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Sample records for dar sharayet-e adi-e

  1. LiDAR: Providing structure

    USGS Publications Warehouse

    Vierling, Lee A.; Martinuzzi, Sebastián; Asner, Gregory P.; Stoker, Jason M.; Johnson, Brian R.

    2011-01-01

    Since the days of MacArthur, three-dimensional (3-D) structural information on the environment has fundamentally transformed scientific understanding of ecological phenomena (MacArthur and MacArthur 1961). Early data on ecosystem structure were painstakingly laborious to collect. However, as reviewed and reported in recent volumes of Frontiers(eg Vierling et al. 2008; Asner et al.2011), advances in light detection and ranging (LiDAR) remote-sensing technology provide quantitative and repeatable measurements of 3-D ecosystem structure that enable novel ecological insights at scales ranging from the plot, to the landscape, to the globe. Indeed, annual publication of studies using LiDAR to interpret ecological phenomena increased 17-fold during the past decade, with over 180 new studies appearing in 2010 (ISI Web of Science search conducted on 23 Mar 2011: [{lidar AND ecol*} OR {lidar AND fores*} OR {lidar AND plant*}]).

  2. Characterizing Lava Flows With LiDAR

    NASA Astrophysics Data System (ADS)

    Deligne, N. I.; Cashman, K. V.; Deardorff, N.; Dietterich, H. R.; House, P. K.; Soule, S.

    2009-12-01

    Digital elevation models (DEMs) have been used in volcanology in predictive modeling of lava flow paths, both for assessment of potential hazards and specific predictions of lava flow paths. Topographic analysis of a lava flow is potentially useful for mapping and quantifying flow surface morphologies, which in turn can be used to determine flow emplacement conditions, such as effusion rate, steadiness of flow, and interactions with pre-existing topography and surface water. However, this has been limited in application because of the coarse resolution of most DEMs. In recent years, use of Light Detection and Ranging (LiDAR) airborne laser altimetry, capable of producing high resolution (≤ 1 meter) DEMs, has become increasingly common in the geomorphic and mapping community. However, volcanologists have made little use of airborne LiDAR. Here we compare information obtained using field observations and standard (10 meter) DEMs against LiDAR high resolution DEMs to assess the usefulness, capabilities, and limitations of LiDAR as applicable to lava flows. We compare morphologic characteristics of five lava flows of different compositions, tectonic settings, flow extents, slopes, and eruption duration: (1) 1984 Mauna Loa lava flow, Hawaii; (2) December 1974 Kilauea lava flow, Hawaii; (3) c. 1600 ybp Collier Cone lava flow, central Oregon Cascades; (4) Holocene lava flows from the Sand Mountain volcanic chain, central Oregon Cascades; and (5) Pleistocene lava flows along the Owyhee River, eastern Oregon basin and range. These lava flows range in composition from basalt to andesite, and have eruption durations ranging from 6 hours (observed) to years (inferred). We measure channel width, levee and flow front heights, compression ridge amplitude, wavelength and tumuli dimensions, and surface roughness. For all but the smallest scale features, LiDAR is easily used to quantify these features, which often is impossible or technically challenging to do in the field, while

  3. DoD Architecture Registry System (DARS)

    DTIC Science & Technology

    2012-04-30

    Communications-Electronics Research, Development and Engineering Center (CERDEC), S ft E i i Di t t (SED) UNCLASSIFIED 5 o ware ng neer ng rec ora e...Army 1245 (1183, 5 %)  Air Force 960 (889, 8%)  OSD 358 (346, 3%) M i 223 ( %) ar nes 209, 7  Combatant Command 156 (155, 1%)  Joint Staff...Program • Deployed DARS Release 5 6 in April 29 2011 This releaseCompleted Support . . included: • Migrate Community Management and

  4. Recent development of hyperspectral LiDAR using supercontinuum laser

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Li, Chuanrong; Zhou, Mei; Zhang, Huijing; He, Wenjing; Li, Wei; Qiu, Yuanyuan

    2016-10-01

    Hyperspectral Light Detection And Ranging (Hyperspectral LiDAR), a recently developed technique, combines the advantages of the LiDAR and hyperspectral imaging and has been attractive for many applications. Supercontinuum laser (SC laser), a rapidly developing technique offers hyperspectral LiDAR a suitable broadband laser source and makes hyperspectral Lidar become an installation from a theory. In this paper, the recent research and progressing of the hyperspectral LiDAR are reviewed. The hyperspectral LiDAR has been researched in theory, prototype system, instrument, and application experiment. However, the pulse energy of the SC laser is low so that the range of the hyperspectral LiDAR is limited. Moreover, considering the characteristics of sensors and A/D converter, in order to obtain the full waveform of the echo, the repetition rate and the pulse width of the SC laser needs to be limited. Recently, improving the detection ability of hyperspectral LiDAR, especially improving the detection range, is a main research area. A higher energy pulse SC laser, a more sensitive sensor, or some algorithms are applied in hyperspectral LiDAR to improve the detection distance from 12 m to 1.5 km. At present, a lot of research has been focused on this novel technology which would be applied in more applications.

  5. LiDAR - An emerging tool for geological applications

    USGS Publications Warehouse

    Stoker, Jason M.

    2012-01-01

    Over the past five to ten years the use and applicability of light detection and ranging (LiDAR) technology has increased dramatically. As a result, more and more LiDAR data now are being collected across the country for a wide range of applications, and LiDAR currently is the technology of choice for high resolution terrain model creation, 3-D city and infrastructure modeling, forestry, and a wide range of scientific applications. LiDAR is a key technology for geological applications both within and outside the U.S. Geological Survey, and efforts are underway to try to collect high resolution LiDAR data for the entire United States (https://pubs.usgs.gov/fs/2012/3089/pdf/fs2012-3089.pdf).

  6. Processing LiDAR Data to Predict Natural Hazards

    NASA Technical Reports Server (NTRS)

    Fairweather, Ian; Crabtree, Robert; Hager, Stacey

    2008-01-01

    ELF-Base and ELF-Hazards (wherein 'ELF' signifies 'Extract LiDAR Features' and 'LiDAR' signifies 'light detection and ranging') are developmental software modules for processing remote-sensing LiDAR data to identify past natural hazards (principally, landslides) and predict future ones. ELF-Base processes raw LiDAR data, including LiDAR intensity data that are often ignored in other software, to create digital terrain models (DTMs) and digital feature models (DFMs) with sub-meter accuracy. ELF-Hazards fuses raw LiDAR data, data from multispectral and hyperspectral optical images, and DTMs and DFMs generated by ELF-Base to generate hazard risk maps. Advanced algorithms in these software modules include line-enhancement and edge-detection algorithms, surface-characterization algorithms, and algorithms that implement innovative data-fusion techniques. The line-extraction and edge-detection algorithms enable users to locate such features as faults and landslide headwall scarps. Also implemented in this software are improved methodologies for identification and mapping of past landslide events by use of (1) accurate, ELF-derived surface characterizations and (2) three LiDAR/optical-data-fusion techniques: post-classification data fusion, maximum-likelihood estimation modeling, and hierarchical within-class discrimination. This software is expected to enable faster, more accurate forecasting of natural hazards than has previously been possible.

  7. Tensor Modeling Based for Airborne LiDAR Data Classification

    NASA Astrophysics Data System (ADS)

    Li, N.; Liu, C.; Pfeifer, N.; Yin, J. F.; Liao, Z. Y.; Zhou, Y.

    2016-06-01

    Feature selection and description is a key factor in classification of Earth observation data. In this paper a classification method based on tensor decomposition is proposed. First, multiple features are extracted from raw LiDAR point cloud, and raster LiDAR images are derived by accumulating features or the "raw" data attributes. Then, the feature rasters of LiDAR data are stored as a tensor, and tensor decomposition is used to select component features. This tensor representation could keep the initial spatial structure and insure the consideration of the neighborhood. Based on a small number of component features a k nearest neighborhood classification is applied.

  8. Automatic registration method for mobile LiDAR data

    NASA Astrophysics Data System (ADS)

    Wang, Ruisheng; Ferrie, Frank P.

    2015-01-01

    We present an automatic mutual information (MI) registration method for mobile LiDAR and panoramas collected from a driving vehicle. The suitability of MI for registration of aerial LiDAR and aerial oblique images has been demonstrated under an assumption that minimization of joint entropy (JE) is a sufficient approximation of maximization of MI. We show that this assumption is invalid for the ground-level data. The entropy of a LiDAR image cannot be regarded as approximately constant for small perturbations. Instead of minimizing the JE, we directly maximize MI to estimate corrections of camera poses. Our method automatically registers mobile LiDAR with spherical panoramas over an approximate 4-km drive, and is the first example we are aware of that tests MI registration in a large-scale context.

  9. Shipborne LiDAR system for coastal change monitoring

    NASA Astrophysics Data System (ADS)

    Kim, chang hwan; Park, chang hong; Kim, hyun wook; hyuck Kim, won; Lee, myoung hoon; Park, hyeon yeong

    2016-04-01

    Coastal areas, used as human utilization areas like leisure space, medical care, ports and power plants, etc., are regions that are continuously changing and interconnected with oceans and land and the sea level has risen by about 8cm (1.9mm / yr) due to global warming from 1964 year to 2006 year in Korea. Coastal erosion due to sea-level rise has caused the problem of marine ecosystems and loss of tourism resources, etc. Regular monitoring of coastal erosion is essential at key locations with such volatility. But the survey method of land mobile LiDAR (light detection and ranging) system has much time consuming and many restrictions. For effective monitoring beach erosion, KIOST (Korea Institute of Ocean Science & Technology) has constructed a shipborne mobile LiDAR system. The shipborne mobile LiDAR system comprised a land mobile LiDAR (RIEGL LMS-420i), an INS (inertial navigation system, MAGUS Inertial+), a RTKGPS (LEICA GS15 GS25), and a fixed platform. The shipborne mobile LiDAR system is much more effective than a land mobile LiDAR system in the measuring of fore shore areas without shadow zone. Because the vessel with the shipborne mobile LiDAR system is continuously moved along the shoreline, it is possible to efficiently survey a large area in a relatively short time. Effective monitoring of the changes using the constructed shipborne mobile LiDAR system for seriously eroded coastal areas will be able to contribute to coastal erosion management and response.

  10. Modelling rating curves using remotely sensed LiDAR data

    USGS Publications Warehouse

    Nathanson, Marcus; Kean, Jason W.; Grabs, Thomas J.; Seibert, Jan; Laudon, Hjalmar; Lyon, Steve W.

    2012-01-01

    Accurate stream discharge measurements are important for many hydrological studies. In remote locations, however, it is often difficult to obtain stream flow information because of the difficulty in making the discharge measurements necessary to define stage-discharge relationships (rating curves). This study investigates the feasibility of defining rating curves by using a fluid mechanics-based model constrained with topographic data from an airborne LiDAR scanning. The study was carried out for an 8m-wide channel in the boreal landscape of northern Sweden. LiDAR data were used to define channel geometry above a low flow water surface along the 90-m surveyed reach. The channel topography below the water surface was estimated using the simple assumption of a flat streambed. The roughness for the modelled reach was back calculated from a single measurment of discharge. The topographic and roughness information was then used to model a rating curve. To isolate the potential influence of the flat bed assumption, a 'hybrid model' rating curve was developed on the basis of data combined from the LiDAR scan and a detailed ground survey. Whereas this hybrid model rating curve was in agreement with the direct measurements of discharge, the LiDAR model rating curve was equally in agreement with the medium and high flow measurements based on confidence intervals calculated from the direct measurements. The discrepancy between the LiDAR model rating curve and the low flow measurements was likely due to reduced roughness associated with unresolved submerged bed topography. Scanning during periods of low flow can help minimize this deficiency. These results suggest that combined ground surveys and LiDAR scans or multifrequency LiDAR scans that see 'below' the water surface (bathymetric LiDAR) could be useful in generating data needed to run such a fluid mechanics-based model. This opens a realm of possibility to remotely sense and monitor stream flows in channels in remote

  11. Georeferenced LiDAR 3D Vine Plantation Map Generation

    PubMed Central

    Llorens, Jordi; Gil, Emilio; Llop, Jordi; Queraltó, Meritxell

    2011-01-01

    The use of electronic devices for canopy characterization has recently been widely discussed. Among such devices, LiDAR sensors appear to be the most accurate and precise. Information obtained with LiDAR sensors during reading while driving a tractor along a crop row can be managed and transformed into canopy density maps by evaluating the frequency of LiDAR returns. This paper describes a proposed methodology to obtain a georeferenced canopy map by combining the information obtained with LiDAR with that generated using a GPS receiver installed on top of a tractor. Data regarding the velocity of LiDAR measurements and UTM coordinates of each measured point on the canopy were obtained by applying the proposed transformation process. The process allows overlap of the canopy density map generated with the image of the intended measured area using Google Earth®, providing accurate information about the canopy distribution and/or location of damage along the rows. This methodology was applied and tested on different vine varieties and crop stages in two important vine production areas in Spain. The results indicate that the georeferenced information obtained with LiDAR sensors appears to be an interesting tool with the potential to improve crop management processes. PMID:22163952

  12. Georeferenced LiDAR 3D vine plantation map generation.

    PubMed

    Llorens, Jordi; Gil, Emilio; Llop, Jordi; Queraltó, Meritxell

    2011-01-01

    The use of electronic devices for canopy characterization has recently been widely discussed. Among such devices, LiDAR sensors appear to be the most accurate and precise. Information obtained with LiDAR sensors during reading while driving a tractor along a crop row can be managed and transformed into canopy density maps by evaluating the frequency of LiDAR returns. This paper describes a proposed methodology to obtain a georeferenced canopy map by combining the information obtained with LiDAR with that generated using a GPS receiver installed on top of a tractor. Data regarding the velocity of LiDAR measurements and UTM coordinates of each measured point on the canopy were obtained by applying the proposed transformation process. The process allows overlap of the canopy density map generated with the image of the intended measured area using Google Earth(®), providing accurate information about the canopy distribution and/or location of damage along the rows. This methodology was applied and tested on different vine varieties and crop stages in two important vine production areas in Spain. The results indicate that the georeferenced information obtained with LiDAR sensors appears to be an interesting tool with the potential to improve crop management processes.

  13. LiDAR Vegetation Investigation and Signature Analysis System (LVISA)

    NASA Astrophysics Data System (ADS)

    Höfle, Bernhard; Koenig, Kristina; Griesbaum, Luisa; Kiefer, Andreas; Hämmerle, Martin; Eitel, Jan; Koma, Zsófia

    2015-04-01

    Our physical environment undergoes constant changes in space and time with strongly varying triggers, frequencies, and magnitudes. Monitoring these environmental changes is crucial to improve our scientific understanding of complex human-environmental interactions and helps us to respond to environmental change by adaptation or mitigation. The three-dimensional (3D) description of the Earth surface features and the detailed monitoring of surface processes using 3D spatial data have gained increasing attention within the last decades, such as in climate change research (e.g., glacier retreat), carbon sequestration (e.g., forest biomass monitoring), precision agriculture and natural hazard management. In all those areas, 3D data have helped to improve our process understanding by allowing quantifying the structural properties of earth surface features and their changes over time. This advancement has been fostered by technological developments and increased availability of 3D sensing systems. In particular, LiDAR (light detection and ranging) technology, also referred to as laser scanning, has made significant progress and has evolved into an operational tool in environmental research and geosciences. The main result of LiDAR measurements is a highly spatially resolved 3D point cloud. Each point within the LiDAR point cloud has a XYZ coordinate associated with it and often additional information such as the strength of the returned backscatter. The point cloud provided by LiDAR contains rich geospatial, structural, and potentially biochemical information about the surveyed objects. To deal with the inherently unorganized datasets and the large data volume (frequently millions of XYZ coordinates) of LiDAR datasets, a multitude of algorithms for automatic 3D object detection (e.g., of single trees) and physical surface description (e.g., biomass) have been developed. However, so far the exchange of datasets and approaches (i.e., extraction algorithms) among LiDAR users

  14. Uas Topographic Mapping with Velodyne LiDAR Sensor

    NASA Astrophysics Data System (ADS)

    Jozkow, G.; Toth, C.; Grejner-Brzezinska, D.

    2016-06-01

    Unmanned Aerial System (UAS) technology is nowadays willingly used in small area topographic mapping due to low costs and good quality of derived products. Since cameras typically used with UAS have some limitations, e.g. cannot penetrate the vegetation, LiDAR sensors are increasingly getting attention in UAS mapping. Sensor developments reached the point when their costs and size suit the UAS platform, though, LiDAR UAS is still an emerging technology. One issue related to using LiDAR sensors on UAS is the limited performance of the navigation sensors used on UAS platforms. Therefore, various hardware and software solutions are investigated to increase the quality of UAS LiDAR point clouds. This work analyses several aspects of the UAS LiDAR point cloud generation performance based on UAS flights conducted with the Velodyne laser scanner and cameras. The attention was primarily paid to the trajectory reconstruction performance that is essential for accurate point cloud georeferencing. Since the navigation sensors, especially Inertial Measurement Units (IMUs), may not be of sufficient performance, the estimated camera poses could allow to increase the robustness of the estimated trajectory, and subsequently, the accuracy of the point cloud. The accuracy of the final UAS LiDAR point cloud was evaluated on the basis of the generated DSM, including comparison with point clouds obtained from dense image matching. The results showed the need for more investigation on MEMS IMU sensors used for UAS trajectory reconstruction. The accuracy of the UAS LiDAR point cloud, though lower than for point cloud obtained from images, may be still sufficient for certain mapping applications where the optical imagery is not useful.

  15. Automated Probabilistic LiDAR Swath Registration

    NASA Astrophysics Data System (ADS)

    Jalobeanu, A.; Gonçalves, G. R.

    2014-12-01

    We recently developed a new point cloud registration algorithm. Compared to Iterated Closest Point (ICP) techniques, it is robust to noise and outliers, and easier to use, as it is less sensitive to initial conditions. It minimizes the entropy of the joint point cloud (including intensity attributes to help register areas with poor relief), uses a voxel space and B-Spline interpolation to accelerate computation. A natural application of registration is swath alignment in airborne light detection and ranging (LiDAR). Indeed, due to uncertainty in the inertial navigation system (INS), attitude angles are subject to time-dependent errors. Such errors can be understood as a sum of three terms: 1) a global term, or boresight error, which can be addressed using several existing techniques; 2) a low-frequency term, which is modeled as a constant attitude error for regions several hundred meters along-track; 3) a high-frequency term, responsible for corduroy artifacts (not addressed here). We propose to use the new registration algorithm to correct the low-frequency attitude variations. Relative geometric errors are significantly reduced, as pairs of swaths are registered onto each other local corrections. Absolute geometric errors are reduced during a second step, by applying all the corrections together to the entire dataset. We used a test area of 200 km2 in Portugal, with a density of 3-4 pts/m2. The point clouds were derived from waveform data, and include predictive range uncertainties estimated within a Bayesian framework. The data collection was supported by FCT and FEDER as part of the AutoProbaDTM research project (2009-2012). Modeling and reducing geometric error helps build consistent uncertainty maps. After correction, residual errors are taken into account in the final 3D error budget. For gridded elevation models a vertical uncertainty map is computed. Finally, it is possible to use the inter-swath registration parameters to estimate the distribution of

  16. Wet Channel Network Extraction based on LiDAR Data

    NASA Astrophysics Data System (ADS)

    Hooshyar, M.; Kim, S.; Wang, D.; Medeiros, S. C.

    2015-12-01

    The temporal dynamics of stream network is vitally important for understanding hydrologic processes including groundwater interactions and hydrograph recessions. However, observations are limited on flowing channel heads, which are usually located in headwater catchments and under canopy. Near infrared LiDAR data provides an opportunity to map the flowing channel network owing to the fine spatial resolution, canopy penetration, and strong absorption of the light energy by the water surface. A systematic method is developed herein to map flowing channel networks based on the signal intensity of ground LiDAR return, which is lower on water surfaces than on dry surfaces. Based on the selected sample sites where the wetness conditions are known, the signal intensities of ground returns are extracted from the LiDAR point data. The frequency distributions of wet surface and dry surface returns are constructed. With the aid of LiDAR-based ground elevation, the signal intensity thresholds are identified for mapping flowing channels. The developed method is applied to Lake Tahoe area based on eight LiDAR snapshots during recession periods in five watersheds. A power-law relationship between streamflow and flowing channel length during the recession period is derived based on the result.

  17. Waveform LiDAR across forest biomass gradients

    NASA Astrophysics Data System (ADS)

    Montesano, P. M.; Nelson, R. F.; Dubayah, R.; Sun, G.; Ranson, J.

    2011-12-01

    Detailed information on the quantity and distribution of aboveground biomass (AGB) is needed to understand how it varies across space and changes over time. Waveform LiDAR data is routinely used to derive the heights of scattering elements in each illuminated footprint, and the vertical structure of vegetation is related to AGB. Changes in LiDAR waveforms across vegetation structure gradients can demonstrate instrument sensitivity to land cover transitions. A close examination of LiDAR waveforms in footprints across a forest gradient can provide new insight into the relationship of vegetation structure and forest AGB. In this study we use field measurements of individual trees within Laser Vegetation Imaging Sensor (LVIS) footprints along transects crossing forest to non-forest gradients to examine changes in LVIS waveform characteristics at sites with low (< 50Mg/ha) AGB. We relate field AGB measurements to original and adjusted LVIS waveforms to detect the forest AGB interval along a forest - non-forest transition in which the LVIS waveform lose the ability to discern differences in AGB. Our results help identify the lower end the forest biomass range that a ~20m footprint waveform LiDAR can detect, which can help infer accumulation of biomass after disturbances and during forest expansion, and which can guide the use of LiDAR within a multi-sensor fusion biomass mapping approach.

  18. Using LiDAR technology in forestry activities.

    PubMed

    Akay, Abdullah Emin; Oğuz, Hakan; Karas, Ismail Rakip; Aruga, Kazuhiro

    2009-04-01

    Managing natural resources in wide-scale areas can be highly time and resource consuming task which requires significant amount of data collection in the field and reduction of the data in the office to provide the necessary information. High performance LiDAR remote sensing technology has recently become an effective tool for use in applications of natural resources. In the field of forestry, the LiDAR measurements of the forested areas can provide high-quality data on three-dimensional characterizations of forest structures. Besides, LiDAR data can be used to provide very high quality and accurate Digital Elevation Model (DEM) for the forested areas. This study presents the progress and opportunities of using LiDAR remote sensing technology in various forestry applications. The results indicate that LiDAR based forest structure data and high-resolution DEMs can be used in wide-scale forestry activities such as stand characterizations, forest inventory and management, fire behaviour modeling, and forest operations.

  19. Application of LiDAR's multiple attributes for wetland classification

    NASA Astrophysics Data System (ADS)

    Ding, Qiong; Ji, Shengyue; Chen, Wu

    2016-03-01

    Wetlands have received intensive interdisciplinary attention as a unique ecosystem and valuable resources. As a new technology, the airborne LiDAR system has been applied in wetland research these years. However, most of the studies used only one or two LiDAR observations to extract either terrain or vegetation in wetlands. This research aims at integrating LiDAR's multiple attributes (DSM, DTM, off-ground features, Slop map, multiple pulse returns, and normalized intensity) to improve mapping and classification of wetlands based on a multi-level object-oriented classification method. By using this method, we are able to classify the Yellow River Delta wetland into eight classes with overall classification accuracy of 92.5%

  20. Raster Vs. Point Cloud LiDAR Data Classification

    NASA Astrophysics Data System (ADS)

    El-Ashmawy, N.; Shaker, A.

    2014-09-01

    Airborne Laser Scanning systems with light detection and ranging (LiDAR) technology is one of the fast and accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models (DTM/DSM) is the main application of collecting LiDAR range data. Recently, LiDAR range and intensity data have been used for land cover classification applications. Data range and Intensity, (strength of the backscattered signals measured by the LiDAR systems), are affected by the flying height, the ground elevation, scanning angle and the physical characteristics of the objects surface. These effects may lead to uneven distribution of point cloud or some gaps that may affect the classification process. Researchers have investigated the conversion of LiDAR range point data to raster image for terrain modelling. Interpolation techniques have been used to achieve the best representation of surfaces, and to fill the gaps between the LiDAR footprints. Interpolation methods are also investigated to generate LiDAR range and intensity image data for land cover classification applications. In this paper, different approach has been followed to classifying the LiDAR data (range and intensity) for land cover mapping. The methodology relies on the classification of the point cloud data based on their range and intensity and then converted the classified points into raster image. The gaps in the data are filled based on the classes of the nearest neighbour. Land cover maps are produced using two approaches using: (a) the conventional raster image data based on point interpolation; and (b) the proposed point data classification. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to compare the results of the two approaches. Five different land cover classes can be distinguished in that area: buildings, roads and parking areas, trees, low vegetation (grass), and bare soil. The results show that an improvement of around 10 % in the

  1. Modeling low-height vegetation with airborne LiDAR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Low-height vegetation, common in semiarid regions, is difficult to characterize with LiDAR (Light Detection and Ranging) due to similarities, in time and space, of the point returns of vegetation and ground. Other complications may occur due to the low-height vegetation structural characteristics a...

  2. Airborne LiDAR based Mapping of Alpine Permafrost Distribution

    NASA Astrophysics Data System (ADS)

    Sailer, Rudolf; Bollmann, Erik; Briese, Christian; Fischer, Andrea; Krainer, Karl; Pfeifer, Norbert; Rieg, Lorenzo; Stötter, Johann

    2010-05-01

    Recent global climate change findings show an acceleration of melting of glaciers, ice-sheets and ice caps. Extended remote sensing and in-situ measurements demonstrate that glaciers are losing mass at an increasing rate. In contrast to glaciers with large mass losses (about 5 m per year at the lower parts of the glacier tongue of Hintereisferner, Ötztal Alps, Tyrol, Austria), moderate to small changing rates (centimetres to decimetres per year) characterize the surface variations caused by permafrost degradation in high mountain areas. For a reliable mapping of the spatial permafrost distribution advanced remote sensing techniques with a high degree of vertical accuracy have to be applied. Recent studies have shown that airborne LiDAR survey in mountainous regions provide high-resolution spatial data with a vertical accuracy range of centimetre to decimetre. This prediction is based on a world wide unique dataset of 18 airborne LiDAR campaigns covering the Hintereisferner region . Furthermore, the according multi-temporal dataset offers the opportunity to identify surface changes (altitudinal changes) outside glaciated areas, which have not been observed until now. Excluding gravitational induced processes these altitudinal changes have to be assigned to alpine permafrost degradations, although detailed information from prominent permafrost features like rock glaciers are missing. Beyond the detection of the climate induced permafrost degradation, based on the multi-temporal LiDAR data set, the method (point based and avoiding point to raster conversions) will be applied to identify altitudinal changes and displacement rates of prominent rock glaciers in the Stubai and Ötztal Alps (Tyrol, Austria). In contrast to the multi-temporal approach, with at least one LiDAR terrain model per ablation period (June to September), the analysis of the rock glacier features is based on a data set of only two LiDAR campaigns, which were carried out with a time shift of four

  3. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Satellite DARS applications subject to...) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401 Satellite DARS applications subject to competitive bidding. Mutually exclusive initial applications for...

  4. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 2 2012-10-01 2012-10-01 false Satellite DARS applications subject to...) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401 Satellite DARS applications subject to competitive bidding. Mutually exclusive initial applications for...

  5. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 47 Telecommunication 2 2014-10-01 2014-10-01 false Satellite DARS applications subject to...) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401 Satellite DARS applications subject to competitive bidding. Mutually exclusive initial applications for...

  6. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 47 Telecommunication 2 2013-10-01 2013-10-01 false Satellite DARS applications subject to...) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401 Satellite DARS applications subject to competitive bidding. Mutually exclusive initial applications for...

  7. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 2 2011-10-01 2011-10-01 false Satellite DARS applications subject to...) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401 Satellite DARS applications subject to competitive bidding. Mutually exclusive initial applications for...

  8. Volume component analysis for classification of LiDAR data

    NASA Astrophysics Data System (ADS)

    Varney, Nina M.; Asari, Vijayan K.

    2015-03-01

    One of the most difficult challenges of working with LiDAR data is the large amount of data points that are produced. Analysing these large data sets is an extremely time consuming process. For this reason, automatic perception of LiDAR scenes is a growing area of research. Currently, most LiDAR feature extraction relies on geometrical features specific to the point cloud of interest. These geometrical features are scene-specific, and often rely on the scale and orientation of the object for classification. This paper proposes a robust method for reduced dimensionality feature extraction of 3D objects using a volume component analysis (VCA) approach.1 This VCA approach is based on principal component analysis (PCA). PCA is a method of reduced feature extraction that computes a covariance matrix from the original input vector. The eigenvectors corresponding to the largest eigenvalues of the covariance matrix are used to describe an image. Block-based PCA is an adapted method for feature extraction in facial images because PCA, when performed in local areas of the image, can extract more significant features than can be extracted when the entire image is considered. The image space is split into several of these blocks, and PCA is computed individually for each block. This VCA proposes that a LiDAR point cloud can be represented as a series of voxels whose values correspond to the point density within that relative location. From this voxelized space, block-based PCA is used to analyze sections of the space where the sections, when combined, will represent features of the entire 3-D object. These features are then used as the input to a support vector machine which is trained to identify four classes of objects, vegetation, vehicles, buildings and barriers with an overall accuracy of 93.8%

  9. LiDAR observation of the flow structure in typhoons

    NASA Astrophysics Data System (ADS)

    Wu, Yu-Ting; Hsuan, Chung-Yao; Lin, Ta-Hui

    2015-04-01

    Taiwan is subject to 3.4 landfall typhoons each year in average, generally occurring in the third quarter of every year (July-September). Understanding of boundary-layer turbulence characteristics of a typhoon is needed to ensure the safety of both onshore and offshore wind turbines used for power generation. In this study, a floating LiDAR (Light Detection and Ranging) was deployed in a harbor to collect data of wind turbulence, atmospheric pressure, and temperature in three typhoon events (Matmo typhoon, Soulik typhoon, Trami typhoon). Data collected from the floating LiDAR and from meteorological stations located at Taipei, Taichung and Kaohsiung are adopted to analyse the wind turbulence characteristics in the three typhoon events. The measurement results show that the maximum 10-min average wind speed measured with the floating LiDAR is up to 24 m/s at a height of 200 m. Compared with other normal days, the turbulence intensity is lower in the three typhoon events where the wind speed has a rapid increase. Changes of wind direction take place clearly as the typhoons cross Taiwan from East to West. Within the crossing intervals, the vertical momentum flux is observed to have a significant pattern with both upward and downward propagating waves which are relevant to the flow structure of the typhoons.

  10. Road Curb Extraction From Mobile LiDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Xu, Sheng; Wang, Ruisheng; Zheng, Han

    2017-02-01

    Automatic extraction of road curbs from uneven, unorganized, noisy and massive 3D point clouds is a challenging task. Existing methods often project 3D point clouds onto 2D planes to extract curbs. However, the projection causes loss of 3D information which degrades the performance of the detection. This paper presents a robust, accurate and efficient method to extract road curbs from 3D mobile LiDAR point clouds. Our method consists of two steps: 1) extracting the candidate points of curbs based on the proposed novel energy function and 2) refining the candidate points using the proposed least cost path model. We evaluated our method on a large-scale of residential area (16.7GB, 300 million points) and an urban area (1.07GB, 20 million points) mobile LiDAR point clouds. Results indicate that the proposed method is superior to the state-of-the-art methods in terms of robustness, accuracy and efficiency. The proposed curb extraction method achieved a completeness of 78.62% and a correctness of 83.29%. These experiments demonstrate that the proposed method is a promising solution to extract road curbs from mobile LiDAR point clouds.

  11. Rockfall hazard analysis using LiDAR and spatial modeling

    NASA Astrophysics Data System (ADS)

    Lan, Hengxing; Martin, C. Derek; Zhou, Chenghu; Lim, Chang Ho

    2010-05-01

    Rockfalls have been significant geohazards along the Canadian Class 1 Railways (CN Rail and CP Rail) since their construction in the late 1800s. These rockfalls cause damage to infrastructure, interruption of business, and environmental impacts, and their occurrence varies both spatially and temporally. The proactive management of these rockfall hazards requires enabling technologies. This paper discusses a hazard assessment strategy for rockfalls along a section of a Canadian railway using LiDAR and spatial modeling. LiDAR provides accurate topographical information of the source area of rockfalls and along their paths. Spatial modeling was conducted using Rockfall Analyst, a three dimensional extension to GIS, to determine the characteristics of the rockfalls in terms of travel distance, velocity and energy. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results based on a high-resolution digital elevation model from a LiDAR dataset were compared with those based on a coarse digital elevation model. A comprehensive methodology for rockfall hazard assessment is proposed which takes into account the characteristics of source areas, the physical processes of rockfalls and the spatial attribution of their frequency and energy.

  12. Increasing the Efficiency of LiDAR Based Forest Inventories: A Novel Approach for Integrating Variable Radius Inventory Plots with LiDAR Data.

    NASA Astrophysics Data System (ADS)

    Falkowski, M. J.; Fekety, P.; Silva, C. A.; Hudak, A. T.

    2015-12-01

    LiDAR data are increasingly applied to support forest inventory and assessment across a variety of spatial scales. Typically this is achieved by integrating LiDAR data with forest inventory collected at fixed radius forest inventory plots. A well-designed forest inventory, one that covers the full range of structural and compositional variation across the forest of interest, is costly especially when collecting fixed radius plot data. Variable radius plots offer an alternative inventory protocol that is more efficient in terms of both time and money. However, integrating variable radius plot data with LiDAR data is problematic because the plots have unknown sizes that vary with variation in tree size. This leads to a spatial mismatch between LiDAR metrics (e.g., mean height, canopy cover, density, etc.) and plot data, which ultimately translates into errors in LiDAR derived forest inventory predictions. We propose and evaluate and novel approach for integrating variable radius plot data into a LiDAR based forest inventories in two different forest systems, one in the inland northwest and another in the northern lakes states of the USA. The novel approach calculates LiDAR metrics by weighting the point cloud proportional to return height, mimicking the way in which variable radius plot data weights tree measurements by tree size. This could increase inventory sampling efficiency, allowing for the collection of a greater number of inventory plots, and ultimately improve the performance of LiDAR based inventories.

  13. Immunogenicity and Protective Efficacy of the DAR-901 Booster Vaccine in a Murine Model of Tuberculosis

    PubMed Central

    Lahey, Timothy; Laddy, Dominick; Hill, Krystal; Schaeffer, Jacqueline; Hogg, Alison; Keeble, James; Dagg, Belinda; Ho, Mei Mei; Arbeit, Robert D.; von Reyn, C. Fordham

    2016-01-01

    Background The development of a novel tuberculosis vaccine is a leading global health priority. SRL172, an inactivated, whole-cell mycobacterial vaccine, was safe, immunogenic and reduced the incidence of culture-confirmed tuberculosis in a phase III trial in HIV-infected and BCG immunized adults in Tanzania. Here we describe the immunogenicity and protective efficacy of DAR-901, a booster vaccine against tuberculosis manufactured from the same seed strain using a new scalable method. Methods We evaluated IFN-γ responses by ELISpot and antibody responses by enzyme linked immunosorbent assay in C57BL/6 and BALB/c mice after three doses of DAR-901. In an aerosol challenge model, we evaluated the protective efficacy of the DAR-901 booster in C57BL/6 mice primed with BCG and boosted with two doses of DAR-901 at 4 dosage levels in comparison with homologous BCG boost. Results DAR-901 vaccination elicited IFN-γ responses to mycobacterial antigen preparations derived from both DAR-901 and Mycobacterium tuberculosis. DAR-901 immunization enhanced antibody responses to DAR-901 but not Mycobacterium tuberculosis lysate or purified protein derivative. Among animals primed with BCG, boosting with DAR-901 at 1 mg provided greater protection against aerosol challenge than a homologous BCG boost (lungs P = 0.036, spleen P = 0.028). Conclusions DAR-901 induces cellular and humoral immunity and boosts protection from M. tuberculosis compared to a homologous BCG boost. PMID:27997597

  14. Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories

    NASA Astrophysics Data System (ADS)

    Tao, Shengli; Wu, Fangfang; Guo, Qinghua; Wang, Yongcai; Li, Wenkai; Xue, Baolin; Hu, Xueyang; Li, Peng; Tian, Di; Li, Chao; Yao, Hui; Li, Yumei; Xu, Guangcai; Fang, Jingyun

    2015-12-01

    The rapid development of light detection and ranging (LiDAR) techniques is advancing ecological and forest research. During the last decade, numerous single tree segmentation techniques have been developed using airborne LiDAR data. However, accurate crown segmentation using terrestrial or mobile LiDAR data, which is an essential prerequisite for extracting branch level forest characteristics, is still challenging mainly because of the difficulties posed by tree crown intersection and irregular crown shape. In the current work, we developed a comparative shortest-path algorithm (CSP) for segmenting tree crowns scanned using terrestrial (T)-LiDAR and mobile LiDAR. The algorithm consists of two steps, namely trunk detection and subsequent crown segmentation, with the latter inspired by the well-proved metabolic ecology theory and the ecological fact that vascular plants tend to minimize the transferring distance to the root. We tested the algorithm on mobile-LiDAR-scanned roadside trees and T-LiDAR-scanned broadleaved and coniferous forests in China. Point-level quantitative assessments of the segmentation results showed that for mobile-LiDAR-scanned roadside trees, all the points were classified to their corresponding trees correctly, and for T-LiDAR-scanned broadleaved and coniferous forests, kappa coefficients ranging from 0.83 to 0.93 were obtained. We believe that our algorithm will make a contribution to solving the problem of crown segmentation in T-LiDAR scanned-forests, and might be of interest to researchers in LiDAR data processing and to forest ecologists. In addition, our research highlights the advantages of using ecological theories as guidelines for processing LiDAR data.

  15. Data management based on geocoding index and adaptive visualization for airborne LiDAR

    NASA Astrophysics Data System (ADS)

    Zhi, Xiaodong

    2008-10-01

    With more surveying practice and deeper application, data post-process for airborne LiDAR system has been extracted lots of attention in data accuracy, post-process, fusion, modeling, automation and visualization. However, post-process and flexible visualization were found to be the bottle-neck which limits the LiDAR data usage for industrial applications. The cause of above bottle-neck problems is great capacity for LiDAR system. Thus in article a geocoding index based multivariate data management and adaptive visualization will be studied for based on the feature of airborne LiDAR's data to improve automatization of post-process and surveying efficiency.

  16. Can we estimate precipitation rate during snowfall using a scanning terrestrial LiDAR?

    NASA Astrophysics Data System (ADS)

    LeWinter, A. L.; Bair, E. H.; Davis, R. E.; Finnegan, D. C.; Gutmann, E. D.; Dozier, J.

    2012-12-01

    Accurate snowfall measurements in windy areas have proven difficult. To examine a new approach, we have installed an automatic scanning terrestrial LiDAR at Mammoth Mountain, CA. With this LiDAR, we have demonstrated effective snow depth mapping over a small study area of several hundred m2. The LiDAR also produces dense point clouds by detecting falling and blowing hydrometeors during storms. Daily counts of airborne detections from the LiDAR show excellent agreement with automated and manual snow water equivalent measurements, suggesting that LiDAR observations have the potential to directly estimate precipitation rate. Thus, we suggest LiDAR scanners offer advantages over precipitation radars, which could lead to more accurate precipitation rate estimates. For instance, uncertainties in mass-diameter and mass-fall speed relationships used in precipitation radar, combined with low reflectivity of snow in the microwave spectrum, produce errors of up to 3X in snowfall rates measured by radar. Since snow has more backscatter in the near-infrared wavelengths used by LiDAR compared to the wavelengths used by radar, and the LiDAR detects individual hydrometeors, our approach has more potential for directly estimating precipitation rate. A key uncertainty is hydrometeor mass. At our study site, we have also installed a Multi Angle Snowflake Camera (MASC) to measure size, fallspeed, and mass of individual hydrometeors. By combining simultaneous MASC and LiDAR measurements, we can estimate precipitation density and rate.

  17. Weibull approximation of LiDAR waveforms for estimating the beam attenuation coefficient.

    PubMed

    Montes-Hugo, Martin A; Vuorenkoski, Anni K; Dalgleish, Fraser R; Ouyang, Bing

    2016-10-03

    Tank experiments were performed at different water turbidities to examine relationships between the beam attenuation coefficient (c) and Weibull shape parameters derived from LiDAR waveforms measured with the Fine Structure Underwater LiDAR (FSUIL). Optical inversions were made at 532 nm, within a c range of 0.045-1.52 m-1, and based on a LiDAR system having two field-of-view (15 and 75.7 mrad) and two linear polarizations. Consistently, the Weibull scale parameter or P2 showed the strongest covariation with c and was a more accurate proxy with respect to the LiDAR attenuation coefficient.

  18. Performance testing of LiDAR exploitation software

    NASA Astrophysics Data System (ADS)

    Varela-González, M.; González-Jorge, H.; Riveiro, B.; Arias, P.

    2013-04-01

    Mobile LiDAR systems are being used widely in recent years for many applications in the field of geoscience. One of most important limitations of this technology is the large computational requirements involved in data processing. Several software solutions for data processing are available in the market, but users are often unknown about the methodologies to verify their performance accurately. In this work a methodology for LiDAR software performance testing is presented and six different suites are studied: QT Modeler, AutoCAD Civil 3D, Mars 7, Fledermaus, Carlson and TopoDOT (all of them in x64). Results depict as QTModeler, TopoDOT and AutoCAD Civil 3D allow the loading of large datasets, while Fledermaus, Mars7 and Carlson do not achieve these powerful performance. AutoCAD Civil 3D needs large loading time in comparison with the most powerful softwares such as QTModeler and TopoDOT. Carlson suite depicts the poorest results among all the softwares under study, where point clouds larger than 5 million points cannot be loaded and loading time is very large in comparison with the other suites even for the smaller datasets. AutoCAD Civil 3D, Carlson and TopoDOT show more threads than other softwares like QTModeler, Mars7 and Fledermaus.

  19. Applying the Moment Distance Framework to LiDAR Waveforms

    NASA Astrophysics Data System (ADS)

    Salas, E. L.; Aguilar-Amuchastegui, N.; Henebry, G. M.

    2010-12-01

    In the past decade or so, there have only been limited approaches formulated for the analysis of waveform LiDAR data. We illustrate how the Moment Distance (MD) framework can characterize the shape of the LiDAR waveforms using simple, computationally fast, geometric operations. We assess the relationship of the MD metrics to some key waveform landmarks - such as locations of peaks, power of returns, and pseudo-heights - using LVIS datasets acquired over a tropical forest in La Selva, Costa Rica in 1998 and 2005. We also apply the MD framework to 2003 LVIS data from Howland Forest, Maine. We also explore the effects of noise on the MD Index (MDI). Our results reveal that the MDI can capture important dynamics in canopy structure. Movement in the location of the peaks is detected by shifts in the MDI. Because this new approach responds to waveform shape, it is more sensitive to changes of location of peak returns than to the power of the return. Results also suggest a positive relationship between the MDI and the canopy pseudo-height.

  20. Identifying Colluvial Slopes by Airborne LiDAR Analysis

    NASA Astrophysics Data System (ADS)

    Kasai, M.; Marutani, T.; Yoshida, H.

    2015-12-01

    Colluvial slopes are one of major sources of landslides. Identifying the locations of the slopes will help reduce the risk of disasters, by avoiding building infrastructure and properties nearby, or if they are already there, by applying appropriate counter measures before it suddenly moves. In this study, airborne LiDAR data was analyzed to find their geomorphic characteristics to use for extracting their locations. The study site was set in the suburb of Sapporo City, Hokkaido in Japan. The area is underlain by Andesite and Tuff and prone to landslides. Slope angle and surface roughness were calculated from 5 m resolution DEM. These filters were chosen because colluvial materials deposit at around the angle of repose and accumulation of loose materials was considered to form a peculiar surface texture differentiable from other slope types. Field survey conducted together suggested that colluvial slopes could be identified by the filters with a probability of 80 percent. Repeat LiDAR monitoring of the site by an unmanned helicopter indicated that those slopes detected as colluviums appeared to be moving at a slow rate. In comparison with a similar study from the crushed zone in Japan, the range of slope angle indicative of colluviums agreed with the Sapporo site, while the texture was rougher due to larger debris composing the slopes.

  1. The Daily Activity Report (DAR) a Novel Measure of Functional Outcome for Serious Mental Illness

    PubMed Central

    Velligan, Dawn I.; Mintz, Jim; Sierra, Cynthia; Martin, Mona L.; Fredrick, Megan; Maglinte, Gregory A.; Corey-Lisle, Patricia K.

    2016-01-01

    The assessment of real-world functional outcomes in clinical trials for medications targeting negative symptoms and cognitive impairment is extremely important. We tested the psychometric properties of the Daily Activity Report (DAR), a novel assessment of productive daily activity. We administered the DAR and additional assessments of functional outcome, functional capacity, cognition and symptomatology to 50 individuals with schizophrenia at 2 time points, 1 month apart and to 25 healthy controls. The DAR records a person’s daily activity for 7 consecutive days based upon phone calls made 3 times a day. A total score and scores in 3 domains; instrumental activities (ie, independent living), social and work or school related activities are generated for the DAR. Inter-item consistency was high 0.89–0.94 for each domain and 0.88 overall. Test–retest reliability across 1 month for the total DAR score was 0.67, P < .0001. The total DAR score as well as scores for social activity and nondomestic work/school differed significantly between control and patient participants (P < .0001). DAR domain scores were associated with negative symptoms and functional outcomes, but the primary score related to these measures was the work/school dimension of the DAR. DAR scores were only weakly and nonsignificantly related to positive symptoms. This study provides preliminary support for the reliability and validity of the DAR using interviewer administration. The development of a patient reported version of the DAR using smart phone technology with automatic scoring is the next step. PMID:26712856

  2. Nacelle LiDAR online wind field reconstruction applied to feedforward pitch control

    NASA Astrophysics Data System (ADS)

    GUILLEMIN, F.; DOMENICO, D. DI; NGUYEN, N.; SABIRON, G.; BOQUET, M.; GIRARD, N.; COUPIAC, O.

    2016-09-01

    This paper presents innovative filtering and reconstruction techniques of nacelle LiDAR data, and exploitation of obtained wind anticipation capabilities for wind turbine control strategy. The implemented algorithms are applied under industrial constraints, on a MAIA EOLIS wind turbine, equipped with a LEOSPHERE 5-beams pulsed LiDAR, during experimental campaigns of SMARTEOLE collaborative project.

  3. LiDAR, a great tool for archaeologists, but how do you interpret it?

    NASA Astrophysics Data System (ADS)

    Leisz, S.; Fisher, C.

    2013-05-01

    This paper focuses on the use of airborne LiDAR to identify archaeological features below forest canopies in Mesoamerica and the challenges faced in interpreting the data. To illustrate the issues involved in interpreting LiDAR point clouds and derived data sets for archaeological purposes, the case study of the use of airborne LiDAR at the archaeological site of Angamuco in West-Central Mexico is discussed. The case study details the reason LiDAR was collected, the challenges in interpreting it, methods and techniques that the authors are investigating to improve the interpretation of the LiDAR, and discoveries that have so far been made through the use of LiDAR. A key point discussed is the need to analyze the LiDAR point cloud in conjunction with products developed from the point cloud. Analyzing the various data sets jointly allows the user to better identify archaeological features of interest. New ways of utilizing hillshades of DEMs, such as creating 360 degree hillshades of the derived DEMs, are also presented. Last the authors discuss their experience in using object-based classification of the products derived from the LiDAR point cloud as an example of one possible technique for automating the delineation and classification of archaeological features.

  4. Remote sensing of Sonoran Desert vegetation structure and phenology with ground-based LiDAR

    USGS Publications Warehouse

    Sankey, Joel B.; Munson, Seth M.; Webb, Robert H.; Wallace, Cynthia S.A.; Duran, Cesar M.

    2015-01-01

    Long-term vegetation monitoring efforts have become increasingly important for understanding ecosystem response to global change. Many traditional methods for monitoring can be infrequent and limited in scope. Ground-based LiDAR is one remote sensing method that offers a clear advancement to monitor vegetation dynamics at high spatial and temporal resolution. We determined the effectiveness of LiDAR to detect intra-annual variability in vegetation structure at a long-term Sonoran Desert monitoring plot dominated by cacti, deciduous and evergreen shrubs. Monthly repeat LiDAR scans of perennial plant canopies over the course of one year had high precision. LiDAR measurements of canopy height and area were accurate with respect to total station survey measurements of individual plants. We found an increase in the number of LiDAR vegetation returns following the wet North American Monsoon season. This intra-annual variability in vegetation structure detected by LiDAR was attributable to a drought deciduous shrub Ambrosia deltoidea, whereas the evergreen shrub Larrea tridentata and cactus Opuntia engelmannii had low variability. Benefits of using LiDAR over traditional methods to census desert plants are more rapid, consistent, and cost-effective data acquisition in a high-resolution, 3-dimensional context. We conclude that repeat LiDAR measurements can be an effective method for documenting ecosystem response to desert climatology and drought over short time intervals and at detailed-local spatial scale.

  5. Wetland inundation mapping and change monitoring using landsat and airborne LiDAR data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper presents a new approach for mapping wetland inundation change using Landsat and LiDAR intensity data. In this approach, LiDAR data were used to derive highly accurate reference subpixel inundation percentage (SIP) maps at the 30-m resolution. The reference SIP maps were then used to est...

  6. Modelling Sensor and Target effects on LiDAR Waveforms

    NASA Astrophysics Data System (ADS)

    Rosette, J.; North, P. R.; Rubio, J.; Cook, B. D.; Suárez, J.

    2010-12-01

    The aim of this research is to explore the influence of sensor characteristics and interactions with vegetation and terrain properties on the estimation of vegetation parameters from LiDAR waveforms. This is carried out using waveform simulations produced by the FLIGHT radiative transfer model which is based on Monte Carlo simulation of photon transport (North, 1996; North et al., 2010). The opportunities for vegetation analysis that are offered by LiDAR modelling are also demonstrated by other authors e.g. Sun and Ranson, 2000; Ni-Meister et al., 2001. Simulations from the FLIGHT model were driven using reflectance and transmittance properties collected from the Howland Research Forest, Maine, USA in 2003 together with a tree list for a 200m x 150m area. This was generated using field measurements of location, species and diameter at breast height. Tree height and crown dimensions of individual trees were calculated using relationships established with a competition index determined for this site. Waveforms obtained by the Laser Vegetation Imaging Sensor (LVIS) were used as validation of simulations. This provided a base from which factors such as slope, laser incidence angle and pulse width could be varied. This has enabled the effect of instrument design and laser interactions with different surface characteristics to be tested. As such, waveform simulation is relevant for the development of future satellite LiDAR sensors, such as NASA’s forthcoming DESDynI mission (NASA, 2010), which aim to improve capabilities of vegetation parameter estimation. ACKNOWLEDGMENTS We would like to thank scientists at the Biospheric Sciences Branch of NASA Goddard Space Flight Center, in particular to Jon Ranson and Bryan Blair. This work forms part of research funded by the NASA DESDynI project and the UK Natural Environment Research Council (NE/F021437/1). REFERENCES NASA, 2010, DESDynI: Deformation, Ecosystem Structure and Dynamics of Ice. http

  7. Applicability of Aerial Green LiDAR to a Large River in the Western United States

    NASA Astrophysics Data System (ADS)

    Conner, J. T.; Welcker, C. W.; Cooper, C.; Faux, R.; Butler, M.; Nayegandhi, A.

    2013-12-01

    In October 2012, aerial green LiDAR data were collected in the Snake River (within Idaho and Oregon) to test this emerging technology in a large river with poor water clarity. Six study areas (total of 30 river miles spread out over 250 river miles) were chosen to represent a variety of depths, channel types, and surface conditions to test the accuracy, depth penetration, data density of aerial green LiDAR. These characteristics along with cost and speed of acquisition were compared to other bathymetric survey techniques including rod surveys (total station and RTK-GPS), single-beam sonar, and multibeam echosounder (MBES). The green LiDAR system typically measured returns from the riverbed through 1-2 meters of water, which was less than one Secchi depth. However, in areas with steep banks or aquatic macrophytes, LiDAR returns from the riverbed were less frequent or non-existent. In areas of good return density, depths measured from green LiDAR data corresponded well with previously collected data sets from traditional bathymetric survey techniques. In such areas, the green LiDAR point density was much higher than both rod and single beam sonar surveys, yet lower than MBES. The green LiDAR survey was also collected more efficiently than all other methods. In the Snake River, green LiDAR does not provide a method to map the entire riverbed as it only receives bottom returns in shallow water, typically at the channel margins. However, green LiDAR does provide survey data that is an excellent complement to MBES, which is more effective at surveying the deeper portions of the channel. In some cases, the green LiDAR was able to provide data in areas that the MBES could not, often due to issues with navigating the survey boat in shallow water. Even where both MBES and green LiDAR mapped the river bottom, green LiDAR often provides more accurate data through a better angle of incidence and less shadowing than the MBES survey. For one MBES survey in 2013, the green LiDAR

  8. Multipath estimation in urban environments from joint GNSS receivers and LiDAR sensors.

    PubMed

    Ali, Khurram; Chen, Xin; Dovis, Fabio; De Castro, David; Fernández, Antonio J

    2012-10-30

    In this paper, multipath error on Global Navigation Satellite System (GNSS) signals in urban environments is characterized with the help of Light Detection and Ranging (LiDAR) measurements. For this purpose, LiDAR equipment and Global Positioning System (GPS) receiver implementing a multipath estimating architecture were used to collect data in an urban environment. This paper demonstrates how GPS and LiDAR measurements can be jointly used to model the environment and obtain robust receivers. Multipath amplitude and delay are estimated by means of LiDAR feature extraction and multipath mitigation architecture. The results show the feasibility of integrating the information provided by LiDAR sensors and GNSS receivers for multipath mitigation.

  9. Multipath Estimation in Urban Environments from Joint GNSS Receivers and LiDAR Sensors

    PubMed Central

    Ali, Khurram; Chen, Xin; Dovis, Fabio; De Castro, David; Fernández, Antonio J.

    2012-01-01

    In this paper, multipath error on Global Navigation Satellite System (GNSS) signals in urban environments is characterized with the help of Light Detection and Ranging (LiDAR) measurements. For this purpose, LiDAR equipment and Global Positioning System (GPS) receiver implementing a multipath estimating architecture were used to collect data in an urban environment. This paper demonstrates how GPS and LiDAR measurements can be jointly used to model the environment and obtain robust receivers. Multipath amplitude and delay are estimated by means of LiDAR feature extraction and multipath mitigation architecture. The results show the feasibility of integrating the information provided by LiDAR sensors and GNSS receivers for multipath mitigation. PMID:23202177

  10. Using a multiwavelength LiDAR for improved remote sensing of natural waters.

    PubMed

    Gray, Deric J; Anderson, John; Nelson, Jean; Edwards, Jarrod

    2015-11-01

    This paper describes research to characterize the benefits of a multiwavelength oceanographic LiDAR for various water types. Field measurements were conducted to establish endmembers representative of both typical and extremely challenging natural conditions. Laboratory tests were performed using a prototype multiwavelength LiDAR in water tanks with optical conditions simulating both sediment-laden and biologically rich water types. LiDAR models were used to simulate the LiDAR signal from both field and laboratory experiments. Our measurements and models show that using a laser wavelength of 470-490 nm in the open ocean leads to an improvement factor of 1.50-1.75 compared to a 532 nm system. In more turbid areas using a laser wavelength of 560-580 nm leads to an improvement factor of 1.25. We conclude by demonstrating how using multiple LiDAR wavelengths can help detect and characterize constituents in the water column.

  11. Full waveform hyperspectral LiDAR for terrestrial laser scanning.

    PubMed

    Hakala, Teemu; Suomalainen, Juha; Kaasalainen, Sanna; Chen, Yuwei

    2012-03-26

    We present the design of a full waveform hyperspectral light detection and ranging (LiDAR) and the first demonstrations of its applications in remote sensing. The novel instrument produces a 3D point cloud with spectral backscattered reflectance data. This concept has a significant impact on remote sensing and other fields where target 3D detection and identification is crucial, such as civil engineering, cultural heritage, material processing, or geomorphological studies. As both the geometry and spectral information on the target are available from a single measurement, this technology will extend the scope of imaging spectroscopy into spectral 3D sensing. To demonstrate the potential of the instrument in the remote sensing of vegetation, 3D point clouds with backscattered reflectance and spectral indices are presented for a specimen of Norway spruce.

  12. Dynamic LiDAR-NDVI classification of fluvial landscape units

    NASA Astrophysics Data System (ADS)

    Ramírez-Núñez, Carolina; Parrot, Jean-François

    2015-04-01

    The lower basin of the Coatzacoalcos River is a wide floodplain in which, during the wet season, local and major flooding are distinguished. Both types of floods, intermittent and regional, are important in terms of resources; the regional flood sediments enrich the soils of the plains and intermittent floods allow obtaining aquatic resources for subsistence during the heatwave. In the floodplain different abandoned meanders and intermittent streams are quickly colonized by aquatic vegetation. However, from the 1990s, the Coatzacoalcos River floodplain has important topographic changes due to mining, road and bridges construction; erosion and sedimentation requires continuous parcel boundaries along with the increasing demand of channel reparation, embankments, levees and bridges associated to tributaries. NDVI data, LiDAR point cloud and various types of flood simulations taking into account the DTM are used to classify the dynamic landscape units. These units are associated to floods in relation with water resources, agriculture and livestock. In the study area, the first returns of the point cloud allow extracting vegetation strata. The last returns correspond to the bare earth surface, especially in this area with few human settlements. The surface that is not covered by trees or by aquatic vegetation, correspond to crops, pastures and bare soils. The classification is obtained by using the NDVI index coupled with vegetation strata and water bodies. The result shows that 47.96% of the area does not present active vegetation and it includes 31.53% of bare soils. Concerning the active vegetation, pastures, bushes and trees represent respectively 25.59%, 11.14% and 13.25%. The remaining 1.25% is distributed between water bodies with aquatic vegetation, trees and shrubs. Dynamic landscape units' classification represents a tool for monitoring water resources in a fluvial plain. This approach can be also applied to forest management, environmental services and

  13. Development of forest growth inputs from LiDAR

    NASA Astrophysics Data System (ADS)

    Tinkham, W. T.; Falkowski, M. J.; Smith, A. M.; Hudak, A. T.; Crookston, N. L.

    2012-12-01

    Investigating the potential impacts of climate change on forest dynamics is a critical area of science, especially given the vast amount of ecosystems services forests provide. Critical understanding of these impacts is lacking, most visibly, at regional to local scales where on-the-ground management activities are implemented. To plan ahead and mitigate the impacts of climate change, land managers need of decision support tools that can be used to evaluate the future impacts of climate change on forest conditions, so that sustainable management practices that enhance ecosystem resilience can be defensibly developed, evaluated, and implemented. However, to be applicable to both regional forest planning and local operational forest management decisions, approaches must be capable of simulating forest dynamics across large spatial extents (required for regional planning) while maintaining a high-level of spatial detail (required for operational management). Numerous studies have demonstrated that LiDAR remote sensing is an effective tool for accurately measuring forest structure at landscape scales, providing information with a level of detail appropriate for operational forest management. This study attempts to develop a system to spatially parameterize and supply critical initial conditions for Climate-FVS and other forest growth models across major ecoregions (in terms of forest structure and composition) in the Pacific Northwest (PNW) of the US, via an integration of airborne LiDAR, spatial measures of productivity, and local climate. Integrating these inputs into forest growth models would be a big step towards planning and optimizing landscape level alterations to forest structure and productivity from climate change.

  14. Urban agriculture and Anopheles habitats in Dar es Salaam, Tanzania.

    PubMed

    Dongus, Stefan; Nyika, Dickson; Kannady, Khadija; Mtasiwa, Deo; Mshinda, Hassan; Gosoniu, Laura; Drescher, Axel W; Fillinger, Ulrike; Tanner, Marcel; Killeen, Gerry F; Castro, Marcia C

    2009-05-01

    A cross-sectional survey of agricultural areas, combined with routinely monitored mosquito larval information, was conducted in urban Dar es Salaam, Tanzania, to investigate how agricultural and geographical features may influence the presence of Anopheles larvae. Data were integrated into a geographical information systems framework, and predictors of the presence of Anopheles larvae in farming areas were assessed using multivariate logistic regression with independent random effects. It was found that more than 5% of the study area (total size 16.8 km2) was used for farming in backyard gardens and larger open spaces. The proportion of habitats containing Anopheles larvae was 1.7 times higher in agricultural areas compared to other areas (95% confidence interval = 1.56-1.92). Significant geographic predictors of the presence of Anopheles larvae in gardens included location in lowland areas, proximity to river, and relatively impermeable soils. Agriculture-related predictors comprised specific seedbed types, mid-sized gardens, irrigation by wells, as well as cultivation of sugar cane or leafy vegetables. Negative predictors included small garden size, irrigation by tap water, rainfed production and cultivation of leguminous crops or fruit trees. Although there was an increased chance of finding Anopheles larvae in agricultural sites, it was found that breeding sites originated by urban agriculture account for less than a fifth of all breeding sites of malaria vectors in Dar es Salaam. It is suggested that strategies comprising an integrated malaria control effort in malaria-endemic African cities include participatory involvement of farmers by planting shade trees near larval habitats.

  15. Advances in animal ecology from 3D ecosystem mapping with LiDAR

    NASA Astrophysics Data System (ADS)

    Davies, A.; Asner, G. P.

    2015-12-01

    The advent and recent advances of Light Detection and Ranging (LiDAR) have enabled accurate measurement of 3D ecosystem structure. Although the use of LiDAR data is widespread in vegetation science, it has only recently (< 14 years) been applied to animal ecology. Despite such recent application, LiDAR has enabled new insights in the field and revealed the fundamental importance of 3D ecosystem structure for animals. We reviewed the studies to date that have used LiDAR in animal ecology, synthesising the insights gained. Structural heterogeneity is most conducive to increased animal richness and abundance, and increased complexity of vertical vegetation structure is more positively influential than traditionally measured canopy cover, which produces mixed results. However, different taxonomic groups interact with a variety of 3D canopy traits and some groups with 3D topography. LiDAR technology can be applied to animal ecology studies in a wide variety of environments to answer an impressive array of questions. Drawing on case studies from vastly different groups, termites and lions, we further demonstrate the applicability of LiDAR and highlight new understanding, ranging from habitat preference to predator-prey interactions, that would not have been possible from studies restricted to field based methods. We conclude with discussion of how future studies will benefit by using LiDAR to consider 3D habitat effects in a wider variety of ecosystems and with more taxa to develop a better understanding of animal dynamics.

  16. DArT Markers Effectively Target Gene Space in the Rye Genome

    PubMed Central

    Gawroński, Piotr; Pawełkowicz, Magdalena; Tofil, Katarzyna; Uszyński, Grzegorz; Sharifova, Saida; Ahluwalia, Shivaksh; Tyrka, Mirosław; Wędzony, Maria; Kilian, Andrzej; Bolibok-Brągoszewska, Hanna

    2016-01-01

    Large genome size and complexity hamper considerably the genomics research in relevant species. Rye (Secale cereale L.) has one of the largest genomes among cereal crops and repetitive sequences account for over 90% of its length. Diversity Arrays Technology is a high-throughput genotyping method, in which a preferential sampling of gene-rich regions is achieved through the use of methylation sensitive restriction enzymes. We obtained sequences of 6,177 rye DArT markers and following a redundancy analysis assembled them into 3,737 non-redundant sequences, which were then used in homology searches against five Pooideae sequence sets. In total 515 DArT sequences could be incorporated into publicly available rye genome zippers providing a starting point for the integration of DArT- and transcript-based genomics resources in rye. Using Blast2Go pipeline we attributed putative gene functions to 1101 (29.4%) of the non-redundant DArT marker sequences, including 132 sequences with putative disease resistance-related functions, which were found to be preferentially located in the 4RL and 6RL chromosomes. Comparative analysis based on the DArT sequences revealed obvious inconsistencies between two recently published high density consensus maps of rye. Furthermore we demonstrated that DArT marker sequences can be a source of SSR polymorphisms. Obtained data demonstrate that DArT markers effectively target gene space in the large, complex, and repetitive rye genome. Through the annotation of putative gene functions and the alignment of DArT sequences relative to reference genomes we obtained information, that will complement the results of the studies, where DArT genotyping was deployed, by simplifying the gene ontology and microcolinearity based identification of candidate genes. PMID:27833625

  17. Automatic registration of UAV-borne sequent images and LiDAR data

    NASA Astrophysics Data System (ADS)

    Yang, Bisheng; Chen, Chi

    2015-03-01

    Use of direct geo-referencing data leads to registration failure between sequent images and LiDAR data captured by mini-UAV platforms because of low-cost sensors. This paper therefore proposes a novel automatic registration method for sequent images and LiDAR data captured by mini-UAVs. First, the proposed method extracts building outlines from LiDAR data and images and estimates the exterior orientation parameters (EoPs) of the images with building objects in the LiDAR data coordinate framework based on corresponding corner points derived indirectly by using linear features. Second, the EoPs of the sequent images in the image coordinate framework are recovered using a structure from motion (SfM) technique, and the transformation matrices between the LiDAR coordinate and image coordinate frameworks are calculated using corresponding EoPs, resulting in a coarse registration between the images and the LiDAR data. Finally, 3D points are generated from sequent images by multi-view stereo (MVS) algorithms. Then the EoPs of the sequent images are further refined by registering the LiDAR data and the 3D points using an iterative closest-point (ICP) algorithm with the initial results from coarse registration, resulting in a fine registration between sequent images and LiDAR data. Experiments were performed to check the validity and effectiveness of the proposed method. The results show that the proposed method achieves high-precision robust co-registration of sequent images and LiDAR data captured by mini-UAVs.

  18. 4D Near Real-Time Environmental Monitoring Using Highly Temporal LiDAR

    NASA Astrophysics Data System (ADS)

    Höfle, Bernhard; Canli, Ekrem; Schmitz, Evelyn; Crommelinck, Sophie; Hoffmeister, Dirk; Glade, Thomas

    2016-04-01

    The last decade has witnessed extensive applications of 3D environmental monitoring with the LiDAR technology, also referred to as laser scanning. Although several automatic methods were developed to extract environmental parameters from LiDAR point clouds, only little research has focused on highly multitemporal near real-time LiDAR (4D-LiDAR) for environmental monitoring. Large potential of applying 4D-LiDAR is given for landscape objects with high and varying rates of change (e.g. plant growth) and also for phenomena with sudden unpredictable changes (e.g. geomorphological processes). In this presentation we will report on the most recent findings of the research projects 4DEMON (http://uni-heidelberg.de/4demon) and NoeSLIDE (https://geomorph.univie.ac.at/forschung/projekte/aktuell/noeslide/). The method development in both projects is based on two real-world use cases: i) Surface parameter derivation of agricultural crops (e.g. crop height) and ii) change detection of landslides. Both projects exploit the "full history" contained in the LiDAR point cloud time series. One crucial initial step of 4D-LiDAR analysis is the co-registration over time, 3D-georeferencing and time-dependent quality assessment of the LiDAR point cloud time series. Due to the high amount of datasets (e.g. one full LiDAR scan per day), the procedure needs to be performed fully automatically. Furthermore, the online near real-time 4D monitoring system requires to set triggers that can detect removal or moving of tie reflectors (used for co-registration) or the scanner itself. This guarantees long-term data acquisition with high quality. We will present results from a georeferencing experiment for 4D-LiDAR monitoring, which performs benchmarking of co-registration, 3D-georeferencing and also fully automatic detection of events (e.g. removal/moving of reflectors or scanner). Secondly, we will show our empirical findings of an ongoing permanent LiDAR observation of a landslide (Gresten

  19. LiDAR-derived snowpack data sets from mixed conifer forests across the Western United States

    NASA Astrophysics Data System (ADS)

    Harpold, A. A.; Guo, Q.; Molotch, N.; Brooks, P. D.; Bales, R.; Fernandez-Diaz, J. C.; Musselman, K. N.; Swetnam, T. L.; Kirchner, P.; Meadows, M. W.; Flanagan, J.; Lucas, R.

    2014-03-01

    Airborne-based Light Detection and Ranging (LiDAR) offers the potential to measure snow depth and vegetation structure at high spatial resolution over large extents and thereby increase our ability to quantify snow water resources. Here we present airborne LiDAR data products at four Critical Zone Observatories (CZO) in the Western United States: Jemez River Basin, NM, Boulder Creek Watershed, CO, Kings River Experimental Watershed, CA, and Wolverton Basin, CA. We make publicly available snow depth data products (1 m2 resolution) derived from LiDAR with an estimated accuracy of <30 cm compared to limited in situ snow depth observations.

  20. Compression strategies for LiDAR waveform cube

    NASA Astrophysics Data System (ADS)

    Jóźków, Grzegorz; Toth, Charles; Quirk, Mihaela; Grejner-Brzezinska, Dorota

    2015-01-01

    Full-waveform LiDAR data (FWD) provide a wealth of information about the shape and materials of the surveyed areas. Unlike discrete data that retains only a few strong returns, FWD generally keeps the whole signal, at all times, regardless of the signal intensity. Hence, FWD will have an increasingly well-deserved role in mapping and beyond, in the much desired classification in the raw data format. Full-waveform systems currently perform only the recording of the waveform data at the acquisition stage; the return extraction is mostly deferred to post-processing. Although the full waveform preserves most of the details of the real data, it presents a serious practical challenge for a wide use: much larger datasets compared to those from the classical discrete return systems. Atop the need for more storage space, the acquisition speed of the FWD may also limit the pulse rate on most systems that cannot store data fast enough, and thus, reduces the perceived system performance. This work introduces a waveform cube model to compress waveforms in selected subsets of the cube, aimed at achieving decreased storage while maintaining the maximum pulse rate of FWD systems. In our experiments, the waveform cube is compressed using classical methods for 2D imagery that are further tested to assess the feasibility of the proposed solution. The spatial distribution of airborne waveform data is irregular; however, the manner of the FWD acquisition allows the organization of the waveforms in a regular 3D structure similar to familiar multi-component imagery, as those of hyper-spectral cubes or 3D volumetric tomography scans. This study presents the performance analysis of several lossy compression methods applied to the LiDAR waveform cube, including JPEG-1, JPEG-2000, and PCA-based techniques. Wide ranges of tests performed on real airborne datasets have demonstrated the benefits of the JPEG-2000 Standard where high compression rates incur fairly small data degradation. In

  1. Frontiers in Using LiDAR to Analyze Urban Landscape Heterogeneity

    NASA Astrophysics Data System (ADS)

    Singh, Kunwar Krishna Veer

    Light Detection and Ranging (LiDAR) technology has facilitated extraordinary advances in our ability to remotely sense precise details of both built and natural environments. The inherent complexity of urban landscapes and the massive data volumes produced by LiDAR require unique methodological considerations for big data remote sensing over large metropolitan regions. The heterogeneous landscapes of the rapidly urbanizing Charlotte Metropolitan Region of North Carolina provided an ideal testing ground for developing methods of analysis for urban ecosystems over large regional extents, including: (1) fusion of LiDAR digital surface models (DSMs) with Landsat TM imagery to balance spatial resolution, data volume, and mapping accuracy of urban land covers, (2) comparison of LiDAR-derived metrics to fine grain optical imagery -- and their integration -- for detecting forest understory plant invaders, and (3) data reduction techniques for computationally efficient estimation of aboveground woody biomass in urban forests. In Chapter 1, I examined tradeoffs between potential gains in mapping accuracy and computational costs by integrating DSMs (structural and intensity) extracted from LiDAR with TM imagery and evaluating the degree to which TM, LiDAR, and LiDAR-TM fusion data discriminated land covers. I used Maximum Likelihood and Classification Tree algorithms to classify TM data, LiDAR data, and LiDAR-TM fusions. I assessed the relative contributions of LiDAR DSMs to map classification accuracy and identified an optimal spatial resolution of LiDAR DSMs for large area assessments of urban land cover. In Chapter 2, I analyzed combinations of datasets developed from categorized LiDAR-derived variables (Overstory, Understory, Topography, and Overall Vegetation Characteristics) and IKONOS imagery ( Optical) to detect and map the understory plant invader, Ligustrum sinense, using Random Forest (RF) and logistic regression (LR) algorithms, and I assessed the relative

  2. Homicide death in Dar es Salaam, Tanzania 2005.

    PubMed

    Outwater, Anne H; Campbell, Jacquelyn C; Mgaya, Edward; Abraham, Alison G; Kinabo, Linna; Kazaura, Method; Kub, Joan

    2008-12-01

    Violence disproportionately affects low- and middle-income countries. Deeper understanding is needed in areas where little research has occurred. The objectives of the study were to: (a) ascertain rate of homicide death; (b) describe the victims and circumstances surrounding their deaths in Dar es Salaam, Tanzania in 2005. This study was developed by adapting the WHO/CDC Injury Surveillance Guidelines (Holder et al., 2001). Data on 12 variables were collected on all homicide deaths. Descriptive statistics and hypothesis tests were done when appropriate. Age standardised, age-specific and cause-specific mortality rates are presented. The overall homicide rate was 12.57 (males and females respectively: 22.26 and 2.64). Homicide deaths were 93.4% male, mostly unemployed, with a mean age of 28.2 years. Most deaths occurred in urban areas. Mob violence was the cause of 57% of deaths. The risk of homicide death for males was greater than the world average, but for females it was less. Most homicides were committed by community members policing against thieves.

