SO2 photolysis is not the sole process balancing the growth and loss of the cloud top SO (and SO2). As the parent species of Venus’ H2SO4 clouds, these results indicated that additional sulfur chemistry must be considered when defining the mechanisms controlling Venus’ H2SO4 formation process (Jessup et al. 2015). The STIS observations also showed decisively that vertical transport of Venus’ key UV absorbers: SO2, SO and the unnamed absorber are sensitive to the underlying surface elevation (Jessup et al. 2018). This implies that observations made over varying terrain types can be used to parameterize a) the energy and momentum released during surface-atmosphere interactions, which is essential for understanding Venus’ slow body and fast cloud rotation; and b) the sensitivity of the vertical profiles of the species having the greatest impact on Venus’ energy balance and climate to the underlying terrain. Cross-calibration of STIS and Venus Express data also enabled definitive identification of a 6 year decline in the cloud albedo resulting in a nearly 40% increase in the solar heating rate, suggesting dramatic climate change unparalleled in the solar system (Lee et al. 2018). Studies of the links between these phenomena, the super-rotation speed and the solar cycle will be revelatory for inter-stellar habitability studies.
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On the performance of metrics to predict quality in point cloud representations
NASA Astrophysics Data System (ADS)
Alexiou, Evangelos; Ebrahimi, Touradj
2017-09-01
Point clouds are a promising alternative for immersive representation of visual contents. Recently, an increased interest has been observed in the acquisition, processing and rendering of this modality. Although subjective and objective evaluations are critical in order to assess the visual quality of media content, they still remain open problems for point cloud representation. In this paper we focus our efforts on subjective quality assessment of point cloud geometry, subject to typical types of impairments such as noise corruption and compression-like distortions. In particular, we propose a subjective methodology that is closer to real-life scenarios of point cloud visualization. The performance of the state-of-the-art objective metrics is assessed by considering the subjective scores as the ground truth. Moreover, we investigate the impact of adopting different test methodologies by comparing them. Advantages and drawbacks of every approach are reported, based on statistical analysis. The results and conclusions of this work provide useful insights that could be considered in future experimentation.
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Semantic Segmentation of Building Elements Using Point Cloud Hashing
NASA Astrophysics Data System (ADS)
Chizhova, M.; Gurianov, A.; Hess, M.; Luhmann, T.; Brunn, A.; Stilla, U.
2018-05-01
For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and scene databases. The proposed semantic segmentation method is based on the psychological human interpretation of geometric objects, especially on fundamental rules of primary comprehension. Starting from these rules the buildings could be quite well and simply classified by a human operator (e.g. architect) into different building types and structural elements (dome, nave, transept etc.), including particular building parts which are visually detected. The key part of the procedure is a novel method based on hashing where point cloud projections are transformed into binary pixel representations. A segmentation approach released on the example of classical Orthodox churches is suitable for other buildings and objects characterized through a particular typology in its construction (e.g. industrial objects in standardized enviroments with strict component design allowing clear semantic modelling).
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NASA Astrophysics Data System (ADS)
Alidoost, F.; Arefi, H.
2017-11-01
Nowadays, Unmanned Aerial System (UAS)-based photogrammetry offers an affordable, fast and effective approach to real-time acquisition of high resolution geospatial information and automatic 3D modelling of objects for numerous applications such as topography mapping, 3D city modelling, orthophoto generation, and cultural heritages preservation. In this paper, the capability of four different state-of-the-art software packages as 3DSurvey, Agisoft Photoscan, Pix4Dmapper Pro and SURE is examined to generate high density point cloud as well as a Digital Surface Model (DSM) over a historical site. The main steps of this study are including: image acquisition, point cloud generation, and accuracy assessment. The overlapping images are first captured using a quadcopter and next are processed by different software to generate point clouds and DSMs. In order to evaluate the accuracy and quality of point clouds and DSMs, both visual and geometric assessments are carry out and the comparison results are reported.
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Multiview point clouds denoising based on interference elimination
NASA Astrophysics Data System (ADS)
Hu, Yang; Wu, Qian; Wang, Le; Jiang, Huanyu
2018-03-01
Newly emerging low-cost depth sensors offer huge potentials for three-dimensional (3-D) modeling, but existing high noise restricts these sensors from obtaining accurate results. Thus, we proposed a method for denoising registered multiview point clouds with high noise to solve that problem. The proposed method is aimed at fully using redundant information to eliminate the interferences among point clouds of different views based on an iterative procedure. In each iteration, noisy points are either deleted or moved to their weighted average targets in accordance with two cases. Simulated data and practical data captured by a Kinect v2 sensor were tested in experiments qualitatively and quantitatively. Results showed that the proposed method can effectively reduce noise and recover local features from highly noisy multiview point clouds with good robustness, compared to truncated signed distance function and moving least squares (MLS). Moreover, the resulting low-noise point clouds can be further smoothed by the MLS to achieve improved results. This study provides the feasibility of obtaining fine 3-D models with high-noise devices, especially for depth sensors, such as Kinect.
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Feature-based three-dimensional registration for repetitive geometry in machine vision
Gong, Yuanzheng; Seibel, Eric J.
2016-01-01
As an important step in three-dimensional (3D) machine vision, 3D registration is a process of aligning two or multiple 3D point clouds that are collected from different perspectives together into a complete one. The most popular approach to register point clouds is to minimize the difference between these point clouds iteratively by Iterative Closest Point (ICP) algorithm. However, ICP does not work well for repetitive geometries. To solve this problem, a feature-based 3D registration algorithm is proposed to align the point clouds that are generated by vision-based 3D reconstruction. By utilizing texture information of the object and the robustness of image features, 3D correspondences can be retrieved so that the 3D registration of two point clouds is to solve a rigid transformation. The comparison of our method and different ICP algorithms demonstrates that our proposed algorithm is more accurate, efficient and robust for repetitive geometry registration. Moreover, this method can also be used to solve high depth uncertainty problem caused by little camera baseline in vision-based 3D reconstruction. PMID:28286703
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An efficient global energy optimization approach for robust 3D plane segmentation of point clouds
NASA Astrophysics Data System (ADS)
Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian
2018-03-01
Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)
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Modeling the clouds on Venus: model development and improvement of a nucleation parameterization
NASA Astrophysics Data System (ADS)
Määttänen, Anni; Bekki, Slimane; Vehkamäki, Hanna; Julin, Jan; Montmessin, Franck; Ortega, Ismael K.; Lebonnois, Sébastien
2014-05-01
As both the clouds of Venus and aerosols in the Earth's stratosphere are composed of sulfuric acid droplets, we use the 1-D version of a model [1,4] developed for stratospheric aerosols and clouds to study the clouds on Venus. We have removed processes and compounds related to the stratospheric clouds so that the only species remaining are water and sulfuric acid, corresponding to the stratospheric sulfate aerosols, and we have added some key processes. The model describes microphysical processes including condensation/evaporation, and sedimentation. Coagulation, turbulent diffusion, and a parameterization for two-component nucleation [8] of water and sulfuric acid have been added in the model. Since the model describes explicitly the size distribution with a large number of size bins (50-500), it can handle multiple particle modes. The validity ranges of the existing nucleation parameterization [7] have been improved to cover a larger temperature range, and the very low relative humidity (RH) and high sulfuric acid concentrations found in the atmosphere of Venus. We have made several modifications to improve the 2002 nucleation parameterization [7], most notably ensuring that the two-component nucleation model behaves as predicted by the analytical studies at the one-component limit reached at extremely low RH. We have also chosen to use a self-consistent cluster distribution [9], constrained by scaling it to recent quantum chemistry calculations [3]. First tests of the cloud model have been carried out with temperature profiles from VIRA [2] and from the LMD Venus GCM [5], and with a compilation of water vapor and sulfuric acid profiles, as in [6]. The temperature and pressure profiles do not evolve with time, but the vapour profiles naturally change with the cloud. However, no chemistry is included for the moment, so the vapor concentrations are only dependent on the microphysical processes. The model has been run for several hundreds of Earth days to reach a steady state. Preliminary results are evaluated against observations. [1] Jumelet et al., JGR, 2009. [2] Kliore et al., 1986. [3] Kurtén et al., BER, 2007 [4] Larsen et al., JGR, 2000. [5] Lebonnois et al. JGR, 2010. [6] McGouldrick and Toon, Icarus 191, 2007. [7] Vehkamäki et al. JGR, 2002 [9] Wilemski and Wyslouzil, J.Chem.Phys. 1995.
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Indoor Modelling from Slam-Based Laser Scanner: Door Detection to Envelope Reconstruction
NASA Astrophysics Data System (ADS)
Díaz-Vilariño, L.; Verbree, E.; Zlatanova, S.; Diakité, A.
2017-09-01
Updated and detailed indoor models are being increasingly demanded for various applications such as emergency management or navigational assistance. The consolidation of new portable and mobile acquisition systems has led to a higher availability of 3D point cloud data from indoors. In this work, we explore the combined use of point clouds and trajectories from SLAM-based laser scanner to automate the reconstruction of building indoors. The methodology starts by door detection, since doors represent transitions from one indoor space to other, which constitutes an initial approach about the global configuration of the point cloud into building rooms. For this purpose, the trajectory is used to create a vertical point cloud profile in which doors are detected as local minimum of vertical distances. As point cloud and trajectory are related by time stamp, this feature is used to subdivide the point cloud into subspaces according to the location of the doors. The correspondence between subspaces and building rooms is not unambiguous. One subspace always corresponds to one room, but one room is not necessarily depicted by just one subspace, for example, in case of a room containing several doors and in which the acquisition is performed in a discontinue way. The labelling problem is formulated as combinatorial approach solved as a minimum energy optimization. Once the point cloud is subdivided into building rooms, envelop (conformed by walls, ceilings and floors) is reconstructed for each space. The connectivity between spaces is included by adding the previously detected doors to the reconstructed model. The methodology is tested in a real case study.
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a Point Cloud Classification Approach Based on Vertical Structures of Ground Objects
NASA Astrophysics Data System (ADS)
Zhao, Y.; Hu, Q.; Hu, W.
2018-04-01
This paper proposes a novel method for point cloud classification using vertical structural characteristics of ground objects. Since urbanization develops rapidly nowadays, urban ground objects also change frequently. Conventional photogrammetric methods cannot satisfy the requirements of updating the ground objects' information efficiently, so LiDAR (Light Detection and Ranging) technology is employed to accomplish this task. LiDAR data, namely point cloud data, can obtain detailed three-dimensional coordinates of ground objects, but this kind of data is discrete and unorganized. To accomplish ground objects classification with point cloud, we first construct horizontal grids and vertical layers to organize point cloud data, and then calculate vertical characteristics, including density and measures of dispersion, and form characteristic curves for each grids. With the help of PCA processing and K-means algorithm, we analyze the similarities and differences of characteristic curves. Curves that have similar features will be classified into the same class and point cloud correspond to these curves will be classified as well. The whole process is simple but effective, and this approach does not need assistance of other data sources. In this study, point cloud data are classified into three classes, which are vegetation, buildings, and roads. When horizontal grid spacing and vertical layer spacing are 3 m and 1 m respectively, vertical characteristic is set as density, and the number of dimensions after PCA processing is 11, the overall precision of classification result is about 86.31 %. The result can help us quickly understand the distribution of various ground objects.
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Tran, Thi Huong Giang; Ressl, Camillo; Pfeifer, Norbert
2018-02-03
This paper suggests a new approach for change detection (CD) in 3D point clouds. It combines classification and CD in one step using machine learning. The point cloud data of both epochs are merged for computing features of four types: features describing the point distribution, a feature relating to relative terrain elevation, features specific for the multi-target capability of laser scanning, and features combining the point clouds of both epochs to identify the change. All these features are merged in the points and then training samples are acquired to create the model for supervised classification, which is then applied to the whole study area. The final results reach an overall accuracy of over 90% for both epochs of eight classes: lost tree, new tree, lost building, new building, changed ground, unchanged building, unchanged tree, and unchanged ground.
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A curvature-based weighted fuzzy c-means algorithm for point clouds de-noising
NASA Astrophysics Data System (ADS)
Cui, Xin; Li, Shipeng; Yan, Xiutian; He, Xinhua
2018-04-01
In order to remove the noise of three-dimensional scattered point cloud and smooth the data without damnify the sharp geometric feature simultaneity, a novel algorithm is proposed in this paper. The feature-preserving weight is added to fuzzy c-means algorithm which invented a curvature weighted fuzzy c-means clustering algorithm. Firstly, the large-scale outliers are removed by the statistics of r radius neighboring points. Then, the algorithm estimates the curvature of the point cloud data by using conicoid parabolic fitting method and calculates the curvature feature value. Finally, the proposed clustering algorithm is adapted to calculate the weighted cluster centers. The cluster centers are regarded as the new points. The experimental results show that this approach is efficient to different scale and intensities of noise in point cloud with a high precision, and perform a feature-preserving nature at the same time. Also it is robust enough to different noise model.
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NASA Astrophysics Data System (ADS)
Hoegner, L.; Tuttas, S.; Xu, Y.; Eder, K.; Stilla, U.
2016-06-01
This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR) images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i) coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii) coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii) coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv) coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v) coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.
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NASA Astrophysics Data System (ADS)
Deng, S.; Katoh, M.; Takenaka, Y.; Cheung, K.; Ishii, A.; Fujii, N.; Gao, T.
2017-10-01
This study attempted to classify three coniferous and ten broadleaved tree species by combining airborne laser scanning (ALS) data and multispectral images. The study area, located in Nagano, central Japan, is within the broadleaved forests of the Afan Woodland area. A total of 235 trees were surveyed in 2016, and we recorded the species, DBH, and tree height. The geographical position of each tree was collected using a Global Navigation Satellite System (GNSS) device. Tree crowns were manually detected using GNSS position data, field photographs, true-color orthoimages with three bands (red-green-blue, RGB), 3D point clouds, and a canopy height model derived from ALS data. Then a total of 69 features, including 27 image-based and 42 point-based features, were extracted from the RGB images and the ALS data to classify tree species. Finally, the detected tree crowns were classified into two classes for the first level (coniferous and broadleaved trees), four classes for the second level (Pinus densiflora, Larix kaempferi, Cryptomeria japonica, and broadleaved trees), and 13 classes for the third level (three coniferous and ten broadleaved species), using the 27 image-based features, 42 point-based features, all 69 features, and the best combination of features identified using a neighborhood component analysis algorithm, respectively. The overall classification accuracies reached 90 % at the first and second levels but less than 60 % at the third level. The classifications using the best combinations of features had higher accuracies than those using the image-based and point-based features and the combination of all of the 69 features.
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NASA Astrophysics Data System (ADS)
Bunds, M. P.
2017-12-01
Point clouds are a powerful data source in the geosciences, and the emergence of structure-from-motion (SfM) photogrammetric techniques has allowed them to be generated quickly and inexpensively. Consequently, applications of them as well as methods to generate, manipulate, and analyze them warrant inclusion in undergraduate curriculum. In a new course called Geospatial Field Methods at Utah Valley University, students in small groups use SfM to generate a point cloud from imagery collected with a small unmanned aerial system (sUAS) and use it as a primary data source for a research project. Before creating their point clouds, students develop needed technical skills in laboratory and class activities. The students then apply the skills to construct the point clouds, and the research projects and point cloud construction serve as a central theme for the class. Intended student outcomes for the class include: technical skills related to acquiring, processing, and analyzing geospatial data; improved ability to carry out a research project; and increased knowledge related to their specific project. To construct the point clouds, students first plan their field work by outlining the field site, identifying locations for ground control points (GCPs), and loading them onto a handheld GPS for use in the field. They also estimate sUAS flight elevation, speed, and the flight path grid spacing required to produce a point cloud with the resolution required for their project goals. In the field, the students place the GCPs using handheld GPS, and survey the GCP locations using post-processed-kinematic (PPK) or real-time-kinematic (RTK) methods. The students pilot the sUAS and operate its camera according to the parameters that they estimated in planning their field work. Data processing includes obtaining accurate locations for the PPK/RTK base station and GCPs, and SfM processing with Agisoft Photoscan. The resulting point clouds are rasterized into digital surface models, assessed for accuracy, and analyzed in Geographic Information System software. Student projects have included mapping and analyzing landslide morphology, fault scarps, and earthquake ground surface rupture. Students have praised the geospatial skills they learn, whereas helping them stay on schedule to finish their projects is a challenge.
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Building a LiDAR point cloud simulator: Testing algorithms for high resolution topographic change
NASA Astrophysics Data System (ADS)
Carrea, Dario; Abellán, Antonio; Derron, Marc-Henri; Jaboyedoff, Michel
2014-05-01
Terrestrial laser technique (TLS) is becoming a common tool in Geosciences, with clear applications ranging from the generation of a high resolution 3D models to the monitoring of unstable slopes and the quantification of morphological changes. Nevertheless, like every measurement techniques, TLS still has some limitations that are not clearly understood and affect the accuracy of the dataset (point cloud). A challenge in LiDAR research is to understand the influence of instrumental parameters on measurement errors during LiDAR acquisition. Indeed, different critical parameters interact with the scans quality at different ranges: the existence of shadow areas, the spatial resolution (point density), and the diameter of the laser beam, the incidence angle and the single point accuracy. The objective of this study is to test the main limitations of different algorithms usually applied on point cloud data treatment, from alignment to monitoring. To this end, we built in MATLAB(c) environment a LiDAR point cloud simulator able to recreate the multiple sources of errors related to instrumental settings that we normally observe in real datasets. In a first step we characterized the error from single laser pulse by modelling the influence of range and incidence angle on single point data accuracy. In a second step, we simulated the scanning part of the system in order to analyze the shifting and angular error effects. Other parameters have been added to the point cloud simulator, such as point spacing, acquisition window, etc., in order to create point clouds of simple and/or complex geometries. We tested the influence of point density and vitiating point of view on the Iterative Closest Point (ICP) alignment and also in some deformation tracking algorithm with same point cloud geometry, in order to determine alignment and deformation detection threshold. We also generated a series of high resolution point clouds in order to model small changes on different environments (erosion, landslide monitoring, etc) and we then tested the use of filtering techniques using 3D moving windows along the space and time, which considerably reduces data scattering due to the benefits of data redundancy. In conclusion, the simulator allowed us to improve our different algorithms and to understand how instrumental error affects final results. And also, improve the methodology of scans acquisition to find the best compromise between point density, positioning and acquisition time with the best accuracy possible to characterize the topographic change.
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NASA Astrophysics Data System (ADS)
Muir, J.; Phinn, S. R.; Armston, J.; Scarth, P.; Eyre, T.
2014-12-01
Coarse woody debris (CWD) provides important habitat for many species and plays a vital role in nutrient cycling within an ecosystem. In addition, CWD makes an important contribution to forest biomass and fuel loads. Airborne or space based remote sensing instruments typically do not detect CWD beneath the forest canopy. Terrestrial laser scanning (TLS) provides a ground based method for three-dimensional (3-D) reconstruction of surface features and CWD. This research produced a 3-D reconstruction of the ground surface and automatically classified coarse woody debris from registered TLS scans. The outputs will be used to inform the development of a site-based index for the assessment of forest condition, and quantitative assessments of biomass and fuel loads. A survey grade terrestrial laser scanner (Riegl VZ400) was used to scan 13 positions, in an open eucalypt woodland site at Karawatha Forest Park, near Brisbane, Australia. Scans were registered, and a digital surface model (DSM) produced using an intensity threshold and an iterative morphological filter. The DSMs produced from single scans were compared to the registered multi-scan point cloud using standard error metrics including: Root Mean Squared Error (RMSE), Mean Squared Error (MSE), range, absolute error and signed error. In addition the DSM was compared to a Digital Elevation Model (DEM) produced from Airborne Laser Scanning (ALS). Coarse woody debris was subsequently classified from the DSM using laser pulse properties, including: width and amplitude, as well as point spatial relationships (e.g. nearest neighbour slope vectors). Validation of the coarse woody debris classification was completed using true-colour photographs co-registered to the TLS point cloud. The volume and length of the coarse woody debris was calculated from the classified point cloud. A representative network of TLS sites will allow for up-scaling to large area assessment using airborne or space based sensors to monitor forest condition, biomass and fuel loads.
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Thermal zonal winds in the Venus mesosphere from the Venus Express temperature soundings
NASA Astrophysics Data System (ADS)
Piccialli, Arianna; Titov, Dmitri; Tellmann, Silvia; Migliorini, Alessandra; Read, Peter; Grassi, Davide; Paetzold, Martin; Haeusler, Bernd; Piccioni, Giuseppe; Drossart, Pierre
The Venus mesosphere (60-100 km altitude) is a transition region characterized by extremely complex dynamics: strong retrograde zonal winds dominate in the troposphere and lower meso-sphere while a solar-antisolar circulation can be observed in the upper mesosphere. The super-rotation extends from the surface up to the cloud top (˜65 km altitude) with wind speeds of only a few meters per second near the surface and reaching a maximum value of ˜100 m s-1 at cloud top, corresponding to a rotation period of ˜4 Earth days (˜60 times faster than Venus itself). The solar-antisolar circulation is driven by the day-night contrast in solar heating, and occurs above 110 km altitude with speeds of 120 m s-1 . The processes responsible for maintain-ing the zonal super-rotation in the lower atmosphere and its transition to the solar-antisolar circulation in the upper atmosphere are still poorly understood (Schubert et al.,2007). Different techniques have been used to obtain direct observations of wind at various altitudes: tracking of clouds in ultraviolet (UV) and near infrared (NIR) images give information on wind speeds at the cloud top (Moissl et al., 2009; Sanchez-Lavega et al., 2008) and within the clouds (˜47 km, ˜61 km) (Sanchez-Lavega et al., 2008) while ground-based measurements of Doppler shifts in the CO2 band at 10 µm (Sornig et al., 2008) and in several CO millimiter lines (Rengel et al., 2008) provide wind speeds above the clouds up to ˜110 km altitude. The deep atmosphere from the surface up to the cloud top has been investigated through the Doppler tracking of descent probes and balloons (Counselman et al., 1980; Kerzhanovich and Limaye, 1985). In the mesosphere, between 45-85 km of altitude, where direct observations of wind are not possible, the zonal wind field can be derived from the vertical temperature structure using a special approximation of the thermal wind equation: based on cyclostrophic balance. Previous studies (Leovy, 1973; Newman et al., 1984) showed that on a slowly rotating planet, like Venus, strong zonal winds at the cloud top can be described by a cyclostrophic balance in which the equatorward component of centrifugal force is balanced by the meridional pressure gradient. This equation gives a possibility to reconstruct the zonal wind if the temperature field is known, together with a suitable boundary condition on u. Two experiments onboard Venus Express are sounding the temperature structure of the Venus mesosphere: VIRTIS sounds the Venus Southern hemisphere in the altitude range 65-90 km with a very good spatial and temporal coverage (Grassi et al., 2008) and the Northern hemi-sphere but with more limited coverage; VeRa observes both northern and southern hemispheres between 40-90 km altitude with a vertical resolution of ˜500 m (Tellmann et al., 2008). Here we present zonal thermal winds derived applying cyclostrophic balance from VIRTIS and VeRa temperature retrievals. The main features of the retrieved winds are: (1) a midlatitude jet with a maximum speed up to 140 ± 15 m s-1 which occurs around 50° S latitude at 70 km altitude; (2) the fast decrease of the wind speed from 60° S toward the pole; (3) the decrease of the wind speed with increasing height above the jet (Piccialli et al., 2008). Cyclostrophic winds show satisfactory agreement with the cloud-tracked winds derived from the Venus Monitoring Camera (VMC/VEx) UV images, although a disagreement is observed at the equator and near the pole due to the breakdown of the cyclostrophic approximation. From zonal thermal winds the Richardson number has been evaluated. In good agreement with previous studies (Allison et al., 1994), we have found that the atmosphere is dominated by convection from ˜45 km altitude up to the cloud top. A high value of Richardson number has been determined, cor-responding to the midlatitude jet and indicating a highly stable atmosphere. Verification of the necessary condition for barotropic instability implies that barotropic instability may occur on the poleward side of the midlatitude jet where planetary waves are expected to play an important role in the maintenance of the circulation.
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NASA Astrophysics Data System (ADS)
Niedermeier, Dennis; Augustin-Bauditz, Stefanie; Hartmann, Susan; Wex, Heike; Ignatius, Karoliina; Stratmann, Frank
2015-04-01
The formation of ice in atmospheric clouds has a substantial influence on the radiative properties of clouds as well as on the formation of precipitation. Therefore much effort has been made to understand and quantify the major ice formation processes in clouds. Immersion freezing has been suggested to be a dominant primary ice formation process in low and mid-level clouds (mixed-phase cloud conditions). It also has been shown that mineral dust particles are the most abundant ice nucleating particles in the atmosphere and thus may play an important role for atmospheric ice nucleation (Murray et al., 2012). Additionally, biological particles like bacteria and pollen are suggested to be potentially involved in atmospheric ice formation, at least on a regional scale (Murray et al., 2012). In recent studies for biological particles (SNOMAX and birch pollen), it has been demonstrated that freezing is induced by ice nucleating macromolecules and that an asymptotic value for the mass density of these ice nucleating macromolecules can be determined (Hartmann et al., 2013; Augustin et al., 2013, Wex et al., 2014). The question arises whether such an asymptotic value can also be determined for the ice active surface site density ns, a parameter which is commonly used to describe the ice nucleation activity of e.g., mineral dust. Such an asymptotic value for ns could be an important input parameter for atmospheric modeling applications. In the presented study, we therefore investigated the immersion freezing behavior of droplets containing size-segregated, monodisperse feldspar particles utilizing the Leipzig Aerosol Cloud Interaction Simulator (LACIS). For all particle sizes considered in the experiments, we observed a leveling off of the frozen droplet fraction reaching a plateau within the heterogeneous freezing temperature regime (T > -38°C) which was proportional to the particle surface area. Based on these findings, we could determine an asymptotic value for the ice active surface site density, which we named ns*, for the investigated feldspar sample. The comparison of these results with those of other studies elucidates the general feasibility of determining such an asymptotic value and also show that the value of ns* strongly depends on the method of the particle surface area determination. Acknowledgement This work is partly funded by the Federal Ministry of Education and Research (BMBF - project CLOUD 12) and by the German Research Foundation (DFG project WE 4722/1-1, part of the research unit INUIT, FOR 1525). D. Niedermeier acknowledges financial support from the Alexander von Humboldt-foundation. References Augustin et al.: Immersion freezing of birch pollen washing water, Atmos. Chem. Phys., 13, 10989-11003, doi:10.5194/acp-13-10989-2013, 2013. Hartmann et al.: Immersion freezing of ice nucleation active protein complexes, Atmos. Chem. Phys., 13, 5751-5766, doi:10.5194/acp-13-5751-2013, 2013. Murray et al.: Ice nucleation by particles immersed in supercooled cloud droplets, Chem. Soc. Rev., 41, 6519-6554, 2012. Wex et al.: Intercomparing different devices for the investigation of ice nucleating particles using Snomax® as test substance, Atmos. Chem. Phys. Discuss., 14, 22321-22384, doi:10.5194/acpd-14-22321-2014, 2014.
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Detection of fallen trees in ALS point clouds using a Normalized Cut approach trained by simulation
NASA Astrophysics Data System (ADS)
Polewski, Przemyslaw; Yao, Wei; Heurich, Marco; Krzystek, Peter; Stilla, Uwe
2015-07-01
Downed dead wood is regarded as an important part of forest ecosystems from an ecological perspective, which drives the need for investigating its spatial distribution. Based on several studies, Airborne Laser Scanning (ALS) has proven to be a valuable remote sensing technique for obtaining such information. This paper describes a unified approach to the detection of fallen trees from ALS point clouds based on merging short segments into whole stems using the Normalized Cut algorithm. We introduce a new method of defining the segment similarity function for the clustering procedure, where the attribute weights are learned from labeled data. Based on a relationship between Normalized Cut's similarity function and a class of regression models, we show how to learn the similarity function by training a classifier. Furthermore, we propose using an appearance-based stopping criterion for the graph cut algorithm as an alternative to the standard Normalized Cut threshold approach. We set up a virtual fallen tree generation scheme to simulate complex forest scenarios with multiple overlapping fallen stems. This simulated data is then used as a basis to learn both the similarity function and the stopping criterion for Normalized Cut. We evaluate our approach on 5 plots from the strictly protected mixed mountain forest within the Bavarian Forest National Park using reference data obtained via a manual field inventory. The experimental results show that our method is able to detect up to 90% of fallen stems in plots having 30-40% overstory cover with a correctness exceeding 80%, even in quite complex forest scenes. Moreover, the performance for feature weights trained on simulated data is competitive with the case when the weights are calculated using a grid search on the test data, which indicates that the learned similarity function and stopping criterion can generalize well on new plots.
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Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data
NASA Astrophysics Data System (ADS)
Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.
2016-06-01
Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.
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Registration of Vehicle-Borne Point Clouds and Panoramic Images Based on Sensor Constellations.
Yao, Lianbi; Wu, Hangbin; Li, Yayun; Meng, Bin; Qian, Jinfei; Liu, Chun; Fan, Hongchao
2017-04-11
A mobile mapping system (MMS) is usually utilized to collect environmental data on and around urban roads. Laser scanners and panoramic cameras are the main sensors of an MMS. This paper presents a new method for the registration of the point clouds and panoramic images based on sensor constellation. After the sensor constellation was analyzed, a feature point, the intersection of the connecting line between the global positioning system (GPS) antenna and the panoramic camera with a horizontal plane, was utilized to separate the point clouds into blocks. The blocks for the central and sideward laser scanners were extracted with the segmentation feature points. Then, the point clouds located in the blocks were separated from the original point clouds. Each point in the blocks was used to find the accurate corresponding pixel in the relative panoramic images via a collinear function, and the position and orientation relationship amongst different sensors. A search strategy is proposed for the correspondence of laser scanners and lenses of panoramic cameras to reduce calculation complexity and improve efficiency. Four cases of different urban road types were selected to verify the efficiency and accuracy of the proposed method. Results indicate that most of the point clouds (with an average of 99.7%) were successfully registered with the panoramic images with great efficiency. Geometric evaluation results indicate that horizontal accuracy was approximately 0.10-0.20 m, and vertical accuracy was approximately 0.01-0.02 m for all cases. Finally, the main factors that affect registration accuracy, including time synchronization amongst different sensors, system positioning and vehicle speed, are discussed.
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NASA Technical Reports Server (NTRS)
Andrefeouet, Serge; Robinson, Julie
2000-01-01
Coral reefs worldwide are suffering from severe and rapid degradation (Bryant et A, 1998; Hoegh-Guldberg, 1999). Quick, consistent, large-scale assessment is required to assess and monitor their status (e.g., USDOC/NOAA NESDIS et al., 1999). On-going systematic collection of high resolution digital satellite data will exhaustively complement the relatively small number of SPOT, Landsat 4-5, and IRS scenes acquired for coral reefs the last 20 years. The workhorse for current image acquisition is the Landsat 7 ETM+ Long Term Acquisition Plan (Gasch et al. 2000). Coral reefs are encountered in tropical areas and cloud contamination in satellite images is frequently a problem (Benner and Curry 1998), despite new automated techniques of cloud cover avoidance (Gasch and Campana 2000). Fusion of multidate acquisitions is a classical solution to solve the cloud problems. Though elegant, this solution is costly since multiple images must be purchased for one location; the cost may be prohibitive for institutions in developing countries. There are other difficulties associated with fusing multidate images as well. For example, water quality or surface state can significantly change through time in coral reef areas making the bathymetric processing of a mosaiced image strenuous. Therefore, another strategy must be selected to detect clouds and improve coral reefs mapping. Other supplemental data could be helpful and cost-effective for distinguishing clouds and generating the best possible reef maps in the shortest amount of time. Photographs taken from the 1960s to the present from the Space Shuttle and other human-occupied spacecraft are one under-used source of alternative multitemporal data (Lulla et al. 1996). Nearly 400,000 photographs have been acquired during this period, an estimated 28,000 of these taken to date are of potential value for reef remote sensing (Robinson et al. 2000a). The photographic images can be digitized into three bands (red, green and blue) and processed for various applications (e.g., Benner and Curry 1998, Nedeltchev 1999, Glasser and Lulla 2000, Robinson et al. 2000c, Webb et al, in press).
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NASA Astrophysics Data System (ADS)
Korzeniowska, Karolina; Mandlburger, Gottfried; Klimczyk, Agata
2013-04-01
The paper presents an evaluation of different terrain point extraction algorithms for Airborne Laser Scanning (ALS) point clouds. The research area covers eight test sites in the Małopolska Province (Poland) with varying point density between 3-15points/m² and surface as well as land cover characteristics. In this paper the existing implementations of algorithms were considered. Approaches based on mathematical morphology, progressive densification, robust surface interpolation and segmentation were compared. From the group of morphological filters, the Progressive Morphological Filter (PMF) proposed by Zhang K. et al. (2003) in LIS software was evaluated. From the progressive densification filter methods developed by Axelsson P. (2000) the Martin Isenburg's implementation in LAStools software (LAStools, 2012) was chosen. The third group of methods are surface-based filters. In this study, we used the hierarchic robust interpolation approach by Kraus K., Pfeifer N. (1998) as implemented in SCOP++ (Trimble, 2012). The fourth group of methods works on segmentation. From this filtering concept the segmentation algorithm available in LIS was tested (Wichmann V., 2012). The main aim in executing the automatic classification for ground extraction was operating in default mode or with default parameters which were selected by the developers of the algorithms. It was assumed that the default settings were equivalent to the parameters on which the best results can be achieved. In case it was not possible to apply an algorithm in default mode, a combination of the available and most crucial parameters for ground extraction were selected. As a result of these analyses, several output LAS files with different ground classification were achieved. The results were described on the basis of qualitative and quantitative analyses, both being in a formal description. The classification differences were verified on point cloud data. Qualitative verification of ground extraction was made on the basis of a visual inspection of the results (Sithole G., Vosselman G., 2004; Meng X. et al., 2010). The results of these analyses were described as a graph using weighted assumption. The quantitative analyses were evaluated on a basis of Type I, Type II and Total errors (Sithole G., Vosselman G., 2003). The achieved results show that the analysed algorithms yield different classification accuracies depending on the landscape and land cover. The simplest terrain for ground extraction was flat rural area with sparse vegetation. The most difficult were mountainous areas with very dense vegetation where only a few ground points were available. Generally the LAStools algorithm gives good results in every type of terrain, but the ground surface is too smooth. The LIS Progressive Morphological Filter algorithm gives good results in forested flat and low slope areas. The surface-based algorithm from SCOP++ gives good results in mountainous areas - both forested and built-up because it better preserves steep slopes, sharp ridges and breaklines, but sometimes it fails to remove off-terrain objects from the ground class. The segmentation-based algorithm in LIS gives quite good results in built-up flat areas, but in forested areas it does not work well. Bibliography: Axelsson, P., 2000. DEM generation from laser scanner data using adaptive TIN models. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIII (Pt. B4/1), 110- 117 Kraus, K., Pfeifer, N., 1998. Determination of terrain models in wooded areas with airborne laser scanner data. ISPRS Journal of Photogrammetry & Remote Sensing 53 (4), 193-203 LAStools website http://www.cs.unc.edu/~isenburg/lastools/ (verified in September 2012) Meng, X., Currit, N., Zhao, K., 2010. Ground Filtering Algorithms for Airborne LiDAR Data: A Review of Critical Issues. Remote Sensing 2, 833-860 Sithole, G., Vosselman, G., 2003. Report: ISPRS Comparison of Filters. Commission III, Working Group 3. Department of Geodesy, Faculty of Civil Engineering and Geosciences, Delft University of technology, The Netherlands Sithole, G., Vosselman, G., 2004. Experimental comparison of filter algorithms for bare-Earth extraction form airborne laser scanning point clouds. ISPRS Journal of Photogrammetry & Remote Sensing 59, 85-101 Trimble, 2012 http://www.trimble.com/geospatial/aerial-software.aspx (verified in November 2012) Wichmann, V., 2012. LIS Command Reference, LASERDATA GmbH, 1-231 Zhang, K., Chen, S.-C., Whitman, D., Shyu, M.-L., Yan, J., Zhang, C., 2003. A progressive morphological filter for removing non-ground measurements from airborne LIDAR data. IEEE Transactions on Geoscience and Remote Sensing, 41(4), 872-882
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Scavenging of ammonia by raindrops in Saturn's great storm clouds
NASA Astrophysics Data System (ADS)
Delitsky, M. L.; Baines, Kevin
2016-10-01
Observations of the great Saturn storms of 2010-2011 by Cassini instruments showed a very large depletion in atmospheric ammonia. While dynamics will play a role, the very high solubility of ammonia in water may be another important contributor to ammonia depletion in storms. Ammonia exists in Earth's atmosphere and rainstorms dissolve ammonia to a great degree, leaving almost no NH3 in the atmosphere. Studies by Elperin et al (2011, 2013) show that scavenging of ammonia is greatest as a rainstorm starts and lessens as raindrops fall, tapering off to almost zero by the time the rain reaches the ground (Elperin et al 2009). Ammonia is reaching saturation as it dissolves in the aqueous solution. As concentration increases, NH3 is then converted to aqueous species (NH3)x.(H2O)y (Max and Chapados 2013).Ammonia has the highest solubility in water compared to all other gases in the Saturn atmosphere. The Henry's Law constant for NH3 in water is 60 M/atm at 25 C. For H2S, it is 0.001 M/atm. In Saturn storms, it is "raining UP": As water-laden storm clouds convectively rise, ammonia gas will be scavenged and go into solution to a great degree, whilst all the other gases remain mostly in the gas phase. Aqueous ammonia acts as an antifreeze: if ammonia is dissolved in water cloud droplets to the limit of its solubility, as water droplets rise, they can stay liquid (and continue to scavenge NH3) to well below their normal freezing point of 0 Celsius (273 K). The freezing point for a 30 wt % water-ammonia solution is ~189 K. The pressure level where T = 189 K is at 2.8 bars. The normal freezing point of water occurs at the 9 bar pressure level in Saturn's atmosphere. 2.8 bars occurs at the -51 km altitude (below the 1 bar level). 9 bars is at the -130 km level: a difference of 79 km. A water droplet containing 30 wt% NH3 can move upwards from 9 bars to 2.8 bars (79 km) and still remain liquid, only freezing above that altitude. Calculations by the E-AIM model show that ammonia becomes the dominant species as the water droplets rise and cool. Ammonia will be effectively depleted as it is scavenged into water droplets in Saturn's storms.
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The role of marine organic ice nuclei in a global climate model
NASA Astrophysics Data System (ADS)
Hummel, Matthias; Egill Kristjansson, Jon
2016-04-01
Ice particle concentrations are a key parameter for cold clouds, exerting a strong influence on cloud lifetime, precipitation release, and the cloud radiative effect. The availability of ice-nucleating particles (INPs) and the temperature range in which they become activated determine the rate of ice formation in clouds (Hoose und Möhler, 2012). Particles from marine sources may contribute to ice formation in clouds, as they are abundant in the atmosphere and some of them have been found to be ice-nucleating active, but the extent of their influence on clouds is not known (Wilson et al., 2015). Wilson et al. (2015) collected marine INPs from the sea surface microlayer and analyzed their ice nucleation efficiency with a cold stage. Even in cirrus clouds, marine INPs may play a role, as their ice nucleation surface site density as a function of RHice at -40° C has been shown to be larger than for mineral dusts (ATD, kaolinite, and feldspar). In this study, we test the influence of marine organic aerosols on clouds via immersion freezing with the earth system model NorESM2 (Version 2 of the Norwegian Earth System Model; Bentsen et al., 2013). The model is based on the Community Earth System Model (CESM1.2) and its atmospheric part (CAM5 Oslo) is based on the Community Atmosphere Model (CAM5.3). The parameterization of ice nucleation of marine INPs is expressed as an exponential function of temperature multiplied by the total organic content. Marine organic aerosols are part of the sea spray aerosol and are ejected during bubble bursting. INPs are associated with exudates or other macromolecules mainly from diatoms. Hence, their concentration is related to the sea salt aerosols in the model simulation. Our first results indicate that the high marine INP concentrations at around 850 hPa occur at high latitudes. These regions have low mineral dust concentrations, which might increase the influence of marine INP on clouds. However, they do not coincide with regions of high winds and therefore large sea spray aerosol concentrations, contrary to model simulations in Wilson et al. (2015) with the global aerosol process model (GLOMAP), but are shifted further polewards. Therefore, marine INP concentrations strongly depend on temperature and do not necessarily coincide with large sea spray concentrations. At mid-latitudes, marine INP concentrations rank below dust INP by at least one order of magnitude. Further, this presentation will describe the influence of marine INP on cloud properties and give an estimate of the cloud radiative effect of marine INP. Bentsen, M., I. Bethke, et al. (2013): The Norwegian Earth System Model, NorESM1-M - Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev. 6(3): 687-720. Hoose, C. und O. Möhler (2012): Heterogeneous ice nucleation on atmospheric aerosols: a review of results from laboratory experiments, Atmos. Chem. Phys. 12(20): 9817-9854. Wilson, T. W., L. A. Ladino, et al. (2015): A marine biogenic source of atmospheric ice-nucleating particles, Nature 525(7568): 234-238.
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CLouds, and Aerosols Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016)
NASA Astrophysics Data System (ADS)
Haywood, J. M.; Bellouin, N.; Carslaw, K. S.; Coe, H.; Field, P.; Highwood, E. J.; Redemann, J.; Stier, P.; Wood, R.; Zuidema, P.
2013-12-01
Strongly absorbing biomass burning aerosols (BBAs) exist above highly reflectant stratocumulus clouds in the SE Atlantic with implications on the direct (e.g. Haywood et al., 2003), semi-direct (e.g. Johnson et al., 2006), and indirect effect of aerosols, implications on the remote sensing of cloud optical properties, development of clouds and feedback processes. Here, we present an analysis of modelled estimates of the direct effect using twelve models from the AEROCOM project (Myhre et al., 2013) to show that estimates of the direct effect in SE Atlantic range from strongly negative to strongly positive. Furthermore, we evaluate the performance of the HadGEM2 model and show it cannot replicate the extreme values of positive forcing inferred from high spectral resolution satellite retrievals. By examining patterns of deposition, we infer that the indirect effect from biomass burning aerosols is very limited in the model, but without detailed measurements we are unsure of the validity of this inference. We conclude that the SE Atlantic is therefore of key importance in determining the radiative forcing of biomass burning aerosols and provides a very stringent test for global climate models as they need to accurately represent the geographic distribution of the aerosol optical depth, the wavelength dependent aerosol single scattering albedo, the vertical profile of the aerosol, the geographic distribution of the cloud, the cloud fraction, the cloud liquid water content, the cloud droplet effective radii, and the vertical profile of the cloud. These results are used as scientific rationale to justify a new measurement campaign: CLouds and Aerosol Radiative Impacts and Forcing: Year-2016 (CLARIFY-2016). Haywood, J.M., Osborne, S.R. Francis, P.N., Keil, A., Formenti, P., Andreae, M.O., and Kaye, P.H., The mean physical and optical properties of regional haze dominated by biomass burning aerosol measured from the C-130 aircraft during SAFARI 2000, J. Geophys. Res., 108(D13), 8473, doi:10.1029/2002JD002226, 2003. Johnson, B.T., K.P. Shine, and P.M. Forster, The semi-direct aerosol effect: Impact of absorbing aerosols on marine stratocumulus, QJRMS, DOI: 10.1256/qj.03.61, 2006. Myhre, G. et al. Radiative forcing of the direct aerosol effect from AeroCom Phase II simulations, Atmos. Chem. Phys., 13, 1853-1877, doi:10.5194/acp-13-1853-2013, 2013
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How Is the Oxidative Capacity of the Cloud Aqueous Phase Modified By Bacteria?
