The fragmented nature of tundra landscape

NASA Astrophysics Data System (ADS)

Virtanen, Tarmo; Ek, Malin

2014-04-01

The vegetation and land cover structure of tundra areas is fragmented when compared to other biomes. Thus, satellite images of high resolution are required for producing land cover classifications, in order to reveal the actual distribution of land cover types across these large and remote areas. We produced and compared different land cover classifications using three satellite images (QuickBird, Aster and Landsat TM5) with different pixel sizes (2.4 m, 15 m and 30 m pixel size, respectively). The study area, in north-eastern European Russia, was visited in July 2007 to obtain ground reference data. The QuickBird image was classified using supervised segmentation techniques, while the Aster and Landsat TM5 images were classified using a pixel-based supervised classification method. The QuickBird classification showed the highest accuracy when tested against field data, while the Aster image was generally more problematic to classify than the Landsat TM5 image. Use of smaller pixel sized images distinguished much greater levels of landscape fragmentation. The overall mean patch sizes in the QuickBird, Aster, and Landsat TM5-classifications were 871 m2, 2141 m2 and 7433 m2, respectively. In the QuickBird classification, the mean patch size of all the tundra and peatland vegetation classes was smaller than one pixel of the Landsat TM5 image. Water bodies and fens in particular occur in the landscape in small or elongated patches, and thus cannot be realistically classified from larger pixel sized images. Land cover patterns vary considerably at such a fine-scale, so that a lot of information is lost if only medium resolution satellite images are used. It is crucial to know the amount and spatial distribution of different vegetation types in arctic landscapes, as carbon dynamics and other climate related physical, geological and biological processes are known to vary greatly between vegetation types.

Automated, per pixel Cloud Detection from High-Resolution VNIR Data

NASA Technical Reports Server (NTRS)

Varlyguin, Dmitry L.

2007-01-01

CASA is a fully automated software program for the per-pixel detection of clouds and cloud shadows from medium- (e.g., Landsat, SPOT, AWiFS) and high- (e.g., IKONOS, QuickBird, OrbView) resolution imagery without the use of thermal data. CASA is an object-based feature extraction program which utilizes a complex combination of spectral, spatial, and contextual information available in the imagery and the hierarchical self-learning logic for accurate detection of clouds and their shadows.

Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses

NASA Astrophysics Data System (ADS)

Agüera, Francisco; Aguilar, Fernando J.; Aguilar, Manuel A.

The area occupied by plastic-covered greenhouses has undergone rapid growth in recent years, currently exceeding 500,000 ha worldwide. Due to the vast amount of input (water, fertilisers, fuel, etc.) required, and output of different agricultural wastes (vegetable, plastic, chemical, etc.), the environmental impact of this type of production system can be serious if not accompanied by sound and sustainable territorial planning. For this, the new generation of satellites which provide very high resolution imagery, such as QuickBird and IKONOS can be useful. In this study, one QuickBird and one IKONOS satellite image have been used to cover the same area under similar circumstances. The aim of this work was an exhaustive comparison of QuickBird vs. IKONOS images in land-cover detection. In terms of plastic greenhouse mapping, comparative tests were designed and implemented, each with separate objectives. Firstly, the Maximum Likelihood Classification (MLC) was applied using five different approaches combining R, G, B, NIR, and panchromatic bands. The combinations of the bands used, significantly influenced some of the indexes used to classify quality in this work. Furthermore, the quality classification of the QuickBird image was higher in all cases than that of the IKONOS image. Secondly, texture features derived from the panchromatic images at different window sizes and with different grey levels were added as a fifth band to the R, G, B, NIR images to carry out the MLC. The inclusion of texture information in the classification did not improve the classification quality. For classifications with texture information, the best accuracies were found in both images for mean and angular second moment texture parameters. The optimum window size in these texture parameters was 3×3 for IK images, while for QB images it depended on the quality index studied, but the optimum window size was around 15×15. With regard to the grey level, the optimum was 128. Thus, the optimum texture parameter depended on the main objective of the image classification. If the main classification goal is to minimize the number of pixels wrongly classified, the mean texture parameter should be used, whereas if the main classification goal is to minimize the unclassified pixels the angular second moment texture parameter should be used. On the whole, both QuickBird and IKONOS images offered promising results in classifying plastic greenhouses.

A new method of Quickbird own image fusion

NASA Astrophysics Data System (ADS)

Han, Ying; Jiang, Hong; Zhang, Xiuying

2009-10-01

With the rapid development of remote sensing technology, the means of accessing to remote sensing data become increasingly abundant, thus the same area can form a large number of multi-temporal, different resolution image sequence. At present, the fusion methods are mainly: HPF, IHS transform method, PCA method, Brovey, Mallat algorithm and wavelet transform and so on. There exists a serious distortion of the spectrums in the IHS transform, Mallat algorithm omits low-frequency information of the high spatial resolution images, the integration results of which has obvious blocking effects. Wavelet multi-scale decomposition for different sizes, the directions, details and the edges can have achieved very good results, but different fusion rules and algorithms can achieve different effects. This article takes the Quickbird own image fusion as an example, basing on wavelet transform and HVS, wavelet transform and IHS integration. The result shows that the former better. This paper introduces the correlation coefficient, the relative average spectral error index and usual index to evaluate the quality of image.

Los Angeles 1-Million tree canopy cover assessment

Treesearch

Gregory E. McPherson; James R. Simpson; Qingfu Xiao; Wu Chunxia

2008-01-01

The Million Trees LA initiative intends to chart a course for sustainable growth through planting and stewardship of trees. The purpose of this study was to measure Los Angeles's existing tree canopy cover (TCC), determine if space exists for 1 million additional trees, and estimate future benefits from the planting. High resolution QuickBird remote sensing data,...

Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

PubMed Central

Moran, Emilio Federico.

2010-01-01

High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervised classification, incorporation of textural images and multispectral images, spectral-spatial classifier, and segmentation-based classification are examined in a relatively new developing urban landscape, Lucas do Rio Verde in Mato Grosso State, Brazil. This research shows that use of spatial information during the image classification procedure, either through the integrated use of textural and spectral images or through the use of segmentation-based classification method, can significantly improve land cover classification performance. PMID:21643433

Measurement Sets and Sites Commonly Used for High Spatial Resolution Image Product Characterization

NASA Technical Reports Server (NTRS)

Pagnutti, Mary

2006-01-01

Scientists within NASA's Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site has enabled the in-flight characterization of satellite high spatial resolution remote sensing system products form Space Imaging IKONOS, Digital Globe QuickBird, and ORBIMAGE OrbView, as well as advanced multispectral airborne digital camera products. SSC utilizes engineered geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment and their Instrument Validation Laboratory to characterize high spatial resolution remote sensing data products. This presentation describes the SSC characterization capabilities and techniques in the visible through near infrared spectrum and examples of calibration results.

Land area change and fractional water maps in the Chenier Plain, Louisiana, following hurricane Rita

NASA Astrophysics Data System (ADS)

Palaseanu-Lovejoy, M.; Kranenburg, C.; Brock, J. C.

2009-12-01

The objective of this study is to develop a fractional water map at 30-m resolution scale using QuickBird and/or IKONOS high-resolution imagery as dependent variable to investigate the impact of hurricane Rita in the Chenier Plain, Louisiana. Eleven different indices were tested to obtain a high-resolution land / water classification on QuickBird (acquired on 05/23/2003) and IKONOS (acquired on 03/25/2006) images. The percent area covered by water in the high resolution images varied from 22 to 26% depending on the index used , with the simple ratio index (red band / NIR band) accounting for the lowest percent and the blue ratio index (blue band / sum(all bands)) for the highest percent. Using the ERDAS NLCD (National Land Cover Data) Mapping tool module, 100, 000 stratified random sample points with minimum 1000 points per stratum were selected from the high resolution dependent variable as training information for the independent variable layers. The rules for the regression tree were created using the data mining software Rulequest Cubist v. 2.05. This information was used to generate a fractional water map for the entire Landsat scene. The increase in water areas of about 10 - 15% between 2003 to 2006, as well as temporary changes in the water - land configurations are attributed to remnant flooding and removal of aquatic vegetation caused by hurricane Rita, and water level variations caused by tidal and / or meteorological variations between the acquisition dates of the satellite images. This analysis can assist in monitoring post-hurricane wetland recovery and assess trends in land loss due to extreme storm events, although estimation of permanent land loss cannot be made until wetland areas have the opportunity to recover from hurricane impacts.

Utility of remotely sensed imagery for assessing the impact of salvage logging after forest fires

Treesearch

Sarah A. Lewis; Peter R. Robichaud; Andrew T. Hudak; Brian Austin; Robert J. Liebermann

2012-01-01

Remotely sensed imagery provides a useful tool for land managers to assess the extent and severity of post-wildfire salvage logging disturbance. This investigation uses high resolution QuickBird and National Agricultural Imagery Program (NAIP) imagery to map soil exposure after ground-based salvage operations. Three wildfires with varying post-fire salvage activities...

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

NASA Astrophysics Data System (ADS)

Meusburger, K.; Konz, N.; Schaub, M.; Alewell, C.

2010-06-01

The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km 2) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed "hotspots" of high erosion of up to 16 t ha -1 a -1. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.

A Procedure for High Resolution Satellite Imagery Quality Assessment

PubMed Central

Crespi, Mattia; De Vendictis, Laura

2009-01-01

Data products generated from High Resolution Satellite Imagery (HRSI) are routinely evaluated during the so-called in-orbit test period, in order to verify if their quality fits the desired features and, if necessary, to obtain the image correction parameters to be used at the ground processing center. Nevertheless, it is often useful to have tools to evaluate image quality also at the final user level. Image quality is defined by some parameters, such as the radiometric resolution and its accuracy, represented by the noise level, and the geometric resolution and sharpness, described by the Modulation Transfer Function (MTF). This paper proposes a procedure to evaluate these image quality parameters; the procedure was implemented in a suitable software and tested on high resolution imagery acquired by the QuickBird, WorldView-1 and Cartosat-1 satellites. PMID:22412312

MODIS Tree Cover Validation for the Circumpolar Taiga-Tundra Transition Zone

NASA Technical Reports Server (NTRS)

Montesano, P. M.; Nelson, R.; Sun, G.; Margolis, H.; Kerber, A.; Ranson, K. J.

2009-01-01

A validation of the 2005 500m MODIS vegetation continuous fields (VCF) tree cover product in the circumpolar taiga-tundra ecotone was performed using high resolution Quickbird imagery. Assessing the VCF's performance near the northern limits of the boreal forest can help quantify the accuracy of the product within this vegetation transition area. The circumpolar region was divided into longitudinal zones and validation sites were selected in areas of varying tree cover where Quickbird imagery is available in Google Earth. Each site was linked to the corresponding VCF pixel and overlaid with a regular dot grid within the VCF pixel's boundary to estimate percent tree crown cover in the area. Percent tree crown cover was estimated using Quickbird imagery for 396 sites throughout the circumpolar region and related to the VCF's estimates of canopy cover for 2000-2005. Regression results of VCF inter-annual comparisons (2000-2005) and VCF-Quickbird image-interpreted estimates indicate that: (1) Pixel-level, inter-annual comparisons of VCF estimates of percent canopy cover were linearly related (mean R(sup 2) = 0.77) and exhibited an average root mean square error (RMSE) of 10.1 % and an average root mean square difference (RMSD) of 7.3%. (2) A comparison of image-interpreted percent tree crown cover estimates based on dot counts on Quickbird color images by two different interpreters were more variable (R(sup 2) = 0.73, RMSE = 14.8%, RMSD = 18.7%) than VCF inter-annual comparisons. (3) Across the circumpolar boreal region, 2005 VCF-Quickbird comparisons were linearly related, with an R(sup 2) = 0.57, a RMSE = 13.4% and a RMSD = 21.3%, with a tendency to over-estimate areas of low percent tree cover and anomalous VCF results in Scandinavia. The relationship of the VCF estimates and ground reference indicate to potential users that the VCF's tree cover values for individual pixels, particularly those below 20% tree cover, may not be precise enough to monitor 500m pixel-level tree cover in the taiga-tundra transition zone.

Million trees Los Angeles canopy cover and benefit assessment

Treesearch

E.G. McPherson; J.R. Simpson; Q. Xiao; C. Wu

2011-01-01

The Million Trees LA initiative intends to improve Los Angeles’s environment through planting and stewardship of 1 million trees. The purpose of this study was to measure Los Angeles’s existing tree canopy cover (TCC), determine if space exists for 1 million additional trees, and estimate future benefits from the planting. High-resolution QuickBird remote sensing data...

System Characterization Results for the QuickBird Sensor

NASA Technical Reports Server (NTRS)

Holekamp, Kara; Ross, Kenton; Blonski, Slawomir

2007-01-01

An overall system characterization was performed on several DigitalGlobe' QuickBird image products by the NASA Applied Research & Technology Project Office (formerly the Applied Sciences Directorate) at the John C. Stennis Space Center. This system characterization incorporated geopositional accuracy assessments, a spatial resolution assessment, and a radiometric calibration assessment. Geopositional assessments of standard georeferenced multispectral products were obtained using an array of accurately surveyed geodetic targets evenly spaced throughout a scene. Geopositional accuracy was calculated in terms of circular error. Spatial resolution of QuickBird panchromatic imagery was characterized based on edge response measurements using edge targets and the tilted-edge technique. Relative edge response was estimated as a geometric mean of normalized edge response differences measured in two directions of image pixels at points distanced from the edge by -0.5 and 0.5 of ground sample distance. A reflectance-based vicarious calibration approach, based on ground-based measurements and radiative transfer calculations, was used to estimate at-sensor radiance. These values were compared to those measured by the sensor to determine the sensor's radiometric accuracy. All imagery analyzed was acquired between fall 2005 and spring 2006. These characterization results were compared to previous years' results to identify any temporal drifts or trends.

[An object-oriented remote sensing image segmentation approach based on edge detection].

PubMed

Tan, Yu-Min; Huai, Jian-Zhu; Tang, Zhong-Shi

2010-06-01

Satellite sensor technology endorsed better discrimination of various landscape objects. Image segmentation approaches to extracting conceptual objects and patterns hence have been explored and a wide variety of such algorithms abound. To this end, in order to effectively utilize edge and topological information in high resolution remote sensing imagery, an object-oriented algorithm combining edge detection and region merging is proposed. Susan edge filter is firstly applied to the panchromatic band of Quickbird imagery with spatial resolution of 0.61 m to obtain the edge map. Thanks to the resulting edge map, a two-phrase region-based segmentation method operates on the fusion image from panchromatic and multispectral Quickbird images to get the final partition result. In the first phase, a quad tree grid consisting of squares with sides parallel to the image left and top borders agglomerates the square subsets recursively where the uniform measure is satisfied to derive image object primitives. Before the merger of the second phrase, the contextual and spatial information, (e. g., neighbor relationship, boundary coding) of the resulting squares are retrieved efficiently by means of the quad tree structure. Then a region merging operation is performed with those primitives, during which the criterion for region merging integrates edge map and region-based features. This approach has been tested on the QuickBird images of some site in Sanxia area and the result is compared with those of ENVI Zoom Definiens. In addition, quantitative evaluation of the quality of segmentation results is also presented. Experiment results demonstrate stable convergence and efficiency.

Mineral resources prospecting by synthetic application of TM/ETM+, Quickbird and Hyperion data in the Hatu area, West Junggar, Xinjiang, China

PubMed Central

Liu, Lei; Zhou, Jun; Jiang, Dong; Zhuang, Dafang; Mansaray, Lamin R.; Hu, Zhijun; Ji, Zhengbao

2016-01-01

The Hatu area, West Junggar, Xinjiang, China, is situated at a potential gold-copper mineralization zone in association with quartz veins and small granitic intrusions. In order to identify the alteration zones and mineralization occurrences in this area, the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+), Quickbird, Hyperion data and laboratory measured spectra were combined in identifying structures, alteration zones, quartz veins and small intrusions. The hue-saturation-intensity (HSI) color model transformation was applied to transform principal component analysis (PCA) combinations from R (Red), G (Green) and B (Blue) to HSI space to enhance faults. To wipe out the interference of the noise, a method, integrating Crosta technique and anomaly-overlaying selection, was proposed and implemented. Both Jet Propulsion Laboratory Spectral Library spectra and laboratory-measured spectra, combining with matched filtering method, were used to process Hyperion data. In addition, high-resolution Quickbird data were used for unraveling the quartz veins and small intrusions along the alteration zones. The Baobei fault and a SW-NE-oriented alteration zone were identified for the first time. This study eventually led to the discovery of four weak gold-copper mineralized locations through ground inspection and brought new geological knowledge of the region’s metallogeny. PMID:26911195

Developing Remote Sensing Capabilities for Meter-Scale Sea Ice Properties

DTIC Science & Technology

2013-09-30

such as MODIS . APPROACH 1. Task and acquire high resolution panchromatic and multispectral optical (e.g. Quickbird, Worldview, National Assets...does not display a currently valid OMB control number. 1. REPORT DATE 30 SEP 2013 2. REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4...cloud cover , an excessive percentage of the imagery acquired over drifting sites was cloud covered , and the vendor did not delay acquisitions or

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

PubMed

Li, Linyi; Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

PubMed Central

Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images. PMID:28761440

Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying

2011-01-01

Accurately detecting urban expansion with remote sensing techniques is a challenge due to the complexity of urban landscapes. This paper explored methods for detecting urban expansion with multitemporal QuickBird images in Lucas do Rio Verde, Mato Grosso, Brazil. Different techniques, including image differencing, principal component analysis (PCA), and comparison of classified impervious surface images with the matched filtering method, were used to examine urbanization detection. An impervious surface image classified with the hybrid method was used to modify the urbanization detection results. As a comparison, the original multispectral image and segmentation-based mean-spectral images were used during the detection of urbanization. This research indicates that the comparison of classified impervious surface images with matched filtering method provides the best change detection performance, followed by the image differencing method based on segmentation-based mean spectral images. The PCA is not a good method for urban change detection in this study. Shadows and high spectral variation within the impervious surfaces represent major challenges to the detection of urban expansion when high spatial resolution images are used. PMID:21799706

A Fully Automated Method of Locating Building Shadows for Aerosol Optical Depth Calculations in High-Resolution Satellite Imagery

DTIC Science & Technology

2010-09-01

absorption, limiting the effectiveness of intelligence collection and weapon systems that operate in those portions of the spectrum by reducing the amount of... Intelligence Agency Web site in NITF 2.0 format. This study used basic imagery from DigitalGlobe (QuickBird, WorldView-1). This imagery is not...databases. Militarily, FASTEC could enable in-scene correction in intelligence collection and possibly influence electro- optical targeting decisions

[Extraction of buildings three-dimensional information from high-resolution satellite imagery based on Barista software].

PubMed

Zhang, Pei-feng; Hu, Yuan-man; He, Hong-shi

2010-05-01

The demand for accurate and up-to-date spatial information of urban buildings is becoming more and more important for urban planning, environmental protection, and other vocations. Today's commercial high-resolution satellite imagery offers the potential to extract the three-dimensional information of urban buildings. This paper extracted the three-dimensional information of urban buildings from QuickBird imagery, and validated the precision of the extraction based on Barista software. It was shown that the extraction of three-dimensional information of the buildings from high-resolution satellite imagery based on Barista software had the advantages of low professional level demand, powerful universality, simple operation, and high precision. One pixel level of point positioning and height determination accuracy could be achieved if the digital elevation model (DEM) and sensor orientation model had higher precision and the off-Nadir View Angle was relatively perfect.

Mapping invasive wetland plants in the Hudson River National Estuarine Research Reserve using quickbird satellite imagery

USGS Publications Warehouse

Laba, M.; Downs, R.; Smith, S.; Welsh, S.; Neider, C.; White, S.; Richmond, M.; Philpot, W.; Baveye, P.

2008-01-01

The National Estuarine Research Reserve (NERR) program is a nationally coordinated research and monitoring program that identifies and tracks changes in ecological resources of representative estuarine ecosystems and coastal watersheds. In recent years, attention has focused on using high spatial and spectral resolution satellite imagery to map and monitor wetland plant communities in the NERRs, particularly invasive plant species. The utility of this technology for that purpose has yet to be assessed in detail. To that end, a specific high spatial resolution satellite imagery, QuickBird, was used to map plant communities and monitor invasive plants within the Hudson River NERR (HRNERR). The HRNERR contains four diverse tidal wetlands (Stockport Flats, Tivoli Bays, Iona Island, and Piermont), each with unique water chemistry (i.e., brackish, oligotrophic and fresh) and, consequently, unique assemblages of plant communities, including three invasive plants (Trapa natans, Phragmites australis, and Lythrum salicaria). A maximum-likelihood classification was used to produce 20-class land cover maps for each of the four marshes within the HRNERR. Conventional contingency tables and a fuzzy set analysis served as a basis for an accuracy assessment of these maps. The overall accuracies, as assessed by the contingency tables, were 73.6%, 68.4%, 67.9%, and 64.9% for Tivoli Bays, Stockport Flats, Piermont, and Iona Island, respectively. Fuzzy assessment tables lead to higher estimates of map accuracies of 83%, 75%, 76%, and 76%, respectively. In general, the open water/tidal channel class was the most accurately mapped class and Scirpus sp. was the least accurately mapped. These encouraging accuracies suggest that high-resolution satellite imagery offers significant potential for the mapping of invasive plant species in estuarine environments. ?? 2007 Elsevier Inc. All rights reserved.

Application and evaluation of ISVR method in QuickBird image fusion

NASA Astrophysics Data System (ADS)

Cheng, Bo; Song, Xiaolu

2014-05-01

QuickBird satellite images are widely used in many fields, and applications have put forward high requirements for the integration of the spatial information and spectral information of the imagery. A fusion method for high resolution remote sensing images based on ISVR is identified in this study. The core principle of ISVS is taking the advantage of radicalization targeting to remove the effect of different gain and error of satellites' sensors. Transformed from DN to radiance, the multi-spectral image's energy is used to simulate the panchromatic band. The linear regression analysis is carried through the simulation process to find a new synthetically panchromatic image, which is highly linearly correlated to the original panchromatic image. In order to evaluate, test and compare the algorithm results, this paper used ISVR and other two different fusion methods to give a comparative study of the spatial information and spectral information, taking the average gradient and the correlation coefficient as an indicator. Experiments showed that this method could significantly improve the quality of fused image, especially in preserving spectral information, to maximize the spectral information of original multispectral images, while maintaining abundant spatial information.

Use of UAVs for Remote Measurement of Vegetation Canopy Variables

NASA Astrophysics Data System (ADS)

Rango, A.; Laliberte, A.; Herrick, J.; Steele, C.; Bestelmeyer, B.; Chopping, M. J.

2006-12-01

Remote sensing with different sensors has proven useful for measuring vegetation canopy variables at scales ranging from landscapes down to individual plants. For use at landscape scales, such as desert grasslands invaded by shrubs, it is possible to use multi-angle imagery from satellite sensors, such as MISR and CHRIS/Proba, with geometric optical models to retrieve fractional woody plant cover. Vegetation community states can be mapped using visible and near infrared ASTER imagery at 15 m resolution. At finer scales, QuickBird satellite imagery with approximately 60 cm resolution and piloted aircraft photography with 25-80 cm resolution can be used to measure shrubs above a critical size. Tests conducted with the QuickBird data in the Jornada basin of southern New Mexico have shown that 87% of all shrubs greater than 2 m2 were detected whereas only about 29% of all shrubs less than 2 m2 were detected, even at these high resolutions. Because there is an observational gap between satellite/aircraft measurements and ground observations, we have experimented with Unmanned Aerial Vehicles (UAVs) producing digital photography with approximately 5 cm resolution. We were able to detect all shrubs greater than 2 m2, and we were able to map small subshrubs indicative of rangeland deterioration, as well as remnant grass patches, for the first time. None of these could be identified on the 60 cm resolution data. Additionally, we were able to measure canopy gaps, shrub patterns, percent bare soil, and vegetation cover over mixed rangeland vegetation. This approach is directly applicable to rangeland health monitoring, and it provides a quantitative way to assess shrub invasion over time and to detect the depletion or recovery of grass patches. Further, if the UAV images have sufficient overlap, it may be possible to exploit the stereo viewing capabilities to develop a digital elevation model from the orthophotos, with a potential for extracting canopy height. We envision two parallel routes for investigation: one which emphasizes utilization of the most technically advanced passive and active space and aircraft sensors (e.g., LIDAR, radar, Hyperion, ASTER, QuickBird follow-on) for modeling research, and a second which emphasizes minimization of costs and maximization of simplicity for monitoring purposes utilizing inexpensive sensors such as digital cameras on UAVs for arid and semiarid rangelands. The use of UAVs will provide management agencies a way to assess various vegetation canopy variables for a very reasonable cost.

Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation

NASA Astrophysics Data System (ADS)

Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

2014-02-01

A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

Implementing and validating of pan-sharpening algorithms in open-source software

NASA Astrophysics Data System (ADS)

Pesántez-Cobos, Paúl; Cánovas-García, Fulgencio; Alonso-Sarría, Francisco

2017-10-01

Several approaches have been used in remote sensing to integrate images with different spectral and spatial resolutions in order to obtain fused enhanced images. The objective of this research is three-fold. To implement in R three image fusion techniques (High Pass Filter, Principal Component Analysis and Gram-Schmidt); to apply these techniques to merging multispectral and panchromatic images from five different images with different spatial resolutions; finally, to evaluate the results using the universal image quality index (Q index) and the ERGAS index. As regards qualitative analysis, Landsat-7 and Landsat-8 show greater colour distortion with the three pansharpening methods, although the results for the other images were better. Q index revealed that HPF fusion performs better for the QuickBird, IKONOS and Landsat-7 images, followed by GS fusion; whereas in the case of Landsat-8 and Natmur-08 images, the results were more even. Regarding the ERGAS spatial index, the ACP algorithm performed better for the QuickBird, IKONOS, Landsat-7 and Natmur-08 images, followed closely by the GS algorithm. Only for the Landsat-8 image did, the GS fusion present the best result. In the evaluation of spectral components, HPF results tended to be better and ACP results worse, the opposite was the case with the spatial components. Better quantitative results are obtained in Landsat-7 and Landsat-8 images with the three fusion methods than with the QuickBird, IKONOS and Natmur-08 images. This contrasts with the qualitative evaluation reflecting the importance of splitting the two evaluation approaches (qualitative and quantitative). Significant disagreement may arise when different methodologies are used to asses the quality of an image fusion. Moreover, it is not possible to designate, a priori, a given algorithm as the best, not only because of the different characteristics of the sensors, but also because of the different atmospherics conditions or peculiarities of the different study areas, among other reasons.

Shadow Detection from Very High Resoluton Satellite Image Using Grabcut Segmentation and Ratio-Band Algorithms

NASA Astrophysics Data System (ADS)

Kadhim, N. M. S. M.; Mourshed, M.; Bray, M. T.

2015-03-01

Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of the ratio algorithm. The differences in the characteristics of the two satellite imageries in terms of spatial and spectral resolution can play an important role in the estimation and detection of the shadow of urban objects.

Built-Up Area Detection from High-Resolution Satellite Images Using Multi-Scale Wavelet Transform and Local Spatial Statistics

NASA Astrophysics Data System (ADS)

Chen, Y.; Zhang, Y.; Gao, J.; Yuan, Y.; Lv, Z.

2018-04-01

Recently, built-up area detection from high-resolution satellite images (HRSI) has attracted increasing attention because HRSI can provide more detailed object information. In this paper, multi-resolution wavelet transform and local spatial autocorrelation statistic are introduced to model the spatial patterns of built-up areas. First, the input image is decomposed into high- and low-frequency subbands by wavelet transform at three levels. Then the high-frequency detail information in three directions (horizontal, vertical and diagonal) are extracted followed by a maximization operation to integrate the information in all directions. Afterward, a cross-scale operation is implemented to fuse different levels of information. Finally, local spatial autocorrelation statistic is introduced to enhance the saliency of built-up features and an adaptive threshold algorithm is used to achieve the detection of built-up areas. Experiments are conducted on ZY-3 and Quickbird panchromatic satellite images, and the results show that the proposed method is very effective for built-up area detection.

Approaching bathymetry estimation from high resolution multispectral satellite images using a neuro-fuzzy technique

NASA Astrophysics Data System (ADS)

Corucci, Linda; Masini, Andrea; Cococcioni, Marco

2011-01-01

This paper addresses bathymetry estimation from high resolution multispectral satellite images by proposing an accurate supervised method, based on a neuro-fuzzy approach. The method is applied to two Quickbird images of the same area, acquired in different years and meteorological conditions, and is validated using truth data. Performance is studied in different realistic situations of in situ data availability. The method allows to achieve a mean standard deviation of 36.7 cm for estimated water depths in the range [-18, -1] m. When only data collected along a closed path are used as a training set, a mean STD of 45 cm is obtained. The effect of both meteorological conditions and training set size reduction on the overall performance is also investigated.

High-resolution land cover classification using low resolution global data

NASA Astrophysics Data System (ADS)

Carlotto, Mark J.

2013-05-01

A fusion approach is described that combines texture features from high-resolution panchromatic imagery with land cover statistics derived from co-registered low-resolution global databases to obtain high-resolution land cover maps. The method does not require training data or any human intervention. We use an MxN Gabor filter bank consisting of M=16 oriented bandpass filters (0-180°) at N resolutions (3-24 meters/pixel). The size range of these spatial filters is consistent with the typical scale of manmade objects and patterns of cultural activity in imagery. Clustering reduces the complexity of the data by combining pixels that have similar texture into clusters (regions). Texture classification assigns a vector of class likelihoods to each cluster based on its textural properties. Classification is unsupervised and accomplished using a bank of texture anomaly detectors. Class likelihoods are modulated by land cover statistics derived from lower resolution global data over the scene. Preliminary results from a number of Quickbird scenes show our approach is able to classify general land cover features such as roads, built up area, forests, open areas, and bodies of water over a wide range of scenes.

Radiometric Characterization of the IKONOS, QuickBird, and OrbView-3 Sensors

NASA Technical Reports Server (NTRS)

Holekamp, Kara

2006-01-01

Radiometric calibration of commercial imaging satellite products is required to ensure that science and application communities can better understand their properties. Inaccurate radiometric calibrations can lead to erroneous decisions and invalid conclusions and can limit intercomparisons with other systems. To address this calibration need, satellite at-sensor radiance values were compared to those estimated by each independent team member to determine the sensor's radiometric accuracy. The combined results of this evaluation provide the user community with an independent assessment of these commercially available high spatial resolution sensors' absolute calibration values.

Semi-automatic mapping of linear-trending bedforms using 'Self-Organizing Maps' algorithm

NASA Astrophysics Data System (ADS)

Foroutan, M.; Zimbelman, J. R.

2017-09-01

Increased application of high resolution spatial data such as high resolution satellite or Unmanned Aerial Vehicle (UAV) images from Earth, as well as High Resolution Imaging Science Experiment (HiRISE) images from Mars, makes it necessary to increase automation techniques capable of extracting detailed geomorphologic elements from such large data sets. Model validation by repeated images in environmental management studies such as climate-related changes as well as increasing access to high-resolution satellite images underline the demand for detailed automatic image-processing techniques in remote sensing. This study presents a methodology based on an unsupervised Artificial Neural Network (ANN) algorithm, known as Self Organizing Maps (SOM), to achieve the semi-automatic extraction of linear features with small footprints on satellite images. SOM is based on competitive learning and is efficient for handling huge data sets. We applied the SOM algorithm to high resolution satellite images of Earth and Mars (Quickbird, Worldview and HiRISE) in order to facilitate and speed up image analysis along with the improvement of the accuracy of results. About 98% overall accuracy and 0.001 quantization error in the recognition of small linear-trending bedforms demonstrate a promising framework.

High resolution remote sensing information identification for characterizing uranium mineralization setting in Namibia

NASA Astrophysics Data System (ADS)

Zhang, Jie-Lin; Wang, Jun-hu; Zhou, Mi; Huang, Yan-ju; Xuan, Yan-xiu; Wu, Ding

2011-11-01

The modern Earth Observation System (EOS) technology takes important role in the uranium geological exploration, and high resolution remote sensing as one of key parts of EOS is vital to characterize spectral and spatial information of uranium mineralization factors. Utilizing satellite high spatial resolution and hyperspectral remote sensing data (QuickBird, Radarsat2, ASTER), field spectral measurement (ASD data) and geological survey, this paper established the spectral identification characteristics of uranium mineralization factors including six different types of alaskite, lower and upper marble of Rössing formation, dolerite, alkali metasomatism, hematization and chloritization in the central zone of Damara Orogen, Namibia. Moreover, adopted the texture information identification technology, the geographical distribution zones of ore-controlling faults and boundaries between the different strata were delineated. Based on above approaches, the remote sensing geological anomaly information and image interpretation signs of uranium mineralization factors were extracted, the metallogenic conditions were evaluated, and the prospective areas have been predicted.

Estimation of the distribution of Tabebuia guayacan (Bignoniaceae) using high-resolution remote sensing imagery.

PubMed

Sánchez-Azofeifa, Arturo; Rivard, Benoit; Wright, Joseph; Feng, Ji-Lu; Li, Peijun; Chong, Mei Mei; Bohlman, Stephanie A

2011-01-01

Species identification and characterization in tropical environments is an emerging field in tropical remote sensing. Significant efforts are currently aimed at the detection of tree species, of levels of forest successional stages, and the extent of liana occurrence at the top of canopies. In this paper we describe our use of high resolution imagery from the Quickbird Satellite to estimate the flowering population of Tabebuia guayacan trees at Barro Colorado Island (BCI), in Panama. The imagery was acquired on 29 April 2002 and 21 March 2004. Spectral Angle Mapping via a One-Class Support Vector machine was used to detect the presence of 422 and 557 flowering tress in the April 2002 and March 2004 imagery. Of these, 273 flowering trees are common to both dates. This study presents a new perspective on the effectiveness of high resolution remote sensing for monitoring a phenological response and its use as a tool for potential conservation and management of natural resources in tropical environments.

Estimation of the Distribution of Tabebuia guayacan (Bignoniaceae) Using High-Resolution Remote Sensing Imagery

PubMed Central

Sánchez-Azofeifa, Arturo; Rivard, Benoit; Wright, Joseph; Feng, Ji-Lu; Li, Peijun; Chong, Mei Mei; Bohlman, Stephanie A.

2011-01-01

Species identification and characterization in tropical environments is an emerging field in tropical remote sensing. Significant efforts are currently aimed at the detection of tree species, of levels of forest successional stages, and the extent of liana occurrence at the top of canopies. In this paper we describe our use of high resolution imagery from the Quickbird Satellite to estimate the flowering population of Tabebuia guayacan trees at Barro Colorado Island (BCI), in Panama. The imagery was acquired on 29 April 2002 and 21 March 2004. Spectral Angle Mapping via a One-Class Support Vector machine was used to detect the presence of 422 and 557 flowering tress in the April 2002 and March 2004 imagery. Of these, 273 flowering trees are common to both dates. This study presents a new perspective on the effectiveness of high resolution remote sensing for monitoring a phenological response and its use as a tool for potential conservation and management of natural resources in tropical environments. PMID:22163825

High-Resolution Satellite Data Open for Government Research

NASA Technical Reports Server (NTRS)

Neigh, Christopher S. R.; Masek, Jeffrey G.; Nickeson, Jaime E.

2013-01-01

U.S. satellite commercial imagery (CI) with resolution less than 1 meter is a common geospatial reference used by the public through Web applications, mobile devices, and the news media. However, CI use in the scientific community has not kept pace, even though those who are performing U.S. government research have access to these data at no cost.Previously, studies using multiple CI acquisitions from IKONOS-2, Quickbird-2, GeoEye-1, WorldView-1, and WorldView-2 would have been cost prohibitive. Now, with near-global submeter coverage and online distribution, opportunities abound for future scientific studies. This archive is already quite extensive (examples are shown in Figure 1) and is being used in many novel applications.

Satellite image analysis for surveillance, vegetation and climate change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, D Michael

2011-01-18

Recently, many studies have provided abundant evidence to show the trend of tree mortality is increasing in many regions, and the cause of tree mortality is associated with drought, insect outbreak, or fire. Unfortunately, there is no current capability available to monitor vegetation changes, and correlate and predict tree mortality with CO{sub 2} change, and climate change on the global scale. Different survey platforms (methods) have been used for forest management. Typical ground-based forest surveys measure tree stem diameter, species, and alive or dead. The measurements are low-tech and time consuming, but the sample sizes are large, running into millionsmore » of trees, covering large areas, and spanning many years. These field surveys provide powerful ground validation for other survey methods such as photo survey, helicopter GPS survey, and aerial overview survey. The satellite imagery has much larger coverage. It is easier to tile the different images together, and more important, the spatial resolution has been improved such that close to or even higher than aerial survey platforms. Today, the remote sensing satellite data have reached sub-meter spatial resolution for panchromatic channels (IKONOS 2: 1 m; Quickbird-2: 0.61 m; Worldview-2: 0.5 m) and meter spatial resolution for multi-spectral channels (IKONOS 2: 4 meter; Quickbird-2: 2.44 m; Worldview-2: 2 m). Therefore, high resolution satellite imagery can allow foresters to discern individual trees. This vital information should allow us to quantify physiological states of trees, e.g. healthy or dead, shape and size of tree crowns, as well as species and functional compositions of trees. This is a powerful data resource, however, due to the vast amount of the data collected daily, it is impossible for human analysts to review the imagery in detail to identify the vital biodiversity information. Thus, in this talk, we will discuss the opportunities and challenges to use high resolution satellite imagery and machine learning theory to monitor tree mortality at the level of individual trees.« less

Impervious surfaces mapping using high resolution satellite imagery

NASA Astrophysics Data System (ADS)

Shirmeen, Tahmina

In recent years, impervious surfaces have emerged not only as an indicator of the degree of urbanization, but also as an indicator of environmental quality. As impervious surface area increases, storm water runoff increases in velocity, quantity, temperature and pollution load. Any of these attributes can contribute to the degradation of natural hydrology and water quality. Various image processing techniques have been used to identify the impervious surfaces, however, most of the existing impervious surface mapping tools used moderate resolution imagery. In this project, the potential of standard image processing techniques to generate impervious surface data for change detection analysis using high-resolution satellite imagery was evaluated. The city of Oxford, MS was selected as the study site for this project. Standard image processing techniques, including Normalized Difference Vegetation Index (NDVI), Principal Component Analysis (PCA), a combination of NDVI and PCA, and image classification algorithms, were used to generate impervious surfaces from multispectral IKONOS and QuickBird imagery acquired in both leaf-on and leaf-off conditions. Accuracy assessments were performed, using truth data generated by manual classification, with Kappa statistics and Zonal statistics to select the most appropriate image processing techniques for impervious surface mapping. The performance of selected image processing techniques was enhanced by incorporating Soil Brightness Index (SBI) and Greenness Index (GI) derived from Tasseled Cap Transformed (TCT) IKONOS and QuickBird imagery. A time series of impervious surfaces for the time frame between 2001 and 2007 was made using the refined image processing techniques to analyze the changes in IS in Oxford. It was found that NDVI and the combined NDVI--PCA methods are the most suitable image processing techniques for mapping impervious surfaces in leaf-off and leaf-on conditions respectively, using high resolution multispectral imagery. It was also found that IS data generated by these techniques can be refined by removing the conflicting dry soil patches using SBI and GI obtained from TCT of the same imagery used for IS data generation. The change detection analysis of the IS time series shows that Oxford experienced the major changes in IS from the year 2001 to 2004 and 2006 to 2007.

Quality evaluation of different fusion techniques applied on Worldview-2 data

NASA Astrophysics Data System (ADS)

Vaiopoulos, Aristides; Nikolakopoulos, Konstantinos G.

2015-10-01

In the current study a Worldview-2 image was used for fusion quality assessment. The bundle image was collected on July 2014 over Araxos area in Western Peloponnese. Worldview-2 is the first satellite that collects at the same time a panchromatic (Pan) image and 8 band multispectral (MS) image. The Pan data have a spatial resolution of 0.46m while the MS data have a spatial resolution of 1.84m. In contrary to the respective Pan band of Ikonos and Quickbird that range between 0.45 and 0.90 micrometers the Worldview Pan band is narrower and ranges between 0.45 and 0.8 micrometers. The MS bands include four conventional visible and near-infrared bands common to multispectral satellites like Ikonos Quickbird, Geoeye Landsat-7 etc., and four new bands. Thus, it is quite interesting to investigate the assessment of commonly used fusion algorithms with Worldview-2 data. Twelve fusion techniques and more especially the Ehlers, Gram-Schmidt, Color Normalized, High Pass Filter, Hyperspherical Color Space, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Modified IHS (ModIHS), Pansharp, Pansharp2, PCA and Wavelet were used for the fusion of Worldview-2 panchromatic and multispectral data. The optical result, the statistical parameters and different quality indexes such as ERGAS, Q and entropy difference were examined and the results are presented. The quality control was evaluated both in spectral and spatial domain.

Proceedings of the 2006 Civil Commercial Imagery Evaluation Workshop

NASA Technical Reports Server (NTRS)

Stanley, Thomas; Pagnutti, Mary

2007-01-01

The Joint Agency Commercial Imagery Evaluation (JACIE) team is a collaborative interagency working group formed to leverage different government agencies' capabilities for the characterization of commercial remote sensing products. The team is composed of staff from the National Aeronautics and Space Administration (NASA), the National Geospatial-Intelligence Agency (NGA), and the U.S. Geological Survey (USGS). Each JACIE agency has a vested interest in the purchase and use of commercial imagery to support government research and operational applications. The intent of the 2006 workshop is to exchange information regarding the characterization and application of commercial imagery used by the government. The main focus of previous workshops has been on high-resolution satellite imagery from systems; such as, IKONOS (Space Imaging, Inc.), QuickBird (DigitalGlobe, Inc.), and OrbView-3 (ORBIMAGE). This workshop is being expanded to cover all civil medium- and high-resolution commercial imagery used by the government.

Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery

PubMed Central

Tsai, Yu Hsin; Stow, Douglas; Weeks, John

2013-01-01

The goal of this study was to map and quantify the number of newly constructed buildings in Accra, Ghana between 2002 and 2010 based on high spatial resolution satellite image data. Two semi-automated feature detection approaches for detecting and mapping newly constructed buildings based on QuickBird very high spatial resolution satellite imagery were analyzed: (1) post-classification comparison; and (2) bi-temporal layerstack classification. Feature Analyst software based on a spatial contextual classifier and ENVI Feature Extraction that uses a true object-based image analysis approach of image segmentation and segment classification were evaluated. Final map products representing new building objects were compared and assessed for accuracy using two object-based accuracy measures, completeness and correctness. The bi-temporal layerstack method generated more accurate results compared to the post-classification comparison method due to less confusion with background objects. The spectral/spatial contextual approach (Feature Analyst) outperformed the true object-based feature delineation approach (ENVI Feature Extraction) due to its ability to more reliably delineate individual buildings of various sizes. Semi-automated, object-based detection followed by manual editing appears to be a reliable and efficient approach for detecting and enumerating new building objects. A bivariate regression analysis was performed using neighborhood-level estimates of new building density regressed on a census-derived measure of socio-economic status, yielding an inverse relationship with R2 = 0.31 (n = 27; p = 0.00). The primary utility of the new building delineation results is to support spatial analyses of land cover and land use and demographic change. PMID:24415810

Laboratory Measurement of Bidirectional Reflectance of Radiometric Tarps

NASA Technical Reports Server (NTRS)

Knowlton, Kelly

2006-01-01

Objectives: a) To determine the magnitude of radiometric tarp BRDF; b) To determine whether an ASD FieldSpec Pro spectroradiometer can be used to perform the experiment. Radiometric tarps with nominal reflectance values of 52%, 35%, and 3.5%, deployed for IKONOS. QuickBird, and OrbView-3 overpasses Ground-based spectroradiometric measurements of tarp and Spectralon@ panel taken during overpass using ASD FieldSpec Pro spectroradiometer, and tarp reflectance calculated. Reflectance data used in atmospheric radiative transfer model (MODTRAN) to predict satellite at-sensor radiance for radiometric calibration. Reflectance data also used to validate atmospheric correction of high-spatial-resolution multispectral image products

Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Tolpekin, Valentyn A.; Bijker, Wietske; Stein, Alfred

2011-11-01

Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches.

Depth Derivation from the Worldview-2 Satellite Using Hyperspectral Imagery

DTIC Science & Technology

2009-03-01

6 C. MULTISPECTRAL IMAGERY FROM QUICKBIRD ..............................7 D . HYPERSPECTRAL IMAGERY FROM AVIRIS...27 D . TRANSECTS .................................................................................................29 1. Transect 1...520-600nm), red (630-690nm) and near-IR (760-900nm). Figure 4. Quickbird Satellite (from: http://www.digitalglobe.com/index.php/85/QuickBird) D

Classification of Tree Species in Overstorey Canopy of Subtropical Forest Using QuickBird Images.

PubMed

Lin, Chinsu; Popescu, Sorin C; Thomson, Gavin; Tsogt, Khongor; Chang, Chein-I

2015-01-01

This paper proposes a supervised classification scheme to identify 40 tree species (2 coniferous, 38 broadleaf) belonging to 22 families and 36 genera in high spatial resolution QuickBird multispectral images (HMS). Overall kappa coefficient (OKC) and species conditional kappa coefficients (SCKC) were used to evaluate classification performance in training samples and estimate accuracy and uncertainty in test samples. Baseline classification performance using HMS images and vegetation index (VI) images were evaluated with an OKC value of 0.58 and 0.48 respectively, but performance improved significantly (up to 0.99) when used in combination with an HMS spectral-spatial texture image (SpecTex). One of the 40 species had very high conditional kappa coefficient performance (SCKC ≥ 0.95) using 4-band HMS and 5-band VIs images, but, only five species had lower performance (0.68 ≤ SCKC ≤ 0.94) using the SpecTex images. When SpecTex images were combined with a Visible Atmospherically Resistant Index (VARI), there was a significant improvement in performance in the training samples. The same level of improvement could not be replicated in the test samples indicating that a high degree of uncertainty exists in species classification accuracy which may be due to individual tree crown density, leaf greenness (inter-canopy gaps), and noise in the background environment (intra-canopy gaps). These factors increase uncertainty in the spectral texture features and therefore represent potential problems when using pixel-based classification techniques for multi-species classification.

Multi- and hyperspectral remote sensing of tropical marine benthic habitats

NASA Astrophysics Data System (ADS)

Mishra, Deepak R.

Tropical marine benthic habitats such as coral reef and associated environments are severely endangered because of the environmental degradation coupled with hurricanes, El Nino events, coastal pollution and runoff, tourism, and economic development. To monitor and protect this diverse environment it is important to not only develop baseline maps depicting their spatial distribution but also to document their changing conditions over time. Remote sensing offers an important means of delineating and monitoring coral reef ecosystems. Over the last twenty years the scientific community has been investigating the use and potential of remote sensing techniques to determine the conditions of the coral reefs by analyzing their spectral characteristics from space. One of the problems in monitoring coral reefs from space is the effect of the water column on the remotely sensed signal. When light penetrates water its intensity decreases exponentially with increasing depth. This process, known as water column attenuation, exerts a profound effect on remotely sensed data collected over water bodies. The approach presented in this research focuses on the development of semi-analytical models that resolves the confounding influence water column attenuation on substrate reflectance to characterize benthic habitats from high resolution remotely sensed imagery on a per-pixel basis. High spatial resolution satellite and airborne imagery were used as inputs in the models to derive water depth and water column optical properties (e.g., absorption and backscattering coefficients). These parameters were subsequently used in various bio-optical algorithms to deduce bottom albedo and then to classify the benthos, generating a detailed map of benthic habitats. IKONOS and QuickBird multispectral satellite data and AISA Eagle hyperspectral airborne data were used in this research for benthic habitat mapping along the north shore of Roatan Island, Honduras. The AISA Eagle classification was consistently more accurate (84%) including finer definition of geomorphological features than the satellite sensors. IKONOS (81%) and QuickBird (81%) sensors showed similar accuracy to AISA, however, such similarity was only reached at the coarse classification levels of 5 and 6 habitats. These results confirm the potential of an effective combination of high spectral and spatial resolution sensor, for accurate benthic habitat mapping.

An integrated approach for updating cadastral maps in Pakistan using satellite remote sensing data

NASA Astrophysics Data System (ADS)

Ali, Zahir; Tuladhar, Arbind; Zevenbergen, Jaap

2012-08-01

Updating cadastral information is crucial for recording land ownership and property division changes in a timely fashioned manner. In most cases, the existing cadastral maps do not provide up-to-date information on land parcel boundaries. Such a situation demands that all the cadastral data and parcel boundaries information in these maps to be updated in a timely fashion. The existing techniques for acquiring cadastral information are discipline-oriented based on different disciplines such as geodesy, surveying, and photogrammetry. All these techniques require a large number of manpower, time, and cost when they are carried out separately. There is a need to integrate these techniques for acquiring cadastral information to update the existing cadastral data and (re)produce cadastral maps in an efficient manner. To reduce the time and cost involved in cadastral data acquisition, this study develops an integrated approach by integrating global position system (GPS) data, remote sensing (RS) imagery, and existing cadastral maps. For this purpose, the panchromatic image with 0.6 m spatial resolution and the corresponding multi-spectral image with 2.4 m spatial resolution and 3 spectral bands from QuickBird satellite were used. A digital elevation model (DEM) was extracted from SPOT-5 stereopairs and some ground control points (GCPs) were also used for ortho-rectifying the QuickBird images. After ortho-rectifying these images and registering the multi-spectral image to the panchromatic image, fusion between them was attained to get good quality multi-spectral images of these two study areas with 0.6 m spatial resolution. Cadastral parcel boundaries were then identified on QuickBird images of the two study areas via visual interpretation using participatory-GIS (PGIS) technique. The regions of study are the urban and rural areas of Peshawar and Swabi districts in the Khyber Pakhtunkhwa province of Pakistan. The results are the creation of updated cadastral maps with a lot of cadastral information which can be used in updating the existing cadastral data with less time and cost.

[Remote sensing estimation of urban forest carbon stocks based on QuickBird images].

PubMed

Xu, Li-Hua; Zhang, Jie-Cun; Huang, Bo; Wang, Huan-Huan; Yue, Wen-Ze

2014-10-01

Urban forest is one of the positive factors that increase urban carbon sequestration, which makes great contribution to the global carbon cycle. Based on the high spatial resolution imagery of QuickBird in the study area within the ring road in Yiwu, Zhejiang, the forests in the area were divided into four types, i. e., park-forest, shelter-forest, company-forest and others. With the carbon stock from sample plot as dependent variable, at the significance level of 0.01, the stepwise linear regression method was used to select independent variables from 50 factors such as band grayscale values, vegetation index, texture information and so on. Finally, the remote sensing based forest carbon stock estimation models for the four types of forest were established. The estimation accuracies for all the models were around 70%, with the total carbon reserve of each forest type in the area being estimated as 3623. 80, 5245.78, 5284.84, 5343.65 t, respectively. From the carbon density map, it was found that the carbon reserves were mainly in the range of 25-35 t · hm(-2). In the future, urban forest planners could further improve the ability of forest carbon sequestration through afforestation and interplanting of trees and low shrubs.

Main Road Extraction from ZY-3 Grayscale Imagery Based on Directional Mathematical Morphology and VGI Prior Knowledge in Urban Areas

PubMed Central

Liu, Bo; Wu, Huayi; Wang, Yandong; Liu, Wenming

2015-01-01

Main road features extracted from remotely sensed imagery play an important role in many civilian and military applications, such as updating Geographic Information System (GIS) databases, urban structure analysis, spatial data matching and road navigation. Current methods for road feature extraction from high-resolution imagery are typically based on threshold value segmentation. It is difficult however, to completely separate road features from the background. We present a new method for extracting main roads from high-resolution grayscale imagery based on directional mathematical morphology and prior knowledge obtained from the Volunteered Geographic Information found in the OpenStreetMap. The two salient steps in this strategy are: (1) using directional mathematical morphology to enhance the contrast between roads and non-roads; (2) using OpenStreetMap roads as prior knowledge to segment the remotely sensed imagery. Experiments were conducted on two ZiYuan-3 images and one QuickBird high-resolution grayscale image to compare our proposed method to other commonly used techniques for road feature extraction. The results demonstrated the validity and better performance of the proposed method for urban main road feature extraction. PMID:26397832

On the use of wavelet for extracting feature patterns from Multitemporal google earth satellite data sets

NASA Astrophysics Data System (ADS)

Lasaponara, R.

2012-04-01

The great amount of multispectral VHR satellite images, even available free of charge in Google earth has opened new strategic challenges in the field of remote sensing for archaeological studies. These challenges substantially deal with: (i) the strategic exploitation of satellite data as much as possible, (ii) the setting up of effective and reliable automatic and/or semiautomatic data processing strategies and (iii) the integration with other data sources from documentary resources to the traditional ground survey, historical documentation, geophysical prospection, etc. VHR satellites provide high resolution data which can improve knowledge on past human activities providing precious qualitative and quantitative information developed to such an extent that currently they share many of the physical characteristics of aerial imagery. This makes them ideal for investigations ranging from a local to a regional scale (see. for example, Lasaponara and Masini 2006a,b, 2007a, 2011; Masini and Lasaponara 2006, 2007, Sparavigna, 2010). Moreover, satellite data are still the only data source for research performed in areas where aerial photography is restricted because of military or political reasons. Among the main advantages of using satellite remote sensing compared to traditional field archaeology herein we briefly focalize on the use of wavelet data processing for enhancing google earth satellite data with particular reference to multitemporal datasets. Study areas selected from Southern Italy, Middle East and South America are presented and discussed. Results obtained point out the use of automatic image enhancement can successfully applied as first step of supervised classification and intelligent data analysis for semiautomatic identification of features of archaeological interest. Reference Lasaponara R, Masini N (2006a) On the potential of panchromatic and multispectral Quickbird data for archaeological prospection. Int J Remote Sens 27: 3607-3614. Lasaponara R, Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological remains buried under vegetated and not vegetated areas. J Cult Heri 8 (1): 53-60. Sparavigna Enhancing the Google imagery using a wavelet filter, A.C. Sparavigna,http://arxiv.org/abs/1009.1590

Automated high resolution mapping of coffee in Rwanda using an expert Bayesian network

NASA Astrophysics Data System (ADS)

Mukashema, A.; Veldkamp, A.; Vrieling, A.

2014-12-01

African highland agro-ecosystems are dominated by small-scale agricultural fields that often contain a mix of annual and perennial crops. This makes such systems difficult to map by remote sensing. We developed an expert Bayesian network model to extract the small-scale coffee fields of Rwanda from very high resolution data. The model was subsequently applied to aerial orthophotos covering more than 99% of Rwanda and on one QuickBird image for the remaining part. The method consists of a stepwise adjustment of pixel probabilities, which incorporates expert knowledge on size of coffee trees and fields, and on their location. The initial naive Bayesian network, which is a spectral-based classification, yielded a coffee map with an overall accuracy of around 50%. This confirms that standard spectral variables alone cannot accurately identify coffee fields from high resolution images. The combination of spectral and ancillary data (DEM and a forest map) allowed mapping of coffee fields and associated uncertainties with an overall accuracy of 87%. Aggregated to district units, the mapped coffee areas demonstrated a high correlation with the coffee areas reported in the detailed national coffee census of 2009 (R2 = 0.92). Unlike the census data our map provides high spatial resolution of coffee area patterns of Rwanda. The proposed method has potential for mapping other perennial small scale cropping systems in the East African Highlands and elsewhere.

Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen; Li, Shutao

2015-12-01

The remote sensing image fusion is an important preprocessing technique in remote sensing image processing. In this paper, a remote sensing image fusion method based on the nonsubsampled shearlet transform (NSST) with sparse representation (SR) is proposed. Firstly, the low resolution multispectral (MS) image is upsampled and color space is transformed from Red-Green-Blue (RGB) to Intensity-Hue-Saturation (IHS). Then, the high resolution panchromatic (PAN) image and intensity component of MS image are decomposed by NSST to high and low frequency coefficients. The low frequency coefficients of PAN and the intensity component are fused by the SR with the learned dictionary. The high frequency coefficients of intensity component and PAN image are fused by local energy based fusion rule. Finally, the fused result is obtained by performing inverse NSST and inverse IHS transform. The experimental results on IKONOS and QuickBird satellites demonstrate that the proposed method provides better spectral quality and superior spatial information in the fused image than other remote sensing image fusion methods both in visual effect and object evaluation.

Radiometric Characterization Results for the IKONOS, Quickbird, and OrbView-3 Sensor

NASA Technical Reports Server (NTRS)

Holekamp, Kara; Aaron, David; Thome, Kurtis

2006-01-01

Radiometric calibration of commercial imaging satellite products is required to ensure that science and application communities better understand commercial imaging satellite properties. Inaccurate radiometric calibrations can lead to erroneous decisions and invalid conclusions and can limit intercomparisons with other systems. To address this calibration need, the NASA Applied Sciences Directorate (ASD) at Stennis Space Center established a commercial satellite imaging radiometric calibration team consisting of three independent groups: NASA ASD, the University of Arizona Remote Sensing Group, and South Dakota State University. Each group independently determined the absolute radiometric calibration coefficients of available high-spatial-resolution commercial 4-band multispectral products, in the visible though near-infrared spectrum, from GeoEye(tradeMark) (formerly SpaceImaging(Registered TradeMark)) IKONOS, DigitalGlobe(Regitered TradeMark) QuickBird, and GeoEye (formerly ORBIMAGE(Registered TradeMark) OrbView. Each team member employed some variant of reflectance-based vicarious calibration approach, requiring ground-based measurements coincident with image acquisitions and radiative transfer calculations. Several study sites throughout the United States that covered a significant portion of the sensor's dynamic range were employed. Satellite at-sensor radiance values were compared to those estimated by each independent team member to evaluate the sensor's radiometric accuracy. The combined results of this evaluation provide the user community with an independent assessment of these sensors' absolute calibration values.

Unsupervised individual tree crown detection in high-resolution satellite imagery

DOE PAGES

Skurikhin, Alexei N.; McDowell, Nate G.; Middleton, Richard S.

2016-01-26

Rapidly and accurately detecting individual tree crowns in satellite imagery is a critical need for monitoring and characterizing forest resources. We present a two-stage semiautomated approach for detecting individual tree crowns using high spatial resolution (0.6 m) satellite imagery. First, active contours are used to recognize tree canopy areas in a normalized difference vegetation index image. Given the image areas corresponding to tree canopies, we then identify individual tree crowns as local extrema points in the Laplacian of Gaussian scale-space pyramid. The approach simultaneously detects tree crown centers and estimates tree crown sizes, parameters critical to multiple ecosystem models. Asmore » a demonstration, we used a ground validated, 0.6 m resolution QuickBird image of a sparse forest site. The two-stage approach produced a tree count estimate with an accuracy of 78% for a naturally regenerating forest with irregularly spaced trees, a success rate equivalent to or better than existing approaches. In addition, our approach detects tree canopy areas and individual tree crowns in an unsupervised manner and helps identify overlapping crowns. Furthermore, the method also demonstrates significant potential for further improvement.« less

Unsupervised individual tree crown detection in high-resolution satellite imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skurikhin, Alexei N.; McDowell, Nate G.; Middleton, Richard S.

Rapidly and accurately detecting individual tree crowns in satellite imagery is a critical need for monitoring and characterizing forest resources. We present a two-stage semiautomated approach for detecting individual tree crowns using high spatial resolution (0.6 m) satellite imagery. First, active contours are used to recognize tree canopy areas in a normalized difference vegetation index image. Given the image areas corresponding to tree canopies, we then identify individual tree crowns as local extrema points in the Laplacian of Gaussian scale-space pyramid. The approach simultaneously detects tree crown centers and estimates tree crown sizes, parameters critical to multiple ecosystem models. Asmore » a demonstration, we used a ground validated, 0.6 m resolution QuickBird image of a sparse forest site. The two-stage approach produced a tree count estimate with an accuracy of 78% for a naturally regenerating forest with irregularly spaced trees, a success rate equivalent to or better than existing approaches. In addition, our approach detects tree canopy areas and individual tree crowns in an unsupervised manner and helps identify overlapping crowns. Furthermore, the method also demonstrates significant potential for further improvement.« less

Transfer of Technology for Cadastral Mapping in Tajikistan Using High Resolution Satellite Data

NASA Astrophysics Data System (ADS)

Kaczynski, R.

2012-07-01

European Commission funded project entitled: "Support to the mapping and certification capacity of the Agency of Land Management, Geodesy and Cartography" in Tajikistan was run by FINNMAP FM-International and Human Dynamics from Nov. 2006 to June 2011. The Agency of Land Management, Geodesy and Cartography is the state agency responsible for development, implementation, monitoring and evaluation of state policies on land tenure and land management, including the on-going land reform and registration of land use rights. The specific objective was to support and strengthen the professional capacity of the "Fazo" Institute in the field of satellite geodesy, digital photogrammetry, advanced digital satellite image processing of high resolution satellite data and digital cartography. Lectures and on-the-job trainings for the personnel of "Fazo" and Agency in satellite geodesy, digital photogrammetry, cartography and the use of high resolution satellite data for cadastral mapping have been organized. Standards and Quality control system for all data and products have been elaborated and implemented in the production line. Technical expertise and trainings in geodesy, photogrammetry and satellite image processing to the World Bank project "Land Registration and Cadastre System for Sustainable Agriculture" has also been completed in Tajikistan. The new map projection was chosen and the new unclassified geodetic network has been established for all of the country in which all agricultural parcel boundaries are being mapped. IKONOS, QuickBird and WorldView1 panchromatic data have been used for orthophoto generation. Average accuracy of space triangulation of non-standard (long up to 90km) satellite images of QuickBird Pan and IKONOS Pan on ICPs: RMSEx = 0.5m and RMSEy = 0.5m have been achieved. Accuracy of digital orthophoto map is RMSExy = 1.0m. More then two and half thousands of digital orthophoto map sheets in the scale of 1:5000 with pixel size 0.5m have been produced so far by the "Fazo" Institute in Tajikistan on the basis of technology elaborated in the framework of this project. Digital cadastral maps are produced in "Fazo" and Cadastral Regional Centers in Tajikistan using ArcMap software. These digital orthophotomaps will also be used for digital mapping of water resources and other needs of the country.

Multispectral Resampling of Seagrass Species Spectra: WorldView-2, Quickbird, Sentinel-2A, ASTER VNIR, and Landsat 8 OLI

NASA Astrophysics Data System (ADS)

Wicaksono, Pramaditya; Salivian Wisnu Kumara, Ignatius; Kamal, Muhammad; Afif Fauzan, Muhammad; Zhafarina, Zhafirah; Agus Nurswantoro, Dwi; Noviaris Yogyantoro, Rifka

2017-12-01

Although spectrally different, seagrass species may not be able to be mapped from multispectral remote sensing images due to the limitation of their spectral resolution. Therefore, it is important to quantitatively assess the possibility of mapping seagrass species using multispectral images by resampling seagrass species spectra to multispectral bands. Seagrass species spectra were measured on harvested seagrass leaves. Spectral resolution of multispectral images used in this research was adopted from WorldView-2, Quickbird, Sentinel-2A, ASTER VNIR, and Landsat 8 OLI. These images are widely available and can be a good representative and baseline for previous or future remote sensing images. Seagrass species considered in this research are Enhalus acoroides (Ea), Thalassodendron ciliatum (Tc), Thalassia hemprichii (Th), Cymodocea rotundata (Cr), Cymodocea serrulata (Cs), Halodule uninervis (Hu), Halodule pinifolia (Hp), Syringodum isoetifolium (Si), Halophila ovalis (Ho), and Halophila minor (Hm). Multispectral resampling analysis indicate that the resampled spectra exhibit similar shape and pattern with the original spectra but less precise, and they lose the unique absorption feature of seagrass species. Relying on spectral bands alone, multispectral image is not effective in mapping these seagrass species individually, which is shown by the poor and inconsistent result of Spectral Angle Mapper (SAM) classification technique in classifying seagrass species using seagrass species spectra as pure endmember. Only Sentinel-2A produced acceptable classification result using SAM.

Feature Selection for Object-Based Classification of High-Resolution Remote Sensing Images Based on the Combination of a Genetic Algorithm and Tabu Search

PubMed Central

Shi, Lei; Wan, Youchuan; Gao, Xianjun

2018-01-01

In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA) and tabu search (TS) is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS. A prematurity index is first defined to judge the convergence situation during the search. When premature convergence does take place, an improved mutation operator is executed, in which TS is performed on individuals with higher fitness values. As for the other individuals with lower fitness values, mutation with a higher probability is carried out. Experiments using the proposed GATS feature selection method and three other methods, a standard GA, the multistart TS method, and ReliefF, were conducted on WorldView-2 and QuickBird images. The experimental results showed that the proposed method outperforms the other methods in terms of the final classification accuracy. PMID:29581721

Colour space influence for vegetation image classification application to Caribbean forest and agriculture

NASA Astrophysics Data System (ADS)

Abadi, M.; Grandchamp, E.

2008-10-01

This paper deals with a comparison of different colour space in order to improve high resolution images classification. The background of this study is the measure of the agriculture impact on the environment in islander context. Biodiversity is particularly sensitive and relevant in such areas and the follow-up of the forest front is a way to ensure its preservation. Very high resolution satellite images are used such as QuickBird and IKONOS scenes. In order to segment the images into forest and agriculture areas, we characterize both ground covers with colour and texture features. A classical unsupervised classifier is then used to obtain labelled areas. As features are computed on coloured images, we can wonder if the colour space choice is relevant. This study has been made considering more than fourteen colour spaces (RGB, YUV, Lab, YIQ, YCrCs, XYZ, CMY, LMS, HSL, KLT, IHS, I1I2I3, HSV, HSI, etc.) and shows the visual and quantitative superiority of IHS on all others. For conciseness reasons, results only show RGB, I1I2I3 and IHS colour spaces.

Pan-sharpening via compressed superresolution reconstruction and multidictionary learning

NASA Astrophysics Data System (ADS)

Shi, Cheng; Liu, Fang; Li, Lingling; Jiao, Licheng; Hao, Hongxia; Shang, Ronghua; Li, Yangyang

2018-01-01

In recent compressed sensing (CS)-based pan-sharpening algorithms, pan-sharpening performance is affected by two key problems. One is that there are always errors between the high-resolution panchromatic (HRP) image and the linear weighted high-resolution multispectral (HRM) image, resulting in spatial and spectral information lost. The other is that the dictionary construction process depends on the nontruth training samples. These problems have limited applications to CS-based pan-sharpening algorithm. To solve these two problems, we propose a pan-sharpening algorithm via compressed superresolution reconstruction and multidictionary learning. Through a two-stage implementation, compressed superresolution reconstruction model reduces the error effectively between the HRP and the linear weighted HRM images. Meanwhile, the multidictionary with ridgelet and curvelet is learned for both the two stages in the superresolution reconstruction process. Since ridgelet and curvelet can better capture the structure and directional characteristics, a better reconstruction result can be obtained. Experiments are done on the QuickBird and IKONOS satellites images. The results indicate that the proposed algorithm is competitive compared with the recent CS-based pan-sharpening methods and other well-known methods.

Future Applications of Remote Sensing to Archeological Research

NASA Technical Reports Server (NTRS)

Sever, Thomas L.

2003-01-01

Archeology was one of the first disciplines to use aerial photography in its investigations at the turn of the 20th century. However, the low resolution of satellite technology that became available in the 1970 s limited their application to regional studies. That has recently changed. The arrival of the high resolution, multi-spectral capabilities of the IKONOS and QUICKBIRD satellites and the scheduled launch of new satellites in the next few years provides an unlimited horizon for future archeological research. In addition, affordable aerial and ground-based remote sensing instrumentation are providing archeologists with information that is not available through traditional methodologies. Although many archeologists are not yet comfortable with remote sensing technology a new generation has embraced it and is accumulating a wealth of new evidence. They have discovered that through the use of remote sensing it is possible to gather information without disturbing the site and that those cultural resources can be monitored and protected for the future.

Multi-scale investigation of shrub encroachment in southern Africa

NASA Astrophysics Data System (ADS)

Aplin, Paul; Marston, Christopher; Wilkinson, David; Field, Richard; O'Regan, Hannah

2016-04-01

There is growing speculation that savannah environments throughout Africa have been subject to shrub encroachment in recent years, whereby grassland is lost to woody vegetation cover. Changes in the relative proportions of grassland and woodland are important in the context of conservation of savannah systems, with implications for faunal distributions, environmental management and tourism. Here, we focus on southern Kruger National Park, South Africa, and investigate whether or not shrub encroachment has occurred over the last decade and a half. We use a multi-scale approach, examining the complementarity of medium (e.g. Landsat TM and OLI) and fine (e.g. QuickBird and WorldView-2) spatial resolution satellite sensor imagery, supported by intensive field survey in 2002 and 2014. We employ semi-automated land cover classification, involving a hybrid unsupervised clustering approach with manual class grouping and checking, followed by change detection post-classification comparison analysis. The results show that shrub encroachment is indeed occurring, a finding evidenced through three fine resolution replicate images plus medium resolution imagery. The results also demonstrate the complementarity of medium and fine resolution imagery, though some thematic information must be sacrificed to maintain high medium resolution classification accuracy. Finally, the findings have broader implications for issues such as vegetation seasonality, spatial transferability and management practices.

Radiometric and Spatial Characterization of High-Spatial Resolution Sensors

NASA Technical Reports Server (NTRS)

Thome, Kurtis; Zanoni, Vicki (Technical Monitor)

2002-01-01

The development and improvement of commercial hyperspatial sensors in recent years has increased the breadth of information that can be retrieved from spaceborne and airborne imagery. NASA, through it's Scientific Data Purchases, has successfully provided such data sets to its user community. A key element to the usefulness of these data are an understanding of the radiometric and spatial response quality of the imagery. This proposal seeks funding to examine the absolute radiometric calibration of the Ikonos sensor operated by Space Imaging and the recently-launched Quickbird sensor from DigitalGlobe. In addition, we propose to evaluate the spatial response of the two sensors. The proposed methods rely on well-understood, ground-based targets that have been used by the University of Arizona for more than a decade.

Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations

USGS Publications Warehouse

Cook, B.D.; Bolstad, P.V.; Naesset, E.; Anderson, R. Scott; Garrigues, S.; Morisette, J.T.; Nickeson, J.; Davis, K.J.

2009-01-01

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30??m to 1??km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600??ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400??m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

Using LIDAR and Quickbird Data to Model Plant Production and Quantify Uncertainties Associated with Wetland Detection and Land Cover Generalizations

NASA Technical Reports Server (NTRS)

Cook, Bruce D.; Bolstad, Paul V.; Naesset, Erik; Anderson, Ryan S.; Garrigues, Sebastian; Morisette, Jeffrey T.; Nickeson, Jaime; Davis, Kenneth J.

2009-01-01

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the MOderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

Determining Trends in Impervious Cover for the Mobile Bay, AL Region for 1974-2008, Based on a Landsat Time Series

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Smoot, James; Ellis, Jean; Swann, Roberta

2011-01-01

This presentation will discuss the development and use of Landsat-based impervious cover products in conjunction with land use land cover change products to assess multi-decadal urbanization across the Mobile Bay region at regional and watershed scales. This nationally important coastal region has undergone a variety of ephemeral and permanent land use land cover change since the mid-1970s, including gradual but consequential increases in urban surface cover. This urban sprawl corresponds with increased regional percent impervious cover. The region s coastal zone managers are concerned about the increasing percent impervious cover, since it can negatively influence water quality and is an important consideration for coastal conservation and restoration work. In response, we processed multi-temporal Landsat data to compute maps of percent impervious cover for multiple dates from 1974 through 2008, roughly at 5-year intervals. Each year of product was classified using one single date of leaf-on and leaf-off Landsat data in conjunction with Cubist software. We are assessing Landsat impervious cover product accuracy through comparisons to available reference data, including available NLCD impervious cover products from the USGS, raw Landsat data, plus higher spatial resolution aerial and satellite data. In particular, we are quantitatively comparing the 2008 Landsat impervious cover products to those from QuickBird 2.4-meter multispectral data. Initial visual comparisons with the QuickBird impervious cover product suggest that the 2008 Landsat product tends to underestimate impervious cover for high density urban areas and to overestimate impervious cover in established residential subdivisions mixed with forested cover. Landsat TM and ETM data appears to produce more accurate impervious cover products compared to those using lower resolution Landsat MSS data. Although imperfect, these Landsat impervious cover products have helped the Mobile Bay National Estuary Program visualize basic urbanization trends for multiple HUC-12 watersheds of concern to them and their constituents

Land Cover Change in Colombia: Surprising Forest Recovery Trends between 2001 and 2010

PubMed Central

Sánchez-Cuervo, Ana María; Aide, T. Mitchell; Clark, Matthew L.; Etter, Andrés

2012-01-01

Background Monitoring land change at multiple spatial scales is essential for identifying hotspots of change, and for developing and implementing policies for conserving biodiversity and habitats. In the high diversity country of Colombia, these types of analyses are difficult because there is no consistent wall-to-wall, multi-temporal dataset for land-use and land-cover change. Methodology/Principal Findings To address this problem, we mapped annual land-use and land-cover from 2001 to 2010 in Colombia using MODIS (250 m) products coupled with reference data from high spatial resolution imagery (QuickBird) in Google Earth. We used QuickBird imagery to visually interpret percent cover of eight land cover classes used for classifier training and accuracy assessment. Based on these maps we evaluated land cover change at four spatial scales country, biome, ecoregion, and municipality. Of the 1,117 municipalities, 820 had a net gain in woody vegetation (28,092 km2) while 264 had a net loss (11,129 km2), which resulted in a net gain of 16,963 km2 in woody vegetation at the national scale. Woody regrowth mainly occurred in areas previously classified as mixed woody/plantation rather than agriculture/herbaceous. The majority of this gain occurred in the Moist Forest biome, within the montane forest ecoregions, while the greatest loss of woody vegetation occurred in the Llanos and Apure-Villavicencio ecoregions. Conclusions The unexpected forest recovery trend, particularly in the Andes, provides an opportunity to expand current protected areas and to promote habitat connectivity. Furthermore, ecoregions with intense land conversion (e.g. Northern Andean Páramo) and ecoregions under-represented in the protected area network (e.g. Llanos, Apure-Villavicencio Dry forest, and Magdalena-Urabá Moist forest ecoregions) should be considered for new protected areas. PMID:22952816

Quickbird Geometry Report for Summer 2003

NASA Technical Reports Server (NTRS)

Darbha, Ravikanth; Helder, Dennis; Choi, Taeyoung

2005-01-01

Digital Globe provides for general use 2.4 m multi-spectral and 0.7 m panchromatic imagery acquired by the Quickbird satellite. This geometrically corrected imagery was obtained as standard and orthorectified products; the difference between the two products is primarily in the degree of geometric accuracy that Digital Globe claims. For both products, every image pixel contains estimated sets of Northing/Easting and lat/long coordinates accessible through an image display application such as ENVI. Ground processing was performed by Digital Globe using the ADP 2.1 version of their system. Analysis conducted at South Dakota State University attempted to verify the geometric accuracy of standard and orthorectified Quickbird imagery to determine if specifications for the NASA Science Data Purchase (SDP) were met. These specifications are in Table 1 of Appendix 1. In this analysis, we had approximately 90 Ground Control Points (varies depending on scene size on each date), uniformly distributed over the Brookings, SD, area, from 4 Quickbird scenes acquired August 23, September 15, and October 21 of 2003.