  3. Validation points generation for LiDAR-extracted hydrologic features

    NASA Astrophysics Data System (ADS)

    Felicen, M. M.; De La Cruz, R. M.; Olfindo, N. T.; Borlongan, N. J. B.; Ebreo, D. J. R.; Perez, A. M. C.

    2016-10-01

    This paper discusses a novel way of generating sampling points of hydrologic features, specifically streams, irrigation network and inland wetlands, that could provide a promising measure of accuracy using combinations of traditional statistical sampling methods. Traditional statistical sampling techniques such as simple random sampling, systematic sampling, stratified sampling and disproportionate random sampling were all designed to generate points in an area where all the cells are classified and subjected to actual field validation. However, these sampling techniques are not applicable when generating points along linear features. This paper presents the Weighted Disproportionate Stratified Systematic Random Sampling (WDSSRS), a tool that combines the systematic and disproportionate stratified random sampling methods in generating points for accuracy computation. This tool makes use of a map series boundary shapefile covering around 27 by 27 kilometers at a scale of 1:50000, and the LiDAR-extracted hydrologic features shapefiles (e.g. wetland polygons and linear features of stream and irrigation network). Using the map sheet shapefile, a 10 x 10 grid is generated, and grid cells with water and non-water features are tagged accordingly. Cells with water features are checked for the presence of intersecting linear features, and the intersections are given higher weights in the selection of validation points. The grid cells with non-intersecting linear features are then evaluated and the remaining points are generated randomly along these features. For grid cells with nonwater features, the sample points are generated randomly.

  4. Surface characteristics modeling and performance evaluation of urban building materials using LiDAR data.

    PubMed

    Li, Xiaolu; Liang, Yu

    2015-05-20

    Analysis of light detection and ranging (LiDAR) intensity data to extract surface features is of great interest in remote sensing research. One potential application of LiDAR intensity data is target classification. A new bidirectional reflectance distribution function (BRDF) model is derived for target characterization of rough and smooth surfaces. Based on the geometry of our coaxial full-waveform LiDAR system, the integration method is improved through coordinate transformation to establish the relationship between the BRDF model and intensity data of LiDAR. A series of experiments using typical urban building materials are implemented to validate the proposed BRDF model and integration method. The fitting results show that three parameters extracted from the proposed BRDF model can distinguish the urban building materials from perspectives of roughness, specular reflectance, and diffuse reflectance. A comprehensive analysis of these parameters will help characterize surface features in a physically rigorous manner.

  5. Automatic representation and reconstruction of DBM from LiDAR data using Recursive Minimum Bounding Rectangle

    NASA Astrophysics Data System (ADS)

    Kwak, Eunju; Habib, Ayman

    2014-07-01

    Three-dimensional building models are important for various applications, such as disaster management and urban planning. The development of laser scanning sensor technologies has resulted in many different approaches for efficient building model generation using LiDAR data. Despite this effort, generation of these models lacks economical and reliable techniques that fully exploit the advantage of LiDAR data. Therefore, this research aims to develop a framework for fully-automated building model generation by integrating data-driven and model-driven methods using LiDAR datasets. The building model generation starts by employing LiDAR data for building detection and approximate boundary determination. The generated building boundaries are then integrated into a model-based processing strategy because LiDAR derived planes show irregular boundaries due to the nature of LiDAR point acquisition. The focus of the research is generating models for the buildings with right-angled-corners, which can be described with a collection of rectangles under the assumption that the majority of the buildings in urban areas belong to this category. Therefore, by applying the Minimum Bounding Rectangle (MBR) algorithm recursively, the LiDAR boundaries are decomposed into sets of rectangles for further processing. At the same time, the quality of the MBRs is examined to verify that the buildings, from which the boundaries are generated, are buildings with right-angled-corners. The parameters that define the model primitives are adjusted through a model-based boundary fitting procedure using LiDAR boundaries. The level of details in the final Digital Building Model is based on the number of recursions during the MBR processing, which in turn are determined by the LiDAR point density. The model-based boundary fitting improves the quality of the generated boundaries and as seen in experimental results, the quality depends on the average LiDAR point spacing. This research thus develops an

  6. Detecting understory plant invasion in urban forests using LiDAR

    NASA Astrophysics Data System (ADS)

    Singh, Kunwar K.; Davis, Amy J.; Meentemeyer, Ross K.

    2015-06-01

    Light detection and ranging (LiDAR) data are increasingly used to measure structural characteristics of urban forests but are rarely used to detect the growing problem of exotic understory plant invaders. We explored the merits of using LiDAR-derived metrics alone and through integration with spectral data to detect the spatial distribution of the exotic understory plant Ligustrum sinense, a rapidly spreading invader in the urbanizing region of Charlotte, North Carolina, USA. We analyzed regional-scale L. sinense occurrence data collected over the course of three years with LiDAR-derived metrics of forest structure that were categorized into the following groups: overstory, understory, topography, and overall vegetation characteristics, and IKONOS spectral features - optical. Using random forest (RF) and logistic regression (LR) classifiers, we assessed the relative contributions of LiDAR and IKONOS derived variables to the detection of L. sinense. We compared the top performing models developed for a smaller, nested experimental extent using RF and LR classifiers, and used the best overall model to produce a predictive map of the spatial distribution of L. sinense across our country-wide study extent. RF classification of LiDAR-derived topography metrics produced the highest mapping accuracy estimates, outperforming IKONOS data by 17.5% and the integration of LiDAR and IKONOS data by 5.3%. The top performing model from the RF classifier produced the highest kappa of 64.8%, improving on the parsimonious LR model kappa by 31.1% with a moderate gain of 6.2% over the county extent model. Our results demonstrate the superiority of LiDAR-derived metrics over spectral data and fusion of LiDAR and spectral data for accurately mapping the spatial distribution of the forest understory invader L. sinense.

  7. Aboveground Biomass Modeling from Field and LiDAR Data in Brazilian Amazon Tropical Rain Forest

    NASA Astrophysics Data System (ADS)

    Silva, C. A.; Hudak, A. T.; Vierling, L. A.; Keller, M. M.; Klauberg Silva, C. K.

    2015-12-01

    Tropical forests are an important component of global carbon stocks, but tropical forest responses to climate change are not sufficiently studied or understood. Among remote sensing technologies, airborne LiDAR (Light Detection and Ranging) may be best suited for quantifying tropical forest carbon stocks. Our objective was to estimate aboveground biomass (AGB) using airborne LiDAR and field plot data in Brazilian tropical rain forest. Forest attributes such as tree density, diameter at breast height, and heights were measured at a combination of square plots and linear transects (n=82) distributed across six different geographic zones in the Amazon. Using previously published allometric equations, tree AGB was computed and then summed to calculate total AGB at each sample plot. LiDAR-derived canopy structure metrics were also computed at each sample plot, and random forest regression modelling was applied to predict AGB from selected LiDAR metrics. The LiDAR-derived AGB model was assessed using the random forest explained variation, adjusted coefficient of determination (Adj. R²), root mean square error (RMSE, both absolute and relative) and BIAS (both absolute and relative). Our findings showed that the 99th percentile of height and height skewness were the best LiDAR metrics for AGB prediction. The AGB model using these two best predictors explained 59.59% of AGB variation, with an Adj. R² of 0.92, RMSE of 33.37 Mg/ha (20.28%), and bias of -0.69 (-0.42%). This study showed that LiDAR canopy structure metrics can be used to predict AGC stocks in Tropical Forest with acceptable precision and accuracy. Therefore, we conclude that there is good potential to monitor carbon sequestration in Brazilian Tropical Rain Forest using airborne LiDAR data, large field plots, and the random forest algorithm.

  8. Change Detection from differential airborne LiDAR using a weighted Anisotropic Iterative Closest Point Algorithm

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Kusari, A.; Glennie, C. L.; Oskin, M. E.; Hinojosa-Corona, A.; Borsa, A. A.; Arrowsmith, R.

    2013-12-01

    Differential LiDAR (Light Detection and Ranging) from repeated surveys has recently emerged as an effective tool to measure three-dimensional (3D) change for applications such as quantifying slip and spatially distributed warping associated with earthquake ruptures, and examining the spatial distribution of beach erosion after hurricane impact. Currently, the primary method for determining 3D change is through the use of the iterative closest point (ICP) algorithm and its variants. However, all current studies using ICP have assumed that all LiDAR points in the compared point clouds have uniform accuracy. This assumption is simplistic given that the error for each LiDAR point is variable, and dependent upon highly variable factors such as target range, angle of incidence, and aircraft trajectory accuracy. Therefore, to rigorously determine spatial change, it would be ideal to model the random error for every LiDAR observation in the differential point cloud, and use these error estimates as apriori weights in the ICP algorithm. To test this approach, we implemented a rigorous LiDAR observation error propagation method to generate estimated random error for each point in a LiDAR point cloud, and then determine 3D displacements between two point clouds using an anistropic weighted ICP algorithm. The algorithm was evaluated by qualitatively and quantitatively comparing post earthquake slip estimates from the 2010 El Mayor-Cucapah Earthquake between a uniform weight and anistropically weighted ICP algorithm, using pre-event LiDAR collected in 2006 by Instituto Nacional de Estadística y Geografía (INEGI), and post-event LiDAR collected by The National Center for Airborne Laser Mapping (NCALM).

  9. Synergy of VSWIR and LiDAR for Ecosystem Structure, Biomass, and Canopy Diversity

    NASA Technical Reports Server (NTRS)

    Cook, Bruce D.; Asner, Gregory P.

    2010-01-01

    This slide presentation reviews the use of Visible ShortWave InfraRed (VSWIR) Imaging Spectrometer and LiDAR to study ecosystem structure, biomass and canopy diversity. It is shown that the biophysical data from LiDAR and biochemical information from hyperspectral remote sensing provides complementary data for: (1) describing spatial patterns of vegetation and biodiversity, (2) characterizing relationships between ecosystem form and function, and (3) detecting natural and human induced change that affects the biogeochemical cycles.

  10. Modeling marbled murrelet (Brachyramphus marmoratus) habitat using LiDAR-derived canopy data

    USGS Publications Warehouse

    Hagar, Joan C.; Eskelson, Bianca N.I.; Haggerty, Patricia K.; Nelson, S. Kim; Vesely, David G.

    2014-01-01

    LiDAR (Light Detection And Ranging) is an emerging remote-sensing tool that can provide fine-scale data describing vertical complexity of vegetation relevant to species that are responsive to forest structure. We used LiDAR data to estimate occupancy probability for the federally threatened marbled murrelet (Brachyramphus marmoratus) in the Oregon Coast Range of the United States. Our goal was to address the need identified in the Recovery Plan for a more accurate estimate of the availability of nesting habitat by developing occupancy maps based on refined measures of nest-strand structure. We used murrelet occupancy data collected by the Bureau of Land Management Coos Bay District, and canopy metrics calculated from discrete return airborne LiDAR data, to fit a logistic regression model predicting the probability of occupancy. Our final model for stand-level occupancy included distance to coast, and 5 LiDAR-derived variables describing canopy structure. With an area under the curve value (AUC) of 0.74, this model had acceptable discrimination and fair agreement (Cohen's κ = 0.24), especially considering that all sites in our sample were regarded by managers as potential habitat. The LiDAR model provided better discrimination between occupied and unoccupied sites than did a model using variables derived from Gradient Nearest Neighbor maps that were previously reported as important predictors of murrelet occupancy (AUC = 0.64, κ = 0.12). We also evaluated LiDAR metrics at 11 known murrelet nest sites. Two LiDAR-derived variables accurately discriminated nest sites from random sites (average AUC = 0.91). LiDAR provided a means of quantifying 3-dimensional canopy structure with variables that are ecologically relevant to murrelet nesting habitat, and have not been as accurately quantified by other mensuration methods.

  11. Urban Classification Techniques Using the Fusion of LiDAR and Spectral Data

    DTIC Science & Technology

    2012-09-01

    TECHNIQUES USING THE FUSION OF LIDAR AND SPECTRAL DATA by Justin E. Mesina September 2012 Thesis Advisor: Richard C. Olsen Second...TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE Urban Classification Techniques Using the Fusion of LiDAR and Spectral Data 5...the potential to be more accurate than a single sensor. This research fused airborne LiDAR data and WorldView-2 (WV-2) multispectral imagery (MSI) data

  12. Automated Aerial Refueling Position Estimation Using a Scanning LiDAR

    DTIC Science & Technology

    2012-03-22

    early analysis of algorithms that use LiDAR measurements [20]. Powell et al. [21] have shown LiDAR simulation with commercial ray tracing software is... tracing , where ray tracing is considered the true measurement. The speedup from using these two methods over the brute force methods is required to...as dark green arrows, are used to determine the green set of points. These points trace out the base of a cone created by all the slope lines

  13. Have I Been Here Before? A Method for Detecting Loop Closure With LiDAR

    DTIC Science & Technology

    2015-01-01

    JOHN G ROGERS III (1 HC, 1 PDF) JASON M GREGORY (1 HC, 1 PDF) STUART H YOUNG (1 PDF) 18 INTENTIONALLY LEFT BLANK. ...Have I Been Here Before? A Method for Detecting Loop Closure With LiDAR by John G Rogers III and Jason M Gregory ARL-TR-7165 January...TR-7165 January 2015 Have I Been Here Before? A Method for Detecting Loop Closure With LiDAR John G Rogers III and Jason M

  14. On the impact of a refined stochastic model for airborne LiDAR measurements

    NASA Astrophysics Data System (ADS)

    Bolkas, Dimitrios; Fotopoulos, Georgia; Glennie, Craig

    2016-09-01

    Accurate topographic information is critical for a number of applications in science and engineering. In recent years, airborne light detection and ranging (LiDAR) has become a standard tool for acquiring high quality topographic information. The assessment of airborne LiDAR derived DEMs is typically based on (i) independent ground control points and (ii) forward error propagation utilizing the LiDAR geo-referencing equation. The latter approach is dependent on the stochastic model information of the LiDAR observation components. In this paper, the well-known statistical tool of variance component estimation (VCE) is implemented for a dataset in Houston, Texas, in order to refine the initial stochastic information. Simulations demonstrate the impact of stochastic-model refinement for two practical applications, namely coastal inundation mapping and surface displacement estimation. Results highlight scenarios where erroneous stochastic information is detrimental. Furthermore, the refined stochastic information provides insights on the effect of each LiDAR measurement in the airborne LiDAR error budget. The latter is important for targeting future advancements in order to improve point cloud accuracy.

  15. Homicide of children in Dar es Salaam, Tanzania, 2005

    PubMed Central

    Outwater, Anne; Mgaya, Edward; Campbell, Jacquelyn C.; Becker, Stan; Kinabo, Linna; Menick, Daniel Mbassa

    2014-01-01

    Background Although data are sparse, it has been estimated that the highest rates of homicide death amongst children are in Africa. Little information is available on ages 0 -< 15 years. No reliable quantitative surveillance analysis of neonaticide (killed at less than one week) has been done. Methods A Violent Death Survey following WHO/CDC Guidelines was completed in Dar es Salaam region, Tanzania (DSM) (population 2.845 million) in 2005. Qualitative and quantitative data were gathered and analyzed using mixed methods techniques. Results The overall age adjusted rate of discarded and killed children in DSM was 2.05. The rate of neonaticide was 27.7 per 100,000) while the rate of homicide incidence for children > one day was Discussion The overall estimated homicide rate for Africa of children under age 15 was 4.53 per 100,000, whereas. The estimated global rate is 1.7 per 100,000 closer to DSM‘s rate. The results in DSM show that broad age groupings such as ” <1 year” or “0–4 years” or “0 – <15 years” may mask a high incidence of neonaticide and an otherwise low incidence of murdered children. The print media provided good in-depth coverage for a few cases but it is not known if the reported cases are representative. Conclusion Eighty percent of homicides of children in DSM are neonaticides. Since it is believed that the forces behind neonaticide are fundamentally different than homicides of older children, it is suggested that data of future surveys be parsed to include neonates, until the phenomenon is more clearly understood and addressed. Further understanding of the mother and father of the deceased is needed. Continued surveillance data collection is important to expand the sample size. PMID:22066333

  16. Quantifying Forest Carbon and Structure with Terrestrial LiDAR

    NASA Astrophysics Data System (ADS)

    Stovall, A. E.; Shugart, H. H., Jr.

    2014-12-01

    Current rising atmospheric CO2 concentrations are a major concern with significant global ramifications, however, of the carbon (C) fluxes that are known to occur on Earth, the terrestrial sink has the greatest amount of uncertainty. Improved monitoring of forest cover and change is required for reducing emissions from deforestation and forest degradation (REDD). We determine C storage from volume measurements with a high-precision Terrestrial Laser Scanner (TLS), substantially improving current standard ground validation techniques. This technology is utilized on several 30 m x 30 m plots in a Virginia temperate forest. Aboveground C is calculated on each of the study sites with commonly used allometric equations to offer a realistic comparison of field-based estimations to TLS-derived methods. The TLS and aerial LiDAR point cloud data are compared via the development of canopy height models at the plot scale. The novel method of point cloud voxelization is applied to our TLS data in order to produce detailed volumetric calculations in these complex forest ecosystems. Statistical output from the TLS data allows us to resolve and compare forest structure on scales from the individual plot to the entire forest landscape. The estimates produced from this research will be used to inform more widely available remote sensing datasets provided by NASA's Landsat satellites, significantly reducing the uncertainty of the terrestrial C cycle in temperate forests. Preliminary findings corroborate previous research, suggesting the potential for highly detailed monitoring of forest C storage as defined by the REDD initiative and analysis of complex ecosystem structure.

  17. Classification of LiDAR Data with Point Based Classification Methods

    NASA Astrophysics Data System (ADS)

    Yastikli, N.; Cetin, Z.

    2016-06-01

    LiDAR is one of the most effective systems for 3 dimensional (3D) data collection in wide areas. Nowadays, airborne LiDAR data is used frequently in various applications such as object extraction, 3D modelling, change detection and revision of maps with increasing point density and accuracy. The classification of the LiDAR points is the first step of LiDAR data processing chain and should be handled in proper way since the 3D city modelling, building extraction, DEM generation, etc. applications directly use the classified point clouds. The different classification methods can be seen in recent researches and most of researches work with the gridded LiDAR point cloud. In grid based data processing of the LiDAR data, the characteristic point loss in the LiDAR point cloud especially vegetation and buildings or losing height accuracy during the interpolation stage are inevitable. In this case, the possible solution is the use of the raw point cloud data for classification to avoid data and accuracy loss in gridding process. In this study, the point based classification possibilities of the LiDAR point cloud is investigated to obtain more accurate classes. The automatic point based approaches, which are based on hierarchical rules, have been proposed to achieve ground, building and vegetation classes using the raw LiDAR point cloud data. In proposed approaches, every single LiDAR point is analyzed according to their features such as height, multi-return, etc. then automatically assigned to the class which they belong to. The use of un-gridded point cloud in proposed point based classification process helped the determination of more realistic rule sets. The detailed parameter analyses have been performed to obtain the most appropriate parameters in the rule sets to achieve accurate classes. The hierarchical rule sets were created for proposed Approach 1 (using selected spatial-based and echo-based features) and Approach 2 (using only selected spatial-based features

  18. LiDAR Applications in Resource Geology and Benefits for Land Management

    NASA Astrophysics Data System (ADS)

    Mikulovsky, R. P.; De La Fuente, J. A.

    2013-12-01

    The US Forest Service (US Department of Agriculture) manages a broad range of geologic resources and hazards on National Forests and Grass Lands throughout the United States. Resources include rock and earth materials, groundwater, caves and paleontological resources, minerals, energy resources, and unique geologic areas. Hazards include landslides, floods, earthquakes, volcanic eruptions, and naturally hazardous materials (e.g., asbestos, radon). Forest Service Geologists who address these issues are Resource Geologists. They have been exploring LiDAR as a revolutionary tool to efficiently manage all of these hazards and resources. However, most LiDAR applications for management have focused on timber and fuels management, rather than landforms. This study shows the applications and preliminary results of using LiDAR for managing geologic resources and hazards on public lands. Applications shown include calculating sediment budgets, mapping and monitoring landslides, mapping and characterizing borrow pits or mines, determining landslide potential, mapping faults, and characterizing groundwater dependent ecosystems. LiDAR can be used to model potential locations of groundwater dependent ecosystems with threatened or endangered plant species such as Howellia aquatilis. This difficult to locate species typically exists on the Mendocino National Forest within sag ponds on landslide benches. LiDAR metrics of known sites are used to model potential habitat. Thus LiDAR can link the disciplines of geology, hydrology, botany, archaeology and others for enhanced land management. As LiDAR acquisition costs decrease and it becomes more accessible, land management organizations will find a wealth of applications with potential far-reaching benefits for managing geologic resources and hazards.

  19. Effects of LiDAR point density and landscape context on estimates of urban forest biomass

    NASA Astrophysics Data System (ADS)

    Singh, Kunwar K.; Chen, Gang; McCarter, James B.; Meentemeyer, Ross K.

    2015-03-01

    Light Detection and Ranging (LiDAR) data is being increasingly used as an effective alternative to conventional optical remote sensing to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and improved data accuracies accompanied by challenges for procuring and processing voluminous LiDAR data for large-area assessments. Reducing point density lowers data acquisition costs and overcomes computational challenges for large-area forest assessments. However, how does lower point density impact the accuracy of biomass estimation in forests containing a great level of anthropogenic disturbance? We evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing region of Charlotte, North Carolina, USA. We used multiple linear regression to establish a statistical relationship between field-measured biomass and predictor variables derived from LiDAR data with varying densities. We compared the estimation accuracies between a general Urban Forest type and three Forest Type models (evergreen, deciduous, and mixed) and quantified the degree to which landscape context influenced biomass estimation. The explained biomass variance of the Urban Forest model, using adjusted R2, was consistent across the reduced point densities, with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models at the representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, highlighting a distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional

  20. Elements of systemic sensitivity and propagated uncertainty in LiDAR-based forest attribute maps (Invited)

    NASA Astrophysics Data System (ADS)

    Hopkinson, C.; Chasmer, L.; Kljun, N.; van Gorsel, E.

    2013-12-01

    The application of airborne LiDAR to vegetation and forest attribute extraction and modeling is now common place. Direct estimates of tree-, plot- or stand-level height and canopy cover are frequently made as pre-cursors to more complex and indirect attribute derivations such as leaf area, biomass, basal area, fuel, even species. Frequently, the faith placed in LiDAR to produce these spatial variables appears so complete that raw data properties or the methods employed in the modeling of direct or indirect attributes are glossed over. The assumption being that if basic variables and derivatives can be easily predicted across a few studies, then it follows this will always be the case. Few studies address explicitly the range of sensitivity in direct and indirect forest attribute estimations: a) derived from LiDAR data of differing fundamental acquisition or point cloud properties; or b) produced using different data extraction, filtering or raster interpolation approaches. The paper will illustrate some of the critical acquisition and point cloud attributes (such as pulse power, flight line configuration, timing and point density) that strongly influence mapped and modeled forest attributes at a range of case study sites in North America and Australia. Further, the influence of multiple seemingly defensible canopy height model generation criteria will be compared to illustrate the high sensitivity in even the most basic of LiDAR-based forest attribute maps. We conclude that not all LiDAR are created equal and that both raw data properties and all data manipulation steps must be communicated when utilising such data. Finally, we believe that as with more standard products like LiDAR point cloud formats and digital terrain models (DTMs), an international committee is needed to provide guidance on airborne LiDAR vegetation products so that uncertainties can be mitigated when data are shared or compared across sites and through time.

  1. Estimation of effective plant area index for South Korean forests using LiDAR system.

    PubMed

    Kwak, Doo-Ahn; Lee, Woo-Kyun; Kafatos, Menas; Son, Yowhan; Cho, Hyun-Kook; Lee, Seung-Ho

    2010-07-01

    Light Detection and Ranging (LiDAR) systems can be used to estimate both vertical and horizontal forest structure. Woody components, the leaves of trees and the understory can be described with high precision, using geo-registered 3D-points. Based on this concept, the Effective Plant Area Indices (PAI(e)) for areas of Korean Pine (Pinus koraiensis), Japanese Larch (Larix leptolepis) and Oak (Quercus spp.) were estimated by calculating the ratio of intercepted and incident LIDAR laser rays for the canopies of the three forest types. Initially, the canopy gap fraction (G ( LiDAR )) was generated by extracting the LiDAR data reflected from the canopy surface, or inner canopy area, using k-means statistics. The LiDAR-derived PAI(e) was then estimated by using G ( LIDAR ) with the Beer-Lambert law. A comparison of the LiDAR-derived and field-derived PAI(e) revealed the coefficients of determination for Korean Pine, Japanese Larch and Oak to be 0.82, 0.64 and 0.59, respectively. These differences between field-based and LIDAR-based PAI(e) for the different forest types were attributed to the amount of leaves and branches in the forest stands. The absence of leaves, in the case of both Larch and Oak, meant that the LiDAR pulses were only reflected from branches. The probability that the LiDAR pulses are reflected from bare branches is low as compared to the reflection from branches with a high leaf density. This is because the size of the branch is smaller than the resolution across and along the 1 meter LIDAR laser track. Therefore, a better predictive accuracy would be expected for the model if the study would be repeated in late spring when the shoots and leaves of the deciduous trees begin to appear.

  2. Estimating FPAR of maize canopy using airborne discrete-return LiDAR data.

    PubMed

    Luo, Shezhou; Wang, Cheng; Xi, Xiaohuan; Pan, Feifei

    2014-03-10

    The fraction of absorbed photosynthetically active radiation (FPAR) is a key parameter for ecosystem modeling, crop growth monitoring and yield prediction. Ground-based FPAR measurements are time consuming and labor intensive. Remote sensing provides an alternative method to obtain repeated, rapid and inexpensive estimates of FPAR over large areas. LiDAR is an active remote sensing technology and can be used to extract accurate canopy structure parameters. A method to estimating FPAR of maize from airborne discrete-return LiDAR data was developed and tested in this study. The raw LiDAR point clouds were processed to separate ground returns from vegetation returns using a filter method over a maize field in the Heihe River Basin, northwest China. The fractional cover (fCover) of maize canopy was computed using the ratio of canopy return counts or intensity sums to the total of returns or intensities. FPAR estimation models were established based on linear regression analysis between the LiDAR-derived fCover and the field-measured FPAR (R(2) = 0.90, RMSE = 0.032, p < 0.001). The reliability of the constructed regression model was assessed using the leave-one-out cross-validation procedure and results show that the regression model is not overfitting the data and has a good generalization capability. Finally, 15 independent field-measured FPARs were used to evaluate accuracy of the LiDAR-predicted FPARs and results show that the LiDAR-predicted FPAR has a high accuracy (R(2) = 0.89, RMSE = 0.034). In summary, this study suggests that the airborne discrete-return LiDAR data could be adopted to accurately estimate FPAR of maize.

  3. Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale.

    PubMed

    Vierling, Lee A; Vierling, Kerri T; Adam, Patrick; Hudak, Andrew T

    2013-01-01

    Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2

  4. Challenges in diagnosing paediatric malaria in Dar es Salaam, Tanzania

    PubMed Central

    2013-01-01

    Background Malaria is a major cause of paediatric morbidity and mortality. As no clinical features clearly differentiate malaria from other febrile illnesses, and malaria diagnosis is challenged by often lacking laboratory equipment and expertise, overdiagnosis and overtreatment is common. Methods Children admitted with fever at the general paediatric wards at Muhimbili National Hospital (MNH), Dar es Salaam, Tanzania from January to June 2009 were recruited consecutively and prospectively. Demographic and clinical features were registered. Routine thick blood smear microscopy at MNH was compared to results of subsequent thin blood smear microscopy, and rapid diagnostics tests (RDTs). Genus-specific PCR of Plasmodium mitochondrial DNA was performed on DNA extracted from whole blood and species-specific PCR was done on positive samples. Results Among 304 included children, 62.6% had received anti-malarials during the last four weeks prior to admission and 65.1% during the hospital stay. Routine thick blood smears, research blood smears, PCR and RDT detected malaria in 13.2%, 6.6%, 25.0% and 13.5%, respectively. Positive routine microscopy was confirmed in only 43% (17/40), 45% (18/40) and 53% (21/40), by research microscopy, RDTs and PCR, respectively. Eighteen percent (56/304) had positive PCR but negative research microscopy. Reported low parasitaemia on routine microscopy was associated with negative research blood slide and PCR. RDT-positive cases were associated with signs of severe malaria. Palmar pallor, low haemoglobin and low platelet count were significantly associated with positive PCR, research microscopy and RDT. Conclusions The true morbidity attributable to malaria in the study population remains uncertain due to the discrepancies in results among the diagnostic methods. The current routine microscopy appears to result in overdiagnosis of malaria and, consequently, overuse of anti-malarials. Conversely, children with a false positive malaria diagnosis

  5. Demonstration of LiDAR and Orthophotography for Wide Area Assessment at Pueblo Precision Bombing Range #2, Colorado

    DTIC Science & Technology

    2008-01-01

    for classification of LiDAR points into vegetation, ground, and “other,” creating bare earth and surface model digital terrain models ( DTM ...for rectification of the photography to the DTM . 2.1.6 Data Analysis Once processed, the LiDAR /orthophotography datasets are analyzed to...creation: Triangulation results were loaded into ortho-processing software, along with a LiDAR -derived DTM and aerial photography. Aerial photographs

  6. Spinning a laser web: predicting spider distributions using LiDAR.

    PubMed

    Vierling, K T; Bässler, C; Brandl, R; Vierling, L A; Weiss, I; Müller, J

    2011-03-01

    LiDAR remote sensing has been used to examine relationships between vertebrate diversity and environmental characteristics, but its application to invertebrates has been limited. Our objectives were to determine whether LiDAR-derived variables could be used to accurately describe single-species distributions and community characteristics of spiders in remote forested and mountainous terrain. We collected over 5300 spiders across multiple transects in the Bavarian National Park (Germany) using pitfall traps. We examined spider community characteristics (species richness, the Shannon index, the Simpson index, community composition, mean body size, and abundance) and single-species distribution and abundance with LiDAR variables and ground-based measurements. We used the R2 and partial R2 provided by variance partitioning to evaluate the predictive power of LiDAR-derived variables compared to ground measurements for each of the community characteristics. The total adjusted R2 for species richness, the Shannon index, community species composition, and body size had a range of 25-57%. LiDAR variables and ground measurements both contributed >80% to the total predictive power. For species composition, the explained variance was approximately 32%, which was significantly greater than expected by chance. The predictive power of LiDAR-derived variables was comparable or superior to that of the ground-based variables for examinations of single-species distributions, and it explained up to 55% of the variance. The predictability of species distributions was higher for species that had strong associations with shade in open-forest habitats, and this niche position has been well documented across the European continent for spider species. The similar statistical performance between LiDAR and ground-based measures at our field sites indicated that deriving spider community and species distribution information using LiDAR data can provide not only high predictive power at

  7. Development of LiDAR measurements for the German offshore test site

    NASA Astrophysics Data System (ADS)

    Rettenmeier, A.; Kühn, M.; Wächter, M.; Rahm, S.; Mellinghoff, H.; Siegmeier, B.; Reeder, L.

    2008-05-01

    The paper introduces the content of the recently started joint research project 'Development of LiDAR measurements for the German Offshore Test Site' which has the objective to support other research projects at the German offshore test site 'alpha ventus'. The project has started before the erection of the offshore wind farm and one aim is to give recommendations concerning LiDAR technology useable for offshore measurement campaigns and data analysis. The work is organized in four work packages. The work package LiDAR technology deals with the specification, acquisition and calibration of a commercial LiDAR system for the measurement campaigns. Power curve measurements are dedicated to power curve assessment with ground-based LiDAR using standard statistical methods. Additionally, it deals with the development of new methods for the measurement of non-steady short-term power curves. Wind field research aims at the development of wake loading simulation methods of wind turbines and the exploration of loading control strategies and nacelle-based wind field measurement techniques. Finally, dissemination of results to the industry takes place in work package Technology transfer.

  8. Octree-based segmentation for terrestrial LiDAR point cloud data in industrial applications

    NASA Astrophysics Data System (ADS)

    Su, Yun-Ting; Bethel, James; Hu, Shuowen

    2016-03-01

    Automated and efficient algorithms to perform segmentation of terrestrial LiDAR data is critical for exploitation of 3D point clouds, where the ultimate goal is CAD modeling of the segmented data. In this work, a novel segmentation technique is proposed, starting with octree decomposition to recursively divide the scene into octants or voxels, followed by a novel split and merge framework that uses graph theory and a series of connectivity analyses to intelligently merge components into larger connected components. The connectivity analysis, based on a combination of proximity, orientation, and curvature connectivity criteria, is designed for the segmentation of pipes, vessels, and walls from terrestrial LiDAR data of piping systems at industrial sites, such as oil refineries, chemical plants, and steel mills. The proposed segmentation method is exercised on two terrestrial LiDAR datasets of a steel mill and a chemical plant, demonstrating its ability to correctly reassemble and segregate features of interest.

  9. The role of terrestrial 3D LiDAR scan in bridge health monitoring

    NASA Astrophysics Data System (ADS)

    Liu, Wanqiu; Chen, Shen-En; Sajedi, Allen; Hauser, Edd

    2010-04-01

    This paper addresses the potential applications of terrestrial 3D LiDAR scanning technologies for bridge monitoring. High resolution ground-based optical-photonic images from LiDAR scans can provide detailed geometric information about a bridge. Applications of simple algorithms can retrieve damage information from the geometric point cloud data, which can be correlated to possible damage quantification including concrete mass loss due to vehicle collisions, large permanent steel deformations, and surface erosions. However, any proposed damage detection technologies should provide information that is relevant and useful to bridge managers for their decision making process. This paper summaries bridge issues that can be detected from the 3D LiDAR technologies, establishes the general approach in using 3D point clouds for damage evaluation and suggests possible bridge state ratings that can be used as supplements to existing bridge management systems (BMS).

  10. The IsoDAR high intensity H2+ transport and injection tests

    NASA Astrophysics Data System (ADS)

    Alonso, J.; Axani, S.; Calabretta, L.; Campo, D.; Celona, L.; Conrad, J. M.; Day, A.; Castro, G.; Labrecque, F.; Winklehner, D.

    2015-10-01

    This technical report reviews the tests performed at the Best Cyclotron Systems, Inc. facility in regards to developing a cost effective ion source, beam line transport system, and acceleration system capable of high H2+ current output for the IsoDAR (Isotope Decay At Rest) experiment. We begin by outlining the requirements for the IsoDAR experiment then provide overviews of the Versatile Ion Source (VIS), Low Energy Beam Transport (LEBT) system, spiral inflector, and cyclotron. The experimental measurements are then discussed and the results are compared with a thorough set of simulation studies. Of particular importance we note that the VIS proved to be a reliable ion source capable of generating a large amount of H2+ current. The results suggest that with further upgrades, the VIS could potentially be a suitable candidate for IsoDAR. The conclusion outlines the key results from our tests and introduces the forthcoming work this technical report has motivated.

  11. [Analysis of an Air Pollution Process Using LiDAR in Nanjing, Spring of 2014].

    PubMed

    Bao, Qing; He, Jun-liang; Zha, Yong; Cheng, Feng; Li, Qian-nan

    2015-04-01

    Based on environmental monitoring data, meteorological data and the results of numerical simulation, a typical air pollution process in Nanjing, from 26th May to 1st June, 2014 was deeply analyzed combining aerosol extinction coefficient derived from LiDAR system. Experimental results showed that the entire pollution process was affected by both local pollution and exogenous inputs including dust and smoke. Meteorological factors played a significant role in the generation and elimination of pollutants. Low pressure and temperature inversion also hindered the diffusion of pollutants, while strong rainfall terminated the pollution process. During the pollution, the height of atmospheric boundary layer was lower than normal situation and changed little during the pollution period, which provided a poor diffusion condition for pollutants. LiDAR could accurately detect aerosol vertical structure which was able to capture the temporal and spatial variation of pollutant distributions. Therefore, LiDAR can be of great significance for the atmospheric pollution monitoring.

  12. LiDAR remote sensing observations for forest assessment and recovery responses following disturbance

    NASA Astrophysics Data System (ADS)

    Rosette, J.; Suárez, J.; Fonweben, J.; North, P.

    2013-12-01

    LiDAR data covering 400 km2 in the Cowal and Trossacs Forest District, Scotland, U.K., were used to provide a low cost solution to update the database of public forests and to produce multi-scale cartographic products for supporting management decisions in the event of forest disturbance such as infestation or wind damage. All parameter estimates were directly obtained from the LiDAR data without the necessity of field calibration. This was achieved using a hybrid approach integrating current stand models for Sitka spruce (Picea sitchensis bong. Carr) and LiDAR analysis. More conventional field methods offer percentage sampling, permitting only a proportion of stands to be surveyed each year and aiming to represent stand-level conditions. The use of LiDAR is advantageous in allowing a complete observation-based assessment throughout the forest and greatly-improved spatial representation of important forest parameters. Time-series analysis was performed using LiDAR data collected in the past 10 years. This analysis allowed us to establish growth trajectories in the forest stands, automatically discriminating areas of growth, those whose growth had been affected by disease and the occurrence of windthrow gaps. The results were compared to the cartography produced by the Forest District after a severe wind storm that affected the area in 2012. This analysis showed the ability of LiDAR to create a more precise location and extent of catastrophic damage and windthrow gaps. In addition, once windthrow has occurred, progression of further damage in existing canopy gaps can be observed. This approach additionally allows the impact of disease on forest growth and subsequent recovery response to be monitored.

  13. Estimating stem volume and biomass of Pinus koraiensis using LiDAR data.

    PubMed

    Kwak, Doo-Ahn; Lee, Woo-Kyun; Cho, Hyun-Kook; Lee, Seung-Ho; Son, Yowhan; Kafatos, Menas; Kim, So-Ra

    2010-07-01

    The objective of this study was to estimate the stem volume and biomass of individual trees using the crown geometric volume (CGV), which was extracted from small-footprint light detection and ranging (LiDAR) data. Attempts were made to analyze the stem volume and biomass of Korean Pine stands (Pinus koraiensis Sieb. et Zucc.) for three classes of tree density: low (240 N/ha), medium (370 N/ha), and high (1,340 N/ha). To delineate individual trees, extended maxima transformation and watershed segmentation of image processing methods were applied, as in one of our previous studies. As the next step, the crown base height (CBH) of individual trees has to be determined; information for this was found in the LiDAR point cloud data using k-means clustering. The LiDAR-derived CGV and stem volume can be estimated on the basis of the proportional relationship between the CGV and stem volume. As a result, low tree-density plots had the best performance for LiDAR-derived CBH, CGV, and stem volume (R (2) = 0.67, 0.57, and 0.68, respectively) and accuracy was lowest for high tree-density plots (R (2) = 0.48, 0.36, and 0.44, respectively). In the case of medium tree-density plots accuracy was R (2) = 0.51, 0.52, and 0.62, respectively. The LiDAR-derived stem biomass can be predicted from the stem volume using the wood basic density of coniferous trees (0.48 g/cm(3)), and the LiDAR-derived above-ground biomass can then be estimated from the stem volume using the biomass conversion and expansion factors (BCEF, 1.29) proposed by the Korea Forest Research Institute (KFRI).

  14. Reconstruction and analysis of a deciduous sapling using digital photographs or terrestrial-LiDAR technology

    PubMed Central

    Delagrange, Sylvain; Rochon, Pascal

    2011-01-01

    Background and Aims To meet the increasing need for rapid and non-destructive extraction of canopy traits, two methods were used and compared with regard to their accuracy in estimatating 2-D and 3-D parameters of a hybrid poplar sapling. Methods The first method consisted of the analysis of high definition photographs in Tree Analyser (TA) software (PIAF-INRA/Kasetsart University). TA allowed the extraction of individual traits using a space carving approach. The second method utilized 3-D point clouds acquired from terrestrial light detection and ranging (T-LiDAR) scans. T-LiDAR scans were performed on trees without leaves to reconstruct the lignified structure of the sapling. From this skeleton, foliage was added using simple modelling rules extrapolated from field measurements. Validation of the estimated dimension and the accuracy of reconstruction was then achieved by comparison with an empirical data set. Key Results TA was found to be slightly less precise than T-LiDAR for estimating tree height, canopy height and mean canopy diameter, but for 2-D traits both methods were, however, fully satisfactory. TA tended to over-estimate total leaf area (error up to 50 %), but better estimates were obtained by reducing the size of the voxels used for calculations. In contrast, T-LiDAR estimated total leaf area with an error of <6 %. Finally, both methods led to an over-estimation of canopy volume. With respect to this trait, T-LiDAR (14·5 % deviation) greatly surpassed the accuracy of TA (up to 50 % deviation), even if the voxels used were reduced in size. Conclusions Taking into account their magnitude of data acquisition and analysis and their accuracy in trait estimations, both methods showed contrasting potential future uses. Specifically, T-LiDAR is a particularly promising tool for investigating the development of large perennial plants, by itself or in association with plant modelling. PMID:21515607

  15. Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data

    SciTech Connect

    Danny L. Anderson

    2012-05-01

    Detailed hydrographic feature extraction from high-resolution light detection and ranging (LiDAR) data is investigated. Methods for quantitatively evaluating and comparing such extractions are presented, including the use of sinuosity and longitudinal root-mean-square-error (LRMSE). These metrics are then used to quantitatively compare stream networks in two studies. The first study examines the effect of raster cell size on watershed boundaries and stream networks delineated from LiDAR-derived digital elevation models (DEMs). The study confirmed that, with the greatly increased resolution of LiDAR data, smaller cell sizes generally yielded better stream network delineations, based on sinuosity and LRMSE. The second study demonstrates a new method of delineating a stream directly from LiDAR point clouds, without the intermediate step of deriving a DEM. Direct use of LiDAR point clouds could improve efficiency and accuracy of hydrographic feature extractions. The direct delineation method developed herein and termed “mDn”, is an extension of the D8 method that has been used for several decades with gridded raster data. The method divides the region around a starting point into sectors, using the LiDAR data points within each sector to determine an average slope, and selecting the sector with the greatest downward slope to determine the direction of flow. An mDn delineation was compared with a traditional grid-based delineation, using TauDEM, and other readily available, common stream data sets. Although, the TauDEM delineation yielded a sinuosity that more closely matches the reference, the mDn delineation yielded a sinuosity that was higher than either the TauDEM method or the existing published stream delineations. Furthermore, stream delineation using the mDn method yielded the smallest LRMSE.

  16. Parallel algorithm for linear feature detection from airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Mareboyana, Manohar; Chi, Paul

    2006-05-01

    Linear features from airport images correspond to runways, taxiways and roads. Detecting runways helps pilots to focus on runway incursions in poor visibility conditions. In this work, we attempt to detect linear features from LiDAR swath in near real time using parallel implementation on G5-based apple cluster called Xseed. Data from LiDAR swath is converted into a uniform grid with nearest neighbor interpolation. The edges and gradient directions are computed using standard edge detection algorithms such as Canny's detector. Edge linking and detecting straight-line features are described. Preliminary results on Reno, Nevada airport data are included.

  17. Visualization of High-Resolution LiDAR Topography in Google Earth

    NASA Astrophysics Data System (ADS)

    Crosby, C. J.; Nandigam, V.; Arrowsmith, R.; Blair, J. L.

    2009-12-01

    The growing availability of high-resolution LiDAR (Light Detection And Ranging) topographic data has proven to be revolutionary for Earth science research. These data allow scientists to study the processes acting on the Earth’s surfaces at resolutions not previously possible yet essential for their appropriate representation. In addition to their utility for research, the data have also been recognized as powerful tools for communicating earth science concepts for education and outreach purposes. Unfortunately, the massive volume of data produced by LiDAR mapping technology can be a barrier to their use. To facilitate access to these powerful data for research and educational purposes, we have been exploring the use of Keyhole Markup Language (KML) and Google Earth to deliver LiDAR-derived visualizations. The OpenTopography Portal (http://www.opentopography.org/) is a National Science Foundation-funded facility designed to provide access to Earth science-oriented LiDAR data. OpenTopography hosts a growing collection of LiDAR data for a variety of geologic domains, including many of the active faults in the western United States. We have found that the wide spectrum of LiDAR users have variable scientific applications, computing resources, and technical experience and thus require a data distribution system that provides various levels of access to the data. For users seeking a synoptic view of the data, and for education and outreach purposes, delivering full-resolution images derived from LiDAR topography into the Google Earth virtual globe is powerful. The virtual globe environment provides a freely available and easily navigated viewer and enables quick integration of the LiDAR visualizations with imagery, geographic layers, and other relevant data available in KML format. Through region-dependant network linked KML, OpenTopography currently delivers over 20 GB of LiDAR-derived imagery to users via simple, easily downloaded KMZ files hosted at the Portal

  18. Investigation of the Hector Mine Earthquake Surface Rupture with Airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Chen, T.; Zhang, D.; Akciz, S. O.; Hudnut, K. W.

    2011-12-01

    The 16 October 1999 Hector Mine earthquake (Mw7.1) generated significant surface rupture along the Lavic Lake Fault through almost 60 kilometers of sparsely vegetated, relatively barren desert terrain. It was the first large earthquake for which post-earthquake airborne LiDAR, collected to image the fault surface rupture, exists. Despite the lack of pre-earthquake high-resolution topographic data, we were able to make both horizontal and vertical displacement measurements, which complement published field investigation results that include ~254 data points (164 of which are within LiDAR coverage area). We made 255 new horizontal and 83 vertical displacement measurements using a 0.5 m DEM generated from the LiDAR dataset. The maximum horizontal offset value is 6.6 ± 1.1 m, and is located approximately ~700 m south of the maximum horizontal offset observed during the field work. The average horizontal offset value from LiDAR measurements is ~2.27 m, whereas the average calculated from field data is ~2.5 m. The maximum vertical displacement is ~1.2 m, and the average vertical offset value is less than 1 m. No consistent trends are apparent in the sense of the vertical component, except in the north of the mountainous section, which is predominated by east-side-down measurements. Compared to field data, LiDAR-based measurements (a) have larger measurement uncertainties, (b) have slightly higher values, (c) do not include many measurements of offsets <1 m due to the DEM resolution, and (d) are spatially denser. The field investigation produced measurements of higher quality in alluvial deposits (e.g. tire tracks, offset rock or pebble lineaments) which are not typically visible with 0.5 m resolution DEMs unless a piercing feature has a very large or clear offset. LiDAR measurements included more geomorphic features with larger measurement uncertainties, which may not have been measured in the field due to their proximity to higher quality measurements. However, along

  19. Differential regulation of dendritic and axonal development by the novel Krüppel-like factor Dar1

    PubMed Central

    Ye, Bing; Kim, Jung Hwan; Yang, Limin; McLachlan, Ian; Younger, Susan; Jan, Lily Yeh; Jan, Yuh Nung

    2011-01-01

    Dendrites and axons are two major neuronal compartments with differences that are critical for neuronal functions. To learn about the differential regulation of dendritic and axonal development, we conducted a genetic screen in Drosophila and isolated the dendritic arbor reduction 1 (dar1) mutants, which display defects in dendritic but not axonal growth. The dar1 gene encodes a novel transcription regulator in the Krüppel-like factor family. Neurons lacking dar1 function have severely reduced growth of microtubule- but not F-actin-based dendritic branches. In contrast, overexpression of Dar1 dramatically increased the growth of microtubule-based dendritic branches. Our results suggest that Dar1 promotes dendrite growth in part by suppressing the expression of the microtubule severing protein Spastin. Our study thus uncovers a novel transcriptional program for microtubule regulation that preferentially controls dendrite growth. PMID:21368042

  20. Integrating ICT into Teaching and Learning at the University of Dar es Salaam

    ERIC Educational Resources Information Center

    Mtebe, Joel S.; Dachi, Hilary; Raphael, Christina

    2011-01-01

    Since 1985, Tanzania has been undergoing significant political and economic changes from a centralized to a more market-oriented and globally connected economy. The University of Dar es Salaam (UDSM) has responded to these changes by reviewing its legal status, vision, and functions, particularly those related to research, teaching, and public…

  1. Students' Experiences and Challenges of Blended Learning at the University of Dar Es Salaam, Tanzania

    ERIC Educational Resources Information Center

    Mtebe, Joel S.; Raphael, Christina

    2013-01-01

    Recent developments in Information and Communication Technologies (ICTs), especially eLearning, have heightened the need for University of Dar es Salaam (UDSM) to supplement on-campus face-to-face delivery as well as meeting increased students' enrolments through blended distance learning. Since 2008, the University has been offering three…

  2. Biomass estimation of Douglas fir stands using airborne LiDAR data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Biomass is an important parameter not only for carbon cycle modeling, but also for supporting land management operations (e.g. land use policy, forest fire management). Various remote sensing data have been utilized for biomass estimation, especially in forested areas. LiDAR (Light Detection And Ran...

  3. Mapping of post-event earthquake induced landslides in Sg. Mesilou using LiDAR

    NASA Astrophysics Data System (ADS)

    Hanan Mat Yusoff, Habibah; Azahari Razak, Khamarrul; Yuen, Florence; Harun, Afifi; Talib, Jasmi; Mohamad, Zakaria; Ramli, Zamri; Abd Razab, Razain

    2016-06-01

    Earthquake is a common natural disaster in active tectonic regions. The disaster can induce cascading disasters such as debris flow, mudflow and reactivated old landslides. M 6.0 Ranau earthquake dated on June 05, 2015 coupling with intense and prolonged rainfall caused several mass movements such as debris flow, deep-seated and shallow landslides in Mesilou, Sabah. This study aims at providing a better insight into the use of advanced LiDAR mapping technology for recognizing landslide induced by earthquakes particularly in a vegetated terrain, assessing post event hazard and analyzing its distribution for hazard zonation. We developed the landslide inventory using LiDAR-derived visual analysis method and validated in the field. A landslide inventory map improved with the support of LiDAR derivative data. Finally, landslide inventory was analysed by emphasizing its distribution and density in such a way that it provides clues of risky zone as a result of debris flow. We recommend that mitigation action and risk reduction should be taken place at a transport zone of the channel compared to other zones. This study indicates that modern airborne LiDAR can be a good complementary tool for improving landslide inventory in a complex environment, and an effective tool for rapid regional hazard and risk assessment in the tropics.

  4. Geospatial revolution and remote sensing LiDAR in Mesoamerican archaeology

    PubMed Central

    Chase, Arlen F.; Fisher, Christopher T.; Leisz, Stephen J.; Weishampel, John F.

    2012-01-01

    The application of light detection and ranging (LiDAR), a laser-based remote-sensing technology that is capable of penetrating overlying vegetation and forest canopies, is generating a fundamental shift in Mesoamerican archaeology and has the potential to transform research in forested areas world-wide. Much as radiocarbon dating that half a century ago moved archaeology forward by grounding archaeological remains in time, LiDAR is proving to be a catalyst for an improved spatial understanding of the past. With LiDAR, ancient societies can be contextualized within a fully defined landscape. Interpretations about the scale and organization of densely forested sites no longer are constrained by sample size, as they were when mapping required laborious on-ground survey. The ability to articulate ancient landscapes fully permits a better understanding of the complexity of ancient Mesoamerican urbanism and also aids in modern conservation efforts. The importance of this geospatial innovation is demonstrated with newly acquired LiDAR data from the archaeological sites of Caracol, Cayo, Belize and Angamuco, Michoacán, Mexico. These data illustrate the potential of technology to act as a catalytic enabler of rapid transformational change in archaeological research and interpretation and also underscore the value of on-the-ground archaeological investigation in validating and contextualizing results. PMID:22802623

  5. Clinical, Virologic, and Epidemiologic Characteristics of Dengue Outbreak, Dar es Salaam, Tanzania, 2014

    PubMed Central

    Mboera, Leonard E.G.; De Nardo, Pasquale; Oriyo, Ndekya M.; Meschi, Silvia; Rumisha, Susan F.; Colavita, Francesca; Mhina, Athanas; Carletti, Fabrizio; Mwakapeje, Elibariki; Capobianchi, Maria Rosaria; Castilletti, Concetta; Di Caro, Antonino; Nicastri, Emanuele; Malecela, Mwelecele N.; Ippolito, Giuseppe

    2016-01-01

    We investigated a dengue outbreak in Dar es Salaam, Tanzania, in 2014, that was caused by dengue virus (DENV) serotype 2. DENV infection was present in 101 (20.9%) of 483 patients. Patient age and location of residence were associated with infection. Seven (4.0%) of 176 patients were co-infected with malaria and DENV. PMID:27088845

  6. Terrain Referenced Navigation Using SIFT Features in LiDAR Range-Based Data

    DTIC Science & Technology

    2014-12-26

    Geomorphology , 182:147– 156, 2013. [39] Jiaping Zhao, Suya You. “Road Network Extraction from Airbone LiDAR Data using Scene Context”. International...New Opportunities from High Resolution DTMs”. Geomorphology , 113(1):47–56, 2009. [106] The National Coordination Office. “GPS Applications”, September

  7. Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping

    PubMed Central

    Cui, Tingting; Ji, Shunping; Shan, Jie; Gong, Jianya; Liu, Kejian

    2016-01-01

    For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable. PMID:28042855

  8. Registration of optical imagery and LiDAR data using an inherent geometrical constraint.

    PubMed

    Zhang, Wuming; Zhao, Jing; Chen, Mei; Chen, Yiming; Yan, Kai; Li, Linyuan; Qi, Jianbo; Wang, Xiaoyan; Luo, Jinghui; Chu, Qing

    2015-03-23

    A novel method for registering imagery with Light Detection And Ranging (LiDAR) data is proposed. It is based on the phenomenon that the back-projection of LiDAR point cloud of an object should be located within the object boundary in the image. Using this inherent geometrical constraint, the registration parameters computation of both data sets only requires LiDAR point clouds of several objects and their corresponding boundaries in the image. The proposed registration method comprises of four steps: point clouds extraction, boundary extraction, back-projection computation and registration parameters computation. There are not any limitations on the geometrical and spectral properties of the object. So it is suitable not only for structured scenes with man-made objects but also for natural scenes. Moreover, the proposed method based on the inherent geometrical constraint can register two data sets derived from different parts of an object. It can be used to co-register TLS (Terrestrial Laser Scanning) LiDAR point cloud and UAV (Unmanned aerial vehicle) image, which are obtaining more attention in the forest survey application. Using initial registration parameters comparable to POS (position and orientation system) accuracy, the performed experiments validated the feasibility of the proposed registration method.

  9. Clinical, Virologic, and Epidemiologic Characteristics of Dengue Outbreak, Dar es Salaam, Tanzania, 2014.

    PubMed

    Vairo, Francesco; Mboera, Leonard E G; De Nardo, Pasquale; Oriyo, Ndekya M; Meschi, Silvia; Rumisha, Susan F; Colavita, Francesca; Mhina, Athanas; Carletti, Fabrizio; Mwakapeje, Elibariki; Capobianchi, Maria Rosaria; Castilletti, Concetta; Di Caro, Antonino; Nicastri, Emanuele; Malecela, Mwelecele N; Ippolito, Giuseppe

    2016-05-01

    We investigated a dengue outbreak in Dar es Salaam, Tanzania, in 2014, that was caused by dengue virus (DENV) serotype 2. DENV infection was present in 101 (20.9%) of 483 patients. Patient age and location of residence were associated with infection. Seven (4.0%) of 176 patients were co-infected with malaria and DENV.

  10. An Analysis of Student Reading as Measured on the Diagnostic Assessment of Reading (DAR)

    ERIC Educational Resources Information Center

    Baca, Jo-Ann M.; Shepperson, Barbara A.

    2006-01-01

    As part of the reporting of Delaware's State Improvement Grant (DelaSIG), the Delaware Education Research and Development Center (R&D Center) completed a study on the Diagnostic Assessment of Reading (DAR) scores of students whose teachers attended a professional development program designed to help focus teacher instruction of struggling …

  11. Spatial Patterns of Trees from Airborne LiDAR Using a Simple Tree Segmentation Algorithm

    NASA Astrophysics Data System (ADS)

    Jeronimo, S.; Kane, V. R.; McGaughey, R. J.; Franklin, J. F.

    2015-12-01

    Objectives for management of forest ecosystems on public land incorporate a focus on maintenance and restoration of ecological functions through silvicultural manipulation of forest structure. The spatial pattern of residual trees - the horizontal element of structure - is a key component of ecological restoration prescriptions. We tested the ability of a simple LiDAR individual tree segmentation method - the watershed transform - to generate spatial pattern metrics similar to those obtained by the traditional method - ground-based stem mapping - on forested plots representing the structural diversity of a large wilderness area (Yosemite NP) and a large managed area (Sierra NF) in the Sierra Nevada, Calif. Most understory and intermediate-canopy trees were not detected by the LiDAR segmentation; however, LiDAR- and field-based assessments of spatial pattern in terms of tree clump size distributions largely agreed. This suggests that (1) even when individual tree segmentation is not effective for tree density estimates, it can provide a good measurement of tree spatial pattern, and (2) a simple segmentation method is adequate to measure spatial pattern of large areas with a diversity of structural characteristics. These results lay the groundwork for a LiDAR tool to assess clumping patterns across forest landscapes in support of restoration silviculture. This tool could describe spatial patterns of functionally intact reference ecosystems, measure departure from reference targets in treatment areas, and, with successive acquisitions, monitor treatment efficacy.

  12. a Data Driven Method for Building Reconstruction from LiDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Sajadian, M.; Arefi, H.

    2014-10-01

    Airborne laser scanning, commonly referred to as LiDAR, is a superior technology for three-dimensional data acquisition from Earth's surface with high speed and density. Building reconstruction is one of the main applications of LiDAR system which is considered in this study. For a 3D reconstruction of the buildings, the buildings points should be first separated from the other points such as; ground and vegetation. In this paper, a multi-agent strategy has been proposed for simultaneous extraction and segmentation of buildings from LiDAR point clouds. Height values, number of returned pulse, length of triangles, direction of normal vectors, and area are five criteria which have been utilized in this step. Next, the building edge points are detected using a new method named "Grid Erosion". A RANSAC based technique has been employed for edge line extraction. Regularization constraints are performed to achieve the final lines. Finally, by modelling of the roofs and walls, 3D building model is reconstructed. The results indicate that the proposed method could successfully extract the building from LiDAR data and generate the building models automatically. A qualitative and quantitative assessment of the proposed method is then provided.

  13. Dynamic displacement estimation by fusing LDV and LiDAR measurements via smoothing based Kalman filtering

    NASA Astrophysics Data System (ADS)

    Kim, Kiyoung; Sohn, Hoon

    2017-01-01

    This paper presents a smoothing based Kalman filter to estimate dynamic displacement in real-time by fusing the velocity measured from a laser Doppler vibrometer (LDV) and the displacement from a light detection and ranging (LiDAR). LiDAR can measure displacement based on the time-of-flight information or the phase-shift of the laser beam reflected off form a target surface, but it typically has a high noise level and a low sampling rate. On the other hand, LDV primarily measures out-of-plane velocity of a moving target, and displacement is estimated by numerical integration of the measured velocity. Here, the displacement estimated by LDV suffers from integration error although LDV can achieve a lower noise level and a much higher sampling rate than LiDAR. The proposed data fusion technique estimates high-precision and high-sampling rate displacement by taking advantage of both LiDAR and LDV measurements and overcomes their limitations by adopting a real-time smoothing based Kalman filter. To verify the performance of the proposed dynamic displacement estimation technique, a series of lab-scale tests are conducted under various loading conditions.

  14. An Algorithm to Identify and Localize Suitable Dock Locations from 3-D LiDAR Scans

    DTIC Science & Technology

    2013-05-10

    3-D) LiDARs have proved themselves very useful on many autonomous ground vehicles, such as the Google Driverless Car Project, the DARPA, Defense...appear in a typical point cloud data set, relative to other clusters such as cars , trees, boulders, etc. In this algorithm, these values were

  15. Diversity Arrays Technology (DArT) platform for genotyping and mapping in carrot (Daucus carota L.)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Carrot is one of the most important root vegetable crops grown worldwide on more than one million hectares. Its progenitor, wild Daucus carota, is a weed commonly occurring across continents in the temperate climatic zone. Diversity Array Technology (DArT) is a microarray-based molecular marker syst...

  16. Pit Latrine Emptying Behavior and Demand for Sanitation Services in Dar Es Salaam, Tanzania

    PubMed Central

    Jenkins, Marion W.; Cumming, Oliver; Cairncross, Sandy

    2015-01-01

    Pit latrines are the main form of sanitation in unplanned areas in many rapidly growing developing cities. Understanding demand for pit latrine fecal sludge management (FSM) services in these communities is important for designing demand-responsive sanitation services and policies to improve public health. We examine latrine emptying knowledge, attitudes, behavior, trends and rates of safe/unsafe emptying, and measure demand for a new hygienic latrine emptying service in unplanned communities in Dar Es Salaam (Dar), Tanzania, using data from a cross-sectional survey at 662 residential properties in 35 unplanned sub-wards across Dar, where 97% had pit latrines. A picture emerges of expensive and poor FSM service options for latrine owners, resulting in widespread fecal sludge exposure that is likely to increase unless addressed. Households delay emptying as long as possible, use full pits beyond what is safe, face high costs even for unhygienic emptying, and resort to unsafe practices like ‘flooding out’. We measured strong interest in and willingness to pay (WTP) for the new pit emptying service at 96% of residences; 57% were WTP ≥U.S. $17 to remove ≥200 L of sludge. Emerging policy recommendations for safe FSM in unplanned urban communities in Dar and elsewhere are discussed. PMID:25734790

  17. How Children Living in Poor Areas of Dar Es Salaam, Tanzania Perceive Their Own Multiple Intelligences

    ERIC Educational Resources Information Center

    Dixon, Pauline; Humble, Steve; Chan, David W.

    2016-01-01

    This study was carried out with 1,857 poor children from 17 schools, living in low-income areas of Dar Es Salaam, Tanzania. All children took the "Student Multiple Intelligences Profile" (SMIP) questionnaire as part of a bigger project that gathered data around concepts and beliefs of talent. This paper sets out two aims, first to…

  18. High-throughput genotyping of hop (Humulus lupulus L.) utilising diversity arrays technology (DArT)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Implementation of molecular methods in hop breeding is dependent on the availability of sizeable numbers of polymorphic markers and a comprehensive understanding of genetic variation. Diversity Arrays Technology (DArT) is a high-throughput cost-effective method for the discovery of large numbers of...

  19. High-throughput genotyping of hop (Humulus lupulus L.) utilising diversity arrays technology (DArT).

    PubMed

    Howard, E L; Whittock, S P; Jakše, J; Carling, J; Matthews, P D; Probasco, G; Henning, J A; Darby, P; Cerenak, A; Javornik, B; Kilian, A; Koutoulis, A

    2011-05-01

    Implementation of molecular methods in hop (Humulus lupulus L.) breeding is dependent on the availability of sizeable numbers of polymorphic markers and a comprehensive understanding of genetic variation. However, use of molecular marker technology is limited due to expense, time inefficiency, laborious methodology and dependence on DNA sequence information. Diversity arrays technology (DArT) is a high-throughput cost-effective method for the discovery of large numbers of quality polymorphic markers without reliance on DNA sequence information. This study is the first to utilise DArT for hop genotyping, identifying 730 polymorphic markers from 92 hop accessions. The marker quality was high and similar to the quality of DArT markers previously generated for other species; although percentage polymorphism and polymorphism information content (PIC) were lower than in previous studies deploying other marker systems in hop. Genetic relationships in hop illustrated by DArT in this study coincide with knowledge generated using alternate methods. Several statistical analyses separated the hop accessions into genetically differentiated North American and European groupings, with hybrids between the two groups clearly distinguishable. Levels of genetic diversity were similar in the North American and European groups, but higher in the hybrid group. The markers produced from this time and cost-efficient genotyping tool will be a valuable resource for numerous applications in hop breeding and genetics studies, such as mapping, marker-assisted selection, genetic identity testing, guidance in the maintenance of genetic diversity and the directed breeding of superior cultivars.

  20. The Effect of Lava Texture on LiDAR Attributes and Full Waveform

    NASA Astrophysics Data System (ADS)

    Anderson, S. W.; Finnegan, D. C.; LeWinter, A.

    2013-12-01

    The distribution of glassy, vesicular, and crystalline textures on lava flow and dome surfaces provides insights regarding the physical and chemical processes occurring during emplacement. For silicic flows, these textures may reflect variations in the volatile content of lava upon eruption. To assess the efficacy of texture detection with our terrestrial full waveform LiDAR system capable of measuring ~125,000 topographic points/second, we analyzed attribute and full waveform data from a variety of lava textures displayed on recent rhyolitic obsidian flows of the Inyo Dome chain (California) and pahoehoe and aa flows at Kilauea volcano (Hawaii). We find that attributes such as intensity, amplitude and deviation of the returned 1550nm laser pulse fall into discrete ranges associated with glassy, pumiceous and crystalline textures on both the rhyolitic and basaltic surfaces. This enables detection of vesicularity at ranges in excess of 500 m, making LiDAR a useful tool for remotely determining lava texture. Scan times using our Riegl VZ1000 and VZ400 systems require only minutes, allowing for repeated scans over a short time period, and processing times are <1 hour. We have also analyzed the full digitized waveforms of LiDAR pulses returned from these surfaces, and find that they also have unique signatures related to texture. We therefore suggest that LiDAR can provide reliable information on lava texture during eruption, aiding in the interpretation of eruption hazards from increasing volatile contents.

  1. Airborne hyperspectral and LiDAR data integration for weed detection

    NASA Astrophysics Data System (ADS)

    Tamás, János; Lehoczky, Éva; Fehér, János; Fórián, Tünde; Nagy, Attila; Bozsik, Éva; Gálya, Bernadett; Riczu, Péter

    2014-05-01

    Agriculture uses 70% of global available fresh water. However, ca. 50-70% of water used by cultivated plants, the rest of water transpirated by the weeds. Thus, to define the distribution of weeds is very important in precision agriculture and horticulture as well. To survey weeds on larger fields by traditional methods is often time consuming. Remote sensing instruments are useful to detect weeds in larger area. In our investigation a 3D airborne laser scanner (RIEGL LMS-Q680i) was used in agricultural field near Sopron to scouting weeds. Beside the airborne LiDAR, hyperspectral imaging system (AISA DUAL) and air photos helped to investigate weed coverage. The LiDAR survey was carried out at early April, 2012, before sprouting of cultivated plants. Thus, there could be detected emerging of weeds and direction of cultivation. However airborne LiDAR system was ideal to detect weeds, identification of weeds at species level was infeasible. Higher point density LiDAR - Terrestrial laser scanning - systems are appropriate to distinguish weed species. Based on the results, laser scanner is an effective tool to scouting of weeds. Appropriate weed detection and mapping systems could contribute to elaborate water and herbicide saving management technique. This publication was supported by the OTKA project K 105789.

  2. Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping.

    PubMed

    Cui, Tingting; Ji, Shunping; Shan, Jie; Gong, Jianya; Liu, Kejian

    2016-12-31

    For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.

  3. Errors in LiDAR-derived shrub height and crown area on sloped terrain

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study developed and tested four methodologies for determining shrub height measurements with LiDAR data in a semiarid shrub-steppe in southwestern Idaho, USA. Unique to this study was the focus of sagebrush height measurements on sloped terrain. The study also developed one of the first metho...

  4. Shape Detection from Raw LiDAR Data with Subspace Modeling.

    PubMed

    Wang, Jun; Xu, Kevin Kai

    2016-08-31

    LiDAR scanning has become a prevalent technique for digitalizing large-scale outdoor scenes. However, the raw LiDAR data often contain imperfections, e.g., missing large regions, anisotropy of sampling density, and contamination of noise and outliers, which are the major obstacles that hinder its more ambitious and higher level applications in digital city modeling. Observing that 3D urban scenes can be locally described with several low dimensional subspaces, we propose to locally classify the neighborhoods of the scans to model the substructures of the scenes. The key enabler is the adaptive kernel-scale scoring, filtering and clustering of substructures, making it possible to recover the local structures at all points simultaneously, even in the presence of severe data imperfections. Integrating the local analyses leads to robust shape detection from raw LiDAR data. On this basis, we develop several urban scene applications and verify them on a number of LiDAR scans with various complexities and styles, which demonstrates the effectiveness and robustness of our methods.

  5. A comparison of two open source LiDAR surface classification algorithms

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are op...

  6. Geospatial revolution and remote sensing LiDAR in Mesoamerican archaeology.

    PubMed

    Chase, Arlen F; Chase, Diane Z; Fisher, Christopher T; Leisz, Stephen J; Weishampel, John F

    2012-08-07

    The application of light detection and ranging (LiDAR), a laser-based remote-sensing technology that is capable of penetrating overlying vegetation and forest canopies, is generating a fundamental shift in Mesoamerican archaeology and has the potential to transform research in forested areas world-wide. Much as radiocarbon dating that half a century ago moved archaeology forward by grounding archaeological remains in time, LiDAR is proving to be a catalyst for an improved spatial understanding of the past. With LiDAR, ancient societies can be contextualized within a fully defined landscape. Interpretations about the scale and organization of densely forested sites no longer are constrained by sample size, as they were when mapping required laborious on-ground survey. The ability to articulate ancient landscapes fully permits a better understanding of the complexity of ancient Mesoamerican urbanism and also aids in modern conservation efforts. The importance of this geospatial innovation is demonstrated with newly acquired LiDAR data from the archaeological sites of Caracol, Cayo, Belize and Angamuco, Michoacán, Mexico. These data illustrate the potential of technology to act as a catalytic enabler of rapid transformational change in archaeological research and interpretation and also underscore the value of on-the-ground archaeological investigation in validating and contextualizing results.

  7. Genetics and Human Agency: Comment on Dar-Nimrod and Heine (2011)

    ERIC Educational Resources Information Center

    Turkheimer, Eric

    2011-01-01

    Dar-Nimrod and Heine (2011) decried genetic essentialism without denying the importance of genetics in the genesis of human behavior, and although I agree on both counts, a deeper issue remains unaddressed: how should we adjust our cognitions about our own behavior in light of genetic influence, or is it perhaps not necessary to take genetics into…

  8. Draft genome sequence of Bacillus thuringiensis strain DAR 81934, which exhibits molluscicidal activity.

    PubMed

    Wang, Aisuo; Pattemore, Julie; Ash, Gavin; Williams, Angela; Hane, James

    2013-03-21

    Bacillus thuringiensis has been widely used as a biopesticide for a long time. Its molluscicidal activity, however, is rarely realized. Here, we report the genome sequence of B. thuringiensis strain DAR 81934, a strain with molluscicidal activity against the pest snail Cernuella virgata.

