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Sample records for eo-1 hyperspectral hyperion

  1. Mapping the land cover in coastal Gabes oases using the EO-1 HYPERION hyperspectral sensor

    NASA Astrophysics Data System (ADS)

    Ben-Arfa, Jouda; Bergès, Jean Claude; Beltrando, Gérard; Rim, Katlane; Zargouni, Fouad

    2015-04-01

    Gabes region is characterized by unique maritime oases in Mediterranean basin. Unfortunately these oases are sensitive areas due to a harsh competition for land and water between different user groups (urban, industry, agriculture). An industrial complex is now located in center of this region, cultivation practices have shifted from a traditional multi-layer plant association system and moreover the Gabes city itself is expanding in the very core of oases. The oases of Gabes are transformed into city oases; they undergo multiform interactions whose amplify their environmental dynamic. A proper management of this environment should be based on a fine cartography of land use and remote sensing plays a major role in this issue. However the use of legacy natural resource remote sensing data is disappointing. The crop production strategies rely on a fine scale ground split among various uses and the ground resolution of these satellites is not adequate. Our study relies on hyperspectral images in order to cartography oases boundaries and land use. We tested the potential of Hyperion hyperspectral satellite imagery for mapping dynamics oases covered. We have the opportunity to access EO1/Hyperion data on seven different dates on 2009 and 2010. This dataset allows us to compare various hyperspectral based processing both on the basis on information pertinence and time stability. In this frame some index appear as significantly efficient: cellulose index, vegetation mask, water presence index. On another side spectral unmixing looks as more sensitive to slight ground changes. These results raise the issue of compared interest of enhancing spatial resolution versus spectral resolution. Whereas high resolution ground observation satellites are obviously more appropriate for visual recognition process, reliable information could be extracted from hyperspectral information through a fully automatic process.

  2. Discrimination And Biophysical Characterization Of Brazilian Cerrado Physiognomies With Eo-1 Hyperspectral Hyperion

    NASA Technical Reports Server (NTRS)

    Miura, Tomoaki; Huete, Alfredo R.; Ferreira, Laerte G.; Sano, Edson E.

    2004-01-01

    The savanna, typically found in the sub-tropics and seasonal tropics, are the dominant vegetation biome type in the southern hemisphere, covering approximately 45% of the South America. In Brazil, the savanna, locally known as "cerrado," is the most intensely stressed biome with both natural environmental pressures (e.g., the strong seasonality in weather, extreme soil nutrient impoverishment, and widespread fire occurrences) and rapid/aggressive land conversions (Skole et al., 1994; Ratter et al., 1997). Better characterization and discrimination of cerrado physiognomies are needed in order to improve understanding of cerrado dynamics and its impact on carbon storage, nutrient dynamics, and the prospect for sustainable land use in the Brazilian cerrado biome. Satellite remote sensing have been known to be a useful tool for land cover and land use mapping (Rougharden et al., 1991; Hansen et al., 2000). However, attempts to discriminate and classify Brazilian cerrado using multi-spectral sensors (e.g., Landsat TM) and/or moderate resolution sensors (e.g., NOAA AVHRR NDVI) have often resulted in a limited success due partly to small contrasts depicted in their multiband, spectral reflectance or vegetation index values among cerrado classes (Seyler et al., 2002; Fran a and Setzer, 1998). In this study, we aimed to improve discrimination as well as biophysical characterization of the Brazilian cerrado physiognomies with hyperspectral remote sensing. We used Hyperion, the first satellite-based hyperspectral imager, onboard the Earth Observing-1 (EO-1) platform.

  3. Sub-pixel mineral mapping using EO-1 Hyperion hyperspectral data

    NASA Astrophysics Data System (ADS)

    Kumar, C.; Shetty, A.; Raval, S.; Champatiray, P. K.; Sharma, R.

    2014-11-01

    This study describes the utility of Earth Observation (EO)-1 Hyperion data for sub-pixel mineral investigation using Mixture Tuned Target Constrained Interference Minimized Filter (MTTCIMF) algorithm in hostile mountainous terrain of Rajsamand district of Rajasthan, which hosts economic mineralization such as lead, zinc, and copper etc. The study encompasses pre-processing, data reduction, Pixel Purity Index (PPI) and endmember extraction from reflectance image of surface minerals such as illite, montmorillonite, phlogopite, dolomite and chlorite. These endmembers were then assessed with USGS mineral spectral library and lab spectra of rock samples collected from field for spectral inspection. Subsequently, MTTCIMF algorithm was implemented on processed image to obtain mineral distribution map of each detected mineral. A virtual verification method has been adopted to evaluate the classified image, which uses directly image information to evaluate the result and confirm the overall accuracy and kappa coefficient of 68 % and 0.6 respectively. The sub-pixel level mineral information with reasonable accuracy could be a valuable guide to geological and exploration community for expensive ground and/or lab experiments to discover economic deposits. Thus, the study demonstrates the feasibility of Hyperion data for sub-pixel mineral mapping using MTTCIMF algorithm with cost and time effective approach.

  4. Mapping an invasive plant, Phragmites australis, in coastal wetlands using the EO-1 Hyperion hyperspectral sensor

    USGS Publications Warehouse

    Pengra, B.W.; Johnston, C.A.; Loveland, T.R.

    2007-01-01

    Mapping tools are needed to document the location and extent of Phragmites australis, a tall grass that invades coastal marshes throughout North America, displacing native plant species and degrading wetland habitat. Mapping Phragmites is particularly challenging in the freshwater Great Lakes coastal wetlands due to dynamic lake levels and vegetation diversity. We tested the applicability of Hyperion hyperspectral satellite imagery for mapping Phragmites in wetlands of the west coast of Green Bay in Wisconsin, U.S.A. A reference spectrum created using Hyperion data from several pure Phragmites stands within the image was used with a Spectral Correlation Mapper (SCM) algorithm to create a raster map with values ranging from 0 to 1, where 0 represented the greatest similarity between the reference spectrum and the image spectrum and 1 the least similarity. The final two-class thematic classification predicted monodominant Phragmites covering 3.4% of the study area. Most of this was concentrated in long linear features parallel to the Green Bay shoreline, particularly in areas that had been under water only six years earlier when lake levels were 66??cm higher. An error matrix using spring 2005 field validation points (n = 129) showed good overall accuracy-81.4%. The small size and linear arrangement of Phragmites stands was less than optimal relative to the sensor resolution, and Hyperion's 30??m resolution captured few if any pure pixels. Contemporary Phragmites maps prepared with Hyperion imagery would provide wetland managers with a tool that they currently lack, which could aid attempts to stem the spread of this invasive species. ?? 2006 Elsevier Inc. All rights reserved.

  5. Remote sensing of spruce budworm defoliation using EO-1 Hyperion hyperspectral data: an example in Quebec, Canada

    NASA Astrophysics Data System (ADS)

    Huang, Z.; Zhang, Y.

    2016-04-01

    Each year, the spruce budworm (SBW) causes severe, widespread damage to spruces and fir in east coast Canada. Early estimation of the defoliation can provide crucial support to mitigate the socio-economic impact on vulnerable forests. Remote sensing techniques are suitable to investigate the affected regions that usually consist of large and inaccessible forestry areas. Using satellite images, surface reflectance values at two or more wavelengths are combined to generate vegetation indices (VIs), revealing a relative abundance of features of interest. Forest health analysis based on VIs is considered as one of the primary information sources for monitoring vegetation conditions. Especially the spectral resolution of Hyperion hyperspectral satellite imagery used in this study allows for a detailed examination of the red to near-infrared portion of the spectrum to identify areas of stressed vegetation. Several narrow-band vegetation indices are used to indicate the overall amount and quality of photosynthetic material and moisture content in vegetation. By integrating the information from VIs that focus on different aspects of overall health and vigour in forested areas, the study aims at detecting defoliated condition in a forested region in the Province of Quebec, Canada. In June and August of 2014 two Hyperion images were acquired by NASA's EO-1 satellite for this study. Changes in vegetation health and vigour are observed and quantitatively compared using the multi-temporal remote sensing images. The experimental results suggest that the VI- based forest health analysis is effective in estimating SBW defoliation in the study area.

  6. Geologic Validation of EO-1 Hyperion using AVIRIS

    NASA Technical Reports Server (NTRS)

    Kruse, F. A.; Boardman, J. W.; Huntington, J. H.

    2001-01-01

    Over the last few years, the field of imaging spectrometry has grown rapidly as new instruments and analysis techniques have been developed. The launch of Hyperion as part of NASA's EO-1 program represents a significant landmark in the progression of the technology; the first spaceborne imaging spectrometry system. AIG, in cooperation with CSIRO, is evaluating, validating, and demonstrating use of EO-1 Hyperion hyperspectral data for geologic applications. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) plays a pivotal role in this effort. This manuscript describes the geologic test sites being used and progress on preparing 'ground truth' for anticipated Hyperion data collects using AVIRIS data. Preliminary findings are extrapolated to predict the effect of instrument characteristics and performance on geologic mapping using Hyperion.

  7. Mapping forest biomass from space - Fusion of hyperspectral EO1-hyperion data and Tandem-X and WorldView-2 canopy height models

    NASA Astrophysics Data System (ADS)

    Kattenborn, Teja; Maack, Joachim; Faßnacht, Fabian; Enßle, Fabian; Ermert, Jörg; Koch, Barbara

    2015-03-01

    Spaceborne sensors allow for wide-scale assessments of forest ecosystems. Combining the products of multiple sensors is hypothesized to improve the estimation of forest biomass. We applied interferometric (Tandem-X) and photogrammetric (WorldView-2) based predictors, e.g. canopy height models, in combination with hyperspectral predictors (EO1-Hyperion) by using 4 different machine learning algorithms for biomass estimation in temperate forest stands near Karlsruhe, Germany. An iterative model selection procedure was used to identify the optimal combination of predictors. The most accurate model (Random Forest) reached a r2 of 0.73 with a RMSE of 14.9% (29.4 t/ha). Further results revealed that the predictive accuracy depended highly on the statistical model and the area size of the field samples. We conclude that a fusion of canopy height and spectral information allows for accurate estimations of forest biomass from space.

  8. A whole image approach using field measurements for transforming EO1 Hyperion hyperspectral data into canopy reflectance spectra

    USGS Publications Warehouse

    Ramsey, Elijah W.; Nelson, G.

    2005-01-01

    To maximize the spectral distinctiveness (information) of the canopy reflectance, an atmospheric correction strategy was implemented to provide accurate estimates of the intrinsic reflectance from the Earth Observing 1 (EO1) satellite Hyperion sensor signal. In rendering the canopy reflectance, an estimate of optical depth derived from a measurement of downwelling irradiance was used to drive a radiative transfer simulation of atmospheric scattering and attenuation. During the atmospheric model simulation, the input whole-terrain background reflectance estimate was changed to minimize the differences between the model predicted and the observed canopy reflectance spectra at 34 sites. Lacking appropriate spectrally invariant scene targets, inclusion of the field and predicted comparison maximized the model accuracy and, thereby, the detail and precision in the canopy reflectance necessary to detect low percentage occurrences of invasive plants. After accounting for artifacts surrounding prominent absorption features from about 400nm to 1000nm, the atmospheric adjustment strategy correctly explained 99% of the observed canopy reflectance spectra variance. Separately, model simulation explained an average of 88%??9% of the observed variance in the visible and 98% ?? 1% in the near-infrared wavelengths. In the 34 model simulations, maximum differences between the observed and predicted reflectances were typically less than ?? 1% in the visible; however, maximum reflectance differences higher than ?? 1.6% (

  9. Mapping the invasive species, Chinese tallow, with EO1 satellite Hyperion hyperspectral image data and relating tallow occurrences to a classified Landsat Thematic Mapper land cover map

    USGS Publications Warehouse

    Ramsey, Elijah W.; Rangoonwala, A.; Nelson, G.; Ehrlich, R.

    2005-01-01

    Our objective was to provide a realistic and accurate representation of the spatial distribution of Chinese tallow (Triadica sebifera) in the Earth Observing 1 (EO1) Hyperion hyperspectral image coverage by using methods designed and tested in previous studies. We transformed, corrected, and normalized Hyperion reflectance image data into composition images with a subpixel extraction model. Composition images were related to green vegetation, senescent foliage and senescing cypress-tupelo forest, senescing Chinese tallow with red leaves ('red tallow'), and a composition image that only corresponded slightly to yellowing vegetation. These statistical and visual comparisons confirmed a successful portrayal of landscape features at the time of the Hyperion image collection. These landscape features were amalgamated in the Landsat Thematic Mapper (TM) pixel, thereby preventing the detection of Chinese tallow occurrences in the Landsat TM classification. With the occurrence in percentage of red tallow (as a surrogate for Chinese tallow) per pixel mapped, we were able to link dominant land covers generated with Landsat TM image data to Chinese tallow occurrences as a first step toward determining the sensitivity and susceptibility of various land covers to tallow establishment. Results suggested that the highest occurrences and widest distribution of red tallow were (1) apparent in disturbed or more open canopy woody wetland deciduous forests (including cypress-tupelo forests), upland woody land evergreen forests (dominantly pines and seedling plantations), and upland woody land deciduous and mixed forests; (2) scattered throughout the fallow fields or located along fence rows separating active and non-active cultivated and grazing fields, (3) found along levees lining the ubiquitous canals within the marsh and on the cheniers near the coastline; and (4) present within the coastal marsh located on the numerous topographic highs. ?? 2005 US Government.

  10. Advantage of hyperspectral EO-1 Hyperion over multispectral IKONOS, GeoEye-1, WorldView-2, Landsat ETM+, and MODIS vegetation indices in crop biomass estimation

    USGS Publications Warehouse

    Marshall, Michael T.; Thenkabail, Prasad S.