Automatic Co-Registration of QuickBird Data for Change Detection Applications

NASA Technical Reports Server (NTRS)

Bryant, Nevin A.; Logan, Thomas L.; Zobrist, Albert L.

2006-01-01

This viewgraph presentation reviews the use Automatic Fusion of Image Data System (AFIDS) for Automatic Co-Registration of QuickBird Data to ascertain if changes have occurred in images. The process is outlined, and views from Iraq and Los Angelels are shown to illustrate the process.

Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete.

PubMed

Karydas, Christos G; Sekuloska, Tijana; Silleos, Georgios N

2009-02-01

Due to inappropriate agricultural management practices, soil erosion is becoming one of the most dangerous forms of soil degradation in many olive farming areas in the Mediterranean region, leading to significant decrease of soil fertility and yield. In order to prevent further soil degradation, proper measures are necessary to be locally implemented. In this perspective, an increase in the spatial accuracy of remote sensing datasets and advanced image analysis are significant tools necessary and efficient for mapping soil erosion risk on a fine scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) was implemented in the spatial domain using GIS, while a very high resolution satellite image, namely a QuickBird image, was used for deriving cover management (C) and support practice (P) factors, in order to map the risk of soil erosion in Kolymvari, a typical olive farming area in the island of Crete, Greece. The results comprised a risk map of soil erosion when P factor was taken uniform (conventional approach) and a risk map when P factor was quantified site-specifically using object-oriented image analysis. The results showed that the QuickBird image was necessary in order to achieve site-specificity of the P factor and therefore to support fine scale mapping of soil erosion risk in an olive cultivation area, such as the one of Kolymvari in Crete. Increasing the accuracy of the QB image classification will further improve the resulted soil erosion mapping.

Extending a prototype knowledge- and object-based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

USGS Publications Warehouse

Strong, Laurence L.

2012-01-01

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

USGS Publications Warehouse

Strong, Laurence L.

2012-01-01

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Land area change analysis following hurricane impacts in Delacroix, Louisiana, 2004--2009

USGS Publications Warehouse

Palaseanu-Lovejoy, Monica; Kranenburg, Christine J.; Brock, John C.

2012-01-01

The purpose of this project is to provide improved estimates of Louisiana wetland land loss due to hurricane impacts between 2004 and 2009 based upon a change detection mapping analysis that incorporates pre- and post-landfall (Hurricanes Katrina, Rita, Gustav, and Ike) fractional water classification of a combination of high resolution (QuickBird, IKONOS and Geoeye-1) and medium resolution (Landsat) satellite imagery. This second dataset focuses on Hurricanes Katrina and Gustav, which made landfall on August 29, 2005, and September 1, 2008, respectively. The study area is an approximately 1208-square-kilometer region surrounding Delacroix, Louisiana, in the eastern Delta Plain. Overall, 77 percent of the area remained unchanged between 2004 and 2009, and over 11 percent of the area was changed permanently by Hurricane Katrina (including both land gain and loss). Less than 3 percent was affected, either temporarily or permanently, by Hurricane Gustav. A related dataset (SIM 3141) focused on Hurricane Rita, which made landfall on the Louisiana/Texas border on September 24, 2005, as a Category 3 hurricane.

Measurement Sets and Sites Commonly Used for Characterization

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert; Sellers, Richard; Davis, Bruce; Zanoni, Vicki

2002-01-01

Scientists at NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center. This site enables the in-flight characterization of remote sensing systems and the data they acquire. The data are predominantly acquired by commercial, high spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active LIDAR systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible through long-wave infrared remote sensing systems and a description of the Stennis characterization. Other topics discussed include: 1) The use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations; 2) Additional sites used for radiometric, geometric, and spatial characterization in the continental United States; 3) The need for a standardized technique to be adopted by CEOS and other organizations.

Measurement Sets and Sites Commonly used for Characterizations

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert; Blonski, Slawomir; Sellers, Richard; Davis, Bruce; Zanoni, Vicki

2002-01-01

Scientists with NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center (SSC). This site enables the in-flight characterization of remote sensing systems and the data that they require. The data are predominantly acquired by commercial, high-spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high-resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active Light Detection and Ranging (LIDAR) systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible-through-longwave infrared remote sensing systems, and a description of the Stennis characterization. Other topics discussed inslude: 1) use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations, 2) other sites used for radiometric, geometric, and spatial characterization in the continental United States,a nd 3) the need for a standardized technique to be adopted by the Committee on Earth Observation Satellites (CEOS) and other organizations.

An efficient mosaic algorithm considering seasonal variation: application to KOMPSAT-2 satellite images.

PubMed

Choi, Jaewon; Jung, Hyung-Sup; Yun, Sang-Ho

2015-03-09

As the aerospace industry grows, images obtained from Earth observation satellites have been successfully used in various fields. Specifically, the demand for a high-resolution (HR) optical images is gradually increasing, and hence the generation of a high-quality mosaic image is being magnified as an interesting issue. In this paper, we have proposed an efficient mosaic algorithm for HR optical images that are significantly different due to seasonal change. The algorithm includes main steps such as: (1) seamline extraction from gradient magnitude and seam images; (2) histogram matching; and (3) image feathering. Eleven Kompsat-2 images characterized by seasonal variations are used for the performance validation of the proposed method. The results of the performance test show that the proposed method effectively mosaics Kompsat-2 adjacent images including severe seasonal changes. Moreover, the results reveal that the proposed method is applicable to HR optic images such as GeoEye, IKONOS, QuickBird, RapidEye, SPOT, WorldView, etc.

Mapping Spatial Variability in Health and Wealth Indicators in Accra, Ghana Using High Spatial Resolution Imagery

NASA Astrophysics Data System (ADS)

Engstrom, R.; Ashcroft, E.

2014-12-01

There has been a tremendous amount of research conducted that examines disparities in health and wealth of persons between urban and rural areas however, relatively little research has been undertaken to examine variations within urban areas. A major limitation to elucidating differences with urban areas is the lack of social and demographic data at a sufficiently high spatial resolution to determine these differences. Generally the only available data that contain this information are census data which are collected at most every ten years and are often difficult to obtain at a high enough spatial resolution to allow for examining in depth variability in health and wealth indicators at high spatial resolutions, especially in developing countries. High spatial resolution satellite imagery may be able to provide timely and synoptic information that is related to health and wealth variability within a city. In this study we use two dates of Quickbird imagery (2003 and 2010) classified into the vegetation-impervious surface-soil (VIS) model introduced by Ridd (1995). For 2003 we only have partial coverage of the city, while for 2010 we have a mosaic, which covers the entire city of Accra, Ghana. Variations in the VIS values represent the physical variations within the city and these are compared to variations in economic, and/or sociodemographic data derived from the 2000 Ghanaian census at two spatial resolutions, the enumeration area (approximately US Census Tract) and the neighborhood for the city. Results indicate a significant correlation between both vegetation and impervious surface to type of cooking fuel used in the household, population density, housing density, availability of sewers, cooking space usage, and other variables. The correlations are generally stronger at the neighborhood level and the relationships are stable through time and space. Overall, the results indicate that information derived from high resolution satellite data is related to indicators of health and wealth within a developing world city and that the even if the imagery is collected 10 years after the census information, the relationships are still significant.

Old high resolution satellite images for landscape archaeology: case studies from Turkey and Iraq

NASA Astrophysics Data System (ADS)

Scardozzi, Giuseppe

2008-10-01

The paper concerns the contribution for Landscape Archaeology from satellite images of 1960s and 1970s, very useful when old aerial photographs are scarce. Particularly, the study concerns the panchromatic photos taken by USA reconnaissance satellites from 1963 to 1972, declassified for civil use in 1995 and 2002, that in the last years are very used in the archaeological research; in fact, a lot of these images have an high geometric resolution, about between 2.74 and 1.83 m (Corona KH-4A and KH-4B), and some have a ground resolution about between 1.20 and 0.60 m (Gambit KH-7). These satellite images allow to examine very in detail ancient urban areas and territories that later are changed or partially destroyed; so, it is possible to detect and examine ancient structures, palaeo-environmental elements and archaeological traces of buried features now not visible. The paper presents some exemplificative cases study in Turkey and Iraq, in which the analysis of these images has made a fundamental contribution to the archaeological researches: particularly, for the reconstruction of the urban layout of the ancient city of Hierapolis of Phrygia and for the surveys in its territory, and for the study of the ancient topography of some archaeological sites of Iraq. In this second case, the research is gained in the context of the Iraq Virtual Museum Project; the comparison with recent high resolution satellite images (Ikonos-2, QuickBird-2, WorldView-1) also provide a fundamental tool for monitoring archaeological areas and for an evaluation of the situation after the first and the second Gulf War.

a Novel Ihs-Ga Fusion Method Based on Enhancement Vegetated Area

NASA Astrophysics Data System (ADS)

Niazi, S.; Mokhtarzade, M.; Saeedzadeh, F.

2015-12-01

Pan sharpening methods aim to produce a more informative image containing the positive aspects of both source images. However, the pan sharpening process usually introduces some spectral and spatial distortions in the resulting fused image. The amount of these distortions varies highly depending on the pan sharpening technique as well as the type of data. Among the existing pan sharpening methods, the Intensity-Hue-Saturation (IHS) technique is the most widely used for its efficiency and high spatial resolution. When the IHS method is used for IKONOS or QuickBird imagery, there is a significant color distortion which is mainly due to the wavelengths range of the panchromatic image. Regarding the fact that in the green vegetated regions panchromatic gray values are much larger than the gray values of intensity image. A novel method is proposed which spatially adjusts the intensity image in vegetated areas. To do so the normalized difference vegetation index (NDVI) is used to identify vegetation areas where the green band is enhanced according to the red and NIR bands. In this way an intensity image is obtained in which the gray values are comparable to the panchromatic image. Beside the genetic optimization algorithm is used to find the optimum weight parameters in order to gain the best intensity image. Visual and statistical analysis proved the efficiency of the proposed method as it significantly improved the fusion quality in comparison to conventional IHS technique. The accuracy of the proposed pan sharpening technique was also evaluated in terms of different spatial and spectral metrics. In this study, 7 metrics (Correlation Coefficient, ERGAS, RASE, RMSE, SAM, SID and Spatial Coefficient) have been used in order to determine the quality of the pan-sharpened images. Experiments were conducted on two different data sets obtained by two different imaging sensors, IKONOS and QuickBird. The result of this showed that the evaluation metrics are more promising for our fused image in comparison to other pan sharpening methods.

Mapping of Geographically Isolated Wetlands of Western Siberia Using High Resolution Space Images

NASA Astrophysics Data System (ADS)

Dyukarev, E.; Pologova, N.; Dyukarev, A.; Lane, C.; Autrey, B. C.

2014-12-01

Using the remote sensing data for integrated study of natural objects is actual for investigation of difficult to access areas of West Siberia. The research of this study focuses on determining the extent and spectral signatures of isolated wetlands within Ob-Tom Interfluve area using Landsat and Quickbird space images. High-resolution space images were carefully examined and wetlands were manually delineated. Wetlands have clear visible signs at the high resolution space images. 567 wetlands were recognized as isolated wetlands with the area about 10 000 ha (of 2.5% of the study area). Isolated wetlands with area less 2 ha are the most frequent. Half of the total amount of wetlands has area less than 6.4 ha. The largest isolated wetland occupies 797 ha, and only 5% have area more than 50 ha. The Landsat 7 ETM+ data were used for analysis of vegetation structure and spectral characteristics of wetlands. The masked isolated wetlands image was classified into 12 land cover classes using ISODATA unsupervised classification. The attribution of unsupervised classification results allowed us to clearly recognize 7 types of wetlands: tall, low and sparse ryams (Pine-Shrub-Sphagnum community), open wetlands with shrub, moss or sedge cover, and open water objects. Analysis of spectral profiles for all classes has shown that Landsat spectral bands 4 and 5 have higher variability. These bands allow to separate wetland classed definitely. Accuracy assessment of isolated wetland map shows a good agreement with expert field data. The work was supported by grants ISTC № 4079.

Impervious surface mapping with Quickbird imagery

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio

2010-01-01

This research selects two study areas with different urban developments, sizes, and spatial patterns to explore the suitable methods for mapping impervious surface distribution using Quickbird imagery. The selected methods include per-pixel based supervised classification, segmentation-based classification, and a hybrid method. A comparative analysis of the results indicates that per-pixel based supervised classification produces a large number of “salt-and-pepper” pixels, and segmentation based methods can significantly reduce this problem. However, neither method can effectively solve the spectral confusion of impervious surfaces with water/wetland and bare soils and the impacts of shadows. In order to accurately map impervious surface distribution from Quickbird images, manual editing is necessary and may be the only way to extract impervious surfaces from the confused land covers and the shadow problem. This research indicates that the hybrid method consisting of thresholding techniques, unsupervised classification and limited manual editing provides the best performance. PMID:21643434

Multitemporal satellite change detection investigations for documentation and valorization of cultural landscape

NASA Astrophysics Data System (ADS)

Lasaponara, R.; Masini, n.

2012-04-01

The paper focus on the setting up of a methodology for analyzing cultural landscapes to extract information about ancient civilization settlements, land-use variations, stratified anthropogenic environment, human impacts on landscape, as well as climate driven changes over short, medium, and long periods of time. The analysis of cultural landscape along with its protection and preservation strategies requires the contribution of integrated disciplines and data source, and, above all, the fusion of multi-temporal and multi dimensional data available from different sources. In this contest satellite time series may help us in improve knowledge content of cultural landscape and heritage . The methodology approach we devised is focused on multitemporal/multisource/multiscale data analysis as a support for extracting (i) archaeological settlements and (ii) potential ancient land-use patterning. To these aims, DTM from SRTM and ASTER along multispectral data from TM, ASTER and Quikbird have been used. In order to make the satellite data more meaningful and more exploitable for investigations, reliable data processing have been carried out. Over the years a great variety of digital image enhancement techniques have been devised for specific application fields according to data availability. Nevertheless, only recently these methods have captured great attention also in the field of archaeology for an easier extraction of quantitative information using effective and reliable semiautomatic data processing. The setting up of fully-automatic methodologies is a big challenge to be strategically addressed by research communities in the next years. Multitemporal, multiscale and multisensor satellite data sets can provide useful tool for extracting information and traces related both to modern and ancient civilizations still fossilized in the modern landscape. Reference Lasaponara R, Masini N (2006a) On the potential of panchromatic and multispectral Quickbird data for archaeological prospection. Int J Remote Sens 27: 3607-3614. Lasaponara R, Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological remains buried under vegetated and not vegetated areas. J Cult Heri 8 (1): 53-60.

Rapid Disaster Damage Estimation

NASA Astrophysics Data System (ADS)

Vu, T. T.

2012-07-01

The experiences from recent disaster events showed that detailed information derived from high-resolution satellite images could accommodate the requirements from damage analysts and disaster management practitioners. Richer information contained in such high-resolution images, however, increases the complexity of image analysis. As a result, few image analysis solutions can be practically used under time pressure in the context of post-disaster and emergency responses. To fill the gap in employment of remote sensing in disaster response, this research develops a rapid high-resolution satellite mapping solution built upon a dual-scale contextual framework to support damage estimation after a catastrophe. The target objects are building (or building blocks) and their condition. On the coarse processing level, statistical region merging deployed to group pixels into a number of coarse clusters. Based on majority rule of vegetation index, water and shadow index, it is possible to eliminate the irrelevant clusters. The remaining clusters likely consist of building structures and others. On the fine processing level details, within each considering clusters, smaller objects are formed using morphological analysis. Numerous indicators including spectral, textural and shape indices are computed to be used in a rule-based object classification. Computation time of raster-based analysis highly depends on the image size or number of processed pixels in order words. Breaking into 2 level processing helps to reduce the processed number of pixels and the redundancy of processing irrelevant information. In addition, it allows a data- and tasks- based parallel implementation. The performance is demonstrated with QuickBird images captured a disaster-affected area of Phanga, Thailand by the 2004 Indian Ocean tsunami are used for demonstration of the performance. The developed solution will be implemented in different platforms as well as a web processing service for operational uses.

Aerosol Optical Depth Retrievals From High-Resolution Commercial Satellite Imagery Over Areas of High Surface Reflectance

NASA Astrophysics Data System (ADS)

Vincent, D. A.; Nielsen, K. E.; Durkee, P. A.; Reid, J. S.

2005-12-01

The advancement and proliferation of high-resolution commercial imaging satellites presents a new opportunity for overland aerosol characterization. Current aerosol optical depth retrieval methods typically fail over areas with high surface reflectance, such as urban areas and deserts, since the upwelling radiance due to scattering by aerosols is small compared to the radiance resulting from surface reflection. The method proposed here uses shadows cast on the surface to exploit the differences between radiance from the adjacent shaded and unshaded areas of the scene. Shaded areas of the scene are primarily illuminated by diffuse irradiance that is scattered downward from the atmosphere, while unshaded areas are illuminated by both diffuse and direct solar irradiance. The first-order difference between the shaded and unshaded areas is the direct component. Given uniform surface reflectance for the shaded and unshaded areas, the difference in reflected radiance measured by a satellite sensor is related to the direct transmission of solar radiation and inversely proportional to total optical depth. Using an iterative approach, surface reflectance and mean aerosol reflectance can be partitioned to refine the retrieved total optical depth. Aerosol optical depth can then be determined from its contribution to the total atmospheric optical depth (following correction for molecular Rayleigh scattering). Intitial results based on QuickBird imagery and AERONET data collected during the United Arab Emirates Unified Aerosol Experiment (UAE2) indicate that aerosol optical depth retrievals are possible in the visible and near-infrared region with an accuracy of ~0.04.

VISTA - A Constellation for Real Time Regional Imaging

NASA Astrophysics Data System (ADS)

Meerman, Max; Boland, Lee; da Silva Curiel, Alex; Sweeting, Martin, , Sir

2002-01-01

The role of satellites in medium and high-resolution reconnaissance of the Earth's surface has been well demonstrated in recent years through missions such as Landsat, SPOT, IKONOS, ImageSat and Quickbird. The market for such data products is well served and likely to become more competitive with further very-high-resolution missions. Whereas commercial markets have concentrated on enhancing resolution, the small satellite sector has concentrated on reducing the cost of data products, and the development of systems providing niche services. One such EO requirement that can be well met by smaller satellites is the need for higher temporal resolution, as this typically requires a large number of satellites to operate as a constellation - thus far financially impractical using conventional EO satellites. Surrey is currently engaged in building its first constellation that will provide daily global coverage at moderate resolution (32-metre GSD and 600km swath) in three spectral bands. Targeted at providing timely quick-look data products for disaster mitigation and monitoring, the constellation comprises 7 satellites in a single orbital plane. Each satellite has a wide swath so that successive satellites progressively cover the entire globe in a single day. The Vista constellation takes this concept a step further, and is proposed for applications requiring near-continuous surveillance of regional activity. By introducing a multiple plane constellation of small Earth observation satellites, it is possible to monitor continuously selected regions anywhere on the globe. The paper describes the system trades and outlines the scope of the performance that could be obtained from such a system. A cost model illustrates that the balance between launch and space segment costs must be reached by considering suitable replacement strategies, and that the system is highly sensitive to requirement creep. Finally, it is shown that the use of cost effective, small satellites leads to solutions previously thought to be financially beyond sensible reach.

Hillslope terracing effects on the spatial variability of plant development as assessed by NDVI in vineyards of the Priorat region (NE Spain).

PubMed

Martínez-Casasnovas, José A; Ramos, María Concepción; Espinal-Utgés, Sílvia

2010-04-01

The availability of heavy machinery and the vineyard restructuring and conversion plans of the European Union Common Agricultural Policy (Commission Regulation EC no. 1227/2000 of 31 May 2000) have encouraged the restructuring of many vineyards on hillslopes of Mediterranean Europe, through the creation of terraces to favor the mechanization of agricultural work. Terrace construction requires cutting and filling operations that create soil spatial variability, which affects soil properties and plant development. In the present paper, we study the effects of hillslope terracing on the spatial variability of the normalized difference vegetation index (NDVI) in fields of the Priorat region (NE Spain) during 2004, 2005, and 2006. This index was computed from high-resolution remote sensing data (Quickbird-2). Detailed digital terrain models before and after terrace construction were used to assess the earth movements. The results indicate that terracing by heavy machinery induced high variability on the NDVI values over the years, showing significant differences as effect of the cut and fill operations.

Evaluation and sensitivity testing of a coupled Landsat-MODIS downscaling method for land surface temperature and vegetation indices in semi-arid regions

NASA Astrophysics Data System (ADS)

Kim, Jongyoun; Hogue, Terri S.

2012-01-01

The current study investigates a method to provide land surface parameters [i.e., land surface temperature (LST) and normalized difference vegetation index (NDVI)] at a high spatial (˜30 and 60 m) and temporal (daily and 8-day) resolution by combining advantages from Landsat and moderate-resolution imaging spectroradiometer (MODIS) satellites. We adopt a previously developed subtraction method that merges the spatial detail of higher-resolution imagery (Landsat) with the temporal change observed in coarser or moderate-resolution imagery (MODIS). Applying the temporal difference between MODIS images observed at two different dates to a higher-resolution Landsat image allows prediction of a combined or fused image (Landsat+MODIS) at a future date. Evaluation of the resultant merged products is undertaken within the Southeastern Arizona region where data is available from a range of flux tower sites. The Landsat+MODIS fused products capture the raw Landsat values and also reflect the MODIS temporal variation. The predicted Landsat+MODIS LST improves mean absolute error around 5°C at the more heterogeneous sites compared to the original satellite products. The fused Landsat+MODIS NDVI product also shows good correlation to ground-based data and is relatively consistent except during the acute (monsoon) growing season. The sensitivity of the fused product relative to temporal gaps in Landsat data appears to be more affected by uncertainty associated with regional precipitation and green-up, than the length of the gap associated with Landsat viewing, suggesting the potential to use a minimal number of original Landsat images during relatively stable land surface and climate conditions. Our extensive validation yields insight on the ability of the proposed method to integrate multiscale platforms and the potential for reducing costs associated with high-resolution satellite systems (e.g., SPOT, QuickBird, IKONOS).

IDP camp evolvement analysis in Darfur using VHSR optical satellite image time series and scientific visualization on virtual globes

NASA Astrophysics Data System (ADS)

Tiede, Dirk; Lang, Stefan

2010-11-01

In this paper we focus on the application of transferable, object-based image analysis algorithms for dwelling extraction in a camp for internally displaced people (IDP) in Darfur, Sudan along with innovative means for scientific visualisation of the results. Three very high spatial resolution satellite images (QuickBird: 2002, 2004, 2008) were used for: (1) extracting different types of dwellings and (2) calculating and visualizing added-value products such as dwelling density and camp structure. The results were visualized on virtual globes (Google Earth and ArcGIS Explorer) revealing the analysis results (analytical 3D views,) transformed into the third dimension (z-value). Data formats depend on virtual globe software including KML/KMZ (keyhole mark-up language) and ESRI 3D shapefiles streamed as ArcGIS Server-based globe service. In addition, means for improving overall performance of automated dwelling structures using grid computing techniques are discussed using examples from a similar study.

[An object-based information extraction technology for dominant tree species group types].

PubMed

Tian, Tian; Fan, Wen-yi; Lu, Wei; Xiao, Xiang

2015-06-01

Information extraction for dominant tree group types is difficult in remote sensing image classification, howevers, the object-oriented classification method using high spatial resolution remote sensing data is a new method to realize the accurate type information extraction. In this paper, taking the Jiangle Forest Farm in Fujian Province as the research area, based on the Quickbird image data in 2013, the object-oriented method was adopted to identify the farmland, shrub-herbaceous plant, young afforested land, Pinus massoniana, Cunninghamia lanceolata and broad-leave tree types. Three types of classification factors including spectral, texture, and different vegetation indices were used to establish a class hierarchy. According to the different levels, membership functions and the decision tree classification rules were adopted. The results showed that the method based on the object-oriented method by using texture, spectrum and the vegetation indices achieved the classification accuracy of 91.3%, which was increased by 5.7% compared with that by only using the texture and spectrum.

Multiscale Geological Mapping Using Multispectral Data- The Jabali (Yemen) Case Study (ADEN AO 3643)

NASA Astrophysics Data System (ADS)

Deroin, Jean-Paul; Ganad, Ismail Al; Benoit, Paul; Tereygeol, Florian; Heckes, Jurgen

2008-11-01

The Jabali test site, Yemen, is part of the ALOS evaluation project named 'Geological Mapping of Sensitive Environments', which concerns also Lebanon, Tunisia, and France. The present paper illustrates the interest of the ALOS AVNIR-2 sensor for the geological mapping in arid country. The 10m-ground resolution data are compared with those obtained by Landsat TM (30m) and QuickBird (0.67m), in the same range of the electromagnetic spectrum (visible and near infrared). It appears that AVNIR-2 is relevant for geological mapping at a scale of about 1:50,000. The specific interest of the AVNIR-2 'blue' band is also put into light.

Landscape Characterization of Arctic Ecosystems Using Data Mining Algorithms and Large Geospatial Datasets

NASA Astrophysics Data System (ADS)

Langford, Z. L.; Kumar, J.; Hoffman, F. M.

2015-12-01

Observations indicate that over the past several decades, landscape processes in the Arctic have been changing or intensifying. A dynamic Arctic landscape has the potential to alter ecosystems across a broad range of scales. Accurate characterization is useful to understand the properties and organization of the landscape, optimal sampling network design, measurement and process upscaling and to establish a landscape-based framework for multi-scale modeling of ecosystem processes. This study seeks to delineate the landscape at Seward Peninsula of Alaska into ecoregions using large volumes (terabytes) of high spatial resolution satellite remote-sensing data. Defining high-resolution ecoregion boundaries is difficult because many ecosystem processes in Arctic ecosystems occur at small local to regional scales, which are often resolved in by coarse resolution satellites (e.g., MODIS). We seek to use data-fusion techniques and data analytics algorithms applied to Phased Array type L-band Synthetic Aperture Radar (PALSAR), Interferometric Synthetic Aperture Radar (IFSAR), Satellite for Observation of Earth (SPOT), WorldView-2, WorldView-3, and QuickBird-2 to develop high-resolution (˜5m) ecoregion maps for multiple time periods. Traditional analysis methods and algorithms are insufficient for analyzing and synthesizing such large geospatial data sets, and those algorithms rarely scale out onto large distributed- memory parallel computer systems. We seek to develop computationally efficient algorithms and techniques using high-performance computing for characterization of Arctic landscapes. We will apply a variety of data analytics algorithms, such as cluster analysis, complex object-based image analysis (COBIA), and neural networks. We also propose to use representativeness analysis within the Seward Peninsula domain to determine optimal sampling locations for fine-scale measurements. This methodology should provide an initial framework for analyzing dynamic landscape trends in Arctic ecosystems, such as shrubification and disturbances, and integration of ecoregions into multi-scale models.

Modeling Above-Ground Biomass Across Multiple Circum-Arctic Tundra Sites Using High Spatial Resolution Remote Sensing

NASA Astrophysics Data System (ADS)

Räsänen, Aleksi; Juutinen, Sari; Aurela, Mika; Virtanen, Tarmo

2017-04-01

Biomass is one of the central bio-geophysical variables in Earth observation for tracking plant productivity, and flow of carbon, nutrients, and water. Most of the satellite based biomass mapping exercises in Arctic environments have been performed by using rather coarse spatial resolution data, e.g. Landsat and AVHRR which have spatial resolutions of 30 m and >1 km, respectively. While the coarse resolution images have high temporal resolution, they are incapable of capturing the fragmented nature of tundra environment and fine-scale changes in vegetation and carbon exchange patterns. Very high spatial resolution (VHSR, spatial resolution 0.5-2 m) satellite images have the potential to detect environmental variables with an ecologically sound spatial resolution. The usage of VHSR images has, nevertheless, been modest so far in biomass modeling in the Arctic. Our objectives were to use VHSR for predicting above ground biomass in tundra landscapes, evaluate whether a common predictive model can be applied across circum-Arctic tundra and peatland sites having different types of vegetation, and produce knowledge on distribution of plant functional types (PFT) in these sites. Such model development is dependent on ground-based surveys of vegetation with the same spatial resolution and extent with the VHSR images. In this study, we conducted ground-based surveys of vegetation composition and biomass in four different arctic tundra or peatland areas located in Russia, Canada, and Finland. First, we sorted species into PFTs and developed PFT-specific models to predict biomass on the basis of non-destructive measurements (cover, height). Second, we predicted overall biomass on landscape scale by combinations of single bands and vegetation indices of very high resolution satellite images (QuickBird or WorldView-2 images of the eight sites). We compared area-specific empirical regression models and common models that were applied across all sites. We found that NDVI was usually the highest scoring spectral indices in explaining biomass distribution with good explanatory power. Furthermore, models which had more than one explanatory variable had higher explanatory power than models with a single index. The dissimilarity between common and site-specific model estimates was, however, high and data indicates that variation in vegetation properties and its impact on spectral reflectance needs to be acknowledged. Our work produced knowledge on above-ground biomass distribution and contribution of PFTs across circum-Arctic low-growth landscapes and will contribute to developing space-borne vegetation monitoring schemes utilizing VHSR satellite images.

Does the spatial arrangement of vegetation and anthropogenic land cover features matter? Case studies of urban warming and cooling in Phoenix and Las Vegas

NASA Astrophysics Data System (ADS)

Myint, S. W.; Zheng, B.; Fan, C.; Kaplan, S.; Brazel, A.; Middel, A.; Smith, M.

2014-12-01

While the relationship between fractional cover of anthropogenic and vegetation features and the urban heat island has been well studied, the effect of spatial arrangements (e.g., clustered, dispersed) of these features on urban warming or cooling are not well understood. The goal of this study is to examine if and how spatial configuration of land cover features influence land surface temperatures (LST) in urban areas. This study focuses on Phoenix, AZ and Las Vegas, NV that have undergone dramatic urban expansion. The data used to classify detailed urban land cover types include Geoeye-1 (Las Vegas) and QuickBird (Phoenix). The Geoeye-1 image (3 m resolution) was acquired on October 12, 2011 and the QuickBird image (2.4 m resolution) was taken on May 29, 2007. Classification was performed using object based image analysis (OBIA). We employed a spatial autocorrelation approach (i.e., Moran's I) that measures the spatial dependence of a point to its neighboring points and describes how clustered or dispersed points are arranged in space. We used Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data acquired over Phoenix (daytime on June 10, 2011 and nighttime on October 17, 2011) and Las Vegas (daytime on July 6, 2005 and nighttime on August 27, 2005) to examine daytime and nighttime LST with regards to the spatial arrangement of anthropogenic and vegetation features. We spatially correlate Moran's I values of each land cover per surface temperature, and develop regression models. The spatial configuration of grass and trees shows strong negative correlations with LST, implying that clustered vegetation lowers surface temperatures more effectively. In contrast, a clustered spatial arrangement of anthropogenic land-cover features, especially impervious surfaces, significantly elevates surface temperatures. Results from this study suggest that the spatial configuration of anthropogenic and vegetation features influence urban warming and cooling.

Vegetation Continuous Fields--Transitioning from MODIS to VIIRS

NASA Astrophysics Data System (ADS)

DiMiceli, C.; Townshend, J. R.; Sohlberg, R. A.; Kim, D. H.; Kelly, M.

2015-12-01

Measurements of fractional vegetation cover are critical for accurate and consistent monitoring of global deforestation rates. They also provide important parameters for land surface, climate and carbon models and vital background data for research into fire, hydrological and ecosystem processes. MODIS Vegetation Continuous Fields (VCF) products provide four complementary layers of fractional cover: tree cover, non-tree vegetation, bare ground, and surface water. MODIS VCF products are currently produced globally and annually at 250m resolution for 2000 to the present. Additionally, annual VCF products at 1/20° resolution derived from AVHRR and MODIS Long-Term Data Records are in development to provide Earth System Data Records of fractional vegetation cover for 1982 to the present. In order to provide continuity of these valuable products, we are extending the VCF algorithms to create Suomi NPP/VIIRS VCF products. This presentation will highlight the first VIIRS fractional cover product: global percent tree cover at 1 km resolution. To create this product, phenological and physiological metrics were derived from each complete year of VIIRS 8-day surface reflectance products. A supervised regression tree method was applied to the metrics, using training derived from Landsat data supplemented by high-resolution data from Ikonos, RapidEye and QuickBird. The regression tree model was then applied globally to produce fractional tree cover. In our presentation we will detail our methods for creating the VIIRS VCF product. We will compare the new VIIRS VCF product to our current MODIS VCF products and demonstrate continuity between instruments. Finally, we will outline future VIIRS VCF development plans.

A new approach to monitoring spatial distribution and dynamics of wetlands and associated flows of Australian Great Artesian Basin springs using QuickBird satellite imagery

NASA Astrophysics Data System (ADS)

White, Davina C.; Lewis, Megan M.

2011-09-01

SummaryThis study develops an expedient digital mapping technique using Very High Resolution satellite imagery to monitor the temporal response of permanent wetland vegetation to changes in spring flow rates from the Australian Great Artesian Basin at Dalhousie Springs Complex, South Australia. Three epochs of QuickBird satellite multispectral imagery acquired between 2006 and 2010 were analysed using the Normalised Difference Vegetation Index (NDVI). A regression of 2009 NDVI values against vegetation cover from field botanical survey plots provided a relationship of increasing NDVI with increased vegetation cover ( R2 = 0.86; p < 0.001). On the basis of this relationship a vegetation threshold was determined (NDVI ⩾ 0.35), which discriminated perennial and ephemeral wetland vegetation from surrounding dryland vegetation in the imagery. The extent of wetlands for the entire Dalhousie Springs Complex mapped from the imagery increased from 607 ha in December 2006 to 913 ha in May 2009 and 1285 ha in May 2010. Comparison of the three NDVI images showed considerable localised change in wetland vegetation greenness, distribution and extent in response to fires, alien vegetation removal, rainfall and fluctuations in spring flow. A strong direct relationship ( R2 = 0.99; p < 0.001) was exhibited between spring flow rate and the area of associated wetland vegetation for eight individual springs. This relationship strongly infers that wetland area is an indicator of spring flow and can be used for monitoring purposes. This method has the potential to determine the sensitivity of spring wetland vegetation extent and distribution to associated changes in spring flow rates due to land management and aquifer extractions. Furthermore, this approach is timely and provides reliable and repeatable monitoring, particularly needed given the projected increased demand for groundwater extractions from the GAB for mining operations.

Topographic correction realization based on the CBERS-02B image

NASA Astrophysics Data System (ADS)

Qin, Hui-ping; Yi, Wei-ning; Fang, Yong-hua

2011-08-01

The special topography of mountain terrain will induce the retrieval distortion in same species and surface spectral lines. In order to improve the research accuracy of topographic surface characteristic, many researchers have focused on topographic correction. Topographic correction methods can be statistical-empirical model or physical model, in which the methods based on the digital elevation model data are most popular. Restricted by spatial resolution, previous model mostly corrected topographic effect based on Landsat TM image, whose spatial resolution is 30 meter that can be easily achieved from internet or calculated from digital map. Some researchers have also done topographic correction based on high spatial resolution images, such as Quickbird and Ikonos, but there is little correlative research on the topographic correction of CBERS-02B image. In this study, liao-ning mountain terrain was taken as the objective. The digital elevation model data was interpolated to 2.36 meter by 15 meter original digital elevation model one meter by one meter. The C correction, SCS+C correction, Minnaert correction and Ekstrand-r were executed to correct the topographic effect. Then the corrected results were achieved and compared. The images corrected with C correction, SCS+C correction, Minnaert correction and Ekstrand-r were compared, and the scatter diagrams between image digital number and cosine of solar incidence angel with respect to surface normal were shown. The mean value, standard variance, slope of scatter diagram, and separation factor were statistically calculated. The analysed result shows that the shadow is weakened in corrected images than the original images, and the three-dimensional affect is removed. The absolute slope of fitting lines in scatter diagram is minished. Minnaert correction method has the most effective result. These demonstrate that the former correction methods can be successfully adapted to CBERS-02B images. The DEM data can be interpolated step by step to get the corresponding spatial resolution approximately for the condition that high spatial resolution elevation data is hard to get.

Evaluation of the U.S. Geological Survey Landsat burned area essential climate variable across the conterminous U.S. using commercial high-resolution imagery

USGS Publications Warehouse

Vanderhoof, Melanie; Brunner, Nicole M.; Beal, Yen-Ju G.; Hawbaker, Todd J.

2017-01-01

The U.S. Geological Survey has produced the Landsat Burned Area Essential Climate Variable (BAECV) product for the conterminous United States (CONUS), which provides wall-to-wall annual maps of burned area at 30 m resolution (1984–2015). Validation is a critical component in the generation of such remotely sensed products. Previous efforts to validate the BAECV relied on a reference dataset derived from Landsat, which was effective in evaluating the product across its timespan but did not allow for consideration of inaccuracies imposed by the Landsat sensor itself. In this effort, the BAECV was validated using 286 high-resolution images, collected from GeoEye-1, QuickBird-2, Worldview-2 and RapidEye satellites. A disproportionate sampling strategy was utilized to ensure enough burned area pixels were collected. Errors of omission and commission for burned area averaged 22 ± 4% and 48 ± 3%, respectively, across CONUS. Errors were lowest across the western U.S. The elevated error of commission relative to omission was largely driven by patterns in the Great Plains which saw low errors of omission (13 ± 13%) but high errors of commission (70 ± 5%) and potentially a region-growing function included in the BAECV algorithm. While the BAECV reliably detected agricultural fires in the Great Plains, it frequently mapped tilled areas or areas with low vegetation as burned. Landscape metrics were calculated for individual fire events to assess the influence of image resolution (2 m, 30 m and 500 m) on mapping fire heterogeneity. As the spatial detail of imagery increased, fire events were mapped in a patchier manner with greater patch and edge densities, and shape complexity, which can influence estimates of total greenhouse gas emissions and rates of vegetation recovery. The increasing number of satellites collecting high-resolution imagery and rapid improvements in the frequency with which imagery is being collected means greater opportunities to utilize these sources of imagery for Landsat product validation. 

Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland

NASA Astrophysics Data System (ADS)

Lu, Bing; He, Yuhong

2017-06-01

Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition, owing to its high spatial resolution. The overall accuracy is around 85% for images acquired at different times. Species composition is spatially attributed by topographical features and soil moisture conditions. Spatio-temporal variation of species composition implies the growing process and succession of different species, which is critical for understanding the evolutionary features of grassland ecosystems. Strengths and challenges of applying UAV-acquired imagery for vegetation studies are summarized at the end.

Identifying landscape features associated with Rift Valley fever virus transmission, Ferlo region, Senegal, using very high spatial resolution satellite imagery.

PubMed

Soti, Valérie; Chevalier, Véronique; Maura, Jonathan; Bégué, Agnès; Lelong, Camille; Lancelot, Renaud; Thiongane, Yaya; Tran, Annelise

2013-03-01

Dynamics of most of vector-borne diseases are strongly linked to global and local environmental changes. Landscape changes are indicators of human activities or natural processes that are likely to modify the ecology of the diseases. Here, a landscape approach developed at a local scale is proposed for extracting mosquito favourable biotopes, and for testing ecological parameters when identifying risk areas of Rift Valley fever (RVF) transmission. The study was carried out around Barkedji village, Ferlo region, Senegal. In order to test whether pond characteristics may influence the density and the dispersal behaviour of RVF vectors, and thus the spatial variation in RVFV transmission, we used a very high spatial resolution remote sensing image (2.4 m resolution) provided by the Quickbird sensor to produce a detailed land-cover map of the study area. Based on knowledge of vector and disease ecology, seven landscape attributes were defined at the pond level and computed from the land-cover map. Then, the relationships between landscape attributes and RVF serologic incidence rates in small ruminants were analyzed through a beta-binomial regression. Finally, the best statistical model according to the Akaike Information Criterion corrected for small samples (AICC), was used to map areas at risk for RVF. Among the derived landscape variables, the vegetation density index (VDI) computed within a 500 m buffer around ponds was positively correlated with serologic incidence (p<0.001), suggesting that the risk of RVF transmission was higher in the vicinity of ponds surrounded by a dense vegetation cover. The final risk map of RVF transmission displays a heterogeneous spatial distribution, corroborating previous findings from the same area. Our results highlight the potential of very high spatial resolution remote sensing data for identifying environmental risk factors and mapping RVF risk areas at a local scale.

Identifying landscape features associated with Rift Valley fever virus transmission, Ferlo region, Senegal, using very high spatial resolution satellite imagery

PubMed Central

2013-01-01

Introduction Dynamics of most of vector-borne diseases are strongly linked to global and local environmental changes. Landscape changes are indicators of human activities or natural processes that are likely to modify the ecology of the diseases. Here, a landscape approach developed at a local scale is proposed for extracting mosquito favourable biotopes, and for testing ecological parameters when identifying risk areas of Rift Valley fever (RVF) transmission. The study was carried out around Barkedji village, Ferlo region, Senegal. Methods In order to test whether pond characteristics may influence the density and the dispersal behaviour of RVF vectors, and thus the spatial variation in RVFV transmission, we used a very high spatial resolution remote sensing image (2.4 m resolution) provided by the Quickbird sensor to produce a detailed land-cover map of the study area. Based on knowledge of vector and disease ecology, seven landscape attributes were defined at the pond level and computed from the land-cover map. Then, the relationships between landscape attributes and RVF serologic incidence rates in small ruminants were analyzed through a beta-binomial regression. Finally, the best statistical model according to the Akaike Information Criterion corrected for small samples (AICC), was used to map areas at risk for RVF. Results Among the derived landscape variables, the vegetation density index (VDI) computed within a 500 m buffer around ponds was positively correlated with serologic incidence (p<0.001), suggesting that the risk of RVF transmission was higher in the vicinity of ponds surrounded by a dense vegetation cover. The final risk map of RVF transmission displays a heterogeneous spatial distribution, corroborating previous findings from the same area. Conclusions Our results highlight the potential of very high spatial resolution remote sensing data for identifying environmental risk factors and mapping RVF risk areas at a local scale. PMID:23452759

Mapping wetlands in Nova Scotia with multi-beam RADARSAT-2 Polarimetric SAR, optical satellite imagery, and Lidar data

NASA Astrophysics Data System (ADS)

Jahncke, Raymond; Leblon, Brigitte; Bush, Peter; LaRocque, Armand

2018-06-01

Wetland maps currently in use by the Province of Nova Scotia, namely the Department of Natural Resources (DNR) wetland inventory map and the swamp wetland classes of the DNR forest map, need to be updated. In this study, wetlands were mapped in an area southwest of Halifax, Nova Scotia by classifying a combination of multi-date and multi-beam RADARSAT-2 C-band polarimetric SAR (polSAR) images with spring Lidar, and fall QuickBird optical data using the Random Forests (RF) classifier. The resulting map has five wetland classes (open-water/marsh complex, open bog, open fen, shrub/treed fen/bog, swamp), plus lakes and various upland classes. Its accuracy was assessed using data from 156 GPS wetland sites collected in 2012 and compared to the one obtained with the current wetland map of Nova Scotia. The best overall classification was obtained using a combination of Lidar, RADARSAT-2 HH, HV, VH, VV intensity with polarimetric variables, and QuickBird multispectral (89.2%). The classified image was compared to GPS validation sites to assess the mapping accuracy of the wetlands. It was first done considering a group consisting of all wetland classes including lakes. This showed that only 69.9% of the wetland sites were correctly identified when only the QuickBird classified image was used in the classification. With the addition of variables derived from lidar, the number of correctly identified wetlands increased to 88.5%. The accuracy remained the same with the addition of RADARSAT-2 (88.5%). When we tested the accuracy for identifying wetland classes (e.g. marsh complex vs. open bog) instead of grouped wetlands, the resulting wetland map performed best with either QuickBird and Lidar, or QuickBird, Lidar, and RADARSAT-2 (66%). The Province of Nova Scotia's current wetland inventory and its associated wetland classes (aerial-photo interpreted) were also assessed against the GPS wetland sites. This provincial inventory correctly identified 62.2% of the grouped wetlands and only 18.6% of the wetland classes. The current inventory's poor performance demonstrates the value of incorporating a combination of new data sources into the provincial wetland mapping.

Controls with remote sensing of Common Agricultural Policy (CAP) arable- and forage- area-based subsidies: a yearly more than 700-image and 3-M euro affair

NASA Astrophysics Data System (ADS)

Astrand, Par-Johan; Wirnhardt, Csaba; Biagini, Bruno; Weber, Michaela; Hellerman, Rani

2004-11-01

Since 1993, the EC DG Agriculture has promoted the use of "Controls with Remote Sensing" (CwRS) as appropriate control system within the Common Agricultural Policy (CAP). CwRS is considered suitable to check if agricultural area-based subsidies (yearly > 25 billion euro EC expenditure) are correctly granted. On the basis of the Council Regulation (EC) 165/94 and of the Commission Regulation (EC) 601/94, the Commission Services are required to centralize the satellite images acquisition. This task has been managed by the MARS Project at the JRC since 1999, where the whole controls activity is coordinated. The activity also includes the setting up of specifications, recommendations, performing Quality Controls (QC) and auditing of the selected contractors, and evaluation of new methods. Satellite image acquisition involves the control site definition within each Member State, and the subsequent chain of image acquisition over the defined sites including feasibility with image providers, acquisition, validation, ordering, delivery and final archiving of the imagery. In summary the 2004 years campaign involved a budget of approximately 3.2 M euro to cover some 150 High Resolution (HR) sites and 71 Very High Resolution (VHR) sites. The objective of this paper is to describe the CwRS image acquisition with emphasis on the Ikonos, Quickbird, and EROS A satellites for the 2004 years CwRS Campaign, to give preliminary results, recommendations and future trends.

Remote Sensing in a Changing Climate and Environment: the Rift Valley Fever Case

NASA Astrophysics Data System (ADS)

Tourre, Y. M.; Lacaux, J.-P.; Vignolles, C.; Lafaye, M.

2012-07-01

Climate and environment are changing rapidly whilst global population already reached 7 billions people. New public health challenges are posed by new and re-emerging diseases. Innovation is a must i.e., 1) using high resolution remote sensing, 2) re-invent health politics and trans-disciplinary management. The above are part of the 'TransCube Approach' i.e., Transition, Translation, and Transformation. The new concept of Tele-epidemiology includes such approach. A conceptual approach (CA) associated with Rift Valley Fever (RVF) epidemics in Senegal is presented. Ponds are detected using high-resolution SPOT-5 satellite images and radar data from space. Data on rainfall events obtained from the Tropical Rainfall Measuring Mission (NASA/JAXA) are combined with in-situ data. Localization of vulnerable and parked hosts (obtained from QuickBird satellite) is also used. The dynamic spatio-temporal distribution and aggressiveness of RVF mosquitoes, are based on total rainfall amounts, ponds' dynamics and entomological observations. Detailed risks maps (hazards + vulnerability) in real-time are expressed in percentages of parks where animals are potentially at risks. This CA which simply relies upon rainfall distribution from space, is meant to contribute to the implementation of the RVF early warning system (RVFews). It is meant to be applied to other diseases and elsewhere. This is particularly true in new places where new vectors have been rapidly adapting (such as Aedes albopictus) whilst viruses (such as West Nile and Chikungunya,) circulate from constantly moving reservoirs and increasing population.

Optimizing spectral resolutions for the classification of C3 and C4 grass species, using wavelengths of known absorption features

NASA Astrophysics Data System (ADS)

Adjorlolo, Clement; Cho, Moses A.; Mutanga, Onisimo; Ismail, Riyad

2012-01-01

Hyperspectral remote-sensing approaches are suitable for detection of the differences in 3-carbon (C3) and four carbon (C4) grass species phenology and composition. However, the application of hyperspectral sensors to vegetation has been hampered by high-dimensionality, spectral redundancy, and multicollinearity problems. In this experiment, resampling of hyperspectral data to wider wavelength intervals, around a few band-centers, sensitive to the biophysical and biochemical properties of C3 or C4 grass species is proposed. The approach accounts for an inherent property of vegetation spectral response: the asymmetrical nature of the inter-band correlations between a waveband and its shorter- and longer-wavelength neighbors. It involves constructing a curve of weighting threshold of correlation (Pearson's r) between a chosen band-center and its neighbors, as a function of wavelength. In addition, data were resampled to some multispectral sensors-ASTER, GeoEye-1, IKONOS, QuickBird, RapidEye, SPOT 5, and WorldView-2 satellites-for comparative purposes, with the proposed method. The resulting datasets were analyzed, using the random forest algorithm. The proposed resampling method achieved improved classification accuracy (κ=0.82), compared to the resampled multispectral datasets (κ=0.78, 0.65, 0.62, 0.59, 0.65, 0.62, 0.76, respectively). Overall, results from this study demonstrated that spectral resolutions for C3 and C4 grasses can be optimized and controlled for high dimensionality and multicollinearity problems, yet yielding high classification accuracies. The findings also provide a sound basis for programming wavebands for future sensors.

Context-sensitive extraction of tree crown objects in urban areas using VHR satellite images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Bijker, Wietske; Tolpekin, Valentyn A.; Stein, Alfred

2012-04-01

Municipalities need accurate and updated inventories of urban vegetation in order to manage green resources and estimate their return on investment in urban forestry activities. Earlier studies have shown that semi-automatic tree detection using remote sensing is a challenging task. This study aims to develop a reproducible geographic object-based image analysis (GEOBIA) methodology to locate and delineate tree crowns in urban areas using high resolution imagery. We propose a GEOBIA approach that considers the spectral, spatial and contextual characteristics of tree objects in the urban space. The study presents classification rules that exploit object features at multiple segmentation scales modifying the labeling and shape of image-objects. The GEOBIA methodology was implemented on QuickBird images acquired over the cities of Enschede and Delft (The Netherlands), resulting in an identification rate of 70% and 82% respectively. False negative errors concentrated on small trees and false positive errors in private gardens. The quality of crown boundaries was acceptable, with an overall delineation error <0.24 outside of gardens and backyards.

Satellite Map of Port-au-Prince, Haiti-2010-Natural Color

USGS Publications Warehouse

Cole, Christopher J.; Sloan, Jeff

2010-01-01

The U.S. Geological Survey produced 1:24,000-scale post-earthquake image base maps incorporating high- and medium-resolution remotely sensed imagery following the 7.0 magnitude earthquake near the capital city of Port au Prince, Haiti, on January 12, 2010. Commercial 2.4-meter multispectral QuickBird imagery was acquired by DigitalGlobe on January 15, 2010, following the initial earthquake. Ten-meter multispectral ALOS AVNIR-2 imagery was collected by the Japanese Space Agency (JAXA) on January 12, 2010. These data were acquired under the Remote Sensing International Charter, a global team of space and satellite agencies that provide timely imagery in support of emergency response efforts worldwide. The images shown on this map were employed to support earthquake response efforts, specifically for use in determining ground deformation, damage assessment, and emergency management decisions. The raw, unprocessed imagery was geo-corrected, mosaicked, and reproduced onto a cartographic 1:24,000-scale base map. These maps are intended to provide a temporally current representation of post-earthquake ground conditions, which may be of use to decision makers and to the general public.

Satellite Map of Port-au-Prince, Haiti-2010-Infrared

USGS Publications Warehouse

Cole, Christopher J.; Sloan, Jeff

2010-01-01

The U.S. Geological Survey produced 1:24,000-scale post-earthquake image base maps incorporating high- and medium-resolution remotely sensed imagery following the 7.0 magnitude earthquake near the capital city of Port au Prince, Haiti, on January 12, 2010. Commercial 2.4-meter multispectral QuickBird imagery was acquired by DigitalGlobe on January 15, 2010, following the initial earthquake. Ten-meter multispectral ALOS AVNIR-2 imagery was collected by the Japanese Space Agency (JAXA) on January 12, 2010. These data were acquired under the Remote Sensing International Charter, a global team of space and satellite agencies that provide timely imagery in support of emergency response efforts worldwide. The images shown on this map were employed to support earthquake response efforts, specifically for use in determining ground deformation, damage assessment, and emergency management decisions. The raw, unprocessed imagery was geo-corrected, mosaicked, and reproduced onto a cartographic 1:24,000-scale base map. These maps are intended to provide a temporally current representation of post-earthquake ground conditions, which may be of use to decision makers and to the general public.

Urban structure and dengue fever in Puntarenas, Costa Rica

PubMed Central

Troyo, Adriana; Fuller, Douglas O.; Calderón-Arguedas, Olger; Solano, Mayra E.; Beier, John C.

2009-01-01

Dengue is currently the most important arboviral disease globally and is usually associated with built environments in tropical areas. Remotely sensed information can facilitate the study of urban mosquito-borne diseases by providing multiple temporal and spatial resolutions appropriate to investigate urban structure and ecological characteristics associated with infectious disease. In this study, coarse, medium and fine resolution satellite imagery (Moderate Resolution Imaging Spectrometer, Advanced Spaceborne Thermal Emission and Reflection Radiometer and QuickBird respectively) and ground-based data were analyzed for the Greater Puntarenas area, Costa Rica for the years 2002–04. The results showed that the mean normalized difference vegetation index (NDVI) was generally higher in the localities with lower incidence of dengue fever during 2002, although the correlation was statistically significant only in the dry season (r=−0.40; p=0.03). Dengue incidence was inversely correlated to built area and directly correlated with tree cover (r=0.75, p=0.01). Overall, the significant correlations between dengue incidence and urban structural variables (tree cover and building density) suggest that properties of urban structure may be associated with dengue incidence in tropical urban settings. PMID:20161131

Land-cover mapping of Red Rock Canyon National Conservation Area and Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern, Clark County, Nevada

USGS Publications Warehouse

Smith, J. LaRue; Damar, Nancy A.; Charlet, David A.; Westenburg, Craig L.

2014-01-01

DigitalGlobe’s QuickBird satellite high-resolution multispectral imagery was classified by using Visual Learning Systems’ Feature Analyst feature extraction software to produce land-cover data sets for the Red Rock Canyon National Conservation Area and the Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern in Clark County, Nevada. Over 1,000 vegetation field samples were collected at the stand level. The field samples were classified to the National Vegetation Classification Standard, Version 2 hierarchy at the alliance level and above. Feature extraction models were developed for vegetation on the basis of the spectral and spatial characteristics of selected field samples by using the Feature Analyst hierarchical learning process. Individual model results were merged to create one data set for the Red Rock Canyon National Conservation Area and one for each of the Areas of Critical Environmental Concern. Field sample points and photographs were used to validate and update the data set after model results were merged. Non-vegetation data layers, such as roads and disturbed areas, were delineated from the imagery and added to the final data sets. The resulting land-cover data sets are significantly more detailed than previously were available, both in resolution and in vegetation classes.

Small Glacier Area Studies: A New Approach for Turkey

NASA Technical Reports Server (NTRS)

Yavasli, Dogukan D.; Tucker, Compton J.

2012-01-01

Many regions of Earth have glaciers that have been neglected for study because they are small. We report on a new approach to overcome the problem of studying small glaciers, using Turkey as an example. Prior to our study, no reliable estimates of Turkish glaciers existed because of a lack of systematic mapping, difficulty in using Landsat data collected before 1982, snowpack vs. glacier ice differentiation using existing satellite data and aerial photography, the previous high cost of Landsat images, and a lack of high-resolution imagery of small Turkish glaciers. Since 2008, a large number of < 1 m satellite images have become available at no cost to the research community. In addition, Landsat data are now free of charge from the U.S. Geological Survey, enabling the use of multiple images. We used 174 Landsat and eight high-resolution satellite images to document the areal extent of Turkish glaciers from the 1970s to 2007-2011. Multiple Landsat images, primarily Thematic Mapper (TM) data from 1984 to 2011, enabled us to minimize differentiation problems between snow and glacier ice, a potential source of error. In addition, we used Ikonos, Quickbird, and World View-1 & -2 very high-resolution imagery to evaluate our TM accuracies and determine the area of nine smaller glaciers in Turkey. We also used five Landsat-3 Return Beam Videcon (RBV) 30 m pixel resolution images, all from 1980, for six glaciers. The total area of Turkish glaciers decreased from 23 km2 in the 1970s to 10.1 km2 in 2007-2011. By 2007-2011, six Turkish glaciers disappeared, four were < 0.3 km2, and only three were 1.0 km2 or larger. No trends in precipitation from 1970 to 2006 and cloud cover from 1980 to 2010 were found, while surface temperatures increased, with summer minimum temperatures showing the greatest increase. We conclude that increased surface temperatures during the summer were responsible for the 56% recession of Turkish glaciers from the 1970s to 2006-2011.

[Spatial distribution characteristics of urban potential population in Shenyang City based on QuickBird image and GIS].

PubMed

Li, Jun-Ying; Hu, Yuan-Man; Chen, Wei; Liu, Miao; Hu, Jian-Bo; Zhong, Qiao-Lin; Lu, Ning

2012-06-01

Population is the most active factor affecting city development. To understand the distribution characteristics of urban population is of significance for making city policy decisions and for optimizing the layout of various urban infrastructures. In this paper, the information of the residential buildings in Shenyang urban area was extracted from the QuickBird remote sensing images, and the spatial distribution characteristics of the population within the Third-Ring Road of the City were analyzed, according to the social and economic statistics data. In 2010, the population density in different types of residential buildings within the Third-Ring Road of the City decreased in the order of high-storey block, mixed block, mixed garden, old multi-storey building, high-storey garden, multi-storey block, multi-storey garden, villa block, shanty, and villa garden. The vacancy rate of the buildings within the Third-Ring Road was more than 30%, meaning that the real estate market was seriously overstocked. Among the five Districts of Shenyang City, Shenhe District had the highest potential population density, while Tiexi District and Dadong District had a lower one. The gravity center of the City and its five Districts was also analyzed, which could provide basic information for locating commercial facilities and planning city infrastructure.

Multiscale sagebrush rangeland habitat modeling in the Gunnison Basin of Colorado

USGS Publications Warehouse

Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.

2013-01-01

North American sagebrush-steppe ecosystems have decreased by about 50 percent since European settlement. As a result, sagebrush-steppe dependent species, such as the Gunnison sage-grouse, have experienced drastic range contractions and population declines. Coordinated ecosystem-wide research, integrated with monitoring and management activities, is needed to help maintain existing sagebrush habitats; however, products that accurately model and map sagebrush habitats in detail over the Gunnison Basin in Colorado are still unavailable. The goal of this project is to provide a rigorous large-area sagebrush habitat classification and inventory with statistically validated products and estimates of precision across the Gunnison Basin. This research employs a combination of methods, including (1) modeling sagebrush rangeland as a series of independent objective components that can be combined and customized by any user at multiple spatial scales; (2) collecting ground measured plot data on 2.4-meter QuickBird satellite imagery in the same season the imagery is acquired; (3) modeling of ground measured data on 2.4-meter imagery to maximize subsequent extrapolation; (4) acquiring multiple seasons (spring, summer, and fall) of Landsat Thematic Mapper imagery (30-meter) for optimal modeling; (5) using regression tree classification technology that optimizes data mining of multiple image dates, ratios, and bands with ancillary data to extrapolate ground training data to coarser resolution Landsat Thematic Mapper; and 6) employing accuracy assessment of model predictions to enable users to understand their dependencies. Results include the prediction of four primary components including percent bare ground, percent herbaceous, percent shrub, and percent litter, and four secondary components including percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata wyomingensis), and shrub height (centimeters). Results were validated with an independent accuracy assessment, with root mean square error values ranging from 3.5 (percent big sagebrush) to 10.8 (percent bare ground) at the QuickBird scale, and from 4.5 (percent Wyoming sagebrush) to 12.4 (percent herbaceous) at the full Landsat scale. These results offer significant improvement in sagebrush ecosystem quantification across the Gunnison Basin, and also provide maximum flexibility to users to employ for a wide variety of applications. Further refinement of these remote sensing component predictions in the future will be most likely achieved by focusing on more extensive ground plot sampling, employing new high and moderate-resolution satellite sensors that offer additional spectral bands for vegetation discrimination, and capturing more dates of satellite imagery to better represent phenological variation.

WorldView-2 and the evolution of the DigitalGlobe remote sensing satellite constellation: introductory paper for the special session on WorldView-2

NASA Astrophysics Data System (ADS)

Anderson, Neal T.; Marchisio, Giovanni B.

2012-06-01

Over the last decade DigitalGlobe (DG) has built and launched a series of remote sensing satellites with steadily increasing capabilities: QuickBird, WorldView-1 (WV-1), and WorldView-2 (WV-2). Today, this constellation acquires over 2.5 million km2 of imagery on a daily basis. This paper presents the configuration and performance capabilities of each of these satellites, with emphasis on the unique spatial and spectral capabilities of WV-2. WV-2 employs high-precision star tracker and inertial measurement units to achieve a geolocation accuracy of 5 m Circular Error, 90% confidence (CE90). The native resolution of WV-2 is 0.5 m GSD in the panchromatic band and 2 m GSD in 8 multispectral bands. Four of the multispectral bands match those of the Landsat series of satellites; four new bands enable novel and expanded applications. We are rapidly establishing and refreshing a global database of very high resolution (VHR) 8-band multispectral imagery. Control moment gyroscopes (CMGs) on both WV-1 and WV-2 improve collection capacity and provide the agility to capture multi-angle sequences in rapid succession. These capabilities result in a rich combination of image features that can be exploited to develop enhanced monitoring solutions. Algorithms for interpretation and analysis can leverage: 1) broader and more continuous spectral coverage at 2 m resolution; 2) textural and morphological information from the 0.5 m panchromatic band; 3) ancillary information from stereo and multi-angle collects, including high precision digital elevation models; 4) frequent revisits and time-series collects; and 5) the global reference image archives. We introduce the topic of creative fusion of image attributes, as this provides a unifying theme for many of the papers in this WV-2 Special Session.

Implementing Natural Resources Cadastral Plan in Pasargadae District of Iran by Using Quick Bird Images

NASA Astrophysics Data System (ADS)

Azhdari, G. H.; Deilami, K.; Firooznia, E.

2015-12-01

Natural Resources are essential for security and sustainable development of each country. Therefore, in order to reach sustainable development, conservation as well as optimum utilization of natural resources, executing of natural resources cadastral plan is necessary and essential. Governments conduct lands management in Iran, so there is a need for comprehensive plan with arranged program for best evaluation. In this research as a pilot, Pasargadae city is opted. Pasargadae region is located in north-east of Shiraz in Fars province with Latitude and longitude of 30° 15 ´ 53 ° N and 53° 13 ´ 29 ° E respectively. In order to generate the cadastral maps, Firstly, images from QuickBird satellite with 50-60 centimeters resolution were georeferenced by utilizing ground control points with accurate GPS coordinates. In addition to satellite images, old paper maps with 1:10000 scale in local coordinate system from agriculture ministry in 1963 were digitized according to 1:25000 scale map from army geographical organization with AutoCad software. Beside, paper maps with 1:50000 scale and Google Earth were used to find the changes during time. All the above maps were added to QuickBird images as new layers by using ArcMap software. These maps also were utilized to determine the different land-uses. Thus, by employing ArcMap software lands divide into 2 groups: firstly, lands with official document, which is owned by either natural or legal persons, and secondly national lands under different uses such as forestry, range management and desertification plans. Consequently, the generation of cadastral maps leads to better difference between private and national lands. In addition, producing cadastral maps prevent the destruction and illegal possession of natural lands by individuals.

Analysing land and vegetation cover dynamics during last three decades in Katerniaghat wildlife sanctuary, India

NASA Astrophysics Data System (ADS)

Chitale, V. S.; Behera, M. D.

2014-10-01

The change in the tropical forests could be clearly linked to the expansion of the human population and economies. An understanding of the anthropogenic forcing plays an important role in analyzing the impacts of climate change and the fate of tropical forests in the present and future scenario. In the present study, we analyze the impact of natural and anthropogenic factors in forest dynamics in Katerniaghat wildlife sanctuary situated along the Indo-Nepal border in Uttar Pradesh state, India. The study site is under tremendous pressure due to anthropogenic factors from surrounding areas since last three decades. The vegetation cover of the sanctuary primarily comprised of Shorea robusta forests, Tectona grandis plantation, and mixed deciduous forest; while the land cover comprised of agriculture, barren land, and water bodies. The classification accuracy was 83.5%, 91.5%, and 95.2% with MSS, IKONOS, and Quickbird datasets, respectively. Shorea robusta forests showed an increase of 16 km2; while Tectona grandis increased by 63.01 km2 during 1975-2010. The spatial heterogeneity in these tropical vegetation classes surrounded by the human dominated agricultural lands could not be addressed using Landsat MSS data due to coarse spatial resolution; whereas the IKONOS and Quickbird satellite datasets proved to advantageous, thus being able to precisely address the variations within the vegetation classes as well as in the land cover classes and along the edge areas. Massive deforestation during 1970s along the adjoining international boundary with Nepal has led to destruction of the wildlife corridor and has exposed the wildlife sanctuary to human interference like grazing and poaching. Higher rates of forest dynamics during the 25-year period indicate the vulnerability of the ecosystem to the natural and anthropogenic disturbances in the proximity of the sanctuary.

Developing Coastal Surface Roughness Maps Using ASTER and QuickBird Data Sources

NASA Technical Reports Server (NTRS)

Spruce, Joe; Berglund, Judith; Davis, Bruce

2006-01-01

This viewgraph presentation regards one element of a larger project on the integration of NASA science models and data into the Hazards U.S. Multi-Hazard (HAZUS-MH) Hurricane module for hurricane damage and loss risk assessment. HAZUS-MH is a decision support tool being developed by the National Institute of Building Sciences for the Federal Emergency Management Agency (FEMA). It includes the Hurricane Module, which employs surface roughness maps made from National Land Cover Data (NLCD) maps to estimate coastal hurricane wind damage and loss. NLCD maps are produced and distributed by the U.S. Geological Survey. This presentation discusses an effort to improve upon current HAZUS surface roughness maps by employing ASTER multispectral classifications with QuickBird "ground reference" imagery.

Estimating Carbon Storage and Sequestration by Urban Trees at Multiple Spatial Resolutions

NASA Astrophysics Data System (ADS)

Wu, J.; Tran, A.; Liao, A.

2010-12-01

Urban forests are an important component of urban-suburban environments. Urban trees provide not only a full range of social and psychological benefits to city dwellers, but also valuable ecosystem services to communities, such as removing atmospheric carbon dioxide, improving air quality, and reducing storm water runoff. There is an urgent need for developing strategic conservation plans for environmentally sustainable urban-suburban development based on the scientific understanding of the extent and function of urban forests. However, several challenges remain to accurately quantify various environmental benefits provided by urban trees, among which is to deal with the effect of changing spatial resolution and/or scale. In this study, we intended to examine the uncertainties of carbon storage and sequestration associated with the tree canopy coverage of different spatial resolutions. Multi-source satellite imagery data were acquired for the City of Fullerton, located in Orange County of California. The tree canopy coverage of the study area was classified at three spatial resolutions, ranging from 30 m (Landsat-5 Thematic Mapper), 15 m (Advanced Spaceborne Thermal Emission and Reflection Radiometer), to 2.5 m (QuickBird). We calculated the amount of carbon stored in the trees represented on the individual tree coverage maps and the annual carbon taken up by the trees with a model (i.e., CITYgreen) developed by the U.S. Forest Service. The results indicate that urban trees account for significant proportions of land cover in the study area even with the low spatial resolution data. The estimated carbon fixation benefits vary greatly depending on the details of land use and land cover classification. The extrapolation of estimation from the fine-resolution stand-level to the low-resolution landscape-scale will likely not preserve reasonable accuracy.

Use of Visible Satellite Imagery to Determine Velocity in Tidal Rivers

NASA Astrophysics Data System (ADS)

Mied, R. P.; Donato, T. F.; Chen, W.

2006-05-01

In the open ocean and on the continental shelf, current velocities have traditionally been calculated remotely using the Maximum Correlation Coefficient (MCC) technique to track features between sequential sea surface temperature image scenes. These images are obtained from NOAA polar orbiters having an effective ground pixel size of 1.47 km. In contrast to this relatively large distance, spatial scales over which current velocities can vary in rivers and estuaries are hundreds of meters; associated temporal scales vary from tens of minutes to hours. Traditional in-situ measurements can be instructive in determining some aspects of the flow, but truly synoptic overviews are possible only with remote sensing, provided high-resolution imagery is available. With the advent of a constellation of moderate- to high-resolution imaging systems (e.g., Landsat, ASTER, SPOT, Quickbird, Ikonos, and Orbview-3) it is now available to extend current estimations to these areas. For instance, Landsat-7 and ASTER produce imagery with spatial resolutions on the order of 30 m or less and within 30 min of each other. This is sufficient to spatially resolve a wide variety of surface features, and to maintain feature integrity over time for tracking purposes. We apply this approach to a portion of the tidal Potomac River by using pairs of co-registered, sequential, multi-spectral Landsat-7 and ASTER images. The final data used in the analysis set contain three spectral bands (green, red, and near-infrared), and have a ground pixel spacing (GSD) of 30m. The time step between each Landsat-7 and ASTER pair is approximately 29 minutes. Two image sets are used in the present study, one occurring on 5 October 2001 and the other on 2 April 2003. We show current maps derived from both image pairs an discuss the results in the light of model and

Automated protocols for spaceborne sub-meter resolution "Big Data" products for Earth Science

NASA Astrophysics Data System (ADS)

Neigh, C. S. R.; Carroll, M.; Montesano, P.; Slayback, D. A.; Wooten, M.; Lyapustin, A.; Shean, D. E.; Alexandrov, O.; Macander, M. J.; Tucker, C. J.

2017-12-01

The volume of available remotely sensed data has grown exceeding Petabytes per year and the cost for data, storage systems and compute power have both dropped exponentially. This has opened the door for "Big Data" processing systems with high-end computing (HEC) such as the Google Earth Engine, NASA Earth Exchange (NEX), and NASA Center for Climate Simulation (NCCS). At the same time, commercial very high-resolution (VHR) satellites have grown into a constellation with global repeat coverage that can support existing NASA Earth observing missions with stereo and super-spectral capabilities. Through agreements with the National Geospatial-Intelligence Agency NASA-Goddard Space Flight Center is acquiring Petabytes of global sub-meter to 4 meter resolution imagery from WorldView-1,2,3 Quickbird-2, GeoEye-1 and IKONOS-2 satellites. These data are a valuable no-direct cost for the enhancement of Earth observation research that supports US government interests. We are currently developing automated protocols for generating VHR products to support NASA's Earth observing missions. These include two primary foci: 1) on demand VHR 1/2° ortho mosaics - process VHR to surface reflectance, orthorectify and co-register multi-temporal 2 m multispectral imagery compiled as user defined regional mosaics. This will provide an easy access dataset to investigate biodiversity, tree canopy closure, surface water fraction, and cropped area for smallholder agriculture; and 2) on demand VHR digital elevation models (DEMs) - process stereo VHR to extract VHR DEMs with the NASA Ames stereo pipeline. This will benefit Earth surface studies on the cryosphere (glacier mass balance, flow rates and snow depth), hydrology (lake/water body levels, landslides, subsidence) and biosphere (forest structure, canopy height/cover) among others. Recent examples of products used in NASA Earth Science projects will be provided. This HEC API could foster surmounting prior spatial-temporal limitations while providing broad benefits to Earth Science.

Classification Accuracy Increase Using Multisensor Data Fusion

NASA Astrophysics Data System (ADS)

Makarau, A.; Palubinskas, G.; Reinartz, P.

2011-09-01

The practical use of very high resolution visible and near-infrared (VNIR) data is still growing (IKONOS, Quickbird, GeoEye-1, etc.) but for classification purposes the number of bands is limited in comparison to full spectral imaging. These limitations may lead to the confusion of materials such as different roofs, pavements, roads, etc. and therefore may provide wrong interpretation and use of classification products. Employment of hyperspectral data is another solution, but their low spatial resolution (comparing to multispectral data) restrict their usage for many applications. Another improvement can be achieved by fusion approaches of multisensory data since this may increase the quality of scene classification. Integration of Synthetic Aperture Radar (SAR) and optical data is widely performed for automatic classification, interpretation, and change detection. In this paper we present an approach for very high resolution SAR and multispectral data fusion for automatic classification in urban areas. Single polarization TerraSAR-X (SpotLight mode) and multispectral data are integrated using the INFOFUSE framework, consisting of feature extraction (information fission), unsupervised clustering (data representation on a finite domain and dimensionality reduction), and data aggregation (Bayesian or neural network). This framework allows a relevant way of multisource data combination following consensus theory. The classification is not influenced by the limitations of dimensionality, and the calculation complexity primarily depends on the step of dimensionality reduction. Fusion of single polarization TerraSAR-X, WorldView-2 (VNIR or full set), and Digital Surface Model (DSM) data allow for different types of urban objects to be classified into predefined classes of interest with increased accuracy. The comparison to classification results of WorldView-2 multispectral data (8 spectral bands) is provided and the numerical evaluation of the method in comparison to other established methods illustrates the advantage in the classification accuracy for many classes such as buildings, low vegetation, sport objects, forest, roads, rail roads, etc.

Spatial Analysis of Environmental Factors Related to Lyme Disease in Alabama by Means of NASA Earth Observation Systems

NASA Technical Reports Server (NTRS)

Renneboog, Nathan; Capilouto, Emily G.; Firsing, Stephen L., III; Levy, Kyle; McAllister, Marilyn; Roa, Kathryn; Setia,Shveta; Xie, Lili; Burnett, Donna; Luvall, Jeffrey C.

2009-01-01

This slide presentation reviews the epidemiology of Lyme Disease that accounts for more than 95% or vector borne diseases in the United States. The history, symptoms and the life cycle of the tick, the transmitting agent of Lyme Disease, a map that shows the cases reported to the CDC between1990 and 2006 and the number of cases in Alabama by year from 1986 to 2007. A NASA project is described, the goals of which are to (1) Demonstrate the presence of the chain of infection of Lyme disease in Alabama (2) Identify areas with environmental factors that support tick population using NASA Earth Observation Systems data in selected areas of Alabama and (3) Increase community awareness of Lyme disease and recommend primary and secondary prevention strategies. The remote sensing methods included: Analyzed Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and DigitalGlobe Quickbird satellite imagery from summer months and Performed image analyses in ER Mapper 7.1. Views from the ASTER and Quickbird land cover are shown, the Normalized Difference Vegetation Index (NDVI) algorithm was applied to all ASTER and Quickbird imagery. The use of the images to obtain the level of soil moisture is reviewed, and this analysis was used along with the NDVI, was used to identify the areas that support the tick population.

Geomorphology and vegetation mapping the ice-free terrains of the Western Antarctic Peninsula region using very high resolution imagery from an UAV

NASA Astrophysics Data System (ADS)

Vieira, G.; Mora, C.; Pina, P.; Bandeira, L.; Hong, S. G.