NASA Astrophysics Data System (ADS)
Deguillaume, L.; Mouchel-Vallon, C.; Passananti, M.; Wirgot, N.; Joly, M.; Sancelme, M.; Bianco, A.; Cartier, N.; Brigante, M.; Mailhot, G.; Delort, A. M.; Chaumerliac, N. M.
2014-12-01
The aqueous phase photochemical reactions of constituents present in atmospheric water like H2O2, NO3-, NO2- and Fe(III) aqua-complexes or organic complexes can form radicals such as the hydroxyl radical HO within the water drop. However, the literature lacks of data precising the rate of HO formation and the relative contribution of the photochemical sources of HO. The production of radicals in cloud aqueous phase drives the oxidative capacity of the cloud medium and the efficiency of organic matter oxidation. The oxidation of organic compounds is suspected to lead to oxygenated species that could contribute to secondary organic aerosol (SOA) mass (Ervens et al., 2011). In current cloud chemistry models, HO concentrations strongly depend on the organic and iron amount. For high concentrations of organic compounds, this radical is efficiently consumed during the day due to the oxidation process. When iron concentrations are typical from continental cloud, the photolysis of Fe(III) complexes and the Fenton reaction drive the HO concentrations in the cloud models. The concept of biocatalysed reactions contributing to atmospheric chemistry as an alternative route to photochemistry is quite new (Vaïtilingom et al., 2013); it emerged from the recent discovery of metabolically active microorganisms in clouds. Microorganisms are well-known to degrade organic matter but they could also interact with oxidant species such as H2O2 (or their precursors) thanks to their oxidative and nitrosative stress metabolism that will act directly on these species and on their interactions with iron (metalloproteins and siderophores). For the moment, biological impact on radical chemistry within cloud has not been yet considered in cloud chemistry models. Bacterial activity will be introduced as catalysts in a multiphase cloud chemistry model using degradation rates measured in the laboratory. For example, biodegradation rates of the oxidants H2O2 by model bacteria will be tested in the model. Interactions of bacteria with iron through siderophore production will be also parameterized in the model. For this, we will perform idealistic scenarii to quantify the effect of bacteria on the aqueous budget of oxidants. Ervens et al., ACP, 11, 11069-11102, 2011. Vaïtilingom et al., PNAS, 110-2, 559-564, 2013.
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2017-04-01
ADVANCED VISUALIZATION AND INTERACTIVE DISPLAY RAPID INNOVATION AND DISCOVERY EVALUATION RESEARCH (VISRIDER) PROGRAM TASK 6: POINT CLOUD...To) OCT 2013 – SEP 2014 4. TITLE AND SUBTITLE ADVANCED VISUALIZATION AND INTERACTIVE DISPLAY RAPID INNOVATION AND DISCOVERY EVALUATION RESEARCH...various point cloud visualization techniques for viewing large scale LiDAR datasets. Evaluate their potential use for thick client desktop platforms
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Inventory of File WAFS_blended_2014102006f06.grib2
) [%] 004 700 mb CTP 6 hour fcst In-Cloud Turbulence [%] spatial ave,code table 4.15=3,#points=1 005 700 mb CTP 6 hour fcst In-Cloud Turbulence [%] spatial max,code table 4.15=3,#points=1 006 600 mb CTP 6 hour fcst In-Cloud Turbulence [%] spatial ave,code table 4.15=3,#points=1 007 600 mb CTP 6 hour fcst In
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NASA Astrophysics Data System (ADS)
Zheng, X.; Albrecht, B.; Jonsson, H. H.; Khelif, D.; Feingold, G.; Minnis, P.; Ayers, K.; Chuang, P.; Donaher, S.; Rossiter, D.; Ghate, V.; Ruiz-Plancarte, J.; Sun-Mack, S.
2011-09-01
Aircraft observations made off the coast of northern Chile in the Southeastern Pacific (20° S, 72° W; named Point Alpha) from 16 October to 13 November 2008 during the VAMOS Ocean-Cloud- Atmosphere-Land Study-Regional Experiment (VOCALS-REx), combined with meteorological reanalysis, satellite measurements, and radiosonde data, are used to investigate the boundary layer (BL) and aerosol-cloud-drizzle variations in this region. On days without predominately synoptic and meso-scale influences, the BL at Point Alpha was typical of a non-drizzling stratocumulus-topped BL. Entrainment rates calculated from the near cloud-top fluxes and turbulence in the BL at Point Alpha appeared to be weaker than those in the BL over the open ocean west of Point Alpha and the BL near the coast of the northeast Pacific. The cloud liquid water path (LWP) varied between 15 g m-2 and 160 g m-2. The BL had a depth of 1140 ± 120 m, was generally well-mixed and capped by a sharp inversion without predominately synoptic and meso-scale influences. The wind direction generally switched from southerly within the BL to northerly above the inversion. On days when a synoptic system and related mesoscale costal circulations affected conditions at Point Alpha (29 October-4 November), a moist layer above the inversion moved over Point Alpha, and the total-water mixing ratio above the inversion was larger than that within the BL. The accumulation mode aerosol varied from 250 to 700 cm-3 within the BL, and CCN at 0.2 % supersaturation within the BL ranged between 150 and 550 cm-3. The main aerosol source at Point Alpha was horizontal advection within the BL from south. The average cloud droplet number concentration ranged between 80 and 400 cm-3. While the mean LWP retrieved from GOES was in good agreement with the in situ measurements, the GOES-derived cloud droplet effective radius tended to be larger than that from the aircraft in situ observations near cloud top. The aerosol and cloud LWP relationship reveals that during the typical well-mixed BL days the cloud LWP increased with the CCN concentrations. On the other hand, meteorological factors and the decoupling processes have large influences on the cloud LWP variation as well.
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Impact of survey workflow on precision and accuracy of terrestrial LiDAR datasets
NASA Astrophysics Data System (ADS)
Gold, P. O.; Cowgill, E.; Kreylos, O.
2009-12-01
Ground-based LiDAR (Light Detection and Ranging) survey techniques are enabling remote visualization and quantitative analysis of geologic features at unprecedented levels of detail. For example, digital terrain models computed from LiDAR data have been used to measure displaced landforms along active faults and to quantify fault-surface roughness. But how accurately do terrestrial LiDAR data represent the true ground surface, and in particular, how internally consistent and precise are the mosaiced LiDAR datasets from which surface models are constructed? Addressing this question is essential for designing survey workflows that capture the necessary level of accuracy for a given project while minimizing survey time and equipment, which is essential for effective surveying of remote sites. To address this problem, we seek to define a metric that quantifies how scan registration error changes as a function of survey workflow. Specifically, we are using a Trimble GX3D laser scanner to conduct a series of experimental surveys to quantify how common variables in field workflows impact the precision of scan registration. Primary variables we are testing include 1) use of an independently measured network of control points to locate scanner and target positions, 2) the number of known-point locations used to place the scanner and point clouds in 3-D space, 3) the type of target used to measure distances between the scanner and the known points, and 4) setting up the scanner over a known point as opposed to resectioning of known points. Precision of the registered point cloud is quantified using Trimble Realworks software by automatic calculation of registration errors (errors between locations of the same known points in different scans). Accuracy of the registered cloud (i.e., its ground-truth) will be measured in subsequent experiments. To obtain an independent measure of scan-registration errors and to better visualize the effects of these errors on a registered point cloud, we scan from multiple locations an object of known geometry (a cylinder mounted above a square box). Preliminary results show that even in a controlled experimental scan of an object of known dimensions, there is significant variability in the precision of the registered point cloud. For example, when 3 scans of the central object are registered using 4 known points (maximum time, maximum equipment), the point clouds align to within ~1 cm (normal to the object surface). However, when the same point clouds are registered with only 1 known point (minimum time, minimum equipment), misalignment of the point clouds can range from 2.5 to 5 cm, depending on target type. The greater misalignment of the 3 point clouds when registered with fewer known points stems from the field method employed in acquiring the dataset and demonstrates the impact of field workflow on LiDAR dataset precision. By quantifying the degree of scan mismatch in results such as this, we can provide users with the information needed to maximize efficiency in remote field surveys.
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Study of Venus' cloud layers by polarimetry using SPICAV/VEx
NASA Astrophysics Data System (ADS)
Rossi, Loïc; Marcq, Emmanuel; Montmessin, Franck; Bertaux, Jean-Loup; Korablev, Oleg; Fedorova, Anna
2013-04-01
The study of Venus's cloud layers is important in order to understand the structure, radiative balance and dynamics of the Venusian atmosphere. The main cloud layers between 50 and 70km are thought to consist in ~ 1μm radius droplets of a H2SO4-H2O solution. Nevertheless, the composition and the size distribution of the droplets are difficult to constrain more precisely. The polarization measurements have given great results in the determination of the constituents of the haze. In the early 1980s, Kawabata et al.(1980) used the polarization data from the OCPP instrument on the spacecraft Pioneer Venus to constrain the properties of the haze. They obtained a refractive index of 1.45 ± 0.04 at ? = 550nm and an effective radius of 0.23 ± 0.04μm, with a normalized size distribution variance of 0.18 ± 0.1. Our work aims to reproduce the method used by Kawabata et al. by writing a Lorentz-Mie scattering model and apply it to the so far unexploited polarization data of the SPICAV-IR instrument on-board ESA's Venus Express in order to better constrain haze and cloud particles at the top of Venus's clouds, as well as their spatial and temporal variability. We introduce here the model we developed, based on the BH-MIE scattering model. Taking into account the same size distribution of droplets as Kawabata et al., we obtained the polarization degree after a single Mie scattering by a haze at all phase angles given the effective radius and variance of the distribution and the refractive index of the droplets. Our model seems consistent as it reproduces the polarization degree modeled by Kawabata et al. We also present the first application of our model to the SPICAV-IR data under the single scattering assumption. Hence we can confirm the mean constraints on the size and refractive index of the haze and cloud droplets. In the near future, we then aim to extend our study of the polarization data by integrating our model into a radiative transfer model which will take into account the multiple scattering. Having more recent observations in wavelengths ranging from 650 to 1625nm, will put better constraints on the properties of both cloud and haze particles, with a primary focus on the cloud droplets characterization. Bibliography: BOHREN, C. F. AND HUMAN, D.R., in Absorption and Scattering of light by small particles, Wiley, 1983 KAWABATA, K. et al., Cloud and haze properties from Pioneer Venus Polarimetry, JGR, 1980
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Characterization of SO2 abundance in Venus' night-side mesosphere from SPICAV/VEX observations
NASA Astrophysics Data System (ADS)
Belyaev, Denis; Fedorova, Anna; Piccialli, Arianna; Marcq, Emmanuel; Montmessin, Franck; Bertaux, Jean-Loup; Evdokimova, Daria
Sulfur dioxide (SO _{2}) is a key component of Venus’ atmosphere since the planet is totally covered by H _{2}SO _{4} droplets clouds at altitudes 50-70 km. Any significant change in the SO _{x} oxides above and within the clouds affects the photochemistry in the mesosphere (70-120 km). Recent continuous observations from the Venus Express orbiter (Belyaev et al., 2012; Marcq et al., 2013) and ground-based telescopes (Sandor et al., 2010; Krasnopolsky, 2010; Encrenaz et al., 2012) showed high variability of SO _{2} abundance with years, diurnal time and latitude on the day-side and terminators (commonly from 20 to 500 ppbv above the clouds). In the night-side mesosphere SO _{2} is not photo dissociative but, so far, its behavior has never been explored in details. In this paper we present first results from sulfur dioxide observations made by SPICAV UV spectrometer onboard Venus Express orbiter in regime of stellar occultation (Bertaux et al., 2007). In this mode the instrument observes night-side mesosphere and can register SO _{2} absorption bands in 190-220 nm and CO _{2} bands in 120-200 nm at altitudes from 85 to 110 km (spectral resolution is ˜2 nm). As a result, vertical distribution of SO _{2} and CO _{2} concentrations has been retrieved in observation period from June 2006 to April 2012, at latitude range 60(°) S-60(°) N and Venus local time 20:00-04:00. On the average, mixing ratio of sulfur dioxide fluctuates around ˜100 ppbv along altitude range 90-100 km. Our work is supported by the Program No.22 of RAS and grant of the Russian Government to MIPT. References: Belyaev D. et al., 2012. Vertical profiling of SO _{2} and SO above Venus' clouds by SPICAV/SOIR solar occultations. Icarus 217, 740-751. Bertaux J.-L. et al., 2007. SPICAV on Venus Express: three spectrometers to study the global structure and composition of Venus atmosphere. Planet. Space Sci. 55, 1673-1700. Encrenaz T. et al., 2012. HDO and SO _{2} thermal mapping on Venus: evidence for strong SO _{2} variability. A&A 543, A153. Krasnopolsky V.A., 2010. Spatially-resolved high-resolution spectroscopy of Venus. 2. Variations of HDO, OCS, and SO _{2} at the cloud tops. Icarus 209, 314-322. Marcq E. et al., 2013. Variations of sulphur dioxide at the cloud top of Venus’s dynamic atmosphere. Nature Geoscience, vol. 6, 25-28. DOI: 10.1038/NGEO1650. Sandor B.J. et al., 2010. Sulfur chemistry in the Venus mesosphere from SO _{2} and SO microwave spectra. Icarus 208, 49-60.
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Effect of Particle Non-Sphericity on Satellite Monitoring of Drifting Volcanic Ash Clouds
NASA Technical Reports Server (NTRS)
Krotkov, Nicholay A.; Flittner, D. E.; Krueger, A. J.; Kostinski, A.; Riley, C.; Rose, W.
1998-01-01
Volcanic eruptions loft gases and ash particles into the atmosphere and produce effects that are both short term (aircraft hazards, interference with satellite measurements) and long term (atmospheric chemistry, climate). Large (greater than 0.5mm) ash particles fall out in minutes [Rose et al, 1995], but fine ash particles can remain in the atmosphere for many days. This fine volcanic ash is a hazard to modem jet aircraft because the operating temperatures of jet engines are above the solidus temperature of volcanic ash, and because ash causes abrasion of windows and airframe, and disruption of avionics. At large distances(10(exp 2)-10(exp 4) km or more) from their source, drifting ash clouds are increasingly difficult to distinguish from meteorological clouds, both visually and on radar [Rose et al., 1995]. Satellites above the atmosphere are unique platforms for viewing volcanic clouds on a global basis and measuring their constituents and total mass. Until recently, only polar AVHRR and geostationary GOES instruments could be used to determine characteristics of drifting volcanic ash clouds using the 10-12 micron window [Prata 1989; Wen and Rose 1994; Rose and Schneider 1996]. The NASA Total Ozone Mapping Spectrometer (TOMS) instruments aboard the Nimbus-7, Meteor3, ADEOS, and Earth Probe satellites have produced a unique data set of global SO2 volcanic emissions since 1978 (Krueger et al., 1995). Besides SO2, a new technique has been developed which uses the measured spectral contrast of the backscattered radiances in the 330-380nm spectral region (where gaseous absorption is negligible) in conjunction with radiative transfer models to retrieve properties of volcanic ash (Krotkov et al., 1997) and other types of absorbing aerosols (Torres et al., 1998).
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Towards global Landsat burned area mapping: revisit time and availability of cloud free observations
NASA Astrophysics Data System (ADS)
Melchiorre, A.; Boschetti, L.
2016-12-01
Global, daily coarse resolution satellite data have been extensively used for systematic burned area mapping (Giglio et al. 2013; Mouillot et al. 2014). The adoption of similar approaches for producing moderate resolution (10 - 30 m) global burned area products would lead to very significant improvements for the wide variety of fire information users. It would meet a demand for accurate burned area perimeters needed for fire management, post-fire assessment and environmental restoration, and would lead to more accurate and precise atmospheric emission estimations, especially over heterogeneous areas (Mouillot et al. 2014; Randerson et al. 2012; van der Werf et al. 2010). The increased spatial resolution clearly benefits mapping accuracy: the reduction of mixed pixels directly translates in increased spectral separation compared to coarse resolution data. As a tradeoff, the lower temporal resolution (e.g. 16 days for Landsat), could potentially cause large omission errors in ecosystems with fast post-fire recovery. The spectral signal due to the fire effects is non-permanent, can be detected for a period ranging from a few weeks in savannas and grasslands, to over a year in forest ecosystems (Roy et al. 2010). Additionally, clouds, smoke, and other optically thick aerosols limit the number of available observations (Roy et al. 2008; Smith and Wooster 2005), exacerbating the issues related to mapping burned areas globally with moderate resolution sensors. This study presents a global analysis of the effect of cloud cover on Landsat data availability over burned areas, by analyzing the MODIS data record of burned area (MCD45) and cloud detections (MOD35), and combining it with the Landsat acquisition calendar and viewing geometry. For each pixel classified as burned in the MCD45 product, the MOD35 data are used to determine how many cloud free observations would have been available on Landsat overpass days, within the period of observability of the burned area spectral signal in the specific ecosystem. If a burned area pixel is covered by clouds on all the post-fire Landsat overpass days, we assume that it would not be detected in a hypothetical Landsat global burned area product. The resulting maps of expected omission errors are combined for the full 15-year MODIS dataset, and summarized by ecoregion and landcover class.
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Cassini Imaging of Titan’s North Polar Cloud With the Visual and Infrared Mapping Spectrometer
NASA Astrophysics Data System (ADS)
Le Mouélic, S.; Rannou, P.; Rodriguez, S.; Sotin, C.; Le Corre, L.; Barnes, J. W.; Brown, R. H.; Griffith, C. A.; Baines, K. H.; Buratti, B. J.; Clark, R. N.; Nicholson, P.
2009-12-01
We report on the Visual and Infrared Mapping Spectrometer (VIMS) observations of a giant cloud over the north pole of Titan. Griffith et al. [Science, 2006] described the first evidence of a north polar feature having the form of an ubiquitous bright band at 51° to 68°N in VIMS images acquired in December 2004, August and September 2005. Rodriguez et al. [Nature, 2009] systematically detect spectral signatures of clouds with VIMS at latitudes higher than 50°N between July 2004 and December 2007, with no attempt to show the structure of each individual cloud. The first good opportunity to observe the fully illuminated north pole, that we described here, occurred on December 28, 2006. The north cloud was then continuously monitored in various geometries during 3 years after its first discovery. This cloud shows much less signal at 5-µm than southern and tropical clouds which are thought to be composed of liquid/solid methane. This indicates a lower backscattering at 5-µm. It is consistent with clouds composed of micron-sized particles made of solid ethane. A radiative transfer model in spherical geometry (SPDISORT) shows that it is found at an altitude between 30 and 40 km. This observation confirms the IPSL Titan global circulation model of Rannou et al. [Science 2006] that predicted the formation of large polar ethane clouds due to the downwelling of atmospheric streams exactly at the same latitudes. The limits of the observed northern cloud between 50-60°N corresponds to the limit between filled and dry lakes as observed by the RADAR of Cassini. The cloud cover appears less widespread in the last observations, which could indicate that it is progressively vanishing. This is also in agreement with the predictions of the IPSL general circulation model as we approach the equinox in August 2009. Dedicated observations by the Cassini spacecraft during the extended mission possibly up to 2017 should allow the observation of the forthcoming seasonal circulation turnover, with possibly the complete disappearance of this type of cloud that caps the north pole.
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Making lidar more photogenic: creating band combinations from lidar information
Stoker, Jason M.
2010-01-01
Over the past five to ten years the use and applicability of light detection and ranging (lidar) technology has increased dramatically. As a result, an almost exponential amount of lidar data is being collected across the country for a wide range of applications, and it is currently the technology of choice for high resolution terrain model creation, 3-dimensional city and infrastructure modeling, forestry and a wide range of scientific applications (Lin and Mills, 2010). The amount of data that is being delivered across the country is impressive. For example, the U.S. Geological Survey’s (USGS) Center for Lidar Information Coordination and Knowledge (CLICK), which is a National repository of USGS and partner lidar point cloud datasets (Stoker et al., 2006), currently has 3.5 percent of the United States covered by lidar, and has approximately another 5 percent in the processing queue. The majority of data being collected by the commercial sector are from discrete-return systems, which collect billions of lidar points in an average project. There are also a lot of discussions involving a potential National-scale Lidar effort (Stoker et al., 2008).
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NASA Astrophysics Data System (ADS)
Tsurutani, Bruce T.; Lakhina, Gurbax S.; Echer, Ezequiel; Hajra, Rajkumar; Nayak, Chinmaya; Mannucci, Anthony J.; Meng, Xing
2018-02-01
An alternative scenario to the Ngwira et al. (2014, https://doi.org/10.1002/2013JA019661) high sheath densities is proposed for modeling the Carrington magnetic storm. Typical slow solar wind densities ( 5 cm-3) and lower interplanetary magnetic cloud magnetic field intensities ( 90 nT) can be used to explain the observed initial and main phase storm features. A second point is that the fast storm recovery may be explained by ring current losses due to electromagnetic ion cyclotron wave scattering.
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Comparison of 3D point clouds produced by LIDAR and UAV photoscan in the Rochefort cave (Belgium)
NASA Astrophysics Data System (ADS)
Watlet, Arnaud; Triantafyllou, Antoine; Kaufmann, Olivier; Le Mouelic, Stéphane
2016-04-01
Amongst today's techniques that are able to produce 3D point clouds, LIDAR and UAV (Unmanned Aerial Vehicle) photogrammetry are probably the most commonly used. Both methods have their own advantages and limitations. LIDAR scans create high resolution and high precision 3D point clouds, but such methods are generally costly, especially for sporadic surveys. Compared to LIDAR, UAV (e.g. drones) are cheap and flexible to use in different kind of environments. Moreover, the photogrammetric processing workflow of digital images taken with UAV becomes easier with the rise of many affordable software packages (e.g. Agisoft, PhotoModeler3D, VisualSFM). We present here a challenging study made at the Rochefort Cave Laboratory (South Belgium) comprising surface and underground surveys. The site is located in the Belgian Variscan fold-and-thrust belt, a region that shows many karstic networks within Devonian limestone units. A LIDAR scan has been acquired in the main chamber of the cave (~ 15000 m³) to spatialize 3D point cloud of its inner walls and infer geological beds and structures. Even if the use of LIDAR instrument was not really comfortable in such caving environment, the collected data showed a remarkable precision according to few control points geometry. We also decided to perform another challenging survey of the same cave chamber by modelling a 3D point cloud using photogrammetry of a set of DSLR camera pictures taken from the ground and UAV pictures. The aim was to compare both techniques in terms of (i) implementation of data acquisition and processing, (ii) quality of resulting 3D points clouds (points density, field vs cloud recovery and points precision), (iii) their application for geological purposes. Through Rochefort case study, main conclusions are that LIDAR technique provides higher density point clouds with slightly higher precision than photogrammetry method. However, 3D data modeled by photogrammetry provide visible light spectral information for each modeled voxel and interpolated vertices that can be a useful attributes for clustering during data treatment. We thus illustrate such applications to the Rochefort cave by using both sources of 3D information to quantify the orientation of inaccessible geological structures (e.g. faults, tectonic and gravitational joints, and sediments bedding), cluster these structures using color information gathered from UAV's 3D point cloud and compare these data to structural data surveyed on the field. An additional drone photoscan was also conducted in the surface sinkhole giving access to the surveyed underground cavity to seek geological bodies' connections.
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NASA Technical Reports Server (NTRS)
Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Shinozuka, Y.; Schmid, B.
2015-01-01
Absorbing smoke or mineral dust aerosols above clouds (AAC) are a frequent occurrence in certain regions and seasons. Operational aerosol retrievals from sensors like MODIS omit AAC because they are designed to work only over cloud-free scenes. However, AAC can in principle be quantified by these sensors in some situations (e.g. Jethva et al., 2013; Meyer et al., 2013). We present a summary of some analyses of the potential of MODIS-like instruments for this purpose, along with two case studies using airborne observations from the Ames Airborne Tracking Sunphotometer (AATS; http://geo.arc.nasa.gov/sgg/AATS-website/) as a validation data source for a preliminary AAC algorithm applied to MODIS measurements. AAC retrievals will eventually be added to the MODIS Deep Blue (Hsu et al., 2013) processing chain.
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NASA Astrophysics Data System (ADS)
Klapa, Przemyslaw; Mitka, Bartosz; Zygmunt, Mariusz
2017-12-01
Capability of obtaining a multimillion point cloud in a very short time has made the Terrestrial Laser Scanning (TLS) a widely used tool in many fields of science and technology. The TLS accuracy matches traditional devices used in land surveying (tacheometry, GNSS - RTK), but like any measurement it is burdened with error which affects the precise identification of objects based on their image in the form of a point cloud. The point’s coordinates are determined indirectly by means of measuring the angles and calculating the time of travel of the electromagnetic wave. Each such component has a measurement error which is translated into the final result. The XYZ coordinates of a measuring point are determined with some uncertainty and the very accuracy of determining these coordinates is reduced as the distance to the instrument increases. The paper presents the results of examination of geometrical stability of a point cloud obtained by means terrestrial laser scanner and accuracy evaluation of solids determined using the cloud. Leica P40 scanner and two different settings of measuring points were used in the tests. The first concept involved placing a few balls in the field and then scanning them from various sides at similar distances. The second part of measurement involved placing balls and scanning them a few times from one side but at varying distances from the instrument to the object. Each measurement encompassed a scan of the object with automatic determination of its position and geometry. The desk studies involved a semiautomatic fitting of solids and measurement of their geometrical elements, and comparison of parameters that determine their geometry and location in space. The differences of measures of geometrical elements of balls and translations vectors of the solids centres indicate the geometrical changes of the point cloud depending on the scanning distance and parameters. The results indicate the changes in the geometry of scanned objects depending on the point cloud quality and distance from the measuring instrument. Varying geometrical dimensions of the same element suggest also that the point cloud does not keep a stable geometry of measured objects.
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NASA Astrophysics Data System (ADS)
Hanel, A.; Stilla, U.
2017-05-01
Vehicle environment cameras observing traffic participants in the area around a car and interior cameras observing the car driver are important data sources for driver intention recognition algorithms. To combine information from both camera groups, a camera system calibration can be performed. Typically, there is no overlapping field-of-view between environment and interior cameras. Often no marked reference points are available in environments, which are a large enough to cover a car for the system calibration. In this contribution, a calibration method for a vehicle camera system with non-overlapping camera groups in an urban environment is described. A-priori images of an urban calibration environment taken with an external camera are processed with the structure-frommotion method to obtain an environment point cloud. Images of the vehicle interior, taken also with an external camera, are processed to obtain an interior point cloud. Both point clouds are tied to each other with images of both image sets showing the same real-world objects. The point clouds are transformed into a self-defined vehicle coordinate system describing the vehicle movement. On demand, videos can be recorded with the vehicle cameras in a calibration drive. Poses of vehicle environment cameras and interior cameras are estimated separately using ground control points from the respective point cloud. All poses of a vehicle camera estimated for different video frames are optimized in a bundle adjustment. In an experiment, a point cloud is created from images of an underground car park, as well as a point cloud of the interior of a Volkswagen test car is created. Videos of two environment and one interior cameras are recorded. Results show, that the vehicle camera poses are estimated successfully especially when the car is not moving. Position standard deviations in the centimeter range can be achieved for all vehicle cameras. Relative distances between the vehicle cameras deviate between one and ten centimeters from tachymeter reference measurements.
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NASA Astrophysics Data System (ADS)
Duarte, João; Gonçalves, Gil; Duarte, Diogo; Figueiredo, Fernando; Mira, Maria
2015-04-01
Photogrammetric Unmanned Aerial Vehicles (UAVs) and Terrestrial Laser Scanners (TLS) are two emerging technologies that allows the production of dense 3D point clouds of the sensed topographic surfaces. Although image-based stereo-photogrammetric point clouds could not, in general, compete on geometric quality over TLS point clouds, fully automated mapping solutions based on ultra-light UAVs (or drones) have recently become commercially available at very reasonable accuracy and cost for engineering and geological applications. The purpose of this paper is to compare the two point clouds generated by these two technologies, in order to automatize the manual process tasks commonly used to detect and represent the attitude of discontinuities (Stereographic projection: Schmidt net - Equal area). To avoid the difficulties of access and guarantee the data survey security conditions, this fundamental step in all geological/geotechnical studies, applied to the extractive industry and engineering works, has to be replaced by a more expeditious and reliable methodology. This methodology will allow, in a more actuated clear way, give answers to the needs of evaluation of rock masses, by mapping the structures present, which will reduce considerably the associated risks (investment, structures dimensioning, security, etc.). A case study of a dolerite outcrop locate in the center of Portugal (the dolerite outcrop is situated in the volcanic complex of Serra de Todo-o-Mundo, Casais Gaiola, intruded in Jurassic sandstones) will be used to assess this methodology. The results obtained show that the 3D point cloud produced by the Photogrammetric UAV platform has the appropriate geometric quality for extracting the parameters that define the discontinuities of the dolerite outcrops. Although, they are comparable to the manual extracted parameters, their quality is inferior to parameters extracted from the TLS point cloud.
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Cloud-point detection using a portable thickness shear mode crystal resonator
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mansure, A.J.; Spates, J.J.; Germer, J.W.
1997-08-01
The Thickness Shear Mode (TSM) crystal resonator monitors the crude oil by propagating a shear wave into the oil. The coupling of the shear wave and the crystal vibrations is a function of the viscosity of the oil. By driving the crystal with circuitry that incorporates feedback, it is possible to determine the change from Newtonian to non-Newtonian viscosity at the cloud point. A portable prototype TSM Cloud Point Detector (CPD) has performed flawlessly during field and lab tests proving the technique is less subjective or operator dependent than the ASTM standard. The TSM CPD, in contrast to standard viscositymore » techniques, makes the measurement in a closed container capable of maintaining up to 100 psi. The closed container minimizes losses of low molecular weight volatiles, allowing samples (25 ml) to be retested with the addition of chemicals. By cycling/thermal soaking the sample, the effects of thermal history can be investigated and eliminated as a source of confusion. The CPD is portable, suitable for shipping the field offices for use by personnel without special training or experience in cloud point measurements. As such, it can make cloud point data available without the delays and inconvenience of sending samples to special labs. The crystal resonator technology can be adapted to in-line monitoring of cloud point and deposition detection.« less
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NASA Astrophysics Data System (ADS)
Micheletti, Natan; Tonini, Marj; Lane, Stuart N.
2017-02-01
Acquisition of high density point clouds using terrestrial laser scanners (TLSs) has become commonplace in geomorphic science. The derived point clouds are often interpolated onto regular grids and the grids compared to detect change (i.e. erosion and deposition/advancement movements). This procedure is necessary for some applications (e.g. digital terrain analysis), but it inevitably leads to a certain loss of potentially valuable information contained within the point clouds. In the present study, an alternative methodology for geomorphological analysis and feature detection from point clouds is proposed. It rests on the use of the Density-Based Spatial Clustering of Applications with Noise (DBSCAN), applied to TLS data for a rock glacier front slope in the Swiss Alps. The proposed methods allowed the detection and isolation of movements directly from point clouds which yield to accuracies in the following computation of volumes that depend only on the actual registered distance between points. We demonstrated that these values are more conservative than volumes computed with the traditional DEM comparison. The results are illustrated for the summer of 2015, a season of enhanced geomorphic activity associated with exceptionally high temperatures.
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Metric Scale Calculation for Visual Mapping Algorithms
NASA Astrophysics Data System (ADS)
Hanel, A.; Mitschke, A.; Boerner, R.; Van Opdenbosch, D.; Hoegner, L.; Brodie, D.; Stilla, U.
2018-05-01
Visual SLAM algorithms allow localizing the camera by mapping its environment by a point cloud based on visual cues. To obtain the camera locations in a metric coordinate system, the metric scale of the point cloud has to be known. This contribution describes a method to calculate the metric scale for a point cloud of an indoor environment, like a parking garage, by fusing multiple individual scale values. The individual scale values are calculated from structures and objects with a-priori known metric extension, which can be identified in the unscaled point cloud. Extensions of building structures, like the driving lane or the room height, are derived from density peaks in the point distribution. The extension of objects, like traffic signs with a known metric size, are derived using projections of their detections in images onto the point cloud. The method is tested with synthetic image sequences of a drive with a front-looking mono camera through a virtual 3D model of a parking garage. It has been shown, that each individual scale value improves either the robustness of the fused scale value or reduces its error. The error of the fused scale is comparable to other recent works.
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GPU-Based Point Cloud Superpositioning for Structural Comparisons of Protein Binding Sites.
Leinweber, Matthias; Fober, Thomas; Freisleben, Bernd
2018-01-01
In this paper, we present a novel approach to solve the labeled point cloud superpositioning problem for performing structural comparisons of protein binding sites. The solution is based on a parallel evolution strategy that operates on large populations and runs on GPU hardware. The proposed evolution strategy reduces the likelihood of getting stuck in a local optimum of the multimodal real-valued optimization problem represented by labeled point cloud superpositioning. The performance of the GPU-based parallel evolution strategy is compared to a previously proposed CPU-based sequential approach for labeled point cloud superpositioning, indicating that the GPU-based parallel evolution strategy leads to qualitatively better results and significantly shorter runtimes, with speed improvements of up to a factor of 1,500 for large populations. Binary classification tests based on the ATP, NADH, and FAD protein subsets of CavBase, a database containing putative binding sites, show average classification rate improvements from about 92 percent (CPU) to 96 percent (GPU). Further experiments indicate that the proposed GPU-based labeled point cloud superpositioning approach can be superior to traditional protein comparison approaches based on sequence alignments.
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Real object-based 360-degree integral-floating display using multiple depth camera
NASA Astrophysics Data System (ADS)
Erdenebat, Munkh-Uchral; Dashdavaa, Erkhembaatar; Kwon, Ki-Chul; Wu, Hui-Ying; Yoo, Kwan-Hee; Kim, Young-Seok; Kim, Nam
2015-03-01
A novel 360-degree integral-floating display based on the real object is proposed. The general procedure of the display system is similar with conventional 360-degree integral-floating displays. Unlike previously presented 360-degree displays, the proposed system displays the 3D image generated from the real object in 360-degree viewing zone. In order to display real object in 360-degree viewing zone, multiple depth camera have been utilized to acquire the depth information around the object. Then, the 3D point cloud representations of the real object are reconstructed according to the acquired depth information. By using a special point cloud registration method, the multiple virtual 3D point cloud representations captured by each depth camera are combined as single synthetic 3D point cloud model, and the elemental image arrays are generated for the newly synthesized 3D point cloud model from the given anamorphic optic system's angular step. The theory has been verified experimentally, and it shows that the proposed 360-degree integral-floating display can be an excellent way to display real object in the 360-degree viewing zone.
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The Feasibility of 3d Point Cloud Generation from Smartphones
NASA Astrophysics Data System (ADS)
Alsubaie, N.; El-Sheimy, N.
2016-06-01
This paper proposes a new technique for increasing the accuracy of direct geo-referenced image-based 3D point cloud generated from low-cost sensors in smartphones. The smartphone's motion sensors are used to directly acquire the Exterior Orientation Parameters (EOPs) of the captured images. These EOPs, along with the Interior Orientation Parameters (IOPs) of the camera/ phone, are used to reconstruct the image-based 3D point cloud. However, because smartphone motion sensors suffer from poor GPS accuracy, accumulated drift and high signal noise, inaccurate 3D mapping solutions often result. Therefore, horizontal and vertical linear features, visible in each image, are extracted and used as constraints in the bundle adjustment procedure. These constraints correct the relative position and orientation of the 3D mapping solution. Once the enhanced EOPs are estimated, the semi-global matching algorithm (SGM) is used to generate the image-based dense 3D point cloud. Statistical analysis and assessment are implemented herein, in order to demonstrate the feasibility of 3D point cloud generation from the consumer-grade sensors in smartphones.
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Registration of Vehicle-Borne Point Clouds and Panoramic Images Based on Sensor Constellations
Yao, Lianbi; Wu, Hangbin; Li, Yayun; Meng, Bin; Qian, Jinfei; Liu, Chun; Fan, Hongchao
2017-01-01
A mobile mapping system (MMS) is usually utilized to collect environmental data on and around urban roads. Laser scanners and panoramic cameras are the main sensors of an MMS. This paper presents a new method for the registration of the point clouds and panoramic images based on sensor constellation. After the sensor constellation was analyzed, a feature point, the intersection of the connecting line between the global positioning system (GPS) antenna and the panoramic camera with a horizontal plane, was utilized to separate the point clouds into blocks. The blocks for the central and sideward laser scanners were extracted with the segmentation feature points. Then, the point clouds located in the blocks were separated from the original point clouds. Each point in the blocks was used to find the accurate corresponding pixel in the relative panoramic images via a collinear function, and the position and orientation relationship amongst different sensors. A search strategy is proposed for the correspondence of laser scanners and lenses of panoramic cameras to reduce calculation complexity and improve efficiency. Four cases of different urban road types were selected to verify the efficiency and accuracy of the proposed method. Results indicate that most of the point clouds (with an average of 99.7%) were successfully registered with the panoramic images with great efficiency. Geometric evaluation results indicate that horizontal accuracy was approximately 0.10–0.20 m, and vertical accuracy was approximately 0.01–0.02 m for all cases. Finally, the main factors that affect registration accuracy, including time synchronization amongst different sensors, system positioning and vehicle speed, are discussed. PMID:28398256
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Martin, Shawn
This code consists of Matlab routines which enable the user to perform non-manifold surface reconstruction via triangulation from high dimensional point cloud data. The code was based on an algorithm originally developed in [Freedman (2007), An Incremental Algorithm for Reconstruction of Surfaces of Arbitrary Codimension Computational Geometry: Theory and Applications, 36(2):106-116]. This algorithm has been modified to accommodate non-manifold surface according to the work described in [S. Martin and J.-P. Watson (2009), Non-Manifold Surface Reconstruction from High Dimensional Point Cloud DataSAND #5272610].The motivation for developing the code was a point cloud describing the molecular conformation space of cyclooctane (C8H16). Cyclooctanemore » conformation space was represented using points in 72 dimensions (3 coordinates for each molecule). The code was used to triangulate the point cloud and thereby study the geometry and topology of cyclooctane. Futures applications are envisioned for peptides and proteins.« less
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Classification of Mobile Laser Scanning Point Clouds from Height Features
NASA Astrophysics Data System (ADS)
Zheng, M.; Lemmens, M.; van Oosterom, P.
2017-09-01
The demand for 3D maps of cities and road networks is steadily growing and mobile laser scanning (MLS) systems are often the preferred geo-data acquisition method for capturing such scenes. Because MLS systems are mounted on cars or vans they can acquire billions of points of road scenes within a few hours of survey. Manual processing of point clouds is labour intensive and thus time consuming and expensive. Hence, the need for rapid and automated methods for 3D mapping of dense point clouds is growing exponentially. The last five years the research on automated 3D mapping of MLS data has tremendously intensified. In this paper, we present our work on automated classification of MLS point clouds. In the present stage of the research we exploited three features - two height components and one reflectance value, and achieved an overall accuracy of 73 %, which is really encouraging for further refining our approach.
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Outdoor Illegal Construction Identification Algorithm Based on 3D Point Cloud Segmentation
NASA Astrophysics Data System (ADS)
An, Lu; Guo, Baolong
2018-03-01
Recently, various illegal constructions occur significantly in our surroundings, which seriously restrict the orderly development of urban modernization. The 3D point cloud data technology is used to identify the illegal buildings, which could address the problem above effectively. This paper proposes an outdoor illegal construction identification algorithm based on 3D point cloud segmentation. Initially, in order to save memory space and reduce processing time, a lossless point cloud compression method based on minimum spanning tree is proposed. Then, a ground point removing method based on the multi-scale filtering is introduced to increase accuracy. Finally, building clusters on the ground can be obtained using a region growing method, as a result, the illegal construction can be marked. The effectiveness of the proposed algorithm is verified using a publicly data set collected from the International Society for Photogrammetry and Remote Sensing (ISPRS).
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Effect of electromagnetic field on Kordylewski clouds formation
NASA Astrophysics Data System (ADS)
Salnikova, Tatiana; Stepanov, Sergey
2018-05-01
In previous papers the authors suggest a clarification of the phenomenon of appearance-disappearance of Kordylewski clouds - accumulation of cosmic dust mass in the vicinity of the triangle libration points of the Earth-Moon system. Under gravi-tational and light perturbation of the Sun the triangle libration points aren't the points of relative equilibrium. However, there exist the stable periodic motion of the particles, surrounding every of the triangle libration points. Due to this fact we can consider a probabilistic model of the dust clouds formation. These clouds move along the periodical orbits in small vicinity of the point of periodical orbit. To continue this research we suggest a mathematical model to investigate also the electromagnetic influences, arising under consideration of the charged dust particles in the vicinity of the triangle libration points of the Earth-Moon system. In this model we take under consideration the self-unduced force field within the set of charged particles, the probability distribution density evolves according to the Vlasov equation.
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NASA Technical Reports Server (NTRS)
Kawamoto, K.; Minnis, P.; Smith, W. L., Jr.
2001-01-01
One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum et al used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. used a combination infrared (IR), visible (VIS), and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne proposed a 1.6 and 11 micron bispectral threshold method. While all of these methods have made progress in solving this stubborn problem none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the Atmospheric Radiation Measurement (ARM) domains and hence should be identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) used over the ARM Program's Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites to study the capability of detecting overlapping clouds.