    2015-01-01

    Crop biomass is increasingly being measured with surface reflectance data derived from multispectral broadband (MSBB) and hyperspectral narrowband (HNB) space-borne remotely sensed data to increase the accuracy and efficiency of crop yield models used in a wide array of agricultural applications. However, few studies compare the ability of MSBBs versus HNBs to capture crop biomass variability. Therefore, we used standard data mining techniques to identify a set of MSBB data from the IKONOS, GeoEye-1, Landsat ETM+, MODIS, WorldView-2 sensors and compared their performance with HNB data from the EO-1 Hyperion sensor in explaining crop biomass variability of four important field crops (rice, alfalfa, cotton, maize). The analysis employed two-band (ratio) vegetation indices (TBVIs) and multiband (additive) vegetation indices (MBVIs) derived from Singular Value Decomposition (SVD) and stepwise regression. Results demonstrated that HNB-derived TBVIs and MBVIs performed better than MSBB-derived TBVIs and MBVIs on a per crop basis and for the pooled data: overall, HNB TBVIs explained 5–31% greater variability when compared with various MSBB TBVIs; and HNB MBVIs explained 3–33% greater variability when compared with various MSBB MBVIs. The performance of MSBB MBVIs and TBVIs improved mildly, by combining spectral information across multiple sensors involving IKONOS, GeoEye-1, Landsat ETM+, MODIS, and WorldView-2. A number of HNBs that advance crop biomass modeling were determined. Based on the highest factor loadings on the first component of the SVD, the “red-edge” spectral range (700–740 nm) centered at 722 nm (bandwidth = 10 nm) stood out prominently, while five additional and distinct portions of the recorded spectral range (400–2500 nm) centered at 539 nm, 758 nm, 914 nm, 1130 nm, 1320 nm (bandwidth = 10 nm) were also important. The best HNB vegetation indices for crop biomass estimation involved 549 and 752 nm for rice (R2 = 0.91); 925 and 1104 nm for

  11. Advantage of hyperspectral EO-1 Hyperion over multispectral IKONOS, GeoEye-1, WorldView-2, Landsat ETM+, and MODIS vegetation indices in crop biomass estimation

    NASA Astrophysics Data System (ADS)

    Marshall, Michael; Thenkabail, Prasad

    2015-10-01

    Crop biomass is increasingly being measured with surface reflectance data derived from multispectral broadband (MSBB) and hyperspectral narrowband (HNB) space-borne remotely sensed data to increase the accuracy and efficiency of crop yield models used in a wide array of agricultural applications. However, few studies compare the ability of MSBBs versus HNBs to capture crop biomass variability. Therefore, we used standard data mining techniques to identify a set of MSBB data from the IKONOS, GeoEye-1, Landsat ETM+, MODIS, WorldView-2 sensors and compared their performance with HNB data from the EO-1 Hyperion sensor in explaining crop biomass variability of four important field crops (rice, alfalfa, cotton, maize). The analysis employed two-band (ratio) vegetation indices (TBVIs) and multiband (additive) vegetation indices (MBVIs) derived from Singular Value Decomposition (SVD) and stepwise regression. Results demonstrated that HNB-derived TBVIs and MBVIs performed better than MSBB-derived TBVIs and MBVIs on a per crop basis and for the pooled data: overall, HNB TBVIs explained 5-31% greater variability when compared with various MSBB TBVIs; and HNB MBVIs explained 3-33% greater variability when compared with various MSBB MBVIs. The performance of MSBB MBVIs and TBVIs improved mildly, by combining spectral information across multiple sensors involving IKONOS, GeoEye-1, Landsat ETM+, MODIS, and WorldView-2. A number of HNBs that advance crop biomass modeling were determined. Based on the highest factor loadings on the first component of the SVD, the "red-edge" spectral range (700-740 nm) centered at 722 nm (bandwidth = 10 nm) stood out prominently, while five additional and distinct portions of the recorded spectral range (400-2500 nm) centered at 539 nm, 758 nm, 914 nm, 1130 nm, 1320 nm (bandwidth = 10 nm) were also important. The best HNB vegetation indices for crop biomass estimation involved 549 and 752 nm for rice (R2 = 0.91); 925 and 1104 nm for alfalfa (R2 = 0

  12. Karst rocky desertification information extraction with EO-1 Hyperion data

    NASA Astrophysics Data System (ADS)

    Yue, Yuemin; Wang, Kelin; Zhang, Bing; Jiao, Quanjun; Yu, Yizun

    2008-12-01

    Karst rocky desertification is a special kind of land desertification developed under violent human impacts on the vulnerable eco-geo-environment of karst ecosystem. The process of karst rocky desertification results in simultaneous and complex variations of many interrelated soil, rock and vegetation biogeophysical parameters, rendering it difficult to develop simple and robust remote sensing mapping and monitoring approaches. In this study, we aimed to use Earth Observing 1 (EO-1) Hyperion hyperspectral data to extract the karst rocky desertification information. A spectral unmixing model based on Monte Carlo approach, was employed to quantify the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare substrates. The results showed that SWIR (1.9-2.35μm) portions of the spectrum were significantly different in PV, NPV and bare rock spectral properties. It has limitations in using full optical range or only SWIR (1.9-2.35μm) region of Hyperion to decompose image into PV, NPV and bare substrates covers. However, when use the tied-SWIR, the sub-pixel fractional covers of PV, NPV and bare substrates were accurately estimated. Our study indicates that the "tied-spectrum" method effectively accentuate the spectral characteristics of materials, while the spectral unmixing model based on Monte Carlo approach is a useful tool to automatically extract mixed ground objects in karst ecosystem. Karst rocky desertification information can be accurately extracted with EO-1 Hyperion. Imaging spectroscopy can provide a powerful methodology toward understanding the extent and spatial pattern of land degradation in karst ecosystem.

  13. Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion-EO-1 Data

    NASA Technical Reports Server (NTRS)

    Thenkabail, Prasad S.; Mariotto, Isabella; Gumma, Murali Krishna; Middleton, Elizabeth M.; Landis, David R.; Huemmrich, K. Fred

    2013-01-01

    The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy approx. 70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using approx. 20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was approx. 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or "the curse of high dimensionality") in hyperspectral data for a particular application (e

  14. Selection of hyperspectral narrowbands (HNBs) and composition of hyperspectral twoband vegetation indices (HVIs) for biophysical characterization and discrimination of crop types using field reflectance and Hyperion/EO-1 data

    USGS Publications Warehouse

    Thenkabail, P.S.; Mariotto, I.; Gumma, M.K.; Middleton, E.M.; Landis, D.R.; Huemmrich, K.F.

    2013-01-01

    The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy ~70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using ~20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was ~ 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or “the curse of high dimensionality”) in hyperspectral data for a particular application (e.g., biophysi- al

  15. EO-1/Hyperion: Nearing Twelve Years of Successful Mission Science Operation and Future Plans

    NASA Technical Reports Server (NTRS)

    Middleton, Elizabeth M.; Campbell, Petya K.; Huemmrich, K. Fred; Zhang, Qingyuan; Landis, David R.; Ungar, Stephen G.; Ong, Lawrence; Pollack, Nathan H.; Cheng, Yen-Ben

    2012-01-01

    The Earth Observing One (EO-1) satellite is a technology demonstration mission that was launched in November 2000, and by July 2012 will have successfully completed almost 12 years of high spatial resolution (30 m) imaging operations from a low Earth orbit. EO-1 has two unique instruments, the Hyperion and the Advanced Land Imager (ALI). Both instruments have served as prototypes for NASA's newer satellite missions, including the forthcoming (in early 2013) Landsat-8 and the future Hyperspectral Infrared Imager (HyspIRI). As well, EO-1 is a heritage platform for the upcoming German satellite, EnMAP (2015). Here, we provide an overview of the mission, and highlight the capabilities of the Hyperion for support of science investigations, and present prototype products developed with Hyperion imagery for the HyspIRI and other space-borne spectrometers.

  16. Vicarious Calibration of EO-1 Hyperion

    NASA Technical Reports Server (NTRS)

    McCorkel, Joel; Thome, Kurt; Lawrence, Ong

    2012-01-01

    The Hyperion imaging spectrometer on the Earth Observing-1 satellite is the first high-spatial resolution imaging spectrometer to routinely acquire science-grade data from orbit. Data gathered with this instrument needs to be quantitative and accurate in order to derive meaningful information about ecosystem properties and processes. Also, comprehensive and long-term ecological studies require these data to be comparable over time, between coexisting sensors and between generations of follow-on sensors. One method to assess the radiometric calibration is the reflectance-based approach, a common technique used for several other earth science sensors covering similar spectral regions. This work presents results of radiometric calibration of Hyperion based on the reflectance-based approach of vicarious calibration implemented by University of Arizona during 2001 2005. These results show repeatability to the 2% level and accuracy on the 3 5% level for spectral regions not affected by strong atmospheric absorption. Knowledge of the stability of the Hyperion calibration from moon observations allows for an average absolute calibration based on the reflectance-based results to be determined and applicable for the lifetime of Hyperion.

  17. Hyperspectral Transformation from EO-1 ALI Imagery Using Pseudo-Hyperspectral Image Synthesis Algorithm

    NASA Astrophysics Data System (ADS)

    Tien Hoang, Nguyen; Koike, Katsuaki

    2016-06-01

    Hyperspectral remote sensing is more effective than multispectral remote sensing in many application fields because of having hundreds of observation bands with high spectral resolution. However, hyperspectral remote sensing resources are limited both in temporal and spatial coverage. Therefore, simulation of hyperspectral imagery from multispectral imagery with a small number of bands must be one of innovative topics. Based on this background, we have recently developed a method, Pseudo-Hyperspectral Image Synthesis Algorithm (PHISA), to transform Landsat imagery into hyperspectral imagery using the correlation of reflectance at the corresponding bands between Landsat and EO-1 Hyperion data. This study extends PHISA to simulate pseudo-hyperspectral imagery from EO-1 ALI imagery. The pseudo-hyperspectral imagery has the same number of bands as that of high-quality Hyperion bands and the same swath width as ALI scene. The hyperspectral reflectance data simulated from the ALI data show stronger correlation with the original Hyperion data than the one simulated from Landsat data. This high correlation originates from the concurrent observation by the ALI and Hyperion sensors that are on-board the same satellite. The accuracy of simulation results are verified by a statistical analysis and a surface mineral mapping. With a combination of the advantages of both ALI and Hyperion image types, the pseudo-hyperspectral imagery is proved to be useful for detailed identification of minerals for the areas outside the Hyperion coverage.

  18. What We Have Learned with 16 Years of EO-1 Hyperion

    NASA Astrophysics Data System (ADS)

    Ungar, S.

    2016-12-01

    The Earth Observing-One (EO-1) satellite, launched in November of 2000, will complete its sixteenth and final year of operation at the end of calendar year 2016. Observations from the Hyperion Imaging Spectrometer on board EO-1 have contributed to hundreds of papers in refereed journals, conference proceeds and other presentations. The EO-1 Hyperion imaging spectrometer is the first and longest operating instrument that provides visible to shortwave infrared science-grade data from orbit. Hyperion has been used to study a variety of natural and anthropogenic phenomena including hazards and catastrophes, agricultural health and productivity, ecological disturbance/development, and land use/land cover change. As an example, Hyperion has been used in hazard and catastrophe studies to monitor and assess effects of tsunamis, earthquakes, volcanic eruptions, mudslides, tornadoes, hurricanes, wild-fires (natural and human ignited), oil spills, and the aftermath of world trade center bombing. This presentation summarizes the current status of EO-1 Hyperion in terms of key scientific findings to date and presents future plans for exploiting the upward of 90,000 scenes expected to be archived at USGS EROS by the end of the mission. Hyperion serves as the heritage orbital spectrometer for future global platforms, including the proposed NASA Hyperspectral Infrared Imager (HyspIRI) and the forthcoming German satellite, EnMAP. A key EO-1 mission goal was to evaluate the ability of satellite high spectral resolution imaging to characterize terrestrial surface state and processes at 30 m resolution. Researchers engaged in NASA's Terrestrial Ecology, Carbon Science, Land Use Change and other programs using the EO-1 Hyperion imaging spectrometer have achieved results with accuracies far exceeding those reached with the current spaceborne fleet of multispectral sensors. Hyperion data provide several advantages over data from multispectral satellite systems: they inherently provide

  19. Endmember identification from EO-1 Hyperion L1_R hyperspectral data to build saltmarsh spectral library in Hunter Wetland, NSW, Australia

    NASA Astrophysics Data System (ADS)

    Rasel, Sikdar M. M.; Chang, Hsing-Chung; Ralph, Tim; Saintilan, Neil

    2015-10-01

    Saltmarsh is one of the important communities of wetlands, however, due to a range of pressures, it has been declared as an EEC (Ecological Endangered Community) in Australia. In order to correctly identify different saltmarsh species, development of spectral libraries of saltmarsh species is essential to monitor this EEC. Hyperspectral remote sensing, can explore the area of wetland monitoring and mapping. The benefits of Hyperion data to wetland monitoring have been studied at Hunter Wetland Park, NSW, Australia. After exclusion of bad bands from the original data, an atmospheric correction model was applied to minimize atmospheric effect and to retrieve apparent surface reflectance for different land cover. Large data dimensionality was reduced by Forward Minimum Noise Fraction (MNF) algorithm. It was found that first 32 MNF band contains more than 80% information of the image. Pixel Purity Index (PPI) algorithm worked properly to extract pure pixel for water, builtup area and three vegetation Casuarina sp., Phragmitis sp. and green grass. The result showed it was challenging to extract extreme pure pixel for Sporobolus and Sarcocornia from the data due to coarse resolution (30 m) and small patch size (<3 m) of those vegetation on the ground . Spectral Angle Mapper, classified the image into five classes: Casuarina, Saltmarsh (Phragmitis), Green grass, Water and Builtup area with 43.55 % accuracy. This classification also failed to classify Sporobolus as a distinct group due to the same reason. A high spatial resolution airborne hyperspectral data and a new study site with a bigger patch of Sporobolus and Sarcocornia is proposed to overcome the issue.

  20. Autonomous Volcanic Activity Detection with ASE on EO-1 Hyperion: Applications for Planetary Missions

    NASA Astrophysics Data System (ADS)

    Davies, A. G.; Baker, V.; Castano, R.; Chien, S.; Cichy, B.; Doggett, T.; Dohm, J.; Greeley, R.; Rabideau, G.; Sherwood, R.; Williams, K.; ASE Project Team

    2003-05-01

    The New Millennium Program (NMP) Space Technology 6 (ST-6) Autonomous Sciencecraft Experiment (ASE) will fly two scene classifiers on the Earth Orbiting 1 (EO-1) spacecraft in the fall of 2003, and will demonstrate autonomous, onboard processing of Hyperion imager 0.4-2.4 micron hyperspectral data, and autonomous, science-driven planning and acquisition of subsequent observations. ASE is an experiment to meet NASA's call for systems with reduced downlink and onboard data processing to enable autonomous missions. ASE software is divided into three classes: (1) spacecraft command and control; (2) an onboard planner (CASPER); and (3) modular science algorithms, which are used to process raw data to search out specific features and spectral signatures. The ASE Science Team has developed scene classifiers to detect thermal emission in both day and nighttime Hyperion data, and are continuing to develop other scene classifiers for ice, snow, water and land for future release and flight on EO-1. Once uploaded, the thermal scene classifier effectively turns the EO-1 spacecraft into an autonomously operating and reacting volcanic activity detector. It is possible to envision such a capability on spacecraft observing volcanism on Io and Triton, autonomously identifying and classifying activity, identifying sites deserving of closer scrutiny, and retasking the spacecraft to observe them, thus fulfilling NASA's goal of fully-autonomous, science-driven spacecraft. This work was carried out at the Jet Propulsion Laboratory-California Institute of Technology, under contract to NASA.