2014-12-01

The West Antarctic Peninsula (WAP) is one of the Earth's regions with a fastest warming signal since the 1950's with an increase of over +2.5 ºC in MAAT. Significant changes have been reported for glaciers, ice-shelves, sea-ice and also for the permafrost environment. Mapping and monitoring the ice-free areas of the WAP has been until recently limited by the available aerial photo surveys, but also by the scarce high resolution satellite imagery (e.g. QuickBird, WorldView, etc.) that are seriously constrained by the high cloudiness of the region. Recent developments in Unmanned Aerial Vehicles (UAV's), which have seen significant technological advances and price reduction in the last few years, allow for its systematical use for mapping and monitoring in remote environments. In the framework of projects PERMANTAR-3 (PTDC/AAG-GLO/3908/2012 - FCT) and 3DAntártida (Ciência Viva), we complement traditional terrain surveying and mapping, satellite remote sensing (SAR and optical) and D-GPS deformation monitoring, with the application of an UAV. In this communication, we present the results from the application of a Sensefly ebee UAV in mapping the vegetation and geomorphological processes (e.g. sorted circles), as well as for digital elevation model generation in a test site in Barton Pen., King George Isl.. The UAV is a lightweight (ci. 700g) aircraft, with a 96 cm wingspan, which is portable and easy to transport. It allows for up to 40 min flight time, with application of RGB or NIR cameras. We have tested the ebee successfully with winds up to 10 m/s and obtained aerial photos with a ground resolution of 4 cm/pixel. The digital orthophotomaps, high resolution DEM's together with field observations have allowed for deriving geomorphological maps with unprecedented detail and accuracy, providing new insight into the controls on the spatial distribution of geomorphological processes. The talk will focus on the first results from the field surveys of February and March 2014 and will also include some test data from the mountains of serra da Estrela, Portugal. New surveying is planned for the season of 2014-15 with mapping to be conducted in Livingston and King George Islands.

Mixing geometric and radiometric features for change classification

NASA Astrophysics Data System (ADS)

Fournier, Alexandre; Descombes, Xavier; Zerubia, Josiane

2008-02-01

Most basic change detection algorithms use a pixel-based approach. Whereas such approach is quite well defined for monitoring important area changes (such as urban growth monitoring) in low resolution images, an object based approach seems more relevant when the change detection is specifically aimed toward targets (such as small buildings and vehicles). In this paper, we present an approach that mixes radiometric and geometric features to qualify the changed zones. The goal is to establish bounds (appearance, disappearance, substitution ...) between the detected changes and the underlying objects. We proceed by first clustering the change map (containing each pixel bitemporal radiosity) in different classes using the entropy-kmeans algorithm. Assuming that most man-made objects have a polygonal shape, a polygonal approximation algorithm is then used in order to characterize the resulting zone shapes. Hence allowing us to refine the primary rough classification, by integrating the polygon orientations in the state space. Tests are currently conducted on Quickbird data.

Using High Resolution Remote Sensing Images to Investigate Hydrologic Connectivity and Degradation Thresholds along a Precipitation Gradient in Semiarid Australia

NASA Astrophysics Data System (ADS)

Azadi, S.; Saco, P. M.; Moreno-de las Heras, M.; Willgoose, G. R.

2016-12-01

Arid and semiarid landscapes are particularly sensitive to climatic and anthropogenic disturbances. Previous work has identified that these landscapes are prone to undergo critical degradation thresholds above which rehabilitation is difficult to achieve. This threshold behaviour is tightly linked to the overland flow redistribution and an increase in hydrologic connectivity associated with the climatic or anthropogenic disturbances. In fact, disturbances (such as wildfire, overgrazing or harvesting activities) can disrupt the spatial structure of vegetation, increase landscape hydrologic connectivity, trigger erosion and produce a substantial loss of water. All these effects can eventually affect ecosystem functionality (e.g. Rainfall Use Efficiency). In this study, we explore the impact of degradation processes induced by vegetation disturbances (mostly due to grazing pressure) on ecosystem functionality and connectivity along a precipitation gradient (250 mm to 490 mm annual average rainfall) using a combination of remote sensing observations and Digital Elevation Model data. The sites were carefully selected in the Mulga landscapes bioregion (New South Wales, Queensland) and in sites of the Northern Territory in Australia, which display similar vegetation characteristics and good quality rainfall information. Vegetation patterns and the percent of fractional cover were obtained from high resolution remote sensing images (IKONOS, QuickBird and Pleiades). We computed rainfall use efficiency and precipitation marginal response using local precipitation data and MODIS vegetation indices. We estimated mean Flowlength as an indicator of structural hydrologic connectivity using vegetation binary maps and digital elevation models. We compared the trends for several sites along the precipitation gradient, and found that disturbances substantially increase hydrologic connectivity following a threshold behaviour that affects landscape functionality. Though this threshold behaviour is found in all sites, the plots in higher rainfall landscapes show evidence of higher resilience.

Mapping post-fire forest regeneration and vegetation recovery using a combination of very high spatial resolution and hyperspectral satellite imagery

NASA Astrophysics Data System (ADS)

Mitri, George H.; Gitas, Ioannis Z.

2013-02-01

Careful evaluation of forest regeneration and vegetation recovery after a fire event provides vital information useful in land management. The use of remotely sensed data is considered to be especially suitable for monitoring ecosystem dynamics after fire. The aim of this work was to map post-fire forest regeneration and vegetation recovery on the Mediterranean island of Thasos by using a combination of very high spatial (VHS) resolution (QuickBird) and hyperspectral (EO-1 Hyperion) imagery and by employing object-based image analysis. More specifically, the work focused on (1) the separation and mapping of three major post-fire classes (forest regeneration, other vegetation recovery, unburned vegetation) existing within the fire perimeter, and (2) the differentiation and mapping of the two main forest regeneration classes, namely, Pinus brutia regeneration, and Pinus nigra regeneration. The data used in this study consisted of satellite images and field observations of homogeneous regenerated and revegetated areas. The methodology followed two main steps: a three-level image segmentation, and, a classification of the segmented images. The process resulted in the separation of classes related to the aforementioned objectives. The overall accuracy assessment revealed very promising results (approximately 83.7% overall accuracy, with a Kappa Index of Agreement of 0.79). The achieved accuracy was 8% higher when compared to the results reported in a previous work in which only the EO-1 Hyperion image was employed in order to map the same classes. Some classification confusions involving the classes of P. brutia regeneration and P. nigra regeneration were observed. This could be attributed to the absence of large and dense homogeneous areas of regenerated pine trees in the study area.

Generic Sensor Modeling Using Pulse Method

NASA Technical Reports Server (NTRS)

Helder, Dennis L.; Choi, Taeyoung

2005-01-01

Recent development of high spatial resolution satellites such as IKONOS, Quickbird and Orbview enable observation of the Earth's surface with sub-meter resolution. Compared to the 30 meter resolution of Landsat 5 TM, the amount of information in the output image was dramatically increased. In this era of high spatial resolution, the estimation of spatial quality of images is gaining attention. Historically, the Modulation Transfer Function (MTF) concept has been used to estimate an imaging system's spatial quality. Sometimes classified by target shapes, various methods were developed in laboratory environment utilizing sinusoidal inputs, periodic bar patterns and narrow slits. On-orbit sensor MTF estimation was performed on 30-meter GSD Landsat4 Thematic Mapper (TM) data from the bridge pulse target as a pulse input . Because of a high resolution sensor s small Ground Sampling Distance (GSD), reasonably sized man-made edge, pulse, and impulse targets can be deployed on a uniform grassy area with accurate control of ground targets using tarps and convex mirrors. All the previous work cited calculated MTF without testing the MTF estimator's performance. In previous report, a numerical generic sensor model had been developed to simulate and improve the performance of on-orbit MTF estimating techniques. Results from the previous sensor modeling report that have been incorporated into standard MTF estimation work include Fermi edge detection and the newly developed 4th order modified Savitzky-Golay (MSG) interpolation technique. Noise sensitivity had been studied by performing simulations on known noise sources and a sensor model. Extensive investigation was done to characterize multi-resolution ground noise. Finally, angle simulation was tested by using synthetic pulse targets with angles from 2 to 15 degrees, several brightness levels, and different noise levels from both ground targets and imaging system. As a continuing research activity using the developed sensor model, this report was dedicated to MTF estimation via pulse input method characterization using the Fermi edge detection and 4th order MSG interpolation method. The relationship between pulse width and MTF value at Nyquist was studied including error detection and correction schemes. Pulse target angle sensitivity was studied by using synthetic targets angled from 2 to 12 degrees. In this report, from the ground and system noise simulation, a minimum SNR value was suggested for a stable MTF value at Nyquist for the pulse method. Target width error detection and adjustment technique based on a smooth transition of MTF profile is presented, which is specifically applicable only to the pulse method with 3 pixel wide targets.

The ASTER emergency scheduling system: A new project linking near-real-time satellite monitoring of disasters to the acquisition of high-resolution remote sensing data

NASA Astrophysics Data System (ADS)

Ramsey, M.; Dehn, J.; Wessels, R.; Byrnes, J.; Duda, K.; Maldonado, L.; Dwyer, J.

2004-12-01

Numerous government agencies and university partnerships are currently utilizing orbital instruments with high-temporal/low-spatial resolution (e.g. MODIS, AVHRR) to monitor hazards. These hazards are varied and include both natural (volcanic eruptions, severe weather, wildfires, earthquake damage) and anthropogenic (environmental damage, urban terrorism). Although monitoring a hazardous situation is critical, a key strategy of NASA's Earth science program is to develop a scientific understanding of the Earth system and its responses to changes, as well as to improve prediction of hazard onset. In order to develop a quantitative scientific basis from which to model transient geological and climatological hazards, much higher spatial/spectral resolution datasets are required. Such datasets are sparse, currently available from certain government (e.g. ASTER, Hyperion) and commercial (e.g. IKONOS, QuickBird) instruments. However, only ASTER has the capability to acquire high spatial resolution data from the visible to thermal infrared (TIR) wavelength region in conjunction with digital elevation models (DEM) generation. These capabilities are particularly useful for numerous aspects of volcanic remote sensing. For example, multispectral TIR data are critical for monitoring low temperature anomalies and mapping both chemical and textural variations on volcanic surfaces. Because ASTER data are scheduled in advance and the raw data are sent to Japan for calibration processing, rapid acquisition of hazards becomes problematic. However, a "rapid response" mode does exist for ASTER data scheduling and processing, but its availability is limited and requires significant human interaction. A newly-funded NASA ASTER science team project seeks to link this ASTER rapid response pathway to larger-scale monitoring alerts, which are already in-place and in-use by other organizations. By refining the initial event detection criteria and improving interfaces between these organizations and the ASTER project, we expect to minimize lag time and use existing monitoring tools as triggers for the emergency response of ASTER. The first phase of this project will be integrated into the Alaska Volcano Observatory's current near-real-time volcanic monitoring system, which relies on high temporal/low spatial resolution orbital data. This synergy will allow small-scale activity to be targeted for science and response, and a calibration baseline between each sensor to be established. If successful, this will be the first time that high spatial resolution, multispectral satellite data will be routinely scheduled, acquired, and analyzed in a "rapid response" mode within an existing hazard monitoring framework. Initial testing of this system is now underway using data from previous eruptions in the north Pacific region, and modifications to the rapid data flow procedure within the ASTER science and support structure has begun.

Generating Ground Reference Data for a Global Impervious Surface Survey

NASA Technical Reports Server (NTRS)

Tilton, James C.; deColstoun, Eric Brown; Wolfe, Robert E.; Tan, Bin; Huang, Chengquan

2012-01-01

We are engaged in a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. The GLS data from Landsat provide an unprecedented opportunity to map global urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such as buildings, roads and parking lots. Finally, with GLS data available for the 1975, 1990, 2000, and 2005 time periods, and soon for the 2010 period, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. Our approach works across spatial scales using very high spatial resolution commercial satellite data to both produce and evaluate continental scale products at the 30m spatial resolution of Landsat data. We are developing continental scale training data at 1m or so resolution and aggregating these to 30m for training a regression tree algorithm. Because the quality of the input training data are critical, we have developed an interactive software tool, called HSegLearn, to facilitate the photo-interpretation of high resolution imagery data, such as Quickbird or Ikonos data, into an impervious versus non-impervious map. Previous work has shown that photo-interpretation of high resolution data at 1 meter resolution will generate an accurate 30m resolution ground reference when coarsened to that resolution. Since this process can be very time consuming when using standard clustering classification algorithms, we are looking at image segmentation as a potential avenue to not only improve the training process but also provide a semi-automated approach for generating the ground reference data. HSegLearn takes as its input a hierarchical set of image segmentations produced by the HSeg image segmentation program [1, 2]. HSegLearn lets an analyst specify pixel locations as being either positive or negative examples, and displays a classification of the study area based on these examples. For our study, the positive examples are examples of impervious surfaces and negative examples are examples of non-impervious surfaces. HSegLearn searches the hierarchical segmentation from HSeg for the coarsest level of segmentation at which selected positive example locations do not conflict with negative example locations and labels the image accordingly. The negative example regions are always defined at the finest level of segmentation detail. The resulting classification map can be then further edited at a region object level using the previously developed HSegViewer tool [3]. After providing an overview of the HSeg image segmentation program, we provide a detailed description of the HSegLearn software tool. We then give examples of using HSegLearn to generate ground reference data and conclude with comments on the effectiveness of the HSegLearn tool.

Benchmarking of data fusion algorithms in support of earth observation based Antarctic wildlife monitoring

NASA Astrophysics Data System (ADS)

Witharana, Chandi; LaRue, Michelle A.; Lynch, Heather J.

2016-03-01

Remote sensing is a rapidly developing tool for mapping the abundance and distribution of Antarctic wildlife. While both panchromatic and multispectral imagery have been used in this context, image fusion techniques have received little attention. We tasked seven widely-used fusion algorithms: Ehlers fusion, hyperspherical color space fusion, high-pass fusion, principal component analysis (PCA) fusion, University of New Brunswick fusion, and wavelet-PCA fusion to resolution enhance a series of single-date QuickBird-2 and Worldview-2 image scenes comprising penguin guano, seals, and vegetation. Fused images were assessed for spectral and spatial fidelity using a variety of quantitative quality indicators and visual inspection methods. Our visual evaluation elected the high-pass fusion algorithm and the University of New Brunswick fusion algorithm as best for manual wildlife detection while the quantitative assessment suggested the Gram-Schmidt fusion algorithm and the University of New Brunswick fusion algorithm as best for automated classification. The hyperspherical color space fusion algorithm exhibited mediocre results in terms of spectral and spatial fidelities. The PCA fusion algorithm showed spatial superiority at the expense of spectral inconsistencies. The Ehlers fusion algorithm and the wavelet-PCA algorithm showed the weakest performances. As remote sensing becomes a more routine method of surveying Antarctic wildlife, these benchmarks will provide guidance for image fusion and pave the way for more standardized products for specific types of wildlife surveys.

Monitoring changes in landscape pattern: use of Ikonos and Quickbird images.

PubMed

Alphan, Hakan; Çelik, Nil

2016-02-01

This paper aimed to analyze short-term changes in landscape pattern that primarily results from building development in the east coast of Mersin Province (Turkey). Three sites were selected. Ikonos (2003) and Quickbird (2009) images for these sites were classified, and land cover transformations were quantitatively analyzed using cross-tabulation of classification results. Changes in landscape structure were assessed by comparing the calculated values of area/edge and shape metrics for the earlier and later dates. Area/edge metrics included percentage of land and edge density, while shape metrics included perimeter-area ratio, fractal dimension, and related circumscribing circle (RCC) metrics. Orchards and buildings were dominating land cover classes. Variations in patch edge, size, and shapes were also analyzed and discussed. Degradation of prime agricultural areas due to building development and implications of such development on habitat fragmentation were highlighted.

An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

NASA Technical Reports Server (NTRS)

Tan, Bin; Brown de Colstoun, Eric; Wolfe, Robert E.; Tilton, James C.; Huang, Chengquan; Smith, Sarah E.

2012-01-01

An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to the phenology, solar-view geometry, and atmospheric condition etc. factors but not actual landcover difference. Finally, we will compare the classification results from screened and unscreened training samples to assess the improvement achieved by cleaning up the training samples. Keywords:

Effects of urban sprawl on agricultural land: a case study of Kahramanmaraş, Turkey.

PubMed

Doygun, Hakan

2009-11-01

The main objective of this study is to quantify areal loss of olive groves due to urban sprawl of the city of Kahramanmaraş, Turkey. Spatial changes were analysed by interpreting the digitized data derived from a black-white monoscopic aerial photograph taken in 1985, panchromatic IKONOS image of 2000 and two pan-sharpened Quickbird images of 2004 and 2006. Data obtained revealed that the area of olive groves decreased by 25% from 460.55 ha in 1985 to 344.46 in 2006, while the number of parcels increased from 170 to 445. Of the total areal loss, 60% was due to building constructions, with the rest being due to clear-cut for new residential gardens composed of exotic plants, new buildings, or new roads. Rapid population growth, increased land prices due to urban expansion, and abandonment of agricultural practices to construction of multi-storey buildings were the main causes of the process that transformed the olive groves into urbanized areas. Results pointed to an urgent need to (1) revise the national and municipal land management practices, (2) balance the gap between the short- and long-term economic benefits that urban and community development plans ignore, and (3) monitor land-use changes periodically by using high resolution satellite images.

Satellite imagery time series for the detection of looting activities at archaeological sites

NASA Astrophysics Data System (ADS)

Coluzzi, Rosa; Lasaponara, Rosa; Masini, Nicola

2010-05-01

Clandestine excavations is one of the biggest man-made risks which affect the archaeological heritage, especially in some countries of Southern America, Asia and Middle East. To contrast and limit this phenomenon a systematic monitoring is required. The protection of archaeological heritage from clandestine excavations is generally based on a direct surveillance, but it is time consuming and expensive for remote archaeological sites and non practicable in several countries due to military or political restrictions. In such conditions, Very high resolution (VHR) satellite imagery offer a suitable chance thanks to their global coverage and frequent revisitation times. This paper is focused on the results we obtained from ongoing research focused on the use of VHR satellite images for the identification and monitoring of looting. A time series of satellite images (QuickBird-2 and World-View-1) has been exploited to analyze and monitor archaeological looting in the Nasca Ceremonial Centre of Cahuachi (Peru) dating back between the 4th centurt B.C. and the 4th century A.D. The Cahuachi study case herein presented put in evidence the limits of VHR satellite imagery in detecting features linked to looting activity. This suggested to experience local spatial autocorrelation statistics which allowed us to improve the reliability of satellite in mapping looted area.

Arctic Digital Elevation Models (DEMs) generated by Surface Extraction from TIN-Based Searchspace Minimization (SETSM) algorithm from RPCs-based Imagery

NASA Astrophysics Data System (ADS)

Noh, M. J.; Howat, I. M.; Porter, C. C.; Willis, M. J.; Morin, P. J.

2016-12-01

The Arctic is undergoing rapid change associated with climate warming. Digital Elevation Models (DEMs) provide critical information for change measurement and infrastructure planning in this vulnerable region, yet the existing quality and coverage of DEMs in the Arctic is poor. Low contrast and repeatedly-textured surfaces, such as snow and glacial ice and mountain shadows, all common in the Arctic, challenge existing stereo-photogrammetric techniques. Submeter resolution, stereoscopic satellite imagery with high geometric and radiometric quality, and wide spatial coverage are becoming increasingly accessible to the scientific community. To utilize these imagery for extracting DEMs at a large scale over glaciated and high latitude regions we developed the Surface Extraction from TIN-based Searchspace Minimization (SETSM) algorithm. SETSM is fully automatic (i.e. no search parameter settings are needed) and uses only the satellite rational polynomial coefficients (RPCs). Using SETSM, we have generated a large number of DEMs (> 100,000 scene pair) from WorldView, GeoEye and QuickBird stereo images collected by DigitalGlobe Inc. and archived by the Polar Geospatial Center (PGC) at the University of Minnesota through an academic licensing program maintained by the US National Geospatial-Intelligence Agency (NGA). SETSM is the primary DEM generation software for the US National Science Foundation's ArcticDEM program, with the objective of generating high resolution (2-8m) topography for the entire Arctic landmass, including seamless DEM mosaics and repeat DEM strips for change detection. ArcticDEM is collaboration between multiple US universities, governmental agencies and private companies, as well as international partners assisting with quality control and registration. ArcticDEM is being produced using the petascale Blue Waters supercomputer at the National Center for Supercomputer Applications at the University of Illinois. In this paper, we introduce the SETSM algorithm and the processing system used for the ArcticDEM project, as well as provide notable examples of ArcticDEM products.

[Application of optical flow dynamic texture in land use/cover change detection].

PubMed

Yan, Li; Gong, Yi-Long; Zhang, Yi; Duan, Wei

2014-11-01

In the present study, a novel change detection approach for high resolution remote sensing images is proposed based on the optical flow dynamic texture (OFDT), which could achieve the land use & land cover change information automatically with a dynamic description of ground-object changes. This paper describes the ground-object gradual change process from the principle using optical flow theory, which breaks the ground-object sudden change hypothesis in remote sensing change detection methods in the past. As the steps of this method are simple, it could be integrated in the systems and software such as Land Resource Management and Urban Planning software that needs to find ground-object changes. This method takes into account the temporal dimension feature between remote sensing images, which provides a richer set of information for remote sensing change detection, thereby improving the status that most of the change detection methods are mainly dependent on the spatial dimension information. In this article, optical flow dynamic texture is the basic reflection of changes, and it is used in high resolution remote sensing image support vector machine post-classification change detection, combined with spectral information. The texture in the temporal dimension which is considered in this article has a smaller amount of data than most of the textures in the spatial dimensions. The highly automated texture computing has only one parameter to set, which could relax the onerous manual evaluation present status. The effectiveness of the proposed approach is evaluated with the 2011 and 2012 QuickBird datasets covering Duerbert Mongolian Autonomous County of Daqing City, China. Then, the effects of different optical flow smooth coefficient and the impact on the description of the ground-object changes in the method are deeply analyzed: The experiment result is satisfactory, with an 87.29% overall accuracy and an 0.850 7 Kappa index, and the method achieves better performance than the post-classification change detection methods using spectral information only.

Bathymetric mapping of shallow water surrounding Dongsha Island using QuickBird image

NASA Astrophysics Data System (ADS)

Li, Dongling; Zhang, Huaguo; Lou, Xiulin

2018-03-01

This article presents an experiment of water depth inversion using the band ratio method in Dongsha Island shallow water. The remote sensing data is from QuickBird satellite on April 19, 2004. The bathymetry result shows an extensive agreement with the charted depths. 129 points from the chart depth data were chosen to evaluate the accuracy of the inversion depth. The results show that when the water depth is less than 20m, the inversion depth is accord with the chart, while the water depth is more than 20m, the inversion depth is still among 15- 25m. Therefore, the remote sensing methods can only be effective with the inversion of 20m in Dongsha Island shallow water, rather than in deep water area. The total of 109 depth points less than 20m were used to evaluate the accuracy, the root mean square error is 2.2m.

Shoreline change after 12 years of tsunami in Banda Aceh, Indonesia: a multi-resolution, multi-temporal satellite data and GIS approach

NASA Astrophysics Data System (ADS)

Sugianto, S.; Heriansyah; Darusman; Rusdi, M.; Karim, A.

2018-04-01

The Indian Ocean Tsunami event on the 26 December 2004 has caused severe damage of some shorelines in Banda Aceh City, Indonesia. Tracing back the impact can be seen using remote sensing data combined with GIS. The approach is incorporated with image processing to analyze the extent of shoreline changes with multi-temporal data after 12 years of tsunami. This study demonstrates multi-resolution and multi-temporal satellite images of QuickBird and IKONOS to demarcate the shoreline of Banda Aceh shoreline from before and after tsunami. The research has demonstrated a significant change to the shoreline in the form of abrasion between 2004 and 2005 from few meters to hundred meters’ change. The change between 2004 and 2011 has not returned to the previous stage of shoreline before the tsunami, considered post tsunami impact. The abrasion occurs between 18.3 to 194.93 meters. Further, the change in 2009-2011 shows slowly change of shoreline of Banda Aceh, considered without impact of tsunami e.g. abrasion caused by ocean waves that erode the coast and on specific areas accretion occurs caused by sediment carried by the river flow into the sea near the shoreline of the study area.

U.S. Government Open Internet Access to Sub-meter Satellite Data

NASA Technical Reports Server (NTRS)

Neigh, Christopher S. R> ; Masek, Jeffery G.; Nickeson, Jaime E.

2012-01-01

The National Geospatial-Intelligence Agency (NGA) has contracted United States commercial remote sensing companies GeoEye and Digital Globe to provide very high resolution commercial quality satellite imagery to federal/state government agencies and those projects/people who support government interests. Under NextView contract terms, those engaged in official government programs/projects can gain online access to NGA's vast global archive. Additionally, data from vendor's archives of IKONOS-2 (IK-2), OrbView-3 (OB-3), GeoEye-1 (GE-1), QuickBird-1 (QB-1), WorldView-1 (WV-1), and WorldView-2 (WV-2), sensors can also be requested under these agreements. We report here the current extent of this archive, how to gain access, and the applications of these data by Earth science investigators to improve discoverability and community use of these data. Satellite commercial quality imagery (CQI) at very high resolution (< 1 m) (here after referred to as CQI) over the past decade has become an important data source to U.S. federal, state, and local governments for many different purposes. The rapid growth of free global CQI data has been slow to disseminate to NASA Earth Science community and programs such as the Land-Cover Land-Use Change (LCLUC) program which sees potential benefit from unprecedented access. This article evolved from a workshop held on February 23rd, 2012 between representatives from NGA, NASA, and NASA LCLUC Scientists discussion on how to extend this resource to a broader license approved community. Many investigators are unaware of NGA's archive availability or find it difficult to access CQI data from NGA. Results of studies, both quality and breadth, could be improved with CQI data by combining them with other moderate to coarse resolution passive optical Earth observation remote sensing satellites, or with RADAR or LiDAR instruments to better understand Earth system dynamics at the scale of human activities. We provide the evolution of this effort, a guide for qualified user access, and describe current to potential use of these data in earth science.

Land loss due to recent hurricanes in coastal Louisiana, U.S.A.

USGS Publications Warehouse

Palaseanu-Lovejoy, Monica; Kranenburg, Christine J.; Barras, John A.; Brock, John C.

2013-01-01

The aim of this study is to improve estimates of wetland land loss in two study regions of coastal Louisiana, U.S.A., due to the extreme storms that impacted the region between 2004 and 2009. The estimates are based on change-detection-mapping analysis that incorporates pre and postlandfall (Hurricanes Katrina, Rita, Gustav, and Ike) fractional-water classifications using a combination of high-resolution (<5 m) QuickBird, IKONOS, and GeoEye-1, and medium-resolution (30 m) Landsat Thematic Mapper satellite imagery. This process was applied in two study areas: the Hackberry area located in the southwestern part of chenier plain that was impacted by Hurricanes Rita (September 24, 2005) and Ike (September 13, 2008), and the Delacroix area located in the eastern delta plain that was impacted by Hurricanes Katrina (August 29, 2005) and Gustav (September 1, 2008). In both areas, effects of the hurricanes include enlargement of existing bodies of open water and erosion of fringing marsh areas. Surge-removed marsh was easily identified in stable marshes but was difficult to identify in degraded or flooded marshes. Persistent land loss in the Hackberry area due to Hurricane Rita was approximately 5.8% and increased by an additional 7.9% due to Hurricane Ike, although this additional area may yet recover. About 80% of the Hackberry study area remained unchanged since 2003. In the Delacroix area, persistent land loss due to Hurricane Katrina measured approximately 4.9% of the study area, while Hurricane Gustav caused minimal impact of 0.6% land loss by November 2009. Continued recovery in this area may further erase Hurricane Gustav's impact in the absence of new storm events.

Spatial variation and seasonal dynamics of leaf-area index in the arctic tundra-implications for linking ground observations and satellite images

NASA Astrophysics Data System (ADS)

Juutinen, Sari; Virtanen, Tarmo; Kondratyev, Vladimir; Laurila, Tuomas; Linkosalmi, Maiju; Mikola, Juha; Nyman, Johanna; Räsänen, Aleksi; Tuovinen, Juha-Pekka; Aurela, Mika

2017-09-01

Vegetation in the arctic tundra typically consists of a small-scale mosaic of plant communities, with species differing in growth forms, seasonality, and biogeochemical properties. Characterization of this variation is essential for understanding and modeling the functioning of the arctic tundra in global carbon cycling, as well as for evaluating the resolution requirements for remote sensing. Our objective was to quantify the seasonal development of the leaf-area index (LAI) and its variation among plant communities in the arctic tundra near Tiksi, coastal Siberia, consisting of graminoid, dwarf shrub, moss, and lichen vegetation. We measured the LAI in the field and used two very-high-spatial resolution multispectral satellite images (QuickBird and WorldView-2), acquired at different phenological stages, to predict landscape-scale patterns. We used the empirical relationships between the plant community-specific LAI and degree-day accumulation (0 °C threshold) and quantified the relationship between the LAI and satellite NDVI (normalized difference vegetation index). Due to the temporal difference between the field data and satellite images, the LAI was approximated for the imagery dates, using the empirical model. LAI explained variation in the NDVI values well (R 2 adj. 0.42-0.92). Of the plant functional types, the graminoid LAI showed the largest seasonal amplitudes and was the main cause of the varying spatial patterns of the NDVI and the related LAI between the two images. Our results illustrate how the short growing season, rapid development of the LAI, yearly climatic variation, and timing of the satellite data should be accounted for in matching imagery and field verification data in the Arctic region.

Radiometric and geometric characteristics of Pleiades images

NASA Astrophysics Data System (ADS)

Jacobsen, K.; Topan, H.; Cam, A.; Özendi, M.; Oruc, M.

2014-11-01

Pleiades images are distributed with 50 cm ground sampling distance (GSD) even if the physical resolution for nadir images is just 70 cm. By theory this should influence the effective GSD determined by means of point spread function at image edges. Nevertheless by edge enhancement the effective GSD can be improved, but this should cause enlarged image noise. Again image noise can be reduced by image restoration. Finally even optimized image restoration cannot improve the image information from 70 cm to 50 cm without loss of details, requiring a comparison of Pleiades image details with other very high resolution space images. The image noise has been determined by analysis of the whole images for any sub-area with 5 pixels times 5 pixels. Based on the standard deviation of grey values in the small sub-areas the image noise has been determined by frequency analysis. This leads to realistic results, checked by test targets. On the other hand the visual determination of image noise based on apparently homogenous sub-areas results in too high values because the human eye is not able to identify small grey value differences - it is limited to just approximately 40 grey value steps over the available gray value range, so small difference in grey values cannot be seen, enlarging results of a manual noise determination. A tri-stereo combination of Pleiades 1A in a mountainous, but partially urban, area has been analyzed and compared with images of the same area from WorldView-1, QuickBird and IKONOS. The image restoration of the Pleiades images is very good, so the effective image resolution resulted in a factor 1.0, meaning that the effective resolution corresponds to the nominal resolution of 50 cm. This does not correspond to the physical resolution of 70 cm, but by edge enhancement the steepness of the grey value profile across the edge can be enlarged, reducing the width of the point spread function. Without additional filtering edge enhancement enlarges the image noise, but the average image noise of approximately 1.0 grey values related to 8 bit images is very small, not indicating the edge enhancement and the down sampling of the GSD from 70 cm to 50 cm. So the direct comparison with the other images has to give the answer if the image quality of Pleiades images is on similar level as corresponding to the nominal resolution. As expected with the image geometry there is no problem. This is the case for all used space images in the test area, where the point identification limits the accuracy of the scene orientation.

Mapping Impervious Surfaces Globally at 30m Resolution Using Global Land Survey Data

NASA Technical Reports Server (NTRS)

DeColstoun, Eric Brown; Huang, Chengquan; Tan, Bin; Smith, Sarah Elizabeth; Phillips, Jacqueline; Wang, Panshi; Ling, Pui-Yu; Zhan, James; Li, Sike; Taylor, Michael P.;

Mapping Impervious Surfaces Globally at 30m Resolution Using Landsat Global Land Survey Data

NASA Astrophysics Data System (ADS)

Brown de Colstoun, E.; Huang, C.; Wolfe, R. E.; Tan, B.; Tilton, J.; Smith, S.; Phillips, J.; Wang, P.; Ling, P.; Zhan, J.; Xu, X.; Taylor, M. P.

2013-12-01

Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (~2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified archive of the National Geospatial Intelligence Agency (NGA). For each continental area several million training pixels are derived by analysts using image segmentation algorithms and tools and then aggregated to the 30m resolution of Landsat. Here we will discuss the production/testing of this massive data set for Europe, North and South America and Africa, including assessments of the 2010 surface reflectance data. This type of analysis is only possible because of the availability of long term 30m data sets from GLS and shows much promise for integration of Landsat 8 data in the future.

Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery.

PubMed

Belgiu, Mariana; Dr Guţ, Lucian

2014-10-01

Although multiresolution segmentation (MRS) is a powerful technique for dealing with very high resolution imagery, some of the image objects that it generates do not match the geometries of the target objects, which reduces the classification accuracy. MRS can, however, be guided to produce results that approach the desired object geometry using either supervised or unsupervised approaches. Although some studies have suggested that a supervised approach is preferable, there has been no comparative evaluation of these two approaches. Therefore, in this study, we have compared supervised and unsupervised approaches to MRS. One supervised and two unsupervised segmentation methods were tested on three areas using QuickBird and WorldView-2 satellite imagery. The results were assessed using both segmentation evaluation methods and an accuracy assessment of the resulting building classifications. Thus, differences in the geometries of the image objects and in the potential to achieve satisfactory thematic accuracies were evaluated. The two approaches yielded remarkably similar classification results, with overall accuracies ranging from 82% to 86%. The performance of one of the unsupervised methods was unexpectedly similar to that of the supervised method; they identified almost identical scale parameters as being optimal for segmenting buildings, resulting in very similar geometries for the resulting image objects. The second unsupervised method produced very different image objects from the supervised method, but their classification accuracies were still very similar. The latter result was unexpected because, contrary to previously published findings, it suggests a high degree of independence between the segmentation results and classification accuracy. The results of this study have two important implications. The first is that object-based image analysis can be automated without sacrificing classification accuracy, and the second is that the previously accepted idea that classification is dependent on segmentation is challenged by our unexpected results, casting doubt on the value of pursuing 'optimal segmentation'. Our results rather suggest that as long as under-segmentation remains at acceptable levels, imperfections in segmentation can be ruled out, so that a high level of classification accuracy can still be achieved.

Point- and line-based transformation models for high resolution satellite image rectification

NASA Astrophysics Data System (ADS)

Abd Elrahman, Ahmed Mohamed Shaker

Rigorous mathematical models with the aid of satellite ephemeris data can present the relationship between the satellite image space and the object space. With government funded satellites, access to calibration and ephemeris data has allowed the development and use of these models. However, for commercial high-resolution satellites, which have been recently launched, these data are withheld from users, and therefore alternative empirical models should be used. In general, the existing empirical models are based on the use of control points and involve linking points in the image space and the corresponding points in the object space. But the lack of control points in some remote areas and the questionable accuracy of the identified discrete conjugate points provide a catalyst for the development of algorithms based on features other than control points. This research, concerned with image rectification and 3D geo-positioning determination using High-Resolution Satellite Imagery (HRSI), has two major objectives. First, the effects of satellite sensor characteristics, number of ground control points (GCPs), and terrain elevation variations on the performance of several point based empirical models are studied. Second, a new mathematical model, using only linear features as control features, or linear features with a minimum number of GCPs, is developed. To meet the first objective, several experiments for different satellites such as Ikonos, QuickBird, and IRS-1D have been conducted using different point based empirical models. Various data sets covering different terrain types are presented and results from representative sets of the experiments are shown and analyzed. The results demonstrate the effectiveness and the superiority of these models under certain conditions. From the results obtained, several alternatives to circumvent the effects of the satellite sensor characteristics, the number of GCPs, and the terrain elevation variations are introduced. To meet the second objective, a new model named the Line Based Transformation Model (LBTM) is developed for HRSI rectification. The model has the flexibility to either solely use linear features or use linear features and a number of control points to define the image transformation parameters. Unlike point features, which must be explicitly defined, linear features have the advantage that they can be implicitly defined by any segment along the line. (Abstract shortened by UMI.)

An improved method for precise automatic co-registration of moderate and high-resolution spacecraft imagery

NASA Technical Reports Server (NTRS)

Bryant, Nevin A.; Logan, Thomas L.; Zobrist, Albert L.

2006-01-01

Improvements to the automated co-registration and change detection software package, AFIDS (Automatic Fusion of Image Data System) has recently completed development for and validation by NGA/GIAT. The improvements involve the integration of the AFIDS ultra-fine gridding technique for horizontal displacement compensation with the recently evolved use of Rational Polynomial Functions/ Coefficients (RPFs/RPCs) for image raster pixel position to Latitude/Longitude indexing. Mapping and orthorectification (correction for elevation effects) of satellite imagery defies exact projective solutions because the data are not obtained from a single point (like a camera), but as a continuous process from the orbital path. Standard image processing techniques can apply approximate solutions, but advances in the state-of-the-art had to be made for precision change-detection and time-series applications where relief offsets become a controlling factor. The earlier AFIDS procedure required the availability of a camera model and knowledge of the satellite platform ephemeredes. The recent design advances connect the spacecraft sensor Rational Polynomial Function, a deductively developed model, with the AFIDS ultrafine grid, an inductively developed representation of the relationship raster pixel position to latitude /longitude. As a result, RPCs can be updated by AFIDS, a situation often necessary due to the accuracy limits of spacecraft navigation systems. An example of precision change detection will be presented from Quickbird.

Climate impacts on environmental risks evaluated from space: a conceptual approach to the case of Rift Valley Fever in Senegal.

PubMed

Tourre, Yves M; Lacaux, Jean-Pierre; Vignolles, Cécile; Lafaye, Murielle

2009-11-11

Climate and environment vary across many spatio-temporal scales, including the concept of climate change, which impact on ecosystems, vector-borne diseases and public health worldwide. To develop a conceptual approach by mapping climatic and environmental conditions from space and studying their linkages with Rift Valley Fever (RVF) epidemics in Senegal. Ponds in which mosquitoes could thrive were identified from remote sensing using high-resolution SPOT-5 satellite images. Additional data on pond dynamics and rainfall events (obtained from the Tropical Rainfall Measuring Mission) were combined with hydrological in-situ data. Localisation of vulnerable hosts such as penned cattle (from QuickBird satellite) were also used. Dynamic spatio-temporal distribution of Aedes vexans density (one of the main RVF vectors) is based on the total rainfall amount and ponds' dynamics. While Zones Potentially Occupied by Mosquitoes are mapped, detailed risk areas, i.e. zones where hazards and vulnerability occur, are expressed in percentages of areas where cattle are potentially exposed to mosquitoes' bites. This new conceptual approach, using precise remote-sensing techniques, simply relies upon rainfall distribution also evaluated from space. It is meant to contribute to the implementation of operational early warning systems for RVF based on both natural and anthropogenic climatic and environmental changes. In a climate change context, this approach could also be applied to other vector-borne diseases and places worldwide.

Assimilation of measurement data in hydrodynamic modeling

NASA Astrophysics Data System (ADS)

Karamuz, Emilia; Romanowicz, Renata J.

2016-04-01

This study focuses on developing methods to combine ground-based data from operational monitoring with data from satellite imaging to obtain a more accurate evaluation of flood inundation extents. The distributed flow model MIKE 11 was used to determine the flooding areas for a flood event with available satellite data. Model conditioning was based on the integrated use of data from remote measurement techniques and traditional data from gauging stations. Such conditioning of the model improves the quality of fit of the model results. The use of high resolution satellite images (from IKONOS, QuickBird e.t.c) and LiDAR Digital Elevation Model (DEM) allows information on water levels to be extended to practically any chosen cross-section of the tested section of the river. This approach allows for a better assessment of inundation extent, particularly in areas with a scarce network of gauging stations. We apply approximate Bayesian analysis to integrate the information on flood extent originating from different sources. The approach described above was applied to the Middle River Vistula reach, from the Zawichost to Warsaw gauging stations. For this part of the river the detailed geometry of the river bed and floodplain data were available. Finally, three selected sub-sections were analyzed with the most suitable satellite images of inundation area. ACKNOWLEDGEMENTS This research was supported by the Institute of Geophysics Polish Academy of Sciences through the Young Scientist Grant no. 3b/IGF PAN/2015.

Remote sensing of a dynamic sub-arctic peatland reservoir using optical and synthetic aperture radar data

NASA Astrophysics Data System (ADS)

Larter, Jarod Lee

Stephens Lake, Manitoba is an example of a peatland reservoir that has undergone physical changes related to mineral erosion and peatland disintegration processes since its initial impoundment. In this thesis I focused on the processes of peatland upheaval, transport, and disintegration as the primary drivers of dynamic change within the reservoir. The changes related to these processes are most frequent after initial reservoir impoundment and decline over time. They continue to occur over 35 years after initial flooding. I developed a remote sensing approach that employs both optical and microwave sensors for discriminating land (Le. floating peatlands, forested land, and barren land) from open water within the reservoir. High spatial resolution visible and near-infrared (VNIR) optical data obtained from the QuickBird satellite, and synthetic aperture radar (SAR) microwave data obtained from the RADARSAT-1 satellite were implemented. The approach was facilitated with a Geographic Information System (GIS) based validation map for the extraction of optical and SAR pixel data. Each sensor's extracted data set was first analyzed separately using univariate and multivariate statistical methods to determine the discriminant ability of each sensor. The initial analyses were followed by an integrated sensor approach; the development of an image classification model; and a change detection analysis. Results showed excellent (> 95%) classification accuracy using QuickBird satellite image data. Discrimination and classification of studied land cover classes using SAR image texture data resulted in lower overall classification accuracies (˜ 60%). SAR data classification accuracy improved to > 90% when classifying only land and water, demonstrating SAR's utility as a land and water mapping tool. An integrated sensor data approach showed no considerable improvement over the use of optical satellite image data alone. An image classification model was developed that could be used to map both detailed land cover classes and the land and water interface within the reservoir. Change detection analysis over a seven year period indicated that physical changes related to mineral erosion, peatland upheaval, transport, and disintegration, and operational water level variation continue to take place in the reservoir some 35 years after initial flooding. This thesis demonstrates the ability of optical and SAR satellite image remote sensing data sets to be used in an operational context for the routine discrimination of the land and water boundaries within a dynamic peatland reservoir. Future monitoring programs would benefit most from a complementary image acquisition program in which SAR images, known for their acquisition reliability under cloud cover, are acquired along with optical images given their ability to discriminate land cover classes in greater detail.

From local spectral measurements to maps of vegetation cover and biomass on the Qinghai-Tibet-Plateau: Do we need hyperspectral information?

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Lehnert, Lukas W.; Wang, Yun; Reudenbach, Christoph; Nauss, Thomas; Bendix, Jörg

2017-03-01

Though the relevance of pasture degradation on the Qinghai-Tibet Plateau (QTP) is widely postulated, its extent is still unknown. Due to the enormous spatial extent, remote sensing provides the only possibility to investigate pasture degradation via frequently used proxies such as vegetation cover and aboveground biomass (AGB). However, unified remote sensing approaches are still lacking. This study tests the applicability of hyper- and multispectral in situ measurements to map vegetation cover and AGB on regional scales. Using machine learning techniques, it is tested whether the full hyperspectral information is needed or if multispectral information is sufficient to accurately estimate pasture degradation proxies. To regionalize pasture degradation proxies, the transferability of the locally derived ML-models to high resolution multispectral satellite data is assessed. 1183 hyperspectral measurements and vegetation records were performed at 18 locations on the QTP. Random Forests models with recursive feature selection were trained to estimate vegetation cover and AGB using narrow-band indices (NBI) as predictors. Separate models were calculated using NBI from hyperspectral data as well as from the same data resampled to WorldView-2, QuickBird and RapidEye channels. The hyperspectral results were compared to the multispectral results. Finally, the models were applied to satellite data to map vegetation cover and AGB on a regional scale. Vegetation cover was accurately predicted by Random Forest if hyperspectral measurements were used (cross validated R2 = 0.89). In contrast, errors in AGB estimations were considerably higher (cross validated R2 = 0.32). Only small differences in accuracy were observed between the models based on hyperspectral compared to multispectral data. The application of the models to satellite images generally resulted in an increase of the estimation error. Though this reflects the challenge of applying in situ measurements to satellite data, the results still show a high potential to map pasture degradation proxies on the QTP. Thus, this study presents robust methodology to remotely detect and monitor pasture degradation at high spatial resolutions.

Volumetric Forest Change Detection Through Vhr Satellite Imagery

NASA Astrophysics Data System (ADS)

Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

2016-06-01

Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in six case studies located in Austria, Cyprus, Spain, Switzerland and Turkey, using optical data from different sensors and with the purpose to monitor forest with different geometric characteristics. The validation run on Cyprus dataset is reported and commented.

Coral colonisation of a shallow reef flat in response to rising sea level: quantification from 35 years of remote sensing data at Heron Island, Australia

NASA Astrophysics Data System (ADS)

Scopélitis, J.; Andréfouët, S.; Phinn, S.; Done, T.; Chabanet, P.

2011-12-01

Observations made on Heron Island reef flat during the 1970s-1990s highlighted the importance of rapid change in hydrodynamics and accommodation space for coral development. Between the 1940s and the 1990s, the minimum reef-flat top water level varied by some tens of centimetres, successively down then up, in rapid response to local engineering works. Coral growth followed sea-level variations and was quantified here for several coral communities using horizontal two-dimensional above water remotely sensed observations. This required seven high spatial resolution aerial photographs and Quickbird satellite images spanning 35 years: 1972, 1979, 1990, 1992, 2002, 2006 and 2007. The coral growth dynamics followed four regimes corresponding to artificially induced changes in sea levels: 1972-1979 (lowest growth rate): no detectable coral development, due to high tidal currents and minimum mean low-tide water level; 1979-1991 (higher growth rate): horizontal coral development promoted by calmer hydrodynamic conditions; 1991-2001(lower growth rate): vertical coral development, induced by increased local sea level by ~12 cm due to construction of new bund walls; 2001-2007 (highest growth rate): horizontal coral development after that vertical growth had become limited by sea level. This unique time-series displays a succession of ecological stage comprising a `catch-up' dynamic in response to a rapid local sea-level rise in spite of the occurrences of the most severe bleaching events on record (1998, 2002) and the decreasing calcification rates reported in massive corals in the northern part of the Great Barrier Reef.

Possible return of Acropora cervicornis at Pulaski Shoal, Dry Tortugas National Park, Florida

USGS Publications Warehouse

Lidz, Barbara H.; Zawada, David G.

2013-01-01

Seabed classification is essential to assessing environmental associations and physical status in coral reef ecosystems. At Pulaski Shoal in Dry Tortugas National Park, Florida, nearly continuous underwater-image coverage was acquired in 15.5 hours in 2009 along 70.2 km of transect lines spanning ~0.2 km2. The Along-Track Reef-Imaging System (ATRIS), a boat-based, high-speed, digital imaging system, was used. ATRIS-derived benthic classes were merged with a QuickBird satellite image to create a habitat map that defines areas of senile coral reef, carbonate sand, seagrasses, and coral rubble. This atypical approach of starting with extensive, high-resolution in situ imagery and extrapolating between transect lines using satellite imagery leverages the strengths of each remote-sensing modality. The ATRIS images also captured the spatial distribution of two species once common on now-degraded Florida-Caribbean coral reefs: the stony staghorn coral Acropora cervicornis, a designated threatened species, and the long-spined urchin Diadema antillarum. This article documents the utility of ATRIS imagery for quantifying number and estimating age of A. cervicornis colonies (n = 400, age range, 5–11 y) since the severe hypothermic die-off in the Dry Tortugas in 1976–77. This study is also the first to document the largest number of new colonies of A. cervicornis tabulated in an area of the park where coral-monitoring stations maintained by the Fish and Wildlife Research Institute have not been established. The elevated numbers provide an updated baseline for tracking revival of this species at Pulaski Shoal.

The Joint Agency Commercial Imagery Evaluation (JACIE) Team: Overview and IKONOS Joint Characterization Approach

NASA Technical Reports Server (NTRS)

Zanoni, Vicki; Ryan, Robert; Pagnutti, Mary; Baldridge, Braxton; Roylance, Spencer; Snyder, Greg; Lee, George; Stanley, Tom

2002-01-01

An overview of the Joint Agency Commercial Imagery Evalation (JACIE) team is presented. JACIE, composed of the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA), and the U.S. Geological Survey (USGS), was formed to leverage government agencies' capabilities for the characterization of commercial remote sensing data. Each JACIE agency purchases, or plans to purchase, commercial imagery to support its research and applications. It is critical that the data be assessed for its accuracy and utility. Through JACIE, NASA, NIMA, and USGS jointly characterized image products from Space Imaging's IKONOS satellite. Each JACIE agency performed an aspect of the characterization based on its expertise. NASA and its university partners performed a system characterization focusing on radiometric calibration, geopositional accuracy, and spatial resolution assessment; NIMA performed image interpretability and feature extraction evaluations; and USGS assessed geopositional accuracy of several IKONOS products. The JACIE team purchased IKONOS imagery of several study sites to perform the assessments and presented results at an industry-government workshop. Future plans for JACIE include the characterization of DigitalGlobe's QuickBird-2 image products.

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

Comparing Pixel- and Object-Based Approaches in Effectively Classifying Wetland-Dominated Landscapes

PubMed Central

Berhane, Tedros M.; Lane, Charles R.; Wu, Qiusheng; Anenkhonov, Oleg A.; Chepinoga, Victor V.; Autrey, Bradley C.; Liu, Hongxing

2018-01-01

Wetland ecosystems straddle both terrestrial and aquatic habitats, performing many ecological functions directly and indirectly benefitting humans. However, global wetland losses are substantial. Satellite remote sensing and classification informs wise wetland management and monitoring. Both pixel- and object-based classification approaches using parametric and non-parametric algorithms may be effectively used in describing wetland structure and habitat, but which approach should one select? We conducted both pixel- and object-based image analyses (OBIA) using parametric (Iterative Self-Organizing Data Analysis Technique, ISODATA, and maximum likelihood, ML) and non-parametric (random forest, RF) approaches in the Barguzin Valley, a large wetland (~500 km2) in the Lake Baikal, Russia, drainage basin. Four Quickbird multispectral bands plus various spatial and spectral metrics (e.g., texture, Non-Differentiated Vegetation Index, slope, aspect, etc.) were analyzed using field-based regions of interest sampled to characterize an initial 18 ISODATA-based classes. Parsimoniously using a three-layer stack (Quickbird band 3, water ratio index (WRI), and mean texture) in the analyses resulted in the highest accuracy, 87.9% with pixel-based RF, followed by OBIA RF (segmentation scale 5, 84.6% overall accuracy), followed by pixel-based ML (83.9% overall accuracy). Increasing the predictors from three to five by adding Quickbird bands 2 and 4 decreased the pixel-based overall accuracy while increasing the OBIA RF accuracy to 90.4%. However, McNemar’s chi-square test confirmed no statistically significant difference in overall accuracy among the classifiers (pixel-based ML, RF, or object-based RF) for either the three- or five-layer analyses. Although potentially useful in some circumstances, the OBIA approach requires substantial resources and user input (such as segmentation scale selection—which was found to substantially affect overall accuracy). Hence, we conclude that pixel-based RF approaches are likely satisfactory for classifying wetland-dominated landscapes. PMID:29707381

Comparing Pixel- and Object-Based Approaches in Effectively Classifying Wetland-Dominated Landscapes.

PubMed

Berhane, Tedros M; Lane, Charles R; Wu, Qiusheng; Anenkhonov, Oleg A; Chepinoga, Victor V; Autrey, Bradley C; Liu, Hongxing

2018-01-01

Wetland ecosystems straddle both terrestrial and aquatic habitats, performing many ecological functions directly and indirectly benefitting humans. However, global wetland losses are substantial. Satellite remote sensing and classification informs wise wetland management and monitoring. Both pixel- and object-based classification approaches using parametric and non-parametric algorithms may be effectively used in describing wetland structure and habitat, but which approach should one select? We conducted both pixel- and object-based image analyses (OBIA) using parametric (Iterative Self-Organizing Data Analysis Technique, ISODATA, and maximum likelihood, ML) and non-parametric (random forest, RF) approaches in the Barguzin Valley, a large wetland (~500 km 2 ) in the Lake Baikal, Russia, drainage basin. Four Quickbird multispectral bands plus various spatial and spectral metrics (e.g., texture, Non-Differentiated Vegetation Index, slope, aspect, etc.) were analyzed using field-based regions of interest sampled to characterize an initial 18 ISODATA-based classes. Parsimoniously using a three-layer stack (Quickbird band 3, water ratio index (WRI), and mean texture) in the analyses resulted in the highest accuracy, 87.9% with pixel-based RF, followed by OBIA RF (segmentation scale 5, 84.6% overall accuracy), followed by pixel-based ML (83.9% overall accuracy). Increasing the predictors from three to five by adding Quickbird bands 2 and 4 decreased the pixel-based overall accuracy while increasing the OBIA RF accuracy to 90.4%. However, McNemar's chi-square test confirmed no statistically significant difference in overall accuracy among the classifiers (pixel-based ML, RF, or object-based RF) for either the three- or five-layer analyses. Although potentially useful in some circumstances, the OBIA approach requires substantial resources and user input (such as segmentation scale selection-which was found to substantially affect overall accuracy). Hence, we conclude that pixel-based RF approaches are likely satisfactory for classifying wetland-dominated landscapes.

Vegetation dynamics in response to water inflow rates and fire in a brackish Typha domingensis Pers. marsh in the delta of the Colorado River, Mexico

USGS Publications Warehouse

Mexicano, Lourdes; Nagler, Pamela L.; Zamora-Arroyo, Francisco; Glenn, Edward P.

2012-01-01

The Cienega de Santa Clara is a 5600 ha, anthropogenic wetland in the delta of the Colorado River in Mexico. It is the inadvertent creation of the disposal of brackish agricultural waste water from the U.S. into the intertidal zone of the river delta in Mexico, but has become an internationally important wetland for resident and migratory water birds. We used high resolution Quickbird and WorldView-2 images to produce seasonal vegetation maps of the Cienega before, during and after a test run of the Yuma Desalting Plant, which will remove water from the inflow stream and replace it with brine. We also used moderate resolution, 16-day composite NDVI imagery from the Moderate Resolution Imaging Spectrometer (MODIS) sensors on the Terra satellite to determine the main factors controlling green vegetation density over the years 2000–2011. The marsh is dominated by Typha domingensis Pers. with Phragmites australis (Cav.) Trin. Ex Steud. as a sub-dominant species in shallower marsh areas. The most important factor controlling vegetation density was fire. Spring fires in 2006 and 2011 were followed by much more rapid green-up of T. domingensis in late spring and 30% higher peak summer NDVI values compared to non-fire years (P < 0.001). Fires removed thatch and returned nutrients to the water, resulting in more vigorous vegetation growth compared to non-fire years. The second significant (P < 0.01) factor controlling NDVI was flow rate of agricultural drain water from the U.S. into the marsh. Reduced summer flows in 2001 due to canal repairs, and in 2010 during the YDP test run, produced the two lowest NDVI values of the time series from 2000 to 2011 (P < 0.05). Salinity is a further determinant of vegetation dynamics as determined by greenhouse experiments, but was nearly constant over the period 2000–2011, so it was not a significant variable in regression analyses. It is concluded that any reduction in inflow volumes will result in a linear decrease in green foliage density in the marsh.

QuickBird satellite imagery as a tool for restoration and rehabilitation of Lake Sevan, Armenia

USGS Publications Warehouse

Stapanian, Martin A.

2011-01-01

Lake Sevan in Armenia is the largest freshwater lake in the Transcaucasus region and is one of the largest high-altitude freshwater lakes in Eurasia (Babayan et al., 2006). Armenia is a small (29,743 km2), land- locked country that is comparatively poor in natural resources and nearly surrounded by borders that are blockaded by its neighbors (Babayan et al., 2006; Rhoades, 2008 and references therein; CIA, 2010). Despite these obstacles, ecological research and environmental restoration efforts continue. For the most part, ecological research in Lake Sevan during the twentieth century was restricted to Soviet-era journals, or was otherwise unavailable to western scientists. 

Climate impacts on environmental risks evaluated from space: a conceptual approach to the case of Rift Valley Fever in Senegal

PubMed Central

Tourre, Yves M.; Lacaux, Jean-Pierre; Vignolles, Cécile; Lafaye, Murielle

2009-01-01

Background Climate and environment vary across many spatio-temporal scales, including the concept of climate change, which impact on ecosystems, vector-borne diseases and public health worldwide. Objectives To develop a conceptual approach by mapping climatic and environmental conditions from space and studying their linkages with Rift Valley Fever (RVF) epidemics in Senegal. Design Ponds in which mosquitoes could thrive were identified from remote sensing using high-resolution SPOT-5 satellite images. Additional data on pond dynamics and rainfall events (obtained from the Tropical Rainfall Measuring Mission) were combined with hydrological in-situ data. Localisation of vulnerable hosts such as penned cattle (from QuickBird satellite) were also used. Results Dynamic spatio-temporal distribution of Aedes vexans density (one of the main RVF vectors) is based on the total rainfall amount and ponds’ dynamics. While Zones Potentially Occupied by Mosquitoes are mapped, detailed risk areas, i.e. zones where hazards and vulnerability occur, are expressed in percentages of areas where cattle are potentially exposed to mosquitoes’ bites. Conclusions This new conceptual approach, using precise remote-sensing techniques, simply relies upon rainfall distribution also evaluated from space. It is meant to contribute to the implementation of operational early warning systems for RVF based on both natural and anthropogenic climatic and environmental changes. In a climate change context, this approach could also be applied to other vector-borne diseases and places worldwide. PMID:20052381

Preliminary Results of Earthquake-Induced Building Damage Detection with Object-Based Image Classification

NASA Astrophysics Data System (ADS)

Sabuncu, A.; Uca Avci, Z. D.; Sunar, F.

2016-06-01

Earthquakes are the most destructive natural disasters, which result in massive loss of life, infrastructure damages and financial losses. Earthquake-induced building damage detection is a very important step after earthquakes since earthquake-induced building damage is one of the most critical threats to cities and countries in terms of the area of damage, rate of collapsed buildings, the damage grade near the epicenters and also building damage types for all constructions. Van-Ercis (Turkey) earthquake (Mw= 7.1) was occurred on October 23th, 2011; at 10:41 UTC (13:41 local time) centered at 38.75 N 43.36 E that places the epicenter about 30 kilometers northern part of the city of Van. It is recorded that, 604 people died and approximately 4000 buildings collapsed or seriously damaged by the earthquake. In this study, high-resolution satellite images of Van-Ercis, acquired by Quickbird-2 (Digital Globe Inc.) after the earthquake, were used to detect the debris areas using an object-based image classification. Two different land surfaces, having homogeneous and heterogeneous land covers, were selected as case study areas. As a first step of the object-based image processing, segmentation was applied with a convenient scale parameter and homogeneity criterion parameters. As a next step, condition based classification was used. In the final step of this preliminary study, outputs were compared with streetview/ortophotos for the verification and evaluation of the classification accuracy.

Comparison and evaluation on image fusion methods for GaoFen-1 imagery

NASA Astrophysics Data System (ADS)

Zhang, Ningyu; Zhao, Junqing; Zhang, Ling

2016-10-01

Currently, there are many research works focusing on the best fusion method suitable for satellite images of SPOT, QuickBird, Landsat and so on, but only a few of them discuss the application of GaoFen-1 satellite images. This paper proposes a novel idea by using four fusion methods, such as principal component analysis transform, Brovey transform, hue-saturation-value transform, and Gram-Schmidt transform, from the perspective of keeping the original image spectral information. The experimental results showed that the transformed images by the four fusion methods not only retain high spatial resolution on panchromatic band but also have the abundant spectral information. Through comparison and evaluation, the integration of Brovey transform is better, but the color fidelity is not the premium. The brightness and color distortion in hue saturation-value transformed image is the largest. Principal component analysis transform did a good job in color fidelity, but its clarity still need improvement. Gram-Schmidt transform works best in color fidelity, and the edge of the vegetation is the most obvious, the fused image sharpness is higher than that of principal component analysis. Brovey transform, is suitable for distinguishing the Gram-Schmidt transform, and the most appropriate for GaoFen-1 satellite image in vegetation and non-vegetation area. In brief, different fusion methods have different advantages in image quality and class extraction, and should be used according to the actual application information and image fusion algorithm.

Rift Valley fever in a zone potentially occupied by Aedes vexans in Senegal: dynamics and risk mapping

NASA Astrophysics Data System (ADS)

Tourre, Y. M.; Vignolles, C.; Lacaux, J.-P.; Bigeard, G.; Ndione, J.-A.; Lafaye, M.

2009-09-01

This paper presents an analysis of the interaction between the various variables associated with Rift Valley fever (RVF) such as the mosquito vector, available hosts and rainfall distribution. To that end, the varying zones potentially occupied by mosquitoes (ZPOM), rainfall events and pond dynamics, and the associated exposure of hosts to the RVF virus by Aedes vexans, were analyzed in the Barkedji area of the Ferlo, Senegal, during the 2003 rainy season. Ponds were identified by remote sensing using a high-resolution SPOT-5 satellite image. Additional data on ponds and rainfall events from the Tropical Rainfall Measuring Mission were combined with in-situ entomological and limnimetric measurements, and the localization of vulnerable ruminant hosts (data derived from QuickBird satellite). Since "Ae. vexans productive events” are dependent on the timing of rainfall for their embryogenesis (six days without rain are necessary to trigger hatching), the dynamic spatio-temporal distribution of Ae. vexans density was based on the total rainfall amount and pond dynamics. Detailed ZPOM mapping was obtained on a daily basis and combined with aggressiveness temporal profiles. Risks zones, i.e. zones where hazards and vulnerability are combined, are expressed by the percentages of parks where animals are potentially exposed to mosquito bites. This new approach, simply relying upon rainfall distribution evaluated from space, is meant to contribute to the implementation of a new, operational early warning system for RVF based on environmental risks linked to climatic and environmental conditions.

Climate impacts on environmental risks evaluated from space: a contribution to social benefits within the GEOSS Health Area: The case of Rift Valley Fever in Senegal

NASA Astrophysics Data System (ADS)

Tourre, Y. M.

2009-12-01

Climate and environment vary on many spatio-temporal scales, including climate change, with impacts on ecosystems, vector-borne diseases and public health worldwide. This study is to enable societal benefits from a conceptual approach by mapping climatic and environmental conditions from space and understanding the mechanisms within the Health Social Benefit GEOSS area. The case study is for Rift Valley Fever (RVF) epidemics in Senegal is presented. Ponds contributing to mosquitoes’ thriving, were identified from remote sensing using high-resolution SPOT-5 satellite images. Additional data on ponds’ dynamics and rainfall events (obtained from the Tropical Rainfall Measuring Mission) were combined with hydrological in-situ data. Localization of vulnerable hosts such as parked cattle (from QuickBird satellite) are also used. Dynamic spatio-temporal distribution of Aedes vexans density (one of the main RVF vectors) is based on the total rainfall amount and ponds’ dynamics. While Zones Potentially Occupied by Mosquitoes (ZPOM) are mapped, detailed risks areas, i.e. zones where hazards and vulnerability occur, are expressed in percentages of parks where cattle is potentially exposed to mosquitoes’ bites. This new conceptual approach, using remote-sensing techniques belonging to GEOSS, simply relies upon rainfall distribution also evaluated from space. It is meant to contribute to the implementation of integrated operational early warning system within the health application communities since climatic and environmental conditions (both natural and anthropogenic) are changing rapidly.

Analysis of the relationship between the volumetric soil moisture content and the NDVI from high resolution multi-spectral images for definition of vineyard management zones to improve irrigation

NASA Astrophysics Data System (ADS)

Martínez-Casasnovas, J. A.; Ramos, M. C.

2009-04-01

As suggested by previous research in the field of precision viticulture, intra-field yield variability is dependent on the variation of soil properties, and in particular the soil moisture content. Since the mapping in detail of this soil property for precision viticulture applications is highly costly, the objective of the present research is to analyse its relationship with the normalised difference vegetation index from high resolution satellite images to the use it in the definition of vineyard zonal management. The final aim is to improve irrigation in commercial vineyard blocks for better management of inputs and to deliver a more homogeneous fruit to the winery. The study was carried out in a vineyard block located in Raimat (NE Spain, Costers del Segre Designation of Origin). This is a semi-arid area with continental Mediterranean climate and a total annual precipitation between 300-400 mm. The vineyard block (4.5 ha) is planted with Syrah vines in a 3x2 m pattern. The vines are irrigated by means of drips under a partial root drying schedule. Initially, the irrigation sectors had a quadrangular distribution, with a size of about 1 ha each. Yield is highly variable within the block, presenting a coefficient of variation of 24.9%. For the measurement of the soil moisture content a regular sampling grid of 30 x 40 m was defined. This represents a sample density of 8 samples ha-1. At the nodes of the grid, TDR (Time Domain Reflectometer) probe tubes were permanently installed up to the 80 cm or up to reaching a contrasting layer. Multi-temporal measures were taken at different depths (each 20 cm) between November 2006 and December 2007. For each date, a map of the variability of the profile soil moisture content was interpolated by means of geostatistical analysis: from the measured values at the grid points the experimental variograms were computed and modelled and global block kriging (10 m squared blocks) undertaken with a grid spacing of 3 m x 3 m. On the other hand, three Quickbird-2 satellite images where acquired and processed to monitor plant vigour. The dates of images acquisition were: 29-07-2004, 13-07-2005 and 13-07-2006. They are within the range of

Mapping Post-Fire Vegetation Recovery at Different Lithologies of Taygetos mt (greece) with Multi-Temporal Remote Sensing Data

NASA Astrophysics Data System (ADS)

Vassilakis, Emmanuel; Mallinis, George; Christopoulou, Anastasia; Farangitakis, Georgios-Pavlos; Papanikolaou, Ioannis; Arianoutsou, Margarita

2017-04-01

Mt Taygetos (2407m), located at southern Peloponnese (Greece) suffered a large fire during the summer of 2007. The fire burned approximately 45% of the area covered by the endemic Greek fir (Abies cephalonica) and Black Pine (Pinus nigra) forest ecosystems. The aim of the current study is to examine the potential differences on post-fire vegetation recovery imposed by the lithology as well as the geomorphology of the given area over sites of the same climatic and landscape conditions (elevation, aspect, slope etc.). The main lithologies consist of carbonate, permeable, not easily erodible formations (limestones and marbles) and clastic, impermeable (schists, slate and flysch) erodible ones. A time-series of high spatial resolution satellite images were interpreted, analyzed and compared in order to detect changes in vegetation coverage which could prioritize areas of interest for fieldwork campaigns. The remote sensing datasets were acquired before (Ikonos-2), a few months after (Quickbird-2) and some years after (Worldview-3) the 2007 fire. High resolution Digital Elevation Model was used for the ortho-rectification and co-registration of the remote sensing data, but also for the extraction of the mountainous landscape characteristics. The multi-temporal image dataset was analyzed through GEographic-Object Based Image Analysis (GEOBIA). Objects corresponding to different vegetation types through time were identified through spectral and textural features. The classification results were combined with basic layers such as lithological outcrops, pre-fire vegetation, landscape morphology etc., supplementing a spatial geodatabase used for classifying burnt areas with varying post-fire plant community recovery. We validated the results of the classification during fieldwork and found that at a local scale, where the landscape features are quite similar, the bedrock type proves to be an important factor for vegetation recovery, as it clearly defines the soil generation along with its properties. Plant species recovery seems to be controlled by the local lithology as it was found weaker in plots overlying limestones and marbles, comparing to that observed over schists, even for the same species. In conclusion, post-fire vegetation recovery seems to be a complex process controlled not only from species biology, but also from the geological features.

Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method

NASA Astrophysics Data System (ADS)

Brovelli, Maria Antonia; Crespi, Mattia; Fratarcangeli, Francesca; Giannone, Francesca; Realini, Eugenio

Interest in high-resolution satellite imagery (HRSI) is spreading in several application fields, at both scientific and commercial levels. Fundamental and critical goals for the geometric use of this kind of imagery are their orientation and orthorectification, processes able to georeference the imagery and correct the geometric deformations they undergo during acquisition. In order to exploit the actual potentialities of orthorectified imagery in Geomatics applications, the definition of a methodology to assess the spatial accuracy achievable from oriented imagery is a crucial topic. In this paper we want to propose a new method for accuracy assessment based on the Leave-One-Out Cross-Validation (LOOCV), a model validation method already applied in different fields such as machine learning, bioinformatics and generally in any other field requiring an evaluation of the performance of a learning algorithm (e.g. in geostatistics), but never applied to HRSI orientation accuracy assessment. The proposed method exhibits interesting features which are able to overcome the most remarkable drawbacks involved by the commonly used method (Hold-Out Validation — HOV), based on the partitioning of the known ground points in two sets: the first is used in the orientation-orthorectification model (GCPs — Ground Control Points) and the second is used to validate the model itself (CPs — Check Points). In fact the HOV is generally not reliable and it is not applicable when a low number of ground points is available. To test the proposed method we implemented a new routine that performs the LOOCV in the software SISAR, developed by the Geodesy and Geomatics Team at the Sapienza University of Rome to perform the rigorous orientation of HRSI; this routine was tested on some EROS-A and QuickBird images. Moreover, these images were also oriented using the world recognized commercial software OrthoEngine v. 10 (included in the Geomatica suite by PCI), manually performing the LOOCV since only the HOV is implemented. The software comparison guaranteed about the overall correctness and good performances of the SISAR model, whereas the results showed the good features of the LOOCV method.

Analysis of urban land use in the megacity of Dhaka, Bangladesh: Roof-top detection in the context of assessing solar photovoltaic potential

NASA Astrophysics Data System (ADS)

Jaegermeyr, J.; Kabir, H.; Endlicher, W.

2009-12-01

The megacity of Dhaka, Bangladesh is considered to be one of the world’s fastest growing urban centers. With nearly 14 million people Dhaka currently faces tremendous power crisis. The available power supply of Dhaka Megacity is currently 1000-1200 MW against the maximum demand of nearly 2000 MW. The objective of this study is to classify land cover of Dhaka to locate roof-top areas which are adequate for solar photovoltaic applications. Usually this task is performed with additional building-heights data. With lack of that, we present an object-based classification approach which is based on high resolution Quickbird data only. Extensive formal buildings in Dhaka mostly have flat roof-tops made from concrete which are well suited for PV applications. The classification is focused to detect these ‘Bright Roof-Tops’ to assess a lower limit for potential PV areas. With that conservative approach bright roof-top areas of 10.554 km2 out of the city’s 134.282 km2 could be found. The overall classification accuracy is 0.918, the producer’s accuracy of ‘Bright Roof-Tops’ is 0.833. Preliminary result of the PhD work of Humayun Kabir indicates that the application of only 75 Wp stand-alone solar modules on these available bright roof-tops can generate nearly 1,000 MW of electricity. The application of solar modules with high capacity (i.e., >200 Wp) preferably through grid-connected PV systems can substantially meet-up the city’s power demand, although several techno-economic and socio-political factors are certainly involved.

An improved automated procedure for informal and temporary dwellings detection and enumeration, using mathematical morphology operators on VHR satellite data

NASA Astrophysics Data System (ADS)

Jenerowicz, Małgorzata; Kemper, Thomas

2016-10-01

Every year thousands of people are displaced by conflicts or natural disasters and often gather in large camps. Knowing how many people have been gathered is crucial for an efficient relief operation. However, it is often difficult to collect exact information on the total number of the population. This paper presents the improved morphological methodology for the estimation of dwellings structures located in several Internally Displaced Persons (IDPs) Camps, based on Very High Resolution (VHR) multispectral satellite imagery with pixel sizes of 1 meter or less including GeoEye-1, WorldView-2, QuickBird-2, Ikonos-2, Pléiades-A and Pléiades-B. The main topic of this paper is the approach enhancement with selection of feature extraction algorithm, the improvement and automation of pre-processing and results verification. For the informal and temporary dwellings extraction purpose the high quality of data has to be ensured. The pre-processing has been extended by including the input data hierarchy level assignment and data fusion method selection and evaluation. The feature extraction algorithm follows the procedure presented in Jenerowicz, M., Kemper, T., 2011. Optical data are analysed in a cyclic approach comprising image segmentation, geometrical, textural and spectral class modeling aiming at camp area identification. The successive steps of morphological processing have been combined in a one stand-alone application for automatic dwellings detection and enumeration. Actively implemented, these approaches can provide a reliable and consistent results, independent of the imaging satellite type and different study sites location, providing decision support in emergency response for the humanitarian community like United Nations, European Union and Non-Governmental relief organizations.

Assessing forest degradation in Guyana with GeoEye, Quickbird and Landsat

Treesearch

Bobby Braswell; Steve Hagen; William Salas; Michael Palace; Sandra Brown; Felipe Casarim; Nancy Harris

2013-01-01

Forest degradation is defined as a change in forest quality and condition (e.g. reduction in biomass), while deforestation is a change in forest area. This pilot study evaluated several image processing approaches to map degradation and estimate carbon removals from logging. From the Joint Concept Note on REDD+ cooperation between Guyana and Norway carbon loss as...

QuickBird and OrbView-3 Geopositional Accuracy Assessment

NASA Technical Reports Server (NTRS)

Helder, Dennis; Ross, Kenton

2006-01-01

Objective: Compare vendor-provided image coordinates with known references visible in the imagery. Approach: Use multiple, well-characterized sites with >40 ground control points (GCPs); sites that are a) Well distributed; b) Accurately surveyed; and c) Easily found in imagery. Perform independent assessments with independent teams. Each team has slightly different measurement techniques and data processing methods. NASA Stennis Space Center. South Dakota State University.

Climate-Induced Landslides within the Larch Dominant Permafrost Zone of Central Siberia.

PubMed

Kharuk, Viacheslav I; Shushpanov, Alexandr S; Im, Sergei T; Ranson, Kenneth J

2016-04-01

Climate impact on landslide occurrence and spatial patterns were analyzed within the larch-dominant communities associated with continuous permafrost areas of Central Siberia. We used high resolution satellite imagery (i.e. QuickBird, WorldView) to identify landslide scars over an area of 62000 km 2 . Landslide occurrence was analyzed with respect to climate variables (air temperature, precipitation, drought index SPEI), and GRACE satellite derived equivalent of water thickness anomalies (EWTA). Landslides were found only on southward facing slopes, and the occurrence of landslides increased exponentially with increasing slope steepness. Lengths of landslides correlated positively with slope steepness. The observed upper elevation limit of landslides tended to coincide with the tree line. Observations revealed landslides occurrence was also found to be strongly correlated with August precipitation (r = 0.81) and drought index (r = 0.7), with June-July-August soil water anomalies (i.e., EWTA, r = 0.68-0.7), and number of thawing days (i.e., a number of days with t max > 0°C; r = 0.67). A significant increase in the variance of soil water anomalies was observed, indicating that occurrence of landslides may increase even with a stable mean precipitation level. The key-findings of this study are (1) landslides occurrence increased within the permafrost zone of Central Siberia in the beginning of the 21st century; (2) the main cause of increased landslides occurrence are extremes in precipitation and soil water anomalies; and (3) landslides occurrence are strongly dependent on relief features such as southward facing steep slopes.

Climate-Induced Landsliding within the Larch Dominant Permafrost Zone of Central Siberia

NASA Technical Reports Server (NTRS)

Kharuk, Viacheslav I.; Shushpanov, Alexandr S.; Im, Sergei T.; Ranson, Kenneth J.