  9. Hyperspectral and LiDAR remote sensing of fire fuels in Hawaii Volcanoes National Park.

    PubMed

    Varga, Timothy A; Asner, Gregory P

    2008-04-01

    Alien invasive grasses threaten to transform Hawaiian ecosystems through the alteration of ecosystem dynamics, especially the creation or intensification of a fire cycle. Across sub-montane ecosystems of Hawaii Volcanoes National Park on Hawaii Island, we quantified fine fuels and fire spread potential of invasive grasses using a combination of airborne hyperspectral and light detection and ranging (LiDAR) measurements. Across a gradient from forest to savanna to shrubland, automated mixture analysis of hyperspectral data provided spatially explicit fractional cover estimates of photosynthetic vegetation, non-photosynthetic vegetation, and bare substrate and shade. Small-footprint LiDAR provided measurements of vegetation height along this gradient of ecosystems. Through the fusion of hyperspectral and LiDAR data, a new fire fuel index (FFI) was developed to model the three-dimensional volume of grass fuels. Regionally, savanna ecosystems had the highest volumes of fire fuels, averaging 20% across the ecosystem and frequently filling all of the three-dimensional space represented by each image pixel. The forest and shrubland ecosystems had lower FFI values, averaging 4.4% and 8.4%, respectively. The results indicate that the fusion of hyperspectral and LiDAR remote sensing can provide unique information on the three-dimensional properties of ecosystems, their flammability, and the potential for fire spread.

  10. Child Labour in Urban Agriculture: The Case of Dar es Salaam, Tanzania.

    ERIC Educational Resources Information Center

    Mlozi, Malongo R. S.

    1995-01-01

    Urban agriculture in Dar es Salaam was found to use child labor of both children with parents of higher and lower socioeconomic status (SES). Discusses policy implications and calls for the education of parents of lower SES not to expect an economic contribution from their children's labor, and the education of children about their rights. (LZ)

  11. Genetic Essentialism, Neuroessentialism, and Stigma: Commentary on Dar-Nimrod and Heine (2011)

    ERIC Educational Resources Information Center

    Haslam, Nick

    2011-01-01

    Dar-Nimrod and Heine (2011) presented a masterfully broad review of the implications of genetic essentialism for understandings of human diversity. This commentary clarifies the reasons that essentialist thinking has problematic social consequences and links genetic forms of essentialism to those invoking neural essences. The mounting evidence…

  12. Multitemporal Error Analysis of LiDAR Data for Geomorphological Feature Detection

    NASA Astrophysics Data System (ADS)

    Sailer, R.; Höfle, B.; Bollmann, E.; Vetter, M.; Stötter, J.; Pfeifer, N.; Rutzinger, M.; Geist, T.

    2009-04-01

    Since 2001 airborne LiDAR measurements have been carried out regularly at the Hintereisferner region (Ötztal, Tyrol, Austria). This results in a worldwide unique data set, which is primarily used for multitemporal glacial and periglacial analyses. Several methods and tools i) to delineate the glacier boundary, ii) to derive standard glaciological mass balance parameters (e.g. volume changes), iii) to excerpt crevasse zones or iv) to classify glacier surface features (e.g. snow, firn, glacier ice, debris covered glacier ice) have been developed as yet. Furthermore, the available multitemporal LiDAR data set offers the opportunity to identify surface changes occurring outside the glacier boundary, which have not been recognized until now. The respective areas are characterized by small variations of the surface topography from year to year. These changes of the surface topography are primarily caused by periglacial processes further initiating secondary gravitative mass movements. The present study aims at quantifying the error range of LiDAR measurements. The error analysis, which is based on (at least) 66 cross-combinations of the single LiDAR measurement campaigns, excluding areas which are obviously related to glacial surface changes, results in statistically derived error margins. Hence, surface changes which exceed these error margins have to be assigned to periglacial or gravitative process activities. The study further aims at identifying areas which are explicitly related to those periglacial and gravitative processes.

  13. Pit latrine emptying behavior and demand for sanitation services in Dar Es Salaam, Tanzania.

    PubMed

    Jenkins, Marion W; Cumming, Oliver; Cairncross, Sandy

    2015-02-27

    Pit latrines are the main form of sanitation in unplanned areas in many rapidly growing developing cities. Understanding demand for pit latrine fecal sludge management (FSM) services in these communities is important for designing demand-responsive sanitation services and policies to improve public health. We examine latrine emptying knowledge, attitudes, behavior, trends and rates of safe/unsafe emptying, and measure demand for a new hygienic latrine emptying service in unplanned communities in Dar Es Salaam (Dar), Tanzania, using data from a cross-sectional survey at 662 residential properties in 35 unplanned sub-wards across Dar, where 97% had pit latrines. A picture emerges of expensive and poor FSM service options for latrine owners, resulting in widespread fecal sludge exposure that is likely to increase unless addressed. Households delay emptying as long as possible, use full pits beyond what is safe, face high costs even for unhygienic emptying, and resort to unsafe practices like 'flooding out'. We measured strong interest in and willingness to pay (WTP) for the new pit emptying service at 96% of residences; 57% were WTP≥U.S. $17 to remove ≥200 L of sludge. Emerging policy recommendations for safe FSM in unplanned urban communities in Dar and elsewhere are discussed.

  14. Effects of atmospheric stability on the evolution of wind turbine wakes: Volumetric LiDAR scans

    NASA Astrophysics Data System (ADS)

    Valerio Iungo, Giacomo; Porté-Agel, Fernando

    2014-05-01

    Aerodynamic optimization of wind farm layout is a fundamental task to reduce wake effects on downstream wind turbines, thus to maximize wind power harvesting. However, downstream evolution and recovery of wind turbine wakes are strongly affected by the characteristics of the incoming atmospheric boundary layer (ABL) flow, like the vertical profiles of the mean wind velocity and the turbulence intensity, which are in turn affected by the ABL stability regime. Therefore, the characterization of the variability of wind turbine wakes under different ABL stability regimes becomes fundamental to better predict wind power harvesting and improve wind farm efficiency. To this aim, wind velocity measurements of the wake produced by a 2 MW Enercon E-70 wind turbine were performed with three scanning Doppler wind Light Detection and Ranging (LiDAR) instruments. One LiDAR was typically devoted to the characterization of the incoming wind, in particular wind velocity, shear and turbulence intensity at the height of the rotor disc. The other two LiDARs performed scans in order to characterize the wake velocity field produced by the tested wind turbine. The main challenge in performing field measurements of wind turbine wakes is represented by the varying wind conditions, and by the consequent adjustments of the turbine yaw angle needed to maximize power production. Consequently, taking into account possible variations of the relative position between LiDAR measurement volume and wake location, different LiDAR measurement procedures were carried out in order to perform 2-D and 3-D characterizations of the mean wake velocity field. However, larger measurement volumes and higher spatial resolution require longer sampling periods; thus, to investigate wake turbulence tests were also performed by staring the LiDAR laser beam over fixed directions and with the maximum sampling frequency. Furthermore, volumetric scans of the wind turbine wake were performed under different wind

  15. Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

    PubMed Central

    Vierling, Lee A.; Vierling, Kerri T.; Adam, Patrick; Hudak, Andrew T.

    2013-01-01

    Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2

  16. Distinguishing grass from ground using LiDAR: Techniques and applications

    NASA Astrophysics Data System (ADS)

    Pelletier, J. D.; Swetnam, T.; Papuga, S. A.; Nelson, K.; Brooks, P. D.; Harpold, A. A.; Chorover, J.

    2011-12-01

    Standard protocols exist for extracting bare-earth Digital Elevation Models (DEMs) from LiDAR point clouds that include trees and other large woody vegetation. Grasses and other herbaceous plants can also obscure the ground surface, yet methods for optimally distinguishing grass from ground to generate accurate LiDAR-based raster products for geomorphic and ecological applications are still under development. Developing such methods is important because LiDAR-based difference products (e.g. snow thickness) require accurate representations of the ground surface and because raster data for grass height and density have important applications in ecology. In this study, we developed and tested methods for constructing optimal bare-earth and grass height raster layers from LiDAR point clouds and compared the results to high-quality field-based measurements of grass height, density, and species type for nearly 1000 precisely geo-referenced locations collected during the acquisition of a >200 km^2 airborne LiDAR flight of the Valles Caldera National Preserve (New Mexico). In cases of partially bare ground (where the skewness of return heights above a plane fit to the lowest first returns is sufficiently large), a planar fit to the lowest first returns provides a good method of producing an accurate bare-earth DEM and the statistics of the first returns above that planar fit provide good estimates of the mean and variance of grass height. In areas of relatively thick grass cover, however, a fit to the lowest first returns yields a bare-earth DEM that may be a meter or more above the actual ground surface. Here we propose a method to solve this problem using field-measured correlations among the mean, variance, and skewness of grass heights. In this method, the variance and skewness of the differences between LiDAR first returns and a 10m^2 planar fit to the lowest first returns is used, together with field-based correlations of grass height statistics, to estimate the mean

  17. Building Damage Assessment after Earthquake Using Post-Event LiDAR Data

    NASA Astrophysics Data System (ADS)

    Rastiveis, H.; Eslamizade, F.; Hosseini-Zirdoo, E.

    2015-12-01

    After an earthquake, damage assessment plays an important role in leading rescue team to help people and decrease the number of mortality. Damage map is a map that demonstrates collapsed buildings with their degree of damage. With this map, finding destructive buildings can be quickly possible. In this paper, we propose an algorithm for automatic damage map generation after an earthquake using post-event LiDAR Data and pre-event vector map. The framework of the proposed approach has four main steps. To find the location of all buildings on LiDAR data, in the first step, LiDAR data and vector map are registered by using a few number of ground control points. Then, building layer, selected from vector map, are mapped on the LiDAR data and all pixels which belong to the buildings are extracted. After that, through a powerful classifier all the extracted pixels are classified into three classes of "debris", "intact building" and "unclassified". Since textural information make better difference between "debris" and "intact building" classes, different textural features are applied during the classification. After that, damage degree for each candidate building is estimated based on the relation between the numbers of pixels labelled as "debris" class to the whole building area. Calculating the damage degree for each candidate building, finally, building damage map is generated. To evaluate the ability proposed method in generating damage map, a data set from Port-au-Prince, Haiti's capital after the 2010 Haiti earthquake was used. In this case, after calculating of all buildings in the test area using the proposed method, the results were compared to the damage degree which estimated through visual interpretation of post-event satellite image. Obtained results were proved the reliability of the proposed method in damage map generation using LiDAR data.

  18. Mapping the Risk of Forest Wind Damage Using Airborne Scanning LiDAR

    NASA Astrophysics Data System (ADS)

    Saarinen, N.; Vastaranta, M.; Honkavaara, E.; Wulder, M. A.; White, J. C.; Litkey, P.; Holopainen, M.; Hyyppä, J.

    2015-03-01

    Wind damage is known for causing threats to sustainable forest management and yield value in boreal forests. Information about wind damage risk can aid forest managers in understanding and possibly mitigating damage impacts. The objective of this research was to better understand and quantify drivers of wind damage, and to map the probability of wind damage. To accomplish this, we used open-access airborne scanning light detection and ranging (LiDAR) data. The probability of wind-induced forest damage (PDAM) in southern Finland (61°N, 23°E) was modelled for a 173 km2 study area of mainly managed boreal forests (dominated by Norway spruce and Scots pine) and agricultural fields. Wind damage occurred in the study area in December 2011. LiDAR data were acquired prior to the damage in 2008. High spatial resolution aerial imagery, acquired after the damage event (January, 2012) provided a source of model calibration via expert interpretation. A systematic grid (16 m x 16 m) was established and 430 sample grid cells were identified systematically and classified as damaged or undamaged based on visual interpretation using the aerial images. Potential drivers associated with PDAM were examined using a multivariate logistic regression model. Risk model predictors were extracted from the LiDAR-derived surface models. Geographic information systems (GIS) supported spatial mapping and identification of areas of high PDAM across the study area. The risk model based on LiDAR data provided good agreement with detected risk areas (73 % with kappa-value 0,47). The strongest predictors in the risk model were mean canopy height and mean elevation. Our results indicate that open-access LiDAR data sets can be used to map the probability of wind damage risk without field data, providing valuable information for forest management planning.

  19. Object-Based Land Use Classification using Airborne LiDAR

    NASA Astrophysics Data System (ADS)

    Antonarakis, A. S.; Richards, K. S.; Brasington, J.

    2007-12-01

    Better information on roughness of various types of vegetation is needed for use in resistance equations and eventually in flood modelling. These types include woody riparian species with different structural characteristics. Remote Sensing information such as 3D point cloud data from LiDAR can be used as a tool for extracting simple roughness information relevant for the condition of below canopy flow, as well as roughness relevant for more complex tree morphology that affects the flow when it enters the canopy levels. A strategy for extracting roughness parameters from remote sensing techniques is to use a data fusion object classification model. This means that multiple datasets such as LiDAR, digital aerial photography, ground data and satellite data can be combined to produce roughness parameters estimated for different vegetative patches, which can subsequently be mapped spatially using a classification methodology. Airborne LiDAR is used in this study in order to classify forest and ground types quickly and efficiently without the need for manipulating multispectral image files. LiDAR has the advantage of being able to create elevation surfaces that are in 3D, while also having information on LiDAR intensity values, thus it is a spatial and spectral segmentation tool. This classification method also uses point distribution frequency criteria to differentiate between land cover types. The classification of three meanders of the Garonne and Allier rivers in France has demonstrated overall classification accuracies of 95%. Five types of riparian forest were classified with accuracies between 66-98%. These forest types included planted and natural forest stands of different ages. Classifications of short vegetation and bare earth also produced high accuracies averaging above 90%.

  20. Effects of LiDAR Derived DEM Resolution on Hydrographic Feature Extraction

    NASA Astrophysics Data System (ADS)

    Yang, P.; Ames, D. P.; Glenn, N. F.; Anderson, D.

    2010-12-01

    This paper examines the effect of LiDAR-derived digital elevation model (DEM) resolution on digitally extracted stream networks with respect to known stream channel locations. Two study sites, Reynolds Creek Experimental Watershed (RCEW) and Dry Creek Experimental Watershed (DCEW), which represent terrain characteristics for lower and intermediate elevation mountainous watersheds in the Intermountain West, were selected as study areas for this research. DEMs reflecting bare earth ground were created from the LiDAR observations at a series of raster cell sizes (from 1 m to 60 m) using spatial interpolation techniques. The effect of DEM resolution on resulting hydrographic feature (specifically stream channel) derivation was studied. Stream length, watershed area, and sinuosity were explored at each of the raster cell sizes. Also, variation from known channel location as estimated by root mean square error (RMSE) between surveyed channel location and extracted channel was computed for each of the DEMs and extracted stream networks. As expected, the results indicate that the DEM based hydrographic extraction process provides more detailed hydrographic features at a finer resolution. RMSE between the known channel location and modeled locations generally increased with larger cell size DEM with a greater effect in the larger RCEW. Sensitivity analyses on sinuosity demonstrated that the resulting shape of streams obtained from LiDAR data matched best with the reference data at an intermediate cell size instead of highest resolution, which is at a range of cell size from 5 to 10 m likely due to original point spacing, terrain characteristics, and LiDAR noise influence. More importantly, the absolute sinuosity deviation displayed a smallest value at the cell size of 10 m in both experimental watersheds, which suggests that optimal cell size for LiDAR-derived DEMs used for hydrographic feature extraction is 10 m.

  1. Combined use of LiDAR data and multispectral earth observation imagery for wetland habitat mapping

    NASA Astrophysics Data System (ADS)

    Rapinel, Sébastien; Hubert-Moy, Laurence; Clément, Bernard

    2015-05-01

    Although wetlands play a key role in controlling flooding and nonpoint source pollution, sequestering carbon and providing an abundance of ecological services, the inventory and characterization of wetland habitats are most often limited to small areas. This explains why the understanding of their ecological functioning is still insufficient for a reliable functional assessment on areas larger than a few hectares. While LiDAR data and multispectral Earth Observation (EO) images are often used separately to map wetland habitats, their combined use is currently being assessed for different habitat types. The aim of this study is to evaluate the combination of multispectral and multiseasonal imagery and LiDAR data to precisely map the distribution of wetland habitats. The image classification was performed combining an object-based approach and decision-tree modeling. Four multispectral images with high (SPOT-5) and very high spatial resolution (Quickbird, KOMPSAT-2, aerial photographs) were classified separately. Another classification was then applied integrating summer and winter multispectral image data and three layers derived from LiDAR data: vegetation height, microtopography and intensity return. The comparison of classification results shows that some habitats are better identified on the winter image and others on the summer image (overall accuracies = 58.5 and 57.6%). They also point out that classification accuracy is highly improved (overall accuracy = 86.5%) when combining LiDAR data and multispectral images. Moreover, this study highlights the advantage of integrating vegetation height, microtopography and intensity parameters in the classification process. This article demonstrates that information provided by the synergetic use of multispectral images and LiDAR data can help in wetland functional assessment

  2. A universal airborne LiDAR approach for tropical forest carbon mapping.

    PubMed

    Asner, Gregory P; Mascaro, Joseph; Muller-Landau, Helene C; Vieilledent, Ghislain; Vaudry, Romuald; Rasamoelina, Maminiaina; Hall, Jefferson S; van Breugel, Michiel

    2012-04-01

    Airborne light detection and ranging (LiDAR) is fast turning the corner from demonstration technology to a key tool for assessing carbon stocks in tropical forests. With its ability to penetrate tropical forest canopies and detect three-dimensional forest structure, LiDAR may prove to be a major component of international strategies to measure and account for carbon emissions from and uptake by tropical forests. To date, however, basic ecological information such as height-diameter allometry and stand-level wood density have not been mechanistically incorporated into methods for mapping forest carbon at regional and global scales. A better incorporation of these structural patterns in forests may reduce the considerable time needed to calibrate airborne data with ground-based forest inventory plots, which presently necessitate exhaustive measurements of tree diameters and heights, as well as tree identifications for wood density estimation. Here, we develop a new approach that can facilitate rapid LiDAR calibration with minimal field data. Throughout four tropical regions (Panama, Peru, Madagascar, and Hawaii), we were able to predict aboveground carbon density estimated in field inventory plots using a single universal LiDAR model (r ( 2 ) = 0.80, RMSE = 27.6 Mg C ha(-1)). This model is comparable in predictive power to locally calibrated models, but relies on limited inputs of basal area and wood density information for a given region, rather than on traditional plot inventories. With this approach, we propose to radically decrease the time required to calibrate airborne LiDAR data and thus increase the output of high-resolution carbon maps, supporting tropical forest conservation and climate mitigation policy.

  3. Water turbidity estimation from airborne hyperspectral imagery and full waveform bathymetric LiDAR

    NASA Astrophysics Data System (ADS)

    Pan, Z.; Glennie, C. L.; Fernandez-Diaz, J. C.

    2015-12-01

    The spatial and temporal variations in water turbidity are of great interest for the study of fluvial and coastal environments; and for predicting the performance of remote sensing systems that are used to map these. Conventional water turbidity estimates from remote sensing observations have normally been derived using near infrared reflectance. We have investigated the potential of determining water turbidity from additional remote sensing sources, namely airborne hyperspectral imagery and single wavelength bathymetric LiDAR (Light Detection and Ranging). The confluence area of the Blue and Colorado River, CO was utilized as a study area to investigate the capabilities of both airborne bathymetric LiDAR and hyperspectral imagery for water turbidity estimation. Discrete and full waveform bathymetric data were collected using Optech's Gemini (1064 nm) and Aquarius (532 nm) LiDAR sensors. Hyperspectral imagery (1.2 m pixel resolution and 72 spectral bands) was acquired using an ITRES CASI-1500 imaging system. As an independent reference, measurements of turbidity were collected concurrent with the airborne remote sensing acquisitions, using a WET Labs EcoTriplet deployed from a kayak and turbidity was then derived from the measured backscatter. The bathymetric full waveform dataset contains a discretized sample of the full backscatter of water column and benthic layer. Therefore, the full waveform records encapsulate the water column characteristics of turbidity. A nonparametric support vector regression method is utilized to estimate water turbidity from both hyperspectral imagery and voxelized full waveform LiDAR returns, both individually and as a fused dataset. Results of all the evaluations will be presented, showing an initial turbidity prediction accuracy of approximately 1.0 NTU. We will also discuss our future strategy for enhanced fusion of the full waveform LiDAR and hyperspectral imagery for improved turbidity estimation.

  4. Estimating Above Ground Biomass using LiDAR in the Northcoast Redwood Forests

    NASA Astrophysics Data System (ADS)

    Rao, M.; Stewart, E.

    2010-12-01

    In recent years, LiDAR (Light Intensity Detection Amplification and Ranging) is increasingly being used in estimating biophysical parameters related to forested environments. The main goal of the project is to estimate long-term biomass accumulation and carbon sequestration potential of the redwoods ecosystem. The project objectives are aimed at providing an assessment of carbon pools within the redwood ecosystem. Specifically, we intend to develop a relational model based on LiDAR-based canopy estimates and extensive ground-based measurements available for the old-growth redwood forest located within the Prairie Creek Redwoods State Park, CA. Our preliminary analysis involved developing a geospatial database, including LiDAR data collected in 2007 for the study site, and analyzing the data using USFS Fusion software. The study area comprised of a 12-acres section of coastal redwood (Sequoia sempervirens) in the Prairie Creek Redwoods State Park, located in Orick, CA. A series of analytical steps were executed using the USFS FUSION software to produce some intermediate data such as bare earth model, canopy height model, canopy coverage model, and canopy maxima treelist. Canopy maxima tree tops were compared to ground layer to determine height of tree tops. A total of over 1000 trees were estimated, and then with thinning (to eliminate errors due to low vegetation > 3 meters tall), a total of 950 trees were delineated. Ground measurements were imported as a point based shapefile and then compared to the treetop heights created from LiDAR data to the actual ground referenced data. The results were promising as most estimated treetops were within 1-3 meters of the ground measurements and generally within 3-5m of the actual tree height. Finally, we are in the process of applying some allometric equations to estimate above ground biomass using some of the LiDAR-derived canopy metrics.

  5. Characterizing Wildlife Habitat With LiDAR Data: Distribution Mapping Of Snags And Understory Shrubs

    NASA Astrophysics Data System (ADS)

    Martinuzzi, S.; Vierling, L.; Gould, W.; Falkowski, M.; Evans, J.; Hudak, A.; Vierling, K.

    2008-12-01

    Spatial data about the distribution of snags and understory shrubs is a major need for managing wildlife habitat in forests. We are evaluating the use of discrete return LiDAR data for predicting the distribution (presence/absence) of understory shrubs and different classes (i.e. diameters) of snags, in a managed, mixed-conifer forest in Northern Idaho, US. We are using a variety of ground and vegetation metrics derived from LiDAR data and the Random Forest algorithm to build our distribution models, and have obtained overall accuracies >80%. These preliminary results indicate that LiDAR data are valuable for predicting the distribution of understory shrubs and common snag diameter classes in the study area. In particular, LiDAR-derived metrics allow us to 1) quantify a variety of ecological factors (e.g. canopy structure, topography) that are known to influence the distribution and abundance of understory vegetation and snags in temperate, mountainous forests, and 2) quantify structural characteristics that are known to directly or indirectly indicate the presence of our classes of interest, such as the percent of vegetation returns in the lower strata of the canopy (for the shrubs), and the structural heterogeneity of the forest canopy (for the snags). Finally, and in order to further evaluate the use of LiDAR data for characterizing wildlife habitat, we integrate our maps of snags and shrubs distribution into models of habitat suitability, using four avian species (i.e. three woodpeckers and a flycatcher) as a case study.

  6. Applying a weighted random forests method to extract karst sinkholes from LiDAR data

    NASA Astrophysics Data System (ADS)

    Zhu, Junfeng; Pierskalla, William P.

    2016-02-01

    Detailed mapping of sinkholes provides critical information for mitigating sinkhole hazards and understanding groundwater and surface water interactions in karst terrains. LiDAR (Light Detection and Ranging) measures the earth's surface in high-resolution and high-density and has shown great potentials to drastically improve locating and delineating sinkholes. However, processing LiDAR data to extract sinkholes requires separating sinkholes from other depressions, which can be laborious because of the sheer number of the depressions commonly generated from LiDAR data. In this study, we applied the random forests, a machine learning method, to automatically separate sinkholes from other depressions in a karst region in central Kentucky. The sinkhole-extraction random forest was grown on a training dataset built from an area where LiDAR-derived depressions were manually classified through a visual inspection and field verification process. Based on the geometry of depressions, as well as natural and human factors related to sinkholes, 11 parameters were selected as predictive variables to form the dataset. Because the training dataset was imbalanced with the majority of depressions being non-sinkholes, a weighted random forests method was used to improve the accuracy of predicting sinkholes. The weighted random forest achieved an average accuracy of 89.95% for the training dataset, demonstrating that the random forest can be an effective sinkhole classifier. Testing of the random forest in another area, however, resulted in moderate success with an average accuracy rate of 73.96%. This study suggests that an automatic sinkhole extraction procedure like the random forest classifier can significantly reduce time and labor costs and makes its more tractable to map sinkholes using LiDAR data for large areas. However, the random forests method cannot totally replace manual procedures, such as visual inspection and field verification.

  7. LiDAR-IMU Time Delay Calibration Based on Iterative Closest Point and Iterated Sigma Point Kalman Filter.

    PubMed

    Liu, Wanli

    2017-03-08

    The time delay calibration between Light Detection and Ranging (LiDAR) and Inertial Measurement Units (IMUs) is an essential prerequisite for its applications. However, the correspondences between LiDAR and IMU measurements are usually unknown, and thus cannot be computed directly for the time delay calibration. In order to solve the problem of LiDAR-IMU time delay calibration, this paper presents a fusion method based on iterative closest point (ICP) and iterated sigma point Kalman filter (ISPKF), which combines the advantages of ICP and ISPKF. The ICP algorithm can precisely determine the unknown transformation between LiDAR-IMU; and the ISPKF algorithm can optimally estimate the time delay calibration parameters. First of all, the coordinate transformation from the LiDAR frame to the IMU frame is realized. Second, the measurement model and time delay error model of LiDAR and IMU are established. Third, the methodology of the ICP and ISPKF procedure is presented for LiDAR-IMU time delay calibration. Experimental results are presented that validate the proposed method and demonstrate the time delay error can be accurately calibrated.

  8. LiDAR-IMU Time Delay Calibration Based on Iterative Closest Point and Iterated Sigma Point Kalman Filter

    PubMed Central

    Liu, Wanli

    2017-01-01

    The time delay calibration between Light Detection and Ranging (LiDAR) and Inertial Measurement Units (IMUs) is an essential prerequisite for its applications. However, the correspondences between LiDAR and IMU measurements are usually unknown, and thus cannot be computed directly for the time delay calibration. In order to solve the problem of LiDAR-IMU time delay calibration, this paper presents a fusion method based on iterative closest point (ICP) and iterated sigma point Kalman filter (ISPKF), which combines the advantages of ICP and ISPKF. The ICP algorithm can precisely determine the unknown transformation between LiDAR-IMU; and the ISPKF algorithm can optimally estimate the time delay calibration parameters. First of all, the coordinate transformation from the LiDAR frame to the IMU frame is realized. Second, the measurement model and time delay error model of LiDAR and IMU are established. Third, the methodology of the ICP and ISPKF procedure is presented for LiDAR-IMU time delay calibration. Experimental results are presented that validate the proposed method and demonstrate the time delay error can be accurately calibrated. PMID:28282897

  9. Development and validation of the Dimensional Anhedonia Rating Scale (DARS) in a community sample and individuals with major depression.

    PubMed

    Rizvi, Sakina J; Quilty, Lena C; Sproule, Beth A; Cyriac, Anna; Michael Bagby, R; Kennedy, Sidney H

    2015-09-30

    Anhedonia, a core symptom of Major Depressive Disorder (MDD), is predictive of antidepressant non-response. In contrast to the definition of anhedonia as a "loss of pleasure", neuropsychological studies provide evidence for multiple facets of hedonic function. The aim of the current study was to develop and validate the Dimensional Anhedonia Rating Scale (DARS), a dynamic scale that measures desire, motivation, effort and consummatory pleasure across hedonic domains. Following item selection procedures and reliability testing using data from community participants (N=229) (Study 1), the 17-item scale was validated in an online study with community participants (N=150) (Study 2). The DARS was also validated in unipolar or bipolar depressed patients (n=52) and controls (n=50) (Study 3). Principal components analysis of the 17-item DARS revealed a 4-component structure mapping onto the domains of anhedonia: hobbies, food/drink, social activities, and sensory experience. Reliability of the DARS subscales was high across studies (Cronbach's α=0.75-0.92). The DARS also demonstrated good convergent and divergent validity. Hierarchical regression analysis revealed the DARS showed additional utility over the Snaith-Hamilton Pleasure Scale (SHAPS) in predicting reward function and distinguishing MDD subgroups. These studies provide support for the reliability and validity of the DARS.

  10. Importance of High-Resolution LiDAR Data in Modeling Runoff Levels Over Impervious Surfaces

    NASA Astrophysics Data System (ADS)

    Melosh, C.; Rao, M.

    2013-12-01

    Directly connected impervious areas collect and deliver unfiltered runoff to modified and impacted waterways. Modeling water flow over the landscape is an effective method of observing drainage patterns and predicting pollutant and sediment loadings. Improved models applying high-resolution elevation data can identify key areas with high pollutant output. This is a crucial issue in the Lake Tahoe Basin where lakeshore urban development has increased and lake clarity has been declining for years. This study aims to evaluate an integrated LiDAR and GIS-based modeling approach that uses a fine-scaled ground surface and impervious surface connectivity to predict the pollutant load in the Lake Tahoe Basin This study produced a fine-scaled surface model of nine subset catchments in the South Tahoe basin, including areas of low (below 20%), medium (30% to 50%) and high (above 50%) impervious surface cover. Our method integrated LiDAR, multispectral imagery, and GIS data to develop accurate terrain models, hydrologic routing, and directly connected impervious area layers for the Lake Tahoe basin. The high-density ground and object elevation data collected using Light Detection and Ranging (LiDAR) creates an accurate picture of water flow over the land, and obstacles to the flow such as buildings. High-resolution LiDAR data was obtained from the Round 10 Lake Tahoe Southern Nevada Public Land Management capital program from the year 2010. This data was processed to create a digital elevation model of the ground surface. Land use classification used object height information from the LiDAR cloud, NAIP 4-band images with 1-meter resolution and a normalized difference vegetation index image derived from the NAIP imagery. The US Army Core of Engineers hydrologic modeling system (HEC-HMS) will be used to model runoff. Based on long-term simulations the effect of directly connected impervious area on rainfall-runoff characteristics for the South Lake Tahoe catchments will be

  11. Investigating the spatial distribution of water levels in the Mackenzie Delta using airborne LiDAR

    USGS Publications Warehouse

    Hopkinson, C.; Crasto, N.; Marsh, P.; Forbes, D.; Lesack, L.

    2011-01-01

    Airborne light detection and ranging (LiDAR) data were used to map water level (WL) and hydraulic gradients (??H/??x) in the Mackenzie Delta. The LiDAR WL data were validated against eight independent hydrometric gauge measurements and demonstrated mean offsets from - 0??22 to + 0??04 m (??< 0??11). LiDAR-based WL gradients could be estimated with confidence over channel lengths exceeding 5-10 km where the WL change exceeded local noise levels in the LiDAR data. For the entire Delta, the LiDAR sample coverage indicated a rate of change in longitudinal gradient (??2H/??x) of 5??5 ?? 10-10 m m-2; therefore offering a potential means to estimate average flood stage hydraulic gradient for areas of the Delta not sampled or monitored. In the Outer Delta, within-channel and terrain gradient measurements all returned a consistent estimate of - 1 ?? 10-5 m m-1, suggesting that this is a typical hydraulic gradient for the downstream end of the Delta. For short reaches (<10 km) of the Peel and Middle Channels in the middle of the Delta, significant and consistent hydraulic gradient estimates of - 5 ?? 10-5 m m-1 were observed. Evidence that hydraulic gradients can vary over short distances, however, was observed in the Peel Channel immediately upstream of Aklavik. A positive elevation anomaly (bulge) of > 0??1 m was observed at a channel constriction entering a meander bend, suggesting a localized modification of the channel hydraulics. Furthermore, water levels in the anabranch channels of the Peel River were almost 1 m higher than in Middle Channel of the Mackenzie River. This suggests: (i) the channels are elevated and have shallower bank heights in this part of the delta, leading to increased cross-delta and along-channel hydraulic gradients; and/or (ii) a proportion of the Peel River flow is lost to Middle Channel due to drainage across the delta through anastamosing channels. This study has demonstrated that airborne LiDAR data contain valuable information describing

  12. DArT markers: diversity analyses, genomes comparison, mapping and integration with SSR markers in Triticum monococcum

    PubMed Central

    Jing, Hai-Chun; Bayon, Carlos; Kanyuka, Kostya; Berry, Simon; Wenzl, Peter; Huttner, Eric; Kilian, Andrzej; E Hammond-Kosack, Kim

    2009-01-01

    Background Triticum monococcum (2n = 2x = 14) is an ancient diploid wheat with many useful traits and is used as a model for wheat gene discovery. DArT (Diversity Arrays Technology) employs a hybridisation-based approach to type thousands of genomic loci in parallel. DArT markers were developed for T. monococcum to assess genetic diversity, compare relationships with hexaploid genomes, and construct a genetic linkage map integrating DArT and microsatellite markers. Results A DArT array, consisting of 2304 hexaploid wheat, 1536 tetraploid wheat, 1536 T. monococcum as well as 1536 T. boeoticum representative genomic clones, was used to fingerprint 16 T. monococcum accessions of diverse geographical origins. In total, 846 polymorphic DArT markers were identified, of which 317 were of T. monococcum origin, 246 of hexaploid, 157 of tetraploid, and 126 of T. boeoticum genomes. The fingerprinting data indicated that the geographic origin of T. monococcum accessions was partially correlated with their genetic variation. DArT markers could also well distinguish the genetic differences amongst a panel of 23 hexaploid wheat and nine T. monococcum genomes. For the first time, 274 DArT markers were integrated with 82 simple sequence repeat (SSR) and two morphological trait loci in a genetic map spanning 1062.72 cM in T. monococcum. Six chromosomes were represented by single linkage groups, and chromosome 4Am was formed by three linkage groups. The DArT and SSR genetic loci tended to form independent clusters along the chromosomes. Segregation distortion was observed for one third of the DArT loci. The Ba (black awn) locus was refined to a 23.2 cM region between the DArT marker locus wPt-2584 and the microsatellite locus Xgwmd33 on 1Am; and the Hl (hairy leaf) locus to a 4.0 cM region between DArT loci 376589 and 469591 on 5Am. Conclusion DArT is a rapid and efficient approach to develop many new molecular markers for genetic studies in T. monococcum. The constructed genetic

  13. Evaluation of hyperspectral LiDAR for monitoring rice leaf nitrogen by comparison with multispectral LiDAR and passive spectrometer

    NASA Astrophysics Data System (ADS)

    Sun, Jia; Shi, Shuo; Gong, Wei; Yang, Jian; Du, Lin; Song, Shalei; Chen, Biwu; Zhang, Zhenbing

    2017-01-01

    Fast and nondestructive assessment of leaf nitrogen concentration (LNC) is critical for crop growth diagnosis and nitrogen management guidance. In the last decade, multispectral LiDAR (MSL) systems have promoted developments in the earth and ecological sciences with the additional spectral information. With more wavelengths than MSL, the hyperspectral LiDAR (HSL) system provides greater possibilities for remote sensing crop physiological conditions. This study compared the performance of ASD FieldSpec Pro FR, MSL, and HSL for estimating rice (Oryza sativa) LNC. Spectral reflectance and biochemical composition were determined in rice leaves of different cultivars (Yongyou 4949 and Yangliangyou 6) throughout two growing seasons (2014–2015). Results demonstrated that HSL provided the best indicator for predicting rice LNC, yielding a coefficient of determination (R2) of 0.74 and a root mean square error of 2.80 mg/g with a support vector machine, similar to the performance of ASD (R2 = 0.73). Estimation of rice LNC could be significantly improved with the finer spectral resolution of HSL compared with MSL (R2 = 0.56).

  14. Evaluation of hyperspectral LiDAR for monitoring rice leaf nitrogen by comparison with multispectral LiDAR and passive spectrometer

    PubMed Central

    Sun, Jia; Shi, Shuo; Gong, Wei; Yang, Jian; Du, Lin; Song, Shalei; Chen, Biwu; Zhang, Zhenbing

    2017-01-01

    Fast and nondestructive assessment of leaf nitrogen concentration (LNC) is critical for crop growth diagnosis and nitrogen management guidance. In the last decade, multispectral LiDAR (MSL) systems have promoted developments in the earth and ecological sciences with the additional spectral information. With more wavelengths than MSL, the hyperspectral LiDAR (HSL) system provides greater possibilities for remote sensing crop physiological conditions. This study compared the performance of ASD FieldSpec Pro FR, MSL, and HSL for estimating rice (Oryza sativa) LNC. Spectral reflectance and biochemical composition were determined in rice leaves of different cultivars (Yongyou 4949 and Yangliangyou 6) throughout two growing seasons (2014–2015). Results demonstrated that HSL provided the best indicator for predicting rice LNC, yielding a coefficient of determination (R2) of 0.74 and a root mean square error of 2.80 mg/g with a support vector machine, similar to the performance of ASD (R2 = 0.73). Estimation of rice LNC could be significantly improved with the finer spectral resolution of HSL compared with MSL (R2 = 0.56). PMID:28091610

  15. Evaluation of hyperspectral LiDAR for monitoring rice leaf nitrogen by comparison with multispectral LiDAR and passive spectrometer.

    PubMed

    Sun, Jia; Shi, Shuo; Gong, Wei; Yang, Jian; Du, Lin; Song, Shalei; Chen, Biwu; Zhang, Zhenbing

    2017-01-16

    Fast and nondestructive assessment of leaf nitrogen concentration (LNC) is critical for crop growth diagnosis and nitrogen management guidance. In the last decade, multispectral LiDAR (MSL) systems have promoted developments in the earth and ecological sciences with the additional spectral information. With more wavelengths than MSL, the hyperspectral LiDAR (HSL) system provides greater possibilities for remote sensing crop physiological conditions. This study compared the performance of ASD FieldSpec Pro FR, MSL, and HSL for estimating rice (Oryza sativa) LNC. Spectral reflectance and biochemical composition were determined in rice leaves of different cultivars (Yongyou 4949 and Yangliangyou 6) throughout two growing seasons (2014-2015). Results demonstrated that HSL provided the best indicator for predicting rice LNC, yielding a coefficient of determination (R(2)) of 0.74 and a root mean square error of 2.80 mg/g with a support vector machine, similar to the performance of ASD (R(2) = 0.73). Estimation of rice LNC could be significantly improved with the finer spectral resolution of HSL compared with MSL (R(2) = 0.56).

  16. LiDAR Point Cloud and Stereo Image Point Cloud Fusion

    DTIC Science & Technology

    2013-09-01

    Photogrammetry , Fusion, Accuracy 15. NUMBER OF PAGES 81 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION...similar to those of Photogrammetry . In Photogrammetry , the objective is to extract precision three-dimensional representations of the earth’s surface...knowledge problems. 4 The history of LiDAR and photogrammetry fusion shows that many individuals with diverse interests are studying this problem

  17. Use of LiDAR to Assist in Delineating Waters of the United States, Including Wetlands

    DTIC Science & Technology

    2014-03-01

    position in the land- scape. Wetness indices are often calculated using the general formula WI = ln(A/tanβ) where A is the catchment area (m2/m...delineations of an Ordinary High Water Mark (OHWM) boundary, LiDAR data or products may be used to view the OHWM signature across a project area ...view vegeta- tive, topographic, and hydrologic patterns across a project area and to focus the investigation on transitional areas . They cannot

  18. Estimating Volume, Biomass, and Carbon in Hedmark County, Norway Using a Profiling LiDAR

    NASA Technical Reports Server (NTRS)

    Nelson, Ross; Naesset, Erik; Gobakken, T.; Gregoire, T.; Stahl, G.

    2009-01-01

    A profiling airborne LiDAR is used to estimate the forest resources of Hedmark County, Norway, a 27390 square kilometer area in southeastern Norway on the Swedish border. One hundred five profiling flight lines totaling 9166 km were flown over the entire county; east-west. The lines, spaced 3 km apart north-south, duplicate the systematic pattern of the Norwegian Forest Inventory (NFI) ground plot arrangement, enabling the profiler to transit 1290 circular, 250 square meter fixed-area NFI ground plots while collecting the systematic LiDAR sample. Seven hundred sixty-three plots of the 1290 plots were overflown within 17.8 m of plot center. Laser measurements of canopy height and crown density are extracted along fixed-length, 17.8 m segments closest to the center of the ground plot and related to basal area, timber volume and above- and belowground dry biomass. Linear, nonstratified equations that estimate ground-measured total aboveground dry biomass report an R(sup 2) = 0.63, with an regression RMSE = 35.2 t/ha. Nonstratified model results for the other biomass components, volume, and basal area are similar, with R(sup 2) values for all models ranging from 0.58 (belowground biomass, RMSE = 8.6 t/ha) to 0.63. Consistently, the most useful single profiling LiDAR variable is quadratic mean canopy height, h (sup bar)(sub qa). Two-variable models typically include h (sup bar)(sub qa) or mean canopy height, h(sup bar)(sub a), with a canopy density or a canopy height standard deviation measure. Stratification by productivity class did not improve the nonstratified models, nor did stratification by pine/spruce/hardwood. County-wide profiling LiDAR estimates are reported, by land cover type, and compared to NFI estimates.

  19. Mapping Vegetation Canopy Structure and Distribution for Great Smoky Mountains National Park Using LiDAR

    NASA Astrophysics Data System (ADS)

    Weiner, J.; Kumar, J.; Norman, S. P.

    2015-12-01

    A major challenge in forest management is the inaccessibility of large swaths of land, which makes accurate monitoring of forest change difficult. Remote sensing methods can help address this issue by allowing investigators to monitor remote or inaccessible regions using aerial or satellite-based platforms. However, most remote sensing methods do not provide a full three-dimensional (3D) description of the area. Rather, they return only a single elevation point or landcover description. Multiple-return LiDAR (Light Detection and Ranging) gathers data in a 3D point cloud, which allows forest managers to more accurately characterize and monitor changes in canopy structure and vegetation-type distribution. Our project used high-resolution aerial multiple-return LiDAR data to determine vegetation canopy structures and their spatial distribution in Great Smoky Mountains National Park. To ensure sufficient data density and to match LANDSAT resolution, we gridded the data into 30m x 30m cells. The LiDAR data points within each cell were then used to generate the vertical canopy structure for that cell. After vertical profiles had been created, we used a k-means cluster analysis algorithm to classify the landscape based on the canopy structure. The spatial distribution of distinct and unique canopy structures was mapped across the park and compared to a vegetation-type map to determine the correlation of canopy structure to vegetation types. Preliminary analysis conducted at a number of phenology sites maintained by the Great Smoky Mountains Institute at Tremont shows strong correspondence between canopy structure and vegetation type. However, more validation is needed in other regions of the park to establish this method as a reliable tool. LiDAR data has a unique ability to map full 3D structures of vegetation and the methods developed in this project offer an extensible tool for forest mapping and monitoring.

  20. Combining LiDAR and IKONOS data for eco-hydrological classification of an ombrotrophic peatland.

    PubMed

    Anderson, K; Bennie, J J; Milton, E J; Hughes, P D M; Lindsay, R; Meade, R

    2010-01-01

    Remote sensing techniques have potential for peatland monitoring, but most previous work has focused on spectral approaches that often result in poor discrimination of cover types and neglect structural information. Peatlands contain structural "microtopes" (e.g., hummocks and hollows) which are linked to hydrology, biodiversity and carbon sequestration, and information on surface structure is thus a useful proxy for peatland condition. The objective of this work was to develop and test a new eco-hydrological mapping technique for ombrotrophic (rain-fed) peatlands using a combined spectral-structural remote sensing approach. The study site was Wedholme Flow, Cumbria, UK. Airborne light dectection and ranging (LiDAR) data were used with IKONOS data in a combined multispectral-structural approach for mapping peatland condition classes. LiDAR data were preprocessed so that spatial estimates of minimum and maximum land surface height, variance and semi-variance (from semi-variogram analysis) were extracted. These were assimilated alongside IKONOS data into a maximum likelihood classification procedure, and thematic outputs were compared. Ecological survey data were used to validate the results. Considerable improvements in thematic separation of peatland classes were achieved when spatially-distributed measurements of LiDAR variance or semi-variance were included. Specifically, the classification accuracy improved from 71.8% (IKONOS data only) to 88.0% when a LiDAR semi-variance product was used. Of note was the improved delineation of management classes (including Eriophorum bog, active raised bog and degraded raised bog). The application of a combined textural-optical approach can improve land cover mapping in areas where reliance on purely spectral discrimination approaches would otherwise result in considerable thematic uncertainty.

  1. Flying Under the LiDAR: Relating Forest Structure to Bat Community Diversity

    NASA Astrophysics Data System (ADS)

    Swanson, A. C.; Weishampel, J. F.

    2015-12-01

    Bats are important to many ecological processes such as pollination, insect (and by proxy, disease) control, and seed dispersal and can be used to monitor ecosystem health. However, they are facing unprecedented extinction risks from habitat degradation as well as pressures from pathogens (e.g., white-nose syndrome) and wind turbines. LiDAR allows ecologists to measure structural variables of forested landscapes with increased precision and accuracy at broader spatial scales than previously possible. This study used airborne LiDAR to classify forest habitat/canopy structure at the Ordway-Swisher Biological Station (OSBS) in north central Florida. LiDAR data were acquired by the NEON airborne observation platform in summer 2014. OSBS consists of open-canopy pine savannas, closed-canopy hardwood hammocks, and seasonally wet prairies. Multiple forest structural parameters (e.g., mean, maximum, and standard deviation of height returns) were derived from LiDAR point clouds using the USDA software program FUSION. K-means clustering was used to segregate each 5x5 m raster across the ~3765 ha OSBS area into six different clusters based on the derived canopy metrics. Cluster averages for maximum, mean, and standard deviation of return heights ranged from 0 to 19.4 m, 0 to 15.3 m, and 0 to 3.0 m, respectively. To determine the relationships among these landscape-canopy features and bat species diversity and abundances, AnaBat II bat detectors were deployed from May to September in 2015 stratified by these distinct clusters. Bat calls were recorded from sunset to sunrise during each sampling period. Species were identified using AnalookW. A statistical regression model selection approach was performed in order to evaluate how forest attributes such as understory clutter, open regions, open and closed canopy, etc. influence bat communities. This knowledge provides a deeper understanding of habitat-species interactions to better manage survival of these species.

  2. Road centerline extraction from airborne LiDAR point cloud based on hierarchical fusion and optimization

    NASA Astrophysics Data System (ADS)

    Hui, Zhenyang; Hu, Youjian; Jin, Shuanggen; Yevenyo, Yao Ziggah

    2016-08-01

    Road information acquisition is an important part of city informatization construction. Airborne LiDAR provides a new means of acquiring road information. However, the existing road extraction methods using LiDAR point clouds always decide the road intensity threshold based on experience, which cannot obtain the optimal threshold to extract a road point cloud. Moreover, these existing methods are deficient in removing the interference of narrow roads and several attached areas (e.g., parking lot and bare ground) to main roads extraction, thereby imparting low completeness and correctness to the city road network extraction result. Aiming at resolving the key technical issues of road extraction from airborne LiDAR point clouds, this paper proposes a novel method to extract road centerlines from airborne LiDAR point clouds. The proposed approach is mainly composed of three key algorithms, namely, Skewness balancing, Rotating neighborhood, and Hierarchical fusion and optimization (SRH). The skewness balancing algorithm used for the filtering was adopted as a new method for obtaining an optimal intensity threshold such that the "pure" road point cloud can be obtained. The rotating neighborhood algorithm on the other hand was developed to remove narrow roads (corridors leading to parking lots or sidewalks), which are not the main roads to be extracted. The proposed hierarchical fusion and optimization algorithm caused the road centerlines to be unaffected by certain attached areas and ensured the road integrity as much as possible. The proposed method was tested using the Vaihingen dataset. The results demonstrated that the proposed method can effectively extract road centerlines in a complex urban environment with 91.4% correctness and 80.4% completeness.

  3. Fast Surface Reconstruction and Segmentation with Terrestrial LiDAR Range Data

    DTIC Science & Technology

    2009-05-18

    SUPPLEMENTARY NOTES 14. ABSTRACT Recent advances in range measurement devices have opened up new opportunities and challenges for fast 3D modeling of...which are composed of partially ordered terrestrial range data. Our algorithms can be applied to a large class of LiDAR data acquisition systems, where...obtained by two different terrestrial acquisition systems. The first dataset contains 94 million points obtained by a vehicle-borne acquisition system

  4. Abu Dhabi Basemap Update Using the LiDAR Mobile Mapping Technology

    NASA Astrophysics Data System (ADS)

    Alshaiba, Omar; Amparo Núñez-Andrés, M.; Lantada, Nieves

    2016-04-01

    Mobile LiDAR system provides a new technology which can be used to update geospatial information by direct and rapid data collection. This technology is faster than the traditional survey ways and has lower cost. Abu Dhabi Municipal System aims to update its geospatial system frequently as the government entities have invested heavily in GIS technology and geospatial data to meet the repaid growth in the infrastructure and construction projects in recent years. The Emirate of Abu Dhabi has witnessed a huge growth in infrastructure and construction projects in recent years. Therefore, it is necessary to develop and update its basemap system frequently to meet their own organizational needs. Currently, the traditional ways are used to update basemap system such as human surveyors, GPS receivers and controller (GPS assigned computer). Then the surveyed data are downloaded, edited and reviewed manually before it is merged to the basemap system. Traditional surveying ways may not be applicable in some conditions such as; bad weather, difficult topographic area and boundary area. This paper presents a proposed methodology which uses the Mobile LiDAR system to update basemap in Abu Dhabi by using daily transactions services. It aims to use and integrate the mobile LiDAR technology into the municipality's daily workflow such that it becomes the new standard cost efficiency operating procedure for updating the base-map in Abu Dhabi Municipal System. On another note, the paper will demonstrate the results of the innovated workflow for the base-map update using the mobile LiDAR point cloud and few processing algorithms.

  5. 3D turbulence measurements in inhomogeneous boundary layers with three wind LiDARs

    NASA Astrophysics Data System (ADS)

    Carbajo Fuertes, Fernando; Valerio Iungo, Giacomo; Porté-Agel, Fernando

    2014-05-01

    One of the most challenging tasks in atmospheric anemometry is obtaining reliable turbulence measurements of inhomogeneous boundary layers at heights or in locations where is not possible or convenient to install tower-based measurement systems, e.g. mountainous terrain, cities, wind farms, etc. Wind LiDARs are being extensively used for the measurement of averaged vertical wind profiles, but they can only successfully accomplish this task under the limiting conditions of flat terrain and horizontally homogeneous flow. Moreover, it has been shown that common scanning strategies introduce large systematic errors in turbulence measurements, regardless of the characteristics of the flow addressed. From the point of view of research, there exist a variety of techniques and scanning strategies to estimate different turbulence quantities but most of them rely in the combination of raw measurements with atmospheric models. Most of those models are only valid under the assumption of horizontal homogeneity. The limitations stated above can be overcome by a new triple LiDAR technique which uses simultaneous measurements from three intersecting Doppler wind LiDARs. It allows for the reconstruction of the three-dimensional velocity vector in time as well as local velocity gradients without the need of any turbulence model and with minimal assumptions [EGU2013-9670]. The triple LiDAR technique has been applied to the study of the flow over the campus of EPFL in Lausanne (Switzerland). The results show the potential of the technique for the measurement of turbulence in highly complex boundary layer flows. The technique is particularly useful for micrometeorology and wind engineering studies.

  6. Step by step error assessment in braided river sediment budget using airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Lallias-Tacon, S.; Liébault, F.; Piégay, H.

    2014-06-01

    Sequential airborne LiDAR surveys were used to reconstruct the sediment budget of a 7-km-long braided river channel in southeastern France following a 14-year return period flood and to improve its accuracy step by step. Data processing involved (i) surface matching of the sequential point clouds, (ii) spatially distributed propagation of uncertainty based on surface conditions of the channel, and (iii) water depth subtraction from the digital elevation models based on water depths measured in the field. The respective influence of each processing step on sediment budget computation was systematically documented. This showed that surface matching and water depth subtraction both have a considerable effect on the net sediment budget. Although DEM of difference thresholding based on uncertainty analysis on absolute elevation values had a smaller effect on the sediment budget, this step is crucial for the production of a comprehensive map of channel deformations. A large independent data set of RTK-GPS checkpoints was used to control the quality of the LiDAR altimetry. The results showed that high density (7-9 points/m2) airborne LiDAR surveys can provide a very high level of detection of elevation changes on the exposed surfaces of the channel, with a 95% confidence interval level of detection between 19 and 30 cm. Change detection from LiDAR data revealed that 54% of the pre-flood active channel was reworked by the flood. The braided channel pattern was highly disturbed by the flood owing to the occurrence of several channel avulsions.

  7. Evaluation of Landslide Mapping Techniques and LiDAR-based Conditioning Factors

    NASA Astrophysics Data System (ADS)

    Mahalingam, R.; Olsen, M. J.

    2014-12-01

    Landslides are a major geohazard, which result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping can help communities to plan and prepare for these damaging events. Mapping landslide susceptible locations using GIS and remote sensing techniques is gaining popularity in the past three decades. These efforts use a wide variety of procedures and consider a wide range of factors. Unfortunately, each study is often completed differently and independently of others. Further, the quality of the datasets used varies in terms of source, data collection, and generation, which can propagate errors or inconsistencies into the resulting output maps. Light detection and ranging (LiDAR) has proved to have higher accuracy in representing the continuous topographic surface, which can help minimize this uncertainty. The primary objectives of this paper are to investigate the applicability and performance of terrain factors in landslide hazard mapping, determine if LiDAR-derived datasets (slope, slope roughness, terrain roughness, stream power index and compound topographic index) can be used for predictive mapping without data representing other common landslide conditioning factors, and evaluate the differences in landslide susceptibility mapping using widely-used statistical approaches. The aforementioned factors were used to produce landslide susceptibility maps for a 140 km2 study area in northwest Oregon using six representative techniques: frequency ratio, weights of evidence, logistic regression, discriminant analysis, artificial neural network, and support vector machine. Most notably, the research showed an advantage in selecting fewer critical conditioning factors. The most reliable factors all could be derived from a single LiDAR DEM, reducing the need for laborious and costly data gathering. Most of the six techniques showed similar statistical results; however, ANN showed less accuracy for predictive mapping. Keywords : LiDAR

  8. Multispectral Airborne Mapping LiDAR Observations of the McMurdo Dry Valleys

    NASA Astrophysics Data System (ADS)

    Fernandez Diaz, J. C.; Fountain, A. G.; Morin, P. J.; Singhania, A.; Hauser, D.; Obryk, M.; Shrestha, R. L.; Carter, W. E.; Sartori, M. P.

    2015-12-01

    Field observations have documented dramatic changes over the past decade in the McMurdo Dry Valleys of Antarctica: extreme river incisions, significant glacier loss, and the appearance of numerous thermokarst slumps. To date these observations have been sporadic and localized, and have not been able to capture change on a valley-wide scale. During the 2014-2015 Antarctic summer season, specifically between December 4th, 2014 and January 19th, 2015, we undertook a widescale airborne laser mapping campaign to collect a baseline digital elevation model for 3500 km2 area of the Dry Valleys and other areas of interest. The airborne LiDAR observations were acquired with a novel multi-spectral LiDAR sensor with active laser observations at three light wavelengths (532 nm, 1064 nm, and 1550 nm) simultaneously; which not only allowed the generation of a high resolution elevation model of the area, but also provides multispectral signatures for observed terrain features. In addition to the LiDAR data, high resolution (5-15 cm pixels) digital color images were collected. During the six week survey campaign of the Dry Valleys a total of 30 flights were performed, in which about 20 billion LiDAR returns and 21,000 60-Mpixels images were collected. The primary objective of this project is to perform a topographic change detection analysis by comparing the recently acquired dataset to a lower resolution dataset collected by NASA in the 2001-2002 season. This presentation will describe the processing and analysis of this significant mapping dataset and will provide some initial observations from the high resolution topography acquired.

  9. NASA Goddards LiDAR, Hyperspectral and Thermal (G-LiHT) Airborne Imager

    NASA Technical Reports Server (NTRS)

    Cook, Bruce D.; Corp, Lawrence A.; Nelson, Ross F.; Middleton, Elizabeth M.; Morton, Douglas C.; McCorkel, Joel T.; Masek, Jeffrey G.; Ranson, Kenneth J.; Ly, Vuong; Montesano, Paul M.

    2013-01-01

    The combination of LiDAR and optical remotely sensed data provides unique information about ecosystem structure and function. Here, we describe the development, validation and application of a new airborne system that integrates commercial off the shelf LiDAR hyperspectral and thermal components in a compact, lightweight and portable system. Goddard's LiDAR, Hyperspectral and Thermal (G-LiHT) airborne imager is a unique system that permits simultaneous measurements of vegetation structure, foliar spectra and surface temperatures at very high spatial resolution (approximately 1 m) on a wide range of airborne platforms. The complementary nature of LiDAR, optical and thermal data provide an analytical framework for the development of new algorithms to map plant species composition, plant functional types, biodiversity, biomass and carbon stocks, and plant growth. In addition, G-LiHT data enhance our ability to validate data from existing satellite missions and support NASA Earth Science research. G-LiHT's data processing and distribution system is designed to give scientists open access to both low- and high-level data products (http://gliht.gsfc.nasa.gov), which will stimulate the community development of synergistic data fusion algorithms. G-LiHT has been used to collect more than 6,500 km2 of data for NASA-sponsored studies across a broad range of ecoregions in the USA and Mexico. In this paper, we document G-LiHT design considerations, physical specifications, instrument performance and calibration and acquisition parameters. In addition, we describe the data processing system and higher-level data products that are freely distributed under NASA's Data and Information policy.

  10. Reduction of training costs using active classification in fused hyperspectral and LiDAR data

    NASA Astrophysics Data System (ADS)

    Wuttke, Sebastian; Schilling, Hendrik; Middelmann, Wolfgang

    2012-11-01

    This paper presents a novel approach for the reduction of training costs in classification with co-registered hyperspectral (HS) and Light Detection and Ranging (LiDAR) data using an active classification framework. Fully automatic classification can be achieved by unsupervised learning, which is not suited for adjustment to specific classes. On the other hand, supervised classification with predefined classes needs a lot of training examples, which need to be labeled with the ground truth, usually at a significant cost. The concept of active classification alleviates these problems by the use of a selection strategy: only selected samples are ground truth labeled and used as training data. One common selection strategy is to incorporate in a first step the current state of the classification algorithm and choose only the examples for which the expected information gain is maximized. In the second step a conventional classification algorithm is trained using this data. By alternating between these two steps the algorithm reaches high classification accuracy results with less training samples and therefore lower training costs. The approach presented in this paper involves the user in the active selection strategy and the k-NN algorithm is chosen for classification. The results further benefit from fusing the heterogeneous information of HS and LiDAR data within the classification algorithm. For this purpose, several HS features, such as vegetation indices, and LiDAR features, such as relative height and roughness, are extracted. This increases the separability between different classes and reduces the dimensionality of the HS data. The practicability and performance of this framework is shown for the detection and separation of different kinds of vegetation, e.g. trees and grass in an urban area of Berlin. The HS data was obtained by the SPECIM AISA Eagle 2 sensor, LiDAR data by Riegl LMS Q560.

  11. Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory

    USGS Publications Warehouse

    Junttila, Virpi; Finley, Andrew O.; Bradford, John B.; Kauranne, Tuomo

    2013-01-01

    Recently airborne Light Detection And Ranging (LiDAR) has emerged as a highly accurate remote sensing modality to be used in operational scale forest inventories. Inventories conducted with the help of LiDAR are most often model-based, i.e. they use variables derived from LiDAR point clouds as the predictive variables that are to be calibrated using field plots. The measurement of the necessary field plots is a time-consuming and statistically sensitive process. Because of this, current practice often presumes hundreds of plots to be collected. But since these plots are only used to calibrate regression models, it should be possible to minimize the number of plots needed by carefully selecting the plots to be measured. In the current study, we compare several systematic and random methods for calibration plot selection, with the specific aim that they be used in LiDAR based regression models for forest parameters, especially above-ground biomass. The primary criteria compared are based on both spatial representativity as well as on their coverage of the variability of the forest features measured. In the former case, it is important also to take into account spatial auto-correlation between the plots. The results indicate that choosing the plots in a way that ensures ample coverage of both spatial and feature space variability improves the performance of the corresponding models, and that adequate coverage of the variability in the feature space is the most important condition that should be met by the set of plots collected.

  12. Single Pass LiDAR-derived Estimate of Site Productivity in Western Oregon

    NASA Astrophysics Data System (ADS)

    McAdam, E.; Hilker, T.; Waring, R. H.; Sousa, C. H. R. D.; Moura, Y. M.

    2014-12-01

    Accurate estimates of forest growth at different ages are essential to evaluate the effect of a changing climate and to adjust management practices accordingly. Most current approaches are spatially discrete and therefore unable to predict forest growth accurately across landscapes. While airborne LiDAR has been widely used in forestry, it can only estimate growth rates with repeated passes. In contrast, Landsat imagery records disturbances (at 30 m resolution) but is unable to measure changes in growth rates. Historical archives of Landsat imagery provided us a way of knowing when and where even-aged stands of Pseudotsuga menziesii (Douglas-fir) were cut and replanted. Since early growth rates are nearly linear with age, the height of dominant trees recorded in one pass by LiDAR yields a direct measure of growth and likely changes as stands age under recent climatic conditions. Process-based growth models are available to assess possible shifts in the growth rates of stands under a changing climate; the accuracy of such model predictions can be evaluated with additional LiDAR coverage. In this study we use the Physiological Principles Predicting Growth Model (3-PG) to estimate site index at the landscape level to predict site productivity based on the year of stand establishment obtained from Landsat, and one-pass airborne LiDAR measurement of forest height. We are monitoring forest plantations of known ages and with data on their current age we will calculate site index for 60 separate sites across western Oregon. The results of this study will allow us to create updated site index maps for the state of Oregon under varying climate scenarios.

  13. Quantitative study of tectonic geomorphology along Haiyuan fault based on airborne LiDAR

    USGS Publications Warehouse

    Chen, Tao; Zhang, Pei Zhen; Liu, Jing; Li, Chuan You; Ren, Zhi Kun; Hudnut, Kenneth W.

    2014-01-01

    High-precision and high-resolution topography are the fundamental data for active fault research. Light detection and ranging (LiDAR) presents a new approach to build detailed digital elevation models effectively. We take the Haiyuan fault in Gansu Province as an example of how LiDAR data may be used to improve the study of active faults and the risk assessment of related hazards. In the eastern segment of the Haiyuan fault, the Shaomayin site has been comprehensively investigated in previous research because of its exemplary tectonic topographic features. Based on unprecedented LiDAR data, the horizontal and vertical coseismic offsets at the Shaomayin site are described. The measured horizontal value is about 8.6 m, and the vertical value is about 0.8 m. Using prior dating ages sampled from the same location, we estimate the horizontal slip rate as 4.0 ± 1.0 mm/a with high confidence and define that the lower bound of the vertical slip rate is 0.4 ± 0.1 mm/a since the Holocene. LiDAR data can repeat the measurements of field work on quantifying offsets of tectonic landform features quite well. The offset landforms are visualized on an office computer workstation easily, and specialized software may be used to obtain displacement quantitatively. By combining precious chronological results, the fundamental link between fault activity and large earthquakes is better recognized, as well as the potential risk for future earthquake hazards.

  14. Mapping and Monitoring Delmarva Fox Squirrel Habitat Using an Airborne LiDAR Profiler

    NASA Technical Reports Server (NTRS)

    Nelson, Ross; Ratnaswamy, Mary; Keller, Cherry

    2004-01-01

    Twenty five hundred thirty nine kilometers of airborne laser profiling and videography data were acquired over the state of Delaware during the summer of 2000. The laser ranging measurements and video from approximately one-half of that data set (1304 km) were analyzed to identify and locate forested sites that might potentially support populations of Delmarva fox squirrel (DFS, Sciurus niger cinereus). The DFS is an endangered species previously endemic to tall, dense, mature forests with open understories on the Eastern Shore of the Chesapeake Bay. The airborne LiDAR employed in this study can measure forest canopy height and canopy closure, but cannot measure or infer understory canopy conditions. Hence the LiDAR must be viewed as a tool to map potential, not actual, habitat. Fifty-three potentially suitable DFS sites were identified in the 1304 km of flight transect data. Each of the 53 sites met the following criteria according to the LiDAR and video record: (1 ) at least 120m of contiguous forest; (2) an average canopy height greater than 20m; (3) an average canopy closure of >80%; and (4) no roofs, impervious surface (e.g., asphalt, concrete), and/or open water anywhere along the 120m length of the laser segment. Thirty-two of the 53 sites were visited on the ground and measurements taken for a DFS habitat suitability model. Seventy eight percent of the sites (25 of 32) were judged by the model to be suited to supporting a DFS population. Twenty-eight of the 32 sites visited in the field were in forest cover types (hardwood, mixed wood, conifer, wetlands) according to a land cover GIS map. Of these, 23 (82%) were suited to support DFS. The remaining 4 sites were located in nonforest cover types - agricultural or residential areas. Two of the four, or 50% were suited to the DFS. All of the LiDAR flight data, 2539 km, were analyzed to

  15. Evaluation of the contribution of LiDAR data and postclassification procedures to object-based classification accuracy

    NASA Astrophysics Data System (ADS)

    Styers, Diane M.; Moskal, L. Monika; Richardson, Jeffrey J.; Halabisky, Meghan A.

    2014-01-01

    Object-based image analysis (OBIA) is becoming an increasingly common method for producing land use/land cover (LULC) classifications in urban areas. In order to produce the most accurate LULC map, LiDAR data and postclassification procedures are often employed, but their relative contributions to accuracy are unclear. We examined the contribution of LiDAR data and postclassification procedures to increase classification accuracies over using imagery alone and assessed sources of error along an ecologically complex urban-to-rural gradient in Olympia, Washington. Overall classification accuracy and user's and producer's accuracies for individual classes were evaluated. The addition of LiDAR data to the OBIA classification resulted in an 8.34% increase in overall accuracy, while manual postclassification to the imagery+LiDAR classification improved accuracy only an additional 1%. Sources of error in this classification were largely due to edge effects, from which multiple different types of errors result.

  16. Analyzing Hydro-Geomorphic Responses in Post-Fire Stream Channels with Terrestrial LiDAR

    NASA Astrophysics Data System (ADS)

    Nourbakhshbeidokhti, S.; Kinoshita, A. M.; Chin, A.

    2015-12-01

    Wildfires have potential to significantly alter soil properties and vegetation within watersheds. These alterations often contribute to accelerated erosion, runoff, and sediment transport in stream channels and hillslopes. This research applies repeated Terrestrial Laser Scanning (TLS) Light Detection and Ranging (LiDAR) to stream reaches within the Pike National Forest in Colorado following the 2012 Waldo Canyon Fire. These scans allow investigation of the relationship between sediment delivery and environmental characteristics such as precipitation, soil burn severity, and vegetation. Post-fire LiDAR images provide high resolution information of stream channel changes in eight reaches for three years (2012-2014). All images are processed with RiSCAN PRO to remove vegetation and triangulated and smoothed to create a Digital Elevation Model (DEM) with 0.1 m resolution. Study reaches with two or more successive DEM images are compared using a differencing method to estimate the volume of sediment erosion and deposition. Preliminary analysis of four channel reaches within Williams Canyon and Camp Creek yielded erosion estimates between 0.035 and 0.618 m3 per unit area. Deposition was estimated as 0.365 to 1.67 m3 per unit area. Reaches that experienced higher soil burn severity or larger rainfall events produced the greatest geomorphic changes. Results from LiDAR analyses can be incorporated into post-fire hydrologic models to improve estimates of runoff and sediment yield. These models will, in turn, provide guidance for water resources management and downstream hazards mitigation.

  17. Automated object detection and tracking with a flash LiDAR system

    NASA Astrophysics Data System (ADS)

    Hammer, Marcus; Hebel, Marcus; Arens, Michael

    2016-10-01

    The detection of objects, or persons, is a common task in the fields of environment surveillance, object observation or danger defense. There are several approaches for automated detection with conventional imaging sensors as well as with LiDAR sensors, but for the latter the real-time detection is hampered by the scanning character and therefore by the data distortion of most LiDAR systems. The paper presents a solution for real-time data acquisition of a flash LiDAR sensor with synchronous raw data analysis, point cloud calculation, object detection, calculation of the next best view and steering of the pan-tilt head of the sensor. As a result the attention is always focused on the object, independent of the behavior of the object. Even for highly volatile and rapid changes in the direction of motion the object is kept in the field of view. The experimental setup used in this paper is realized with an elementary person detection algorithm in medium distances (20 m to 60 m) to show the efficiency of the system for objects with a high angular speed. It is easy to replace the detection part by any other object detection algorithm and thus it is easy to track nearly any object, for example a car or a boat or an UAV in various distances.

  18. Geodetic imaging with airborne LiDAR: the Earth's surface revealed.

    PubMed

    Glennie, C L; Carter, W E; Shrestha, R L; Dietrich, W E

    2013-08-01

    The past decade has seen an explosive increase in the number of peer reviewed papers reporting new scientific findings in geomorphology (including fans, channels, floodplains and landscape evolution), geologic mapping, tectonics and faulting, coastal processes, lava flows, hydrology (especially snow and runoff routing), glaciers and geo-archaeology. A common genesis of such findings is often newly available decimeter resolution 'bare Earth' geodetic images, derived from airborne laser swath mapping, a.k.a. airborne LiDAR, observations. In this paper we trace nearly a half century of advances in geodetic science made possible by space age technology, such as the invention of short-pulse-length high-pulse-rate lasers, solid state inertial measurement units, chip-based high speed electronics and the GPS satellite navigation system, that today make it possible to map hundreds of square kilometers of terrain in hours, even in areas covered with dense vegetation or shallow water. To illustrate the impact of the LiDAR observations we present examples of geodetic images that are not only stunning to the eye, but help researchers to develop quantitative models explaining how terrain evolved to its present form, and how it will likely change with time. Airborne LiDAR technology continues to develop quickly, promising ever more scientific discoveries in the years ahead.

  19. Range determination for generating point clouds from airborne small footprint LiDAR waveforms.

    PubMed

    Qin, Yuchu; Vu, Tuong Thuy; Ban, Yifang; Niu, Zheng

    2012-11-05

    This paper presents a range determination approach for generating point clouds from small footprint LiDAR waveforms. Waveform deformation over complex terrain area is simulated using convolution. Drift of the peak center position is analyzed to identify the first echo returned by the illuminated objects in the LiDAR footprint. An approximate start point of peak in the waveform is estimated and adopted as the indicator of range calculation; range correction method is proposed to correct pulse widening over complex terrain surface. The experiment was carried out on small footprint LiDAR waveform data acquired by RIEGL LMS-Q560. The results suggest that the proposed approach generates more points than standard commercial products; based on field measurements, a comparative analysis between the point clouds generated by the proposed approach and the commercial software GeocodeWF indicates that: 1). the proposed approach obtained more accurate tree heights; 2). smooth surface can be achieved with low standard deviation. In summary, the proposed approach provides a satisfactory solution for range determination in estimating 3D coordinate values of point clouds, especially for correcting range information of waveforms containing deformed peaks.