  1. Status of Current and Future Remote Sensing with EO-1 Hyperion

    NASA Technical Reports Server (NTRS)

    Ungar, Stephen

    2006-01-01

    The Earth Observing-One (EO-1) satellite, launched in November of 2000, will complete six full years of operation near the end of this year. Observations from the Hyperion Imaging Spectrometer on board EO-1 have contributed to over 300 papers in refereed journals, conference proceeds and other presentations. Hyperion has been used to study a variety of natural and anthropogenic phenomena including hazards and catastrophes, agricultural health and productivity, ecological disturbance/development, and land use/land cover change. As an example, Hyperion has been used in hazard and catastrophe studies to monitor and assess effects of tsunamis, earthquakes, volcanic eruptions, mudslides, tornadoes, hurricanes, wild-fires (natural and human ignited), oil spills, and the aftermath of world trade center bombing. This presentation summarizes the current status of EO-1 Hyperion in terms of key scientific findings to date and future plans for operation of this instrument through 2007.

  2. Status of Current and Future Remote Sensing with EO-1 Hyperion

    NASA Technical Reports Server (NTRS)

    Ungar, Stephen

    2006-01-01

    The Earth Observing-One (EO-1) satellite, launched in November of 2000, will complete six full years of operation near the end of this year. Observations from the Hyperion Imaging Spectrometer on board EO-1 have contributed to over 300 papers in refereed journals, conference proceeds and other presentations. Hyperion has been used to study a variety of natural and anthropogenic phenomena including hazards and catastrophes, agricultural health and productivity, ecological disturbance/development, and land use/land cover change. As an example, Hyperion has been used in hazard and catastrophe studies to monitor and assess effects of tsunamis, earthquakes, volcanic eruptions, mudslides, tornadoes, hurricanes, wild-fires (natural and human ignited), oil spills, and the aftermath of world trade center bombing. This presentation summarizes the current status of EO-1 Hyperion in terms of key scientific findings to date and future plans for operation of this instrument through 2007.

  3. Mineral Mapping with AVIRIS and EO-1 Hyperion

    NASA Technical Reports Server (NTRS)

    Kruse, Fred A.

    2004-01-01

    Imaging Spectrometry data or Hyperspectral Imagery (HSI) acquired using airborne systems have been used in the geologic community since the early 1980 s and represent a mature technology (Goetz et al., 1985; Kruse et al., 1999). The solar spectral range, 0.4 to 2.5 m, provides abundant information about many important Earth-surface minerals (Clark et al., 1990). In particular, the 2.0 to 2.5 m (SWIR) spectral range covers spectral features of hydroxyl-bearing minerals, sulfates, and carbonates common to many geologic units and hydrothermal alteration assemblages. Previous research has proven the ability of airborne and spaceborne hyperspectral systems to uniquely identify and map these and other minerals, even in sub-pixel abundances (Kruse and Lefkoff, 1993; Boardman and Kruse, 1994; Boardman et al., 1995; Kruse, et al., 1999). This paper describes a case history for a site in northern Death Valley, California and Nevada along with selected SNR calculations/results for other sites around the world. Various hyperspectral mineral mapping results for this site have previously been presented and published (Kruse, 1988; Kruse et al., 1993, 1999, 2001, 2002, 2003), however, this paper presents a condensed summary of key details for hyperspectral data from 2000 and 2001 and the results of accuracy assessment for satellite hyperspectral data compared to airborne hyperspectral data used as ground truth.

  4. Eo-1 Hyperion Measures Canopy Drought Stress In Amazonia

    NASA Technical Reports Server (NTRS)

    Asner, Gregory P.; Nepstad, Daniel; Cardinot, Gina; Moutinho, Paulo; Harris, Thomas; Ray, David

    2004-01-01

    The central, south and southeast portions of the Amazon Basin experience a period of decreased cloud cover and precipitation from June through November. There are likely important effects of seasonal and interannual rainfall variation on forest leaf area index, canopy water stress, productivity and regional carbon cycling in the Amazon. While both ground and spaceborne studies of precipitation continue to improve, there has been almost no progress made in observing forest canopy responses to rainfall variability in the humid tropics. This shortfall stems from the large stature of the vegetation and great spatial extent of tropical forests, both of which strongly impede field studies of forest responses to water availability. Those few studies employing satellite measures of canopy responses to seasonal and interannual drought (e.g., Bohlman et al. 1998, Asner et al. 2000) have been limited by the spectral resolution and sampling available from Landsat and AVHRR sensors. We report on a study combining the first landscape-level, managed drought experiment in Amazon tropical forest with the first spaceborne imaging spectrometer observations of this experimental area. Using extensive field data on rainfall inputs, soil water content, and both leaf and canopy responses, we test the hypothesis that spectroscopic signatures unique to hyperspectral observations can be used to quantify relative differences in canopy stress resulting from water availability.

  5. Using EO-1 Hyperion Images to Prototype Environmental Products for Hyspiri

    NASA Technical Reports Server (NTRS)

    Middleton, Elizabeth M.; Campbell, Petya K. E.; Ungar, Stephen G.; Ong, Lawrence; Zhang, Qingyuan; Huemmrich, K. Fred; Mandl, Daniel J.; Frye, Stuart W.

    2011-01-01

    In November 2010, the Earth Observing One (EO-1) Satellite Mission will successfully complete a decade of Earth imaging by its two unique instruments, the Hyperion and the Advanced Land Imager (ALI). Both instruments are serving as prototypes for new orbital sensors, and the EO-1 is a heritage platform for the upcoming German mission, EnMAP. We provide an overview of the mission's lifetime. We briefly describe calibration & validation activities and overview the technical and scientific accomplishments of this mission. Some examples of the Mission Science Office (MSO) products are provided, as is an example of a image collected for disaster monitoring.

  6. Using EO-1 Hyperion Images to Prototype Environmental Products for Hyspiri

    NASA Technical Reports Server (NTRS)

    Middleton, Elizabeth M.; Campbell, Petya K. E.; Ungar, Stephen G.; Ong, Lawrence; Zhang, Qingyuan; Huemmrich, K. Fred; Mandl, Daniel J.; Frye, Stuart W.

    2011-01-01

    In November 2010, the Earth Observing One (EO-1) Satellite Mission will successfully complete a decade of Earth imaging by its two unique instruments, the Hyperion and the Advanced Land Imager (ALI). Both instruments are serving as prototypes for new orbital sensors, and the EO-1 is a heritage platform for the upcoming German mission, EnMAP. We provide an overview of the mission's lifetime. We briefly describe calibration & validation activities and overview the technical and scientific accomplishments of this mission. Some examples of the Mission Science Office (MSO) products are provided, as is an example of a image collected for disaster monitoring.

  7. Simulation of EO-1 Hyperion Data from ALI Multispectral Data Based on the Spectral Reconstruction Approach.

    PubMed

    Liu, Bo; Zhang, Lifu; Zhang, Xia; Zhang, Bing; Tong, Qingxi

    2009-01-01

    Data simulation is widely used in remote sensing to produce imagery for a new sensor in the design stage, for scale issues of some special applications, or for testing of novel algorithms. Hyperspectral data could provide more abundant information than traditional multispectral data and thus greatly extend the range of remote sensing applications. Unfortunately, hyperspectral data are much more difficult and expensive to acquire and were not available prior to the development of operational hyperspectral instruments, while large amounts of accumulated multispectral data have been collected around the world over the past several decades. Therefore, it is reasonable to examine means of using these multispectral data to simulate or construct hyperspectral data, especially in situations where hyperspectral data are necessary but hard to acquire. Here, a method based on spectral reconstruction is proposed to simulate hyperspectral data (Hyperion data) from multispectral Advanced Land Imager data (ALI data). This method involves extraction of the inherent information of source data and reassignment to newly simulated data. A total of 106 bands of Hyperion data were simulated from ALI data covering the same area. To evaluate this method, we compare the simulated and original Hyperion data by visual interpretation, statistical comparison, and classification. The results generally showed good performance of this method and indicated that most bands were well simulated, and the information both preserved and presented well. This makes it possible to simulate hyperspectral data from multispectral data for testing the performance of algorithms, extend the use of multispectral data and help the design of a virtual sensor.

  8. Ameliorating the spatial resolution of Hyperion hyperspectral data

    NASA Astrophysics Data System (ADS)

    Nikolakopoulos, Konstantinos G.; Tsombos, Panagiotis I.; Skianis, George A.; Vaiopoulos, Dimitrios A.

    2009-09-01

    In this study seven fusion techniques and more especially the Ehlers, Gram-Schmidt, High Pass Filter, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Pansharp and PCA, were used for the fusion of Hyperion hyperspectral data with ALI panchromatic data. Both sensors are onboard on EO-1 satellite and the data are collected simultaneously. The panchromatic data has a spatial resolution of 10m while the hyperspectral data has a spatial resolution of 30m. All the fusion techniques are designed for use with classical multispectral data. Thus, it is quite interesting to investigate the assessment of the common used fusion algorithms with the hyperspectral data. The area of study is the broader area of North Western Athens near to Thrakomakedones village.

  9. Land coverage classification using EO-1/Hyperion and ALOS/PALSAR: Possibility of combined analysis with different type of sensors

    NASA Astrophysics Data System (ADS)

    Koizumi, E.; Furuta, R.; Yamamoto, A.

    2012-12-01

    Hyper-spectral has huge advantage in determining the land surface coverage due to its spectral resolution and large number of bands, however, its swath is comparatively narrow, and there is cloud problem. In contrast, radar sensor can observe under almost all weather condition, and has wide observation swath. Therefore, if radar data can be used for the detection of land surface with hyper-spectral data, it will be useful tool for the monitoring in any field. However, there are not so many reports about the land-cover detection with combination use of both hyper-spectral data and SAR data so far. In our previous study, we detected wet area around Sendai Airport where suffered Tsunami by 2011 great earthquake in the northern Japan by combined analysis of satellite hyper-spectral and SAR data. In that study, the possible wet regions were successfully detected objectively in wide area. In this study, we adopted similar method on soil surface to investigate the relationship between land coverage classification by hyper-spectral data (EO-1/Hyperion) and physical values from L-band SAR (ALOS/PALSAR), and to study how to apply the combined analysis of hyper-spectral and SAR data to land coverage monitoring (e.g. landslides). Mauna Kea, Hawaii was selected as the test site of this study because whose land coverage shows variety; various volcanic soils, mixture of soil and vegetation, and lava flow from Mauna Loa from top to hillside. The Hyperion equipment has 242 channels but some of them include full noise or have no data. We selected channels by checking each channel, and select 105 channels. Before analysis, the atmospheric correction was applied by ENVI/FLAASH for the selected channels. The corrected data were analyzed by both unsupervised and supervised classification (based on the result from field work). Each classified results were extracted as vector data. For SAR data analysis, Dual Polarization data (FBD) is selected. SAR data were converted to backscattered

  10. Integrating Chlorophyll fapar and Nadir Photochemical Reflectance Index from EO-1/Hyperion to Predict Cornfield Daily Gross Primary Production

    NASA Technical Reports Server (NTRS)

    Zhang, Qingyuan; Middleton, Elizabeth M.; Cheng, Yen-Ben; Huemmrich, K. Fred; Cook, Bruce D.; Corp, Lawrence A.; Kustas, William P.; Russ, Andrew L.; Prueger, John H.; Yao, Tian

    2016-01-01

    .57%. Both seasonal Epsilon (sub chl) and PRI (sub nadir) were strongly correlated with fAPAR (sub chl ) retrieved from field measurements, which indicates that chlorophyll content strongly affects seasonal epsilon (sub chl) and PRI (sub nadir). We demonstrate the potential capacity to monitor GPP with space-based visible through shortwave infrared (VSWIR) imaging spectrometers such as NASA's soon to be decommissioned EO- 1/Hyperion and the future Hyperspectral Infrared Imager (HyspIRI).

  11. Integrating Chlorophyll fapar and Nadir Photochemical Reflectance Index from EO-1/Hyperion to Predict Cornfield Daily Gross Primary Production

    NASA Technical Reports Server (NTRS)

    Zhang, Qingyuan; Middleton, Elizabeth M.; Cheng, Yen-Ben; Huemmrich, K. Fred; Cook, Bruce D.; Corp, Lawrence A.; Kustas, William P.; Russ, Andrew L.; Prueger, John H.; Yao, Tian

    2016-01-01

    .57%. Both seasonal Epsilon (sub chl) and PRI (sub nadir) were strongly correlated with fAPAR (sub chl ) retrieved from field measurements, which indicates that chlorophyll content strongly affects seasonal epsilon (sub chl) and PRI (sub nadir). We demonstrate the potential capacity to monitor GPP with space-based visible through shortwave infrared (VSWIR) imaging spectrometers such as NASA's soon to be decommissioned EO- 1/Hyperion and the future Hyperspectral Infrared Imager (HyspIRI).

  12. Initial lunar calibration observations by the EO-1 Hyperion imaging spectrometer

    USGS Publications Warehouse

    Kieffer, H.H.; Jarecke, P.; Pearlman, Jay; ,

    2002-01-01

    The Moon provides an exo-atmospheric radiance source that can be used to determine trends in instrument radio-metric responsivity with high precision. Lunar observations can also be used for absolute radiometric calibration; knowledge of the radiometric scale will steadily improve through independent study of lunar spectral photometry and with sharing of the Moon as a calibration target by increasing numbers of spacecraft, each with its own calibration history. EO-1 calibration includes periodic observation of the Moon by all three of its instruments. Observations are normally made with a phase angle of about 7 degrees (or about 12 hours from the time of Full Moon). Also, SeaWiFS has been making observations at such phase angles for several years, and observations of the Moon by instrument pairs, even if at different times, can be used to transfer absolute calibration. A challenge for EO-1 is pointing to include the entire full Moon in the narrow Hyperion scan. Three Hyperion observations in early 2001 covering an order-of-magnitude difference in lunar irradiance show good agreement for responsivity; the SWIR detector has undergone some changes in responsivity. Small discrepancies of calibration with wavelength could be smoothed using the Moon as a source. Off-axis scattered light response and cross-track response variations can be assessed using the lunar image.