2016-01-01

Climate impact on landslide occurrence and spatial patterns were analyzed within the larch-dominant communities associated with continuous permafrost areas of central Siberia. We used high resolution satellite imagery (i.e. QuickBird, WorldView) to identify landslide scars over an area of 62 000 km2. Landslide occurrence was analyzed with respect to climate variables (air temperature, precipitation, drought index SPEI), and Gravity Recovery and Climate Experiment satellite derived equivalent of water thickness anomalies (EWTA). Landslides were found only on southward facing slopes, and the occurrence of landslides increased exponentially with increasing slope steepness. Lengths of landslides correlated positively with slope steepness. The observed upper elevation limit of landslides tended to coincide with the tree line. Observations revealed landslides occurrence was also found to be strongly correlated with August precipitation (r = 0.81) and drought index (r = 0.7), with June-July-August soil water anomalies (i.e., EWTA, r = 0.68-0.7), and number of thawing days (i.e., a number of days with t (max) > 0 deg C; r = 0.67). A significant increase in the variance of soil water anomalies was observed, indicating that occurrence of landslides may increase even with a stable mean precipitation level. The key-findings of this study are (1) landslides occurrence increased within the permafrost zone of central Siberia in the beginning of the 21st century; (2) the main cause of increased landslides occurrence are extremes in precipitation and soil water anomalies; and (3) landslides occurrence are strongly dependent on relief features such as southward facing steep slopes.

Ecohydrology and tipping points in semiarid australian rangelands

NASA Astrophysics Data System (ADS)

Saco, P. M.; Azadi, S.; Moreno de las Heras, M.; Willgoose, G. R.

2017-12-01

Semiarid landscapes are often characterised by a spatially heterogeneous vegetation cover forming mosaics of patches with dense vegetation within bare soil. This patchy vegetation cover, which is linked to the healthy function of these ecosystems, is sensitive to human disturbances that can lead to degradation. Previous work suggests that vegetation loss below a critical value can lead to a sudden decrease in landscape functionality following threshold behaviour. The decrease in vegetation cover is linked to erosion and substantial water losses by increasing landscape hydrological connectivity. We study these interactions and the possible existence of tipping points in the Mulga land bioregion, by combining remote sensing observations and results from an eco-geomorphologic model to investigate changes in ecosystem connectivity and the existence of threshold behaviour. More than 30 sites were selected along a precipitation gradient spanning a range from approximately 250 to 500 mm annual rainfall. The analysis of vegetation patterns is derived from high resolution remote sensing images (IKONOS, QuickBird, Pleiades) and MODIS NDVI, which combined with local precipitation data is used to compute rainfall use efficiency to assess the ecosystem function. A critical tipping point associated to loss of vegetation cover appears in the sites with lower annual precipitation. We found that this tipping point behaviour decreases for sites with higher rainfall. We use the model to investigate the relation between structural and functional connectivity and the emergence of threshold behaviour for selected plots along this precipitation gradient. Both observations and modelling results suggest that sites with higher rainfall are more resilient to changes in surface connectivity. The implications for ecosystem resilience and land management are discussed

Forest Canopy Cover and Height from MISR in Topographically Complex Southwestern US Landscape Assessed with High Quality Reference Data

NASA Technical Reports Server (NTRS)

Chopping, Mark; North, Malcolm; Chen, Jiquan; Schaaf, Crystal B.; Blair, J. Bryan; Martonchik, John V.; Bull, Michael A.

2012-01-01

This study addresses the retrieval of spatially contiguous canopy cover and height estimates in southwestern USforests via inversion of a geometric-optical (GO) model against surface bidirectional reflectance factor (BRF) estimates from the Multi-angle Imaging SpectroRadiometer (MISR). Model inversion can provide such maps if good estimates of the background bidirectional reflectance distribution function (BRDF) are available. The study area is in the Sierra National Forest in the Sierra Nevada of California. Tree number density, mean crown radius, and fractional cover reference estimates were obtained via analysis of QuickBird 0.6 m spatial resolution panchromatic imagery usingthe CANopy Analysis with Panchromatic Imagery (CANAPI) algorithm, while RH50, RH75 and RH100 (50, 75, and 100 energy return) height data were obtained from the NASA Laser Vegetation Imaging Sensor (LVIS), a full waveform light detection and ranging (lidar) instrument. These canopy parameters were used to drive a modified version of the simple GO model (SGM), accurately reproducing patterns ofMISR 672 nm band surface reflectance (mean RMSE 0.011, mean R2 0.82, N 1048). Cover and height maps were obtained through model inversion against MISR 672 nm reflectance estimates on a 250 m grid.The free parameters were tree number density and mean crown radius. RMSE values with respect to reference data for the cover and height retrievals were 0.05 and 6.65 m, respectively, with of 0.54 and 0.49. MISR can thus provide maps of forest cover and height in areas of topographic variation although refinements are required to improve retrieval precision.

Climate-Induced Landslides within the Larch Dominant Permafrost Zone of Central Siberia

PubMed Central

Shushpanov, Alexandr S; Im, Sergei T; Ranson, Kenneth J

2017-01-01

Climate impact on landslide occurrence and spatial patterns were analyzed within the larch-dominant communities associated with continuous permafrost areas of Central Siberia. We used high resolution satellite imagery (i.e. QuickBird, WorldView) to identify landslide scars over an area of 62000 km2. Landslide occurrence was analyzed with respect to climate variables (air temperature, precipitation, drought index SPEI), and GRACE satellite derived equivalent of water thickness anomalies (EWTA). Landslides were found only on southward facing slopes, and the occurrence of landslides increased exponentially with increasing slope steepness. Lengths of landslides correlated positively with slope steepness. The observed upper elevation limit of landslides tended to coincide with the tree line. Observations revealed landslides occurrence was also found to be strongly correlated with August precipitation (r = 0.81) and drought index (r = 0.7), with June-July-August soil water anomalies (i.e., EWTA, r = 0.68–0.7), and number of thawing days (i.e., a number of days with tmax > 0°C; r = 0.67). A significant increase in the variance of soil water anomalies was observed, indicating that occurrence of landslides may increase even with a stable mean precipitation level. The key-findings of this study are (1) landslides occurrence increased within the permafrost zone of Central Siberia in the beginning of the 21st century; (2) the main cause of increased landslides occurrence are extremes in precipitation and soil water anomalies; and (3) landslides occurrence are strongly dependent on relief features such as southward facing steep slopes. PMID:29326754

Estimating average tree crown size using spatial information from Ikonos and QuickBird images: Across-sensor and across-site comparisons

Treesearch

Conghe Song; Matthew B. Dickinson; Lihong Su; Su Zhang; Daniel Yaussey

2010-01-01

The forest canopy is the medium for energy, mass, and momentum exchanges between the forest ecosystem and the atmosphere. Tree crown size is a critical aspect of canopy structure that significantly influences these biophysical processes in the canopy. Tree crown size is also strongly related to other canopy structural parameters, such as tree height, diameter at breast...

Beyond modern landscape features: New insights in the archaeological area of Tiwanaku in Bolivia from satellite data

NASA Astrophysics Data System (ADS)

Lasaponara, Rosa; Masini, Nicola

2014-02-01

The aim of this paper is to investigate the cultural landscape of the archaeological area of Tiwanaku (Bolivia) using multiscale, multispectral and multitemporal satellite data. Geospatial analysis techniques were applied to the satellite data sets in order to enhance and map traces of past human activities and perform a spatial characterization of environmental and cultural patterns. In particular, in the Tiwanaku area, the approach based on local indicators of spatial autocorrelation (LISA) applied to ASTER data allowed us to identify traces of a possible ancient hydrographic network with a clear spatial relation with the well-known moat surrounding the core of the monumental area. The same approach applied to QuickBird data, allowed us to identify numerous traces of archaeological interest, in Mollo Kontu mound, less investigated than the monumental area. Some of these traces were in perfect accordance with the results of independent studies, other were completely unknown. As a whole, the detected features, composing a geometric pattern with roughly North-South orientation, closely match those of the other residential contexts at Tiwanaku. These new insights, captured from ASTER and QuickBird data processing, suggested new questions on the ancient landscape and provided important information for planning future field surveys and archaeogeophyical investigations.

Mapping vegetation cover and biomass on the Qinghai-Tibet-Plateau using hyperspectral measurements and multispectral satellite images

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Lehnert, Lukas W.; Wang, Yun; Reudenbach, Christoph; Nauss, Thomas; Bendix, Jörg

2016-04-01

Pastoralism is the dominant land-use on the Qinghai-Tibet-Plateau (QTP) providing the major economic resource for the local population. However, the pastures are highly supposed to be affected by ongoing degradation whose extent is still disputed. This study uses hyperspectral in situ measurements and multispectral satellite images to assess vegetation cover and above ground biomass (AGB) as proxies of pasture degradation on a regional scale. Using Random Forests in conjunction with recursive feature selection as modeling tool, it is tested whether the full hyperspectral information is needed or if multispectral information is sufficient to accurately estimate vegetation cover and AGB. To regionalize pasture degradation proxies, the transferability of the locally derived models to high resolution multispectral satellite data is assessed. For this purpose, 1183 hyperspectral measurements and vegetation records were sampled at 18 locations on the QTP. AGB was determined on 25 0.5x0.5m plots. Proxies for pasture degradation were derived from the spectra by calculating narrow-band indices (NBI). Using the NBI as predictor variables vegetation cover and AGB were modeled. Models were calculated using the hyperspectral data as well as the same data resampled to WorldView-2, QuickBird and RapidEye channels. The hyperspectral results were compared to the multispectral results. Finally, the models were applied to satellite data to map vegetation cover and AGB on a regional scale. Vegetation cover was accurately predicted by Random Forest if hyperspectral measurements were used. In contrast, errors in AGB estimations were considerably higher. Only small differences in accuracy were observed between the models based on hyper- compared to multispectral data. The application of the models to satellite images generally resulted in an increase of the estimation error. Though this reflects the challenge of applying in situ measurements to satellite data, the results still show a high potential to map pasture degradation proxies on the QTP even for larger scales.

High Accuracy 3D Processing of Satellite Imagery

NASA Technical Reports Server (NTRS)

Gruen, A.; Zhang, L.; Kocaman, S.

2007-01-01

Automatic DSM/DTM generation reproduces not only general features, but also detailed features of the terrain relief. Height accuracy of around 1 pixel in cooperative terrain. RMSE values of 1.3-1.5 m (1.0-2.0 pixels) for IKONOS and RMSE values of 2.9-4.6 m (0.5-1.0 pixels) for SPOT5 HRS. For 3D city modeling, the manual and semi-automatic feature extraction capability of SAT-PP provides a good basis. The tools of SAT-PP allowed the stereo-measurements of points on the roofs in order to generate a 3D city model with CCM The results show that building models with main roof structures can be successfully extracted by HRSI. As expected, with Quickbird more details are visible.

Developments in remote sensing technology enable more detailed urban flood risk analysis.

NASA Astrophysics Data System (ADS)

Denniss, A.; Tewkesbury, A.

2009-04-01

Spaceborne remote sensors have been allowing us to build up a profile of planet earth for many years. With each new satellite launched we see the capabilities improve: new bands of data, higher resolution imagery, the ability to derive better elevation information. The combination of this geospatial data to create land cover and usage maps, all help inform catastrophe modelling systems. From Landsat 30m resolution to 2.44m QuickBird multispectral imagery; from 1m radar data collected by TerraSAR-X which enables rapid tracking of the rise and fall of a flood event, and will shortly have a twin satellite launched enabling elevation data creation; we are spoilt for choice in available data. However, just what is cost effective? It is always a question of choosing the appropriate level of input data detail for modelling, depending on the value of the risk. In the summer of 2007, the cost of the flooding in the UK was approximately £3bn and affected over 58,000 homes and businesses. When it comes to flood risk, we have traditionally considered rising river levels and surge tides, but with climate change and variations in our own construction behaviour, there are other factors to be taken into account. During those summer 2007 events, the Environment Agency suggested that around 70% of the properties damaged were the result of pluvial flooding, where high localised rainfall events overload localised drainage infrastructure, causing widespread flooding of properties and infrastructure. To create a risk model that is able to simulate such an event requires much more accurate source data than can be provided from satellite or radar. As these flood events cause considerable damage within relatively small, complex urban environments, therefore new high resolution remote sensing techniques have to be applied to better model these events. Detailed terrain data of England and Wales, plus cities in Scotland, have been produced by combining terrain measurements from the latest digital airborne sensors, both optical and lidar, to produce the input layer for surface water flood modelling. A national flood map product has been created. The new product utilises sophisticated modelling techniques, perfected over many years, which harness graphical processing power. This product will prove particularly valuable for risk assessment decision support within insurance/reinsurance, property/environmental, utilities, risk management and government agencies. However, it is not just the ground elevation that determines the behaviour of surface water. By combining height information (surface and terrain) with high resolution aerial photography and colour infrared imagery, a high definition land cover mapping dataset (LandBase) is being produced, which provides a precise measure of sealed versus non sealed surface. This will allows even more sophisticated modelling of flood scenarios. Thus, the value of airborne survey data can be demonstrated by flood risk analysis down to individual addresses in urban areas. However for some risks, an even more detailed survey may be justified. In order to achieve this, Infoterra is testing new 360˚ mobile lidar technology. Collecting lidar data from a moving vehicle allows each street to be mapped in very high detail, allowing precise information about the location, size and shape of features such as kerbstones, gullies, road camber and building threshold level to be captured quickly and accurately. These data can then be used to model the problem of overland flood risk at the scale of individual properties. Whilst at present it might be impractical to undertake such detailed modelling for all properties, these techniques can certainly be used to improve the flood risk analysis of key locations. This paper will demonstrate how these new high resolution remote sensing techniques can be combined to provide a new resolution of detail to aid urban flood modelling.

On the integration of Airborne full-waveform laser scanning and optical imagery for Site Detection and Mapping: Monteserico study case

NASA Astrophysics Data System (ADS)

Coluzzi, R.; Guariglia, A.; Lacovara, B.; Lasaponara, R.; Masini, N.

2009-04-01

This paper analyses the capability of airborne LiDAR derived data in the recognition of archaeological marks. It also evaluates the benefits to integrate them with aerial photos and very high resolution satellite imagery. The selected test site is Monteserico, a medieval village located on a pastureland hill in the North East of Basilicata (Southern Italy). The site, attested by documentary sources beginning from the 12th century, was discovered by aerial survey in 1996 [1] and investigated in 2005 by using QuickBird imagery [2]. The only architectural evidence is a castle, built on the western top of the hill; whereas on the southern side, earthenware, pottery and crumbling building materials, related to the medieval settlement, could be observed. From a geological point of view, the stratigraphic sequence is composed of Subappennine Clays, Monte Marano sands and Irsina conglomerates. Sporadic herbaceous plants grow over the investigated area. For the purpose of this study, a full-waveform laser scanning with a 240.000 Hz frequency was used. The average point density value of dataset is about 30 points/m2. The final product is a 0.30 m Digital Surface Models (DSMs) accurately modelled. To derive the DSM the point cloud of the ALS was filtered and then classified by applying appropriate algorithms. In this way surface relief and archaeological features were surveyed with great detail. The DSM was compared with other remote sensing data source such as oblique and nadiral aerial photos and QuickBird imagery, acquired in different time. In this way it was possible to evaluate, compare each other and overlay the archaeological features recorded from each data source (aerial, satellite and lidar). Lidar data showed some interesting results. In particular, they allowed for identifying and recording differences in height on the ground produced by surface and shallow archaeological remains (the so-called shadow marks). Most of these features are visible also by the optical dataset, whereas other only by lidar. The pattern of shadow-marks has been integrated by processing the optic imagery (aerial and satellite), which put in evidence other features related to buried deposits of archaeological interest. Another contribution of lidar to the knowledge of the medieval site was the survey of eroded earthworks, that are very small differences in height, related to possible ancient human transformations of the hill. The numerical modelling of DSM has allowed for integrating and managing all the different georeferenced data for the reconstruction of urban fabric of the medieval village. [1] N. MASINI, Note storico-topografiche e fotointerpretazione aerea per la ricostruzione della '"forma urbis" del sito medievale di Monte Serico, Tarsia, 16-17 (1995), pp. 45-64. [2] R. LASAPONARA, N. MASINI, QuickBird-based analysis for the spatial characterization of archaeological sites: case study of the Monte Serico Medioeval village, Geophysical Research Letter, Vol. 32, No. 12 (2005), L12313.

Employing UAVs to Acquire Detailed Vegetation and Bare Ground Data for Assessing Rangeland Health

NASA Astrophysics Data System (ADS)

Rango, A.; Laliberte, A.; Herrick, J. E.; Winters, C.

2007-12-01

Because of its value as a historical record (extending back to the mid 1930s), aerial photography is an important tool used in many rangeland studies. However, these historical photos are not very useful for detailed analysis of rangeland health because of inadequate spatial resolution and scheduling limitations. These issues are now being resolved by using Unmanned Aerial Vehicles (UAVs) over rangeland study areas. Spatial resolution improvements have been rapid in the last 10 years from the QuickBird satellite through improved aerial photography to the new UAV coverage and have utilized improved sensors and the more simplistic approach of low altitude flights. Our rangeland health experiments have shown that the low altitude UAV digital photography is preferred by rangeland scientists because it allows, for the first time, their identification of vegetation and land surface patterns and patches, gap sizes, bare soil percentages, and vegetation type. This hyperspatial imagery (imagery with a resolution finer than the object of interest) is obtained at about 5cm resolution by flying at an altitude of 150m above the surface of the Jornada Experimental Range in southern New Mexico. Additionally, the UAV provides improved temporal flexibility, such as flights immediately following fires, floods, and other catastrophic disturbances, because the flight capability is located near the study area and the vehicles are under the direct control of the users, eliminating the additional steps associated with budgets and contracts. There are significant challenges to improve the data to make them useful for operational agencies, namely, image distortion with inexpensive, consumer grade digital cameras, difficulty in detecting sufficient ground control points in small scenes (152m by 114m), accuracy of exterior UAV information on X,Y, Z, roll, pitch, and heading, the sheer number of images collected, and developing reliable relationships with ground-based data across a broad range of topographies and plant communities. Our efforts are currently focused on developing a complete and efficient workflow for UAV operational missions consisting of flight planning, image acquisition, image rectification and mosaicking, and image classification. The remote sensing capability is being incorporated into existing rangeland health assessment and monitoring protocols.

Connotations of pixel-based scale effect in remote sensing and the modified fractal-based analysis method

NASA Astrophysics Data System (ADS)

Feng, Guixiang; Ming, Dongping; Wang, Min; Yang, Jianyu

2017-06-01

Scale problems are a major source of concern in the field of remote sensing. Since the remote sensing is a complex technology system, there is a lack of enough cognition on the connotation of scale and scale effect in remote sensing. Thus, this paper first introduces the connotations of pixel-based scale and summarizes the general understanding of pixel-based scale effect. Pixel-based scale effect analysis is essentially important for choosing the appropriate remote sensing data and the proper processing parameters. Fractal dimension is a useful measurement to analysis pixel-based scale. However in traditional fractal dimension calculation, the impact of spatial resolution is not considered, which leads that the scale effect change with spatial resolution can't be clearly reflected. Therefore, this paper proposes to use spatial resolution as the modified scale parameter of two fractal methods to further analyze the pixel-based scale effect. To verify the results of two modified methods (MFBM (Modified Windowed Fractal Brownian Motion Based on the Surface Area) and MDBM (Modified Windowed Double Blanket Method)); the existing scale effect analysis method (information entropy method) is used to evaluate. And six sub-regions of building areas and farmland areas were cut out from QuickBird images to be used as the experimental data. The results of the experiment show that both the fractal dimension and information entropy present the same trend with the decrease of spatial resolution, and some inflection points appear at the same feature scales. Further analysis shows that these feature scales (corresponding to the inflection points) are related to the actual sizes of the geo-object, which results in fewer mixed pixels in the image, and these inflection points are significantly indicative of the observed features. Therefore, the experiment results indicate that the modified fractal methods are effective to reflect the pixel-based scale effect existing in remote sensing data and it is helpful to analyze the observation scale from different aspects. This research will ultimately benefit for remote sensing data selection and application.

Mapping gully-affected areas in the region of Taroudannt, Morocco based on Object-Based Image Analysis (OBIA)

NASA Astrophysics Data System (ADS)

d'Oleire-Oltmanns, Sebastian; Marzolff, Irene; Tiede, Dirk; Blaschke, Thomas

2015-04-01

The need for area-wide landform mapping approaches, especially in terms of land degradation, can be ascribed to the fact that within area-wide landform mapping approaches, the (spatial) context of erosional landforms is considered by providing additional information on the physiography neighboring the distinct landform. This study presents an approach for the detection of gully-affected areas by applying object-based image analysis in the region of Taroudannt, Morocco, which is highly affected by gully erosion while simultaneously representing a major region of agro-industry with a high demand of arable land. Various sensors provide readily available high-resolution optical satellite data with a much better temporal resolution than 3D terrain data which lead to the development of an area-wide mapping approach to extract gully-affected areas using only optical satellite imagery. The classification rule-set was developed with a clear focus on virtual spatial independence within the software environment of eCognition Developer. This allows the incorporation of knowledge about the target objects under investigation. Only optical QuickBird-2 satellite data and freely-available OpenStreetMap (OSM) vector data were used as input data. The OSM vector data were incorporated in order to mask out plantations and residential areas. Optical input data are more readily available for a broad range of users compared to terrain data, which is considered to be a major advantage. The methodology additionally incorporates expert knowledge and freely-available vector data in a cyclic object-based image analysis approach. This connects the two fields of geomorphology and remote sensing. The classification results allow conclusions on the current distribution of gullies. The results of the classification were checked against manually delineated reference data incorporating expert knowledge based on several field campaigns in the area, resulting in an overall classification accuracy of 62%. The error of omission accounts for 38% and the error of commission for 16%, respectively. Additionally, a manual assessment was carried out to assess the quality of the applied classification algorithm. The limited error of omission contributes with 23% to the overall error of omission and the limited error of commission contributes with 98% to the overall error of commission. This assessment improves the results and confirms the high quality of the developed approach for area-wide mapping of gully-affected areas in larger regions. In the field of landform mapping, the overall quality of the classification results is often assessed with more than one method to incorporate all aspects adequately.

Aboveground biomass mapping of African forest mosaics using canopy texture analysis: toward a regional approach.

PubMed

Bastin, Jean-François; Barbier, Nicolas; Couteron, Pierre; Adams, Benoît; Shapiro, Aurélie; Bogaert, Jan; De Cannière, Charles

In the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the REDD+ program), optical very high resolution (VHR) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass (AGB) at less expense than methods based on airborne remote sensing data. Among the methods for processing these VHR images, Fourier textural ordination (FOTO) presents a good method to detect forest canopy structural heterogeneity and therefore to predict AGB variations. Notably, the method does not saturate at intermediate AGB values as do pixelwise processing of available space borne optical and radar signals. However, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun–scene–sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in Central Africa. In this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing FOTO indices of images acquired from two different sensors (Geoeye-1 and QuickBird-2) and different sun–scene–sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. A good agreement was found between observed and predicted AGB (residual standard error [RSE] = 15%; R2 = 0.85; P < 0.001) across a wide range of AGB levels from 26 Mg/ha to 460 Mg/ha, and was confirmed by cross validation. A high-resolution biomass map (100-m pixels) was produced for a 400-km2 area, and predictions obtained from both imagery sources were consistent with each other (r = 0.86; slope = 1.03; intercept = 12.01 Mg/ha). These results highlight the horizontal structure of forest canopy as a powerful descriptor of the entire forest stand structure and heterogeneity. In particular, we show that quantitative metrics resulting from such textural analysis offer new opportunities to characterize the spatial and temporal variation of the structure of dense forests and may complement the toolbox used by tropical forest ecologists, managers or REDD+ national monitoring, reporting and verification bodies.

Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

NASA Astrophysics Data System (ADS)

Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

2014-10-01

The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure variables from VHR satellite images. Thus an average prediction error of ˜ 1.1 m is expected on crown diameter, ˜ 0.9 m on tree spacing, ˜ 3 m on height and ˜ 0.06 m on diameter at breast height.

Comparison of two satellite imaging platforms for evaluating quasi-circular vegetation patch in the Yellow River Delta, China

NASA Astrophysics Data System (ADS)

Liu, Qingsheng; Liang, Li; Liu, Gaohuan; Huang, Chong

2017-09-01

Vegetation often exists as patch in arid and semi-arid region throughout the world. Vegetation patch can be effectively monitored by remote sensing images. However, not all satellite platforms are suitable to study quasi-circular vegetation patch. This study compares fine (GF-1) and coarse (CBERS-04) resolution platforms, specifically focusing on the quasicircular vegetation patches in the Yellow River Delta (YRD), China. Vegetation patch features (area, shape) were extracted from GF-1 and CBERS-04 imagery using unsupervised classifier (K-Means) and object-oriented approach (Example-based feature extraction with SVM classifier) in order to analyze vegetation patterns. These features were then compared using vector overlay and differencing, and the Root Mean Squared Error (RMSE) was used to determine if the mapped vegetation patches were significantly different. Regardless of K-Means or Example-based feature extraction with SVM classification, it was found that the area of quasi-circular vegetation patches from visual interpretation from QuickBird image (ground truth data) was greater than that from both of GF-1 and CBERS-04, and the number of patches detected from GF-1 data was more than that of CBERS-04 image. It was seen that without expert's experience and professional training on object-oriented approach, K-Means was better than example-based feature extraction with SVM for detecting the patch. It indicated that CBERS-04 could be used to detect the patch with area of more than 300 m2, but GF-1 data was a sufficient source for patch detection in the YRD. However, in the future, finer resolution platforms such as Worldview are needed to gain more detailed insight on patch structures and components and formation mechanism.

Mapping landslide source and transport areas in VHR images with Object-Based Analysis and Support Vector Machines

NASA Astrophysics Data System (ADS)

Heleno, Sandra; Matias, Magda; Pina, Pedro

2015-04-01

Visual interpretation of satellite imagery remains extremely demanding in terms of resources and time, especially when dealing with numerous multi-scale landslides affecting wide areas, such as is the case of rainfall-induced shallow landslides. Applying automated methods can contribute to more efficient landslide mapping and updating of existing inventories, and in recent years the number and variety of approaches is rapidly increasing. Very High Resolution (VHR) images, acquired by space-borne sensors with sub-metric precision, such as Ikonos, Quickbird, Geoeye and Worldview, are increasingly being considered as the best option for landslide mapping, but these new levels of spatial detail also present new challenges to state of the art image analysis tools, asking for automated methods specifically suited to map landslide events on VHR optical images. In this work we develop and test a methodology for semi-automatic landslide recognition and mapping of landslide source and transport areas. The method combines object-based image analysis and a Support Vector Machine supervised learning algorithm, and was tested using a GeoEye-1 multispectral image, sensed 3 days after a damaging landslide event in Madeira Island, together with a pre-event LiDAR DEM. Our approach has proved successful in the recognition of landslides on a 15 Km2-wide study area, with 81 out of 85 landslides detected in its validation regions. The classifier also showed reasonable performance (false positive rate 60% and false positive rate below 36% in both validation regions) in the internal mapping of landslide source and transport areas, in particular in the sunnier east-facing slopes. In the less illuminated areas the classifier is still able to accurately map the source areas, but performs poorly in the mapping of landslide transport areas.

Spatial and environmental connectivity analysis in a cholera vaccine trial.

PubMed

Emch, Michael; Ali, Mohammad; Root, Elisabeth D; Yunus, Mohammad

2009-02-01

This paper develops theory and methods for vaccine trials that utilize spatial and environmental information. Satellite imagery is used to identify whether households are connected to one another via water bodies in a study area in rural Bangladesh. Then relationships between neighborhood-level cholera vaccine coverage and placebo incidence and neighborhood-level spatial variables are measured. The study hypothesis is that unvaccinated people who are environmentally connected to people who have been vaccinated will be at lower risk compared to unvaccinated people who are environmentally connected to people who have not been vaccinated. We use four datasets including: a cholera vaccine trial database, a longitudinal demographic database of the rural population from which the vaccine trial participants were selected, a household-level geographic information system (GIS) database of the same study area, and high resolution Quickbird satellite imagery. An environmental connectivity metric was constructed by integrating the satellite imagery with the vaccine and demographic databases linked with GIS. The results show that there is a relationship between neighborhood rates of cholera vaccination and placebo incidence. Thus, people are indirectly protected when more people in their environmentally connected neighborhood are vaccinated. This result is similar to our previous work that used a simpler Euclidean distance neighborhood to measure neighborhood vaccine coverage [Ali, M., Emch, M., von Seidlein, L., Yunus, M., Sack, D. A., Holmgren, J., et al. (2005). Herd immunity conferred by killed oral cholera vaccines in Bangladesh. Lancet, 366(9479), 44-49]. Our new method of measuring environmental connectivity is more precise since it takes into account the transmission mode of cholera and therefore this study validates our assertion that the oral cholera vaccine provides indirect protection in addition to direct protection.

Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS

NASA Astrophysics Data System (ADS)

Yusof, Norbazlan M.; Pradhan, Biswajeet

2014-06-01

PLUS Berhad holds the concession for a total of 987 km of toll expressways in Malaysia, the longest of which is the North-South Expressway or NSE. Acting as the backbone' of the west coast of the peninsula, the NSE stretches from the Malaysian-Thai border in the north to the border with neighbouring Singapore in the south, linking several major cities and towns along the way. North-South Expressway in Malaysia contributes to the country economic development through trade, social and tourism sector. Presently, the highway is good in terms of its condition and connection to every state but some locations need urgent attention. Stability of slopes at these locations is of most concern as any instability can cause danger to the motorist. In this paper, two study locations have been analysed; they are Gua Tempurung (soil slope) and Jelapang (rock slope) which are obviously having two different characteristics. These locations passed through undulating terrain with steep slopes where landslides are common and the probability of slope instability due to human activities in surrounding areas is high. A combination of twelve (12) landslide conditioning factors database on slope stability such as slope degree and slope aspect were extracted from IFSAR (interoferometric synthetic aperture radar) while landuse, lithology and structural geology were constructed from interpretation of high resolution satellite data from World View II, Quickbird and Ikonos. All this information was analysed in geographic information system (GIS) environment for landslide susceptibility mapping using probabilistic based frequency ratio model. Consequently, information on the slopes such as inventories, condition assessments and maintenance records were assessed through total expressway maintenance management system or better known as TEMAN. The above mentioned system is used by PLUS as an asset management and decision support tools for maintenance activities along the highways as well as for data quality checking and integrity. In this study, TEMAN data were further analysed and subsequently integrated with landslide susceptible map for Gua Tempurung and Jelapang area in Perak.

Hydrogeophysics and remote sensing for the design of hydrogeological conceptual models in hard rocks - Sardón catchment (Spain)

NASA Astrophysics Data System (ADS)

Francés, Alain P.; Lubczynski, Maciek W.; Roy, Jean; Santos, Fernando A. M.; Mahmoudzadeh Ardekani, Mohammad R.

2014-11-01

Hard rock aquifers are highly heterogeneous and hydrogeologically complex. To contribute to the design of hydrogeological conceptual models of hard rock aquifers, we propose a multi-techniques methodology based on a downward approach that combines remote sensing (RS), non-invasive hydrogeophysics and hydrogeological field data acquisition. The proposed methodology is particularly suitable for data scarce areas. It was applied in the pilot research area of Sardón catchment (80 km2) located west of Salamanca (Spain). The area was selected because of hard-rock hydrogeology, semi-arid climate and scarcity of groundwater resources. The proposed methodology consisted of three main steps. First, we detected the main hydrogeological features at the catchment scale by processing: (i) a high resolution digital terrain model to map lineaments and to outline fault zones; and (ii) high-resolution, multispectral satellite QuickBird and WorldView-2 images to map the outcropping granite. Second, we characterized at the local scale the hydrogeological features identified at step one with: i) ground penetrating radar (GPR) to assess groundwater table depth complementing the available monitoring network data; ii) 2D electric resistivity tomography (ERT) and frequency domain electromagnetic (FDEM) to retrieve the hydrostratigraphy along selected survey transects; iii) magnetic resonance soundings (MRS) to retrieve the hydrostratigraphy and aquifer parameters at the selected survey sites. In the third step, we drilled 5 boreholes (25 to 48 m deep) and performed slug tests to verify the hydrogeophysical interpretation and to calibrate the MRS parameters. Finally, we compiled and integrated all acquired data to define the geometry and parameters of the Sardón aquifer at the catchment scale. In line with a general conceptual model of hard rock aquifers, we identified two main hydrostratigraphic layers: a saprolite layer and a fissured layer. Both layers were intersected and drained by fault zones that control the hydrogeology of the catchment. The spatial discontinuities of the saprolite layer were well defined by RS techniques while subsurface geometry and aquifer parameters by hydrogeophysics. The GPR method was able to detect shallow water table at depth between 1 and 3 m b.g.s. The hydrostratigraphy and parameterization of the fissured layer remained uncertain because ERT and FDEM geophysical methods were quantitatively not conclusive while MRS detectability was restricted by low volumetric water content. The proposed multi-technique methodology integrating cost efficient RS, hydrogeophysics and hydrogeological field investigations allowed us to characterize geometrically and parametrically the Sardón hard rock aquifer system, facilitating the design of hydrogeological conceptual model of the area.

Himalayan glaciers: understanding contrasting patterns of glacier behavior using multi-temporal satellite imagery

NASA Astrophysics Data System (ADS)

Racoviteanu, A.

2014-12-01

High rates of glacier retreat for the last decades are often reported, and believed to be induced by 20th century climate changes. However, regional glacier fluctuations are complex, and depend on a combination of climate and local topography. Furthermore, in ares such as the Hindu-Kush Himalaya, there are concerns about warming, decreasing monsoon precipitation and their impact on local glacier regimes. Currently, the challenge is in understanding the magnitude of feedbacks between large-scale climate forcing and small-scale glacier behavior. Spatio-temporal patterns of glacier distribution are still llimited in some areas of the high Hindu-Kush Himalaya, but multi-temporal satellite imagery has helped fill spatial and temporal gaps in regional glacier parameters in the last decade. Here I present a synopsis of the behavior of glaciers across the Himalaya, following a west to east gradient. In particular, I focus on spatial patterns of glacier parameters in the eastern Himalaya, which I investigate at multi-spatial scales using remote sensing data from declassified Corona, ASTER, Landsat ETM+, Quickbird and Worldview2 sensors. I also present the use of high-resolution imagery, including texture and thermal analysis for mapping glacier features at small scale, which are particularly useful in understanding surface trends of debris-covered glaciers, which are prevalent in the Himalaya. I compare and contrast spatial patterns of glacier area and élévation changes in the monsoon-influenced eastern Himalaya (the Everest region in the Nepal Himalaya and Sikkim in the Indian Himalaya) with other observations from the dry western Indian Himalaya (Ladakh and Lahul-Spiti), both field measurements and remote sensing-based. In the eastern Himalaya, results point to glacier area change of -0.24 % ± 0.08% per year from the 1960's to the 2006's, with a higher rate of retreat in the last decade (-0.43% /yr). Debris-covered glacier tongues show thinning trends of -30.8 m± 39 m on average over the last four decades, similar to other studies in the same climatic area. However, at small scales, the behavior of glaciers is highly heterogenous, with contrasting patterns of thickening glacier termini versus retreating nad thinning glacier tongues.

Remote sensing fusion based on guided image filtering

NASA Astrophysics Data System (ADS)

Zhao, Wenfei; Dai, Qinling; Wang, Leiguang

2015-12-01

In this paper, we propose a novel remote sensing fusion approach based on guided image filtering. The fused images can well preserve the spectral features of the original multispectral (MS) images, meanwhile, enhance the spatial details information. Four quality assessment indexes are also introduced to evaluate the fusion effect when compared with other fusion methods. Experiments carried out on Gaofen-2, QuickBird, WorldView-2 and Landsat-8 images. And the results show an excellent performance of the proposed method.

Estimating Wood Volume for Pinus Brutia Trees in Forest Stands from QUICKBIRD-2 Imagery

NASA Astrophysics Data System (ADS)

Patias, Petros; Stournara, Panagiota

2016-06-01

Knowledge of forest parameters, such as wood volume, is required for a sustainable forest management. Collecting such information in the field is laborious and even not feasible in inaccessible areas. In this study, tree wood volume is estimated utilizing remote sensing techniques, which can facilitate the extraction of relevant information. The study area is the University Forest of Taxiarchis, which is located in central Chalkidiki, Northern Greece and covers an area of 58km2. The tree species under study is the conifer evergreen species P. brutia (Calabrian pine). Three plot surfaces of 10m radius were used. VHR Quickbird-2 images are used in combination with an allometric relationship connecting the Tree Crown with the Diameter at breast height (Dbh), and a volume table developed for Greece. The overall methodology is based on individual tree crown delineation, based on (a) the marker-controlled watershed segmentation approach and (b) the GEographic Object-Based Image Analysis approach. The aim of the first approach is to extract separate segments each of them including a single tree and eventual lower vegetation, shadows, etc. The aim of the second approach is to detect and remove the "noisy" background. In the application of the first approach, the Blue, Green, Red, Infrared and PCA-1 bands are tested separately. In the application of the second approach, NDVI and image brightness thresholds are utilized. The achieved results are evaluated against field plot data. Their observed difference are between -5% to +10%.

Multiscale, multispectral and multitemporal satellite data to identify archaeological remains in the archaeological area of Tiwanaku (Bolivia)

NASA Astrophysics Data System (ADS)

Masini, Nicola; Lasaponara, Rosa

2015-04-01

The aim of this paper is to investigate the cultural landscape of the archaeological area of Tiwanaku (Bolivia) using multiscale, multispectral and multitemporal satellite data. Geospatial analysis techniques were applied to the satellite data sets in order to enhance and map traces of past human activities and perform a spatial characterization of environmental and cultural patterns. In particular, in the Tiwanaku area, the approach based on local indicators of spatial autocorrelation (LISA) applied to ASTER data allowed us to identify traces of a possible ancient hydrographic network with a clear spatial relation with the well-known moat surrounding the core of the monumental area. The same approach applied to QuickBird data, allowed us to identify numerous traces of archaeological interest, in Mollo Kontu mound, less investigated than the monumental area. Some of these traces were in perfect accordance with the results of independent studies, other were completely unknown. As a whole, the detected features, composing a geometric pattern with roughly North-South orientation, closely match those of the other residential contexts at Tiwanaku. These new insights, captured from multitemporal ASTER and QuickBird data processing, suggested new questions on the ancient landscape and provided important information for planning future field surveys and archaeogeophyical investigations. Reference [1] Lasaponara R., Masini N. 2014. Beyond modern landscape features: New insights in thearchaeological area of Tiwanaku in Bolivia from satellite data. International Journal of Applied Earth Observation and Geoinformation, 26, 464-471, http://dx.doi.org/10.1016/j.jag.2013.09.00. [2] Tapete D., Cigna F., Masini N., Lasaponara R. 2013. Prospection and monitoring of the archaeological heritage of Nasca, Peru, with ENVISAT ASAR, Archaeological Prospection, 20, 133-147, doi: 10.1002/arp.1449. [3] Lasaponara R, N Masini, 2012 Satellite Remote Sensing, A New Tool for Archaeology (Series Remote Sensing and Digital Image) Springer book [4] Masini N., Lasaponara N., Orefici G. 2009, Addressing the challenge of detecting archaeological adobe structures in Southern Peru using QuickBird imagery, Journal of Cultural Heritage, 10S, pp. e3-e9 [doi:10.1016/j.culher.2009.10.005]. [5] Masini N, R Lasaponara, 2006, Satellite-based recognition of landscape archaeological features related to ancient human transformation Journal of Geophysics and Engineering 3 (3), 230. Lasaponara R., Masini N. 2013, Satellite Synthetic Aperture Radar in Archaeology and Cultural Landscape: An Overview. Archaeological Prospection, 20, 71-78, doi: 10.1002/arp.1452

Unsupervised change detection in a particular vegetation land cover type using spectral angle mapper

NASA Astrophysics Data System (ADS)

Renza, Diego; Martinez, Estibaliz; Molina, Iñigo; Ballesteros L., Dora M.

2017-04-01

This paper presents a new unsupervised change detection methodology for multispectral images applied to specific land covers. The proposed method involves comparing each image against a reference spectrum, where the reference spectrum is obtained from the spectral signature of the type of coverage you want to detect. In this case the method has been tested using multispectral images (SPOT5) of the community of Madrid (Spain), and multispectral images (Quickbird) of an area over Indonesia that was impacted by the December 26, 2004 tsunami; here, the tests have focused on the detection of changes in vegetation. The image comparison is obtained by applying Spectral Angle Mapper between the reference spectrum and each multitemporal image. Then, a threshold to produce a single image of change is applied, which corresponds to the vegetation zones. The results for each multitemporal image are combined through an exclusive or (XOR) operation that selects vegetation zones that have changed over time. Finally, the derived results were compared against a supervised method based on classification with the Support Vector Machine. Furthermore, the NDVI-differencing and the Spectral Angle Mapper techniques were selected as unsupervised methods for comparison purposes. The main novelty of the method consists in the detection of changes in a specific land cover type (vegetation), therefore, for comparison purposes, the best scenario is to compare it with methods that aim to detect changes in a specific land cover type (vegetation). This is the main reason to select NDVI-based method and the post-classification method (SVM implemented in a standard software tool). To evaluate the improvements using a reference spectrum vector, the results are compared with the basic-SAM method. In SPOT5 image, the overall accuracy was 99.36% and the κ index was 90.11%; in Quickbird image, the overall accuracy was 97.5% and the κ index was 82.16%. Finally, the precision results of the method are comparable to those of a supervised method, supported by low detection of false positives and false negatives, along with a high overall accuracy and a high kappa index. On the other hand, the execution times were comparable to those of unsupervised methods of low computational load.

REFLECT: Logiciel de restitution des reflectances au sol pour l'amelioration de la qualite de l'information extraite des images satellitales a haute resolution spatiale

NASA Astrophysics Data System (ADS)

Bouroubi, Mohamed Yacine

Multi-spectral satellite imagery, especially at high spatial resolution (finer than 30 m on the ground), represents an invaluable source of information for decision making in various domains in connection with natural resources management, environment preservation or urban planning and management. The mapping scales may range from local (finer resolution than 5 m) to regional (resolution coarser than 5m). The images are characterized by objects reflectance in the electromagnetic spectrum witch represents the key information in many applications. However, satellite sensor measurements are also affected by parasite input due to illumination and observation conditions, to the atmosphere, to topography and to sensor properties. Two questions have oriented this research. What is the best approach to retrieve surface reflectance with the measured values while taking into account these parasite factors? Is this retrieval a sine qua non condition for reliable image information extraction for the diverse domains of application for the images (mapping, environmental monitoring, landscape change detection, resources inventory, etc.)? The goals we have delineated for this research are as follow: (1) Develop software to retrieve ground reflectance while taking into account the aspects mentioned earlier. This software had to be modular enough to allow improvement and adaptation to diverse remote sensing application problems; and (2) Apply this software in various context (urban, agricultural, forest) and analyse results to evaluate the accuracy gain of extracted information from remote sensing imagery transformed in ground reflectance images to demonstrate the necessity of operating in this way, whatever the type of application. During this research, we have developed a tool to retrieve ground reflectance (the new version of the REFLECT software). This software is based on the formulas (and routines) of the 6S code (Second Simulation of Satellite Signal in the Solar Spectrum) and on the dark targets method to estimated the aerosol optical thickness, representing the most difficult factor to correct. Substantial improvements have been made to the existing models. These improvements essentially concern the aerosols properties (integration of a more recent model, improvement of the dark targets selection to estimate the AOD), the adjacency effect, the adaptation to most used high resolution (Landsat TM and ETM+, all HR SPOT 1 to 5, EO-1 ALI and ASTER) and very high resolution (QuickBird et Ikonos) sensors and the correction of topographic effects with a model that separate direct and diffuse solar radiation components and the adaptation of this model to forest canopy. Validation has shown that ground reflectance estimation with REFLECT is performed with an accuracy of approximately +/-0.01 in reflectance units (for in the visible, near-infrared and middle-infrared spectral bands) even for a surface with varying topography. This software has allowed demonstrating, through apparent reflectance simulations, how much parasite factors influencing numerical values of the images may alter the ground reflectance (errors ranging from 10 to 50%). REFLECT has also been used to examine the usefulness of ground reflectance instead of raw data for various common remote sensing applications in domains such as classification, change detection, agriculture and forestry. In most applications (multi-temporal change monitoring, use of vegetation indices, biophysical parameters estimation, etc.) image correction is a crucial step to obtain reliable results. From the computer environment standpoint, REFLECT is organized as a series of menus, corresponding to different steps of: input parameters introducing, gas transmittances calculation, AOD estimation, and finally image correction application, with the possibility of using the fast option witch process an image of 5000 by 5000 pixels in approximately 15 minutes. (Abstract shortened by UMI.)

An Integrated Atmospheric and Hydrological Based Malaria Epidemic Alert System

NASA Astrophysics Data System (ADS)

Asefi Najafabady, S.; Li, J.; Nair, U. S.; Welch, R. M.; Srivastava, A.; Nagpal, B. N.; Saxena, R.; Benedict, M. E.

2005-05-01

Malaria is a growing global threat, with increasing morbidity and mortality. In India there have been >40 epidemics in the last five years, in part due to abnormal meteorological conditions as well as the buildup of an immunologically naïve population. In most parts of India, periodic epidemics of malaria occur every five to seven years. Malaria epidemics are serious national/regional health emergencies, occurring with little or no warning where the public health system is unprepared to respond to the emerging problem. However, epidemic conditions develop over several weeks, theoretically allowing time for preventative action. The study area for the proposed research is located in Mewat, south of Delhi. It is estimated that 90% of the malaria burden is influenced by environmental factors, so that successful malaria intervention approaches must be adapted to local environmental conditions. Of particular importance are air and water temperature, relative humidity, soil moisture, and precipitation. Extreme climatic conditions prevail in Mewat, with uneven topography, 450mm average annual rainfall in 25 to 35 days, high temperature variability in different seasons, low relative humidity. Automated surface measurements are obtained for temperature, relative humidity, water temperature, precipitation and soil moisture. The Regional Atmospheric Modeling System (RAMS) is used to predict these variables over the spatial domain which are used in dynamic hydrological models to yield the parameters important to malaria transmission, including surface wetness, mean water table depth, percent surface saturation and total surface runoff. The locations of saturated surface regions associated with mosquito breeding sites near populated regions, along with water temperature, and then are used to determine larvae development and mosquito abundance. ASTER, LANDSAT and MODIS imagery are used to retrieve soil moisture, vegetation indices and land cover types. Pan-sharpened 1m spatial resolution QuickBird data has been used to identify small mosquito breeding sites with an accuracy of 90 %, as verified by ground observations. These layers of information, along with a 30m resolution Digital Elevation Model and field measurements of malaria incidence, larvae and mosquito counts, were examined in a GIS system to identify the environmental parameters effective in mosquito distribution. The Genetic Algorithm for Rule Set Production (GARP) has been applied to the region using the parameters defined above to predict regions susceptible to malaria transmission.

Satellite and aerial data as a tool for digs localisation and their verification using geophysical methods

NASA Astrophysics Data System (ADS)

Pavelka, Karel; Faltynova, Martina; Bila, Zdenka

2013-04-01

The Middle Europe such as next world cultural centres are inhabited by humans tens of thousands years. In the last ten years, new methods are implemented in archaeology. It means new sensitive geophysical methods, very high resolution remote sensing and Airborne Laser Scanning (ALS). This contribution will refer about new technological possibilities for archaeology in the Czech Republic to two project examples. VHR satellite data or aerial image data can be used for searching of potential archaeological sites. In some cases, orthophoto mosaic is very useful; nowadays, different aerial orthophotomosaic layers are available in the Czech Republic (2002-3, 2006 and 2009) with pixel resolution 25cm. The archaeological findings are best visible in the Czech Republic by their vegetation indices. For this reason, the best time for data acquiring is mid of spring, in rapid vegetation process. Another option is the soil indices - the best time is early spring or autumn, after crop. A new progressive method is ALS, which can be used for spatial indices. Since autumn 2009 the entire area of the Czech Republic is mapped by technology of ALS. The aim of mapping is to get authentic and detailed digital terrain model (DTM) of the Czech Republic. About 80% (autumn 2012) of the Czech territory is currently covered by the DTM based on ALS. The standard deviation of model points in altitude is better than 20cm. The DTM displayed in appropriate form (as shaded surface) can be used as a data source for searching and description of archaeological sites - mainly in forested areas. By using of above mentioned methods a lot of interesting historical sites were discovered. The logical next step is a verification of these findings by using terrestrial methods - in this case by using of geophysical instruments. At the CTU Prague, the walking gradiometer GSM-19 and georadar SIR-3000 are at disposal. In first example the former fortification from Prussia - Austrian was localized on orthophoto mosaic and QuickBird satellite data. Normally is not visible from the surface. Secondary was fortification localized on shaded relief by spatial indices. Last verification has been made by walking magnetometer. Second example is joining of both magnetometers and GPR data. These technology and 3D modelling was used for localisation and verification of unknown tomb in the neighbourhood of church ruins in Panensky Tynec.

Building Exposure Maps Of Urban Infrastructure And Crop Fields In The Mekong River Basin

NASA Astrophysics Data System (ADS)

Haas, E.; Weichselbaum, J.; Gangkofner, U.; Miltzer, J.; Wali, A.

2013-12-01

In the frame of the Integrated Water Resources Management (IWRM) initiative for the Mekong river basin World Bank is collaborating with the Mekong River Commission and governmental organizations in Cambodia, Lao PDR, Thailand and Vietnam to build national and regional capacities for managing the risks associated with natural disasters, such as floods, flash floods and droughts. Within ‘eoworld', a joint initiative set up by ESA and World Bank to foster the use of Earth Observation (EO) for sustainable development work, a comprehensive database of elements at risk in the Lower Mekong river basin has been established by GeoVille, including urban infrastructure and crops (primarily rice paddies). In the long term, this exposure information shall be fed into an open-source multi- hazard modeling tool for risk assessment along the Mekong River, which then shall be used by national stakeholders as well as insurance and financial institutions for planning, disaster preparedness and emergency management. Earth Observation techniques can provide objective, synoptic and repetitive observations of elements at risk including buildings, infrastructure and crops. Through the fusion of satellite-based with in-situ data from field surveys and local knowledge (e.g. on building materials) features at risk can be characterised and mapped with high accuracy. Earth Observation data utilised comprise bi-weekly Envisat ASAR imagery programmed for a period of 9 months in 2011 to map the development of the rice cultivation area, identify predominant cropping systems (wet-season vs. dry season cultivation), crop cycles (single /double / triple crop per year), date of emergence/harvest and the distinction between rice planted under intensive (SRI) vs. regular rice cultivation techniques. Very High Resolution (VHR) optical data from SPOT, KOMPSAT and QuickBird were used for mapping of buildings and infrastructure, such as building footprints, residential / commercial areas, industrial buildings, main infrastructure, and other public assets. A key input to this work was data collected by the project team in the field with the purpose of scoping information about buildings including material, height (number of stories), construction technique, and floor area. A high resolution satellite-based Digital Elevation Model was additionally generated to provide surface elevations of vegetation and man-made objects with a vertical accuracy of 10 m. By using this methodology thousands of buildings and infrastructure features were mapped, clearly indicating the location and characteristics of the assets. Exposure maps were complemented with the analysis of historical flood and drought events using ERS and Envisat ASAR radar data for historical flood mapping alongside with vegetation index data from SPOT-VEGETATION and NOAA-AVHRR, concerning drought events.

Monitoring Corals and Submerged Aquatic Vegetation in Western Pacific Using Satellite Remote Sensing Integrated with Field Data

NASA Astrophysics Data System (ADS)

Roelfsema, C. M.; Phinn, S. R.; Lyons, M. B.; Kovacs, E.; Saunders, M. I.; Leon, J. X.

2013-12-01

Corals and Submerged Aquatic Vegetation (SAV) are typically found in highly dynamic environments where the magnitude and types of physical and biological processes controlling their distribution, diversity and function changes dramatically. Recent advances in the types of satellite image data and the length of their archives that are available globally, coupled with new techniques for extracting environmental information from these data sets has enabled significant advances to be made in our ability to map and monitor coral and SAV environments. Object Based Image Analysis techniques are one of the most significant advances in information extraction techniques for processing images to deliver environmental information at multiple spatial scales. This poster demonstrates OBIA applied to high spatial resolution satellite image data to map and monitor coral and SAV communities across a variety of environments in the Western Pacific that vary in their extent, biological composition, forcing physical factors and location. High spatial resolution satellite imagery (Quickbird, Ikonos and Worldview2) were acquired coincident with field surveys on each reef to collect georeferenced benthic photo transects, over various areas in the Western Pacific. Base line maps were created, from Roviana Lagoon Solomon island (600 km2), Bikini Atoll Marshall Island (800 Km2), Lizard Island, Australia (30 km2) and time series maps for geomorphic and benthic communities were collected for Heron Reef, Australia (24 km2) and Eastern Banks area of Moreton Bay, Australia (200 km2). The satellite image data were corrected for radiometric and atmospheric distortions to at-surface reflectance. Georeferenced benthic photos were acquired by divers or Autonomous Underwater Vehicles, analysed for benthic cover composition, and used for calibration and validation purposes. Hierarchical mapping from: reef/non-reef (1000's - 10000's m); reef type (100's - 1000's m); 'geomorphic zone' (10's - 100's m); to dominant components of benthic cover compositions (1 - 10's m); and individual benthic cover type scale (0.5-5.0's m), was completed using object based segmentation and semi-automated labelling through membership rules. Accuracy assessment of the satellite image based maps and field data sets scales maps produced with 90% maximum accuracy larger scales and less complex maps, versus 40 % at smaller scale and complex maps. The study showed that current data sets and object based analysis are able to reliable map at various scales and level of complexity covering a variety of extent and environments at various times; as a result science and management can use these tools to assess and understand the ecological processes taking place in coral and SAV environments.

Classification method, spectral diversity, band combination and accuracy assessment evaluation for urban feature detection

NASA Astrophysics Data System (ADS)

Erener, A.

2013-04-01

Automatic extraction of urban features from high resolution satellite images is one of the main applications in remote sensing. It is useful for wide scale applications, namely: urban planning, urban mapping, disaster management, GIS (geographic information systems) updating, and military target detection. One common approach to detecting urban features from high resolution images is to use automatic classification methods. This paper has four main objectives with respect to detecting buildings. The first objective is to compare the performance of the most notable supervised classification algorithms, including the maximum likelihood classifier (MLC) and the support vector machine (SVM). In this experiment the primary consideration is the impact of kernel configuration on the performance of the SVM. The second objective of the study is to explore the suitability of integrating additional bands, namely first principal component (1st PC) and the intensity image, for original data for multi classification approaches. The performance evaluation of classification results is done using two different accuracy assessment methods: pixel based and object based approaches, which reflect the third aim of the study. The objective here is to demonstrate the differences in the evaluation of accuracies of classification methods. Considering consistency, the same set of ground truth data which is produced by labeling the building boundaries in the GIS environment is used for accuracy assessment. Lastly, the fourth aim is to experimentally evaluate variation in the accuracy of classifiers for six different real situations in order to identify the impact of spatial and spectral diversity on results. The method is applied to Quickbird images for various urban complexity levels, extending from simple to complex urban patterns. The simple surface type includes a regular urban area with low density and systematic buildings with brick rooftops. The complex surface type involves almost all kinds of challenges, such as high dense build up areas, regions with bare soil, and small and large buildings with different rooftops, such as concrete, brick, and metal. Using the pixel based accuracy assessment it was shown that the percent building detection (PBD) and quality percent (QP) of the MLC and SVM depend on the complexity and texture variation of the region. Generally, PBD values range between 70% and 90% for the MLC and SVM, respectively. No substantial improvements were observed when the SVM and MLC classifications were developed by the addition of more variables, instead of the use of only four bands. In the evaluation of object based accuracy assessment, it was demonstrated that while MLC and SVM provide higher rates of correct detection, they also provide higher rates of false alarms.

The 2006 July 17 Java (Indonesia) tsunami from satellite imagery and numerical modelling: a single or complex source?

NASA Astrophysics Data System (ADS)

Hébert, H.; Burg, P.-E.; Binet, R.; Lavigne, F.; Allgeyer, S.; Schindelé, F.

2012-12-01

The Mw 7.8 2006 July 17 earthquake off the southern coast of Java, Indonesia, has been responsible for a very large tsunami causing more than 700 casualties. The tsunami has been observed on at least 200 km of coastline in the region of Pangandaran (West Java), with run-up heights from 5 to more than 20 m. Such a large tsunami, with respect to the source magnitude, has been attributed to the slow character of the seismic rupture, defining the event as a so-called tsunami earthquake, but it has also been suggested that the largest run-up heights are actually the result of a second local landslide source. Here we test whether a single slow earthquake source can explain the tsunami run-up, using a combination of new detailed data in the region of the largest run-ups and comparison with modelled run-ups for a range of plausible earthquake source models. Using high-resolution satellite imagery (SPOT 5 and Quickbird), the coastal impact of the tsunami is refined in the surroundings of the high-security Permisan prison on Nusa Kambangan island, where 20 m run-up had been recorded directly after the event. These data confirm the extreme inundation lengths close to the prison, and extend the area of maximum impact further along the Nusa Kambangan island (about 20 km of shoreline), where inundation lengths reach several hundreds of metres, suggesting run-up as high as 10-15 m. Tsunami modelling has been conducted in detail for the high run-up Permisan area (Nusa Kambangan) and the PLTU power plant about 25 km eastwards, where run-up reached only 4-6 m and a video recording of the tsunami arrival is available. For the Permisan prison a high-resolution DEM was built from stereoscopic satellite imagery. The regular basin of the PLTU plant was designed using photographs and direct observations. For the earthquake's mechanism, both static (infinite) and finite (kinematic) ruptures are investigated using two published source models. The models account rather well for the sea level variation at PLTU, showing a better agreement in arrival times with the finite rupture, and predict the Permisan area to be one of the regions where tsunami waves would have focussed. However, the earthquake models that match the data at PTLU do not predict that the wave heights at Permisan are an overall maximum, and do not predict there more than 10 m of the 21 observed. Hence, our results confirm that an additional localized tsunami source off Nusa Kambangan island, such as a submarine landslide, may have increased the tsunami impact for the Permisan site. This reinforces the importance for hazard assessment of further mapping and understanding local potential for submarine sliding, as a tsunami source added to usual earthquake sources.

Shrub Abundance Mapping in Arctic Tundra with Misr

NASA Astrophysics Data System (ADS)

Duchesne, R.; Chopping, M. J.; Wang, Z.; Schaaf, C.; Tape, K. D.

2013-12-01

Over the last 60 years an increase in shrub abundance has been observed in the Arctic tundra in connection with a rapid surface warming trend. Rapid shrub expansion may have consequences in terms of ecosystem structure and function, albedo, and feedbacks to climate; however, its rate is not yet known. The goal of this research effort is thus to map large scale changes in Arctic tundra vegetation by exploiting the structural signal in moderate resolution satellite remote sensing images from NASA's Multiangle Imaging SpectroRadiometer (MISR), mapped onto a 250m Albers Conic Equal Area grid. We present here large area shrub mapping supported by reference data collated using extensive field inventory data and high resolution panchromatic imagery. MISR Level 1B2 Terrain radiance scenes from the Terra satellite from 15 June-31 July, 2000 - 2010 were converted to surface bidirectional reflectance factors (BRF) using MISR Toolkit routines and the MISR 1 km LAND product BRFs. The red band data in all available cameras were used to invert the RossThick-LiSparse-Reciprocal BRDF model to retrieve kernel weights, model-fitting RMSE, and Weights of Determination. The reference database was constructed using aerial survey, three field campaigns (field inventory for shrub count, cover, mean radius and height), and high resolution imagery. Tall shrub number, mean crown radius, cover, and mean height estimates were obtained from QuickBird and GeoEye panchromatic image chips using the CANAPI algorithm, and calibrated using field-based estimates, thus extending the database to over eight hundred locations. Tall shrub fractional cover maps for the North Slope of Alaska were constructed using the bootstrap forest machine learning algorithm that exploits the surface information provided by MISR. The reference database was divided into two datasets for training and validation. The model derived used a set of 19 independent variables(the three kernel weights, ratios and interaction terms; white and black sky albedos; and blue, green, red, and NIR nadir camera BRFs), to grow a forest of decision trees. The final estimate is the average of the predicted values from each tree. Observations not used in constructing the trees were used in validation. The model was applied with a large volume of MISR data and the resulting fractional cover estimates were combined into annual maps using a compositing algorithm that flags results affected by cloud, cloud shadow, surface water, extreme outliers, topographic shading, and burned areas. The maps show that shrub cover is lower on the north slope in comparison to southern part, as expected, however, a preliminary assessment of the fractional cover change over the last decade, achieved by averaging fractional cover values for 2000-2002 and 2008-2010 and then calculating the change between the two periods, revealed that there are large areas for which we cannot determine the sign of the change with high confidence, as the precision of our estimate is close to the magnitude of the cover values. Additional research is thus required to reliably map shrub cover in this environment at annual intervals.

Assessment of Tropical Cyclone Induced Transgression of the Chandeleur Islands for Restoration and Wildlife Management

NASA Technical Reports Server (NTRS)

Mitchell, Brandie; Reahard, Ross; Billiot, Amanda; Brown, Tevin; Childs, Lauren

2009-01-01

The Chandeleur Islands are the first line of defense against tropical storms and hurricanes for coastal Louisiana. They provide habitats for birds species and are a wildlife refuge; however, distressingly, they are eroding and transgressing at an alarming rate. In 1998, Hurricane Georges caused severe damage to the chain, prompting restoration and monitoring efforts by both Federal and State agencies. Since then, storm events have steadily diminished the condition of the islands. Quantification of shoreline erosion, vegetation, and land loss, from 1979 to 2009, was achieved through the analysis of imagery from Landsat 2-4 Multispectral Scanner, Landsat 4 & 5 Thematic Mapper, and Advanced Spaceborne Thermal Emission and Reflection Radiometer sensors. QuickBird imagery was used to validate the accuracy of these results. In addition, this study presents an application of Moderate Resolution Imaging Spectroradiometer data to assist in tracking the transgression of the Chandeleur Islands. The use of near infrared reflectance calculated from MOD09 surface reflectance data from 2000 to 2009 was analyzed using the Time Series Product Tool. The scope of this project includes not only assessments of the tropical cyclonic events during this time period, but also the effects of tides, winds, and cold fronts on the spatial extent of the islands. Partnering organizations, such as the Pontchartrain Institute for Environmental Research, will utilize those results in an effort to better monitor and address the continual change of the island chain.

A fast and fully automatic registration approach based on point features for multi-source remote-sensing images

NASA Astrophysics Data System (ADS)

Yu, Le; Zhang, Dengrong; Holden, Eun-Jung

2008-07-01

Automatic registration of multi-source remote-sensing images is a difficult task as it must deal with the varying illuminations and resolutions of the images, different perspectives and the local deformations within the images. This paper proposes a fully automatic and fast non-rigid image registration technique that addresses those issues. The proposed technique performs a pre-registration process that coarsely aligns the input image to the reference image by automatically detecting their matching points by using the scale invariant feature transform (SIFT) method and an affine transformation model. Once the coarse registration is completed, it performs a fine-scale registration process based on a piecewise linear transformation technique using feature points that are detected by the Harris corner detector. The registration process firstly finds in succession, tie point pairs between the input and the reference image by detecting Harris corners and applying a cross-matching strategy based on a wavelet pyramid for a fast search speed. Tie point pairs with large errors are pruned by an error-checking step. The input image is then rectified by using triangulated irregular networks (TINs) to deal with irregular local deformations caused by the fluctuation of the terrain. For each triangular facet of the TIN, affine transformations are estimated and applied for rectification. Experiments with Quickbird, SPOT5, SPOT4, TM remote-sensing images of the Hangzhou area in China demonstrate the efficiency and the accuracy of the proposed technique for multi-source remote-sensing image registration.

Louisiana Natural Disasters and Ecological Forecasting: Assessment of Tropical Cyclone Induced Transgression of the Chandeleur Islands for Restoration and Wildlife Management

NASA Astrophysics Data System (ADS)

Reahard, R. R.; Mitchell, B. S.; Childs, L. M.; Billiot, A.; Brown, T.

2009-12-01

The Chandeleur Islands are the first line of defense against tropical storms and hurricanes for coastal Louisiana. They provide habitats for bird species and are a national wildlife refuge; however, they are eroding and transgressing at an alarming rate. In 1998, Hurricane Georges caused severe damage to the chain, prompting restoration and monitoring efforts by both Federal and State agencies. Since then, storm events have steadily diminished the condition of the islands. Quantification of shoreline erosion, vegetation, and land loss, from 1979 to 2009, was calculated through the analysis of imagery from Landsat 2-4 Multispectral Scanner, Landsat 4 & 5 Thematic Mapper, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensors. QuickBird imagery was used to validate the accuracy of these results. In addition, this study presents an application of Moderate Resolution Imaging Spectroradiometer (MODIS) data to assist in tracking the landward migration of the Chandeleur Islands. The use of near infrared reflectance calculated from MOD09 surface reflectance data from 2000 to 2008 was analyzed using the Time Series Product Tool. The scope of this project includes not only assessments of the tropical cyclonic events during this time period, but also the effects of tides, winds, and cold fronts on the spatial extent of the islands. Partnering organizations, such as the Pontchartrain Institute for Environmental Sciences, will utilize those results in an effort to better monitor and address the continual change of the Chandeleur Islands.

Vegetation Patterns and Degradation Thresholds in the Mulga Landscapes of Australia

NASA Astrophysics Data System (ADS)

Azadi, Samira; Saco, Patricia; Moreno-de las Heras, Mariano; Willgoose, Garry

2017-04-01

Drylands are often characterised by a spatially heterogeneous vegetation cover forming mosaics of patches dense vegetation within bare soil. This 'patterned' or 'patchy' vegetation cover is sensitive to human pressures. Previous work suggests that within these landscapes there is a critical vegetation cover threshold below which the landscape functionality is lost. This threshold behaviour is tightly linked to the overland flow redistribution and an increase in hydrologic connectivity that induces loss of resources (i.e., leakiness). In fact, disturbances (such as wildfire, overgrazing or harvesting activities) can disrupt the spatial structure of vegetation, increase landscape hydrologic connectivity, trigger erosion and produce a substantial loss of water. All these effects affect ecosystem functionality. Here we present the results of exploring the impact of degradation processes induced by vegetation disturbances (mainly grazing) on ecosystem functionality and connectivity in semiarid landscapes with various types of vegetation patterns. The sites are carefully selected in Mulga landscapes bioregion (New South Wales, Queensland) and in sites of Northern Territory in Australia, which display similar vegetation characteristics but with different vegetation patterns and good quality rainfall information. The analysis of vegetation patterns is derived from high resolution remote sensing images (IKONOS, QuickBird, Pleiades). Using MODIS NDVI and local precipitation data, we compute rainfall use efficiency and precipitation marginal response in order to assess the ecosystem functionality. We use vegetation binary maps and digital elevation models to estimate mean Flowlength as an indicator of structural hydrologic connectivity. We compare the trends for several sites with varying vegetation patterns (i.e., banded versus spotted patterns). Our results show that disturbances increase hydrologic connectivity and suggest threshold behaviour that affects landscape functionality. Though this threshold behaviour is found in all sites, the plots in higher rainfall landscapes with banded vegetation patterns show evidence of higher resilience. We will also present some preliminary modelling results that complement this analysis and capture the coevolution of vegetation and landforms (erosion), leading to this type of threshold behaviour.

Putting us on the Map: Remote Sensing Investigation of the Ancient Maya Landscape

NASA Technical Reports Server (NTRS)

Sever, Thomas L.; Saturno, William; Irwin, Daniel E.

2004-01-01

A common problem for archaeologists studying ancient settlement in the Maya Lowlands is overcoming the dense vegetation in order to obtain an accurate regional perspective of the presence of archaeological sites, their exact locations and their overall extents. Most often this is done by extensive ground surveys in which many individuals chop parallel paths through the vegetation in search of sites. Once a site is found an effort is made to mark its location on a regional map and to explore its perimeter. Obtaining locational information has been made dramatically easier in recent years with the advent of improved Global Positioning Systems (GPS), however the process of initial identification of sites and the determination of their borders is exceedingly labor intensive and has remained relatively unchanged since the beginning of settlement surveys in the region in the 1950's. Currently, we are revolutionizing settlement survey in the Maya Lowlands by using remotely sensed data from IKONOS, Quickbird, and Eol, satellites. The Ancient Maya built their cities, towns and even their smallest hamlets using excavated limestone and lime plasters. We propose that the decay of these structures provides a unique microenvironment for the growth of vegetation as the levels of moisture and nutrition within the ruins vary substantially from those in the surrounding forest. These microenvironmental differences on the ground are likewise represented by compositional differences in the forest canopy both in the species present and in leaf color (representing moisture/nutritional stress) visible through the analysis of high- resolution satellite data. In this way the detailed analysis of forest composition can reveal a detailed picture of the ancient settlements that lie beneath it. Preliminary examinations using this technique have been very successful and we are refining these techniques in order to efficiently comprehend the details of Ancient Maya settlement in the Lowlands.

Putting Us on the Map: Remote Sensing Investigation of the Ancient Maya Landscape

NASA Technical Reports Server (NTRS)

Sever, Thomas L.; Saturno, William

2004-01-01

A common problem for archaeologists studying ancient settlement in the Maya Lowlands is overcoming the dense vegetation in order to obtain an accurate regional perspective of the presence of archaeological sites, their exact locations and their overall extents. Most often this is done by extensive ground surveys in which many individuals chop parallel paths through the vegetation in search of sites. Once a site is found an effort is made to mark its location on a regional map and to explore its perimeter. Obtaining locational information has been made dramatically easier in recent years with the advent of improved Global Positioning Systems (GPS), however the process of initial identification of sites and the determination of their borders is exceedingly labor intensive and has remained relatively unchanged since the beginning of settlement surveys in the region in the 1950 s. Currently, we are revolutionizing settlement survey in the Maya Lowlands by using remotely sensed data from IKONOS, Quickbird, and Eo 1, satellites as well as airborne AIRSAR radar data. The Ancient Maya built their cities, towns and even their smallest hamlets using excavated limestone and lime plasters. We propose that the decay of these structures provides a unique microenvironment for the growth of vegetation as the levels of moisture and nutrition within the ruins vary substantially from those in the surrounding forest. These microenvironmental differences on the ground are likewise represented by compositional differences in the forest canopy both in the species present and in leaf color (representing moisture/nutritional stress) visible through the analysis of high-resolution satellite data. In this way the detailed analysis of forest composition can reveal a detailed picture of the ancient settlements that lie beneath it. Preliminary examinations using this technique have been very successful and we are refining these techniques in order to efficiently comprehend the details of Ancient Maya settlement in the Lowlands.

Assessment of impact of mass movements on the upper Tayyah valley's bridge along Shear escarpment highway, Asir region (Saudi Arabia) using remote sensing data and field investigation

NASA Astrophysics Data System (ADS)

Youssef, A. M.; Al-Kathery, M.; Pradhan, B.

2015-01-01

Escarpment highways, roads and mountainous areas in Saudi Arabia are facing landslide hazards that are frequently occurring from time to time causing considerable damage to these areas. Shear escarpment highway is located in the north of the Abha city. It is the most important escarpment highway in the area, where all the light and heavy trucks and vehicle used it as the only corridor that connects the coastal areas in the western part of the Saudi Arabia with the Asir and Najran Regions. More than 10 000 heavy trucks and vehicles use this highway every day. In the upper portion of Tayyah valley of Shear escarpment highway, there are several landslide and erosion potential zones that affect the bridges between tunnel 7 and 8 along the Shear escarpment Highway. In this study, different types of landslides and erosion problems were considered to access their impacts on the upper Tayyah valley's bridge along Shear escarpment highway using remote sensing data and field investigation. These landslides and erosion problems have a negative impact on this section of the highway. Results indicate that the areas above the highway and bridge level between bridge 7 and 8 have different landslides including planar, circular, rockfall failures and debris flows. In addition, running water through the gullies cause different erosional (scour) features between and surrounding the bridge piles and culverts. A detailed landslides and erosion features map was created based on intensive field investigation (geological, geomorphological, and structural analysis), and interpretation of Landsat image 15 m and high resolution satellite image (QuickBird 0.61 m), shuttle radar topography mission (SRTM 90 m), geological and topographic maps. The landslides and erosion problems could exhibit serious problems that affect the stability of the bridge. Different mitigation and remediation strategies have been suggested to these critical sites to minimize and/or avoid these problems in the future.

Multitemporal satellite images for the knowledge of ancient Assyrian capital cities and for the analysis of landscape transformations in the upper course of the Tigris

NASA Astrophysics Data System (ADS)

Scardozzi, Giuseppe

2010-05-01

The paper concerns the contribution that a rich documentation of multitemporal optical satellite images at high resolution provides for the knowledge of the four great Assyrian capital cities (Ashur, Nimrud, Khorsabad, Niniveh in Northern Iraq), and to analyze and monitor changes in the landscape in the higher course of the Tigris during the last half century. The data set, available for each city, consists of both panchromatic and multispectral images of modern satellites for civil use (Ikonos-2, QuickBird-2), both panchromatic photographs of U.S. spy satellites operating in the years 1960s and 1970s (Corona KH-4A, Corona KH-4B, Gambit KH-7), before diffusion of mechanized agriculture and the expansion of urban areas. They are therefore images that also allow to monitor the damage to archaeological sites during the two Gulf Wars, especially the second. The rich data set was collected as part of Iraq Virtual Museum Project, realized by the Italian National Research Council, under which the Institute for Archaeological and Monumental Heritage has dealt with the contextualization of the materials (stored in the Baghdad National Museum) in their archaeological sites of origin, and with the virtual reconstruction of some "rooms" of the virtual museum. The most interesting data emerged in the research concerns, for example, the reconstruction of the paleo-river bed of the Tigris (and channels connected to it) near the ancient urban areas of Ashur, Nimrud and Niniveh; in the latter city, in addition, the expansion of modern Mosul in recent decades has obliterated part of the ancient urban area and the ancient canals network that surrounded it. In the case of Khorsabad, the images taken in different years allow us to reconstruct the layout of the ancient city and offer a planimetric vision of structures excavated in the XIX-XX centuries and later heavily damaged by weathering, by agricultural works and by the second Gulf War.