  20. Supporting Indonesia's National Forest Monitoring System with LiDAR Observations

    NASA Astrophysics Data System (ADS)

    Hagen, S. C.

    2015-12-01

    Scientists at Applied GeoSolutions, Jet Propulsion Laboratory, Winrock International, and the University of New Hampshire are working with the government of Indonesia to enhance the National Forest Monitoring System in Kalimantan, Indonesia. The establishment of a reliable, transparent, and comprehensive NFMS has been limited by a dearth of relevant data that are accurate, low-cost, and spatially resolved at subnational scales. In this NASA funded project, we are developing, evaluating, and validating several critical components of a NFMS in Kalimantan, Indonesia, focusing on the use of LiDAR and radar imagery for improved carbon stock and forest degradation information. Applied GeoSolutions and the University of New Hampshire have developed an Open Source Software package to process large amounts LiDAR data quickly, easily, and accurately. The Open Source project is called lidar2dems and includes the classification of raw LAS point clouds and the creation of Digital Terrain Models (DTMs), Digital Surface Models (DSMs), and Canopy Height Models (CHMs). Preliminary estimates of forest structure and forest damage from logging from these data sets support the idea that comprehensive, well documented, freely available software for processing LiDAR data can enable countries such as Indonesia to cost effectively monitor their forests with high precision.

  1. Motion field estimation for a dynamic scene using a 3D LiDAR.

    PubMed

    Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington

    2014-09-09

    This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively.

  2. Motion Field Estimation for a Dynamic Scene Using a 3D LiDAR

    PubMed Central

    Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington

    2014-01-01

    This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively. PMID:25207868

  3. A signal denoising method for full-waveform LiDAR data

    NASA Astrophysics Data System (ADS)

    Azadbakht, M.; Fraser, C. S.; Zhang, C.; Leach, J.

    2013-10-01

    The lack of noise reduction methods resistant to waveform distortion can hamper correct and accurate decomposition in the processing of full-waveform LiDAR data. This paper evaluates a time-domain method for smoothing and reducing the noise level in such data. The Savitzky-Golay (S-G) approach approximates and smooths data by taking advantage of fitting a polynomial of degree d, using local least-squares. As a consequence of the integration of this method with the Singular Value Decomposition (SVD) approach, and applying this filter on the singular vectors of the SVD, satisfactory denoising results can be obtained. The results of this SVD-based S-G approach have been evaluated using two different LiDAR datasets and also compared with those of other popular methods in terms of the degree of preservation of the moments of the signal and closeness to the noisy signal. The results indicate that the SVD-based S-G approach has superior performance in denoising full-waveform LiDAR data.

  4. An Efficient Method for Automatic Road Extraction Based on Multiple Features from LiDAR Data

    NASA Astrophysics Data System (ADS)

    Li, Y.; Hu, X.; Guan, H.; Liu, P.

    2016-06-01

    The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D) points with less occlusions and smaller shadows. The elevation information and surface roughness are distinguishing features to separate roads. However, LiDAR data has some disadvantages are not beneficial to object extraction, such as the irregular distribution of point clouds and lack of clear edges of roads. For these problems, this paper proposes an automatic road centerlines extraction method which has three major steps: (1) road center point detection based on multiple feature spatial clustering for separating road points from ground points, (2) local principal component analysis with least squares fitting for extracting the primitives of road centerlines, and (3) hierarchical grouping for connecting primitives into complete roads network. Compared with MTH (consist of Mean shift algorithm, Tensor voting, and Hough transform) proposed in our previous article, this method greatly reduced the computational cost. To evaluate the proposed method, the Vaihingen data set, a benchmark testing data provided by ISPRS for "Urban Classification and 3D Building Reconstruction" project, was selected. The experimental results show that our method achieve the same performance by less time in road extraction using LiDAR data.

  5. Extracting cross sections and water levels of vegetated ditches from LiDAR point clouds

    NASA Astrophysics Data System (ADS)

    Roelens, Jennifer; Dondeyne, Stefaan; Van Orshoven, Jos; Diels, Jan

    2016-12-01

    The hydrologic response of a catchment is sensitive to the morphology of the drainage network. Dimensions of bigger channels are usually well known, however, geometrical data for man-made ditches is often missing as there are many and small. Aerial LiDAR data offers the possibility to extract these small geometrical features. Analysing the three-dimensional point clouds directly will maintain the highest degree of information. A longitudinal and cross-sectional buffer were used to extract the cross-sectional profile points from the LiDAR point cloud. The profile was represented by spline functions fitted through the minimum envelop of the extracted points. The cross-sectional ditch profiles were classified for the presence of water and vegetation based on the normalized difference water index and the spatial characteristics of the points along the profile. The normalized difference water index was created using the RGB and intensity data coupled to the LiDAR points. The mean vertical deviation of 0.14 m found between the extracted and reference cross sections could mainly be attributed to the occurrence of water and partly to vegetation on the banks. In contrast to the cross-sectional area, the extracted width was not influenced by the environment (coefficient of determination R2 = 0.87). Water and vegetation influenced the extracted ditch characteristics, but the proposed method is still robust and therefore facilitates input data acquisition and improves accuracy of spatially explicit hydrological models.

  6. Geodetic imaging with airborne LiDAR: the Earth's surface revealed

    NASA Astrophysics Data System (ADS)

    Glennie, C. L.; Carter, W. E.; Shrestha, R. L.; Dietrich, W. E.

    2013-08-01

    The past decade has seen an explosive increase in the number of peer reviewed papers reporting new scientific findings in geomorphology (including fans, channels, floodplains and landscape evolution), geologic mapping, tectonics and faulting, coastal processes, lava flows, hydrology (especially snow and runoff routing), glaciers and geo-archaeology. A common genesis of such findings is often newly available decimeter resolution ‘bare Earth’ geodetic images, derived from airborne laser swath mapping, a.k.a. airborne LiDAR, observations. In this paper we trace nearly a half century of advances in geodetic science made possible by space age technology, such as the invention of short-pulse-length high-pulse-rate lasers, solid state inertial measurement units, chip-based high speed electronics and the GPS satellite navigation system, that today make it possible to map hundreds of square kilometers of terrain in hours, even in areas covered with dense vegetation or shallow water. To illustrate the impact of the LiDAR observations we present examples of geodetic images that are not only stunning to the eye, but help researchers to develop quantitative models explaining how terrain evolved to its present form, and how it will likely change with time. Airborne LiDAR technology continues to develop quickly, promising ever more scientific discoveries in the years ahead.

  7. Phylogenetic relationships between four Salix L. species based on DArT markers.

    PubMed

    Przyborowski, Jerzy A; Sulima, Paweł; Kuszewska, Anna; Załuski, Dariusz; Kilian, Andrzej

    2013-12-11

    The objectives of this study were to evaluate the usefulness of DArT markers in genotypic identification of willow species and describe genetic relationships between four willow species: Salix viminalis, S. purpurea, S. alba and S. triandra. The experimental plant material comprised 53 willow genotypes of these four species, which are popularly grown in Poland. DArT markers seem to identify Salix species with a high degree of accuracy. As a result, the examined species were divided into four distinct groups which corresponded to the four analyzed species. In our study, we observed that S. triandra was very different genetically from the other species, including S. alba which is generally classified into the same subgenus of Salix. The above corroborates the findings of other authors who relied on molecular methods to reveal that the classification of S. triandra to the subgenus Salix was erroneous. The Principal Coordinate Analysis (PCoA) and the neighbor-joining dendrogram also confirmed the clear division of the studied willow genotypes into four clusters corresponding to individual species. This confirmed the usefulness of DArT markers in taxonomic analyses and identification of willow species.

  8. Downstream hydraulic geometry relationships: Gathering reference reach-scale width values from LiDAR

    NASA Astrophysics Data System (ADS)

    Sofia, G.; Tarolli, P.; Cazorzi, F.; Dalla Fontana, G.

    2015-12-01

    This paper examines the ability of LiDAR topography to provide reach-scale width values for the analysis of downstream hydraulic geometry relationships along some streams in the Dolomites (northern Italy). Multiple reach-scale dimensions can provide representative geometries and statistics characterising the longitudinal variability in the channel, improving the understanding of geomorphic processes across networks. Starting from the minimum curvature derived from a LiDAR DTM, the proposed algorithm uses a statistical approach for the identification of the scale of analysis, and for the automatic characterisation of reach-scale bankfull widths. The downstream adjustment in channel morphology is then related to flow parameters (drainage area and stream power). With the correct planning of a LiDAR survey, uncertainties in the procedure are principally due to the resolution of the DTM. The outputs are in general comparable in quality to field survey measurements, and the procedure allows the quick comparison among different watersheds. The proposed automatic approach could improve knowledge about river systems with highly variable widths, and about systems in areas covered by vegetation or inaccessible to field surveys. With proven effectiveness, this research could offer an interesting starting point for the analysis of differences between watersheds, and to improve knowledge about downstream channel adjustment in relation, for example, to scale and landscape forcing (e.g. sediment transport, tectonics, lithology, climate, geomorphology, and anthropic pressure).

  9. Assessment of human thermal perception in the hot-humid climate of Dar es Salaam, Tanzania

    NASA Astrophysics Data System (ADS)

    Ndetto, Emmanuel L.; Matzarakis, Andreas

    2017-01-01

    Dar es Salaam, Tanzania, is a typical African city along the Indian Ocean coast, and therefore an important urban area to examine human thermal perception in the hot-humid tropical climate. Earlier research on human bioclimate at Dar es Salaam indicated that heat stress prevails during the hot season from October to March, peaking between December and February, particularly the early afternoons. In order to assess the human thermal perception and adaptation, two popular places, one at an urban park and another at a beach environment, were selected and questionnaire surveys were conducted in August-September 2013 and January 2014, concurrently with local micro-meteorological measurements at survey locations. The thermal conditions were quantified in terms of the thermal index of the physiologically equivalent temperature (PET) using the micro-scale climate model RayMan. The thermal comfort range of human thermal comfort and the local thermal adaptive capacity were determined in respect to the thermal index by binning thermal sensation votes. The thermal comfort range was found to be well above that in temperate climates at about 23-31 °C of PET. The study could significantly contribute to urban planning in Dar es Salaam and other coastal cities in the tropics.

  10. Effects of LiDAR point density, sampling size and height threshold on estimation accuracy of crop biophysical parameters.

    PubMed

    Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong

    2016-05-30

    Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.

  11. Spatiotemporal analysis of stream network structure based on snow-on and snow-off LiDAR

    NASA Astrophysics Data System (ADS)

    Yang, P.; Ames, D. P.; Shrestha, R.

    2011-12-01

    The spatio-temporal analysis of ephemeral and intermittent stream structure provides valuable information for streamflow or discharge estimation, which can be important for snow pack volume and vegetation biomass calculation. Airborne LiDAR data collected under snow-on and snow-off conditions from Dry Creek Experimental Watershed (DCEW), a semi-arid region in southern Idaho, USA, were used to create a vegetation and snow height model based on the intensity information from the LiDAR point cloud. Stream networks under two conditions were delineated based on LiDAR-generated DEMs from snow and vegetation filtered point clouds. Ephemeral streams and perennial streams were identified through a difference analysis between snow-on and snow-off LiDAR derivatives, together with remote sensing imagery integration. A spatiotemporal analysis of stream network structure was carried out using a newly developed open source GIS software, HydroLiDAR, designed for accessing both point cloud and interpolated raster of LiDAR data. Field surveys are being conducted for validating and assessment.

  12. [Estimating individual tree aboveground biomass of the mid-subtropical forest using airborne LiDAR technology].

    PubMed

    Liu, Feng; Tan, Chang; Lei, Pi-Feng

    2014-11-01

    Taking Wugang forest farm in Xuefeng Mountain as the research object, using the airborne light detection and ranging (LiDAR) data under leaf-on condition and field data of concomitant plots, this paper assessed the ability of using LiDAR technology to estimate aboveground biomass of the mid-subtropical forest. A semi-automated individual tree LiDAR cloud point segmentation was obtained by using condition random fields and optimization methods. Spatial structure, waveform characteristics and topography were calculated as LiDAR metrics from the segmented objects. Then statistical models between aboveground biomass from field data and these LiDAR metrics were built. The individual tree recognition rates were 93%, 86% and 60% for coniferous, broadleaf and mixed forests, respectively. The adjusted coefficients of determination (R(2)adj) and the root mean squared errors (RMSE) for the three types of forest were 0.83, 0.81 and 0.74, and 28.22, 29.79 and 32.31 t · hm(-2), respectively. The estimation capability of model based on canopy geometric volume, tree percentile height, slope and waveform characteristics was much better than that of traditional regression model based on tree height. Therefore, LiDAR metrics from individual tree could facilitate better performance in biomass estimation.

  13. Multiple-LiDAR measurements of wind turbine wakes: effect of the atmospheric stability

    NASA Astrophysics Data System (ADS)

    Valerio Iungo, Giacomo; Porté-Agel, Fernando

    2013-04-01

    Aerodynamic design and optimization of a wind farm layout are mainly based on the evaluation of wind turbine wake recovery by moving downstream, and on the characterization of wake interactions within a wind farm. Indeed, the power production of downstream wind turbine rows is strictly affected by the cumulative wake produced by the turbines deployed upstream. Wind turbine wakes are dependent on their aerodynamic features, and being immersed in the atmospheric boundary layer (ABL), they are also affected by surface heterogeneity, e.g. site topography and surface coverage, and atmospheric stability. The ABL stability is typically classified as neutral, convective or stable. In a neutral ABL the mechanical turbulent production is the dominating phenomenon. Conversely, for a convective ABL the turbulent kinetic energy and vertical transport phenomena are enhanced by positive buoyancy. Finally, for a stable ABL, a lower turbulence level is typically observed with an increased wind shear. For the present campaign convective ABL was typically observed during day-time, and neutral ABL for early morning and sunset periods. The aim of the present work is the evaluation of the influence of the ABL stability on downstream evolution of wind turbine wakes, which is mainly controlled by different ABL turbulence characteristics. Field measurements of the wake produced from a 2 MW Enercon E-70 wind turbine were performed with three scanning Doppler wind LiDARs. The wind and atmospheric conditions were characterized through a sonic anemometer deployed in proximity of the wind turbine. One LiDAR was placed at a distance about 12 rotor diameters upstream of the turbine in order to characterize the incoming wind. Two additional LiDARs were typically used to perform wake measurements. Tests were performed over the wake vertical symmetry plane in order to characterize wake recovery. Measurements were also carried out over conical surfaces in order to investigate the wind turbine wake

  14. Classification and Characterization of Neotropical Rainforest Vegetation from Hyperspectral and LiDAR Data

    NASA Astrophysics Data System (ADS)

    Crawford, M. M.; Prasad, S.; Jung, J.; Yang, H.; Zhang, Y.

    2013-12-01

    Mapping species and forest vertical structure at regional, continental, and global scale is of increasing importance for climate science and decision support systems. Remote sensing technologies have been widely utilized to achieve this goal since they help overcome limitations of the direct and indirect measurement approaches. While the use of multi-sensor data for characterizing forest structure has gained significant attention in recent years, research on the integration of full waveform LiDAR and hyperspectral data for a) classification and b) characterization of vegetation structure has been limited. Given sufficient labeled ground reference samples, supervised learning methods have evolved to effectively classify data in a high dimensional feature space. However, it is expensive and time-consuming to obtain labeled data, although the very high dimensionality of feature spaces from hyperspectral and LiDAR inputs make it difficult to design reliable classifiers with a limited quantity of labeled data. Therefore, it is important to concentrate on developing training data sets which are the most 'informative' and 'useful' for the classification task. Active learning (AL) was developed in the machine learning community, and has been demonstrated to be useful for classification of remote sensing data. In the active learning framework, classifiers are initially trained on a very limited pool of training samples, but additional informative and representative samples are identified from the abundant unlabeled data, labeled, and then inducted into this pool, thereby growing the training dataset in a systematic way. The goal is to choose data points such that a more accurate classification boundary is learned. We propose a novel Multi-kernel Active Learning (MKL-AL) approach that incorporates features from multiple sensors with an automatically optimized kernel composite ¬function, and kernel parameters are selected intelligently during the AL learning process. The

  15. Mobile LiDAR Measurement for Aerosol Investigation in South-Central Hebei, China

    NASA Astrophysics Data System (ADS)

    qin, kai; Wu, Lixin; Zheng, Yunhui; Wong Man, Sing; Wang, Runfeng; Hu, Mingyu; Lang, Hongmei; Wang, Luyao; Bai, Yang; Rao, Lanlan

    2016-04-01

    With the rapid industrialization and urbanization in China during the last decades, the increasing anthropogenic pollutant emissions have significantly caused serious air pollution problems which are adversely influencing public health. Hebei is one of the most air polluted provinces in China. In January 2013, an extremely severe and persistent haze episode with record-breaking PM2.5 outbreak affecting hundreds of millions of people occurred over eastern and northern China. During that haze episode, 7 of the top 10 most polluted cities in China were located in the Hebei Province according to the report of China's Ministry of Environmental Protection. To investigate and the spatial difference and to characterize the vertical distribution of aerosol in different regions of south-central Hebei, mobile measurements were carried out using a mini micro pulse LiDAR system (model: MiniMPL) in March 2014. The mobile LiDAR kit consisting of a MiniMPL, a vibration reduction mount, a power inverter, a Windows surface tablet and a GPS receiver were mounted in a car watching though the sunroof opening. For comparison, a fixed measurement using a traditional micro pulse LiDAR system (model: MPL-4B) was conducted simultaneously in Shijiazhuang, the capital of Hebei Province. The equipped car was driven from downtown Shijiazhuang by way of suburban and rural area to downtown Cangzhou, Handan, and Baoding respectively at almost stable speed around 100Km per hour along different routes which counted in total more than 1000Km. The results can be summarized as: 1) the spatial distribution of total aerosol optical depth along the measurement routes in south-central Hebei was controlled by local terrain and population in general, with high values in downtown and suburban in the plain areas, and low values in rural areas along Taihang mountain to the west and Yan mountain to the north; 2) obviously high AODs were obtained at roads crossing points, inside densely populated area and nearby

  16. Glacier surface feature detection and classification from airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Höfle, B.; Sailer, R.; Vetter, M.; Rutzinger, M.; Pfeifer, N.

    2009-04-01

    In recent years airborne LiDAR evolved to the state-of-the-art technology for topographic data acquisition. Up to now mainly the derived elevation information has been used in glaciology (e.g. roughness determination, multitemporal elevation and volume changes). Few studies have already shown the potential of using LiDAR signal intensities for glacier surface differentiation, primarily based on visual interpretation of signal intensity images. This contribution brings together the spatial and radiometric information provided by airborne LiDAR, in order to make an automatic glacier surface feature detection and classification possible. The automation of the processing workflow and the standardization of the used input data become important particularly for multitemporal analysis where surface changes and feature tracking are of major interest. This study is carried out at the Hintereisferner, Ötztal Alps/Austria, where 16 airborne LiDAR acquisitions have taken place since 2001. We aim at detecting the main glacier surface classes as defined by crevasses, snow, firn, ice and debris covered ice areas. Prior to the glacier facies differentiation, an automated glacier delineation based on roughness constraints is performed. It is assumed that the glacier surface, except the crevasse zone, tends to a smoother surface than the adjacent slopes and represents one large connected spatial unit. The developed method combines raster and point cloud based processing steps in an object-based segmentation and classification procedure where elevation and calibrated signal intensity are used as complementary input. The calibration of the recorded signal intensity removes known effects originating from the atmosphere, topography and scan geometry (e.g. distance to target) and hence provides a value proportional to surface reflectance in the wavelength of the laser system. Since the Bidirectional Reflectance Distribution Function (BRDF) of the scanned surface is not known beforehand

  17. Calculation and Evaluation of the Mass Balance of Hintereisferner using Airborne LiDAR Data

    NASA Astrophysics Data System (ADS)

    Bollmann, Erik; Fischer, Andrea; Fritzmann, Patrick; Sailer, Rudolf; Stötter, Hans

    2010-05-01

    Since 2001 airborne LiDAR measurements have been carried out regularly at the Hintereisferner region (Ötztal, Tyrol, Austria). This results in a worldwide unique data set of 18 airborne LiDAR flight campaigns, which is primarily used for multitemporal glacial and periglacial surface analyses. The potential of this data set for the quantification of glacier surface elevation changes with high spatial and temporal resolution has already been shown in several studies. In this study we go beyond this stage and calculate the net mass balance of Hintereisferner by applying the geodetic method on regular raster digital elevation models (DEMs) with 1 m spatial resolution. The total geodetic net mass balance of the glacier is determined on an interannual time-scale as well as over the whole investigation period from 2001 - 2008. The accuracy of the geodetic net mass balance mainly depends on the accuracy of the input airborne LiDAR data and on density assumptions which have to be made to convert surface elevation changes to mass changes. To determine the accuracy of the LiDAR data and the derived DEMs, an accuracy assessment was computed comprising i) deviations between dGPS- and LiDAR-points, ii) errors resulting from point to raster conversion and iii) accuracy dependence of the DEMs on terrain slope angles. The calculated geodetic net mass balances of Hintereisferner are compared to results from the direct glaciological method. Mass balance calculations using the direct glaciological method already started in glaciological year 1952/53 and are continued up to the present day. Thus, a wide experience and well-founded knowledge on the application of the method at Hintereisferner was obtained and its accuracy is determined to be ± 100 mm water equivalent a-1 for the mean specific mass balance. Comparing the results of the geodetic method to direct measurements on the total net mass balance on an interannual time-scale, some stronger deviations between the two methods

  18. Buildings classification from airborne LiDAR point clouds through OBIA and ontology driven approach

    NASA Astrophysics Data System (ADS)

    Tomljenovic, Ivan; Belgiu, Mariana; Lampoltshammer, Thomas J.

    2013-04-01

    In the last years, airborne Light Detection and Ranging (LiDAR) data proved to be a valuable information resource for a vast number of applications ranging from land cover mapping to individual surface feature extraction from complex urban environments. To extract information from LiDAR data, users apply prior knowledge. Unfortunately, there is no consistent initiative for structuring this knowledge into data models that can be shared and reused across different applications and domains. The absence of such models poses great challenges to data interpretation, data fusion and integration as well as information transferability. The intention of this work is to describe the design, development and deployment of an ontology-based system to classify buildings from airborne LiDAR data. The novelty of this approach consists of the development of a domain ontology that specifies explicitly the knowledge used to extract features from airborne LiDAR data. The overall goal of this approach is to investigate the possibility for classification of features of interest from LiDAR data by means of domain ontology. The proposed workflow is applied to the building extraction process for the region of "Biberach an der Riss" in South Germany. Strip-adjusted and georeferenced airborne LiDAR data is processed based on geometrical and radiometric signatures stored within the point cloud. Region-growing segmentation algorithms are applied and segmented regions are exported to the GeoJSON format. Subsequently, the data is imported into the ontology-based reasoning process used to automatically classify exported features of interest. Based on the ontology it becomes possible to define domain concepts, associated properties and relations. As a consequence, the resulting specific body of knowledge restricts possible interpretation variants. Moreover, ontologies are machinable and thus it is possible to run reasoning on top of them. Available reasoners (FACT++, JESS, Pellet) are used to check

  19. Seagrass Identification Using High-Resolution 532nm Bathymetric LiDAR and Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Pan, Z.; Prasad, S.; Starek, M. J.; Fernandez Diaz, J. C.; Glennie, C. L.; Carter, W. E.; Shrestha, R. L.; Singhania, A.; Gibeaut, J. C.

    2013-12-01

    Seagrass provides vital habitat for marine fisheries and is a key indicator species of coastal ecosystem vitality. Monitoring seagrass is therefore an important environmental initiative, but measuring details of seagrass distribution over large areas via remote sensing has proved challenging. Developments in airborne bathymetric light detection and ranging (LiDAR) provide great potential in this regard. Traditional bathymetric LiDAR systems have been limited in their ability to map within the shallow water zone (< 1 m) where seagrass is typically present due to limitations in receiver response and laser pulse length. Emergent short-pulse width bathymetric LiDAR sensors and waveform processing algorithms enable depth measurements in shallow water environments previously inaccessible. This 3D information of the benthic layer can be applied to detect seagrass and characterize its distribution. Researchers with the National Center for Airborne Laser Mapping (NCALM) at the University of Houston (UH) and the Coastal and Marine Geospatial Sciences Lab (CMGL) of the Harte Research Institute at Texas A&M University-Corpus Christi conducted a coordinated airborne and boat-based survey of the Redfish Bay State Scientific Area as part of a collaborative study to investigate the capabilities of bathymetric LiDAR and hyperspectral imaging for seagrass mapping. Redfish Bay, located along the middle Texas coast of the Gulf of Mexico, is a state scientific area designated for the purpose of protecting and studying native seagrasses. Redfish Bay is part of the broader Coastal Bend Bays estuary system recognized by the US Environmental Protection Agency (EPA) as a national estuary of significance. For this survey, UH acquired high-resolution discrete-return and full-waveform bathymetric data using their Optech Aquarius 532 nm green LiDAR. In a separate flight, UH collected 2 sets of hyperspectral imaging data (1.2-m pixel resolution and 72 bands, and 0.6m pixel resolution and 36

  20. A Geoinformatics Approach to LiDAR / ALSM Data Distribution, Interpolation, and Analysis

    NASA Astrophysics Data System (ADS)

    Crosby, C. J.; Conner, J.; Frank, E.; Arrowsmith, J. R.; Memon, A.; Nandigam, V.; Wurman, G.; Baru, C.

    2005-12-01

    Distribution, interpolation and analysis of large LiDAR (Light Distance And Ranging, also known as ALSM (Airborne Laser Swath Mapping)) datasets pushes the computational limits of typical data distribution and processing systems. The high point-density of LiDAR datasets makes grid interpolation difficult for geoscience users who lack the computing and software resources necessary to handle these massive data volumes. We are using a geoinformatics approach to the distribution, interpolation and analysis of LiDAR data that capitalizes on cyberinfrastructure being developed as part of the GEON project (http://www.geongrid.org). Our approach utilizes a comprehensive workflow-based solution that begins with user-defined selection of a subset of raw data and ends with download and visualization of interpolated surfaces and derived products. The workflow environment allows us to modularize and generalize the procedure. It provides the freedom to easily plug-in new processes, to utilize existing sub workflows within an analysis, and easily extend or modify the analysis using drag-and-drop functionality through the Kepler workflow management system. In this GEON-based workflow, the billions of points within a LiDAR dataset point cloud are hosted in an IBM DB2 spatial database running on the DataStar terascale computer at San Diego Supercomputer Center; a machine designed specifically for data intensive computations. Data selection is performed via an ArcIMS-based interface that allows users to execute spatial and attribute subset queries on the larger dataset. The subset of data is then passed to a GRASS Open Source GIS-based web service, "lservice", that handles interpolation to grid and analysis of the data. Lservice was developed entirely within the open source domain and offers spline and inverse distance weighted (IDW) interpolation to grid with user-defined resolution and parameters. We also compute geomorphic metrics such as slope, curvature, and aspect. Users may

  1. LESTO: an Open Source GIS-based toolbox for LiDAR analysis

    NASA Astrophysics Data System (ADS)

    Franceschi, Silvia; Antonello, Andrea; Tonon, Giustino

    2015-04-01

    During the last five years different research institutes and private companies stared to implement new algorithms to analyze and extract features from LiDAR data but only a few of them also created a public available software. In the field of forestry there are different examples of software that can be used to extract the vegetation parameters from LiDAR data, unfortunately most of them are closed source (even if free), which means that the source code is not shared with the public for anyone to look at or make changes to. In 2014 we started the development of the library LESTO (LiDAR Empowered Sciences Toolbox Opensource): a set of modules for the analysis of LiDAR point cloud with an Open Source approach with the aim of improving the performance of the extraction of the volume of biomass and other vegetation parameters on large areas for mixed forest structures. LESTO contains a set of modules for data handling and analysis implemented within the JGrassTools spatial processing library. The main subsections are dedicated to 1) preprocessing of LiDAR raw data mainly in LAS format (utilities and filtering); 2) creation of raster derived products; 3) flight-lines identification and normalization of the intensity values; 4) tools for extraction of vegetation and buildings. The core of the LESTO library is the extraction of the vegetation parameters. We decided to follow the single tree based approach starting with the implementation of some of the most used algorithms in literature. These have been tweaked and applied on LiDAR derived raster datasets (DTM, DSM) as well as point clouds of raw data. The methods range between the simple extraction of tops and crowns from local maxima, the region growing method, the watershed method and individual tree segmentation on point clouds. The validation procedure consists in finding the matching between field and LiDAR-derived measurements at individual tree and plot level. An automatic validation procedure has been developed

  2. An application of vessel-based LiDAR to quantify coastal retreat in Southern Monterey Bay, CA

    NASA Astrophysics Data System (ADS)

    Quan, S.; Kvitek, R.; Smith, D. P.

    2009-12-01

    Coastal erosion has become a prominent issue in Monterey Bay, California. Areas at high risk include native coastal dunes, private and public beachfront properties, municipal sewage lines, and areas of the highway 1 corridor. Traditional airborne LiDAR has been an effective method in measuring coastal topography by providing high resolution and great coverage, but it remains costly. In 1997 and 1998, NASA, USGS, and NOAA collaborated to conduct pre- and post- El Niño airborne LiDAR surveys of the California coastline. Since then, there have been no further, publically available LiDAR surveys of the Monterey Bay shoreline. The goal of this project is to apply a vessel-based LiDAR system to measure coastal geomorphology, determine the efficiency of vessel-based topographic LiDAR for mapping coastal geomorphology, and quantify the spatial distribution of coastal retreat for Monterey Bay, California. The area of study was the Monterey Bay coastline from the Monterey Bay Commercial Wharf II to Marina State Beach at Reservation Rd. Sea cliff morphology data were measured on Dec 9th and 10th, 2008 through the use of a terrestrial LiDAR system mounted atop the CSUMB Seafloor Mapping Lab’s R/V VenTresca. These vessel based LiDAR data were compared with 1998 NOAA Airborne Topographic Mapper LiDAR data using mapping, modeling and spatial analysis tools in ArcGIS to quantify the spatial distribution of coastal retreat and calculate annualized rates of erosion for the Monterey Bay shoreline over the past decade. Preliminary results show a slight correlation between volumetric change and distance along the coast from Wharf II, in keeping with previous published results. On the other hand, average sand dune apron retreat rate is 0.92 m/yr with a significant relationship between sand dune apron retreat rate and distance along the coast. The utilization of vessel based LiDAR is an effective and cost efficient method to frequently measure sea cliff geomorphology with very high

  3. The Hintereisferner - eight years of experience in method development for glacier monitoring with airborne LiDAR

    NASA Astrophysics Data System (ADS)

    Vetter, M.; Höfle, B.; Pfeifer, N.; Rutzinger, M.; Sailer, R.; Stötter, J.; Geist, T.

    2009-04-01

    Topographic data acquisition with LiDAR technology, airborne or terrestrial, has become the state-of-the-art procedure for Earth surface surveying. For glacier monitoring different remote sensing technologies are used for many years. With the advent of airborne LiDAR a paradigm shift in glacier monitoring has taken place. Eight years ago pioneer work within glacier surface surveying and monitoring has been carried out at the Institute of Geography (Innsbruck) within the OMEGA (Development of Operational Monitoring System for European Glacial Areas) project by using airborne LiDAR. Since 2001, 16 single airborne LiDAR campaigns have been carried out by collecting data of Hintereisferner, Kesselwandferner and adjacent small glaciers as well as their surrounding areas (Ötztal Alps, Tyrol, Austria). We present the main results of this period of glacier monitoring based on LiDAR data. One major task was to set up a geo-database system to manage the huge amount of LiDAR data, offering the opportunity to compute various point features and different rasterized data sets using this LiDAR data management and analysis system. In this context some basic routines were developed (e.g. a tool for intensity calibration, for derive intensity and point density images, and for modeling the locations of laser shot dropouts). In addition, tools for the analysis of the glacier surface have been developed: (a) a glacier delineation tool, using intensity and roughness information, (b) tools to compute and visualize the volume and elevation changes using multitemporal data, (c) a tool to calculate the ice flow velocity at the glacier surface, (d) a classification tool to detect crevasses, snow, firn, ice and debris covered ice areas, using calibrated intensity data, roughness information and modeled laser shot dropouts. For the analysis of glacial geomorphologic processes (i) a routine for the delineation of moraine ridges and rock glaciers works on the basis of break lines, (ii) a

  4. Quantifying soil carbon loss and uncertainty from a peatland wildfire using multi-temporal LiDAR

    USGS Publications Warehouse

    Reddy, Ashwan D.; Hawbaker, Todd J.; Wurster, F.; Zhu, Zhiliang; Ward, S.; Newcomb, Doug; Murray, R.

    2015-01-01

    Peatlands are a major reservoir of global soil carbon, yet account for just 3% of global land cover. Human impacts like draining can hinder the ability of peatlands to sequester carbon and expose their soils to fire under dry conditions. Estimating soil carbon loss from peat fires can be challenging due to uncertainty about pre-fire surface elevations. This study uses multi-temporal LiDAR to obtain pre- and post-fire elevations and estimate soil carbon loss caused by the 2011 Lateral West fire in the Great Dismal Swamp National Wildlife Refuge, VA, USA. We also determine how LiDAR elevation error affects uncertainty in our carbon loss estimate by randomly perturbing the LiDAR point elevations and recalculating elevation change and carbon loss, iterating this process 1000 times. We calculated a total loss using LiDAR of 1.10 Tg C across the 25 km2 burned area. The fire burned an average of 47 cm deep, equivalent to 44 kg C/m2, a value larger than the 1997 Indonesian peat fires (29 kg C/m2). Carbon loss via the First-Order Fire Effects Model (FOFEM) was estimated to be 0.06 Tg C. Propagating the LiDAR elevation error to the carbon loss estimates, we calculated a standard deviation of 0.00009 Tg C, equivalent to 0.008% of total carbon loss. We conclude that LiDAR elevation error is not a significant contributor to uncertainty in soil carbon loss under severe fire conditions with substantial peat consumption. However, uncertainties may be more substantial when soil elevation loss is of a similar or smaller magnitude than the reported LiDAR error.

  5. Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon

    USGS Publications Warehouse

    Burns, W.J.; Coe, J.A.; Kaya, B.S.; Ma, L.

    2010-01-01

    We examined elevation changes detected from two successive sets of Light Detection and Ranging (LiDAR) data in the northern Coast Range of Oregon. The first set of LiDAR data was acquired during leafon conditions and the second set during leaf-off conditions. We were able to successfully identify and map active landslides using a differential digital elevation model (DEM) created from the two LiDAR data sets, but this required the use of thresholds (0.50 and 0.75 m) to remove noise from the differential elevation data, visual pattern recognition of landslideinduced elevation changes, and supplemental QuickBird satellite imagery. After mapping, we field-verified 88 percent of the landslides that we had mapped with high confidence, but we could not detect active landslides with elevation changes of less than 0.50 m. Volumetric calculations showed that a total of about 18,100 m3 of material was missing from landslide areas, probably as a result of systematic negative elevation errors in the differential DEM and as a result of removal of material by erosion and transport. We also examined the accuracies of 285 leaf-off LiDAR elevations at four landslide sites using Global Positioning System and total station surveys. A comparison of LiDAR and survey data indicated an overall root mean square error of 0.50 m, a maximum error of 2.21 m, and a systematic error of 0.09 m. LiDAR ground-point densities were lowest in areas with young conifer forests and deciduous vegetation, which resulted in extensive interpolations of elevations in the leaf-on, bare-earth DEM. For optimal use of multi-temporal LiDAR data in forested areas, we recommend that all data sets be flown during leaf-off seasons.

  6. Similarity and Complementarity of Airborne and Terrestrial LiDAR Data in High Mountain Regions

    NASA Astrophysics Data System (ADS)

    Kamp, Nicole; Glira, Philipp; Pfeifer, Norbert

    2013-04-01

    Glacier melt and a consequential increased sediment transport (erosion, transportation and accumulation) in high mountain regions are causing a frequent occurrence of geomorphic processes such as landslides and other natural hazards. These effects are investigated at the Gepatschferner (Kaunertal, Oetztal Alps, Tyrol), the second largest glacier in Austria, in the PROSA project (Catholic University Eichstätt - Ingolstadt, Vienna University of Technology, Friedrich Alexander University Erlangen-Nürnberg, Martin-Luther-University Halle-Wittenberg, University of Innsbruck, Munich University of Technology). To monitor these geomorphic processes, data with a very high spatial and very high temporally accuracy and resolution are needed. For this purpose multi-temporal terrestrial and aerial laser scanning data are acquired, processed and analysed. Airborne LiDAR data are collected with a density of 10 points/m² over the whole study area of the glacier and its foreland. Terrestrial LiDAR data are gathered to complement and improve the airborne LiDAR data. The different viewing geometry results in differences between airborne and terrestrial data. Very steep slopes and rock faces (around 90°, depending on the viewing direction) are not visible from the airborne view point. On the other hand, terrestrial viewpoints exhibit shadows for areas above the scanner position and in viewing direction behind vertical or steep faces. In addition, the density of terrestrial data is varying strongly, but has for most of the covered area a much higher level of detail than the airborne dataset. A small temporal baseline is also inevitable and may cause differences between acquisition of airborne and terrestrial data. The goal of this research work is to develop a method for merging airborne and terrestrial LiDAR data. One prerequisite for merging is the identification of areas which are measurements of the same physical surface in either data set. This allows a transformation of the

  7. Modeling of a sensitive time-of-flight flash LiDAR system

    NASA Astrophysics Data System (ADS)

    Fathipour, V.; Wheaton, S.; Johnson, W. E.; Mohseni, H.

    2016-09-01

    used for monitoring and profiling structures, range, velocity, vibration, and air turbulence. Remote sensing in the IR region has several advantages over the visible region, including higher transmitter energy while maintaining eye-safety requirements. Electron-injection detectors are a new class of detectors with high internal avalanche-free amplification together with an excess-noise-factor of unity. They have a cutoff wavelength of 1700 nm. Furthermore, they have an extremely low jitter. The detector operates in linear-mode and requires only bias voltage of a few volts. This together with the feedback stabilized gain mechanism, makes formation of large-format high pixel density electron-injection FPAs less challenging compared to other detector technologies such as avalanche photodetectors. These characteristics make electron-injection detectors an ideal choice for flash LiDAR application with mm scale resolution at longer ranges. Based on our experimentally measured device characteristics, a detailed theoretical LiDAR model was developed. In this model we compare the performance of the electron-injection detector with commercially available linear-mode InGaAs APD from (Hamamatsu G8931-20) as well as a p-i-n diode (Hamamatsu 11193 p-i-n). Flash LiDAR images obtained by our model, show the electron-injection detector array (of 100 x 100 element) achieves better resolution with higher signal-to-noise compared with both the InGaAs APD and the p-i-n array (of 100 x 100 element).

  8. 3D Scene Reconstruction Using Omnidirectional Vision and LiDAR: A Hybrid Approach

    PubMed Central

    Vlaminck, Michiel; Luong, Hiep; Goeman, Werner; Philips, Wilfried

    2016-01-01

    In this paper, we propose a novel approach to obtain accurate 3D reconstructions of large-scale environments by means of a mobile acquisition platform. The system incorporates a Velodyne LiDAR scanner, as well as a Point Grey Ladybug panoramic camera system. It was designed with genericity in mind, and hence, it does not make any assumption about the scene or about the sensor set-up. The main novelty of this work is that the proposed LiDAR mapping approach deals explicitly with the inhomogeneous density of point clouds produced by LiDAR scanners. To this end, we keep track of a global 3D map of the environment, which is continuously improved and refined by means of a surface reconstruction technique. Moreover, we perform surface analysis on consecutive generated point clouds in order to assure a perfect alignment with the global 3D map. In order to cope with drift, the system incorporates loop closure by determining the pose error and propagating it back in the pose graph. Our algorithm was exhaustively tested on data captured at a conference building, a university campus and an industrial site of a chemical company. Experiments demonstrate that it is capable of generating highly accurate 3D maps in very challenging environments. We can state that the average distance of corresponding point pairs between the ground truth and estimated point cloud approximates one centimeter for an area covering approximately 4000 m2. To prove the genericity of the system, it was tested on the well-known Kitti vision benchmark. The results show that our approach competes with state of the art methods without making any additional assumptions. PMID:27854315

  9. The offshore wind resources assessment application of floating LiDAR in the Taiwan Strait

    NASA Astrophysics Data System (ADS)

    Hsuan, Chung-Yao; Wu, Yu-Ting; Lin, Ta-Hui

    2015-04-01

    Wind and wave measurements of a Floating LiDAR (Light Detection And Ranging) Device (FLD) are performed on the site of Fuhai Offshore Wind Farm in the Taiwan Strait. The location of the deployment is situated 10 kilometers off-coast of Changhua County, and the anchored water depth is 25 meters. It is the very first time in Asia Pacific Region to use such device for tasks of offshore wind and wave measurement. Six range gate heights were set at 55m, 71m, 90m, 110m, 150m and 200m from the FLD sensor lens. Wind speeds and wind directions were measured by a remote sensing technology. Wave heights and periods were also measured by the buoy wave sensor. A validation campaign of NCKU WindSentinel has performed by a portable LiDAR (WINDCUBE v2) at Hsing-Da Harbor in the south of Taiwan from October 16th to 26th, 2013. The results showed good agreements with 10 minute averaged data of the wind speed and wind direction measured by the two LiDARs. NCKU WindSentinel data are planning comparisons with Fuhai's offshore fixed mast data when the meteorological mast is completed. The goal is to convince the wind energy community that FLD are a reliable and cost effective way of obtaining data for resource assessment. Until this moment, The FLD are observing and measuring the offshore wind farm's meteorological and oceanographic data. In September of 2014, a mild typhoon (Fung-Wong) passed through from east of Taiwan. NCKU WindSentinel continuously measured during typhoon period in the sea. The present preliminary measurements campaign presented the convenient and more cost effective option of the FLD, which may be a key tool for assessment of offshore wind resources in the near-future offshore wind farm developments.

  10. LiDAR Individual Tree Detection for Assessing Structurally Diverse Forest Landscapes

    NASA Astrophysics Data System (ADS)

    Jeronimo, Sean

    Contemporary forest management on public land incorporates a focus on restoration and maintenance of ecological functions through silvicultural manipulation of forest structure on a landscape scale. Incorporating reference conditions into restoration treatment planning and monitoring can improve treatment efficacy, but the typical ground-based methods of quantifying reference condition data---and comparing it to pre- and post-treatment stands---are expensive, time-consuming, and limited in scale. Airborne LiDAR may be part of the solution to this problem, since LiDAR acquisitions have both broad coverage and high resolution. I evaluated the ability of LiDAR Individual Tree Detection (ITD) to describe forest structure across a structurally variable landscape in support of large-scale forest restoration. I installed nineteen 0.25 ha stem map plots across a range of structural conditions in potential reference areas (Yosemite National Park) and potential restoration treatment areas (Sierra National Forest) in the Sierra Nevada of California. I used the plots to evaluate a common ITD algorithm, the watershed transform, compare it to past uses of ITD, and determine which aspects of forest structure contributed to errors in ITD. I found that ITD across this structurally diverse landscape was generally less accurate than across the smaller and less diverse areas over which it has previously been studied. However, the pattern of tree recognition is consistent: regardless of forest structure, canopy dominants are almost always detected and relatively shorter trees are almost never detected. Correspondingly, metrics dominated by large trees, such as biomass, basal area, and spatial heterogeneity, can be measured using ITD, while metrics dominated by smaller trees, such as stand density, cannot. Bearing these limitations in mind, ITD can be a powerful tool for describing forest structure across heterogeneous landscape restoration project areas.

  11. Fusing Hyperspectral and LiDAR data from CAO-VSWIR for Increased Data Dimensionality

    NASA Astrophysics Data System (ADS)

    Knapp, D. E.; Asner, G. P.; Boardman, J. W.; Kennedy-Bowdoin, T.; Eastwood, M.; Anderson, C.; Martin, R. E.; Green, R. O.

    2012-12-01

    The use of multi-sensor platforms for scientific data collection requires precise co-location in order to gain maximum data dimensionality for Earth system research. The different types of collection mechanisms of the sensors (e.g., scanning and pushbroom) can make it difficult to precisely match data from multiple sensors, even when the sensors are flown on the same aircraft at the same time. To overcome these problems, the Carnegie Airborne Observatory (CAO) AToMS sensor suite uses a method that maximizes the match between the Light Detection and Ranging (LiDAR), Visible-to-Near Infrared (VNIR), and Visible-to-Shortwave Infrared (VSWIR) sensors. This is done by generating an intensity image from the LiDAR data that serves as a base on which the spectrometers (VNIR and VSWIR) are matched using ground control points (GCPs). To do so, we employ the use of automated tie point matching in the overlap regions of the spectrometers to improve the co-location between flightlines. The combination of the GCPs and tie points produce data that is used to build camera models for the VNIR and VSWIR spectrometers such that they will match the LiDAR data. The result produces a matched hyper-dimensional data set with great scientific information content. We compare the data dimensionality of two contrasting scenes - a built environment at Stanford University and a lowland tropical forest in Amazonia. Principal components analysis revealed 336 dimensions (degrees of freedom) in the Stanford case, and 218 dimensions in the Amazon. The Amazon case presents what could be the highest level of remotely sensed data dimensionality ever reported for a forested ecosystem. Simulated misalignment of data streams reduced the effective information content by up to 48%, highlighting the critical role of achieving high precision when undertaking multi-sensor fusion. The instrumentation and methods described here are a pathfinder for future airborne applications undertaken by the National

  12. Numerical simulation of groundwater flow in Dar es Salaam Coastal Plain (Tanzania)

    NASA Astrophysics Data System (ADS)

    Luciani, Giulia; Sappa, Giuseppe; Cella, Antonella

    2016-04-01

    They are presented the results of a groundwater modeling study on the Coastal Aquifer of Dar es Salaam (Tanzania). Dar es Salaam is one of the fastest-growing coastal cities in Sub-Saharan Africa, with with more than 4 million of inhabitants and a population growth rate of about 8 per cent per year. The city faces periodic water shortages, due to the lack of an adequate water supply network. These two factors have determined, in the last ten years, an increasing demand of groundwater exploitation, carried on by quite a number of private wells, which have been drilled to satisfy human demand. A steady-state three dimensional groundwater model has been set up by the MODFLOW code, and calibrated with the UCODE code for inverse modeling. The aim of the model was to carry out a characterization of groundwater flow system in the Dar es Salaam Coastal Plain. The inputs applied to the model included net recharge rate, calculated from time series of precipitation data (1961-2012), estimations of average groundwater extraction, and estimations of groundwater recharge, coming from zones, outside the area under study. Parametrization of the hydraulic conductivities was realized referring to the main geological features of the study area, based on available literature data and information. Boundary conditions were assigned based on hydrogeological boundaries. The conceptual model was defined in subsequent steps, which added some hydrogeological features and excluded other ones. Calibration was performed with UCODE 2014, using 76 measures of hydraulic head, taken in 2012 referred to the same season. Data were weighted on the basis of the expected errors. Sensitivity analysis of data was performed during calibration, and permitted to identify which parameters were possible to be estimated, and which data could support parameters estimation. Calibration was evaluated based on statistical index, maps of error distribution and test of independence of residuals. Further model

  13. Regional forest biomass estimation using ICESat/GLAS spaceborne LiDAR

    NASA Astrophysics Data System (ADS)

    Hayashi, M.; Saigusa, N.; Habura, B.; Sawada, Y.; Yamagata, Y.; Hirano, T.; Ichii, K.

    2015-12-01

    Spaceborne LiDAR can observe vertical structure of forests and provide a means for accurate forest monitoring, therefore, it may meet the growing demand of forest resources monitoring on a large scale. This study aims to clarify the potential of ICESat/GLAS, which had been the only spaceborne LiDAR up to now, for forest resources monitoring on a regional scale. The study areas were three regions: Hokkaido Island in Japan (cool-temperate forest), Borneo Island (tropical forest) and Siberia (boreal forest). Firstly, we conducted field measurements at 106 points in Hokkaido and 37 points in Borneo to measure the average canopy height (Lorey's height) and the above-ground biomass (AGB) for each GLAS-footprint, then, we developed some models to estimate canopy height and AGB from the GLAS waveform parameters. Next, we applied the developed models to the GLAS data which were 14,000 points in Hokkaido, and 130,000 points in Borneo, to estimate canopy height and AGB on a regional scale. As a result, we clarified the forest condition concerning canopy height and AGB for each region, namely, the average value, the comparison between the average of each forest type, and the spatial distribution. Furthermore, we detected the AGB change over the years (forest degradation) and estimated the forest loss rate of 1.6% yr-1 in Borneo. Next, we applied the developed models in Hokkaido to the 1,600,000 points GLAS data observed in Siberia. As a result, we clarified that the average AGB in Siberia was a remarkable low value as compared with those in Hokkaido and Borneo, and that the AGB change over the years (forest degradation) was significant in the southern region of western Siberia. This study showed that spaceborne LiDAR had an ability of forest resources monitoring on a regional scale for various forests over the world.

  14. 3D Scene Reconstruction Using Omnidirectional Vision and LiDAR: A Hybrid Approach.

    PubMed

    Vlaminck, Michiel; Luong, Hiep; Goeman, Werner; Philips, Wilfried

    2016-11-16

    In this paper, we propose a novel approach to obtain accurate 3D reconstructions of large-scale environments by means of a mobile acquisition platform. The system incorporates a Velodyne LiDAR scanner, as well as a Point Grey Ladybug panoramic camera system. It was designed with genericity in mind, and hence, it does not make any assumption about the scene or about the sensor set-up. The main novelty of this work is that the proposed LiDAR mapping approach deals explicitly with the inhomogeneous density of point clouds produced by LiDAR scanners. To this end, we keep track of a global 3D map of the environment, which is continuously improved and refined by means of a surface reconstruction technique. Moreover, we perform surface analysis on consecutive generated point clouds in order to assure a perfect alignment with the global 3D map. In order to cope with drift, the system incorporates loop closure by determining the pose error and propagating it back in the pose graph. Our algorithm was exhaustively tested on data captured at a conference building, a university campus and an industrial site of a chemical company. Experiments demonstrate that it is capable of generating highly accurate 3D maps in very challenging environments. We can state that the average distance of corresponding point pairs between the ground truth and estimated point cloud approximates one centimeter for an area covering approximately 4000 m 2 . To prove the genericity of the system, it was tested on the well-known Kitti vision benchmark. The results show that our approach competes with state of the art methods without making any additional assumptions.

  15. Horizontal geometrical reaction time model for two-beam nacelle LiDARs

    NASA Astrophysics Data System (ADS)

    Beuth, Thorsten; Fox, Maik; Stork, Wilhelm

    2015-06-01

    Wind energy is one of the leading sustainable energies. To attract further private and state investment in this technology, a broad scaled drop of the cost of energy has to be enforced. There is a trend towards using Laser Doppler Velocimetry LiDAR systems for enhancing power output and minimizing downtimes, fatigue and extreme forces. Since most used LiDARs are horizontally setup on a nacelle and work with two beams, it is important to understand the geometrical configuration which is crucial to estimate reaction times for the actuators to compensate wind gusts. In the beginning of this article, the basic operating modes of wind turbines are explained and the literature on wind behavior is analyzed to derive specific wind speed and wind angle conditions in relation to the yaw angle of the hub. A short introduction to the requirements for the reconstruction of the wind vector length and wind angle leads to the problem of wind shear detection of angled but horizontal homogeneous wind fronts due to the spatial separation of the measuring points. A distance is defined in which the wind shear of such homogeneous wind fronts is not present which is used as a base to estimate further distance calculations. The reaction time of the controller and the actuators are having a negative effect on the effective overall reaction time for wind regulation as well. In the end, exemplary calculations estimate benefits and disadvantages of system parameters for wind gust regulating LiDARs for a wind turbine of typical size. An outlook shows possible future improvements concerning the vertical wind behavior.

  16. LiDAR-based volume assessment of the origin of the Wadena drumlin field, Minnesota, USA

    NASA Astrophysics Data System (ADS)

    Sookhan, Shane; Eyles, Nick; Putkinen, Niko

    2016-06-01

    The Wadena drumlin field (WDF; ~ 7500 km2) in west-central Minnesota, USA, is bordered along its outer extremity by the till-cored Alexandria moraine marking the furthest extent of the southwesterly-flowing Wadena ice lobe at c. 15,000 kyr BP. Newly available high-resolution Light Detection and Ranging (LiDAR) data reveal new information regarding the number, morphology and extent of streamlined bedforms in the WDF. In addition, a newly-developed quantitative methodology based on relief curvature analysis of LiDAR elevation-based raster data is used to evaluate sediment volumes represented by the WDF and its bounding end moraine. These data are used to evaluate models for the origin of drumlins. High-resolution LiDAR-based mapping doubles the streamlined footprint of the Wadena Lobe to ~ 16,500 km2 increases the number of bedforms from ~ 2000 to ~ 6000, and most significantly, reclassifies large numbers of bedforms mapped previously as 'drumlins' as 'mega-scale glacial lineations' (MSGLs), indicating that the Wadena ice lobe experienced fast ice flow. The total volume of sediment in the Alexandria moraine is ~ 71-110 km3, that in the drumlins and MSGLs is ~ 2.83 km3, and the volume of swales between these bedforms is ~ 74.51 km3. The moraine volume is equivalent to a till layer 6.8 m thick across the entire bed of the Wadena lobe, suggesting drumlinization and moraine formation were accompanied by widespread lowering of the bed. This supports the hypothesis that drumlins and MSGLs are residual erosional features carved from a pre-existing till; swales represent 'missing sediment' that was eroded subglacially and advected downglacier to build the Alexandria Moraine during fast ice flow. Alternatively, the relatively small volume of sediment represented by subglacial bedforms indicates they could have formed rapidly by depositional processes.

  17. Demonstration of LiDAR and Orthophotography for Wide Area Assessment at Pueblo Precision Bombing Range #2 Colorado and Borrego Military Wash Area, California

    DTIC Science & Technology

    2008-12-01

    software for rectification of the photography to the DTM . 2.2.3 Data Analysis Once processed, the LiDAR /orthophotography data sets are analyzed to...ESTCP Cost and Performance Report ENVIRONMENTAL SECURITY TECHNOLOGY CERTIFICATION PROGRAM U.S. Department of Defense (MM-0535) Demonstration of LiDAR ...DEC 2008 2. REPORT TYPE 3. DATES COVERED 00-00-2008 to 00-00-2008 4. TITLE AND SUBTITLE Demonstration of LiDAR and Orthophotography for Wide

  18. Unsupervised building detection from irregularly spaced LiDAR and aerial imagery

    NASA Astrophysics Data System (ADS)

    Shorter, Nicholas Sven

    As more data sources containing 3-D information are becoming available, an increased interest in 3-D imaging has emerged. Among these is the 3-D reconstruction of buildings and other man-made structures. A necessary preprocessing step is the detection and isolation of individual buildings that subsequently can be reconstructed in 3-D using various methodologies. Applications for both building detection and reconstruction have commercial use for urban planning, network planning for mobile communication (cell phone tower placement), spatial analysis of air pollution and noise nuisances, microclimate investigations, geographical information systems, security services and change detection from areas affected by natural disasters. Building detection and reconstruction are also used in the military for automatic target recognition and in entertainment for virtual tourism. Previously proposed building detection and reconstruction algorithms solely utilized aerial imagery. With the advent of Light Detection and Ranging (LiDAR) systems providing elevation data, current algorithms explore using captured LiDAR data as an additional feasible source of information. Additional sources of information can lead to automating techniques (alleviating their need for manual user intervention) as well as increasing their capabilities and accuracy. Several building detection approaches surveyed in the open literature have fundamental weaknesses that hinder their use; such as requiring multiple data sets from different sensors, mandating certain operations to be carried out manually, and limited functionality to only being able to detect certain types of buildings. In this work, a building detection system is proposed and implemented which strives to overcome the limitations seen in existing techniques. The developed framework is flexible in that it can perform building detection from just LiDAR data (first or last return), or just nadir, color aerial imagery. If data from both LiDAR and

  19. Interoperable Data Systems for Satellite, Airborne, and Terrestrial LiDAR Data

    NASA Astrophysics Data System (ADS)

    Meertens, C. M.; Baru, C.; Blair, B.; Crosby, C. J.; Haran, T. M.; Harding, D. J.; Hofton, M. A.; Khalsa, S. S.; McWhirter, J.

    2010-12-01

    LiDAR (Light Detection and Ranging) technology is being widely applied to scientific problems on global to local scales using a range of laser technologies mounted on satellite, low- and high-altitude airborne and terrestrial platforms. Modern laser ranging instruments are increasingly capable of providing full waveform data, multiple detectors, higher sample rates and longer ranges. Accompanying these improvements, however, are rapidly growing data volumes and ever more complex data formats and processing algorithms. This presents significant challenges for existing Earth science data systems serving these data and creates barriers to the efficient use of these data by a growing and diverse community of scientific and other users who are studying deformation of the solid Earth, the cryosphere, vegetation structure, and land form evolution. To address these challenges, a group of data centers is collaborating under a project funded by the NASA ROSES ACCESS Program to develop interoperable LiDAR data access systems to provide integrated access to data and derived products in common data formats via simple-to-navigate web interfaces. The web service-based systems created by this project, called NLAS, will enhance access to existing laser data sources hosted at the National Snow and Ice Data Center DAAC, Goddard Space Flight Center LVIS Data Center, UNAVCO, and the OpenTopography Facility at the San Diego Supercomputer Center (SDSC). Through the OpenTopography portal, NLAS systems will provide access to satellite laser altimetry data from ICESat and high altitude airborne laser scanning data from LVIS, as well as low altitude airborne LiDAR and terrestrial laser scanning data hosted at OpenTopography and UNAVCO. NLAS will develop new web service interfaces for NASA data archives at GSFC/LVIS and NSIDC in an effort to improve and streamline access to these data archives. The OpenTopography portal will act as a client to the NLAS services and will provide integrated

  20. Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds†

    PubMed Central

    Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

    2016-01-01

    Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average

  1. Temporal Analysis and Automatic Calibration of the Velodyne HDL-32E LiDAR System

    NASA Astrophysics Data System (ADS)

    Chan, T. O.; Lichti, D. D.; Belton, D.

    2013-10-01

    At the end of the first quarter of 2012, more than 600 Velodyne LiDAR systems had been sold worldwide for various robotic and high-accuracy survey applications. The ultra-compact Velodyne HDL-32E LiDAR has become a predominant sensor for many applications that require lower sensor size/weight and cost. For high accuracy applications, cost-effective calibration methods with minimal manual intervention are always desired by users. However, the calibrations are complicated by the Velodyne LiDAR's narrow vertical field of view and the very highly time-variant nature of its measurements. In the paper, the temporal stability of the HDL-32E is first analysed as the motivation for developing a new, automated calibration method. This is followed by a detailed description of the calibration method that is driven by a novel segmentation method for extracting vertical cylindrical features from the Velodyne point clouds. The proposed segmentation method utilizes the Velodyne point cloud's slice-like nature and first decomposes the point clouds into 2D layers. Then the layers are treated as 2D images and are processed with the Generalized Hough Transform which extracts the points distributed in circular patterns from the point cloud layers. Subsequently, the vertical cylindrical features can be readily extracted from the whole point clouds based on the previously extracted points. The points are passed to the calibration that estimates the cylinder parameters and the LiDAR's additional parameters simultaneously by constraining the segmented points to fit to the cylindrical geometric model in such a way the weighted sum of the adjustment residuals are minimized. The proposed calibration is highly automatic and this allows end users to obtain the time-variant additional parameters instantly and frequently whenever there are vertical cylindrical features presenting in scenes. The methods were verified with two different real datasets, and the results suggest that up to 78

  2. Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds.

    PubMed

    Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

    2016-06-17

    Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average

  3. Financial sustainability in municipal solid waste management--costs and revenues in Bahir Dar, Ethiopia.

    PubMed

    Lohri, Christian Riuji; Camenzind, Ephraim Joseph; Zurbrügg, Christian

    2014-02-01

    Providing good solid waste management (SWM) services while also ensuring financial sustainability of the system continues to be a major challenge in cities of developing countries. Bahir Dar in northwestern Ethiopia outsourced municipal waste services to a private waste company in 2008. While this institutional change has led to substantial improvement in the cleanliness of the city, its financial sustainability remains unclear. Is the private company able to generate sufficient revenues from their activities to offset the costs and generate some profit? This paper presents a cost-revenue analysis, based on data from July 2009 to June 2011. The analysis reveals that overall costs in Bahir Dar's SWM system increased significantly during this period, mainly due to rising costs related to waste transportation. On the other hand, there is only one major revenue stream in place: the waste collection fee from households, commercial enterprises and institutions. As the efficiency of fee collection from households is only around 50%, the total amount of revenues are not sufficient to cover the running costs. This results in a substantial yearly deficit. The results of the research therefore show that a more detailed cost structure and cost-revenue analysis of this waste management service is important with appropriate measures, either by the privates sector itself or with the support of the local authorities, in order to enhance cost efficiency and balance the cost-revenues towards cost recovery. Delays in mitigating the evident financial deficit could else endanger the public-private partnership (PPP) and lead to failure of this setup in the medium to long term, thus also endangering the now existing improved and currently reliable service. We present four options on how financial sustainability of the SWM system in Bahir Dar might be enhanced: (i) improved fee collection efficiency by linking the fees of solid waste collection to water supply; (ii) increasing the value

  4. Wallace Creek Virtual Field Trip: Teaching Geoscience Concepts with LiDAR

    NASA Astrophysics Data System (ADS)

    Robinson, S. E.; Arrowsmith, R.; Crosby, C. J.

    2009-12-01

    Recently available data such as LiDAR (Light Detection and Ranging) high-resolution topography can assist students to better visualize and understand geosciences concepts. It is important to bring these data into geosciences curricula as teaching aids while ensuring that the visualization tools, virtual environments, etc. do not serve as barriers to student learning. As a Southern California Earthquake Center ACCESS-G intern, I am creating a “virtual field trip” to Wallace Creek along the San Andreas Fault (SAF) using Google Earth as a platform and the B4 project LiDAR data. Wallace Creek is an excellent site for understanding the centennial-to-millennial record of SAF slip because of its dramatic stream offsets. Using the LiDAR data instead of, or alongside, traditional visualizations and teaching methods enhances a student’s ability to understand plate tectonics, the earthquake cycle, strike-slip faults, and geomorphology. Viewing a high-resolution representation of the topography in Google Earth allows students to analyze the landscape and answer questions about the behavior of the San Andreas Fault. The activity guides students along the fault allowing them to measure channel offsets using the Google Earth measuring tool. Knowing the ages of channels, they calculate slip rate. They look for the smallest channel offsets around Wallace Creek in order to determine the slip per event. At both a “LiDAR and Education” workshop and the Cyberinfrastructure Summer Institute for Geoscientists (CSIG), I presented the Wallace Creek activity to high school and college earth science teachers. The teachers were positive in their responses and had numerous important suggestions including the need for a teacher’s manual for instruction and scientific background, and that the student goals and science topics should be specific and well-articulated for the sake of both the teacher and the student. The teachers also noted that the technology in classrooms varies

  5. Decomposition of small-footprint full waveform LiDAR data based on generalized Gaussian model and grouping LM optimization

    NASA Astrophysics Data System (ADS)

    Ma, Hongchao; Zhou, Weiwei; Zhang, Liang; Wang, Suyuan

    2017-04-01

    Full waveform airborne Light Detection And Ranging(LiDAR) data contains abundant information which may overcome some deficiencies of discrete LiDAR point cloud data provided by conventional LiDAR systems. Processing full waveform data to extract more information than coordinate values alone is of great significance for potential applications. The Levenberg–Marquardt (LM) algorithm is a traditional method used to estimate parameters of a Gaussian model when Gaussian decomposition of full waveform LiDAR data is performed. This paper employs the generalized Gaussian mixture function to fit a waveform, and proposes using the grouping LM algorithm to optimize the parameters of the function. It is shown that the grouping LM algorithm overcomes the common drawbacks which arise from the conventional LM for parameter optimization, such as the final results being influenced by the initial parameters, possible algorithm interruption caused by non-numerical elements that occurred in the Jacobian matrix, etc. The precision of the point cloud generated by the grouping LM is evaluated by comparing it with those provided by the LiDAR system and those generated by the conventional LM. Results from both simulation and real data show that the proposed algorithm can generate a higher-quality point cloud, in terms of point density and precision, and can extract other information, such as echo location, pulse width, etc., more precisely as well.

  6. Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping.

    PubMed

    Qin, Yuchu; Li, Shihua; Vu, Tuong-Thuy; Niu, Zheng; Ban, Yifang

    2015-06-01

    Urban land cover map is essential for urban planning, environmental studies and management. This paper aims to demonstrate the potential of geometric and radiometric features derived from LiDAR waveform and point cloud data in urban land cover mapping with both parametric and non-parametric classification algorithms. Small footprint LiDAR waveform data acquired by RIEGL LMS-Q560 in Zhangye city, China is used in this study. A LiDAR processing chain is applied to perform waveform decomposition, range determination and radiometric characterization. With the synergic utilization of geometric and radiometric features derived from LiDAR data, urban land cover classification is then conducted using the Maximum Likelihood Classification (MLC), Support Vector Machines (SVM) and random forest algorithms. The results suggest that the random forest classifier achieved the most accurate result with overall classification accuracy of 91.82% and the kappa coefficient of 0.88. The overall accuracies of MLC and SVM are 84.02, and 88.48, respectively. The study suggest that the synergic utilization of geometric and radiometric features derived from LiDAR data can be efficiently used for urban land cover mapping, the non-parametric random forest classifier is a promising approach for the various features with different physical meanings.

  7. INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm.

    PubMed

    Gao, Yanbin; Liu, Shifei; Atia, Mohamed M; Noureldin, Aboelmagd

    2015-09-15

    This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory.

  8. INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm

    PubMed Central

    Gao, Yanbin; Liu, Shifei; Atia, Mohamed M.; Noureldin, Aboelmagd

    2015-01-01

    This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory. PMID:26389906

  9. LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments.

    PubMed

    Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha

    2015-07-10

    A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies-INS and LiDAR SLAM-into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform-NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment.

  10. Body-Art Practices Among Undergraduate Medical University Students in Dar Es Salaam, Tanzania, 2014

    PubMed Central

    Chacha, Chacha Emmanuel; Kazaura, Method R.

    2015-01-01

    Background: Body-art practices are increasing among adolescents and young adults. Although substantial data are available in developed countries, little has been documented about body-art practices in developing countries. Objective: To determine the magnitude, types and reasons for practicing body-art practices among undergraduate medical University students in Dar es Salaam, Tanzania. Materials and Methods: A cross-sectional descriptive study was conducteed among undergraduate University students in Dar es Salaam involving 536 respondents from two Universities. We used a self-administered questionnaire to collect data. Analyses were based on summary measures and bivariate analyses. Results: While 7.5% of undergraduate students reported having tattoos, 20% reported having body puncturing or piercing. Body piercing is reported more among female university undergraduate students than their male counterparts. Reported main reasons for undergoing body-art include “a mark of beauty,” 24%, “just wanted one,” 18% and “a mark of femininity or masculinity,” 17%. The majority (98%) of students were aware that unsafe body-art practices may lead to contracting HIV and more than half (52%) reported awareness of the risk of Hepatitis B infection. Conclusions: Despite high awareness of the potential risks involved in unsafe body arts that include tattoo and piercing, these practices are increasing among adolescents and young adults. There is need to have educational and counseling efforts so as to minimize associated health risks. PMID:25814729

  11. Research on high resolution spectral method of hyperspectral LiDAR

    NASA Astrophysics Data System (ADS)

    Li, Feng; Jiang, Chenghao; Zhu, Jingguo; Li, Menglin; Meng, Zhe

    2016-10-01

    Hyperspectral LiDAR using supercontinuum laser as light source, applying spectroscopic technology gets backscattered reflectance of different wavelengths, and can acquire both the geometry and spectral information on the target. Due to the development of the photoelectric sensor, hyperspectral LiDAR has fewer spectral channels, which limits its application in physical properties detection. To solve this problem, this paper proposes a new method based on the micro mirror array. By blaze grating, the supercontinuum laser is grating into monochromatic light in space, first projected to the micro mirror array, by controlling the micro mirror array flip, specific spectrum and reflection to corresponding photoelectric sensor channels, improve the spectral resolution. The micro mirror array photoelectric sensor resolution is much higher than the number of channels, through this method, can greatly improve the spectral resolution. In this paper, based on the micro mirror array, the simulation design is carried out and the feasibility of the method is verified by experiments. The simulation and experimental results show that the spectral resolution can be improved greatly by controlling the turning of the micro mirror.

  12. Automatic detection of zebra crossings from mobile LiDAR data

    NASA Astrophysics Data System (ADS)

    Riveiro, B.; González-Jorge, H.; Martínez-Sánchez, J.; Díaz-Vilariño, L.; Arias, P.

    2015-07-01

    An algorithm for the automatic detection of zebra crossings from mobile LiDAR data is developed and tested to be applied for road management purposes. The algorithm consists of several subsequent processes starting with road segmentation by performing a curvature analysis for each laser cycle. Then, intensity images are created from the point cloud using rasterization techniques, in order to detect zebra crossing using the Standard Hough Transform and logical constrains. To optimize the results, image processing algorithms are applied to the intensity images from the point cloud. These algorithms include binarization to separate the painting area from the rest of the pavement, median filtering to avoid noisy points, and mathematical morphology to fill the gaps between the pixels in the border of white marks. Once the road marking is detected, its position is calculated. This information is valuable for inventorying purposes of road managers that use Geographic Information Systems. The performance of the algorithm has been evaluated over several mobile LiDAR strips accounting for a total of 30 zebra crossings. That test showed a completeness of 83%. Non-detected marks mainly come from painting deterioration of the zebra crossing or by occlusions in the point cloud produced by other vehicles on the road.

  13. Identifying Ancient Settlement Patterns through LiDAR in the Mosquitia Region of Honduras

    PubMed Central

    Fernández-Diaz, Juan Carlos; Cohen, Anna S.; Neil Cruz, Oscar; Gonzáles, Alicia M.; Leisz, Stephen J.; Pezzutti, Florencia; Shrestha, Ramesh; Carter, William

    2016-01-01

    The Mosquitia ecosystem of Honduras occupies the fulcrum between the American continents and as such constitutes a critical region for understanding past patterns of socio-political development and interaction. Heavy vegetation, rugged topography, and remoteness have limited scientific investigation. This paper presents prehistoric patterns of settlement and landuse for a critical valley within the Mosquitia derived from airborne LiDAR scanning and field investigation. We show that (i) though today the valley is a wilderness it was densely inhabited in the past; (ii) that this population was organized into a three-tiered system composed of 19 settlements dominated by a city; and, (iii) that this occupation was embedded within a human engineered landscape. We also add to a growing body of literature that demonstrates the utility of LiDAR as means for rapid cultural assessments in undocumented regions for analysis and conservation. Our ultimate hope is for our work to promote protections to safeguard the unique and critically endangered Mosquitia ecosystem and other similar areas in need of preservation. PMID:27560962

  14. A comparison of waveform processing algorithms for single-wavelength LiDAR bathymetry

    NASA Astrophysics Data System (ADS)

    Wang, Chisheng; Li, Qingquan; Liu, Yanxiong; Wu, Guofeng; Liu, Peng; Ding, Xiaoli

    2015-03-01

    Due to the low-cost and lightweight units, single-wavelength LiDAR bathymetric systems are an ideal option for shallow-water (<12 m) bathymetry. However, one disadvantage of such systems is the lack of near-infrared and Raman channels, which results in difficulties in extracting the water surface. Therefore, the choice of a suitable waveform processing method is extremely important to guarantee the accuracy of the bathymetric retrieval. In this paper, we test six algorithms for single-wavelength bathymetric waveform processing, i.e. peak detection (PD), the average square difference function (ASDF), Gaussian decomposition (GD), quadrilateral fitting (QF), Richardson-Lucy deconvolution (RLD), and Wiener filter deconvolution (WD). To date, most of these algorithms have previously only been applied in topographic LiDAR waveforms captured over land. A simulated dataset and an Optech Aquarius dataset were used to assess the algorithms, with the focus being on their capability of extracting the depth and the bottom response. The influences of a number of water and equipment parameters were also investigated by the use of a Monte Carlo method. The results showed that the RLD method had a superior performance in terms of a high detection rate and low errors in the retrieved depth and magnitude. The attenuation coefficient, noise level, water depth, and bottom reflectance had significant influences on the measurement error of the retrieved depth, while the effects of scan angle and water surface roughness were not so obvious.