  13. Use of EO-1 Hyperion data to calculate spectral band adjustment factors (SBAF) between the L7 ETM+ and Terra MODIS sensors

    USGS Publications Warehouse

    Chander, Gyanesh; Mishra, N.; Helder, Dennis L.; Aaron, D.; Choi, T.; Angal, A.; Xiong, X.

    2010-01-01

    Different applications and technology developments in Earth observations necessarily require different spectral coverage. Thus, even for the spectral bands designed to look at the same region of the electromagnetic spectrum, the relative spectral responses (RSR) of different sensors may be different. In this study, spectral band adjustment factors (SBAF) are derived using hyperspectral Earth Observing-1 (EO-1) Hyperion measurements to adjust for the spectral band differences between the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) top-of-atmosphere (TOA) reflectance measurements from 2000 to 2009 over the pseudo-invariant Libya 4 reference standard test site.

  14. EO-1 Hyperion reflectance time series at calibration and validation sites: stability and sensitivity to seasonal dynamics

    Treesearch

    Petya K. Entcheva Campbell; Elizabeth M. Middleton; Kurt J. Thome; Raymond F. Kokaly; Karl Fred Huemmrich; David Lagomasino; Kimberly A. Novick; Nathaniel A. Brunsell

    2013-01-01

    This study evaluated Earth Observing 1 (EO-1) Hyperion reflectance time series at established calibration sites to assess the instrument stability and suitability for monitoring vegetation functional parameters. Our analysis using three pseudo-invariant calibration sites in North America indicated that the reflectance time series are devoid of apparent spectral trends...

  15. [Comparison of performances in retrieving impervious surface between hyperspectral (Hyperion) and multispectral (TM/ETM+) images].

    PubMed

    Tang, Fei; Xu, Han-Qiu

    2014-04-01

    The retrieval of impervious surface is a hot topic in the remote sensing field in the past decade. Nevertheless, studies on retrieving impervious surface from hyperspectral image and the comparison of the performances in retrieving impervious surface between hyperspectral and multispectral images are rarely reported. Therefore, The present paper focuses on the characteristics of hyperspectral (EO-1 Hyperion) and multispectral (Landsat TM/ETM+) images and implements a complementary study on the comparison based on the retrieved impervious surface information between Hyperion and TM/ETM+ data. For up to 242 bands of Hyperion image, a further study was carried out to select feature bands for impervious surface retrieving using stepwise discriminant analysis. As a result, 11 feature bands were selected and a new image named Hyperion' was thus composed. The new Hyperion' image was used to investigate whether this band-reduced image could obtain higher accuracy in retrieving impervious surface. The three test regions were selected from Fuzhou, Guangzhou and Hangzhou of China, with date-coincident or nearly coincident image pairs of the used sensors. The linear spectral mixture analysis (LSMA) was employed to retrieve impervious surface and the results were accessed for their accuracy. The comparison shows that the Hyperion image has higher accuracy than TM/ETM+, and the Hyperion' composed of the selected 11 feature bands has the highest accuracy. The advantages of Hyperion in spectral and radiometric resolutions over TM/ETM+ are believed to be the main factors contributing to the higher accuracy. The high spectral and radiometric resolutions of Hyperion image allow the sensor to have higher sensitivity in distinguishing subtle spectral changes of ground objects. While, the highest accuracy the 11-band Hyperion' image achieved is owing to the significant reduction of the band dimension of the image and thus the band redundancy.

  16. Information analysis of hyperspectral images from the hyperion satellite

    NASA Astrophysics Data System (ADS)

    Puzachenko, Yu. G.; Sandlersky, R. B.; Krenke, A. N.; Puzachenko, M. Yu.

    2017-07-01

    A new method of estimating the outgoing radiation spectra data obtained from the Hyperion EO-1 satellite is considered. In theoretical terms, this method is based on the nonequilibrium thermodynamics concept with corresponding estimates of the entropy and the Kullbak information. The obtained information estimates make it possible to assess the effective work of the landscape cover both in general and for its various types and to identify the spectrum ranges primarily responsible for the information increment and, accordingly, for the effective work. The information is measured in the frequency band intervals corresponding to the peaks of solar radiation absorption by different pigments, mesophyll, and water to evaluate the system operation by their synthesis and moisture accumulation. This method is assumed to be effective in investigation of ecosystem functioning by hyperspectral remote sensing.

  17. Seasonal spectral dynamics and carbon fluxes at core EOS sites using EO-1 Hyperion images

    NASA Astrophysics Data System (ADS)

    Lagomasino, D.; Campbell, P.; Price, R. M.

    2010-12-01

    Fluxes of water and carbon into the atmosphere are critical components in order to monitor and predict climate change. Spatial heterogeneity and seasonal changes in vegetation contribute to ambiguities in regional and global CO2 and water cycle dynamics. Satellite remote sensing is essential for monitoring the spatial and temporal dynamics of various vegetation types for the purposes of determining carbon and water fluxes. Satellite data from the EO-1 Hyperion sensor was acquired for five Earth Observing Satellite (EOS) sites, Mongu (Zambia, Africa), Konza Prairie (Kansas, USA), Duke Forest (North Carolina, USA), Barrow (Alaska, USA) and Sevilleta (New Mexico, USA). Each EOS site represented a distinct vegetative ecosystem type; hardwood forest, grassland, evergreen forest, lichens, and shrubland/grassland respectively. Satellite data was atmospherically corrected using the Atmosphere CORrection Now (ACORN) model and subsequently, the spectral reflectance data was extracted in the vicinity of existing flux towers. The EO-1 Hyperion sensor proved advantageous because of its high and continuous spectral resolution (10 nm intervals from 355 to 2578 nm wavelengths). The high spectral resolution allowed us calculate biophysical indices based on specific wavelengths in the electromagnetic spectrum that are associated with alterations in foliar chemistry and plant membrane structure (i.e., vegetation stress) brought upon by many environmental factors. Previous studies have focused on relationships within a specific site or vegetation community. This study however, incorporated many sites with different vegetation types and various geographic locations throughout the world. Monitoring the fluctuations in vegetation stress with contemporaneous environmental conditions and carbon flux measurements from each site will provide better insight into water and carbon flux dynamics in many different biomes. Noticeable spectral signatures were identified based on site specific

  18. Validation of EO-1 Hyperion and Advanced Land Imager Using the Radiometric Calibration Test Site at Railroad Valley, Nevada

    NASA Technical Reports Server (NTRS)

    Czapla-Myers, Jeffrey; Ong, Lawrence; Thome, Kurtis; McCorkel, Joel

    2015-01-01

    The Earth-Observing One (EO-1) satellite was launched in 2000. Radiometric calibration of Hyperion and the Advanced Land Imager (ALI) has been performed throughout the mission lifetime using various techniques that include ground-based vicarious calibration, pseudo-invariant calibration sites, and also the moon. The EO-1 mission is nearing its useful lifetime, and this work seeks to validate the radiometric calibration of Hyperion and ALI from 2013 until the satellite is decommissioned. Hyperion and ALI have been routinely collecting data at the automated Radiometric Calibration Test Site [RadCaTS/Railroad Valley (RRV)] since launch. In support of this study, the frequency of the acquisitions at RadCaTS has been significantly increased since 2013, which provides an opportunity to analyze the radiometric stability and accuracy during the final stages of the EO-1 mission. The analysis of Hyperion and ALI is performed using a suite of ground instrumentation that measures the atmosphere and surface throughout the day. The final product is an estimate of the top-of-atmosphere (TOA) spectral radiance, which is compared to Hyperion and ALI radiances. The results show that Hyperion agrees with the RadCaTS predictions to within 5% in the visible and near-infrared (VNIR) and to within 10% in the shortwave infrared (SWIR). The 2013-2014 ALI results show agreement to within 6% in the VNIR and 7.5% in the SWIR bands. A cross comparison between ALI and the Operational Land Imager (OLI) using RadCaTS as a transfer source shows agreement of 3%-6% during the period of 2013-2014.

  19. Generation and validation of characteristic spectra from EO1 Hyperion image data for detecting the occurrence of the invasive species, Chinese tallow

    USGS Publications Warehouse

    Ramsey, Elijah W.; Rangoonwala, A.; Nelson, G.; Ehrlich, R.; Martella, K.

    2005-01-01

    Chinese tallow (Triadica sebifera) is an invasive tree that is spreading throughout the south-eastern United States and now into the west, and in many places causing extensive change to native habitat and associated wildlife. Detecting and mapping the relative distribution of this species is important to its control and eradication. To map the relative distribution of Chinese tallow within a southwestern Louisiana coastal wetland to upland environment, Earth Observing 1 (EO1) satellite Hyperion sensor hyperspectral image data were combined with a subpixel extraction method that modelled characteristic spectra from the image data without requiring a priori characteristic spectra. Because of the low percentage occurrences of Chinese tallow and high spectral covariation in the environment, unique validation and verification methods were implemented, relying on simultaneous collection of field canopy reflectance spectra and subsequent classification of canopy compositions. The subpixel extraction method produced five characteristic spectra, which we further refined to four that adequately represented the field spectra, as well as the Hyperion imaged canopy reflectance datasets. Characteristic spectra were designated as senescing foliage, cypress-tupelo trees, and trees without leaves; shadows and green vegetation; senescing Chinese tallow with yellow leaves and yellowing foliage; and senescing Chinese tallow with red leaves ('red tallow'). About 81% (n=34) of the field and 78% (n=33) of the Hyperion imaged characteristic spectra associated with 'red tallow' were explained by the compositions generated in the field slide classifications. ?? 2005 US Government.

  20. The EO-1 hyperion and advanced land imager sensors for use in tundra classification studies within the Upper Kuparuk River Basin, Alaska

    NASA Astrophysics Data System (ADS)

    Hall-Brown, Mary

    The heterogeneity of Arctic vegetation can make land cover classification vey difficult when using medium to small resolution imagery (Schneider et al., 2009; Muller et al., 1999). Using high radiometric and spatial resolution imagery, such as the SPOT 5 and IKONOS satellites, have helped arctic land cover classification accuracies rise into the 80 and 90 percentiles (Allard, 2003; Stine et al., 2010; Muller et al., 1999). However, those increases usually come at a high price. High resolution imagery is very expensive and can often add tens of thousands of dollars onto the cost of the research. The EO-1 satellite launched in 2002 carries two sensors that have high specral and/or high spatial resolutions and can be an acceptable compromise between the resolution versus cost issues. The Hyperion is a hyperspectral sensor with the capability of collecting 242 spectral bands of information. The Advanced Land Imager (ALI) is an advanced multispectral sensor whose spatial resolution can be sharpened to 10 meters. This dissertation compares the accuracies of arctic land cover classifications produced by the Hyperion and ALI sensors to the classification accuracies produced by the Systeme Pour l' Observation de le Terre (SPOT), the Landsat Thematic Mapper (TM) and the Landsat Enhanced Thematic Mapper Plus (ETM+) sensors. Hyperion and ALI images from August 2004 were collected over the Upper Kuparuk River Basin, Alaska. Image processing included the stepwise discriminant analysis of pixels that were positively classified from coinciding ground control points, geometric and radiometric correction, and principle component analysis. Finally, stratified random sampling was used to perform accuracy assessments on satellite derived land cover classifications. Accuracy was estimated from an error matrix (confusion matrix) that provided the overall, producer's and user's accuracies. This research found that while the Hyperion sensor produced classfication accuracies that were

  1. Fusion of Hyperspectral Hyperion and Multispectral Landsat Time Series Imagery to Improve Results and Capabilities

    NASA Astrophysics Data System (ADS)

    Franks, S.; Neigh, C. S. R.; Campell, P. K.; Sun, G.; Zhang, Q.; Middleton, E.

    2015-12-01

    Since the opening of the USGS archive to no cost Landsat data distribution, time series analysis has grown immensely. With this new era of possibilities, people are able to do science in ways that were never able to be done. The aim of this project is to explore how EO-1 Hyperion data can add value to an already valuable resource. We used a region of interest that had Landsat time series data and coincident Hyperion data to determine how Landsat classifications can be improved by using hyperspectral data with much greater spectral resolution. We hope to find innovative ways to fuse the data sources and come up with new and improved ways to study our changing Earth. With the HyspIRI (Hyperspectral Infrared Imager) satellite being launched shortly, this provides an opportunity to evaluate potential benefits that it may provide when in conjunction with other technologies and missions.

  2. Comparison of Very Near Infrared (vnir) Wavelength from EO-1 Hyperion and Worldview 2 Images for Saltmarsh Classification

    NASA Astrophysics Data System (ADS)

    Rasel, Sikdar M. M.; Chang, Hsing-Chung; Jahan Diti, Israt; Ralph, Tim; Saintilan, Neil

    2016-06-01

    Saltmarsh is one of the important communities of wetlands. Due to a range of pressures, it has been declared as an EEC (Ecological Endangered Community) in Australia. In order to correctly identify different saltmarsh species, development of distinct spectral characteristics is essential to monitor this EEC. This research was conducted to classify saltmarsh species based on spectral characteristics in the VNIR wavelength of Hyperion Hyperspectral and Worldview 2 multispectral remote sensing data. Signal Noise Ratio (SNR) and Principal Component Analysis (PCA) were applied in Hyperion data to test data quality and to reduce data dimensionality respectively. FLAASH atmospheric correction was done to get surface reflectance data. Based on spectral and spatial information a supervised classification followed by Mapping Accuracy (%) was used to assess the classification result. SNR of Hyperion data was varied according to season and wavelength and it was higher for all land cover in VNIR wavelength. There was a significant difference between radiance and reflectance spectra. It was found that atmospheric correction improves the spectral information. Based on the PCA of 56 VNIR band of Hyperion, it was possible to segregate 16 bands that contain 99.83 % variability. Based on reference 16 bands were compared with 8 bands of Worldview 2 for classification accuracy. Overall Accuracy (OA) % for Worldview 2 was increased from 72 to 79 while for Hyperion, it was increased from 70.47 to 71.66 when bands were added orderly. Considering the significance test with z values and kappa statistics at 95% confidence level, Worldview 2 classification accuracy was higher than Hyperion data.

  3. Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index.