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Point Cloud Based Change Detection - an Automated Approach for Cloud-based Services
NASA Astrophysics Data System (ADS)
Collins, Patrick; Bahr, Thomas
2016-04-01
The fusion of stereo photogrammetric point clouds with LiDAR data or terrain information derived from SAR interferometry has a significant potential for 3D topographic change detection. In the present case study latest point cloud generation and analysis capabilities are used to examine a landslide that occurred in the village of Malin in Maharashtra, India, on 30 July 2014, and affected an area of ca. 44.000 m2. It focuses on Pléiades high resolution satellite imagery and the Airbus DS WorldDEMTM as a product of the TanDEM-X mission. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. The pre-event topography is represented by the WorldDEMTM product, delivered with a raster of 12 m x 12 m and based on the EGM2008 geoid (called pre-DEM). For the post-event situation a Pléiades 1B stereo image pair of the AOI affected was obtained. The ENVITask "GeneratePointCloudsByDenseImageMatching" was implemented to extract passive point clouds in LAS format from the panchromatic stereo datasets: • A dense image-matching algorithm is used to identify corresponding points in the two images. • A block adjustment is applied to refine the 3D coordinates that describe the scene geometry. • Additionally, the WorldDEMTM was input to constrain the range of heights in the matching area, and subsequently the length of the epipolar line. The "PointCloudFeatureExtraction" task was executed to generate the post-event digital surface model from the photogrammetric point clouds (called post-DEM). Post-processing consisted of the following steps: • Adding the geoid component (EGM 2008) to the post-DEM. • Pre-DEM reprojection to the UTM Zone 43N (WGS-84) coordinate system and resizing. • Subtraction of the pre-DEM from the post-DEM. • Filtering and threshold based classification of the DEM difference to analyze the surface changes in 3D. The automated point cloud generation and analysis introduced here can be embedded in virtually any existing geospatial workflow for operational applications. Three integration options were implemented in this case study: • Integration within any ArcGIS environment whether deployed on the desktop, in the cloud, or online. Execution uses a customized ArcGIS script tool. A Python script file retrieves the parameters from the user interface and runs the precompiled IDL code. That IDL code is used to interface between the Python script and the relevant ENVITasks. • Publishing the point cloud processing tasks as services via the ENVI Services Engine (ESE). ESE is a cloud-based image analysis solution to publish and deploy advanced ENVI image and data analytics to existing enterprise infrastructures. For this purpose the entire IDL code can be capsuled in a single ENVITask. • Integration in an existing geospatial workflow using the Python-to-IDL Bridge. This mechanism allows calling IDL code within Python on a user-defined platform. The results of this case study allow a 3D estimation of the topographic changes within the tectonically active and anthropogenically invaded Malin area after the landslide event. Accordingly, the point cloud analysis was correlated successfully with modelled displacement contours of the slope. Based on optical satellite imagery, such point clouds of high precision and density distribution can be obtained in a few minutes to support the operational monitoring of landslide processes.
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NASA Astrophysics Data System (ADS)
Zheng, X.; Albrecht, B.; Jonsson, H. H.; Khelif, D.; Feingold, G.; Minnis, P.; Ayers, K.; Chuang, P.; Donaher, S.; Rossiter, D.; Ghate, V.; Ruiz-Plancarte, J.; Sun-Mack, S.
2011-05-01
Aircraft observations made off the coast of northern Chile in the Southeastern Pacific (20° S, 72° W; named Point Alpha) from 16 October to 13 November 2008 during the VAMOS Ocean-Cloud-Atmosphere-Land Study-Regional Experiment (VOCALS-REx), combined with meteorological reanalysis, satellite measurements, and radiosonde data, are used to investigate the boundary layer (BL) and aerosol-cloud-drizzle variations in this region. The BL at Point Alpha was typical of a non-drizzling stratocumulus-topped BL on days without predominately synoptic and meso-scale influences. The BL had a depth of 1140 ± 120 m, was well-mixed and capped by a sharp inversion. The wind direction generally switched from southerly within the BL to northerly above the inversion. The cloud liquid water path (LWP) varied between 15 g m-2 and 160 g m-2. From 29 October to 4 November, when a synoptic system affected conditions at Point Alpha, the cloud LWP was higher than on the other days by around 40 g m-2. On 1 and 2 November, a moist layer above the inversion moved over Point Alpha. The total-water specific humidity above the inversion was larger than that within the BL during these days. Entrainment rates (average of 1.5 ± 0.6 mm s-1) calculated from the near cloud-top fluxes and turbulence (vertical velocity variance) in the BL at Point Alpha appeared to be weaker than those in the BL over the open ocean west of Point Alpha and the BL near the coast of the northeast Pacific. The accumulation mode aerosol varied from 250 to 700 cm-3 within the BL, and CCN at 0.2 % supersaturation within the BL ranged between 150 and 550 cm-3. The main aerosol source at Point Alpha was horizontal advection within the BL from south. The average cloud droplet number concentration ranged between 80 and 400 cm-3, which was consistent with the satellite-derived values. The relationship of cloud droplet number concentration and CCN at 0.2 % supersaturation from 18 flights is Nd =4.6 × CCN0.71. While the mean LWP retrieved from GOES was in good agreement with the in situ measurements, the GOES-derived cloud droplet effective radius tended to be larger than that from the aircraft {in situ} observations near cloud top. The aerosol and cloud LWP relationship reveals that during the typical well-mixed BL days the cloud LWP increased with the CCN concentrations. On the other hand, meteorological factors and the decoupling processes have large influences on the cloud LWP variation as well.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Warner-Schmid, D.; Hoshi, Suwaru; Armstrong, D.W.
Aqueous solutions of nonionic surfactants are known to undergo phase separations at elevated temperatures. This phenomenon is known as clouding,' and the temperature at which it occurs is refereed to as the cloud point. Permethylhydroxypropyl-[beta]-cyclodextrin (PMHP-[beta]-CD) was synthesized and aqueous solutions containing it were found to undergo similar cloud-point behavior. Factors that affect the phase separation of PMHP-[beta]-CD were investigated. Subsequently, the cloud-point extractions of several aromatic compounds (i.e., acetanilide, aniline, 2,2[prime]-dihydroxybiphenyl, N-methylaniline, 2-naphthol, o-nitroaniline, m-nitroaniline, p-nitroaniline, nitrobenzene, o-nitrophenol, m-nitrophenol, p-nitrophenol, 4-phenazophenol, 3-phenylphenol, and 2-phenylbenzimidazole) from dilute aqueous solution were evaluated. Although the extraction efficiency of the compounds varied, mostmore » can be quantitatively extracted if sufficient PMHP-[beta]-CD is used. For those few compounds that are not extracted (e.g., o-nitroacetanilide), the cloud-point procedure may be an effective one-step isolation or purification method. 18 refs., 2 figs., 3 tabs.« less
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Comment on "The shape and composition of interstellar silicate grains"
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bradley, J P; Ishii, H
2007-09-27
In the paper entitled 'The shape and composition of interstellar silicate grains' (A & A, 462, 667-676 (2007)), Min et al. explore non-spherical grain shape and composition in modeling the interstellar 10 and 20 {micro}m extinction features. This progression towards more realistic models is vitally important to enabling valid comparisons between dust observations and laboratory measurements. Min et al. proceed to compare their model results with GEMS (glass with embedded metals and sulfides) from IDPs (interplanetary dust particles) and to discuss the nature and origin of GEMS. Specifically, they evaluate the hypothesis of Bradley (1994) that GEMS are interstellar (IS)more » amorphous silicates. From a comparison of the mineralogy, chemical compositions, and infrared (IR) spectral properties of GEMS with their modeling results, Min et al. conclude: 'GEMS are, in general, not unprocessed leftovers from the diffuse ISM'. This conclusion is based, however, on erroneous and incomplete GEMS data. It is important to clarify first that Bradley (1994) never proposed that GEMS are unprocessed leftovers from the diffuse ISM, nor did he suggest that individual subnanogram mass GEMS are a representative sampling of the enormous mass of silicates in the diffuse ISM. Bradley (1994) simply showed that GEMS properties are consistent with those of IS amorphous silicates. It is widely accepted that circumstellar outflows are important sources of IS silicates, and whether GEMS are processed or not, the circumstellar heritage of some has been rigorously confirmed through measurements of non-solar oxygen (O) isotope abundances (Messenger et al., 2003; Floss et al., 2006). Keller et al. (2000) assert that even GEMS without detectable O isotope anomalies are probably also extrasolar IS silicates because they are embedded in carbonaceous material with non-solar D/H isotopic composition. (Much of the silicate dust in the ISM may be isotopically homogenized (Zhukovska et al., 2007)). Recent measurements show that the elemental compositions of GEMS with non-solar isotopic compositions are 'remarkably similar' to those with solar isotopic compositions (Keller & Messenger, 2007). About 80% of all isotopically anomalous IS silicates identified to date are GEMS with detectable and variable O isotopic memories of a circumstellar ancestry (Messenger, 2007). Bradley (1999) proposed that GEMS are IS silicates from 'a presolar interstellar molecular cloud, presumably the local molecular cloud from which the solar system formed'. Although based on incorrect data (detailed below), Min et al. propose that most GEMS actually formed in the presolar molecular cloud, and they further propose that none of them are IS silicates. IS silicate sources include molecular clouds, circumstellar outflows, supernovae, and even recently discovered black hole winds (Molster & Waters; 2003; Jones, 2005; Zhukovska et al. 2007; Markwick-Kemper et al. 2007). The average IS 10 {micro}m extinction feature observed along lines of sight towards the galactic center (modeled by Min et al.) presumably provides a good average for IS silicates, but it cannot distinguish amorphous silicates originating in the presolar molecular cloud from amorphous silicates originating in other interstellar molecular clouds or indeed other sources of amorphous IS silicates. Even if most GEMS accreted in the presolar molecular cloud, then they must also be representatives of some portion of the IS amorphous silicate population. Laboratory heating experiments indicate it is highly unlikely that GEMS were modified in a protoplanetary accretion disk environment (Brownlee et al. 2005). In summary, Min et al. conclude from their modeling of the shape and composition of IS silicates that the properties of GEMS are generally inconsistent with those of IS silicates. First, it has been rigorously confirmed via ion microprobe measurements that some GEMS are indeed presolar IS silicates. Second, regardless of whether GEMS, or components of GEMS, originated in presolar circumstellar outflows or a presolar molecular cloud they are all IS silicates. Third, key GEMS data reported in Min et al. are inaccurate. Had complete isotopic, chemical, mineralogical and infrared (IR) spectral properties of GEMS been considered, Min et al. may have concluded that the properties of GEMS, although not an exact match, are generally consistent with those of amorphous silicates in the ISM.« less
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Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method
Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu
2016-01-01
A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis. PMID:28029121
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Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method.
Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu
2016-12-24
A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis.
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La Asociación OB Bochum7 combinando datos IR y ópticos
NASA Astrophysics Data System (ADS)
Corti, M. A.; Bosch, G. L.; Niemela, V. S.
We present the results of an analysis of IR data in the region of the galactic OB association Bo7, obtained from the archives of the IRAS satellite mission and the 2MASS survey. Bo7 is located at the end of Perseus spiral arm. Distances of possible members of the Bo7 association were determined calculating the absorption from the E(V-K) colour excess. These members had been previously selected according to their UBV colours and spectra. The distance values obtained with IR excess have a smaller error than those obtained considering the E(B-V) excess. An extended interstellar dust cloud (detected in IRAS maps) is found to be probably associated with the members of Bo7. Two IRAS point sources observed in the region have characteristics of star formation sites. One of these point sources has been observed in CS(2-1) by Bronfman et al. (1996), who determined a value of (LSR) velocity of 44 km/s, close to the velocity of stars in Bo7 (Corti et al. 2003). A group of main sequence O - B0.5 stars appear near the location of the aforementioned IRAS point source, suggesting sequential star formation in the Bo7 region.
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NASA Astrophysics Data System (ADS)
Sromovsky, L. A.; Baines, K. H.; Fry, P. M.
2018-03-01
A 5° latitude band on Saturn centered near planetocentric latitude 36°S is known as "Storm Alley" because it has been for several extended periods a site of frequent lightning activity and associated thunderstorms, first identified by Porco et al. (2005). The thunderstorms appeared as bright clouds at short and long continuum wavelengths, and over a period of a week or so transformed into dark ovals (Dyudina et al., 2007). The ovals were found to be dark over a wide spectral range, which led Baines et al. (2009) to suggest the possibility that a broadband absorber such as soot produced by lightning could play a significant role in darkening the clouds relative to their surroundings. Here we show that an alternative explanation, which is that the clouds are less reflective because of reduced optical depth, provides an excellent fit to near infrared spectra of similar features obtained by the Cassini Visual and Infrared Mapping Spectrometer (VIMS) in 2008, and leads to a plausible scenario for cloud evolution. We find that the background clouds and the oval clouds are both dominated by the optical properties of a ubiquitous upper cloud layer, which has the same particle size in both regions, but about half the optical depth and physical thickness in the dark oval regions. The dark oval regions are also marked by enhanced emissions in the 5-μm window region, a result of lower optical depth of the deep cloud layer near 3.1-3.8 bar, presumably composed of ammonium hydrosulfide (NH4SH). The bright storm clouds completely block this deep thermal emission with a thick layer of ammonia (NH3) clouds extending from the middle of the main visible cloud layer probably as deep as the 1.7-bar NH3 condensation level. Other condensates might also be present at higher pressures, but are obscured by the NH3 cloud. The strong 3-μm spectral absorption that was displayed by Saturn's Great Storm of 2010-2011 (Sromovsky et al., 2013) is weaker in these storms because the contrast is muted by the overlying cloud deck that these less intense storms do not fully penetrate. Our speculated evolutionary scenario that seems consistent with these results is that deep convection produces lightning and bright clouds of large ammonia particles that rise up into the mid level of the overlying visible deck, pushing out the particles in that layer with the outflow at the top of the convective towers. When the convective pulse subsides, these large particles fall out of the column within a week or so, leaving behind less optical depth than background clouds, making them appear darker because they are less reflective. However, this simple picture does not explain all details of the phenomenon, e.g. the irregular morphology of the bright convective regions and the stable regular shapes of the dark ovals that are formed in their wake.
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NASA Astrophysics Data System (ADS)
Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti
2016-04-01
Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the displacement fields. Displacement fields derived from both approaches are then combined and provide a better understanding of the landslide kinematics.
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Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval
NASA Astrophysics Data System (ADS)
Chen, Yi-Chen; Lin, Chao-Hung
2016-06-01
With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority over related methods.
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NASA Technical Reports Server (NTRS)
Starr, David OC.; Benedetti, Angela; Boehm, Matt; Brown, Philip R. A.; Gierens, Klaus M.; Girard, Eric; Giraud, Vincent; Jakob, Christian; Jensen, Eric; Khvorostyanov, Vitaly;
2000-01-01
The GEWEX Cloud System Study (GCSS, GEWEX is the Global Energy and Water Cycle Experiment) is a community activity aiming to promote development of improved cloud parameterizations for application in the large-scale general circulation models (GCMs) used for climate research and for numerical weather prediction (Browning et al, 1994). The GCSS strategy is founded upon the use of cloud-system models (CSMs). These are "process" models with sufficient spatial and temporal resolution to represent individual cloud elements, but spanning a wide range of space and time scales to enable statistical analysis of simulated cloud systems. GCSS also employs single-column versions of the parametric cloud models (SCMs) used in GCMs. GCSS has working groups on boundary-layer clouds, cirrus clouds, extratropical layer cloud systems, precipitating deep convective cloud systems, and polar clouds.
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Integration of Point Clouds Dataset from Different Sensors
NASA Astrophysics Data System (ADS)
Abdullah, C. K. A. F. Che Ku; Baharuddin, N. Z. S.; Ariff, M. F. M.; Majid, Z.; Lau, C. L.; Yusoff, A. R.; Idris, K. M.; Aspuri, A.
2017-02-01
Laser Scanner technology become an option in the process of collecting data nowadays. It is composed of Airborne Laser Scanner (ALS) and Terrestrial Laser Scanner (TLS). ALS like Phoenix AL3-32 can provide accurate information from the viewpoint of rooftop while TLS as Leica C10 can provide complete data for building facade. However if both are integrated, it is able to produce more accurate data. The focus of this study is to integrate both types of data acquisition of ALS and TLS and determine the accuracy of the data obtained. The final results acquired will be used to generate models of three-dimensional (3D) buildings. The scope of this study is focusing on data acquisition of UTM Eco-home through laser scanning methods such as ALS which scanning on the roof and the TLS which scanning on building façade. Both device is used to ensure that no part of the building that are not scanned. In data integration process, both are registered by the selected points among the manmade features which are clearly visible in Cyclone 7.3 software. The accuracy of integrated data is determined based on the accuracy assessment which is carried out using man-made registration methods. The result of integration process can achieve below 0.04m. This integrated data then are used to generate a 3D model of UTM Eco-home building using SketchUp software. In conclusion, the combination of the data acquisition integration between ALS and TLS would produce the accurate integrated data and able to use for generate a 3D model of UTM eco-home. For visualization purposes, the 3D building model which generated is prepared in Level of Detail 3 (LOD3) which recommended by City Geographic Mark-Up Language (CityGML).
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Single tree biomass modelling using airborne laser scanning
NASA Astrophysics Data System (ADS)
Kankare, Ville; Räty, Minna; Yu, Xiaowei; Holopainen, Markus; Vastaranta, Mikko; Kantola, Tuula; Hyyppä, Juha; Hyyppä, Hannu; Alho, Petteri; Viitala, Risto
2013-11-01
Accurate forest biomass mapping methods would provide the means for e.g. detecting bioenergy potential, biofuel and forest-bound carbon. The demand for practical biomass mapping methods at all forest levels is growing worldwide, and viable options are being developed. Airborne laser scanning (ALS) is a promising forest biomass mapping technique, due to its capability of measuring the three-dimensional forest vegetation structure. The objective of the study was to develop new methods for tree-level biomass estimation using metrics derived from ALS point clouds and to compare the results with field references collected using destructive sampling and with existing biomass models. The study area was located in Evo, southern Finland. ALS data was collected in 2009 with pulse density equalling approximately 10 pulses/m2. Linear models were developed for the following tree biomass components: total, stem wood, living branch and total canopy biomass. ALS-derived geometric and statistical point metrics were used as explanatory variables when creating the models. The total and stem biomass root mean square error per cents equalled 26.3% and 28.4% for Scots pine (Pinus sylvestris L.), and 36.8% and 27.6% for Norway spruce (Picea abies (L.) H. Karst.), respectively. The results showed that higher estimation accuracy for all biomass components can be achieved with models created in this study compared to existing allometric biomass models when ALS-derived height and diameter were used as input parameters. Best results were achieved when adding field-measured diameter and height as inputs in the existing biomass models. The only exceptions to this were the canopy and living branch biomass estimations for spruce. The achieved results are encouraging for the use of ALS-derived metrics in biomass mapping and for further development of the models.
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Star-Forming Clouds Feed, Churn, and Fall
NASA Astrophysics Data System (ADS)
Kohler, Susanna
2017-12-01
Molecular clouds, the birthplaces of stars in galaxies throughout the universe, are complicated and dynamic environments. A new series of simulations has explored how these clouds form, grow, and collapse over their lifetimes.This composite image shows part of the Taurus Molecular Cloud. [ESO/APEX (MPIfR/ESO/OSO)/A. Hacar et al./Digitized Sky Survey]Stellar BirthplacesMolecular clouds form out of the matter in between stars, evolving through constant interactions with their turbulent environments. These interactions taking the form of accretion flows and surface forces, while gravity, turbulence, and magnetic fields interplay are thought to drive the properties and evolution of the clouds.Our understanding of the details of this process, however, remains fuzzy. How does mass accretion affect these clouds as they evolve? What happens when nearby supernova explosions blast the outsides of the clouds? What makes the clouds churn, producing the motion within them that prevents them from collapsing? The answers to these questions can tellus about the gas distributed throughout galaxies, revealing information about the environments in which stars form.A still from the simulation results showing the broader population of molecular clouds that formed in the authors simulations, as well as zoom-in panels of three low-mass clouds tracked in high resolution. [Ibez-Meja et al. 2017]Models of TurbulenceIn a new study led by Juan Ibez-Meja (MPI Garching and Universities of Heidelberg and Cologne in Germany, and American Museum of Natural History), scientists have now explored these questions using a series of three-dimensional simulations of a population of molecular clouds forming and evolving in the turbulent interstellar medium.The simulations take into account a whole host of physics, including the effects of nearby supernova explosions, self-gravitation, magnetic fields, diffuse heating, and radiative cooling. After looking at the behavior of the broader population of clouds, the authors zoom in and explore three clouds in high-resolution to learn more about the details.Watching Clouds EvolveIbez-Meja and collaborators find that mass accretion occurring after the molecular clouds form plays an important role in the clouds evolution, increasing the mass available to form stars and carrying kinetic energy into the cloud. The accretion process is driven both by background turbulent flows and gravitational attraction as the cloud draws in the gas in its nearby environment.Plots of the cloud mass and radius (top) and mass accretion rate (bottom) for one of the three zoomed-in clouds, shown as a function of time over the 10-Myr simulation. [Adapted from Ibez-Meja et al. 2017]The simulations show that nearby supernovae have two opposing effects on a cloud. On one hand, the blast waves from supernovae compress the envelope of the cloud, increasing the instantaneous rate of accretion. On the other hand, the blast waves disrupt parts of the envelope and erode mass from the clouds surface, decreasing accretion overall. These events ensure that the mass accretion rate of molecular clouds is non-uniform, regularly punctuated by sporadic increases and decreases as the clouds are battered by nearby explosions.Lastly, Ibez-Meja and collaborators show that mass accretion alone isnt enough to power the turbulent internal motions we observe inside molecular clouds. Instead, they conclude, the cloud motions must be primarily powered by gravitational potential energy being converted into kinetic energy as the cloud contracts.The authors simulations therefore show that molecular clouds exist in a state of precarious balance, prevented from collapsing by internal turbulence driven by interactions with their environment and by their own contraction. These results give us an intriguing glimpse into the complex environments in which stars are born.BonusCheck out the animated figure below, which displays how the clouds in the authors simulations evolve over the span of 10 million years.http://cdn.iopscience.com/images/0004-637X/850/1/62/Full/apjaa93fef1_video.mp4CitationJuan C. Ibez-Meja et al 2017 ApJ 850 62. doi:10.3847/1538-4357/aa93fe
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NASA Astrophysics Data System (ADS)
Farrington, Robert; Connolly, Paul J.; Lloyd, Gary; Bower, Keith N.; Flynn, Michael J.; Gallagher, Martin W.; Field, Paul R.; Dearden, Chris; Choularton, Thomas W.; Hoyle, Chris
2016-04-01
At temperatures between -35°C and 0°C, the presence of insoluble aerosols acting as ice nuclei (IN) is the only way in which ice can nucleate under atmospheric conditions. Previous field and laboratory campaigns have suggested that mineral dust present in the atmosphere act as IN at temperatures warmer than -35°C (e.g. Sassen et al. 2003); however, the cause of ice nucleation at temperatures greater than -10°C is less certain. In-situ measurements of aerosol properties and cloud micro-physical processes are required to drive the improvement of aerosol-cloud processes in numerical models. As part of the Ice NUcleation Process Investigation and Quantification (INUPIAQ) project, two field campaigns were conducted in the winters of 2013 and 2014 (Lloyd et al. 2014). Both campaigns included measurements of cloud micro-physical properties at the summit of Jungfraujoch in Switzerland (3580m asl), using cloud probes, including the Two-Dimensional Stereo Hydrometeor Spectrometer (2D-S), the Cloud Particle Imager 3V (CPI-3V) and the Cloud Aerosol Spectrometer with Depolarization (CAS-DPOL). The first two of these probes measured significantly higher ice number concentrations than those observed in clouds at similar altitudes from aircraft. In this contribution, we assess the source of the high ice number concentrations observed by comparing in-situ measurements at Jungfraujoch with WRF simulations applied to the region around Jungfraujoch. During the 2014 field campaign the model simulations regularly simulated ice particle concentrations that were 3 orders of magnitude per litre less than the observed ice number concentration, even taking into account the aerosol properties measured upwind. WRF was used to investigate a number of potential sources of the high ice crystal concentrations, including: an increased ice nucleating particle (INP) concentration, secondary ice multiplication and the advection of surface ice or snow crystals into the clouds. It was found that the influence of these processes on the ice particle concentrations could not explain the observations. We also assessed whether the inclusion of a surface flux of hoar crystals into the WRF model could account for the increased ice concentrations in the orographic clouds found at Jungfraujoch. By including a simple parameterisation based on the surface wind speed, the inclusion of the surface crystal flux provided good agreement with the measurements at Jungfraujoch. A summary of these results will be presented at the meeting. References Lloyd, G., et al., 2015. The origins of ice crystals measured in mixed-phase clouds at the high-alpine site Jungfraujoch. Atmos. Chem. Phys., 15, 12953-12969. Sassen, K., et al., 2003. Saharan dust storms and indirect aerosol effects on clouds: Crystal-face results. Geophys. Res. Lett., 30, 1633-1636.
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MAVEN Mapping of Plasma Clouds Near Mars
NASA Astrophysics Data System (ADS)
Hurley, D.; Tran, T.; DiBraccio, G. A.; Espley, J. R.; Soobiah, Y. I. J.
2017-12-01
Brace et al. identified parcels of ionospheric plasma above the nominal ionosphere of Venus, dubbed plasma clouds. These were envisioned as instabilities on the ionopause that evolved to escaping parcels of ionospheric plasma. Mars Global Surveyor (MGS) Electron Reflectometer (ER) also detected signatures of ionospheric plasma above the nominal ionopause of Mars. Initial examination of the MGS ER data suggests that plasma clouds are more prevalent at Mars than at Venus, and similarly exhibit a connection to rotations in the upstream Interplanetary Magnetic Field (IMF) as Zhang et al. showed at Venus. We examine electron data from Mars to determine the locations of plasma clouds in the near-Mars environment using MGS and MAVEN data. The extensive coverage of the MAVEN orbit enables mapping an occurrence rate of the photoelectron spectra in Solar Wind Electron Analyzer (SWEA) data spanning all relevant altitudes and solar zenith angles. Martian plasma clouds are observed near the terminator like at Venus. They move to higher altitude as solar zenith angle increases, consistent with the escaping plasma hypothesis.
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NASA Astrophysics Data System (ADS)
Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.
2018-04-01
Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.
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Development of Data-Assimilation-Quality MODIS and MISR Over Ocean Aerosol Products
2009-08-01
fires to rainforests in order to clear land for agricultural purposes (Koren et al., 2004). During the Northern Hemisphere summer (June, July...atmosphere and dissipate clouds (Koren et al., 2004). Other studies have found that biomass-burning-generated aerosols over the Amazon basin could...Remer, and J. V. Martins, (2004), Measurement of the Effect of Amazon Smoke on Inhibition of Cloud Formation, Science 27 February 2004:Vol. 303. no
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Street curb recognition in 3d point cloud data using morphological operations
NASA Astrophysics Data System (ADS)
Rodríguez-Cuenca, Borja; Concepción Alonso-Rodríguez, María; García-Cortés, Silverio; Ordóñez, Celestino
2015-04-01
Accurate and automatic detection of cartographic-entities saves a great deal of time and money when creating and updating cartographic databases. The current trend in remote sensing feature extraction is to develop methods that are as automatic as possible. The aim is to develop algorithms that can obtain accurate results with the least possible human intervention in the process. Non-manual curb detection is an important issue in road maintenance, 3D urban modeling, and autonomous navigation fields. This paper is focused on the semi-automatic recognition of curbs and street boundaries using a 3D point cloud registered by a mobile laser scanner (MLS) system. This work is divided into four steps. First, a coordinate system transformation is carried out, moving from a global coordinate system to a local one. After that and in order to simplify the calculations involved in the procedure, a rasterization based on the projection of the measured point cloud on the XY plane was carried out, passing from the 3D original data to a 2D image. To determine the location of curbs in the image, different image processing techniques such as thresholding and morphological operations were applied. Finally, the upper and lower edges of curbs are detected by an unsupervised classification algorithm on the curvature and roughness of the points that represent curbs. The proposed method is valid in both straight and curved road sections and applicable both to laser scanner and stereo vision 3D data due to the independence of its scanning geometry. This method has been successfully tested with two datasets measured by different sensors. The first dataset corresponds to a point cloud measured by a TOPCON sensor in the Spanish town of Cudillero. That point cloud comprises more than 6,000,000 points and covers a 400-meter street. The second dataset corresponds to a point cloud measured by a RIEGL sensor in the Austrian town of Horn. That point cloud comprises 8,000,000 points and represents a 160-meter street. The proposed method provides success rates in curb recognition of over 85% in both datasets.
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NASA Technical Reports Server (NTRS)
Irwin, Patrick G. J.; Wong, Michael H.; Simon, Amy A.; Orton, G. S.; Toledo, Daniel
2017-01-01
In November 2014 Uranus was observed with the Wide Field Camera 3 (WFC3) instrument of the Hubble Space Telescope as part of the Hubble 2020: Outer Planet Atmospheres Legacy program, OPAL. OPAL annually maps Jupiter, Uranus and Neptune (and will also map Saturn from 2018) in several visible near- infrared wavelength filters. The Uranus 2014 OPAL observations were made on the 89th November at a time when a huge cloud complex, first observed by de Pater et al. (2015) and subsequently tracked by professional and amateur astronomers (Sayanagi et al., 2016), was present at 30-40deg N. We imaged the entire visible atmosphere, including the storm system, in seven filters spanning 467924 nm, capturing variations in the coloration of Uranus clouds and also vertical distribution due to wavelength dependent changes in Rayleigh scattering and methane absorption optical depth. Here we analyse these new HST observations with the NEMESIS radiative-transfer and retrieval code in multiple-scattering mode to determine the vertical cloud structure in and around the storm cloud system. The same storm system was also observed in the H-band (1.4-1.8 micrometers) with the SINFONI Integral Field Unit Spectrometer on the Very Large Telescope (VLT) on 31st October and 11th November, reported by Irwin et al. (2016, 10.1016j.icarus.2015.09.010). To constrain better the cloud particle sizes and scattering properties over a wide wavelength range we also conducted a limb-darkening analysis of the background cloud structure in the 30-40deg N latitude band by simultaneously fitting: a) these HSTOPAL observations at a range of zenith angles; b) the VLTSINFONI observations at a range of zenith angles; and c) IRTFSpeX observations of this latitude band made in 2009 at a single zenith angle of 23deg, spanning the wavelength range 0.8-1.8 micrometers (Irwin et al., 2015, 10.1016j.icarus.2014.12.020). We find that the HST observations, and the combined HSTVLTIRTF observations at all locations are well modelled with a three-component cloud comprised of: 1) a vertically thin, but optically thick deep tropospheric cloud at a pressure of approximately 2 bars; 2) a methane-ice cloud based at the methane-condensation level of approximately 1.23 bar, with variable vertical extent; and 3) a vertically extended tropospheric haze, also based at the methane-condensation level of 1.23 bar. We find that modelling both haze and tropospheric cloud with particles having an effective radius of approximately 0.1 micron provides a good fit the observations, although for the tropospheric cloud, particles with an effective radius as large as 1.0 micron provide a similarly good fit. We find that the particles in both the tropospheric cloud and haze are more scattering at short wave- lengths, giving them a blue color, but are more absorbing at longer wavelengths, especially for the tropospheric haze. We find that the spectra of the storm clouds are well modelled by localized thickening and vertical extension of the methane-ice cloud. For the particles in the storm clouds, which we assume to be composed of methane ice particles, we find that their mean radii must lie somewhere in the range 0. 1 1. 0 m. We find that the high clouds have low integrated opacity, and that streamers reminiscent of convective thunderstorm anvils are confined to levels deeper than 1 bar. These results argue against vigorous moist convective origins for the cloud features.
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3D reconstruction from non-uniform point clouds via local hierarchical clustering
NASA Astrophysics Data System (ADS)
Yang, Jiaqi; Li, Ruibo; Xiao, Yang; Cao, Zhiguo
2017-07-01
Raw scanned 3D point clouds are usually irregularly distributed due to the essential shortcomings of laser sensors, which therefore poses a great challenge for high-quality 3D surface reconstruction. This paper tackles this problem by proposing a local hierarchical clustering (LHC) method to improve the consistency of point distribution. Specifically, LHC consists of two steps: 1) adaptive octree-based decomposition of 3D space, and 2) hierarchical clustering. The former aims at reducing the computational complexity and the latter transforms the non-uniform point set into uniform one. Experimental results on real-world scanned point clouds validate the effectiveness of our method from both qualitative and quantitative aspects.
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Applications of low altitude photogrammetry for morphometry, displacements, and landform modeling
NASA Astrophysics Data System (ADS)
Gomez, F. G.; Polun, S. G.; Hickcox, K.; Miles, C.; Delisle, C.; Beem, J. R.
2016-12-01
Low-altitude aerial surveying is emerging as a tool that greatly improves the ease and efficiency of measuring landforms for quantitative geomorphic analyses. High-resolution, close-range photogrammetry produces dense, 3-dimensional point clouds that facilitate the construction of digital surface models, as well as a potential means of classifying ground targets using spatial structure. This study presents results from recent applications of UAS-based photogrammetry, including high resolution surface morphometry of a lava flow, repeat-pass applications to mass movements, and fault scarp degradation modeling. Depending upon the desired photographic resolution and the platform/payload flown, aerial photos are typically acquired at altitudes of 40 - 100 meters above the ground surface. In all cases, high-precision ground control points are key for accurate (and repeatable) orientation - relying on low-precision GPS coordinates (whether on the ground or geotags in the aerial photos) typically results in substantial rotations (tilt) of the reference frame. Using common ground control points between repeat surveys results in matching point clouds with RMS residuals better than 10 cm. In arid regions, the point cloud is used to assess lava flow surface roughness using multi-scale measurements of point cloud dimensionality. For the landslide study, the point cloud provides a basis for assessing possible displacements. In addition, the high resolution orthophotos facilitate mapping of fractures and their growth. For neotectonic applications, we compare fault scarp modeling results from UAV-derived point clouds versus field-based surveys (kinematic GPS and electronic distance measurements). In summary, there is a wide ranging toolbox of low-altitude aerial platforms becoming available for field geoscientists. In many instances, these tools will present convenience and reduced cost compared with the effort and expense to contract acquisitions of aerial imagery.
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SEMANTIC3D.NET: a New Large-Scale Point Cloud Classification Benchmark
NASA Astrophysics Data System (ADS)
Hackel, T.; Savinov, N.; Ladicky, L.; Wegner, J. D.; Schindler, K.; Pollefeys, M.
2017-05-01
This paper presents a new 3D point cloud classification benchmark data set with over four billion manually labelled points, meant as input for data-hungry (deep) learning methods. We also discuss first submissions to the benchmark that use deep convolutional neural networks (CNNs) as a work horse, which already show remarkable performance improvements over state-of-the-art. CNNs have become the de-facto standard for many tasks in computer vision and machine learning like semantic segmentation or object detection in images, but have no yet led to a true breakthrough for 3D point cloud labelling tasks due to lack of training data. With the massive data set presented in this paper, we aim at closing this data gap to help unleash the full potential of deep learning methods for 3D labelling tasks. Our semantic3D.net data set consists of dense point clouds acquired with static terrestrial laser scanners. It contains 8 semantic classes and covers a wide range of urban outdoor scenes: churches, streets, railroad tracks, squares, villages, soccer fields and castles. We describe our labelling interface and show that our data set provides more dense and complete point clouds with much higher overall number of labelled points compared to those already available to the research community. We further provide baseline method descriptions and comparison between methods submitted to our online system. We hope semantic3D.net will pave the way for deep learning methods in 3D point cloud labelling to learn richer, more general 3D representations, and first submissions after only a few months indicate that this might indeed be the case.
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Cloud Security: Issues and Research Directions
2014-11-18
4. Cloud Computing Security: What Changes with Software - Defined Networking ? Maur´ıcio Tsugawa, Andr´ea Matsunaga, and Jos´e A. B. Fortes 5...machine’s memory from an untrusted or malicious hypervisor. In Chapter 4, Tsugawa et al. discuss the security issues introduced when Software - Defined ... Networking ( SDN ) is deployed within and across clouds. Chapters 5-9 are focused on the protection of data stored in the cloud. In Chapter 5, Wang et
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NASA Technical Reports Server (NTRS)
Rosen, James M.; Hofmann, D. J.; Carpenter, J. R.; Harder, J. W.; Oltmans, S. J.
1988-01-01
The first balloon-borne frost point measurements over Antarctica were made during September and October, 1987 as part of the NOZE 2 effort at McMurdo. The results indicate water vapor mixing ratios on the order of 2 ppmv in the 15 to 20 km region which is somewhat smaller than the typical values currently being used significantly smaller than the typical values currently being used in polar stratospheric cloud (PSC) theories. The observed water vapor mixing ratio would correspond to saturated conditions for what is thought to be the lowest stratospheric temperatures encountered over the Antarctic. Through the use of available lidar observations there appears to be significant evidence that some PSCs form at temperatures higher than the local frost point (with respect to water) in the 10 to 20 km region thus supporting the nitric acid theory of PSC composition. Clouds near 15 km and below appear to form in regions saturated with respect to water and thus are probably mostly ice water clouds although they could contain relatively small amounts of other constituents. Photographic evidence suggests that the clouds forming above the frost point probably have an appearance quite different from the lower altitude iridescent, colored nacreous clouds.
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An approach of point cloud denoising based on improved bilateral filtering
NASA Astrophysics Data System (ADS)
Zheng, Zeling; Jia, Songmin; Zhang, Guoliang; Li, Xiuzhi; Zhang, Xiangyin
2018-04-01
An omnidirectional mobile platform is designed for building point cloud based on an improved filtering algorithm which is employed to handle the depth image. First, the mobile platform can move flexibly and the control interface is convenient to control. Then, because the traditional bilateral filtering algorithm is time-consuming and inefficient, a novel method is proposed which called local bilateral filtering (LBF). LBF is applied to process depth image obtained by the Kinect sensor. The results show that the effect of removing noise is improved comparing with the bilateral filtering. In the condition of off-line, the color images and processed images are used to build point clouds. Finally, experimental results demonstrate that our method improves the speed of processing time of depth image and the effect of point cloud which has been built.
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Point cloud modeling using the homogeneous transformation for non-cooperative pose estimation
NASA Astrophysics Data System (ADS)
Lim, Tae W.
2015-06-01
A modeling process to simulate point cloud range data that a lidar (light detection and ranging) sensor produces is presented in this paper in order to support the development of non-cooperative pose (relative attitude and position) estimation approaches which will help improve proximity operation capabilities between two adjacent vehicles. The algorithms in the modeling process were based on the homogeneous transformation, which has been employed extensively in robotics and computer graphics, as well as in recently developed pose estimation algorithms. Using a flash lidar in a laboratory testing environment, point cloud data of a test article was simulated and compared against the measured point cloud data. The simulated and measured data sets match closely, validating the modeling process. The modeling capability enables close examination of the characteristics of point cloud images of an object as it undergoes various translational and rotational motions. Relevant characteristics that will be crucial in non-cooperative pose estimation were identified such as shift, shadowing, perspective projection, jagged edges, and differential point cloud density. These characteristics will have to be considered in developing effective non-cooperative pose estimation algorithms. The modeling capability will allow extensive non-cooperative pose estimation performance simulations prior to field testing, saving development cost and providing performance metrics of the pose estimation concepts and algorithms under evaluation. The modeling process also provides "truth" pose of the test objects with respect to the sensor frame so that the pose estimation error can be quantified.
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Quality Assessment and Comparison of Smartphone and Leica C10 Laser Scanner Based Point Clouds
NASA Astrophysics Data System (ADS)
Sirmacek, Beril; Lindenbergh, Roderik; Wang, Jinhu
2016-06-01
3D urban models are valuable for urban map generation, environment monitoring, safety planning and educational purposes. For 3D measurement of urban structures, generally airborne laser scanning sensors or multi-view satellite images are used as a data source. However, close-range sensors (such as terrestrial laser scanners) and low cost cameras (which can generate point clouds based on photogrammetry) can provide denser sampling of 3D surface geometry. Unfortunately, terrestrial laser scanning sensors are expensive and trained persons are needed to use them for point cloud acquisition. A potential effective 3D modelling can be generated based on a low cost smartphone sensor. Herein, we show examples of using smartphone camera images to generate 3D models of urban structures. We compare a smartphone based 3D model of an example structure with a terrestrial laser scanning point cloud of the structure. This comparison gives us opportunity to discuss the differences in terms of geometrical correctness, as well as the advantages, disadvantages and limitations in data acquisition and processing. We also discuss how smartphone based point clouds can help to solve further problems with 3D urban model generation in a practical way. We show that terrestrial laser scanning point clouds which do not have color information can be colored using smartphones. The experiments, discussions and scientific findings might be insightful for the future studies in fast, easy and low-cost 3D urban model generation field.
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Knowledge-Based Object Detection in Laser Scanning Point Clouds
NASA Astrophysics Data System (ADS)
Boochs, F.; Karmacharya, A.; Marbs, A.
2012-07-01
Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.
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Stratus Cloud Radiative Effects from Cloud Processed Bimodal CCN Distributions
NASA Astrophysics Data System (ADS)
Noble, S. R., Jr.; Hudson, J. G.
2016-12-01
Inability to understand cloud processes is a large component of climate uncertainty. Increases in cloud condensation nuclei (CCN) concentrations are known to increase cloud droplet number concentrations (Nc). This aerosol-cloud interaction (ACI) produces greater Nc at smaller sizes, which brightens clouds. A lesser understood ACI is cloud processing of CCN. This improves CCN that then more easily activate at lower cloud supersaturations (S). Bimodal CCN distributions thus ensue from these evaporated cloud droplets. Hudson et al. (2015) related CCN bimodality to Nc. In stratus clouds, bimodal CCN created greater Nc whereas in cumulus less Nc. Thus, CCN distribution shape influences cloud properties; microphysics and radiative properties. Measured uni- and bimodal CCN distributions were input into an adiabatic droplet growth model using various specified vertical wind speeds (W). Bimodal CCN produced greater Nc (Fig. 1a) and smaller mean diameters (MD; Fig. 1b) at lower W typical of stratus clouds (<70 cm/s). Improved CCN (low critical S) were more easily activated at the lower S of stratus from low W, thus, creating greater Nc. Competition for condensate thus reduced MD and drizzle. At greater W, typical of cumulus clouds (>70 cm/s), bimodal CCN made lower Nc with larger MD thus enhancing drizzle whereas unimodal CCN made greater Nc with smaller MD, thus reducing drizzle. Thus, theoretical predictions of Nc and MD for uni- and bimodal CCN agree with the sense of the observations. Radiative effects were determined using a cloud grown to a 250-meter thickness. Bimodal CCN at low W reduced cloud effective radius (re), made greater cloud optical thickness (COT), and made greater cloud albedo (Fig. 1c). At very low W changes were as much as +9% for albedo, +17% for COT, and -12% for re. Stratus clouds typically have low W and cover large areas. Thus, these changes in cloud radiative properties at low W impact climate. Stratus cloud susceptibility to CCN distribution thus requires further investigation to determine their impact on ACI. Hudson et al. (2015), JGRA, 120, 3436-3452.