  15. Wet channel network extraction by integrating LiDAR intensity and elevation data

    NASA Astrophysics Data System (ADS)

    Hooshyar, Milad; Kim, Seoyoung; Wang, Dingbao; Medeiros, Stephen C.

    2015-12-01

    The temporal dynamics of stream networks are vitally important for understanding hydrologic processes including surface water and groundwater interaction and hydrograph recession. However, observations of wet channel networks are limited, especially in headwater catchments. Near-infrared LiDAR data provide an opportunity to map wet channel networks owing to the fine spatial resolution and strong absorption of light energy by water surfaces. A systematic method is developed to map wet channel networks by integrating elevation and signal intensity of ground returns. The signal intensity thresholds for identifying wet pixels are extracted from frequency distributions of intensity return within the convergent topography extent using a Gaussian mixture model. Moreover, the concept of edge in digital image processing, defined based on the intensity gradient, is utilized to enhance detection of small wet channels. The developed method is applied to the Lake Tahoe area based on eight LiDAR snapshots during recession periods in five watersheds. A power law relationship between streamflow and wetted channel length during recession periods is derived, and the scaling exponent (L∝Q0.44) is within the range of reported values from fieldwork in other regions.

  16. Genetic diversity of carotenoid-rich bananas evaluated by Diversity Arrays Technology (DArT).

    PubMed

    Amorim, Edson P; Vilarinhos, Alberto D; Cohen, Kelly O; Amorim, Vanusia B O; Dos Santos-Serejo, Janay A; Silva, Sebastião Oliveira E; Pestana, Kátia N; Dos Santos, Vânia J; Paes, Norma S; Monte, Damares C; Dos Reis, Ronaldo V

    2009-01-01

    The aim of this work was to evaluate the carotenoid content and genetic variability of banana accessions from the Musa germplasm collection held at Embrapa Cassava and Tropical Fruits, Brazil. Forty-two samples were analyzed, including 21 diploids, 19 triploids and two tetraploids. The carotenoid content was analyzed spectrophotometrically and genetic variability was estimated using 653 DArT markers. The average carotenoid content was 4.73 μg.g (-1) , and ranged from 1.06 μg.g (-1) for the triploid Nanica (Cavendish group) to 19.24 μg.g (-1) for the triploid Saney. The diploids Modok Gier and NBA-14 and the triploid Saney had a carotenoid content that was, respectively, 7-fold, 6-fold and 9-fold greater than that of cultivars from the Cavendish group (2.19 μg.g (-1)). The mean similarity among the 42 accessions was 0.63 (range: 0.24 to 1.00). DArT analysis revealed extensive genetic variability in accessions from the Embrapa Musa germplasm bank.

  17. Indirect Correspondence-Based Robust Extrinsic Calibration of LiDAR and Camera.

    PubMed

    Sim, Sungdae; Sock, Juil; Kwak, Kiho

    2016-06-22

    LiDAR and cameras have been broadly utilized in computer vision and autonomous vehicle applications. However, in order to convert data between the local coordinate systems, we must estimate the rigid body transformation between the sensors. In this paper, we propose a robust extrinsic calibration algorithm that can be implemented easily and has small calibration error. The extrinsic calibration parameters are estimated by minimizing the distance between corresponding features projected onto the image plane. The features are edge and centerline features on a v-shaped calibration target. The proposed algorithm contributes two ways to improve the calibration accuracy. First, we use different weights to distance between a point and a line feature according to the correspondence accuracy of the features. Second, we apply a penalizing function to exclude the influence of outliers in the calibration datasets. Additionally, based on our robust calibration approach for a single LiDAR-camera pair, we introduce a joint calibration that estimates the extrinsic parameters of multiple sensors at once by minimizing one objective function with loop closing constraints. We conduct several experiments to evaluate the performance of our extrinsic calibration algorithm. The experimental results show that our calibration method has better performance than the other approaches.

  18. Identifying Ancient Settlement Patterns through LiDAR in the Mosquitia Region of Honduras.

    PubMed

    Fisher, Christopher T; Fernández-Diaz, Juan Carlos; Cohen, Anna S; Neil Cruz, Oscar; Gonzáles, Alicia M; Leisz, Stephen J; Pezzutti, Florencia; Shrestha, Ramesh; Carter, William

    2016-01-01

    The Mosquitia ecosystem of Honduras occupies the fulcrum between the American continents and as such constitutes a critical region for understanding past patterns of socio-political development and interaction. Heavy vegetation, rugged topography, and remoteness have limited scientific investigation. This paper presents prehistoric patterns of settlement and landuse for a critical valley within the Mosquitia derived from airborne LiDAR scanning and field investigation. We show that (i) though today the valley is a wilderness it was densely inhabited in the past; (ii) that this population was organized into a three-tiered system composed of 19 settlements dominated by a city; and, (iii) that this occupation was embedded within a human engineered landscape. We also add to a growing body of literature that demonstrates the utility of LiDAR as means for rapid cultural assessments in undocumented regions for analysis and conservation. Our ultimate hope is for our work to promote protections to safeguard the unique and critically endangered Mosquitia ecosystem and other similar areas in need of preservation.

  19. The use of social media among adolescents in Dar es Salaam and Mtwara, Tanzania.

    PubMed

    Pfeiffer, Constanze; Kleeb, Matthis; Mbelwa, Alice; Ahorlu, Collins

    2014-05-01

    Social media form part of the rapid worldwide digital development that is re-shaping the life of many young people. While the use of social media by youths is increasingly researched in the North, studies about youth in the South are missing. It therefore remains unclear how social media can be included in interventions that aim at informing young people in many countries of the global South about sexual and reproductive health. This paper presents findings of a mixed-methods study of young people's user behaviour on the internet and specifically of social media as a platform for sexual health promotion in Tanzania. The study used questionnaires with 60 adolescents and in-depth interviews with eight students aged 15 to 19 years in Dar es Salaam, and in Mtwara, Southern Tanzania. Findings show that youth in Dar es Salaam and Mtwara access the internet mainly through mobile phones. Facebook is by far the most popular internet site. Adolescents highlighted their interest in reproductive and sexual health messages and updates being delivered through humorous posts, links and clips, as well as by youth role models like music stars and actors that are entertaining and reflect up-to-date trends of modern youth culture.

  20. Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas

    NASA Astrophysics Data System (ADS)

    Zhao, Xiaoqian; Guo, Qinghua; Su, Yanjun; Xue, Baolin

    2016-07-01

    Filtering of light detection and ranging (LiDAR) data into the ground and non-ground points is a fundamental step in processing raw airborne LiDAR data. This paper proposes an improved progressive triangulated irregular network (TIN) densification (IPTD) filtering algorithm that can cope with a variety of forested landscapes, particularly both topographically and environmentally complex regions. The IPTD filtering algorithm consists of three steps: (1) acquiring potential ground seed points using the morphological method; (2) obtaining accurate ground seed points; and (3) building a TIN-based model and iteratively densifying TIN. The IPTD filtering algorithm was tested in 15 forested sites with various terrains (i.e., elevation and slope) and vegetation conditions (i.e., canopy cover and tree height), and was compared with seven other commonly used filtering algorithms (including morphology-based, slope-based, and interpolation-based filtering algorithms). Results show that the IPTD achieves the highest filtering accuracy for nine of the 15 sites. In general, it outperforms the other filtering algorithms, yielding the lowest average total error of 3.15% and the highest average kappa coefficient of 89.53%.

  1. Genetic diversity of carotenoid-rich bananas evaluated by Diversity Arrays Technology (DArT)

    PubMed Central

    2009-01-01

    The aim of this work was to evaluate the carotenoid content and genetic variability of banana accessions from the Musa germplasm collection held at Embrapa Cassava and Tropical Fruits, Brazil. Forty-two samples were analyzed, including 21 diploids, 19 triploids and two tetraploids. The carotenoid content was analyzed spectrophotometrically and genetic variability was estimated using 653 DArT markers. The average carotenoid content was 4.73 μg.g -1 , and ranged from 1.06 μg.g -1 for the triploid Nanica (Cavendish group) to 19.24 μg.g -1 for the triploid Saney. The diploids Modok Gier and NBA-14 and the triploid Saney had a carotenoid content that was, respectively, 7-fold, 6-fold and 9-fold greater than that of cultivars from the Cavendish group (2.19 μg.g -1). The mean similarity among the 42 accessions was 0.63 (range: 0.24 to 1.00). DArT analysis revealed extensive genetic variability in accessions from the Embrapa Musa germplasm bank. PMID:21637652

  2. LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments

    PubMed Central

    Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha

    2015-01-01

    A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies—INS and LiDAR SLAM—into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform—NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment. PMID:26184206

  3. An Airborne Scanning LiDAR System for Ocean and Coastal Applications

    NASA Astrophysics Data System (ADS)

    Reineman, B. D.; Lenain, L.; Castel, D.; Melville, W. K.

    2008-12-01

    We have developed an airborne scanning LiDAR (Light Detection And Ranging) system and demonstrated its functionality for terrestrial and oceanographic measurements. Differential GPS (DGPS) and an Inertial Navigation System (INS) are synchronized with the LiDAR, providing end result vertical rms errors of approximately 6~cm. Flying 170~m above the surface, we achieve a point density of ~ 0.7 m-2 and a swath width of 90 to 120~m over ocean and 200~m over land. Georeferencing algorithms were developed in-house and earth-referenced data are available several hours after acquisition. Surveys from the system are compared with ground DGPS surveys and existing airborne surveys of fixed targets. Twelve research flights in a Piper Twin Comanche from August 2007 to July 2008 have provided topography of the Southern California coastline and sea surface wave fields in the nearshore ocean environment. Two of the flights also documented the results of the October 2007 landslide on Mt.~Soledad in La Jolla, California. Eight research flights aboard a Cessna Caravan surveyed the topography, lagoon, reef, and surrounding seas of Lady Elliot Island (LEI) in Australia's Great Barrier Reef in April 2008. We describe applications for the system, including coastal topographic surveys, wave measurements, reef research, and ship wake studies.

  4. Strata-based forest fuel classification for wild fire hazard assessment using terrestrial LiDAR

    NASA Astrophysics Data System (ADS)

    Chen, Yang; Zhu, Xuan; Yebra, Marta; Harris, Sarah; Tapper, Nigel

    2016-10-01

    Fuel structural characteristics affect fire behavior including fire intensity, spread rate, flame structure, and duration, therefore, quantifying forest fuel structure has significance in understanding fire behavior as well as providing information for fire management activities (e.g., planned burns, suppression, fuel hazard assessment, and fuel treatment). This paper presents a method of forest fuel strata classification with an integration between terrestrial light detection and ranging (LiDAR) data and geographic information system for automatically assessing forest fuel structural characteristics (e.g., fuel horizontal continuity and vertical arrangement). The accuracy of fuel description derived from terrestrial LiDAR scanning (TLS) data was assessed by field measured surface fuel depth and fuel percentage covers at distinct vertical layers. The comparison of TLS-derived depth and percentage cover at surface fuel layer with the field measurements produced root mean square error values of 1.1 cm and 5.4%, respectively. TLS-derived percentage cover explained 92% of the variation in percentage cover at all fuel layers of the entire dataset. The outcome indicated TLS-derived fuel characteristics are strongly consistent with field measured values. TLS can be used to efficiently and consistently classify forest vertical layers to provide more precise information for forest fuel hazard assessment and surface fuel load estimation in order to assist forest fuels management and fire-related operational activities. It can also be beneficial for mapping forest habitat, wildlife conservation, and ecosystem management.

  5. Optical turbulence profiling with SloDAR in the Canadian High Arctic

    NASA Astrophysics Data System (ADS)

    Maire, Jérôme; Mieda, Etsuko; Steinbring, Eric; Murowinski, Richard; Graham, James R.; Carlberg, Raymond; Wright, Shelley A.; Law, Nicholas M.; Sivanandam, Suresh

    2014-07-01

    The Earth's polar regions offer unique advantages for ground-based astronomical observations with its cold and dry climate, long periods of darkness, and the potential for exquisite image quality. We present preliminary results from a site-testing campaign during nighttime from October to November 2012 at the Polar Environment Atmospheric Research Laboratory (PEARL), on a 610-m high ridge near the Eureka weatherstation on Ellesmere Island, Canada. A Shack-Hartmann wavefront sensor was employed, using the Slope Detection and Ranging (SloDAR) method. This instrument (Mieda et al, this conference) was designed to measure the altitude, strength and variability of atmospheric turbulence, in particular for operation under Arctic conditions. First SloDAR optical turbulence profiles above PEARL show roughly half of the optical turbulence confined to the boundary layer, below about 1 km, with the majority of the remainder in one or two thin layers between 2 km and 5 km, or above. The median seeing during this campaign was measured to be 0.65 arcsec.

  6. Characterizing Croatian Wheat Germplasm Diversity and Structure in a European Context by DArT Markers.

    PubMed

    Novoselović, Dario; Bentley, Alison R; Šimek, Ruđer; Dvojković, Krešimir; Sorrells, Mark E; Gosman, Nicolas; Horsnell, Richard; Drezner, Georg; Šatović, Zlatko

    2016-01-01

    Narrowing the genetic base available for future genetic progress is a major concern to plant breeders. In order to avoid this, strategies to characterize and protect genetic diversity in regional breeding pools are required. In this study, 89 winter wheat cultivars released in Croatia between 1936 and 2006 were genotyped using 1,229 DArT (diversity array technology) markers to assess the diversity and population structure. In order to place Croatian breeding pool (CBP) in a European context, Croatian wheat cultivars were compared to 523 European cultivars from seven countries using a total of 166 common DArT markers. The results show higher genetic diversity in the wheat breeding pool from Central Europe (CE) as compared to that from Northern and Western European (NWE) countries. The most of the genetic diversity was attributable to the differences among cultivars within countries. When the geographical criterion (CE vs. NWE) was applied, highly significant difference between regions was obtained that accounted for 16.19% of the total variance, revealing that the CBP represents genetic variation not currently captured in elite European wheat. The current study emphasizes the important contribution made by plant breeders to maintaining wheat genetic diversity and suggests that regional breeding is essential to the maintenance of this diversity. The usefulness of open-access wheat datasets is also highlighted.

  7. LiDAR-Assisted identification of an active fault near Truckee, California

    USGS Publications Warehouse

    Hunter, L.E.; Howle, J.F.; Rose, R.S.; Bawden, G.W.

    2011-01-01

    We use high-resolution (1.5-2.4 points/m2) bare-earth airborne Light Detection and Ranging (LiDAR) imagery to identify, map, constrain, and visualize fault-related geomorphology in densely vegetated terrain surrounding Martis Creek Dam near Truckee, California. Bare-earth LiDAR imagery reveals a previously unrecognized and apparently youthful right-lateral strike-slip fault that exhibits laterally continuous tectonic geomorphic features over a 35-km-long zone. If these interpretations are correct, the fault, herein named the Polaris fault, may represent a significant seismic hazard to the greater Truckee-Lake Tahoe and Reno-Carson City regions. Three-dimensional modeling of an offset late Quaternary terrace riser indicates a minimum tectonic slip rate of 0.4 ?? 0.1 mm/yr.Mapped fault patterns are fairly typical of regional patterns elsewhere in the northern Walker Lane and are in strong coherence with moderate magnitude historical seismicity of the immediate area, as well as the current regional stress regime. Based on a range of surface-rupture lengths and depths to the base of the seismogenic zone, we estimate a maximum earthquake magnitude (M) for the Polaris fault to be between 6.4 and 6.9.

  8. Invasive Shrub Mapping in an Urban Environment from Hyperspectral and LiDAR-Derived Attributes

    PubMed Central

    Chance, Curtis M.; Coops, Nicholas C.; Plowright, Andrew A.; Tooke, Thoreau R.; Christen, Andreas; Aven, Neal

    2016-01-01

    Proactive management of invasive species in urban areas is critical to restricting their overall distribution. The objective of this work is to determine whether advanced remote sensing technologies can help to detect invasions effectively and efficiently in complex urban ecosystems such as parks. In Surrey, BC, Canada, Himalayan blackberry (Rubus armeniacus) and English ivy (Hedera helix) are two invasive shrub species that can negatively affect native ecosystems in cities and managed urban parks. Random forest (RF) models were created to detect these two species using a combination of hyperspectral imagery, and light detection and ranging (LiDAR) data. LiDAR-derived predictor variables included irradiance models, canopy structural characteristics, and orographic variables. RF detection accuracy ranged from 77.8 to 87.8% for Himalayan blackberry and 81.9 to 82.1% for English ivy, with open areas classified more accurately than areas under canopy cover. English ivy was predicted to occur across a greater area than Himalayan blackberry both within parks and across the entire city. Both Himalayan blackberry and English ivy were mostly located in clusters according to a Local Moran’s I analysis. The occurrence of both species decreased as the distance from roads increased. This study shows the feasibility of producing highly accurate detection maps of plant invasions in urban environments using a fusion of remotely sensed data, as well as the ability to use these products to guide management decisions. PMID:27818664

  9. Scintillation measurements at Bahir Dar during the high solar activity phase of solar cycle 24

    NASA Astrophysics Data System (ADS)

    Kriegel, Martin; Jakowski, Norbert; Berdermann, Jens; Sato, Hiroatsu; Wassaie Mersha, Mogese

    2017-01-01

    Small-scale ionospheric disturbances may cause severe radio scintillations of signals transmitted from global navigation satellite systems (GNSSs). Consequently, small-scale plasma irregularities may heavily degrade the performance of current GNSSs such as GPS, GLONASS or Galileo. This paper presents analysis results obtained primarily from two high-rate GNSS receiver stations designed and operated by the German Aerospace Center (DLR) in cooperation with Bahir Dar University (BDU) at 11.6° N, 37.4° E. Both receivers collect raw data sampled at up to 50 Hz, from which characteristic scintillation parameters such as the S4 index are deduced. This paper gives a first overview of the measurement set-up and the observed scintillation events over Bahir Dar in 2015. Both stations are located close to one another and aligned in an east-west, direction which allows us to estimate the zonal drift velocity and spatial dimension of equatorial ionospheric plasma irregularities. Therefore, the lag times of moving electron density irregularities and scintillation patterns are derived by applying cross-correlation analysis to high-rate measurements of the slant total electron content (sTEC) along radio links between a GPS satellite and both receivers and to the associated signal power, respectively. Finally, the drift velocity is derived from the estimated lag time, taking into account the geometric constellation of both receiving antennas and the observed GPS satellites.

  10. Indirect Correspondence-Based Robust Extrinsic Calibration of LiDAR and Camera

    PubMed Central

    Sim, Sungdae; Sock, Juil; Kwak, Kiho

    2016-01-01

    LiDAR and cameras have been broadly utilized in computer vision and autonomous vehicle applications. However, in order to convert data between the local coordinate systems, we must estimate the rigid body transformation between the sensors. In this paper, we propose a robust extrinsic calibration algorithm that can be implemented easily and has small calibration error. The extrinsic calibration parameters are estimated by minimizing the distance between corresponding features projected onto the image plane. The features are edge and centerline features on a v-shaped calibration target. The proposed algorithm contributes two ways to improve the calibration accuracy. First, we use different weights to distance between a point and a line feature according to the correspondence accuracy of the features. Second, we apply a penalizing function to exclude the influence of outliers in the calibration datasets. Additionally, based on our robust calibration approach for a single LiDAR-camera pair, we introduce a joint calibration that estimates the extrinsic parameters of multiple sensors at once by minimizing one objective function with loop closing constraints. We conduct several experiments to evaluate the performance of our extrinsic calibration algorithm. The experimental results show that our calibration method has better performance than the other approaches. PMID:27338416

  11. Invasive Shrub Mapping in an Urban Environment from Hyperspectral and LiDAR-Derived Attributes.

    PubMed

    Chance, Curtis M; Coops, Nicholas C; Plowright, Andrew A; Tooke, Thoreau R; Christen, Andreas; Aven, Neal

    2016-01-01

    Proactive management of invasive species in urban areas is critical to restricting their overall distribution. The objective of this work is to determine whether advanced remote sensing technologies can help to detect invasions effectively and efficiently in complex urban ecosystems such as parks. In Surrey, BC, Canada, Himalayan blackberry (Rubus armeniacus) and English ivy (Hedera helix) are two invasive shrub species that can negatively affect native ecosystems in cities and managed urban parks. Random forest (RF) models were created to detect these two species using a combination of hyperspectral imagery, and light detection and ranging (LiDAR) data. LiDAR-derived predictor variables included irradiance models, canopy structural characteristics, and orographic variables. RF detection accuracy ranged from 77.8 to 87.8% for Himalayan blackberry and 81.9 to 82.1% for English ivy, with open areas classified more accurately than areas under canopy cover. English ivy was predicted to occur across a greater area than Himalayan blackberry both within parks and across the entire city. Both Himalayan blackberry and English ivy were mostly located in clusters according to a Local Moran's I analysis. The occurrence of both species decreased as the distance from roads increased. This study shows the feasibility of producing highly accurate detection maps of plant invasions in urban environments using a fusion of remotely sensed data, as well as the ability to use these products to guide management decisions.

  12. Characterization of the OPAL LiDAR under controlled obscurant conditions

    NASA Astrophysics Data System (ADS)

    Cao, Xiaoying; Church, Philip; Matheson, Justin

    2016-05-01

    Neptec Technologies' OPAL-120 3D LiDAR is optimized for obscurant penetration. The OPAL-120 uses a scanning mechanism based on the Risley prism pair. The scan patterns are created by rotating two prisms under independent motor control. The geometry and material properties of the prisms define the conical field-of-view of the sensor, which can be built to between 60 to 120 degrees. The OPAL-120 was recently evaluated using a controlled obscurant chamber capable of generating clouds of obscurants over a depth of 22m. Obscurants used in this investigation include: Arizona road dust, water fog, and fog-oil. The obscurant cloud optical densities were monitored with a transmissometer. Optical depths values ranged from an upper value of 6 and progressively decreased to 0. Targets were positioned at the back of the obscurant chamber at a distance of 60m from the LiDAR. The targets are made of a foreground array of equally spaced painted wood stripes in front of a solid background. Reflectivity contrasts were achieved with foreground/background combinations of white/white, white/black and black/white. Data analysis will be presented on the effect of optical densities on range and cross-range resolution, and accuracy. The analysis includes the combinations of all obscurant types and target reflectivity contrasts.

  13. New SHARE 2010 HSI-LiDAR dataset: re-calibration, detection assessment and delivery

    NASA Astrophysics Data System (ADS)

    Ientilucci, Emmett J.

    2016-09-01

    This paper revisits hyperspectral data collected from the SpecTIR hyperspectral airborne Rochester Experiment (SHARE) in 2010. It has been determined that there were calibration issues in the SWIR portion of the data. This calibration issue is discussed and has been rectified. Approaches for calibration to radiance and compensation to reflectance are discussed based on in-scene information and radiative transfer codes. In addition to the entire flight line, a much large target detection test and evaluation chip has been created which includes an abundance of potential false alarms. New truth masks are created along with results from target detection algorithms. Co-registered LiDAR data is also presented. Finally, all ground truth information (ground photos, metadata, MODTRAN tape5, ASD ground spectral measurements, target truth masks, etc.), in addition to the HSI flight lines and co-registered LiDAR data, has been organized, packaged and uploaded to the Center for Imaging Science / Digital Imaging and Remote Sensing Lab web server for public use.

  14. Irrigation network extraction methodology from LiDAR DTM using Whitebox and ArcGIS

    NASA Astrophysics Data System (ADS)

    Mahor, M. A. P.; De La Cruz, R. M.; Olfindo, N. T.; Perez, A. M. C.

    2016-10-01

    Irrigation networks are important in distributing water resources to areas where rainfall is not enough to sustain agriculture. They are also crucial when it comes to being able to redirect vast amounts of water to decrease the risks of flooding in flat areas, especially near sources of water. With the lack of studies about irrigation feature extraction, which range from wide canals to small ditches, this study aims to present a method of extracting these features from LiDAR-derived digital terrain models (DTMs) using Geographic Information Systems (GIS) tools such as ArcGIS and Whitebox Geospatial Analysis Tools (Whitebox GAT). High-resolution LiDAR DTMs with 1-meter horizontal and 0.25-meter vertical accuracies were processed to generate the gully depth map. This map was then reclassified, converted to vector, and filtered according to segment length, and sinuosity to be able to isolate these irrigation features. Initial results in the test area show that the extraction completeness is greater than 80% when compared with data obtained from the National Irrigation Administration (NIA).

  15. Arrangements for enhanced measurements of a large turbine near-wake using LiDAR from the nacelle

    NASA Astrophysics Data System (ADS)

    Trujillo, J. J.; Rettenmeier, A.; Schlipf, D.

    2008-05-01

    New LiDAR techniques are being tested and developed to support the development of large offshore wind turbines. Our interest in this paper is concentrated in wake measurements; therefore, a pulsed standard LiDAR is adapted for fullscale wind field measurements from the nacelle of a large wind turbine. We show the conceptual framework for planned adaptations to a Windcube® LiDAR for operation at the nacelle of a 5 MW wind turbine. The standard scanning mode is to be modified to properly obtain downstream and also upstream wind speeds. The wind field measurements are intended for verification of models for near-wake wind speed, wake meandering and new predictive control estrategies.

  16. 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

  17. Modeling Urban Growth Spatial Dynamics: Case studies of Addis Ababa and Dar es Salaam

    NASA Astrophysics Data System (ADS)

    Buchta, Katja; Abo El Wafa, Hany; Printz, Andreas; Pauleit, Stephan

    2013-04-01

    Rapid urbanization, and consequently, the dramatic spatial expansion of mostly informal urban areas increases the vulnerability of African cities to the effects of climate change such as sea level rise, more frequent flooding, droughts and heat waves. The EU FP 7 funded project CLUVA (Climate Change and Urban Vulnerability in Africa, www.cluva.eu) aims to develop strategies for minimizing the risks of natural hazards caused by climate change and to improve the coping capacity of African cities. Green infrastructure may play a particular role in climate change adaptation by providing ecosystem services for flood protection, stormwater retention, heat island moderation and provision of food and fuel wood. In this context, a major challenge is to gain a better understanding of the spatial and temporal dynamics of the cities and how these impact on green infrastructure and hence their vulnerability. Urban growth scenarios for two African cities, namely Addis Ababa, Ethiopia and Dar es Salaam, Tanzania, were developed based on a characterization of their urban morphology. A population growth driven - GIS based - disaggregation modeling approach was applied. Major impact factors influencing the urban dynamics were identified both from literature and interviews with local experts. Location based factors including proximity to road infrastructure and accessibility, and environmental factors including slope, surface and flood risk areas showed a particular impact on urban growth patterns. In Addis Ababa and Dar es Salaam, population density scenarios were modeled comparing two housing development strategies. Results showed that a densification scenario significantly decreases the loss of agricultural and green areas such as forests, bushland and sports grounds. In Dar es Salaam, the scenario of planned new settlements with a population density of max. 350 persons per hectare would lead until 2025 to a loss of agricultural land (-10.1%) and green areas (-6.6%). On the other

  18. Coastal and tidal landform detection from high resolution topobathymetric LiDAR data

    NASA Astrophysics Data System (ADS)

    Skovgaard Andersen, Mikkel; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Brandbyge Ernstsen, Verner

    2016-04-01

    Coastal and tidal environments are valuable ecosystems, which, however, are under pressure in many areas around the world due to globalisation and/or climate change. Detailed mapping of these environments is required in order to manage the coastal zone in a sustainable way. However, historically these transition zones between land and water are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. The new generation of airborne topobathymetric light detection and ranging (LiDAR) potentially enables full-coverage and high-resolution mapping of these land-water transition zones. We have carried out topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the LiDAR point cloud with a mean point density in the order of 20 points/m2. The DEM was analysed morphometrically using a modification of the tool Benthic Terrain Modeler (BTM) developed by Wright et al. (2005). Initially, stage (the elevation in relation to tidal range) was used to divide the area of investigation into the different tidal zones, i.e. subtidal, intertidal and supratidal. Subsequently, morphometric units were identified and characterised by a combination of statistical neighbourhood analysis with varying window sizes (using the Bathymetric Positioning Index (BPI) from the BTM, moving average and standard deviation), slope parameters and area/perimeter ratios. Finally, these morphometric units were classified into six different types of landforms based on their stage and morphometric characteristics, i.e. either subtidal channel, intertidal flat, intertidal creek, linear bar, swash bar or beach dune. We hereby demonstrate the potential of using airborne topobathymetric LiDAR for seamless mapping of land

  19. Using LiDAR to Estimate Total Aboveground Biomass of Redwood Stands in the Jackson Demonstration State Forest, Mendocino, California

    NASA Astrophysics Data System (ADS)

    Rao, M.; Vuong, H.

    2013-12-01

    The overall objective of this study is to develop a method for estimating total aboveground biomass of redwood stands in Jackson Demonstration State Forest, Mendocino, California using airborne LiDAR data. LiDAR data owing to its vertical and horizontal accuracy are increasingly being used to characterize landscape features including ground surface elevation and canopy height. These LiDAR-derived metrics involving structural signatures at higher precision and accuracy can help better understand ecological processes at various spatial scales. Our study is focused on two major species of the forest: redwood (Sequoia semperirens [D.Don] Engl.) and Douglas-fir (Pseudotsuga mensiezii [Mirb.] Franco). Specifically, the objectives included linear regression models fitting tree diameter at breast height (dbh) to LiDAR derived height for each species. From 23 random points on the study area, field measurement (dbh and tree coordinate) were collected for more than 500 trees of Redwood and Douglas-fir over 0.2 ha- plots. The USFS-FUSION application software along with its LiDAR Data Viewer (LDV) were used to to extract Canopy Height Model (CHM) from which tree heights would be derived. Based on the LiDAR derived height and ground based dbh, a linear regression model was developed to predict dbh. The predicted dbh was used to estimate the biomass at the single tree level using Jenkin's formula (Jenkin et al 2003). The linear regression models were able to explain 65% of the variability associated with Redwood's dbh and 80% of that associated with Douglas-fir's dbh.

  20. 3-D earthquake surface displacements from differencing pre- and post-event LiDAR point clouds

    NASA Astrophysics Data System (ADS)

    Krishnan, A. K.; Nissen, E.; Arrowsmith, R.; Saripalli, S.

    2012-12-01

    The explosion in aerial LiDAR surveying along active faults across the western United States and elsewhere provides a high-resolution topographic baseline against which to compare repeat LiDAR datasets collected after future earthquakes. We present a new method for determining 3-D coseismic surface displacements and rotations by differencing pre- and post-earthquake LiDAR point clouds using an adaptation of the Iterative Closest Point (ICP) algorithm, a point set registration technique widely used in medical imaging, computer vision and graphics. There is no need for any gridding or smoothing of the LiDAR data and the method works well even with large mismatches in the density of the two point clouds. To explore the method's performance, we simulate pre- and post-event point clouds using real ("B4") LiDAR data on the southern San Andreas Fault perturbed with displacements of known magnitude. For input point clouds with ~2 points per square meter, we are able to reproduce displacements with a 50 m grid spacing and with horizontal and vertical accuracies of ~20 cm and ~4 cm. In the future, finer grids and improved precisions should be possible with higher shot densities and better survey geo-referencing. By capturing near-fault deformation in 3-D, LiDAR differencing with ICP will complement satellite-based techniques such as InSAR which map only certain components of the surface deformation and which often break down close to surface faulting or in areas of dense vegetation. It will be especially useful for mapping shallow fault slip and rupture zone deformation, helping inform paleoseismic studies and better constrain fault zone rheology. Because ICP can image rotations directly, the technique will also help resolve the detailed kinematics of distributed zones of faulting where block rotations may be common.

  1. Quantification of LiDAR measurement uncertainty through propagation of errors due to sensor sub-systems and terrain morphology

    NASA Astrophysics Data System (ADS)

    Goulden, T.; Hopkinson, C.

    2013-12-01

    The quantification of LiDAR sensor measurement uncertainty is important for evaluating the quality of derived DEM products, compiling risk assessment of management decisions based from LiDAR information, and enhancing LiDAR mission planning capabilities. Current quality assurance estimates of LiDAR measurement uncertainty are limited to post-survey empirical assessments or vendor estimates from commercial literature. Empirical evidence can provide valuable information for the performance of the sensor in validated areas; however, it cannot characterize the spatial distribution of measurement uncertainty throughout the extensive coverage of typical LiDAR surveys. Vendor advertised error estimates are often restricted to strict and optimal survey conditions, resulting in idealized values. Numerical modeling of individual pulse uncertainty provides an alternative method for estimating LiDAR measurement uncertainty. LiDAR measurement uncertainty is theoretically assumed to fall into three distinct categories, 1) sensor sub-system errors, 2) terrain influences, and 3) vegetative influences. This research details the procedures for numerical modeling of measurement uncertainty from the sensor sub-system (GPS, IMU, laser scanner, laser ranger) and terrain influences. Results show that errors tend to increase as the laser scan angle, altitude or laser beam incidence angle increase. An experimental survey over a flat and paved runway site, performed with an Optech ALTM 3100 sensor, showed an increase in modeled vertical errors of 5 cm, at a nadir scan orientation, to 8 cm at scan edges; for an aircraft altitude of 1200 m and half scan angle of 15°. In a survey with the same sensor, at a highly sloped glacial basin site absent of vegetation, modeled vertical errors reached over 2 m. Validation of error models within the glacial environment, over three separate flight lines, respectively showed 100%, 85%, and 75% of elevation residuals fell below error predictions. Future

  2. Measuring the effects of morphological changes to sea turtle nesting beaches over time with LiDAR data

    NASA Astrophysics Data System (ADS)

    Yamamoto, Kristina H.; Anderson, Sharolyn J.; Sutton, Paul C.

    2015-10-01

    Sea turtle nesting beaches in southeastern Florida were evaluated for changes from 1999 to 2005 using LiDAR datasets. Changes to beach volume were correlated with changes in several elevation-derived characteristics, such as elevation and slope. In addition, these changes to beach geomorphology were correlated to changes in nest success, illustrating that beach alterations may affect sea turtle nesting behavior. The ability to use LiDAR datasets to quickly and efficiently conduct beach comparisons for habitat use represents another benefit to this high spatial resolution data.

  3. Quantification of L-band InSAR decorrelation in volcanic terrains using airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Sedze, M.; Heggy, E.; Jacquemoud, S.; Bretar, F.

    2011-12-01

    Repeat-pass InSAR LOS measurements of the Piton de La Fournaise (La Reunion Island, France) suffer from substantial phase decorrelation due to the occurrence of vegetation and ash deposits on the caldera and slopes of the edifice. To correct this deficiency, we combine normalized airborne LiDAR (Light Detection and Ranging) intensity data with spaceborne InSAR coherence images from ALOS PALSAR L-band acquired over the volcano in 2008 and 2009, following the 2007 major eruption. The fusion of the two data sets improves the calculation of coherence and the textural classification of different volcanic surfaces. For future missions considering both InSAR and/or LiDAR such as DESDynI (Deformation, Ecosystem Structure and Dynamics of Ice), such data fusion studies can provide a better analysis of the spatiotemporal variations in InSAR coherence in order to enhance the monitoring of pre-eruptive ground displacements. The airborne surveys conducted in 2008 and 2009, cover different types of vegetation and terrain roughness on the central and western parts of the volcano. The topographic data are first processed to generate a high-resolution digital terrain model (DTM) of the volcanic edifice with elevation accuracy better than 1 m. For our purposes, the phase variations caused by the surface relief can be eliminated using the LiDAR-derived DTM. Then normalized LiDAR intensities are correlated to the L-band polarimetric coherence for different zones of the volcano to assess the LiDAR-InSAR statistical behavior of different lava flows, pyroclastics, and vegetated surfaces. Results suggest that each volcanic terrain type is characterized by a unique LiDAR-InSAR histogram pattern. We identified four LiDAR-InSAR distinguished relations: (1) pahoehoe lava flow surfaces show an agglomerate histogram pattern which may be explained by low surface scattering and low wave penetration into the geological medium; (2) eroded a'a lava surfaces is characterized by high standard deviation

  4. Diameter at breast height estimation in Mt. Makiling, Laguna, Philippines using metrics derived from airborne LiDAR data and Worldview-2 bands

    NASA Astrophysics Data System (ADS)

    Tandoc, Fe Andrea M.; Paringit, Enrico C.; Bantayan, Nathaniel C.; Argamosa, Reginald Jay L.; Faelga, Regine Anne G.; Ibañez, Carlyn Ann G.; Posilero, Mark Anthony V.; Zaragosa, Gio P.; Malabanan, Matthew V.

    2016-05-01

    Airborne LiDAR is fast becoming an innovation for forest inventory. It aids in obtaining forest characteristics in areas or cases where actual field inventory would be very tedious. This study aims to estimate diameter at breast height (DBH) using airborne LiDAR point-cloud parameters with Worldview-2 satellite images, and to validate these with actual measurements done in the field. The study site is a field plot with forest inventory at Mt. Makiling, Laguna, Philippines that was surveyed into 20m, 10m and 5m subplots or grids. The estimation of DBH was carried out by extracting the said parameters from the LiDAR point-cloud, and extracting different bands from the Worldview image and performing linear and log-linear regression of these values. The regressions were done in four different cases, namely: LiDAR parameters without intensity (case1), LiDAR parameters without intensity with Worldview bands (case 2), intensity of LiDAR points (case 3), and LiDAR parameters with intensity and Worldview bands (case 4). From these it was found that the best case for estimating DBH is with the use of LiDAR parameters with intensity and Worldview bands in a 10x10 grid, in Log-Linear regression with a root mean squared error of 1.96 cm and an adjusted R2 value of 0.65. This was further improved through stepwise regression, and adjusted R2 value was 0.71.

  5. 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

  6. Long-term persistence of throughfall yield assessed by small footprint LiDAR data

    NASA Astrophysics Data System (ADS)

    Bischoff, Sebastian; Levia, Delphis F.; Nieschulze, Jens; Schulz, Florian; Michalzik, Beate

    2016-04-01

    Throughfall (TF) represents an important relocation mechanism for the spatial distribution of intercepted precipitation and hence associated nutrients in wooded ecosystems. To date, a broad range of studies showed that the spatial patterns of TF distribution exhibit a pronounced temporal stability. These studies, however, have examined TF temporal stability at the tree scale or they were computed from event-based data. Here, we seek to evaluate the utility of temporally aggregated TF data at one, three, and six year intervals to determine whether such long-term TF monitoring data could serve as the basis for TF temporal persistence measurements for both beech and spruce forests. In addition, we examine the temporal persistence of TF in relation to small footprint LiDAR data. In context of the German Science Foundation (DFG) founded "Biodiversity Exploratories" (www.biodiversity-exploratories.de) we studied water-bound nutrient fluxes on a set of three differently managed forest plots (spruce plantation, age class forest beech, unmanaged beech) in central Germany throughout the vegetation periods of 2010 - 2015. For long-term monitoring purposes, TF samples were collected in biweekly routine sampling intervals using X-shaped transects of 20 bulk samplers (axis length 32 m) per experimental plot. In this study, we aim to identify canopy structural parameters explaining the temporal patterns observed. We therefore used small footprint LiDAR (Light Detection And Ranging) data to calculate several canopy structural parameters on base of a gridded canopy model (grid cell resolution = 0.75 m). As LiDAR allows a three-dimensional description of the complex forest canopy structure it might help to extend our understanding of complex canopy processes influencing the spatial dispersal of precipitation water, and hence associated nutrient fluxes, in wooded ecosystems. Preliminary data analysis reveals that normalized TF values identify a number of TF collectors on each of the

  7. Human Impact Intertwined with Glacial Legacy: Hydro-Geomorphologic Exploration using LiDAR data

    NASA Astrophysics Data System (ADS)

    Yan, Q.; Kumar, P.

    2014-12-01

    Intensively managed landscapes (IMLs) in the Midwestern United States are heavily modified by agriculture, artificial drainage, deforestation, urbanization, and wetland destruction. These landscapes have been shaped by repeated glacial events over geologic time scales followed with rapid human modifications for agriculture and drainage that are overlaid on extremely low gradient stream networks. In this study, using LiDAR data from the Upper Sangamon River Basin in Illinois, we attempt to understand how the long-term glacial legacy has shaped the landscape and what is the impact from short-term human activities, such as channel straightening and periodic dredging. Glacial and human legacy impact landscape dynamics simultaneously. Therefore, we evaluate the present-day dynamics of landscapes by attempting to address several questions. First, we explore whether the watershed is in equilibrium conditions or away from it due to human activities. Second, we study how this relates to the degree of maturity in the river valley. Moreover, we map the spatial distributions of terraces and floodplains to understand depositional and erosional history. High-resolution LiDAR data is ideal for such a study as it reveals the impact of both glacial episodes and human activities. Methods used for extraction of useful information from LiDAR data include the TerEx tool, Stream Profiler, and Hec-GeoRas, among others. We analyze the terrace and floodplain geomorphic features, quantify stream sinuosity, and cross section geometries. An integral method is built based on stream power incision model to obtain sub-basin steady state condition. These features help to reveal local and global watershed properties. A bounded relationship between terraces/floodplains, sinuosity, cross section maturity, as well as sub-basin equilibrium condition is explored. In general, we find that the glacial legacy and present-day human activity have opposed each other in regards to the sub-basin equilibrium

  8. Sexual behaviour among youths at high risk for HIV-1 infection in Dar es Salaam, Tanzania

    PubMed Central

    Mwakagile, D; Mmari, E; Makwaya, C; Mbwana, J; Biberfeld, G; Mhalu, F; Sandstrom, E

    2001-01-01

    Objectives: To investigate sex specific sexual behaviour in youths visiting a youth clinic for sexual and reproductive health in Dar es Saalam. Methods: A questionnaire was administered to a random sample of youths between 10 and 24 years of age attending the youth health clinic in Dar es Saalam. The clinical investigation included testing for syphilis and HIV-1 antibodies Results: 1423 youths attended the clinic between September 1997 and August 1998. The study population comprised 213 (53.5%) males and 185 (46.5%) females. 97 (24.4%) were below 20 years. The mean age at coitarche was 16.5 and 17.0 years of age for males and females, respectively. The coitarche was involuntary in 15 females (8.6%). 49.5% males reported more than five lifetime partners compared with 14.1% for females (p<0.0001). Males reported recent partners to be 2.5 years younger, while females reported them to be 5.0 years older. No contraceptive use was reported by 29.7% of the males and 40.3% of females. 52.7% females had been pregnant and 26 (14.1%) reported induced abortions. Genital discharge was found in 69.5% and 73.9% and GUD in 36.6% and 27.1% of males and females respectively. 12 males (5.9%) and 43 females (24.6%) were found to be HIV-1 infected. 13.8% of the females with only one lifetime partner were HIV-1 infected compared with 40.9% with more than five partners (p = 0.028). Conclusions: Many youths in Dar es Salaam engage in sexual behaviours that put them at risk of unwanted pregnancies and STIs including HIV infection. Female youths were more likely to contract HIV infection than males. In African urban areas youth oriented clinics can have a pivotal role in HIV/STI prevention and control Key Words: youth; sexual behaviour; HIV PMID:11463924

  9. A LiDAR intensity correction model for vertical geological mapping

    NASA Astrophysics Data System (ADS)

    Carrea, Dario; Humair, Florian; Matasci, Battista; Abellan, Antonio; Derron, Marc-Henri; Jaboyedoff, Michel

    2015-04-01

    Ground-based LiDAR has been traditionally used for surveying purposes via 3D point clouds. In addition to XYZ coordinates, an intensity attribute is also recorded by the LiDAR devices but this parameter is rarely used for geological applications. The intensity of the backscattered signal can be a significant source of information in different geological applications, such as geological remote mapping of vertical surfaces, mineral exploration, stratigraphy, engineering, etc. However, the Intensity value recorded by the LiDAR is a function of several external parameters, thus a correction of the raw intensity information is required prior to make use of this parameter. This study proposes an intensity correction model which takes into account of the range, the incidence angle and the surface roughness based on Oren-Nayar reflectance model (Oren and Nayar, 1994). The Oren-Nayar reflectance model is based on the idea that a surface is composed of micro-facets of various slope angles. The simplified version of this model requires only one parameter to characterize a surface, the standard deviation of the slope angle of the facets. Different discrete pulse laser scanners of Optech's ILRIS category were used to understand how the back-scattered intensity evolves in function of range and incidence angle. This was performed by carrying out different indoor and outdoor experiments, using the following targets: 1) mobile 2m2 board covered by black/white paper, 2) white plaster corridor walls and 3) finally on natural outcrops. First of all, we carried out a simple experiment by placing the mobile board at different distances ranging from 10 to 1000 meters. The analysis of the datasets revealed that the intensity of the backscattered signal decreases with the square of the range to the target, as was expected. However, both for the wall and the natural outcrops, the influence of the incidence angle appears to be more complex than the classical cosine law due to the roughness

  10. Fusion of LiDAR and aerial imagery for the estimation of downed tree volume using Support Vector Machines classification and region based object fitting

    NASA Astrophysics Data System (ADS)

    Selvarajan, Sowmya

    The study classifies 3D small footprint full waveform digitized LiDAR fused with aerial imagery to downed trees using Support Vector Machines (SVM) algorithm. Using small footprint waveform LiDAR, airborne LiDAR systems can provide better canopy penetration and very high spatial resolution. The small footprint waveform scanner system Riegl LMS-Q680 is addition with an UltraCamX aerial camera are used to measure and map downed trees in a forest. The various data preprocessing steps helped in the identification of ground points from the dense LiDAR dataset and segment the LiDAR data to help reduce the complexity of the algorithm. The haze filtering process helped to differentiate the spectral signatures of the various classes within the aerial image. Such processes, helped to better select the features from both sensor data. The six features: LiDAR height, LiDAR intensity, LiDAR echo, and three image intensities are utilized. To do so, LiDAR derived, aerial image derived and fused LiDAR-aerial image derived features are used to organize the data for the SVM hypothesis formulation. Several variations of the SVM algorithm with different kernels and soft margin parameter C are experimented. The algorithm is implemented to classify downed trees over a pine trees zone. The LiDAR derived features provided an overall accuracy of 98% of downed trees but with no classification error of 86%. The image derived features provided an overall accuracy of 65% and fusion derived features resulted in an overall accuracy of 88%. The results are observed to be stable and robust. The SVM accuracies were accompanied by high false alarm rates, with the LiDAR classification producing 58.45%, image classification producing 95.74% and finally the fused classification producing 93% false alarm rates The Canny edge correction filter helped control the LiDAR false alarm to 35.99%, image false alarm to 48.56% and fused false alarm to 37.69% The implemented classifiers provided a powerful tool for

  11. A temperature calibration method for CDOM fluorescence LIF LiDAR

    NASA Astrophysics Data System (ADS)

    Chen, Peng; Mao, Zhihua; Huang, Haiqing; Bai, Yan; Wang, Tianyu

    2016-10-01

    The influence of temperature variations on the determined concentrations of dissolved organic matter (DOM) in water was investigated by laser induced fluorescence (LIF) technique in laboratory. The effect of temperature on CDOM fluorescence was investigated in freshwaters of Xixi River and in aqueous standards. The total luminescence spectra (TLS) of CDOM in several types of water samples with laser-induced fluorescence (LIF) measurements using a 405 nm wavelength excitation source were measured in the laboratory. A temperature calibration equation was derived to standardize CDOM fluorescence measurements to a specific reference temperature. Laboratory experiments with a portable LIF LiDAR showed that CDOM fluorescence intensity decreased as ambient water temperature increased. High correlation (R2=0.91) was observed between concentration of CDOM and fluorescence normalized to water Raman scattering with the temperature calibration method. The results demonstrated that temperature calibration is a necessary and important aspect of CDOM monitoring using in situ fluorescence sensors.

  12. Potential Landslide Detection with Fractal and Roughness by LiDAR Data in Taiwan

    NASA Astrophysics Data System (ADS)

    Cheng, Youg-Sin; Yu, Teng-To

    2015-04-01

    The purpose of this study is to detect the potential landslides since they would be triggered by heavy rain, earthquake and/or larger degree of geomorphology alteration under different terrain characteristics. Not only the newly area but also the past landslide area would generate landslide after serious events. To gather the newly landslides and past landslides overwhelmed by thick vegetation, LiDAR could produce the high resolution DEM, denote actual surface terrain information and identify landform with a spatial resolution of 1m in different time interval. The 1-m interval DEM of Laonong watershed of southern Taiwan is utilized by fractal and roughness calculating with MATLAB code. DEM, aspect, and slope images are adopted to improve the accuracy of potential landslide detection with the random forest (RF) classifier. In present study, we provide the analysis results of the potential landslide area including these features calculation.

  13. Analysis of airborne LiDAR as a basis for digital soil mapping in Alpine areas

    NASA Astrophysics Data System (ADS)

    Kringer, K.; Tusch, M.; Geitner, C.; Meißl, G.; Rutzinger, M.

    2009-04-01

    Especially in mountainous regions like the Alps the formation of soil is highly influenced by relief characteristics. Among all factors included in Jenny's (1941) model for soil development, relief is the one most commonly used in approaches to create digital soil maps and to derive soil properties from secondary data sources (McBratney et al. 2003). Elevation data, first order (slope, aspect) and second order derivates (plan, profile and cross-sectional curvature) as well as complex morphometric parameters (various landform classifications, e.g., Wood 1996) and compound indices (e.g., topographic wetness indices, vertical distance to drainage network, insolation) can be calculated from digital elevation models (DEM). However, while being an important source of information for digital soil mapping on small map scales, "conventional" DEMs are of limited use for the design of large scale conceptual soil maps for small areas due to rather coarse raster resolutions with cell sizes ranging from 20 to 100 meters. Slight variations in elevation and small landform features might not be discernible even though they might have a significant effect to soil formation, e.g., regarding the influence of groundwater in alluvial soils or the extent of alluvial fans. Nowadays, Airborne LiDAR (Light Detection And Ranging) provides highly accurate data for the elaboration of high-resolution digital terrain models (DTM) even in forested areas. In the project LASBO (Laserscanning in der Bodenkartierung) the applicability of digital terrain models derived from LiDAR for the identification of soil-relevant geomorphometric parameter is investigated. Various algorithms which were initially designed for coarser raster data are applied on high-resolution DTMs. Test areas for LASBO are located in the region of Bruneck (Italy) and near the municipality of Kramsach in the Inn Valley (Austria). The freely available DTM for Bruneck has a raster resolution of 2.5 meters while in Kramsach a DTM with

  14. How integrating 3D LiDAR data in the dike surveillance protocol: The French case

    NASA Astrophysics Data System (ADS)

    Bretar, F.; Mériaux, P.; Fauchard, C.

    2012-04-01

    carried out. A LiDAR system is able to acquire data on a dike structure of up to 80 km per day, which makes the use of this technique also valuable in case of emergency situations. It provides additional valuable products like precious information on dike slopes and crest or their near environment (river banks, etc.). Moreover, in case of vegetation, LiDAR data makes possible to study hidden structures or defaults from images like the erosion of riverbanks under forestry vegetation. The possibility of studying the vegetation is also of high importance: the development of woody vegetation near or onto the dike is a major risk factor. Surface singularities are often signs of disorder or suspected disorder in the dike itself: for example a subsidence or a sinkhole on a ridge may result from internal erosion collapse. Finally, high resolution topographic data contribute to build specific geomechanical model of the dike that, after incorporating data provided by geophysical and geotechnical surveys, are integrated in the calculations of the structure stability. Integrating the regular use of LiDAR data in the dike surveillance protocol is not yet operational in France. However, the high number of French stakeholders at the national level (on average, there is one stakeholder for only 8-9km of dike !) and the real added value of LiDAR data makes a spatial data infrastructure valuable (webservices for processing the data, consulting and filling the database on the field when performing the local diagnosis)

  15. Subtropical Forest Biomass Estimation Using Airborne LiDAR and Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Pang, Yong; Li, Zengyuan

    2016-06-01

    Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF's (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province in the Southwest of China. The study site contains typical subtropical species of coniferous forest, evergreen broadleaf forest, and some other mixed forests. The hypersectral images were orthorectified and corrected into surface reflectance with support of Lidar DTM product. The fusion of Lidar and hyperspectral can classify dominate forest types. The lidar metrics improved the classification accuracy. Then forest biomass estimation was carried out for each dominate forest types using waveform Lidar data, which get improved than single Lidar data source.

  16. A gradient-constrained morphological filtering algorithm for airborne LiDAR

    NASA Astrophysics Data System (ADS)

    Li, Yong; Wu, Huayi; Xu, Hanwei; An, Ru; Xu, Jia; He, Qisheng

    2013-12-01

    This paper presents a novel gradient-constrained morphological filtering algorithm for bare-earth extraction from light detection and ranging (LiDAR) data. Based on the gradient feature points determined by morphological half-gradients, the potential object points are located prior to filtering. Innovative gradient-constrained morphological operations are created, which are executed only for the potential object points. Compared with the traditional morphological operations, the new operations reduce many meaningless operations for object removal and consequently decrease the possibility of losing terrain to a great extent. The applicability and reliability of this algorithm are demonstrated by evaluating the filtering performance for fifteen sample datasets in various complex scenes. The proposed algorithm is found to achieve a high level of accuracy compared with eight other filtering algorithms tested by the International Society for Photogrammetry and Remote Sensing. Moreover, the proposed algorithm has minimal error oscillation for different landscapes, which is important for quality control of digital terrain model generation.

  17. Urban mosquitoes, situational publics, and the pursuit of interspecies separation in Dar es Salaam

    PubMed Central

    KELLY, ANN H.; LEZAUN, JAVIER

    2014-01-01

    Recent work in anthropology points to the recognition of multispecies entanglements as the grounds for a more ethical politics. In this article, we examine efforts to control mosquitoes in Dar es Salaam, Tanzania, as an example of the laborious tasks of disentanglement that characterize public health interventions. The mosquito surveillance and larval elimination practices of an urban malaria control program offer an opportunity to observe how efforts to create distance between species relate to the physical and civic textures of the city. Seen in the particular context of the contemporary African metropolis, the work of public health appears less a matter of control than a commitment to constant urban maintenance and political mobilization. PMID:25429167

  18. Climate change induced risk analysis of Dar es Salaam city (Tanzania)

    NASA Astrophysics Data System (ADS)

    Topa, Maria Elena; Herslund, Lise; Cavan, Gina; Printz, Andreas; Simonis, Ingo; Bucchignani, Edoardo; Jean-Baptiste, Nathalie; Hellevik, Siri; Johns, Regina; Kibassa, Deusdedit; Kweka, Clara; Magina, Fredrick; Mangula, Alpha; Mbuya, Elinorata; Uhinga, Guido; Kassenga, Gabriel; Kyessi, Alphonce; Shemdoe, Riziki; Kombe, Wilbard

    2013-04-01

    CLUVA (CLimate change and Urban Vulnerability in Africa; http://www.cluva.eu/) is a 3 years project, funded by the European Commission in 2010. The main objective of CLUVA is to develop context-centered methods and knowledge to be applied to African cities to assess vulnerabilities and increase knowledge on managing climate related risks. The project estimates the impacts of climate changes in the next 40 years at urban scale and downscales IPCC climate projections to evaluate specific threats to selected African test cities. These are mainly from floods, sea-level rise, droughts, heat waves, and desertification. The project evaluates and links: social vulnerability; urban green structures and ecosystem services; urban-rural interfaces; vulnerability of urban built environment and lifelines; and related institutional and governance dimensions of adaptation. The multi-scale and multi-disciplinary qualitative, quantitative and probabilistic approach of CLUVA is currently being applied to selected African test cities (Addis Ababa - Ethiopia; Dar es Salaam - Tanzania; Douala - Cameroun; Ouagadougou - Burkina Faso; St. Louis - Senegal). In particular, the poster will present preliminary findings for the Dar es Salaam case study. Dar es Salaam, which is Tanzania's largest coastal city, is exposed to floods, coastal erosion, droughts and heat waves, and highly vulnerable to impacts as a result of ineffective urban planning (about 70% unplanned settlements), poverty and lack of basic infrastructure (e.g. lack of or poor quality storm water drainage systems). Climate change could exacerbate the current situation increasing hazard-exposure alongside the impacts of development pressures which act to increase urban vulnerability for example because of informal (unregulated) urbanization. The CLUVA research team - composed of climate and environmental scientists, risk management experts, urban planners and social scientists from both European and African institutions - has

  19. Joint Temperature-Lasing Mode Compensation for Time-of-Flight LiDAR Sensors

    PubMed Central

    Alhashimi, Anas; Varagnolo, Damiano; Gustafsson, Thomas

    2015-01-01

    We propose an expectation maximization (EM) strategy for improving the precision of time of flight (ToF) light detection and ranging (LiDAR) scanners. The novel algorithm statistically accounts not only for the bias induced by temperature changes in the laser diode, but also for the multi-modality of the measurement noises that is induced by mode-hopping effects. Instrumental to the proposed EM algorithm, we also describe a general thermal dynamics model that can be learned either from just input-output data or from a combination of simple temperature experiments and information from the laser’s datasheet. We test the strategy on a SICK LMS 200 device and improve its average absolute error by a factor of three. PMID:26690445

  20. Fusion of terrestrial LiDAR and tomographic mapping data for 3D karst landform investigation

    NASA Astrophysics Data System (ADS)

    Höfle, B.; Forbriger, M.; Siart, C.; Nowaczinski, E.

    2012-04-01

    Highly detailed topographic information has gained in importance for studying Earth surface landforms and processes. LiDAR has evolved into the state-of-the-art technology for 3D data acquisition on various scales. This multi-sensor system can be operated on several platforms such as airborne LS (ALS), mobile LS (MLS) from moving vehicles or stationary on ground (terrestrial LS, TLS). In karst research the integral investigation of surface and subsurface components of solution depressions (e.g. sediment-filled dolines) is required to gather and quantify the linked geomorphic processes such as sediment flux and limestone dissolution. To acquire the depth of the different subsurface layers, a combination of seismic refraction tomography (SRT) and electrical resistivity tomography (ERT) is increasingly applied. This multi-method approach allows modeling the extension of different subsurface media (i.e. colluvial fill, epikarst zone and underlying basal bedrock). Subsequent fusion of the complementary techniques - LiDAR surface and tomographic subsurface data - first-time enables 3D prospection and visualization as well as quantification of geomorphometric parameters (e.g. depth, volume, slope and aspect). This study introduces a novel GIS-based method for semi-automated fusion of TLS and geophysical data. The study area is located in the Dikti Mountains of East Crete and covers two adjacent dolines. The TLS data was acquired with a Riegl VZ-400 scanner from 12 scan positions located mainly at the doline divide. The scan positions were co-registered using the iterative closest point (ICP) algorithm of RiSCAN PRO. For the digital elevation rasters a resolution of 0.5 m was defined. The digital surface model (DSM) of the study was derived by moving plane interpolation of all laser points (including objects) using the OPALS software. The digital terrain model (DTM) was generated by iteratively "eroding" objects in the DSM by minimum filter, which additionally accounts for

  1. Tropical Airborne LiDAR for Landslide Assessment in Malaysia: a technical perspective

    NASA Astrophysics Data System (ADS)

    Abd Manap, Mohamad; Azhari Razak, Khamarrul; Mohamad, Zakaria; Ahmad, Azhari; Ahmad, Ferdaus; Mohamad Zin, Mazlan; A'zad Rosle, Qalam

    2015-04-01

    Malaysia has faced a substantial number of landslide events every year. Cameron Highlands, Pahang is one of the badly areas affected by slope failures characterized by extreme climate, rugged topographic and weathered geological structures in a tropical environment. A high frequency of landslide occurrence in the hilly areas is predominantly due to the geological materials, tropical monsoon seasons and uncontrolled agricultural activities. Therefore the Government of Malaysia through the Prime Minister Department has allocated a special budget to conduct national level hazard and risk mapping project through Minerals and Geoscience Department Malaysia, the Ministry of Natural Resources and Environment. The primary aim of this project is to provide slope hazard risk information for a better slope management in Malaysia. In addition this project will establish national infrastructure for geospatial information on the geological terrain and slope by emphasizing the disaster risk throughout the country. The areas of interest are located in the three different selected areas i.e. Cameron Highlands (275 square kilometers), Ipoh (200 square kilometers) and Cheras Kajang -- Batang kali (650 square kilometers). These areas are selected based on National Slope Master Plan (2009 -- 2023) that endorsed by Malaysia Government Cabinet. The national hazard and risk mapping project includes six parts of major tasks: (1) desk study and mobilization, (2) airborne LiDAR data acquisition and analysis, (3) field data acquisition and verification, (4) hazard and risk for natural terrain, (5) hazard and risk analysis for man-made slope and (6) Man-made slope mitigation/preventive measures. The project was authorized in September, 2014 and will be ended in March, 2016. In this paper, the main focus is to evaluate the suitability of integrated capability of airborne- and terrestrial LiDAR data acquisition and analysis, and also digital photography for regional landslide assessment. The

  2. G-LiHT: Goddard's LiDAR, Hyperspectral and Thermal Airborne Imager

    NASA Technical Reports Server (NTRS)

    Cook, Bruce; Corp, Lawrence; Nelson, Ross; Morton, Douglas; Ranson, Kenneth J.; Masek, Jeffrey; Middleton, Elizabeth

    2012-01-01

    Scientists at NASA's Goddard Space Flight Center have developed an ultra-portable, low-cost, multi-sensor remote sensing system for studying the form and function of terrestrial ecosystems. G-LiHT integrates two LIDARs, a 905 nanometer single beam profiler and 1550 nm scanner, with a narrowband (1.5 nanometers) VNIR imaging spectrometer and a broadband (8-14 micrometers) thermal imager. The small footprint (approximately 12 centimeters) LIDAR data and approximately 1 meter ground resolution imagery are advantageous for high resolution applications such as the delineation of canopy crowns, characterization of canopy gaps, and the identification of sparse, low-stature vegetation, which is difficult to detect from space-based instruments and large-footprint LiDAR. The hyperspectral and thermal imagery can be used to characterize species composition, variations in biophysical variables (e.g., photosynthetic pigments), surface temperature, and responses to environmental stressors (e.g., heat, moisture loss). Additionally, the combination of LIDAR optical, and thermal data from G-LiHT is being used to assess forest health by sensing differences in foliage density, photosynthetic pigments, and transpiration. Low operating costs (approximately $1 ha) have allowed us to evaluate seasonal differences in LiDAR, passive optical and thermal data, which provides insight into year-round observations from space. Canopy characteristics and tree allometry (e.g., crown height:width, canopy:ground reflectance) derived from G-LiHT data are being used to generate realistic scenes for radiative transfer models, which in turn are being used to improve instrument design and ensure continuity between LiDAR instruments. G-LiHT has been installed and tested in aircraft with fuselage viewports and in a custom wing-mounted pod that allows G-LiHT to be flown on any Cessna 206, a common aircraft in use throughout the world. G-LiHT is currently being used for forest biomass and growth estimation

  3. Fine-scale ignimbrite morphology revealed in LiDAR at Crater Lake, OR

    NASA Astrophysics Data System (ADS)

    Robinson, J. E.; Bacon, C. R.; Wright, H. M.

    2011-12-01

    Mount Mazama erupted ~7,700 years ago resulting in the collapse of Crater Lake caldera, ash fall across the Pacific Northwest, and emplacement of compositionally zoned ignimbrite. Early climactic ignimbrite contains uniform rhyodacitic pumice and traveled far from the vent, whereas late, less mobile ignimbrite is dominated by crystal-rich andesitic scoria and mafic crystal mush. Funded by the USGS, NPS, and FHWA, the DOGAMI-led Oregon LiDAR Consortium contracted with Watershed Services to collect ~800 km2 of LiDAR over Crater Lake National Park from Aug 2010 to Sept 2010. Ground laser returns have an average density of 1.63 returns/m2 over the heavily forested area of interest. The data have a lateral RMSE and vertical accuracy of 0.05 m. A bare earth terrain model allows a virtual removal of the forest, revealing fine-scale surface morphology, notably in the climactic ignimbrite. Secondary pyroclastic flows, explosion craters, erosion by water, and compaction-related deformation modified the originally smooth ignimbrite surface. Distinct pyroclastic flow fronts are evident in the LiDAR in Annie Creek valley. Leveed flows stand approximately 5 m above the lower ignimbrite surface, and individual toes are about 1-2 m high. Preliminary field checking indicates that rhyodacitic pumice dominates the lower ignimbrite surface, but the leveed flows are a subequal mix of locally oxidized rhyodacitic pumice and andesitic scoria. We hypothesize that these deposits were secondary pyroclastic flows formed by gravitational failure of late ignimbrite. In the Castle Creek valley, is a 2-meter collapse scarp that may have spawned a small secondary pyroclastic flow; several such headwall scarps are present in Sand Creek valley. Differential compaction features are common in many thick ignimbrites. We suggest this caused the deformation of the ignimbrite apparent in the LiDAR. In Annie Creek valley are a series of flow parallel asymmetric ridges, with shallower slopes toward the

  4. On the use of airborne LiDAR for braided river monitoring and water surface delineation

    NASA Astrophysics Data System (ADS)

    Vetter, M.; Höfle, B.; Pfeifer, N.; Rutzinger, M.; Stötter, J.

    2009-04-01

    Airborne LiDAR is an established technology for Earth surface surveying. With LiDAR data sets it is possible to derive maps with different land use classes, which are important for hydraulic simulations. We present a 3D point cloud based method for automatic water surface delineation using single as well as multitemporal LiDAR data sets. With the developed method it is possible to detect the location of the water surface with high planimetric accuracy. The multitemporal analysis of different LiDAR data sets makes it possible to visualize, monitor and quantify the changes of the flow path of braided rivers as well as derived water surface land use classes. The reflection properties from laser beams (1064 nm wavelength) on water surfaces are characterized by strong absorption or specular reflection resulting in a dominance of low signal amplitude values and a high number of laser shot dropouts (i.e. non-recorded laser echoes). The occurrence of dropouts is driven by (i) the incidence angle, (ii) the surface reflectance and (iii) the roughness of the water body. The input data of the presented delineation method are the modeled dropouts and the point cloud attributes of geometry and signal amplitude. A terrestrial orthophoto is used to explore the point cloud in order to find proper information about the geometry and amplitude attributes that are characteristic for water surfaces. The delineation method is divided into five major steps. (a) We compute calibrated amplitude values by reducing the atmospheric, topographic influences and the scan geometry for each laser echo. (b) Then, the dropouts are modeled by using the information from the time stamps, the pulse repetition frequency, the inertial measurement unit and the GPS information of the laser shots and the airplane. The next step is to calculate the standard deviation of the heights for all reflections and all modeled dropouts (c) in a specific radius around the points. (d) We compute the amplitude ratio

  5. Approaching a more Complete Picture of Rockfall Activity: Seismic and LiDAR Detection, Loaction and Volume Estimates

    NASA Astrophysics Data System (ADS)

    Dietze, Michael; Mohadjer, Solmaz; Turowski, Jens; Ehlers, Todd; Hovius, Niels

    2016-04-01

    Rockfall activity in steep alpine landscapes is often difficult to survey due to its infrequent nature. Classic approaches are limited by temporal and spatial resolution. In contrast, seismic monitoring provides access to catchment-wide analysis of activity patterns in rockfall-dominated environments. The deglaciated U-shaped Lauterbrunnen Valley in the Bernese Oberland, Switzerland, is a perfect example of such landscapes. It was instrumented with up to six broadband seismometers and repeatedly surveyed by terrestrial LiDAR to provide independent validation data. During August-October 2014 and April-June 2015 more than 23 (LiDAR) to hundred (seismic) events were detected. Their volumes range from < 0.01 to 5.80 cubic metres as detected by LiDAR. The evolution of individual events (i.e., precursor activity, detachment, falling phase, impact, talus cone activity) can be quantified in terms of location and duration. For events that consist of single detachments rather than a series of releases, volume scaling relationships are possible. Seismic monitoring approaches are well-suited for studying not only the rockfall process but also for understanding the geomorphic framework and boundary conditions that control such processes in a comprehensive way. Taken together, the combined LiDAR and seismic monitoring approach provides high fidelity spatial and temporal resolution of individual events.

  6. Automatic construction of aerial corridor for navigation of unmanned aircraft systems in class G airspace using LiDAR

    NASA Astrophysics Data System (ADS)

    Feng, Dengchao; Yuan, Xiaohui

    2016-05-01

    According to the airspace classification by the Federal Aviation Agency, Class G airspace is the airspace at 1,200 feet or less to the ground, which is beneath class E airspace and between classes B-D cylinders around towered airstrips. However, the lack of flight supervision mechanism in this airspace, unmanned aerial system (UAS) missions pose many safety issues. Collision avoidance and route planning for UASs in class G airspace is critical for broad deployment of UASs in commercial and security applications. Yet, unlike road network, there is no stationary marker in airspace to identify corridors that are available and safe for UASs to navigate. In this paper, we present an automatic LiDAR-based airspace corridor construction method for navigation in class G airspace and a method for route planning to minimize collision and intrusion. Our idea is to combine LiDAR to automatically identify ground objects that pose navigation restrictions such as airports and high-rises. Digital terrain model (DTM) is derived from LiDAR point cloud to provide an altitude-based class G airspace description. Following the FAA Aeronautical Information Manual, the ground objects that define the restricted airspaces are used together with digital surface model derived from LiDAR data to construct the aerial corridor for navigation of UASs. Preliminary results demonstrate competitive performance and the construction of aerial corridor can be automated with much great efficiency.

  7. Calculating the ecosystem service of water storage in isolated wetlands using LiDAR in north central Florida, USA (presentation)

    EPA Science Inventory

    This study used remotely-sensed Light Detection and Ranging (LiDAR) data to estimate potential water storage capacity of isolated wetlands in north central Florida. The data were used to calculate the water storage potential of >8500 polygons identified as isolated wetlands. We f...

  8. Assessing Surface Fuel Hazard in Coastal Conifer Forests through the Use of LiDAR Remote Sensing

    NASA Astrophysics Data System (ADS)

    Koulas, Christos

    The research problem that this thesis seeks to examine is a method of predicting conventional fire hazards using data drawn from specific regions, namely the Sooke and Goldstream watershed regions in coastal British Columbia. This thesis investigates whether LiDAR data can be used to describe conventional forest stand fire hazard classes. Three objectives guided this thesis: to discuss the variables associated with fire hazard, specifically the distribution and makeup of fuel; to examine the relationship between derived LiDAR biometrics and forest attributes related to hazard assessment factors defined by the Capitol Regional District (CRD); and to assess the viability of the LiDAR biometric decision tree in the CRD based on current frameworks for use. The research method uses quantitative datasets to assess the optimal generalization of these types of fire hazard data through discriminant analysis. Findings illustrate significant LiDAR-derived data limitations, and reflect the literature in that flawed field application of data modelling techniques has led to a disconnect between the ways in which fire hazard models have been intended to be used by scholars and the ways in which they are used by those tasked with prevention of forest fires. It can be concluded that a significant trade-off exists between computational requirements for wildfire simulation models and the algorithms commonly used by field teams to apply these models with remote sensing data, and that CRD forest management practices would need to change to incorporate a decision tree model in order to decrease risk.