    PubMed

    Pu, Ruiliang; Gong, Peng; Yu, Qian

    2008-06-06

    In this study, a comparative analysis of capabilities of three sensors for mapping forest crown closure (CC) and leaf area index (LAI) was conducted. The three sensors are Hyperspectral Imager (Hyperion) and Advanced Land Imager (ALI) onboard EO-1 satellite and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). A total of 38 mixed coniferous forest CC and 38 LAI measurements were collected at Blodgett Forest Research Station, University of California at Berkeley, USA. The analysis method consists of (1) extracting spectral vegetation indices (VIs), spectral texture information and maximum noise fractions (MNFs), (2) establishing multivariate prediction models, (3) predicting and mapping pixel-based CC and LAI values, and (4) validating the mapped CC and LAI results with field validated photo-interpreted CC and LAI values. The experimental results indicate that the Hyperion data are the most effective for mapping forest CC and LAI (CC mapped accuracy (MA) = 76.0%, LAI MA = 74.7%), followed by ALI data (CC MA = 74.5%, LAI MA = 70.7%), with ETM+ data results being least effective (CC MA = 71.1%, LAI MA = 63.4%). This analysis demonstrates that the Hyperion sensor outperforms the other two sensors: ALI and ETM+. This is because of its high spectral resolution with rich subtle spectral information, of its short-wave infrared data for constructing optimal VIs that are slightly affected by the atmosphere, and of its more available MNFs than the other two sensors to be selected for establishing prediction models. Compared to ETM+ data, ALI data are better for mapping forest CC and LAI due to ALI data with more bands and higher signal-to-noise ratios than those of ETM+ data.

  4. Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index

    PubMed Central

    Pu, Ruiliang; Gong, Peng; Yu, Qian

    2008-01-01

    In this study, a comparative analysis of capabilities of three sensors for mapping forest crown closure (CC) and leaf area index (LAI) was conducted. The three sensors are Hyperspectral Imager (Hyperion) and Advanced Land Imager (ALI) onboard EO-1 satellite and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). A total of 38 mixed coniferous forest CC and 38 LAI measurements were collected at Blodgett Forest Research Station, University of California at Berkeley, USA. The analysis method consists of (1) extracting spectral vegetation indices (VIs), spectral texture information and maximum noise fractions (MNFs), (2) establishing multivariate prediction models, (3) predicting and mapping pixel-based CC and LAI values, and (4) validating the mapped CC and LAI results with field validated photo-interpreted CC and LAI values. The experimental results indicate that the Hyperion data are the most effective for mapping forest CC and LAI (CC mapped accuracy (MA) = 76.0%, LAI MA = 74.7%), followed by ALI data (CC MA = 74.5%, LAI MA = 70.7%), with ETM+ data results being least effective (CC MA = 71.1%, LAI MA = 63.4%). This analysis demonstrates that the Hyperion sensor outperforms the other two sensors: ALI and ETM+. This is because of its high spectral resolution with rich subtle spectral information, of its short-wave infrared data for constructing optimal VIs that are slightly affected by the atmosphere, and of its more available MNFs than the other two sensors to be selected for establishing prediction models. Compared to ETM+ data, ALI data are better for mapping forest CC and LAI due to ALI data with more bands and higher signal-to-noise ratios than those of ETM+ data. PMID:27879906

  5. Quantifying Libya-4 Surface Reflectance Heterogeneity With WorldView-1, 2 and EO-1 Hyperion

    NASA Technical Reports Server (NTRS)

    Neigh, Christopher S. R.; McCorkel, Joel; Middleton, Elizabeth M.

    2015-01-01

    The land surface imaging (LSI) virtual constellation approach promotes the concept of increasing Earth observations from multiple but disparate satellites. We evaluated this through spectral and spatial domains, by comparing surface reflectance from 30-m Hyperion and 2-m resolution WorldView-2 (WV-2) data in the Libya-4 pseudoinvariant calibration site. We convolved and resampled Hyperion to WV-2 bands using both cubic convolution and nearest neighbor (NN) interpolation. Additionally, WV-2 and WV-1 same-date imagery were processed as a cross-track stereo pair to generate a digital terrain model to evaluate the effects from large (>70 m) linear dunes. Agreement was moderate to low on dune peaks between WV-2 and Hyperion (R2 <; 0.4) but higher in areas of lower elevation and slope (R2 > 0.6). Our results provide a satellite sensor intercomparison protocol for an LSI virtual constellation at high spatial resolution, which should start with geolocation of pixels, followed by NN interpolation to avoid tall dunes that enhance surface reflectance differences across this internationally utilized site.

  6. Quantifying Libya-4 Surface Reflectance Heterogeneity With WorldView-1, 2 and EO-1 Hyperion

    NASA Technical Reports Server (NTRS)

    Neigh, Christopher S. R.; McCorkel, Joel; Middleton, Elizabeth M.

    2015-01-01

    The land surface imaging (LSI) virtual constellation approach promotes the concept of increasing Earth observations from multiple but disparate satellites. We evaluated this through spectral and spatial domains, by comparing surface reflectance from 30-m Hyperion and 2-m resolution WorldView-2 (WV-2) data in the Libya-4 pseudoinvariant calibration site. We convolved and resampled Hyperion to WV-2 bands using both cubic convolution and nearest neighbor (NN) interpolation. Additionally, WV-2 and WV-1 same-date imagery were processed as a cross-track stereo pair to generate a digital terrain model to evaluate the effects from large (>70 m) linear dunes. Agreement was moderate to low on dune peaks between WV-2 and Hyperion (R2 <; 0.4) but higher in areas of lower elevation and slope (R2 > 0.6). Our results provide a satellite sensor intercomparison protocol for an LSI virtual constellation at high spatial resolution, which should start with geolocation of pixels, followed by NN interpolation to avoid tall dunes that enhance surface reflectance differences across this internationally utilized site.

  7. Low-Cost Evaluation of EO-1 Hyperion and ALI for Detection and Biophysical Characterization of Forest Logging in Amazonia (NCC5-481)

    NASA Technical Reports Server (NTRS)

    Asner, Gregory P.; Keller, Michael M.; Silva, Jose Natalino; Zweede, Johan C.; Pereira, Rodrigo, Jr.

    2002-01-01

    quantify both the presence and degree of structural disturbance caused by various logging regimes. Our quantitative assessment of Hyperion hyperspectral and ALI multi-spectral data for the detection and structural characterization of selective logging in Amazonia will benefit from data collected through an ongoing project run by the Tropical Forest Foundation, within which we have developed a study of the canopy and landscape biophysics of conventional and reduced-impact logging. We will add to our base of forest structural information in concert with an EO-1 overpass. Using a photon transport model inversion technique that accounts for non-linear mixing of the four biogeophysical indicators, we will estimate these parameters across a gradient of selective logging intensity provided by conventional and reduced impact logging sites. We will also compare our physical ly-based approach to both conventional (e.g., NDVI) and novel (e.g., SWIR-channel) vegetation indices as well as to linear mixture modeling methods. We will cross-compare these approaches using Hyperion and ALI imagers to determine the strengths and limitations of these two sensors for applications of forest biophysics. This effort will yield the first physical ly-based, quantitative analysis of the detection and intensity of selective logging in Amazonia, comparing hyperspectral and improved multi-spectral approaches as well as inverse modeling, linear mixture modeling, and vegetation index techniques.

  8. EO-1 Hyperion Reflectance Time Series at Calibration and Validation Sites: Stability and Sensitivity to Seasonal Dynamics

    NASA Technical Reports Server (NTRS)

    Campbell, Petya K. Entcheva; Middleton, Elizabeth M.; Thome, Kurt J.; Kokaly, Raymond F.; Huemmrich, Karl Fred; Lagomasino, David; Novick, Kimberly A.; Brunsell, Nathaniel A.

    2013-01-01

    This study evaluated Earth Observing 1 (EO-1) Hyperion reflectance time series at established calibration sites to assess the instrument stability and suitability for monitoring vegetation functional parameters. Our analysis using three pseudo-invariant calibration sites in North America indicated that the reflectance time series are devoid of apparent spectral trends and their stability consistently is within 2.5-5 percent throughout most of the spectral range spanning the 12-plus year data record. Using three vegetated sites instrumented with eddy covariance towers, the Hyperion reflectance time series were evaluated for their ability to determine important variables of ecosystem function. A number of narrowband and derivative vegetation indices (VI) closely described the seasonal profiles in vegetation function and ecosystem carbon exchange (e.g., net and gross ecosystem productivity) in three very different ecosystems, including a hardwood forest and tallgrass prairie in North America, and a Miombo woodland in Africa. Our results demonstrate the potential for scaling the carbon flux tower measurements to local and regional landscape levels. The VIs with stronger relationships to the CO2 parameters were derived using continuous reflectance spectra and included wavelengths associated with chlorophyll content and/or chlorophyll fluorescence. Since these indices cannot be calculated from broadband multispectral instrument data, the opportunity to exploit these spectrometer-based VIs in the future will depend on the launch of satellites such as EnMAP and HyspIRI. This study highlights the practical utility of space-borne spectrometers for characterization of the spectral stability and uniformity of the calibration sites in support of sensor cross-comparisons, and demonstrates the potential of narrowband VIs to track and spatially extend ecosystem functional status as well as carbon processes measured at flux towers.

  9. EO-1 Hyperion reflectance time series at calibration and validation sites: stability and sensitivity to seasonal dynamics

    USGS Publications Warehouse

    Campbell, P.K.E.; Middleton, E.M.; Thome, K.J.; Kokaly, Raymond F.; Huemmrich, K.F.; Novick, K.A.; Brunsell, N.A.

    2013-01-01

    This study evaluated Earth Observing 1 (EO-1) Hyperion reflectance time series at established calibration sites to assess the instrument stability and suitability for monitoring vegetation functional parameters. Our analysis using three pseudo-invariant calibration sites in North America indicated that the reflectance time series are devoid of apparent spectral trends and their stability consistently is within 2.5-5 percent throughout most of the spectral range spanning the 12+ year data record. Using three vegetated sites instrumented with eddy covariance towers, the Hyperion reflectance time series were evaluated for their ability to determine important variables of ecosystem function. A number of narrowband and derivative vegetation indices (VI) closely described the seasonal profiles in vegetation function and ecosystem carbon exchange (e.g., net and gross ecosystem productivity) in three very different ecosystems, including a hardwood forest and tallgrass prairie in North America, and a Miombo woodland in Africa. Our results demonstrate the potential for scaling the carbon flux tower measurements to local and regional landscape levels. The VIs with stronger relationships to the CO2 parameters were derived using continuous reflectance spectra and included wavelengths associated with chlorophyll content and/or chlorophyll fluorescence. Since these indices cannot be calculated from broadband multispectral instrument data, the opportunity to exploit these spectrometer-based VIs in the future will depend on the launch of satellites such as EnMAP and HyspIRI. This study highlights the practical utility of space-borne spectrometers for characterization of the spectral stability and uniformity of the calibration sites in support of sensor cross-comparisons, and demonstrates the potential of narrowband VIs to track and spatially extend ecosystem functional status as well as carbon processes measured at flux towers.

  10. Monitoring Orbital Precession of EO-1 Hyperion With Three Atmospheric Correction Models in the Libya-4 PICS

    NASA Technical Reports Server (NTRS)

    Neigh, Christopher S. R.; McCorkel, Joel; Campbell, Petya K. E.; Ong, Lawrence; Ly, Vuong; Landis, David; Middleton, Elizabeth M.

    2016-01-01

    Spaceborne spectrometers require spectral-temporal stability characterization to aid in validation of derived data products. Earth Observation 1 (EO-1) began orbital precession in 2011 after exhausting onboard fuel resources. In the Libya-4 pseudo-invariant calibration site (PICS), this resulted in a progressive shift from a mean local equatorial crossing time of approximately10:00 A.M. in 2011 to approximately 8:30 A.M. in late 2015. Here, we studied precession impacts to Hyperion surface reflectance products using three atmospheric correction approaches from 2004 to 2015. Combined difference estimates of surface reflectance were less than 5 percent in the visible near infrared (VNIR) and less than 10 percent for most of the shortwave infrared (SWIR). Combined coefficient of variation estimates in the VNIR ranged from 0.025 to 0.095, and in the SWIR it ranged from 0.025 to 0.06, excluding bands near atmospheric absorption features. Reflectances produced with different atmospheric models were correlated (R squared) in VNIR from 0.25 to 0.94 and in SWIR from 0.12 to 0.88 (p value (calculated probability) less than 0.01). The uncertainties in all the models increased with a terrain slope up to 15 degrees and selecting dune flats could reduce errors. We conclude that these data remain a valuable resource over this period for sensor intercalibration despite orbital decay.

  11. Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data

    USGS Publications Warehouse

    Henry, P.; Chander, G.; Fougnie, B.; Thomas, C.; Xiong, Xiaoxiong

    2013-01-01

    Since the beginning of the 1990s, stable desert sites have been used for the calibration monitoring of many different sensors. Many attempts at sensor intercalibration have been also conducted using these stable desert sites. As a result, site characterization techniques and the quality of intercalibration techniques have gradually improved over the years. More recently, the Committee on Earth Observation Satellites has recommended a list of reference pseudo-invariant calibration sites for frequent image acquisition by multiple agencies. In general, intercalibration should use well-known or spectrally flat reference. The reflectance profile of desert sites, however, might not be flat or well characterized (from a fine spectral point of view). The aim of this paper is to assess the expected accuracy that can be reached when using desert sites for intercalibration. In order to have a well-mastered estimation of different errors or error sources, this study is performed with simulated data from a hyperspectral sensor. Earth Observing-1 Hyperion images are chosen to provide the simulation input data. Two different cases of intercalibration are considered, namely, Landsat 7 Enhanced Thematic Mapper Plus with Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Environmental Satellite MEdium Resolution Imaging Spectrometer (MERIS) with Aqua MODIS. The simulation results have confirmed that intercalibration accuracy of 1% to 2% can be achieved between sensors, provided there are a sufficient number of available measurements. The simulated intercalibrations allow explaining results obtained during real intercalibration exercises and to establish some recommendations for the use of desert sites for intercalibration.