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New Developments in the SCIAMACHY Level 2 Ground Processor Towards Version 7
NASA Astrophysics Data System (ADS)
Meringer, Markus; Noël, Stefan; Lichtenberg, Günter; Lerot, Christophe; Theys, Nicolas; Fehr, Thorsten; Dehn, Angelika; Liebing, Patricia; Gretschany, Sergei
2016-07-01
SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric ChartographY) aboard ESA's environmental satellite ENVISAT observed the Earth's atmosphere in limb, nadir, and solar/lunar occultation geometries covering the UV-Visible to NIR spectral range. It is a joint project of Germany, the Netherlands and Belgium and was launched in February 2002. SCIAMACHY doubled its originally planned in-orbit lifetime of five years before the communication to ENVISAT was severed in April 2012, and the mission entered its post-operational phase. In order to preserve the best quality of the outstanding data recorded by SCIAMACHY, data processors are still being updated. This presentation will highlight three new developments that are currently being incorporated into the forthcoming version 7 of ESA's operational level 2 processor: 1. Tropospheric BrO, a new retrieval based on the scientific algorithm of (Theys et al., 2011). This algorithm had originally been developed for the GOME-2 sensor and was later adapted for SCIAMACHY. The main principle of the new algorithm is to split BrO total columns, which are already an operational product, into stratospheric VCD_{strat} and tropospheric VCD_{trop} fractions. BrO VCD_{strat} is determined from a climatological approach, driven by SCIAMACHY O_3 and NO_2 observations. Tropospheric vertical column densities are then determined as difference VCD_{trop}=VCD_{total}-VCD_{strat}. 2. Improved cloud flagging using limb measurements (Liebing, 2015). Limb cloud flags are already part of the SCIAMACHY L2 product. They are currently calculated employing the scientific algorithm developed by (Eichmann et al., 2015). Clouds are categorized into four types: water, ice, polar stratospheric and noctilucent clouds. High atmospheric aerosol loadings, however, often lead to spurious cloud flags, when aerosols had been misidentified as clouds. The new algorithm will better discriminate between aerosol and clouds. It will also have a higher sensitivity w.r.t. thin clouds. 3. A new, future-proof file format for the level 2 product based on NetCDF. The data format will be aligned and harmonized with other missions, particularly GOME and Sentinels. The final concept for the new format is still under discussion within the SCIAMACHY Quality Working Group. References: K.-U. Eichmann et al.: Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results, Atmos. Meas. Tech. Discuss., 8, 8295-8352, 2015. P. Liebing: New Limb Cloud Detection Algorithm Theoretical Basis Document, 2016. N. Theys et al.: Global observations of tropospheric BrO columns using GOME-2 satellite data, Atmos. Chem. Phys., 11, 1791-1811, 2011.
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NASA Astrophysics Data System (ADS)
Rutzinger, Martin; Bremer, Magnus; Ragg, Hansjörg
2013-04-01
Recently, terrestrial laser scanning (TLS) and matching of images acquired by unmanned arial vehicles (UAV) are operationally used for 3D geodata acquisition in Geoscience applications. However, the two systems cover different application domains in terms of acquisition conditions and data properties i.e. accuracy and line of sight. In this study we investigate the major differences between the two platforms for terrain roughness estimation. Terrain roughness is an important input for various applications such as morphometry studies, geomorphologic mapping, and natural process modeling (e.g. rockfall, avalanche, and hydraulic modeling). Data has been collected simultaneously by TLS using an Optech ILRIS3D and a rotary UAV using an octocopter from twins.nrn for a 900 m² test site located in a riverbed in Tyrol, Austria (Judenbach, Mieming). The TLS point cloud has been acquired from three scan positions. These have been registered using iterative closest point algorithm and a target-based referencing approach. For registration geometric targets (spheres) with a diameter of 20 cm were used. These targets were measured with dGPS for absolute georeferencing. The TLS point cloud has an average point density of 19,000 pts/m², which represents a point spacing of about 5 mm. 15 images where acquired by UAV in a height of 20 m using a calibrated camera with focal length of 18.3 mm. A 3D point cloud containing RGB attributes was derived using APERO/MICMAC software, by a direct georeferencing approach based on the aircraft IMU data. The point cloud is finally co-registered with the TLS data to guarantee an optimal preparation in order to perform the analysis. The UAV point cloud has an average point density of 17,500 pts/m², which represents a point spacing of 7.5 mm. After registration and georeferencing the level of detail of roughness representation in both point clouds have been compared considering elevation differences, roughness and representation of different grain sizes. UAV closes the gap between aerial and terrestrial surveys in terms of resolution and acquisition flexibility. This is also true for the data accuracy. Considering these data collection and data quality properties of both systems they have their merit on its own in terms of scale, data quality, data collection speed and application.
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Io's Sodium Clouds and Plasma Torus: Three Quiet Apparitions
NASA Astrophysics Data System (ADS)
Wilson, Jody; Mendillo, M.; Baumgardner, J.
2007-10-01
Ground-based observations of Io's sodium clouds from February 2005 to June 2007 indicate that Io was in an unusually quiet state of atmospheric escape. Simultaneous observations of the sulfur-ion plasma torus in that same period indicate that the torus has been gradually dimming, which is also consistent with below-average atmospheric escape rates from Io. The S+ torus was essentially undetectable in May 2007. Our goal in this 3-year project was to compare variability in the clouds and torus with observations of Io's volcanic infrared ``hot spots'' (e.g., Marchis et al. 2005) in order to track the flow of mass from Io's volcanoes into Jupiter's magnetosphere. Of particular interest was the 18-month cycle of Io's large volcano Loki (Rathbun et al. 2002, Mendillo et al. 2004), however it seems that Loki has settled into an unusually long-term quiescent state (Rathbun and Spencer, 2006). Thus, although we have been unable to monitor the month-to-month effects of the Loki cycle, we nonetheless have indirect evidence for Loki's long-term effects on Io's atmosphere and Jupiter's magnetosphere by observing their weak states when Loki is not actively contributing. This research is funded in part by NASA's Planetary Astronomy Program. Marchis et al., Keck AO survey of Io global volcanic activity between 2 and 5 microns, Icarus, 176, 96-122, 2005. Mendillo et al., Io's volcanic control of Jupiter's extended neutral clouds, Icarus, 170, 430-442, 2004. Rathbun, J.A. et al., Loki, Io: A periodic volcano, Geophysical Research Letters, 29, Issue 10, pp. 84-1, 2002. Rathbun, J.A. and J.R. Spencer, Loki, Io: New ground-based observations and a model describing the change from periodic overturn, Geophysical Research Letters, 33, Issue 17, 2006.
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Point Cloud Based Relative Pose Estimation of a Satellite in Close Range
Liu, Lujiang; Zhao, Gaopeng; Bo, Yuming
2016-01-01
Determination of the relative pose of satellites is essential in space rendezvous operations and on-orbit servicing missions. The key problems are the adoption of suitable sensor on board of a chaser and efficient techniques for pose estimation. This paper aims to estimate the pose of a target satellite in close range on the basis of its known model by using point cloud data generated by a flash LIDAR sensor. A novel model based pose estimation method is proposed; it includes a fast and reliable pose initial acquisition method based on global optimal searching by processing the dense point cloud data directly, and a pose tracking method based on Iterative Closest Point algorithm. Also, a simulation system is presented in this paper in order to evaluate the performance of the sensor and generate simulated sensor point cloud data. It also provides truth pose of the test target so that the pose estimation error can be quantified. To investigate the effectiveness of the proposed approach and achievable pose accuracy, numerical simulation experiments are performed; results demonstrate algorithm capability of operating with point cloud directly and large pose variations. Also, a field testing experiment is conducted and results show that the proposed method is effective. PMID:27271633
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NASA Astrophysics Data System (ADS)
Budge, Scott E.; Badamikar, Neeraj S.; Xie, Xuan
2015-03-01
Several photogrammetry-based methods have been proposed that the derive three-dimensional (3-D) information from digital images from different perspectives, and lidar-based methods have been proposed that merge lidar point clouds and texture the merged point clouds with digital imagery. Image registration alone has difficulty with smooth regions with low contrast, whereas point cloud merging alone has difficulty with outliers and a lack of proper convergence in the merging process. This paper presents a method to create 3-D images that uses the unique properties of texel images (pixel-fused lidar and digital imagery) to improve the quality and robustness of fused 3-D images. The proposed method uses both image processing and point-cloud merging to combine texel images in an iterative technique. Since the digital image pixels and the lidar 3-D points are fused at the sensor level, more accurate 3-D images are generated because registration of image data automatically improves the merging of the point clouds, and vice versa. Examples illustrate the value of this method over other methods. The proposed method also includes modifications for the situation where an estimate of position and attitude of the sensor is known, when obtained from low-cost global positioning systems and inertial measurement units sensors.
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NASA Astrophysics Data System (ADS)
Ma, Hongchao; Cai, Zhan; Zhang, Liang
2018-01-01
This paper discusses airborne light detection and ranging (LiDAR) point cloud filtering (a binary classification problem) from the machine learning point of view. We compared three supervised classifiers for point cloud filtering, namely, Adaptive Boosting, support vector machine, and random forest (RF). Nineteen features were generated from raw LiDAR point cloud based on height and other geometric information within a given neighborhood. The test datasets issued by the International Society for Photogrammetry and Remote Sensing (ISPRS) were used to evaluate the performance of the three filtering algorithms; RF showed the best results with an average total error of 5.50%. The paper also makes tentative exploration in the application of transfer learning theory to point cloud filtering, which has not been introduced into the LiDAR field to the authors' knowledge. We performed filtering of three datasets from real projects carried out in China with RF models constructed by learning from the 15 ISPRS datasets and then transferred with little to no change of the parameters. Reliable results were achieved, especially in rural area (overall accuracy achieved 95.64%), indicating the feasibility of model transfer in the context of point cloud filtering for both easy automation and acceptable accuracy.
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Large Scale Ice Water Path and 3-D Ice Water Content
Liu, Guosheng
2008-01-15
Cloud ice water concentration is one of the most important, yet poorly observed, cloud properties. Developing physical parameterizations used in general circulation models through single-column modeling is one of the key foci of the ARM program. In addition to the vertical profiles of temperature, water vapor and condensed water at the model grids, large-scale horizontal advective tendencies of these variables are also required as forcing terms in the single-column models. Observed horizontal advection of condensed water has not been available because the radar/lidar/radiometer observations at the ARM site are single-point measurement, therefore, do not provide horizontal distribution of condensed water. The intention of this product is to provide large-scale distribution of cloud ice water by merging available surface and satellite measurements. The satellite cloud ice water algorithm uses ARM ground-based measurements as baseline, produces datasets for 3-D cloud ice water distributions in a 10 deg x 10 deg area near ARM site. The approach of the study is to expand a (surface) point measurement to an (satellite) areal measurement. That is, this study takes the advantage of the high quality cloud measurements at the point of ARM site. We use the cloud characteristics derived from the point measurement to guide/constrain satellite retrieval, then use the satellite algorithm to derive the cloud ice water distributions within an area, i.e., 10 deg x 10 deg centered at ARM site.
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Coarse Point Cloud Registration by Egi Matching of Voxel Clusters
NASA Astrophysics Data System (ADS)
Wang, Jinhu; Lindenbergh, Roderik; Shen, Yueqian; Menenti, Massimo
2016-06-01
Laser scanning samples the surface geometry of objects efficiently and records versatile information as point clouds. However, often more scans are required to fully cover a scene. Therefore, a registration step is required that transforms the different scans into a common coordinate system. The registration of point clouds is usually conducted in two steps, i.e. coarse registration followed by fine registration. In this study an automatic marker-free coarse registration method for pair-wise scans is presented. First the two input point clouds are re-sampled as voxels and dimensionality features of the voxels are determined by principal component analysis (PCA). Then voxel cells with the same dimensionality are clustered. Next, the Extended Gaussian Image (EGI) descriptor of those voxel clusters are constructed using significant eigenvectors of each voxel in the cluster. Correspondences between clusters in source and target data are obtained according to the similarity between their EGI descriptors. The random sampling consensus (RANSAC) algorithm is employed to remove outlying correspondences until a coarse alignment is obtained. If necessary, a fine registration is performed in a final step. This new method is illustrated on scan data sampling two indoor scenarios. The results of the tests are evaluated by computing the point to point distance between the two input point clouds. The presented two tests resulted in mean distances of 7.6 mm and 9.5 mm respectively, which are adequate for fine registration.
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A physically-based approach of treating dust-water cloud interactions in climate models
NASA Astrophysics Data System (ADS)
Kumar, P.; Karydis, V.; Barahona, D.; Sokolik, I. N.; Nenes, A.
2011-12-01
All aerosol-cloud-climate assessment studies to date assume that the ability of dust (and other insoluble species) to act as a Cloud Condensation Nuclei (CCN) is determined solely by their dry size and amount of soluble material. Recent evidence however clearly shows that dust can act as efficient CCN (even if lacking appreciable amounts of soluble material) through adsorption of water vapor onto the surface of the particle. This "inherent" CCN activity is augmented as the dust accumulates soluble material through atmospheric aging. A comprehensive treatment of dust-cloud interactions therefore requires including both of these sources of CCN activity in atmospheric models. This study presents a "unified" theory of CCN activity that considers both effects of adsorption and solute. The theory is corroborated and constrained with experiments of CCN activity of mineral aerosols generated from clays, calcite, quartz, dry lake beds and desert soil samples from Northern Africa, East Asia/China, and Northern America. The unified activation theory then is included within the mechanistic droplet activation parameterization of Kumar et al. (2009) (including the giant CCN correction of Barahona et al., 2010), for a comprehensive treatment of dust impacts on global CCN and cloud droplet number. The parameterization is demonstrated with the NASA Global Modeling Initiative (GMI) Chemical Transport Model using wind fields computed with the Goddard Institute for Space Studies (GISS) general circulation model. References Barahona, D. et al. (2010) Comprehensively Accounting for the Effect of Giant CCN in Cloud Activation Parameterizations, Atmos.Chem.Phys., 10, 2467-2473 Kumar, P., I.N. Sokolik, and A. Nenes (2009), Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN, Atmos.Chem.Phys., 9, 2517- 2532
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NASA Astrophysics Data System (ADS)
Jethva, H. T.; Torres, O.; Waquet, F.; Chand, D.
2013-12-01
Atmospheric aerosols are known to produce a net cooling effect in the cloud-free conditions. However, when present over the reflective cloud decks, absorbing aerosols such as biomass burning generated smoke and wind-blown dust can potentially exert a large positive forcing through enhanced atmospheric heating resulting from cloud-aerosol radiative interactions. The interest on this aspect of aerosol science has grown significantly in the recent years. Particularly, development of the satellite-based retrieval techniques and unprecedented knowledge on the above-cloud aerosol optical depth (ACAOD) is of great relevance. A direct validation of satellite ACAOD is a difficult task primarily due to lack of ample in situ and/or remote sensing measurements of aerosols above cloud. In these circumstances, a comparative analysis on the inter-satellite ACAOD retrievals can be performed for the sack of consistency check. Here, we inter-compare the ACAOD of biomass burning plumes observed from different A-train sensors, i.e., MODIS [Jethva et al., 2013], CALIOP [Chand et al., 2008], POLDER [Waquet et al., 2009], and OMI [Torres et al., 2012]. These sensors have been shown to acquire sensitivity and independent capabilities to detect and retrieve aerosol loading above marine stratocumulus clouds--a kind of situation often found over the southeastern Atlantic Ocean during dry burning season. A systematic one-to-one comparison reveals that, in general, all passive sensors and CALIOP-based research methods retrieve comparable ACAOD over homogeneous cloud fields. The high-resolution sensors (MODIS and CALIOP) are able to retrieve aerosols over thin clouds but with larger discrepancies. Given the different types of sensor measurements processed with different algorithms, a reasonable agreement between them is encouraging. A direct validation of satellite-based ACAOD remains an open challenge for which dedicated field measurements over the region of frequent aerosol/cloud overlap are a prime requirement. Jethva, H., O. Torres, L. A. Remer, P. K. Bhartia (2013), A Color Ratio Method for Simultaneous Retrieval of Aerosol and Cloud Optical Thickness of Above-Cloud Absorbing Aerosols From Passive Sensors: Application to MODIS Measurements, Geoscience and Remote Sensing, IEEE Transactions on, 51(7), pp. 3862-3870, doi: 10.1109/TGRS.2012.2230008. Chand, D., T. L. Anderson, R. Wood, R. J. Charlson, Y. Hu, Z. Liu, and M. Vaughan (2008), Quantifying above-cloud aerosol using spaceborne lidar for improved understanding of cloudy-sky direct climate forcing, J. Geophys. Res., 113, D13206, doi:10.1029/2007JD009433. Waquet, F., J. Riedi, L. C. Labonnote, P. Goloub, B. Cairns, J.-L. Deuzeand, and D. Tanre (2009), Aerosol remote sensing over clouds using a-train observations, J. Atmos. Sci., 66(8), 2468-2480, doi: http://dx.doi.org/10.1175/2009JAS3026.1 Torres, O., H. Jethva, and P. K. Bhartia (2012), Retrieval of aerosol optical depth above clouds from OMI observations: Sensitivity analysis and case studies, J. Atmos. Sci., 69(3), 1037-1053, doi: http://dx.doi.org/10.1175/JAS-D-11-0130.
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Satellite Imagery Analysis for Nighttime Temperature Inversion Clouds
NASA Technical Reports Server (NTRS)
Kawamoto, K.; Minnis, P.; Arduini, R.; Smith, W., Jr.
2001-01-01
Clouds play important roles in the climate system. Their optical and microphysical properties, which largely determine their radiative property, need to be investigated. Among several measurement means, satellite remote sensing seems to be the most promising. Since most of the cloud algorithms proposed so far are daytime use which utilizes solar radiation, Minnis et al. (1998) developed a nighttime use one using 3.7-, 11 - and 12-microns channels. Their algorithm, however, has a drawback that is not able to treat temperature inversion cases. We update their algorithm, incorporating new parameterization by Arduini et al. (1999) which is valid for temperature inversion cases. This updated algorithm has been applied to GOES satellite data and reasonable retrieval results were obtained.
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NASA Astrophysics Data System (ADS)
Ovadnevaite, Jurgita; Fossum, Kirsten; Ceburnis, Darius; Dall'Osto, Manuel; Simo, Rafel; O'Dowd, Colin
2016-04-01
Marine aerosol occurring in cloud condensation nucleus (CCN) sizes suggest that it may contribute notably to the CCN population [1, 2], but further cloud droplet number concentration would strongly depend on the ambient (cloud) conditions, such as available water content, supersaturation and competition between the CCN of different composition [3]. Since the global importance of marine aerosol particles to the cloud formation was postulated several decades ago [4], it has progressed from the evaluation of the nss-sulphate and sea salt effects to an acknowledgement of the significant role of organic aerosol [5]. It was demonstrated that primary marine organics, despite its hydrophobic nature, can possess the high CCN activation efficiency, resulting in the efficient cloud formation [6]. Results from two intensive measurement campaigns in The Eastern North Atlantic (Mace Head) and The Southern Ocean (PEGASO cruise) is presented here with the main focus on ssCCN dependence on aerosol chemical composition and, especially, origin and sources of marine organic. We investigate the activation of sea spray composed of the sea salt and externally mixed with nss-sulphate as well as the sea spray highly enriched in organics, stressing the importance of the latter to the formation of the cloud droplets. We also explore the suitability of existing theories to explain the marine aerosol activation to CCN. Acknowledgments The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) project BACCHUS under grant agreement n° 603445; Spanish Ministry of Economy and Competitiveness (MINECO) as part of the PEGASO (Ref.: CTM2012-37615) and BIO-NUC (Ref.: CGL2013-49020-R); HEA-PRTLI4;EC ACTRIS. [1] Meskhidze & Nenes (2006) Science 314, 1419-1423. [2] Sorooshian et al. (2009) Global Biogeochemical Cycles 23, GB4007. [3] O'Dowd et al. (1999) Quarterly Journal of the Royal Meteorological Society 125, 1295-1313. [4] Charlson et al. (1987) Nature 326, 655-661. [5] O'Dowd et al. (2004) Nature 431, 676-680. [6] Ovadnevaite et al. (2011) Geophysical Research Letters 38, L21806.
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NASA Astrophysics Data System (ADS)
Pepe, M.; Ackermann, S.; Fregonese, L.; Achille, C.
2017-02-01
The paper describes a method for Point Clouds Color management and Integration obtained from Terrestrial Laser Scanner (TLS) and Image Based (IB) survey techniques. Especially in the Cultural Heritage (CH) environment, methods and techniques to improve the color quality of Point Clouds have a key role because a homogenous texture brings to a more accurate reconstruction of the investigated object and to a more pleasant perception of the color object as well. A color management method for point clouds can be useful in case of single data set acquired by TLS or IB technique as well as in case of chromatic heterogeneity resulting by merging different datasets. The latter condition can occur when the scans are acquired in different moments of the same day or when scans of the same object are performed in a period of weeks or months, and consequently with a different environment/lighting condition. In this paper, a procedure to balance the point cloud color in order to uniform the different data sets, to improve the chromatic quality and to highlight further details will be presented and discussed.
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NASA Technical Reports Server (NTRS)
Marley, Mark Scott; Hammel, Heidi
2014-01-01
A space based coronagraph, whether as part of the WFIRST/AFTA mission or on a dedicated space telescope such as Exo-C or -S, will be able to obtain photometry and spectra of multiple gas giant planets around nearby stars, including many known from radial velocity detections. Such observations will constrain the masses, atmospheric compositions, clouds, and photochemistry of these worlds. Giant planet albedo models, such as those of Cahoy et al. (2010) and Lewis et al. (this meeting), will be crucial for mission planning and interpreting the data. However it is equally important that insights gleaned from decades of solar system imaging and spectroscopy of giant planets be leveraged to optimize both instrument design and data interpretation. To illustrate these points we will draw on examples from solar system observations, by both HST and ground based telescopes, as well as by Voyager, Galileo, and Cassini, to demonstrate the importance clouds, photochemical hazes, and various molecular absorbers play in sculpting the light scattered by solar system giant planets. We will demonstrate how measurements of the relative depths of multiple methane absorption bands of varying strengths have been key to disentangling the competing effects of gas column abundances, variations in cloud height and opacity, and scattering by high altitude photochemical hazes. We will highlight both the successes, such as the accurate remote determination of the atmospheric methane abundance of Jupiter, and a few failures from these types of observations. These lessons provide insights into technical issues facing spacecraft designers, from the selection of the most valuable camera filters to carry to the required capabilities of the flight spectrometer, as well as mission design questions such as choosing the most favorable phase angles for atmospheric characterization.
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Classification of Aerial Photogrammetric 3d Point Clouds
NASA Astrophysics Data System (ADS)
Becker, C.; Häni, N.; Rosinskaya, E.; d'Angelo, E.; Strecha, C.
2017-05-01
We present a powerful method to extract per-point semantic class labels from aerial photogrammetry data. Labelling this kind of data is important for tasks such as environmental modelling, object classification and scene understanding. Unlike previous point cloud classification methods that rely exclusively on geometric features, we show that incorporating color information yields a significant increase in accuracy in detecting semantic classes. We test our classification method on three real-world photogrammetry datasets that were generated with Pix4Dmapper Pro, and with varying point densities. We show that off-the-shelf machine learning techniques coupled with our new features allow us to train highly accurate classifiers that generalize well to unseen data, processing point clouds containing 10 million points in less than 3 minutes on a desktop computer.
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Characteristics of downward leaders in a cloud-to-ground lightning strike on a lightning rod
NASA Astrophysics Data System (ADS)
Wang, Caixia; Sun, Zhuling; Jiang, Rubin; Tian, Yangmeng; Qie, Xiushu
2018-05-01
A natural downward negative cloud-to-ground (CG) lightning was observed at a close distance of 370 m by using electric field change measurements and a high-speed camera at 5400 frames per second (fps). Two subsequent leader-return strokes of the lightning hit a lightning rod installed on the top of a seven-story building in Beijing city, while the grounding point for the stepped leader-first return stroke was 12 m away, on the roof of the building. The 2-D average speed of the downward stepped leader (L1) before the first return stroke (R1) was approximately 5.1 × 104 m/s during its propagation over the 306 m above the building, and those before the subsequent strokes (R2 and R3) ranged from 1.1 × 106 m/s to 2.2 × 106 m/s. An attempted leader (AL) occurred 201 ms after R1 and 10 ms before R2 reached approximately 99 m above the roof and failed to connect to the ground. The 2-D average speed of the AL was approximately 7.4 × 104 m/s. The luminosity at tip of the leader was brighter than the channel behind it. The leader inducing the R2 with an alteration of terminating point was a dart-stepped leader (DSL), which propagated through the channel of AL and continued to develop downward with new branches at about 17 m above the roof. The 2-D speed of the DSL at the bottom 99 m was 6.6 × 105 m/s. The average time interval between the stepped pulses of the DSL was approximately 10 μs, smaller than that of L1 with value of about 17 μs. The average step lengths of the DSL were approximately 6.6 m. The study shows that the stepped leader-first return stroke of lightning will not always hit the tip of a tall metal rod due to the significant branching property of the leader. However, under certain conditions, the subsequent return strokes may alter the grounding point to the tip of a tall metal rod. For the lightning rod, the protection against subsequent return strokes may be better than that against the first return stroke.
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Microphysical Processes Affecting the Pinatubo Volcanic Plume
NASA Technical Reports Server (NTRS)
Hamill, Patrick; Houben, Howard; Young, Richard; Turco, Richard; Zhao, Jingxia
1996-01-01
In this paper we consider microphysical processes which affect the formation of sulfate particles and their size distribution in a dispersing cloud. A model for the dispersion of the Mt. Pinatubo volcanic cloud is described. We then consider a single point in the dispersing cloud and study the effects of nucleation, condensation and coagulation on the time evolution of the particle size distribution at that point.
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Optical properties of marine stratocumulus clouds modified by ship track effluents
NASA Technical Reports Server (NTRS)
King, Michael D.; Nakajima, Teruyuki
1990-01-01
The angular distribution of scattered radiation deep within a cloud layer was measured in marine stratocumulus clouds modified by the emissions from ships. These observations, obtained at thirteen discrete wavelengths between 0.5 and 2.3 microns, were obtained as the University of Washington Convair C-131A aircraft flew through a pair of roughly parallel ship tracks off the coast of southern California on 10 July 1987. In the first of these ship tracks, the cloud droplet concentration increased from 40 to 107/cu cm (125/cu cm in the second ship track). Simultaneous to this spectacular change, the aircraft measured interstitial aerosol (Aitken nucleus) concentration that increased from 400 to 1000/cu cm and cloud liquid water content that increased from 0.03 to 0.75 g/cu m. Broadband pyranometer measurements showed that the upwelling flux density increased from 150 to 280 W/sq m. These in-situ microphysics and broadband pyranometer results, together with AVHRR satellite images obtained with the NOAA-10 satellite, are described in detail by Radke et al., (1989). Internal scattered radiation measurements at selected wavelengths obtained with the cloud absorption radiometer (King et al., 1986) for a 100 km section of marine stratocumulus clouds containing these two ship track features are presented.
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Harmonic regression based multi-temporal cloud filtering algorithm for Landsat 8
NASA Astrophysics Data System (ADS)
Joshi, P.
2015-12-01
Landsat data archive though rich is seen to have missing dates and periods owing to the weather irregularities and inconsistent coverage. The satellite images are further subject to cloud cover effects resulting in erroneous analysis and observations of ground features. In earlier studies the change detection algorithm using statistical control charts on harmonic residuals of multi-temporal Landsat 5 data have been shown to detect few prominent remnant clouds [Brooks, Evan B., et al, 2014]. So, in this work we build on this harmonic regression approach to detect and filter clouds using a multi-temporal series of Landsat 8 images. Firstly, we compute the harmonic coefficients using the fitting models on annual training data. This time series of residuals is further subjected to Shewhart X-bar control charts which signal the deviations of cloud points from the fitted multi-temporal fourier curve. For the process with standard deviation σ we found the second and third order harmonic regression with a x-bar chart control limit [Lσ] ranging between [0.5σ < Lσ < σ] as most efficient in detecting clouds. By implementing second order harmonic regression with successive x-bar chart control limits of L and 0.5 L on the NDVI, NDSI and haze optimized transformation (HOT), and utilizing the seasonal physical properties of these parameters, we have designed a novel multi-temporal algorithm for filtering clouds from Landsat 8 images. The method is applied to Virginia and Alabama in Landsat8 UTM zones 17 and 16 respectively. Our algorithm efficiently filters all types of cloud cover with an overall accuracy greater than 90%. As a result of the multi-temporal operation and the ability to recreate the multi-temporal database of images using only the coefficients of the fourier regression, our algorithm is largely storage and time efficient. The results show a good potential for this multi-temporal approach for cloud detection as a timely and targeted solution for the Landsat 8 research community, catering to the need for innovative processing solutions in the infant stage of the satellite.
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3D local feature BKD to extract road information from mobile laser scanning point clouds
NASA Astrophysics Data System (ADS)
Yang, Bisheng; Liu, Yuan; Dong, Zhen; Liang, Fuxun; Li, Bijun; Peng, Xiangyang
2017-08-01
Extracting road information from point clouds obtained through mobile laser scanning (MLS) is essential for autonomous vehicle navigation, and has hence garnered a growing amount of research interest in recent years. However, the performance of such systems is seriously affected due to varying point density and noise. This paper proposes a novel three-dimensional (3D) local feature called the binary kernel descriptor (BKD) to extract road information from MLS point clouds. The BKD consists of Gaussian kernel density estimation and binarization components to encode the shape and intensity information of the 3D point clouds that are fed to a random forest classifier to extract curbs and markings on the road. These are then used to derive road information, such as the number of lanes, the lane width, and intersections. In experiments, the precision and recall of the proposed feature for the detection of curbs and road markings on an urban dataset and a highway dataset were as high as 90%, thus showing that the BKD is accurate and robust against varying point density and noise.
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Sun, Lei; Wang, Yan; Yue, Taixing; Yang, Xueqiao; Xue, Likun; Wang, Wenxing
2015-09-01
Cloud samples were collected during the summer of 2011 and the spring of 2012 at a high-elevation site in southern China in an effort to examine the chemical characteristics of acid clouds. In total, 141 cloud samples were collected during 44 cloud events over the observation period. The dominant ionic species were SO4(2-), NH4(+), and NO3(-), contributing approximately 75% of the total inorganic ion concentration. The primary acidifying factors were sulfate and nitrate, and the primary neutralizing factors were ammonium and calcium. The volume-weighted mean (VWM) pH of the cloud water was 3.79, indicating an acidic nature. In these cloud samples, Zn and Al exhibited the highest trace metal concentrations, contributing approximately 60% of the total trace element concentration. Toxic metals, such as Pb, Ba, As, and Cr, were detected at high concentrations, indicating potential hazards for human health, vegetation, and waters in this region. Visual MINTEQ 3.0 results revealed that the majority of Zn(II) and Pb(II) existed in the form of free ions. The behavior of Al, however, differed from the behaviors of zinc and lead. The temporal variation in cloud chemistry indicated that temperature, sandstorms, and long-range transport could affect the concentrations of species. During the lifetime of a cloud event, the concentrations of the chemical species were controlled by the transfer of gases or particles to liquid droplets.
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Hierarchical Regularization of Polygons for Photogrammetric Point Clouds of Oblique Images
NASA Astrophysics Data System (ADS)
Xie, L.; Hu, H.; Zhu, Q.; Wu, B.; Zhang, Y.
2017-05-01
Despite the success of multi-view stereo (MVS) reconstruction from massive oblique images in city scale, only point clouds and triangulated meshes are available from existing MVS pipelines, which are topologically defect laden, free of semantical information and hard to edit and manipulate interactively in further applications. On the other hand, 2D polygons and polygonal models are still the industrial standard. However, extraction of the 2D polygons from MVS point clouds is still a non-trivial task, given the fact that the boundaries of the detected planes are zigzagged and regularities, such as parallel and orthogonal, cannot preserve. Aiming to solve these issues, this paper proposes a hierarchical polygon regularization method for the photogrammetric point clouds from existing MVS pipelines, which comprises of local and global levels. After boundary points extraction, e.g. using alpha shapes, the local level is used to consolidate the original points, by refining the orientation and position of the points using linear priors. The points are then grouped into local segments by forward searching. In the global level, regularities are enforced through a labeling process, which encourage the segments share the same label and the same label represents segments are parallel or orthogonal. This is formulated as Markov Random Field and solved efficiently. Preliminary results are made with point clouds from aerial oblique images and compared with two classical regularization methods, which have revealed that the proposed method are more powerful in abstracting a single building and is promising for further 3D polygonal model reconstruction and GIS applications.
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Multiview 3D sensing and analysis for high quality point cloud reconstruction
NASA Astrophysics Data System (ADS)
Satnik, Andrej; Izquierdo, Ebroul; Orjesek, Richard
2018-04-01
Multiview 3D reconstruction techniques enable digital reconstruction of 3D objects from the real world by fusing different viewpoints of the same object into a single 3D representation. This process is by no means trivial and the acquisition of high quality point cloud representations of dynamic 3D objects is still an open problem. In this paper, an approach for high fidelity 3D point cloud generation using low cost 3D sensing hardware is presented. The proposed approach runs in an efficient low-cost hardware setting based on several Kinect v2 scanners connected to a single PC. It performs autocalibration and runs in real-time exploiting an efficient composition of several filtering methods including Radius Outlier Removal (ROR), Weighted Median filter (WM) and Weighted Inter-Frame Average filtering (WIFA). The performance of the proposed method has been demonstrated through efficient acquisition of dense 3D point clouds of moving objects.
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Performance testing of 3D point cloud software
NASA Astrophysics Data System (ADS)
Varela-González, M.; González-Jorge, H.; Riveiro, B.; Arias, P.
2013-10-01
LiDAR systems are being used widely in recent years for many applications in the engineering field: civil engineering, cultural heritage, mining, industry and environmental engineering. One of the most important limitations of this technology is the large computational requirements involved in data processing, especially for large mobile LiDAR datasets. Several software solutions for data managing are available in the market, including open source suites, however, users often unknown methodologies to verify their performance properly. In this work a methodology for LiDAR software performance testing is presented and four different suites are studied: QT Modeler, VR Mesh, AutoCAD 3D Civil and the Point Cloud Library running in software developed at the University of Vigo (SITEGI). The software based on the Point Cloud Library shows better results in the loading time of the point clouds and CPU usage. However, it is not as strong as commercial suites in working set and commit size tests.
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NASA Technical Reports Server (NTRS)
Long, S. A. T.
1973-01-01
The triangulation method developed specifically for the Barium Ion Cloud Project is discussed. Expression for the four displacement errors, the three slope errors, and the curvature error in the triangulation solution due to a probable error in the lines-of-sight from the observation stations to points on the cloud are derived. The triangulation method is then used to determine the effect of the following on these different errors in the solution: the number and location of the stations, the observation duration, east-west cloud drift, the number of input data points, and the addition of extra cameras to one of the stations. The pointing displacement errors, and the pointing slope errors are compared. The displacement errors in the solution due to a probable error in the position of a moving station plus the weighting factors for the data from the moving station are also determined.
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3D reconstruction of wooden member of ancient architecture from point clouds
NASA Astrophysics Data System (ADS)
Zhang, Ruiju; Wang, Yanmin; Li, Deren; Zhao, Jun; Song, Daixue
2006-10-01
This paper presents a 3D reconstruction method to model wooden member of ancient architecture from point clouds based on improved deformable model. Three steps are taken to recover the shape of wooden member. Firstly, Hessian matrix is adopted to compute the axe of wooden member. Secondly, an initial model of wooden member is made by contour orthogonal to its axis. Thirdly, an accurate model is got through the coupling effect between the initial model and the point clouds of the wooden member according to the theory of improved deformable model. Every step and algorithm is studied and described in the paper. Using the point clouds captured from Forbidden City of China, shaft member and beam member are taken as examples to test the method proposed in the paper. Results show the efficiency and robustness of the method addressed in the literature to model the wooden member of ancient architecture.
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NASA Astrophysics Data System (ADS)
Le Mouelic, S.; Rousseau, B.; Rodriguez, S.; Cornet, T.; Sotin, C.; Barnes, J. W.; Brown, R. H.; Buratti, B. J.; Baines, K. H.; Clark, R. N.; Nicholson, P. D.
2014-12-01
Cassini entered in Saturn's orbit in July 2004. In ten years, more than 100 targeted flybys of Titan have been performed. We focus our study on the comprehensive analysis of the Visual and Infrared Mapping Spectrometer data set acquired between 2004 and 2014, with a particular emphasis on the atmospheric polar features. First evidences for a vast ethane cloud covering the North Pole have been detected as soon as the second targeted flyby in December 2005 [1]. The first detailed imaging of this north polar feature with VIMS was obtained in December 2006, thanks to a change in inclination of the spacecraft orbit [2]. At this time, the northern lakes and seas of Titan were totally masked to the optical instruments by the haze and clouds, whereas the southern pole was well illuminated and mostly clear of haze and vast clouds. Subsequent flybys revealed that the vast north polar feature was progressively vanishing around the equinox in 2009 [2,3,4], in agreement with the predictions of Global Circulation Models [5]. It revealed progressively the underlying lakes to the ISS and VIMS instruments. First evidences of an atmospheric vortex growing over the South Pole occurred in May 2012, with a high altitude feature detected at each flybys since then. In this study, we have computed individual global maps of the north and south poles for each of the 100 targeted flybys, using VIMS wavelengths sensitive both to clouds and surface features. This allows a more complete monitoring of the evolution of the north polar cloud than was previously done before using a selection of individual flybys only. It also provides a detailed investigation of what is currently acting over the South Pole. [1] Griffith et al., Science, 2006. [2] Le Mouélic et al., PSS, 2012. [3] Rodriguez et al., Nature, 2009. [4] Rodriguez et al., Icarus 2011. [5] Rannou et al., Science 2005
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NASA Astrophysics Data System (ADS)
Wasserburg, G. J.; Karakas, Amanda I.; Lugaro, Maria
2017-02-01
We explore the possibility that the short-lived radionuclides {}26{{A}}l, {}60{{F}}e, {}107{{P}}d, and {}182{{H}}f inferred to be present in the proto-solar cloud originated from 3-8 {M}⊙ asymptotic giant branch (AGB) stars. Models of AGB stars with initial mass above 5 {M}⊙ are prolific producers of {}26{{A}}l owing to hot bottom burning (HBB). In contrast, {}60{{F}}e, {}107{{P}}d, and {}182{{H}}f are produced by neutron captures: {}107{{P}}d and {}182{{H}}f in models ≲ 5 {M}⊙ , and {}60{{F}}e in models with higher mass. We mix stellar yields from solar-metallicity AGB models into a cloud of solar mass and composition to investigate whether it is possible to explain the abundances of the four radioactive nuclides at the Sun’s birth using one single value of the mixing ratio between the AGB yields and the initial cloud material. We find that AGB stars that experience efficient HBB (≥slant 6 {M}⊙ ) cannot provide a solution because they produce too little {}182{{H}}f and {}107{{P}}d relative to {}26{{A}}l and {}60{{F}}e. Lower-mass AGB stars cannot provide a solution because they produce too little {}26{{A}}l relative to {}107{{P}}d and {}182{{H}}f. A self-consistent solution may be found for AGB stars with masses in between (4-5.5 {M}⊙ ), provided that HBB is stronger than in our models and the {}13{{C}}(α, n){}16{{O}} neutron source is mildly activated. If stars of {{M}}< 5.5 {M}⊙ are the source of the radioactive nuclides, then some basis for their existence in proto-solar clouds needs to be explored, given that the stellar lifetimes are longer than the molecular cloud lifetimes.
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NASA Astrophysics Data System (ADS)
Baines, Kevin; Sromovsky, Lawrence A.; Fry, Patrick M.; Carlson, Robert W.; Momary, Thomas W.
2016-10-01
We report results incorporating the red-tinted photochemically-generated aerosols of Carlson et al (2016, Icarus 274, 106-115) in spectral models of Jupiter's Great Red Spot (GRS). Spectral models of the 0.35-1.0-micron spectrum show good agreement with Cassini/VIMS near-center-meridian and near-limb GRS spectra for model morphologies incorporating an optically-thin layer of Carlson (2016) aerosols at high altitudes, either at the top of the tropospheric GRS cloud, or in a distinct stratospheric haze layer. Specifically, a two-layer "crème brûlée" structure of the Mie-scattering Carlson et al (2016) chromophore attached to the top of a conservatively scattering (hereafter, "white") optically-thick cloud fits the spectra well. Currently, best agreement (reduced χ2 of 0.89 for the central-meridian spectrum) is found for a 0.195-0.217-bar, 0.19 ± 0.02 opacity layer of chromophores with mean particle radius of 0.14 ± 0.01 micron. As well, a structure with a detached stratospheric chromophore layer ~0.25 bar above a white tropospheric GRS cloud provides a good spectral match (reduced χ2 of 1.16). Alternatively, a cloud morphology with the chromophore coating white particles in a single optically- and physically-thick cloud (the "coated-shell model", initially explored by Carlson et al 2016) was found to give significantly inferior fits (best reduced χ2 of 2.9). Overall, we find that models accurately fit the GRS spectrum if (1) most of the optical depth of the chromophore is in a layer near the top of the main cloud or in a distinct separated layer above it, but is not uniformly distributed within the main cloud, (2) the chromophore consists of relatively small, 0.1-0.2-micron-radius particles, and (3) the chromophore layer optical depth is small, ~ 0.1-0.2. Thus, our analysis supports the exogenic origin of the red chromophore consistent with the Carlson et al (2016) photolytic production mechanism rather than an endogenic origin, such as upwelling of material from the depths of Jupiter.
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NASA Astrophysics Data System (ADS)
Thompson, D. R.; Kahn, B. H.; Green, R. O.; Chien, S.; Middleton, E.; Tran, D. Q.