  9. Computing Risk to West Coast Intertidal Rocky Habitat due to Sea Level Rise using LiDAR Topobathy

    EPA Science Inventory

    Compared to marshes, little information is available on the potential for rocky intertidal habitats to migrate upward in response to sea level rise (SLR). To address this gap, we utilized topobathy LiDAR digital elevation models (DEMs) downloaded from NOAA’s Digital Coast G...

  10. Intimate Partner Violence and the Association with HIV Risk Behaviors among Young Men in Dar Es Salaam, Tanzania

    ERIC Educational Resources Information Center

    Maman, Suzanne; Yamanis, Thespina; Kouyoumdjian, Fiona; Watt, Melissa; Mbwambo, Jessie

    2010-01-01

    There is growing evidence of the association between gender-based violence and HIV from the perspective and experiences of women. The purpose of this study is to examine these associations from the perspective of young men living in Dar es Salaam, Tanzania. A community-based sample of 951 men were interviewed, of whom 360 had sex in the past 6…

  11. Testing the Suitability of a Terrestrial 2D LiDAR Scanner for Canopy Characterization of Greenhouse Tomato Crops.

    PubMed

    Llop, Jordi; Gil, Emilio; Llorens, Jordi; Miranda-Fuentes, Antonio; Gallart, Montserrat

    2016-09-06

    Canopy characterization is essential for pesticide dosage adjustment according to vegetation volume and density. It is especially important for fresh exportable vegetables like greenhouse tomatoes. These plants are thin and tall and are planted in pairs, which makes their characterization with electronic methods difficult. Therefore, the accuracy of the terrestrial 2D LiDAR sensor is evaluated for determining canopy parameters related to volume and density and established useful correlations between manual and electronic parameters for leaf area estimation. Experiments were performed in three commercial tomato greenhouses with a paired plantation system. In the electronic characterization, a LiDAR sensor scanned the plant pairs from both sides. The canopy height, canopy width, canopy volume, and leaf area were obtained. From these, other important parameters were calculated, like the tree row volume, leaf wall area, leaf area index, and leaf area density. Manual measurements were found to overestimate the parameters compared with the LiDAR sensor. The canopy volume estimated with the scanner was found to be reliable for estimating the canopy height, volume, and density. Moreover, the LiDAR scanner could assess the high variability in canopy density along rows and hence is an important tool for generating canopy maps.

  12. Characterization and classification of vegetation canopy structure and distribution within the Great Smoky Mountains National Park using LiDAR

    SciTech Connect

    Kumar, Jitendra; HargroveJr., William Walter; Norman, Steven P; Hoffman, Forrest M; Newcomb, Doug

    2015-01-01

    Vegetation canopy structure is a critically important habit characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape pro- vided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify and analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and to characterize and map the vegetation canopy structures for 139,859 hectares (540 sq. miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.

  13. Fine-spatial scale predictions of understory species using climate- and LiDAR-derived terrain and canopy metrics

    NASA Astrophysics Data System (ADS)

    Nijland, Wiebe; Nielsen, Scott E.; Coops, Nicholas C.; Wulder, Michael A.; Stenhouse, Gordon B.

    2014-01-01

    Food and habitat resources are critical components of wildlife management and conservation efforts. The grizzly bear (Ursus arctos) has diverse diets and habitat requirements particularly for understory plant species, which are impacted by human developments and forest management activities. We use light detection and ranging (LiDAR) data to predict the occurrence of 14 understory plant species relevant to bear forage and compare our predictions with more conventional climate- and land cover-based models. We use boosted regression trees to model each of the 14 understory species across 4435 km2 using occurrence (presence-absence) data from 1941 field plots. Three sets of models were fitted: climate only, climate and basic land and forest covers from Landsat 30-m imagery, and a climate- and LiDAR-derived model describing both the terrain and forest canopy. Resulting model accuracies varied widely among species. Overall, 8 of 14 species models were improved by including the LiDAR-derived variables. For climate-only models, mean annual precipitation and frost-free periods were the most important variables. With inclusion of LiDAR-derived attributes, depth-to-water table, terrain-intercepted annual radiation, and elevation were most often selected. This suggests that fine-scale terrain conditions affect the distribution of the studied species more than canopy conditions.

  14. National and Global: A History of Scholars' Experiences with Research at the University of Dar Es Salaam, Tanzania (1961-Present)

    ERIC Educational Resources Information Center

    Jamison, Amy J.

    2010-01-01

    In this dissertation, I draw on research carried out at the University of Dar es Salaam (UDSM), Tanzania in 2008 to examine Tanzanian academics' experience with research throughout the history of this institution. This dissertation is designed as an historical case study and investigates how economic and political changes in Tanzania's…

  15. Provision of Vocational Skills Education to Orphans: Lessons from Orphanage Centres in Dar es Salaam City, Tanzania

    ERIC Educational Resources Information Center

    Meli, Benjamin Mbeba

    2015-01-01

    This paper utilises data from a study that investigated the efficacy of vocational skills training provided to orphans from three orphanages in Temeke District, Dar es Salaam. The three orphanage centres that were studied are Kurasini National Children Home, Saudia and Don Bosco Vocational Centre. The sample comprised of 45 orphans, an official…

  16. A categorical, improper probability method for combining NDVI and LiDAR elevation information for potential cotton precision agricultural applications

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An algorithm is presented to fuse the Normalized Difference Vegetation Index (NDVI) with Light Detection and Ranging (LiDAR) elevation data to produce a map potentially useful for the site-specific scouting and pest management of several insect pests. In cotton, these pests include the Tarnished Pl...

  17. Vegetation and slope effects on accuracy of a LiDAR-derived DEM in the sagebrush steppe

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study analyzed the errors associated with vegetation cover type and slope on a LiDAR derived DEM in a semiarid environment in southwestern Idaho, USA. Reference data were collected over a range of vegetation cover types and slopes. Reference data were compared to ground raster values and Root...

  18. Testing the Suitability of a Terrestrial 2D LiDAR Scanner for Canopy Characterization of Greenhouse Tomato Crops

    PubMed Central

    Llop, Jordi; Gil, Emilio; Llorens, Jordi; Miranda-Fuentes, Antonio; Gallart, Montserrat

    2016-01-01

    Canopy characterization is essential for pesticide dosage adjustment according to vegetation volume and density. It is especially important for fresh exportable vegetables like greenhouse tomatoes. These plants are thin and tall and are planted in pairs, which makes their characterization with electronic methods difficult. Therefore, the accuracy of the terrestrial 2D LiDAR sensor is evaluated for determining canopy parameters related to volume and density and established useful correlations between manual and electronic parameters for leaf area estimation. Experiments were performed in three commercial tomato greenhouses with a paired plantation system. In the electronic characterization, a LiDAR sensor scanned the plant pairs from both sides. The canopy height, canopy width, canopy volume, and leaf area were obtained. From these, other important parameters were calculated, like the tree row volume, leaf wall area, leaf area index, and leaf area density. Manual measurements were found to overestimate the parameters compared with the LiDAR sensor. The canopy volume estimated with the scanner was found to be reliable for estimating the canopy height, volume, and density. Moreover, the LiDAR scanner could assess the high variability in canopy density along rows and hence is an important tool for generating canopy maps. PMID:27608025

  19. A model for predicting GPS-GDOP and its probability using LiDAR data and ultra rapid product

    NASA Astrophysics Data System (ADS)

    Lohani, Bharat; Kumar, Raman

    2008-12-01

    This paper presents a model to predict the GDOP value (Geometric Dilution of Precision) and the probability of its occurrence at a point in space and time using airborne LiDAR (Light Detection and Ranging) data and the ultra-rapid product (URP) available from the International GPS Service. LiDAR data help to classify the terrain around a GPS (Global Positioning System) receiver into categories such as ground, opaque objects, translucent objects and transparent regions as per their response to the transmission of GPS signal. Through field experiments it is established that URP can be used satisfactorily to determine GDOP. Further experiments have shown that the translucent objects (mainly trees here) lower the GDOP quality as they obstruct the GPS signal. LiDAR data density on trees is used as a measure of the translucency of trees to the GPS signal. Through GPS observations taken in field a relationship has been established between LiDAR data density on trees and the probability that a satellite which is behind the tree is visible at the GPS receiver. A model is presented which, for all possible combinations of visible satellites, computes the GDOP value along with the probability of occurrence of this GDOP. A few results are presented to show the performance of the model developed and its possible application in location based queries.

  20. Data Archiving and Distribution of LiDAR and Derived Datasets in the Philippines

    NASA Astrophysics Data System (ADS)

    Tupas, M. E. A.; Lat, S. C.; Magturo, R. A.

    2016-06-01

    LiDAR programs in the Philippines have been generating valuable resource and hazard information for most of the country at a substantial rate since 2012. Significant progress have been made due to the programs design of engaging 16 Universities and research institutions spatially distributed across the country. Because of this, data has been accumulating at a brisk rate which poses significant technical and logistic issues. While a central node, the University of the Philippines, Diliman, handles data acquisition, pre-processing, and quality checking, processing and ground validation are devolved to the various nodes. For this setup to be successful, an efficient data access and distribution system should be in place. In this paper, we discuss the spatial data infrastructure and data access protocols implemented by the program. At the center of the data access and distribution operations is LiPAD or our LiDAR portal for archiving and distribution. LiPAD is built on open source technologies, established web standards, and protocols. At its back-end a central data archive has been established using state of the art Object Storage technology to store both raw, processed Lidar and derived data sets. Catalog of available data sets ranging from data acquisition foot prints, to DEM coverages, to derived products such as flood hazard, and crop suitability are viewable and accessible on the main site based on the popular GeoNode application. Data exchange is performed using varying protocols to address various logistical problems. Given the various challenges the program is successful in distributing data sets not just to partner processing nodes but to other stakeholders where main requesters include national agencies and general research and academic institutions.

  1. First LiDAR images of the Alpine Fault, central South Island, New Zealand

    NASA Astrophysics Data System (ADS)

    Langridge, R. M.; Toy, V. G.; Barth, N.; de Pascale, G. P.; Sutherland, R.; Farrier, T.

    2010-12-01

    In central South Island, New Zealand, the dextral-reverse Alpine fault forms the principal component of the Australia-Pacific plate boundary. The fault typically accommodates slip rates of the order of ~27-29 mm/yr (dextral) and up to 6-11 mm/yr (reverse), mostly uplifting Pacific plate rocks that form the Southern Alps. However, the associated high relief, rapid uplift and erosion and high rainfall and accompanying dense temperate rainforest along the western side of the island has typically hampered geological efforts to better understand the neotectonics of the Alpine fault. LiDAR data have been acquired over a 34 km stretch of the fault between Whataroa in the northeast and Franz Josef in the southwest to test the viability of this technique under dense vegetation and in steep, dissected terrain. LiDAR has been collected from a fixed wing base (1300m above ground level) at a frequency of 70k Hz, with 33.5 Hz scan frequency and a 39° field of view. We employed a strategy of flying a dense pattern of 6 flight lines across a swath width of 1.3 km. This creates areas of both single and double overlap coverage that have allowed for accurate landscape models to be created. Results show that this strategy has provided an optimum level of forest penetration and ground returns. Initial results show remarkable level of detail in DEM’s of the landscape along the Alpine fault. Examples of results presented here include: Franz Josef, where the fault traverses the township; and Gaunt Creek, where a Deep Fault Drilling Project will be sited in early 2011.

  2. Full-waveform LiDAR echo decomposition based on wavelet decomposition and particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Li, Duan; Xu, Lijun; Li, Xiaolu

    2017-04-01

    To measure the distances and properties of the objects within a laser footprint, a decomposition method for full-waveform light detection and ranging (LiDAR) echoes is proposed. In this method, firstly, wavelet decomposition is used to filter the noise and estimate the noise level in a full-waveform echo. Secondly, peak and inflection points of the filtered full-waveform echo are used to detect the echo components in the filtered full-waveform echo. Lastly, particle swarm optimization (PSO) is used to remove the noise-caused echo components and optimize the parameters of the most probable echo components. Simulation results show that the wavelet-decomposition-based filter is of the best improvement of SNR and decomposition success rates than Wiener and Gaussian smoothing filters. In addition, the noise level estimated using wavelet-decomposition-based filter is more accurate than those estimated using other two commonly used methods. Experiments were carried out to evaluate the proposed method that was compared with our previous method (called GS-LM for short). In experiments, a lab-build full-waveform LiDAR system was utilized to provide eight types of full-waveform echoes scattered from three objects at different distances. Experimental results show that the proposed method has higher success rates for decomposition of full-waveform echoes and more accurate parameters estimation for echo components than those of GS-LM. The proposed method based on wavelet decomposition and PSO is valid to decompose the more complicated full-waveform echoes for estimating the multi-level distances of the objects and measuring the properties of the objects in a laser footprint.

  3. Underwater monitoring experiment using hyperspectral sensor, LiDAR and high resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Yang, Chan-Su; Kim, Sun-Hwa

    2014-10-01

    In general, hyper-spectral sensor, LiDAR and high spatial resolution satellite imagery for underwater monitoring are dependent on water clarity or water transparency that can be measured using a Secchi disk or satellite ocean color data. Optical properties in the sea waters of South Korea are influenced mainly by a strong tide and oceanic currents, diurnal, daily and seasonal variations of water transparency. The satellite-based Secchi depth (ZSD) analysis showed the applicability of hyper-spectral sensor, LiDAR and optical satellite, determined by the location connected with the local distribution of Case 1 and 2 waters. The southeast coastal areas of Jeju Island are selected as test sites for a combined underwater experiment, because those areas represent Case 1 water. Study area is a small port (<15m) in the southeast area of the island and linear underwater target used by sewage pipe is located in this area. Our experiments are as follows: 1. atmospheric and sun-glint correction methods to improve the underwater monitoring ability; 2. intercomparison of water depths obtained from three different sensors. Three sensors used here are the CASI-1500 (Wide-Array Airborne Hyperspectral VNIR Imager (0.38-1.05 microns), the Coastal Zone Mapping and Imaging Lidar (CZMIL) and Korean Multi-purpose Satellite-3 (KOMPSAT-3) with 2.8 meter multi-spectral resolution. The experimental results were affected by water clarity and surface condition, and the bathymetric results of three sensors show some differences caused by sensor-itself, bathymetric algorithm and tide level. It is shown that CASI-1500 was applicable for bathymetry and underwater target detection in this area, but KOMPSAT-3 should be improved for Case 1 water. Although this experiment was designed to compare underwater monitoring ability of LIDAR, CASI-1500, KOMPSAT-3 data, this paper was based on initial results and suggested only results about the bathymetry and underwater target detection.

  4. Tracking geomorphic signatures of watershed suburbanization with multi-temporal LiDAR

    USGS Publications Warehouse

    Jones, Daniel K.; Baker, Matthew E.; Miller, Andrew J.; Jarnagin, S. Taylor; Hogan, Dianna M.

    2014-01-01

    Urban development practices redistribute surface materials through filling, grading, and terracing, causing drastic changes to the geomorphic organization of the landscape. Many studies document the hydrologic, biologic, or geomorphic consequences of urbanization using space-for-time comparisons of disparate urban and rural landscapes. However, no previous studies have documented geomorphic changes from development using multiple dates of high-resolution topographic data at the watershed scale. This study utilized a time series of five sequential light detection and ranging (LiDAR) derived digital elevation models (DEMs) to track watershed geomorphic changes within two watersheds throughout development (2002–2008) and across multiple spatial scales (0.01–1 km2). Development-induced changes were compared against an undeveloped forested watershed during the same time period. Changes in elevations, slopes, hypsometry, and surface flow pathways were tracked throughout the development process to assess watershed geomorphic alterations. Results suggest that development produced an increase in sharp topographic breaks between relatively flat surfaces and steep slopes, replacing smoothly varying hillslopes and leading to greater variation in slopes. Examinations of flowpath distributions highlight systematic modifications that favor rapid convergence in unchanneled upland areas. Evidence of channel additions in the form of engineered surface conduits is apparent in comparisons of pre- and post-development stream maps. These results suggest that topographic modification, in addition to impervious surfaces, contributes to altered hydrologic dynamics observed in urban systems. This work highlights important considerations for the use of repeat LiDAR flights in analyzing watershed change through time. Novel methods introduced here may allow improved understanding and targeted mitigation of the processes driving geomorphic changes during development and help guide future

  5. Using LiDAR, RADAR, and Optical data to improve a NFMS in Kalimantan, Indonesia

    NASA Astrophysics Data System (ADS)

    Hagen, S. C.; Saatchi, S. S.; Braswell, B. H., Jr.; Palace, M. W.; Salas, W.; Walker, S.; Hoekman, D.; Ipsan, C.; Brown, S.; Sullivan, F.

    2014-12-01

    Around the world, governments are establishing national forest monitoring systems (NFMS) that use a combination of remote sensing and ground-based forest carbon inventory approaches to estimate anthropogenic forest-related greenhouse gas emissions and removals. The NFMS forms the link between historical assessments and current/future assessments of forests, enabling consistency in the data and information to support the implementation of REDD+ activities. The creation of a reliable, transparent, and comprehensive NFMS is currently limited by a dearth of relevant data that are accurate, low-cost, and spatially resolved at subnational scales. With funding from a 3-year NASA Carbon Monitoring System project beginning in September 2013, we are developing, evaluating, and validating several critical components of an NFMS in Kalimantan, Indonesia, focusing on the use of LiDAR and radar imagery for improved carbon stock and forest degradation information. Here, we present results from an initial analysis of a spatially extensive set of LiDAR data collected across the Indonesian provinces on the island of Borneo together with RADAR and optical data. Our objectives are to evaluate sensor and platform tradeoffs systematically against in situ investments, as well as provide detailed tracking and characterization of uncertainty in a cost-benefit framework. Kalimantan is an ideal area to evaluate the use of remote sensing methods because measuring forest carbon stocks and their human caused changes with a high degree of certainty on the ground can be difficult. While our work focuses at the subnational scale for Kalimantan, we are targeting these methods for applicability across broader geographies and for implementation at various scales.

  6. Tracking geomorphic signatures of watershed suburbanization with multitemporal LiDAR

    NASA Astrophysics Data System (ADS)

    Jones, Daniel K.; Baker, Matthew E.; Miller, Andrew J.; Jarnagin, S. Taylor; Hogan, Dianna M.

    2014-08-01

    Urban development practices redistribute surface materials through filling, grading, and terracing, causing drastic changes to the geomorphic organization of the landscape. Many studies document the hydrologic, biologic, or geomorphic consequences of urbanization using space-for-time comparisons of disparate urban and rural landscapes. However, no previous studies have documented geomorphic changes from development using multiple dates of high-resolution topographic data at the watershed scale. This study utilized a time series of five sequential light detection and ranging (LiDAR) derived digital elevation models (DEMs) to track watershed geomorphic changes within two watersheds throughout development (2002-2008) and across multiple spatial scales (0.01-1 km2). Development-induced changes were compared against an undeveloped forested watershed during the same time period. Changes in elevations, slopes, hypsometry, and surface flow pathways were tracked throughout the development process to assess watershed geomorphic alterations. Results suggest that development produced an increase in sharp topographic breaks between relatively flat surfaces and steep slopes, replacing smoothly varying hillslopes and leading to greater variation in slopes. Examinations of flowpath distributions highlight systematic modifications that favor rapid convergence in unchanneled upland areas. Evidence of channel additions in the form of engineered surface conduits is apparent in comparisons of pre- and post-development stream maps. These results suggest that topographic modification, in addition to impervious surfaces, contributes to altered hydrologic dynamics observed in urban systems. This work highlights important considerations for the use of repeat LiDAR flights in analyzing watershed change through time. Novel methods introduced here may allow improved understanding and targeted mitigation of the processes driving geomorphic changes during development and help guide future

  7. Assessing and Correcting Topographic Effects on Forest Canopy Height Retrieval Using Airborne LiDAR Data

    PubMed Central

    Duan, Zhugeng; Zhao, Dan; Zeng, Yuan; Zhao, Yujin; Wu, Bingfang; Zhu, Jianjun

    2015-01-01

    Topography affects forest canopy height retrieval based on airborne Light Detection and Ranging (LiDAR) data a lot. This paper proposes a method for correcting deviations caused by topography based on individual tree crown segmentation. The point cloud of an individual tree was extracted according to crown boundaries of isolated individual trees from digital orthophoto maps (DOMs). Normalized canopy height was calculated by subtracting the elevation of centres of gravity from the elevation of point cloud. First, individual tree crown boundaries are obtained by carrying out segmentation on the DOM. Second, point clouds of the individual trees are extracted based on the boundaries. Third, precise DEM is derived from the point cloud which is classified by a multi-scale curvature classification algorithm. Finally, a height weighted correction method is applied to correct the topological effects. The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots. The results show that the terrain impacts the canopy height of individual trees in that the downslope side of the tree trunk is elevated and the upslope side is depressed. This further affects the extraction of the location and crown of individual trees. A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively. PMID:26016907

  8. Automatic extraction of insulators from 3D LiDAR data of an electrical substation

    NASA Astrophysics Data System (ADS)

    Arastounia, M.; Lichti, D. D.

    2013-10-01

    A considerable percentage of power outages are caused by animals that come into contact with conductive elements of electrical substations. These can be prevented by insulating conductive electrical objects, for which a 3D as-built plan of the substation is crucial. This research aims to create such a 3D as-built plan using terrestrial LiDAR data while in this paper the aim is to extract insulators, which are key objects in electrical substations. This paper proposes a segmentation method based on a new approach of finding the principle direction of points' distribution. This is done by forming and analysing the distribution matrix whose elements are the range of points in 9 different directions in 3D space. Comparison of the computational performance of our method with PCA (principal component analysis) shows that our approach is 25% faster since it utilizes zero-order moments while PCA computes the first- and second-order moments, which is more time-consuming. A knowledge-based approach has been developed to automatically recognize points on insulators. The method utilizes known insulator properties such as diameter and the number and the spacing of their rings. The results achieved indicate that 24 out of 27 insulators could be recognized while the 3 un-recognized ones were highly occluded. Check point analysis was performed by manually cropping all points on insulators. The results of check point analysis show that the accuracy, precision and recall of insulator recognition are 98%, 86% and 81%, respectively. It is concluded that automatic object extraction from electrical substations using only LiDAR data is not only possible but also promising. Moreover, our developed approach to determine the directional distribution of points is computationally more efficient for segmentation of objects in electrical substations compared to PCA. Finally our knowledge-based method is promising to recognize points on electrical objects as it was successfully applied for

  9. Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR

    USGS Publications Warehouse

    Jones, Benjamin M.; Stoker, Jason M.; Gibbs, Ann E.; Grosse, Guido; Romanovsky, Vladimir E.; Douglas, Thomas A.; Kinsman, Nichole E.M.; Richmond, Bruce M.

    2013-01-01

    Increases in air, permafrost, and sea surface temperature, loss of sea ice, the potential for increased wave energy, and higher river discharge may all be interacting to escalate erosion of arctic coastal lowland landscapes. Here we use airborne light detection and ranging (LiDAR) data acquired in 2006 and 2010 to detect landscape change in a 100 km2 study area on the Beaufort Sea coastal plain of northern Alaska. We detected statistically significant change (99% confidence interval), defined as contiguous areas (>10 m2) that had changed in height by at least 0.55 m, in 0.3% of the study region. Erosional features indicative of ice-rich permafrost degradation were associated with ice-bonded coastal, river, and lake bluffs, frost mounds, ice wedges, and thermo-erosional gullies. These features accounted for about half of the area where vertical change was detected. Inferred thermo-denudation and thermo-abrasion of coastal and river bluffs likely accounted for the dominant permafrost-related degradational processes with respect to area (42%) and volume (51%). More than 300 thermokarst pits significantly subsided during the study period, likely as a result of storm surge flooding of low-lying tundra (<1.4 m asl) as well as the lasting impact of warm summers in the late-1980s and mid-1990s. Our results indicate that repeat airborne LiDAR can be used to detect landscape change in arctic coastal lowland regions at large spatial scales over sub-decadal time periods.

  10. Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR

    NASA Astrophysics Data System (ADS)

    Jones, Benjamin M.; Stoker, Jason M.; Gibbs, Ann E.; Grosse, Guido; Romanovsky, Vladimir E.; Douglas, Thomas A.; Kinsman, Nicole E. M.; Richmond, Bruce M.

    2013-12-01

    Increases in air, permafrost, and sea surface temperature, loss of sea ice, the potential for increased wave energy, and higher river discharge may all be interacting to escalate erosion of arctic coastal lowland landscapes. Here we use airborne light detection and ranging (LiDAR) data acquired in 2006 and 2010 to detect landscape change in a 100 km2 study area on the Beaufort Sea coastal plain of northern Alaska. We detected statistically significant change (99% confidence interval), defined as contiguous areas (>10 m2) that had changed in height by at least 0.55 m, in 0.3% of the study region. Erosional features indicative of ice-rich permafrost degradation were associated with ice-bonded coastal, river, and lake bluffs, frost mounds, ice wedges, and thermo-erosional gullies. These features accounted for about half of the area where vertical change was detected. Inferred thermo-denudation and thermo-abrasion of coastal and river bluffs likely accounted for the dominant permafrost-related degradational processes with respect to area (42%) and volume (51%). More than 300 thermokarst pits significantly subsided during the study period, likely as a result of storm surge flooding of low-lying tundra (<1.4 m asl) as well as the lasting impact of warm summers in the late-1980s and mid-1990s. Our results indicate that repeat airborne LiDAR can be used to detect landscape change in arctic coastal lowland regions at large spatial scales over sub-decadal time periods.

  11. Genetic Map of Triticale Integrating Microsatellite, DArT and SNP Markers

    PubMed Central

    Tyrka, Mirosław; Tyrka, Dorota; Wędzony, Maria

    2015-01-01

    Triticale (×Triticosecale Wittm) is an economically important crop for fodder and biomass production. To facilitate the identification of markers for agronomically important traits and for genetic and genomic characteristics of this species, a new high-density genetic linkage map of triticale was constructed using doubled haploid (DH) population derived from a cross between cultivars ‘Hewo’ and ‘Magnat’. The map consists of 1615 bin markers, that represent 50 simple sequence repeat (SSR), 842 diversity array technology (DArT), and 16888 DArTseq markers mapped onto 20 linkage groups assigned to the A, B, and R genomes of triticale. No markers specific to chromosome 7R were found, instead mosaic linkage group composed of 1880 highly distorted markers (116 bins) from 10 wheat chromosomes was identified. The genetic map covers 4907 cM with a mean distance between two bins of 3.0 cM. Comparative analysis in respect to published maps of wheat, rye and triticale revealed possible deletions in chromosomes 4B, 5A, and 6A, as well as inversion in chromosome 7B. The number of bin markers in each chromosome varied from 24 in chromosome 3R to 147 in chromosome 6R. The length of individual chromosomes ranged between 50.7 cM for chromosome 2R and 386.2 cM for chromosome 7B. A total of 512 (31.7%) bin markers showed significant (P < 0.05) segregation distortion across all chromosomes. The number of 8 the segregation distorted regions (SDRs) were identified on 1A, 7A, 1B, 2B, 7B (2 SDRs), 5R and 6R chromosomes. The high-density genetic map of triticale will facilitate fine mapping of quantitative trait loci, the identification of candidate genes and map-based cloning. PMID:26717308

  12. LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

    USGS Publications Warehouse

    Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

    2015-01-01

    Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

  13. Evaluating dryland ecological and river restoration using repeat LiDAR and hydrological monitoring

    NASA Astrophysics Data System (ADS)

    Henderson, W. M.; DeLong, S.

    2012-12-01

    Recent improvements in the collection of multitemporal, high-resolution topographic data such as Light Detection and Ranging (LiDAR) have done a great deal to increase our ability to quantify the details of landscape change. Both Terrestrial Laser Scanning (TLS) and Airborne Laser Swath Mapping (ALSM) can be used to easily assess how Earth surface processes affect landscape form to a level of precision that was previously more difficult to attain. A comprehensive approach using ALSM, TLS-TLS comparison, and hydrological monitoring is being used to assess the effectiveness of a large scale ecological and river restoration effort by the Cuenca los Ojos Foundation at San Bernardino Ranch near Agua Prieta, Sonora, Mexico. In the study area, historical arroyo cutting and changes in land use led to the abandonment of a ciénega wetland and resulted in widespread ecological destruction. The current land managers have employed engineering methods in order to restore stream and ciénega ecology, including the installation of large rock gabions, earthen berms, and concrete spillways along channels. Our goal is to test the hypothesis that the use of dam and gabion structures leads to stream aggradation, flash flood dampening, and ultimately, increased available water and reestablishment of historic wetland plant and animal communities. We present results from LiDAR change detection that includes 2007-2011 ALSM to TLS change, and several 2011-2012 TLS-TLS comparisons. We also present results from streamflow monitoring, field observation, and monitoring of shallow groundwater and soil moisture conditions. Preliminary results show that channel aggradation occurs rapidly upstream of engineered structures. However, the apparent dampening of sediment transport by the structures leads to less aggradation and even incision immediately downstream of structures. Peak flood flows are decreased by the reservoirs formed behind large earthen berms. After several years of water retention

  14. Tree Canopy Cover Mapping Using LiDAR in Urban Barangays of Cebu City, Central Philippines

    NASA Astrophysics Data System (ADS)

    Ejares, J. A.; Violanda, R. R.; Diola, A. G.; Dy, D. T.; Otadoy, J. B.; Otadoy, R. E. S.

    2016-06-01

    This paper investigates tree canopy cover mapping of urban barangays (smallest administrative division in the Philippines) in Cebu City using LiDAR (Light Detection and Ranging). Object-Based Image Analysis (OBIA) was used to extract tree canopy cover. Multi-resolution segmentation and a series of assign-class algorithm in eCognition software was also performed to extract different land features. Contextual features of tree canopies such as height, area, roundness, slope, length-width and elliptic fit were also evaluated. The results showed that at the time the LiDAR data was collected (June 24, 2014), the tree cover was around 25.11 % (or 15,674,341.8 m2) of the city's urban barangays (or 62,426,064.6 m2). Among all urban barangays in Cebu City, Barangay Busay had the highest cover (55.79 %) while barangay Suba had the lowest (0.8 %). The 16 barangays with less than 10 % tree cover were generally located in the coastal area, presumably due to accelerated urbanization. Thirty-one barangays have tree cover ranging from 10.59--27.3 %. Only 3 barangays (i.e., Lahug, Talamban, and Busay) have tree cover greater than 30 %. The overall accuracy of the analysis was 96.6 % with the Kappa Index of Agreement or KIA of 0.9. From the study, a grouping can be made of the city's urban barangays with regards to tree cover. The grouping will be useful to urban planners not only in allocating budget to the tree planting program of the city but also in planning and creation of urban parks and playgrounds.

  15. Effect of slope on treetop detection using a LiDAR Canopy Height Model

    NASA Astrophysics Data System (ADS)

    Khosravipour, Anahita; Skidmore, Andrew K.; Wang, Tiejun; Isenburg, Martin; Khoshelham, Kourosh

    2015-06-01

    Canopy Height Models (CHMs) or normalized Digital Surface Models (nDSM) derived from LiDAR data have been applied to extract relevant forest inventory information. However, generating a CHM by height normalizing the raw LiDAR points is challenging if trees are located on complex terrain. On steep slopes, the raw elevation values located on either the downhill or the uphill part of a tree crown are height-normalized with parts of the digital terrain model that may be much lower or higher than the tree stem base, respectively. In treetop detection, a highest crown return located in the downhill part may prove to be a "false" local maximum that is distant from the true treetop. Based on this observation, we theoretically and experimentally quantify the effect of slope on the accuracy of treetop detection. The theoretical model presented a systematic horizontal displacement of treetops that causes tree height to be systematically displaced as a function of terrain slope and tree crown radius. Interestingly, our experimental results showed that the effect of CHM distortion on treetop displacement depends not only on the steepness of the slope but more importantly on the crown shape, which is species-dependent. The influence of the systematic error was significant for Scots pine, which has an irregular crown pattern and weak apical dominance, but not for mountain pine, which has a narrow conical crown with a distinct apex. Based on our findings, we suggest that in order to minimize the negative effect of steep slopes on the CHM, especially in heterogeneous forest with multiple species or species which change their morphological characteristics as they mature, it is best to use raw elevation values (i.e., use the un-normalized DSM) and compute the height after treetop detection.

  16. Deconstructing a Polygenetic Landscape Using LiDAR and Multi-Resolution Analysis

    NASA Astrophysics Data System (ADS)

    Houser, C.; Barrineau, C. P.; Dobreva, I. D.; Bishop, M. P.

    2015-12-01

    In many earth surface systems characteristic morphologies are associated with various regimes both past and present. Aeolian systems contain a variety of features differentiated largely by morphometric differences, which in turn reflect age and divergent process regimes. Using quantitative analysis of high-resolution elevation data to generate detailed information regarding these characteristic morphometries enables geomorphologists to effectively map process regimes from a distance. Combined with satellite imagery and other types of remotely sensed data, the outputs can even help to delineate phases of activity within aeolian systems. The differentiation of regimes and identification of relict features together enables a greater level of rigor to analyses leading to field-based investigations, which are highly dependent on site-specific historical contexts that often obscure distinctions between separate process-form regimes. We present results from a Principal Components Analysis (PCA) performed on a LiDAR-derived elevation model of a largely stabilized aeolian system in South Texas. The resulting components are layered and classified to generate a map of aeolian morphometric signatures for a portion of the landscape. Several of these areas do not immediately appear to be aeolian in nature in satellite imagery or LiDAR-derived models, yet field observations and historical imagery reveal the PCA did in fact identify stabilized and relict dune features. This methodology enables researchers to generate a morphometric classification of the land surface. We believe this method is a valuable and innovative tool for researchers identifying process regimes within a study area, particularly in field-based investigations that rely heavily on site-specific context.

  17. Open-Source Digital Elevation Model (DEMs) Evaluation with GPS and LiDAR Data

    NASA Astrophysics Data System (ADS)

    Khalid, N. F.; Din, A. H. M.; Omar, K. M.; Khanan, M. F. A.; Omar, A. H.; Hamid, A. I. A.; Pa'suya, M. F.

    2016-09-01

    Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model (ASTER GDEM), Shuttle Radar Topography Mission (SRTM), and Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) are freely available Digital Elevation Model (DEM) datasets for environmental modeling and studies. The quality of spatial resolution and vertical accuracy of the DEM data source has a great influence particularly on the accuracy specifically for inundation mapping. Most of the coastal inundation risk studies used the publicly available DEM to estimated the coastal inundation and associated damaged especially to human population based on the increment of sea level. In this study, the comparison between ground truth data from Global Positioning System (GPS) observation and DEM is done to evaluate the accuracy of each DEM. The vertical accuracy of SRTM shows better result against ASTER and GMTED10 with an RMSE of 6.054 m. On top of the accuracy, the correlation of DEM is identified with the high determination of coefficient of 0.912 for SRTM. For coastal zone area, DEMs based on airborne light detection and ranging (LiDAR) dataset was used as ground truth data relating to terrain height. In this case, the LiDAR DEM is compared against the new SRTM DEM after applying the scale factor. From the findings, the accuracy of the new DEM model from SRTM can be improved by applying scale factor. The result clearly shows that the value of RMSE exhibit slightly different when it reached 0.503 m. Hence, this new model is the most suitable and meets the accuracy requirement for coastal inundation risk assessment using open source data. The suitability of these datasets for further analysis on coastal management studies is vital to assess the potentially vulnerable areas caused by coastal inundation.

  18. Guild-specific responses of avian species richness to LiDAR-derived habitat heterogeneity

    USGS Publications Warehouse

    Weisberg, Peter J.; Dilts, Thomas E.; Becker, Miles E.; Young, Jock S.; Wong-Kone, Diane C.; Newton, Wesley E.; Ammon, Elisabeth M.

    2014-01-01

    Ecological niche theory implies that more heterogeneous habitats have the potential to support greater biodiversity. Positive heterogeneity-diversity relationships have been found for most studies investigating animal taxa, although negative relationships also occur and the scale dependence of heterogeneity-diversity relationships is little known. We investigated multi-scale, heterogeneity-diversity relationships for bird communities in a semi-arid riparian landscape, using airborne LiDAR data to derive key measures of structural habitat complexity. Habitat heterogeneity-diversity relationships were generally positive, although the overall strength of relationships varied across avian life history guilds (R2 range: 0.03–0.41). Best predicted were the species richness indices of cavity nesters, habitat generalists, woodland specialists, and foliage foragers. Heterogeneity-diversity relationships were also strongly scale-dependent, with strongest associations at the 200-m scale (4 ha) and weakest associations at the 50-m scale (0.25 ha). Our results underscore the value of LiDAR data for fine-grained quantification of habitat structure, as well as the need for biodiversity studies to incorporate variation among life-history guilds and to simultaneously consider multiple guild functional types (e.g. nesting, foraging, habitat). Results suggest that certain life-history guilds (foliage foragers, cavity nesters, woodland specialists) are more susceptible than others (ground foragers, ground nesters, low nesters) to experiencing declines in local species richness if functional elements of habitat heterogeneity are lost. Positive heterogeneity-diversity relationships imply that riparian conservation efforts need to not only provide high-quality riparian habitat locally, but also to provide habitat heterogeneity across multiple scales.

  19. Coastal change analysis of Lovells Island using high resolution ground based LiDAR imagery

    NASA Astrophysics Data System (ADS)

    Ly, Jennifer K.

    Many methods have been employed to study coastline change. These methods range from historical map analysis to GPS surveys to modern airborne LiDAR and satellite imagery. These previously used methods can be time consuming, labor intensive, and expensive and have varying degrees of accuracy and temporal coverage. Additionally, it is often difficult to apply such techniques in direct response to an isolated event within an appropriate temporal framework. Here we utilize a new ground based Canopy Biomass LiDAR (CBL) system built at The University of Massachusetts Boston (in collaboration with the Rochester Institute of Technology) in order to identify and analyze coastal change on Lovells Island, Boston Harbor. Surveys of a bluff developing in an eroding drumlin and beach cusps on a high-energy cobble beach on Lovells Island were conducted in June, September and December of 2013. At each site for each survey, the CBL was set up and multiple scans of each feature were taken on a predetermined transect that was established parallel to the high-water mark at distances relative to the scale of the bluff and cusps. The scans from each feature were compiled, integrated and visualized using Meshlab. Results from our surveys indicate that the highly portable and easy to deploy CBL system produces images of exceptional clarity, with the capacity to resolve small-scale changes to coastal features and systems. The CBL, while still under development (and coastal surveying protocols with it are just being established), appears to be an ideal tool for analyzing coastal geological features and is anticipated to prove to be a useful tool for the observation and analysis of coastal change. Furthermore, there is significant potential for utilizing the low cost ultra-portable CBL in frequent deployments to develop small-scale erosion rate and sediment budget analyses.

  20. A graph-based segmentation algorithm for tree crown extraction using airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Strîmbu, Victor F.; Strîmbu, Bogdan M.

    2015-06-01

    This work proposes a segmentation method that isolates individual tree crowns using airborne LiDAR data. The proposed approach captures the topological structure of the forest in hierarchical data structures, quantifies topological relationships of tree crown components in a weighted graph, and finally partitions the graph to separate individual tree crowns. This novel bottom-up segmentation strategy is based on several quantifiable cohesion criteria that act as a measure of belief on weather two crown components belong to the same tree. An added flexibility is provided by a set of weights that balance the contribution of each criterion, thus effectively allowing the algorithm to adjust to different forest structures. The LiDAR data used for testing was acquired in Louisiana, inside the Clear Creek Wildlife management area with a RIEGL LMS-Q680i airborne laser scanner. Three 1 ha forest areas of different conditions and increasing complexity were segmented and assessed in terms of an accuracy index (AI) accounting for both omission and commission. The three areas were segmented under optimum parameterization with an AI of 98.98%, 92.25% and 74.75% respectively, revealing the excellent potential of the algorithm. When segmentation parameters are optimized locally using plot references the AI drops to 98.23%, 89.24%, and 68.04% on average with plot sizes of 1000 m2 and 97.68%, 87.78% and 61.1% on average with plot sizes of 500 m2. More than introducing a segmentation algorithm, this paper proposes a powerful framework featuring flexibility to support a series of segmentation methods including some of those recurring in the tree segmentation literature. The segmentation method may extend its applications to any data of topological nature or data that has a topological equivalent.

  1. Guild-specific responses of avian species richness to LiDAR-derived habitat heterogeneity

    NASA Astrophysics Data System (ADS)

    Weisberg, Peter J.; Dilts, Thomas E.; Becker, Miles E.; Young, Jock S.; Wong-Kone, Diane C.; Newton, Wesley E.; Ammon, Elisabeth M.

    2014-08-01

    Ecological niche theory implies that more heterogeneous habitats have the potential to support greater biodiversity. Positive heterogeneity-diversity relationships have been found for most studies investigating animal taxa, although negative relationships also occur and the scale dependence of heterogeneity-diversity relationships is little known. We investigated multi-scale, heterogeneity-diversity relationships for bird communities in a semi-arid riparian landscape, using airborne LiDAR data to derive key measures of structural habitat complexity. Habitat heterogeneity-diversity relationships were generally positive, although the overall strength of relationships varied across avian life history guilds (R2 range: 0.03-0.41). Best predicted were the species richness indices of cavity nesters, habitat generalists, woodland specialists, and foliage foragers. Heterogeneity-diversity relationships were also strongly scale-dependent, with strongest associations at the 200-m scale (4 ha) and weakest associations at the 50-m scale (0.25 ha). Our results underscore the value of LiDAR data for fine-grained quantification of habitat structure, as well as the need for biodiversity studies to incorporate variation among life-history guilds and to simultaneously consider multiple guild functional types (e.g. nesting, foraging, habitat). Results suggest that certain life-history guilds (foliage foragers, cavity nesters, woodland specialists) are more susceptible than others (ground foragers, ground nesters, low nesters) to experiencing declines in local species richness if functional elements of habitat heterogeneity are lost. Positive heterogeneity-diversity relationships imply that riparian conservation efforts need to not only provide high-quality riparian habitat locally, but also to provide habitat heterogeneity across multiple scales.

  2. Characterization of an alpine tree line using airborne LiDAR data and physiological modeling.

    PubMed

    Coops, Nicholas C; Morsdorf, Felix; Schaepman, Michael E; Zimmermann, Niklaus E

    2013-12-01

    Understanding what environmental drivers control the position of the alpine tree line is important for refining our understanding of plant stress and tree development, as well as for climate change studies. However, monitoring the location of the tree line position and potential movement is difficult due to cost and technical challenges, as well as a lack of a clear boundary. Advanced remote sensing technologies such as Light Detection and Ranging (LiDAR) offer significant potential to map short individual tree crowns within the transition zone despite the lack of predictive capacity. Process-based forest growth models offer a complementary approach by quantifying the environmental stresses trees experience at the tree line, allowing transition zones to be defined and ultimately mapped. In this study, we investigate the role remote sensing and physiological, ecosystem-based modeling can play in the delineation of the alpine tree line. To do so, we utilize airborne LiDAR data to map tree height and stand density across a series of altitudinal gradients from below to above the tree line within the Swiss National Park (SNP), Switzerland. We then utilize a simple process-based model to assess the importance of seasonal variations on four climatically related variables that impose non-linear constraints on photosynthesis. Our results indicate that all methods predict the tree line to within a 50 m altitudinal zone and indicate that aspect is not a driver of significant variations in tree line position in the region. Tree cover, rather than tree height is the main discriminator of the tree line at higher elevations. Temperatures in fall and spring are responsible for the major differences along altitudinal zones, however, changes in evaporative demand also control plant growth at lower altitudes. Our results indicate that the two methods provide complementary information on tree line location and, when combined, provide additional insights into potentially endangered

  3. Assessing and correcting topographic effects on forest canopy height retrieval using airborne LiDAR data.

    PubMed

    Duan, Zhugeng; Zhao, Dan; Zeng, Yuan; Zhao, Yujin; Wu, Bingfang; Zhu, Jianjun

    2015-05-26

    Topography affects forest canopy height retrieval based on airborne Light Detection and Ranging (LiDAR) data a lot. This paper proposes a method for correcting deviations caused by topography based on individual tree crown segmentation. The point cloud of an individual tree was extracted according to crown boundaries of isolated individual trees from digital orthophoto maps (DOMs). Normalized canopy height was calculated by subtracting the elevation of centres of gravity from the elevation of point cloud. First, individual tree crown boundaries are obtained by carrying out segmentation on the DOM. Second, point clouds of the individual trees are extracted based on the boundaries. Third, precise DEM is derived from the point cloud which is classified by a multi-scale curvature classification algorithm. Finally, a height weighted correction method is applied to correct the topological effects. The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots. The results show that the terrain impacts the canopy height of individual trees in that the downslope side of the tree trunk is elevated and the upslope side is depressed. This further affects the extraction of the location and crown of individual trees. A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively.

  4. Effects of LiDAR point density and landscape context on the retrieval of urban forest biomass

    NASA Astrophysics Data System (ADS)

    Singh, K. K.; Chen, G.; McCarter, J. B.; Meentemeyer, R. K.

    2014-12-01

    Light Detection and Ranging (LiDAR), as an alternative to conventional optical remote sensing, is being increasingly used to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and better data accuracies, which however pose challenges to the procurement and processing of LiDAR data for large-area assessments. Reducing point density cuts data acquisition costs and overcome computational challenges for broad-scale forest management. However, how does that impact the accuracy of biomass estimation in an urban environment containing a great level of anthropogenic disturbances? The main goal of this study is to evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing regions of Charlotte, North Carolina, USA. We used multiple linear regression to establish the statistical relationship between field-measured biomass and predictor variables (PVs) derived from LiDAR point clouds with varying densities. We compared the estimation accuracies between the general Urban Forest models (no discrimination of forest type) and the Forest Type models (evergreen, deciduous, and mixed), which was followed by quantifying the degree to which landscape context influenced biomass estimation. The explained biomass variance of Urban Forest models, adjusted R2, was fairly consistent across the reduced point densities with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models using two representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, signifying the distance impact of development on biomass estimation. Our evaluation

  5. Urban flood modelling combining top-view LiDAR data with ground-view SfM observations

    NASA Astrophysics Data System (ADS)

    Meesuk, Vorawit; Vojinovic, Zoran; Mynett, Arthur E.; Abdullah, Ahmad F.

    2015-01-01

    Remote Sensing technologies are capable of providing high-resolution spatial data needed to set up advanced flood simulation models. Amongst them, aerial Light Detection and Ranging (LiDAR) surveys or Airborne Laser Scanner (ALS) systems have long been used to provide digital topographic maps. Nowadays, Remote Sensing data are commonly used to create Digital Terrain Models (DTMs) for detailed urban-flood modelling. However, the difficulty of relying on top-view LiDAR data only is that it cannot detect whether passages for floodwaters are hidden underneath vegetated areas or beneath overarching structures such as roads, railroads, and bridges. Such (hidden) small urban features can play an important role in urban flood propagation. In this paper, a complex urban area of Kuala Lumpur, Malaysia was chosen as a study area to simulate the extreme flooding event that occurred in 2003. Three different DTMs were generated and used as input for a two-dimensional (2D) urban flood model. A top-view LiDAR approach was used to create two DTMs: (i) a standard LiDAR-DTM and (ii) a Filtered LiDAR-DTM taking into account specific ground-view features. In addition, a Structure from Motion (SfM) approach was used to detect hidden urban features from a sequence of ground-view images; these ground-view SfM data were then combined with top-view Filtered LiDAR data to create (iii) a novel Multidimensional Fusion of Views-Digital Terrain Model (MFV-DTM). These DTMs were then used as a basis for the 2D urban flood model. The resulting dynamic flood maps are compared with observations at six measurement locations. It was found that when applying only top-view DTMs as input data, the flood simulation results appear to have mismatches in both floodwater depths and flood propagation patterns. In contrast, when employing the top-ground-view fusion approach (MFV-DTM), the results not only show a good agreement in floodwater depth, but also simulate more correctly the floodwater dynamics around

  6. Improving the efficiency and accuracy of individual tree crown delineation from high-density LiDAR data

    NASA Astrophysics Data System (ADS)

    Hu, Baoxin; Li, Jili; Jing, Linhai; Judah, Aaron

    2014-02-01

    Canopy height model (CHM) derived from LiDAR (Light Detection And Ranging) data has been commonly used to generate segments of individual tree crowns for forest inventory and sustainable management. However, branches, tree crowns, and tree clusters usually have similar shapes and overlapping sizes, which cause current individual tree crown delineation methods to work less effectively on closed canopy, deciduous or mixedwood forests. In addition, the potential of 3-dimentional (3-D) LiDAR data is not fully realized by CHM-oriented methods. In this study, a framework was proposed to take advantage of the simplicity of a CHM-oriented method, detailed vertical structures of tree crowns represented in high-density LiDAR data, and any prior knowledge of tree crowns. The efficiency and accuracy of ITC delineation can be improved. This framework consists of five steps: (1) determination of dominant crown sizes; (2) generation of initial tree segments using a multi-scale segmentation method; (3) identification of “problematic” segments; (4) determination of the number of trees based on the 3-D LiDAR points in each of the identified segments; and (5) refinement of the “problematic” segments by splitting and merging operations. The proposed framework was efficient, since the detailed examination of 3-D LiDAR points was not applied to all initial segments, but only to those needed further evaluations based on prior knowledge. It was also demonstrated to be effective based on an experiment on natural forests in Ontario, Canada. The proposed framework and specific methods yielded crown maps having a good consistency with manual and visual interpretation. The automated method correctly delineated about 74% and 72% of the tree crowns in two plots with mixedwood and deciduous trees, respectively.

  7. A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

    NASA Technical Reports Server (NTRS)

    Jung, Jinha; Pasolli, Edoardo; Prasad, Saurabh; Tilton, James C.; Crawford, Melba M.

    2014-01-01

    Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

  8. The suitability of LiDAR-derived forest attributes for use in individual-tree distance-dependent growth-and-yield modeling

    NASA Astrophysics Data System (ADS)

    Londo, Hilary Alexis

    Studies have not been conducted examining the influence of the spatial distribution of LiDAR-derived tree measuresments and their affects the predictive ability of LiDAR-derived forest metrics as input for growth-and-yield analysis on individual trees. This study addresses both of these voids in current knowledge and determines the suitability, concerns and application of LiDAR for time-series analysis, specifically forest growth-and-yield. LiDAR datasets of the same site acquired in 1999, 2000, 2002, and 2006 by different vendors using different specifications were utilized in this study. Directional differences of Lidar-identified tree top locations were examined. Minimal location differences were noted, but no bias occurred. Differences in locations appeared to be from environmental effects such as wind. Improvements on individual-tree identification using a time-series analysis approach were implemented. The tree-finding model was improved with a Boolean decision rule yielding significant differences in stand density calculations in 1.4 m spacing plots and for overall calculations of the 2000 and 2002 LiDAR datasets. Individual tree measurements derived from the 1999 LiDAR data were used to estimate growth to the 2006 data. These growth-and-yield values were compared with field-derived and field-measured values. Significant differences were found between the LiDAR- and field-derived measures of growth-and-yield. These increased over time and were believe to be compounded error from the LiDAR-estimated tree diameters. LiDAR datasets can be correlated to previous LiDAR datasets of the same area with very little effort. LiDAR tree identification can be improved using decision criteria based on subsequent LiDAR datasets of the same area. The ability to track individual trees by location over time using LiDAR could yield large datasets to potentially improve growth-and-yield modeling efforts and other stand characterization procedures.

  9. LiDAR-Landsat data fusion for large-area assessment of urban land cover: Balancing spatial resolution, data volume and mapping accuracy

    NASA Astrophysics Data System (ADS)

    Singh, Kunwar K.; Vogler, John B.; Shoemaker, Douglas A.; Meentemeyer, Ross K.

    2012-11-01

    The structural characteristics of Light Detection and Ranging (LiDAR) data are increasingly used to classify urban environments at fine scales, but have been underutilized for distinguishing heterogeneous land covers over large urban regions due to high cost, limited spectral information, and the computational difficulties posed by inherently large data volumes. Here we explore tradeoffs between potential gains in mapping accuracy with computational costs by integrating structural and intensity surface models extracted from LiDAR data with Landsat Thematic Mapper (TM) imagery and evaluating the degree to which TM, LiDAR, and LiDAR-TM fusion data discriminated land covers in the rapidly urbanizing region of Charlotte, North Carolina, USA. Using supervised maximum likelihood (ML) and classification tree (CT) methods, we classified TM data at 30 m and LiDAR data and LiDAR-TM fusions at 1 m, 5 m, 10 m, 15 m and 30 m resolutions. We assessed the relative contributions of LiDAR structural and intensity surface models to classification map accuracy and identified optimal spatial resolution of LiDAR surface models for large-area assessments of urban land cover. ML classification of 1 m LiDAR-TM fusions using both structural and intensity surface models increased total accuracy by 32% compared to LiDAR alone and by 8% over TM at 30 m. Fusion data using all LiDAR surface models improved class discrimination of spectrally similar forest, farmland, and managed clearings and produced the highest total accuracies at 1 m, 5 m, and 10 m resolutions (87.2%, 86.3% and 85.4%, respectively). At all resolutions of fusion data and using either ML or CT classifier, the relative contribution of the LiDAR structural surface models (canopy height and normalized digital surface model) to classification accuracy is greater than the intensity surface. Our evaluation of tradeoffs between data volume and thematic map accuracy for this study system suggests that a spatial resolution of 5 m for LiDAR

  10. Improving Measurement of Forest Structural Parameters by Co-Registering of High Resolution Aerial Imagery and Low Density LiDAR Data.

    PubMed

    Huang, Huabing; Gong, Peng; Cheng, Xiao; Clinton, Nick; Li, Zengyuan

    2009-01-01

    Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to generate a DEM (Digital Elevation Model) and a CHM (Canopy Height Model) from LiDAR data. The LiDAR camera image is matched to the aerial image with an automated keypoints search algorithm. As a result, a high registration accuracy of 0.5 pixels was obtained. A local maximum filter, watershed segmentation, and object-oriented image segmentation are used to obtain tree height and crown width. Results indicate that the camera data collected by the integrated LiDAR system plays an important role in registration with aerial imagery. The synthesis with aerial imagery increases the accuracy of forest structural parameter extraction when compared to only using the low density LiDAR data.

  11. Damage Assessment for Disaster Relief Efforts in Urban Areas Using Optical Imagery and LiDAR Data

    NASA Astrophysics Data System (ADS)

    Bahr, Thomas

    2014-05-01

    Imagery combined with LiDAR data and LiDAR-derived products provides a significant source of geospatial data which is of use in disaster mitigation planning. Feature rich building inventories can be constructed from tools with 3D rooftop extraction capabilities, and two dimensional outputs such as DSMs and DTMs can be used to generate layers to support routing efforts in Spatial Analyst and Network Analyst workflows. This allows us to leverage imagery and LiDAR tools for disaster mitigation or other scenarios. Software such as ENVI, ENVI LiDAR, and ArcGIS® Spatial and Network Analyst can therefore be used in conjunction to help emergency responders route ground teams in support of disaster relief efforts. This is exemplified by a case study against the background of the magnitude 7.0 earthquake that struck Haiti's capital city of Port-au-Prince on January 12, 2010. Soon after, both LiDAR data and an 8-band WorldView-2 scene were collected to map the disaster zone. The WorldView-2 scene was orthorectified and atmospherically corrected in ENVI prior to use. ENVI LiDAR was used to extract the DSM, DTM, buildings, and debris from the LiDAR data point cloud. These datasets provide a foundation for the 2D portion of the analysis. As the data was acquired over an area of dense urbanization, the majority of ground surfaces are roads, and standing buildings and debris are actually largely separable on the basis of elevation classes. To extract the road network of Port-au-Prince, the LiDAR-based feature height information was fused with the WorldView-2 scene, using ENVI's object-based feature extraction approach. This road network was converted to a network dataset for further analysis by the ArcGIS Network Analyst. For the specific case of Haiti, the distribution of blue tarps, used as accommodations for refugees, provided a spectrally distinct target. Pure blue tarp pixel spectra were selected from the WorldView-2 scene and input as a reference into ENVI's Spectral Angle

  12. How Well Can We Predict Salmonid Spawning Habitat with LiDAR?

    NASA Astrophysics Data System (ADS)

    Pfeiffer, A.; Finnegan, N. J.; Hayes, S.

    2013-12-01

    Suitable salmonid spawning habitat is, to a great extent, determined by physical, landscape driven characteristics such as channel morphology and grain size. Identifying reaches with high-quality spawning habitat is essential to restoration efforts in areas where salmonid species are endangered or threatened. While both predictions of suitable habitat and observations of utilized habitat are common in the literature, they are rarely combined. Here we exploit a unique combination of high-resolution LiDAR data and seven years of 387 individually surveyed Coho and Steelhead redds in Scott Creek, a 77 km2 un-glaciated coastal California drainage in the Santa Cruz Mountains, to both make and test predictions of spawning habitat. Using a threshold channel assumption, we predict grain size throughout Scott Creek via a shear stress model that incorporates channel width, instead of height, using Manning's equation (Snyder et al., 2013). Slope and drainage area are computed from a LiDAR-derived DEM, and channel width is calculated via hydraulic modeling. Our results for median grain size predictions closely match median grain sizes (D50) measured in the field, with the majority of sites having predicted D50's within a factor of two of the observed values, especially for reaches with D50 > 0.02m. This success suggests that the threshold model used to predict grain size is appropriate for un-glaciated alluvial channel systems. However, it appears that grain size alone is not a strong predictor of salmon spawning. Reaches with a high (>0.1m) average predicted D50 do have lower redd densities, as expected based on spawning gravel sizes in the literature. However, reaches with lower (<0.1m) predicted D50 have a wide range of redd densities, suggesting that reach-average grain size alone cannot explain spawning site selection in the finer-grained reaches of Scott Creek. We turn to analysis of bedform morphology in order to explain the variation in redd density in the low

  13. Probabilistic change mapping from airborne LiDAR for post-disaster damage assessment

    NASA Astrophysics Data System (ADS)

    Jalobeanu, A.; Runyon, S. C.; Kruse, F. A.

    2013-12-01

    When both pre- and post-event LiDAR point clouds are available, change detection can be performed to identify areas that were most affected by a disaster event, and to obtain a map of quantitative changes in terms of height differences. In the case of earthquakes in built-up areas for instance, first responders can use a LiDAR change map to help prioritize search and recovery efforts. The main challenge consists of producing reliable change maps, robust to collection conditions, free of processing artifacts (due for instance to triangulation or gridding), and taking into account the various sources of uncertainty. Indeed, datasets acquired within a few years interval are often of different point density (sometimes an order of magnitude higher for recent data), different acquisition geometries, and very likely suffer from georeferencing errors and geometric discrepancies. All these differences might not be important for producing maps from each dataset separately, but they are crucial when performing change detection. We have developed a novel technique for the estimation of uncertainty maps from the LiDAR point clouds, using Bayesian inference, treating all variables as random. The main principle is to grid all points on a common grid before attempting any comparison, as working directly with point clouds is cumbersome and time consuming. A non-parametric approach based on local linear regression was implemented, assuming a locally linear model for the surface. This enabled us to derive error bars on gridded elevations, and then elevation differences. In this way, a map of statistically significant changes could be computed - whereas a deterministic approach would not allow testing of the significance of differences between the two datasets. This approach allowed us to take into account not only the observation noise (due to ranging, position and attitude errors) but also the intrinsic roughness of the observed surfaces occurring when scanning vegetation. As only

  14. Financial sustainability in municipal solid waste management – Costs and revenues in Bahir Dar, Ethiopia

    SciTech Connect

    Lohri, Christian Riuji Camenzind, Ephraim Joseph Zurbrügg, Christian

    2014-02-15

    Highlights: • Cost-revenue analysis over 2 years revealed insufficient cost-recovery. • Expenses for motorized secondary collection increased by 82% over two years. • Low fee collection rate and reliance on only one revenue stream are problematic. • Different options for cost reduction and enhanced revenue streams are recommended. • Good public–private alliance is crucial to plan and implement improvement measures. - Abstract: Providing good solid waste management (SWM) services while also ensuring financial sustainability of the system continues to be a major challenge in cities of developing countries. Bahir Dar in northwestern Ethiopia outsourced municipal waste services to a private waste company in 2008. While this institutional change has led to substantial improvement in the cleanliness of the city, its financial sustainability remains unclear. Is the private company able to generate sufficient revenues from their activities to offset the costs and generate some profit? This paper presents a cost-revenue analysis, based on data from July 2009 to June 2011. The analysis reveals that overall costs in Bahir Dar’s SWM system increased significantly during this period, mainly due to rising costs related to waste transportation. On the other hand, there is only one major revenue stream in place: the waste collection fee from households, commercial enterprises and institutions. As the efficiency of fee collection from households is only around 50%, the total amount of revenues are not sufficient to cover the running costs. This results in a substantial yearly deficit. The results of the research therefore show that a more detailed cost structure and cost-revenue analysis of this waste management service is important with appropriate measures, either by the privates sector itself or with the support of the local authorities, in order to enhance cost efficiency and balance the cost-revenues towards cost recovery. Delays in mitigating the evident

  15. Effects of the D1 dopamine receptor agonist dihydrexidine (DAR-0100A) on working memory in schizotypal personality disorder.

    PubMed

    Rosell, Daniel R; Zaluda, Lauren C; McClure, Margaret M; Perez-Rodriguez, M Mercedes; Strike, K Sloan; Barch, Deanna M; Harvey, Philip D; Girgis, Ragy R; Hazlett, Erin A; Mailman, Richard B; Abi-Dargham, Anissa; Lieberman, Jeffrey A; Siever, Larry J

    2015-01-01

    Pharmacological enhancement of prefrontal D1 dopamine receptor function remains a promising therapeutic approach to ameliorate schizophrenia-spectrum working memory deficits, but has yet to be rigorously evaluated clinically. This proof-of-principle study sought to determine whether the active enantiomer of the selective and full D1 receptor agonist dihydrexidine (DAR-0100A) could attenuate working memory impairments in unmedicated patients with schizotypal personality disorder (SPD). We performed a randomized, double-blind, placebo-controlled trial of DAR-0100A (15 mg/150 ml of normal saline administered intravenously over 30 min) in medication-free patients with SPD (n=16) who met the criteria for cognitive impairment (ie, scoring below the 25th percentile on tests of working memory). We employed two measures of verbal working memory that are salient to schizophrenia-spectrum cognitive deficits, and that clinical data implicate as being associated with prefrontal D1 availability: (1) the Paced Auditory Serial Addition Test (PASAT); and (2) the N-back test (ratio of 2-back:0-back scores). Study procedures occurred over four consecutive days, with working memory testing on Days 1 and 4, and DAR-0100A/placebo administration on Days 2-4. Treatment with DAR-0100A was associated with significantly improved PASAT performance relative to placebo, with a very large effect size (Cohen's d=1.14). Performance on the N-back ratio was also significantly improved; however, this effect rested on both a non-significant enhancement and diminution of 2-back and 0-back performance, respectively; therefore interpretation of this finding is more complicated. DAR-0100A was generally well tolerated, with no serious medical or psychiatric adverse events; common side effects were mild to moderate and transient, consisting mainly of sedation, lightheadedness, tachycardia, and hypotension; however, we were able to minimize these effects, without altering the dose, with supportive

  16. Automatic 3D Building Model Generation by Integrating LiDAR and Aerial Images Using a Hybrid Approach

    NASA Astrophysics Data System (ADS)

    Kwak, Eunju

    The development of sensor technologies and the increase in user requirements have resulted in many different approaches for efficient building model generation. Three-dimensional building models are important in various applications, such as disaster management and urban planning. Despite this importance, generation of these models lacks economical and reliable techniques which take advantage of the available multi-sensory data from single and multiple platforms. Therefore, this research develops a framework for fully-automated building model generation by integrating data-driven and model-driven methods as well as exploiting the advantages of images and LiDAR datasets. The building model generation starts by employing LiDAR data for building detection and approximate boundary determination. The generated building boundaries are then integrated into a model-based image processing strategy, because LiDAR derived planes show irregular boundaries due to the nature of LiDAR point acquisition. The focus of the research is generating models for the buildings with right-angled-corners, which can be described with a collection of rectangles (e.g., L-shape, T-shape, U-shape, gable roofs, and more complex building shapes which are combinations of the aforementioned shapes), under the assumption that the majority of the buildings in urban areas belong to this category. Therefore, by applying the Minimum Bounding Rectangle (MBR) algorithm recursively, the LiDAR boundaries are decomposed into sets of rectangles for further processing. At the same time the quality of the MBRs are examined to verify that the buildings, from which the boundaries are generated, are buildings with right-angled-corners. These rectangles are preliminary model primitives. The parameters that define the model primitives are adjusted using detected edges in the imagery through the least-squares adjustment procedure, i.e., model-based image fitting. The level of detail in the final Digital Building Model

  17. Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

    NASA Technical Reports Server (NTRS)

    Morton, D. C.; Keller, M.; Cook, B. D.; Hunter, Maria; Sales, Marcio; Spinelli, L.; Victoria, D.; Andersen, H.-E.; Saleska, S.

    2012-01-01

    Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap

  18. Quantifying Soil Carbon Change from Wildfires in Peatland Ecosystems of the Eastern United States Using Repeat LiDAR

    NASA Astrophysics Data System (ADS)

    Reddy, A.; Hawbaker, T. J.; Zhu, Z.; Ward, S.; Wurster, F.; Newcomb, D.

    2013-12-01

    Wildfires are an increasing concern in peatland ecosystems along the coastal plains of the Eastern US. Human- and climate-induced changes to the ecosystems' hydrology can leave the soils, heavy with organic matter, susceptible to combustion in wildfires. This results in large losses of carbon that took many years to accumulate. However, accurately quantifying carbon losses in peatlands from wildfires is challenging because field data collection over extensive areas is difficult. For this study, our first objective was to evaluate the use of pre- and post-fire LiDAR data to quantify changes in surface elevations and soil carbon stocks for the 2011 Lateral West fire, which occurred in the Great Dismal Swamp National Wildlife Refuge (GDSNWR), Virginia, USA. Our second objective was to use a Monte Carlo approach to estimate how the vertical error in LiDAR points affected our calculation of soil carbon emissions. Bare-earth LiDAR points from 2010 and 2012 were obtained for GDSNWR with densities of 2 pulses/m2 and vertical elevation RMSE of 9 and 7 cm, respectively. Monte Carlo replicates were used to perturb individual bare-earth LiDAR points and generate probability distributions of elevation change within 10 m grid cells. Change in soil carbon were calculated within the Monte Carlo replicates by multiplying the LiDAR-derived volume of soil loss by depth-specific published values of soil bulk density, organic matter content, and carbon content. The 5th, 50th and 95th percentiles of the elevation and carbon change distributions were outputted as raster layers. Loss in soil volume ranged from 10,820,000 to 13,190,000 m3 based on vertical error. Carbon loss within the entire area burned by the Lateral West fire perimeter (32.1 km2), based on the 5th, 50th and 95th percentiles was 0.64, 0.96, and 1.33 Tg C, respectively. Our study demonstrated a method to use LiDAR data to quantify carbon loss following fires in peatland ecosystems and incorporate elevation errors to

  19. Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

    NASA Technical Reports Server (NTRS)

    Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

    2012-01-01

    The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized

  20. Subjectivity of LiDAR-Based Offset Measurements: Results from a Public Online Survey

    NASA Astrophysics Data System (ADS)

    Salisbury, J. B.; Arrowsmith, R.; Rockwell, T. K.; Haddad, D. E.; Zielke, O.; Madden, C.

    2012-12-01

    Geomorphic features (e.g., stream channels) that are offset in an earthquake can be measured to determine slip at that location. Analysis of these and other offset features can provide useful information for generating fault slip distributions. Remote analyses of active fault zones using high-resolution LiDAR data have recently been pursued in several studies, but there is a lack of consistency between users both for data analysis and results reporting. Individual investigators typically make offset measurements in a particular study area with their own protocols for measurement, assessing uncertainty, and quality rating, yet there is no coherent understanding of the reliability and repeatability of the measurements from observer to observer. We invited the participation of colleagues, interested geoscience communities, and the general public to measure ten geomorphic offsets from active faults in western North America using remote measurement methods that span a range of complexity (e.g., paper image and scale, the Google Earth ruler tool, and a MATLAB GUI for calculating backslip required to properly restore tectonic deformation) to explore the subjectivity involved with measuring geomorphic offsets. We provided a semi-quantitative quality-rating rubric for a description of offset quality, but there was a general lack of quality rating/offset uncertainty reporting. Survey responses (including mapped fault traces and piercing lines) were anonymously submitted along with user experience information. We received 11 paper-, 28 Google Earth-, and 16 MATLAB-based survey responses, though not all individuals measured every feature provided. For all survey methods, the majority of responses are in close agreement. However, large discrepancies arise where users interpret landforms differently, specifically the pre-earthquake morphologies and total offset accumulation of geomorphic features. Experienced users make more consistent measurements, whereas beginners less

  1. Mapping Forest Carbon by Fusing Terrestrial and Airborne LiDAR Datasets

    NASA Astrophysics Data System (ADS)

    Stovall, A. E.

    2015-12-01

    The storage and flux of terrestrial carbon (C) is one of the largest and most uncertain components of the global C budget, the vast majority of which is held within the biomass of the world's forests. However, the spatial distribution and quantification of forest C remains difficult to measure on a large scale. Remote sensing of forests with airborne LiDAR has proven to be an extremely effective method of bridging the gap between data from plot-level forestry mensuration and landscape-scale C storage estimates, but the standard method of assessing forest C is typically based on national or regional-scale allometric equations that are often not representative on the local-scale. Improvement of these measurements is necessary in order for collaborative multi-national carbon monitoring programs such as REDD implemented by the UNFCCC to be successful in areas, such as tropical forests, with tree species that have insufficiently documented allometric relationships. The primary goal of this study is to set forth a pipeline for precise non-destructive monitoring of C storage by: 1) determining C storage on 15 1/10th ha plots in a 25.6 ha Virginia temperate forest using the recently updated national allometric equations from Chojnacky et. al 2014, 2) comparing these estimates to non-destructively determined individual tree biomass using several semi-automated approaches of three-dimensionally analyzing the point cloud from a high-precision Terrestrial Laser Scanner (TLS), and 3) creating a predictive model of forest C storage by fusing airborne LiDAR data to the plot-level TLS measurements. Our findings align with several other studies, indicating a strong relationship between allometrically-derived C estimates and TLS-derived C measurements (R2=0.93, n=30) using relatively few individuals, suggesting the potential application of these methods to species that are understudied or are without allometric relationships. Voxel based C storage was estimated on the plot level and

  2. 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

  3. Using LiDAR Metrics to Characterize Forest Structural Complexity at Multiple Scales

    NASA Astrophysics Data System (ADS)

    Kane, V. R.; McGaughey, R. J.; Gersonde, R.; Franklin, J. F.

    2007-12-01

    Forest structure - the size and arrangement of trees and foliage - reflects a stand's history of initiation, growth, disturbance, and mortality. Because of this, studying the structure of forests can provide key insights into ecological processes, guides to silvicultural prescriptions to improve habitat, and assessments of forested landscapes. This study tested LiDAR metrics to characterize stands based on canopy structure. The study site was the 34,591 ha of forests in the Cedar River Watershed in western Washington State, USA. Stands ranged in age from <25 years old to >350 years old (including old-growth). Study sites spanned the western hemlock- Douglas fir (Tsuga heterophylla-Pseudotsuga menziesii), Pacific silver fir (Abies amabilis), and mountain hemlock (Tsuga mertansiana) forest zones. Eighty sample plots were used to ground truth the LiDAR data. A variety of structural indices were used to study canopy structural variations at the plot, stand, and landscape scales. The two most successful indices used the exposed geometry of the canopy surface: (1) the ratio of the canopy surface area to ground surface area (rumple index), and (2) the ratio of the volume beneath the canopy surface to maximum volume beneath the 95th percentile height (modified canopy volume method). These two indices integrated the spatial effects of tree heights, foliage distribution, and tree arrangement within 15m pixels. Variation between pixels revealed structural complexity at larger scales. Results: At the plot scale (~4 pixels), correlations with standard plot metrics (e.g., diameter at breast height) were similar to those reported by other studies. Comparison of structural complexity with age and height revealed a diversity of development pathways. The relationship between height and complexity allowed stands to be classified by the degree to which they have achieved their potential structural complexity, a new way to examine forest development. At the stand scale, the indices

  4. Quantifying sand storage capacity of large woody debris on beaches using LiDAR

    NASA Astrophysics Data System (ADS)

    Eamer, Jordan B. R.; Walker, Ian J.