  12. Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

    NASA Technical Reports Server (NTRS)

    Blonksi, Slawomir; Gasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

    2001-01-01

    Multispectral data requirements for Earth science applications are not always studied rigorously studied before a new remote sensing system is designed. A study of the spatial resolution, spectral bandpasses, and radiometric sensitivity requirements of real-world applications would focus the design onto providing maximum benefits to the end-user community. To support systematic studies of multispectral data requirements, the Applications Research Toolbox (ART) has been developed at NASA's Stennis Space Center. The ART software allows users to create and assess simulated datasets while varying a wide range of system parameters. The simulations are based on data acquired by existing multispectral and hyperspectral instruments. The produced datasets can be further evaluated for specific end-user applications. Spectral synthesis of multispectral images from hyperspectral data is a key part of the ART software. In this process, hyperspectral image cubes are transformed into multispectral imagery without changes in spatial sampling and resolution. The transformation algorithm takes into account spectral responses of both the synthesized, broad, multispectral bands and the utilized, narrow, hyperspectral bands. To validate the spectral synthesis algorithm, simulated multispectral images are compared with images collected near-coincidentally by the Landsat 7 ETM+ and the EO-1 ALI instruments. Hyperspectral images acquired with the airborne AVIRIS instrument and with the Hyperion instrument onboard the EO-1 satellite were used as input data to the presented simulations.

  13. Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

    NASA Technical Reports Server (NTRS)

    Blonksi, Slawomir; Gasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

    2001-01-01

    Multispectral data requirements for Earth science applications are not always studied rigorously studied before a new remote sensing system is designed. A study of the spatial resolution, spectral bandpasses, and radiometric sensitivity requirements of real-world applications would focus the design onto providing maximum benefits to the end-user community. To support systematic studies of multispectral data requirements, the Applications Research Toolbox (ART) has been developed at NASA's Stennis Space Center. The ART software allows users to create and assess simulated datasets while varying a wide range of system parameters. The simulations are based on data acquired by existing multispectral and hyperspectral instruments. The produced datasets can be further evaluated for specific end-user applications. Spectral synthesis of multispectral images from hyperspectral data is a key part of the ART software. In this process, hyperspectral image cubes are transformed into multispectral imagery without changes in spatial sampling and resolution. The transformation algorithm takes into account spectral responses of both the synthesized, broad, multispectral bands and the utilized, narrow, hyperspectral bands. To validate the spectral synthesis algorithm, simulated multispectral images are compared with images collected near-coincidentally by the Landsat 7 ETM+ and the EO-1 ALI instruments. Hyperspectral images acquired with the airborne AVIRIS instrument and with the Hyperion instrument onboard the EO-1 satellite were used as input data to the presented simulations.

  14. Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

    NASA Technical Reports Server (NTRS)

    Blonski, Slawomir; Glasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

    2003-01-01

    Spectral band synthesis is a key step in the process of creating a simulated multispectral image from hyperspectral data. In this step, narrow hyperspectral bands are combined into broader multispectral bands. Such an approach has been used quite often, but to the best of our knowledge accuracy of the band synthesis simulations has not been evaluated thus far. Therefore, the main goal of this paper is to provide validation of the spectral band synthesis algorithm used in the ART software. The next section contains a description of the algorithm and an example of its application. Using spectral responses of AVIRIS, Hyperion, ALI, and ETM+, the following section shows how the synthesized spectral bands compare with actual bands, and it presents an evaluation of the simulation accuracy based on results of MODTRAN modeling. In the final sections of the paper, simulated images are compared with data acquired by actual satellite sensors. First, a Landsat 7 ETM+ image is simulated using an AVIRIS hyperspectral data cube. Then, two datasets collected with the Hyperion instrument from the EO-1 satellite are used to simulate multispectral images from the ALI and ETM+ sensors.

  15. Hyperspectral band selection and classification of Hyperion image of Bhitarkanika mangrove ecosystem, eastern India

    NASA Astrophysics Data System (ADS)

    Ashokkumar, L.; Shanmugam, S.

    2014-10-01

    Tropical mangrove forests along the coast evolve dynamically due to constant changes in the natural ecosystem and ecological cycle. Remote sensing has paved the way for periodic monitoring and conservation of such floristic resources, compared to labour intensive in-situ observations. With the laboratory quality image spectra obtained from hyperspectral image data, species level discrimination in habitats and ecosystems is attainable. One of the essential steps before classification of hyperspectral image data is band selection. It is important to eliminate the redundant bands to mitigate the problems of Hughes effect that are likely to affect further image analysis and classification accuracy. This paper presents a methodology for the selection of appropriate hyperspectral bands from the EO-1 Hyperion image for the identification and mapping of mangrove species and coastal landcover types in the Bhitarkanika coastal forest region, eastern India. Band selection procedure follows class based elimination procedure and the separability of the classes are tested in the band selection process. Individual bands are de-correlated and redundant bands are removed from the bandwise correlation matrix. The percent contribution of class variance in each band is analysed from the factors of PCA component ranking. Spectral bands are selected from the wavelength groups and statistically tested. Further, the band selection procedure is compared with similar techniques (Band Index and Mutual information) for validation. The number of bands in the Hyperion image was reduced from 196 to 88 by the Factor-based ranking approach. Classification was performed by Support Vector Machine approach. It is observed that the proposed Factor-based ranking approach performed well in discriminating the mangrove species and other landcover units compared to the other statistical approaches. The predominant mangrove species Heritiera fomes, Excoecaria agallocha and Cynometra ramiflora are spectral

  16. EO-1 analysis applicable to coastal characterization

    NASA Astrophysics Data System (ADS)

    Burke, Hsiao-hua K.; Misra, Bijoy; Hsu, Su May; Griffin, Michael K.; Upham, Carolyn; Farrar, Kris

    2003-09-01

    The EO-1 satellite is part of NASA's New Millennium Program (NMP). It consists of three imaging sensors: the multi-spectral Advanced Land Imager (ALI), Hyperion and Atmospheric Corrector. Hyperion provides a high-resolution hyperspectral imager capable of resolving 220 spectral bands (from 0.4 to 2.5 micron) with a 30 m resolution. The instrument images a 7.5 km by 100 km land area per image. Hyperion is currently the only space-borne HSI data source since the launch of EO-1 in late 2000. The discussion begins with the unique capability of hyperspectral sensing to coastal characterization: (1) most ocean feature algorithms are semi-empirical retrievals and HSI has all spectral bands to provide legacy with previous sensors and to explore new information, (2) coastal features are more complex than those of deep ocean that coupled effects are best resolved with HSI, and (3) with contiguous spectral coverage, atmospheric compensation can be done with more accuracy and confidence, especially since atmospheric aerosol effects are the most pronounced in the visible region where coastal feature lie. EO-1 data from Chesapeake Bay from 19 February 2002 are analyzed. In this presentation, it is first illustrated that hyperspectral data inherently provide more information for feature extraction than multispectral data despite Hyperion has lower SNR than ALI. Chlorophyll retrievals are also shown. The results compare favorably with data from other sources. The analysis illustrates the potential value of Hyperion (and HSI in general) data to coastal characterization. Future measurement requirements (air borne and space borne) are also discussed.

  17. Detecting vegetation stress in coastal Gabes oases using Hyperion hyperspectral sensor

    NASA Astrophysics Data System (ADS)

    Ben Arfa, Jouda; Beltrando, Gerard; Berges, Jean Claude; Zargouni, Fouad

    2016-04-01

    In the last decades, the environmental changes due to the human activities are the main causes of disturbance of oasian agro-systems. Gabes region, in the southeastern of Tunisia, is characterized by unique maritime oases in Mediterranean basin. Unfortunately these oases are sensitive areas due to a harsh competition for land and water between different user groups (urban, industry, agriculture). An industrial complex is now located in center of this region, cultivation practices have shifted from a traditional multi-layer plant association system and moreover the Gabes city itself is expanding in the very core of oases. The oases of Gabes are transformed into city oases; they undergo multiform interactions whose amplify their environmental dynamic. A proper management of this environment should be based on a fine cartography of land use change and remote sensing plays a major role in this issue. Although Landsat long time series archive is a valuable tool it gets some limitations due to TM sensor spectral definition. Both sparse vegetation cover area and crop stress and disease are difficult to assess. Our study deals on potential improvement of hyperspectral sensor to overcome these limitations. EO1/Hyperion data on seven different dates on 2009 and 2010 have been retrieved from NASA Web-site. From this dataset dataset, an intercomparison of various hyperspectral based indices has been carried out with a focus on information complimentary from normalized vegetation index. On this basis the most efficient indices are the anthocyanin reflectance index (ARI2), the disease water stress index (DWSI) and the photochemical reflectance index (PRI). They allow an analysis of vegetation status beyond a global greenness assessment.

  18. Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll (fAPAR(sub chl)) and Leaf Water Content (LWC)

    NASA Technical Reports Server (NTRS)

    Zhang, Qingyuan; Middleton, Elizabeth M.; Gao, Bo-Cai; Cheng, Yen-Ben

    2011-01-01

    This study presents development of prototype products for terrestrial ecosystems in preparation for the future imaging spectrometer planned for the Hyperspectral Infrared Imager (HyspIRI) mission. We present a successful demonstration example in a coniferous forest of two product prototypes: fraction of photosynthetic active radiation (PAR) absorbed by chlorophyll of a canopy (fAPAR(sub chl)) and leaf water content (LWC), for future HyspIRI implementation at 60 m spatial resolution. For this, we used existing 30 m resolution imaging spectrometer data available from the Earth Observing One (EO-1) Hyperion satellite to simulate and prototype the level one radiometrically corrected radiance (L1R) images expected from the HyspIRI visible through shortwave infrared spectrometer. The HyspIRI-like images were atmospherically corrected to obtain surface reflectance, and spectrally resampled to produce 60 m reflectance images for wavelength regions that were comparable to all seven of the MODerate resolution Imaging Spectroradiometer (MODIS) land bands. Thus, we developed MODIS-like surface reflectance in seven spectral bands at the HyspIRI-like spatial scale, which was utilized to derive fAPARchl and LWC with a coupled canopy-leaf radiative transfer model (PROSAIL2) for the coniferous forest[1]. With this study, we provide additional evidence that the fAPARchl product is more realistic for describing the physiologically active canopy than the traditional fAPAR parameter for the whole canopy (fAPAR(sub canopy)), and thus should replace it in ecosystem process models to reduce uncertainties in terrestrial carbon cycle studies and ecosystem studies.

  19. Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll (fAPAR(sub chl)) and Leaf Water Content(LWC)

    NASA Technical Reports Server (NTRS)

    Zhang, Qingyuan; Middleton, Elizabeth M.; Gao, Bo-Cai; Cheng, Yen-Ben

    2012-01-01

    This paper presents development of prototype products for terrestrial ecosystems in preparation for the future imaging spectrometer planned for the Hyperspectral Infrared Imager (HyspIRI) mission. We present a successful demonstration example in a coniferous forest of two product prototypes: fraction of photosynthetically active radiation (PAR) absorbed by chlorophyll of a canopy (fAPARchl) and leaf water content (LWC), for future HyspIRI implementation at 60-m spatial resolution. For this, we used existing 30-m resolution imaging spectrometer data available from the Earth Observing One (EO-1) Hyperion satellite to simulate and prototype the level one radiometrically corrected radiance (L1R) images expected from the HyspIRI visible through shortwave infrared spectrometer. The HyspIRIlike images were atmospherically corrected to obtain surface reflectance and spectrally resampled to produce 60-m reflectance images for wavelength regions that were comparable to all seven of the MODerate resolution Imaging Spectroradiometer (MODIS) land bands. Thus, we developed MODIS-like surface reflectance in seven spectral bands at the HyspIRI-like spatial scale, which was utilized to derive fAPARchl and LWC with a coupled canopy-leaf radiative transfer model (PROSAIL2) for the coniferous forest. With this paper, we provide additional evidence that the fAPARchl product is more realistic in describing the physiologically active canopy than the traditional fAPAR parameter for the whole canopy (fAPARcanopy), and thus, it should replace it in ecosystem process models to reduce uncertainties in terrestrial carbon cycle and ecosystem studies.

  20. A protocol for improving mapping and assessing of seagrass abundance along the West Central Coast of Florida using Landsat TM and EO-1 ALI/Hyperion images

    NASA Astrophysics Data System (ADS)

    Pu, Ruiliang; Bell, Susan

    2013-09-01

    Seagrass habitats are characteristic features of shallow waters worldwide and provide a variety of ecosystem functions. Remote sensing techniques can help collect spatial and temporal information about seagrass resources. In this study, we evaluate a protocol that utilizes image optimization algorithms followed by atmospheric and sunglint corrections to the three satellite sensors [Landsat 5 Thematic Mapper (TM), Earth Observing-1 (EO-1) Advanced Land Imager (ALI) and Hyperion (HYP)] and a fuzzy synthetic evaluation technique to map and assess seagrass abundance in Pinellas County, FL, USA. After image preprocessed with image optimization algorithms and atmospheric and sunglint correction approaches, the three sensors' data were used to classify the submerged aquatic vegetation cover (%SAV cover) into 5 classes with a maximum likelihood classifier. Based on three biological metrics [%SAV, leaf area index (LAI), and Biomass] measured from the field, nine multiple regression models were developed for estimating the three biometrics with spectral variables derived from the three sensors' data. Then, five membership maps were created with the three biometrics along with two environmental factors (water depth and distance-to-shoreline). Finally, seagrass abundance maps were produced by using a fuzzy synthetic evaluation technique and five membership maps. The experimental results indicate that the HYP sensor produced the best results of the 5-class classification of %SAV cover (overall accuracy = 87% and Kappa = 0.83 vs. 82% and 0.77 by ALI and 79% and 0.73 by TM) and better multiple regression models for estimating the three biometrics (R2 = 0.66, 0.62 and 0.61 for %SAV, LAI and Biomass vs. 0.62, 0.61 and 0.55 by ALI and 0.58, 0.56 and 0.52 by TM) for creating seagrass abundance maps along with two environmental factors. Combined our results demonstrate that the image optimization algorithms and the fuzzy synthetic evaluation technique were effective in mapping

  1. An ensemble training scheme for machine-learning classification of Hyperion satellite imagery with independent hyperspectral libraries

    NASA Astrophysics Data System (ADS)

    Friedel, Michael; Buscema, Massimo

    2016-04-01

    A training scheme is proposed for the real-time classification of soil and vegetation (landscape) components in EO-1 Hyperion hyperspectral images. First, an auto-contractive map is used to compute connectivity of reflectance values for spectral bands (N=200) from independent laboratory spectral library components. Second, a minimum spanning tree is used to identify optimal grouping of training components from connectivity values. Third, the reflectance values for optimal landscape component signatures are sorted. Fourth, empirical distribution functions (EDF) are computed for each landscape component. Fifth, the Monte-Carlo technique is used to generate realizations (N=30) for each landscape EDF. The correspondence of component realizations to original signatures validates the stochastic procedure. Presentation of the realizations to the self-organizing map (SOM) is done using three different map sizes: 14x10, 28x20, and 40 x 30. In each case, the SOM training proceeds first with a rough phase (20 iterations using a Gaussian neighborhood with an initial and final radius of 11 units and 3 units) and then fine phase (400 iterations using a Gaussian neighborhood with an initial and final radius of 3 units and 1 unit). The initial and final learning rates of 0.5 and 0.05 decay linearly down to 10-5, and the Gaussian neighborhood function decreases exponentially (decay rate of 10-3 iteration-1) providing reasonable convergence. Following training of the three networks, each corresponding SOM is used to independently classify the original spectral library signatures. In comparing the different SOM networks, the 28x20 map size is chosen for independent reproducibility and processing speed. The corresponding universal distance matrix reveals separation of the seven component classes for this map size thereby supporting it use as a Hyperion classifier.