2017-12-01
Clouds' variable ice and liquid content significantly influences their optical properties, evolution, and radiative forcing potential (Tan and Storelvmo, J. Atmos. Sci, 73, 2016). However, most remote measurements of thermodynamic phase have spatial resolutions of 1 km or more and are insensitive to mixed phases. This under-constrains important processes, such as spatial partitioning within mixed phase clouds, that carry outsize radiative forcing impacts. These uncertainties could shift Global Climate Model (GCM) predictions of future warming by over 1 degree Celsius (Tan et al., Science 352:6282, 2016). Imaging spectroscopy of reflected solar energy from the 1.4 - 1.8 μm shortwave infrared (SWIR) spectral range can address this observational gap. These observations can distinguish ice and water absorption, providing a robust and sensitive measurement of cloud top thermodynamic phase including mixed phases. Imaging spectrometers can resolve variations at scales of tens to hundreds of meters (Thompson et al., JGR-Atmospheres 121, 2016). We report the first such global high spatial resolution (30 m) survey, based on data from 2005-2015 acquired by the Hyperion imaging spectrometer onboard NASA's EO-1 spacecraft (Pearlman et al., Proc. SPIE 4135, 2001). Estimated seasonal and latitudinal distributions of cloud thermodynamic phase generally agree with observations made by other satellites such as the Atmospheric Infrared Sounder (AIRS). Variogram analyses reveal variability at different spatial scales. Our results corroborate previously observed zonal distributions, while adding insight into the spatial scales of processes governing cloud top thermodynamic phase. Figure: Thermodynamic phase retrievals. Top: Example of a cloud top thermodynamic phase map from the EO-1/Hyperion. Bottom: Latitudinal distributions of pure and mixed phase clouds, 2005-2015, showing Liquid Thickness Fraction (LTF). LTF=0 corresponds to pure ice absorption, while LTF=1 is pure liquid. The archive contains over 45,000 scenes. Copyright 2017, California Institute of Technology. Government Support Acknowledged.
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NASA Astrophysics Data System (ADS)
Hueso, R.; Garate-Lopez, I.; Sanchez-Lavega, A.
2011-12-01
The VIRTIS instrument onboard Venus Express observes Venus in two channels (visible and infrared) obtaining spectra and multi-wavelength images of the planet. The images have been used to trace the motions of the atmosphere at different layers of clouds [1-3]. We review the VIRTIS cloud image data and wind results obtained by different groups [1-3] and we present new results concerning the morphology and evolution of the South Polar Vortex at the upper and lower cloud levels with data covering the first 900 days of the mission. We present wind measurements of the South hemisphere obtained by cloud tracking individual cloud features and higher-resolution wind results of the polar region covering the evolution of the South polar vortex. The later were obtained by an image correlation algorithm run under human supervision to validate the data. We present day-side data of the upper clouds obtained at 380 and 980 nm sensitive to altitudes of 66-70 km, night-side data in the near infrared at 1.74 microns of the lower cloud (45-50 km) and day and night-side data obtained in the thermal infrared (wavelengths of 3.8 and 5.1 microns) which covers the dynamical evolution of Venus South Polar vortex at the cloud tops (66-70 km). We explore the different dynamics associated to the varying morphology of the vortex, its dynamical structure at different altitudes, the variability of the global wind data of the southern hemisphere and the interrelation of the polar vortex dynamics with the wind dynamics at subpolar and mid-latitudes. Acknowledgements: Work funded by Spanish MICIIN AYA2009-10701 with FEDER support and Grupos Gobierno Vasco IT-464-07. References [1] A. Sánchez-Lavega et al., Geophys. Res. Lett. 35, L13204, (2008). [2] D. Luz et al., Science, 332, 577-580 (2011). [3] R. Hueso, et al., Icarus doi:10.1016/j.icarus.2011.04.020 (2011)
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Daytime Cloud Property Retrievals Over the Arctic from Multispectral MODIS Data
NASA Technical Reports Server (NTRS)
Spangenberg, Douglas A.; Trepte, Qing; Minnis, Patrick; Uttal, Taneil
2004-01-01
Improving climate model predictions over Earth's polar regions requires a complete understanding of polar clouds properties. Passive satellite remote sensing techniques can be used to retrieve macro and microphysical properties of polar cloud systems. However, over the Arctic, there is minimal contrast between clouds and the background snow surface observed in satellite data, especially for visible wavelengths. This makes it difficult to identify clouds and retrieve their properties from space. Variable snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds further complicate cloud property identification. For this study, the operational Clouds and the Earth s Radiant Energy System (CERES) cloud mask is first used to discriminate clouds from the background surface in Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data. A solar-infrared infrared nearinfrared technique (SINT) first used by Platnick et al. (2001) is used here to retrieve cloud properties over snow and ice covered regions.
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NASA Astrophysics Data System (ADS)
Tuttas, S.; Braun, A.; Borrmann, A.; Stilla, U.
2014-08-01
For construction progress monitoring a planned state of the construction at a certain time (as-planed) has to be compared to the actual state (as-built). The as-planed state is derived from a building information model (BIM), which contains the geometry of the building and the construction schedule. In this paper we introduce an approach for the generation of an as-built point cloud by photogrammetry. It is regarded that that images on a construction cannot be taken from everywhere it seems to be necessary. Because of this we use a combination of structure from motion process together with control points to create a scaled point cloud in a consistent coordinate system. Subsequently this point cloud is used for an as-built - as-planed comparison. For that voxels of an octree are marked as occupied, free or unknown by raycasting based on the triangulated points and the camera positions. This allows to identify not existing building parts. For the verification of the existence of building parts a second test based on the points in front and behind the as-planed model planes is performed. The proposed procedure is tested based on an inner city construction site under real conditions.
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Localization of Pathology on Complex Architecture Building Surfaces
NASA Astrophysics Data System (ADS)
Sidiropoulos, A. A.; Lakakis, K. N.; Mouza, V. K.
2017-02-01
The technology of 3D laser scanning is considered as one of the most common methods for heritage documentation. The point clouds that are being produced provide information of high detail, both geometric and thematic. There are various studies that examine techniques of the best exploitation of this information. In this study, an algorithm of pathology localization, such as cracks and fissures, on complex building surfaces is being tested. The algorithm makes use of the points' position in the point cloud and tries to distinguish them in two groups-patterns; pathology and non-pathology. The extraction of the geometric information that is being used for recognizing the pattern of the points is being accomplished via Principal Component Analysis (PCA) in user-specified neighborhoods in the whole point cloud. The implementation of PCA leads to the definition of the normal vector at each point of the cloud. Two tests that operate separately examine both local and global geometric criteria among the points and conclude which of them should be categorized as pathology. The proposed algorithm was tested on parts of the Gazi Evrenos Baths masonry, which are located at the city of Giannitsa at Northern Greece.
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Coupled Photochemical and Condensation Model for the Venus Atmosphere
NASA Astrophysics Data System (ADS)
Bierson, Carver; Zhang, Xi; Mendonca, Joao; Liang, Mao-Chang
2017-10-01
Ground based and Venus Express observations have provided a wealth of information on the vertical and latitudinal distribution of many chemical species in the Venus atmosphere [1,2]. Previous 1D models have focused on the chemistry of either the lower [3] or middle atmosphere [4,5]. Photochemical models focusing on the sulfur gas chemistry have also been independent from models of the sulfuric acid haze and cloud formation [6,7]. In recent years sulfur-bearing particles have become important candidates for the observed SO2 inversion above 80 km [5]. To test this hypothesis it is import to create a self-consistent model that includes photochemistry, transport, and cloud condensation.In this work we extend the domain of the 1D chemistry model of Zhang et al. (2012) [5] to encompass the region between the surface to 110 km. This model includes a simple sulfuric acid condensation scheme with gravitational settling. It simultaneously solves for the chemistry and condensation allowing for self-consistent cloud formation. We compare the resulting chemical distributions to observations at all altitudes. We have also validated our model cloud mass against pioneer Venus observations [8]. This updated full atmosphere chemistry model is also being applied in our 2D solver (altitude and altitude). With this 2D model we can model how the latitudinal distribution of chemical species depends on the meridional circulation. This allows us to use the existing chemical observations to place constraints on Venus GCMs [9-11].References: [1] Arney et al., JGR:Planets, 2014 [2] Vandaele et al., Icarus 2017 (pt. 1 & 2) [3] Krasnopolsky, Icarus, 2007 [4] Krasnopolsky, Icarus, 2012 [5] Zhang et al., Icarus 2012 [6] Gao et al., Icarus, 2014 [7] Krasnopolsky, Icarus, 2015 [8] Knollenberg and Hunten, JGR:Space Physics, 1980 [9] Lee et al., JGR:Planets, 2007 [10] Lebonnois et al., Towards Understanding the Climate of Venus, 2013 [11] Mendoncca and Read, Planetary and Space Science, 2016
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Error reduction in three-dimensional metrology combining optical and touch probe data
NASA Astrophysics Data System (ADS)
Gerde, Janice R.; Christens-Barry, William A.
2010-08-01
Analysis of footwear under the Harmonized Tariff Schedule of the United States (HTSUS) is partly based on identifying the boundary ("parting line") between the "external surface area upper" (ESAU) and the sample's sole. Often, that boundary is obscured. We establish the parting line as the curved intersection between the sample outer surface and its insole surface. The outer surface is determined by discrete point cloud coordinates obtained using a laser scanner. The insole surface is defined by point cloud data, obtained using a touch probe device-a coordinate measuring machine (CMM). Because these point cloud data sets do not overlap spatially, a polynomial surface is fitted to the insole data and extended to intersect a mesh fitted to the outer surface point cloud. This line of intersection defines the ESAU boundary, permitting further fractional area calculations to proceed. The defined parting line location is sensitive to the polynomial used to fit experimental data. Extrapolation to the intersection with the ESAU can heighten this sensitivity. We discuss a methodology for transforming these data into a common reference frame. Three scenarios are considered: measurement error in point cloud coordinates, from fitting a polynomial surface to a point cloud then extrapolating beyond the data set, and error from reference frame transformation. These error sources can influence calculated surface areas. We describe experiments to assess error magnitude, the sensitivity of calculated results on these errors, and minimizing error impact on calculated quantities. Ultimately, we must ensure that statistical error from these procedures is minimized and within acceptance criteria.
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NASA Astrophysics Data System (ADS)
Nex, F.; Gerke, M.
2014-08-01
Image matching techniques can nowadays provide very dense point clouds and they are often considered a valid alternative to LiDAR point cloud. However, photogrammetric point clouds are often characterized by a higher level of random noise compared to LiDAR data and by the presence of large outliers. These problems constitute a limitation in the practical use of photogrammetric data for many applications but an effective way to enhance the generated point cloud has still to be found. In this paper we concentrate on the restoration of Digital Surface Models (DSM), computed from dense image matching point clouds. A photogrammetric DSM, i.e. a 2.5D representation of the surface is still one of the major products derived from point clouds. Four different algorithms devoted to DSM denoising are presented: a standard median filter approach, a bilateral filter, a variational approach (TGV: Total Generalized Variation), as well as a newly developed algorithm, which is embedded into a Markov Random Field (MRF) framework and optimized through graph-cuts. The ability of each algorithm to recover the original DSM has been quantitatively evaluated. To do that, a synthetic DSM has been generated and different typologies of noise have been added to mimic the typical errors of photogrammetric DSMs. The evaluation reveals that standard filters like median and edge preserving smoothing through a bilateral filter approach cannot sufficiently remove typical errors occurring in a photogrammetric DSM. The TGV-based approach much better removes random noise, but large areas with outliers still remain. Our own method which explicitly models the degradation properties of those DSM outperforms the others in all aspects.
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NASA Astrophysics Data System (ADS)
Bonduel, M.; Bassier, M.; Vergauwen, M.; Pauwels, P.; Klein, R.
2017-11-01
The use of Building Information Modeling (BIM) for existing buildings based on point clouds is increasing. Standardized geometric quality assessment of the BIMs is needed to make them more reliable and thus reusable for future users. First, available literature on the subject is studied. Next, an initial proposal for a standardized geometric quality assessment is presented. Finally, this method is tested and evaluated with a case study. The number of specifications on BIM relating to existing buildings is limited. The Levels of Accuracy (LOA) specification of the USIBD provides definitions and suggestions regarding geometric model accuracy, but lacks a standardized assessment method. A deviation analysis is found to be dependent on (1) the used mathematical model, (2) the density of the point clouds and (3) the order of comparison. Results of the analysis can be graphical and numerical. An analysis on macro (building) and micro (BIM object) scale is necessary. On macro scale, the complete model is compared to the original point cloud and vice versa to get an overview of the general model quality. The graphical results show occluded zones and non-modeled objects respectively. Colored point clouds are derived from this analysis and integrated in the BIM. On micro scale, the relevant surface parts are extracted per BIM object and compared to the complete point cloud. Occluded zones are extracted based on a maximum deviation. What remains is classified according to the LOA specification. The numerical results are integrated in the BIM with the use of object parameters.
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Multi-band Emission Light Curves of Jupiter: Insights on Brown Dwarfs and Directly Imaged Exoplanets
NASA Astrophysics Data System (ADS)
Zhang, Xi; Ge, Huazhi; Orton, Glenn S.; Fletcher, Leigh N.; Sinclair, James; Fernandes, Joshua; Momary, Thomas W.; Kasaba, Yasumasa; Sato, Takao M.; Fujiyoshi, Takuya
2016-10-01
Many brown dwarfs exhibit significant infrared flux variability (e.g., Artigau et al. 2009, ApJ, 701, 1534; Radigan et al. 2012, ApJ, 750, 105), ranging from several to twenty percent of the brightness. Current hypotheses include temperature variations, cloud holes and patchiness, and cloud height and thickness variations (e.g., Apai et al. 2013, ApJ, 768, 121; Robinson and Marley 2014, ApJ, 785, 158; Zhang and Showman 2014, ApJ, 788, L6). Some brown dwarfs show phase shifts in the light curves among different wavelengths (e.g., Buenzli et al. 2012, ApJ, 760, L31; Yang et al. 2016, arXiv:1605.02708), indicating vertical variations of the cloud distribution. The current observational technique can barely detect the brightness changes on the surfaces of nearby brown dwarfs (Crossfield et al. 2014, Nature, 505, 654) let alone resolve detailed weather patterns that cause the flux variability. The infrared emission maps of Jupiter might shed light on this problem. Using COMICS at Subaru Telescope, VISIR at Very Large Telescope (VLT) and NASA's Infrared Telescope Facility (IRTF), we obtained infrared images of Jupiter over several nights at multiple wavelengths that are sensitive to several pressure levels from the stratosphere to the deep troposphere below the ammonia clouds. The rotational maps and emission light curves are constructed. The individual pixel brightness varies up to a hundred percent level and the variation of the full-disk brightness is around several percent. Both the shape and amplitude of the light curves are significantly distinct at different wavelengths. Variation of light curves at different epochs and phase shift among different wavelengths are observed. We will present principle component analysis to identify dominant emission features such as stable vortices, cloud holes and eddies in the belts and zones and strong emissions in the aurora region. A radiative transfer model is used to simulate those features to get a more quantitative understanding. This work provides rich insights on the relationship between observed light curves and weather on brown dwarfs and perhaps on directly imaged exoplanets in the future.
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Temporal resolution requirements of satellite constellations for 30 m global burned area mapping
NASA Astrophysics Data System (ADS)
Melchiorre, A.; Boschetti, L.
2017-12-01
Global burned area maps have been generated systematically with daily, coarse resolution satellite data (Giglio et al. 2013). The production of moderate resolution (10 - 30 m) global burned area products would meet the needs of several user communities: improved carbon emission estimations due to heterogeneous landscapes and for local scale air quality and fire management applications (Mouillot et al. 2014; van der Werf et al. 2010). While the increased spatial resolution reduces the influence of mixed burnt/unburnt pixels and it would increase the spectral separation of burned areas, moderate resolution satellites have reduced temporal resolution (10 - 16 days). Fire causes a land-cover change spectrally visible for a period ranging from a few weeks in savannas to over a year in forested ecosystems (Roy et al. 2010); because clouds, smoke, and other optically thick aerosols limit the number of available observations (Roy et al. 2008; Smith and Wooster 2005), burned areas might disappear before they are observed by moderate resolution sensors. Data fusion from a constellation of different sensors has been proposed to overcome these limits (Boschetti et al. 2015; Roy 2015). In this study, we estimated the probability of moderate resolution satellites and virtual constellations (including Landsat-8/9, Sentinel-2A/B) to provide sufficient observations for burned area mapping globally, and by ecosystem. First, we estimated the duration of the persistence of the signal associated with burned areas by combining the MODIS Global Burned Area and the Nadir BRDF-Adjusted Reflectance Product by characterizing the post-fire trends in reflectance to determine the length of the period in which the burn class is spectrally distinct from the unburned and, therefore, detectable. The MODIS-Terra daily cloud data were then used to estimate the probability of cloud cover. The cloud probability was used at each location to estimate the minimum revisit time needed to obtain at least one cloud-free observation within the duration of the persistence of burned areas. As complementary results, the expected omission error due to insufficient observations was estimated for each of the satellite combination considered making use of the calendar and geometry of acquisition for each of the sensor included in the virtual constellation.
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NASA Astrophysics Data System (ADS)
Stöcker, Claudia; Eltner, Anette
2016-04-01
Advances in computer vision and digital photogrammetry (i.e. structure from motion) allow for fast and flexible high resolution data supply. Within geoscience applications and especially in the field of small surface topography, high resolution digital terrain models and dense 3D point clouds are valuable data sources to capture actual states as well as for multi-temporal studies. However, there are still some limitations regarding robust registration and accuracy demands (e.g. systematic positional errors) which impede the comparison and/or combination of multi-sensor data products. Therefore, post-processing of 3D point clouds can heavily enhance data quality. In this matter the Iterative Closest Point (ICP) algorithm represents an alignment tool which iteratively minimizes distances of corresponding points within two datasets. Even though tool is widely used; it is often applied as a black-box application within 3D data post-processing for surface reconstruction. Aiming for precise and accurate combination of multi-sensor data sets, this study looks closely at different variants of the ICP algorithm including sub-steps of point selection, point matching, weighting, rejection, error metric and minimization. Therefore, an agricultural utilized field was investigated simultaneously by terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) sensors two times (once covered with sparse vegetation and once bare soil). Due to different perspectives both data sets show diverse consistency in terms of shadowed areas and thus gaps so that data merging would provide consistent surface reconstruction. Although photogrammetric processing already included sub-cm accurate ground control surveys, UAV point cloud exhibits an offset towards TLS point cloud. In order to achieve the transformation matrix for fine registration of UAV point clouds, different ICP variants were tested. Statistical analyses of the results show that final success of registration and therefore data quality depends particularly on parameterization and choice of error metric, especially for erroneous data sets as in the case of sparse vegetation cover. At this, the point-to-point metric is more sensitive to data "noise" than the point-to-plane metric which results in considerably higher cloud-to-cloud distances. Concluding, in order to comply with accuracy demands of high resolution surface reconstruction and the aspect that ground control surveys can reach their limits both in time exposure and terrain accessibility ICP algorithm represents a great tool to refine rough initial alignment. Here different variants of registration modules allow for individual application according to the quality of the input data.
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Characteristics of mid-level clouds over West Africa
NASA Astrophysics Data System (ADS)
Bourgeois, Elsa; Bouniol, Dominique; Couvreux, Fleur; Guichard, Françoise; Marsham, John; Garcia-Carreras, Luis; Birch, Cathryn; Parker, Doug
2017-04-01
Clouds have a major impact on the distribution of water and energy fluxes within the atmosphere. They also represent one of the main sources of uncertainties in global climate models as a result of the difficulty to parametrize cloud processes. However, in West Africa, the cloud type, occurrence and radiative effects have not been extensively documented. This region is characterized by a strong seasonality with precipitation occurring in the Sahel from June to September (monsoon season). This period also coincides with the annual maximum of the cloud cover. Taking advantage of the one-year ARM Mobile Facility (AMF) deployment in 2006 in Niamey (Niger), Bouniol et al (2012) documented the distinct cloud types and showed the frequent occurrence of mid-level clouds (around 6 km height) and their substantial impact on the surface short-wave and long-wave radiative fluxes. Furthermore, in a process-oriented evaluation of climate models, Roehrig et al (2013) showed that these mid-level clouds are poorly represented in numerical models. The aim of this work is to document the macro- and microphysical properties of mid-level clouds and the environment in which such clouds occur across West Africa. To document those clouds, we extensively make use of observations from lidar and cloud radar either deployed at ground-based sites (Niamey and Bordj Badji Mokhtar (Sahara)) or on-board the A-Train constellation (CloudSat/CALIPSO). These datasets reveal the temporal and spatial occurrence of those clouds. They are found throughout the year with a predominance around the monsoon season and are preferentially observed in the Southern and Western part of West Africa which could be linked to the dynamics of the Saharan heat low. Those clouds are usually quite thin (most of them are less than 1000m deep). A clustering method applied to this data allows us to identify three different types of clouds : one with low bases, one with high bases and another with large thicknesses. The first two clouds families are associated with potential temperature inversions at the top of the clouds. Complementary observations such as radiosondes and radiation measurements allow us to determine the thermodynamical stratification in which they occur as well as their radiative properties.
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A Regional Real-time Forecast of Marine Boundary Layers During VOCALS-REx
2011-01-01
Condensation Nuclei) concentration pro- motes more precipitation, leading to the destruction and structural change of the clouds (e.g., Stevens et al...and Muñoz, 2004), investigations of cloud and dynamic pro- cesses in case studies (Mocko and Cotton , 1995; Mechem and Kogan, 2003; Thompson et al...land breeze, Geophys. Res. Lett., 32, L05605, doi:10.1029/2004GL022139, 2005. Golaz, J.-C., Larson, V. E., and Cotton ,W. R: A PDF-based model for
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Response to "No Evidence for Iris"
NASA Technical Reports Server (NTRS)
Chou, Ming-Dah; Lindzen, Richard S.; Hou, Arthur Y.; Lau, William K. M. (Technical Monitor)
2001-01-01
Hartmann and Michelsen claimed that there was no evidence for the negative relation between the high-level clouds and the sea surface temperature as suggested by Lindzen et al. The assertion made by Hartmann and Michelsen that there is a need for clouds thousands of kilometers away from the equator to be connected to convection at the equator does not seem to have any validity. Nor does their suggestion that the causes of the observational relations shown in Lindzen et al. do not involve detrainment.
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Chance Encounter with a Stratospheric Kerosene Rocket Plume From Russia Over California
NASA Technical Reports Server (NTRS)
Newman, P. A.; Wilson, J. C.; Ross, M. N.; Brock, C. A.; Sheridan, P. J.; Schoeberl, M. R.; Lait, L. R.; Bui, T. P.; Loewenstein, M.; Podolske, J. R.;
2000-01-01
A high-altitude aircraft flight on April 18, 1997 detected an enormous aerosol cloud at 20 km altitude near California (37 N). Not visually observed, the cloud had high concentrations of soot and sulfate aerosol, and was over 180 km in horizontal extent. The cloud was probably a large hydrocarbon fueled vehicle, most likely from rocket motors burning liquid oxygen and kerosene. One of two Russian Soyuz rockets could have produced the cloud: a launch from the Baikonur Cosmodrome, Kazakhstan on April 6; or from Plesetsk, Russia on April 9. Parcel trajectories and long-lived trace gas concentrations suggest the Baikonur launch as the cloud source. Cloud trajectories do not trace the Soyuz plume from Asia to North America, illustrating the uncertainties of point-to-point trajectories. This cloud encounter is the only stratospheric measurement of a hydrocarbon fuel powered rocket.
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Improvements in AVHRR Daytime Cloud Detection Over the ARM NSA Site
NASA Technical Reports Server (NTRS)
Chakrapani, V.; Spangenberg, D. A.; Doelling, D. R.; Minnis, P.; Trepte, Q. Z.; Arduini, R. F.
2001-01-01
Clouds play an important role in the radiation budget over Arctic and Antarctic. Because of limited surface observing capabilities, it is necessary to detect clouds over large areas using satellite imagery. At low and mid-latitudes, satellite-observed visible (VIS; 0.65 micrometers) and infrared (IR; 11 micrometers) radiance data are used to derive cloud fraction, temperature, and optical depth. However, the extreme variability in the VIS surface albedo makes the detection of clouds from satellite a difficult process in polar regions. The IR data often show that the surface is nearly the same temperature or even colder than clouds, further complicating cloud detection. Also, the boundary layer can have large areas of haze, thin fog, or diamond dust that are not seen in standard satellite imagery. Other spectral radiances measured by satellite imagers provide additional information that can be used to more accurately discriminate clouds from snow and ice. Most techniques currently use a fixed reflectance or temperature threshold to decide between clouds and clear snow. Using a subjective approach, Minnis et al. (2001) found that the clear snow radiance signatures vary as a function of viewing and illumination conditions as well as snow condition. To routinely process satellite imagery over polar regions with an automated algorithm, it is necessary to account for this angular variability and the change in the background reflectance as snow melts, vegetation grows over land, and melt ponds form on pack ice. This paper documents the initial satellite-based cloud product over the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site at Barrow for use by the modeling community. Cloud amount and height are determined subjectively using an adaptation of the methodology of Minnis et al. (2001) and the radiation fields arc determined following the methods of Doelling et al. (2001) as applied to data taken during the Surface Heat and Energy Budget of the Arctic (SHEBA). The procedures and data produced in this empirically based analysis will also facilitate the development of the automated algorithm for future processing of satellite data over the ARM NSA domain. Results are presented for May, June, and July 1998. ARM surface data are use to partially validate the results taken directly over the ARM site.
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a Method for the Registration of Hemispherical Photographs and Tls Intensity Images
NASA Astrophysics Data System (ADS)
Schmidt, A.; Schilling, A.; Maas, H.-G.
2012-07-01
Terrestrial laser scanners generate dense and accurate 3D point clouds with minimal effort, which represent the geometry of real objects, while image data contains texture information of object surfaces. Based on the complementary characteristics of both data sets, a combination is very appealing for many applications, including forest-related tasks. In the scope of our research project, independent data sets of a plain birch stand have been taken by a full-spherical laser scanner and a hemispherical digital camera. Previously, both kinds of data sets have been considered separately: Individual trees were successfully extracted from large 3D point clouds, and so-called forest inventory parameters could be determined. Additionally, a simplified tree topology representation was retrieved. From hemispherical images, leaf area index (LAI) values, as a very relevant parameter for describing a stand, have been computed. The objective of our approach is to merge a 3D point cloud with image data in a way that RGB values are assigned to each 3D point. So far, segmentation and classification of TLS point clouds in forestry applications was mainly based on geometrical aspects of the data set. However, a 3D point cloud with colour information provides valuable cues exceeding simple statistical evaluation of geometrical object features and thus may facilitate the analysis of the scan data significantly.
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NASA Astrophysics Data System (ADS)
Bassier, M.; Bonduel, M.; Van Genechten, B.; Vergauwen, M.
2017-11-01
Point cloud segmentation is a crucial step in scene understanding and interpretation. The goal is to decompose the initial data into sets of workable clusters with similar properties. Additionally, it is a key aspect in the automated procedure from point cloud data to BIM. Current approaches typically only segment a single type of primitive such as planes or cylinders. Also, current algorithms suffer from oversegmenting the data and are often sensor or scene dependent. In this work, a method is presented to automatically segment large unstructured point clouds of buildings. More specifically, the segmentation is formulated as a graph optimisation problem. First, the data is oversegmented with a greedy octree-based region growing method. The growing is conditioned on the segmentation of planes as well as smooth surfaces. Next, the candidate clusters are represented by a Conditional Random Field after which the most likely configuration of candidate clusters is computed given a set of local and contextual features. The experiments prove that the used method is a fast and reliable framework for unstructured point cloud segmentation. Processing speeds up to 40,000 points per second are recorded for the region growing. Additionally, the recall and precision of the graph clustering is approximately 80%. Overall, nearly 22% of oversegmentation is reduced by clustering the data. These clusters will be classified and used as a basis for the reconstruction of BIM models.
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NASA Astrophysics Data System (ADS)
Wang, Jinhu; Lindenbergh, Roderik; Menenti, Massimo
2017-06-01
Urban road environments contain a variety of objects including different types of lamp poles and traffic signs. Its monitoring is traditionally conducted by visual inspection, which is time consuming and expensive. Mobile laser scanning (MLS) systems sample the road environment efficiently by acquiring large and accurate point clouds. This work proposes a methodology for urban road object recognition from MLS point clouds. The proposed method uses, for the first time, shape descriptors of complete objects to match repetitive objects in large point clouds. To do so, a novel 3D multi-scale shape descriptor is introduced, that is embedded in a workflow that efficiently and automatically identifies different types of lamp poles and traffic signs. The workflow starts by tiling the raw point clouds along the scanning trajectory and by identifying non-ground points. After voxelization of the non-ground points, connected voxels are clustered to form candidate objects. For automatic recognition of lamp poles and street signs, a 3D significant eigenvector based shape descriptor using voxels (SigVox) is introduced. The 3D SigVox descriptor is constructed by first subdividing the points with an octree into several levels. Next, significant eigenvectors of the points in each voxel are determined by principal component analysis (PCA) and mapped onto the appropriate triangle of a sphere approximating icosahedron. This step is repeated for different scales. By determining the similarity of 3D SigVox descriptors between candidate point clusters and training objects, street furniture is automatically identified. The feasibility and quality of the proposed method is verified on two point clouds obtained in opposite direction of a stretch of road of 4 km. 6 types of lamp pole and 4 types of road sign were selected as objects of interest. Ground truth validation showed that the overall accuracy of the ∼170 automatically recognized objects is approximately 95%. The results demonstrate that the proposed method is able to recognize street furniture in a practical scenario. Remaining difficult cases are touching objects, like a lamp pole close to a tree.
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Genomic cloud computing: legal and ethical points to consider
Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Burton, Paul; Chisholm, Rex; Fortier, Isabel; Goodwin, Pat; Harris, Jennifer; Hveem, Kristian; Kaye, Jane; Kent, Alistair; Knoppers, Bartha Maria; Lindpaintner, Klaus; Little, Julian; Riegman, Peter; Ripatti, Samuli; Stolk, Ronald; Bobrow, Martin; Cambon-Thomsen, Anne; Dressler, Lynn; Joly, Yann; Kato, Kazuto; Knoppers, Bartha Maria; Rodriguez, Laura Lyman; McPherson, Treasa; Nicolás, Pilar; Ouellette, Francis; Romeo-Casabona, Carlos; Sarin, Rajiv; Wallace, Susan; Wiesner, Georgia; Wilson, Julia; Zeps, Nikolajs; Simkevitz, Howard; De Rienzo, Assunta; Knoppers, Bartha M
2015-01-01
The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key ‘points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These ‘points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure. PMID:25248396
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Genomic cloud computing: legal and ethical points to consider.
Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Knoppers, Bartha M
2015-10-01
The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key 'points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These 'points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Çağlar, Halife, E-mail: hlfcglr@gmail.com; Aygün, Sezgin, E-mail: saygun@comu.edu.tr
In this study, we have investigated bulk viscous with strange quark matter attached to the string cloud for higher dimensional Friedman-Robertson-Walker (FRW) universe in Lyra geometry. By using varying deceleration parameter and conservation equations we have solved Einstein Field Equations (EFE’s) and obtained generalized exact solutions for our model. Also we have found that string is not survived for bulk viscous with strange quark matter attached to the string cloud in framework higher dimensional FRW universe in Lyra geometry. This result agrees with Kiran and Reddy, Krori et al, Sahoo and Mishra and Mohanty et al. in four and fivemore » dimensions.« less
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Droplet Growth Kinetics in Various Environments
NASA Astrophysics Data System (ADS)
Raatikainen, T. E.; Lathem, T. L.; Moore, R.; Lin, J. J.; Cerully, K. M.; Padro, L.; Lance, S.; Cozic, J.; Anderson, B. E.; Nenes, A.
2012-12-01
The largest uncertainties in the effects of atmospherics aerosols on the global radiation budget are related to their indirect effects on cloud properties (IPCC, the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007). Cloud formation is a kinetic process where the resulting cloud properties depend on aerosol properties and meteorological parameters such as updraft velocity (e.g. McFiggans et al., Atmos. Chem. Phys., 6, 2593-2649, 2006). Droplet growth rates are limited by the water vapor diffusion, but additional kinetic limitations, e.g., due to organic surface films, slow solute dissociation or highly viscous or glassy aerosol states have been hypothesized. Significant additional kinetic limitations can lead to increased cloud droplet number concentration, thus the effect is similar to those of increased aerosol number concentration or changes in vertical velocity (e.g. Nenes et al., Geophys. Res. Lett., 29, 1848, 2002). There are a few studies where slow droplet growth has been observed (e.g. Ruehl et al., Geophys. Res. Lett., 36, L15814, 2009), however, little is currently known about their global occurrence and magnitude. Cloud micro-physics models often describe kinetic limitations by an effective water vapor uptake coefficient or similar parameter. Typically, determining aerosol water vapor uptake coefficients requires experimental observations of droplet growth which are interpreted by a numerical droplet growth model where the uptake coefficient is an adjustable parameter (e.g. Kolb et al., Atmos. Chem. Phys., 10, 10561-10605, 2010). Such methods have not been practical for high time-resolution or long term field measurements, until a model was recently developed for analyzing Droplet Measurement Technologies (DMT) cloud condensation nuclei (CCN) counter data (Raatikainen et al., Atmos. Chem. Phys., 12, 4227-4243, 2012). Model verification experiments showed that the calibration aerosol droplet size can be predicted accurately for various instrument settings and also in the case of high CCN concentrations when water vapor depletion decreases supersaturation and droplet size (Lathem and Nenes, Aerosol Sci. Tech., 45, 604-615, 2011). The model also accounts for aerosol hygroscopicity and size distribution variations, which can have significant effects on the droplet size. We have examined cloud droplet activation and growth kinetics by analyzing several DMT CCN counter data sets collected from various environments including boreal forests, arctic areas, fresh and aged biomass burning plumes, and polluted and biogenically influenced urban areas (Raatikainen et al., In preparation, 2012). Model simulations show that the variations in observed droplet size are caused by water vapor depletion effects, changes in dry particle size distributions and hygroscopicity, and changes in instrument supersaturation profiles. This means that fast droplet growth kinetics with water uptake coefficient close to 0.2 is prevalent at least for the studied environments.
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Comparison of roadway roughness derived from LIDAR and SFM 3D point clouds.
DOT National Transportation Integrated Search
2015-10-01
This report describes a short-term study undertaken to investigate the potential for using dense three-dimensional (3D) point : clouds generated from light detection and ranging (LIDAR) and photogrammetry to assess roadway roughness. Spatially : cont...
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Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR
Bartholomeus, Harm M.; Kooistra, Lammert
2017-01-01
In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is labour intense and time demanding. Unmanned Aerial Vehicle (UAV)-borne laser scanning can be the way in between. In this study, we present first results and experiences with the RIEGL RiCOPTER with VUX®-1UAV ALS system and compare it with the well tested RIEGL VZ-400 TLS system. We scanned the same forest plots with both systems over the course of two days. We derived Digital Terrain Models (DTMs), Digital Surface Models (DSMs) and finally Canopy Height Models (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 cm higher in five plots with different canopy conditions. This showed that TLS could not always detect the top of canopy. Moreover, we extracted trunk segments of 58 trees for ALS and TLS simultaneously, of which 39 could be used to model Diameter at Breast Height (DBH). ALS DBH showed a high agreement with TLS DBH with a correlation coefficient of 0.98 and root mean square error of 4.24 cm. We conclude that RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions. Further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB). PMID:29039755
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Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR.
Brede, Benjamin; Lau, Alvaro; Bartholomeus, Harm M; Kooistra, Lammert
2017-10-17
In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is labour intense and time demanding. Unmanned Aerial Vehicle (UAV)-borne laser scanning can be the way in between. In this study, we present first results and experiences with the RIEGL RiCOPTER with VUX ® -1UAV ALS system and compare it with the well tested RIEGL VZ-400 TLS system. We scanned the same forest plots with both systems over the course of two days. We derived Digital Terrain Model (DTMs), Digital Surface Model (DSMs) and finally Canopy Height Model (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 c m higher in five plots with different canopy conditions. This showed that TLS could not always detect the top of canopy. Moreover, we extracted trunk segments of 58 trees for ALS and TLS simultaneously, of which 39 could be used to model Diameter at Breast Height (DBH). ALS DBH showed a high agreement with TLS DBH with a correlation coefficient of 0.98 and root mean square error of 4.24 c m . We conclude that RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions. Further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB).
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D Modeling of Components of a Garden by Using Point Cloud Data
NASA Astrophysics Data System (ADS)
Kumazakia, R.; Kunii, Y.
2016-06-01
Laser measurement is currently applied to several tasks such as plumbing management, road investigation through mobile mapping systems, and elevation model utilization through airborne LiDAR. Effective laser measurement methods have been well-documented in civil engineering, but few attempts have been made to establish equally effective methods in landscape engineering. By using point cloud data acquired through laser measurement, the aesthetic landscaping of Japanese gardens can be enhanced. This study focuses on simple landscape simulations for pruning and rearranging trees as well as rearranging rocks, lanterns, and other garden features by using point cloud data. However, such simulations lack concreteness. Therefore, this study considers the construction of a library of garden features extracted from point cloud data. The library would serve as a resource for creating new gardens and simulating gardens prior to conducting repairs. Extracted garden features are imported as 3ds Max objects, and realistic 3D models are generated by using a material editor system. As further work toward the publication of a 3D model library, file formats for tree crowns and trunks should be adjusted. Moreover, reducing the size of created models is necessary. Models created using point cloud data are informative because simply shaped garden features such as trees are often seen in the 3D industry.
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Pan, Tao; Deng, Tao; Zeng, Xinying; Dong, Wei; Yu, Shuijing
2016-01-01
The biological treatment of polycyclic aromatic hydrocarbons is an important issue. Most microbes have limited practical applications because of the poor bioavailability of polycyclic aromatic hydrocarbons. In this study, the extractive biodegradation of phenanthrene by Sphingomonas polyaromaticivorans was conducted by introducing the cloud point system. The cloud point system is composed of a mixture of (40 g/L) Brij 30 and Tergitol TMN-3, which are nonionic surfactants, in equal proportions. After phenanthrene degradation, a higher wet cell weight and lower phenanthrene residue were obtained in the cloud point system than that in the control system. According to the results of high-performance liquid chromatography, the residual phenanthrene preferred to partition from the dilute phase into the coacervate phase. The concentration of residual phenanthrene in the dilute phase (below 0.001 mg/L) is lower than its solubility in water (1.18 mg/L) after extractive biodegradation. Therefore, dilute phase detoxification was achieved, thus indicating that the dilute phase could be discharged without causing phenanthrene pollution. Bioavailability was assessed by introducing the apparent logP in the cloud point system. Apparent logP decreased significantly, thus indicating that the bioavailability of phenanthrene increased remarkably in the system. This study provides a potential application of biological treatment in water and soil contaminated by phenanthrene.
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NASA Astrophysics Data System (ADS)
Zhang, Yuyan; Guo, Quanli; Wang, Zhenchun; Yang, Degong
2018-03-01
This paper proposes a non-contact, non-destructive evaluation method for the surface damage of high-speed sliding electrical contact rails. The proposed method establishes a model of damage identification and calculation. A laser scanning system is built to obtain the 3D point cloud data of the rail surface. In order to extract the damage region of the rail surface, the 3D point cloud data are processed using iterative difference, nearest neighbours search and a data registration algorithm. The curvature of the point cloud data in the damage region is mapped to RGB color information, which can directly reflect the change trend of the curvature of the point cloud data in the damage region. The extracted damage region is divided into three prism elements by a method of triangulation. The volume and mass of a single element are calculated by the method of geometric segmentation. Finally, the total volume and mass of the damage region are obtained by the principle of superposition. The proposed method is applied to several typical injuries and the results are discussed. The experimental results show that the algorithm can identify damage shapes and calculate damage mass with milligram precision, which are useful for evaluating the damage in a further research stage.
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Properties of the +70 kilometers per second cloud toward HD 203664
NASA Technical Reports Server (NTRS)
Sembach, Kenneth R.
1995-01-01
I present high-resolution International Ultraviolet Explorer (IUE) spectra of the ultraviolet absorption in an intermediate-velocity interstellar cloud (nu(sub LSR) approximately equal to +70 km/s) toward HD 203664. The combined, multiple IUE images result in spectra with S/N = 15-40 and resolutions of approximately 20-25 km/s. The intermediate-velocity cloud absorption is present in ultraviolet lines of C II, C II(sup *), C IV, N I, O I, Mg I, Mg II, Al II, Al III, Si II, Si III, Si IV, S II, Cr II, Mn II, Fe II, and Zn II. The relative abundances of low-ionization species suggest an electron density of 0.15-0.34/cu cm and a temperature of 5300-6100 K in the neutral and weakly ionized gas. Given the presence of high-ionization gas tracers such as Si IV and C IV, ionized portions of the cloud probably contribute to the relatively large values of n(sub e) derived from measurements of the lower ionization species. The high-ionization species in the cloud have an abundance ratio, N(C IV)/N(Si IV) approximately equal to 4.5, similar to that inferred for collisionally ionized cloud interfaces at temperatures near 10(exp 5) K along other sight lines. When referenced to sulfur, the abundances of most elements in the cloud are within a factor of 5 of their solar values, which suggests that the +70 km/s gas has a previous origin in the Galactic disk despite a recent determination by Little et al. that the cloud lies at a distance of 200-1500 pc below the Galactic plane. I have checked this result against a model of the ionization for the diffuse ionized gas layer of the Galaxy and find that this conclusion is essentially unchanged as long as the ionization parameter is low as implied by the abundances of adjoining ionization states of aluminum and silicon. The processes responsible for the production of highly ionized gas in the +70 km/s cloud appear to be able to account for the inferred dust grain destruction as well.
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NASA Technical Reports Server (NTRS)
Hofmann, D. J.; Rosen, J. M.; Harder, J. W.
1988-01-01
Aerosol measurements collected from August 25-November 3, 1986 at McMurdo Station using balloon-borne optical particle counters are examined in order to study the relationship between aerosol and ozone distribution and the formation of polar stratospheric clouds (PSCs). Ozone, aerosol, and condensation nuclei profiles, and pressure, temperature, and humidity measurements are analyzed. It is observed that the height of the stratospheric sulfate layer decreases over the period of measurement suggesting that upwelling in the votex is not important in the zone depletion process. Three theories on PSC formation are described, and the effects of the aerosol measurements on the theories are considered. The three theories are: (1) the original theory of water vapor pressure over a solution of H2SO4 of Steele et al. (1983) and Hamill and Mc Master (1984); (2) the nitric acid theory of PSCs of Toon et al. (1986) and Hamill et al. (1986); and (3) the quasi-cirrus cloud theory of Heymsfield (1986).