    2010-05-01

    The sedimentological role of large woody debris (LWD) on beaches is understudied and is relevant for the morphodynamics of sandy, high-energy beach-dune systems of the northeast Pacific Ocean. On the west coast of Canada, this debris consists largely of historical escape logs from the coastal logging industry. In areas with competent wind regimes, LWD can trap appreciable amounts of windblown sand in the backshore, which can alter beach-foredune sediment budgets and initiate incipient dune formation. As this additional store of sediment must be reworked first during high water events, it provides an important buffer that reduces erosion of established foredunes. This study examines the morphology and sand storage capacity of three backshore LWD deposits of varying morphologies on northeastern Graham Island, Haida Gwaii (Queen Charlotte Islands) British Columbia, Canada. A new method was developed using coincident high spatial resolution LiDAR data and digital orthophotographs to derive DEMs for distinct ground cover classes (sand, LWD). These DEMs were then used to quantify relative storage capacities of LWD and sand in the backshore. Significant amounts of sand are stored within and around LWD on beaches in the study region. Existing storage quantities (above HHWMT) range from 9.19 × 10 4 to 1.39 × 10 5 kg m - 1 beach width or ˜ 1.14 to 1.60 m storage depth. The same LWD deposits have a further potential storage capacity ranging from 1.04 to 1.70 × 10 4 kg m - 1 beach width or ˜ 0.21 to 0.28 m depth. The relative storage capacity of these features is reflected in the backshore morphology of each site, with sediment transport further into the backshore dependent upon the morphology and relative in-filling of the log debris jam. With this additional sediment storage, log debris could enhance development of large incipient dunes in the backshore thereby buffering against increasing storminess and gradual sea-level rise in the region. As the use of precise LiDAR

  5. 2011 Japan tsunami current and flow velocity measurements from survivor videos using LiDAR

    NASA Astrophysics Data System (ADS)

    Fritz, H. M.; Phillips, D. A.; Okayasu, A.; Shimozono, T.; Liu, H.; Mohammed, F.; Skanavis, V.; Synolakis, C.; Takahashi, T.

    2011-12-01

    On March 11, 2011, a magnitude Mw 9.0 earthquake occurred off the coast of Japan's Tohoku region causing catastrophic damage and loss of life. Numerous tsunami reconnaissance trips were conducted in Japan (Tohoku Earthquake and Tsunami Joint Survey Group). This report focuses on the surveys at 9 tsunami eyewitness video recording locations in Yoriisohama, Kesennuma, Kamaishi and Miyako along Japan's Sanriku coast and the subsequent video image calibration, processing and tsunami flow velocity analysis. Selected tsunami video recording sites were visited, eyewitnesses interviewed and some ground control points recorded during the initial tsunami reconnaissance from April 9 to 25. A follow-up survey from June 9 to 15, 2011 focused on terrestrial laser scanning (TLS) at locations with previously identified high quality eyewitness videos. We acquired precise topographic data using TLS at nine video sites with multiple scans acquired from different instrument positions at each site. These ground-based LiDAR measurements produce a 3-dimensional "point cloud" dataset. Digital photography from a scanner-mounted camera yields photorealistic 3D images. Integrated GPS measurements allow accurate georeferencing of the TLS data in an absolute reference frame such as WGS84. We deployed a Riegl VZ-400 scanner (1550 nm wavelength laser, 42,000 measurements/second, <600 meter max range) and peripheral equipment from the UNAVCO instrument pool. The original full length videos recordings were recovered from eyewitnesses and the Japanese Coast Guard (JCG). Multiple videos were synchronized and referenced in time (UTC). The analysis of the tsunami videos follows a four step procedure developed for the analysis of 2004 Indian Ocean tsunami videos at Banda Aceh, Indonesia (Fritz et al., 2006). The first step requires the calibration of the sector of view present in the eyewitness video recording based on visually identifiable ground control points measured in the LiDAR point cloud data

  6. 2011 Japan tsunami survivor video based hydrograph and flow velocity measurements using LiDAR

    NASA Astrophysics Data System (ADS)

    Fritz, H. M.; Phillips, D. A.; Okayasu, A.; Shimozono, T.; Liu, H.; Mohammed, F.; Skanavis, V.; Synolakis, C. E.; Takahashi, T.

    2012-04-01

    On March 11, 2011, a magnitude Mw 9.0 earthquake occurred off the coast of Japan's Tohoku region causing catastrophic damage and loss of life. Numerous tsunami reconnaissance trips were conducted in Japan (Tohoku Earthquake and Tsunami Joint Survey Group). This report focuses on the surveys at 9 tsunami eyewitness video recording locations in Yoriisohama, Kesennuma, Kamaishi and Miyako along Japan's Sanriku coast and the subsequent video image calibration, processing, tsunami hydrograph and flow velocity analysis. Selected tsunami video recording sites were visited, eyewitnesses interviewed and some ground control points recorded during the initial tsunami reconnaissance from April 9 to 25. A follow-up survey from June 9 to 15, 2011 focused on terrestrial laser scanning (TLS) at locations with previously identified high quality eyewitness videos. We acquired precise topographic data using TLS at nine video sites with multiple scans acquired from different instrument positions at each site. These ground-based LiDAR measurements produce a 3-dimensional "point cloud" dataset. Digital photography from a scanner-mounted camera yields photorealistic 3D images. Integrated GPS measurements allow accurate georeferencing of the TLS data in an absolute reference frame such as WGS84. We deployed a Riegl VZ-400 scanner (1550 nm wavelength laser, 42,000 measurements/second, <600 meter max range) and peripheral equipment from the UNAVCO instrument pool. The original full length videos recordings were recovered from eyewitnesses and the Japanese Coast Guard (JCG). Multiple videos were synchronized and referenced in time (UTC). The analysis of the tsunami videos follows a four step procedure developed for the analysis of 2004 Indian Ocean tsunami videos at Banda Aceh, Indonesia (Fritz et al., 2006). The first step requires the calibration of the sector of view present in the eyewitness video recording based on visually identifiable ground control points measured in the LiDAR point

  7. A Decade Remote Sensing River Bathymetry with the Experimental Advanced Airborne Research LiDAR

    NASA Astrophysics Data System (ADS)

    Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.; Skinner, K.

    2012-12-01

    Since 2002, the first generation of the Experimental Advanced Airborne Research LiDAR (EAARL-A) sensor has been deployed for mapping rivers and streams. We present and summarize the results of comparisons between ground truth surveys and bathymetry collected by the EAARL-A sensor in a suite of rivers across the United States. These comparisons include reaches on the Platte River (NE), Boise and Deadwood Rivers (ID), Blue and Colorado Rivers (CO), Klamath and Trinity Rivers (CA), and the Shenandoah River (VA). In addition to diverse channel morphologies (braided, single thread, and meandering) these rivers possess a variety of substrates (sand, gravel, and bedrock) and a wide range of optical characteristics which influence the attenuation and scattering of laser energy through the water column. Root mean square errors between ground truth elevations and those measured by the EAARL-A ranged from 0.15-m in rivers with relatively low turbidity and highly reflective sandy bottoms to over 0.5-m in turbid rivers with less reflective substrates. Mapping accuracy with the EAARL-A has proved challenging in pools where bottom returns are either absent in waveforms or are of such low intensity that they are treated as noise by waveform processing algorithms. Resolving bathymetry in shallow depths where near surface and bottom returns are typically convolved also presents difficulties for waveform processing routines. The results of these evaluations provide an empirical framework to discuss the capabilities and limitations of the EAARL-A sensor as well as previous generations of post-processing software for extracting bathymetry from complex waveforms. These experiences and field studies not only provide benchmarks for the evaluation of the next generation of bathymetric LiDARs for use in river mapping, but also highlight the importance of developing and standardizing more rigorous methods to characterize substrate reflectance and in-situ optical properties at study sites

  8. What is the effect of LiDAR-derived DEM resolution on large-scale watershed model results?

    SciTech Connect

    Ping Yang; Daniel B. Ames; Andre Fonseca; Danny Anderson; Rupesh Shrestha; Nancy F. Glenn; Yang Cao

    2014-08-01

    This paper examines the effect of raster cell size on hydrographic feature extraction and hydrological modeling using LiDAR derived DEMs. LiDAR datasets for three experimental watersheds were converted to DEMs at various cell sizes. Watershed boundaries and stream networks were delineated from each DEM and were compared to reference data. Hydrological simulations were conducted and the outputs were compared. Smaller cell size DEMs consistently resulted in less difference between DEM-delineated features and reference data. However, minor differences been found between streamflow simulations resulted for a lumped watershed model run at daily simulations aggregated at an annual average. These findings indicate that while higher resolution DEM grids may result in more accurate representation of terrain characteristics, such variations do not necessarily improve watershed scale simulation modeling. Hence the additional expense of generating high resolution DEM's for the purpose of watershed modeling at daily or longer time steps may not be warranted.

  9. Post-construction monitoring of a Core-Loc™ breakwater using tripod-based LiDAR

    USGS Publications Warehouse

    Podoski, Jessica H.; Bawden, Gerald W.; Bond, Sandra; Smith, Thomas D.; Foster, James

    2010-01-01

    The goal of the technology application described herein is to determine whether breakwater monitoring data collected using Tripod (or Terrestrial) Light Detection and Ranging (T-LiDAR) can give insight into processes such as how Core-Loc™ concrete armour units nest following construction, and in turn how settlement affects armour layer stability, concrete cap performance, and armour unit breakage.  A further objective is that this information can then be incorporated into the design of future projects using concrete armour units.  The results of this application of T-LiDAR, including the challenges encountered and the conclusions drawn regarding initial concrete armour unit movement will be presented in this paper.

  10. Rape against women: the magnitude, perpetrators and patterns of disclosure of events in Dar es Salaam, Tanzania.

    PubMed

    Muganyizi, Projestine S; Kilewo, Charles; Moshiro, Candida

    2004-12-01

    This cross-sectional household survey was conducted in Dar es Salaam between July and August 2000. The objectives were to establish the magnitude of rape against women, the perpetrators, disclosure of events and other related factors. Among the 1004 women who completed their interviews, 20% said they were ever raped. The known perpetrators were responsible for 92% of the most recent events. Whereas 34% of events were disclosed for non-legal purposes, only 10% were disclosed to the police. Repeated rape and patterns of disclosure were significantly associated with existing social relationships with the perpetrator. The results indicate that rape against women is a serious public health problem in Dar es Salaam commonly involving people who are close to the victims.

  11. Automated As-Built Model Generation of Subway Tunnels from Mobile LiDAR Data

    PubMed Central

    Arastounia, Mostafa

    2016-01-01

    This study proposes fully-automated methods for as-built model generation of subway tunnels employing mobile Light Detection and Ranging (LiDAR) data. The employed dataset is acquired by a Velodyne HDL 32E and covers 155 m of a subway tunnel containing six million points. First, the tunnel’s main axis and cross sections are extracted. Next, a preliminary model is created by fitting an ellipse to each extracted cross section. The model is refined by employing residual analysis and Baarda’s data snooping method to eliminate outliers. The final model is then generated by applying least squares adjustment to outlier-free data. The obtained results indicate that the tunnel’s main axis and 1551 cross sections at 0.1 m intervals are successfully extracted. Cross sections have an average semi-major axis of 7.8508 m with a standard deviation of 0.2 mm and semi-minor axis of 7.7509 m with a standard deviation of 0.1 mm. The average normal distance of points from the constructed model (average absolute error) is also 0.012 m. The developed algorithm is applicable to tunnels with any horizontal orientation and degree of curvature since it makes no assumptions, nor does it use any a priori knowledge regarding the tunnel’s curvature and horizontal orientation. PMID:27649172

  12. An efficient approach to 3D single tree-crown delineation in LiDAR data

    NASA Astrophysics Data System (ADS)

    Mongus, Domen; Žalik, Borut

    2015-10-01

    This paper proposes a new method for 3D delineation of single tree-crowns in LiDAR data by exploiting the complementaries of treetop and tree trunk detections. A unified mathematical framework is provided based on the graph theory, allowing for all the segmentations to be achieved using marker-controlled watersheds. Treetops are defined by detecting concave neighbourhoods within the canopy height model using locally fitted surfaces. These serve as markers for watershed segmentation of the canopy layer where possible oversegmentation is reduced by merging the regions based on their heights, areas, and shapes. Additional tree crowns are delineated from mid- and under-storey layers based on tree trunk detection. A new approach for estimating the verticalities of the points' distributions is proposed for this purpose. The watershed segmentation is then applied on a density function within the voxel space, while boundaries of delineated trees from the canopy layer are used to prevent the overspreading of regions. The experiments show an approximately 6% increase in the efficiency of the proposed treetop definition based on locally fitted surfaces in comparison with the traditionally used local maxima of the smoothed canopy height model. In addition, 4% increase in the efficiency is achieved by the proposed tree trunk detection. Although the tree trunk detection alone is dependent on the data density, supplementing it with the treetop detection the proposed approach is efficient even when dealing with low density point-clouds.

  13. A temperature inversion-induced air pollution process as analyzed from Mie LiDAR data.

    PubMed

    Wu, Wanning; Zha, Yong; Zhang, Jiahua; Gao, Jay; He, Junliang

    2014-05-01

    A severe air pollution event in the Xianlin District of Nanjing City, China during 23-24 December 2012 was analyzed in terms of aerosol extinction coefficient and AOT retrieved from Mie scattering LiDAR data, in conjunction with in situ particulate concentrations measured near the Earth's surface, and the Weather Research Forecast-derived meteorological conditions. Comprehensive analyses of temperature, humidity, wind direction and velocity, and barometric pressure led to the conclusion that this pollution event was caused by advection inversion. In the absence of temperature inversion, the atmosphere at a height of 0.15 km has a relatively large extinction coefficient. In situ measured particulates exhibited a very large diurnal range. However, under the influence of turbulences, AOT was rather stable with a value <0.2 at an altitude below 0.8 km. Advection inversion appeared at 9:00 AM on 24 December, and did not dissipate until 22:00 PM. This temperature inversion, to some degree, inhibited the dispersion of near-surface particulates. Affected by this temperature inversion, the atmospheric extinction coefficient near the surface became noticeably larger. Near-surface particulates hardly varied at a concentration around 0.2mg/m(3). AOT at an altitude below 0.8 km rose to 0.31.

  14. Monitoring changes in the Platte River riparian corridor with serial LiDAR surveys

    USGS Publications Warehouse

    Kinzel, Paul J.; Nelson, Jonathan M.; Wright, C. Wayne

    2006-01-01

    The Platte River in central Nebraska is a wide, sand-bedded river that provides habitat for migratory water birds along the North American flyway. The central Platte River functions as critical habitat for the endangered whooping crane (Grus americana) and also is an important habitat for the endangered least tern (Sterna antillarum) and the threatened piping plover (Charadrius melodus). Upstream water-resource development over the last century has decreased the water and sediment supplied to the central Platte River. This has resulted in vegetation encroachment and narrowing of Platte River channels. The National Academy of Sciences' National Research Council, in a recent review of these critical habitat designations, concluded that the current morphology of Platte River channels is limiting the recovery of the endangered and threatened avian species. Habitat-enhancement efforts along the Platte River currently (2006) are focused on the clearing of vegetation from in-channel and riparian areas, whereas future plans propose the release of water from upstream dams as a means to prevent vegetation from encroaching on the active river channel. For this reason, monitoring the physical response of the river channel to these management treatments is an important component of a proposed habitat recovery program. Understanding the effects of management strategies on Platte River riparian habitat also is a key objective of the U.S. Geological Survey's Platte River Priority Ecosystem Program (http://mcmcweb.er.usgs.gov/platte/). This fact sheet describes applications of LiDAR to monitor changes in the Platte River riparian corridor.

  15. Mapping of ice, snow and water using aircraft-mounted LiDAR

    NASA Astrophysics Data System (ADS)

    Church, Philip; Matheson, Justin; Owens, Brett

    2016-05-01

    Neptec Technologies Corp. has developed a family of obscurant-penetrating 3D laser scanners (OPAL 2.0) that are being adapted for airborne platforms for operations in Degraded Visual Environments (DVE). The OPAL uses a scanning mechanism based on the Risley prism pair. Data acquisition rates can go as high as 200kHz for ranges within 240m and 25kHz for ranges exceeding 240m. The scan patterns are created by rotating two prisms under independent motor control producing a conical Field-Of-View (FOV). An OPAL laser scanner with 90° FOV was installed on a Navajo aircraft, looking down through an aperture in the aircraft floor. The rotation speeds of the Risley prisms were selected to optimize a uniformity of the data samples distribution on the ground. Flight patterns simulating a landing approach over snow and ice in an unprepared Arctic environment were also performed to evaluate the capability of the OPAL LiDAR to map snow and ice elevation distribution in real-time and highlight potential obstacles. Data was also collected to evaluate the detection of wires when flying over water, snow and ice. Main results and conclusions obtained from the flight data analysis are presented.

  16. Automated As-Built Model Generation of Subway Tunnels from Mobile LiDAR Data.

    PubMed

    Arastounia, Mostafa

    2016-09-13

    This study proposes fully-automated methods for as-built model generation of subway tunnels employing mobile Light Detection and Ranging (LiDAR) data. The employed dataset is acquired by a Velodyne HDL 32E and covers 155 m of a subway tunnel containing six million points. First, the tunnel's main axis and cross sections are extracted. Next, a preliminary model is created by fitting an ellipse to each extracted cross section. The model is refined by employing residual analysis and Baarda's data snooping method to eliminate outliers. The final model is then generated by applying least squares adjustment to outlier-free data. The obtained results indicate that the tunnel's main axis and 1551 cross sections at 0.1 m intervals are successfully extracted. Cross sections have an average semi-major axis of 7.8508 m with a standard deviation of 0.2 mm and semi-minor axis of 7.7509 m with a standard deviation of 0.1 mm. The average normal distance of points from the constructed model (average absolute error) is also 0.012 m. The developed algorithm is applicable to tunnels with any horizontal orientation and degree of curvature since it makes no assumptions, nor does it use any a priori knowledge regarding the tunnel's curvature and horizontal orientation.

  17. Taking Stock of Circumboreal Forest Carbon With Ground Measurements, Airborne and Spaceborne LiDAR

    NASA Technical Reports Server (NTRS)

    Neigh, Christopher S. R.; Nelson, Ross F.; Ranson, K. Jon; Margolis, Hank A.; Montesano, Paul M.; Sun, Guoqing; Kharuk, Viacheslav; Naesset, Erik; Wulder, Michael A.; Andersen, Hans-Erik

    2013-01-01

    The boreal forest accounts for one-third of global forests, but remains largely inaccessible to ground-based measurements and monitoring. It contains large quantities of carbon in its vegetation and soils, and research suggests that it will be subject to increasingly severe climate-driven disturbance. We employ a suite of ground-, airborne- and space-based measurement techniques to derive the first satellite LiDAR-based estimates of aboveground carbon for the entire circumboreal forest biome. Incorporating these inventory techniques with uncertainty analysis, we estimate total aboveground carbon of 38 +/- 3.1 Pg. This boreal forest carbon is mostly concentrated from 50 to 55degN in eastern Canada and from 55 to 60degN in eastern Eurasia. Both of these regions are expected to warm >3 C by 2100, and monitoring the effects of warming on these stocks is important to understanding its future carbon balance. Our maps establish a baseline for future quantification of circumboreal carbon and the described technique should provide a robust method for future monitoring of the spatial and temporal changes of the aboveground carbon content.

  18. Morphometry and core type of streamlined bedforms in southern Sweden from high resolution LiDAR

    NASA Astrophysics Data System (ADS)

    Dowling, Thomas P. F.; Spagnolo, Matteo; Möller, Per

    2015-05-01

    This paper generates a new data set of streamlined glacial bedforms in southern Sweden, which is used both to test conclusions from previous work on streamlined bedform morphometrics and to advance our knowledge of streamlined bedforms on the Scandinavian Shield. The data set consists of streamlined glacial bedforms in southeast Sweden mapped from the new LiDAR-derived Swedish National Height Model, which has a pixel resolution of 2.0 m with a vertical resolution of 1 cm. We have mapped 10,311 features; of the mapped features, 135 are known to have an unconsolidated sediment core, 2120 a bedrock component, and 8055 whose core composition is unknown. The extracted morphological variables are then subjected to a univariate and bivariate analysis. We find that the extracted characteristics broadly fit into the lower end of the modal and median value spectrum of similar bedforms from around the world. The distribution of the variables is found to be log-normal to a first-order approximation. The covariant relationships between height and length, width and area are examined after the variables have been log-transformed and are found to be significant, if not particularly strong. Rock-cored features are found to have a longer modal length than soft-cored features, which suggests that reconstructions of past flow velocities from streamlined landforms need to closely consider core-type. Additionally, we find no support for a derived scaling law for streamlined features by plotting length, width, and elongation ratio against one another.

  19. Interpretations of GLAS LiDAR for the Tapajos National Forest, Brazil

    NASA Astrophysics Data System (ADS)

    Hunter, M. O.; Keller, M.; Lefsky, M.; Espà­Rito-Santo, F.

    2007-12-01

    LiDAR remote sensing has proven to be a valuable source of information for characterization of forest structure. We conducted a study at the Tapajós National Forest (TNF) in the state of Pará, Brazil (centered at 3.56S 55.06W) to understand how forest structural properties interpreted from GLAS derived forest heights compared to a more traditional forest classification. The vegetation classification map was based on forest surveys, topography, soils, and interpretation of Landsat data. The original map groups TNF into 16 vegetation classifications. Using approximately 1500 GLAS waveform height predictions (Lefsky, ICESat Vegetation Product, heights ver.0.2) we calculated the 10th and 90th percentile values of distributions. These were interpreted as signals of disturbance and potential forest stand height respectively. We found no clear agreement on an area by area basis though general coherent patterns were observed. Areas close to human populations and those with high water-table depths showed a lower 10th percentile signal indicative of frequent recent disturbance. High plateau areas on clay soils had the greatest 90th percentile values. Our data suggests that statistical interpretation of GLAS may be valuable for comprehensive analyses of forest structure.

  20. Automated delineation of karst sinkholes from LiDAR-derived digital elevation models

    NASA Astrophysics Data System (ADS)

    Wu, Qiusheng; Deng, Chengbin; Chen, Zuoqi

    2016-08-01

    Sinkhole mapping is critical for understanding hydrological processes and mitigating geological hazards in karst landscapes. Current methods for identifying sinkholes are primarily based on visual interpretation of low-resolution topographic maps and aerial photographs with subsequent field verification, which is labor-intensive and time-consuming. The increasing availability of high-resolution LiDAR-derived digital elevation data allows for an entirely new level of detailed delineation and analyses of small-scale geomorphologic features and landscape structures at fine scales. In this paper, we present a localized contour tree method for automated extraction of sinkholes in karst landscapes. One significant advantage of our automated approach for sinkhole extraction is that it may reduce inconsistencies and alleviate repeatability concerns associated with visual interpretation methods. In addition, the proposed method has contributed to improving the sinkhole inventory in several ways: (1) detection of non-inventoried sinkholes; (2) identification of previously inventoried sinkholes that have been filled; (3) delineation of sinkhole boundaries; and (4) characterization of sinkhole morphometric properties. We applied the method to Fillmore County in southeastern Minnesota, USA, and identified three times as many sinkholes as the existing database for the same area. The results suggest that previous visual interpretation method might significantly underestimate the number of potential sinkholes in the region. Our method holds great potential for creating and updating sinkhole inventory databases at a regional scale in a timely manner.

  1. Petroleum potential of the Amu Dar`ya Province, Western Uzbekistan and Eastern Turkmenistan

    SciTech Connect

    Clarke, J.W.

    1995-05-01

    The Amu Dar`ya gas-oil province coincides with a Mesozoic and Cenozoic sag basin that developed on an intermontane depression filled largely by Permian-Triassic redbeds and volcanics. The stratigraphic section of the basin is divided into two parts by an extensive evaporite deposit of Kimmeridgian age. The section below the evaporite consists of Lower-Middle Jurassic clastic rocks overlain by reef-bearing carbonate rocks of Callovian and Oxfordian age. The upper Jurassic and Cretaceous-Paleogene section consists largely of clastic rocks. Structurally the province is a mosaic of highs and lows controlled by basement faults. The Kimmeridgian evaporite is a regional seal for numerous pools in the Callovian-Oxfordian carbonate rocks. In the border areas of the province where the evaporite is not present, the hydrocarbons have migrated farther upward to collect in Lower Cretaceous traps. Prospects for further discovery are excellent in most parts of the province, but are particularly favorable in carbonate reef buildups in the southeastern part of the province. 18 refs., 6 figs.

  2. Deconstructing a polygenetic landscape using LiDAR and multi-resolution analysis

    NASA Astrophysics Data System (ADS)

    Barrineau, Patrick; Dobreva, Iliyana; Bishop, Michael P.; Houser, Chris

    2016-04-01

    It is difficult to deconstruct a complex polygenetic landscape into distinct process-form regimes using digital elevation models (DEMs) and fundamental land-surface parameters. This study describes a multi-resolution analysis approach for extracting geomorphological information from a LiDAR-derived DEM over a stabilized aeolian landscape in south Texas that exhibits distinct process-form regimes associated with different stages in landscape evolution. Multi-resolution analysis was used to generate average altitudes using a Gaussian filter with a maximum radius of 1 km at 20 m intervals, resulting in 50 generated DEMs. This multi-resolution dataset was analyzed using Principal Components Analysis (PCA) to identify the dominant variance structure in the dataset. The first 4 principal components (PC) account for 99.9% of the variation, and classification of the variance structure reveals distinct multi-scale topographic variation associated with different process-form regimes and evolutionary stages. Our results suggest that this approach can be used to generate quantitatively rigorous morphometric maps to guide field-based sedimentological and geophysical investigations, which tend to use purposive sampling techniques resulting in bias and error.

  3. Mapping of GDOP estimates through the use of LiDAR data

    NASA Astrophysics Data System (ADS)

    Amolins, Krista

    The positioning accuracy of the Global Positioning System (GPS) and other Global Navigation Satellite Systems is affected by the configuration of visible satellites. Dilution of Precision (DOP) values are a measure of the strength of the satellite configuration but the software tools currently available for calculating DOP values have a limited ability to take into account obstructions. Determining when the best satellite configuration will be observable at a particular location requires identifying obstructions in the area and ascertaining whether they are blocking satellite signals. In this research, Light Detection and Ranging (LiDAR) data were used to locate all the obstructions around each terrain point by extracting and comparing two surfaces, one that represented obstructions and one that represented the terrain. Once all the obstructions in a selected area had been identified, GPS satellite location data were used to determine satellite visibility at different epochs and to calculate GDOP (Geometrical DOP) at locations where at least four satellites were visible. Maps were then generated for each epoch showing the GDOP values over the selected area. Some small differences were noted between the clear sky GDOP values calculated by the proposed method and those output by an available software planning tool and in a few cases there was a discrepancy in the number of visible satellites identified due to slight differences in the calculated satellite elevations. Nevertheless, the maps produced by the proposed method give a better representation of the GDOP values in the field than do traditional methods or other software tools.

  4. Occupational environment as perceived by workers at a textile mill in Bahir Dar, northwest Ethiopia.

    PubMed

    Abebe, Y; Fantahun, M

    2000-10-01

    This cross sectional study was conducted among textile mill workers in Bahir Dar town in 1995/96. The main objective of the study was to investigate how workers perceive their work environment and explore their state of satisfaction with their work. A pretested questionnaire was administered by trained health workers to 394 production workers. The majority of the workers (53.6%) claimed the work environment to be hot. For 66.8%, the physical conditions around the working departments was worst during the hot season. The work place was perceived as dusty and noisy by 47.2% and 36.0% of the respondents respectively. The distribution of adverse environmental complaint by work department was not the same. A higher proportion of the workers in the spinning department complained of inadequate air movement (64.5%) and dusty work place (53.3%); whereas those in the weaving department complained the work place to be hot and noisy (60.5%, 53.5% respectively). Aprons were used by 95.7%, but other personal protectors such as ear protectors, gloves and goggles were used rarely. In general, 228 (57.9%) workers were satisfied but the rest were dissatisfied with their work environment. In order to improve the hygienic conditions in the work place, 71.2% suggested use of different kinds of personal protectors. In conclusion, personal protectors should always be used, environmental hygiene should be conducted and health education should be provided to workers.

  5. Hepatitis B virus markers in the population of Dar es Salaam, Tanzania.

    PubMed

    Haukenes, G; Shao, J F; Mbena, E; Rustad, S

    1987-09-01

    A total of 542 serum samples from healthy adults (medical students and medical staff, blood donors and pregnant women) residing in or near the city of Dar es Salaam, Tanzania were examined for markers of hepatitis B virus (HBV) infection. Of these samples, 95 (17.5%) were not found to contain any HBV marker when examined by enzyme-linked immunoassay for hepatitis B surface antigen (HBsAg), antibody to hepatitis B surface antigen (anti-HBs) and antibody to hepatitis B core antigen (anti-HBc). HBsAg was demonstrated in 52 (9.6%) samples of which 7 (13.5%) were positive for hepatitis Be antigen (HBeAg) and 17 (32.7%) were positive for anti-HBc IgM. None of 9 HBsAg positive pregnant women were carriers of HBeAg. These results show that hepatitis B infection is very common in this country. The relatively low prevalence of HBeAg among HBsAg carriers may indicate that transmission of hepatitis B at birth is not of major importance.

  6. LiDAR DEM for Slope regulations of land development in Taiwan

    NASA Astrophysics Data System (ADS)

    Liu, J.-K.; Yang, M.-S.; Wu, M.-C.; Hsu, W.-C.

    2012-04-01

    Slope gradient is a major parameter for regulating the development of slope-lands in Taiwan. According to official guidelines, only two methods can be adopted, namely the rectangular parcel method and the parcel contouring method. Both of them are manual methods using conventional analogue maps produced by photogrammetric method. As the trend of technology is in favor of adopting digital elevation models for automated production of slope maps and complete coverage of the territory of Taiwan with DEM in 40m, 5m and 1m grids have been mostly completed, it is needed to assess the difference of DEM approaches in comparison to the official approaches which is recognized as the only legal procedure until now. Thus, a 1/1000 contour map in the sloping land of suburban area of New Taipei City is selected for this study. Manual approaches are carried out using the contour lines with 2m intervals. DEM grids of 1m, 5m, and 10m are generated by LiDAR survey. It is shown that the slope maps generated by Eight Neighbors Unweighted method are comparable or even better than the conventional approaches. As the conventional approach is prone to error propagations and uncertainties, the new digital approach should be implemented and enforced in the due process of law.

  7. Optimizing embedded sensor network design for catchment-scale snow-depth estimation using LiDAR and machine learning

    NASA Astrophysics Data System (ADS)

    Oroza, Carlos A.; Zheng, Zeshi; Glaser, Steven D.; Tuia, Devis; Bales, Roger C.

    2016-10-01

    We evaluate the accuracy of a machine-learning algorithm that uses LiDAR data to optimize ground-based sensor placements for catchment-scale snow measurements. Sampling locations that best represent catchment physiographic variables are identified with the Expectation Maximization algorithm for a Gaussian mixture model. A Gaussian process is then used to model the snow depth in a 1 km2 area surrounding the network, and additional sensors are placed to minimize the model uncertainty. The aim of the study is to determine the distribution of sensors that minimizes the bias and RMSE of the model. We compare the accuracy of the snow-depth model using the proposed placements to an existing sensor network at the Southern Sierra Critical Zone Observatory. Each model is validated with a 1 m2 LiDAR-derived snow-depth raster from 14 March 2010. The proposed algorithm exhibits higher accuracy with fewer sensors (8 sensors, RMSE 38.3 cm, bias = 3.49 cm) than the existing network (23 sensors, RMSE 53.0 cm, bias = 15.5 cm) and randomized placements (8 sensors, RMSE 63.7 cm, bias = 24.7 cm). We then evaluate the spatial and temporal transferability of the method using 14 LiDAR scenes from two catchments within the JPL Airborne Snow Observatory. In each region, the optimized sensor placements are determined using the first available snow raster for the year. The accuracy in the remaining LiDAR surveys is then compared to 100 configurations of sensors selected at random. We find the error statistics (bias and RMSE) to be more consistent across the additional surveys than the average random configuration.

  8. Automatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models

    NASA Astrophysics Data System (ADS)

    Abayowa, Bernard O.; Yilmaz, Alper; Hardie, Russell C.

    2015-08-01

    This paper presents a framework for automatic registration of both the optical and 3D structural information extracted from oblique aerial imagery to a Light Detection and Ranging (LiDAR) point cloud without prior knowledge of an initial alignment. The framework employs a coarse to fine strategy in the estimation of the registration parameters. First, a dense 3D point cloud and the associated relative camera parameters are extracted from the optical aerial imagery using a state-of-the-art 3D reconstruction algorithm. Next, a digital surface model (DSM) is generated from both the LiDAR and the optical imagery-derived point clouds. Coarse registration parameters are then computed from salient features extracted from the LiDAR and optical imagery-derived DSMs. The registration parameters are further refined using the iterative closest point (ICP) algorithm to minimize global error between the registered point clouds. The novelty of the proposed approach is in the computation of salient features from the DSMs, and the selection of matching salient features using geometric invariants coupled with Normalized Cross Correlation (NCC) match validation. The feature extraction and matching process enables the automatic estimation of the coarse registration parameters required for initializing the fine registration process. The registration framework is tested on a simulated scene and aerial datasets acquired in real urban environments. Results demonstrates the robustness of the framework for registering optical and 3D structural information extracted from aerial imagery to a LiDAR point cloud, when co-existing initial registration parameters are unavailable.

  9. Approach to voxel-based carbon stock quanticiation using LiDAR data in tropical rainforest, Brunei

    NASA Astrophysics Data System (ADS)

    Kim, Eunji; Piao, Dongfan; Lee, Jongyeol; Lee, Woo-Kyun; Yoon, Mihae; Moon, Jooyeon

    2016-04-01

    Forest is an important means to adapt climate change as the only carbon sink recognized by the international community (KFS 2009). According to the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5), Agriculture, Forestry, and Other Land Use (AFOLU) sectors including forestry contributed 24% of total anthropogenic emissions in 2010 (IPCC 2014; Tubiello et al. 2015). While all sectors excluding AFOLU have increased Greenhouse Gas (GHG) emissions, land use sectors including forestry remains similar level as before due to decreasing deforestation and increasing reforestation. In earlier researches, optical imagery has been applied for analysis (Jakubowski et al. 2013). Optical imagery collects spectral information in 2D. It is difficult to effectively quantify forest stocks, especially in dense forest (Cui et al. 2012). To detect individual trees information from remotely sensed data, Light detection and ranging (LiDAR) has been used (Hyyppäet al. 2001; Persson et al. 2002; Chen et al. 2006). Moreover, LiDAR has the ability to actively acquire vertical tree information such as tree height using geo-registered 3D points (Kwak et al. 2007). In general, however, geo-register 3D point was used with a raster format which contains only 2D information by missing all the 3D data. Therefore, this research aimed to use the volumetric pixel (referred as "voxel") approach using LiDAR data in tropical rainforest, Brunei. By comparing the parameters derived from voxel based LiDAR data and field measured data, we examined the relationships between them for the quantification of forest carbon. This study expects to be more helpful to take advantage of the strategic application of climate change adaption.

  10. Towards a more Complete Survey of Rockfall Activity: Seismic and LiDAR Detection, Location and Volume Estimate

    NASA Astrophysics Data System (ADS)

    Dietze, M., VI; Mohadjer, S.; Burtin, A.; Turowski, J. M.; Ehlers, T. A.; Hovius, N.

    2015-12-01

    Rockfall activity in steep alpine landscapes is often difficult to survey due to its infrequent nature. Classical approaches are limited by temporal and spatial resolution. In contrast, seismic monitoring provides access to catchment-wide analysis of activity patterns in rockfall-dominated environments. The deglaciated U-shaped Lauterbrunnen Valley in the Bernese Oberland, Switzerland, is a perfect example of such landscapes. It was instrumented with up to six broadband seismometers (capable of detecting volumes down to individual clasts) and repeatedly surveyed by terrestrial LiDAR (few weeks lapse time) to provide independent validation of the seismic data. During August-October 2014 and April-June 2015 more than 23 (LiDAR) to hundred (seismic) rockfall and icefall events were detected. Their volumes range from 0.1 to 5.80 m3 as detected by LiDAR. At the beginning of April 2015, increased activity was detected with more than 40 ice- or rockfalls in less than two hours. The evolution of these individual events (i.e., precursor activity, detachment, falling phase, impact, talus cone activity) is quantified in terms of location (within less than 200 m uncertainty) and duration. For events that consist of single detachments rather than a series of releases, volume scaling relationships are presented. Rockfall activity is linked to meteorological patterns at different temporal cycles. Seismic monitoring approaches are well-suited for studying not only the rockfall process but also for understanding the geomorphic framework and boundary conditions that control such processes in a comprehensive way. Taken together, the combined LiDAR and seismic monitoring approach provides high fidelity spatial and temporal resolution of individual events.

  11. To the Application of LiDAR to Detect the Geological Structures in Sulphurets Property, British Columbia, Canada

    NASA Astrophysics Data System (ADS)

    Koohzare, A.; Rezaeian, M.; McIntosh, A.

    2009-05-01

    The Kerr Sulphurets property in North Western British Columbia has been explored primarily as a placer gold holding since the 1880s; and, potentially includes one of Canada's largest gold deposits (e.g. the Mitchell Zone). The Sulphurets camp has been classified by Taylor in 2007 as a prominent global epithermal high-sulphidation subtype with 10 million tonnes of ore (reserves + production) containing approximately 10 g/t gold. The geological and geophysical observations of this deposit indicate intrusion- related mineralized veins which are known to overlap as the result of structural complexities. Faulting predates mineralization and alteration and dramatically dominates the location of the mineralization for this porphyry- epithermal high-sulphidation deposit (Britton and Alldrick 1988, British Columbia Ministry of Energy, Mines and Petroleum Resources, 1992; Margolis, 1993). However, the surface trace of these structures and lineaments within the site is obscured by vegetation, glacial cover and steep topographic relief. We used high resolution LiDAR airborne bare-earth sensing (vegetative data deleted) in an effort to detect the surface geological features and lineaments in the Kerr Sulphurets site. The LiDAR flight was designed to acquire high density data with 2 points per square meter using a 150 kHz multipulse system. High resolution LiDAR data provides a level of detail not achievable by other digital terrain modelling techniques, whether extracted from aerial photography, low-resolution topographic contour maps, 10-30 meter USGS, or SRTM digital elevation models. LiDAR bare-earth data spectacularly revealed hidden geological structures within the property district, which in turn assisted in identifying the high potential zones for mineralization in Sulphurets.

  12. Characteristics and geographic distribution of HIV-positive women diagnosed with cervical cancer in Dar es Salaam, Tanzania.

    PubMed

    Lovgren, Kathleen; Soliman, Amr S; Ngoma, Twalib; Kahesa, Crispin; Meza, Jane

    2016-10-01

    Cervical cancer is the leading incident cancer and the main cause of cancer-related mortality among women in sub-Saharan Africa. Furthermore, HIV-infected women are at a higher risk of developing cervical cancer than HIV-negative women. The purpose of this study was to distinguish differences in characteristics of HIV-positive and HIV-negative patients with cervical cancer in Dar es Salaam, Tanzania. The HIV status of cervical cancer patients diagnosed and/or treated at Ocean Road Cancer Institute in Dar es Salaam, Tanzania, during the period 2007-2011 was abstracted from the medical records. Additional abstracted information included patient's name, age, place of residence, occupation, education, marital status, age at marriage, gravidity, and screening clinic visit results. Ocean Road Cancer Institute patients came from two sources: the screening clinic followed by treatment clinic or the treatment clinic without prior screening. HIV-positive and HIV-negative patients were compared regarding the above-listed clinical and epidemiologic factors. Multivariable analysis was also performed to assess the risk factors associated with cervical cancer treatment without prior screening at Ocean Road Cancer Institute. HIV-positive cervical cancer patients tended to be younger, with higher education and lower parity. Patients screened for cervical cancer prior to treatment were more likely to be HIV-positive (OR: 2.09, 95% CI: 1.36, 3.21), less likely to have higher disease stages (OR: 0.64, 95% CI: 0.43, 0.94), and less likely to reside outside of Dar es Salaam (OR: 0.44, 95% CI: 0.30, 0.65). Screening for cervical cancer at Ocean Road Cancer Institute is utilised by more HIV-positive patients from Dar es Salaam. Future studies should focus on identifying the reasons for lower utilisation of screening by HIV-negative patients and patients from other distant rural regions in Tanzania.

  13. Assessment of seismic loading on structures based on airborne LiDAR data from the Kalochori urban area (N. Greece)

    NASA Astrophysics Data System (ADS)

    Rovithis, Emmanouil; Kirtas, Emmanouil; Marini, Eleftheria; Bliziotis, Dimitris; Maltezos, Evangelos; Pitilakis, Dimitris; Makra, Konstantia; Savvaidis, Alexandros

    2016-08-01

    Airborne LiDAR monitoring integrated with field data is employed to assess the fundamental period and the seismic loading of structures composing an urban area under prescribed earthquake scenarios. Α piecewise work-flow is adopted by combining geometrical data of the building stock derived from a LiDAR-based 3D city model, structural data from in-situ inspections on representative city blocks and results of soil response analyses. The procedure is implemented in the residential area of Kalochori, (west of Thessaloniki in Northern Greece). Special attention is paid to the in-situ inspection of the building stock in order to discriminate recordings between actual buildings and man-made constructions that do not conform to seismic design codes and to acquire additional building stock data on structural materials, typologies and number of stories which is not feasible by the LiDAR process. The processed LiDAR and field data are employed to compute the fundamental period of each building by means of code-defined formulas. Knowledge of soil conditions in the Kalochoti area allows for soil response analyses to obtain free-field at ground surface under earthquake scenarios with varying return period. Upon combining the computed vibrational characteristics of the structures with the free-field response spectra, the seismic loading imposed on the structures of the urban area under investigation is derived for each one of the prescribed seismic motions. Results are presented in GIS environment in the form of spatially distributed spectral accelerations with direct implications in seismic vulnerability studies of an urban area.

  14. A Whole Genome DArTseq and SNP Analysis for Genetic Diversity Assessment in Durum Wheat from Central Fertile Crescent

    PubMed Central

    Shahid, Muhammad Qasim; Çiftçi, Vahdettin; E. Sáenz de Miera, Luis; Aasim, Muhammad; Nadeem, Muhammad Azhar; Aktaş, Husnu; Özkan, Hakan; Hatipoğlu, Rüştü

    2017-01-01

    Until now, little attention has been paid to the geographic distribution and evaluation of genetic diversity of durum wheat from the Central Fertile Crescent (modern-day Turkey and Syria). Turkey and Syria are considered as primary centers of wheat diversity, and thousands of locally adapted wheat landraces are still present in the farmers’ small fields. We planned this study to evaluate the genetic diversity of durum wheat landraces from the Central Fertile Crescent by genotyping based on DArTseq and SNP analysis. A total of 39,568 DArTseq and 20,661 SNP markers were used to characterize the genetic characteristic of 91 durum wheat land races. Clustering based on Neighbor joining analysis, principal coordinate as well as Bayesian model implemented in structure, clearly showed that the grouping pattern is not associated with the geographical distribution of the durum wheat due to the mixing of the Turkish and Syrian landraces. Significant correlation between DArTseq and SNP markers was observed in the Mantel test. However, we detected a non-significant relationship between geographical coordinates and DArTseq (r = -0.085) and SNP (r = -0.039) loci. These results showed that unconscious farmer selection and lack of the commercial varieties might have resulted in the exchange of genetic material and this was apparent in the genetic structure of durum wheat in Turkey and Syria. The genomic characterization presented here is an essential step towards a future exploitation of the available durum wheat genetic resources in genomic and breeding programs. The results of this study have also depicted a clear insight about the genetic diversity of wheat accessions from the Central Fertile Crescent. PMID:28099442

  15. Genetic Structure, Linkage Disequilibrium and Signature of Selection in Sorghum: Lessons from Physically Anchored DArT Markers

    PubMed Central

    Bouchet, Sophie; Pot, David; Deu, Monique; Rami, Jean-François; Billot, Claire; Perrier, Xavier; Rivallan, Ronan; Gardes, Laëtitia; Xia, Ling; Wenzl, Peter; Kilian, Andrzej; Glaszmann, Jean-Christophe

    2012-01-01

    Population structure, extent of linkage disequilibrium (LD) as well as signatures of selection were investigated in sorghum using a core sample representative of worldwide diversity. A total of 177 accessions were genotyped with 1122 informative physically anchored DArT markers. The properties of DArTs to describe sorghum genetic structure were compared to those of SSRs and of previously published RFLP markers. Model-based (STRUCTURE software) and Neighbor-Joining diversity analyses led to the identification of 6 groups and confirmed previous evolutionary hypotheses. Results were globally consistent between the different marker systems. However, DArTs appeared more robust in terms of data resolution and bayesian group assignment. Whole genome linkage disequilibrium as measured by mean r2 decreased from 0.18 (between 0 to 10 kb) to 0.03 (between 100 kb to 1 Mb), stabilizing at 0.03 after 1 Mb. Effects on LD estimations of sample size and genetic structure were tested using i. random sampling, ii. the Maximum Length SubTree algorithm (MLST), and iii. structure groups. Optimizing population composition by the MLST reduced the biases in small samples and seemed to be an efficient way of selecting samples to make the best use of LD as a genome mapping approach in structured populations. These results also suggested that more than 100,000 markers may be required to perform genome-wide association studies in collections covering worldwide sorghum diversity. Analysis of DArT markers differentiation between the identified genetic groups pointed out outlier loci potentially linked to genes controlling traits of interest, including disease resistance genes for which evidence of selection had already been reported. In addition, evidence of selection near a homologous locus of FAR1 concurred with sorghum phenotypic diversity for sensitivity to photoperiod. PMID:22428056

  16. Automated Detection of Geomorphic Features in LiDAR Point Clouds of Various Spatial Density

    NASA Astrophysics Data System (ADS)

    Dorninger, Peter; Székely, Balázs; Zámolyi, András.; Nothegger, Clemens

    2010-05-01

    LiDAR, also referred to as laser scanning, has proved to be an important tool for topographic data acquisition. Terrestrial laser scanning allows for accurate (several millimeter) and high resolution (several centimeter) data acquisition at distances of up to some hundred meters. By contrast, airborne laser scanning allows for acquiring homogeneous data for large areas, albeit with lower accuracy (decimeter) and resolution (some ten points per square meter) compared to terrestrial laser scanning. Hence, terrestrial laser scanning is preferably used for precise data acquisition of limited areas such as landslides or steep structures, while airborne laser scanning is well suited for the acquisition of topographic data of huge areas or even country wide. Laser scanners acquire more or less homogeneously distributed point clouds. These points represent natural objects like terrain and vegetation and artificial objects like buildings, streets or power lines. Typical products derived from such data are geometric models such as digital surface models representing all natural and artificial objects and digital terrain models representing the geomorphic topography only. As the LiDAR technology evolves, the amount of data produced increases almost exponentially even in smaller projects. This means a considerable challenge for the end user of the data: the experimenter has to have enough knowledge, experience and computer capacity in order to manage the acquired dataset and to derive geomorphologically relevant information from the raw or intermediate data products. Additionally, all this information might need to be integrated with other data like orthophotos. In all theses cases, in general, interactive interpretation is necessary to determine geomorphic structures from such models to achieve effective data reduction. There is little support for the automatic determination of characteristic features and their statistical evaluation. From the lessons learnt from automated

  17. An Integrated Method for Mapping Impervious and Pervious Areas in Urban Environments Using Hyperspectral and LiDAR Data

    NASA Astrophysics Data System (ADS)

    Hashemi Beni, L.; McArdle, S.; Khayer, Y.

    2014-11-01

    As urbanization continues to increase and extreme climatic events become more prevalent, urban planners and engineers are actively implementing adaptive measures to protect urban assets and communities. To support the urban planning adaptation process, mapping of impervious and pervious areas is essential to understanding the hydrodynamic environment within urban areas for flood risk planning. The application of advance geospatial data and analytical techniques using remote sensing and GIS can improve land surface characterization to better quantify surface run-off and infiltration. This study presents a method to combine airborne hyperspectral and LiDAR data for classifying pervious (e.g. vegetation, gravel, and soil) and impervious (e.g. asphalt and concrete) areas within road allowance areas for the City of Surrey, British Columbia, Canada. Hyperspectral data was acquired using the Compact Airborne Spectrographic Imager (CASI) at 1 m ground spatial resolution, consisting of 72 spectral bands, and LiDAR data acquired from Leica Airborne LiDAR system at a density of 20 points/m2. A spectral library was established using 10 cm orthophotography and GIS data to identify surface features. In addition to spectral functions such as mean and standard deviation, several spectral indices were developed to discriminate between asphalt, concrete, gravel, vegetation, and shadows respectively. A spectral analysis of selected endmembers was conducted and an initial classification technique was applied using Spectral Angle Mapper (SAM). The classification results (i.e. shadows) were improved by integrating LIDAR data with the hyperspectral data.

  18. Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification

    PubMed Central

    Gong, Wei; Sun, Jia; Shi, Shuo; Yang, Jian; Du, Lin; Zhu, Bo; Song, Shalei

    2015-01-01

    The abilities of multispectral LiDAR (MSL) as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%–39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image. PMID:26340630

  19. Quantifying erosion and deposition patterns using airborne LiDAR following the 2012 High Park Fire and 2013 Colorado Flood

    NASA Astrophysics Data System (ADS)

    Brogan, D. J.; Nelson, P. A.; MacDonald, L. H.

    2015-12-01

    Quantifying and predicting geomorphic change over large spatial scales is increasingly feasible and of growing interest as repeat high resolution topography becomes available. We began detailed field studies of channel geomorphic change using RTK-GPS in two 15 km2 watersheds following the 2012 High Park Fire; the watersheds were then subjected to a several-hundred year flood in September 2013. During this time a series of airborne LiDAR datasets were collected, and the objectives of this study were to: 1) determine and compare the spatial variability in channel and valley erosion and deposition over time from the LiDAR; and 2) determine if the observed changes can be predicted from channel and valley bottom characteristics. Data quality issues in the initial LiDAR required us to rotate and translate flight lines in order to co-register ground-classified point clouds between successive datasets; uncertainty was then estimated using our RTK-GPS field measurements. Topographic changes were calculated using the Multiscale Model to Model Cloud Comparison (M3C2) algorithm. Results indicate that the 2013 flood mobilized much more sediment than was mobilized due to the fire alone; unfortunately the uncertainty in differencing is still frequently greater than the observed changes, especially within transfer reaches. Valley expansion and constriction are major controls on spatial patterns of erosion and deposition, suggesting that topographic metrics such as longitudinal distributions of channel slope and valley confinement may provide quasi-physically based estimates of sediment deposition and delivery potential.

  20. Hydrography change detection: the usefulness of surface channels derived From LiDAR DEMs for updating mapped hydrography

    USGS Publications Warehouse

    Poppenga, Sandra K.; Gesch, Dean B.; Worstell, Bruce B.

    2013-01-01

    The 1:24,000-scale high-resolution National Hydrography Dataset (NHD) mapped hydrography flow lines require regular updating because land surface conditions that affect surface channel drainage change over time. Historically, NHD flow lines were created by digitizing surface water information from aerial photography and paper maps. Using these same methods to update nationwide NHD flow lines is costly and inefficient; furthermore, these methods result in hydrography that lacks the horizontal and vertical accuracy needed for fully integrated datasets useful for mapping and scientific investigations. Effective methods for improving mapped hydrography employ change detection analysis of surface channels derived from light detection and ranging (LiDAR) digital elevation models (DEMs) and NHD flow lines. In this article, we describe the usefulness of surface channels derived from LiDAR DEMs for hydrography change detection to derive spatially accurate and time-relevant mapped hydrography. The methods employ analyses of horizontal and vertical differences between LiDAR-derived surface channels and NHD flow lines to define candidate locations of hydrography change. These methods alleviate the need to analyze and update the nationwide NHD for time relevant hydrography, and provide an avenue for updating the dataset where change has occurred.

  1. Mapping standing dead trees (snags) in the aftermath of the 2013 Rim Fire using airborne LiDAR data.

    NASA Astrophysics Data System (ADS)

    Casas Planes, Á.; Garcia-Alonso, M.; Koltunov, A.; Ustin, S.; Falk, M.; Ramirez, C.; Siegel, R.

    2014-12-01

    Abundance and spatial distribution of standing dead trees (snags) are key indicators of forest biodiversity and ecosystem health and represent a critical component of habitat for various wildlife species, including the great grey owl and the black-backed woodpecker. In this work we assess the potential of light detection and ranging (LiDAR) to discriminate snags from the live trees and map their distribution. The study area encompasses the burn perimeter of the Rim Fire, the third largest wildfire in California's recorded history (~104.000 ha) and represents a heterogeneous mosaic of mixed conifer forests, hardwood, and meadows. The snags mapping procedure is based on a 3D single tree detection using a Watershed algorithm and the extraction of height and intensity metrics within each segment. Variables selected using Gaussian processes form a feature space for a classifier to distinguish between dead trees and live trees. Finally, snag density and snag diameter classes that are relevant for avian species are mapped. This work shows the use of LiDAR metrics to quantify ecological variables related to the vertical heterogeneity of the forest canopy that are important in the identification of snags, for example, fractional cover. We observed that intensity-related variables are critical to the successful identification of snags and their distribution. Our study highlights the importance of high-density LiDAR for characterizing the forest structural variables that contribute to the assessment of wildlife habitat suitability.

  2. Molecular epidemiology of HIV-associated tuberculosis in Dar es Salaam, Tanzania: strain predominance, clustering, and polyclonal disease.

    PubMed

    Adams, Lisa V; Kreiswirth, Barry N; Arbeit, Robert D; Soini, Hanna; Mtei, Lillian; Matee, Mecky; Bakari, Muhammad; Lahey, Timothy; Wieland-Alter, Wendy; Shashkina, Elena; Kurepina, Natalia; Driscoll, Jeffrey R; Pallangyo, Kisali; Horsburgh, C Robert; von Reyn, C Fordham

    2012-08-01

    Molecular typing of Mycobacterium tuberculosis can be used to elucidate the epidemiology of tuberculosis, including the rates of clustering, the frequency of polyclonal disease, and the distribution of genotypic families. We performed IS6110 typing and spoligotyping on M. tuberculosis strains isolated from HIV-infected subjects at baseline or during follow-up in the DarDar Trial in Tanzania and on selected community isolates. Clustering occurred in 203 (74%) of 275 subjects: 124 (80%) of 155 HIV-infected subjects with baseline isolates, 56 (69%) of 81 HIV-infected subjects with endpoint isolates, and 23 (59%) of 39 community controls. Overall, 113 (41%) subjects had an isolate representing the East Indian "GD" family. The rate of clustering was similar among vaccine and placebo recipients and among subjects with or without cellular immune responses to mycobacterial antigens. Polyclonal disease was detected in 6 (43%) of 14 patients with multiple specimens typed. Most cases of HIV-associated tuberculosis among subjects from this study in Dar es Salaam resulted from recently acquired infection. Polyclonal infection was detected and isolates representing the East Indian GD strain family were the most common.

  3. Intergration of LiDAR Data with Aerial Imagery for Estimating Rooftop Solar Photovoltaic Potentials in City of Cape Town

    NASA Astrophysics Data System (ADS)

    Adeleke, A. K.; Smit, J. L.

    2016-06-01

    Apart from the drive to reduce carbon dioxide emissions by carbon-intensive economies like South Africa, the recent spate of electricity load shedding across most part of the country, including Cape Town has left electricity consumers scampering for alternatives, so as to rely less on the national grid. Solar energy, which is adequately available in most part of Africa and regarded as a clean and renewable source of energy, makes it possible to generate electricity by using photovoltaics technology. However, before time and financial resources are invested into rooftop solar photovoltaic systems in urban areas, it is important to evaluate the potential of the building rooftop, intended to be used in harvesting the solar energy. This paper presents methodologies making use of LiDAR data and other ancillary data, such as high-resolution aerial imagery, to automatically extract building rooftops in City of Cape Town and evaluate their potentials for solar photovoltaics systems. Two main processes were involved: (1) automatic extraction of building roofs using the integration of LiDAR data and aerial imagery in order to derive its' outline and areal coverage; and (2) estimating the global solar radiation incidence on each roof surface using an elevation model derived from the LiDAR data, in order to evaluate its solar photovoltaic potential. This resulted in a geodatabase, which can be queried to retrieve salient information about the viability of a particular building roof for solar photovoltaic installation.

  4. Prediction of L-band signal attenuation in forests using 3D vegetation structure from airborne LiDAR

    NASA Astrophysics Data System (ADS)

    Liu, Pang-Wei; Lee, Heezin; Judge, Jasmeet; Wright, William C.; Clint Slatton, K.

    2011-09-01

    In this study, we propose a novel method to predict microwave attenuation in forested areas by using airborne Light Detection and Ranging (LiDAR). While propagating through a vegetative medium, microwave signals suffer from reflection, absorption, and scattering within vegetation, which cause signal attenuation and, consequently, deteriorate signal reception and information interpretation. A Fresnel zone enveloping the radio frequency line-of-sight is applied to segment vegetation structure occluding signal propagation. Return parameters and the spatial distribution of vegetation from the airborne LiDAR inside Fresnel zones are used to weight the laser points to estimate directional vegetation structure. A Directional Vegetation Density (DVD) model is developed through regression that links the vegetation structure to the signal attenuation at the L-band using GPS observations in a mixed forest in North Central Florida. The DVD model is compared with currently-used empirical models and obtained better R2 values of 0.54 than the slab-based models. Finally, the model is evaluated by comparing with GPS observations of signal attenuation. An overall root mean square error of 3.51 dB and a maximum absolute error of 9.38 dB are found. Sophisticated classification algorithms and full-waveform LiDAR systems may significantly improve the estimation of signal attenuation.

  5. Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification.

    PubMed

    Gong, Wei; Sun, Jia; Shi, Shuo; Yang, Jian; Du, Lin; Zhu, Bo; Song, Shalei

    2015-09-02

    The abilities of multispectral LiDAR (MSL) as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%-39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image.

  6. Use of LiDAR in the conservation management of the endangered red squirrel (Sciurus vulgaris L.)

    NASA Astrophysics Data System (ADS)

    Flaherty, Silvia; Lurz, Peter W. W.; Patenaude, Genevieve

    2014-01-01

    LiDAR remote sensing allows the direct retrieval of vegetation structure parameters and has been widely used to assess habitat quality for various species. The aim of this study is to test whether LiDAR can help in providing estimates of habitat suitability over larger scales and inform conservation management planning in stronghold areas of an endangered forest mammal, the red squirrel (Sciurus vulgaris L.). The Eurasian red squirrel is endangered in the UK and under strict legal protection. Hence, long-term habitat management is a key goal of the UK conservation strategy. This involves understanding habitat preferences of the species. In a previous study, we demonstrated the importance of forest structure for red squirrels' habitat preference. We used a general linear model (GLM) to relate the distribution and abundance of squirrel feeding signs to mean canopy closure, mean tree height, and the total number of trees at the plot level. However, this analysis was limited to a few sample areas. In the current study, we implement the GLM using LiDAR-derived explanatory variables in Abernethy Forest. Results suggest that when forest structure is considered, only 27% of the total forest area is highly suitable for red squirrel. Implications for management are discussed.

  7. Comparison of four methods of aerodynamic roughness length parameterization in semi-arid shrublands with airborne LiDAR, hyperspectral, and meteorological data

    NASA Astrophysics Data System (ADS)

    Li, A.; Mitchell, J. J.; Glenn, N. F.; Zhao, W.; Germino, M. J.; Allen, R.; Sankey, J. B.

    2013-12-01

    The aerodynamic roughness length (z0) plays an important role in the flux exchange between the land surface and atmosphere. Especially in semiarid shrublands, z0 is a key parameter for physical models of aeolian transport. z0 is influenced by the height, geometry, density and pattern of roughness elements. Light detection and ranging (LiDAR) is well suited to measure the vegetation height and has been used to estimate z0 across large areas. In this study, we combined airborne LiDAR, hyperspectral imagery and meteorological measurements to estimate z0, and assessed the ability of airborne LiDAR to estimate z0 over semi-arid shrublands. Airborne LiDAR data was used to derive the height of Wyoming big sagebrush (Artemisia tridentate subsp. wyomingensis) over a study area in the Great Basin, Idaho. Roughness density was related with percent vegetation cover which was estimated by integrating LiDAR and hyperspectral data, both collected in August 2011. Four methods of parameterization of z0 were applied and compared with the vegetation height from LiDAR; roughness from LiDAR and hyperspectral; NDVI and LAI from HyMap; and a geometric approach using meteorological data (e.g. wind speed). Micrometeorological measurements at two eddy covariance sites in the study area were used for validation of parameterized z0. The spatial variability of z0 was analyzed and the relationship with vegetation density was explored. The results demonstrated the potential of using airborne LiDAR data to estimate z0 at a regional scale in semi-arid shrublands. Furthermore, z0 showed a tight relationship with local variance of vegetation height and vegetation density.

  8. Description of durum wheat linkage map and comparative sequence analysis of wheat mapped DArT markers with rice and Brachypodium genomes

    PubMed Central

    2013-01-01

    Background The importance of wheat to the world economy, together with progresses in high-throughput next-generation DNA sequencing, have accelerated initiatives of genetic research for wheat improvement. The availability of high density linkage maps is crucial to identify genotype-phenotype associations, but also for anchoring BAC contigs to genetic maps, a strategy followed for sequencing the wheat genome. Results Here we report a genetic linkage map in a durum wheat segregating population and the study of mapped DArT markers. The linkage map consists of 126 gSSR, 31 EST-SSR and 351 DArT markers distributed in 24 linkage groups for a total length of 1,272 cM. Through bioinformatic approaches we have analysed 327 DArT clones to reveal their redundancy, syntenic and functional aspects. The DNA sequences of 174 DArT markers were assembled into a non-redundant set of 60 marker clusters. This explained the generation of clusters in very small chromosome regions across genomes. Of these DArT markers, 61 showed highly significant (Expectation < E-10) BLAST similarity to gene sequences in public databases of model species such as Brachypodium and rice. Based on sequence alignments, the analysis revealed a mosaic gene conservation, with 54 and 72 genes present in rice and Brachypodium species, respectively. Conclusions In the present manuscript we provide a detailed DArT markers characterization and the basis for future efforts in durum wheat map comparing. PMID:24304553

  9. Mapping tropical forest biomass with radar and spaceborne LiDAR: overcoming problems of high biomass and persistent cloud

    NASA Astrophysics Data System (ADS)

    Mitchard, E. T. A.; Saatchi, S. S.; White, L. J. T.; Abernethy, K. A.; Jeffery, K. J.; Lewis, S. L.; Collins, M.; Lefsky, M. A.; Leal, M. E.; Woodhouse, I. H.; Meir, P.

    2011-08-01

    Spatially-explicit maps of aboveground biomass are essential for calculating the losses and gains in forest carbon at a regional to national level. The production of such maps across wide areas will become increasingly necessary as international efforts to protect primary forests, such as the REDD+ (Reducing Emissions from Deforestation and forest Degradation) mechanism, come into effect, alongside their use for management and research more generally. However, mapping biomass over high-biomass tropical forest is challenging as (1) direct regressions with optical and radar data saturate, (2) much of the tropics is persistently cloud-covered, reducing the availability of optical data, (3) many regions include steep topography, making the use of radar data complex, (4) while LiDAR data does not suffer from saturation, expensive aircraft-derived data are necessary for complete coverage. We present a solution to the problems, using a combination of terrain-corrected L-band radar data (ALOS PALSAR), spaceborne LiDAR data (ICESat GLAS) and ground-based data. We map Gabon's Lopé National Park (5000 km2) because it includes a range of vegetation types from savanna to closed-canopy tropical forest, is topographically complex, has no recent cloud-free high-resolution optical data, and the dense forest is above the saturation point for radar. Our 100 m resolution biomass map is derived from fusing spaceborne LiDAR (7142 ICESat GLAS footprints), 96 ground-based plots (average size 0.8 ha) and an unsupervised classification of terrain-corrected ALOS PALSAR radar data, from which we derive the aboveground biomass stocks of the park to be 78 Tg C (173 Mg C ha-1). This value is consistent with our field data average of 181 Mg C ha-1, from the field plots measured in 2009 covering a total of 78 ha, and which are independent as they were not used for the GLAS-biomass estimation. We estimate an uncertainty of ± 25 % on our carbon stock value for the park. This error term includes

  10. Using LiDAR to Estimate Surface Erosion Volumes within the Post-storm 2012 Bagley Fire

    NASA Astrophysics Data System (ADS)

    Mikulovsky, R. P.; De La Fuente, J. A.; Mondry, Z. J.

    2014-12-01

    The total post-storm 2012 Bagley fire sediment budget of the Squaw Creek watershed in the Shasta-Trinity National Forest was estimated using many methods. A portion of the budget was quantitatively estimated using LiDAR. Simple workflows were designed to estimate the eroded volume's of debris slides, fill failures, gullies, altered channels and streams. LiDAR was also used to estimate depositional volumes. Thorough manual mapping of large erosional features using the ArcGIS 10.1 Geographic Information System was required as these mapped features determined the eroded volume boundaries in 3D space. The 3D pre-erosional surface for each mapped feature was interpolated based on the boundary elevations. A surface difference calculation was run using the estimated pre-erosional surfaces and LiDAR surfaces to determine volume of sediment potentially delivered into the stream system. In addition, cross sections of altered channels and streams were taken using stratified random selection based on channel gradient and stream order respectively. The original pre-storm surfaces of channel features were estimated using the cross sections and erosion depth criteria. Open source software Inkscape was used to estimate cross sectional areas for randomly selected channel features and then averaged for each channel gradient and stream order classes. The average areas were then multiplied by the length of each class to estimate total eroded altered channel and stream volume. Finally, reservoir and in-channel depositional volumes were estimated by mapping channel forms and generating specific reservoir elevation zones associated with depositional events. The in-channel areas and zones within the reservoir were multiplied by estimated and field observed sediment thicknesses to attain a best guess sediment volume. In channel estimates included re-occupying stream channel cross sections established before the fire. Once volumes were calculated, other erosion processes of the Bagley

  11. Volumetric LiDAR scanning of a wind turbine wake and comparison with a 3D analytical wake model

    NASA Astrophysics Data System (ADS)

    Carbajo Fuertes, Fernando; Porté-Agel, Fernando

    2016-04-01

    A correct estimation of the future power production is of capital importance whenever the feasibility of a future wind farm is being studied. This power estimation relies mostly on three aspects: (1) a reliable measurement of the wind resource in the area, (2) a well-established power curve of the future wind turbines and, (3) an accurate characterization of the wake effects; the latter being arguably the most challenging one due to the complexity of the phenomenon and the lack of extensive full-scale data sets that could be used to validate analytical or numerical models. The current project addresses the problem of obtaining a volumetric description of a full-scale wake of a 2MW wind turbine in terms of velocity deficit and turbulence intensity using three scanning wind LiDARs and two sonic anemometers. The characterization of the upstream flow conditions is done by one scanning LiDAR and two sonic anemometers, which have been used to calculate incoming vertical profiles of horizontal wind speed, wind direction and an approximation to turbulence intensity, as well as the thermal stability of the atmospheric boundary layer. The characterization of the wake is done by two scanning LiDARs working simultaneously and pointing downstream from the base of the wind turbine. The direct LiDAR measurements in terms of radial wind speed can be corrected using the upstream conditions in order to provide good estimations of the horizontal wind speed at any point downstream of the wind turbine. All this data combined allow for the volumetric reconstruction of the wake in terms of velocity deficit as well as turbulence intensity. Finally, the predictions of a 3D analytical model [1] are compared to the 3D LiDAR measurements of the wind turbine. The model is derived by applying the laws of conservation of mass and momentum and assuming a Gaussian distribution for the velocity deficit in the wake. This model has already been validated using high resolution wind-tunnel measurements

  12. Extracting cross sections and water levels of minor streams and ditches from LiDAR point data

    NASA Astrophysics Data System (ADS)

    Roelens, Jennifer; Dondeyne, Stefaan; Deckers, Jozef; Van Orshoven, Jos; Diels, Jan

    2016-04-01

    Quantitative data on the shape and dimensions of location-specific cross-sections is useful for water and floodplain management. In addition, information about the water level is often needed, for example to be used as a boundary condition in hydrological, hydraulic and groundwater models. To detect a water course, let alone the cross section of small streams, the spatial resolution of DEM's derived from LiDAR or other data sources is insufficient. This is not the case for high resolution LiDAR data clouds. An aerial LiDAR database encompassing on average 16 points per square meter is available for the entire Flanders region. LiDAR elevation point clouds and digital RGB aerial images were collected simultaneously. To extract the right points for determination of the water course's cross-section at a given location, a buffer zone is defined around a predefined cross-section. This is based on the assumption that the cross-section of a channel is invariable over a small distance (0.1-1m). The set of extracted and then projected points was subjected to curve fitting based on shape language modelling (SLM). Based on the modelled cross-sectional profile, characteristics like cross-sectional area, width and water level were extracted. Furthermore, normalized indices combining the RGB and intensity data were used to detect the presence of water and the different characteristics of the points close to the water level and close to the banks. The study area is located in the alluvial valley of the Dijle, 20 km east of Brussels. It is part of the nature reserve 'de Doode Bemde'. The area of the test site is 10.3 ha and contains a ditch network of approximately three km. The field data, collected during August 2015 with a real time kinematic (RTK) GPS, was used for validation. The measurement result contained 153 cross sections with all the bathymetry data under the water level. Validation showed that all of the cross-sections modelled with the LiDAR data had a positive mean

  13. Processing and utilization of LiDAR data as a support for a good management of DDBR

    NASA Astrophysics Data System (ADS)

    Nichersu, I.; Grigoras, I.; Constantinescu, A.; Mierla, M.; Tifanov, C.

    2012-04-01

    Danube Delta Biosphere Reserve (DDBR) has 5,800 km2 as surface and it is situated in the South-East of Europe, in the East of Romania. The paper is taking into account the data related to the elevation surfaces of the DDBR (Digital Terrain Model DTM and Digital Surface Model DSM). To produce such kind of models of elevation for the entire area of DDBR it was used the most modern method that utilizes the Light Detection And Ranging (LiDAR). The raw LiDAR data (x, y, z) for each point were transformed into grid formats for DTM and DSM. Based on these data multiple GIS analyses can be done for management purposes : hydraulic modeling 1D2D scenarios, flooding regime and protection, biomass volume estimation, GIS biodiversity processing. These analyses are very useful in the management planning process. The hydraulic modeling 1D2D scenarios are used by the administrative authority to predict the sense of the fluvial water flow and also to predict the places where the flooding could occur. Also it can be predicted the surface of the terrain that will be occupied by the water from floods. Flooding regime gives information about the frequency of the floods and also the intensity of these. In the same time it could be predicted the time of water remanence period. The protection face of the flooding regime is in direct relation with the socio-cultural communities and all their annexes those that are in risk of being flooded. This raises the problem of building dykes and other flooding protection systems. The biomass volume contains information derived from the LiDAR cloud points that describes only the vegetation. The volume of biomass is an important item in the management of a Biosphere Reserve. Also the LiDAR cloud points that refer to vegetation could help in identifying the groups of vegetal association. All these information corroborated with other information build good premises for a good management. Keywords: Danube Delta Biosphere Reserve, LiDAR data, DTM, DSM

  14. Application of airborne LiDAR to the detailed geological mapping of mineralised terrain: the Troodos ophiolite, Cyprus

    NASA Astrophysics Data System (ADS)

    Grebby, S.; Cunningham, D.; Naden, J.; Tansey, K.