Quickbird Satellite in-orbit Modulation Transfer Function (MTF) Measurement Using Edge, Pulse and Impulse Methods for Summer 2003

NASA Technical Reports Server (NTRS)

Helder, Dennis; Choi, Taeyoung; Rangaswamy, Manjunath

2005-01-01

The spatial characteristics of an imaging system cannot be expressed by a single number or simple statement. However, the Modulation Transfer Function (MTF) is one approach to measure the spatial quality of an imaging system. Basically, MTF is the normalized spatial frequency response of an imaging system. The frequency response of the system can be evaluated by applying an impulse input. The resulting impulse response is termed the Point Spread function (PSF). This function is a measure of the amount of blurring present in the imaging system and is itself a useful measure of spatial quality. An underlying assumption is that the imaging system is linear and shift-independent. The Fourier transform of the PSF is called the Optical Transfer Function (OTF) and the normalized magnitude of the OTF is the MTF. In addition to using an impulse input, a knife-edge in technique has also been used in this project. The sharp edge exercises an imaging system at all spatial frequencies. The profile of an edge response from an imaging system is called an Edge Spread Function (ESF). Differentiation of the ESF results in a one-dimensional version of the Point Spread Function (PSF). Finally, MTF can be calculated through use of Fourier transform of the PSF as stated previously. Every image includes noise in some degree which makes MTF of PSF estimation more difficult. To avoid the noise effects, many MTF estimation approaches use smooth numerical models. Historically, Gaussian models and Fermi functions were applied to reduce the random noise in the output profiles. The pulse-input method was used to measure the MTF of the Landsat Thematic Mapper (TM) using 8th order even functions over the San Mateo Bridge in San Francisco, California. Because the bridge width was smaller than the 30-meter ground sample distance (GSD) of the TM, the Nyquist frequency was located before the first zero-crossing point of the sinc function from the Fourier transformation of the bridge pulse. To avoid the zero-crossing points in the frequency domain from a pulse, the pulse width should be less than the width of two pixels (or 2 GSD's), but the short extent of the pulse results in a poor signal-to-noise ratio. Similarly, for a high-resolution satellite imaging system such as Quickbird, the input pulse width was critical because of the zero crossing points and noise present in the background area. It is important, therefore, that the width of the input pulse be appropriately sized. Finally, the MTF was calculated by taking ratio between Fourier transform of output and Fourier transform of input. Regardless of whether the edge, pulse and impulse target method is used, the orientation of the targets is critical in order to obtain uniformly spaced sub-pixel data points. When the orientation is incorrect, sample data points tend to be located in clusters that result in poor reconstruction of the edge or pulse profiles. Thus, a compromise orientation must be selected so that all spectral bands can be accommodated. This report continues by outlining the objectives in Section 2, procedures followed in Section 3, descriptions of the field campaigns in Section 4, results in Section 5, and a brief summary in Section 6.

Decadal changes in tundra land cover on Yamal Peninsula, Northwest Siberia

NASA Astrophysics Data System (ADS)

Forbes, B. C.; Kumpula, T.; Macias-Fauria, M.

2017-12-01

The Yamal-Nenets Okrug in Russia has experienced significant changes in land use and climate in recent decades. Average year-round air temperatures have increased ca. 2°C since the 1970's, with much - but not all - of the warming taking place in winter. In association with ongoing summer warming, the annual growth of erect deciduous shrubs has been accelerating while growing season seasonality has diminished, characterized by shifts in the spatial patterns of key phenological parameters. We prepared LANDSAT-derived land cover classifications for 1988 and 2014 using change detection analysis, supported by extensive ground truthing bolstered with data from Very High-Resolution (VHR) imagery (e.g. Quickbird-2, Worldview-2/3). Research was conducted within summer reindeer pastures utilized by the Yarsalinksi sovhoz, whose animals are collectively owned, as well as many privately-owned herds. The area represents bioclimatic Subzone D of the Circumpolar Arctic Vegetation Map and covers about 8500 km2. This is a key subzone for several reasons: (1) it includes Bovanenkovo, the first and largest gas deposit on Yamal to be developed; (2) it is a zone of extremely active periglacial processes (e.g. active layer detachment slides, lake drainage and recent methane-mediated craters); and (3) it is characterized by steadily increasing growth of tall willow shrubs (Salix spp.), which comprise an important source of fodder by reindeer migrating through the area in summer. These results are unique as our dataset: (1) covers sizable inland regions lying entirely within the Russian tundra zone; (2) derives from extensive ground truthing; and (3) treats all plant taxonomic groups (vascular, bryophytes, lichens) at the plot scale. Here we present the first such classifications, based on LANDSAT images from 1988 and 2014. We identify 16 classes ranging from bare ground and drained lakes, anthropogenic disturbances, through several wetland types, to various dwarf and erect tundra shrub habitats. Given that Yamal is such a highly dynamic periglacial environment, our change detection results over a 36-year period strongly indicate that several processes, such as drying tundra lakes, landslides, expanding gas development, will continue to influence the changes in landscape-level vegetation and permafrost substrate processes.

Nile Delta exhibited a spatial reversal in the rates of shoreline retreat on the Rosetta promontory comparing pre- and post-beach protection

NASA Astrophysics Data System (ADS)

Ghoneim, Eman; Mashaly, Jehan; Gamble, Douglas; Halls, Joanne; AbuBakr, Mostafa

2015-01-01

The coastline of the Nile Delta experienced accelerated erosion since the construction of the Aswan High Dam in 1964 and, consequently, the entrapment of a large amount of river sediments behind it. The coastline of the Rosetta promontory showed the highest erosion in the Delta with an average retreat rate of 137.4 m year- 1. In 1991, in an effort to mitigate sediment loss, a 4.85 km long seawall was built on the outer margin of the promontory. For additional beach protection, 15 groins were constructed along the eastern and western sides of the seawall in 2003 and 2005. To quantify erosion and accretion patterns along the Rosetta promontory, 11 Landsat images acquired at unequal intervals during a 40 year time span (1972 and 2012) were analyzed. The positions of shorelines were automatically extracted from satellite imagery and compared with three very high resolution QuickBird and WorldView2 images for data validation. Analysis of the rates of shoreline change revealed that the construction of the seawall was largely successful in halting the recession along the tip of the promontory, which lost 10.8 km2 prior to coastal protection. Conversely, the construction of the 15 groins has negatively affected the coastal morphology of the promontory and caused a reversal from accretion to fast erosion along the promontory leeside, where some segments of the shoreline have undergone as much as 30.8 m year- 1 of erosion. Without hard structures, the tip of the Rosetta promontory would have retreated 2.3 km by 2013 and lost 7.2 km2 of land. About 10% of this land is deltaic fertile cultivated farms. Moreover, without additional protection the sides of the promontory will lose about 1.3 km2 of land and the coastline would recede at an average rate of 200 m by 2020. Unless action is taken, coastal erosion, enhanced by rising sea level, will steadily eat away the Nile Delta at an alarming rate. The successful demonstration of the advocated procedures in this study could be adopted, with appropriate modifications, for other deltas worldwide.

Multi-scale remote sensing sagebrush characterization with regression trees over Wyoming, USA: laying a foundation for monitoring

USGS Publications Warehouse

Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.

2012-01-01

agebrush ecosystems in North America have experienced extensive degradation since European settlement. Further degradation continues from exotic invasive plants, altered fire frequency, intensive grazing practices, oil and gas development, and climate change – adding urgency to the need for ecosystem-wide understanding. Remote sensing is often identified as a key information source to facilitate ecosystem-wide characterization, monitoring, and analysis; however, approaches that characterize sagebrush with sufficient and accurate local detail across large enough areas to support this paradigm are unavailable. We describe the development of a new remote sensing sagebrush characterization approach for the state of Wyoming, U.S.A. This approach integrates 2.4 m QuickBird, 30 m Landsat TM, and 56 m AWiFS imagery into the characterization of four primary continuous field components including percent bare ground, percent herbaceous cover, percent litter, and percent shrub, and four secondary components including percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata Wyomingensis), and shrub height using a regression tree. According to an independent accuracy assessment, primary component root mean square error (RMSE) values ranged from 4.90 to 10.16 for 2.4 m QuickBird, 6.01 to 15.54 for 30 m Landsat, and 6.97 to 16.14 for 56 m AWiFS. Shrub and herbaceous components outperformed the current data standard called LANDFIRE, with a shrub RMSE value of 6.04 versus 12.64 and a herbaceous component RMSE value of 12.89 versus 14.63. This approach offers new advancements in sagebrush characterization from remote sensing and provides a foundation to quantitatively monitor these components into the future.

Object-based landslide mapping on satellite images from different sensors

NASA Astrophysics Data System (ADS)

Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens; Blaschke, Thomas

2015-04-01

Several studies have proven that object-based image analysis (OBIA) is a suitable approach for landslide mapping using remote sensing data. Mostly, optical satellite images are utilized in combination with digital elevation models (DEMs) for semi-automated mapping. The ability of considering spectral, spatial, morphometric and contextual features in OBIA constitutes a significant advantage over pixel-based methods, especially when analysing non-uniform natural phenomena such as landslides. However, many of the existing knowledge-based OBIA approaches for landslide mapping are rather complex and are tailored to specific data sets. These restraints lead to a lack of transferability of OBIA mapping routines. The objective of this study is to develop an object-based approach for landslide mapping that is robust against changing input data with different resolutions, i.e. optical satellite imagery from various sensors. Two study sites in Taiwan were selected for developing and testing the landslide mapping approach. One site is located around the Baolai village in the Huaguoshan catchment in the southern-central part of the island, the other one is a sub-area of the Taimali watershed in Taitung County near the south-eastern Pacific coast. Both areas are regularly affected by severe landslides and debris flows. A range of very high resolution (VHR) optical satellite images was used for the object-based mapping of landslides and for testing the transferability across different sensors and resolutions: (I) SPOT-5, (II) Formosat-2, (III) QuickBird, and (IV) WorldView-2. Additionally, a digital elevation model (DEM) with 5 m spatial resolution and its derived products (e.g. slope, plan curvature) were used for supporting the semi-automated mapping, particularly for differentiating source areas and accumulation areas according to their morphometric characteristics. A focus was put on the identification of comparatively stable parameters (e.g. relative indices), which could be transferred to the different satellite images. The presence of bare ground was assumed to be an evidence for the occurrence of landslides. For separating vegetated from non-vegetated areas the Normalized Difference Vegetation Index (NDVI) was primarily used. Each image was divided into two respective parts based on an automatically calculated NDVI threshold value in eCognition (Trimble) software by combining the homogeneity criterion of multiresolution segmentation and histogram-based methods, so that heterogeneity is increased to a maximum. Expert knowledge models, which depict features and thresholds that are usually used by experts for digital landslide mapping, were considered for refining the classification. The results were compared to the respective results from visual image interpretation (i.e. manually digitized reference polygons for each image), which were produced by an independent local expert. By that, the spatial overlaps as well as under- and over-estimated areas were identified and the performance of the approach in relation to each sensor was evaluated. The presented method can complement traditional manual mapping efforts. Moreover, it contributes to current developments for increasing the transferability of semi-automated OBIA approaches and for improving the efficiency of change detection approaches across multi-sensor imagery.

Spatial Heterogeneity of Ice Cover Sediment and Thickness and Its Effects on Photosynthetically Active Radiation and Chlorophyll-a Distribution: Lake Bonney, Antarctica

NASA Astrophysics Data System (ADS)

Obryk, M.; Doran, P. T.; Priscu, J. C.; Morgan-Kiss, R. M.; Siebenaler, A. G.

2012-12-01

The perennially ice-covered lakes in the McMurdo Dry Valleys, Antarctica have been extensively studied under the Long Term Ecological Research project. But sampling has been spatially restricted due to the logistical difficulty of penetrating the 3-6 m of ice cover. The ice covers restrict wind-driven turbulence and its associated mixing of water, resulting in a unique thermal stratification and a strong vertical gradient of salinity. The permanent ice covers also shade the underlying water column, which, in turn, controls photosynthesis. Here, we present results of a three-dimensional record of lake processes obtained with an autonomous underwater vehicle (AUV). The AUV was deployed at West Lake Bonney, located in Taylor Valley, Dry Valleys, to further understand biogeochemical and physical properties of the Dry Valley lakes. The AUV was equipped with depth, conductivity, temperature, under water photosynthetically active radiation (PAR), turbidity, chlorophyll-and-DOM fluorescence, pH, and REDOX sensors. Measurements were taken over the course of two years in a 100 x 100 meter spaced horizontal sampling grid (and 0.2 m vertical resolution). In addition, the AUV measured ice thickness and collected 200 images looking up through the ice, which were used to quantify sediment distribution. Comparison with high-resolution satellite QuickBird imagery demonstrates a strong correlation between aerial sediment distribution and ice cover thickness. Our results are the first to show the spatial heterogeneity of lacustrine ecosystems in the McMurdo Dry Valleys, significantly improving our understanding of lake processes. Surface sediment is responsible for localized thinning of ice cover due to absorption of solar radiation, which in turn increases total available PAR in the water column. Higher PAR values are negatively correlated with chlorophyll-a, presenting a paradox; historically, long-term studies of PAR and chlorophyll-a have shown positive trends. We hypothesized that this paradox is a result of short-term photoadaptation of phytoplanktonic communities to spatial and temporal variations of PAR within the water column. To test this hypothesis, we established phytoplankton enrichment cultures from depths of maximum primary production (13 m) and tested whether dry valley lake phytoplankton respond to daily variations in controlled light environment. Laboratory-grown cultures exhibited a strong response at 12 hr:12 hr day:night cycle at the level of both photochemistry and chlorophyll biosynthesis, indicating that Lake Bonney possess the ability to quickly respond to changes in their light environment.

A multi-sensor approach to assess erosion risk in low mountain range landscapes - a comparative case study in western Germany

NASA Astrophysics Data System (ADS)

Seeling, S.; Buddenbaum, H.; Seeger, M.; Löhnertz, M.

2009-04-01

In this presentation we summarize our experience in the derivation of variables for identification of erosion and areas endagered of erosion from different remote sensing sensors. The field study is situated at the "Zemmer-Plateau" (north-east from Trier) and was undertaken to compare the ability of different, passive and active, remote sensing sensors to derive several process parameters of soil erosion in agricultural landscapes. Additionally the added value of sensor combinations was investigated. Backscatter of C-Band microwave instruments is known to be sensitive to soil roughness and surface soil moisture. If landuse and roughness is approximately constant, backscatter is mostly affected by temporal changes in soil moisture. For the test site multitemporal imagery from the ASAR and ERS2 sensors was available. For the identification of areas prone to waterlogging an approach based on principal component analysis was used. Multitemporal imagery from optical sensors like Landsat and SPOT HRV allow the assessment of slow changes within the landscape and annual changes of vegetation cover. We used Landsat imagery from 1975, 1984 and 2000 to map the changes in landuse and associated soil development, multi temporal imagery from SPOT 4 and 5 satellites was used to identify different crop types. Additionally we investigated which areas that are prone to erosion by their topography position, have, due to maladjusted land management, not been protected by vegetation cover during the main annual rainfall season in 2003. Airborne Laser Scanning (ALS) data is well suited for discovering areas susceptible of erosion. Even under forest canopies ALS can provide high-resolution terrain models that can be used for identifying trenches, linear features, steep hills and other terrain features, which trigger erosion or are even results of erosion. ALS-derived DTMs usually have a spatial resolution of about 1 m, while DTMs from other data sources are much coarser. A key problem when working with ALS is finding the echoes that have really been reflected by the ground and not by buildings or vegetation. This is achieved by filtering the last and only return laser points. The investigations were aided be the analyses of two Quickbird datasets. The information layers derived from different sensors were merged into a preliminary erosion information system. This data base allows the identification of areas prone to erosion risk. Furthermore the results allow setting the focus on the most effective methods for further investigations.

Diagnostic Features of Lava Flows in Satellite and Airborne Images (Invited)

NASA Astrophysics Data System (ADS)

Rowland, S. K.; Bruno, B. C.; Comeau, D.; Mouginis-Mark, P. J.; Fagents, S. A.; Harris, A. J.

2013-12-01

Characteristic surface features on lava flows can be seen in, and measured from, nadir and oblique airborne and space borne images. Some are diagnostic of volumetric flow rate, lava-transport mode, rheology, and composition. These in turn can be used to infer eruption styles, magma chamber stress regimes, volcanic histories, etc. Where independent methods can determine these properties, the image-based methods can be refined and (tentatively) extended to other planets. For example, the planimetric outline of a lava flow is determined by the lava's volumetric flow rate and rheology, the strength of the cooled skin relative to that of the fluid interior, and the extent to which a flow can conform to, or over-run, pre-existing topography. Fluid, skin-strength-dominated lava such as pāhoehoe, has a very convoluted outline; more viscous, interior-strength-dominated lava such as ';a';ā (as well as more silicic compositions) have more linear outlines. This can be quantified by the fractal dimension, which increases with convolution. Spatial resolution and degradation of the flow margin are important caveats. Flow margins are relatively easy to measure with IKONOS and QuickBird (Earth), HiRISE (Mars), and LROC NAC (Moon) data, all of which have spatial resolutions < 1 m. They become more difficult to measure in Landsat (30 m), THEMIS vis. (Mars; 18 m), or Magellan (75 m; Venus) data. Also useful is the ratio between the radius of curvature of the flow front and the flow length, which is small for long narrow (fluid) flows, and large for short stubby (viscous) flows. Even incipient channels display shear zones across which there were sharp velocity gradients, and these are preserved on flow surfaces. Tube-fed flows may display lines of skylights that indicate master tubes. Whether a flow is channel-fed ';a';ā or tube-fed pāhoehoe is determined by the volumetric flow rate, which is almost always directly related to the eruption rate. This may be related to the driving pressure in the magma chamber. Relative age information from stratigraphic, cross-cutting, and weathering relationships, in combination with eruption style information, can be used to determine changes in volcanic behavior through time. Diagnostic features on part of the 1907 Mauna Loa SW rift zone flow. Flow margin (red, B), shear planes (green, C), and clefts between pressure ridges (blue, D). If the only information available were that in B, C, or D, it would still be possible to identify this as a high volumetric flow-rate channel-fed ';a';ā flow.

Exploitation of multi-temporal Earth Observation imagery for monitoring land cover change in mining sites

NASA Astrophysics Data System (ADS)

Petropoulos, G.; Partsinevelos, P.; Mitraka, Z.

2012-04-01

Surface mining has been shown to cause intensive environmental degradation in terms of landscape, vegetation and biological communities. Nowadays, the commercial availability of remote sensing imagery at high spatiotemporal scales, has improved dramatically our ability to monitor surface mining activity and evaluate its impact on the environment and society. In this study we investigate the potential use of Landsat TM imagery combined with diverse classification techniques, namely artificial neural networks and support vector machines for delineating mining exploration and assessing its effect on vegetation in various surface mining sites in the Greek island of Milos. Assessment of the mining impact in the study area is validated through the analysis of available QuickBird imagery acquired nearly concurrently to the TM overpasses. Results indicate the capability of the TM sensor combined with the image analysis applied herein as a potential economically viable solution to provide rapidly and at regular time intervals information on mining activity and its impact to the local environment. KEYWORDS: mining environmental impact, remote sensing, image classification, change detection, land reclamation, support vector machines, neural networks

Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data

NASA Astrophysics Data System (ADS)

Greco, M.; Simoniello, T.; Lanfredi, M.; Russo, A. L.

2010-09-01

In the last years, the theme of suitable assessment of irrigation water supply has been raised relevant interest for both general principles of sustainable development and optimization of water resources techniques and management. About 99% of the water used in agriculture is lost by crops as evapotranspiration (ET). Thus, it becomes crucial to drive direct or indirect measurement in order to perform a suitable evaluation of water loss by evapotranspiration (i.e. actual evapotranspiration) as well as crop water status and its effect on the production. The main methods used to measure evapotranspiration are available only at field scale (Bowen ratio, eddy correlation system, soil water balance) confined to a small pilot area, generally due to expense and logistical constraints. This led over the last 50 years to the development of a large number of empirical methods to estimate evapotranspiration through different climatic and meteorological variables as well as combining models, based on aerodynamic theory and energy balance, taking into account both canopy properties and meteorological conditions. Among these, the Penman-Monteith equation seems to give the best results providing a robust and consistent method world wide accepted. Such conventional methods only provide accurate evapotranspiration assessment for a homogeneous region nearby the meteorological gauge station and cannot be extrapolated to other different sites; whereas remote sensing techniques allow for filling up such a gap. Some of these satellite techniques are based on the use of thermal band signals as inputs for energy balance equations. Another common approach is mainly based on the FAO method for estimating crop evapotranspiration, in which evapotranspiration data are multiplied by crop coefficients, Kc, derived from satellite multispectral vegetation indices obtained. The rationale behind such a link considers that Kc and vegetation indices are sensitive to both leaf area index and fractional ground cover. Thermal-based energy balance models are more suitable than the FAO-Kc model for estimating crop ET, especially under moisture stress conditions, but they require many inputs and detailed theoretical background knowledge; so they can be only used in regions where high quality, hourly agricultural weather data are readily available providing instantaneous values of heat fluxes corresponding to the time of the satellite overpass. Thus, FAO-Kc approach is widely used in research activities and real-time irrigation scheduling for several water applications since it does not require temporal upscaling for obtaining daily values and satellite imagery in the reflective bands used for vegetation index computation are more readily available at higher spatial resolution than thermal band data. There is no simple way to compute crop coefficients because they depend on climate, soil type, crop and its varieties, irrigation method, soil water, nutrient content and plant phenology. Consequently, specific calibrations of crop coefficient are required in various climatic regions. Many authors suggested a linear relationship between Kc and vegetation indices, but non-linear relationships have been proposed too. However, according to the radiative transfer theory, the nature of such relationships depends on the crop architecture and the definition of the adopted vegetation index, but the linear assumption can be adopted as first. Such studies, mainly investigated the possibility to use high resolution satellite data, such as Quickbird, Ikonos, TM, which are not suitable for operational purposes since in spite of the high spatial sampling they have an inadequate revisiting time over a given area. To obtain adequate temporal sampling, some authors proposed the use of a virtual constellation made by all currently available high-resolution satellites (e.g., DEMETER project). However the joint use of data from different satellites requires a carefully inter-satellite cross-calibration and co-registration. In order to avoid such problems and to generate spatially distributed values of Kc capturing field-specific crop development, the employment of vegetation indices derived from medium resolution MODIS data having a higher temporal sampling has been investigated. The spatial and temporal correlation between NDVI (Normalized Difference Vegetation Index) and crop coefficients for different herbaceous and arboreal cultivations has been investigated to define their relationships. Through this approach site-specific crop coefficients were derived taking into account the effective ground coverage and status. The analysis has been applied on the 2005-2008 time series for the Basilicata region, Southern Italy.

Investigating change detection of archaeological sites by multiscale and multitemporal satellite imagery

NASA Astrophysics Data System (ADS)

Lasaponara, R.; Lanorte, A.; Coluzzi, R.; Masini, N.

2009-04-01

The systematic monitoring of cultural and natural heritage is a basic step for its conservation. Monitoring strategies should constitute an integral component of policies relating to land use, development, and planning. To this aim remote sensing technologies can be used profitably. This paper deals with the use of multitemporal, multisensors, and multiscale satellite data for assessing and monitoring changes affecting cultural landscapes and archaeological sites. The discussion is focused on some significant test cases selected in Peru (South America) and Southern Italy . Artifacts, unearthed sites, and marks of buried remains have been investigated by using multitemporal aerial and satellite data, such as Quickbird, ASTER, Landsat MSS and TM.

Multi-Feature Based Information Extraction of Urban Green Space Along Road

NASA Astrophysics Data System (ADS)

Zhao, H. H.; Guan, H. Y.

2018-04-01

Green space along road of QuickBird image was studied in this paper based on multi-feature-marks in frequency domain. The magnitude spectrum of green along road was analysed, and the recognition marks of the tonal feature, contour feature and the road were built up by the distribution of frequency channels. Gabor filters in frequency domain were used to detect the features based on the recognition marks built up. The detected features were combined as the multi-feature-marks, and watershed based image segmentation were conducted to complete the extraction of green space along roads. The segmentation results were evaluated by Fmeasure with P = 0.7605, R = 0.7639, F = 0.7622.

Improvements in agricultural water decision support using remote sensing

NASA Astrophysics Data System (ADS)

Marshall, M. T.

2012-12-01

Population driven water scarcity, aggravated by climate-driven evaporative demand in dry regions of the world, has the potential of transforming ecological and social systems to the point of armed conflict. Water shortages will be most severe in agricultural areas, as the priority shifts to urban and industrial use. In order to design, evaluate, and monitor appropriate mitigation strategies, predictive models must be developed that quantify exposure to water shortage. Remote sensing data has been used for more than three decades now to parametrize these models, because field measurements are costly and difficult in remote regions of the world. In the past decade, decision-makers for the first time can make accurate and near real-time evaluations of field conditions with the advent of hyper- spatial and spectral and coarse resolution continuous remote sensing data. Here, we summarize two projects representing diverse applications of remote sensing to improve agricultural water decision support. The first project employs MODIS (coarse resolution continuous data) to drive an evapotranspiration index, which is combined with the Standardized Precipitation Index driven by meteorological satellite data to improve famine early warning in Africa. The combined index is evaluated using district-level crop yield data from Kenya and Malawi and national-level crop yield data from the United Nations Food and Agriculture Organization. The second project utilizes hyper- spatial (GeoEye 1, Quickbird, IKONOS, and RapidEye) and spectral (Hyperion/ALI), as well as multi-spectral (Landsat ETM+, SPOT, and MODIS) data to develop biomass estimates for key crops (alfalfa, corn, cotton, and rice) in the Central Valley of California. Crop biomass is an important indicator of crop water productivity. The remote sensing data is combined using various data fusion techniques and evaluated with field data collected in the summer of 2012. We conclude with a brief discussion on implementation of these tools into two new decision support systems: FEWSNET Early Warning Explorer (http://earlywarning.usgs.gov/fews/ewxindex.php) and the NASA Terrestrial Observation and Prediction System (http://ecocast.arc.nasa.gov/) for the first and second project respectively.

The effects of war on land-use/land-cover change: An analysis of Landsat imagery for northeast Bosnia

NASA Astrophysics Data System (ADS)

Witmer, Frank D. W.

The use of satellite technology by military planners has a relatively long history as a tool of warfare, but little research has used satellite technology to study the effects of war. This research addresses this gap by applying satellite remote sensing imagery to study the effects of war on land-use/land-cover change in northeast Bosnia. The war in Bosnia, 1992-1995, resulted in over 100,000 deaths, many more wounded, and the mass displacement of nearly half the population of 4.2 million. When combined with the destruction of much of the transportation infrastructure and housing stock, widespread mine placement, and loss of agricultural machinery, the impacts to both the people and land were dramatic. Though the most severe war impacts are visible at local scales (e.g. destroyed buildings), this study focuses on impacts to agricultural land, a larger scale visible to satellite sensors. Multispectral Landsat Thematic Mapper (TM) data (30m pixels) from before and during the war in addition to recent imagery from 2004/05 were used to detect abandoned agricultural land. The satellite images were co-registered to enable a perpixel analysis of changes based on the statistical properties of the pixels using multiple change detection methods. Ground reference data were collected in May of 2006 at survey sites selected using a stratified random sampling approach based on the derived map of abandoned agricultural land. Fine resolution (60cm) Quickbird imagery was also used to verify the accuracy of the classification. The remote sensing analysis results were then used to test two hypotheses related to war outcomes: (a) land abandonment is due to wartime minefields and (b) land abandonment is greater in pre-war Croat areas and areas where ethnic cleansing was heaviest. The effects of minefields on land abandonment was first tested in a geographic information system (GIS), and then by using multiple regression models that account for spatial autocorrelation among observations. The spatial regression analysis was conducted at the opstina (county) areal unit and used minefield locations, refugee returns and population change data as predictors of abandoned agricultural land. Results from these analyses show that a supervised classification of the Landsat TM data identified abandoned agricultural land with an overall accuracy of 82.5%. The GIS and spatial regression analysis of how war affects agricultural land showed that the presence of minefields and population declines are both associated with abandoned agricultural land. This research holds significance for both the remote sensing and civil war research communities. The use of freely available Quickbird imagery both as training data for the supervised classifier and as supplementary ground reference data suggest these methods are applicable to other civil wars (e.g. Darfur region of Sudan and the Horn of Africa) that may still be too dangerous for researchers to conduct field work in. By extending these methods to other war zones, comparisons of similarities and differences between such studies can then be made to draw broader conclusions of war impacts to land use and land cover.

Simultaneous glacier surface elevation and flow velocity mapping from cross-track pushbroom satellite Imagery

NASA Astrophysics Data System (ADS)

Noh, M. J.; Howat, I. M.

2017-12-01

Glaciers and ice sheets are changing rapidly. Digital Elevation Models (DEMs) and Velocity Maps (VMs) obtained from repeat satellite imagery provide critical measurements of changes in glacier dynamics and mass balance over large, remote areas. DEMs created from stereopairs obtained during the same satellite pass through sensor re-pointing (i.e. "in-track stereo") have been most commonly used. In-track stereo has the advantage of minimizing the time separation and, thus, surface motion between image acquisitions, so that the ice surface can be assumed motionless in when collocating pixels between image pairs. Since the DEM extraction process assumes that all motion between collocated pixels is due to parallax or sensor model error, significant ice motion results in DEM quality loss or failure. In-track stereo, however, puts a greater demand on satellite tasking resources and, therefore, is much less abundant than single-scan imagery. Thus, if ice surface motion can be mitigated, the ability to extract surface elevation measurements from pairs of repeat single-scan "cross-track" imagery would greatly increase the extent and temporal resolution of ice surface change. Additionally, the ice motion measured by the DEM extraction process would itself provide a useful velocity measurement. We develop a novel algorithm for generating high-quality DEMs and VMs from cross-track image pairs without any prior information using the Surface Extraction from TIN-based Searchspace Minimization (SETSM) algorithm and its sensor model bias correction capabilities. Using a test suite of repeat, single-scan imagery from WorldView and QuickBird sensors collected over fast-moving outlet glaciers, we develop a method by which RPC biases between images are first calculated and removed over ice-free surfaces. Subpixel displacements over the ice are then constrained and used to correct the parallax estimate. Initial tests yield DEM results with the same quality as in-track stereo for cases where snowfall has not occurred between the two images and when the images have similar ground sample distances. The resulting velocity map also closely matches independent measurements.

Nonlinear bias compensation of ZiYuan-3 satellite imagery with cubic splines

NASA Astrophysics Data System (ADS)

Cao, Jinshan; Fu, Jianhong; Yuan, Xiuxiao; Gong, Jianya

2017-11-01

Like many high-resolution satellites such as the ALOS, MOMS-2P, QuickBird, and ZiYuan1-02C satellites, the ZiYuan-3 satellite suffers from different levels of attitude oscillations. As a result of such oscillations, the rational polynomial coefficients (RPCs) obtained using a terrain-independent scenario often have nonlinear biases. In the sensor orientation of ZiYuan-3 imagery based on a rational function model (RFM), these nonlinear biases cannot be effectively compensated by an affine transformation. The sensor orientation accuracy is thereby worse than expected. In order to eliminate the influence of attitude oscillations on the RFM-based sensor orientation, a feasible nonlinear bias compensation approach for ZiYuan-3 imagery with cubic splines is proposed. In this approach, no actual ground control points (GCPs) are required to determine the cubic splines. First, the RPCs are calculated using a three-dimensional virtual control grid generated based on a physical sensor model. Second, one cubic spline is used to model the residual errors of the virtual control points in the row direction and another cubic spline is used to model the residual errors in the column direction. Then, the estimated cubic splines are used to compensate the nonlinear biases in the RPCs. Finally, the affine transformation parameters are used to compensate the residual biases in the RPCs. Three ZiYuan-3 images were tested. The experimental results showed that before the nonlinear bias compensation, the residual errors of the independent check points were nonlinearly biased. Even if the number of GCPs used to determine the affine transformation parameters was increased from 4 to 16, these nonlinear biases could not be effectively compensated. After the nonlinear bias compensation with the estimated cubic splines, the influence of the attitude oscillations could be eliminated. The RFM-based sensor orientation accuracies of the three ZiYuan-3 images reached 0.981 pixels, 0.890 pixels, and 1.093 pixels, which were respectively 42.1%, 48.3%, and 54.8% better than those achieved before the nonlinear bias compensation.

The Joint Agency Commercial Imagery Evaluation Team and Product Characterization Approach

NASA Technical Reports Server (NTRS)

Zanoni, Vicki; Pagnutti, Mary; Ryan, Robert E.; Snyder, Greg; Lehman, William; Roylance, Spencer

2003-01-01

The Joint Agency Commercial Imagery Evaluation (JACIE) team is a collaborative interagency group focused on the characterization of commercial remote sensing data products. The team members - the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA), and the U.S. Geological Survey (USGS) - each have a vested interest in the purchase and use of commercial imagery to support government research and operational applications. For both research and applications, commercial products must be well characterized for precision, accuracy, and repeatability. Since commercial systems are built and operated with no government insight or oversight, the JACIE team provides an independent product characterization of delivered image and image-derived end products. End product characterization differs from the systems calibration approach that is typically used with government systems, where detailed system design information is available. The product characterization approach addresses three primary areas of product performance: geopositional accuracy, image quality, and radiometric accuracy. The JACIE team utilizes well-characterized test sites to support characterization activities. To characterize geopositional accuracy, the team utilizes sites containing several "photo-identifiable" targets and compares their precisely known locations with those defined by the commercial image product. In the area of image quality, spatial response is characterized using edge targets and pulse targets to measure edge response and to estimate image modulation transfer function. Additionally, imagery is also characterized using the National Imagery Interpretability Rating Scale, a means of quantifying the ability to identify certain targets (e.g., rail-cars, airplanes) within an image product. Radiometric accuracy is characterized using reflectance-based vicarious calibration methods at several uniform sites. Each JACIE agency performs an aspect of product characterization based on its area of expertise, thus minimizing duplication of effort. The JACIE team collaborated to perform comprehensive characterization of products from Space Imaging Inc.'s IKONOS satellite and from DigitalGlobe's QuickBird satellite and is currently characterizing products from OrbImage s OrbView-3. JACIE assessments have resulted in several improvements to commercial image product quality and have enhanced working relationships between government and industry. Assessment results are presented at an annual JACIE High Spatial Resolution Commercial Imagery Workshop.

Research of BRDF effects on remote sensing imagery

NASA Astrophysics Data System (ADS)

Nina, Peng; Kun, Wang; Tao, Li; Yang, Pan

2011-08-01

The gray distribution and contrast of the optical satellite remote sensing imagery in the same kind of ground surface acquired by sensor is quite different, it depends not only on the satellite's observation and the sun incidence orientation but also the structural and optical properties of the surface. Therefore, the objectives of this research are to analyze the different BRDF characters of soil, vegetation, water and urban surface and also their BRDF effects on the quality of satellite image through 6S radiative transfer model. Furthermore, the causation of CCD blooming and spilling by ground reflectance is discussed by using QUICKBIRD image data and the corresponding ground image data. The general conclusion of BRDF effects on remote sensing imagery is proposed.

Quasi-Likelihood Techniques in a Logistic Regression Equation for Identifying Simulium damnosum s.l. Larval Habitats Intra-cluster Covariates in Togo.

PubMed

Jacob, Benjamin G; Novak, Robert J; Toe, Laurent; Sanfo, Moussa S; Afriyie, Abena N; Ibrahim, Mohammed A; Griffith, Daniel A; Unnasch, Thomas R

2012-01-01

The standard methods for regression analyses of clustered riverine larval habitat data of Simulium damnosum s.l. a major black-fly vector of Onchoceriasis, postulate models relating observational ecological-sampled parameter estimators to prolific habitats without accounting for residual intra-cluster error correlation effects. Generally, this correlation comes from two sources: (1) the design of the random effects and their assumed covariance from the multiple levels within the regression model; and, (2) the correlation structure of the residuals. Unfortunately, inconspicuous errors in residual intra-cluster correlation estimates can overstate precision in forecasted S.damnosum s.l. riverine larval habitat explanatory attributes regardless how they are treated (e.g., independent, autoregressive, Toeplitz, etc). In this research, the geographical locations for multiple riverine-based S. damnosum s.l. larval ecosystem habitats sampled from 2 pre-established epidemiological sites in Togo were identified and recorded from July 2009 to June 2010. Initially the data was aggregated into proc genmod. An agglomerative hierarchical residual cluster-based analysis was then performed. The sampled clustered study site data was then analyzed for statistical correlations using Monthly Biting Rates (MBR). Euclidean distance measurements and terrain-related geomorphological statistics were then generated in ArcGIS. A digital overlay was then performed also in ArcGIS using the georeferenced ground coordinates of high and low density clusters stratified by Annual Biting Rates (ABR). This data was overlain onto multitemporal sub-meter pixel resolution satellite data (i.e., QuickBird 0.61m wavbands ). Orthogonal spatial filter eigenvectors were then generated in SAS/GIS. Univariate and non-linear regression-based models (i.e., Logistic, Poisson and Negative Binomial) were also employed to determine probability distributions and to identify statistically significant parameter estimators from the sampled data. Thereafter, Durbin-Watson test statistics were used to test the null hypothesis that the regression residuals were not autocorrelated against the alternative that the residuals followed an autoregressive process in AUTOREG. Bayesian uncertainty matrices were also constructed employing normal priors for each of the sampled estimators in PROC MCMC. The residuals revealed both spatially structured and unstructured error effects in the high and low ABR-stratified clusters. The analyses also revealed that the estimators, levels of turbidity and presence of rocks were statistically significant for the high-ABR-stratified clusters, while the estimators distance between habitats and floating vegetation were important for the low-ABR-stratified cluster. Varying and constant coefficient regression models, ABR- stratified GIS-generated clusters, sub-meter resolution satellite imagery, a robust residual intra-cluster diagnostic test, MBR-based histograms, eigendecomposition spatial filter algorithms and Bayesian matrices can enable accurate autoregressive estimation of latent uncertainity affects and other residual error probabilities (i.e., heteroskedasticity) for testing correlations between georeferenced S. damnosum s.l. riverine larval habitat estimators. The asymptotic distribution of the resulting residual adjusted intra-cluster predictor error autocovariate coefficients can thereafter be established while estimates of the asymptotic variance can lead to the construction of approximate confidence intervals for accurately targeting productive S. damnosum s.l habitats based on spatiotemporal field-sampled count data.

Land cover mapping at sub-pixel scales

NASA Astrophysics Data System (ADS)

Makido, Yasuyo Kato

One of the biggest drawbacks of land cover mapping from remotely sensed images relates to spatial resolution, which determines the level of spatial details depicted in an image. Fine spatial resolution images from satellite sensors such as IKONOS and QuickBird are now available. However, these images are not suitable for large-area studies, since a single image is very small and therefore it is costly for large area studies. Much research has focused on attempting to extract land cover types at sub-pixel scale, and little research has been conducted concerning the spatial allocation of land cover types within a pixel. This study is devoted to the development of new algorithms for predicting land cover distribution using remote sensory imagery at sub-pixel level. The "pixel-swapping" optimization algorithm, which was proposed by Atkinson for predicting sub-pixel land cover distribution, is investigated in this study. Two limitations of this method, the arbitrary spatial range value and the arbitrary exponential model of spatial autocorrelation, are assessed. Various weighting functions, as alternatives to the exponential model, are evaluated in order to derive the optimum weighting function. Two different simulation models were employed to develop spatially autocorrelated binary class maps. In all tested models, Gaussian, Exponential, and IDW, the pixel swapping method improved classification accuracy compared with the initial random allocation of sub-pixels. However the results suggested that equal weight could be used to increase accuracy and sub-pixel spatial autocorrelation instead of using these more complex models of spatial structure. New algorithms for modeling the spatial distribution of multiple land cover classes at sub-pixel scales are developed and evaluated. Three methods are examined: sequential categorical swapping, simultaneous categorical swapping, and simulated annealing. These three methods are applied to classified Landsat ETM+ data that has been resampled to 210 meters. The result suggested that the simultaneous method can be considered as the optimum method in terms of accuracy performance and computation time. The case study employs remote sensing imagery at the following sites: tropical forests in Brazil and temperate multiple land mosaic in East China. Sub-areas for both sites are used to examine how the characteristics of the landscape affect the ability of the optimum technique. Three types of measurement: Moran's I, mean patch size (MPS), and patch size standard deviation (STDEV), are used to characterize the landscape. All results suggested that this technique could increase the classification accuracy more than traditional hard classification. The methods developed in this study can benefit researchers who employ coarse remote sensing imagery but are interested in detailed landscape information. In many cases, the satellite sensor that provides large spatial coverage has insufficient spatial detail to identify landscape patterns. Application of the super-resolution technique described in this dissertation could potentially solve this problem by providing detailed land cover predictions from the coarse resolution satellite sensor imagery.

NASA/SDSU Geopositional Characterization

NASA Technical Reports Server (NTRS)

Helder, Dennis; Ross, Kenton; Helder, Dennis; Ross, Kentron

2006-01-01

The geolocational accuracy of products from the IKONOS, QuickBird, and OrbView-3 sensors was evaluated using two test sites: one developed in and around Brookings, SD, and one near Stennis Space Center, MS. Both of these relatively flat sites host over 100 ground control points surveyed to an accuracy of approximately 5 cm. They provide robust locations to test the basic geolocational accuracy of a variety of spaceborne and aircraft sensor systems. Imagery of both test sites was acquired by these three sensors in 2004 and in 2005; several products from each sensor, ranging from basic datasets through orthorectified imagery, were analyzed at Stennis Space Center and at South Dakota State University. While direct comparisons between sensors and products are difficult because of differing processing schemes, results indicate that these products tend to display stated levels of accuracy.

Observing Muostakh Island disappear: erosion of a ground-ice-rich coast in response to summer warming and sea ice reduction on the East Siberian shelf

NASA Astrophysics Data System (ADS)

Günther, F.; Overduin, P. P.; Baranskaya, A.; Opel, T.; Grigoriev, M. N.

2013-08-01

Observations of coastline retreat using contemporary very high resolution satellite and historical aerial imagery were compared to measurements of open water fractions and summer air temperatures. We analyzed seasonal and interannual variations of thawing-induced cliff top retreat (thermo-denudation) and marine abrasion (thermo-abrasion) on Muostakh Island in the southern central Laptev Sea. The island is composed of ground-ice-rich permafrost deposits of Ice Complex type that render it particularly susceptible to erosion along the coast, resulting in land loss. Based on topographic reference measurements during field campaigns, we generated digital elevation models using stereophotogrammetry, in order to block adjust and ortho-rectify aerial photographies from 1951 and GeoEye, QuickBird, WorldView-1, and WorldView-2 imagery from 2010 to 2012 for change detection. Coastline retreat for erosive segments ranged from -13 to -585 m and was -109 ± 81 m (-1.8 ± 1.3 m a-1) on average during the historical period. Current seasonal dynamics of cliff top retreat revealed rapid thermo-denudation rates of -10.2 ± 4.5 m a-1 in mid summer and -4.1 ± 2.0 m a-1 on average during the 2010-2012 observation period. Using sea ice concentration data from the Special Sensor Microwave Imager (SSM/I) and air temperature time series from Tiksi, we calculated seasonal duration available for thermo-abrasion, expressed as open water days, and for thermo-denudation, based on thawing degree days. Geomorphometric analysis revealed that total ground ice content on Muostakh is made up of equal amounts of intrasedimentary and macro ground ice, while its vertical hourglass distribution provides favorable local preconditions for subsidence and the acceleration of coastal thermo-erosion under intensifying environmental forcings. Our results showed a~close relationship between mean summer air temperature and coastal thermo-erosion rates, in agreement with observations made for various permafrost coastlines different from East Siberian Ice Complex coasts elsewhere in the Arctic. Seasonality and recent interannual variations of coastline retreat rates suggest that the combination of macro ground ice distribution in the ground and changes in enviromental forcing generate a cyclicity in coastal thermo-erosion, that is currently increasing in frequency.

Characterizing human-environment interactions in the Galapagos Islands: A case study of land use/land cover dynamics in Isabela Island

NASA Astrophysics Data System (ADS)

McCleary, Amy L.

This dissertation examines contemporary land use and land cover (LULC) change in the communities and protected areas of Isabela Island to provide insights into human-environment interactions in the Galapagos Islands of Ecuador. The growing human presence in Galapagos over the last four decades has been accompanied by significant changes in LULC on inhabited islands in the archipelago. Local stakeholders and decision-makers have recently called for a more integrative approach to understanding interactions between people and the environment in the archipelago. This study is guided by two complementary bodies of work situated within the human-environment tradition of Geography---land change science and landscape ecology. First, support Vector Machine (SVM) and Object Based Image Analysis (OBIA) classifiers are evaluated for mapping LULC from high spatial resolution satellite images. The results show that thematic LULC classifications produced by OBIA are more accurate overall than those generated by SVM. However, important tradeoffs exist between improvements in classification accuracy and processing requirements. The composition and spatial configuration of LULC change are then mapped and quantified from a time series of QuickBird and WorldView-2 satellite images from 2003 to 2010. The pattern metric and change detection analyses reveal that land use change is extensive within the communities due to the expansion and consolidation of built-up areas, and fragmentation of and declines in agriculture. The Galapagos National Park is primarily transformed by exotic plant invasion, forests expansion, and shrinking coastal lagoons. Patterns of agricultural land abandonment, plant invasion, and forest expansion over the same period are described from pattern metric and overlay analyses. Potential drivers of these LULC transitions are identified from logistic regression models, descriptive statistics of agricultural surveys and population censuses, and interviews with landowners. The results reveal that agricultural abandonment is widespread throughout Isabela, and many abandoned fields are invaded by introduced plants, such as guava. Biophysical and geographic factors, such as topography and distance to roads, do not significantly explain patterns of agricultural land abandonment or associated land cover transitions at the pixel level. However, rural-urban migration, declines in the profitability of agriculture, and small labor pools appear to influence agricultural abandonment.

Urban structure analysis of mega city Mexico City using multisensoral remote sensing data

NASA Astrophysics Data System (ADS)

Taubenböck, H.; Esch, T.; Wurm, M.; Thiel, M.; Ullmann, T.; Roth, A.; Schmidt, M.; Mehl, H.; Dech, S.

2008-10-01

Mega city Mexico City is ranked the third largest urban agglomeration to date around the globe. The large extension as well as dynamic urban transformation and sprawl processes lead to a lack of up-to-date and area-wide data and information to measure, monitor, and understand the urban situation. This paper focuses on the capabilities of multisensoral remotely sensed data to provide a broad range of products derived from one scientific field - remote sensing - to support urban managing and planning. Therefore optical data sets from the Landsat and Quickbird sensors as well as radar data from the Shuttle Radar Topography Mission (SRTM) and the TerraSAR-X sensor are utilised. Using the multi-sensoral data sets the analysis are scale-dependent. On the one hand change detection on city level utilising the derived urban footprints enables to monitor and to assess spatiotemporal urban transformation, areal dimension of urban sprawl, its direction, and the built-up density distribution over time. On the other hand, structural characteristics of an urban landscape - the alignment and types of buildings, streets and open spaces - provide insight in the very detailed physical pattern of urban morphology on higher scale. The results show high accuracies of the derived multi-scale products. The multi-scale analysis allows quantifying urban processes and thus leading to an assessment and interpretation of urban trends.

Archaeological prospection of cultural heritage in the Nasca region, Peru, by coupling ENVISAT ASAR 2003-2007 and optical-VHR time series

NASA Astrophysics Data System (ADS)

Tapete, Deodato; Cigna, Francesca; Masini, Nicola; Lasaponara, Rosa

2013-04-01

We present the radar-interpretation of a 4year-long stack of ENVISAT ASAR imagery, integrated and cross-validated with optical-Very High Resolution (VHR) data from QuickBird2, GeoEye and WorldView-1/2, and carried out over the cultural and natural heritage of the Nasca region in Southern Peru. This research is performed thanks to the provision of free-access archive SAR data from the European Space Agency (ESA) through the Cat-1 project 11073, and is supporting the activities of the Italian mission of heritage Conservation and Archaeogeophysics (ITACA), which directly involve researchers from the Institute for Archaeological and Monumental Heritage (IBAM) and the Institute of Methodologies for Environmental Analysis (IMAA), National Research Council (CNR) of Italy. The whole ENVISAT ASAR imagery archive, consisting of 8 ASAR IS2 scenes acquired in descending mode between 04/02/2003 and 15/11/2005 and 5 images in ascending mode between 24/07/2005 and 11/11/2007, was processed by exploiting and analyzing SAR amplitude information and change detection to reconstruct the temporal evolution of radar signatures and related backscattering coefficient (σ0) of the targets on the ground in the monitoring period 2003-2007. The selection of a SAR amplitude-based change detection method was made to explore its actual potentials for archaeological prospection and monitoring purposes, complementarily to approaches of interferometric coherence used by other scholars over the same region of investigation. The novel contribution to heritage studies over Nasca includes remote sensing insights into the renowned UNESCO-WHL Nasca geoglyphs and archaeological mounds of the adobe Ceremonial Centre of Cahuachi, as well as the ancient puquios within the Rio Grande drainage basin. The latter are prehispanic underground aqueducts, and nowadays represent not only important cultural features to preserve, but also a potential driver to revitalize waterways and oases in such a dry region. Advantages and shortcomings of the SAR signature-based recognition of archaeological features on the ground are discussed through the test sites of the geoglyphs groups belonging to the Nasca Lines and the puquios along Rio Taruga, with specific reference to the medium spatial resolution offered by ENVISAT ASAR scenes and the supporting comparison with the VHR-optical imagery. Amplitude change detection demonstrates high suitability to highlight temporal differences from which we can infer: (i) modifications due to human activity (e.g., looting in Cahuachi); (ii) surface alteration of the exposed archaeological structures (i.e. site conservation issues); (iii) variations of soil water content and vegetation in agricultural areas where puquios are built; and (iv) land surface processes which can trigger natural hazards potentially damaging cultural and natural heritage, as also demonstrated by past and recent mudslides in Cahuachi and the Andean foot-hills. References Lasaponara R., Masini N. 2012. Investigating satellite Landsat TM and ASTER multitemporal data set to discover ancient canals and acqueduct systems, in Lecture Notes in Computer Science, Vol. 7335, Issue 3, 2012, Pages 497-511, 12th International Conference on Computational Science and Its Applications, ICCSA 2012, doi: 10.1007/978-3-642-31137-6_38. Masini N., Lasaponara R., Rizzo E., Orefici G. 2012. Integrated Remote Sensing Approach in Cahuachi (Peru): Studies and Results of the ITACA Mission (2007-2010), In: Lasaponara R., Masini N. (Eds) 2012, Satellite Remote Sensing: a new tool for Archaeology, Springer, Verlag Berlin Heidelberg, ISBN 978-90-481-8800-0, doi: 10.1007/978-90-481-8801-7_14; pp. 307-344.

High resolution time interval meter

DOEpatents

Martin, A.D.

1986-05-09

Method and apparatus are provided for measuring the time interval between two events to a higher resolution than reliability available from conventional circuits and component. An internal clock pulse is provided at a frequency compatible with conventional component operating frequencies for reliable operation. Lumped constant delay circuits are provided for generating outputs at delay intervals corresponding to the desired high resolution. An initiation START pulse is input to generate first high resolution data. A termination STOP pulse is input to generate second high resolution data. Internal counters count at the low frequency internal clock pulse rate between the START and STOP pulses. The first and second high resolution data are logically combined to directly provide high resolution data to one counter and correct the count in the low resolution counter to obtain a high resolution time interval measurement.

Comparison of Two Grid Refinement Approaches for High Resolution Regional Climate Modeling: MPAS vs WRF

NASA Astrophysics Data System (ADS)

Leung, L.; Hagos, S. M.; Rauscher, S.; Ringler, T.

2012-12-01

This study compares two grid refinement approaches using global variable resolution model and nesting for high-resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales (MPAS), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context with a focus on the spatial and temporal characteristics of tropical precipitation simulated by the models using the same physics package from the Community Atmosphere Model (CAM4). For MPAS, simulations have been performed with a quasi-uniform resolution global domain at coarse (1 degree) and high (0.25 degree) resolution, and a variable resolution domain with a high-resolution region at 0.25 degree configured inside a coarse resolution global domain at 1 degree resolution. Similarly, WRF has been configured to run on a coarse (1 degree) and high (0.25 degree) resolution tropical channel domain as well as a nested domain with a high-resolution region at 0.25 degree nested two-way inside the coarse resolution (1 degree) tropical channel. The variable resolution or nested simulations are compared against the high-resolution simulations that serve as virtual reality. Both MPAS and WRF simulate 20-day Kelvin waves propagating through the high-resolution domains fairly unaffected by the change in resolution. In addition, both models respond to increased resolution with enhanced precipitation. Grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. However, there are important differences between the anomalous patterns in MPAS and WRF due to differences in the grid refinement approaches and sensitivity of model physics to grid resolution. This study highlights the need for "scale aware" parameterizations in variable resolution and nested regional models.

Evaluating the condition of a mangrove forest of the Mexican Pacific based on an estimated leaf area index mapping approach.

PubMed

Kovacs, J M; King, J M L; Flores de Santiago, F; Flores-Verdugo, F

2009-10-01

Given the alarming global rates of mangrove forest loss it is important that resource managers have access to updated information regarding both the extent and condition of their mangrove forests. Mexican mangroves in particular have been identified as experiencing an exceptional high annual rate of loss. However, conflicting studies, using remote sensing techniques, of the current state of many of these forests may be hindering all efforts to conserve and manage what remains. Focusing on one such system, the Teacapán-Agua Brava-Las Haciendas estuarine-mangrove complex of the Mexican Pacific, an attempt was made to develop a rapid method of mapping the current condition of the mangroves based on estimated LAI. Specifically, using an AccuPAR LP-80 Ceptometer, 300 indirect in situ LAI measurements were taken at various sites within the black mangrove (Avicennia germinans) dominated forests of the northern section of this system. From this sample, 225 measurements were then used to develop linear regression models based on their relationship with corresponding values derived from QuickBird very high resolution optical satellite data. Specifically, regression analyses of the in situ LAI with both the normalized difference vegetation index (NDVI) and the simple ration (SR) vegetation index revealed significant positive relationships [LAI versus NDVI (R (2) = 0.63); LAI versus SR (R (2) = 0.68)]. Moreover, using the remaining sample, further examination of standard errors and of an F test of the residual variances indicated little difference between the two models. Based on the NDVI model, a map of estimated mangrove LAI was then created. Excluding the dead mangrove areas (i.e. LAI = 0), which represented 40% of the total 30.4 km(2) of mangrove area identified in the scene, a mean estimated LAI value of 2.71 was recorded. By grouping the healthy fringe mangrove with the healthy riverine mangrove and by grouping the dwarf mangrove together with the poor condition mangrove, mean estimated LAI values of 4.66 and 2.39 were calculated, respectively. Given that the former healthy group only represents 8% of the total mangrove area examined, it is concluded that this mangrove system, considered one of the most important of the Pacific coast of the Americas, is currently experiencing a considerable state of degradation. Furthermore, based on the results of this investigation it is suggested that this approach could provide resource managers and scientists alike with a very rapid and effective method for monitoring the state of remaining mangrove forests of the Mexican Pacific and, possibly, other areas of the tropics.

A method for generating high resolution satellite image time series

NASA Astrophysics Data System (ADS)

Guo, Tao

2014-10-01

There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation, environment and etc. applications.

Surface Deformation During a Magmatic Intrusion: the Example of the Dabba'hu Rift Crisis of 2005-2006 (Afar, Ethiopia)

NASA Astrophysics Data System (ADS)

Grandin, R.; Socquet, A.; Binet, R.; Jacques, E.; Klinger, Y.; de Chabalier, J.; King, G.; Tait, S.; Tapponnier, P.; Delorme, A.; Elissalde, C.

2007-12-01

In September 2005, a magmato-tectonic episode initiated in Western Afar (Ethiopia) when a swarm of moderate magnitude earthquakes (M<5.6) was recorded for several days. A small eruption also occurred on the eastern flank of Dabba'hu, a large silicic volcano located at the northern extremity of the Dabba'hu rift segment. The terrain is exceptionally favorable for InSAR imagery and surface fault mapping, making this event a rare opportunity to study how surface faulting and dike injection were mechanically coupled during the rifting event. Based on the combination of InSAR images shot on both ascending and descending tracks, and the correlation of SAR amplitude images, we deduced the vertical motions inside the rift during the main intrusion event. Together with the correlation of SPOT optical images, the horizontal component of opening can be retrieved. We provide evidence for an average of 6 m of opening across the 40 km northern Dabba'hu segment, during the September crisis. The inner floor of the rift subsided by ~ 2m, while the shoulders were uplifted by ~ 2m. A deficit of opening was observed in the southern segment during the main crisis. However, a second intrusive event occurred in mid-2006, leading to the further opening of this 20 km segment by an additional ~ 2m. A series of interferograms covering the post-crises periods show that significant motion also occurred between the crises and after the second crisis. Using a comparison between pre-crisis aerial photographs and post-crisis high-resolution Quickbird images, combined with SAR coherence images, we are able to map the structures that were reactivated during the crisis, and show extensive evidence of newly exposed fractures in recent basalts. The motion on a large number of en echelon faults and fissures could be observed with much greater detail than during the main rifting event. Using a DEM of the area, generated using SPOT images, the relation between faulting and rift morphology is addressed. Concentric subsidence and/or uplift occurred at various stages of the crisis on distinct volcanic edifices, pointing to a complex scenario for the possible connection between shallow and deep magmatic chambers. The estimated extension rate of 15 mm/year across the plate boundary [Vigny et al., 2006] yields a recurrence time of the order of 500 years for events of this magnitude. Surprisingly, despite the large volume of magma intruded during the September 2005 event (~ 15 km2), no basalt flows were observed.

The potential for remote sensing and hydrologic modelling to assess the spatio-temporal dynamics of ponds in the Ferlo Region (Senegal)

NASA Astrophysics Data System (ADS)

Soti, V.; Puech, C.; Lo Seen, D.; Bertran, A.; Vignolles, C.; Mondet, B.; Dessay, N.; Tran, A.

2010-08-01

In the Ferlo Region in Senegal, livestock depend on temporary ponds for water but are exposed to the Rift Valley Fever (RVF), a disease transmitted to herds by mosquitoes which develop in these ponds. Mosquito abundance is related to the emptying and filling phases of the ponds, and in order to study the epidemiology of RVF, pond modelling is required. In the context of a data scarce region, a simple hydrologic model which makes use of remote sensing data was developed to simulate pond water dynamics from daily rainfall. Two sets of ponds were considered: those located in the main stream of the Ferlo Valley whose hydrological dynamics are essentially due to runoff, and the ponds located outside, which are smaller and whose filling mechanisms are mainly due to direct rainfall. Separate calibrations and validations were made for each set of ponds. Calibration was performed from daily field data (rainfall, water level) collected during the 2001 and 2002 rainy seasons and from three different sources of remote sensing data: 1) very high spatial resolution optical satellite images to access pond location and surface area at given dates, 2) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM) data to estimate pond catchment area and 3) Tropical Rainfall Measuring Mission (TRMM) data for rainfall estimates. The model was applied to all ponds of the study area, the results were validated and a sensitivity analysis was performed. Water height simulations using gauge rainfall as input were compared to water level measurements from four ponds and Nash coefficients >0.7 were obtained. Comparison with simulations using TRMM rainfall data gave mixed results, with poor water height simulations for the year 2001 and good estimations for the year 2002. A pond map derived from a Quickbird satellite image was used to assess model accuracy for simulating pond water areas for all the ponds of the study area. The validation showed that modelled water areas were mostly underestimated but significantly correlated, particularly for the larger ponds. The results of the sensitivity analysis showed that parameters relative to pond shape and catchment area estimation have less effects on model simulation than parameters relative to soil properties (rainfall threshold causing runoff in dry soils and the coefficient expressing soil moisture decrease with time) or the water loss coefficient. Overall, our results demonstrate the possibility of using a simple hydrologic model with remote sensing data to track pond water heights and water areas in a homogeneous arid area.

Combining Landform Thematic Layer and Object-Oriented Image Analysis to Map the Surface Features of Mountainous Flood Plain Areas

NASA Astrophysics Data System (ADS)

Chuang, H.-K.; Lin, M.-L.; Huang, W.-C.

2012-04-01

The Typhoon Morakot on August 2009 brought more than 2,000 mm of cumulative rainfall in southern Taiwan, the extreme rainfall event caused serious damage to the Kaoping River basin. The losses were mostly blamed on the landslides along sides of the river, and shifting of the watercourse even led to the failure of roads and bridges, as well as flooding and levees damage happened around the villages on flood bank and terraces. Alluvial fans resulted from debris flow of stream feeders blocked the main watercourse and debris dam was even formed and collapsed. These disasters have highlighted the importance of identification and map the watercourse alteration, surface features of flood plain area and artificial structures soon after the catastrophic typhoon event for natural hazard mitigation. Interpretation of remote sensing images is an efficient approach to acquire spatial information for vast areas, therefore making it suitable for the differentiation of terrain and objects near the vast flood plain areas in a short term. The object-oriented image analysis program (Definiens Developer 7.0) and multi-band high resolution satellite images (QuickBird, DigitalGlobe) was utilized to interpret the flood plain features from Liouguei to Baolai of the the Kaoping River basin after Typhoon Morakot. Object-oriented image interpretation is the process of using homogenized image blocks as elements instead of pixels for different shapes, textures and the mutual relationships of adjacent elements, as well as categorized conditions and rules for semi-artificial interpretation of surface features. Digital terrain models (DTM) are also employed along with the above process to produce layers with specific "landform thematic layers". These layers are especially helpful in differentiating some confusing categories in the spectrum analysis with improved accuracy, such as landslides and riverbeds, as well as terraces, riverbanks, which are of significant engineering importance in disaster mitigation. In this study, an automatic and fast image interpretation process for eight surface features including main channel, secondary channel, sandbar, flood plain, river terrace, alluvial fan, landslide, and the nearby artificial structures in the mountainous flood plain is proposed. Images along timelines can even be compared in order to differentiate historical events such as village inundations, failure of roads, bridges and levees, as well as alternation of watercourse, and therefore can be used as references for safety evaluation of engineering structures near rivers, disaster prevention and mitigation, and even future land-use planning. Keywords: Flood plain area, Remote sensing, Object-oriented, Surface feature interpretation, Terrain analysis, Thematic layer, Typhoon Morakot

Single sensor processing to obtain high resolution color component signals

NASA Technical Reports Server (NTRS)

Glenn, William E. (Inventor)

2010-01-01

A method for generating color video signals representative of color images of a scene includes the following steps: focusing light from the scene on an electronic image sensor via a filter having a tri-color filter pattern; producing, from outputs of the sensor, first and second relatively low resolution luminance signals; producing, from outputs of the sensor, a relatively high resolution luminance signal; producing, from a ratio of the relatively high resolution luminance signal to the first relatively low resolution luminance signal, a high band luminance component signal; producing, from outputs of the sensor, relatively low resolution color component signals; and combining each of the relatively low resolution color component signals with the high band luminance component signal to obtain relatively high resolution color component signals.

Spatiotemporal Features of the Three-Dimensional Architectural Landscape in Qingdao, China.

PubMed

Zhang, Peifeng

2015-01-01

The evolution and development of the three-dimensional (3D) architectural landscape is the basis of proper urban planning, eco-environment construction and the improvement of environmental quality. This paper presents the spatiotemporal characteristics of the 3D architectural landscape of the Shinan and Shibei districts in Qingdao, China, based on buildings' 3D information extracted from Quickbird images from 2003 to 2012, supported by Barista, landscape metrics and GIS. The results demonstrated that: (1) Shinan and Shibei districts expanded vertically and urban land use intensity increased noticeably from year to year. (2) Significant differences in the 3D architectural landscape existed among the western, central and eastern regions, and among the 26 sub-districts over the study period. The differentiation was consistent with the diverse development history, function and planning of the two districts. Finally, we found that population correlates positively with the variation in the 3D architectural landscape. This research provides an important reference for related studies, urban planning and eco-city construction.

Spatiotemporal Features of the Three-Dimensional Architectural Landscape in Qingdao, China

PubMed Central

Zhang, Peifeng

2015-01-01

The evolution and development of the three-dimensional (3D) architectural landscape is the basis of proper urban planning, eco-environment construction and the improvement of environmental quality. This paper presents the spatiotemporal characteristics of the 3D architectural landscape of the Shinan and Shibei districts in Qingdao, China, based on buildings’ 3D information extracted from Quickbird images from 2003 to 2012, supported by Barista, landscape metrics and GIS. The results demonstrated that: (1) Shinan and Shibei districts expanded vertically and urban land use intensity increased noticeably from year to year. (2) Significant differences in the 3D architectural landscape existed among the western, central and eastern regions, and among the 26 sub-districts over the study period. The differentiation was consistent with the diverse development history, function and planning of the two districts. Finally, we found that population correlates positively with the variation in the 3D architectural landscape. This research provides an important reference for related studies, urban planning and eco-city construction. PMID:26361016

Satellite imaging coral reef resilience at regional scale. A case-study from Saudi Arabia.

PubMed

Rowlands, Gwilym; Purkis, Sam; Riegl, Bernhard; Metsamaa, Liisa; Bruckner, Andrew; Renaud, Philip

2012-06-01

We propose a framework for spatially estimating a proxy for coral reef resilience using remote sensing. Data spanning large areas of coral reef habitat were obtained using the commercial QuickBird satellite, and freely available imagery (NASA, Google Earth). Principles of coral reef ecology, field observation, and remote observations, were combined to devise mapped indices. These capture important and accessible components of coral reef resilience. Indices are divided between factors known to stress corals, and factors incorporating properties of the reef landscape that resist stress or promote coral growth. The first-basis for a remote sensed resilience index (RSRI), an estimate of expected reef resilience, is proposed. Developed for the Red Sea, the framework of our analysis is flexible and with minimal adaptation, could be extended to other reef regions. We aim to stimulate discussion as to use of remote sensing to do more than simply deliver habitat maps of coral reefs. Copyright © 2012 Elsevier Ltd. All rights reserved.

Image resolution enhancement via image restoration using neural network

NASA Astrophysics Data System (ADS)

Zhang, Shuangteng; Lu, Yihong

2011-04-01

Image super-resolution aims to obtain a high-quality image at a resolution that is higher than that of the original coarse one. This paper presents a new neural network-based method for image super-resolution. In this technique, the super-resolution is considered as an inverse problem. An observation model that closely follows the physical image acquisition process is established to solve the problem. Based on this model, a cost function is created and minimized by a Hopfield neural network to produce high-resolution images from the corresponding low-resolution ones. Not like some other single frame super-resolution techniques, this technique takes into consideration point spread function blurring as well as additive noise and therefore generates high-resolution images with more preserved or restored image details. Experimental results demonstrate that the high-resolution images obtained by this technique have a very high quality in terms of PSNR and visually look more pleasant.

Impact of high resolution land surface initialization in Indian summer monsoon simulation using a regional climate model

NASA Astrophysics Data System (ADS)

Unnikrishnan, C. K.; Rajeevan, M.; Rao, S. Vijaya Bhaskara

2016-06-01

The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years over Indian summer monsoon region is investigated. Two sets of regional climate model simulations are performed, one with a coarse resolution land surface initial conditions and second one used a high resolution land surface data for initial condition. The results show that all monsoon years respond differently to the high resolution land surface initialization. The drought monsoon year 2009 and extended break periods were more sensitive to the high resolution land surface initialization. These results suggest that the drought monsoon year predictions can be improved with high resolution land surface initialization. Result also shows that there are differences in the response to the land surface initialization within the monsoon season. Case studies of heat wave and a monsoon depression simulation show that, the model biases were also improved with high resolution land surface initialization. These results show the need for a better land surface initialization strategy in high resolution regional models for monsoon forecasting.

High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

NASA Technical Reports Server (NTRS)

Mareboyana, Manohar; Le Moigne-Stewart, Jacqueline; Bennett, Jerome

2016-01-01

In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

Arctic storms simulated in atmospheric general circulation models under uniform high, uniform low, and variable resolutions

NASA Astrophysics Data System (ADS)

Roesler, E. L.; Bosler, P. A.; Taylor, M.

2016-12-01

The impact of strong extratropical storms on coastal communities is large, and the extent to which storms will change with a warming Arctic is unknown. Understanding storms in reanalysis and in climate models is important for future predictions. We know that the number of detected Arctic storms in reanalysis is sensitive to grid resolution. To understand Arctic storm sensitivity to resolution in climate models, we describe simulations designed to identify and compare Arctic storms at uniform low resolution (1 degree), at uniform high resolution (1/8 degree), and at variable resolution (1 degree to 1/8 degree). High-resolution simulations resolve more fine-scale structure and extremes, such as storms, in the atmosphere than a uniform low-resolution simulation. However, the computational cost of running a globally uniform high-resolution simulation is often prohibitive. The variable resolution tool in atmospheric general circulation models permits regional high-resolution solutions at a fraction of the computational cost. The storms are identified using the open-source search algorithm, Stride Search. The uniform high-resolution simulation has over 50% more storms than the uniform low-resolution and over 25% more storms than the variable resolution simulations. Storm statistics from each of the simulations is presented and compared with reanalysis. We propose variable resolution as a cost-effective means of investigating physics/dynamics coupling in the Arctic environment. Future work will include comparisons with observed storms to investigate tuning parameters for high resolution models. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. SAND2016-7402 A

An Hour of Spectacular Visualization

NASA Technical Reports Server (NTRS)

Hasler, Arthur F.

2005-01-01

The NASA/NOAA Electronic Theater presents Earth science observations and visualizations from space in a historical perspective. Fly in from outer space to Athens and site of the 2004 Summer Olympics and the Far East using 1 m IKONOS "Spy Satellite" data. Contrast the 1972 Apollo 17 "Blue Marble" image of the Earth with the latest US and International global satellite images that allow us to view our Planet from any vantage point. See the latest spectacular images from NASA/NOAA/Commercial remote sensing missions like Terra, GOES, TRMM, SeaWiFS, & Landsat 7, QuickBird of the SE Asia Tsunami, devastation of Hurricane Katrina this year in New Orleans, and the LA/San Diego Fires of 2003. See how High Definition Television (HDTV) is revolutionizing the way we do science communication. Take the pulse of the planet on a daily, annual and 30-year time scale. See daily thunderstorms, the annual blooming of the northern hemisphere land masses and oceans, fires in Africa, dust storms in Iraq, and carbon monoxide exhaust from global burning. See visualizations featured on Newsweek, TIME, National Geographic, Popular Science covers & National & International Network TV. Spectacular new global visualizations of the observed and simulated atmosphere & oceans are shown. See the currents and vortexes in the oceans that bring up the nutrients to feed tiny plankton and draw the fish, whales and fishermen. See the how the ocean blooms in response to El Nino/La Nina climate changes. The Etheater will be presented using the latest High Definition TV (HDTV) and video projection technology on a large screen. See city lights around the globe and in your area observed by the "night-vision" DMSP satellite, Also see how Keyhole and Google Maps are using satellite and aerial photography to help you find your house and plan your vacation.

Attention Modifies Spatial Resolution According to Task Demands.

PubMed

Barbot, Antoine; Carrasco, Marisa

2017-03-01

How does visual attention affect spatial resolution? In texture-segmentation tasks, exogenous (involuntary) attention automatically increases resolution at the attended location, which improves performance where resolution is too low (at the periphery) but impairs performance where resolution is already too high (at central locations). Conversely, endogenous (voluntary) attention improves performance at all eccentricities, which suggests a more flexible mechanism. Here, using selective adaptation to spatial frequency, we investigated the mechanism by which endogenous attention benefits performance in resolution tasks. Participants detected a texture target that could appear at several eccentricities. Adapting to high or low spatial frequencies selectively affected performance in a manner consistent with changes in resolution. Moreover, adapting to high, but not low, frequencies mitigated the attentional benefit at central locations where resolution was too high; this shows that attention can improve performance by decreasing resolution. Altogether, our results indicate that endogenous attention benefits performance by modulating the contribution of high-frequency information in order to flexibly adjust spatial resolution according to task demands.

Attention Modifies Spatial Resolution According to Task Demands

PubMed Central

Barbot, Antoine; Carrasco, Marisa

2017-01-01

How does visual attention affect spatial resolution? In texture-segmentation tasks, exogenous (involuntary) attention automatically increases resolution at the attended location, which improves performance where resolution is too low (at the periphery) but impairs performance where resolution is already too high (at central locations). Conversely, endogenous (voluntary) attention improves performance at all eccentricities, which suggests a more flexible mechanism. Here, using selective adaptation to spatial frequency, we investigated the mechanism by which endogenous attention benefits performance in resolution tasks. Participants detected a texture target that could appear at several eccentricities. Adapting to high or low spatial frequencies selectively affected performance in a manner consistent with changes in resolution. Moreover, adapting to high, but not low, frequencies mitigated the attentional benefit at central locations where resolution was too high; this shows that attention can improve performance by decreasing resolution. Altogether, our results indicate that endogenous attention benefits performance by modulating the contribution of high-frequency information in order to flexibly adjust spatial resolution according to task demands. PMID:28118103

Mapping Of Leptospirosis Environmental Risk Factors and Determining the Level of Leptospirosis Vulnerable Zone In Demak District Using Remote Sensing Image

NASA Astrophysics Data System (ADS)

Rahayu, Siti; Sakundarno Adi, Mateus; Saraswati, Lintang Dian

2018-02-01

Leptospirosis, a zoonotic disease, transmitted to human trough contact with contaminated animal urine and contaminated environment. Demak District is an endemic area where cases increased in the past 2 years. The aim of the study was to map environmental risk factor of Leptospirosis and to determine Leptospirosis vulnerable zone using cross-sectional study design. There were 42 cases mapped by GPS and overlaid using remote sensing (Quickbird image) by using ArcView program then interpreted by Spatial Feature and Spatial Analyses. Leptospirosis cases were spread out and grouped in Demak Sub District area. More cases were males (61.9%), 21-50 years old age group (59.3%) and farmers (40.4%). Spatial analyses showed that all the leptospirosis cases took place in the area with low plain <47 msl, rainfall ≥220 mm/month (64.7%), clay soil (100%), buffer river <50 m (71.4%), presence of rat (100%), wastewater disposal (100%), waste disposal facilities (97.7%), flood's profile (28.6%), tidal inundation's profile (7.1%), vegetation (59.5%). Leptospirosis high-risk zone was in 37,801.8 ha (41.32%), moderate risk zone was 43,570.23 ha (48.55%), and low-risk zone was 9,090.96 ha (10.13%). Densely populated housing, bad environment condition, and the presence of rat and puddles that were contaminated by rat's urine were risk factors of Leptospirosis cases in Demak District.

Nanga Parbat Revisited: Glacier changes between the 1930s and 2010

NASA Astrophysics Data System (ADS)

Nüsser, M.; Schmidt, S.

2012-04-01

In contrast to the relatively well investigated glacier changes in the mountains of Europe and North America, very few investigations using repeat photography have been undertaken in the Himalayas and adjacent high mountain regions. The present study seeks to redress this by investigating glacier changes in the Nanga Parbat region (NW-Himalaya) using matched pairs of photographs. A comprehensive collection of historical landscape photographs, taken by members of the German Himalaya expeditions in 1934 and 1937, forms a valuable baseline data set for the area. Our own fieldwork in the 1990s (1992-1997), 2006, and 2010 made it possible to repeat a large number of these photographs from viewpoints identical to the earlier ones. The multi-temporal data allows for direct comparisons and illustrates glacier changes over a span of seventy years. For the purpose of change detection, we also integrate the topographic map of 1934, as well as multi-temporal and multi-scale satellite data (Corona, ASTER, Landsat and Quickbird). The multi-temporal comparison of images detects a complex pattern of glacier retreat and stability in the six glaciers investigated in the Rupal Valley, to the South of Nanga Parbat. Whereas the termini of some of these glaciers are relatively stable since 1934; others such as the Raikot Glacier on the north face of Nanga Parbat are characterized by great fluctuation and a terminus retreat of about 210 m over the last 70 years. The extent of down-wasting displays a similar variation between the different glaciers under investigation.

A digital gigapixel large-format tile-scan camera.

PubMed

Ben-Ezra, M

2011-01-01

Although the resolution of single-lens reflex (SLR) and medium-format digital cameras has increased in recent years, applications for cultural-heritage preservation and computational photography require even higher resolutions. Addressing this issue, a large-format cameras' large image planes can achieve very high resolution without compromising pixel size and thus can provide high-quality, high-resolution images.This digital large-format tile scan camera can acquire high-quality, high-resolution images of static scenes. It employs unique calibration techniques and a simple algorithm for focal-stack processing of very large images with significant magnification variations. The camera automatically collects overlapping focal stacks and processes them into a high-resolution, extended-depth-of-field image.