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NASA Astrophysics Data System (ADS)
Rothmund, Sabrina; Niethammer, Uwe; Walter, Marco; Joswig, Manfred
2013-04-01
In recent years, the high-resolution and multi-temporal 3D mapping of the Earth's surface using terrestrial laser scanning (TLS), ground-based optical images and especially low-cost UAV-based aerial images (Unmanned Aerial Vehicle) has grown in importance. This development resulted from the progressive technical improvement of the imaging systems and the freely available multi-view stereo (MVS) software packages. These different methods of data acquisition for the generation of accurate, high-resolution digital surface models (DSMs) were applied as part of an eight-week field campaign at the Super-Sauze landslide (South French Alps). An area of approximately 10,000 m² with long-term average displacement rates greater than 0.01 m/day has been investigated. The TLS-based point clouds were acquired at different viewpoints with an average point spacing between 10 to 40 mm and at different dates. On these days, more than 50 optical images were taken on points along a predefined line on the side part of the landslide by a low-cost digital compact camera. Additionally, aerial images were taken by a radio-controlled mini quad-rotor UAV equipped with another low-cost digital compact camera. The flight altitude ranged between 20 m and 250 m and produced a corresponding ground resolution between 0.6 cm and 7 cm. DGPS measurements were carried out as well in order to geo-reference and validate the point cloud data. To generate unscaled photogrammetric 3D point clouds from a disordered and tilted image set, we use the widespread open-source software package Bundler and PMVS2 (University of Washington). These multi-temporal DSMs are required on the one hand to determine the three-dimensional surface deformations and on the other hand it will be required for differential correction for orthophoto production. Drawing on the example of the acquired data at the Super-Sauze landslide, we demonstrate the potential but also the limitations of the photogrammetric point clouds. To determine the quality of the photogrammetric point cloud, these point clouds are compared with the TLS-based DSMs. The comparison shows that photogrammetric points accuracies are in the range of cm to dm, therefore don't reach the quality of the high-resolution TLS-based DSMs. Further, the validation of the photogrammetric point clouds reveals that some of them have internal curvature effects. The advantage of the photogrammetric 3D data acquisition is the use of low-cost equipment and less time-consuming data collection in the field. While the accuracy of the photogrammetric point clouds is not as high as TLS-based DSMs, the advantages of the former method are seen when applied in areas where dm-range is sufficient.
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Automated Coarse Registration of Point Clouds in 3d Urban Scenes Using Voxel Based Plane Constraint
NASA Astrophysics Data System (ADS)
Xu, Y.; Boerner, R.; Yao, W.; Hoegner, L.; Stilla, U.
2017-09-01
For obtaining a full coverage of 3D scans in a large-scale urban area, the registration between point clouds acquired via terrestrial laser scanning (TLS) is normally mandatory. However, due to the complex urban environment, the automatic registration of different scans is still a challenging problem. In this work, we propose an automatic marker free method for fast and coarse registration between point clouds using the geometric constrains of planar patches under a voxel structure. Our proposed method consists of four major steps: the voxelization of the point cloud, the approximation of planar patches, the matching of corresponding patches, and the estimation of transformation parameters. In the voxelization step, the point cloud of each scan is organized with a 3D voxel structure, by which the entire point cloud is partitioned into small individual patches. In the following step, we represent points of each voxel with the approximated plane function, and select those patches resembling planar surfaces. Afterwards, for matching the corresponding patches, a RANSAC-based strategy is applied. Among all the planar patches of a scan, we randomly select a planar patches set of three planar surfaces, in order to build a coordinate frame via their normal vectors and their intersection points. The transformation parameters between scans are calculated from these two coordinate frames. The planar patches set with its transformation parameters owning the largest number of coplanar patches are identified as the optimal candidate set for estimating the correct transformation parameters. The experimental results using TLS datasets of different scenes reveal that our proposed method can be both effective and efficient for the coarse registration task. Especially, for the fast orientation between scans, our proposed method can achieve a registration error of less than around 2 degrees using the testing datasets, and much more efficient than the classical baseline methods.
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NASA Astrophysics Data System (ADS)
Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero
2017-06-01
During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are no shadows on intensity images produced from the data. These are significant advantages in developing automated classification and change detection procedures.
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Grabowski, W. W.; Wang, L. -P.; Prabha, T. V.
2015-01-27
This paper discusses impacts of cloud and precipitation processes on macrophysical properties of shallow convective clouds as simulated by a large eddy model applying warm-rain bin microphysics. Simulations with and without collision–coalescence are considered with cloud condensation nuclei (CCN) concentrations of 30, 60, 120, and 240 mg -1. Simulations with collision–coalescence include either the standard gravitational collision kernel or a novel kernel that includes enhancements due to the small-scale cloud turbulence. Simulations with droplet collisions were discussed in Wyszogrodzki et al. (2013) focusing on the impact of the turbulent collision kernel. The current paper expands that analysis and puts modelmore » results in the context of previous studies. Despite a significant increase of the drizzle/rain with the decrease of CCN concentration, enhanced by the effects of the small-scale turbulence, impacts on the macroscopic cloud field characteristics are relatively minor. Model results show a systematic shift in the cloud-top height distributions, with an increasing contribution of deeper clouds for stronger precipitating cases. We show that this is consistent with the explanation suggested in Wyszogrodzki et al. (2013); namely, the increase of drizzle/rain leads to a more efficient condensate offloading in the upper parts of the cloud field. A second effect involves suppression of the cloud droplet evaporation near cloud edges in low-CCN simulations, as documented in previous studies (e.g., Xue and Feingold, 2006). We pose the question whether the effects of cloud turbulence on drizzle/rain formation in shallow cumuli can be corroborated by remote sensing observations, for instance, from space. Although a clear signal is extracted from model results, we argue that the answer is negative due to uncertainties caused by the temporal variability of the shallow convective cloud field, sampling and spatial resolution of the satellite data, and overall accuracy of remote sensing retrievals.« less
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NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)
2001-01-01
Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by clouds, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.
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New Developments in the SCIAMACHY L2 Ground Processor
NASA Astrophysics Data System (ADS)
Gretschany, Sergei; Lichtenberg, Günter; Meringer, Markus; Theys, Nicolas; Lerot, Christophe; Liebing, Patricia; Noel, Stefan; Dehn, Angelika; Fehr, Thorsten
2016-04-01
SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric ChartographY) aboard ESA's environmental satellite ENVISAT observed the Earth's atmosphere in limb, nadir, and solar/lunar occultation geometries covering the UV-Visible to NIR spectral range. It is a joint project of Germany, the Netherlands and Belgium and was launched in February 2002. SCIAMACHY doubled its originally planned in-orbit lifetime of five years before the communication to ENVISAT was severed in April 2012, and the mission entered its post-operational phase. In order to preserve the best quality of the outstanding data recorded by SCIAMACHY, data processors are still being updated. This presentation will highlight three new developments that are currently being incorporated into the forthcoming Version 7 of ESA's operational Level 2 processor: 1. Tropospheric BrO, a new retrieval based on the scientific algorithm of (Theys et al., 2011). This algorithm had been originally developed for the GOME-2 sensor and later adapted for SCIAMACHY. The main principle of the new algorithm is to utilize BrO total columns (already an operational product) and split them into stratospheric VCDstrat and tropospheric VCDtrop fractions. BrO VCDstrat is determined from a climatological approach, driven by SCIAMACHY O3 and NO2 observations. VCDtrop is then determined simply as a difference: VCDtrop = VCDtotal - VCDstrat. 2. Improved cloud flagging using limb measurements (Liebing, 2015). Limb cloud flags are already part of the SCIAMACHY L2 product. They are currently calculated employing the scientific algorithm developed by (Eichmann et al., 2015). Clouds are categorized into four types: water, ice, polar stratospheric and noctilucent clouds. High atmospheric aerosol loadings, however, often lead to spurious cloud flags, when aerosols had been misidentified as clouds. The new algorithm will better discriminate between aerosol and clouds. It will also have a higher sensitivity w.r.t. thin clouds. 3. A new, future-proof file format for the level 2 product based on NetCDF. Although the final concept for the new format is still under discussion within the SCIAMACHY Quality Working Group, main features of the new format have already been clarified. The data format should be aligned and harmonized with other missions (esp. Sentinels and GOME-1). Splitting of the L2 products into profile and column products is also considered. Additionally, reading routines for the new formats will be developed and provided. References: K.-U. Eichmann et al., Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results, Atmos. Meas. Tech. Discuss., 8, 8295-8352, 2015. P. Liebing, New Limb Cloud Detection Algorithm Theoretical Basis Document, 2015. N. Theys et al., Global observations of tropospheric BrO columns using GOME-2 satellite data, Atmos. Chem. Phys., 11, 1791-1811, 2011.
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NASA Astrophysics Data System (ADS)
Coppersmith, R.; Schultz-Fellenz, E. S.; Sussman, A. J.; Vigil, S.; Dzur, R.; Norskog, K.; Kelley, R.; Miller, L.
2015-12-01
While long-term objectives of monitoring and verification regimes include remote characterization and discrimination of surficial geologic and topographic features at sites of interest, ground truth data is required to advance development of remote sensing techniques. Increasingly, it is desirable for these ground-based or ground-proximal characterization methodologies to be as nimble, efficient, non-invasive, and non-destructive as their higher-altitude airborne counterparts while ideally providing superior resolution. For this study, the area of interest is an alluvial site at the Nevada National Security Site intended for use in the Source Physics Experiment's (Snelson et al., 2013) second phase. Ground-truth surface topographic characterization was performed using a DJI Inspire 1 unmanned aerial system (UAS), at very low altitude (< 5-30m AGL). 2D photographs captured by the standard UAS camera payload were imported into Agisoft Photoscan to create three-dimensional point clouds. Within the area of interest, careful installation of surveyed ground control fiducial markers supplied necessary targets for field collection, and information for model georectification. The resulting model includes a Digital Elevation Model derived from 2D imagery. It is anticipated that this flexible and versatile characterization process will provide point cloud data resolution equivalent to a purely ground-based LiDAR scanning deployment (e.g., 1-2cm horizontal and vertical resolution; e.g., Sussman et al., 2012; Schultz-Fellenz et al., 2013). In addition to drastically increasing time efficiency in the field, the UAS method also allows for more complete coverage of the study area when compared to ground-based LiDAR. Comparison and integration of these data with conventionally-acquired airborne LiDAR data from a higher-altitude (~ 450m) platform will aid significantly in the refinement of technologies and detection capabilities of remote optical systems to identify and detect surface geologic and topographic signatures of interest. This work includes a preliminary comparison of surface signatures detected from varying standoff distances to assess current sensor performance and benefits.
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Star formation induced by cloud-cloud collisions and galactic giant molecular cloud evolution
NASA Astrophysics Data System (ADS)
Kobayashi, Masato I. N.; Kobayashi, Hiroshi; Inutsuka, Shu-ichiro; Fukui, Yasuo
2018-05-01
Recent millimeter/submillimeter observations towards nearby galaxies have started to map the whole disk and to identify giant molecular clouds (GMCs) even in the regions between galactic spiral structures. Observed variations of GMC mass functions in different galactic environments indicates that massive GMCs preferentially reside along galactic spiral structures whereas inter-arm regions have many small GMCs. Based on the phase transition dynamics from magnetized warm neutral medium to molecular clouds, Kobayashi et al. (2017, ApJ, 836, 175) proposes a semi-analytical evolutionary description for GMC mass functions including a cloud-cloud collision (CCC) process. Their results show that CCC is less dominant in shaping the mass function of GMCs than the accretion of dense H I gas driven by the propagation of supersonic shock waves. However, their formulation does not take into account the possible enhancement of star formation by CCC. Millimeter/submillimeter observations within the Milky Way indicate the importance of CCC in the formation of star clusters and massive stars. In this article, we reformulate the time-evolution equation largely modified from Kobayashi et al. (2017, ApJ, 836, 175) so that we additionally compute star formation subsequently taking place in CCC clouds. Our results suggest that, although CCC events between smaller clouds are more frequent than the ones between massive GMCs, CCC-driven star formation is mostly driven by massive GMCs ≳ 10^{5.5} M_{⊙} (where M⊙ is the solar mass). The resultant cumulative CCC-driven star formation may amount to a few 10 percent of the total star formation in the Milky Way and nearby galaxies.
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NASA Astrophysics Data System (ADS)
Ding, J.; Wang, G.; Xiong, L.; Zhou, X.; England, E.
2017-12-01
Coastal regions are naturally vulnerable to impact from long-term coastal erosion and episodic coastal hazards caused by extreme weather events. Major geomorphic changes can occur within a few hours during storms. Prediction of storm impact, costal planning and resilience observation after natural events all require accurate and up-to-date topographic maps of coastal morphology. Thus, the ability to conduct rapid and high-resolution-high-accuracy topographic mapping is of critical importance for long-term coastal management and rapid response after natural hazard events. Terrestrial laser scanning (TLS) techniques have been frequently applied to beach and dune erosion studies and post hazard responses. However, TLS surveying is relatively slow and costly for rapid surveying. Furthermore, TLS surveying unavoidably retains gray areas that cannot be reached by laser pulses, particularly in wetland areas where lack of direct access in most cases. Aerial mapping using photogrammetry from images taken by unmanned aerial vehicles (UAV) has become a new technique for rapid topographic mapping. UAV photogrammetry mapping techniques provide the ability to map coastal features quickly, safely, inexpensively, on short notice and with minimal impact. The primary products from photogrammetry are point clouds similar to the LiDAR point clouds. However, a large number of ground control points (ground truth) are essential for obtaining high-accuracy UAV maps. The ground control points are often obtained by GPS survey simultaneously with the TLS survey in the field. The GPS survey could be a slow and arduous process in the field. This study aims to develop methods for acquiring a huge number of ground control points from TLS survey and validating point clouds obtained from photogrammetry with the TLS point clouds. A Rigel VZ-2000 TLS scanner was used for developing laser point clouds and a DJI Phantom 4 Pro UAV was used for acquiring images. The aerial images were processed with the Photogrammetry mapping software Agisoft PhotoScan. A workflow for conducting rapid TLS and UAV survey in the field and integrating point clouds obtained from TLS and UAV surveying will be introduced. Key words: UAV photogrammetry, ground control points, TLS, coastal morphology, topographic mapping
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Sparse Unorganized Point Cloud Based Relative Pose Estimation for Uncooperative Space Target.
Yin, Fang; Chou, Wusheng; Wu, Yun; Yang, Guang; Xu, Song
2018-03-28
This paper proposes an autonomous algorithm to determine the relative pose between the chaser spacecraft and the uncooperative space target, which is essential in advanced space applications, e.g., on-orbit serving missions. The proposed method, named Congruent Tetrahedron Align (CTA) algorithm, uses the very sparse unorganized 3D point cloud acquired by a LIDAR sensor, and does not require any prior pose information. The core of the method is to determine the relative pose by looking for the congruent tetrahedron in scanning point cloud and model point cloud on the basis of its known model. The two-level index hash table is built for speeding up the search speed. In addition, the Iterative Closest Point (ICP) algorithm is used for pose tracking after CTA. In order to evaluate the method in arbitrary initial attitude, a simulated system is presented. Specifically, the performance of the proposed method to provide the initial pose needed for the tracking algorithm is demonstrated, as well as their robustness against noise. Finally, a field experiment is conducted and the results demonstrated the effectiveness of the proposed method.
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NASA Astrophysics Data System (ADS)
Hess, M. R.; Petrovic, V.; Kuester, F.
2017-08-01
Digital documentation of cultural heritage structures is increasingly more common through the application of different imaging techniques. Many works have focused on the application of laser scanning and photogrammetry techniques for the acquisition of threedimensional (3D) geometry detailing cultural heritage sites and structures. With an abundance of these 3D data assets, there must be a digital environment where these data can be visualized and analyzed. Presented here is a feedback driven visualization framework that seamlessly enables interactive exploration and manipulation of massive point cloud data. The focus of this work is on the classification of different building materials with the goal of building more accurate as-built information models of historical structures. User defined functions have been tested within the interactive point cloud visualization framework to evaluate automated and semi-automated classification of 3D point data. These functions include decisions based on observed color, laser intensity, normal vector or local surface geometry. Multiple case studies are presented here to demonstrate the flexibility and utility of the presented point cloud visualization framework to achieve classification objectives.
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Automated Point Cloud Correspondence Detection for Underwater Mapping Using AUVs
NASA Technical Reports Server (NTRS)
Hammond, Marcus; Clark, Ashley; Mahajan, Aditya; Sharma, Sumant; Rock, Stephen
2015-01-01
An algorithm for automating correspondence detection between point clouds composed of multibeam sonar data is presented. This allows accurate initialization for point cloud alignment techniques even in cases where accurate inertial navigation is not available, such as iceberg profiling or vehicles with low-grade inertial navigation systems. Techniques from computer vision literature are used to extract, label, and match keypoints between "pseudo-images" generated from these point clouds. Image matches are refined using RANSAC and information about the vehicle trajectory. The resulting correspondences can be used to initialize an iterative closest point (ICP) registration algorithm to estimate accumulated navigation error and aid in the creation of accurate, self-consistent maps. The results presented use multibeam sonar data obtained from multiple overlapping passes of an underwater canyon in Monterey Bay, California. Using strict matching criteria, the method detects 23 between-swath correspondence events in a set of 155 pseudo-images with zero false positives. Using less conservative matching criteria doubles the number of matches but introduces several false positive matches as well. Heuristics based on known vehicle trajectory information are used to eliminate these.
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NASA Astrophysics Data System (ADS)
Angelats, E.; Parés, M. E.; Kumar, P.
2018-05-01
Accessible cities with accessible services are an old claim of people with reduced mobility. But this demand is still far away of becoming a reality as lot of work is required to be done yet. First step towards accessible cities is to know about real situation of the cities and its pavement infrastructure. Detailed maps or databases on street slopes, access to sidewalks, mobility in public parks and gardens, etc. are required. In this paper, we propose to use smartphone based photogrammetric point clouds, as a starting point to create accessible maps or databases. This paper analyses the performance of these point clouds and the complexity of the image acquisition procedure required to obtain them. The paper proves, through two test cases, that smartphone technology is an economical and feasible solution to get the required information, which is quite often seek by city planners to generate accessible maps. The proposed approach paves the way to generate, in a near term, accessibility maps through the use of point clouds derived from crowdsourced smartphone imagery.
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Sparse Unorganized Point Cloud Based Relative Pose Estimation for Uncooperative Space Target
Chou, Wusheng; Wu, Yun; Yang, Guang; Xu, Song
2018-01-01
This paper proposes an autonomous algorithm to determine the relative pose between the chaser spacecraft and the uncooperative space target, which is essential in advanced space applications, e.g., on-orbit serving missions. The proposed method, named Congruent Tetrahedron Align (CTA) algorithm, uses the very sparse unorganized 3D point cloud acquired by a LIDAR sensor, and does not require any prior pose information. The core of the method is to determine the relative pose by looking for the congruent tetrahedron in scanning point cloud and model point cloud on the basis of its known model. The two-level index hash table is built for speeding up the search speed. In addition, the Iterative Closest Point (ICP) algorithm is used for pose tracking after CTA. In order to evaluate the method in arbitrary initial attitude, a simulated system is presented. Specifically, the performance of the proposed method to provide the initial pose needed for the tracking algorithm is demonstrated, as well as their robustness against noise. Finally, a field experiment is conducted and the results demonstrated the effectiveness of the proposed method. PMID:29597323
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NASA Astrophysics Data System (ADS)
Steer, Philippe; Lague, Dimitri; Gourdon, Aurélie; Croissant, Thomas; Crave, Alain
2016-04-01
The grain-scale morphology of river sediments and their size distribution are important factors controlling the efficiency of fluvial erosion and transport. In turn, constraining the spatial evolution of these two metrics offer deep insights on the dynamics of river erosion and sediment transport from hillslopes to the sea. However, the size distribution of river sediments is generally assessed using statistically-biased field measurements and determining the grain-scale shape of river sediments remains a real challenge in geomorphology. Here we determine, with new methodological approaches based on the segmentation and geomorphological fitting of 3D point cloud dataset, the size distribution and grain-scale shape of sediments located in river environments. Point cloud segmentation is performed using either machine-learning algorithms or geometrical criterion, such as local plan fitting or curvature analysis. Once the grains are individualized into several sub-clouds, each grain-scale morphology is determined using a 3D geometrical fitting algorithm applied on the sub-cloud. If different geometrical models can be conceived and tested, only ellipsoidal models were used in this study. A phase of results checking is then performed to remove grains showing a best-fitting model with a low level of confidence. The main benefits of this automatic method are that it provides 1) an un-biased estimate of grain-size distribution on a large range of scales, from centimeter to tens of meters; 2) access to a very large number of data, only limited by the number of grains in the point-cloud dataset; 3) access to the 3D morphology of grains, in turn allowing to develop new metrics characterizing the size and shape of grains. The main limit of this method is that it is only able to detect grains with a characteristic size greater than the resolution of the point cloud. This new 3D granulometric method is then applied to river terraces both in the Poerua catchment in New-Zealand and along the Laonong river in Taiwan, which point clouds were obtained using both terrestrial lidar scanning and structure from motion photogrammetry.
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Modeling Cloud Phase Fraction Based on In-situ Observations in Stratiform Clouds
NASA Astrophysics Data System (ADS)
Boudala, F. S.; Isaac, G. A.
2005-12-01
Mixed-phase clouds influence weather and climate in several ways. Due to the fact that they exhibit very different optical properties as compared to ice or liquid only clouds, they play an important role in the earth's radiation balance by modifying the optical properties of clouds. Precipitation development in clouds is also enhanced under mixed-phase conditions and these clouds may contain large supercooled drops that freeze quickly in contact with aircraft surfaces that may be a hazard to aviation. The existence of ice and liquid phase clouds together in the same environment is thermodynamically unstable, and thus they are expected to disappear quickly. However, several observations show that mixed-phase clouds are relatively stable in the natural environment and last for several hours. Although there have been some efforts being made in the past to study the microphysical properties of mixed-phase clouds, there are still a number of uncertainties in modeling these clouds particularly in large scale numerical models. In most models, very simple temperature dependent parameterizations of cloud phase fraction are being used to estimate the fraction of ice or liquid phase in a given mixed-phase cloud. In this talk, two different parameterizations of ice fraction using in-situ aircraft measurements of cloud microphysical properties collected in extratropical stratiform clouds during several field programs will be presented. One of the parameterizations has been tested using a single prognostic equation developed by Tremblay et al. (1996) for application in the Canadian regional weather prediction model. The addition of small ice particles significantly increased the vapor deposition rate when the natural atmosphere is assumed to be water saturated, and thus this enhanced the glaciation of simulated mixed-phase cloud via the Bergeron-Findeisen process without significantly affecting the other cloud microphysical processes such as riming and particle sedimentation rates. After the water vapor pressure in mixed-phase cloud was modified based on the Lord et al. (1984) scheme by weighting the saturation water vapor pressure with ice fraction, it was possible to simulate more stable mixed-phase cloud. It was also noted that the ice particle concentration (L>100 μm) in mixed-phase cloud is lower on average by a factor 3 and as a result the parameterization should be corrected for this effect. After accounting for this effect, the parameterized ice fraction agreed well with observed mean ice fraction.
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Surface Fitting Filtering of LIDAR Point Cloud with Waveform Information
NASA Astrophysics Data System (ADS)
Xing, S.; Li, P.; Xu, Q.; Wang, D.; Li, P.
2017-09-01
Full-waveform LiDAR is an active technology of photogrammetry and remote sensing. It provides more detailed information about objects along the path of a laser pulse than discrete-return topographic LiDAR. The point cloud and waveform information with high quality can be obtained by waveform decomposition, which could make contributions to accurate filtering. The surface fitting filtering method with waveform information is proposed to present such advantage. Firstly, discrete point cloud and waveform parameters are resolved by global convergent Levenberg Marquardt decomposition. Secondly, the ground seed points are selected, of which the abnormal ones are detected by waveform parameters and robust estimation. Thirdly, the terrain surface is fitted and the height difference threshold is determined in consideration of window size and mean square error. Finally, the points are classified gradually with the rising of window size. The filtering process is finished until window size is larger than threshold. The waveform data in urban, farmland and mountain areas from "WATER (Watershed Allied Telemetry Experimental Research)" are selected for experiments. Results prove that compared with traditional method, the accuracy of point cloud filtering is further improved and the proposed method has highly practical value.
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Kim, Joongheon; Kim, Jong-Kook
2016-01-01
This paper addresses the computation procedures for estimating the impact of interference in 60 GHz IEEE 802.11ad uplink access in order to construct visual big-data database from randomly deployed surveillance camera sensing devices. The acquired large-scale massive visual information from surveillance camera devices will be used for organizing big-data database, i.e., this estimation is essential for constructing centralized cloud-enabled surveillance database. This performance estimation study captures interference impacts on the target cloud access points from multiple interference components generated by the 60 GHz wireless transmissions from nearby surveillance camera devices to their associated cloud access points. With this uplink interference scenario, the interference impacts on the main wireless transmission from a target surveillance camera device to its associated target cloud access point with a number of settings are measured and estimated under the consideration of 60 GHz radiation characteristics and antenna radiation pattern models.
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Formation of compact HII regions possibly triggered by cloud-cloud collision
NASA Astrophysics Data System (ADS)
Ohama, Akio; Torii, Kazufumi; Hasegawa, Keisuke; Fukui, Yasuo
2015-08-01
Compact HII regions are ionized by young high-mass star(s) and ~1000 compact HII regions are cataloged in the Galaxy (Urquhart et al. MNRAS 443, 1555-1586 (2014)). Compact HII regions are one of the major populations of Galactic HII regions. The molecular environments around compact HII regions are however not well understood due to lack of extensive molecular surveys. In order to better understand formation of exciting stars and compact HII regions, we have carried out a systematic study of molecular clouds toward compact HII regions by using the 12CO datasets obtained with the JCMT and NANTEN2 telescopes for l = 10 - 56, and present here the first results.In one of the present samples, RCW166, we have discovered that the HII region is associated with two molecular clouds whose velocity separation is ~10 km s-1 the two clouds show complimentary spatial distributions, where one of the clouds have a cavity-like distribution apparently embracing the other. We present an interpretation that the two clouds collided with each other and the cavity-like distribution represents a hole created by the collision in the larger cloud as modeled by Habe and Ohta (1992). Similar molecular distributions are often found in the other compact HII regions in the present study.A recent study by Torii et al. (2015, arXiv:1503.00070) indicates that the Spitzer bubble RCW120 was formed by cloud-cloud collision where the inside of the cavity is fully ionized by the exiting stars. RCW166, on the other hand, shows that only a small part of the cavity, the compact HII region, is ionized. We thus suggest that RCW166 represents an evolutionary stage corresponding to an earlier phase of RCW120 in the collision scenario.
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Rao, Wenwei; Wang, Yun; Han, Juan; Wang, Lei; Chen, Tong; Liu, Yan; Ni, Liang
2015-06-25
The cloud point of thermosensitive triblock polymer L61, poly(ethylene oxide)-poly(propylene oxide)-poly(ethylene oxide) (PEO-PPO-PEO), was determined in the presence of various electrolytes (K2HPO4, (NH4)3C6H5O7, and K3C6H5O7). The cloud point of L61 was lowered by the addition of electrolytes, and the cloud point of L61 decreased linearly with increasing electrolyte concentration. The efficacy of electrolytes on reducing cloud point followed the order: K3C6H5O7 > (NH4)3C6H5O7 > K2HPO4. With the increase in salt concentration, aqueous two-phase systems exhibited a phase inversion. In addition, increasing the temperature reduced the concentration of salt needed that could promote phase inversion. The phase diagrams and liquid-liquid equilibrium data of the L61-K2HPO4/(NH4)3C6H5O7/K3C6H5O7 aqueous two-phase systems (before the phase inversion but also after phase inversion) were determined at T = (25, 30, and 35) °C. Phase diagrams of aqueous two-phase systems were fitted to a four-parameter empirical nonlinear expression. Moreover, the slopes of the tie-lines and the area of two-phase region in the diagram have a tendency to rise with increasing temperature. The capacity of different salts to induce aqueous two-phase system formation was the same order as the ability of salts to reduce the cloud point.
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FORMING CHONDRULES IN IMPACT SPLASHES. II. VOLATILE RETENTION
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dullemond, Cornelis Petrus; Harsono, Daniel; Stammler, Sebastian Markus
2016-11-20
Solving the mystery of the origin of chondrules is one of the most elusive goals in the field of meteoritics. Recently, the idea of planet(esimal) collisions releasing splashes of lava droplets, long considered out of favor, has been reconsidered as a possible origin of chondrules by several papers. One of the main problems with this idea is the lack of quantitative and simple models that can be used to test this scenario by directly comparing to the many known observables of chondrules. In Paper I of this series, we presented a simple thermal evolution model of a spherically symmetric expandingmore » cloud of molten lava droplets that is assumed to emerge from a collision between two planetesimals. The production of lava could be either because the two planetesimals were already in a largely molten (or almost molten) state due to heating by {sup 26}Al, or due to impact jetting at higher impact velocities. In the present paper, number II of this series, we use this model to calculate whether or not volatile elements such as Na and K will remain abundant in these droplets or whether they will get depleted due to evaporation. The high density of the droplet cloud (e.g., small distance between adjacent droplets) causes the vapor to quickly reach saturation pressure and thus shuts down further evaporation. We show to what extent, and under which conditions, this keeps the abundances of these elements high, as is seen in chondrules. We find that for most parameters of our model (cloud mass, expansion velocity, initial temperature) the volatile elements Mg, Si, and Fe remain entirely in the chondrules. The Na and K abundances inside the droplets will initially stay mostly at their initial values due to the saturation of the vapor pressure, but at some point start to drop due to the cloud expansion. However, as soon as the temperature starts to decrease, most or all of the vapor recondenses again. At the end, the Na and K elements retain most of their initial abundances, albeit occasionally somewhat reduced, depending on the parameters of the expanding cloud model. These findings appear to be qualitatively consistent with the analysis of Semarkona Type II chondrules by Hewins et al. who found evidence for sodium evaporation followed by recondensation.« less
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NASA Astrophysics Data System (ADS)
Bundke, U.; Jaenicke, R.; Klein, H.; Nillius, B.; Reimann, B.; Wetter, T.; Bingemer, H.
2009-04-01
Ice formation in clouds is a subject of great practical and fundamental importance since the occurrence of ice particle initializes dramatic changes in the microphysical structure of the cloud, which finally ends in the formation of precipitation. The initially step of ice formation is largely unknown. Homogenous nucleation of ice occurs only below -40 °C. If an ice nucleus (IN) is present, heterogeneous nucleation may occur at higher temperature. Here deposition freezing, condensation and immersion freezing as well as contact freezing are known. Also growth rates of ice particles are known as function of crystal surface properties, temperature and super saturation. Timescales for homogenous freezing activation in the order of 0.01 seconds and nucleation rates have been measured by Anderson et al. (1980) and Hagen et al., (1981) using their expansion cloud chamber. This contribution of deposition mode freezing measurements by the ice nucleus counter FINCH presents evidence that the activation timescale of this freezing mode is in the order of 1E-3 seconds. FINCH is an Ice Nucleus counter which activates IN in a supersaturated environment at freezing temperatures. The activation conditions are actively controlled by mixing three gas flows (aerosol, particle-free cold-dry and warm-humid flows).See Bundke et al. 2008 for details. In a special operation mode of FINCH we are able to produce a controlled peak super saturation in the order of 1 ms duration. For several test aerosols the results observed in this particular mode are comparable to normal mode operations, where the maximum super saturation remains for more than a second, thus leading to the conclusion that the time for activation is in the order of 1ms or less. References: R.J. Anderson et al, "A Study of Homogeneous Condensation Freezing Nucleation of Small Water Droplets in an Expansion Cloud Chamber, Journal of the Atmospheric Sciences, Vol. 37, 2508-2520, 1980 U.Bundke et al., "The fast Ice Nucleus chamber FINCH", Atmospheric Research, Volume 90, Issues 2-4, 180-186, DOI:10.1016/j.atmosres.2008.02.008, 2008 D.E. Hagen et al., "Homogenous Condensation Freezing Nucleation Rate Measurements for Small Water Droplets in an Expansion Cloud Chamber", Journal of the Atmospheric Sciences, Vol 38, 1236-1243, 1981 Acknowledgments: This work was supported by the German Research Foundation: SFB 641 "Tropospheric Ice Phase" TP A1, SPP1294 BU1432/3-1, JA344/12-1, by the Helmholtz Association: VI-233 "Aerosol Cloud Interactions" and by and by the EU FP6 Infastructure Project EUSAAR.
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Intensity-corrected Herschel Observations of Nearby Isolated Low-mass Clouds
NASA Astrophysics Data System (ADS)
Sadavoy, Sarah I.; Keto, Eric; Bourke, Tyler L.; Dunham, Michael M.; Myers, Philip C.; Stephens, Ian W.; Di Francesco, James; Webb, Kristi; Stutz, Amelia M.; Launhardt, Ralf; Tobin, John J.
2018-01-01
We present intensity-corrected Herschel maps at 100, 160, 250, 350, and 500 μm for 56 isolated low-mass clouds. We determine the zero-point corrections for Herschel Photodetector Array Camera and Spectrometer (PACS) and Spectral Photometric Imaging Receiver (SPIRE) maps from the Herschel Science Archive (HSA) using Planck data. Since these HSA maps are small, we cannot correct them using typical methods. Here we introduce a technique to measure the zero-point corrections for small Herschel maps. We use radial profiles to identify offsets between the observed HSA intensities and the expected intensities from Planck. Most clouds have reliable offset measurements with this technique. In addition, we find that roughly half of the clouds have underestimated HSA-SPIRE intensities in their outer envelopes relative to Planck, even though the HSA-SPIRE maps were previously zero-point corrected. Using our technique, we produce corrected Herschel intensity maps for all 56 clouds and determine their line-of-sight average dust temperatures and optical depths from modified blackbody fits. The clouds have typical temperatures of ∼14–20 K and optical depths of ∼10‑5–10‑3. Across the whole sample, we find an anticorrelation between temperature and optical depth. We also find lower temperatures than what was measured in previous Herschel studies, which subtracted out a background level from their intensity maps to circumvent the zero-point correction. Accurate Herschel observations of clouds are key to obtaining accurate density and temperature profiles. To make such future analyses possible, intensity-corrected maps for all 56 clouds are publicly available in the electronic version. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.
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NASA Astrophysics Data System (ADS)
Irwin, Patrick G. J.; Wong, Michael H.; Simon, Amy A.; Orton, G. S.; Toledo, Daniel
2017-05-01
In November 2014 Uranus was observed with the Wide Field Camera 3 (WFC3) instrument of the Hubble Space Telescope as part of the Hubble 2020: Outer Planet Atmospheres Legacy program, OPAL. OPAL annually maps Jupiter, Uranus and Neptune (and will also map Saturn from 2018) in several visible/near-infrared wavelength filters. The Uranus 2014 OPAL observations were made on the 8/9th November at a time when a huge cloud complex, first observed by de Pater et al. (2015) and subsequently tracked by professional and amateur astronomers (Sayanagi et al., 2016), was present at 30-40°N. We imaged the entire visible atmosphere, including the storm system, in seven filters spanning 467-924 nm, capturing variations in the coloration of Uranus' clouds and also vertical distribution due to wavelength dependent changes in Rayleigh scattering and methane absorption optical depth. Here we analyse these new HST observations with the NEMESIS radiative-transfer and retrieval code in multiple-scattering mode to determine the vertical cloud structure in and around the storm cloud system. The same storm system was also observed in the H-band (1.4-1.8 μm) with the SINFONI Integral Field Unit Spectrometer on the Very Large Telescope (VLT) on 31st October and 11th November, reported by Irwin et al. (2016, 10.1016/j.icarus.2015.09.010). To constrain better the cloud particle sizes and scattering properties over a wide wavelength range we also conducted a limb-darkening analysis of the background cloud structure in the 30-40°N latitude band by simultaneously fitting: a) these HST/OPAL observations at a range of zenith angles; b) the VLT/SINFONI observations at a range of zenith angles; and c) IRTF/SpeX observations of this latitude band made in 2009 at a single zenith angle of 23°, spanning the wavelength range 0.8-1.8 μm (Irwin et al., 2015, 10.1016/j.icarus.2014.12.020). We find that the HST observations, and the combined HST/VLT/IRTF observations at all locations are well modelled with a three-component cloud comprised of: 1) a vertically thin, but optically thick 'deep' tropospheric cloud at a pressure of ∼ 2 bars; 2) a methane-ice cloud based at the methane-condensation level of 1.23 bar, with variable vertical extent; and 3) a vertically extended tropospheric haze, also based at the methane-condensation level of ∼ 1.23 bar. We find that modelling both haze and tropospheric cloud with particles having an effective radius of ∼ 0.1 μm provides a good fit the observations, although for the tropospheric cloud, particles with an effective radius as large as 1.0 μm provide a similarly good fit. We find that the particles in both the tropospheric cloud and haze are more scattering at short wavelengths, giving them a blue colour, but are more absorbing at longer wavelengths, especially for the tropospheric haze. We find that the spectra of the storm clouds are well modelled by localised thickening and vertical extension of the methane-ice cloud. For the particles in the storm clouds, which we assume to be composed of methane ice particles, we find that their mean radii must lie somewhere in the range 0.1 - 1.0 μ m. We find that the high clouds have low integrated opacity, and that "streamers" reminiscent of convective thunderstorm anvils are confined to levels deeper than 1 bar. These results argue against vigorous moist convective origins for the cloud features.
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NASA Astrophysics Data System (ADS)
Schwind, Michael
Structure from Motion (SfM) is a photogrammetric technique whereby three-dimensional structures (3D) are estimated from overlapping two-dimensional (2D) image sequences. It is studied in the field of computer vision and utilized in fields such as archeology, engineering, and the geosciences. Currently, many SfM software packages exist that allow for the generation of 3D point clouds. Little work has been done to show how topographic data generated from these software differ over varying terrain types and why they might produce different results. This work aims to compare and characterize the differences between point clouds generated by three different SfM software packages: two well-known proprietary solutions (Pix4D, Agisoft PhotoScan) and one open source solution (OpenDroneMap). Five terrain types were imaged utilizing a DJI Phantom 3 Professional small unmanned aircraft system (sUAS). These terrain types include a marsh environment, a gently sloped sandy beach and jetties, a forested peninsula, a house, and a flat parking lot. Each set of imagery was processed with each software and then directly compared to each other. Before processing the sets of imagery, the software settings were analyzed and chosen in a manner that allowed for the most similar settings to be set across the three software types. This was done in an attempt to minimize point cloud differences caused by dissimilar settings. The characteristics of the resultant point clouds were then compared with each other. Furthermore, a terrestrial light detection and ranging (LiDAR) survey was conducted over the flat parking lot using a Riegl VZ- 400 scanner. This data served as ground truth in order to conduct an accuracy assessment of the sUAS-SfM point clouds. Differences were found between the different results, apparent not only in the characteristics of the clouds, but also the accuracy. This study allows for users of SfM photogrammetry to have a better understanding of how different processing software compare and the inherent sensitivity of SfM automation in 3D reconstruction. Because this study used mostly default settings within the software, it would be beneficial for further research to investigate the effects of changing parameters have on the fidelity of point cloud datasets generated from different SfM software packages.
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Sloped terrain segmentation for autonomous drive using sparse 3D point cloud.
Cho, Seoungjae; Kim, Jonghyun; Ikram, Warda; Cho, Kyungeun; Jeong, Young-Sik; Um, Kyhyun; Sim, Sungdae
2014-01-01
A ubiquitous environment for road travel that uses wireless networks requires the minimization of data exchange between vehicles. An algorithm that can segment the ground in real time is necessary to obtain location data between vehicles simultaneously executing autonomous drive. This paper proposes a framework for segmenting the ground in real time using a sparse three-dimensional (3D) point cloud acquired from undulating terrain. A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR) sensors. For efficient ground segmentation, 3D point clouds are quantized in units of volume pixels (voxels) and overlapping data is eliminated. We reduce nonoverlapping voxels to two dimensions by implementing a lowermost heightmap. The ground area is determined on the basis of the number of voxels in each voxel group. We execute ground segmentation in real time by proposing an approach to minimize the comparison between neighboring voxels. Furthermore, we experimentally verify that ground segmentation can be executed at about 19.31 ms per frame.
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Person detection and tracking with a 360° lidar system
NASA Astrophysics Data System (ADS)
Hammer, Marcus; Hebel, Marcus; Arens, Michael
2017-10-01
Today it is easily possible to generate dense point clouds of the sensor environment using 360° LiDAR (Light Detection and Ranging) sensors which are available since a number of years. The interpretation of these data is much more challenging. For the automated data evaluation the detection and classification of objects is a fundamental task. Especially in urban scenarios moving objects like persons or vehicles are of particular interest, for instance in automatic collision avoidance, for mobile sensor platforms or surveillance tasks. In literature there are several approaches for automated person detection in point clouds. While most techniques show acceptable results in object detection, the computation time is often crucial. The runtime can be problematic, especially due to the amount of data in the panoramic 360° point clouds. On the other hand, for most applications an object detection and classification in real time is needed. The paper presents a proposal for a fast, real-time capable algorithm for person detection, classification and tracking in panoramic point clouds.
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Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark
Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchersmore » the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.« less
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Reinelt, Sebastian; Steinke, Daniel
2014-01-01
Summary In this work we report the synthesis of thermo-, oxidation- and cyclodextrin- (CD) responsive end-group-functionalized polymers, based on N,N-diethylacrylamide (DEAAm). In a classical free-radical chain transfer polymerization, using thiol-functionalized 4-alkylphenols, namely 3-(4-(1,1-dimethylethan-1-yl)phenoxy)propane-1-thiol and 3-(4-(2,4,4-trimethylpentan-2-yl)phenoxy)propane-1-thiol, poly(N,N-diethylacrylamide) (PDEAAm) with well-defined hydrophobic end-groups is obtained. These end-group-functionalized polymers show different cloud point values, depending on the degree of polymerization and the presence of randomly methylated β-cyclodextrin (RAMEB-CD). Additionally, the influence of the oxidation of the incorporated thioether linkages on the cloud point is investigated. The resulting hydrophilic sulfoxides show higher cloud point values for the lower critical solution temperature (LCST). A high degree of functionalization is supported by 1H NMR-, SEC-, FTIR- and MALDI–TOF measurements. PMID:24778720
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A method for estimating vertical distibution of the SAGE II opaque cloud frequency
NASA Technical Reports Server (NTRS)
Wang, Pi-Huan; Mccormick, M. Patrick; Minnis, Patrick; Kent, Geoffrey S.; Yue, Glenn K.; Skeens, Kristi M.