  2. Lava Flow Mapping and Change Detection in the Mt. Etna Volcano Between 2009-2012 Using Hyperion Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Karagiannopoulou, Catherine; Sykioti, Olga; Parcharidis, Issaak Briole, Pierre

    2016-08-01

    Mt. Etna is a young composite strato-volcano and one of the most active volcanoes in the world. Eruptions occur almost every year with a persistent degassing activity at the summit craters. In the last 100 years it has produced in average 107m3 of new lava per year. The main goal of our work is to detect land cover changes, including different lava flows, over the volcano that occurred between 2009 and 2012 using hyperspectral imagery (EO-1 Hyperion). For this purpose, we separated the volcano into three main land cover types: dense vegetation, urban and semi-urban areas and bare lava areas. For each area, a change detection map was produced. For the bare lava areas, two classification maps were produced based on (i) reflectance differences and (ii) chronology as proposed in bibliography. Results have shown changes in all three land cover types. In particular, for the bare lava areas, the most significant lava changes are observed in the northern and central part of the volcano, where several lava flows occurred during the 3-year study period.

  3. Mapping impervious surface type and sub-pixel abundance using hyperion hyperspectral imagery

    USGS Publications Warehouse

    Falcone, J.A.; Gomez, R.

    2005-01-01

    Impervious surfaces have been identified as an important and quantifiable indicator of environmental degradation in urban settings. A number of research efforts have been directed at mapping impervious surface type using multispectral imagery. To date, however, no studies have compared equivalent techniques using multispectral and hyperspectral imagery to that end. In this study, data from NASA's 220-channel Hyperion instrument were used to: a) delineate three types of impervious surface, and b) map sub-pixel percent abundance for a study site near Washington, D.C., USA. The results were compared with the results of similar methods using same-spatial-resolution Landsat ETM+ data for mapping impervious surface type, and with the results of the U.S. Geological Survey's National Land Cover Data (NLCD) 2001 impervious surface data layer, which is derived from Landsat and high-resolution Ikonos data. The accuracy of discriminating impervious surface type using Hyperion data was assessed at 88% versus Landsat at 59%. The sub-pixel percent impervious map corresponded well with the NLCD 2001; impervious surface in the study area was calculated at 29.3% for NLCD 2001 and 28.4% for the Hyperion-derived layer. The results suggest that fairly simple techniques using hyperspectral data are effective for quantifying impervious surface type, and that high-spectral- resolution imagery may be a good alternative to high-spatial-resolution data.

  4. Resolution Enhancement of Hyperion Hyperspectral Data using Ikonos Multispectral Data

    DTIC Science & Technology

    2007-09-01

    space-based sensor can be accomplished with the Normalized Difference Vegetation Index ( NDVI ) algorithm7 that uses a normalized difference between...two bands to highlight pixels with a high likelihood of vegetation content. A simple “vegetation sharpening” procedure could use the NDVI output of...hyperspectral imagery data by adding a standard vegetation spectrum with an intensity related to the NDVI score. Such an approach would have a number of

  5. Observations of Active Volcanoes Using the EO-1 Satellite

    NASA Astrophysics Data System (ADS)

    Flynn, L. P.; Harris, A. J.; Wright, R.; Oppenheimer, C.; Geschwind, L. R.; Donegan, S.; Garbeil, H.

    2001-12-01

    Previous satellite observations of active volcanoes have been hampered by instruments that are primarily designed to measure surface reflectance of the Earth's vegetation. Sensors detecting radiation in the near-IR and IR are frequently saturated by highly radiant active volcanic features. Two satellite instruments, Hyperion and the Advanced Land Imager (ALI) on the Earth Observing -1 (EO-1) offer a means to circumvent saturation issues. Hyperion is a hyperspectral instrument that collects data in 242 narrow spectral bands between 0.4 and 2.5 microns and produces images that are 7.5 km x 100 km. For each 30m x 30m pixel, accurate atmospheric corrections and multiple component thermal models for lava flows can be generated. ALI is a Landsat-like instrument having 10 spectral bands at 0.4 - 2.35 microns. One of these, the 1.2 micron band, is sensitive to high temperature thermal anomalies such as overturning lava lakes and open lava channels. ALI also has a 10-m panchromtic band that allows for greater detailed mapping of volcanic features. ALI and Hyperion analyses for Erta Ale (Ethiopia), Mt. Etna (Sicily), Santiaguito (Guatemala), Popocatepetl (Mexico), and Mayon (Philippines) will be presented. While distribution of these data sets is limited to the EO-1 Science Team, the future of NASA's high spatial resolution terrestrial observation program will likely be based on a hybrid of these EO-1 sensors.

  6. Land Cover Change Detection Based on Genetically Feature Aelection and Image Algebra Using Hyperion Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Seydi, S. T.; Hasanlou, M.

    2015-12-01

    The Earth has always been under the influence of population growth and human activities. This process causes the changes in land use. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes. Satellite remote sensing has several advantages for monitoring land use/cover resources, especially for large geographic areas. Change detection and attribution of cultivation area over time present additional challenges for correctly analyzing remote sensing imagery. In this regards, for better identifying change in multi temporal images we use hyperspectral images. Hyperspectral images due to high spectral resolution created special placed in many of field. Nevertheless, selecting suitable and adequate features/bands from this data is crucial for any analysis and especially for the change detection algorithms. This research aims to automatically feature selection for detect land use changes are introduced. In this study, the optimal band images using hyperspectral sensor using Hyperion hyperspectral images by using genetic algorithms and Ratio bands, we select the optimal band. In addition, the results reveal the superiority of the implemented method to extract change map with overall accuracy by a margin of nearly 79% using multi temporal hyperspectral imagery.

  7. Examples of EO-1 Hyperion Data Analysis

    DTIC Science & Technology

    2007-11-02

    divided in eight regions. Regions colored in orange, light sienna, and dark sienna represent soil while five shades from yellow to dark green delineate... chlorophyll -a concentration varies over several orders of magnitude, from about 0.01 to 100 mg m-3. "* Each of the three major components of the...understood that chlorophyll -a absorbs relatively more blue and red light than green, and the spectrum of backscattered sunlight or color of ocean water

  8. Support vector machines and object-based classification for obtaining land-use/cover cartography from Hyperion hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Petropoulos, George P.; Kalaitzidis, Chariton; Prasad Vadrevu, Krishna

    2012-04-01

    The Hyperion hyperspectral sensor has the highest spectral resolution, acquiring spectral information of Earth's surface objects in 242 spectral bands at a spatial resolution of 30 m. In this study, we evaluate the performance of the Hyperion sensor in conjunction with the two different classification algorithms for delineating land use/cover in a typical Mediterranean setting. The algorithms include pixel-based support vector machines (SVMs) and the object-based classification algorithm. Validation of the derived land-use/cover maps from the above two algorithms was performed through error matrix statistics using the validation points from the very high resolution QuickBird imagery. Results suggested both classifiers as highly useful in mapping land use/cover in the study region with the object-based approach slightly outperforming the SVMs classification by overall higher classification accuracy and Kappa statistics. Results from the statistical significance testing using McNemar's chi-square test confirmed the superiority of the object-oriented approach compared to SVM. The relative strengths and weaknesses of the two classification algorithms for land-use/cover mapping studies are highlighted. Overall, our results underline the potential of hyperspectral remote sensing data together with an object-based classification approach for mapping land use/cover in the Mediterranean regions.

  9. Soil Fertility Evaluation for Fertiliser Recommendation Using Hyperion Data

    NASA Astrophysics Data System (ADS)

    Ghosh, Ranendu; Padmanabhan, N.; Patel, K. C.

    2015-12-01

    Soil fertility characterised by nitrogen, phosphorus, potassium, calcium, magnesium and sulphur is traditionally measured from soil samples collected from the field. The process is very cumbersome and time intensive. Hyperspectral data available from Hyperion payload of EO 1 was used for facilitating preparation of soil fertility map of Udaipur district of Rajasthan state, India. Hyperion data was pre-processed for band and area sub setting, atmospheric correction and reflectance data preparation. Spectral analysis in the form of SFF and PPI were carried out for selecting the ground truth sites for soil sample collection. Soil samples collected from forty one sites were analysed for analysis of nutrient composition. Generation of correlogram followed by multiple regressions was done for identifying the most important bands and spectral parameters that can be used for nutrient map generation.

  10. Generating time series of PRI across the Amazon basin using hyperspectral Hyperion data

    NASA Astrophysics Data System (ADS)

    Toh Yuan Kun, L.; Yang, X.; Silva, C. E.; Cushman, K.; Kellner, J. R.

    2016-12-01

    Models of carbon cycling in tropical forests rely on estimates of fAPAR and LUE that are based on field experiments or remote sensing. However, much uncertainty surrounds such models on a regional scale because of unresolved questions over ecosystem response to climate variability. The photochemical reflectance index (PRI) is a normalized difference index that is sensitive to short-term changes in photosynthetic activity, unlike other more commonly used indices like NDVI. This is because PRI is indicative of the epoxidation state of xanthophyll pigments involved in non-photochemical quenching. Hence, an understanding of how PRI varies spatially and temporally would be a useful benchmark against which to evaluate model output and measurements of solar-induced fluorescence (SIF). Computing PRI requires two narrow spectral bands at 531 and 570 nm, and therefore cannot be quantified using broad-band optical sensors. The Hyperion instrument has generated Earth observations since 2000 and provides a unique opportunity to quantify PRI over large spatial and temporal scales. Here we describe a quantitative framework to correct striping, spectral keystone, and spectral smile inherent in the Hyperion data record. We show how these data can be used to generate time series of PRI to facilitate deeper understanding of photosynthetic activity in the Amazon basin.

  11. Predicting Thaumastocoris peregrinus damage using narrow band normalized indices and hyperspectral indices using field spectra resampled to the Hyperion sensor

    NASA Astrophysics Data System (ADS)

    Oumar, Z.; Mutanga, O.; Ismail, R.

    2013-04-01

    Thaumastocoris peregrinus (T. peregrinus) is a sap sucking insect that feeds on Eucalyptus leaves. It poses a threat to the forest industry by reducing the photosynthetic ability of the tree, resulting in stunted growth and even death of severely infested trees. Remote sensing techniques offer the potential to detect and map T. peregrinus infestations in plantation forests using current operational hyperspectral scanners. This study resampled field spectral data measured from a field spectrometer to the band settings of the Hyperion sensor in order to assess its potential in predicting T. peregrinus damage. Normalized indices based on NDVI ratios were calculated using the resampled visible and near-infrared bands of the Hyperion sensor to assess its utility in predicting T. peregrinus damage using Partial Least Squares (PLS) regression. The top 20 normalized indices were based on specific biochemical absorption features that predicted T. peregrinus damage with a mean bootstrapped R2 value of 0.63 on an independent test dataset. The top 20 indices were located in the near-infrared region between 803.3 nm and 894.9 nm. Twenty three previously published hyperspectral indices which have been used to assess stress in vegetation were also used to predict T. peregrinus damage and resulted in a mean bootstrapped R2 value of 0.59 on an independent test dataset. The datasets were combined to assess its collective strength in predicting T. peregrinus damage and significant indices were chosen based on variable importance scores (VIP) and were then entered into a PLS model. The indices chosen by VIP predicted T. peregrinus damage with a mean bootstrapped R2 value of 0.71 on an independent test dataset. A greedy backward variable selection model was further tested on the VIP selected indices in order to find the best subset of indices with the best predictive accuracy. The greedy backward variable selection model identified 3 indices and performed the best by predicting damage

  12. Onboard Classification of Hyperspectral Data on the Earth Observing One Mission

    NASA Technical Reports Server (NTRS)

    Chien, Steve; Tran, Daniel; Schaffer, Steve; Rabideau, Gregg; Davies, Ashley Gerard; Doggett, Thomas; Greeley, Ronald; Ip, Felipe; Baker, Victor; Doubleday, Joshua; hide

    2009-01-01

    Remote-sensed hyperspectral data represents significant challenges in downlink due to its large data volumes. This paper describes a research program designed to process hyperspectral data products onboard spacecraft to (a) reduce data downlink volumes and (b) decrease latency to provide key data products (often by enabling use of lower data rate communications systems). We describe efforts to develop onboard processing to study volcanoes, floods, and cryosphere, using the Hyperion hyperspectral imager and onboard processing for the Earth Observing One (EO-1) mission as well as preliminary work targeting the Hyperspectral Infrared Imager (HyspIRI) mission.

  13. Onboard Classification of Hyperspectral Data on the Earth Observing One Mission

    NASA Technical Reports Server (NTRS)

    Chien, Steve; Tran, Daniel; Schaffer, Steve; Rabideau, Gregg; Davies, Ashley Gerard; Doggett, Thomas; Greeley, Ronald; Ip, Felipe; Baker, Victor; Doubleday, Joshua; Castano, Rebecca; Mandl, Daniel; Frye, Stuart; Ong, Lawrence; Rogez, Francois; Oaida, Bogdan

    2009-01-01

    Remote-sensed hyperspectral data represents significant challenges in downlink due to its large data volumes. This paper describes a research program designed to process hyperspectral data products onboard spacecraft to (a) reduce data downlink volumes and (b) decrease latency to provide key data products (often by enabling use of lower data rate communications systems). We describe efforts to develop onboard processing to study volcanoes, floods, and cryosphere, using the Hyperion hyperspectral imager and onboard processing for the Earth Observing One (EO-1) mission as well as preliminary work targeting the Hyperspectral Infrared Imager (HyspIRI) mission.