CNV detection method optimized for high-resolution arrayCGH by normality test.

PubMed

Ahn, Jaegyoon; Yoon, Youngmi; Park, Chihyun; Park, Sanghyun

2012-04-01

High-resolution arrayCGH platform makes it possible to detect small gains and losses which previously could not be measured. However, current CNV detection tools fitted to early low-resolution data are not applicable to larger high-resolution data. When CNV detection tools are applied to high-resolution data, they suffer from high false-positives, which increases validation cost. Existing CNV detection tools also require optimal parameter values. In most cases, obtaining these values is a difficult task. This study developed a CNV detection algorithm that is optimized for high-resolution arrayCGH data. This tool operates up to 1500 times faster than existing tools on a high-resolution arrayCGH of whole human chromosomes which has 42 million probes whose average length is 50 bases, while preserving false positive/negative rates. The algorithm also uses a normality test, thereby removing the need for optimal parameters. To our knowledge, this is the first formulation for CNV detecting problems that results in a near-linear empirical overall complexity for real high-resolution data. Copyright © 2012 Elsevier Ltd. All rights reserved.

Comparison of High-Resolution MR Imaging and Digital Subtraction Angiography for the Characterization and Diagnosis of Intracranial Artery Disease.

PubMed

Lee, N J; Chung, M S; Jung, S C; Kim, H S; Choi, C-G; Kim, S J; Lee, D H; Suh, D C; Kwon, S U; Kang, D-W; Kim, J S

2016-12-01

High-resolution MR imaging has recently been introduced as a promising diagnostic modality in intracranial artery disease. Our aim was to compare high-resolution MR imaging with digital subtraction angiography for the characterization and diagnosis of various intracranial artery diseases. Thirty-seven patients who had undergone both high-resolution MR imaging and DSA for intracranial artery disease were enrolled in our study (August 2011 to April 2014). The time interval between the high-resolution MR imaging and DSA was within 1 month. The degree of stenosis and the minimal luminal diameter were independently measured by 2 observers in both DSA and high-resolution MR imaging, and the results were compared. Two observers independently diagnosed intracranial artery diseases on DSA and high-resolution MR imaging. The time interval between the diagnoses on DSA and high-resolution MR imaging was 2 weeks. Interobserver diagnostic agreement for each technique and intermodality diagnostic agreement for each observer were acquired. High-resolution MR imaging showed moderate-to-excellent agreement (interclass correlation coefficient = 0.892-0.949; κ = 0.548-0.614) and significant correlations (R = 0.766-892) with DSA on the degree of stenosis and minimal luminal diameter. The interobserver diagnostic agreement was good for DSA (κ = 0.643) and excellent for high-resolution MR imaging (κ = 0.818). The intermodality diagnostic agreement was good (κ = 0.704) for observer 1 and moderate (κ = 0.579) for observer 2, respectively. High-resolution MR imaging may be an imaging method comparable with DSA for the characterization and diagnosis of various intracranial artery diseases. © 2016 by American Journal of Neuroradiology.

Glacier Changes in the Nanga Parbat Region, NW Himalaya: A longitudinal study over 160 years (1856-2016)

NASA Astrophysics Data System (ADS)

Nüsser, Marcus; Schmidt, Susanne

2017-04-01

Against the background of the prominent Himalayan glacier debate of the past decade, global concerns were raised about the severe consequences of detected and expected changes in the South Asian cryosphere. Due to the lack of historical glaciological data in the Himalayan region, studies of glacier changes over long time periods are rare. The present study seeks to analyze and quantify glacier changes in the Nanga Parbat region between 1856 and 2016. Due to the steep topography and great vertical span, the debris-covered glaciers of the mountain massif are largely fed by avalanches of different size. This impact of snow and ice re-distribution by avalanches is often neglected in glacier mass-balances. Therefore, an integrated approach was used to investigate the glacier changes and the impact of avalanches. This approach includes (1) a re-photographic survey with images from several expeditions between 1934 and 2010, (2) mapping during own field surveys between 1992 and 2010, as well as (3) the analyses of remote sensing data (Corona, QuickBird, KompSat, Landsat, etc. and DEM) and (4) historical topographic maps. The re-photographic survey allows for direct comparisons and illustrates glacier changes over a span of seventy years. Changes of glacier lengths were quantified by using remote sensing data and the topographic map of 1934. In order to calculate glacier surface changes, a digital elevation model (DEM) with a spatial resolution of 30 x 30 m2 was derived from the digitized contour lines of the topographic map from 1934 and compared to SRTM-DEM (30 x 30 m2) and ALOS-DSM. Based on remote sensing time-series, avalanche deposits on glaciers were mapped in order to identify their magnitude and frequencies. To calculate the potential glacier catchment, area of steep rock walls and the ratio between accumulation and ablation zones were calculated for each glacier basin. Our field based investigations show that the glaciers in the Rupal Valley are characterized by small retreating rates since 1856, when Adolph Schlagintweit mapped them for the first time; others such as the Raikot Glacier on the northern side of the Nanga Parbat are fluctuating since 1934.

Parameterization of Shape and Compactness in Object-based Image Classification Using Quickbird-2 Imagery

NASA Astrophysics Data System (ADS)

Tonbul, H.; Kavzoglu, T.

2016-12-01

In recent years, object based image analysis (OBIA) has spread out and become a widely accepted technique for the analysis of remotely sensed data. OBIA deals with grouping pixels into homogenous objects based on spectral, spatial and textural features of contiguous pixels in an image. The first stage of OBIA, named as image segmentation, is the most prominent part of object recognition. In this study, multiresolution segmentation, which is a region-based approach, was employed to construct image objects. In the application of multi-resolution, three parameters, namely shape, compactness and scale must be set by the analyst. Segmentation quality remarkably influences the fidelity of the thematic maps and accordingly the classification accuracy. Therefore, it is of great importance to search and set optimal values for the segmentation parameters. In the literature, main focus has been on the definition of scale parameter, assuming that the effect of shape and compactness parameters is limited in terms of achieved classification accuracy. The aim of this study is to deeply analyze the influence of shape/compactness parameters by varying their values while using the optimal scale parameter determined by the use of Estimation of Scale Parameter (ESP-2) approach. A pansharpened Qickbird-2 image covering Trabzon, Turkey was employed to investigate the objectives of the study. For this purpose, six different combinations of shape/compactness were utilized to make deductions on the behavior of shape and compactness parameters and optimal setting for all parameters as a whole. Objects were assigned to classes using nearest neighbor classifier in all segmentation observations and equal number of pixels was randomly selected to calculate accuracy metrics. The highest overall accuracy (92.3%) was achieved by setting the shape/compactness criteria to 0.3/0.3. The results of this study indicate that shape/compactness parameters can have significant effect on classification accuracy with 4% change in overall accuracy. Also, statistical significance of differences in accuracy was tested using the McNemar's test and found that the difference between poor and optimal setting of shape/compactness parameters was statistically significant, suggesting a search for optimal parameterization instead of default setting.

Surface Water Detection Using Fused Synthetic Aperture Radar, Airborne LiDAR and Optical Imagery

NASA Astrophysics Data System (ADS)

Braun, A.; Irwin, K.; Beaulne, D.; Fotopoulos, G.; Lougheed, S. C.

2016-12-01

Each remote sensing technique has its unique set of strengths and weaknesses, but by combining techniques the classification accuracy can be increased. The goal of this project is to underline the strengths and weaknesses of Synthetic Aperture Radar (SAR), LiDAR and optical imagery data and highlight the opportunities where integration of the three data types can increase the accuracy of identifying water in a principally natural landscape. The study area is located at the Queen's University Biological Station, Ontario, Canada. TerraSAR-X (TSX) data was acquired between April and July 2016, consisting of four single polarization (HH) staring spotlight mode backscatter intensity images. Grey-level thresholding is used to extract surface water bodies, before identifying and masking zones of radar shadow and layover by using LiDAR elevation models to estimate the canopy height and applying simple geometry algorithms. The airborne LiDAR survey was conducted in June 2014, resulting in a discrete return dataset with a density of 1 point/m2. Radiometric calibration to correct for range and incidence angle is applied, before classifying the points as water or land based on corrected intensity, elevation, roughness, and intensity density. Panchromatic and multispectral (4-band) imagery from Quickbird was collected in September 2005 at spatial resolutions of 0.6m and 2.5m respectively. Pixel-based classification is applied to identify and distinguish water bodies from land. A classification system which inputs SAR-, LiDAR- and optically-derived water presence models in raster formats is developed to exploit the strengths and weaknesses of each technique. The total percentage of water detected in the sample area for SAR backscatter, LiDAR intensity, and optical imagery was 27%, 19% and 18% respectively. The output matrix of the classification system indicates that in over 72% of the study area all three methods agree on the classification. Analysis was specifically targeted towards areas where the methods disagree, highlighting how each technique should be properly weighted over these areas to increase the classification accuracy of water. The conclusions and techniques developed in this study are applicable to other areas where similar environmental conditions and data availability exist.

Whole-animal imaging with high spatio-temporal resolution

NASA Astrophysics Data System (ADS)

Chhetri, Raghav; Amat, Fernando; Wan, Yinan; Höckendorf, Burkhard; Lemon, William C.; Keller, Philipp J.

2016-03-01

We developed isotropic multiview (IsoView) light-sheet microscopy in order to image fast cellular dynamics, such as cell movements in an entire developing embryo or neuronal activity throughput an entire brain or nervous system, with high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To achieve high temporal resolution and high spatial resolution at the same time, IsoView microscopy rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. In a post-processing step, these four views are then combined by means of high-throughput multiview deconvolution to yield images with a system resolution of ≤ 450 nm in all three dimensions. Using IsoView microscopy, we performed whole-animal functional imaging of Drosophila embryos and larvae at a spatial resolution of 1.1-2.5 μm and at a temporal resolution of 2 Hz for up to 9 hours. We also performed whole-brain functional imaging in larval zebrafish and multicolor imaging of fast cellular dynamics across entire, gastrulating Drosophila embryos with isotropic, sub-cellular resolution. Compared with conventional (spatially anisotropic) light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, such as lattice lightsheet microscopy or diSPIM, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

Regional Community Climate Simulations with variable resolution meshes in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Zarzycki, C. M.; Gettelman, A.; Callaghan, P.

2017-12-01

Accurately predicting weather extremes such as precipitation (floods and droughts) and temperature (heat waves) requires high resolution to resolve mesoscale dynamics and topography at horizontal scales of 10-30km. Simulating such resolutions globally for climate scales (years to decades) remains computationally impractical. Simulating only a small region of the planet is more tractable at these scales for climate applications. This work describes global simulations using variable-resolution static meshes with multiple dynamical cores that target the continental United States using developmental versions of the Community Earth System Model version 2 (CESM2). CESM2 is tested in idealized, aquaplanet and full physics configurations to evaluate variable mesh simulations against uniform high and uniform low resolution simulations at resolutions down to 15km. Different physical parameterization suites are also evaluated to gauge their sensitivity to resolution. Idealized variable-resolution mesh cases compare well to high resolution tests. More recent versions of the atmospheric physics, including cloud schemes for CESM2, are more stable with respect to changes in horizontal resolution. Most of the sensitivity is due to sensitivity to timestep and interactions between deep convection and large scale condensation, expected from the closure methods. The resulting full physics model produces a comparable climate to the global low resolution mesh and similar high frequency statistics in the high resolution region. Some biases are reduced (orographic precipitation in the western United States), but biases do not necessarily go away at high resolution (e.g. summertime JJA surface Temp). The simulations are able to reproduce uniform high resolution results, making them an effective tool for regional climate studies and are available in CESM2.

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical levels

NASA Astrophysics Data System (ADS)

Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.

2011-12-01

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) has been applied to model the spatial distribution of nitrogen deposition and air concentration over the UK at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical loads

NASA Astrophysics Data System (ADS)

Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.

2012-05-01

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) was applied to model the spatial distribution of reactive nitrogen deposition and air concentration over the United Kingdom at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of reactive nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

Very high resolution aerial films

NASA Astrophysics Data System (ADS)

Becker, Rolf

1986-11-01

The use of very high resolution aerial films in aerial photography is evaluated. Commonly used panchromatic, color, and CIR films and their high resolution equivalents are compared. Based on practical experience and systematic investigations, the very high image quality and improved height accuracy that can be achieved using these films are demonstrated. Advantages to be gained from this improvement and operational restrictions encountered when using high resolution film are discussed.

[Study on the effect of solar spectra on the retrieval of atmospheric CO2 concentration using high resolution absorption spectra].

PubMed

Hu, Zhen-Hua; Huang, Teng; Wang, Ying-Ping; Ding, Lei; Zheng, Hai-Yang; Fang, Li

2011-06-01

Taking solar source as radiation in the near-infrared high-resolution absorption spectrum is widely used in remote sensing of atmospheric parameters. The present paper will take retrieval of the concentration of CO2 for example, and study the effect of solar spectra resolution. Retrieving concentrations of CO2 by using high resolution absorption spectra, a method which uses the program provided by AER to calculate the solar spectra at the top of atmosphere as radiation and combine with the HRATS (high resolution atmospheric transmission simulation) to simulate retrieving concentration of CO2. Numerical simulation shows that the accuracy of solar spectrum is important to retrieval, especially in the hyper-resolution spectral retrieavl, and the error of retrieval concentration has poor linear relation with the resolution of observation, but there is a tendency that the decrease in the resolution requires low resolution of solar spectrum. In order to retrieve the concentration of CO2 of atmosphere, the authors' should take full advantage of high-resolution solar spectrum at the top of atmosphere.

Development and application of high-resolution solid- state NMR dipolar recovery techniques for spin-1/2 nuclei

NASA Astrophysics Data System (ADS)

Joers, James M.

The use of magic angle spinning to obtain high resolution solid state spectra has been well documented. This resolution occurs by coherently averaging the chemical shift anisotropy and dipolar interactions to zero over the period of a full rotation. While this allows for higher resolution, the structural information is seemingly lost to the spectrometer eye. Thus, high resolution spectra and structural information appear to be mutually exlusive. Recently, the push in solid state NMR is the development of recoupling techniques which afford both high resolution and structural information. The following dissertation demonstrates the feasibility of implementing such experiments in solving real world problems, and is centered on devising a method to recover homonuclear dipolar interactions in the high resolution regime.

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

High-Spatial and High-Mass Resolution Imaging of Surface Metabolites of Arabidopsis thaliana by Laser Desorption-Ionization Mass Spectrometry Using Colloidal Silver

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jun, Ji Hyun; Song, Zhihong; Liu, Zhenjiu

High-spatial resolution and high-mass resolution techniques are developed and adopted for the mass spectrometric imaging of epicuticular lipids on the surface of Arabidopsis thaliana. Single cell level spatial resolution of {approx}12 {micro}m was achieved by reducing the laser beam size by using an optical fiber with 25 {micro}m core diameter in a vacuum matrix-assisted laser desorption ionization-linear ion trap (vMALDI-LTQ) mass spectrometer and improved matrix application using an oscillating capillary nebulizer. Fine chemical images of a whole flower were visualized in this high spatial resolution showing substructure of an anther and single pollen grains at the stigma and anthers. Themore » LTQ-Orbitrap with a MALDI ion source was adopted to achieve MS imaging in high mass resolution. Specifically, isobaric silver ion adducts of C29 alkane (m/z 515.3741) and C28 aldehyde (m/z 515.3377), indistinguishable in low-resolution LTQ, can now be clearly distinguished and their chemical images could be separately constructed. In the application to roots, the high spatial resolution allowed molecular MS imaging of secondary roots and the high mass resolution allowed direct identification of lipid metabolites on root surfaces.« less

MASH Suite: a user-friendly and versatile software interface for high-resolution mass spectrometry data interpretation and visualization.

PubMed

Guner, Huseyin; Close, Patrick L; Cai, Wenxuan; Zhang, Han; Peng, Ying; Gregorich, Zachery R; Ge, Ying

2014-03-01

The rapid advancements in mass spectrometry (MS) instrumentation, particularly in Fourier transform (FT) MS, have made the acquisition of high-resolution and high-accuracy mass measurements routine. However, the software tools for the interpretation of high-resolution MS data are underdeveloped. Although several algorithms for the automatic processing of high-resolution MS data are available, there is still an urgent need for a user-friendly interface with functions that allow users to visualize and validate the computational output. Therefore, we have developed MASH Suite, a user-friendly and versatile software interface for processing high-resolution MS data. MASH Suite contains a wide range of features that allow users to easily navigate through data analysis, visualize complex high-resolution MS data, and manually validate automatically processed results. Furthermore, it provides easy, fast, and reliable interpretation of top-down, middle-down, and bottom-up MS data. MASH Suite is convenient, easily operated, and freely available. It can greatly facilitate the comprehensive interpretation and validation of high-resolution MS data with high accuracy and reliability.

Resolution Enhancement of Hyperion Hyperspectral Data using Ikonos Multispectral Data

DTIC Science & Technology

2007-09-01

spatial - resolution hyperspectral image to produce a sharpened product. The result is a product that has the spectral properties of the ...multispectral sensors. In this work, we examine the benefits of combining data from high- spatial - resolution , low- spectral - resolution spectral imaging...sensors with data obtained from high- spectral - resolution , low- spatial - resolution spectral imaging sensors.

Interior tomography in microscopic CT with image reconstruction constrained by full field of view scan at low spatial resolution

NASA Astrophysics Data System (ADS)

Luo, Shouhua; Shen, Tao; Sun, Yi; Li, Jing; Li, Guang; Tang, Xiangyang

2018-04-01

In high resolution (microscopic) CT applications, the scan field of view should cover the entire specimen or sample to allow complete data acquisition and image reconstruction. However, truncation may occur in projection data and results in artifacts in reconstructed images. In this study, we propose a low resolution image constrained reconstruction algorithm (LRICR) for interior tomography in microscopic CT at high resolution. In general, the multi-resolution acquisition based methods can be employed to solve the data truncation problem if the project data acquired at low resolution are utilized to fill up the truncated projection data acquired at high resolution. However, most existing methods place quite strict restrictions on the data acquisition geometry, which greatly limits their utility in practice. In the proposed LRICR algorithm, full and partial data acquisition (scan) at low and high resolutions, respectively, are carried out. Using the image reconstructed from sparse projection data acquired at low resolution as the prior, a microscopic image at high resolution is reconstructed from the truncated projection data acquired at high resolution. Two synthesized digital phantoms, a raw bamboo culm and a specimen of mouse femur, were utilized to evaluate and verify performance of the proposed LRICR algorithm. Compared with the conventional TV minimization based algorithm and the multi-resolution scout-reconstruction algorithm, the proposed LRICR algorithm shows significant improvement in reduction of the artifacts caused by data truncation, providing a practical solution for high quality and reliable interior tomography in microscopic CT applications. The proposed LRICR algorithm outperforms the multi-resolution scout-reconstruction method and the TV minimization based reconstruction for interior tomography in microscopic CT.

Partial homogeneity based high-resolution nuclear magnetic resonance spectra under inhomogeneous magnetic fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Zhiliang; Lin, Liangjie; Lin, Yanqin, E-mail: linyq@xmu.edu.cn, E-mail: chenz@xmu.edu.cn

2014-09-29

In nuclear magnetic resonance (NMR) technique, it is of great necessity and importance to obtain high-resolution spectra, especially under inhomogeneous magnetic fields. In this study, a method based on partial homogeneity is proposed for retrieving high-resolution one-dimensional NMR spectra under inhomogeneous fields. Signals from series of small voxels, which characterize high resolution due to small sizes, are recorded simultaneously. Then, an inhomogeneity correction algorithm is developed based on pattern recognition to correct the influence brought by field inhomogeneity automatically, thus yielding high-resolution information. Experiments on chemical solutions and fish spawn were carried out to demonstrate the performance of the proposedmore » method. The proposed method serves as a single radiofrequency pulse high-resolution NMR spectroscopy under inhomogeneous fields and may provide an alternative of obtaining high-resolution spectra of in vivo living systems or chemical-reaction systems, where performances of conventional techniques are usually degenerated by field inhomogeneity.« less

High throughput screening of ligand binding to macromolecules using high resolution powder diffraction

DOEpatents

Von Dreele, Robert B.; D'Amico, Kevin

2006-10-31

A process is provided for the high throughput screening of binding of ligands to macromolecules using high resolution powder diffraction data including producing a first sample slurry of a selected polycrystalline macromolecule material and a solvent, producing a second sample slurry of a selected polycrystalline macromolecule material, one or more ligands and the solvent, obtaining a high resolution powder diffraction pattern on each of said first sample slurry and the second sample slurry, and, comparing the high resolution powder diffraction pattern of the first sample slurry and the high resolution powder diffraction pattern of the second sample slurry whereby a difference in the high resolution powder diffraction patterns of the first sample slurry and the second sample slurry provides a positive indication for the formation of a complex between the selected polycrystalline macromolecule material and at least one of the one or more ligands.

HIRIS (High-Resolution Imaging Spectrometer: Science opportunities for the 1990s. Earth observing system. Volume 2C: Instrument panel report

NASA Technical Reports Server (NTRS)

1987-01-01

The high-resolution imaging spectrometer (HIRIS) is an Earth Observing System (EOS) sensor developed for high spatial and spectral resolution. It can acquire more information in the 0.4 to 2.5 micrometer spectral region than any other sensor yet envisioned. Its capability for critical sampling at high spatial resolution makes it an ideal complement to the MODIS (moderate-resolution imaging spectrometer) and HMMR (high-resolution multifrequency microwave radiometer), lower resolution sensors designed for repetitive coverage. With HIRIS it is possible to observe transient processes in a multistage remote sensing strategy for Earth observations on a global scale. The objectives, science requirements, and current sensor design of the HIRIS are discussed along with the synergism of the sensor with other EOS instruments and data handling and processing requirements.

Image quality improvement in cone-beam CT using the super-resolution technique.

PubMed

Oyama, Asuka; Kumagai, Shinobu; Arai, Norikazu; Takata, Takeshi; Saikawa, Yusuke; Shiraishi, Kenshiro; Kobayashi, Takenori; Kotoku, Jun'ichi

2018-04-05

This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-called dictionaries, constructed respectively from high-resolution and low-resolution image bases. For this study, a CBCT image, as a low-resolution image, is represented as a linear combination of atoms, the image bases in the low-resolution dictionary. The corresponding super-resolution image was inferred by multiplying the coefficients and the high-resolution dictionary atoms extracted from planning CT images. To evaluate the proposed method, we computed the root mean square error (RMSE) and structural similarity (SSIM). The resulting RMSE and SSIM between the super-resolution images and the planning CT images were, respectively, as much as 0.81 and 1.29 times better than those obtained without using the super-resolution technique. We used super-resolution technique to improve the CBCT image quality.

Using high spectral resolution spectrophotometry to study broad mineral absorption features on Mars

NASA Technical Reports Server (NTRS)

Blaney, D. L.; Crisp, D.

1993-01-01

Traditionally telescopic measurements of mineralogic absorption features have been made using relatively low to moderate (R=30-300) spectral resolution. Mineralogic absorption features tend to be broad so high resolution spectroscopy (R greater than 10,000) does not provide significant additional compositional information. Low to moderate resolution spectroscopy allows an observer to obtain data over a wide wavelength range (hundreds to thousands of wavenumbers) compared to the several wavenumber intervals that are collected using high resolution spectrometers. However, spectrophotometry at high resolution has major advantages over lower resolution spectroscopy in situations that are applicable to studies of the Martian surface, i.e., at wavelengths where relatively weak surface absorption features and atmospheric gas absorption features both occur.

Image super-resolution via sparse representation.

PubMed

Yang, Jianchao; Wright, John; Huang, Thomas S; Ma, Yi

2010-11-01

This paper presents a new approach to single-image super-resolution, based on sparse signal representation. Research on image statistics suggests that image patches can be well-represented as a sparse linear combination of elements from an appropriately chosen over-complete dictionary. Inspired by this observation, we seek a sparse representation for each patch of the low-resolution input, and then use the coefficients of this representation to generate the high-resolution output. Theoretical results from compressed sensing suggest that under mild conditions, the sparse representation can be correctly recovered from the downsampled signals. By jointly training two dictionaries for the low- and high-resolution image patches, we can enforce the similarity of sparse representations between the low resolution and high resolution image patch pair with respect to their own dictionaries. Therefore, the sparse representation of a low resolution image patch can be applied with the high resolution image patch dictionary to generate a high resolution image patch. The learned dictionary pair is a more compact representation of the patch pairs, compared to previous approaches, which simply sample a large amount of image patch pairs, reducing the computational cost substantially. The effectiveness of such a sparsity prior is demonstrated for both general image super-resolution and the special case of face hallucination. In both cases, our algorithm generates high-resolution images that are competitive or even superior in quality to images produced by other similar SR methods. In addition, the local sparse modeling of our approach is naturally robust to noise, and therefore the proposed algorithm can handle super-resolution with noisy inputs in a more unified framework.

Assessment of prediction skill in equatorial Pacific Ocean in high resolution model of CFS

NASA Astrophysics Data System (ADS)

Arora, Anika; Rao, Suryachandra A.; Pillai, Prasanth; Dhakate, Ashish; Salunke, Kiran; Srivastava, Ankur

2018-01-01

The effect of increasing atmospheric resolution on prediction skill of El Niño southern oscillation phenomenon in climate forecast system model is explored in this paper. Improvement in prediction skill for sea surface temperature (SST) and winds at all leads compared to low resolution model in the tropical Indo-Pacific basin is observed. High resolution model is able to capture extreme events reasonably well. As a result, the signal to noise ratio is improved in the high resolution model. However, spring predictability barrier (SPB) for summer months in Nino 3 and Nino 3.4 region is stronger in high resolution model, in spite of improvement in overall prediction skill and dynamics everywhere else. Anomaly correlation coefficient of SST in high resolution model with observations in Nino 3.4 region targeting boreal summer months when predicted at lead times of 3-8 months in advance decreased compared its lower resolution counterpart. It is noted that higher variance of winds predicted in spring season over central equatorial Pacific compared to observed variance of winds results in stronger than normal response on subsurface ocean, hence increases SPB for boreal summer months in high resolution model.

An atlas of high-resolution IRAS maps on nearby galaxies

NASA Technical Reports Server (NTRS)

Rice, Walter

1993-01-01

An atlas of far-infrared IRAS maps with near 1 arcmin angular resolution of 30 optically large galaxies is presented. The high-resolution IRAS maps were produced with the Maximum Correlation Method (MCM) image construction and enhancement technique developed at IPAC. The MCM technique, which recovers the spatial information contained in the overlapping detector data samples of the IRAS all-sky survey scans, is outlined and tests to verify the structural reliability and photometric integrity of the high-resolution maps are presented. The infrared structure revealed in individual galaxies is discussed. The atlas complements the IRAS Nearby Galaxy High-Resolution Image Atlas, the high-resolution galaxy images encoded in FITS format, which is provided to the astronomical community as an IPAC product.

NREL: International Activities - Afghanistan Resource Maps

Science.gov Websites

facilities, load centers, terrain conditions, and land use. The high-resolution (1-km) annual wind power maps . The high-resolution (10-km) annual and seasonal solar resource maps were developed using weather -km Resolution Annual Maps (Direct) Low-Res (JPG 104 KB) | High-Res (ZIP 330 KB) 40-km Resolution

The effect of horizontal resolution on simulation quality in the Community Atmospheric Model, CAM5.1

DOE PAGES

Wehner, Michael F.; Reed, Kevin A.; Li, Fuyu; ...

2014-10-13

We present an analysis of version 5.1 of the Community Atmospheric Model (CAM5.1) at a high horizontal resolution. Intercomparison of this global model at approximately 0.25°, 1°, and 2° is presented for extreme daily precipitation as well as for a suite of seasonal mean fields. In general, extreme precipitation amounts are larger in high resolution than in lower-resolution configurations. In many but not all locations and/or seasons, extreme daily precipitation rates in the high-resolution configuration are higher and more realistic. The high-resolution configuration produces tropical cyclones up to category 5 on the Saffir-Simpson scale and a comparison to observations revealsmore » both realistic and unrealistic model behavior. In the absence of extensive model tuning at high resolution, simulation of many of the mean fields analyzed in this study is degraded compared to the tuned lower-resolution public released version of the model.« less

Machine Learning Predictions of a Multiresolution Climate Model Ensemble

NASA Astrophysics Data System (ADS)

Anderson, Gemma J.; Lucas, Donald D.

2018-05-01

Statistical models of high-resolution climate models are useful for many purposes, including sensitivity and uncertainty analyses, but building them can be computationally prohibitive. We generated a unique multiresolution perturbed parameter ensemble of a global climate model. We use a novel application of a machine learning technique known as random forests to train a statistical model on the ensemble to make high-resolution model predictions of two important quantities: global mean top-of-atmosphere energy flux and precipitation. The random forests leverage cheaper low-resolution simulations, greatly reducing the number of high-resolution simulations required to train the statistical model. We demonstrate that high-resolution predictions of these quantities can be obtained by training on an ensemble that includes only a small number of high-resolution simulations. We also find that global annually averaged precipitation is more sensitive to resolution changes than to any of the model parameters considered.

High-resolution X-ray crystal structure of bovine H-protein using the high-pressure cryocooling method.

PubMed

Higashiura, Akifumi; Ohta, Kazunori; Masaki, Mika; Sato, Masaru; Inaka, Koji; Tanaka, Hiroaki; Nakagawa, Atsushi

2013-11-01

Recently, many technical improvements in macromolecular X-ray crystallography have increased the number of structures deposited in the Protein Data Bank and improved the resolution limit of protein structures. Almost all high-resolution structures have been determined using a synchrotron radiation source in conjunction with cryocooling techniques, which are required in order to minimize radiation damage. However, optimization of cryoprotectant conditions is a time-consuming and difficult step. To overcome this problem, the high-pressure cryocooling method was developed (Kim et al., 2005) and successfully applied to many protein-structure analyses. In this report, using the high-pressure cryocooling method, the X-ray crystal structure of bovine H-protein was determined at 0.86 Å resolution. Structural comparisons between high- and ambient-pressure cryocooled crystals at ultra-high resolution illustrate the versatility of this technique. This is the first ultra-high-resolution X-ray structure obtained using the high-pressure cryocooling method.

Relationship between perception of image resolution and peripheral visual field in stereoscopic images

NASA Astrophysics Data System (ADS)

Ogawa, Masahiko; Shidoji, Kazunori

2011-03-01

High-resolution stereoscopic images are effective for use in virtual reality and teleoperation systems. However, the higher the image resolution, the higher is the cost of computer processing and communication. To reduce this cost, numerous earlier studies have suggested the use of multi-resolution images, which have high resolution in region of interests and low resolution in other areas. However, observers can perceive unpleasant sensations and incorrect depth because they can see low-resolution areas in their field of vision. In this study, we conducted an experiment to research the relationship between the viewing field and the perception of image resolution, and determined respective thresholds of image-resolution perception for various positions of the viewing field. The results showed that participants could not distinguish between the high-resolution stimulus and the decreased stimulus, 63 ppi, at positions more than 8 deg outside the gaze point. Moreover, with positions shifted a further 11 and 13 deg from the gaze point, participants could not distinguish between the high-resolution stimulus and the decreased stimuli whose resolution densities were 42 and 25 ppi. Hence, we will propose the composition of multi-resolution images in which observers do not perceive unpleasant sensations and incorrect depth with data reduction (compression).

Single image super-resolution via an iterative reproducing kernel Hilbert space method.

PubMed

Deng, Liang-Jian; Guo, Weihong; Huang, Ting-Zhu

2016-11-01

Image super-resolution, a process to enhance image resolution, has important applications in satellite imaging, high definition television, medical imaging, etc. Many existing approaches use multiple low-resolution images to recover one high-resolution image. In this paper, we present an iterative scheme to solve single image super-resolution problems. It recovers a high quality high-resolution image from solely one low-resolution image without using a training data set. We solve the problem from image intensity function estimation perspective and assume the image contains smooth and edge components. We model the smooth components of an image using a thin-plate reproducing kernel Hilbert space (RKHS) and the edges using approximated Heaviside functions. The proposed method is applied to image patches, aiming to reduce computation and storage. Visual and quantitative comparisons with some competitive approaches show the effectiveness of the proposed method.

High Efficiency Multi-shot Interleaved Spiral-In/Out Acquisition for High Resolution BOLD fMRI

PubMed Central

Jung, Youngkyoo; Samsonov, Alexey A.; Liu, Thomas T.; Buracas, Giedrius T.

2012-01-01

Growing demand for high spatial resolution BOLD functional MRI faces a challenge of the spatial resolution vs. coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in-out trajectory is preferred over spiral-in due to increased BOLD signal CNR and higher acquisition efficiency than that of spiral-out or non-interleaved spiral in/out trajectories (1), but to date applicability of the multi-shot interleaved spiral in-out for high spatial resolution imaging has not been studied. Herein we propose multi-shot interleaved spiral in-out acquisition and investigate its applicability for high spatial resolution BOLD fMRI. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2* decay, off-resonance and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in-out pulse sequence yields high BOLD CNR images at in-plane resolution below 1x1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multi-shot interleaved spiral in-out acquisition is a promising technique for high spatial resolution BOLD fMRI applications. PMID:23023395

High-Resolution Soil Moisture Retrieval using SMAP-L Band Radiometer and RISAT-C band Radar Data for the Indian Subcontinent

NASA Astrophysics Data System (ADS)

Singh, G.; Das, N. N.; Panda, R. K.; Mohanty, B.; Entekhabi, D.; Bhattacharya, B. K.

2016-12-01

Soil moisture status at high resolution (1-10 km) is vital for hydrological, agricultural and hydro-metrological applications. The NASA Soil Moisture Active Passive (SMAP) mission had potential to provide reliable soil moisture estimate at finer spatial resolutions (3 km and 9 km) at the global extent, but suffered a malfunction of its radar, consequently making the SMAP mission observations only from radiometer that are of coarse spatial resolution. At present, the availability of high-resolution soil moisture product is limited, especially in developing countries like India, which greatly depends on agriculture for sustaining a huge population. Therefore, an attempt has been made in the reported study to combine the C-band synthetic aperture radar (SAR) data from Radar Imaging Satellite (RISAT) of the Indian Space Research Organization (ISRO) with the SMAP mission L-band radiometer data to obtain high-resolution (1 km and 3 km) soil moisture estimates. In this study, a downscaling approach (Active-Passive Algorithm) implemented for the SMAP mission was used to disaggregate the SMAP radiometer brightness temperature (Tb) using the fine resolution SAR backscatter (σ0) from RISAT. The downscaled high-resolution Tb was then subjected to tau-omega model in conjunction with high-resolution ancillary data to retrieve soil moisture at 1 and 3 km scale. The retrieved high-resolution soil moisture estimates were then validated with ground based soil moisture measurement under different hydro-climatic regions of India. Initial results show tremendous potential and reasonable accuracy for the retrieved soil moisture at 1 km and 3 km. It is expected that ISRO will implement this approach to produce high-resolution soil moisture estimates for the Indian subcontinent.

A novel ToF-SIMS operation mode for sub 100 nm lateral resolution: Application and performance.

PubMed

Kubicek, Markus; Holzlechner, Gerald; Opitz, Alexander K; Larisegger, Silvia; Hutter, Herbert; Fleig, Jürgen

2014-01-15

A novel operation mode for time of flight-secondary ion mass spectrometry (ToF-SIMS) is described for a TOF.SIMS 5 instrument with a Bi-ion gun. It features sub 100 nm lateral resolution, adjustable primary ion currents and the possibility to measure with high lateral resolution as well as high mass resolution. The adjustment and performance of the novel operation mode are described and compared to established ToF-SIMS operation modes. Several examples of application featuring novel scientific results show the capabilities of the operation mode in terms of lateral resolution, accuracy of isotope analysis of oxygen, and combination of high lateral and mass resolution. The relationship between high lateral resolution and operation of SIMS in static mode is discussed.

Gas scintillation glass GEM detector for high-resolution X-ray imaging and CT

NASA Astrophysics Data System (ADS)

Fujiwara, T.; Mitsuya, Y.; Fushie, T.; Murata, K.; Kawamura, A.; Koishikawa, A.; Toyokawa, H.; Takahashi, H.

2017-04-01

A high-spatial-resolution X-ray-imaging gaseous detector has been developed with a single high-gas-gain glass gas electron multiplier (G-GEM), scintillation gas, and optical camera. High-resolution X-ray imaging of soft elements is performed with a spatial resolution of 281 μm rms and an effective area of 100×100 mm. In addition, high-resolution X-ray 3D computed tomography (CT) is successfully demonstrated with the gaseous detector. It shows high sensitivity to low-energy X-rays, which results in high-contrast radiographs of objects containing elements with low atomic numbers. In addition, the high yield of scintillation light enables fast X-ray imaging, which is an advantage for constructing CT images with low-energy X-rays.

Evaluating an image-fusion algorithm with synthetic-image-generation tools

NASA Astrophysics Data System (ADS)

Gross, Harry N.; Schott, John R.

1996-06-01

An algorithm that combines spectral mixing and nonlinear optimization is used to fuse multiresolution images. Image fusion merges images of different spatial and spectral resolutions to create a high spatial resolution multispectral combination. High spectral resolution allows identification of materials in the scene, while high spatial resolution locates those materials. In this algorithm, conventional spectral mixing estimates the percentage of each material (called endmembers) within each low resolution pixel. Three spectral mixing models are compared; unconstrained, partially constrained, and fully constrained. In the partially constrained application, the endmember fractions are required to sum to one. In the fully constrained application, all fractions are additionally required to lie between zero and one. While negative fractions seem inappropriate, they can arise from random spectral realizations of the materials. In the second part of the algorithm, the low resolution fractions are used as inputs to a constrained nonlinear optimization that calculates the endmember fractions for the high resolution pixels. The constraints mirror the low resolution constraints and maintain consistency with the low resolution fraction results. The algorithm can use one or more higher resolution sharpening images to locate the endmembers to high spatial accuracy. The algorithm was evaluated with synthetic image generation (SIG) tools. A SIG developed image can be used to control the various error sources that are likely to impair the algorithm performance. These error sources include atmospheric effects, mismodeled spectral endmembers, and variability in topography and illumination. By controlling the introduction of these errors, the robustness of the algorithm can be studied and improved upon. The motivation for this research is to take advantage of the next generation of multi/hyperspectral sensors. Although the hyperspectral images will be of modest to low resolution, fusing them with high resolution sharpening images will produce a higher spatial resolution land cover or material map.

High-resolution retinal imaging using adaptive optics and Fourier-domain optical coherence tomography

DOEpatents

Olivier, Scot S.; Werner, John S.; Zawadzki, Robert J.; Laut, Sophie P.; Jones, Steven M.

2010-09-07

This invention permits retinal images to be acquired at high speed and with unprecedented resolution in three dimensions (4.times.4.times.6 .mu.m). The instrument achieves high lateral resolution by using adaptive optics to correct optical aberrations of the human eye in real time. High axial resolution and high speed are made possible by the use of Fourier-domain optical coherence tomography. Using this system, we have demonstrated the ability to image microscopic blood vessels and the cone photoreceptor mosaic.

O-space with high resolution readouts outperforms radial imaging.

PubMed

Wang, Haifeng; Tam, Leo; Kopanoglu, Emre; Peters, Dana C; Constable, R Todd; Galiana, Gigi

2017-04-01

While O-Space imaging is well known to accelerate image acquisition beyond traditional Cartesian sampling, its advantages compared to undersampled radial imaging, the linear trajectory most akin to O-Space imaging, have not been detailed. In addition, previous studies have focused on ultrafast imaging with very high acceleration factors and relatively low resolution. The purpose of this work is to directly compare O-Space and radial imaging in their potential to deliver highly undersampled images of high resolution and minimal artifacts, as needed for diagnostic applications. We report that the greatest advantages to O-Space imaging are observed with extended data acquisition readouts. A sampling strategy that uses high resolution readouts is presented and applied to compare the potential of radial and O-Space sequences to generate high resolution images at high undersampling factors. Simulations and phantom studies were performed to investigate whether use of extended readout windows in O-Space imaging would increase k-space sampling and improve image quality, compared to radial imaging. Experimental O-Space images acquired with high resolution readouts show fewer artifacts and greater sharpness than radial imaging with equivalent scan parameters. Radial images taken with longer readouts show stronger undersampling artifacts, which can cause small or subtle image features to disappear. These features are preserved in a comparable O-Space image. High resolution O-Space imaging yields highly undersampled images of high resolution and minimal artifacts. The additional nonlinear gradient field improves image quality beyond conventional radial imaging. Copyright © 2016 Elsevier Inc. All rights reserved.

Enhancing SMAP Soil Moisture Retrievals via Superresolution Techniques

NASA Astrophysics Data System (ADS)

Beale, K. D.; Ebtehaj, A. M.; Romberg, J. K.; Bras, R. L.

2017-12-01

Soil moisture is a key state variable that modulates land-atmosphere interactions and its high-resolution global scale estimates are essential for improved weather forecasting, drought prediction, crop management, and the safety of troop mobility. Currently, NASA's Soil Moisture Active/Passive (SMAP) satellite provides a global picture of soil moisture variability at a resolution of 36 km, which is prohibitive for some hydrologic applications. The goal of this research is to enhance the resolution of SMAP passive microwave retrievals by a factor of 2 to 4 using modern superresolution techniques that rely on the knowledge of high-resolution land surface models. In this work, we explore several super-resolution techniques including an empirical dictionary method, a learned dictionary method, and a three-layer convolutional neural network. Using a year of global high-resolution land surface model simulations as training set, we found that we are able to produce high-resolution soil moisture maps that outperform the original low-resolution observations both qualitatively and quantitatively. In particular, on a patch-by-patch basis we are able to produce estimates of high-resolution soil moisture maps that improve on the original low-resolution patches by on average 6% in terms of mean-squared error, and 14% in terms of the structural similarity index.

Collection and Analysis of Crowd Data with Aerial, Rooftop, and Ground Views

DTIC Science & Technology

2014-11-10

collected these datasets using different aircrafts. Erista 8 HL OctaCopter is a heavy-lift aerial platform capable of using high-resolution cinema ...is another high-resolution camera that is cinema grade and high quality, with the capability of capturing videos with 4K resolution at 30 frames per...292.58 Imaging Systems and Accessories Blackmagic Production Camera 4 Crowd Counting using 4K Cameras High resolution cinema grade digital video

a Spiral-Based Downscaling Method for Generating 30 M Time Series Image Data

NASA Astrophysics Data System (ADS)

Liu, B.; Chen, J.; Xing, H.; Wu, H.; Zhang, J.

2017-09-01

The spatial detail and updating frequency of land cover data are important factors influencing land surface dynamic monitoring applications in high spatial resolution scale. However, the fragmentized patches and seasonal variable of some land cover types (e. g. small crop field, wetland) make it labor-intensive and difficult in the generation of land cover data. Utilizing the high spatial resolution multi-temporal image data is a possible solution. Unfortunately, the spatial and temporal resolution of available remote sensing data like Landsat or MODIS datasets can hardly satisfy the minimum mapping unit and frequency of current land cover mapping / updating at the same time. The generation of high resolution time series may be a compromise to cover the shortage in land cover updating process. One of popular way is to downscale multi-temporal MODIS data with other high spatial resolution auxiliary data like Landsat. But the usual manner of downscaling pixel based on a window may lead to the underdetermined problem in heterogeneous area, result in the uncertainty of some high spatial resolution pixels. Therefore, the downscaled multi-temporal data can hardly reach high spatial resolution as Landsat data. A spiral based method was introduced to downscale low spatial and high temporal resolution image data to high spatial and high temporal resolution image data. By the way of searching the similar pixels around the adjacent region based on the spiral, the pixel set was made up in the adjacent region pixel by pixel. The underdetermined problem is prevented to a large extent from solving the linear system when adopting the pixel set constructed. With the help of ordinary least squares, the method inverted the endmember values of linear system. The high spatial resolution image was reconstructed on the basis of high spatial resolution class map and the endmember values band by band. Then, the high spatial resolution time series was formed with these high spatial resolution images image by image. Simulated experiment and remote sensing image downscaling experiment were conducted. In simulated experiment, the 30 meters class map dataset Globeland30 was adopted to investigate the effect on avoid the underdetermined problem in downscaling procedure and a comparison between spiral and window was conducted. Further, the MODIS NDVI and Landsat image data was adopted to generate the 30m time series NDVI in remote sensing image downscaling experiment. Simulated experiment results showed that the proposed method had a robust performance in downscaling pixel in heterogeneous region and indicated that it was superior to the traditional window-based methods. The high resolution time series generated may be a benefit to the mapping and updating of land cover data.

Beyond Population Distribution: Enhancing Sociocultural Resolution from Remote Sensing

NASA Astrophysics Data System (ADS)

Bhaduri, B. L.; Rose, A.

2017-12-01

At Oak Ridge National Laboratory, since late 1990s, we have focused on developing high resolution population distribution and dynamics data from local to global scales. Increasing resolutions of geographic data has been mirrored by population data sets developed across the community. However, attempts to increase temporal and sociocultural resolutions have been limited given the lack of high resolution data on human settlements and activities. While recent advancements in moderate to high resolution earth observation have led to better physiographic data, the approach of exploiting very high resolution (sub-meter resolution) imagery has also proven useful for generating accurate human settlement maps. It allows potential (social and vulnerability) characterization of population from settlement structures by exploiting image texture and spectral features. Our recent research utilizing machine learning and geocomputation has not only validated "poverty mapping from imagery" hypothesis, but has delineated a new paradigm of rapid analysis of high resolution imagery to enhance such "neighborhood" mapping techniques. Such progress in GIScience is allowing us to move towards the goal of creating a global foundation level database for impervious surfaces and "neighborhoods," and holds tremendous promise for key applications focusing on sustainable development including many social science applications.

[Selection of distance thresholds of urban forest landscape connectivity in Shenyang City].

PubMed

Liu, Chang-fu; Zhou, Bin; He, Xing-yuan; Chen, Wei

2010-10-01

By using the QuickBird remote sensing image interpretation data of urban forests in Shenyang City in 2006, and with the help of geographical information system, this paper analyzed the landscape patches of the urban forests in the area inside the third ring-road of Shenyang. Based on the habitat availability and the dispersal potential of animal and plant species, 8 distance thresholds (50, 100, 200, 400, 600, 800, 1000, and 1200 m) were selected to compute the integral index of connectivity, probability of connectivity, and important value of the landscape patches, and the computed values were used for analyzing and screening the distance thresholds of urban forest landscape connectivity in the City. The results showed that the appropriate distance thresholds of the urban forest landscape connectivity in Shenyang City in 2006 ranged from 100 to 400 m, with 200 m being most appropriate. It was suggested that the distance thresholds should be increased or decreased according to the performability of urban forest landscape connectivity and the different demands for landscape levels.

Co-Registration Between Multisource Remote-Sensing Images

NASA Astrophysics Data System (ADS)

Wu, J.; Chang, C.; Tsai, H.-Y.; Liu, M.-C.

2012-07-01

Image registration is essential for geospatial information systems analysis, which usually involves integrating multitemporal and multispectral datasets from remote optical and radar sensors. An algorithm that deals with feature extraction, keypoint matching, outlier detection and image warping is experimented in this study. The methods currently available in the literature rely on techniques, such as the scale-invariant feature transform, between-edge cost minimization, normalized cross correlation, leasts-quares image matching, random sample consensus, iterated data snooping and thin-plate splines. Their basics are highlighted and encoded into a computer program. The test images are excerpts from digital files created by the multispectral SPOT-5 and Formosat-2 sensors, and by the panchromatic IKONOS and QuickBird sensors. Suburban areas, housing rooftops, the countryside and hilly plantations are studied. The co-registered images are displayed with block subimages in a criss-cross pattern. Besides the imagery, the registration accuracy is expressed by the root mean square error. Toward the end, this paper also includes a few opinions on issues that are believed to hinder a correct correspondence between diverse images.

High-resolution 3D imaging of polymerized photonic crystals by lab-based x-ray nanotomography with 50-nm resolution

NASA Astrophysics Data System (ADS)

Yin, Leilei; Chen, Ying-Chieh; Gelb, Jeff; Stevenson, Darren M.; Braun, Paul A.

2010-09-01

High resolution x-ray computed tomography is a powerful non-destructive 3-D imaging method. It can offer superior resolution on objects that are opaque or low contrast for optical microscopy. Synchrotron based x-ray computed tomography systems have been available for scientific research, but remain difficult to access for broader users. This work introduces a lab-based high-resolution x-ray nanotomography system with 50nm resolution in absorption and Zernike phase contrast modes. Using this system, we have demonstrated high quality 3-D images of polymerized photonic crystals which have been analyzed for band gap structures. The isotropic volumetric data shows excellent consistency with other characterization results.

High Resolution PET with 250 micrometer LSO Detectors and Adaptive Zoom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cherry, Simon R.; Qi, Jinyi

2012-01-08

There have been impressive improvements in the performance of small-animal positron emission tomography (PET) systems since their first development in the mid 1990s, both in terms of spatial resolution and sensitivity, which have directly contributed to the increasing adoption of this technology for a wide range of biomedical applications. Nonetheless, current systems still are largely dominated by the size of the scintillator elements used in the detector. Our research predicts that developing scintillator arrays with an element size of 250 {micro}m or smaller will lead to an image resolution of 500 {micro}m when using 18F- or 64Cu-labeled radiotracers, giving amore » factor of 4-8 improvement in volumetric resolution over the highest resolution research systems currently in existence. This proposal had two main objectives: (i) To develop and evaluate much higher resolution and efficiency scintillator arrays that can be used in the future as the basis for detectors in a small-animal PET scanner where the spatial resolution is dominated by decay and interaction physics rather than detector size. (ii) To optimize one such high resolution, high sensitivity detector and adaptively integrate it into the existing microPET II small animal PET scanner as a 'zoom-in' detector that provides higher spatial resolution and sensitivity in a limited region close to the detector face. The knowledge gained from this project will provide valuable information for building future PET systems with a complete ring of very high-resolution detector arrays and also lay the foundations for utilizing high-resolution detectors in combination with existing PET systems for localized high-resolution imaging.« less

The Impact of Horizontal and Temporal Resolution on Convection and Precipitation with High-Resolution GEOS-5

NASA Technical Reports Server (NTRS)

Putman, William P.

2012-01-01

Using a high-resolution non-hydrostatic version of GEOS-5 with the cubed-sphere finite-volume dynamical core, the impact of spatial and temporal resolution on cloud properties will be evaluated. There are indications from examining convective cluster development in high resolution GEOS-5 forecasts that the temporal resolution within the model may playas significant a role as horizontal resolution. Comparing modeled convective cloud clusters versus satellite observations of brightness temperature, we have found that improved. temporal resolution in GEOS-S accounts for a significant portion of the improvements in the statistical distribution of convective cloud clusters. Using satellite simulators in GEOS-S we will compare the cloud optical properties of GEOS-S at various spatial and temporal resolutions with those observed from MODIS. The potential impact of these results on tropical cyclone formation and intensity will be examined as well.

Recent applications of gas chromatography with high-resolution mass spectrometry.

PubMed

Špánik, Ivan; Machyňáková, Andrea

2018-01-01

Gas chromatography coupled to high-resolution mass spectrometry is a powerful analytical method that combines excellent separation power of gas chromatography with improved identification based on an accurate mass measurement. These features designate gas chromatography with high-resolution mass spectrometry as the first choice for identification and structure elucidation of unknown volatile and semi-volatile organic compounds. Gas chromatography with high-resolution mass spectrometry quantitative analyses was previously focused on the determination of dioxins and related compounds using magnetic sector type analyzers, a standing requirement of many international standards. The introduction of a quadrupole high-resolution time-of-flight mass analyzer broadened interest in this method and novel applications were developed, especially for multi-target screening purposes. This review is focused on the development and the most interesting applications of gas chromatography coupled to high-resolution mass spectrometry towards analysis of environmental matrices, biological fluids, and food safety since 2010. The main attention is paid to various approaches and applications of gas chromatography coupled to high-resolution mass spectrometry for non-target screening to identify contaminants and to characterize the chemical composition of environmental, food, and biological samples. The most interesting quantitative applications, where a significant contribution of gas chromatography with high-resolution mass spectrometry over the currently used methods is expected, will be discussed as well. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of high-resolution linear Radon transform for Rayleigh-wave dispersive energy imaging and mode separating

USGS Publications Warehouse

Luo, Y.; Xia, J.; Miller, R.D.; Liu, J.; Xu, Y.; Liu, Q.

2008-01-01

Multichannel Analysis of Surface Waves (MASW) analysis is an efficient tool to obtain the vertical shear-wave profile. One of the key steps in the MASW method is to generate an image of dispersive energy in the frequency-velocity domain, so dispersion curves can be determined by picking peaks of dispersion energy. In this paper, we image Rayleigh-wave dispersive energy and separate multimodes from a multichannel record by high-resolution linear Radon transform (LRT). We first introduce Rayleigh-wave dispersive energy imaging by high-resolution LRT. We then show the process of Rayleigh-wave mode separation. Results of synthetic and real-world examples demonstrate that (1) compared with slant stacking algorithm, high-resolution LRT can improve the resolution of images of dispersion energy by more than 50% (2) high-resolution LRT can successfully separate multimode dispersive energy of Rayleigh waves with high resolution; and (3) multimode separation and reconstruction expand frequency ranges of higher mode dispersive energy, which not only increases the investigation depth but also provides a means to accurately determine cut-off frequencies.

High resolution surface plasmon microscopy for cell imaging

NASA Astrophysics Data System (ADS)

Argoul, F.; Monier, K.; Roland, T.; Elezgaray, J.; Berguiga, L.

2010-04-01

We introduce a new non-labeling high resolution microscopy method for cellular imaging. This method called SSPM (Scanning Surface Plasmon Microscopy) pushes down the resolution limit of surface plasmon resonance imaging (SPRi) to sub-micronic scales. High resolution SPRi is obtained by the surface plasmon lauching with a high numerical aperture objective lens. The advantages of SPPM compared to other high resolution SPRi's rely on three aspects; (i) the interferometric detection of the back reflected light after plasmon excitation, (ii) the twodimensional scanning of the sample for image reconstruction, (iii) the radial polarization of light, enhancing both resolution and sensitivity. This microscope can afford a lateral resolution of - 150 nm in liquid environment and - 200 nm in air. We present in this paper images of IMR90 fibroblasts obtained with SSPM in dried environment. Internal compartments such as nucleus, nucleolus, mitochondria, cellular and nuclear membrane can be recognized without labelling. We propose an interpretation of the ability of SSPM to reveal high index contrast zones by a local decomposition of the V (Z) function describing the response of the SSPM.

High Resolution Mesoscale Weather Data Improvement to Spatial Effects for Dose-Rate Contour Plot Predictions

DTIC Science & Technology

2007-03-01

time. This is a very powerful tool in determining fine spatial resolution , as boundary conditions are not only updated at every timestep, but the ...HIGH RESOLUTION MESOSCALE WEATHER DATA IMPROVEMENT TO SPATIAL EFFECTS FOR DOSE-RATE CONTOUR PLOT PREDICTIONS THESIS Christopher P...11 1 HIGH RESOLUTION MESOSCALE WEATHER DATA IMPROVEMENT TO SPATIAL EFFECTS FOR DOSE-RATE CONTOUR PLOT

The influence of spatially and temporally high-resolution wind forcing on the power input to near-inertial waves in the ocean

NASA Astrophysics Data System (ADS)

Rimac, Antonija; von Storch, Jin-Song; Eden, Carsten

2013-04-01

The estimated power required to sustain global general circulation in the ocean is about 2 TW. This power is supplied with wind stress and tides. Energy spectrum shows pronounced maxima at near-inertial frequency. Near-inertial waves excited by high-frequency winds represent an important source for deep ocean mixing since they can propagate into the deep ocean and dissipate far away from the generation sites. The energy input by winds to near-inertial waves has been studied mostly using slab ocean models and wind stress forcing with coarse temporal resolution (e.g. 6-hourly). Slab ocean models lack the ability to reproduce fundamental aspects of kinetic energy balance and systematically overestimate the wind work. Also, slab ocean models do not account the energy used for the mixed layer deepening or the energy radiating downward into the deep ocean. Coarse temporal resolution of the wind forcing strongly underestimates the near-inertial energy. To overcome this difficulty we use an eddy permitting ocean model with high-frequency wind forcing. We establish the following model setup: We use the Max Planck Institute Ocean Model (MPIOM) on a tripolar grid with 45 km horizontal resolution and 40 vertical levels. We run the model with wind forcings that vary in horizontal and temporal resolution. We use high-resolution (1-hourly with 35 km horizontal resolution) and low-resolution winds (6-hourly with 250 km horizontal resolution). We address the following questions: Is the kinetic energy of near-inertial waves enhanced when high-resolution wind forcings are used? If so, is this due to higher level of overall wind variability or higher spatial or temporal resolution of wind forcing? How large is the power of near-inertial waves generated by winds? Our results show that near-inertial waves are enhanced and the near-inertial kinetic energy is two times higher (in the storm track regions 3.5 times higher) when high-resolution winds are used. Filtering high-resolution winds in space and time, the near-inertial kinetic energy reduces. The reduction is faster when a temporal filter is used suggesting that the high-frequency wind forcing is more efficient in generating near-inertial wave energy than the small-scale wind forcing. Using low-resolution wind forcing the wind generated power to near-inertial waves is 0.55 TW. When we use high-resolution wind forcing the result is 1.6 TW meaning that the result increases by 300%.

High-resolution anoscopy or expectant management for anal intraepithelial neoplasia for the prevention of anal cancer: is there really a difference?

PubMed

Crawshaw, Benjamin P; Russ, Andrew J; Stein, Sharon L; Reynolds, Harry L; Marderstein, Eric L; Delaney, Conor P; Champagne, Bradley J

2015-01-01

High-resolution anoscopy has been shown to improve identification of anal intraepithelial neoplasia but a reduction in progression to anal squamous-cell cancer has not been substantiated when serial high-resolution anoscopy is compared with traditional expectant management. The aim of this study was to compare high-resolution anoscopy versus expectant management for the surveillance of anal intraepithelial neoplasia and the prevention of anal cancer. This is a retrospective review of all patients who presented with anal squamous dysplasia, positive anal Pap smears, or anal squamous-cell cancer from 2007 to 2013. This study was performed in the colorectal department of a university-affiliated, tertiary care hospital. Included patients had biopsy-proven anal intraepithelial neoplasia from 2007 to 2013. Patients were treated with high-resolution anoscopy with ablation or standard anoscopy with ablation. Both groups were treated with imiquimod and followed every 6 months indefinitely. The incidence of anal squamous-cell cancer in each group was the primary end point. From 2007 to 2013, 424 patients with anal squamous dysplasia were seen in the clinic (high-resolution anoscopy, 220; expectant management, 204). Three patients (high-resolution anoscopy, 1; expectant management, 2) progressed to anal squamous-cell cancer; 2 were noncompliant with follow-up and with HIV treatment, and the third was allergic to imiquimod and refused to take topical 5-fluorouracil. The 5-year progression rate was 6.0% (95% CI, 1.5-24.6) for expectant management and 4.5% (95% CI, 0.7-30.8) for high-resolution anoscopy (p = 0.37). This was a retrospective review. There is potential for selection and referral bias. Because of the rarity of the outcome, the study may be underpowered. Patients with squamous-cell dysplasia followed with expectant management or high-resolution anoscopy rarely develop squamous-cell cancer if they are compliant with the protocol. The cost, morbidity, and value of high-resolution anoscopy should be further evaluated in lieu of these findings.

Urban-scale mapping of PM2.5 distribution via data fusion between high-density sensor network and MODIS Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei

2017-04-01

High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.

An integrated use of topography with RSI in gully mapping, Shandong Peninsula, China.

PubMed

He, Fuhong; Wang, Tao; Gu, Lijuan; Li, Tao; Jiang, Weiguo; Shao, Hongbo

2014-01-01

Taking the Quickbird optical satellite imagery of the small watershed of Beiyanzigou valley of Qixia city, Shandong province, as the study data, we proposed a new method by using a fused image of topography with remote sensing imagery (RSI) to achieve a high precision interpretation of gully edge lines. The technique first transformed remote sensing imagery into HSV color space from RGB color space. Then the slope threshold values of gully edge line and gully thalweg were gained through field survey and the slope data were segmented using thresholding, respectively. Based on the fused image in combination with gully thalweg thresholding vectors, the gully thalweg thresholding vectors were amended. Lastly, the gully edge line might be interpreted based on the amended gully thalweg vectors, fused image, gully edge line thresholding vectors, and slope data. A testing region was selected in the study area to assess the accuracy. Then accuracy assessment of the gully information interpreted by both interpreting remote sensing imagery only and the fused image was performed using the deviation, kappa coefficient, and overall accuracy of error matrix. Compared with interpreting remote sensing imagery only, the overall accuracy and kappa coefficient are increased by 24.080% and 264.364%, respectively. The average deviations of gully head and gully edge line are reduced by 60.448% and 67.406%, respectively. The test results show the thematic and the positional accuracy of gully interpreted by new method are significantly higher. Finally, the error sources for interpretation accuracy by the two methods were analyzed.

An Integrated Use of Topography with RSI in Gully Mapping, Shandong Peninsula, China

PubMed Central

He, Fuhong; Wang, Tao; Gu, Lijuan; Li, Tao; Jiang, Weiguo; Shao, Hongbo

2014-01-01

Taking the Quickbird optical satellite imagery of the small watershed of Beiyanzigou valley of Qixia city, Shandong province, as the study data, we proposed a new method by using a fused image of topography with remote sensing imagery (RSI) to achieve a high precision interpretation of gully edge lines. The technique first transformed remote sensing imagery into HSV color space from RGB color space. Then the slope threshold values of gully edge line and gully thalweg were gained through field survey and the slope data were segmented using thresholding, respectively. Based on the fused image in combination with gully thalweg thresholding vectors, the gully thalweg thresholding vectors were amended. Lastly, the gully edge line might be interpreted based on the amended gully thalweg vectors, fused image, gully edge line thresholding vectors, and slope data. A testing region was selected in the study area to assess the accuracy. Then accuracy assessment of the gully information interpreted by both interpreting remote sensing imagery only and the fused image was performed using the deviation, kappa coefficient, and overall accuracy of error matrix. Compared with interpreting remote sensing imagery only, the overall accuracy and kappa coefficient are increased by 24.080% and 264.364%, respectively. The average deviations of gully head and gully edge line are reduced by 60.448% and 67.406%, respectively. The test results show the thematic and the positional accuracy of gully interpreted by new method are significantly higher. Finally, the error sources for interpretation accuracy by the two methods were analyzed. PMID:25302333

Glacier changes in the Nanga Parbat Himalayas: a re-photographic survey between the 1930s and now

NASA Astrophysics Data System (ADS)

Schmidt, S.; Nüsser, M.

2009-04-01

In contrast to the relatively well investigated glacier and landscape changes in the mountains of Europe and North America, very little investigations and documentations using repeat photography have been undertaken in the Himalayas and other high mountain regions of Asia. The present study seeks to investigate glacier and landscape changes in the Nanga Parbat region (NW-Himalaya) using a multi-temporal and multi-spatial approach which is based on terrestrial repeat photography and remote sensing data. A comprehensive collection of historical landscape photographs, taken by members of the German Himalaya expeditions 1934 and 1937, forms a valuable baseline data set for the area. Recent fieldwork made it possible to repeat a large number of these photographs viewpoints identical to the earlier ones, and the direct comparisons illustrate glacier dynamics and landscape changes over a span of seventy years. Furthermore, in order to fill the temporal gap and to analyze temporal and spatial dynamics of glaciers over the last 40 years we use different satellite sensors (Corona, Aster, Landsat, Spot, QuickBird). First investigations were carried out at the Raikot Glacier, which is located at the northern declivity of the Nanga Parbat, the ninth highest peak on earth. The multi-temporal comparison detects only small down-wasting rates of the Raikot Glacier over the last 70 years and a retreat of the terminus of about 250 m which is characterized by great fluctuations. Based on this multi-temporal and multi-data approach, we will detect and analyze glacier and landscape changes in the whole Nanga Parbat region.

Drivers of tall shrub proliferation adjacent to the Dempster Highway, Northwest Territories, Canada

NASA Astrophysics Data System (ADS)

Cameron, Emily A.; Lantz, Trevor C.

2016-04-01

Arctic ecosystems are undergoing rapid changes as a result of climate warming and more frequent disturbances. Disturbances can have particularly large effects on high-latitude ecosystems when ecosystem structure and function is controlled by strong feedbacks between soil conditions, vegetation, and ground thermal regime. In this study we investigated the impact of road construction and maintenance on vegetation structure and biomass along the Dempster Highway where it crosses the Peel Plateau in the Northwest Territories. To explore drivers of tall shrub proliferation and to quantify shrub proliferation in this region of continuous permafrost, greyscale air photos (1975) and Quickbird satellite imagery (2008) were used to map landcover change within two 0.6 km2 belts next to the road and two 0.6 km2 belts 500 m away from the road. Maps showing areas where: 1) tall shrubs expanded, and 2) dwarf shrub tundra resisted invasion were then used to select field sites where a suite of biophysical variables were measured. Rapid tall shrub proliferation and greater biomass adjacent to the road indicate that disturbance can facilitate vegetation change in tundra environments. Our field data also suggests that increased shrub proliferation adjacent to the road was caused by greater soil moisture. Tall shrub proliferation adjacent to the road occurred at lower elevation sites characterized by wetter soils with thicker organic layers. Areas that resisted tall shrub encroachment were located at higher elevations and had drier soils with thin organic layers. Our observations also support previous work illustrating that tall shrub expansion next to the highway promotes strong positive feedbacks to ongoing shrub growth and proliferation.

A generic framework for internet-based interactive applications of high-resolution 3-D medical image data.

PubMed

Liu, Danzhou; Hua, Kien A; Sugaya, Kiminobu

2008-09-01

With the advances in medical imaging devices, large volumes of high-resolution 3-D medical image data have been produced. These high-resolution 3-D data are very large in size, and severely stress storage systems and networks. Most existing Internet-based 3-D medical image interactive applications therefore deal with only low- or medium-resolution image data. While it is possible to download the whole 3-D high-resolution image data from the server and perform the image visualization and analysis at the client site, such an alternative is infeasible when the high-resolution data are very large, and many users concurrently access the server. In this paper, we propose a novel framework for Internet-based interactive applications of high-resolution 3-D medical image data. Specifically, we first partition the whole 3-D data into buckets, remove the duplicate buckets, and then, compress each bucket separately. We also propose an index structure for these buckets to efficiently support typical queries such as 3-D slicer and region of interest, and only the relevant buckets are transmitted instead of the whole high-resolution 3-D medical image data. Furthermore, in order to better support concurrent accesses and to improve the average response time, we also propose techniques for efficient query processing, incremental transmission, and client sharing. Our experimental study in simulated and realistic environments indicates that the proposed framework can significantly reduce storage and communication requirements, and can enable real-time interaction with remote high-resolution 3-D medical image data for many concurrent users.

Computation of high-resolution SAR distributions in a head due to a radiating dipole antenna representing a hand-held mobile phone.

PubMed

Van de Kamer, J B; Lagendijk, J J W

2002-05-21

SAR distributions in a healthy female adult head as a result of a radiating vertical dipole antenna (frequency 915 MHz) representing a hand-held mobile phone have been computed for three different resolutions: 2 mm, 1 mm and 0.4 mm. The extremely high resolution of 0.4 mm was obtained with our quasistatic zooming technique, which is briefly described in this paper. For an effectively transmitted power of 0.25 W, the maximum averaged SAR values in both cubic- and arbitrary-shaped volumes are, respectively, about 1.72 and 2.55 W kg(-1) for 1 g and 0.98 and 1.73 W kg(-1) for 10 g of tissue. These numbers do not vary much (<8%) for the different resolutions, indicating that SAR computations at a resolution of 2 mm are sufficiently accurate to describe the large-scale distribution. However, considering the detailed SAR pattern in the head, large differences may occur if high-resolution computations are performed rather than low-resolution ones. These deviations are caused by both increased modelling accuracy and improved anatomical description in higher resolution simulations. For example, the SAR profile across a boundary between tissues with high dielectric contrast is much more accurately described at higher resolutions. Furthermore, low-resolution dielectric geometries may suffer from loss of anatomical detail, which greatly affects small-scale SAR distributions. Thus. for strongly inhomogeneous regions high-resolution SAR modelling is an absolute necessity.

SPARTAN II: An Instructional High Resolution Land Combat Model

DTIC Science & Technology

1993-03-01

93M-09 SPARTAN II: AN INSTRUCTIONAL HIGH RESOLUTION LAND COMBAT MODEL THESIS DWquALfl’ 4 Presented to the Faculty of the School of Engineering of the...ADVISOR NAJ Edward Negrelli/ENS REALDER MAJ Bruce Marl an/MA LD1 { The goal of this thesis was to improve SPARTAN, a high resolution land combat model...should serve as a useful tool for learning about the advantages and disadvantages of high resolution combat modeling. I wish to thank I4AJ Edward

High-Resolution Array with Prony, MUSIC, and ESPRIT Algorithms

DTIC Science & Technology

1992-08-25

N avalI Research La bora tory AD-A255 514 Washington, DC 20375-5320 NRL/FR/5324-92-9397 High-resolution Array with Prony, music , and ESPRIT...unlimited t"orm n pprovoiREPORT DOCUMENTATION PAGE OMB. o 0 104 0188 4. TITLE AND SUBTITLE S. FUNDING NUMBERS High-resolution Array with Prony. MUSIC . and...the array high-resolution properties of three algorithms: the Prony algo- rithm, the MUSIC algorithm, and the ESPRIT algorithm. MUSIC has been much

High efficiency multishot interleaved spiral-in/out: acquisition for high-resolution BOLD fMRI.

PubMed

Jung, Youngkyoo; Samsonov, Alexey A; Liu, Thomas T; Buracas, Giedrius T

2013-08-01

Growing demand for high spatial resolution blood oxygenation level dependent (BOLD) functional magnetic resonance imaging faces a challenge of the spatial resolution versus coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in/out trajectory is preferred over spiral-in due to increased BOLD signal contrast-to-noise ratio (CNR) and higher acquisition efficiency than that of spiral-out or noninterleaved spiral in/out trajectories (Law & Glover. Magn Reson Med 2009; 62:829-834.), but to date applicability of the multishot interleaved spiral in/out for high spatial resolution imaging has not been studied. Herein we propose multishot interleaved spiral in/out acquisition and investigate its applicability for high spatial resolution BOLD functional magnetic resonance imaging. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2 decay, off-resonance, and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in/out pulse sequence yields high BOLD CNR images at in-plane resolution below 1 × 1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multishot interleaved spiral in/out acquisition is a promising technique for high spatial resolution BOLD functional magnetic resonance imaging applications. © 2012 Wiley Periodicals, Inc.

Introducing Graduate Students to High-Resolution Mass Spectrometry (HRMS) Using a Hands-On Approach

ERIC Educational Resources Information Center

Stock, Naomi L.

2017-01-01

High-resolution mass spectrometry (HRMS) features both high resolution and high mass accuracy and is a powerful tool for the analysis and quantitation of compounds, determination of elemental compositions, and identification of unknowns. A hands-on laboratory experiment for upper-level undergraduate and graduate students to investigate HRMS is…

Transmission/Scanning Transmission Electron Microscopy | Materials Science

Science.gov Websites

imaging such as high resolution TEM. Transmission electron diffraction patterns help to determine the microstructure of a material and its defects. Phase-contrast imaging or high-resolution (HR) TEM imaging gives high scattering angle can be collected to form high-resolution, chemically sensitive, atomic number (Z

NREL: International Activities - Pakistan Resource Maps

Science.gov Websites

. The high-resolution (1-km) annual wind power maps were developed using a numerical modeling approach along with NREL's empirical validation methodology. The high-resolution (10-km) annual and seasonal KB) | High-Res (ZIP 281 KB) 40-km Resolution Annual Maps (Direct) Low-Res (JPG 156 KB) | High-Res

A high resolution on-chip delay sensor with low supply-voltage sensitivity for high-performance electronic systems.

PubMed

Sheng, Duo; Lai, Hsiu-Fan; Chan, Sheng-Min; Hong, Min-Rong

2015-02-13

An all-digital on-chip delay sensor (OCDS) circuit with high delay-measurement resolution and low supply-voltage sensitivity for efficient detection and diagnosis in high-performance electronic system applications is presented. Based on the proposed delay measurement scheme, the quantization resolution of the proposed OCDS can be reduced to several picoseconds. Additionally, the proposed cascade-stage delay measurement circuit can enhance immunity to supply-voltage variations of the delay measurement resolution without extra self-biasing or calibration circuits. Simulation results show that the delay measurement resolution can be improved to 1.2 ps; the average delay resolution variation is 0.55% with supply-voltage variations of ±10%. Moreover, the proposed delay sensor can be implemented in an all-digital manner, making it very suitable for high-performance electronic system applications as well as system-level integration.

Basilar artery atherosclerotic plaques in paramedian and lacunar pontine infarctions: a high-resolution MRI study.

PubMed

Klein, Isabelle F; Lavallée, Philippa C; Mazighi, Mikael; Schouman-Claeys, Elisabeth; Labreuche, Julien; Amarenco, Pierre

2010-07-01

Pontine infarction is most often related to basilar artery atherosclerosis when the lesion abuts on the basal surface (paramedian pontine infarction), whereas small medial pontine lesion is usually attributed to small vessel lipohyalinosis. A previous study has found that high-resolution MRI can detect basilar atherosclerotic plaques in up to 70% of patient with paramedian pontine infarction, even in patients with normal angiograms, but none has evaluated the presence of basilar artery plaque by high-resolution MRI in patients with small medial pontine lesion in the medial part of the pons. Consecutive patients with pontine infarction underwent basilar angiography using time-of-flight and contrast-enhanced 3-dimensional MR angiography to assess the presence of basilar artery stenosis and high-resolution MRI to assess the presence of atherosclerotic plaque. Basilar artery angiogram was scored as "normal," "irregular," or "stenosed" >or=30%" and basilar artery by high-resolution MRI was scored as "normal" or "presence of plaque." Medial pontine infarcts were divided into paramedian pontine infarction and small medial pontine lesion groups. Forty-one patients with pontine infarction were included, 26 with paramedian pontine infarction and 15 with small medial pontine lesion. High-resolution MRI detected basilar artery atherosclerosis in 42% of patients with a pontine infarction and normal basilar angiograms. Among patients with paramedian pontine infarction, 65% had normal basilar angiograms but 77% had basilar artery atherosclerosis detected on high-resolution MRI. Among patients with small medial pontine lesion, 46% had normal basilar angiograms but 73% had basilar artery plaques detected on by high-resolution MRI. This study suggests that medial pontine lacunes may be due to a penetrating artery disease secondary to basilar artery atherosclerosis. High-resolution MRI could help precise stroke subtyping.

High-resolution observations of the near-surface wind field over an isolated mountain and in a steep river canyon

Treesearch

B. W. Butler; N. S. Wagenbrenner; J. M. Forthofer; B. K. Lamb; K. S. Shannon; D. Finn; R. M. Eckman; K. Clawson; L. Bradshaw; P. Sopko; S. Beard; D. Jimenez; C. Wold; M. Vosburgh

2015-01-01

A number of numerical wind flow models have been developed for simulating wind flow at relatively fine spatial resolutions (e.g., 100 m); however, there are very limited observational data available for evaluating these high-resolution models. This study presents high-resolution surface wind data sets collected from an isolated mountain and a steep river canyon. The...