1995-01-01
A method is developed to infer the vertical distribution of the occurrence frequency of clouds that are opaque to the Stratospheric Aerosol and Gas Experiment (SAGE) II instrument. An application of the method to the 1986 SAGE II observations is included in this paper. The 1986 SAGE II results are compared with the 1952-1981 cloud climatology of Warren et al. (1986, 1988)
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NASA Astrophysics Data System (ADS)
Sahyoun, Maher; Woetmann Nielsen, Niels; Havskov Sørensen, Jens; Finster, Kai; Bay Gosewinkel Karlson, Ulrich; Šantl-Temkiv, Tina; Smith Korsholm, Ulrik
2014-05-01
Bacteria, e.g. Pseudomonas syringae, have previously been found efficient in nucleating ice heterogeneously at temperatures close to -2°C in laboratory tests. Therefore, ice nucleation active (INA) bacteria may be involved in the formation of precipitation in mixed phase clouds, and could potentially influence weather and climate. Investigations into the impact of INA bacteria on climate have shown that emissions were too low to significantly impact the climate (Hoose et al., 2010). The goal of this study is to clarify the reason for finding the marginal impact on climate when INA bacteria were considered, by investigating the usability of ice nucleation rate parameterization based on classical nucleation theory (CNT). For this purpose, two parameterizations of heterogeneous ice nucleation were compared. Both parameterizations were implemented and tested in a 1-d version of the operational weather model (HIRLAM) (Lynch et al., 2000; Unden et al., 2002) in two different meteorological cases. The first parameterization is based on CNT and denoted CH08 (Chen et al., 2008). This parameterization is a function of temperature and the size of the IN. The second parameterization, denoted HAR13, was derived from nucleation measurements of SnomaxTM (Hartmann et al., 2013). It is a function of temperature and the number of protein complexes on the outer membranes of the cell. The fraction of cloud droplets containing each type of IN as percentage in the cloud droplets population were used and the sensitivity of cloud ice production in each parameterization was compared. In this study, HAR13 produces more cloud ice and precipitation than CH08 when the bacteria fraction increases. In CH08, the increase of the bacteria fraction leads to decreasing the cloud ice mixing ratio. The ice production using HAR13 was found to be more sensitive to the change of the bacterial fraction than CH08 which did not show a similar sensitivity. As a result, this may explain the marginal impact of IN bacteria in climate models when CH08 was used. The number of cell fragments containing proteins appears to be a more important parameter to consider than the size of the cell when parameterizing the heterogeneous freezing of bacteria.
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NASA Technical Reports Server (NTRS)
Koshak, W. J.; Solarkiewicz, R. J.
2009-01-01
Presently, it is not well understood how to best model nitrogen oxides (NOx) emissions from lightning because lightning is highly variable. Peak current, channel length, channel altitude, stroke multiplicity, and the number of flashes that occur in a particular region (i.e., flash density) all influence the amount of lightning NOx produced. Moreover, these 5 variables are not the same for ground and cloud flashes; e.g., cloud flashes normally have lower peak currents, higher altitudes, and higher flash densities than ground flashes [see (Koshak, 2009) for additional details]. Because the existing satellite observations of lightning (Fig. 1) from the Lightning Imaging Sensor/Optical Transient Detector (LIS/OTD) do not distinguish between ground and cloud fashes, which produce different amounts of NOx, it is very difficult to accurately account for the regional/global production of lightning NOx. Hence, the ability to partition the LIS/OTD lightning climatology into separate ground and cloud flash distributions would substantially benefit the atmospheric chemistry modeling community. NOx indirectly influences climate because it controls the concentration of ozone and hydroxyl radicals in the atmosphere. The importance of lightning-produced NOx is empasized throughout the scientific literature (see for example, Huntrieser et al. 1998). In fact, lightning is the most important NOx source in the upper troposphere with a global production rate estimated to vary between 2 and 20 Tg (N)yr(sup -1) (Lee et al., 1997), with more recent estimates of about 6 Tg(N)yr(sup -1) (Martin et al., 2007). In order to make accurate predictions, global chemistry/climate models (as well as regional air quality modells) must more accurately account for the effects of lightning NOx. In particular, the NASA Goddard Institute for Space Studies (GISS) Model E (Schmidt et al., 2005) and the GEOS-CHEM global chemical transport model (Bey et al., 2001) would each benefit from a partitioning of the LIS/OTD lightning climatology. In this study, we introduce a new technique for retrieving the ground flash fraction in a set of N lightning observed from space and that occur within a specific latitude/longitude bin. The method is briefly described and applied to CONUS lightning that have already been partitioned into ground and cloud flashes using independent ground-based observations, in order to assess the accuracy of the retrieval method. The retrieval errors are encouragingly small.
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Cloud level winds from UV and IR images obtained by VMC onboard Venus Express
NASA Astrophysics Data System (ADS)
Khatuntsev, Igor; Patsaeva, Marina; Titov, Dmitri; Ignatiev, Nikolay; Turin, Alexander; Bertaux, Jean-Loup
2017-04-01
During eight years Venus Monitoring Camera (VMC) [1] onboard the Venus Express orbiter has observed the upper cloud layer of Venus. The largest set of images was obtained in the UV (365 nm), visible (513 nm) and two infrared channels - 965 nm and 1010 nm. The UV dayside images were used to study the atmospheric circulation at the Venus cloud tops [2], [3]. Mean zonal and meridional profiles of winds and their variability were derived from cloud tracking of UV images. In low latitudes the mean retrograde zonal wind at the cloud top (67±2 km) is about 95 m/s with a maximum of about 102 m/s at 40-50°S. Poleward from 50°S the zonal wind quickly fades out with latitude. The mean poleward meridional wind slowly increases from zero value at the equator to about 10 m/s at 50°S. Poleward from this latitude, the absolute value of the meridional component monotonically decreases to zero at the pole. The VMC observations suggest clear diurnal signature in the wind field. They also indicate a long term trend for the zonal wind speed at low latitudes to increase from 85 m/s in the beginning of the mission to 110 m/s by the middle of 2012. The trend was explained by influence of the surface topography on the zonal flow [4]. Cloud features tracking in the IR images provided information about winds in the middle cloud deck (55±4 km). In the low and middle latitudes (5-65°S) the IR mean retrograde zonal velocity is about 68-70 m/s. In contrast to poleward flow at the cloud tops, equatorward motions dominate in the middle cloud with maximum speed of 5.8±1.2 m/s at latitude 15°S. The meridional speed slowly decreases to 0 at 65-70°S. At low latitudes the zonal and meridional speed demonstrate long term variations. Following [4] we explain the observed long term trend of zonal and meridional components by the influence of surface topography of highland region Aphrodite Terra on dynamic processes in the middle cloud deck through gravity waves. Acknowledgements: I.V. Khatuntsev, M.V. Patsaeva, N.I. Ignatiev, J.-L. Bertaux were supported by the Ministry of Education and Science of Russian Federation grant 14.W03.31.0017. References: [1] Markiewicz W. J. et al.: Venus Monitoring Camera for Venus Express // Planet. Space Sci., 55(12), 1701-1711. doi:10.1016/j.pss.2007.01.004, 2007. [2] Khatuntsev I.V. et al.: Cloud level winds from the Venus Express Monitoring Camera imaging // Icarus, 226, 140-158. 2013. [3] Patsaeva M.V. et al.: The relationship between mesoscale circulation and cloud morphology at the upper cloud level of Venus from VMC/Venus Express // Planet. Space Sci., 113(08), 100-108, doi:10.1016/j.pss.2015.01.013, 2015. [4] Bertaux J.-L. et al.: Influence of Venus topography on the zonal wind and UV albedo at cloud top level: The role of stationary gravity waves // J. Geophys. Res. Planets, 121, 1087-1101, doi:10.1002/2015JE004958, 2016.
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Comparative Analysis of Data Structures for Storing Massive Tins in a Dbms
NASA Astrophysics Data System (ADS)
Kumar, K.; Ledoux, H.; Stoter, J.
2016-06-01
Point cloud data are an important source for 3D geoinformation. Modern day 3D data acquisition and processing techniques such as airborne laser scanning and multi-beam echosounding generate billions of 3D points for simply an area of few square kilometers. With the size of the point clouds exceeding the billion mark for even a small area, there is a need for their efficient storage and management. These point clouds are sometimes associated with attributes and constraints as well. Storing billions of 3D points is currently possible which is confirmed by the initial implementations in Oracle Spatial SDO PC and the PostgreSQL Point Cloud extension. But to be able to analyse and extract useful information from point clouds, we need more than just points i.e. we require the surface defined by these points in space. There are different ways to represent surfaces in GIS including grids, TINs, boundary representations, etc. In this study, we investigate the database solutions for the storage and management of massive TINs. The classical (face and edge based) and compact (star based) data structures are discussed at length with reference to their structure, advantages and limitations in handling massive triangulations and are compared with the current solution of PostGIS Simple Feature. The main test dataset is the TIN generated from third national elevation model of the Netherlands (AHN3) with a point density of over 10 points/m2. PostgreSQL/PostGIS DBMS is used for storing the generated TIN. The data structures are tested with the generated TIN models to account for their geometry, topology, storage, indexing, and loading time in a database. Our study is useful in identifying what are the limitations of the existing data structures for storing massive TINs and what is required to optimise these structures for managing massive triangulations in a database.
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Fully Convolutional Networks for Ground Classification from LIDAR Point Clouds
NASA Astrophysics Data System (ADS)
Rizaldy, A.; Persello, C.; Gevaert, C. M.; Oude Elberink, S. J.
2018-05-01
Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied. However, point clouds need to be converted into an image in order to use Convolutional Neural Networks (CNNs). In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point cloud into a single image. The classification is then performed by a Fully Convolutional Network (FCN), a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of type I error, and 15.07 % of type II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and type I error (while type II error is slightly higher). The method was also tested on a very high point density LIDAR point clouds resulting in 4.02 % of total error, 2.15 % of type I error and 6.14 % of type II error.
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AKARI Infrared Camera Survey of the Large Magellanic Cloud
NASA Astrophysics Data System (ADS)
Shimonishi, Takashi; Kato, Daisuke; Ita, Yoshifusa; Onaka, Takashi
2015-08-01
The Large Magellanic Cloud (LMC) is one of the closest external galaxies to the Milky Way and has been playing a central role in various fields of modern astronomy and astrophysics. We conducted an unbiased near- to mid-infrared imaging and spectroscopic survey of the LMC with the infrared satellite AKARI. An area of about 10 square degrees of the LMC was observed by five imaging bands (each centered at 3.2, 7, 11, 15, and 24 micron) and the low-resolution slitless prism spectroscopy mode (2--5 micron, R~20) equipped with the Infrared Camera on board AKARI. Based on the data obtained in the survey, we constructed the photometric and spectroscopic catalogues of point sources in the LMC. The photometric catalogue includes about 650,000, 90,000, 49,000, 17,000, 7,000 sources at 3.2, 7, 11, 15, and 24 micron, respectively (Ita et al. 2008, PASJ, 60, 435; Kato et al. 2012, AJ, 144, 179), while the spectroscopic catalogue includes 1,757 sources (Shimonishi et al. 2013, AJ, 145, 32). Both catalogs are publicly released and available through a website (AKARI Observers Page, http://www.ir.isas.ac.jp/AKARI/Observation/). The catalog includes various infrared sources such as young stellar objects, asymptotic giant branch stars, giants/supergiants, and many other cool or dust-enshrouded stars. A large number of near-infrared spectral data, coupled with complementary broadband photometric data, allow us to investigate infrared spectral features of sources by comparison with their spectral energy distributions. Combined use of the present AKARI LMC catalogues with other infrared catalogues such as SAGE and HERITAGE possesses scientific potential that can be applied to various astronomical studies. In this presentation, we report the details of the AKARI photometric and spectroscopic catalogues of the LMC.
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Recent data for the p p at tevatron and odderon description
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fazal-e-Aleem; Ali, M.; Rashid, H.
1991-06-01
The experimental data for pp and {bar p}p at {radical}s = 53 GeV shows the difference between the differential cross sections in the dip region. This prompted the need for a crossing-odd amplitude even at this energy. Further support to this idea was provided by the order of magnitude rise of the measured pp differential cross section in the dip region as we go from ISR to CERN collider energies. In order to overcome the difficulty to explain these phenomena, Gauron et al used the idea of an odderon in addition to the pomeron and explained the then available datamore » for pp and {bar p}p. Dynamical origin to the idea of an odderon was later provided by Islam. He has pointed out that, if the nucleon consists of a core of valence quarks surrounded by a cloud of quark-antiquark pairs, then in elastic scattering an odderon amplitude occurs when the cores interact by exchanging a J = 1, C = {minus}1, u{bar u} + d{bar d} state and the cloud undergoes maximal diffraction scattering. The model has recently been modified by these authors so as to fit the very recent data of {bar p}p at 546 GeV and make predictions at 1.8 TeV. The same idea was also used by Barnbard et al to explain the pp and {bar p}p data , Jankovszky et al have also fitted the data for p ({bar p}) p by employing the odderon in conjunction with the dipole pomeron. In this paper the authors will compare the results of these models with the most recent measurements at tevatron and also compare them with those of other models.« less
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Reflection of solar radiation by a cylindrical cloud
NASA Technical Reports Server (NTRS)
Smith, G. L.
1989-01-01
Potential applications of an analytic method for computing the solar radiation reflected by a cylindrical cloud are discussed, including studies of radiative transfer within finite clouds and evaluations of these effects on other clouds and on remote sensing problems involving finite clouds. The pattern of reflected sunlight from a cylindrical cloud as seen at a large distance has been considered and described by the bidirectional function method for finite cloud analysis, as previously studied theoretically for plane-parallel atmospheres by McKee and Cox (1974); Schmetz and Raschke (1981); and Stuhlmann et al. (1985). However, the lack of three-dimensional radiative transfer solutions for anisotropic scattering media have hampered theoretical investigations of bidirectional functions for finite clouds. The present approach permits expression of the directional variation of the radiation field as a spherical harmonic series to any desired degree and order.
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Towards semi-automatic rock mass discontinuity orientation and set analysis from 3D point clouds
NASA Astrophysics Data System (ADS)
Guo, Jiateng; Liu, Shanjun; Zhang, Peina; Wu, Lixin; Zhou, Wenhui; Yu, Yinan
2017-06-01
Obtaining accurate information on rock mass discontinuities for deformation analysis and the evaluation of rock mass stability is important. Obtaining measurements for high and steep zones with the traditional compass method is difficult. Photogrammetry, three-dimensional (3D) laser scanning and other remote sensing methods have gradually become mainstream methods. In this study, a method that is based on a 3D point cloud is proposed to semi-automatically extract rock mass structural plane information. The original data are pre-treated prior to segmentation by removing outlier points. The next step is to segment the point cloud into different point subsets. Various parameters, such as the normal, dip/direction and dip, can be calculated for each point subset after obtaining the equation of the best fit plane for the relevant point subset. A cluster analysis (a point subset that satisfies some conditions and thus forms a cluster) is performed based on the normal vectors by introducing the firefly algorithm (FA) and the fuzzy c-means (FCM) algorithm. Finally, clusters that belong to the same discontinuity sets are merged and coloured for visualization purposes. A prototype system is developed based on this method to extract the points of the rock discontinuity from a 3D point cloud. A comparison with existing software shows that this method is feasible. This method can provide a reference for rock mechanics, 3D geological modelling and other related fields.
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Automatic Monitoring of Tunnel Deformation Based on High Density Point Clouds Data
NASA Astrophysics Data System (ADS)
Du, L.; Zhong, R.; Sun, H.; Wu, Q.
2017-09-01
An automated method for tunnel deformation monitoring using high density point clouds data is presented. Firstly, the 3D point clouds data are converted to two-dimensional surface by projection on the XOY plane, the projection point set of central axis on XOY plane named Uxoy is calculated by combining the Alpha Shape algorithm with RANSAC (Random Sampling Consistency) algorithm, and then the projection point set of central axis on YOZ plane named Uyoz is obtained by highest and lowest points which are extracted by intersecting straight lines that through each point of Uxoy and perpendicular to the two -dimensional surface with the tunnel point clouds, Uxoy and Uyoz together form the 3D center axis finally. Secondly, the buffer of each cross section is calculated by K-Nearest neighbor algorithm, and the initial cross-sectional point set is quickly constructed by projection method. Finally, the cross sections are denoised and the section lines are fitted using the method of iterative ellipse fitting. In order to improve the accuracy of the cross section, a fine adjustment method is proposed to rotate the initial sectional plane around the intercept point in the horizontal and vertical direction within the buffer. The proposed method is used in Shanghai subway tunnel, and the deformation of each section in the direction of 0 to 360 degrees is calculated. The result shows that the cross sections becomes flat circles from regular circles due to the great pressure at the top of the tunnel
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D Land Cover Classification Based on Multispectral LIDAR Point Clouds
NASA Astrophysics Data System (ADS)
Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong
2016-06-01
Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.
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NASA Astrophysics Data System (ADS)
Charbonnier, P.; Chavant, P.; Foucher, P.; Muzet, V.; Prybyla, D.; Perrin, T.; Grussenmeyer, P.; Guillemin, S.
2013-07-01
With recent developments in the field of technology and computer science, conventional methods are being supplanted by laser scanning and digital photogrammetry. These two different surveying techniques generate 3-D models of real world objects or structures. In this paper, we consider the application of terrestrial Laser scanning (TLS) and photogrammetry to the surveying of canal tunnels. The inspection of such structures requires time, safe access, specific processing and professional operators. Therefore, a French partnership proposes to develop a dedicated equipment based on image processing for visual inspection of canal tunnels. A 3D model of the vault and side walls of the tunnel is constructed from images recorded onboard a boat moving inside the tunnel. To assess the accuracy of this photogrammetric model (PM), a reference model is build using static TLS. We here address the problem comparing the resulting point clouds. Difficulties arise because of the highly differentiated acquisition processes, which result in very different point densities. We propose a new tool, designed to compare differences between pairs of point cloud or surfaces (triangulated meshes). Moreover, dealing with huge datasets requires the implementation of appropriate structures and algorithms. Several techniques are presented : point-to-point, cloud-to-cloud and cloud-to-mesh. In addition farthest point resampling, octree structure and Hausdorff distance are adopted and described. Experimental results are shown for a 475 m long canal tunnel located in France.
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Terrestrial laser scanning in monitoring of anthropogenic objects
NASA Astrophysics Data System (ADS)
Zaczek-Peplinska, Janina; Kowalska, Maria
2017-12-01
The registered xyz coordinates in the form of a point cloud captured by terrestrial laser scanner and the intensity values (I) assigned to them make it possible to perform geometric and spectral analyses. Comparison of point clouds registered in different time periods requires conversion of the data to a common coordinate system and proper data selection is necessary. Factors like point distribution dependant on the distance between the scanner and the surveyed surface, angle of incidence, tasked scan's density and intensity value have to be taken into consideration. A prerequisite for running a correct analysis of the obtained point clouds registered during periodic measurements using a laser scanner is the ability to determine the quality and accuracy of the analysed data. The article presents a concept of spectral data adjustment based on geometric analysis of a surface as well as examples of geometric analyses integrating geometric and physical data in one cloud of points: cloud point coordinates, recorded intensity values, and thermal images of an object. The experiments described here show multiple possibilities of usage of terrestrial laser scanning data and display the necessity of using multi-aspect and multi-source analyses in anthropogenic object monitoring. The article presents examples of multisource data analyses with regard to Intensity value correction due to the beam's incidence angle. The measurements were performed using a Leica Nova MS50 scanning total station, Z+F Imager 5010 scanner and the integrated Z+F T-Cam thermal camera.
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D Point Cloud Model Colorization by Dense Registration of Digital Images
NASA Astrophysics Data System (ADS)
Crombez, N.; Caron, G.; Mouaddib, E.
2015-02-01
Architectural heritage is a historic and artistic property which has to be protected, preserved, restored and must be shown to the public. Modern tools like 3D laser scanners are more and more used in heritage documentation. Most of the time, the 3D laser scanner is completed by a digital camera which is used to enrich the accurate geometric informations with the scanned objects colors. However, the photometric quality of the acquired point clouds is generally rather low because of several problems presented below. We propose an accurate method for registering digital images acquired from any viewpoints on point clouds which is a crucial step for a good colorization by colors projection. We express this image-to-geometry registration as a pose estimation problem. The camera pose is computed using the entire images intensities under a photometric visual and virtual servoing (VVS) framework. The camera extrinsic and intrinsic parameters are automatically estimated. Because we estimates the intrinsic parameters we do not need any informations about the camera which took the used digital image. Finally, when the point cloud model and the digital image are correctly registered, we project the 3D model in the digital image frame and assign new colors to the visible points. The performance of the approach is proven in simulation and real experiments on indoor and outdoor datasets of the cathedral of Amiens, which highlight the success of our method, leading to point clouds with better photometric quality and resolution.
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Analysis of Uncertainty in a Middle-Cost Device for 3D Measurements in BIM Perspective
Sánchez, Alonso; Naranjo, José-Manuel; Jiménez, Antonio; González, Alfonso
2016-01-01
Medium-cost devices equipped with sensors are being developed to get 3D measurements. Some allow for generating geometric models and point clouds. Nevertheless, the accuracy of these measurements should be evaluated, taking into account the requirements of the Building Information Model (BIM). This paper analyzes the uncertainty in outdoor/indoor three-dimensional coordinate measures and point clouds (using Spherical Accuracy Standard (SAS) methods) for Eyes Map, a medium-cost tablet manufactured by e-Capture Research & Development Company, Mérida, Spain. To achieve it, in outdoor tests, by means of this device, the coordinates of targets were measured from 1 to 6 m and cloud points were obtained. Subsequently, these were compared to the coordinates of the same targets measured by a Total Station. The Euclidean average distance error was 0.005–0.027 m for measurements by Photogrammetry and 0.013–0.021 m for the point clouds. All of them satisfy the tolerance for point cloud acquisition (0.051 m) according to the BIM Guide for 3D Imaging (General Services Administration); similar results are obtained in the indoor tests, with values of 0.022 m. In this paper, we establish the optimal distances for the observations in both, Photogrammetry and 3D Photomodeling modes (outdoor) and point out some working conditions to avoid in indoor environments. Finally, the authors discuss some recommendations for improving the performance and working methods of the device. PMID:27669245
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Point-cloud-to-point-cloud technique on tool calibration for dental implant surgical path tracking
NASA Astrophysics Data System (ADS)
Lorsakul, Auranuch; Suthakorn, Jackrit; Sinthanayothin, Chanjira
2008-03-01
Dental implant is one of the most popular methods of tooth root replacement used in prosthetic dentistry. Computerize navigation system on a pre-surgical plan is offered to minimize potential risk of damage to critical anatomic structures of patients. Dental tool tip calibrating is basically an important procedure of intraoperative surgery to determine the relation between the hand-piece tool tip and hand-piece's markers. With the transferring coordinates from preoperative CT data to reality, this parameter is a part of components in typical registration problem. It is a part of navigation system which will be developed for further integration. A high accuracy is required, and this relation is arranged by point-cloud-to-point-cloud rigid transformations and singular value decomposition (SVD) for minimizing rigid registration errors. In earlier studies, commercial surgical navigation systems from, such as, BrainLAB and Materialize, have flexibility problem on tool tip calibration. Their systems either require a special tool tip calibration device or are unable to change the different tool. The proposed procedure is to use the pointing device or hand-piece to touch on the pivot and the transformation matrix. This matrix is calculated every time when it moves to the new position while the tool tip stays at the same point. The experiment acquired on the information of tracking device, image acquisition and image processing algorithms. The key success is that point-to-point-cloud requires only 3 post images of tool to be able to converge to the minimum errors 0.77%, and the obtained result is correct in using the tool holder to track the path simulation line displayed in graphic animation.
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New Insights Concerning the Local Interstellar medium
NASA Astrophysics Data System (ADS)
Linsky, Jeffrey L.; Redfield, Seth
2015-08-01
We have been analyzing HST high-resolution ultraviolet spectra of nearby stars to measure the radial velocities, turbulence, temperature, and depletions on warm diffuse interstellar gas within a few parsecs of the Sun. These data reveal a picture of many partially-ionized warm gas clouds, each with their own vector velocity and physical characteristics. This picture has been recently challenged by Gry and Jenkins (2014), who argue for a single nonrigid cloud surrounding the Sun. We present a test of these two very different morphological structure by checking how well each predicts the radial velocities in a new data set (Malamut et al. 2014) that was not available when both models were constructed. We find that the multicloud model (Redfield & Linsky 2008) provides a much better fit to the new data. We compare the new IBEX results for the temperature and velocity of inflowing He gas (McComas et al. 2015) with the properties of the Local Interstellar Cloud and the G cloud. We also show a preliminary three-dimensional model for the local interstellar medium.
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NASA Astrophysics Data System (ADS)
Clancy, R. T.; Wolff, M. J.; Christensen, P. R.
2001-12-01
A full Mars year (1999-2001) of emission phase function (EPF observations from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) provide the most complete study of Mars dust and ice aerosol properties to date. TES visible (solar band average) and infrared spectral (6-30 micron, 10 invcm res) EPF sequences are analyzed self-consistently with detailed multiple scattering radiative transfer (RT) codes to obtain first-time seasonal/latitudinal distributions of aerosol visible optical depths, particle sizes, and single scattering phase functions. As a consequence of the combined angular and wavelength coverage, we are able to define two distinct ice cloud types at 45S-45N latitudes on Mars. Type 1 ice clouds exhibit small particle sizes (1-2 micron radii), as well as a broad, deep minimum in side scattering indicative of aligned ice grains (see Wolff et al., 2001). Type 1 ice aerosols are most prevalent in the southern hemisphere during Mars aphelion, but also appear more widely distributed in season and latitude as topographic and high altitude (above 20 km) ice hazes. Type 2 ice clouds exhibit larger particle sizes (2-4 microns) and a much narrower side-scattering minimum, indicative of poorer grain alignment or a change in particle shape relative to the type 1 ice clouds (see Wolff et al., 2001). Type 2 ice clouds appear most prominently in the northern subtropical aphelion cloud belt, where relatively low altitudes of water vapor saturation (10 km) coincide with strong advective transport (Clancy et al., 1996). Retrieved dust particle radii of 1.5-1.8 micron are consistent with Pathfinder (Tomasko et al., 1999) and recent Viking/Mariner 9 reanalyses (e.g., size distribution B of Clancy et al., 1995). Detailed spectral modeling of the solar passband also implies agreement of EPF-derived dust single scattering albedos (ssa) with the ssa results from Tomasko et al.(table 8 therein). Spatial and seasonal changes in the dust ssa (0.92-0.95, solar band average) and phase functions suggest possible dust property variations, but may also be a consequence of variable high altitude ice hazes. The annual variations of both dust and ice clouds at 45S-45N latitudes are predominately orbital rather than seasonal in character and have shown close repeatability during the portions of first two Mars years observed by MGS (i.e., prior to the July 2001 global dust storm which began at Ls=185, a most striking departure from the previous two Mars years observed). Minimum visible dust opacities of 0.05-0.10 occur at southern latitudes in aphelion, maximum dust opacities of 1.0-1.5 at northern latitudes after Ls=200 (and greater than 3 in the 2001 global dust storm). Type 2 ice clouds abruptly disappear at Ls=145, as does the widespread occurrence of type 1 clouds in the southern hemisphere. Dust loading in the southern hemisphere increases at this time, but does not do so in the northern hemisphere. A comparison of dust solar band to thermal infrared optical depth ratios also provides strong evidence for non-uniform vertical mixing of the dust loading. A large fraction of the dust column (20-50 percent) appears to be concentrated in the lower boundary layer of the Mars atmosphere, particularly during conditions of low-to-moderate dust loading.
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Data Assimilation Experiments using Quality Controlled AIRS Version 5 Temperature Soundings
NASA Technical Reports Server (NTRS)
Susskind, Joel
2008-01-01
The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AlRS data. Version 5 contains accurate case-by-case error estimates for most derived products, which are also used for quality control. We have conducted forecast impact experiments assimilating AlRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the NASA FVGCM. Assimilation of quality controlled temperature profiles resulted in significantly improved forecast skill in both the Northern Hemisphere and Southern Hemisphere Extra-Tropics, compared to that obtained from analyses obtained when all data used operationally by NCEP except for AlRS data is assimilated. Experiments using different Quality Control thresholds for assimilation of AlRS temperature retrievals showed that a medium quality control threshold performed better than a tighter threshold, which provided better overall sounding accuracy; or a looser threshold, which provided better spatial coverage of accepted soundings. We are conducting more experiments to further optimize this balance of spatial coverage and sounding accuracy from the data assimilation perspective. In all cases, temperature soundings were assimilated well below cloud level in partially cloudy cases. The positive impact of assimilating AlRS derived atmospheric temperatures all but vanished when only AIRS stratospheric temperatures were assimilated. Forecast skill resulting from assimilation of AlRS radiances uncontaminated by clouds, instead of AlRS temperature soundings, was only slightly better than that resulting from assimilation of only stratospheric AlRS temperatures. This reduction in forecast skill is most likely the result of significant loss of tropospheric information when only AIRS radiances unaffected by clouds are used in the data assimilation process.
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Continuing Support of Cloud Free Line of Sight Determination Including Whole Sky Imaging of Clouds
2007-11-30
which is documented in Shields et al. 2007a, Technical Note 271, and Contract N00014-01-D- 0043 DO #11, which is reviewed in Section 2 and documented in...Shields et al. 2007b, Technical Note 272. Under DO #13, we finished preparation of two of the WSI units and their software, and fielded them...and b, and 2005b and c). One of the first two units was fielded at the Air Force’s Starfire Optical Range in October 1992. Technical Memo AV06
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Layer stacking: A novel algorithm for individual forest tree segmentation from LiDAR point clouds
Elias Ayrey; Shawn Fraver; John A. Kershaw; Laura S. Kenefic; Daniel Hayes; Aaron R. Weiskittel; Brian E. Roth
2017-01-01
As light detection and ranging (LiDAR) technology advances, it has become common for datasets to be acquired at a point density high enough to capture structural information from individual trees. To process these data, an automatic method of isolating individual trees from a LiDAR point cloud is required. Traditional methods for segmenting trees attempt to isolate...
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Riihimaki, Laura D.; Comstock, Jennifer M.; Luke, Edward
To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement (ARM) site are used to classify cloud phase within a deep convective cloud in a shallow to deep convection transitional case. The cloud cannot be fully observed by a lidar due to signal attenuation. Thus we develop an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectramore » from vertically pointing Ka band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid, indicating complexity to how ice growth and diabatic heating occurs in the vertical structure of the cloud.« less
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NASA Astrophysics Data System (ADS)
Riihimaki, L. D.; Comstock, J. M.; Luke, E.; Thorsen, T. J.; Fu, Q.
2017-07-01
To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, ground-based vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement site are used to classify cloud phase within a deep convective cloud. The cloud cannot be fully observed by a lidar due to signal attenuation. Therefore, we developed an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectra from vertically pointing Ka-band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid. Diffusional growth calculations show that the conditions for the Wegener-Bergeron-Findeisen process exist within one of these mixed-phase microstructures.
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Efficient characterization of inhomogeneity in contraction strain pattern.
Nazzal, Christina M; Mulligan, Lawrence J; Criscione, John C
2012-05-01
Cardiac dyssynchrony often accompanies patients with heart failure (HF) and can lead to an increase in mortality rate. Cardiac resynchronization therapy (CRT) has been shown to provide substantial benefits to the HF population with ventricular dyssynchrony; however, there still exists a group of patients who do not respond to this treatment. In order to better understand patient response to CRT, it is necessary to quantitatively characterize both electrical and mechanical dyssynchrony. The quantification of mechanical dyssynchrony via characterization of contraction strain field inhomogeneity is the focus of this modeling investigation. Raw data from a 3D finite element (FE) model were received from Roy Kerckhoffs et al. and analyzed in MATLAB. The FE model consisted of canine left and right ventricles coupled to a closed circulation with the effects of the pericardium acting as a pressure on the epicardial surface. For each of three simulations (normal synchronous, SYNC, right ventricular apical pacing, RVA, and left ventricular free wall pacing, LVFW) the Gauss point locations and values were used to generate lookup tables (LUTs) with each entry representing a location in the heart. In essence, we employed piecewise cubic interpolation to generate a fine point cloud (LUTs) from a course point cloud (Gauss points). Strain was calculated in the fiber direction and was then displayed in multiple ways to better characterize strain inhomogeneity. By plotting average strain and standard deviation over time, the point of maximum contraction and the point of maximal inhomogeneity were found for each simulation. Strain values were organized into seven strain bins to show operative strain ranges and extent of inhomogeneity throughout the heart wall. In order to visualize strain propagation, magnitude, and inhomogeneity over time, we created 2D area maps displaying strain over the entire cardiac cycle. To visualize spatial strain distribution at the time point of maximum inhomogeneity, a 3D point cloud was created for each simulation, and a CURE index was calculated. We found that both the RVA and LFVW simulations took longer to reach maximum contraction than the SYNC simulation, while also exhibiting larger disparities in strain values during contraction. Strain in the hoop direction was also analyzed and was found to be similar to the fiber strain results. It was found that our method of analyzing contraction strain pattern yielded more detailed spacial and temporal information about fiber strain in the heart over the cardiac cycle than the more conventional CURE index method. We also observed that our method of strain binning aids in visualization of the strain fields, and in particular, the separation of the mass points into separate images associated with each strain bin allows the strain pattern to be explicitly compartmentalized.
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NASA Astrophysics Data System (ADS)
Sirmacek, B.; Lindenbergh, R. C.; Menenti, M.
2013-10-01
Fusion of 3D airborne laser (LIDAR) data and terrestrial optical imagery can be applied in 3D urban modeling and model up-dating. The most challenging aspect of the fusion procedure is registering the terrestrial optical images on the LIDAR point clouds. In this article, we propose an approach for registering these two different data from different sensor sources. As we use iPhone camera images which are taken in front of the interested urban structure by the application user and the high resolution LIDAR point clouds of the acquired by an airborne laser sensor. After finding the photo capturing position and orientation from the iPhone photograph metafile, we automatically select the area of interest in the point cloud and transform it into a range image which has only grayscale intensity levels according to the distance from the image acquisition position. We benefit from local features for registering the iPhone image to the generated range image. In this article, we have applied the registration process based on local feature extraction and graph matching. Finally, the registration result is used for facade texture mapping on the 3D building surface mesh which is generated from the LIDAR point cloud. Our experimental results indicate possible usage of the proposed algorithm framework for 3D urban map updating and enhancing purposes.
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NASA Technical Reports Server (NTRS)
Kahre, M. A.; Haberle, R. M.; Hollingsworth, J. L.; Wilson, R. J.
2014-01-01
The dust cycle is critically important for the current climate of Mars. The radiative effects of dust impact the thermal and dynamical state of the atmosphere (Gierasch and Goody, 1968; Haberle et al., 1982; Zurek et al., 1992). Although dust is present in the Martian atmosphere throughout the year, the level of dustiness varies with season. The atmosphere is generally the dustiest during northern fall and winter and the least dusty during northern spring and summer (Smith, 2004). Dust particles are lifted into the atmosphere by dust storms that range in size from meters to thousands of kilometers across (Cantor et al., 2001). During some years, regional storms combine to produce hemispheric or planet encircling dust clouds that obscure the surface and raise atmospheric temperatures by as much as 40 K (Smith et al., 2002). Key recent observations of the vertical distribution of dust indicate that elevated layers of dust exist in the tropics and sub-tropics throughout much of the year (Heavens et al., 2011). These observations have brought particular focus on the processes that control the vertical distribution of dust in the Martian atmosphere. The goal of this work is to further our understanding of how clouds in particular control the vertical distribution of dust, particularly during N. H. spring and summer
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Assessment of different models for computing the probability of a clear line of sight
NASA Astrophysics Data System (ADS)
Bojin, Sorin; Paulescu, Marius; Badescu, Viorel
2017-12-01
This paper is focused on modeling the morphological properties of the cloud fields in terms of the probability of a clear line of sight (PCLOS). PCLOS is defined as the probability that a line of sight between observer and a given point of the celestial vault goes freely without intersecting a cloud. A variety of PCLOS models assuming the cloud shape hemisphere, semi-ellipsoid and ellipsoid are tested. The effective parameters (cloud aspect ratio and absolute cloud fraction) are extracted from high-resolution series of sunshine number measurements. The performance of the PCLOS models is evaluated from the perspective of their ability in retrieving the point cloudiness. The advantages and disadvantages of the tested models are discussed, aiming to a simplified parameterization of PCLOS models.
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NASA Astrophysics Data System (ADS)
Wu, J.; Yao, W.; Zhang, J.; Li, Y.
2018-04-01
Labeling 3D point cloud data with traditional supervised learning methods requires considerable labelled samples, the collection of which is cost and time expensive. This work focuses on adopting domain adaption concept to transfer existing trained random forest classifiers (based on source domain) to new data scenes (target domain), which aims at reducing the dependence of accurate 3D semantic labeling in point clouds on training samples from the new data scene. Firstly, two random forest classifiers were firstly trained with existing samples previously collected for other data. They were different from each other by using two different decision tree construction algorithms: C4.5 with information gain ratio and CART with Gini index. Secondly, four random forest classifiers adapted to the target domain are derived through transferring each tree in the source random forest models with two types of operations: structure expansion and reduction-SER and structure transfer-STRUT. Finally, points in target domain are labelled by fusing the four newly derived random forest classifiers using weights of evidence based fusion model. To validate our method, experimental analysis was conducted using 3 datasets: one is used as the source domain data (Vaihingen data for 3D Semantic Labelling); another two are used as the target domain data from two cities in China (Jinmen city and Dunhuang city). Overall accuracies of 85.5 % and 83.3 % for 3D labelling were achieved for Jinmen city and Dunhuang city data respectively, with only 1/3 newly labelled samples compared to the cases without domain adaption.
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Observations of Seven Blue/Gigantic Jets above One Storm over the Atlantic Ocean
NASA Astrophysics Data System (ADS)
Liu, N.; Spiva, N.; Dwyer, J. R.; Rassoul, H.; Free, D. L.; Cummer, S. A.
2013-12-01
Blue/gigantic jets are electrical discharges developing from thundercloud tops and propagating to the upper atmosphere [e.g., Pasko et al., Nature, 416, 152, 2002; Su et al., Nature, 423, 973, 2003]. Not just producing an impressive display, gigantic jets establish a direct path of electrical contact between the upper troposphere and the lower ionosphere, capable of transferring a large amount of charge between them [Cummer et al., Nat. Geosci., 2, 617, 2009]. It has been suggested that they may play an important role in the earth's electrical environment [e. g., Pasko, Nature, 423, 927, 2003]. Upward discharges from thunderstorms like blue/gigantic jets are believed to originate from lightning leaders escaping from thunderclouds when the cloud's charges of different polarities are not balanced [Krehbiel et al., Nat. Geosci., 1, 233, 2008; Riousset et al., JGR, 115, A00E10, 2010]. On the evening of August 2, 2013, 4 gigantic jets, 2 blue jets and 1 blue starter were recorded within 26 min above a storm over the Atlantic Ocean by a low light level camera from the campus of Florida Institute of Technology. The events were also captured by two all-sky cameras: one again from the Florida Tech campus and the other from a nearby location. According to the NLDN data, positive intra-cloud flashes preceded all events except one gigantic jet. The distance between the observation site to the locations of the NLDN lightning discharges varies from 77 to 82 km. Optical signatures of intra-cloud discharge activities accompanied the events are clearly visible in the videos. The duration of each jet varies from about 300 ms to 1.2 s, and the 1.2 s duration is probably the longest that has been reported to date for jets. Rebrightening of gigantic jet structures occurs for at least two of the events. The upper terminal altitude of the 4 gigantic jets is greater than 76-81 km, the 2 blue jets reach about 48 and 51 km altitude, respectively, and the blue starter reaches 24 km altitude. The altitude of cloud tops varies from 14 to 20 km. All events exhibit a tree-like structure and develop in an impulsive manner. Similar to other observations of gigantic jets, bright beads appear at the tops of the gigantic jets. The impulsive upward propagation of the jets together with the positive polarity of the preceding intra-cloud discharges suggests that the jets originate from upward propagating negative leaders initiated inside the thundercloud. All events propagate upward from the top of the cloud nearly vertically except for one event that develops in a slanted direction, about twenty three degrees from the vertical. With only a few branches, the three blue jet/starter events display a structure very similar to a cloud-to-ground lightning stroke. Our observations support the unified view of the upward discharges from thunderclouds advanced by Krehbiel et al. [2008] and Riousset et al. [2010]. In this talk, we discuss the video observations of the events and the associated radio signatures in detail.
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NASA Astrophysics Data System (ADS)
Brégonzio-Rozier, Lola; Siekmann, Frank; Giorio, Chiara; Temime-Roussel, Brice; Pangui, Edouard; Morales, Sébastien; Gratien, Aline; Ravier, Sylvain; Monod, Anne; Doussin, Jean-Francois
2014-05-01
It is acknowledged that atmospheric photo-oxidation of Volatile Organic Compounds (VOC) leads to the formation of less volatile oxidized species. These compounds can undergo gas-to-particle conversion, leading to the formation of Secondary Organic Aerosols (SOA) in the atmosphere. Nevertheless, some of these oxidized species are water soluble and could also partition into cloud droplets. Higher molecular weight and less volatile compounds could be produced in the aqueous phase and remain in the particle phase after water evaporation (Ervens et al., 2011). The aim of the present work is to study SOA formation in the presence of cloud droplets during isoprene photo-oxidation. To this end, an original multiphase approach in a simulation chamber was set up in order to investigate the chemistry occurring in the gaseous, particulate and aqueous phases, and the exchange between these phases. Experiments were performed, within the CUMULUS project (CloUd MULtiphase chemistry of organic compoUndS in the troposphere), in the CESAM chamber (Wang et al., 2011). This chamber was designed to investigate multiphase processes under realistic actinic flux, and accurate control of both temperature and relative humidity. A specific protocol was set up to produce cloud events in the simulation chamber exhibiting a significant lifetime in the presence of light (10-12 minutes). By using this protocol, many clouds could be generated in a single experiment. In each experiment, around 800 ppb of isoprene was injected in the chamber together with HONO under dry conditions before irradiation. A Fourier Transform Infrared Spectrometer (FTIR), a Proton Transfer Reaction Mass Spectrometer (PTR-TOF-MS) and NOx and O3 analyzers were used to analyze gas-phase composition. Dried SOA size distributions and total concentrations were measured by a Scanning Mobility Particle Sizer (SMPS). An Aerodyne High Resolution Time-Of-Flight Aerosol Mass Spectrometer (HR-TOF-AMS) was also used to investigate aerosol composition. Cloud droplets size distributions were measured by a white light Optical Particle Counter (OPC). In all experiments, the dissolution of gaseous oxidation products into aqueous phase and SOA production have been observed during isoprene photo-oxidation in the presence of a cloud event. The overall results in additional SOA mass production and the dynamic of gaseous oxidation products and SOA mass concentrations will be presented. Ervens, B. et al. (2011). Atmospheric Chemistry and Physics 11(21): 11069-11102. Wang, J. et al. (2011). Atmospheric Measurement Techniques 4(11): 2465-2494.