    2009-04-01

    The identification of mineral prospects is highly dependent upon the acquisition and synthesis of a wide variety of geological information, e.g., lithological, structural, geophysical and geochemical data. Conventionally, the majority of this information is acquired through field-based surveys. However, the quality of data collected in this manner is often affected by subjectivity and lack of detail due to coarse sampling over vast areas or inaccessible terrain. Both multi- and hyperspectral satellite remote sensing and the interpretation of aerial photography are typically used to help try and overcome some of the limitations associated with field-based surveys. However, the use of these approaches for the extraction of exploration data can be hindered by spatial and spectral limitations and by dense forest cover. A relatively new active remote sensing technology—known as airborne Light Detection And Ranging (LiDAR)—offers the possibility of acquiring accurate and high-resolution (ca. 1-4 m) topographic data through dense forest cover. The ability of LiDAR systems to detect multiple returns from the emission of a single laser pulse can be utilised to generate a high-resolution digital elevation model (DEM) of the ground beneath the forest canopy. Airborne LiDAR is an important tool for geoscience research, with a wide spectrum of applications including the mapping of landslides and faults to help inform hazard assessment studies. A LiDAR system can also provide an insight into the spectral and textural properties of surface materials using intensity data—a ratio of the reflected laser energy to the emitted laser energy. Where rocks outcrop, these properties are linked to the surface mineralogy and weathering at the LiDAR footprint scale. The ability to acquire two high-resolution datasets simultaneously from a single survey makes airborne LiDAR an attractive tool for the extraction of detailed geological information in terrain with either sparse or dense

  15. Efficient, Off-Grid LiDAR Scanning of Remote Field Sites

    NASA Astrophysics Data System (ADS)

    Gold, P.; Gold, R.; Cowgill, E.; Kreylos, O.; Hamann, B.

    2007-12-01

    As terrestrial LiDAR scanning systems become increasingly available, strategies for executing efficient field surveys in settings without access to the power grid are increasingly needed. To evaluate scan methods and develop an off-grid power system, we used a tripod-mounted laser scanner to create high resolution (≤40 mm point spacing) topographic maps for use in neotectonic studies of active faulting in arid, high elevation settings. We required 1-2 cm internal precision within point clouds spanning field sites that were ~300 x 300 m. Main components of our survey system included a Trimble GX DR200+ terrestrial laser scanner, a Leica TCR407power total station, a ruggedized laptop (2 GB RAM, 2.33 GHz dual-processor, and an Intel GMA 950 graphics card), batteries, and a portable photovoltaic array. Our first goal was to develop an efficient field-survey workflow. We started each survey project by using the total station for 1-2 days to locate an average of 8 ground control locations per site and to measure key geomorphic features within the project area. We then used the laser scanner to capture overlapping scans of the site, which required an average of six, 5-hour scanning sessions and an average of ten station setups. At each station, the scanner located itself on a particular point by measuring the relative positions of an average of four backsights, each of which is a ~17 x 17cm reflective target mounted on a tripod over the ground control point. To locate the scanner at a particular station prior to scanning, we experimented with both setting up over known points as measured using the total station, and resectioning, by positioning the scanner over an unmeasured location and backsighting on previously scanned points. We found that resectioning provided the smallest errors in scan registration. We then framed and queued a series of scans from each station that optimized point density and minimized data repetition. We also increased the accuracy of the

  16. LiDAR DTMs and anthropogenic feature extraction: testing the feasibility of geomorphometric parameters in floodplains

    NASA Astrophysics Data System (ADS)

    Sofia, G.; Tarolli, P.; Dalla Fontana, G.

    2012-04-01

    In floodplains, massive investments in land reclamation have always played an important role in the past for flood protection. In these contexts, human alteration is reflected by artificial features ('Anthropogenic features'), such as banks, levees or road scarps, that constantly increase and change, in response to the rapid growth of human populations. For these areas, various existing and emerging applications require up-to-date, accurate and sufficiently attributed digital data, but such information is usually lacking, especially when dealing with large-scale applications. More recently, National or Local Mapping Agencies, in Europe, are moving towards the generation of digital topographic information that conforms to reality and are highly reliable and up to date. LiDAR Digital Terrain Models (DTMs) covering large areas are readily available for public authorities, and there is a greater and more widespread interest in the application of such information by agencies responsible for land management for the development of automated methods aimed at solving geomorphological and hydrological problems. Automatic feature recognition based upon DTMs can offer, for large-scale applications, a quick and accurate method that can help in improving topographic databases, and that can overcome some of the problems associated with traditional, field-based, geomorphological mapping, such as restrictions on access, and constraints of time or costs. Although anthropogenic features as levees and road scarps are artificial structures that actually do not belong to what is usually defined as the bare ground surface, they are implicitly embedded in digital terrain models (DTMs). Automatic feature recognition based upon DTMs, therefore, can offer a quick and accurate method that does not require additional data, and that can help in improving flood defense asset information, flood modeling or other applications. In natural contexts, morphological indicators derived from high

  17. Surface expression of intraplate postglacial faults in Sweden: from LiDAR data

    NASA Astrophysics Data System (ADS)

    Abduljabbar, Mawaheb; Ask, Maria; Bauer, Tobias; Lund, Björn; Smith, Colby; Mikko, Henrik; Munier, Raymond

    2016-04-01

    Large intraplate earthquakes, up to magnitude 8.0±0.3 (Lindblom et al. 2015) are inferred to have occurred in northern Fennoscandia at the end of, or just after the Weichselian deglaciation. More than a dozen large so-called postglacial faults (PGF) have been found in the region. The present-day microseismic activity is rather high in north Sweden, and there is a correlation between microseismicity and mapped PGF scarps: 71% of the observed earthquakes north of 66°N locate within 30 km to the southeast and 10 km to the northwest of PGFs (Lindblom et al., 2015). Surface expressions of PGFs in Sweden have mainly been mapped using aerial photogrammetry and trenching (e.g. Lagerbäck & Sundh 2008). Their detailed surface geometry may be investigated using the new high-resolution elevation model of Sweden (NNH) that has a vertical- and lateral resolution of 2 m and 0.25 m, respectively. With NNH data, known PGFs have been modified, and a number of new potential PGFs have been identified (Smith et al. 2014; Mikko et al. 2015). However, the detailed variation of their surface expression remains to be determined. Our main objective is to constrain the strike and surface offset (i.e., apparent vertical throw because of soil cover overlays the bedrock) across the PGF scarps. We anticipate using the results to constrain direction of fault motion and paleomagnitudes of PGFs, and in numerical analyzes to investigate the nature of PGFs. We have developed a methodology for analyzing PGF-geomorphology from LiDAR data using two main software platforms (Ask et al. 2015): (1) Move2015 by Midland Valley has been used for constructing 3D models of the surface traces of the PGFs to determine apparent vertical throw. The apparent hanging- and footwall cut off lines are digitized, and subsequent computation of coordinates is rather time efficient and provide continuous data of fault and soil geomorphology that can be statistically analyzed; and (2) ArcGIS 10.3 by Esri has mostly been

  18. A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery

    PubMed Central

    Siddiqui, Fasahat Ullah; Teng, Shyh Wei; Awrangjeb, Mohammad; Lu, Guojun

    2016-01-01

    Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE) method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR) height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality). Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state-of-the-art building

  19. Prevalence and antimicrobial resistance of Campylobacter isolates from humans and chickens in Bahir Dar, Ethiopia.

    PubMed

    Ewnetu, Desalegne; Mihret, Adane

    2010-06-01

    In this study, the isolation and antimicrobial resistance of Campylobacter jejuni and Campylobacter coli strains from chickens and humans in Bahir Dar, Ethiopia, were analyzed. Two hundred and ten human and 220 chicken samples were analyzed between October 2007 and April 2008. Seventeen human and 160 chicken Campylobacter species were isolated. The overall prevalence of thermophilic campylobacters was 8% and 72.7% in humans and chickens, respectively. In humans, 94.1% of the isolates were C. jejuni and 5.9% were C. coli. C. jejuni was a predominant species of thermophilic campylobacters in all categories of patients. In chicken, 92.5% of thermophilic campylobacters isolated were C. jejuni and 7.5% were C. coli. Among the 16 isolates of C. jejuni in humans, 18.8%, 12.5%, 12.5%, 18.8%, 25%, and 22.2% were resistant to ampicillin, ciprofloxacin, erythromycin, nalidixic acid, streptomycin, and tetracycline, respectively, whereas among the 148 C. jejuni isolates from chicken, 17.5%, 14.9%, 12.2%, and 13.5% were resistant to ampicillin, erythromycin, streptomycin, and tetracycline, respectively. Among the 12 isolates of C. coli in chicken, 16.6%, 8.3%, and 16.6% were resistant to ampicillin, streptomycin, and tetracycline, respectively. The overall level of resistance was not significantly different in C. jejuni and C. coli isolates of both humans and poultry. The detection of resistant isolates for commonly used antimicrobials may cause a threat to humans and chickens by limiting therapeutic options.

  20. Evaluation of an experimental LiDAR for surveying a shallow, braided, sand-bedded river

    USGS Publications Warehouse

    Kinzel, P.J.; Wright, C.W.; Nelson, J.M.; Burman, A.R.

    2007-01-01

    Reaches of a shallow (<1.0m), braided, sand-bedded river were surveyed in 2002 and 2005 with the National Aeronautics and Space Administration's Experimental Advanced Airborne Research LiDAR (EAARL) and concurrently with conventional survey-grade, real-time kinematic, global positioning system technology. The laser pulses transmitted by the EAARL instrument and the return backscatter waveforms from exposed sand and submerged sand targets in the river were completely digitized and stored for postflight processing. The vertical mapping accuracy of the EAARL was evaluated by comparing the ellipsoidal heights computed from ranging measurements made using an EAARL terrestrial algorithm to nearby (<0.5m apart) ground-truth ellipsoidal heights. After correcting for apparent systematic bias in the surveys, the root mean square error of these heights with the terrestrial algorithm in the 2002 survey was 0.11m for the 26 measurements taken on exposed sand and 0.18m for the 59 measurements taken on submerged sand. In the 2005 survey, the root mean square error was 0.18m for 92 measurements taken on exposed sand and 0.24m for 434 measurements on submerged sand. In submerged areas the waveforms were complicated by reflections from the surface, water column entrained turbidity, and potentially the riverbed. When applied to these waveforms, especially in depths greater than 0.4m, the terrestrial algorithm calculated the range above the riverbed. A bathymetric algorithm has been developed to approximate the position of the riverbed in these convolved waveforms and preliminary results are encouraging. ?? 2007 ASCE.

  1. Modelling prehistoric terrain Models using LiDAR-data: a geomorphological approach

    NASA Astrophysics Data System (ADS)

    Höfler, Veit; Wessollek, Christine; Karrasch, Pierre

    2015-10-01

    Terrain surfaces conserve human activities in terms of textures and structures. With reference to archaeological questions, the geological archive is investigated by means of models regarding anthropogenic traces. In doing so, the high-resolution digital terrain model is of inestimable value for the decoding of the archive. The evaluation of these terrain models and the reconstruction of historical surfaces is still a challenging issue. Due to the data collection by means of LiDAR systems (light detection and ranging) and despite their subsequent pre-processing and filtering, recently anthropogenic artefacts are still present in the digital terrain model. Analysis have shown that elements, such as contour lines and channels, can well be extracted from a high-resolution digital terrain model. This way, channels in settlement areas show a clear anthropogenic character. This fact can also be observed for contour lines. Some contour lines representing a possibly natural ground surface and avoid anthropogenic artefacts. Comparable to channels, noticeable patterns of contour lines become visible in areas with anthropogenic artefacts. The presented workflow uses functionalities of ArcGIS and the programming language R.1 The method starts with the extraction of contour lines from the digital terrain model. Through macroscopic analyses based on geomorphological expert knowledge, contour lines are selected representing the natural geomorphological character of the surface. In a first step, points are determined along each contour line in regular intervals. This points and the corresponding height information which is taken from an original digital terrain model is saved as a point cloud. Using the programme library gstat, a variographic analysis and the use of a Kriging-procedure based on this follow.2-4 The result is a digital terrain model filtered considering geomorphological expert knowledge showing no human degradation in terms of artefacts, preserving the landscape

  2. Ground-based LiDAR to investigate landscape engineering by woody riparian trees

    NASA Astrophysics Data System (ADS)

    Bywater-Reyes, S.; Wilcox, A. C.; Manners, R.; Lightbody, A.

    2013-12-01

    Plant-scale disruption to flow can result in upstream scour and downstream deposition, creating 'tail bars'. Tail bars have been postulated to exhibit airfoil geometries that reduce drag, causing a positive feedback whereby additional deposition of sediment results in growth of pioneer islands. We quantify the relative influence of vegetation morphology and grain size on morphodynamics by using ground-based LiDAR to scan trees and associated scour and tail bar features. We scanned trees of various growth stages and morphologies (Populus and Tamarix) in both sand- and gravel-bed settings. We post-process vegetation scans for hydrodynamic vegetation density, a proxy for leaf area index that we use in stress partitioning calculations to compare the magnitude of grain versus vegetation roughness. We also quantify the dimensions of upstream scour (maximum depth and volume) and downstream tail bar deposits (maximum height, width, length, volume). The vegetation and ground scans will be used to evaluate whether scour and tail bar geometries can be predicted from hydrodynamic vegetation density, and whether tail bars exhibit airfoil geometries in a manner that reduces drag. Field observations indicate single-stem trees (e.g. Populus) produce greater upstream scour but more subdued tail bar deposits, whereas multi-stem trees (e.g. Tamarix) produce less upstream scour but more tail bar deposition. Scour and tail bar features are more dramatic in the sand-bed setting compared to the gravel-bed, where grain roughness may play a larger role. Our research quantifies the magnitude of vegetation-morphodynamic feedbacks, with implications for plant community and landscape evolution in a multitude of riverine settings.

  3. Petrography and mineralogy of the ungrouped type 3 carbonaceous chondrite Dar al Gani 978

    NASA Astrophysics Data System (ADS)

    Zhang, Ai-Cheng; Yurimoto, Hisayoshi

    2013-09-01

    Dar al Gani (DaG) 978 is an ungrouped type 3 carbonaceous chondrite. In this study, we report the petrography and mineralogy of Ca,Al-rich inclusions (CAI), amoeboid olivine aggregates (AOAs), chondrules, mineral fragments, and the matrix in DaG 978. Twenty-seven CAIs were found: 13 spinel-diopside-rich inclusions, 2 anorthite-rich inclusions, 11 spinel-troilite-rich inclusions, and 1 spinel-melilite-rich inclusion. Most CAIs have a layered texture that indicates a condensation origin and are most similar to those in R chondrites. Compound chondrules represent a high proportion (approximately 8%) of chondrules in DaG 978, which indicates a local dusty chondrule-forming region and multiple heating events. Most spinel and olivine in DaG 978 are highly Fe-rich, which corresponds to a petrologic type of >3.5 and a maximum metamorphic temperature of approximately 850-950 K. This conclusion is also supported by other observations in DaG 978: the presence of coarse inclusions of silicate and phosphate in Fe-Ni metal, restricted Ni-Co distributions in kamacite and taenite, and low S concentrations in the matrix. Mineralogic records of iron-alkali-halogen metasomatism, such as platy and porous olivine, magnetite, hedenbergite, nepheline, Na-rich in CAIs, and chlorapatite, are present, but relatively limited, in DaG 978. The fine-grained, intergrowth texture of spinel-troilite-rich inclusions was probably formed by reaction between pre-existing Al-rich silicates and shock-induced, high-temperature S-rich gas on the surface of the parent body of DaG 978. A shock-induced vein is present in the matrix of DaG 978, which indicates that the parent body of DaG 978 at least experienced a shock event with a shock stage up to S3.

  4. Microbial Efficacy of Waterless Hand Hygiene in Dar es Salaam, Tanzania

    NASA Astrophysics Data System (ADS)

    Pickering, A.; Boehm, A.; Davis, J.

    2008-12-01

    Millions of people die from diarrheal and respiratory diseases every year due to lack of proper sanitation, hygiene, and access to clean water. The act of handwashing with soap has been found to effectively reduce both diarrheal and respiratory illness, however, handwashing at critical times (i.e. after using the toilet, before preparing food) remains infrequent around the world. This research investigates the potential for alcohol- based hand sanitizer (ABHS) to be an effective and appropriate hand hygiene option in developing countries. A study was conducted to assess the microbiological effectiveness of ABHS, as compared to handwashing with soap and water, in field conditions in Dar es Salaam, Tanzania. A total of 205 participants, including mothers, nurses, students, and teachers, were introduced to ABHS, given a standardized amount (2ml) of product, and instructed on how to use the product correctly. Hand samples were obtained using the hand rinse method before and after the use of ABHS from 152 participants. The other 53 participants were hand sampled before and after handwashing with a non-antimicrobial liquid soap and clean water (prior to using ABHS). Visual inspections of the hands were performed before hand sampling to record the level of dirt on the hands. All hand samples were processed and analyzed by membrane filtration for concentrations of two microbial indicators, enterococci and E. coli. User perceptions of the product and willingness to pay are also documented. The results of this study provide valuable insight on the prospective of promoting ABHS in developing countries and water scarce areas.

  5. A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery.

    PubMed

    Siddiqui, Fasahat Ullah; Teng, Shyh Wei; Awrangjeb, Mohammad; Lu, Guojun

    2016-07-19

    Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE) method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR) height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality). Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state-of-the-art building

  6. Evaluation Of Airborne LiDAR Data To Predict Presence / Absence

    NASA Astrophysics Data System (ADS)

    Palaseanu, M.; Nayegandhi, A.; Brock, J.; Woodman, R.; Wright, W. C.

    2008-12-01

    %. Different vegetation categories may be defined by the same structural characteristics, since LiDAR metrics are more closely related to vegetation structure rather than to species alone.

  7. Skinning the goat and pulling the load: transactional sex among youth in Dar es Salaam, Tanzania.

    PubMed

    Maganja, R K; Maman, S; Groves, A; Mbwambo, J K

    2007-09-01

    Transactional sex has been associated with risk of HIV infection in a number of studies throughout sub-Saharan Africa. Urban young women are economically vulnerable and at heightened risk of HIV infection in Tanzania; yet there are few studies that have explored relationship dynamics, including transactional sex, in this setting. This paper sheds light on the broader context of sexual relationships among youth at risk for HIV, how transactional sex plays out in these relationships, and how the transactional nature of relationships affects women's risk for HIV. We conducted 60 in depth interviews and 14 focus group discussions with young men and women, 16-24 years old, in Dar es Salaam, Tanzania. These data guided the development of a community based HIV and violence prevention intervention for young men. Youth described the exchange of sex for money or other material goods in all types of sexual relationships. While the exchange was explicit in casual relationships, young women voiced material and monetary expectations from their committed partners as well. Young men described their pursuit of multiple partners as sexually motivated, while women sought multiple partners for economic reasons. Young men were aware of the expectations of material support from partners, and acknowledged that their ability to provide for a partner affected both the longevity and exclusivity of their relationships. Youth described a deep mistrust of the motivations and commitment of their sexual partners. Furthermore, young women's financial dependence on men impacted their ability to negotiate safe sexual behaviors in both casual and committed relationships. Programs designed to reduce HIV risk among Tanzanian youth need to take into account the transactional component of sexual relationships and how such exchanges differ according to partner type.

  8. [Retrieval of forest topsoil organic matter's spatial pattern based on LiDAR data].

    PubMed

    Li, Chao; Liu, Zhao-Gang; Yue, Shu-Feng; Li, Feng-Ri; Dong, Ling-Bo; Bi, Meng

    2012-09-01

    Forest soil is one of the main carbon pools in terrestrial ecosystem. Its organic matter content can provide basic information for estimating soil carbon storage, and also, is an important index for evaluating the function of soil carbon sink. Based on the LiDAR data and the topsoil organic matter contents in 55 permanent plots at Liangshui National Nature Reserve, Heilongjiang Province of Northeast China in August 2009, and by using partial least squares (PLS) method, this paper retrieved the forest topsoil organic matter's spatial pattern in the Reserve, extracted and screened the variables related to the distribution of the topsoil organic matter (e. g. , intensity, counts, elevation, slope, and aspect), and analyzed and defined the correlations between the screened variables and topsoil organic matter content, with the prediction model of forest soil organic matter content established and validated. In the Reserve, the forest topsoil organic matter content was significantly and positively correlated with three variables (intensity, r = 0.765; counts, r = 0.423; and elevation r = 0.475; all P<0.001). The model prediction on the topsoil organic matter content was reliable (precision = 83.3%, R2 = 0.725, RMSE = 1.955 ). In the areas of forest edge and of low canopy stands, the topsoil organic matter content was less than 100 g x kg(-1). The majority of the study area had a topsoil organic matter content of 100-150 g x kg(-1), while a few areas had the topsoil organic matter content as high as 150-318.4 g x kg(-1).

  9. Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

    NASA Technical Reports Server (NTRS)

    Naesset, Erik; Gobakken, Terje; Bollandsas, Ole Martin; Gregoire, Timothy G.; Nelson, Ross; Stahl, Goeran

    2013-01-01

    Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI

  10. Using LiDAR datasets to improve HSPF water quality modeling in the Red River of the North Basin

    NASA Astrophysics Data System (ADS)

    Burke, M. P.; Foreman, C. S.

    2013-12-01

    The Red River of the North Basin (RRB), located in the lakebed of ancient glacial Lake Agassiz, comprises one of the flattest landscapes in North America. The topography of the basin, coupled with the Red River's direction of flow from south to north results in a system that is highly susceptible to flooding. The magnitude and frequency of flood events in the RRB has prompted several multijurisdictional projects and mitigation efforts. In response to the devastating 1997 flood, an International Joint Commission sponsored task force established the need for accurate elevation data to help improve flood forecasting and better understand risks. This led to the International Water Institute's Red River Basin Mapping Initiative, and the acquisition LiDAR Data for the entire US portion of the RRB. The resulting 1 meter bare earth digital elevation models have been used to improve hydraulic and hydrologic modeling within the RRB, with focus on flood prediction and mitigation. More recently, these LiDAR datasets have been incorporated into Hydrological Simulation Program-FORTRAN (HSPF) model applications to improve water quality predictions in the MN portion of the RRB. RESPEC is currently building HSPF model applications for five of MN's 8-digit HUC watersheds draining to the Red River, including: the Red Lake River, Clearwater River, Sandhill River, Two Rivers, and Tamarac River watersheds. This work is being conducted for the Minnesota Pollution Control Agency (MPCA) as part of MN's statewide watershed approach to restoring and protecting water. The HSPF model applications simulate hydrology (discharge, stage), as well as a number of water quality constituents (sediment, temperature, organic and inorganic nitrogen, total ammonia, organic and inorganic phosphorus, dissolved oxygen and biochemical oxygen demand, and algae) continuously for the period 1995-2009 and are formulated to provide predictions at points of interest within the watersheds, such as observation gages

  11. Identification of Bedrock Lithology using Fractal Dimensions of Drainage Networks extracted from Medium Resolution LiDAR Digital Terrain Models

    NASA Astrophysics Data System (ADS)

    Cámara, Joaquín; Gómez-Miguel, Vicente; Martín, Miguel Ángel

    2016-03-01

    Geologists know that drainage networks can exhibit different drainage patterns depending on the hydrogeological properties of the underlying materials. Geographic Information System (GIS) technologies and the increasing availability and resolution of digital elevation data have greatly facilitated the delineation, quantification, and study of drainage networks. This study investigates the possibility of inferring geological information of the underlying material from fractal and linear parameters describing drainage networks automatically extracted from 5-m-resolution LiDAR digital terrain model (DTM) data. According to the lithological information (scale 1:25,000), the study area is comprised of 30 homogeneous bedrock lithologies, the lithological map units (LMUs). These are mostly igneous and metamorphic rocks, but also include some sedimentary rocks. A statistical classification model of the LMUs by rock type has been proposed based on both the fractal dimension and drainage density of the overlying drainage networks. The classification model has been built using 16 LMUs, and it has correctly classified 13 of the 14 LMUs used for its validation. Results for the study area show that LMUs, with areas ranging from 177.83 ± 0.01 to 3.16 ± 0.01 km2, can be successfully classified by rock type using the fractal dimension and the drainage density of the drainage networks derived from medium resolution LiDAR DTM data with different flow support areas. These results imply that the information included in a 5-m-resolution LiDAR DTM and the appropriate techniques employed to manage it are the only inputs required to identify the underlying geological materials.

  12. Window screening, ceilings and closed eaves as sustainable ways to control malaria in Dar es Salaam, Tanzania

    PubMed Central

    Ogoma, Sheila B; Kannady, Khadija; Sikulu, Maggy; Chaki, Prosper P; Govella, Nicodem J; Mukabana, Wolfgang R; Killeen, Gerry F

    2009-01-01

    Background Malaria transmission in Africa occurs predominantly inside houses where the primary vectors prefer to feed. Human preference and investment in blocking of specific entry points for mosquitoes into houses was evaluated and compared with known entry point preferences of the mosquitoes themselves. Methods Cross-sectional household surveys were conducted in urban Dar es Salaam, Tanzania to estimate usage levels of available options for house proofing against mosquito entry, namely window screens, ceilings and blocking of eaves. These surveys also enabled evaluation of household expenditure on screens and ceilings and the motivation behind their installation. Results Over three quarters (82.8%) of the 579 houses surveyed in Dar es Salaam had window screens, while almost half (48.9%) had ceilings. Prevention of mosquito entry was cited as a reason for installation of window screens and ceilings by 91.4% (394/431) and 55.7% (127/228) of respondents, respectively, but prevention of malaria was rarely cited (4.3%, 22/508). The median cost of window screens was between US $ 21-30 while that of ceilings was between US $301-400. The market value of insecticide-treated nets, window screening and ceilings currently in use in the city was estimated as 2, 5 and 42 million US$. More than three quarters of the respondents that lacked them said it was too expensive to install ceilings (82.2%) or window screens (75.5%). Conclusion High coverage and spending on screens and ceilings implies that these techniques are highly acceptable and excellent uptake can be achieved in urban settings like Dar es Salaam. Effective models for promotion and subsidization should be developed and evaluated, particularly for installation of ceilings that prevent entry via the eaves, which are the most important entry point for mosquitoes that cause malaria, a variety of neglected tropical diseases and the nuisance which motivates uptake. PMID:19785779

  13. The potential for LiDAR technology to map fire fuel hazard over large areas of Australian forest.

    PubMed

    Price, Owen F; Gordon, Christopher E

    2016-10-01

    Fuel load is a primary determinant of fire spread in Australian forests. In east Australian forests, litter and canopy fuel loads and hence fire hazard are thought to be highest at and beyond steady-state fuel loads 15-20 years post-fire. Current methods used to predict fuel loads often rely on course-scale vegetation maps and simple time-since-fire relationships which mask fine-scale processes influencing fuel loads. Here we use Light Detecting and Remote Sensing technology (LiDAR) and field surveys to quantify post-fire mid-story and crown canopy fuel accumulation and fire hazard in Dry Sclerophyll Forests of the Sydney Basin (Australia) at fine spatial-scales (20 × 20 m cell resolution). Fuel cover was quantified in three strata important for crown fire propagation (0.5-4 m, 4-15 m, >15 m) over a 144 km(2) area subject to varying fire fuel ages. Our results show that 1) LiDAR provided a precise measurement of fuel cover in each strata and a less precise but still useful predictor of surface fuels, 2) cover varied greatly within a mapped vegetation class of the same fuel age, particularly for elevated fuel, 3) time-since-fire was a poor predictor of fuel cover and crown fire hazard because fuel loads important for crown fire propagation were variable over a range of fire fuel ages between 2 and 38 years post-fire, and 4) fuel loads and fire hazard can be high in the years immediately following fire. Our results show the benefits of spatially and temporally specific in situ fuel sampling methods such as LiDAR, and are widely applicable for fire management actions which aim to decrease human and environmental losses due to wildfire.

  14. Synergistic Use of WorldView-2 Imagery and Airborne LiDAR Data for Urban Land Cover Classification

    NASA Astrophysics Data System (ADS)

    Wu, M. F.; Sun, Z. C.; Yang, B.; Yu, S. S.

    2017-02-01

    There are lots of challenges for deriving urban land cover types for high resolution optical imagery because of spectral similarity of different objects, mixed pixels, shadows of buildings and large tree crowns. In order to reduce these uncertainties, recently, it’s a trend of the classification of urban land cover from multi-source sensors in the field of urban remote sensing. In this study, a hierarchical support vector machine (SVM) classification method was applied to the urban land cover mapping, using the WorldView-2 imagery and airborne Light Detection and Ranging (LiDAR) data. The results showed that: (1) The overall accuracy (OA) and overall kappa (OK) were 72.92% and 0.66 for WorldView-2 imagery alone; while the OA and OK were improved up to 89.44% and 0.87 for the synergistic use of the two types of data source. (2) Buildings and road/parking lots extracted from fused data were more precision and well-shaped. The two classes from fused data were optimally classified with higher producer’s accuracy and user’s accuracy than WorldView-2 imagery alone. The trees were also easily separated from the grasslands when the airborne LiDAR data was added. (3) The fused data could reduce the phenomenon of different spectral character of the complex and detailed objects. It was also helpful to address the problem of shadows from the high-rise buildings. The results from this study indicate that the synergistic use of high resolution optical imagery and airborne LiDAR data can be an efficient approach to improving the classification of urban land cover.

  15. Landslide Investigation by Repeat Airborne LiDAR and Ground Monitoring in the Western Suburb of Sapporo, Japan

    NASA Astrophysics Data System (ADS)

    Kasai, M.; Marutani, T.; Yoshida, H.

    2014-12-01

    This study presents landslide investigation using the combination of airborne LiDAR and ground monitoring data. The study site is located on the Teine Landslide (width: 2 km, Length: 6.5 km) in the western suburb of Sapporo city in Hokkaido Island, Japan, which collapsed more than 50,000 years ago. Since then streams have been developing and incising the landslide mass consisted of rock debris and volcanic deposits, presently causing a series of small deep-seated landslides along the banks. Because Sapporo is the economic center of Hokkaido and the suburb is expanding at the toe of the Teine slide, it is important to understand the behaviors of these active slopes to protect residents and infrastructures from unexpected disasters possibly triggered by an intense storm or earthquake. The LiDAR data for the area was first obtained by a manned helicopter in August 2010, and another survey by an unmanned helicopter is planned in autumn 2014 to estimate their activities from changes in the ground surfaces during the period from 2010 to 2014. Ground water level and landslide mass movements have also been monitored on site by using the coring holes for sampling since 2013. The combination of the data sets can make up the deficits of these methods, e.g., errors created through data processing for LiDAR survey and spatially limited information for ground monitoring, enabling to provide a solid three dimensional view of the slope movements. The notion obtained can be utilized to predict their future behaviors as well as to discover active but hiding landslides nearby. This study also showed that repeat monitoring of sites is a way of utilizing UAVs, particularly in terms of cost and convenience.

  16. [Characterization of mid-subtropical evergreen broad-leaved forest gap based on light detection and ranging (LiDAR)].

    PubMed

    Liu, Feng; Tan, Chang; Wang, Hong; Zhang, Jiang; Wan, Ying; Long, Jiang-ping; Liu, Rui-xi

    2015-12-01

    Light Detection and Ranging (LiDAR) is an active remote sensing technology for acqui- ring three-dimensional structure parameters of vegetation canopy with high accuracy over multiple spatial scales, which is greatly important to the promotion of forest disturbance ecology and the ap- plication on gaps. This paper focused on mid-subtropical evergreen broadleaved forest in Hunan Province, and small footprint LiDAR point data were adopted to identify canopy gaps. and measure geomagnetic characteristics of gaps. The optimal grid model resolution and interpolation methods were chosen to generate canopy height model, and the computer graphics processing was adopted to estimate characteristics of gaps which involved gap size, canopy height and gap shape index, then field investigation was utilized to validate the estimation results. The results showed that the gap rec- ognition rate was 94.8%, and the major influencing factors were gap size and gap maker type. Line- ar correlation was observed between LiDAR estimation and field investigation, and the R² values of gap size and canopy height case were 0.962 and 0.878, respectively. Compared with field investiga- tion, the size of mean estimated gap was 19.9% larger and the mean estimated canopy height was 9.9% less. Gap density was 12.8 gaps · hm⁻² and the area of gaps occupied 13.3% of the forest area. The average gap size, canopy height and gap shape index were 85.06 m², 15.33 m and 1.71, respectively. The study site usually contained small gaps in which the edge effect was not obvious.

  17. Urban vegetation detection using radiometrically calibrated small-footprint full-waveform airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Höfle, Bernhard; Hollaus, Markus; Hagenauer, Julian

    2012-01-01

    This paper introduces a new GIS workflow for urban vegetation mapping from high-density (50 pts./m 2) full-waveform airborne LiDAR data, combining the advantages of both raster and point cloud based analysis. Polygon segments derived by edge-based segmentation of the normalized digital surface model are used for classification. A rich set of segment features based on the point cloud and derived from full-waveform attributes is built, serving as input for a decision tree and artificial neural network (ANN) classifier. Exploratory data analysis and detailed investigation of the discriminative power of selected point cloud and full-waveform LiDAR observables indicate a high value of the occurrence of multiple distinct targets in a laser beam (i.e. 'echo ratio') for vegetation classification (98% correctness). The radiometric full-waveform observables (e.g. backscattering coefficient) do not suffice as single discriminators with low correctness values using a decision tree classifier (⩽72% correctness) but higher values with ANN (⩽95% correctness). Tests using reduced point densities indicate that the derived segment features and classification accuracies remain relatively stable even up to a reduction factor of 10 (5 pts./m 2). In a representative study area in the City of Vienna/Austria the applicability of the developed object-based GIS workflow is demonstrated. The unique high density full-waveform LiDAR data open a new scale in 3D object characterization but demands for novel joint strategies in object-based raster and 3D point cloud analysis.

  18. Individual tree crown delineation using localized contour tree method and airborne LiDAR data in coniferous forests

    NASA Astrophysics Data System (ADS)

    Wu, Bin; Yu, Bailang; Wu, Qiusheng; Huang, Yan; Chen, Zuoqi; Wu, Jianping

    2016-10-01

    Individual tree crown delineation is of great importance for forest inventory and management. The increasing availability of high-resolution airborne light detection and ranging (LiDAR) data makes it possible to delineate the crown structure of individual trees and deduce their geometric properties with high accuracy. In this study, we developed an automated segmentation method that is able to fully utilize high-resolution LiDAR data for detecting, extracting, and characterizing individual tree crowns with a multitude of geometric and topological properties. The proposed approach captures topological structure of forest and quantifies topological relationships of tree crowns by using a graph theory-based localized contour tree method, and finally segments individual tree crowns by analogy of recognizing hills from a topographic map. This approach consists of five key technical components: (1) derivation of canopy height model from airborne LiDAR data; (2) generation of contours based on the canopy height model; (3) extraction of hierarchical structures of tree crowns using the localized contour tree method; (4) delineation of individual tree crowns by segmenting hierarchical crown structure; and (5) calculation of geometric and topological properties of individual trees. We applied our new method to the Medicine Bow National Forest in the southwest of Laramie, Wyoming and the HJ Andrews Experimental Forest in the central portion of the Cascade Range of Oregon, U.S. The results reveal that the overall accuracy of individual tree crown delineation for the two study areas achieved 94.21% and 75.07%, respectively. Our method holds great potential for segmenting individual tree crowns under various forest conditions. Furthermore, the geometric and topological attributes derived from our method provide comprehensive and essential information for forest management.

  19. Impact of Community-Based Larviciding on the Prevalence of Malaria Infection in Dar es Salaam, Tanzania

    PubMed Central

    Maheu-Giroux, Mathieu; Castro, Marcia C.

    2013-01-01

    Background The use of larval source management is not prioritized by contemporary malaria control programs in sub-Saharan Africa despite historical success. Larviciding, in particular, could be effective in urban areas where transmission is focal and accessibility to Anopheles breeding habitats is generally easier than in rural settings. The objective of this study is to assess the effectiveness of a community-based microbial larviciding intervention to reduce the prevalence of malaria infection in Dar es Salaam, United Republic of Tanzania. Methods and Findings Larviciding was implemented in 3 out of 15 targeted wards of Dar es Salaam in 2006 after two years of baseline data collection. This intervention was subsequently scaled up to 9 wards a year later, and to all 15 targeted wards in 2008. Continuous randomized cluster sampling of malaria prevalence and socio-demographic characteristics was carried out during 6 survey rounds (2004–2008), which included both cross-sectional and longitudinal data (N = 64,537). Bayesian random effects logistic regression models were used to quantify the effect of the intervention on malaria prevalence at the individual level. Effect size estimates suggest a significant protective effect of the larviciding intervention. After adjustment for confounders, the odds of individuals living in areas treated with larviciding being infected with malaria were 21% lower (Odds Ratio = 0.79; 95% Credible Intervals: 0.66–0.93) than those who lived in areas not treated. The larviciding intervention was most effective during dry seasons and had synergistic effects with other protective measures such as use of insecticide-treated bed nets and house proofing (i.e., complete ceiling or window screens). Conclusion A large-scale community-based larviciding intervention significantly reduced the prevalence of malaria infection in urban Dar es Salaam. PMID:23977099

  20. Comparison of Terrestrial LiDAR and Erosion Pin Networks for Bank Geometry Monitoring

    NASA Astrophysics Data System (ADS)

    Frechette, J. D.; Wawrzyniec, T. F.; Stormont, J.; Coonrod, J.

    2007-12-01

    Erosion pins and repeat surveys are valuable tools for measuring geomorphic change where airborne remote sensing platforms do not provide the required accuracy or are impractical. Recent advances in automated systems, e.g. the Photo-Electronic Erosion Pin system, permit the collection of high temporal resolution data, however, these systems do not address the inherently low spatial resolution of erosion pin networks and high spatial resolution digital terrain models (DTM) are time consuming to produce with standard surveying equipment. In contrast, Terrestrial LiDAR systems (TLS) enable the rapid generation of DTMs that routinely contain several thousand data points per m2 without disturbing the target area. We describe the use of TLS to monitor changes in bank geometry along an 800 m reach of the Rio Grande in Albuquerque, NM with comparison to data from an erosion pin network along the same reach. On 31 July 2006, shortly after the inception of our monitoring campaign, a thunderstorm produced flows out of the Calabacillas Arroyo that deposited over 10,000 m3 of sediment into the main stem of the Rio Grande within the study area. These deposits reduced the width of the Rio Grande by half and buried nearly all of the erosion pins downstream of the arroyo. Rio Grande and Calabacillas flows continued to rework these deposits since that time. This sediment pulse exceeded the measurement capacity of the erosion pin network and it only registered a large event, followed along part of the reach by a return to near pre-event conditions months latter. In contrast, the cm scale pre- and post-event DTMs produced by TLS document local changes in geometry and enable volumetric estimates of sediment gain and loss. These are minimum estimates, however, as the DTMs only include sediments exposed by low flows at the time of the scans. Furthermore, as with all resurvey techniques, the temporal resolution of the TLS time series is limited by the frequency with which the site could

  1. LiDAR and Field Observations of Earthquake Slip Distribution for the central San Jacinto fault

    NASA Astrophysics Data System (ADS)

    Salisbury, J. B.; Rockwell, T. K.; Middleton, T.; Hudnut, K. W.

    2010-12-01

    We mapped the tectonic geomorphology of 80 km of the Clark strand of the San Jacinto fault to determine slip per event for the past several surface ruptures. From the southeastern end of Clark Valley (east of Borrego Springs) northwest to the mouth of Blackburn Canyon (near Hemet), we identify 203 offset geomorphic features from which we make over 560 measurements on channel margins, channel thalwegs, ridge noses, and bar crests using filtered B4 LiDAR imagery, aerial photography, and field observations. Displacement estimates show that the most recent large event (MRE) produced an average of 2.5-2.9 m of right-lateral slip, with maximum slip of 3.5 to 4 m at Anza. Double-event offsets for the same 80 km section average ~5.5 m of right-lateral slip. Maximum values near Anza are estimated to be close to 3 m for the penultimate event, suggesting that the penultimate event was similar in size to the MRE. The third event is also similar in size, with cumulative displacement of 9-10 m through Anza for the past three events. Magnitude estimates for the MRE range from Mw 7.2 to Mw 7.5, depending on how far north the rupture continued. Historically, no earthquakes reported along the Clark fault are large enough to have produced the offset geomorphology we observe. However, recent paleoseismic work at Hog Lake dates the most recent surface rupture event at ca. 1790, potentially placing this event in the historic period. A poorly located, large earthquake occurred on November 22, 1800, and is reported to have caused extensive damage (MMI VII) at the San Diego and San Juan Capistrano missions. We infer slightly lower intensity values for the two missions (MMI VI-VII instead of VII) and relocate this event on the Clark fault based on dating of the MRE at Hog Lake. We also recognize the occurrence of a younger offset along ~15-20 km of the fault in Blackburn Canyon, apparently due to lower slip in that area in the November 22, 1800 event. With average displacement of ~1.25 m

  2. Factors associated with different patterns of nonadherence to HIV care in Dar es Salaam, Tanzania.

    PubMed

    Poles, Gabriela; Li, Michelle; Siril, Hellen; Mhalu, Aisa; Hawkins, Claudia; Kaaya, Sylvia; Aris, Eric; Chalamilla, Guerino; Hirschhorn, Lisa R

    2014-01-01

    Health system responsiveness (HSR), a measure of patient health care experience, may influence adherence to HIV/AIDS care and be an important predictor of outcomes. We studied the relationship between HSR, patient factors, and visit nonadherence in 16 President's Emergency Plan for AIDS Relief-supported HIV/AIDS clinics in Dar es Salaam. An HSR survey was administered in 2009, and all clinic visits 1 year following the interviews were analyzed for 720 patients on antiretrovirals (ARVs). Definitions of visit nonadherence were (1) low visit constancy ([VC], no visit in ≥1 quarter), (2) gaps in care (>60 days between visits), (3) no visit in last quarter (VLQ). The relationships between factors were analyzed using multivariate analysis with adjusted odds ratio (AOR) and 95% confidence intervals (CI) reported. Few patients were nonadherent using VLQ (14%) and VC (28%). Gaps in care were more common (49.6%) and associated with younger age (AOR: 3.86 [2.02-7.40]), no explanation of side effects (AOR: 2.21 [1.49-3.28]), and shorter antiretroviral therapy (ART) duration (0-3 months AOR: 1.49 [1.09-2.03]; 3-6 months AOR: 2.44 [1.40-4.25]). No VLQ was associated with younger age (AOR: 3.40 [1.63-7.07]), poor health care worker (HCW) communication (AOR: 4.83 [1.39-16.78]), and less time on ART (0-3 months AOR: 5.04 [2.47-10.30]; 3-6 months AOR: 3.09 [1.72-5.57]). Younger age, poor HCW communication, and shorter ART duration also predicted lower VC, as did higher patient-HCW ratios. The rates of visit nonadherence differed based on the definitions used. Younger age, shorter time on ART, and poor HCW communication predicted lower adherence regardless of the definition. More work is needed to understand the relationship between HSR, patient factors, and different patterns of visit nonadherence and their impact on ART outcomes.

  3. Tree architecture and forest canopy structure obtained from terrestrial LiDAR measurements

    NASA Astrophysics Data System (ADS)

    Hentschel, Reiner; Bittner, Sebastian; Ritter, Daniel; Priesack, Eckart

    2013-04-01

    The modelling of the water transfer in vegetation on a small scale is important when the interaction of single plants and the competition of species are in focus of interest. Explicit geometrical functional-structural models that simulate the water flow in the single plant components such as roots, stem, and branches have been developed recently. These models need an explicit geometrical model of the plant hydrology, more precisely the possible pathway of the xylem and phloem water flow. Roots, stem, and branches are represented by connected porous cylinder elements that are divided into the inner heartwood cylinders surrounded by xylem and phloem. Terrestrial laser scanning (TLS) has been successfully applied to assess the structure of the aboveground vegetation in situ in the last years. Based on the technique of light detection and ranging (LiDAR) this method provides a set of three dimensional points that are located on the surface of objects such as vegetation. A further data processing of this three dimensional point cloud (typically consistent of some million points) enables to obtain structural properties like the spatial leaf distribution or large scale characteristics such as the stand height or plant density. Whereas the resolution and detection rate of the laser scanners have increased in the last years, there is still a need for a data handling especially in the field of ecology. We present the results of a skeleton extraction algorithm that is able to obtain the position and size of branch and stem cylinder elements from a three-dimensional point cloud obtained by TLS field measurements. No manual data processing is necessary to apply the algorithm allowing the analysis of a high number of individual plants. The resulting hydraulic architecture determines the possible pathway of water through the stem and the branches. It can consist of several thousands of connected cylinders depending on the plants that are observed. Examples are given and discussed

  4. Probabilistic terrain models from waveform airborne LiDAR: AutoProbaDTM project results

    NASA Astrophysics Data System (ADS)

    Jalobeanu, A.; Goncalves, G. R.

    2012-12-01

    The main objective of the AutoProbaDTM project was to develop new methods for automated probabilistic topographic map production using the latest LiDAR scanners. It included algorithmic development, implementation and validation over a 200 km2 test area in continental Portugal, representing roughly 100 GB of raw data and half a billion waveforms. We aimed to generate digital terrain models automatically, including ground topography as well as uncertainty maps, using Bayesian inference for model estimation and error propagation, and approaches based on image processing. Here we are presenting the results of the completed project (methodological developments and processing results from the test dataset). In June 2011, the test data were acquired in central Portugal, over an area of geomorphological and ecological interest, using a Riegl LMS-Q680i sensor. We managed to survey 70% of the test area at a satisfactory sampling rate, the angular spacing matching the laser beam divergence and the ground spacing nearly equal to the footprint (almost 4 pts/m2 for a 50cm footprint at 1500 m AGL). This is crucial for a correct processing as aliasing artifacts are significantly reduced. A reverse engineering had to be done as the data were delivered in a proprietary binary format, so we were able to read the waveforms and the essential parameters. A robust waveform processing method has been implemented and tested, georeferencing and geometric computations have been coded. Fast gridding and interpolation techniques have been developed. Validation is nearly completed, as well as geometric calibration, IMU error correction, full error propagation and large-scale DEM reconstruction. A probabilistic processing software package has been implemented and code optimization is in progress. This package includes new boresight calibration procedures, robust peak extraction modules, DEM gridding and interpolation methods, and means to visualize the produced uncertain surfaces (topography

  5. Spatial distribution of lacunarity of voxelized airborne LiDAR point clouds in various forest assemblages

    NASA Astrophysics Data System (ADS)

    Székely, Balázs; Kania, Adam; Standovár, Tibor; Heilmeier, Hermann

    2015-04-01

    Forest ecosystems have characteristic structure of features defined by various structural elements of different scales and vertical positions: shrub layers, understory vegetation, tree trunks, and branches. Furthermore in most of the cases there are superimposed structures in distributions (mosaic or island patterns) due to topography, soil variability, or even anthropogenic factors like past/present forest management activity. This multifaceted spatial context of the forests is relevant for many ecological issues, especially for maintaining forest biodiversity. Our aim in this study is twofold: (1) to quantify this structural variability laterally and vertically using lacunarity, and (2) to relate these results to relevant ecological features, i.e quantitatively described forest properties. Airborne LiDAR data of various quality and point density have been used for our study including a number of forested sites in Central and East Europe (partly Natura 2000 sites). The point clouds have been converted to voxel format and then converted to horizontal layers as images. These images were processed further for the lacunarity calculation. Areas of interest (AOIs) have been selected based on evaluation of the forested areas and auxiliary field information. The calculation has been performed for the AOIs for all available vertical data slices. The lacunarity function referring to a certain point and given vicinity varies horizontally and vertically, depending on the vegetation structure. Furthermore, the topography may also influence this property as the growth of plants, especially spacing and size of trees are influenced by the local topography and relief (e.g., slope, aspect). The comparisons of the flatland and hilly settings show interesting differences and the spatial patterns also vary differently. Because of the large amount of data resulting from these calculations, sophisticated methods are required to analyse the results. The large data amount then has been

  6. Erosion in vineyards and LiDAR: new opportunities for anthropogenic terraced landscapes

    NASA Astrophysics Data System (ADS)

    Tarolli, Paolo; Sofia, Giulia; Calligaro, Simone; Prosdocimi, Massimo; Preti, Federico; Dalla Fontana, Giancarlo

    2014-05-01

    Vineyard landscapes are a relevant part of the European cultivated land, and several authors concluded that they are the agricultural practice that causes the highest soil loss. Since grape quality depends on the availability of water for the vineyards, and since soil erosion is an important parameter dictating the sustainability of vineyards, soil and water conservation are often implemented. The most widely used measure for soil conservation for vineyards in hilly/mountainous landscapes is terracing. However, while improving vineyards stability, the same changes in hillslope hydrology caused by these anthropogenic structures to favor agricultural activities, often result in situations that may lead to local instabilities. Terraces, in fact, when not properly maintained can create hazards for people and settlements, but also for cultivations and for the related economy. Agricultural roads also serve terraced lands, and the construction of these types of anthropogenic features can have deep effects on water flows, in a way similar to the one already registered for forest roads. The goal of this research is to use LiDAR data for the high-resolution hydro-geomorphological analysis of vineyards, underlining the capability of high-resolution topography to provide new tools for a correct management of vineyards terraced landscapes. The work focus on terraced- and road-induced erosion, and it considers a methodology successfully applied to a different environmental context (the RPII index, Tarolli et al. 2013). The index is applied to two study areas, located in the center of Italy, where soil erosion and terrace failures represent a critical issue. The results highlight the effectiveness of high-resolution topography in the analysis of surface erosion, thus providing useful tool to schedule a suitable environmental planning for a sustainable development, and so, to mitigate the consequences of the anthropogenic alterations induced by the terraces structures and

  7. Gender differences in diet and nutrition among adults initiating antiretroviral therapy in Dar es Salaam, Tanzania.

    PubMed

    Abioye, Ajibola I; Isanaka, Sheila; Liu, Enju; Mwiru, Ramadhani S; Noor, Ramadhani A; Spiegelman, Donna; Mugusi, Ferdinand; Fawzi, Wafaie

    2015-01-01

    Human immunodeficiency virus (HIV)-infected males have poor treatment outcomes after initiation of antiretroviral therapy (ART) compared to HIV-infected women. Dietary factors might mediate the association between sex and disease progression. However, the gender difference in diet among HIV-infected individuals in sub-Saharan Africa is largely unknown. The objective of this study was to examine differences in dietary intake among HIV-infected men and women. We conducted a cross-sectional analysis of dietary questionnaire data from 2038 adults initiating ART in Dar es Salaam, Tanzania to assess whether nutrient adequacy differed by sex. We dichotomized participants' nutrient intakes by whether recommended dietary allowances (RDAs) were met and estimated the relative risk (RR) of meeting RDAs in males using binomial regression models. We also estimated the mean difference in intake of foods and food groups by gender. We found poorer dietary practices among men compared to women. Males were less likely to meet the RDAs for micronutrients critical for slowing disease progression among HIV patients: niacin (RR = 0.39, 95% confidence interval [CI]: 0.27 to 0.55), riboflavin (RR = 0.81, 95% CI: 0.73 to 0.91), vitamin C (RR = 0.94, 95% CI: 0.89 to 1.00), and zinc (RR = 0.06, 95% CI: 0.01 to 0.24). Intake of thiamine, pantothenate, vitamins B6, B12, and E did not vary by gender. Males were less likely to eat cereals (mean difference [servings per day] = -0.21, 95% CI: -0.44 to 0.001) and vegetables (mean difference = -0.47, 95% CI: -0.86 to -0.07) in their diet, but more likely to have meat (mean difference = 0.14, 95% CI: 0.06 to 0.21). We conclude that male HIV patients have poorer dietary practices than females, and this may contribute to faster progression of the disease in males.

  8. Development of teaching modules for geology and engineering coursework using terrestrial LiDAR scanning systems

    NASA Astrophysics Data System (ADS)

    Yarbrough, L. D.; Katzenstein, K.

    2012-12-01

    Exposing students to active and local examples of physical geologic processes is beneficial to the learning process. Students typically respond with interest to examples that use state-of-the-art technologies to investigate local or regional phenomena. For lower cognitive level of learning (e.g. knowledge, comprehension, and application), the use of "close-to-home" examples ensures that students better understand concepts. By providing these examples, the students may already have a familiarity or can easily visit the location. Furthermore, these local and regional examples help students to offer quickly other examples of similar phenomena. Investigation of these examples using normal photographic techniques, as well as a more sophisticated 3-D Light Detection And Ranging (LiDAR) (AKA Terrestrial Laser Scanning or TLS) system, allows students to gain a better understanding of the scale and the mechanics of the geologic processes and hazards. The systems are used for research, teaching and outreach efforts and depending on departmental policies can be accessible to students are various learning levels. TLS systems can yield scans at sub-centimeter resolution and contain surface reflectance of targets. These systems can serve a number of learning goals that are essential for training geoscientists and engineers. While querying the data to answer geotechnical or geomorphologic related questions, students will develop skills using large, spatial databases. The upper cognitive level of learning (e.g. analysis, synthesis, and evaluation) is also promoted by using a subset of the data and correlating the physical geologic process of stream bank erosion and rock slope failures with mathematical and computer models using the scanned data. Students use the examples and laboratory exercises to help build their engineering judgment skills with Earth materials. The students learn not only applications of math and engineering science but also the economic and social implication

  9. Wide Area Assessment Demonstration of LiDAR and Orthophotography at Borrego Maneuver Area, Phase II Innovative Multi-Sensor Airborne Wide Area Assessment of UXO Sites, Version 2.0

    DTIC Science & Technology

    2007-12-03

    analysis products. Interpolation of LiDAR digital terrain models ( DTMs ) into DEM rasters was accomplished using Python scripting and the ArcGIS...creation: Triangulation results were loaded into ortho-processing software, along with a LiDAR -derived DTM and aerial photography. Aerial photographs...Environmental Security Technology Certification Program (ESTCP) Final Wide Area Assessment Demonstration of LiDAR and Orthophotography at

  10. Comparison of High Resolution Topographic Data Sources (SAR, IfSAR, and LiDAR) for Storm Surge Hazard Maps

    NASA Astrophysics Data System (ADS)

    Suarez, J. K. B.; Santiago, J. T.; Muldong, T. M. M.; Lagmay, A. M. A.; Caro, C. V.; Ramos, M.

    2014-12-01

    As an archipelagic country, the Philippines has experienced multiple storm surge threats. Moreover, the country's location, adjacent to the Pacific Ocean, results in an average of eight to nine typhoons that make landfall in a year. Storm surge hazard maps require high resolution topographic data to illustrate water inflow in the event of storm surges in vulnerable coastal areas and for accurate boundaries and coastline. Furthermore, potential hazard areas tend to be generalized in lower resolution data. The objective of this research is to compare three sources where accurate and quality storm surge hazard maps will draw bases from. For this purpose, the researcher used and compared SAR, IfSAR and LiDAR. The study involved comparing maps from different topographic data sources in Tacloban, in the province of Leyte. This area was one of the most heavily stricken areas during typhoon Haiyan where more than 6,000 people died and P34.37 billion worth of property was destroyed. In the comparison of the three sources, the following had be taken into consideration: cost of acquiring data, processing time, purpose, and the results. The research learned the following: Synthetic Aperture Radar or SAR produces data with a 30 meter resolution, while Interferometric Synthetic Aperture Radar (IfSAR) offers a resolution of 5 meters. Light Detection and Ranging (LiDAR) has the highest resolution of the three with 1 meter. In addition, higher costs are paid for more detailed topographic data. Also, processing time takes longer for finer details due to the memory of the computer units used for modelling. The sources were also evaluated on the necessity of the scale at which the maps are needed for specific purposes such as practicality and direct disaster response. Results from the maps have been validated through interviews with the locals on the experience of actual storm surges. Through this study, the researcher concluded that although LiDAR can offer a more detailed and

  11. Correction of terrestrial LiDAR intensity channel using Oren-Nayar reflectance model: An application to lithological differentiation

    NASA Astrophysics Data System (ADS)

    Carrea, Dario; Abellan, Antonio; Humair, Florian; Matasci, Battista; Derron, Marc-Henri; Jaboyedoff, Michel

    2016-03-01

    Ground-based LiDAR has been traditionally used for surveying purposes via 3D point clouds. In addition to XYZ coordinates, an intensity value is also recorded by LiDAR devices. The intensity of the backscattered signal can be a significant source of information for various applications in geosciences. Previous attempts to account for the scattering of the laser signal are usually modelled using a perfect diffuse reflection. Nevertheless, experience on natural outcrops shows that rock surfaces do not behave as perfect diffuse reflectors. The geometry (or relief) of the scanned surfaces plays a major role in the recorded intensity values. Our study proposes a new terrestrial LiDAR intensity correction, which takes into consideration the range, the incidence angle and the geometry of the scanned surfaces. The proposed correction equation combines the classical radar equation for LiDAR with the bidirectional reflectance distribution function of the Oren-Nayar model. It is based on the idea that the surface geometry can be modelled by a relief of multiple micro-facets. This model is constrained by only one tuning parameter: the standard deviation of the slope angle distribution (σslope) of micro-facets. Firstly, a series of tests have been carried out in laboratory conditions on a 2 m2 board covered by black/white matte paper (perfect diffuse reflector) and scanned at different ranges and incidence angles. Secondly, other tests were carried out on rock blocks of different lithologies and surface conditions. Those tests demonstrated that the non-perfect diffuse reflectance of rock surfaces can be practically handled by the proposed correction method. Finally, the intensity correction method was applied to a real case study, with two scans of the carbonate rock outcrop of the Dents-du-Midi (Swiss Alps), to improve the lithological identification for geological mapping purposes. After correction, the intensity values are proportional to the intrinsic material reflectance

  12. Assessing the Utility of Green LiDAR for Characterizing Forest Canopy Structure and Stream Bathymetry in Riparian Zones.

    NASA Astrophysics Data System (ADS)

    Moskal, L. M.; Richardson, J.

    2014-12-01

    Forested riparian zones serve many ecosystem functions from species habitat through stream shading and large woody debris recruitment, to improvements in water quality. Moreover, stream depth and bathymetry in forested environments is difficult and costly to measure in the field, but critically important for stream-dwelling organisms. Green (bathymetric) LiDAR (G-L) can be used to characterize stream bathymetry, but little is known of its ability to accurately characterize stream bathymetry in narrow (width less than 5 m), heavily forested streams. Canopy characterization with green LiDAR is also poorly understood. We compared canopy and digital elevation models (DEMs) derived from green and near-infrared LiDAR (NIR-L) to field measurements in a narrow, forested stream in Oregon, USA, as well as comparing the two canopy models and DEMs to each other along the length of the stream and to estimates of leaf area index. We observed that the canopy models from the G-L are lower in accuracy compared to NIR-L canopy models. Canopy height models from the G-L were up to 26% less accurate in dense stands, compared to the NIR-L accuracy of 94%. We attribute these errors in part to the lower quality of DEMs generated from the G-L as compared to the NIR-L DEMs. As for bathymetry, the G-L DEM was 0.05 cm higher in elevation than the field measured stream elevation, while the NIR-L ground model was 0.17mm higher. The elevation difference tended to increase with stream depth for both types of LiDAR-derived DEMs, but stream depth only explained a small portion of the variability (coefficient of determination equals 0.09 for NIR-L DEM and 0.05 for G-L DEM). Our results suggest that G-L may be limited in accurately characterizing the bathymetry of narrow streams in heavily forested environments due to difficulty penetrating canopy and interactions with complex topography.

  13. Mapping and quantifying geodiversity in land-water transition zones using MBES and topobathymetric LiDAR

    NASA Astrophysics Data System (ADS)

    Brandbyge Ernstsen, Verner; Skovgaard Andersen, Mikkel; Gergely, Aron; Schulze Tenberge, Yvonne; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Winter, Christian; Bartholomä, Alexander

    2016-04-01

    Land-water transition zones, like e.g. coastal and fluvial environments, are valuable ecosystems which are often characterised by high biodiversity and geodiversity. However, often these land-water transition zones are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. Combining vessel borne shallow water multibeam echosounder (MBES) surveys ,to cover the subtidal coastal areas and the river channel areas, with airborne topobathymetric light detection and ranging (LiDAR) surveys, to cover the intertidal and supratidal coastal areas and the river floodplain areas, potentially enables full-coverage and high-resolution mapping in these challenging environments. We have carried out MBES and topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage, and in the Ribe Vesterå, a fluvial environment in the Ribe Å river catchment discharging into the Knudedyb tidal basin. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the MBES and the LiDAR point clouds, which both have point densities in the order of 20 points/m2. Morphometric analyses of the DEMs enabled the identification and mapping of the different landforms within the coastal and fluvial environments. Hereby, we demonstrate that vessel borne MBES and airborne topobathymetric LiDAR, here in combination, are promising tools for seamless mapping across land-water transition zones as well as for the quantification of a range of landforms at landscape scale in different land-water transition zone environments. Hence, we demonstrate the potential for mapping and quantifying geomorphological diversity, which is one of the main components of geodiversity and a prerequisite for assessing geoheritage. Acknowledgements This work was funded by the Danish Council for

  14. Fusion of high spatial resolution WorldView-2 imagery and LiDAR pseudo-waveform for object-based image analysis

    NASA Astrophysics Data System (ADS)

    Zhou, Yuhong; Qiu, Fang

    2015-03-01

    High spatial resolution (HSR) imagery and high density LiDAR data provide complementary horizontal and vertical information. Therefore, many studies have focused on fusing the two for mapping geographic features. It has been demonstrated that the synergetic use of LiDAR and HSR imagery greatly improves classification accuracy. This is especially true with waveform LiDAR data since they provide more detailed vertical profiles of geographic objects than discrete-return LiDAR data. Fusion of discrete-return LiDAR and HSR imagery mostly takes place at the object level due to the superiority of object-based image analysis (OBIA) for classifying HSR imagery. However, the fusion of the waveform LiDAR and HSR imagery at the object level has not been adequately studied. To fuse LiDAR waveform and image objects, the waveform for the objects derived from image segmentation are needed. However, the footprints of existing waveform are usually of fixed size and fixed shape, while those of building are of different size and shape. In order to obtain waveforms with footprints that match those of image objects, we proposed synthesizing object-based pseudo-waveforms using discrete-returns LiDAR data by utilizing count or intensity based histogram over the footprints of the objects. The pseudo-waveforms were then fused with the object-level spectral histograms from HSR WorldView-2 imagery to classify the image objects using a Kullback-Leibler divergence-based curve matching approach. The fused dataset achieved an overall classification accuracy of 97.58%, a kappa coefficient of 0.97, and producer's accuracies and user's accuracies all larger than 90%. The use of the fused dataset improved the overall accuracy by 7.61% over the use of HSR imagery alone, and McNemar's test indicated that such improvement was statistically significant (p < 0.001). This study demonstrates the great potential of pseudo-waveform in improving object-based image analysis. This is especially true since

  15. Comparative analysis of genetic variation in kava (Piper methysticum) assessed by SSR and DArT reveals zygotic foundation and clonal diversification.

    PubMed

    Vandenbroucke, Henri; Mournet, Pierre; Malapa, Roger; Glaszmann, Jean-Christophe; Chaïr, Hana; Lebot, Vincent

    2015-01-01

    Kava (Piper methysticum) is a major cash crop in the Pacific. The aim of this study was to assess genetic variation among 103 accessions of kava using SSRs and DArTs. Genetic structure was determined using clustering analyses (WPGMA) and principal coordinate analyses (PCA). Thirteen SSR primers and 75 DArT markers were found polymorphic, and the two types of markers generated similar clustering patterns. Genetic distances ranged from 0 to 0.65 with an average of 0.24 using SSRs and from 0 to 0.64 with an average of 0.24 using DArT. Eleven genotypes were identified with SSR while 28 genotypes were identified with DArT markers. By combining the two sets of markers, a total of only 30 distinct genotypes were observed. In the Vanuatu archipelago, noble cultivars originating from different islands clustered together within a very narrow genetic base despite their diversity of morphotypes. SSR and DArT fingerprints allowed the identification of kava cultivars unsuitable for consumption, so called two-days, and clearly differentiated the wild types classified as P. methysticum var. wichmannii from the cultivars as var. methysticum. Molecular data reveals that all noble cultivars evolved by the predominance of clonal selection. Although they are represented by clearly distinct morphotypes, these cultivars are genetically vulnerable and their potential to adapt to forthcoming changes is limited. These newly developed markers provide high resolution and will be useful for kava diversity analyses and quality assessment.

  16. Adjustment of Measurements with Multiplicative Errors: Error Analysis, Estimates of the Variance of Unit Weight, and Effect on Volume Estimation from LiDAR-Type Digital Elevation Models

    PubMed Central

    Shi, Yun; Xu, Peiliang; Peng, Junhuan; Shi, Chuang; Liu, Jingnan

    2014-01-01

    Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS) adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM) have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM. PMID:24434880

  17. Adjustment of measurements with multiplicative errors: error analysis, estimates of the variance of unit weight, and effect on volume estimation from LiDAR-type digital elevation models.

    PubMed

    Shi, Yun; Xu, Peiliang; Peng, Junhuan; Shi, Chuang; Liu, Jingnan

    2014-01-10

    Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS) adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM) have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM.

  18. Integrating terrestrial LiDAR and stereo photogrammetry to map the Tolay lakebed in northern San Francisco Bay

    USGS Publications Warehouse

    Woo, Isa; Storesund,; Takekawa, John Y.; Gardiner, Rachel J.; Ehret,

    2009-01-01

    The Tolay Creek Watershed drains approximately 3,520 ha along the northern edge of San Francisco Bay. Surrounded by a mosaic of open space conservation easements and public wildlife areas, it is one of the only watersheds in this urbanized estuary that is protected from its headwaters to the bay. Tolay Lake is a seasonal, spring-fed lake found in the upper watershed that historically extended over 120 ha. Although the lakebed was farmed since the early 1860s, the majority of the lakebed was recently acquired by the Sonoma County Regional Parks Department to restore its natural habitat values. As part of the restoration planning process, we produced a digital elevation model (DEM) of the historic extent of Tolay Lake by integrating terrestrial LiDAR (light detection and ranging) and stereo photogrammetry datasets, and real-time kinematic (RTK) global positioning system (GPS) surveys. We integrated the data, generated a DEM of the lakebed and upland areas, and analyzed errors. The accuracy of the composite DEM was verified using spot elevations obtained from the RTK GPS. Thus, we found that by combining photogrammetry, terrestrial LiDAR, and RTK GPS, we created an accurate baseline elevation map to use in watershed restoration planning and design.

  19. Undernutrition and associated factors among 24–36-month-old children in slum areas of Bahir Dar city, Ethiopia

    PubMed Central

    Demilew, Yeshalem Mulugeta; Abie, Dagninet Derebe

    2017-01-01

    Background This study aimed to assess undernutrition and associated factors among 24–36-month-old children in the slum areas of Bahir Dar city. Methods A community-based cross-sectional study was conducted among 480 children from May 1 to 26, 2015. The simple random sampling technique was used to select respondents. Data were collected using a structured interviewer-administered questionnaire. Statistical Package for Social Sciences version 20 was used for analysis. The prevalence of undernutrition was computed. Binary and multivariable logistic regression analyses were also carried out to identify the association between the independent and dependent variables and the predictors of undernutrition, respectively. A P-value <0.05 was considered to be statistically significant in the final model. Result The prevalence of stunting, underweight, and wasting was 42%, 22.1%, and 6.4%, respectively. Independent predictors for stunting were illness in the preceding two weeks, having two children under three years old, taking prelacteal feeding, and early or late initiation of complementary feeding. Illness in the preceding two weeks, lack of latrine utilization, and lack of hand washing practice were independent predictors for underweight. Conclusion There was a high prevalence of undernutrition in this study. Thus, health extension workers and health professionals in Bahir Dar city should educate mothers/caretakers on the health impact of giving prelacteal feeding, hand washing practice, time of initiation of complementary feeding, and birth interval. PMID:28331353

  20. Generating spike-free digital surface models using LiDAR raw point clouds: A new approach for forestry applications

    NASA Astrophysics Data System (ADS)

    Khosravipour, Anahita; Skidmore, Andrew K.; Isenburg, Martin

    2016-10-01

    Accurately detecting single trees from LiDAR data requires generating a high-resolution Digital Surface Model (DSM) that faithfully represents the uppermost layer of the forest canopy. A high-resolution DSM raster is commonly generated by interpolating all first LiDAR returns through a Delaunay TIN. The first-return 2D surface interpolation struggles to produce a faithful representation of the canopy when there are first returns that have very similar x-y coordinates but very different z values. When triangulated together into a TIN, such constellations will form needle-shaped triangles that appear as spikes that geometrically disrupt the DSM and negatively affect treetop detection and subsequent extraction of biophysical parameters. We introduce a spike-free algorithm that considers all returns (e.g. also second and third returns) and systematically prevents spikes formation during TIN construction by ignoring any return whose insertion would result in a spike. Our algorithm takes a raw point cloud (i.e., unclassified) as input and produces a spike-free TIN as output that is then rasterized onto a corresponding pit-free DSM grid. We evaluate the new algorithm by comparing the results of treetop detection using the pit-free DSM with those achieved using a common first-return DSM. The results show that our algorithm significantly improves the accuracy of treetop detection, especially for small trees.

  1. Fine-Scale Topographic Analysis of Rock Size Distributions Derived from High-Resolution Ground-Based LiDAR

    NASA Astrophysics Data System (ADS)

    Finnegan, D. C.; Arcone, S. A.; Bulmer, M. H.; Anderson, S. W.

    2007-05-01

    Quantitative factors such as RMS height, correlation lengths and surface slope derived from fine-scale topographic datasets hold the potential for characterizing surface morphology in relation to its underlying geologic processes. In an attempt to better understand the relationships between topographic roughness characteristics and geologic processes responsible for creating a distinct surface morphology, we utilize ground-based terrestrial LiDAR and coincidental orthorectified imagery to quantify the variability in RMS heights and correlation lengths. The purpose of this study is to understand directly how various topographic data collection techniques such as LiDAR and manual field-based measurements compare to one another and which techniques are most appropriate for characterizing topography at various scales. Topographic data from several platforms were acquired over desert surfaces in the Mojave Desert near Palm Springs, California and southwestern Arizona. The desert surfaces imaged in the Mojave contained average rock sizes ranging from decimeters to a maximum size near one meter and revealed wide variations in RMS heights and correlation lengths, in keeping with the highly variable surface. Alternately, the Arizona site exhibits less topographic variability and consistent statistics. The data are useful for characterizing the roughness of surfaces for a variety of disciplines, such as penetration of remote sensing signals, upwelling of radiation and characterizing the genetic origin of surfaces. Furthermore, these data become essential to airborne and ground-based imaging sensors and understanding how topographic irregularities affect data fidelity.

  2. A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Hamraz, Hamid; Contreras, Marco A.; Zhang, Jun

    2016-10-01

    This paper presents a non-parametric approach for segmenting trees from airborne LiDAR data in deciduous forests. Based on the LiDAR point cloud, the approach collects crown information such as steepness and height on-the-fly to delineate crown boundaries, and most importantly, does not require a priori assumptions of crown shape and size. The approach segments trees iteratively starting from the tallest within a given area to the smallest until all trees have been segmented. To evaluate its performance, the approach was applied to the University of Kentucky Robinson Forest, a deciduous closed-canopy forest with complex terrain and vegetation conditions. The approach identified 94% of dominant and co-dominant trees with a