Data Descriptor: TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

Treesearch

John T. Abatzoglou; Solomon Z. Dobrowski; Sean A. Parks; Katherine C. Hegewisch

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from...

Assessment of a vertical high-resolution distributed-temperature-sensing system in a shallow thermohaline environment

NASA Astrophysics Data System (ADS)

Suárez, F.; Aravena, J. E.; Hausner, M. B.; Childress, A. E.; Tyler, S. W.

2011-03-01

In shallow thermohaline-driven lakes it is important to measure temperature on fine spatial and temporal scales to detect stratification or different hydrodynamic regimes. Raman spectra distributed temperature sensing (DTS) is an approach available to provide high spatial and temporal temperature resolution. A vertical high-resolution DTS system was constructed to overcome the problems of typical methods used in the past, i.e., without disturbing the water column, and with resistance to corrosive environments. This paper describes a method to quantitatively assess accuracy, precision and other limitations of DTS systems to fully utilize the capacity of this technology, with a focus on vertical high-resolution to measure temperatures in shallow thermohaline environments. It also presents a new method to manually calibrate temperatures along the optical fiber achieving significant improved resolution. The vertical high-resolution DTS system is used to monitor the thermal behavior of a salt-gradient solar pond, which is an engineered shallow thermohaline system that allows collection and storage of solar energy for a long period of time. The vertical high-resolution DTS system monitors the temperature profile each 1.1 cm vertically and in time averages as small as 10 s. Temperature resolution as low as 0.035 °C is obtained when the data are collected at 5-min intervals.

High axial resolution imaging system for large volume tissues using combination of inclined selective plane illumination and mechanical sectioning

PubMed Central

Zhang, Qi; Yang, Xiong; Hu, Qinglei; Bai, Ke; Yin, Fangfang; Li, Ning; Gang, Yadong; Wang, Xiaojun; Zeng, Shaoqun

2017-01-01

To resolve fine structures of biological systems like neurons, it is required to realize microscopic imaging with sufficient spatial resolution in three dimensional systems. With regular optical imaging systems, high lateral resolution is accessible while high axial resolution is hard to achieve in a large volume. We introduce an imaging system for high 3D resolution fluorescence imaging of large volume tissues. Selective plane illumination was adopted to provide high axial resolution. A scientific CMOS working in sub-array mode kept the imaging area in the sample surface, which restrained the adverse effect of aberrations caused by inclined illumination. Plastic embedding and precise mechanical sectioning extended the axial range and eliminated distortion during the whole imaging process. The combination of these techniques enabled 3D high resolution imaging of large tissues. Fluorescent bead imaging showed resolutions of 0.59 μm, 0.47μm, and 0.59 μm in the x, y, and z directions, respectively. Data acquired from the volume sample of brain tissue demonstrated the applicability of this imaging system. Imaging of different depths showed uniform performance where details could be recognized in either the near-soma area or terminal area, and fine structures of neurons could be seen in both the xy and xz sections. PMID:29296503

High resolution land surface geophysical parameters estimation from ALOS PALSAR data

USDA-ARS?s Scientific Manuscript database

High resolution land surface geophysical products, such as soil moisture, surface roughness and vegetation water content, are essential for a variety of applications ranging from water management to regional climate predictions. In India high resolution geophysical products, in particular soil moist...

Automatic optimization high-speed high-resolution OCT retinal imaging at 1μm

NASA Astrophysics Data System (ADS)

Cua, Michelle; Liu, Xiyun; Miao, Dongkai; Lee, Sujin; Lee, Sieun; Bonora, Stefano; Zawadzki, Robert J.; Mackenzie, Paul J.; Jian, Yifan; Sarunic, Marinko V.

2015-03-01

High-resolution OCT retinal imaging is important in providing visualization of various retinal structures to aid researchers in better understanding the pathogenesis of vision-robbing diseases. However, conventional optical coherence tomography (OCT) systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking optical coherence tomography (OCT) system with automatic optimization for high-resolution, extended-focal-range clinical retinal imaging. A variable-focus liquid lens was added to correct for de-focus in real-time. A GPU-accelerated segmentation and optimization was used to provide real-time layer-specific enface visualization as well as depth-specific focus adjustment. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the ONH, from which we extracted clinically-relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

Single-shot and single-sensor high/super-resolution microwave imaging based on metasurface.

PubMed

Wang, Libo; Li, Lianlin; Li, Yunbo; Zhang, Hao Chi; Cui, Tie Jun

2016-06-01

Real-time high-resolution (including super-resolution) imaging with low-cost hardware is a long sought-after goal in various imaging applications. Here, we propose broadband single-shot and single-sensor high-/super-resolution imaging by using a spatio-temporal dispersive metasurface and an imaging reconstruction algorithm. The metasurface with spatio-temporal dispersive property ensures the feasibility of the single-shot and single-sensor imager for super- and high-resolution imaging, since it can convert efficiently the detailed spatial information of the probed object into one-dimensional time- or frequency-dependent signal acquired by a single sensor fixed in the far-field region. The imaging quality can be improved by applying a feature-enhanced reconstruction algorithm in post-processing, and the desired imaging resolution is related to the distance between the object and metasurface. When the object is placed in the vicinity of the metasurface, the super-resolution imaging can be realized. The proposed imaging methodology provides a unique means to perform real-time data acquisition, high-/super-resolution images without employing expensive hardware (e.g. mechanical scanner, antenna array, etc.). We expect that this methodology could make potential breakthroughs in the areas of microwave, terahertz, optical, and even ultrasound imaging.

Imaging whole mouse brains with a dual resolution serial swept-source optical coherence tomography scanner

NASA Astrophysics Data System (ADS)

Lefebvre, Joël.; Castonguay, Alexandre; Lesage, Frédéric

2018-02-01

High resolution imaging of whole rodent brains using serial OCT scanners is a promising method to investigate microstructural changes in tissue related to the evolution of neuropathologies. Although micron to sub-micron sampling resolution can be obtained by using high numerical aperture objectives and dynamic focusing, such an imaging system is not adapted to whole brain imaging. This is due to the large amount of data it generates and the significant computational resources required for reconstructing such volumes. To address this limitation, a dual resolution serial OCT scanner was developed. The optical setup consists in a swept-source OCT made of two sample and reference arms, each arm being coupled with different microscope objectives (3X / 40X). Motorized flip mirrors were used to switch between each OCT arm, thus allowing low and high resolution acquisitions within the same sample. The low resolution OCT volumes acquired with the 3X arm were stitched together, providing a 3D map of the whole mouse brain. This brain can be registered to an OCT brain template to enable neurological structures localization. The high resolution volumes acquired with the 40X arm were also stitched together to create local high resolution 3D maps of the tissue microstructure. The 40X data can be acquired at any arbitrary location in the sample, thus limiting storage-heavy high resolution data to application restricted to specific regions of interest. By providing dual-resolution OCT data, this setup can be used to validate diffusion MRI with tissue microstructure derived metrics measured at any location in ex vivo brains.

A compact high-resolution 3-D imaging spectrometer for discovering Oases on Mars

USGS Publications Warehouse

Ge, J.; Ren, D.; Lunine, J.I.; Brown, R.H.; Yelle, R.V.; Soderblom, L.A.; ,

2002-01-01

A new design for a very lightweight, very high throughput reflectance sectrometer enabled by two new technologies being developed is presented. These new technologies include integral field unit optics to enable simultaneous imaging and spectroscopy at high spatial resolution with an infrared (IR) array, and silicon grisms to enable compact and high-resolution spectroscopy.

High-spatial resolution and high-spectral resolution detector for use in the measurement of solar flare hard X-rays

NASA Technical Reports Server (NTRS)

Desai, U. D.; Orwig, Larry E.

1988-01-01

In the areas of high spatial resolution, the evaluation of a hard X-ray detector with 65 micron spatial resolution for operation in the energy range from 30 to 400 keV is proposed. The basic detector is a thick large-area scintillator faceplate, composed of a matrix of high-density scintillating glass fibers, attached to a proximity type image intensifier tube with a resistive-anode digital readout system. Such a detector, combined with a coded-aperture mask, would be ideal for use as a modest-sized hard X-ray imaging instrument up to X-ray energies as high as several hundred keV. As an integral part of this study it was also proposed that several techniques be critically evaluated for X-ray image coding which could be used with this detector. In the area of high spectral resolution, it is proposed to evaluate two different types of detectors for use as X-ray spectrometers for solar flares: planar silicon detectors and high-purity germanium detectors (HPGe). Instruments utilizing these high-spatial-resolution detectors for hard X-ray imaging measurements from 30 to 400 keV and high-spectral-resolution detectors for measurements over a similar energy range would be ideally suited for making crucial solar flare observations during the upcoming maximum in the solar cycle.

Application of Super-Resolution Convolutional Neural Network for Enhancing Image Resolution in Chest CT.

PubMed

Umehara, Kensuke; Ota, Junko; Ishida, Takayuki

2017-10-18

In this study, the super-resolution convolutional neural network (SRCNN) scheme, which is the emerging deep-learning-based super-resolution method for enhancing image resolution in chest CT images, was applied and evaluated using the post-processing approach. For evaluation, 89 chest CT cases were sampled from The Cancer Imaging Archive. The 89 CT cases were divided randomly into 45 training cases and 44 external test cases. The SRCNN was trained using the training dataset. With the trained SRCNN, a high-resolution image was reconstructed from a low-resolution image, which was down-sampled from an original test image. For quantitative evaluation, two image quality metrics were measured and compared to those of the conventional linear interpolation methods. The image restoration quality of the SRCNN scheme was significantly higher than that of the linear interpolation methods (p < 0.001 or p < 0.05). The high-resolution image reconstructed by the SRCNN scheme was highly restored and comparable to the original reference image, in particular, for a ×2 magnification. These results indicate that the SRCNN scheme significantly outperforms the linear interpolation methods for enhancing image resolution in chest CT images. The results also suggest that SRCNN may become a potential solution for generating high-resolution CT images from standard CT images.

Breaking the acoustic diffraction limit via nonlinear effect and thermal confinement for potential deep-tissue high-resolution imaging

PubMed Central

Yuan, Baohong; Pei, Yanbo; Kandukuri, Jayanth

2013-01-01

Our recently developed ultrasound-switchable fluorescence (USF) imaging technique showed that it was feasible to conduct high-resolution fluorescence imaging in a centimeter-deep turbid medium. Because the spatial resolution of this technique highly depends on the ultrasound-induced temperature focal size (UTFS), minimization of UTFS becomes important for further improving the spatial resolution USF technique. In this study, we found that UTFS can be significantly reduced below the diffraction-limited acoustic intensity focal size via nonlinear acoustic effects and thermal confinement by appropriately controlling ultrasound power and exposure time, which can be potentially used for deep-tissue high-resolution imaging. PMID:23479498

Mesosacle eddies in a high resolution OGCM and coupled ocean-atmosphere GCM

NASA Astrophysics Data System (ADS)

Yu, Y.; Liu, H.; Lin, P.

2017-12-01

The present study described high-resolution climate modeling efforts including oceanic, atmospheric and coupled general circulation model (GCM) at the state key laboratory of numerical modeling for atmospheric sciences and geophysical fluid dynamics (LASG), Institute of Atmospheric Physics (IAP). The high-resolution OGCM is established based on the latest version of the LASG/IAP Climate system Ocean Model (LICOM2.1), but its horizontal resolution and vertical resolution are increased to 1/10° and 55 layers, respectively. Forced by the surface fluxes from the reanalysis and observed data, the model has been integrated for approximately more than 80 model years. Compared with the simulation of the coarse-resolution OGCM, the eddy-resolving OGCM not only better simulates the spatial-temporal features of mesoscale eddies and the paths and positions of western boundary currents but also reproduces the large meander of the Kuroshio Current and its interannual variability. Another aspect, namely, the complex structures of equatorial Pacific currents and currents in the coastal ocean of China, are better captured due to the increased horizontal and vertical resolution. Then we coupled the high resolution OGCM to NCAR CAM4 with 25km resolution, in which the mesoscale air-sea interaction processes are better captured.

Human brain diffusion tensor imaging at submillimeter isotropic resolution on a 3 Tesla clinical MRI scanner

PubMed Central

Chang, Hing-Chiu; Sundman, Mark; Petit, Laurent; Guhaniyogi, Shayan; Chu, Mei-Lan; Petty, Christopher; Song, Allen W.; Chen, Nan-kuei

2015-01-01

The advantages of high-resolution diffusion tensor imaging (DTI) have been demonstrated in a recent post-mortem human brain study (Miller et al., NeuroImage 2011;57(1):167–181), showing that white matter fiber tracts can be much more accurately detected in data at submillimeter isotropic resolution. To our knowledge, in vivo human brain DTI at submillimeter isotropic resolution has not been routinely achieved yet because of the difficulty in simultaneously achieving high resolution and high signal-to-noise ratio (SNR) in DTI scans. Here we report a 3D multi-slab interleaved EPI acquisition integrated with multiplexed sensitivity encoded (MUSE) reconstruction, to achieve high-quality, high-SNR and submillimeter isotropic resolution (0.85 × 0.85 × 0.85 mm3) in vivo human brain DTI on a 3 Tesla clinical MRI scanner. In agreement with the previously reported post-mortem human brain DTI study, our in vivo data show that the structural connectivity networks of human brains can be mapped more accurately and completely with high-resolution DTI as compared with conventional DTI (e.g., 2 × 2 × 2 mm3). PMID:26072250

High-resolution dynamic 31 P-MRSI using a low-rank tensor model.

PubMed

Ma, Chao; Clifford, Bryan; Liu, Yuchi; Gu, Yuning; Lam, Fan; Yu, Xin; Liang, Zhi-Pei

2017-08-01

To develop a rapid 31 P-MRSI method with high spatiospectral resolution using low-rank tensor-based data acquisition and image reconstruction. The multidimensional image function of 31 P-MRSI is represented by a low-rank tensor to capture the spatial-spectral-temporal correlations of data. A hybrid data acquisition scheme is used for sparse sampling, which consists of a set of "training" data with limited k-space coverage to capture the subspace structure of the image function, and a set of sparsely sampled "imaging" data for high-resolution image reconstruction. An explicit subspace pursuit approach is used for image reconstruction, which estimates the bases of the subspace from the "training" data and then reconstructs a high-resolution image function from the "imaging" data. We have validated the feasibility of the proposed method using phantom and in vivo studies on a 3T whole-body scanner and a 9.4T preclinical scanner. The proposed method produced high-resolution static 31 P-MRSI images (i.e., 6.9 × 6.9 × 10 mm 3 nominal resolution in a 15-min acquisition at 3T) and high-resolution, high-frame-rate dynamic 31 P-MRSI images (i.e., 1.5 × 1.5 × 1.6 mm 3 nominal resolution, 30 s/frame at 9.4T). Dynamic spatiospectral variations of 31 P-MRSI signals can be efficiently represented by a low-rank tensor. Exploiting this mathematical structure for data acquisition and image reconstruction can lead to fast 31 P-MRSI with high resolution, frame-rate, and SNR. Magn Reson Med 78:419-428, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

40 CFR 766.16 - Developing the analytical test method.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Resolution Gas Chromatography (HRGC) with High Resolution Mass Spectrometry (HRMS) is the method of choice... meet the requirements of the chemical matrix. (d) Analysis. The method of choice is High Resolution Gas...

40 CFR 766.16 - Developing the analytical test method.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Resolution Gas Chromatography (HRGC) with High Resolution Mass Spectrometry (HRMS) is the method of choice... meet the requirements of the chemical matrix. (d) Analysis. The method of choice is High Resolution Gas...

A 4.5 km resolution Arctic Ocean simulation with the global multi-resolution model FESOM 1.4

NASA Astrophysics Data System (ADS)

Wang, Qiang; Wekerle, Claudia; Danilov, Sergey; Wang, Xuezhu; Jung, Thomas

2018-04-01

In the framework of developing a global modeling system which can facilitate modeling studies on Arctic Ocean and high- to midlatitude linkage, we evaluate the Arctic Ocean simulated by the multi-resolution Finite Element Sea ice-Ocean Model (FESOM). To explore the value of using high horizontal resolution for Arctic Ocean modeling, we use two global meshes differing in the horizontal resolution only in the Arctic Ocean (24 km vs. 4.5 km). The high resolution significantly improves the model's representation of the Arctic Ocean. The most pronounced improvement is in the Arctic intermediate layer, in terms of both Atlantic Water (AW) mean state and variability. The deepening and thickening bias of the AW layer, a common issue found in coarse-resolution simulations, is significantly alleviated by using higher resolution. The topographic steering of the AW is stronger and the seasonal and interannual temperature variability along the ocean bottom topography is enhanced in the high-resolution simulation. The high resolution also improves the ocean surface circulation, mainly through a better representation of the narrow straits in the Canadian Arctic Archipelago (CAA). The representation of CAA throughflow not only influences the release of water masses through the other gateways but also the circulation pathways inside the Arctic Ocean. However, the mean state and variability of Arctic freshwater content and the variability of freshwater transport through the Arctic gateways appear not to be very sensitive to the increase in resolution employed here. By highlighting the issues that are independent of model resolution, we address that other efforts including the improvement of parameterizations are still required.

High-resolution harmonic motion imaging (HR-HMI) for tissue biomechanical property characterization

PubMed Central

Ma, Teng; Qian, Xuejun; Chiu, Chi Tat; Yu, Mingyue; Jung, Hayong; Tung, Yao-Sheng; Shung, K. Kirk

2015-01-01

Background Elastography, capable of mapping the biomechanical properties of biological tissues, serves as a useful technique for clinicians to perform disease diagnosis and determine stages of many diseases. Many acoustic radiation force (ARF) based elastography, including acoustic radiation force impulse (ARFI) imaging and harmonic motion imaging (HMI), have been developed to remotely assess the elastic properties of tissues. However, due to the lower operating frequencies of these approaches, their spatial resolutions are insufficient for revealing stiffness distribution on small scale applications, such as cancerous tumor margin detection, atherosclerotic plaque composition analysis and ophthalmologic tissue characterization. Though recently developed ARF-based optical coherence elastography (OCE) methods open a new window for the high resolution elastography, shallow imaging depths significantly limit their usefulness in clinics. Methods The aim of this study is to develop a high-resolution HMI method to assess the tissue biomechanical properties with acceptable field of view (FOV) using a 4 MHz ring transducer for efficient excitation and a 40 MHz needle transducer for accurate detection. Under precise alignment of two confocal transducers, the high-resolution HMI system has a lateral resolution of 314 µm and an axial resolution of 
147 µm with an effective FOV of 2 mm in depth. Results The performance of this high resolution imaging system was validated on the agar-based tissue mimicking phantoms with different stiffness distributions. These data demonstrated the imaging system’s improved resolution and sensitivity on differentiating materials with varying stiffness. In addition, ex vivo imaging of a human atherosclerosis coronary artery demonstrated the capability of high resolution HMI in identifying layer-specific structures and characterizing atherosclerotic plaques based on their stiffness differences. Conclusions All together high resolution HMI appears to be a promising ultrasound-only technology for characterizing tissue biomechanical properties at the microstructural level to improve the image-based diseases diagnosis in multiple clinical applications. PMID:25694960

High-resolution harmonic motion imaging (HR-HMI) for tissue biomechanical property characterization.

PubMed

Ma, Teng; Qian, Xuejun; Chiu, Chi Tat; Yu, Mingyue; Jung, Hayong; Tung, Yao-Sheng; Shung, K Kirk; Zhou, Qifa

2015-02-01

Elastography, capable of mapping the biomechanical properties of biological tissues, serves as a useful technique for clinicians to perform disease diagnosis and determine stages of many diseases. Many acoustic radiation force (ARF) based elastography, including acoustic radiation force impulse (ARFI) imaging and harmonic motion imaging (HMI), have been developed to remotely assess the elastic properties of tissues. However, due to the lower operating frequencies of these approaches, their spatial resolutions are insufficient for revealing stiffness distribution on small scale applications, such as cancerous tumor margin detection, atherosclerotic plaque composition analysis and ophthalmologic tissue characterization. Though recently developed ARF-based optical coherence elastography (OCE) methods open a new window for the high resolution elastography, shallow imaging depths significantly limit their usefulness in clinics. The aim of this study is to develop a high-resolution HMI method to assess the tissue biomechanical properties with acceptable field of view (FOV) using a 4 MHz ring transducer for efficient excitation and a 40 MHz needle transducer for accurate detection. Under precise alignment of two confocal transducers, the high-resolution HMI system has a lateral resolution of 314 µm and an axial resolution of 
147 µm with an effective FOV of 2 mm in depth. The performance of this high resolution imaging system was validated on the agar-based tissue mimicking phantoms with different stiffness distributions. These data demonstrated the imaging system's improved resolution and sensitivity on differentiating materials with varying stiffness. In addition, ex vivo imaging of a human atherosclerosis coronary artery demonstrated the capability of high resolution HMI in identifying layer-specific structures and characterizing atherosclerotic plaques based on their stiffness differences. All together high resolution HMI appears to be a promising ultrasound-only technology for characterizing tissue biomechanical properties at the microstructural level to improve the image-based diseases diagnosis in multiple clinical applications.

Sensitivity to grid resolution in the ability of a chemical transport model to simulate observed oxidant chemistry under high-isoprene conditions

NASA Astrophysics Data System (ADS)

Yu, Karen; Jacob, Daniel J.; Fisher, Jenny A.; Kim, Patrick S.; Marais, Eloise A.; Miller, Christopher C.; Travis, Katherine R.; Zhu, Lei; Yantosca, Robert M.; Sulprizio, Melissa P.; Cohen, Ron C.; Dibb, Jack E.; Fried, Alan; Mikoviny, Tomas; Ryerson, Thomas B.; Wennberg, Paul O.; Wisthaler, Armin

2016-04-01

Formation of ozone and organic aerosol in continental atmospheres depends on whether isoprene emitted by vegetation is oxidized by the high-NOx pathway (where peroxy radicals react with NO) or by low-NOx pathways (where peroxy radicals react by alternate channels, mostly with HO2). We used mixed layer observations from the SEAC4RS aircraft campaign over the Southeast US to test the ability of the GEOS-Chem chemical transport model at different grid resolutions (0.25° × 0.3125°, 2° × 2.5°, 4° × 5°) to simulate this chemistry under high-isoprene, variable-NOx conditions. Observations of isoprene and NOx over the Southeast US show a negative correlation, reflecting the spatial segregation of emissions; this negative correlation is captured in the model at 0.25° × 0.3125° resolution but not at coarser resolutions. As a result, less isoprene oxidation takes place by the high-NOx pathway in the model at 0.25° × 0.3125° resolution (54 %) than at coarser resolution (59 %). The cumulative probability distribution functions (CDFs) of NOx, isoprene, and ozone concentrations show little difference across model resolutions and good agreement with observations, while formaldehyde is overestimated at coarse resolution because excessive isoprene oxidation takes place by the high-NOx pathway with high formaldehyde yield. The good agreement of simulated and observed concentration variances implies that smaller-scale non-linearities (urban and power plant plumes) are not important on the regional scale. Correlations of simulated vs. observed concentrations do not improve with grid resolution because finer modes of variability are intrinsically more difficult to capture. Higher model resolution leads to decreased conversion of NOx to organic nitrates and increased conversion to nitric acid, with total reactive nitrogen oxides (NOy) changing little across model resolutions. Model concentrations in the lower free troposphere are also insensitive to grid resolution. The overall low sensitivity of modeled concentrations to grid resolution implies that coarse resolution is adequate when modeling continental boundary layer chemistry for global applications.

Conductive Atomic Force Microscopy | Materials Science | NREL

Science.gov Websites

electrical measurement techniques is the high spatial resolution. For example, C-AFM measurements on : High-resolution image of a sample semiconductor device; the image shows white puff-like clusters on a dark background and was obtained using atomic force microscopy. Bottom: High-resolution image of the

SALT high resolution spectroscopy of GX339-4 in outburst

NASA Astrophysics Data System (ADS)

Buckley, D. A. H.; Aydi, E.; Kotze, M. M.; Gandhi, P.; Altamirano, D.; Charles, P. A.; Russell, D.

2017-10-01

High resolution (R = 15,000) spectroscopy of the current outbursting black hole transient GX339-4 (ATel #10797) was obtained with the SALT High Resolution Spectrograph (HRS; Crause et al. 2014, Proc SPIE, 91476) on 2017-09-29 starting at 17:28 UTC, during evening twilight.

Application and evaluation of high-resolution WRF-CMAQ with simple urban parameterization.

EPA Science Inventory

The 2-way coupled WRF-CMAQ meteorology and air quality modeling system is evaluated for high-resolution applications by comparing to a regional air quality field study (Discover-AQ). The model was modified to better account for the effects of urban environments. High-resolution...

Mapping evapotranspiration with high resolution aircraft imagery over vineyards using one and two source modeling schemes

USDA-ARS?s Scientific Manuscript database

Thermal and multispectral remote sensing data from low-altitude aircraft can provide high spatial resolution necessary for sub-field (= 10 m) and plant canopy (= 1 m) scale evapotranspiration (ET) monitoring. In this study, high resolution aircraft sub-meter scale thermal infrared and multispectral...

Application and evaluation of high-resolution WRF-CMAQ with simple urban parameterization

EPA Science Inventory

The 2-way coupled WRF-CMAQ meteorology and air quality modeling system is evaluated for high-resolution applications by comparing to a regional air quality field study (Discover-AQ). The model was modified to better account for the effects of urban environments. High-resolution...

Waveform digitization for high resolution timing detectors with silicon photomultipliers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ronzhin, A.; Albrow, M. G.; Los, S.

2012-03-01

The results of time resolution studies with silicon photomultipliers (SiPMs) read out with high bandwidth constant fraction discrimination electronics were presented earlier [1-3]. Here we describe the application of fast waveform digitization readout based on the DRS4 chip [4], a switched capacitor array (SCA) produced by the Paul Scherrer Institute, to further our goal of developing high time resolution detectors based on SiPMs. The influence of the SiPM signal shape on the time resolution was investigated. Different algorithms to obtain the best time resolution are described, and test beam results are presented.

Dual-axis confocal microscope for high-resolution in vivo imaging

PubMed Central

Wang, Thomas D.; Mandella, Michael J.; Contag, Christopher H.; Kino, Gordon S.

2007-01-01

We describe a novel confocal microscope that uses separate low-numerical-aperture objectives with the illumination and collection axes crossed at angle θ from the midline. This architecture collects images in scattering media with high transverse and axial resolution, long working distance, large field of view, and reduced noise from scattered light. We measured transverse and axial (FWHM) resolution of 1.3 and 2.1 μm, respectively, in free space, and confirm subcellular resolution in excised esophageal mucosa. The optics may be scaled to millimeter dimensions and fiber coupled for collection of high-resolution images in vivo. PMID:12659264

Refinement procedure for the image alignment in high-resolution electron tomography.

PubMed

Houben, L; Bar Sadan, M

2011-01-01

High-resolution electron tomography from a tilt series of transmission electron microscopy images requires an accurate image alignment procedure in order to maximise the resolution of the tomogram. This is the case in particular for ultra-high resolution where even very small misalignments between individual images can dramatically reduce the fidelity of the resultant reconstruction. A tomographic-reconstruction based and marker-free method is proposed, which uses an iterative optimisation of the tomogram resolution. The method utilises a search algorithm that maximises the contrast in tomogram sub-volumes. Unlike conventional cross-correlation analysis it provides the required correlation over a large tilt angle separation and guarantees a consistent alignment of images for the full range of object tilt angles. An assessment based on experimental reconstructions shows that the marker-free procedure is competitive to the reference of marker-based procedures at lower resolution and yields sub-pixel accuracy even for simulated high-resolution data. Copyright © 2011 Elsevier B.V. All rights reserved.

Transmission of digital images within the NTSC analog format

DOEpatents

Nickel, George H.

2004-06-15

HDTV and NTSC compatible image communication is done in a single NTSC channel bandwidth. Luminance and chrominance image data of a scene to be transmitted is obtained. The image data is quantized and digitally encoded to form digital image data in HDTV transmission format having low-resolution terms and high-resolution terms. The low-resolution digital image data terms are transformed to a voltage signal corresponding to NTSC color subcarrier modulation with retrace blanking and color bursts to form a NTSC video signal. The NTSC video signal and the high-resolution digital image data terms are then transmitted in a composite NTSC video transmission. In a NTSC receiver, the NTSC video signal is processed directly to display the scene. In a HDTV receiver, the NTSC video signal is processed to invert the color subcarrier modulation to recover the low-resolution terms, where the recovered low-resolution terms are combined with the high-resolution terms to reconstruct the scene in a high definition format.

Mauna Kea Spectrographic Explorer (MSE): a conceptual design for multi-object high resolution spectrograph

NASA Astrophysics Data System (ADS)

Zhang, Kai; Zhu, Yongtian; Hu, Zhongwen

2016-08-01

The Maunakea Spectroscopic Explorer (MSE) project will transform the CFHT 3.6m optical telescope into a 10m class dedicated multi-object spectroscopic facility, with an ability to simultaneously measure thousands of objects with a spectral resolution range spanning 2,000 to 40,000. MSE will develop two spectrographic facilities to meet the science requirements. These are respectively, the Low/Medium Resolution spectrographs (LMRS) and High Resolution spectrographs (HRS). Multi-object high resolution spectrographs with total of 1,156 fibers is a big challenge, one that has never been attempted for a 10m class telescope. To date, most spectral survey facilities work in single order low/medium resolution mode, and only a few Wide Field Spectrographs (WFS) provide a cross-dispersion high resolution mode with a limited number of orders. Nanjing Institute of Astronomical Optics and Technology (NIAOT) propose a conceptual design with the use of novel image slicer arrays and single order immersed Volume Phase Holographic (VPH) grating for the MSE multi-object high resolution spectrographs. The conceptual scheme contains six identical fiber-link spectrographs, each of which simultaneously covers three restricted bands (λ/30, λ/30, λ/15) in the optical regime, with spectral resolution of 40,000 in Blue/Visible bands (400nm / 490nm) and 20,000 in Red band (650nm). The details of the design is presented in this paper.

High-resolution spatial modeling of daily weather elements for a catchment in the Oregon Cascade Mountains, United States

Treesearch

Christopher Daly; Jonathan W. Smith; Joseph I. Smith; Robert B. McKane

2007-01-01

High-quality daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decisionmaking. This paper describes the development. application. and assessment of methods to construct daily high resolution (~50-m cell size) meteorological grids for the...

Land-Use and Land-Cover Change around Mobile Bay, Alabama from 1974-2008

NASA Technical Reports Server (NTRS)

Ellis, Jean; Spruce, Joseph P.; Swann, Roberta; Smooth, James C.

2009-01-01

This document summarizes the major findings of a Gulf of Mexico Application Pilot project led by NASA Stennis Space Center (SSC) in conjunction with a regional collaboration network of the Gulf of Mexico Alliance (GOMA). NASA researchers processed and analyzed multi-temporal Landsat data to assess land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, AL between 1974 and 2008. Our goal was to create satellite-based LULC data products using methods that could be transferable to other coastal areas of concern within the Gulf of Mexico. The Mobile Bay National Estuary Program (MBNEP) is the primary end-user, however, several other state and local groups may benefit from the project s data products that will be available through NOAA-NCDDC s Regional Ecosystem Data Management program. Mobile Bay is a critical ecologic and economic region in the Gulf of Mexico and to the entire country. Mobile Bay was designated as an estuary of national significance in 1996. This estuary receives the fourth largest freshwater inflow in the United States. It provides vital nursery habitat for commercially and recreationally important fish species. It has exceptional aquatic and terrestrial bio-diversity, however, its estuary health is influenced by changing LULC patterns, such as urbanization. Mobile and Baldwin counties have experienced a population growth of 1.1% and 20.5% from 2000-2006. Urban expansion and population growth are likely to accelerate with the construction and operation of the ThyssenKrupp steel mill in the northeast portion of Mobile County. Land-use and land-cover change can negatively impact Gulf coast water quality and ecological resources. The conversion of forest to urban cover types impacts the carbon cycle and increases the freshwater and sediment in coastal waters. Increased freshwater runoff decreases salinity and increases the turbidity of coastal waters, thus impacting the growth potential of submerged aquatic vegetation (SAV), which is critical nursing ground for many Gulf fish species. A survey of Mobile Bay SAV showed widespread decreases since the 1940s. Prior to our project, coastal environmental managers in Baldwin and Mobile counties needed more understanding of the historical LULC for properly assessing the impacts of urbanization. In particular, more information on the location and extent of changing urbanization LULC patterns was needed to aid LULC planning and to assess predictions of future LULC patterns. Our products will assist the coastal environmental managers and land-use planners in making better community growth planning decisions. Our project also will help to establish a historical baseline of LULC distributions, which is a fundamental need in any stewardship plan. The primary research objective of our project was to produce historic and current geospatial LULC change products across a 34-year time frame. A multi-decadal coastal LULC change product was the major project deliverable. The geographic extent and nature of change was quantified and assessed for the upland herbaceous, barren, open water, urban, upland forest, woody wetland, and non-woody wetlanddominated land cover types. We focused on regional analyses of decadal-scale urban expansion and watershed-scaled analyses of LULC change for multiple areas of concern to the Mobile Bay NEP (Figure A). We used the following dates to derive LULC classification products from Landsat data: 1974, 1979, 1984, 1988, 1991, 1996, 2001, 2005, and 2008. We assessed the accuracy of our products using randomly sampled locations and digital geospatial reference data including field survey data, high resolution orthorectified aerial photography, high resolution multispectral and panchromatic satellite data displays (from QuickBird and Corona sensors), digital elevation model data, and National Wetlands Inventory wetland cover type data. NOAA s Coastal Change Assessment Program s (C-CAP) and National Land Cover Database (NLCD) procts were used for qualitative comparison in assessing map accuracy. We calculated an average overall classification accuracy of 87% with similar overall accuracies for the older (MSS) and newer (TM and ETM) Landsat LULC products.

Patch-Based Super-Resolution of MR Spectroscopic Images: Application to Multiple Sclerosis

PubMed Central

Jain, Saurabh; Sima, Diana M.; Sanaei Nezhad, Faezeh; Hangel, Gilbert; Bogner, Wolfgang; Williams, Stephen; Van Huffel, Sabine; Maes, Frederik; Smeets, Dirk

2017-01-01

Purpose: Magnetic resonance spectroscopic imaging (MRSI) provides complementary information to conventional magnetic resonance imaging. Acquiring high resolution MRSI is time consuming and requires complex reconstruction techniques. Methods: In this paper, a patch-based super-resolution method is presented to increase the spatial resolution of metabolite maps computed from MRSI. The proposed method uses high resolution anatomical MR images (T1-weighted and Fluid-attenuated inversion recovery) to regularize the super-resolution process. The accuracy of the method is validated against conventional interpolation techniques using a phantom, as well as simulated and in vivo acquired human brain images of multiple sclerosis subjects. Results: The method preserves tissue contrast and structural information, and matches well with the trend of acquired high resolution MRSI. Conclusions: These results suggest that the method has potential for clinically relevant neuroimaging applications. PMID:28197066

Rayleigh-wave mode separation by high-resolution linear radon transform

USGS Publications Warehouse

Luo, Y.; Xia, J.; Miller, R.D.; Xu, Y.; Liu, J.; Liu, Q.

2009-01-01

Multichannel analysis of surface waves (MASW) method is an effective tool for obtaining vertical shear wave profiles from a single non-invasive measurement. One key step of the MASW method is generation of a dispersion image and extraction of a reliable dispersion curve from raw multichannel shot records. Because different Rayleigh-wave modes normally interfere with each other in the time and space domain, it is necessary to perform mode separation and reconstruction to increase the accuracy of phase velocities determined from a dispersion image. In this paper, we demonstrate the effectiveness of high-resolution linear Radon transform (LRT) as a means of separating and reconstructing multimode, dispersive Rayleigh-wave energy. We first introduce high-resolution LRT methods and Rayleigh-wave mode separation using high-resolution LRT. Next, we use synthetic data and a real-world example to demonstrate the effectiveness of Rayleigh-wave mode separation using high-resolution LRT. Our synthetic and real-world results demonstrate that (1) high-resolution LRT successfully separates and reconstructs multimode dispersive Rayleigh-wave energy with high resolution allowing the multimode energy to be more accurately determined. The horizontal resolution of the Rayleigh-wave method can be increased by extraction of dispersion curves from a pair of traces in the mode-separated shot gather and (2) multimode separation and reconstruction expand the usable frequency range of higher mode dispersive energy, which increases the depth of investigation and provides a means for accurately determining cut-off frequencies. ?? 2009 The Authors Journal compilation ?? 2009 RAS.

High resolution PFPE-based molding High resolution PFPE-based molding High resolution PFPE-based molding techniques for nanofabrication of high pattern density sub-20 nm features: A fundamental materials approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Stuart S; Samulski, Edward; Lopez, Renee

2010-01-01

ABSTRACT. Described herein is the development and investigation of PFPE-based elastomers for high resolution replica molding applications. The modulus of the elastomeric materials was increased through synthetic and additive approaches while maintaining relatively low surface energies (<25 mN/m). Using practically relevant large area master templates, we show that the resolution of the molds is strongly dependant upon the elastomeric mold modulus. A composite mold approach was used to form flexible molds out of stiff, high modulus materials that allow for replication of sub-20 nm post structures. Sub-100 nm line grating master templates, formed using e-beam lithography, were used to determinemore » the experimental stability of the molding materials. It was observed that as the feature spacing decreased, high modulus composite molds were able to effectively replicate the nano-grating structures without cracking or tear-out defects that typically occur with high modulus elastomers.« less

On high-resolution reciprocal-space mapping with a triple-crystal diffractometer for high-energy X-rays.

PubMed

Liss, K D; Royer, A; Tschentscher, T; Suortti, P; Williams, A P

1998-03-01

High-energy X-rav diffraction by means of triple-crystal techniques is a powerful tool for investigating dislocations and strain in bulk materials. Radiation with an energy typically higher than 80 keV combines the advantage of low attenuation with high resolution at large momentum transfers. The triple-crystal diffractometer at the High Energy Beamline of the European Synchrotron Radiation Facility is described. It is shown how the transverse and longitudinal resolution depend on the choice of the crystal reflection, and how the orientation of a reciprocal-lattice distortion in an investigated sample towards the resolution element of the instrument can play an important role. This effect is demonstrated on a single crystal of silicon where a layer of macro pores reveals satellites around the Bragg reflection. The resulting longitudinal distortion can be investigated using the high transverse resolution of the instrument when choosing an appropriate reflection.

MRI Superresolution Using Self-Similarity and Image Priors

PubMed Central

Manjón, José V.; Coupé, Pierrick; Buades, Antonio; Collins, D. Louis; Robles, Montserrat

2010-01-01

In Magnetic Resonance Imaging typical clinical settings, both low- and high-resolution images of different types are routinarily acquired. In some cases, the acquired low-resolution images have to be upsampled to match with other high-resolution images for posterior analysis or postprocessing such as registration or multimodal segmentation. However, classical interpolation techniques are not able to recover the high-frequency information lost during the acquisition process. In the present paper, a new superresolution method is proposed to reconstruct high-resolution images from the low-resolution ones using information from coplanar high resolution images acquired of the same subject. Furthermore, the reconstruction process is constrained to be physically plausible with the MR acquisition model that allows a meaningful interpretation of the results. Experiments on synthetic and real data are supplied to show the effectiveness of the proposed approach. A comparison with classical state-of-the-art interpolation techniques is presented to demonstrate the improved performance of the proposed methodology. PMID:21197094

Satellite image time series simulation for environmental monitoring

NASA Astrophysics Data System (ADS)

Guo, Tao

2014-11-01

The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of costly high resolution data can be reduced as much as possible, and it presents an efficient solution with great cost performance to build up an economically operational monitoring service for environment, agriculture, forest, land use investigation, and other applications.

Spatially detailed retrievals of spring phenology from single-season high-resolution image time series

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Skidmore, Andrew K.; Wang, Tiejun; Meroni, Michele; Ens, Bruno J.; Oosterbeek, Kees; O'Connor, Brian; Darvishzadeh, Roshanak; Heurich, Marco; Shepherd, Anita; Paganini, Marc

2017-07-01

Vegetation indices derived from satellite image time series have been extensively used to estimate the timing of phenological events like season onset. Medium spatial resolution (≥250 m) satellite sensors with daily revisit capability are typically employed for this purpose. In recent years, phenology is being retrieved at higher resolution (≤30 m) in response to increasing availability of high-resolution satellite data. To overcome the reduced acquisition frequency of such data, previous attempts involved fusion between high- and medium-resolution data, or combinations of multi-year acquisitions in a single phenological reconstruction. The objectives of this study are to demonstrate that phenological parameters can now be retrieved from single-season high-resolution time series, and to compare these retrievals against those derived from multi-year high-resolution and single-season medium-resolution satellite data. The study focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamic saltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5 m-resolution) and the SPOT5 Take5 experiment (10m-resolution) acquired between March and August 2015, phenological parameters were estimated using a function fitting approach. We then compared results with phenology retrieved from four years of 30 m Landsat 8 OLI data, and single-year 100 m Proba-V and 250 m MODIS temporal composites of the same period. Retrieved phenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and a large spatial variability, providing complementary information to existing vegetation community maps. Retrievals that combined four years of Landsat observations into a single synthetic year were affected by the inclusion of years with warmer spring temperatures, whereas adjustment of the average phenology to 2015 observations was only feasible for a few pixels due to cloud cover around phenological transition dates. The Proba-V and MODIS phenology retrievals scaled poorly relative to their high-resolution equivalents, indicating that medium-resolution phenology retrievals need to be interpreted with care, particularly in landscapes with fine-scale land cover variability.

High-resolution satellite imagery is an important yet underutilized resource in conservation biology.

PubMed

Boyle, Sarah A; Kennedy, Christina M; Torres, Julio; Colman, Karen; Pérez-Estigarribia, Pastor E; de la Sancha, Noé U

2014-01-01

Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making.

Single-shot and single-sensor high/super-resolution microwave imaging based on metasurface

PubMed Central

Wang, Libo; Li, Lianlin; Li, Yunbo; Zhang, Hao Chi; Cui, Tie Jun

2016-01-01

Real-time high-resolution (including super-resolution) imaging with low-cost hardware is a long sought-after goal in various imaging applications. Here, we propose broadband single-shot and single-sensor high-/super-resolution imaging by using a spatio-temporal dispersive metasurface and an imaging reconstruction algorithm. The metasurface with spatio-temporal dispersive property ensures the feasibility of the single-shot and single-sensor imager for super- and high-resolution imaging, since it can convert efficiently the detailed spatial information of the probed object into one-dimensional time- or frequency-dependent signal acquired by a single sensor fixed in the far-field region. The imaging quality can be improved by applying a feature-enhanced reconstruction algorithm in post-processing, and the desired imaging resolution is related to the distance between the object and metasurface. When the object is placed in the vicinity of the metasurface, the super-resolution imaging can be realized. The proposed imaging methodology provides a unique means to perform real-time data acquisition, high-/super-resolution images without employing expensive hardware (e.g. mechanical scanner, antenna array, etc.). We expect that this methodology could make potential breakthroughs in the areas of microwave, terahertz, optical, and even ultrasound imaging. PMID:27246668

Determination of atmospheric moisture structure and infrared cooling rates from high resolution MAMS radiance data

NASA Technical Reports Server (NTRS)

Menzel, W. Paul; Moeller, Christopher C.; Smith, William L.

1991-01-01

This program has applied Multispectral Atmospheric Mapping Sensor (MAMS) high resolution data to the problem of monitoring atmospheric quantities of moisture and radiative flux at small spatial scales. MAMS, with 100-m horizontal resolution in its four infrared channels, was developed to study small scale atmospheric moisture and surface thermal variability, especially as related to the development of clouds, precipitation, and severe storms. High-resolution Interferometer Sounder (HIS) data has been used to develop a high spectral resolution retrieval algorithm for producing vertical profiles of atmospheric temperature and moisture. The results of this program are summarized and a list of publications resulting from this contract is presented. Selected publications are attached as an appendix.

Photoionization Rate of Atomic Oxygen

NASA Astrophysics Data System (ADS)

Meier, R. R.; McLaughlin, B. M.; Warren, H. P.; Bishop, J.

2006-05-01

Accurate knowledge of the photoionization rate of atomic oxygen is important for the study and understanding of the ionospheres and emission processes of terrestrial, planetary, and cometary atmospheres. Past calculations of the photoionization rate have been carried out at various spectral resolutions, but none were at sufficiently high resolution to accommodate accidental resonances between solar emission lines and highly structured auto-ionization features in the photoionization cross section. A new version of the NRLEUV solar spectral irradiance model (at solar minimum) and a new model of the O photoionization cross section enable calculations at very high spectral resolution. We find unattenuated photoionization rates computed at 0.001 nm resolution are larger than those at moderate resolution (0.1 nm) by amounts approaching 20%. Allowing for attenuation in the terrestrial atmosphere, we find differences in photoionization rates computed at high and moderate resolution to vary with altitude, especially below 200 km where deviations of plus or minus 20% occur between the two cases.

[Possibile application of X-ray and high resolution CT in pneumoconiosis management].

PubMed

Vlasov, V G; Laptev, V Ia; Logvinenko, I I; Smirnova, E L; Brovchenko, E P; Mironova, M V

2011-01-01

The article covers results of clinical and roentgenologic data analysis. The data were obtained in the study that covered 447 pneumoconiosis patients, 75 of which were subjected to high resolution CT. If compared to chest X-ray, high resolution CT helps more precise forecast of further course in pneumoconiosis.

Urban cover mapping using digital, high-resolution aerial imagery

Treesearch

Soojeong Myeong; David J. Nowak; Paul F. Hopkins; Robert H. Brock

2003-01-01

High-spatial resolution digital color-infrared aerial imagery of Syracuse, NY was analyzed to test methods for developing land cover classifications for an urban area. Five cover types were mapped: tree/shrub, grass/herbaceous, bare soil, water and impervious surface. Challenges in high-spatial resolution imagery such as shadow effect and similarity in spectral...

High resolution manometry findings in patients with esophageal epiphrenic diverticula.

PubMed

Vicentine, Fernando P P; Herbella, Fernando A M; Silva, Luciana C; Patti, Marco G

2011-12-01

The pathophysiology of esophageal epiphrenic diverticula is still uncertain even though a concomitant motility disorder is found in the majority of patients in different series. High resolution manometry may allow detection of motor abnormalities in a higher number of patients with esophageal epiphrenic diverticula compared with conventional manometry. This study aims to evaluate the high resolution manometry findings in patients with esophageal epiphrenic diverticula. Nine individuals (mean age 63 ± 10 years, 4 females) with esophageal epiphrenic diverticula underwent high resolution manometry. A single diverticulum was observed in eight patients and multiple diverticula in one. Visual analysis of conventional tracings and color pressure plots for identification of segmental abnormalities was performed by two researchers experienced in high resolution manometry. Upper esophageal sphincter was normal in all patients. Esophageal body was abnormal in eight patients; lower esophageal sphincter was abnormal in seven patients. Named esophageal motility disorders were found in seven patients: achalasia in six, diffuse esophageal spasm in one. In one patient, a segmental hypercontractile zone was noticed with pressure of 196 mm Hg. High resolution manometry demonstrated motor abnormalities in all patients with esophageal epiphrenic diverticula.

Application of Convolutional Neural Network in Classification of High Resolution Agricultural Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yao, C.; Zhang, Y.; Zhang, Y.; Liu, H.

2017-09-01

With the rapid development of Precision Agriculture (PA) promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN). For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

Evaluation of the sparse coding super-resolution method for improving image quality of up-sampled images in computed tomography

NASA Astrophysics Data System (ADS)

Ota, Junko; Umehara, Kensuke; Ishimaru, Naoki; Ohno, Shunsuke; Okamoto, Kentaro; Suzuki, Takanori; Shirai, Naoki; Ishida, Takayuki

2017-02-01

As the capability of high-resolution displays grows, high-resolution images are often required in Computed Tomography (CT). However, acquiring high-resolution images takes a higher radiation dose and a longer scanning time. In this study, we applied the Sparse-coding-based Super-Resolution (ScSR) method to generate high-resolution images without increasing the radiation dose. We prepared the over-complete dictionary learned the mapping between low- and highresolution patches and seek a sparse representation of each patch of the low-resolution input. These coefficients were used to generate the high-resolution output. For evaluation, 44 CT cases were used as the test dataset. We up-sampled images up to 2 or 4 times and compared the image quality of the ScSR scheme and bilinear and bicubic interpolations, which are the traditional interpolation schemes. We also compared the image quality of three learning datasets. A total of 45 CT images, 91 non-medical images, and 93 chest radiographs were used for dictionary preparation respectively. The image quality was evaluated by measuring peak signal-to-noise ratio (PSNR) and structure similarity (SSIM). The differences of PSNRs and SSIMs between the ScSR method and interpolation methods were statistically significant. Visual assessment confirmed that the ScSR method generated a high-resolution image with sharpness, whereas conventional interpolation methods generated over-smoothed images. To compare three different training datasets, there were no significance between the CT, the CXR and non-medical datasets. These results suggest that the ScSR provides a robust approach for application of up-sampling CT images and yields substantial high image quality of extended images in CT.

Ultra high spatial and temporal resolution breast imaging at 7T.

PubMed

van de Bank, B L; Voogt, I J; Italiaander, M; Stehouwer, B L; Boer, V O; Luijten, P R; Klomp, D W J

2013-04-01

There is a need to obtain higher specificity in the detection of breast lesions using MRI. To address this need, Dynamic Contrast-Enhanced (DCE) MRI has been combined with other structural and functional MRI techniques. Unfortunately, owing to time constraints structural images at ultra-high spatial resolution can generally not be obtained during contrast uptake, whereas the relatively low spatial resolution of functional imaging (e.g. diffusion and perfusion) limits the detection of small lesions. To be able to increase spatial as well as temporal resolution simultaneously, the sensitivity of MR detection needs to increase as well as the ability to effectively accelerate the acquisition. The required gain in signal-to-noise ratio (SNR) can be obtained at 7T, whereas acceleration can be obtained with high-density receiver coil arrays. In this case, morphological imaging can be merged with DCE-MRI, and other functional techniques can be obtained at higher spatial resolution, and with less distortion [e.g. Diffusion Weighted Imaging (DWI)]. To test the feasibility of this concept, we developed a unilateral breast coil for 7T. It comprises a volume optimized dual-channel transmit coil combined with a 30-channel receive array coil. The high density of small coil elements enabled efficient acceleration in any direction to acquire ultra high spatial resolution MRI of close to 0.6 mm isotropic detail within a temporal resolution of 69 s, high spatial resolution MRI of 1.5 mm isotropic within an ultra high temporal resolution of 6.7 s and low distortion DWI at 7T, all validated in phantoms, healthy volunteers and a patient with a lesion in the right breast classified as Breast Imaging Reporting and Data System (BI-RADS) IV. Copyright © 2012 John Wiley & Sons, Ltd.

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

NASA Astrophysics Data System (ADS)

Min, Junhong; Vonesch, Cédric; Kirshner, Hagai; Carlini, Lina; Olivier, Nicolas; Holden, Seamus; Manley, Suliana; Ye, Jong Chul; Unser, Michael

2014-04-01

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics.

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

PubMed Central

Min, Junhong; Vonesch, Cédric; Kirshner, Hagai; Carlini, Lina; Olivier, Nicolas; Holden, Seamus; Manley, Suliana; Ye, Jong Chul; Unser, Michael

2014-01-01

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics. PMID:24694686

The Joint Astrophysical Plasmadynamic Experiment (J-PEX): a high-resolution rocket spectrometer

NASA Astrophysics Data System (ADS)

Barstow, Martin A.; Bannister, Nigel P.; Cruddace, Raymond G.; Kowalski, Michael P.; Wood, Kent S.; Yentis, Daryl J.; Gursky, Herbert; Barbee, Troy W., Jr.; Goldstein, William H.; Kordas, Joseph F.; Fritz, Gilbert G.; Culhane, J. Leonard; Lapington, Jonathan S.

2003-02-01

We report on the successful sounding rocket flight of the high resolution (R=3000-4000) J-PEX EUV spectrometer. J-PEX is a novel normal incidence instrument, which combines the focusing and dispersive elements of the spectrometer into a single optical element, a multilayer-coated grating. The high spectral resolution achieved has had to be matched by unprecedented high spatial resolution in the imaging microchannel plate detector used to record the data. We illustrate the performance of the complete instrument through an analysis of the 220-245Å spectrum of the white dwarf G191-B2B obtained with a 300 second exposure. The high resolution allows us to detect a low-density ionized helium component along the line of sight to the star and individual absorption lines from heavier elements in the photosphere.

Flat field concave holographic grating with broad spectral region and moderately high resolution.

PubMed

Wu, Jian Fen; Chen, Yong Yan; Wang, Tai Sheng

2012-02-01

In order to deal with the conflicts between broad spectral region and high resolution in compact spectrometers based on a flat field concave holographic grating and line array CCD, we present a simple and practical method to design a flat field concave holographic grating that is capable of imaging a broad spectral region at a moderately high resolution. First, we discuss the principle of realizing a broad spectral region and moderately high resolution. Second, we provide the practical method to realize our ideas, in which Namioka grating theory, a genetic algorithm, and ZEMAX are used to reach this purpose. Finally, a near-normal-incidence example modeled in ZEMAX is shown to verify our ideas. The results show that our work probably has a general applicability in compact spectrometers with a broad spectral region and moderately high resolution.

Impacts of high resolution data on traveler compliance levels in emergency evacuation simulations

DOE PAGES

Lu, Wei; Han, Lee D.; Liu, Cheng; ...

2016-05-05

In this article, we conducted a comparison study of evacuation assignment based on Traffic Analysis Zones (TAZ) and high resolution LandScan USA Population Cells (LPC) with detailed real world roads network. A platform for evacuation modeling built on high resolution population distribution data and activity-based microscopic traffic simulation was proposed. This platform can be extended to any cities in the world. The results indicated that evacuee compliance behavior affects evacuation efficiency with traditional TAZ assignment, but it did not significantly compromise the performance with high resolution LPC assignment. The TAZ assignment also underestimated the real travel time during evacuation. Thismore » suggests that high data resolution can improve the accuracy of traffic modeling and simulation. The evacuation manager should consider more diverse assignment during emergency evacuation to avoid congestions.« less

High-resolution and high-throughput multichannel Fourier transform spectrometer with two-dimensional interferogram warping compensation

NASA Astrophysics Data System (ADS)

Watanabe, A.; Furukawa, H.

2018-04-01

The resolution of multichannel Fourier transform (McFT) spectroscopy is insufficient for many applications despite its extreme advantage of high throughput. We propose an improved configuration to realise both performance using a two-dimensional area sensor. For the spectral resolution, we obtained the interferogram of a larger optical path difference by shifting the area sensor without altering any optical components. The non-linear phase error of the interferometer was successfully corrected using a phase-compensation calculation. Warping compensation was also applied to realise a higher throughput to accumulate the signal between vertical pixels. Our approach significantly improved the resolution and signal-to-noise ratio by factors of 1.7 and 34, respectively. This high-resolution and high-sensitivity McFT spectrometer will be useful for detecting weak light signals such as those in non-invasive diagnosis.

X-ray structure determination at low resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brunger, Axel T., E-mail: brunger@stanford.edu; Department of Molecular and Cellular Physiology, Stanford University; Department of Neurology and Neurological Sciences, Stanford University

2009-02-01

Refinement is meaningful even at 4 Å or lower, but with present methodologies it should start from high-resolution crystal structures whenever possible. As an example of structure determination in the 3.5–4.5 Å resolution range, crystal structures of the ATPase p97/VCP, consisting of an N-terminal domain followed by a tandem pair of ATPase domains (D1 and D2), are discussed. The structures were originally solved by molecular replacement with the high-resolution structure of the N-D1 fragment of p97/VCP, whereas the D2 domain was manually built using its homology to the D1 domain as a guide. The structure of the D2 domain alonemore » was subsequently solved at 3 Å resolution. The refined model of D2 and the high-resolution structure of the N-D1 fragment were then used as starting models for re-refinement against the low-resolution diffraction data for full-length p97. The re-refined full-length models showed significant improvement in both secondary structure and R values. The free R values dropped by as much as 5% compared with the original structure refinements, indicating that refinement is meaningful at low resolution and that there is information in the diffraction data even at ∼4 Å resolution that objectively assesses the quality of the model. It is concluded that de novo model building is problematic at low resolution and refinement should start from high-resolution crystal structures whenever possible.« less

Large Area Field of View for Fast Temporal Resolution Astronomy

NASA Astrophysics Data System (ADS)

Covarrubias, Ricardo A.

2018-01-01

Scientific CMOS (sCMOS) technology is especially relevant for high temporal resolution astronomy combining high resolution, large field of view with very fast frame rates, without sacrificing ultra-low noise performance. Solar Astronomy, Near Earth Object detections, Space Debris Tracking, Transient Observations or Wavefront Sensing are among the many applications this technology can be utilized. Andor Technology is currently developing the next-generation, very large area sCMOS camera with an extremely low noise, rapid frame rates, high resolution and wide dynamic range.

Current position of high-resolution MS for drug quantification in clinical & forensic toxicology.

PubMed

Meyer, Markus R; Helfer, Andreas G; Maurer, Hans H

2014-08-01

This paper reviews high-resolution MS approaches published from January 2011 until March 2014 for the quantification of drugs (of abuse) and/or their metabolites in biosamples using LC-MS with time-of-flight or Orbitrap™ mass analyzers. Corresponding approaches are discussed including sample preparation and mass spectral settings. The advantages and limitations of high-resolution MS for drug quantification, as well as the demand for a certain resolution or a specific mass accuracy are also explored.

Fiber optic cable-based high-resolution, long-distance VGA extenders

NASA Astrophysics Data System (ADS)

Rhee, Jin-Geun; Lee, Iksoo; Kim, Heejoon; Kim, Sungjoon; Koh, Yeon-Wan; Kim, Hoik; Lim, Jiseok; Kim, Chur; Kim, Jungwon

2013-02-01

Remote transfer of high-resolution video information finds more applications in detached display applications for large facilities such as theaters, sports complex, airports, and security facilities. Active optical cables (AOCs) provide a promising approach for enhancing both the transmittable resolution and distance that standard copper-based cables cannot reach. In addition to the standard digital formats such as HDMI, the high-resolution, long-distance transfer of VGA format signals is important for applications where high-resolution analog video ports should be also supported, such as military/defense applications and high-resolution video camera links. In this presentation we present the development of a compressionless, high-resolution (up to WUXGA, 1920x1200), long-distance (up to 2 km) VGA extenders based on serialized technique. We employed asynchronous serial transmission and clock regeneration techniques, which enables lower cost implementation of VGA extenders by removing the necessity for clock transmission and large memory at the receiver. Two 3.125-Gbps transceivers are used in parallel to meet the required maximum video data rate of 6.25 Gbps. As the data are transmitted asynchronously, 24-bit pixel clock time stamp is employed to regenerate video pixel clock accurately at the receiver side. In parallel to the video information, stereo audio and RS-232 control signals are transmitted as well.

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

NASA Astrophysics Data System (ADS)

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Combined multi-plane phase retrieval and super-resolution optical fluctuation imaging for 4D cell microscopy

NASA Astrophysics Data System (ADS)

Descloux, A.; Grußmayer, K. S.; Bostan, E.; Lukes, T.; Bouwens, A.; Sharipov, A.; Geissbuehler, S.; Mahul-Mellier, A.-L.; Lashuel, H. A.; Leutenegger, M.; Lasser, T.

2018-03-01

Super-resolution fluorescence microscopy provides unprecedented insight into cellular and subcellular structures. However, going `beyond the diffraction barrier' comes at a price, since most far-field super-resolution imaging techniques trade temporal for spatial super-resolution. We propose the combination of a novel label-free white light quantitative phase imaging with fluorescence to provide high-speed imaging and spatial super-resolution. The non-iterative phase retrieval relies on the acquisition of single images at each z-location and thus enables straightforward 3D phase imaging using a classical microscope. We realized multi-plane imaging using a customized prism for the simultaneous acquisition of eight planes. This allowed us to not only image live cells in 3D at up to 200 Hz, but also to integrate fluorescence super-resolution optical fluctuation imaging within the same optical instrument. The 4D microscope platform unifies the sensitivity and high temporal resolution of phase imaging with the specificity and high spatial resolution of fluorescence microscopy.

Sparse super-resolution reconstructions of video from mobile devices in digital TV broadcast applications

NASA Astrophysics Data System (ADS)

Boon, Choong S.; Guleryuz, Onur G.; Kawahara, Toshiro; Suzuki, Yoshinori

2006-08-01

We consider the mobile service scenario where video programming is broadcast to low-resolution wireless terminals. In such a scenario, broadcasters utilize simultaneous data services and bi-directional communications capabilities of the terminals in order to offer substantially enriched viewing experiences to users by allowing user participation and user tuned content. While users immediately benefit from this service when using their phones in mobile environments, the service is less appealing in stationary environments where a regular television provides competing programming at much higher display resolutions. We propose a fast super-resolution technique that allows the mobile terminals to show a much enhanced version of the broadcast video on nearby high-resolution devices, extending the appeal and usefulness of the broadcast service. The proposed single frame super-resolution algorithm uses recent sparse recovery results to provide high quality and high-resolution video reconstructions based solely on individual decoded frames provided by the low-resolution broadcast.

Large-scale microfluidics providing high-resolution and high-throughput screening of Caenorhabditis elegans poly-glutamine aggregation model

NASA Astrophysics Data System (ADS)

Mondal, Sudip; Hegarty, Evan; Martin, Chris; Gökçe, Sertan Kutal; Ghorashian, Navid; Ben-Yakar, Adela

2016-10-01

Next generation drug screening could benefit greatly from in vivo studies, using small animal models such as Caenorhabditis elegans for hit identification and lead optimization. Current in vivo assays can operate either at low throughput with high resolution or with low resolution at high throughput. To enable both high-throughput and high-resolution imaging of C. elegans, we developed an automated microfluidic platform. This platform can image 15 z-stacks of ~4,000 C. elegans from 96 different populations using a large-scale chip with a micron resolution in 16 min. Using this platform, we screened ~100,000 animals of the poly-glutamine aggregation model on 25 chips. We tested the efficacy of ~1,000 FDA-approved drugs in improving the aggregation phenotype of the model and identified four confirmed hits. This robust platform now enables high-content screening of various C. elegans disease models at the speed and cost of in vitro cell-based assays.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia.

PubMed

Dorji, Passang; Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor's radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

PubMed Central

Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor’s radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit. PMID:28380059

Multibeam interferometric illumination as the primary source of resolution in optical microscopy

NASA Astrophysics Data System (ADS)

Ryu, J.; Hong, S. S.; Horn, B. K. P.; Freeman, D. M.; Mermelstein, M. S.

2006-04-01

High-resolution images of a fluorescent target were obtained using a low-resolution optical detector by illuminating the target with interference patterns produced with 31 coherent beams. The beams were arranged in a cone with 78° half angle to produce illumination patterns consistent with a numerical aperture of 0.98. High-resolution images were constructed from low-resolution images taken with 930 different illumination patterns. Results for optical detectors with numerical apertures of 0.1 and 0.2 were similar, demonstrating that the resolution is primarily determined by the illuminator and not by the low-resolution detector. Furthermore, the long working distance, large depth of field, and large field of view of the low-resolution detector are preserved.

Assessment of summer rainfall forecast skill in the Intra-Americas in GFDL high and low-resolution models

NASA Astrophysics Data System (ADS)

Krishnamurthy, Lakshmi; Muñoz, Ángel G.; Vecchi, Gabriel A.; Msadek, Rym; Wittenberg, Andrew T.; Stern, Bill; Gudgel, Rich; Zeng, Fanrong

2018-05-01

The Caribbean low-level jet (CLLJ) is an important component of the atmospheric circulation over the Intra-Americas Sea (IAS) which impacts the weather and climate both locally and remotely. It influences the rainfall variability in the Caribbean, Central America, northern South America, the tropical Pacific and the continental Unites States through the transport of moisture. We make use of high-resolution coupled and uncoupled models from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the simulation of the CLLJ and its teleconnections and further compare with low-resolution models. The high-resolution coupled model FLOR shows improvements in the simulation of the CLLJ and its teleconnections with rainfall and SST over the IAS compared to the low-resolution coupled model CM2.1. The CLLJ is better represented in uncoupled models (AM2.1 and AM2.5) forced with observed sea-surface temperatures (SSTs), emphasizing the role of SSTs in the simulation of the CLLJ. Further, we determine the forecast skill for observed rainfall using both high- and low-resolution predictions of rainfall and SSTs for the July-August-September season. We determine the role of statistical correction of model biases, coupling and horizontal resolution on the forecast skill. Statistical correction dramatically improves area-averaged forecast skill. But the analysis of spatial distribution in skill indicates that the improvement in skill after statistical correction is region dependent. Forecast skill is sensitive to coupling in parts of the Caribbean, Central and northern South America, and it is mostly insensitive over North America. Comparison of forecast skill between high and low-resolution coupled models does not show any dramatic difference. However, uncoupled models show improvement in the area-averaged skill in the high-resolution atmospheric model compared to lower resolution model. Understanding and improving the forecast skill over the IAS has important implications for highly vulnerable nations in the region.

Simulation of Mean Flow and Turbulence over a 2D Building Array Using High-Resolution CFD and a Distributed Drag Force Approach

DTIC Science & Technology

2016-06-16

procedure. The predictive capabilities of the high-resolution computational fluid dynamics ( CFD ) simulations of urban flow are validated against a very...turbulence over a 2D building array using high-resolution CFD and a distributed drag force approach a Department of Mechanical Engineering, University

Nuclear Power Plant environment`s surveillance by satellite remote sensing and in-situ monitoring data

NASA Astrophysics Data System (ADS)

Zoran, Maria

The main environmental issues affecting the broad acceptability of nuclear power plant are the emission of radioactive materials, the generation of radioactive waste, and the potential for nuclear accidents. All nuclear fission reactors, regardless of design, location, operator or regulator, have the potential to undergo catastrophic accidents involving loss of control of the reactor core, failure of safety systems and subsequent widespread fallout of hazardous fission products. Risk is the mathematical product of probability and consequences, so lowprobability and high-consequence accidents, by definition, have a high risk. NPP environment surveillance is a very important task in frame of risk assessment. Satellite remote sensing data had been applied for dosimeter levels first time for Chernobyl NPP accident in 1986. Just for a normal functioning of a nuclear power plant, multitemporal and multispectral satellite data in complementarily with field data are very useful tools for NPP environment surveillance and risk assessment. Satellite remote sensing is used as an important technology to help environmental research to support research analysis of spatio-temporal dynamics of environmental features nearby nuclear facilities. Digital processing techniques applied to several LANDSAT, MODIS and QuickBird data in synergy with in-situ data are used to assess the extent and magnitude of radiation and non-radiation effects on the water, near field soil, vegetation and air. As a test case the methodology was applied for for Nuclear Power Plant (NPP) Cernavoda, Romania. Thermal discharge from nuclear reactors cooling is dissipated as waste heat in Danube-Black -Sea Canal and Danube River. Water temperatures captured in thermal IR imagery are correlated with meteorological parameters. If during the winter thermal plume is localized to an area of a few km of NPP, the temperature difference between the plume and non-plume areas being about 1.5 oC, during summer and fall , is a larger thermal plume up to 5-6 km far along Danube Black Sea Canal ,the temperature change is about 1.0 oC.

Analyzing and leveraging self-similarity for variable resolution atmospheric models

NASA Astrophysics Data System (ADS)

O'Brien, Travis; Collins, William

2015-04-01

Variable resolution modeling techniques are rapidly becoming a popular strategy for achieving high resolution in a global atmospheric models without the computational cost of global high resolution. However, recent studies have demonstrated a variety of resolution-dependent, and seemingly artificial, features. We argue that the scaling properties of the atmosphere are key to understanding how the statistics of an atmospheric model should change with resolution. We provide two such examples. In the first example we show that the scaling properties of the cloud number distribution define how the ratio of resolved to unresolved clouds should increase with resolution. We show that the loss of resolved clouds, in the high resolution region of variable resolution simulations, with the Community Atmosphere Model version 4 (CAM4) is an artifact of the model's treatment of condensed water (this artifact is significantly reduced in CAM5). In the second example we show that the scaling properties of the horizontal velocity field, combined with the incompressibility assumption, necessarily result in an intensification of vertical mass flux as resolution increases. We show that such an increase is present in a wide variety of models, including CAM and the regional climate models of the ENSEMBLES intercomparision. We present theoretical arguments linking this increase to the intensification of precipitation with increasing resolution.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Fan, E-mail: zf5016@126.com; Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin 150080; Tan, Xinran

An autocollimation (AC) setup with ultra-high resolution and stability for micro-angle measurement is presented. The telephoto objective, which is characterized in long focal length at a compact structure size, and the optical enlargement unit, which can magnify the image displacement to improve its measurement resolution and accuracy, are used to obtain an ultra-high measurement resolution of the AC. The common-path beam drift compensation is used to suppress the drift of measurement results, which is evident in the high-resolution AC, thus to obtain a high measurement stability. Experimental results indicate that an effective resolution of better than 0.0005 arc sec (2.42more » nrad) over a measurement range of ±30 arc sec and a 2-h stability of 0.0061 arc sec (29.57 nrad) can be achieved.« less

Comparing Magnetic Resonance Imaging and High-Resolution Dynamic Ultrasonography for Diagnosis of Plantar Plate Pathology: A Case Series.

PubMed

Donegan, Ryan J; Stauffer, Anthony; Heaslet, Michael; Poliskie, Michael

Plantar plate pathology has gained noticeable attention in recent years as an etiology of lesser metatarsophalangeal joint pain. The heightened clinical awareness has led to the need for more effective diagnostic imaging accuracy. Numerous reports have established the accuracy of both magnetic resonance imaging and ultrasonography for the diagnosis of plantar plate pathology. However, no conclusions have been made regarding which is the superior imaging modality. The present study reports a case series directly comparing high-resolution dynamic ultrasonography and magnetic resonance imaging. A multicenter retrospective comparison of magnetic resonance imaging versus high-resolution dynamic ultrasonography to evaluate plantar plate pathology with surgical confirmation was conducted. The sensitivity, specificity, and positive and negative predictive values for magnetic resonance imaging were 60%, 100%, 100%, and 33%, respectively. The overall diagnostic accuracy compared with the intraoperative findings was 66%. The sensitivity, specificity, and positive and negative predictive values for high-resolution dynamic ultrasound imaging were 100%, 100%, 100%, and 100%, respectively. The overall diagnostic accuracy compared with the intraoperative findings was 100%. The p value using Fisher's exact test for magnetic resonance imaging and high-resolution dynamic ultrasonography was p = .45, a difference that was not statistically significant. High-resolution dynamic ultrasonography had greater accuracy than magnetic resonance imaging in diagnosing lesser metatarsophalangeal joint plantar plate pathology, although the difference was not statistically significant. The present case series suggests that high-resolution dynamic ultrasonography can be considered an equally accurate imaging modality for plantar plate pathology at a potential cost savings compared with magnetic resonance imaging. Therefore, high-resolution dynamic ultrasonography warrants further investigation in a prospective study. Copyright © 2016 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Adaptive optics high-resolution IR spectroscopy with silicon grisms and immersion gratings

NASA Astrophysics Data System (ADS)

Ge, Jian; McDavitt, Daniel L.; Chakraborty, Abhijit; Bernecker, John L.; Miller, Shane

2003-02-01

The breakthrough of silicon immersion grating technology at Penn State has the ability to revolutionize high-resolution infrared spectroscopy when it is coupled with adaptive optics at large ground-based telescopes. Fabrication of high quality silicon grism and immersion gratings up to 2 inches in dimension, less than 1% integrated scattered light, and diffraction-limited performance becomes a routine process thanks to newly developed techniques. Silicon immersion gratings with etched dimensions of ~ 4 inches are being developed at Penn State. These immersion gratings will be able to provide a diffraction-limited spectral resolution of R = 300,000 at 2.2 micron, or 130,000 at 4.6 micron. Prototype silicon grisms have been successfully used in initial scientific observations at the Lick 3m telescope with adaptive optics. Complete K band spectra of a total of 6 T Tauri and Ae/Be stars and their close companions at a spectral resolution of R ~ 3000 were obtained. This resolving power was achieved by using a silicon echelle grism with a 5 mm pupil diameter in an IR camera. These results represent the first scientific observations conducted by the high-resolution silicon grisms, and demonstrate the extremely high dispersing power of silicon-based gratings. New discoveries from this high spatial and spectral resolution IR spectroscopy will be reported. The future of silicon-based grating applications in ground-based AO IR instruments is promising. Silicon immersion gratings will make very high-resolution spectroscopy (R > 100,000) feasible with compact instruments for implementation on large telescopes. Silicon grisms will offer an efficient way to implement low-cost medium to high resolution IR spectroscopy (R ~ 1000-50000) through the conversion of existing cameras into spectrometers by locating a grism in the instrument's pupil location.

High Resolution CryoFESEM of Microbial Surfaces

NASA Astrophysics Data System (ADS)

Erlandsen, Stanley; Lei, Ming; Martin-Lacave, Ines; Dunny, Gary; Wells, Carol

2003-08-01

The outer surfaces of three microorganisms, Giardia lamblia, Enterococcus faecalis, and Proteus mirabilis, were investigated by cryo-immobilization followed by sublimation of extracellular ice and cryocoating with either Pt alone or Pt plus carbon. Cryocoated samples were examined at [minus sign]125°C in either an in-lens field emission SEM or a below-the-lens field emission SEM. Cryocoating with Pt alone was sufficient for low magnification observation, but attempts to do high-resolution imaging resulted in radiolysis and cracking of the specimen surface. Double coating with Pt and carbon, in combination with high resolution backscatter electron detectors, enabled high-resolution imaging of the glycocalyx of bacteria, revealing a sponge-like network over the surface. High resolution examination of bacterial flagella also revealed a periodic substructure. Common artifacts included radiolysis leading to “cracking” of the surface, and insufficient deposition of Pt resulting in the absence of detectable surface topography.