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NASA Astrophysics Data System (ADS)
Gupta, S.; Lohani, B.
2014-05-01
Mobile augmented reality system is the next generation technology to visualise 3D real world intelligently. The technology is expanding at a fast pace to upgrade the status of a smart phone to an intelligent device. The research problem identified and presented in the current work is to view actual dimensions of various objects that are captured by a smart phone in real time. The methodology proposed first establishes correspondence between LiDAR point cloud, that are stored in a server, and the image t hat is captured by a mobile. This correspondence is established using the exterior and interior orientation parameters of the mobile camera and the coordinates of LiDAR data points which lie in the viewshed of the mobile camera. A pseudo intensity image is generated using LiDAR points and their intensity. Mobile image and pseudo intensity image are then registered using image registration method SIFT thereby generating a pipeline to locate a point in point cloud corresponding to a point (pixel) on the mobile image. The second part of the method uses point cloud data for computing dimensional information corresponding to the pairs of points selected on mobile image and fetch the dimensions on top of the image. This paper describes all steps of the proposed method. The paper uses an experimental setup to mimic the mobile phone and server system and presents some initial but encouraging results
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Evidence of Chemical Cloud Processing from In Situ Measurements in the Polluted Marine Environment
NASA Astrophysics Data System (ADS)
Hudson, J. G.; Noble, S. R., Jr.
2017-12-01
Chemical cloud processing alters activated cloud condensation nuclei (CCN). Aqueous oxidation of trace gases dissolved within cloud droplets adds soluble material. As most cloud droplets evaporate, the residual material produces CCN that are larger and with a different hygroscopicity (κ). This improves the CCN, lowering the critical supersaturation (Sc), making it more easily activated. This process separates the processed (accumulation) and unprocessed (Aitken) modes creating bimodal CCN distributions (Hudson et al., 2015). Various measurements made during the MArine Stratus/stratocumulus Experiment (MASE), including CCN, exhibited aqueous processing signals. Particle size distributions; measured by a differential mobility analyzer; were compared with CCN distributions; measured by the Desert Research Institute CCN spectrometer; by converting size to Sc using κ to overlay concurrent distributions. By tuning each mode to the best agreement, κ for each mode is determined; processed κ (κp), unprocessed κ (κu). In MASE, 59% of bimodal distributions had different κ for the two modes indicating dominance of chemical processing via aqueous oxidation. This is consistent with Hudson et al. (2015). Figure 1A also indicates chemical processing with larger κp between 0.35-0.75. Processed CCN had an influx of soluble material from aqueous oxidation which increased κp versus κu. Above 0.75 κp is lower than κu (Fig. 1A). When κu is high and sulfate material is added, κp tends towards κ of the added material. Thus, κp is reduced by additional material that is less soluble than the original material. Chemistry measurements in MASE also indicate in-cloud aqueous oxidation (Fig. 1B and 1C). Higher fraction of CCN concentrations in the processed mode are also associated with larger amounts of sulfates (Fig. 1B, red) and nitrates (Fig. 1C, orange) while SO2 (Fig. 1B, black) and O3 (Fig. 1C, blue) have lower amounts. This larger amount of sulfate is at the expense of SO2, indicating aqueous oxidation within cloud as associated with larger concentrations in the processed mode. Thus, in situ measurements indicate that chemical cloud processing alters size, Sc and κ of activated CCN. Hudson et al. (2015), JGRA, 120, 3436-3452.
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Coupling of acoustic waves to clouds in the jovian troposphere
NASA Astrophysics Data System (ADS)
Gaulme, Patrick; Mosser, Benoît
2005-11-01
Seismology is the best tool for investigating the interior structure of stars and giant planets. This paper deals with a photometric study of jovian global oscillations. The propagation of acoustic waves in the jovian troposphere is revisited in order to estimate their effects on the planetary albedo. According to the standard model of the jovian cloud structure there are three major ice cloud layers (e.g., [Atreya et al., 1999. A comparison of the atmospheres of Jupiter and Saturn: Deep atmospheric composition, cloud structure, vertical mixing, and origin. Planet Space Sci. 47, 1243-1262]). We consider only the highest layers, composed of ammonia ice, in the region where acoustic waves are trapped in Jupiter's atmosphere. For a vertical wave propagating in a plane parallel atmosphere with an ammonia ice cloud layer, we calculate first the relative variations of the reflected solar flux due to the smooth oscillations at about the ppm level. We then determine the phase transitions induced by the seismic waves in the clouds. These phase changes, linked to ice particle growth, are limited by kinetics. A Mie model [Mishchenko et al., 2002. Scattering, Absorption, and Emission of Light by Small Particles. Cambridge Univ. Press, Cambridge, pp. 158-190] coupled with a simple radiation transfer model allows us to estimate that the albedo fluctuations of the cloud perturbed by a seismic wave reach relative variations of 70 ppm for a 3-mHz wave. This albedo fluctuation is amplified by a factor of ˜70 relative to the previously published estimates that exclude the effect of the wave on cloud properties. Our computed amplifications imply that jovian oscillations can be detected with very precise photometry, as proposed by the microsatellite JOVIS project, which is dedicated to photometric seismology [Mosser et al., 2004. JOVIS: A microsatellite dedicated to the seismic analysis of Jupiter. In: Combes, F., Barret, D., Contini, T., Meynadier, F., Pagani, L. (Eds.), SF2A-2004, Semaine de l'Astrophysique Francaise, Les Ulis. In: EdP-Sciences Conference Series, pp. 257-258].
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Formation of massive, dense cores by cloud-cloud collisions
NASA Astrophysics Data System (ADS)
Takahira, Ken; Shima, Kazuhiro; Habe, Asao; Tasker, Elizabeth J.
2018-03-01
We performed sub-parsec (˜ 0.014 pc) scale simulations of cloud-cloud collisions of two idealized turbulent molecular clouds (MCs) with different masses in the range of (0.76-2.67) × 104 M_{⊙} and with collision speeds of 5-30 km s-1. Those parameters are larger than in Takahira, Tasker, and Habe (2014, ApJ, 792, 63), in which study the colliding system showed a partial gaseous arc morphology that supports the NANTEN observations of objects indicated to be colliding MCs using numerical simulations. Gas clumps with density greater than 10-20 g cm-3 were identified as pre-stellar cores and tracked through the simulation to investigate the effects of the mass of colliding clouds and the collision speeds on the resulting core population. Our results demonstrate that the smaller cloud property is more important for the results of cloud-cloud collisions. The mass function of formed cores can be approximated by a power-law relation with an index γ = -1.6 in slower cloud-cloud collisions (v ˜ 5 km s-1), and is in good agreement with observation of MCs. A faster relative speed increases the number of cores formed in the early stage of collisions and shortens the gas accretion phase of cores in the shocked region, leading to the suppression of core growth. The bending point appears in the high-mass part of the core mass function and the bending point mass decreases with increase in collision speed for the same combination of colliding clouds. The higher-mass part of the core mass function than the bending point mass can be approximated by a power law with γ = -2-3 that is similar to the power index of the massive part of the observed stellar initial mass function. We discuss implications of our results for the massive-star formation in our Galaxy.
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Formation of massive, dense cores by cloud-cloud collisions
NASA Astrophysics Data System (ADS)
Takahira, Ken; Shima, Kazuhiro; Habe, Asao; Tasker, Elizabeth J.
2018-05-01
We performed sub-parsec (˜ 0.014 pc) scale simulations of cloud-cloud collisions of two idealized turbulent molecular clouds (MCs) with different masses in the range of (0.76-2.67) × 104 M_{⊙} and with collision speeds of 5-30 km s-1. Those parameters are larger than in Takahira, Tasker, and Habe (2014, ApJ, 792, 63), in which study the colliding system showed a partial gaseous arc morphology that supports the NANTEN observations of objects indicated to be colliding MCs using numerical simulations. Gas clumps with density greater than 10-20 g cm-3 were identified as pre-stellar cores and tracked through the simulation to investigate the effects of the mass of colliding clouds and the collision speeds on the resulting core population. Our results demonstrate that the smaller cloud property is more important for the results of cloud-cloud collisions. The mass function of formed cores can be approximated by a power-law relation with an index γ = -1.6 in slower cloud-cloud collisions (v ˜ 5 km s-1), and is in good agreement with observation of MCs. A faster relative speed increases the number of cores formed in the early stage of collisions and shortens the gas accretion phase of cores in the shocked region, leading to the suppression of core growth. The bending point appears in the high-mass part of the core mass function and the bending point mass decreases with increase in collision speed for the same combination of colliding clouds. The higher-mass part of the core mass function than the bending point mass can be approximated by a power law with γ = -2-3 that is similar to the power index of the massive part of the observed stellar initial mass function. We discuss implications of our results for the massive-star formation in our Galaxy.
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Cloud Computing for Geosciences--GeoCloud for standardized geospatial service platforms (Invited)
NASA Astrophysics Data System (ADS)
Nebert, D. D.; Huang, Q.; Yang, C.
2013-12-01
The 21st century geoscience faces challenges of Big Data, spike computing requirements (e.g., when natural disaster happens), and sharing resources through cyberinfrastructure across different organizations (Yang et al., 2011). With flexibility and cost-efficiency of computing resources a primary concern, cloud computing emerges as a promising solution to provide core capabilities to address these challenges. Many governmental and federal agencies are adopting cloud technologies to cut costs and to make federal IT operations more efficient (Huang et al., 2010). However, it is still difficult for geoscientists to take advantage of the benefits of cloud computing to facilitate the scientific research and discoveries. This presentation reports using GeoCloud to illustrate the process and strategies used in building a common platform for geoscience communities to enable the sharing, integration of geospatial data, information and knowledge across different domains. GeoCloud is an annual incubator project coordinated by the Federal Geographic Data Committee (FGDC) in collaboration with the U.S. General Services Administration (GSA) and the Department of Health and Human Services. It is designed as a staging environment to test and document the deployment of a common GeoCloud community platform that can be implemented by multiple agencies. With these standardized virtual geospatial servers, a variety of government geospatial applications can be quickly migrated to the cloud. In order to achieve this objective, multiple projects are nominated each year by federal agencies as existing public-facing geospatial data services. From the initial candidate projects, a set of common operating system and software requirements was identified as the baseline for platform as a service (PaaS) packages. Based on these developed common platform packages, each project deploys and monitors its web application, develops best practices, and documents cost and performance information. This paper presents the background, architectural design, and activities of GeoCloud in support of the Geospatial Platform Initiative. System security strategies and approval processes for migrating federal geospatial data, information, and applications into cloud, and cost estimation for cloud operations are covered. Finally, some lessons learned from the GeoCloud project are discussed as reference for geoscientists to consider in the adoption of cloud computing.
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Clouds off the Aleutian Islands
2017-12-08
March 23, 2010 - Clouds off the Aleutian Islands Interesting cloud patterns were visible over the Aleutian Islands in this image, captured by the MODIS on the Aqua satellite on March 14, 2010. Turbulence, caused by the wind passing over the highest points of the islands, is producing the pronounced eddies that swirl the clouds into a pattern called a vortex "street". In this image, the clouds have also aligned in parallel rows or streets. Cloud streets form when low-level winds move between and over obstacles causing the clouds to line up into rows (much like streets) that match the direction of the winds. At the point where the clouds first form streets, they're very narrow and well-defined. But as they age, they lose their definition, and begin to spread out and rejoin each other into a larger cloud mass. The Aleutians are a chain of islands that extend from Alaska toward the Kamchatka Peninsula in Russia. For more information related to this image go to: modis.gsfc.nasa.gov/gallery/individual.php?db_date=2010-0... For more information about Goddard Space Flight Center go here: www.nasa.gov/centers/goddard/home/index.html
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NASA Astrophysics Data System (ADS)
Zelenyuk, A.; Imre, D. G.; Leaitch, R.; Ovchinnikov, M.; Liu, P.; Macdonald, A.; Strapp, W.; Ghan, S. J.; Earle, M. E.
2012-12-01
Single particle mass spectrometer, SPLAT II, was used to characterize the size, composition, number concentration, density, and shape of individual Arctic spring aerosol. Background particles, particles above and below the cloud, cloud droplet residuals, and interstitial particles were characterized with goal to identify the properties that separate cloud condensation nuclei (CCN) from background aerosol particles. The analysis offers a comparison between warm clouds formed on clean and polluted days, with clean days having maximum particle concentrations (Na) lower than ~250 cm-3, as compared with polluted days, in which maximum concentration was tenfold higher. On clean days, particles were composed of organics, organics mixed with sulfates, biomass burning (BB), sea salt (SS), and few soot and dust particles. On polluted days, BB, organics associated with BB, and their mixtures with sulfate dominated particle compositions. Based on the measured compositions and size distributions of cloud droplet residuals, background aerosols, and interstitial particles, we conclude that these three particle types had virtually the same compositions, which means that cloud activation probabilities were surprisingly nearly composition independent. Moreover, these conclusions hold in cases in which less than 20% or more than 90% of background particles got activated. We concluded that for the warm clouds interrogated in this study particle size played a more important factor on aerosol CCN activity. Comparative analysis of all studied clouds reveals that aerosol activation efficiency strongly depends on the aerosol concentrations, such that at Na <200 cm-3, nearly all particles activate, and at higher concentrations the activation efficiency is lower. For example, when Na was greater than 1500 cm-3, less than ~30% of particles activated. The data suggest that as the number of nucleated droplets increases, condensation on existing droplets effectively competes with particle activation, limiting maximum droplet concentrations Nd = 525 ± 50 cm-3, which is lower than the 750 cm-3 limit found by Leaitch et al. (1986) for mid-latitude continental cloud that had generally larger updraft speeds than the clouds interrogated in Arctic. These findings are important for the aerosol indirect effect, in which increase in aerosol particle number concentrations is expected to result in increase in Nd and decrease in droplet size, leading to increased cloud albedo and potentially lifetimes. Our conclusions point to limited susceptibility to changes in ambient aerosol concentrations, providing simple explanation for the finding of weaker than expected indirect effect. In summary, the data presented here show that Nd increases as the cloud base particle number concentration increases; however, they also show a limit on Nd that is in the range of 500-600 cm-3.
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Simulation of the Upper Clouds and Hazes of Venus Using a Microphysical Cloud Model
NASA Astrophysics Data System (ADS)
McGouldrick, K.
2012-12-01
Several different microphysical and chemical models of the clouds of Venus have been developed in attempts to reproduce the in situ observations of the Venus clouds made by Pioneer Venus, Venera, and Vega descent probes (Turco et al., 1983 (Icarus 53:18-25), James et al, 1997 (Icarus 129:147-171), Imamura and Hashimoto, 2001 (J. Atm. Sci. 58:3597-3612), and McGouldrick and Toon, 2007 (Icarus 191:1-24)). The model of McGouldrick and Toon has successfully reproduced observations within the condensational middle and lower cloud decks of Venus (between about 48 and 57 km altitude, experiencing conditions similar to Earth's troposphere) and it now being extended to also simulate the microphysics occurring in the upper cloud deck (between altitudes of about 57 km and 70 km, experiencing conditions similar to Earth's stratosphere). In the upper clouds, aerosols composed of a solution of sulfuric acid in water are generated from the reservoir of available water vapor and sulfuric acid vapor that is photochemically produced. The manner of particle creation (e.g., activation of cloud condensation nuclei, or homogeneous or heterogeneous nucleation) is still incompletely understood, and the atmospheric environment has been measured to be not inconsistent with frozen aerosol particles (either sulfuric acid monohydrate or water ice). The material phase, viscosity, and surface tension of the aerosols (which are strongly dependent up on the local temperature and water vapor concentration) can affect the coagulation efficiencies of the aerosol, leading to variations in the size distributions, and other microphysical and radiative properties. Here, I present recent work exploring the effects of nucleation rates and coalescence efficiencies on the simulated Venus upper clouds.
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Capturing and modelling high-complex alluvial topography with UAS-borne laser scanning
NASA Astrophysics Data System (ADS)
Mandlburger, Gottfried; Wieser, Martin; Pfennigbauer, Martin
2015-04-01
Due to fluvial activity alluvial forests are zones of highest complexity and relief energy. Alluvial forests are dominated by new and pristine channels in consequence of current and historic flood events. Apart from topographic features, the vegetation structure is typically very complex featuring, both, dense under story as well as high trees. Furthermore, deadwood and debris carried from upstream during periods of high discharge within the river channel are deposited in these areas. Therefore, precise modelling of the micro relief of alluvial forests using standard tools like Airborne Laser Scanning (ALS) is hardly feasible. Terrestrial Laser Scanning (TLS), in turn, is very time consuming for capturing larger areas as many scan positions are necessary for obtaining complete coverage due to view occlusions in the forest. In the recent past, the technological development of Unmanned Arial Systems (UAS) has reached a level that light-weight survey-grade laser scanners can be operated from these platforms. For capturing alluvial topography this could bridge the gap between ALS and TLS in terms of providing a very detailed description of the topography and the vegetation structure due to the achievable very high point density of >100 points per m2. In our contribution we demonstrate the feasibility to apply UAS-borne laser scanning for capturing and modelling the complex topography of the study area Neubacher Au, an alluvial forest at the pre-alpine River Pielach (Lower Austria). The area was captured with Riegl's VUX-1 compact time-of-flight laser scanner mounted on a RiCopter (X-8 array octocopter). The scanner features an effective scan rate of 500 kHz and was flown in 50-100 m above ground. At this flying height the laser footprint is 25-50 mm allowing mapping of very small surface details. Furthermore, online waveform processing of the backscattered laser energy enables the retrieval of multiple targets for single laser shots resulting in a dense point cloud of, both, the ground surface and the alluvial vegetation. From the acquired point cloud the following products could be derived: (i) a very high resolution Digital Terrain Model (10 cm raster), (ii) a high resolution model of the water surface of the River Pielach (especially useful for validation of topo-bathymetry LiDAR data) and (iii) a detailed description of the complex vegetation structure.
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Water Ice Clouds in the Martian Atmosphere: A View from MGS TES
NASA Technical Reports Server (NTRS)
Hale, A. S.; Tamppari, L. K.; Christensen, P. R.; Smith, M. D.; Bass, Deborah; Qu, Zheng; Pearl, J. C.
2005-01-01
We use the method of Tamppari et al. to map water ice clouds in the Martian atmosphere. This technique was originally developed to analyze the broadband Viking IRTM channels and we have now applied it to the TES data. To do this, the TES spectra are convolved to the IRTM bandshapes and spatial resolutions, enabling use of the same processing techniques as were used in Tamppari et al.. This retrieval technique relies on using the temperature difference recorded in the 20 micron and 11 micron IRTM bands (or IRTM convolved TES bands) to map cold water ice clouds above the warmer Martian surface. Careful removal of surface contributions to the observed radiance is therefore necessary, and we have used both older Viking-derived basemaps of the surface emissivity and albedo, and new MGS derived basemaps in order the explore any possible differences on cloud retrieval due to differences in surface contribution removal. These results will be presented in our poster. Our previous work has concentrated primarily on comparing MGS TES to Viking data; that work saw that large-scale cloud features, such as the aphelion cloud belt, are quite repeatable from year to year, though small scale behavior shows some variation. Comparison of Viking and MGS era cloud maps will be presented in our poster. In the current stage of our study, we have concentrated our efforts on close analysis of water ice cloud behavior in the northern summer of the three MGS mapping years on relatively small spatial scales, and present our results below. Additional information is included in the original extended abstract.
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Automated extraction and analysis of rock discontinuity characteristics from 3D point clouds
NASA Astrophysics Data System (ADS)
Bianchetti, Matteo; Villa, Alberto; Agliardi, Federico; Crosta, Giovanni B.
2016-04-01
A reliable characterization of fractured rock masses requires an exhaustive geometrical description of discontinuities, including orientation, spacing, and size. These are required to describe discontinuum rock mass structure, perform Discrete Fracture Network and DEM modelling, or provide input for rock mass classification or equivalent continuum estimate of rock mass properties. Although several advanced methodologies have been developed in the last decades, a complete characterization of discontinuity geometry in practice is still challenging, due to scale-dependent variability of fracture patterns and difficult accessibility to large outcrops. Recent advances in remote survey techniques, such as terrestrial laser scanning and digital photogrammetry, allow a fast and accurate acquisition of dense 3D point clouds, which promoted the development of several semi-automatic approaches to extract discontinuity features. Nevertheless, these often need user supervision on algorithm parameters which can be difficult to assess. To overcome this problem, we developed an original Matlab tool, allowing fast, fully automatic extraction and analysis of discontinuity features with no requirements on point cloud accuracy, density and homogeneity. The tool consists of a set of algorithms which: (i) process raw 3D point clouds, (ii) automatically characterize discontinuity sets, (iii) identify individual discontinuity surfaces, and (iv) analyse their spacing and persistence. The tool operates in either a supervised or unsupervised mode, starting from an automatic preliminary exploration data analysis. The identification and geometrical characterization of discontinuity features is divided in steps. First, coplanar surfaces are identified in the whole point cloud using K-Nearest Neighbor and Principal Component Analysis algorithms optimized on point cloud accuracy and specified typical facet size. Then, discontinuity set orientation is calculated using Kernel Density Estimation and principal vector similarity criteria. Poles to points are assigned to individual discontinuity objects using easy custom vector clustering and Jaccard distance approaches, and each object is segmented into planar clusters using an improved version of the DBSCAN algorithm. Modal set orientations are then recomputed by cluster-based orientation statistics to avoid the effects of biases related to cluster size and density heterogeneity of the point cloud. Finally, spacing values are measured between individual discontinuity clusters along scanlines parallel to modal pole vectors, whereas individual feature size (persistence) is measured using 3D convex hull bounding boxes. Spacing and size are provided both as raw population data and as summary statistics. The tool is optimized for parallel computing on 64bit systems, and a Graphic User Interface (GUI) has been developed to manage data processing, provide several outputs, including reclassified point clouds, tables, plots, derived fracture intensity parameters, and export to modelling software tools. We present test applications performed both on synthetic 3D data (simple 3D solids) and real case studies, validating the results with existing geomechanical datasets.
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Building Facade Modeling Under Line Feature Constraint Based on Close-Range Images
NASA Astrophysics Data System (ADS)
Liang, Y.; Sheng, Y. H.
2018-04-01
To solve existing problems in modeling facade of building merely with point feature based on close-range images , a new method for modeling building facade under line feature constraint is proposed in this paper. Firstly, Camera parameters and sparse spatial point clouds data were restored using the SFM , and 3D dense point clouds were generated with MVS; Secondly, the line features were detected based on the gradient direction , those detected line features were fit considering directions and lengths , then line features were matched under multiple types of constraints and extracted from multi-image sequence. At last, final facade mesh of a building was triangulated with point cloud and line features. The experiment shows that this method can effectively reconstruct the geometric facade of buildings using the advantages of combining point and line features of the close - range image sequence, especially in restoring the contour information of the facade of buildings.
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The 3-D Tropical Convective Cloud Spectrum in AMIE Radar Observations and Global Climate Simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schumacher, Courtney
2015-08-31
During the three years of this grant performance, the PI and her research group have made a number of significant contributions towards determining properties of tropical deep convective clouds and how models depict and respond to the heating associated with tropical convective systems. The PI has also been an active ARM/ASR science team member, including playing a significant role in AMIE and GoAmazon2014/5. She served on the DOE ASR radar science steering committee and was a joint chair of the Mesoscale Convective Organization group under the Cloud Life Cycle working group. This grant has funded a number of graduate students,more » many of them women, and the PI and her group have presented their DOE-supported work at various universities and national meetings. The PI and her group participated in the AMIE (2011-12) and GoAmazon2014/5 (2014-15) DOE field deployments that occurred in the tropical Indian Ocean and Brazilian Amazon, respectively. AMIE observational results (DePasquale et al. 2014, Feng et al. 2014, Ahmed and Schumacher 2015) focus on the variation and possible importance of Kelvin waves in various phases of the Madden-Julian Oscillation (MJO), on the synergy of the different wavelength radars deployed on Addu Atoll, and on the importance of humidity thresholds in the tropics on stratiform rain production. Much of the PIs GoAmazon2014/5 results to date relate to overviews of the observations made during the field campaign (Martin et al. 2015, 2016; Fuentes et al. 2016), but also include the introduction of the descending arm and its link to ozone transport from the mid-troposphere to the surface (Gerken et al. 2016). Vertical motion and mass flux profiles from GoAmazon (Giangrande et al. 2016) also show interesting patterns between seasons and provide targets for model simulations. Results from TWP-ICE (Schumacher et al. 2015), which took place in Darwin, Australia in 2006 show that vertical velocity retrievals from the profilers provide structure to better quantify the transition between convective, stratiform, and anvil cloud types.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Dong, Xiquan
In this proposed research, we will investigate how different meteorological regimes and aerosol sources affect DCS properties, diurnal and life cycles, and precipitation using multiple observational platforms (surface, satellite, and aircraft) and NARR reanalysis at the ARM SGP site. The Feng et al. (2011, 2012) DCS results will serve as a starting point for this proposed research, and help us to address some fundamental issues of DCSs, such as convective initiation, rain rate, areal extent (including stratiform and convective regions), and longevity. Convective properties will be stratified by meteorological regime (synoptic/mesoscale patterns) identified by reanalysis. Aerosol information obtained from themore » ARM SGP site will also be stratified by meteorological regimes to understand their effects on convection. Finally, the aircraft in-situ measurements and various radar observations and retrievals during the MC3E campaign will provide a “cloud-truth” dataset and are an invaluable data source for verifying the findings and investigating the proposed hypotheses in Objective 1.« less
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An observational search for CO2 ice clouds on Mars
NASA Technical Reports Server (NTRS)
Bell, James F., III; Calvin, Wendy M.; Pollack, James B.; Crisp, David
1993-01-01
CO2 ice clouds were first directly identified on Mars by the Mariner 6 and 7 infrared spectrometer limb scans. These observations provided support for early theoretical modeling efforts of CO2 condensation. Mariner 9 IRIS temperature profiles of north polar hood clouds were interpreted as indicating that these clouds were composed of H2O ice at lower latitudes and CO2 ice at higher latitudes. The role of CO2 condensation on Mars has recently received increased attention because (1) Kasting's model results indicated that CO2 cloud condensation limits the magnitude of the proposed early Mars CO2/H2O greenhouse, and (2) Pollack el al.'s GCM results indicated that the formation of CO2 ice clouds is favorable at all polar latitudes during the fall and winter seasons. These latter authors have shown that CO2 clouds play an important role in the polar energy balance, as the amount of CO2 contained in the polar caps is constrained by a balance between latent heat release, heat advected from lower latitudes, and thermal emission to space. The polar hood clouds reduce the amount of CO2 condensation on the polar caps because they reduce the net emission to space. There have been many extensive laboratory spectroscopic studies of H2O and CO2 ices and frosts. In this study, we use results from these and other sources to search for the occurrence of diagnostic CO2 (and H2O) ice and/or frost absorption features in ground based near-infrared imaging spectroscopic data of Mars. Our primary goals are (1) to try to confirm the previous direct observations of CO2 clouds on Mars; (2) to determine the spatial extent, temporal variability, and composition (H2O/CO2 ratio) of any clouds detected; and (3) through radiative transfer modeling, to try to determine the mean particle size and optical depth of polar hood clouds, thus, assessing their role in the polar heat budget.
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Real-time terrain storage generation from multiple sensors towards mobile robot operation interface.
Song, Wei; Cho, Seoungjae; Xi, Yulong; Cho, Kyungeun; Um, Kyhyun
2014-01-01
A mobile robot mounted with multiple sensors is used to rapidly collect 3D point clouds and video images so as to allow accurate terrain modeling. In this study, we develop a real-time terrain storage generation and representation system including a nonground point database (PDB), ground mesh database (MDB), and texture database (TDB). A voxel-based flag map is proposed for incrementally registering large-scale point clouds in a terrain model in real time. We quantize the 3D point clouds into 3D grids of the flag map as a comparative table in order to remove the redundant points. We integrate the large-scale 3D point clouds into a nonground PDB and a node-based terrain mesh using the CPU. Subsequently, we program a graphics processing unit (GPU) to generate the TDB by mapping the triangles in the terrain mesh onto the captured video images. Finally, we produce a nonground voxel map and a ground textured mesh as a terrain reconstruction result. Our proposed methods were tested in an outdoor environment. Our results show that the proposed system was able to rapidly generate terrain storage and provide high resolution terrain representation for mobile mapping services and a graphical user interface between remote operators and mobile robots.
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Sideloading - Ingestion of Large Point Clouds Into the Apache Spark Big Data Engine
NASA Astrophysics Data System (ADS)
Boehm, J.; Liu, K.; Alis, C.
2016-06-01
In the geospatial domain we have now reached the point where data volumes we handle have clearly grown beyond the capacity of most desktop computers. This is particularly true in the area of point cloud processing. It is therefore naturally lucrative to explore established big data frameworks for big geospatial data. The very first hurdle is the import of geospatial data into big data frameworks, commonly referred to as data ingestion. Geospatial data is typically encoded in specialised binary file formats, which are not naturally supported by the existing big data frameworks. Instead such file formats are supported by software libraries that are restricted to single CPU execution. We present an approach that allows the use of existing point cloud file format libraries on the Apache Spark big data framework. We demonstrate the ingestion of large volumes of point cloud data into a compute cluster. The approach uses a map function to distribute the data ingestion across the nodes of a cluster. We test the capabilities of the proposed method to load billions of points into a commodity hardware compute cluster and we discuss the implications on scalability and performance. The performance is benchmarked against an existing native Apache Spark data import implementation.
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Hamraz, Hamid; Contreras, Marco A; Zhang, Jun
2017-07-28
Airborne laser scanning (LiDAR) point clouds over large forested areas can be processed to segment individual trees and subsequently extract tree-level information. Existing segmentation procedures typically detect more than 90% of overstory trees, yet they barely detect 60% of understory trees because of the occlusion effect of higher canopy layers. Although understory trees provide limited financial value, they are an essential component of ecosystem functioning by offering habitat for numerous wildlife species and influencing stand development. Here we model the occlusion effect in terms of point density. We estimate the fractions of points representing different canopy layers (one overstory and multiple understory) and also pinpoint the required density for reasonable tree segmentation (where accuracy plateaus). We show that at a density of ~170 pt/m² understory trees can likely be segmented as accurately as overstory trees. Given the advancements of LiDAR sensor technology, point clouds will affordably reach this required density. Using modern computational approaches for big data, the denser point clouds can efficiently be processed to ultimately allow accurate remote quantification of forest resources. The methodology can also be adopted for other similar remote sensing or advanced imaging applications such as geological subsurface modelling or biomedical tissue analysis.
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Real-Time Terrain Storage Generation from Multiple Sensors towards Mobile Robot Operation Interface
Cho, Seoungjae; Xi, Yulong; Cho, Kyungeun
2014-01-01
A mobile robot mounted with multiple sensors is used to rapidly collect 3D point clouds and video images so as to allow accurate terrain modeling. In this study, we develop a real-time terrain storage generation and representation system including a nonground point database (PDB), ground mesh database (MDB), and texture database (TDB). A voxel-based flag map is proposed for incrementally registering large-scale point clouds in a terrain model in real time. We quantize the 3D point clouds into 3D grids of the flag map as a comparative table in order to remove the redundant points. We integrate the large-scale 3D point clouds into a nonground PDB and a node-based terrain mesh using the CPU. Subsequently, we program a graphics processing unit (GPU) to generate the TDB by mapping the triangles in the terrain mesh onto the captured video images. Finally, we produce a nonground voxel map and a ground textured mesh as a terrain reconstruction result. Our proposed methods were tested in an outdoor environment. Our results show that the proposed system was able to rapidly generate terrain storage and provide high resolution terrain representation for mobile mapping services and a graphical user interface between remote operators and mobile robots. PMID:25101321
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NASA Astrophysics Data System (ADS)
Böhm, J.; Bredif, M.; Gierlinger, T.; Krämer, M.; Lindenberg, R.; Liu, K.; Michel, F.; Sirmacek, B.
2016-06-01
Current 3D data capturing as implemented on for example airborne or mobile laser scanning systems is able to efficiently sample the surface of a city by billions of unselective points during one working day. What is still difficult is to extract and visualize meaningful information hidden in these point clouds with the same efficiency. This is where the FP7 IQmulus project enters the scene. IQmulus is an interactive facility for processing and visualizing big spatial data. In this study the potential of IQmulus is demonstrated on a laser mobile mapping point cloud of 1 billion points sampling ~ 10 km of street environment in Toulouse, France. After the data is uploaded to the IQmulus Hadoop Distributed File System, a workflow is defined by the user consisting of retiling the data followed by a PCA driven local dimensionality analysis, which runs efficiently on the IQmulus cloud facility using a Spark implementation. Points scattering in 3 directions are clustered in the tree class, and are separated next into individual trees. Five hours of processing at the 12 node computing cluster results in the automatic identification of 4000+ urban trees. Visualization of the results in the IQmulus fat client helps users to appreciate the results, and developers to identify remaining flaws in the processing workflow.
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Automatic Modelling of Rubble Mound Breakwaters from LIDAR Data
NASA Astrophysics Data System (ADS)
Bueno, M.; Díaz-Vilariño, L.; González-Jorge, H.; Martínez-Sánchez, J.; Arias, P.
2015-08-01
Rubble mound breakwaters maintenance is critical to the protection of beaches and ports. LiDAR systems provide accurate point clouds from the emerged part of the structure that can be modelled to make it more useful and easy to handle. This work introduces a methodology for the automatic modelling of breakwaters with armour units of cube shape. The algorithm is divided in three main steps: normal vector computation, plane segmentation, and cube reconstruction. Plane segmentation uses the normal orientation of the points and the edge length of the cube. Cube reconstruction uses the intersection of three perpendicular planes and the edge length. Three point clouds cropped from the main point cloud of the structure are used for the tests. The number of cubes detected is around 56 % for two of the point clouds and 32 % for the third one over the total physical cubes. Accuracy assessment is done by comparison with manually drawn cubes calculating the differences between the vertexes. It ranges between 6.4 cm and 15 cm. Computing time ranges between 578.5 s and 8018.2 s. The computing time increases with the number of cubes and the requirements of collision detection.
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Application of Template Matching for Improving Classification of Urban Railroad Point Clouds
Arastounia, Mostafa; Oude Elberink, Sander
2016-01-01
This study develops an integrated data-driven and model-driven approach (template matching) that clusters the urban railroad point clouds into three classes of rail track, contact cable, and catenary cable. The employed dataset covers 630 m of the Dutch urban railroad corridors in which there are four rail tracks, two contact cables, and two catenary cables. The dataset includes only geometrical information (three dimensional (3D) coordinates of the points) with no intensity data and no RGB data. The obtained results indicate that all objects of interest are successfully classified at the object level with no false positives and no false negatives. The results also show that an average 97.3% precision and an average 97.7% accuracy at the point cloud level are achieved. The high precision and high accuracy of the rail track classification (both greater than 96%) at the point cloud level stems from the great impact of the employed template matching method on excluding the false positives. The cables also achieve quite high average precision (96.8%) and accuracy (98.4%) due to their high sampling and isolated position in the railroad corridor. PMID:27973452
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The Use of Uas for Rapid 3d Mapping in Geomatics Education
NASA Astrophysics Data System (ADS)
Teo, Tee-Ann; Tian-Yuan Shih, Peter; Yu, Sz-Cheng; Tsai, Fuan
2016-06-01
With the development of technology, UAS is an advance technology to support rapid mapping for disaster response. The aim of this study is to develop educational modules for UAS data processing in rapid 3D mapping. The designed modules for this study are focused on UAV data processing from available freeware or trial software for education purpose. The key modules include orientation modelling, 3D point clouds generation, image georeferencing and visualization. The orientation modelling modules adopts VisualSFM to determine the projection matrix for each image station. Besides, the approximate ground control points are measured from OpenStreetMap for absolute orientation. The second module uses SURE and the orientation files from previous module for 3D point clouds generation. Then, the ground point selection and digital terrain model generation can be archived by LAStools. The third module stitches individual rectified images into a mosaic image using Microsoft ICE (Image Composite Editor). The last module visualizes and measures the generated dense point clouds in CloudCompare. These comprehensive UAS processing modules allow the students to gain the skills to process and deliver UAS photogrammetric products in rapid 3D mapping. Moreover, they can also apply the photogrammetric products for analysis in practice.
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NASA Astrophysics Data System (ADS)
Hamraz, Hamid; Contreras, Marco A.; Zhang, Jun
2017-08-01
Airborne LiDAR point cloud representing a forest contains 3D data, from which vertical stand structure even of understory layers can be derived. This paper presents a tree segmentation approach for multi-story stands that stratifies the point cloud to canopy layers and segments individual tree crowns within each layer using a digital surface model based tree segmentation method. The novelty of the approach is the stratification procedure that separates the point cloud to an overstory and multiple understory tree canopy layers by analyzing vertical distributions of LiDAR points within overlapping locales. The procedure does not make a priori assumptions about the shape and size of the tree crowns and can, independent of the tree segmentation method, be utilized to vertically stratify tree crowns of forest canopies. We applied the proposed approach to the University of Kentucky Robinson Forest - a natural deciduous forest with complex and highly variable terrain and vegetation structure. The segmentation results showed that using the stratification procedure strongly improved detecting understory trees (from 46% to 68%) at the cost of introducing a fair number of over-segmented understory trees (increased from 1% to 16%), while barely affecting the overall segmentation quality of overstory trees. Results of vertical stratification of the canopy showed that the point density of understory canopy layers were suboptimal for performing a reasonable tree segmentation, suggesting that acquiring denser LiDAR point clouds would allow more improvements in segmenting understory trees. As shown by inspecting correlations of the results with forest structure, the segmentation approach is applicable to a variety of forest types.
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Water-Ammonia Ionic Ocean on Uranus and Neptune-Clue from Tropospheric Hydrogen Sulfide Clouds
NASA Astrophysics Data System (ADS)
Atreya, S. K.; Egeler, P. A.; Wong, A.
2005-12-01
Interior models of the ice-giants, Uranus and Neptune, predict a water-ammonia ionic ocean at tens of kilobar pressure [1,2]. If correct, its implication for planetary formation models is profound. In this presentation we demonstrate that the existence of an ionic ocean will manifest itself in the planets' tropospheric cloud structure, particularly in the form of a hydrogen sulfide, i.e. H2S-ice, cloud. In fact, an H2S cloud was introduced ad hoc in the 3-5 bar region to explain microwave absorption [3] and the methane [4] observations, but its presence cannot be proved in the absence of entry probes. Our equilibrium cloud condensation model (ECCM) shows that an H2S-ice cloud does not form when conventional enrichment factors (20-30× solar at Uranus, and 30-50× solar at Neptune) are employed for all heavy elements (mass >4) [5]. However, a deep ``cloud'' composed of a weak solution of ammonia and water forms, and its base is at 370 and 500 bars, respectively, for 30× solar and 50× solar enrichment factors. If an ionic ``ocean'' exists much deeper, water vapor, as well as ammonia dissolved in it, would be severely depleted at levels above this ocean. The consequences of such water vapor and ammonia depletions are that (1) clouds of water and ammonia, if present, are much less prominent; (2) only small amount of H2S vapor is removed by NH3, to form an NH4SH cloud; so that (3) a cloud of H2S-ice can now form; and (4) an H2O ``ocean'' in the 1-kilobar region [6] does not form. This scenario has important implications for the design of entry probe missions, as measurements to only 10-20 bars, rather than kilobar levels, will need to be made. The heavy elements, Ar, Kr, Xe, Ne, C, and S, as well as He, D/H, GeH4, AsH3, PH3, and CO can all be accessed at pressures less than 20 bars. These measurements are critical for constraining the formation models [5,7,8]. Measurement of water in the well-mixed region of Uranus and Neptune is technologically highly challenging, even if there were no ionic ocean. And, neither H2O nor NH3 can be accessed if there is a deep ionic ocean. On the other hand, if all other heavy elements and above species and isotopes were measured, O and N are not critical for the formation models of Uranus and Neptune [5]. References: [1] Podolak, et al., 1991, in Uranus (J. Bergstralh, et al., eds.), Univ. of Arizona Press. pp 48-49.1991; [2] Ree, FH, Physica, 1986, 139-140B, 73-78; [3] de Pater, et al., 1991, Icarus, 91, 220; [4] Baines, K, Hammel, H, 1994, Icarus, 109, 20 ; [5] Atreya, SK, and Wong, AS, pp121-126, in ``Outer Planets", T. Encrenaz, et al., eds, Springer, 2005; [6] Wiktorowicz, SJ, Ingersoll, AP, 2004 DPS 36.0501; [7] Owen, T, Encrenaz, T, 2003, 106, 121; [8] Atreya, S.K., et al., 2003, Planet Space Sci., 47. 1243.
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NASA Astrophysics Data System (ADS)
Wang, Jinxia; Dou, Aixia; Wang, Xiaoqing; Huang, Shusong; Yuan, Xiaoxiang
2016-11-01
Compared to remote sensing image, post-earthquake airborne Light Detection And Ranging (LiDAR) point cloud data contains a high-precision three-dimensional information on earthquake disaster which can improve the accuracy of the identification of destroy buildings. However after the earthquake, the damaged buildings showed so many different characteristics that we can't distinguish currently between trees and damaged buildings points by the most commonly used method of pre-processing. In this study, we analyse the number of returns for given pulse of trees and damaged buildings point cloud and explore methods to distinguish currently between trees and damaged buildings points. We propose a new method by searching for a certain number of neighbourhood space and calculate the ratio(R) of points whose number of returns for given pulse greater than 1 of the neighbourhood points to separate trees from buildings. In this study, we select some point clouds of typical undamaged building, collapsed building and tree as samples from airborne LiDAR point cloud data which got after 2010 earthquake in Haiti MW7.0 by the way of human-computer interaction. Testing to get the Rvalue to distinguish between trees and buildings and apply the R-value to test testing areas. The experiment results show that the proposed method in this study can distinguish between building (undamaged and damaged building) points and tree points effectively but be limited in area where buildings various, damaged complex and trees dense, so this method will be improved necessarily.
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Diffuse cloud chemistry. [in interstellar matter
NASA Technical Reports Server (NTRS)
Van Dishoeck, Ewine F.; Black, John H.
1988-01-01
The current status of models of diffuse interstellar clouds is reviewed. A detailed comparison of recent gas-phase steady-state models shows that both the physical conditions and the molecular abundances in diffuse clouds are still not fully understood. Alternative mechanisms are discussed and observational tests which may discriminate between the various models are suggested. Recent developments regarding the velocity structure of diffuse clouds are mentioned. Similarities and differences between the chemistries in diffuse clouds and those in translucent and high latitude clouds are pointed out.