Research relative to high resolution camera on the advanced X-ray astrophysics facility

NASA Technical Reports Server (NTRS)

1986-01-01

The HRC (High Resolution Camera) is a photon counting instrument to be flown on the Advanced X-Ray Astrophysics Facility (AXAF). It is a large field of view, high angular resolution, detector for the x-ray telescope. The HRC consists of a CsI coated microchannel plate (MCP) acting as a soft x-ray photocathode, followed by a second MCP for high electronic gain. The MCPs are readout by a crossed grid of resistively coupled wires to provide high spatial resolution along with timing and pulse height data. The instrument will be used in two modes, as a direct imaging detector with a limiting sensitivity of 10 to the -15 ergs sq cm sec in a 10 to the 5th second exposure, and as a readout for an objective transmission grating providing spectral resolution of several hundreds to thousands.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Donald F.; Schulz, Carl; Konijnenburg, Marco

High-resolution Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging enables the spatial mapping and identification of biomolecules from complex surfaces. The need for long time-domain transients, and thus large raw file sizes, results in a large amount of raw data (“big data”) that must be processed efficiently and rapidly. This can be compounded by largearea imaging and/or high spatial resolution imaging. For FT-ICR, data processing and data reduction must not compromise the high mass resolution afforded by the mass spectrometer. The continuous mode “Mosaic Datacube” approach allows high mass resolution visualization (0.001 Da) of mass spectrometry imaging data, butmore » requires additional processing as compared to featurebased processing. We describe the use of distributed computing for processing of FT-ICR MS imaging datasets with generation of continuous mode Mosaic Datacubes for high mass resolution visualization. An eight-fold improvement in processing time is demonstrated using a Dutch nationally available cloud service.« less

High Resolution Tissue Imaging Using the Single-probe Mass Spectrometry under Ambient Conditions

NASA Astrophysics Data System (ADS)

Rao, Wei; Pan, Ning; Yang, Zhibo

2015-06-01

Ambient mass spectrometry imaging (MSI) is an emerging field with great potential for the detailed spatial analysis of biological samples with minimal pretreatment. We have developed a miniaturized sampling and ionization device, the Single-probe, which uses in-situ surface micro-extraction to achieve high detection sensitivity and spatial resolution during MSI experiments. The Single-probe was coupled to a Thermo LTQ Orbitrap XL mass spectrometer and was able to create high spatial and high mass resolution MS images at 8 ± 2 and 8.5 μm on flat polycarbonate microscope slides and mouse kidney sections, respectively, which are among the highest resolutions available for ambient MSI techniques. Our proof-of-principle experiments indicate that the Single-probe MSI technique has the potential to obtain ambient MS images with very high spatial resolutions with minimal sample preparation, which opens the possibility for subcellular ambient tissue MSI to be performed in the future.

High spatial resolution compressed sensing (HSPARSE) functional MRI.

PubMed

Fang, Zhongnan; Van Le, Nguyen; Choy, ManKin; Lee, Jin Hyung

2016-08-01

To propose a novel compressed sensing (CS) high spatial resolution functional MRI (fMRI) method and demonstrate the advantages and limitations of using CS for high spatial resolution fMRI. A randomly undersampled variable density spiral trajectory enabling an acceleration factor of 5.3 was designed with a balanced steady state free precession sequence to achieve high spatial resolution data acquisition. A modified k-t SPARSE method was then implemented and applied with a strategy to optimize regularization parameters for consistent, high quality CS reconstruction. The proposed method improves spatial resolution by six-fold with 12 to 47% contrast-to-noise ratio (CNR), 33 to 117% F-value improvement and maintains the same temporal resolution. It also achieves high sensitivity of 69 to 99% compared the original ground-truth, small false positive rate of less than 0.05 and low hemodynamic response function distortion across a wide range of CNRs. The proposed method is robust to physiological noise and enables detection of layer-specific activities in vivo, which cannot be resolved using the highest spatial resolution Nyquist acquisition. The proposed method enables high spatial resolution fMRI that can resolve layer-specific brain activity and demonstrates the significant improvement that CS can bring to high spatial resolution fMRI. Magn Reson Med 76:440-455, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Comparing high-resolution microscopy techniques for potential intraoperative use in guiding low-grade glioma resections.

PubMed

Meza, Daphne; Wang, Danni; Wang, Yu; Borwege, Sabine; Sanai, Nader; Liu, Jonathan T C

2015-04-01

Fluorescence image-guided surgery (FIGS), with contrast provided by 5-ALA-induced PpIX, has been shown to enable a higher extent of resection of high-grade gliomas. However, conventional FIGS with low-power microscopy lacks the sensitivity to aid in low-grade glioma (LGG) resection because PpIX signal is weak and sparse in such tissues. Intraoperative high-resolution microscopy of PpIX fluorescence has been proposed as a method to guide LGG resection, where sub-cellular resolution allows for the visualization of sparse and punctate mitochondrial PpIX production in tumor cells. Here, we assess the performance of three potentially portable high-resolution microscopy techniques that may be used for the intraoperative imaging of human LGG tissue samples with PpIX contrast: high-resolution fiber-optic microscopy (HRFM), high-resolution wide-field microscopy (WFM), and dual-axis confocal (DAC) microscopy. Thick unsectioned human LGG tissue samples (n = 7) with 5-ALA-induced PpIX contrast were imaged using three imaging techniques (HRFM, WFM, DAC). The average signal-to-background ratio (SBR) was then calculated for each imaging modality (5 images per tissue, per modality). HRFM provides the ease of use and portability of a flexible fiber bundle, and is simple and inexpensive to build. However, in most cases (6/7), HRFM is not capable of detecting PpIX signal from LGGs due to high autofluorescence, generated by the fiber bundle under laser illumination at 405 nm, which overwhelms the PpIX signal and impedes its visualization. WFM is a camera-based method possessing high lateral resolution but poor axial resolution, resulting in sub-optimal image contrast. Consistent successful detection of PpIX signal throughout our human LGG tissue samples (n = 7), with an acceptable image contrast (SBR >2), was only achieved using DAC microscopy, which offers superior image resolution and contrast that is comparable to histology, but requires a laser-scanning mechanism to achieve optical sectioning. © 2015 Wiley Periodicals, Inc.

Submicron-resolution photoacoustic microscopy of endogenous light-absorbing biomolecules

NASA Astrophysics Data System (ADS)

Zhang, Chi

Photoacoustic imaging in biomedicine has the unique advantage of probing endogenous light absorbers at various length scales with a 100% relative sensitivity. Among the several modalities of photoacoustic imaging, optical-resolution photoacoustic microscopy (OR-PAM) can achieve high spatial resolution, on the order of optical wavelength, at <1 mm depth in biological tissue (the optical ballistic regime). OR-PAM has been applied successfully to structural and functional imaging of blood vasculature and red blood cells in vivo. Any molecules which absorb sufficient light at certain wavelengths can potentially be imaged by PAM. Compared with pure optical imaging, which typically targets fluorescent markers, label-free PAM avoids the major concerns that the fluorescent labeling probes may disturb the function of biomolecules and may have an insufficient density. This dissertation aims to advance label-free OR-PAM to the subcellular scale. The first part of this dissertation describes the technological advancement of PAM yielding high spatial resolution in 3D. The lateral resolution was improved by using optical objectives with high numerical apertures for optical focusing. The axial resolution was improved by using broadband ultrasonic transducers for ultrasound detection. We achieved 220 nm lateral resolution in transmission mode, 0.43 microm lateral resolution in reflection mode, 7.6 microm axial resolution in normal tissue, and 5.8 microm axial resolution with silicone oil immersion/injection. The achieved lateral resolution and axial resolution were the finest reported at the time. With high-resolution in 3D, PAM was demonstrated to resolve cellular and subcellular structures in vivo, such as red blood cells and melanosomes in melanoma cells. Compared with previous PAM systems, our high-resolution PAM could resolve capillaries in mouse ears more clearly. As an example application, we demonstrated intracellular temperature imaging, assisted by fluorescence signal detection, with sub-degree temperature resolution and sub-micron lateral resolution. The second part of this dissertation describes the exploration of endogenous light-absorbing biomolecules for PAM. We demonstrated cytochromes and myoglobin as new absorption contrasts for PAM and identified the corresponding optimal wavelengths for imaging. Fixed fibroblasts on slides and mouse ear sections were imaged by PAM at 422 nm and 250 nm wavelengths to reveal cytoplasms and nuclei, respectively, as confirmed by standard hematoxylin and eosin (H&E) histology. By imaging a blood-perfused mouse heart at 532 nm down to 150 microm in depth, we derived the myocardial sheet thickness and the cleavage height from an undehydrated heart for the first time. The findings promote PAM at new wavelengths and open up new possibilities for characterizing biological tissue. Of particular interest, dual-wavelength PAM around 250 nm and 420 nm wavelengths is analogous to H&E histology. The last part of this dissertation describes the development of sectioning photoacoustic microscopy (SPAM), based on the advancement in spatial resolution and new contrasts for PAM, with applications in brain histology. Label-free SPAM, assisted by a microtome, acquires serial distortion-free images of a specimen on the surface. By exciting cell nuclei at 266 nm wavelength with high resolution, SPAM could pinpoint cell nuclei sensitively and specifically in the mouse brain section, as confirmed by H&E histology. SPAM was demonstrated to generate high-resolution 3D images, highlighting cell nuclei, of formalin-fixed paraffin-embedded mouse brains without tissue staining or clearing. SPAM can potentially serve as a high-throughput and minimal-artifact substitute for histology, probe many other biomolecules and cells, and become a universal tool for animal or human whole-organ microscopy, with diverse applications in life sciences.

Effects of spatial resolution ratio in image fusion

USGS Publications Warehouse

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2008-01-01

In image fusion, the spatial resolution ratio can be defined as the ratio between the spatial resolution of the high-resolution panchromatic image and that of the low-resolution multispectral image. This paper attempts to assess the effects of the spatial resolution ratio of the input images on the quality of the fused image. Experimental results indicate that a spatial resolution ratio of 1:10 or higher is desired for optimal multisensor image fusion provided the input panchromatic image is not downsampled to a coarser resolution. Due to the synthetic pixels generated from resampling, the quality of the fused image decreases as the spatial resolution ratio decreases (e.g. from 1:10 to 1:30). However, even with a spatial resolution ratio as small as 1:30, the quality of the fused image is still better than the original multispectral image alone for feature interpretation. In cases where the spatial resolution ratio is too small (e.g. 1:30), to obtain better spectral integrity of the fused image, one may downsample the input high-resolution panchromatic image to a slightly lower resolution before fusing it with the multispectral image.

Extended-range high-resolution dynamical downscaling over a continental-scale spatial domain with atmospheric and surface nudging

NASA Astrophysics Data System (ADS)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

Extended-range high-resolution mesoscale simulations with limited-area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather-dependent renewable energy industry. Long-term simulations over a continental-scale spatial domain, however, require mechanisms to control the large-scale deviations in the high-resolution simulated fields from the coarse-resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high-resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time-varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high-resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high-resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended-range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal resolution.

The fusion of satellite and UAV data: simulation of high spatial resolution band

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

High-resolution ultrashort echo time (UTE) imaging on human knee with AWSOS sequence at 3.0 T.

PubMed

Qian, Yongxian; Williams, Ashley A; Chu, Constance R; Boada, Fernando E

2012-01-01

To demonstrate the technical feasibility of high-resolution (0.28-0.14 mm) ultrashort echo time (UTE) imaging on human knee at 3T with the acquisition-weighted stack of spirals (AWSOS) sequence. Nine human subjects were scanned on a 3T MRI scanner with an 8-channel knee coil using the AWSOS sequence and isocenter positioning plus manual shimming. High-resolution UTE images were obtained on the subject knees at TE = 0.6 msec with total acquisition time of 5.12 minutes for 60 slices at an in-plane resolution of 0.28 mm and 10.24 minutes for 40 slices at an in-plane resolution of 0.14 mm. Isocenter positioning, manual shimming, and the 8-channel array coil helped minimize image distortion and achieve high signal-to-noise ratio (SNR). It is technically feasible on a clinical 3T MRI scanner to perform UTE imaging on human knee at very high spatial resolutions (0.28-0.14 mm) within reasonable scan time (5-10 min) using the AWSOS sequence. Copyright © 2011 Wiley Periodicals, Inc.

High-resolution DEM Effects on Geophysical Flow Models

NASA Astrophysics Data System (ADS)

Williams, M. R.; Bursik, M. I.; Stefanescu, R. E. R.; Patra, A. K.

2014-12-01

Geophysical mass flow models are numerical models that approximate pyroclastic flow events and can be used to assess the volcanic hazards certain areas may face. One such model, TITAN2D, approximates granular-flow physics based on a depth-averaged analytical model using inputs of basal and internal friction, material volume at a coordinate point, and a GIS in the form of a digital elevation model (DEM). The volume of modeled material propagates over the DEM in a way that is governed by the slope and curvature of the DEM surface and the basal and internal friction angles. Results from TITAN2D are highly dependent upon the inputs to the model. Here we focus on a single input: the DEM, which can vary in resolution. High resolution DEMs are advantageous in that they contain more surface details than lower-resolution models, presumably allowing modeled flows to propagate in a way more true to the real surface. However, very high resolution DEMs can create undesirable artifacts in the slope and curvature that corrupt flow calculations. With high-resolution DEMs becoming more widely available and preferable for use, determining the point at which high resolution data is less advantageous compared to lower resolution data becomes important. We find that in cases of high resolution, integer-valued DEMs, very high-resolution is detrimental to good model outputs when moderate-to-low (<10-15°) slope angles are involved. At these slope angles, multiple adjacent DEM cell elevation values are equal due to the need for the DEM to approximate the low slope with a limited set of integer values for elevation. The first derivative of the elevation surface thus becomes zero. In these cases, flow propagation is inhibited by these spurious zero-slope conditions. Here we present evidence for this "terracing effect" from 1) a mathematically defined simulated elevation model, to demonstrate the terracing effects of integer valued data, and 2) a real-world DEM where terracing must be addressed. We discuss the effect on the flow model output and present possible solutions for rectification of the problem.

Fabrication and characterization of a 0.5-mm lutetium oxyorthosilicate detector array for high-resolution PET applications.

PubMed

Stickel, Jennifer R; Qi, Jinyi; Cherry, Simon R

2007-01-01

With the increasing use of in vivo imaging in mouse models of disease, there are many interesting applications that demand imaging of organs and tissues with submillimeter resolution. Though there are other contributing factors, the spatial resolution in small-animal PET is still largely determined by the detector pixel dimensions. In this work, a pair of lutetium oxyorthosilicate (LSO) arrays with 0.5-mm pixels was coupled to multichannel photomultiplier tubes and evaluated for use as high-resolution PET detectors. Flood histograms demonstrated that most crystals were clearly identifiable. Energy resolution varied from 22% to 38%. The coincidence timing resolution was 1.42-ns full width at half maximum (FWHM). The intrinsic spatial resolution was 0.68-mm FWHM as measured with a 30-gauge needle filled with (18)F. The improvement in spatial resolution in a tomographic setting is demonstrated using images of a line source phantom reconstructed with filtered backprojection and compared with images obtained from 2 dedicated small-animal PET scanners. Finally, a projection image of the mouse foot is shown to demonstrate the application of these 0.5-mm LSO detectors to a biologic task. A pair of highly pixelated LSO detections has been constructed and characterized for use as high-spatial-resolution PET detectors. It appears that small-animal PET systems capable of a FWHM spatial resolution of 600 microm or less are feasible and should be pursued.

FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry.

PubMed

Palmer, Andrew; Phapale, Prasad; Chernyavsky, Ilya; Lavigne, Regis; Fay, Dominik; Tarasov, Artem; Kovalev, Vitaly; Fuchser, Jens; Nikolenko, Sergey; Pineau, Charles; Becker, Michael; Alexandrov, Theodore

2017-01-01

High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites in tissues, cell cultures, and agar plates with cellular resolution, but it is hampered by the lack of bioinformatics tools for automated metabolite identification. We report pySM, a framework for false discovery rate (FDR)-controlled metabolite annotation at the level of the molecular sum formula, for high-mass-resolution imaging mass spectrometry (https://github.com/alexandrovteam/pySM). We introduce a metabolite-signal match score and a target-decoy FDR estimate for spatial metabolomics.

High Resolution Gamma Ray Spectroscopy at MHz Counting Rates With LaBr3 Scintillators for Fusion Plasma Applications

NASA Astrophysics Data System (ADS)

Nocente, M.; Tardocchi, M.; Olariu, A.; Olariu, S.; Pereira, R. C.; Chugunov, I. N.; Fernandes, A.; Gin, D. B.; Grosso, G.; Kiptily, V. G.; Neto, A.; Shevelev, A. E.; Silva, M.; Sousa, J.; Gorini, G.

2013-04-01

High resolution γ-ray spectroscopy measurements at MHz counting rates were carried out at nuclear accelerators, combining a LaBr 3(Ce) detector with dedicated hardware and software solutions based on digitization and off-line analysis. Spectra were measured at counting rates up to 4 MHz, with little or no degradation of the energy resolution, adopting a pile up rejection algorithm. The reported results represent a step forward towards the final goal of high resolution γ-ray spectroscopy measurements on a burning plasma device.

High resolution gamma-ray spectroscopy at high count rates with a prototype High Purity Germanium detector

NASA Astrophysics Data System (ADS)

Cooper, R. J.; Amman, M.; Vetter, K.

2018-04-01

High-resolution gamma-ray spectrometers are required for applications in nuclear safeguards, emergency response, and fundamental nuclear physics. To overcome one of the shortcomings of conventional High Purity Germanium (HPGe) detectors, we have developed a prototype device capable of achieving high event throughput and high energy resolution at very high count rates. This device, the design of which we have previously reported on, features a planar HPGe crystal with a reduced-capacitance strip electrode geometry. This design is intended to provide good energy resolution at the short shaping or digital filter times that are required for high rate operation and which are enabled by the fast charge collection afforded by the planar geometry crystal. In this work, we report on the initial performance of the system at count rates up to and including two million counts per second.

High-Resolution of Electron Microscopy of Montmorillonite and Montmorillonite/Epoxy Nanocomposites

DTIC Science & Technology

2005-01-01

AFRL-ML-WP-TP-2006-464 HIGH-RESOLUTION OF ELECTRON MICROSCOPY OF MONTMORILLONITE AND MONTMORILLONITE /EPOXY NANOCOMPOSITES Lawrence F...HIGH-RESOLUTION OF ELECTRON MICROSCOPY OF MONTMORILLONITE AND MONTMORILLONITE /EPOXY NANOCOMPOSITES 5c. PROGRAM ELEMENT NUMBER 62102F 5d...transmission electron microscopy the structure and morphology of montmorillonite (MMT), a material of current interest for use in polymer nanocomposites, was

High resolution scintillation detector with semiconductor readout

DOEpatents

Levin, Craig S.; Hoffman, Edward J.

2000-01-01

A novel high resolution scintillation detector array for use in radiation imaging such as high resolution Positron Emission Tomography (PET) which comprises one or more parallelepiped crystals with at least one long surface of each crystal being in intimate contact with a semiconductor photodetector such that photons generated within each crystal by gamma radiation passing therethrough is detected by the photodetector paired therewith.

High-resolution ground-based spectroscopy: where and how ?

NASA Astrophysics Data System (ADS)

Pallavicini, R.

2002-07-01

An overview is presented of high-resolution optical spectrographs in operation or under development at large telescopes, with emphasis on those facilities best suited for the study of late-type stars and stellar surface inhomogeneities. Plans for the development of new high-resolution spectroscopic instruments are discussed with emphasis on the ICE spectrograph for the PEPSI spectropolarimeter at the LBT.

Microdome-gooved Gd(2)O(2)S:Tb scintillator for flexible and high resolution digital radiography.

PubMed

Jung, Phill Gu; Lee, Chi Hoon; Bae, Kong Myeong; Lee, Jae Min; Lee, Sang Min; Lim, Chang Hwy; Yun, Seungman; Kim, Ho Kyung; Ko, Jong Soo

2010-07-05

A flexible microdome-grooved Gd(2)O(2)S:Tb scintillator is simulated, fabricated, and characterized for digital radiography applications. According to Monte Carlo simulation results, the dome-grooved structure has a high spatial resolution, which is verified by X-ray image performance of the scintillator. The proposed scintillator has lower X-ray sensitivity than a nonstructured scintillator but almost two times higher spatial resolution at high spatial frequency. Through evaluation of the X-ray performance of the fabricated scintillators, we confirm that the microdome-grooved scintillator can be applied to next-generation flexible digital radiography systems requiring high spatial resolution.

Length-extension resonator as a force sensor for high-resolution frequency-modulation atomic force microscopy in air.

PubMed

Beyer, Hannes; Wagner, Tino; Stemmer, Andreas

2016-01-01

Frequency-modulation atomic force microscopy has turned into a well-established method to obtain atomic resolution on flat surfaces, but is often limited to ultra-high vacuum conditions and cryogenic temperatures. Measurements under ambient conditions are influenced by variations of the dew point and thin water layers present on practically every surface, complicating stable imaging with high resolution. We demonstrate high-resolution imaging in air using a length-extension resonator operating at small amplitudes. An additional slow feedback compensates for changes in the free resonance frequency, allowing stable imaging over a long period of time with changing environmental conditions.

High-Resolution NMR Reveals Secondary Structure and Folding of Amino Acid Transporter from Outer Chloroplast Membrane

PubMed Central

Zook, James D.; Molugu, Trivikram R.; Jacobsen, Neil E.; Lin, Guangxin; Soll, Jürgen; Cherry, Brian R.; Brown, Michael F.; Fromme, Petra

2013-01-01

Solving high-resolution structures for membrane proteins continues to be a daunting challenge in the structural biology community. In this study we report our high-resolution NMR results for a transmembrane protein, outer envelope protein of molar mass 16 kDa (OEP16), an amino acid transporter from the outer membrane of chloroplasts. Three-dimensional, high-resolution NMR experiments on the 13C, 15N, 2H-triply-labeled protein were used to assign protein backbone resonances and to obtain secondary structure information. The results yield over 95% assignment of N, HN, CO, Cα, and Cβ chemical shifts, which is essential for obtaining a high resolution structure from NMR data. Chemical shift analysis from the assignment data reveals experimental evidence for the first time on the location of the secondary structure elements on a per residue basis. In addition T 1Z and T2 relaxation experiments were performed in order to better understand the protein dynamics. Arginine titration experiments yield an insight into the amino acid residues responsible for protein transporter function. The results provide the necessary basis for high-resolution structural determination of this important plant membrane protein. PMID:24205117

The implementation of sea ice model on a regional high-resolution scale

NASA Astrophysics Data System (ADS)

Prasad, Siva; Zakharov, Igor; Bobby, Pradeep; McGuire, Peter

2015-09-01

The availability of high-resolution atmospheric/ocean forecast models, satellite data and access to high-performance computing clusters have provided capability to build high-resolution models for regional ice condition simulation. The paper describes the implementation of the Los Alamos sea ice model (CICE) on a regional scale at high resolution. The advantage of the model is its ability to include oceanographic parameters (e.g., currents) to provide accurate results. The sea ice simulation was performed over Baffin Bay and the Labrador Sea to retrieve important parameters such as ice concentration, thickness, ridging, and drift. Two different forcing models, one with low resolution and another with a high resolution, were used for the estimation of sensitivity of model results. Sea ice behavior over 7 years was simulated to analyze ice formation, melting, and conditions in the region. Validation was based on comparing model results with remote sensing data. The simulated ice concentration correlated well with Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and Ocean and Sea Ice Satellite Application Facility (OSI-SAF) data. Visual comparison of ice thickness trends estimated from the Soil Moisture and Ocean Salinity satellite (SMOS) agreed with the simulation for year 2010-2011.

Ultrahigh Frequency (100 MHz–300 MHz) Ultrasonic Transducers for Optical Resolution Medical Imagining

PubMed Central

Fei, Chunlong; Chiu, Chi Tat; Chen, Xiaoyang; Chen, Zeyu; Ma, Jianguo; Zhu, Benpeng; Shung, K. Kirk; Zhou, Qifa

2016-01-01

High resolution ultrasonic imaging requires high frequency wide band ultrasonic transducers, which produce short pulses and highly focused beam. However, currently the frequency of ultrasonic transducers is limited to below 100 MHz, mainly because of the challenge in precise control of fabrication parameters. This paper reports the design, fabrication, and characterization of sensitive broadband lithium niobate (LiNbO3) single element ultrasonic transducers in the range of 100–300 MHz, as well as their applications in high resolution imaging. All transducers were built for an f-number close to 1.0, which was achieved by press-focusing the piezoelectric layer into a spherical curvature. Characterization results demonstrated their high sensitivity and a −6 dB bandwidth greater than 40%. Resolutions better than 6.4 μm in the lateral direction and 6.2 μm in the axial direction were achieved by scanning a 4 μm tungsten wire target. Ultrasonic biomicroscopy images of zebrafish eyes were obtained with these transducers which demonstrate the feasibility of high resolution imaging with a performance comparable to optical resolution. PMID:27329379

Wavelength scanning achieves pixel super-resolution in holographic on-chip microscopy

NASA Astrophysics Data System (ADS)

Luo, Wei; Göröcs, Zoltan; Zhang, Yibo; Feizi, Alborz; Greenbaum, Alon; Ozcan, Aydogan

2016-03-01

Lensfree holographic on-chip imaging is a potent solution for high-resolution and field-portable bright-field imaging over a wide field-of-view. Previous lensfree imaging approaches utilize a pixel super-resolution technique, which relies on sub-pixel lateral displacements between the lensfree diffraction patterns and the image sensor's pixel-array, to achieve sub-micron resolution under unit magnification using state-of-the-art CMOS imager chips, commonly used in e.g., mobile-phones. Here we report, for the first time, a wavelength scanning based pixel super-resolution technique in lensfree holographic imaging. We developed an iterative super-resolution algorithm, which generates high-resolution reconstructions of the specimen from low-resolution (i.e., under-sampled) diffraction patterns recorded at multiple wavelengths within a narrow spectral range (e.g., 10-30 nm). Compared with lateral shift-based pixel super-resolution, this wavelength scanning approach does not require any physical shifts in the imaging setup, and the resolution improvement is uniform in all directions across the sensor-array. Our wavelength scanning super-resolution approach can also be integrated with multi-height and/or multi-angle on-chip imaging techniques to obtain even higher resolution reconstructions. For example, using wavelength scanning together with multi-angle illumination, we achieved a halfpitch resolution of 250 nm, corresponding to a numerical aperture of 1. In addition to pixel super-resolution, the small scanning steps in wavelength also enable us to robustly unwrap phase, revealing the specimen's optical path length in our reconstructed images. We believe that this new wavelength scanning based pixel super-resolution approach can provide competitive microscopy solutions for high-resolution and field-portable imaging needs, potentially impacting tele-pathology applications in resource-limited-settings.

ON THE IMPACT OF SUPER RESOLUTION WSR-88D DOPPLER RADAR DATA ASSIMILATION ON HIGH RESOLUTION NUMERICAL MODEL FORECASTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiswell, S

2009-01-11

Assimilation of radar velocity and precipitation fields into high-resolution model simulations can improve precipitation forecasts with decreased 'spin-up' time and improve short-term simulation of boundary layer winds (Benjamin, 2004 & 2007; Xiao, 2008) which is critical to improving plume transport forecasts. Accurate description of wind and turbulence fields is essential to useful atmospheric transport and dispersion results, and any improvement in the accuracy of these fields will make consequence assessment more valuable during both routine operation as well as potential emergency situations. During 2008, the United States National Weather Service (NWS) radars implemented a significant upgrade which increased the real-timemore » level II data resolution to 8 times their previous 'legacy' resolution, from 1 km range gate and 1.0 degree azimuthal resolution to 'super resolution' 250 m range gate and 0.5 degree azimuthal resolution (Fig 1). These radar observations provide reflectivity, velocity and returned power spectra measurements at a range of up to 300 km (460 km for reflectivity) at a frequency of 4-5 minutes and yield up to 13.5 million point observations per level in super-resolution mode. The migration of National Weather Service (NWS) WSR-88D radars to super resolution is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current operational mesoscale model domains utilize grid spacing several times larger than the legacy data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of super resolution reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution is investigated here to determine the impact of the improved data resolution on model predictions.« less

Survey of currently available high-resolution raster graphics systems

NASA Technical Reports Server (NTRS)

Jones, Denise R.

1987-01-01

Presented are data obtained on high-resolution raster graphics engines currently available on the market. The data were obtained through survey responses received from various vendors and also from product literature. The questionnaire developed for this survey was basically a list of characteristics desired in a high performance color raster graphics system which could perform real-time aircraft simulations. Several vendors responded to the survey, with most reporting on their most advanced high-performance, high-resolution raster graphics engine.

Bibliography of In-House and Contract Reports. Supplement 17

DTIC Science & Technology

1991-10-01

Area Exit Pupil Viewer ETL-0399 1985 63 TILE REPORT NO. YEAR Extension of Kendall’s Concordance Test Where ETL-0316 1983 Ties are Allowed, An Extraction...Phase 11 ETL-0360 1984 High Resolution Optical Power Spectrum Analyzer ETL-0127 1978 High Resolution Orthophoto Output Table (HIROOT) AD 856 731L 1969...High Resolution Orthophoto Output Table ETL-ETR-72-3 1972 High Speed Disc Memory and a Color Image AD 878 975L 1970 Display for a Small Computer High

High Resolution Live Cell Raman Imaging Using Subcellular Organelle-Targeting SERS-Sensitive Gold Nanoparticles with Highly Narrow Intra-Nanogap

PubMed Central

Kang, Jeon Woong; So, Peter T. C.; Dasari, Ramachandra R.; Lim, Dong-Kwon

2015-01-01

We report a method to achieve high speed and high resolution live cell Raman images using small spherical gold nanoparticles with highly narrow intra-nanogap structures responding to NIR excitation (785 nm) and high-speed confocal Raman microscopy. The three different Raman-active molecules placed in the narrow intra-nanogap showed a strong and uniform Raman intensity in solution even under transient exposure time (10 ms) and low input power of incident laser (200 μW), which lead to obtain high-resolution single cell image within 30 s without inducing significant cell damage. The high resolution Raman image showed the distributions of gold nanoparticles for their targeted sites such as cytoplasm, mitochondria, or nucleus. The high speed Raman-based live cell imaging allowed us to monitor rapidly changing cell morphologies during cell death induced by the addition of highly toxic KCN solution to cells. These results strongly suggest that the use of SERS-active nanoparticle can greatly improve the current temporal resolution and image quality of Raman-based cell images enough to obtain the detailed cell dynamics and/or the responses of cells to potential drug molecules. PMID:25646716

High-resolution MRI in detecting subareolar breast abscess.

PubMed

Fu, Peifen; Kurihara, Yasuyuki; Kanemaki, Yoshihide; Okamoto, Kyoko; Nakajima, Yasuo; Fukuda, Mamoru; Maeda, Ichiro

2007-06-01

Because subareolar breast abscess has a high recurrence rate, a more effective imaging technique is needed to comprehensively visualize the lesions and guide surgery. We performed a high-resolution MRI technique using a microscopy coil to reveal the characteristics and extent of subareolar breast abscess. High-resolution MRI has potential diagnostic value in subareolar breast abscess. This technique can be used to guide surgery with the aim of reducing the recurrence rate.

Evaluating the Value of High Spatial Resolution in National Capacity Expansion Models using ReEDS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Venkat; Cole, Wesley

2016-11-14

Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERCmore » region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.« less

In vivo high-resolution cortical imaging with extended-focus optical coherence microscopy in the visible-NIR wavelength range

NASA Astrophysics Data System (ADS)

Marchand, Paul J.; Szlag, Daniel; Bouwens, Arno; Lasser, Theo

2018-03-01

Visible light optical coherence tomography has shown great interest in recent years for spectroscopic and high-resolution retinal and cerebral imaging. Here, we present an extended-focus optical coherence microscopy system operating from the visible to the near-infrared wavelength range for high axial and lateral resolution imaging of cortical structures in vivo. The system exploits an ultrabroad illumination spectrum centered in the visible wavelength range (λc = 650 nm, Δλ ˜ 250 nm) offering a submicron axial resolution (˜0.85 μm in water) and an extended-focus configuration providing a high lateral resolution of ˜1.4 μm maintained over ˜150 μm in depth in water. The system's axial and lateral resolution are first characterized using phantoms, and its imaging performance is then demonstrated by imaging the vasculature, myelinated axons, and neuronal cells in the first layers of the somatosensory cortex of mice in vivo.

Using High Spatial Resolution to Improve BOLD fMRI Detection at 3T

PubMed Central

Claise, Béatrice; Jean, Betty

2015-01-01

For different functional magnetic resonance imaging experiments using blood oxygenation level-dependent (BOLD) contrast, the acquisition of T 2*-weighted scans at a high spatial resolution may be advantageous in terms of time-course signal-to-noise ratio and of BOLD sensitivity when the regions are prone to susceptibility artifacts. In this study, we explore this solution by examining how spatial resolution influences activations elicited when appetizing food pictures are viewed. Twenty subjects were imaged at 3 T with two different voxel volumes, 3.4 μl and 27 μl. Despite the diminution of brain coverage, we found that high-resolution acquisition led to a better detection of activations. Though known to suffer to different degrees from susceptibility artifacts, the activations detected by high spatial resolution were notably consistent with those reported in published activation likelihood estimation meta-analyses, corresponding to taste-responsive regions. Furthermore, these regions were found activated bilaterally, in contrast with previous findings. Both the reduction of partial volume effect, which improves BOLD contrast, and the mitigation of susceptibility artifact, which boosts the signal to noise ratio in certain regions, explained the better detection noted with high resolution. The present study provides further evidences that high spatial resolution is a valuable solution for human BOLD fMRI, especially for studying food-related stimuli. PMID:26550990

Exploring the impacts of physics and resolution on aqua-planet simulations from a nonhydrostatic global variable-resolution modeling framework: IMPACTS OF PHYSICS AND RESOLUTION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Chun; Leung, L. Ruby; Park, Sang-Hun

Advances in computing resources are gradually moving regional and global numerical forecasting simulations towards sub-10 km resolution, but global high resolution climate simulations remain a challenge. The non-hydrostatic Model for Prediction Across Scales (MPAS) provides a global framework to achieve very high resolution using regional mesh refinement. Previous studies using the hydrostatic version of MPAS (H-MPAS) with the physics parameterizations of Community Atmosphere Model version 4 (CAM4) found notable resolution dependent behaviors. This study revisits the resolution sensitivity using the non-hydrostatic version of MPAS (NH-MPAS) with both CAM4 and CAM5 physics. A series of aqua-planet simulations at global quasi-uniform resolutionsmore » ranging from 240 km to 30 km and global variable resolution simulations with a regional mesh refinement of 30 km resolution over the tropics are analyzed, with a primary focus on the distinct characteristics of NH-MPAS in simulating precipitation, clouds, and large-scale circulation features compared to H-MPAS-CAM4. The resolution sensitivity of total precipitation and column integrated moisture in NH-MPAS is smaller than that in H-MPAS-CAM4. This contributes importantly to the reduced resolution sensitivity of large-scale circulation features such as the inter-tropical convergence zone and Hadley circulation in NH-MPAS compared to H-MPAS. In addition, NH-MPAS shows almost no resolution sensitivity in the simulated westerly jet, in contrast to the obvious poleward shift in H-MPAS with increasing resolution, which is partly explained by differences in the hyperdiffusion coefficients used in the two models that influence wave activity. With the reduced resolution sensitivity, simulations in the refined region of the NH-MPAS global variable resolution configuration exhibit zonally symmetric features that are more comparable to the quasi-uniform high-resolution simulations than those from H-MPAS that displays zonal asymmetry in simulations inside the refined region. Overall, NH-MPAS with CAM5 physics shows less resolution sensitivity compared to CAM4. These results provide a reference for future studies to further explore the use of NH-MPAS for high-resolution climate simulations in idealized and realistic configurations.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ogura, Toshihiko, E-mail: t-ogura@aist.go.jp

Scanning electron microscopy (SEM) has been widely used to examine biological specimens of bacteria, viruses and proteins. Until now, atmospheric and/or wet biological specimens have been examined using various atmospheric holders or special equipment involving SEM. Unfortunately, they undergo heavy radiation damage by the direct electron beam. In addition, images of unstained biological samples in water yield poor contrast. We recently developed a new analytical technology involving a frequency transmission electric-field (FTE) method based on thermionic SEM. This method is suitable for high-contrast imaging of unstained biological specimens. Our aim was to optimise the method. Here we describe a high-resolutionmore » FTE system based on field-emission SEM; it allows for imaging and nanoscale examination of various biological specimens in water without radiation damage. The spatial resolution is 8 nm, which is higher than 41 nm of the existing FTE system. Our new method can be easily utilised for examination of unstained biological specimens including bacteria, viruses and protein complexes. Furthermore, our high-resolution FTE system can be used for diverse liquid samples across a broad range of scientific fields, e.g. nanoparticles, nanotubes and organic and catalytic materials. - Highlights: • We developed a high-resolution frequency transmission electric-field (FTE) system. • High-resolution FTE system is introduced in the field-emission SEM. • The spatial resolution of high-resolution FTE method is 8 nm. • High-resolution FTE system enables observation of the intact IgM particles in water.« less

Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

NASA Astrophysics Data System (ADS)

Hong, Liang

2013-10-01

The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

Multiple Sensor Camera for Enhanced Video Capturing

NASA Astrophysics Data System (ADS)

Nagahara, Hajime; Kanki, Yoshinori; Iwai, Yoshio; Yachida, Masahiko

A resolution of camera has been drastically improved under a current request for high-quality digital images. For example, digital still camera has several mega pixels. Although a video camera has the higher frame-rate, the resolution of a video camera is lower than that of still camera. Thus, the high-resolution is incompatible with the high frame rate of ordinary cameras in market. It is difficult to solve this problem by a single sensor, since it comes from physical limitation of the pixel transfer rate. In this paper, we propose a multi-sensor camera for capturing a resolution and frame-rate enhanced video. Common multi-CCDs camera, such as 3CCD color camera, has same CCD for capturing different spectral information. Our approach is to use different spatio-temporal resolution sensors in a single camera cabinet for capturing higher resolution and frame-rate information separately. We build a prototype camera which can capture high-resolution (2588×1958 pixels, 3.75 fps) and high frame-rate (500×500, 90 fps) videos. We also proposed the calibration method for the camera. As one of the application of the camera, we demonstrate an enhanced video (2128×1952 pixels, 90 fps) generated from the captured videos for showing the utility of the camera.

Automatic public access to documents and maps stored on and internal secure system.

NASA Astrophysics Data System (ADS)

Trench, James; Carter, Mary

2013-04-01

The Geological Survey of Ireland operates a Document Management System for providing documents and maps stored internally in high resolution and in a high level secure environment, to an external service where the documents are automatically presented in a lower resolution to members of the public. Security is devised through roles and Individual Users where role level and folder level can be set. The application is an electronic document/data management (EDM) system which has a Geographical Information System (GIS) component integrated to allow users to query an interactive map of Ireland for data that relates to a particular area of interest. The data stored in the database consists of Bedrock Field Sheets, Bedrock Notebooks, Bedrock Maps, Geophysical Surveys, Geotechnical Maps & Reports, Groundwater, GSI Publications, Marine, Mine Records, Mineral Localities, Open File, Quaternary and Unpublished Reports. The Konfig application Tool is both an internal and public facing application. It acts as a tool for high resolution data entry which are stored in a high resolution vault. The public facing application is a mirror of the internal application and differs only in that the application furnishes high resolution data into low resolution format which is stored in a low resolution vault thus, making the data web friendly to the end user for download.

High-resolution mapping based on an Unmanned Aerial Vehicle (UAV) to capture paleoseismic offsets along the Altyn-Tagh fault, China.

PubMed

Gao, Mingxing; Xu, Xiwei; Klinger, Yann; van der Woerd, Jerome; Tapponnier, Paul

2017-08-15

The recent dramatic increase in millimeter- to centimeter- resolution topographic datasets obtained via multi-view photogrammetry raises the possibility of mapping detailed offset geomorphology and constraining the spatial characteristics of active faults. Here, for the first time, we applied this new method to acquire high-resolution imagery and generate topographic data along the Altyn Tagh fault, which is located in a remote high elevation area and shows preserved ancient earthquake surface ruptures. A digital elevation model (DEM) with a resolution of 0.065 m and an orthophoto with a resolution of 0.016 m were generated from these images. We identified piercing markers and reconstructed offsets based on both the orthoimage and the topography. The high-resolution UAV data were used to accurately measure the recent seismic offset. We obtained the recent offset of 7 ± 1 m. Combined with the high resolution satellite image, we measured cumulative offsets of 15 ± 2 m, 20 ± 2 m, 30 ± 2 m, which may be due to multiple paleo-earthquakes. Therefore, UAV mapping can provide fine-scale data for the assessment of the seismic hazards.

TandemPET-A High Resolution, Small Animal, Virtual Pinhole-Based PET Scanner: Initial Design Study

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Stolin, Alexander V.; Martone, Peter F.; Smith, Mark F.

2016-02-01

Mice are the perhaps the most common species of rodents used in biomedical research, but many of the current generation of small animal PET scanners are non-optimal for imaging these small rodents due to their relatively low resolution. Consequently, a number of researchers have investigated the development of high-resolution scanners to address this need. In this investigation, the design of a novel, high-resolution system based on the dual-detector, virtual-pinhole PET concept was explored via Monte Carlo simulations. Specifically, this system, called TandemPET, consists of a 5 cm × 5 cm high-resolution detector made-up of a 90 × 90 array of 0.5 mm × 0.5 × 10 mm (pitch = 0.55 mm) LYSO detector elements in coincidence with a lower resolution detector consisting of a 68 × 68 array of 1.5 mm × 1.5 mm × 10 mm LYSO detector elements (total size = 10.5 cm × 10.5 cm). Analyses indicated that TandemPET's optimal geometry is to position the high-resolution detector 3 cm from the center-of-rotation, with the lower resolution detector positioned 9 cm from center. Measurements using modified NEMA NU4-2008-based protocols revealed that the spatial resolution of the system is 0.5 mm FWHM, after correction of positron range effects. Peak sensitivity is 2.1%, which is comparable to current small animal PET scanners. Images from a digital mouse brain phantom demonstrated the potential of the system for identifying important neurological structures.

A new omni-directional multi-camera system for high resolution surveillance

NASA Astrophysics Data System (ADS)

Cogal, Omer; Akin, Abdulkadir; Seyid, Kerem; Popovic, Vladan; Schmid, Alexandre; Ott, Beat; Wellig, Peter; Leblebici, Yusuf

2014-05-01

Omni-directional high resolution surveillance has a wide application range in defense and security fields. Early systems used for this purpose are based on parabolic mirror or fisheye lens where distortion due to the nature of the optical elements cannot be avoided. Moreover, in such systems, the image resolution is limited to a single image sensor's image resolution. Recently, the Panoptic camera approach that mimics the eyes of flying insects using multiple imagers has been presented. This approach features a novel solution for constructing a spherically arranged wide FOV plenoptic imaging system where the omni-directional image quality is limited by low-end sensors. In this paper, an overview of current Panoptic camera designs is provided. New results for a very-high resolution visible spectrum imaging and recording system inspired from the Panoptic approach are presented. The GigaEye-1 system, with 44 single cameras and 22 FPGAs, is capable of recording omni-directional video in a 360°×100° FOV at 9.5 fps with a resolution over (17,700×4,650) pixels (82.3MP). Real-time video capturing capability is also verified at 30 fps for a resolution over (9,000×2,400) pixels (21.6MP). The next generation system with significantly higher resolution and real-time processing capacity, called GigaEye-2, is currently under development. The important capacity of GigaEye-1 opens the door to various post-processing techniques in surveillance domain such as large perimeter object tracking, very-high resolution depth map estimation and high dynamicrange imaging which are beyond standard stitching and panorama generation methods.

Spatial and temporal resolution effects on urban catchments with different imperviousness degrees

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-Claire; van de Giesen, Nick C.

2015-04-01

One of the main problems in urban hydrological analysis is to measure the rainfall at urban scale with high resolution and use these measurements to model urban runoff processes to predict flows and reduce flood risk. With the aim of building a semi-distribute hydrological sewer model for an urban catchment, high resolution rainfall data are required as input. In this study, the sensitivity of hydrological response to high resolution precipitation data for hydrodynamic models at urban scale is evaluated with different combinations of spatial and temporal resolutions. The aim is to study sensitivity in relation to catchment characteristics, especially drainage area size, imperviousness degree and hydraulic properties such as special structures (weirs, pumping stations). Rainfall data of nine storms are considered with 4 different spatial resolutions (3000m, 1000m, 500m and 100m) combined with 4 different temporal resolutions (10min, 5min, 3min and 1min). The dual polarimetric X-band weather radar, located in the Cabauw Experimental Site for Atmospheric Research (CESAR) provided the high resolution rainfall data of these rainfall events, used to improve the sewer model. The effects of spatial-temporal rainfall input resolution on response is studied in three Districts of Rotterdam (NL): Kralingen, Spaanse Polder and Centrum district. These catchments have different average drainage area size (from 2km2 to 7km2), and different general characteristics. Centrum district and Kralingen are, indeed, more various and include residential and commercial areas, big green areas and a small industrial area, while Spaanse Polder is a industrial area, densely urbanized, and presents a high percentage of imperviousness.

High Resolution Bathymetry Estimation Improvement with Single Image Super-Resolution Algorithm Super-Resolution Forests

DTIC Science & Technology

2017-01-26

Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/5514--17-9692 High Resolution Bathymetry Estimation Improvement with Single Image Super...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources...gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate

Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions

DOE PAGES

Feng, Sha; Lauvaux, Thomas; Newman, Sally; ...

2016-07-22

Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less

Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Sha; Lauvaux, Thomas; Newman, Sally

Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less

The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

NASA Astrophysics Data System (ADS)

Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

2016-09-01

With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

Detection of facilities in satellite imagery using semi-supervised image classification and auxiliary contextual observables

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harvey, Neal R; Ruggiero, Christy E; Pawley, Norma H

2009-01-01

Detecting complex targets, such as facilities, in commercially available satellite imagery is a difficult problem that human analysts try to solve by applying world knowledge. Often there are known observables that can be extracted by pixel-level feature detectors that can assist in the facility detection process. Individually, each of these observables is not sufficient for an accurate and reliable detection, but in combination, these auxiliary observables may provide sufficient context for detection by a machine learning algorithm. We describe an approach for automatic detection of facilities that uses an automated feature extraction algorithm to extract auxiliary observables, and a semi-supervisedmore » assisted target recognition algorithm to then identify facilities of interest. We illustrate the approach using an example of finding schools in Quickbird image data of Albuquerque, New Mexico. We use Los Alamos National Laboratory's Genie Pro automated feature extraction algorithm to find a set of auxiliary features that should be useful in the search for schools, such as parking lots, large buildings, sports fields and residential areas and then combine these features using Genie Pro's assisted target recognition algorithm to learn a classifier that finds schools in the image data.« less

High spatial resolution distributed optical fiber dynamic strain sensor with enhanced frequency and strain resolution.

PubMed

Masoudi, Ali; Newson, Trevor P

2017-01-15

A distributed optical fiber dynamic strain sensor with high spatial and frequency resolution is demonstrated. The sensor, which uses the ϕ-OTDR interrogation technique, exhibited a higher sensitivity thanks to an improved optical arrangement and a new signal processing procedure. The proposed sensing system is capable of fully quantifying multiple dynamic perturbations along a 5 km long sensing fiber with a frequency and spatial resolution of 5 Hz and 50 cm, respectively. The strain resolution of the sensor was measured to be 40 nε.

BLIPPED (BLIpped Pure Phase EncoDing) high resolution MRI with low amplitude gradients

NASA Astrophysics Data System (ADS)

Xiao, Dan; Balcom, Bruce J.

2017-12-01

MRI image resolution is proportional to the maximum k-space value, i.e. the temporal integral of the magnetic field gradient. High resolution imaging usually requires high gradient amplitudes and/or long spatial encoding times. Special gradient hardware is often required for high amplitudes and fast switching. We propose a high resolution imaging sequence that employs low amplitude gradients. This method was inspired by the previously proposed PEPI (π Echo Planar Imaging) sequence, which replaced EPI gradient reversals with multiple RF refocusing pulses. It has been shown that when the refocusing RF pulse is of high quality, i.e. sufficiently close to 180°, the magnetization phase introduced by the spatial encoding magnetic field gradient can be preserved and transferred to the following echo signal without phase rewinding. This phase encoding scheme requires blipped gradients that are identical for each echo, with low and constant amplitude, providing opportunities for high resolution imaging. We now extend the sequence to 3D pure phase encoding with low amplitude gradients. The method is compared with the Hybrid-SESPI (Spin Echo Single Point Imaging) technique to demonstrate the advantages in terms of low gradient duty cycle, compensation of concomitant magnetic field effects and minimal echo spacing, which lead to superior image quality and high resolution. The 3D imaging method was then applied with a parallel plate resonator RF probe, achieving a nominal spatial resolution of 17 μm in one dimension in the 3D image, requiring a maximum gradient amplitude of only 5.8 Gauss/cm.

High-resolution high-efficiency multilayer Fresnel zone plates for soft and hard x-rays

NASA Astrophysics Data System (ADS)

Sanli, Umut T.; Keskinbora, Kahraman; Gregorczyk, Keith; Leister, Jonas; Teeny, Nicolas; Grévent, Corinne; Knez, Mato; Schütz, Gisela

2015-09-01

X-ray microscopy enables high spatial resolutions, high penetration depths and characterization of a broad range of materials. Calculations show that nanometer range resolution is achievable in the hard X-ray regime by using Fresnel zone plates (FZPs) if certain conditions are satisfied. However, this requires, among other things, aspect ratios of several thousands. The multilayer (ML) type FZPs, having virtually unlimited aspect ratios, are strong candidates to achieve single nanometer resolutions. Our research is focused on the fabrication of ML-FZPs which encompasses deposition of multilayers over a glass fiber via the atomic layer deposition (ALD), which is subsequently sliced in the optimum thickness for the X-ray energy by a focused ion beam (FIB). We recently achieved aberration free imaging by resolving 21 nm features with an efficiency of up to 12.5 %, the highest imaging resolution achieved by an ML-FZP. We also showed efficient focusing of 7.9 keV X-rays down to 30 nm focal spot size (FWHM). For resolutions below ~10 nm, efficiencies would decrease significantly due to wave coupling effects. To compensate this effect high efficiency, low stress materials have to be researched, as lower intrinsic stresses will allow fabrication of larger FZPs with higher number of zones, leading to high light intensity at the focus. As a first step we fabricated an ML-FZP with a diameter of 62 μm, an outermost zone width of 12 nm and 452 active zones. Further strategies for fabrication of high resolution high efficiency multilayer FZPs will also be discussed.

Limited Area Coverage/High Resolution Picture Transmission (LAC/HRPT) data vegetative index calculation processor user's manual

NASA Technical Reports Server (NTRS)

Obrien, S. O. (Principal Investigator)

1980-01-01

The program, LACVIN, calculates vegetative indexes numbers on limited area coverage/high resolution picture transmission data for selected IJ grid sections. The IJ grid sections were previously extracted from the full resolution data tapes and stored on disk files.

k-space and q-space: combining ultra-high spatial and angular resolution in diffusion imaging using ZOOPPA at 7 T.

PubMed

Heidemann, Robin M; Anwander, Alfred; Feiweier, Thorsten; Knösche, Thomas R; Turner, Robert

2012-04-02

There is ongoing debate whether using a higher spatial resolution (sampling k-space) or a higher angular resolution (sampling q-space angles) is the better way to improve diffusion MRI (dMRI) based tractography results in living humans. In both cases, the limiting factor is the signal-to-noise ratio (SNR), due to the restricted acquisition time. One possible way to increase the spatial resolution without sacrificing either SNR or angular resolution is to move to a higher magnetic field strength. Nevertheless, dMRI has not been the preferred application for ultra-high field strength (7 T). This is because single-shot echo-planar imaging (EPI) has been the method of choice for human in vivo dMRI. EPI faces several challenges related to the use of a high resolution at high field strength, for example, distortions and image blurring. These problems can easily compromise the expected SNR gain with field strength. In the current study, we introduce an adapted EPI sequence in conjunction with a combination of ZOOmed imaging and Partially Parallel Acquisition (ZOOPPA). We demonstrate that the method can produce high quality diffusion-weighted images with high spatial and angular resolution at 7 T. We provide examples of in vivo human dMRI with isotropic resolutions of 1 mm and 800 μm. These data sets are particularly suitable for resolving complex and subtle fiber architectures, including fiber crossings in the white matter, anisotropy in the cortex and fibers entering the cortex. Copyright © 2011 Elsevier Inc. All rights reserved.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

PubMed

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

PubMed Central

Holl, Felix; Savory, David J.; Andrade-Pacheco, Ricardo; Gething, Peter W.; Bennett, Adam; Sturrock, Hugh J. W.

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth’s land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources. PMID:28953943

Beamline P02.1 at PETRA III for high-resolution and high-energy powder diffraction

PubMed Central

Dippel, Ann-Christin; Liermann, Hanns-Peter; Delitz, Jan Torben; Walter, Peter; Schulte-Schrepping, Horst; Seeck, Oliver H.; Franz, Hermann

2015-01-01

Powder X-ray diffraction techniques largely benefit from the superior beam quality provided by high-brilliance synchrotron light sources in terms of photon flux and angular resolution. The High Resolution Powder Diffraction Beamline P02.1 at the storage ring PETRA III (DESY, Hamburg, Germany) combines these strengths with the power of high-energy X-rays for materials research. The beamline is operated at a fixed photon energy of 60 keV (0.207 Å wavelength). A high-resolution monochromator generates the highly collimated X-ray beam of narrow energy bandwidth. Classic crystal structure determination in reciprocal space at standard and non-ambient conditions are an essential part of the scientific scope as well as total scattering analysis using the real space information of the pair distribution function. Both methods are complemented by in situ capabilities with time-resolution in the sub-second regime owing to the high beam intensity and the advanced detector technology for high-energy X-rays. P02.1’s efficiency in solving chemical and crystallographic problems is illustrated by presenting key experiments that were carried out within these fields during the early stage of beamline operation. PMID:25931084

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, Liwang

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.

High resolution, high frame rate video technology development plan and the near-term system conceptual design

NASA Technical Reports Server (NTRS)

Ziemke, Robert A.

1990-01-01

The objective of the High Resolution, High Frame Rate Video Technology (HHVT) development effort is to provide technology advancements to remove constraints on the amount of high speed, detailed optical data recorded and transmitted for microgravity science and application experiments. These advancements will enable the development of video systems capable of high resolution, high frame rate video data recording, processing, and transmission. Techniques such as multichannel image scan, video parameter tradeoff, and the use of dual recording media were identified as methods of making the most efficient use of the near-term technology.

High-Resolution X-Ray Telescopes

NASA Technical Reports Server (NTRS)

ODell, Stephen L.; Brissenden, Roger J.; Davis, William; Elsner, Ronald F.; Elvis, Martin; Freeman, Mark; Gaetz, Terry; Gorenstein, Paul; Gubarev, Mikhail V.

2010-01-01

Fundamental needs for future x-ray telescopes: a) Sharp images => excellent angular resolution. b) High throughput => large aperture areas. Generation-X optics technical challenges: a) High resolution => precision mirrors & alignment. b) Large apertures => lots of lightweight mirrors. Innovation needed for technical readiness: a) 4 top-level error terms contribute to image size. b) There are approaches to controlling those errors. Innovation needed for manufacturing readiness. Programmatic issues are comparably challenging.

Using High Spatial Resolution Digital Imagery

DTIC Science & Technology

2005-02-01

digital base maps were high resolution U.S. Geological Survey (USGS) Digital Orthophoto Quarter Quadrangles (DOQQ). The Root Mean Square Errors (RMSE...next step was to assign real world coordinates to the linear im- age. The mosaics were geometrically registered to the panchromatic orthophotos ...useable thematic map from high-resolution imagery. A more practical approach may be to divide the Refuge into a set of smaller areas, or tiles

High Resolution Near Real Time Image Processing and Support for MSSS Modernization

DTIC Science & Technology

2012-09-01

00-00-2012 to 00-00-2012 4 . TITLE AND SUBTITLE High Resolution Near Real Time Image Processing and Support for MSSS Modernization 5a. CONTRACT...This current CONOPS is depicted in Fig. 4 . Fig. 4 . PCID/ASPIRE High Resolution Post...experiments were performed, and subsequently addressed in papers and presentations [3, 4 ,] that demonstrated system behavior; with details of the

High Spatiotemporal Resolution Prostate MRI

DTIC Science & Technology

2016-09-01

1 AD AWARD NUMBER: W81XWH-15-1-0341 TITLE: High Spatiotemporal Resolution Prostate MRI PRINCIPAL INVESTIGATOR: Stephen J. Riederer CONTRACTING...REPORT TYPE Annual 3. DATES COVERED 15 Aug 2015 - 14 Aug 2016 4. TITLE AND SUBTITLE High Spatiotemporal Resolution Prostate MRI 5a. CONTRACT NUMBER...improved means using MRI for detecting prostate cancer with the potential for differentiating disease aggressiveness. The hypothesis is that dynamic

Visual short-term memory for high resolution associations is impaired in patients with medial temporal lobe damage.

PubMed

Koen, Joshua D; Borders, Alyssa A; Petzold, Michael T; Yonelinas, Andrew P

2017-02-01

The medial temporal lobe (MTL) plays a critical role in episodic long-term memory, but whether the MTL is necessary for visual short-term memory is controversial. Some studies have indicated that MTL damage disrupts visual short-term memory performance whereas other studies have failed to find such evidence. To account for these mixed results, it has been proposed that the hippocampus is critical in supporting short-term memory for high resolution complex bindings, while the cortex is sufficient to support simple, low resolution bindings. This hypothesis was tested in the current study by assessing visual short-term memory in patients with damage to the MTL and controls for high resolution and low resolution object-location and object-color associations. In the location tests, participants encoded sets of two or four objects in different locations on the screen. After each set, participants performed a two-alternative forced-choice task in which they were required to discriminate the object in the target location from the object in a high or low resolution lure location (i.e., the object locations were very close or far away from the target location, respectively). Similarly, in the color tests, participants were presented with sets of two or four objects in a different color and, after each set, were required to discriminate the object in the target color from the object in a high or low resolution lure color (i.e., the lure color was very similar or very different, respectively, to the studied color). The patients were significantly impaired in visual short-term memory, but importantly, they were more impaired for high resolution object-location and object-color bindings. The results are consistent with the proposal that the hippocampus plays a critical role in forming and maintaining complex, high resolution bindings. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Non-Destructive High-Resolution Organic Matter Record on Lake Sediment using Steady-State Solid Phase Fluorescence: Organic Matter Quality and Quantity Assessment.

NASA Astrophysics Data System (ADS)

Quiers, M.; Perrette, Y.; Etienne, D.; Develle, A. L.; Jacq, K.

2017-12-01

The use of organic proxies increases in paleoenvironmental reconstructions from natural archives. Major advances have been achieved by the development of new highly informative molecular proxies usually linked to specific compounds. While studies focused on targeted compounds, offering a high information degree, advances on bulk organic matter are limited. However, this bulk is the main contributor to carbon cycle and has been shown to be a driver of many mineral or organic compounds transfer and record. Development of target proxies need complementary information on bulk organic matter to understand biases link to controlling factors or analytical methods, and provide a robust interpretation. Fluorescence methods have often been employed to characterize and quantify organic matter. However, these technics are mainly developed for liquid samples, inducing material and resolution loss when working on natural archives (either stalagmite or sediments). High-resolution solid phase fluorescence (SPF) was developed on speleothems. This method allows now to analyse organic matter quality and quantity if procedure to constrain the optical density are adopted. In fact, a calibration method using liquid phase fluorescence (LPF) was developed for speleothem, allowing to quantify organic carbon at high-resolution. We report here an application of such a procedure SPF/LPF measurements on lake sediments. In order to avoid sediment matrix effects on the fluorescence signal, a calibration using LPF measurements was realised. First results using this method provided organic matter quality record of different organic matter compounds (humic-like, protein-like and chlorophylle-like compounds) at high resolution for the sediment core. High resolution organic matter fluxes are obtained in a second time, applying pragmatic chemometrics model (non linear models, partial least square models) on high resolution fluorescence data. SPF method can be considered as a promising tool for high resolution record on organic matter quality and quantity. Potential application of this method will be evocated (lake ecosystem dynamic, changes in trophic levels)

An infrared high resolution silicon immersion grating spectrometer for airborne and space missions

NASA Astrophysics Data System (ADS)

Ge, Jian; Zhao, Bo; Powell, Scott; Jiang, Peng; Uzakbaiuly, Berik; Tanner, David

2014-08-01

Broad-band infrared (IR) spectroscopy, especially at high spectral resolution, is a largely unexplored area for the far IR (FIR) and submm wavelength region due to the lack of proper grating technology to produce high resolution within the very constrained volume and weight required for space mission instruments. High resolution FIR spectroscopy is an essential tool to resolve many atomic and molecular lines to measure physical and chemical conditions and processes in the environments where galaxy, star and planets form. A silicon immersion grating (SIG), due to its over three times high dispersion over a traditional reflective grating, offers a compact and low cost design of new generation IR high resolution spectrographs for space missions. A prototype SIG high resolution spectrograph, called Florida IR Silicon immersion grating spectromeTer (FIRST), has been developed at UF and was commissioned at a 2 meter robotic telescope at Fairborn Observatory in Arizona. The SIG with 54.74 degree blaze angle, 16.1 l/mm groove density, and 50x86 mm2 grating area has produced R=50,000 in FIRST. The 1.4-1.8 um wavelength region is completely covered in a single exposure with a 2kx2k H2RG IR array. The on-sky performance meets the science requirements for ground-based high resolution spectroscopy. Further studies show that this kind of SIG spectrometer with an airborne 2m class telescope such as SOFIA can offer highly sensitive spectroscopy with R~20,000-30,000 at 20 to 55 microns. Details about the on-sky measurement performance of the FIRST prototype SIG spectrometer and its predicted performance with the SOFIA 2.4m telescope are introduced.

Graphene-enabled electron microscopy and correlated super-resolution microscopy of wet cells.

PubMed

Wojcik, Michal; Hauser, Margaret; Li, Wan; Moon, Seonah; Xu, Ke

2015-06-11

The application of electron microscopy to hydrated biological samples has been limited by high-vacuum operating conditions. Traditional methods utilize harsh and laborious sample dehydration procedures, often leading to structural artefacts and creating difficulties for correlating results with high-resolution fluorescence microscopy. Here, we utilize graphene, a single-atom-thick carbon meshwork, as the thinnest possible impermeable and conductive membrane to protect animal cells from vacuum, thus enabling high-resolution electron microscopy of wet and untreated whole cells with exceptional ease. Our approach further allows for facile correlative super-resolution and electron microscopy of wet cells directly on the culturing substrate. In particular, individual cytoskeletal actin filaments are resolved in hydrated samples through electron microscopy and well correlated with super-resolution results.

Speckle correlation resolution enhancement of wide-field fluorescence imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yilmaz, Hasan

2016-03-01

Structured illumination enables high-resolution fluorescence imaging of nanostructures [1]. We demonstrate a new high-resolution fluorescence imaging method that uses a scattering layer with a high-index substrate as a solid immersion lens [2]. Random scattering of coherent light enables a speckle pattern with a very fine structure that illuminates the fluorescent nanospheres on the back surface of the high-index substrate. The speckle pattern is raster-scanned over the fluorescent nanospheres using a speckle correlation effect known as the optical memory effect. A series of standard-resolution fluorescence images per each speckle pattern displacement are recorded by an electron-multiplying CCD camera using a commercial microscope objective. We have developed a new phase-retrieval algorithm to reconstruct a high-resolution, wide-field image from several standard-resolution wide-field images. We have introduced phase information of Fourier components of standard-resolution images as a new constraint in our algorithm which discards ambiguities therefore ensures convergence to a unique solution. We demonstrate two-dimensional fluorescence images of a collection of nanospheres with a deconvolved Abbe resolution of 116 nm and a field of view of 10 µm × 10 µm. Our method is robust against optical aberrations and stage drifts, therefore excellent for imaging nanostructures under ambient conditions. [1] M. G. L. Gustafsson, J. Microsc. 198, 82-87 (2000). [2] H. Yilmaz, E. G. van Putten, J. Bertolotti, A. Lagendijk, W. L. Vos, and A. P. Mosk, Optica 2, 424-429 (2015).

Investigation of spatial resolution and temporal performance of SAPHIRE (scintillator avalanche photoconductor with high resolution emitter readout) with integrated electrostatic focusing

NASA Astrophysics Data System (ADS)

Scaduto, David A.; Lubinsky, Anthony R.; Rowlands, John A.; Kenmotsu, Hidenori; Nishimoto, Norihito; Nishino, Takeshi; Tanioka, Kenkichi; Zhao, Wei

2014-03-01

We have previously proposed SAPHIRE (scintillator avalanche photoconductor with high resolution emitter readout), a novel detector concept with potentially superior spatial resolution and low-dose performance compared with existing flat-panel imagers. The detector comprises a scintillator that is optically coupled to an amorphous selenium photoconductor operated with avalanche gain, known as high-gain avalanche rushing photoconductor (HARP). High resolution electron beam readout is achieved using a field emitter array (FEA). This combination of avalanche gain, allowing for very low-dose imaging, and electron emitter readout, providing high spatial resolution, offers potentially superior image quality compared with existing flat-panel imagers, with specific applications to fluoroscopy and breast imaging. Through the present collaboration, a prototype HARP sensor with integrated electrostatic focusing and nano- Spindt FEA readout technology has been fabricated. The integrated electron-optic focusing approach is more suitable for fabricating large-area detectors. We investigate the dependence of spatial resolution on sensor structure and operating conditions, and compare the performance of electrostatic focusing with previous technologies. Our results show a clear dependence of spatial resolution on electrostatic focusing potential, with performance approaching that of the previous design with external mesh-electrode. Further, temporal performance (lag) of the detector is evaluated and the results show that the integrated electrostatic focusing design exhibits comparable or better performance compared with the mesh-electrode design. This study represents the first technical evaluation and characterization of the SAPHIRE concept with integrated electrostatic focusing.

MSE spectrograph optical design: a novel pupil slicing technique

NASA Astrophysics Data System (ADS)

Spanò, P.

2014-07-01

The Maunakea Spectroscopic Explorer shall be mainly devoted to perform deep, wide-field, spectroscopic surveys at spectral resolutions from ~2000 to ~20000, at visible and near-infrared wavelengths. Simultaneous spectral coverage at low resolution is required, while at high resolution only selected windows can be covered. Moreover, very high multiplexing (3200 objects) must be obtained at low resolution. At higher resolutions a decreased number of objects (~800) can be observed. To meet such high demanding requirements, a fiber-fed multi-object spectrograph concept has been designed by pupil-slicing the collimated beam, followed by multiple dispersive and camera optics. Different resolution modes are obtained by introducing anamorphic lenslets in front of the fiber arrays. The spectrograph is able to switch between three resolution modes (2000, 6500, 20000) by removing the anamorphic lenses and exchanging gratings. Camera lenses are fixed in place to increase stability. To enhance throughput, VPH first-order gratings has been preferred over echelle gratings. Moreover, throughput is kept high over all wavelength ranges by splitting light into more arms by dichroic beamsplitters and optimizing efficiency for each channel by proper selection of glass materials, coatings, and grating parameters.

High-resolution model for estimating the economic and policy implications of agricultural soil salinization in California

NASA Astrophysics Data System (ADS)

Welle, Paul D.; Mauter, Meagan S.

2017-09-01

This work introduces a generalizable approach for estimating the field-scale agricultural yield losses due to soil salinization. When integrated with regional data on crop yields and prices, this model provides high-resolution estimates for revenue losses over large agricultural regions. These methods account for the uncertainty inherent in model inputs derived from satellites, experimental field data, and interpreted model results. We apply this method to estimate the effect of soil salinity on agricultural outputs in California, performing the analysis with both high-resolution (i.e. field scale) and low-resolution (i.e. county-scale) data sources to highlight the importance of spatial resolution in agricultural analysis. We estimate that soil salinity reduced agricultural revenues by 3.7 billion (1.7-7.0 billion) in 2014, amounting to 8.0 million tons of lost production relative to soil salinities below the crop-specific thresholds. When using low-resolution data sources, we find that the costs of salinization are underestimated by a factor of three. These results highlight the need for high-resolution data in agro-environmental assessment as well as the challenges associated with their integration.

Ultra-High Spectral Resolution Observations of Fragmentation in Dark Cloud Cores

NASA Technical Reports Server (NTRS)

Velusamy, T.; Langer, W.; Kuiper, T; Levin, S.; Olsen, E.

1993-01-01

This paper presents new evidence of the fragmentary structure of dense cores in dark clouds using the high resolution spectra of the carbon chain molecule CCS transition (J subscript N = 2 subscript 1 - 1 subscript o) at 22.344033 GHz with 0.008 km s superscript -1 resolution.

A high-resolution cattle CNV map by population-scale genome sequencing

USDA-ARS?s Scientific Manuscript database

Copy Number Variations (CNVs) are common genomic structural variations that have been linked to human diseases and phenotypic traits. Prior studies in cattle have produced low-resolution CNV maps. We constructed a draft, high-resolution map of cattle CNVs based on whole genome sequencing data from 7...

Evaluation of a Moderate Resolution, Satellite-Based Impervious Surface Map Using an Independent, High-Resolution Validation Dataset

EPA Science Inventory

Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data ...

Merging thermal and microwave satellite observations for a high-resolution soil moisture data product

USDA-ARS?s Scientific Manuscript database

Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...

Super-resolution biomolecular crystallography with low-resolution data.

PubMed

Schröder, Gunnar F; Levitt, Michael; Brunger, Axel T

2010-04-22

X-ray diffraction plays a pivotal role in the understanding of biological systems by revealing atomic structures of proteins, nucleic acids and their complexes, with much recent interest in very large assemblies like the ribosome. As crystals of such large assemblies often diffract weakly (resolution worse than 4 A), we need methods that work at such low resolution. In macromolecular assemblies, some of the components may be known at high resolution, whereas others are unknown: current refinement methods fail as they require a high-resolution starting structure for the entire complex. Determining the structure of such complexes, which are often of key biological importance, should be possible in principle as the number of independent diffraction intensities at a resolution better than 5 A generally exceeds the number of degrees of freedom. Here we introduce a method that adds specific information from known homologous structures but allows global and local deformations of these homology models. Our approach uses the observation that local protein structure tends to be conserved as sequence and function evolve. Cross-validation with R(free) (the free R-factor) determines the optimum deformation and influence of the homology model. For test cases at 3.5-5 A resolution with known structures at high resolution, our method gives significant improvements over conventional refinement in the model as monitored by coordinate accuracy, the definition of secondary structure and the quality of electron density maps. For re-refinements of a representative set of 19 low-resolution crystal structures from the Protein Data Bank, we find similar improvements. Thus, a structure derived from low-resolution diffraction data can have quality similar to a high-resolution structure. Our method is applicable to the study of weakly diffracting crystals using X-ray micro-diffraction as well as data from new X-ray light sources. Use of homology information is not restricted to X-ray crystallography and cryo-electron microscopy: as optical imaging advances to subnanometre resolution, it can use similar tools.

Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery

USGS Publications Warehouse

Enwright, Nicholas M.; Jones, William R.; Garber, Adrienne L.; Keller, Matthew J.

2014-01-01

Long-term monitoring efforts often use remote sensing to track trends in habitat or landscape conditions over time. To most appropriately compare observations over time, long-term monitoring efforts strive for consistency in methods. Thus, advances and changes in technology over time can present a challenge. For instance, modern camera technology has led to an increasing availability of very high-resolution imagery (i.e. submetre and metre) and a shift from analogue to digital photography. While numerous studies have shown that image resolution can impact the accuracy of classifications, most of these studies have focused on the impacts of comparing spatial resolution changes greater than 2 m. Thus, a knowledge gap exists on the impacts of minor changes in spatial resolution (i.e. submetre to about 1.5 m) in very high-resolution aerial imagery (i.e. 2 m resolution or less). This study compared the impact of spatial resolution on land/water classifications of an area dominated by coastal marsh vegetation in Louisiana, USA, using 1:12,000 scale colour-infrared analogue aerial photography (AAP) scanned at four different dot-per-inch resolutions simulating ground sample distances (GSDs) of 0.33, 0.54, 1, and 2 m. Analysis of the impact of spatial resolution on land/water classifications was conducted by exploring various spatial aspects of the classifications including density of waterbodies and frequency distributions in waterbody sizes. This study found that a small-magnitude change (1–1.5 m) in spatial resolution had little to no impact on the amount of water classified (i.e. percentage mapped was less than 1.5%), but had a significant impact on the mapping of very small waterbodies (i.e. waterbodies ≤ 250 m2). These findings should interest those using temporal image classifications derived from very high-resolution aerial photography as a component of long-term monitoring programs.

Acceleration of high resolution temperature based optimization for hyperthermia treatment planning using element grouping.

PubMed

Kok, H P; de Greef, M; Bel, A; Crezee, J

2009-08-01

In regional hyperthermia, optimization is useful to obtain adequate applicator settings. A speed-up of the previously published method for high resolution temperature based optimization is proposed. Element grouping as described in literature uses selected voxel sets instead of single voxels to reduce computation time. Elements which achieve their maximum heating potential for approximately the same phase/amplitude setting are grouped. To form groups, eigenvalues and eigenvectors of precomputed temperature matrices are used. At high resolution temperature matrices are unknown and temperatures are estimated using low resolution (1 cm) computations and the high resolution (2 mm) temperature distribution computed for low resolution optimized settings using zooming. This technique can be applied to estimate an upper bound for high resolution eigenvalues. The heating potential of elements was estimated using these upper bounds. Correlations between elements were estimated with low resolution eigenvalues and eigenvectors, since high resolution eigenvectors remain unknown. Four different grouping criteria were applied. Constraints were set to the average group temperatures. Element grouping was applied for five patients and optimal settings for the AMC-8 system were determined. Without element grouping the average computation times for five and ten runs were 7.1 and 14.4 h, respectively. Strict grouping criteria were necessary to prevent an unacceptable exceeding of the normal tissue constraints (up to approximately 2 degrees C), caused by constraining average instead of maximum temperatures. When strict criteria were applied, speed-up factors of 1.8-2.1 and 2.6-3.5 were achieved for five and ten runs, respectively, depending on the grouping criteria. When many runs are performed, the speed-up factor will converge to 4.3-8.5, which is the average reduction factor of the constraints and depends on the grouping criteria. Tumor temperatures were comparable. Maximum exceeding of the constraint in a hot spot was 0.24-0.34 degree C; average maximum exceeding over all five patients was 0.09-0.21 degree C, which is acceptable. High resolution temperature based optimization using element grouping can achieve a speed-up factor of 4-8, without large deviations from the conventional method.

Development of a high resolution optical-fiber tilt sensor by F-P filter

NASA Astrophysics Data System (ADS)

Pan, Jianjun; Nan, Qiuming; Li, Shujie; Hao, Zhonghua

2017-04-01

A high-resolution tilt sensor is developed, which is composed of a pair of optical fiber collimators and a simple pendulum with an F-P filter. The tilt angle is measured by demodulating the shift of center wavelength of F-P filter, which is caused by incidence angle changing. The relationship between tilted angle and the center wavelength is deduced. Calibration experiment results also confirm the deduction, and show that it is easy to obtain a high resolution. Setting the initial angle to 6degree, the measurement range is ±3degree, its average sensitivity is 1104pm/degree, and its average resolution is as high as 0.0009degree.

High Spatial Resolution Thermal Satellite Technologies

NASA Technical Reports Server (NTRS)

Ryan, Robert

2003-01-01

This document in the form of viewslides, reviews various low-cost alternatives to high spatial resolution thermal satellite technologies. There exists no follow-on to Landsat 7 or ASTER high spatial resolution thermal systems. This document reviews the results of the investigation in to the use of new technologies to create a low-cost useful alternative. Three suggested technologies are examined. 1. Conventional microbolometer pushbroom modes offers potential for low cost Landsat Data Continuity Mission (LDCM) thermal or ASTER capability with at least 60-120 ground sampling distance (GSD). 2. Backscanning could produce MultiSpectral Thermal Imager performance without cooled detectors. 3. Cooled detector could produce hyperspectral thermal class system or extremely high spatial resolution class instrument.