  14. Realtime Decision Making on EO-1 Using Onboard Science Analysis

    NASA Technical Reports Server (NTRS)

    Sherwood, Robert; Chien, Steve; Davies, Ashley; Mandl, Dan; Frye, Stu

    2004-01-01

    Recent autonomy experiments conducted on Earth Observing 1 (EO-1) using the Autonomous Sciencecraft Experiment (ASE) flight software has been used to classify key features in hyperspectral images captured by EO-1. Furthermore, analysis is performed by this software onboard EO-1 and then used to modify the operational plan without interaction from the ground. This paper will outline the overall operations concept and provide some details and examples of the onboard science processing, science analysis, and replanning.

  15. Validation of On-board Cloud Cover Assessment Using EO-1

    NASA Technical Reports Server (NTRS)

    Mandl, Dan; Miller, Jerry; Griffin, Michael; Burke, Hsiao-hua

    2003-01-01

    The purpose of this NASA Earth Science Technology Office funded effort was to flight validate an on-board cloud detection algorithm and to determine the performance that can be achieved with a Mongoose V flight computer. This validation was performed on the EO-1 satellite, which is operational, by uploading new flight code to perform the cloud detection. The algorithm was developed by MIT/Lincoln Lab and is based on the use of the Hyperion hyperspectral instrument using selected spectral bands from 0.4 to 2.5 microns. The Technology Readiness Level (TRL) of this technology at the beginning of the task was level 5 and was TRL 6 upon completion. In the final validation, an 8 second (0.75 Gbytes) Hyperion image was processed on-board and assessed for percentage cloud cover within 30 minutes. It was expected to take many hours and perhaps a day considering that the Mongoose V is only a 6-8 MIP machine in performance. To accomplish this test, the image taken had to have level 0 and level 1 processing performed on-board before the cloud algorithm was applied. For almost all of the ground test cases and all of the flight cases, the cloud assessment was within 5% of the correct value and in most cases within 1-2%.

  16. Hyperspectral Cubesat Constellation for Rapid Natural Hazard Response

    NASA Technical Reports Server (NTRS)

    Mandl, Daniel; Huemmrich, Karl; Crum, Gary; Ly, Vuong; Handy, Matthew; Ong, Lawrence

    2015-01-01

    Earth Observing 1 (E0-1) satellite has an imaging spectrometer (hyperspectral) instrument called Hyperion. The satellite is able to image any spot on Earth in the nadir looking direction every 16 days. With slewing of the satellite and allowing for up to a 23 degree view angle, any spot on the Earth can be imaged approximately every 2 to 3 days. EO-1 has been used to track many natural hazards such as wildfires, volcanoes and floods. An enhanced capability that is sought is the ability to image natural hazards in a daily time series for space based imaging spectrometers. The Hyperion can not provide this capability on EO-1 with the present polar orbit. However, a constellation of cubesats, each with the same imaging spectrometer, positioned strategically in the same orbit, can be used to provide daily coverage, cost-effectively.

  17. Unusual Hyperion

    NASA Image and Video Library

    2007-03-26

    Chaotically tumbling and seriously eroded by impacts, Hyperion is one of Saturn more unusual satellites. Scientists believe the moon to be quite porous, with a great deal of its volume being empty space

  18. Assessing wheat residue cover with hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    Tripathy, Rojalin; Manjunath, K. R.

    2016-04-01

    Hyperspectral remote sensing can aid in discriminating crop residue owing to the ability of narrow bands to capture the unique absorption feature of soil and residue. The present study was carried out to find out the suitable narrow spectral bands and hyper-spectral indices for discriminating wheat residue (stubble and burnt). Ground spectra of wheat residue and the adjoining soil were collected using the ASD fieldspec™ spectroradiometer. The best spectral range was derived using the Stepwise Discriminating Analysis (SDA). `F' statistics from one-way ANOVA was used to find out the best index for discriminating wheat residue from soil. EO1-Hyperion data over Anand-Borsad region of Gujarat state in India was acquired free of cost from USGS earth explorer website (http://eo1.usgs.gov/) to apply the field based result over the Hyperion scene. Spectral Angle Mapper (SAM) classification scheme was used to generate the wheat residue cover over the Hyperion scene. Among the hyperspectral indices evaluated for this study the Cellulose Absorption Index (CAI) was found to be the best and hence CAI was used to classify the Hyperion scene for discriminating crop residue in field and also the burnt wheat residue. Results indicated that the wave bands at 10 nm width in the SWIR spectral region specifically from 1500-1700nm and 1900 to 2300nm are most suitable for wheat residue discrimination. The SAM classification technique is suitable for classifying the wheat residues with an overall accuracy of around 80 % whereas classification based on CAI could be used successfully to identify both wheat stubble and the burnt residues. This study concluded that wheat residue can be mapped for a large area with an accuracy of 80% using the space borne hyperspectral data with.

  19. EO-1 Prototyping for Environmental Applications

    NASA Astrophysics Data System (ADS)

    Campbell, P. K.; Middleton, E.; Ungar, S.; Zhang, Q.; Ong, L.; Huemmrich, K. F.

    2009-12-01

    The Earth Observing One (EO-1) Mission, launched in November, 2000 as part of NASA’s New Millennium Program, is in it’s eight year of operation. From the start it was recognized that a key criteria for evaluating the EO-1 technology and outlining future Earth science mission needs is the ability of the technology to characterize terrestrial surface state and processes. EO-1 is participating in a broad range of investigations, demonstrating the utility of imaging spectroscopy in applications relating to forestry, agriculture, species discrimination, invasive species, desertification, land-use, vulcanization, fire management, homeland security, natural and anthropogenic hazards and disaster assessments and has provided characterization for a variety of instruments on EOS platforms. By generating a high spectral and spatial resolution data set for the corral reefs and islands, it is contributing for realizing the goals of the National Decadal survey and providing an excellent platform for testing strategies to be employed in the HyspIRI mission. The EO1 Mission Science Office (MSO) is developing tools and prototypes for new science products, addressing the HyspIRI goals to assess vegetation status and health and provide vegetation spectral bio-indicators and biophysical parameters such as LAI and fAPAR at <100 m spatial resolution. These are being used to resolve variability in heterogeneous areas (e.g. agriculture, narrow shapes, urban and developed lands) and for managed ecosystems less than 10 km2. A set of invariable reference targets (e.g. sun, moon, deserts, Antarctica) are being characterised to allow cross-calibration of current and future EO sensors, comparison of land products generated by multiple sensors and retroactive processing of time series data. Such products are needed to develop Science Requirements for the next generation of hyperspectral satellite sensors and to address global societal needs.

  20. Comparison of EO1 Landsat-7 ETM+ and EO-1 ALI images over Rochester, New York

    NASA Astrophysics Data System (ADS)

    Pedelty, Jeffrey A.; Morisette, Jeffrey T.; Smith, James A.

    2002-08-01

    We present a comparison of images from the ETM+ sensor on Landsat-7 and the ALI instrument on EO-1 over a test site in Rochester, NY. The site contains a variety of features, ranging from water of varying depths, deciduous/coniferous forest, grass fields, to urban areas. The nearly coincident cloud-free images were collected just one minute apart on 25 August, 2001. We atmospherically corrected each image with the 6S atmosphere model, using aerosol optical thickness and water vapor column density measured by a Cimel sun photometer within the Aerosol Robotic Network (Aeronet), along with ozone density derived from NCEP data. We present three-color composites from each instrument that show excellent qualitative agreement. We present ETM+ and ALI reflectance spectra for water, grass, and urban targets. We make a more detailed comparison for our forest site, where we use measured geometric and optical properties as input to the SAIL canopy reflectance model, which we compare to the ETM+, ALI, and EO-1 Hyperion reflectance spectra.

  1. Mineral mapping on the Chilean-Bolivian Altiplano using co-orbital ALI, ASTER and Hyperion imagery: Data dimensionality issues and solutions

    USGS Publications Warehouse

    Hubbard, B.E.; Crowley, J.K.

    2005-01-01

    Hyperspectral data coverage from the EO-1 Hyperion sensor was useful for calibrating Advanced Land Imager (ALI) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images of a volcanic terrane area of the Chilean-Bolivian Altiplano. Following calibration, the ALI and ASTER datasets were co-registered and joined to produce a 13-channel reflectance cube spanning the Visible to Short Wave Infrared (0.4-2.4 ??m). Eigen analysis and comparison of the Hyperion data with the ALI + ASTER reflectance data, as well as mapping results using various ALI+ASTER data subsets, provided insights into the information dimensionality of all the data. In particular, high spectral resolution, low signal-to-noise Hyperion data were only marginally better for mineral mapping than the merged 13-channel, low spectral resolution, high signal-to-noise ALI + ASTER dataset. Neither the Hyperion nor the combined ALI + ASTER datasets had sufficient information dimensionality for mapping the diverse range of surface materials exposed on the Altiplano. However, it is possible to optimize the use of the multispectral data for mineral-mapping purposes by careful data subsetting, and by employing other appropriate image-processing strategies.

  2. [An Analysis of the Spectrums between Different Canopy Structures Based on Hyperion Hyperspectral Data in a Temperate Forest of Northeast China].

    PubMed

    Yu, Quan-zhou; Wang, Shao-qiang; Huang, Kun; Zhou, Lei; Chen, Die-cong

    2015-07-01

    Canopy is a major structural layer for vegetation to carry out ecological activities. The differences of light radiative transfer processes in canopies caused by forest canopy structure directly influence remote sensing inversion of forest canopy biochemical composition. Thus an analysis of spectral characteristics between different canopy structures contributes to improve the accuracy of remote sensing inversion of forest canopy biochemical components. Based on a Hyperion hyperspectral image in the north Slope of Changbai Mountain Nature Reserve, through FLAASH (the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes) atmospheric correction, different canopy reflectance spectra were extracted, and spectral transforms were carried out using continuum removal method and first derivative method for quantitative analysis of the spectral characteristics. A set of spectral indices were calculated, including NIR (near infrared reflectance), NDVI (normalized difference vegetation index), EVI (Enhanced Vegetation Index), NDNI (normalized difference nitrogen index), SPRI (normalized photochemical reflectance index) * NDVI and SPRI * EVI (vegetation productivity index). Combined with the broad foliar dominance index (BFDI), the relationships between the spectral indices and canopy structure composition were investigated. The characteristics of canopy structure composition impacting its spectral curve and indices were clarified in the temperate forest. The results showed that: (1) there existed significantly different spectral characteristics between different canopy structures: comparing to the spectrum of broad-leaved forest canopies, the red edge moved to the left and their slope decreased, blue edge and yellow edge features were also weakened, near-infrared reflectance decreased, normalized reflectance in visible region risen for the spectrum of conifer forest canopies; (2) the spectrum variation were controlled by BFDL The correlations between BFDI and the

  3. Classification of river water pollution using Hyperion data

    NASA Astrophysics Data System (ADS)

    Kar, Soumyashree; Rathore, V. S.; Champati ray, P. K.; Sharma, Richa; Swain, S. K.

    2016-06-01

    A novel attempt is made to use hyperspectral remote sensing to identify the spatial variability of metal pollutants present in river water. It was also attempted to classify the hyperspectral image - Earth Observation-1 (EO-1) Hyperion data of an 8 km stretch of the river Yamuna, near Allahabad city in India depending on its chemical composition. For validating image analysis results, a total of 10 water samples were collected and chemically analyzed using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Two different spectral libraries from field and image data were generated for the 10 sample locations. Advanced per-pixel supervised classifications such as Spectral Angle Mapper (SAM), SAM target finder using BandMax and Support Vector Machine (SVM) were carried out along with the unsupervised clustering procedure - Iterative Self-Organizing Data Analysis Technique (ISODATA). The results were compared and assessed with respect to ground data. Analytical Spectral Devices (ASD), Inc. spectroradiometer, FieldSpec 4 was used to generate the spectra of the water samples which were compiled into a spectral library and used for Spectral Absorption Depth (SAD) analysis. The spectral depth pattern of image and field spectral libraries was found to be highly correlated (correlation coefficient, R2 = 0.99) which validated the image analysis results with respect to the ground data. Further, we carried out a multivariate regression analysis to assess the varying concentrations of metal ions present in water based on the spectral depth of the corresponding absorption feature. Spectral Absorption Depth (SAD) analysis along with metal analysis of field data revealed the order in which the metals affected the river pollution, which was in conformity with the findings of Central Pollution Control Board (CPCB). Therefore, it is concluded that hyperspectral imaging provides opportunity that can be used for satellite based remote monitoring of water quality from

  4. Hyperspectral Cubesat Constellation for Natural Hazard Response

    NASA Technical Reports Server (NTRS)

    Mandl, Daniel; Crum, Gary; Ly, Vuong; Handy, Matthew; Huemmrich, Karl F.; Ong, Lawrence; Holt, Ben; Maharaja, Rishabh

    2016-01-01

    The authors on this paper are team members of the Earth Observing 1 (E0-1) mission which has flown an imaging spectrometer (hyperspectral) instrument called Hyperion for the past 15+ years. The satellite is able to image any spot on Earth in the nadir looking direction every 16 days and with slewing, of the satellite for up to a 23 degree view angle, any spot on the Earth can be imaged approximately every 2 to 3 days. EO-1 has been used to track many natural hazards such as wildfires, volcanoes and floods. An enhanced capability that has been sought is the ability to image natural hazards in a daily time series for space-based imaging spectrometers. The Hyperion cannot provide this capability on EO-1 with the present polar orbit. However, a constellation of cubesats, each with the same imaging spectrometer, positioned strategically can be used to provide daily coverage or even diurnal coverage, cost-effectively. This paper sought to design a cubesat constellation mission that would accomplish this goal and then to articulate the key tradeoffs.

  5. Spectral Super-Resolution for Hyperspectral Images via Sparse Representations

    NASA Astrophysics Data System (ADS)

    Fotiadou, Konstantina; Tsagkatakis, Grigorios; Tsakalides, Panagiotis

    2016-08-01

    The spectral dimension of hyperspectral imaging (HSI) systems plays a fundamental role in numerous terrestrial and earth observation applications, including spectral unmixing, target detection, and classification among others. However, in several cases the spectral resolution of HSI systems is sacrificed for the shake of spatial resolution, as such in the case of snapshot spectral imaging systems that acquire simultaneously the 3D data- cube. We address these limitations by introducing an efficient post-acquisition spectral resolution enhancement scheme that synthesizes the full spectrum from only few acquired spectral bands. To achieve this goal we utilize a regularized sparse-based learning procedure where the relations between high and low-spectral resolution hyper-pixels are efficiently encoded via a coupled dictionary learning scheme. Experimental results and quantitative validation on data acquired by NASA's EO-1 mission's Hyperion sensor, demonstrate the potential of the proposed approach for accurate spectral resolution enhancement of hyperspectral imaging systems.

  6. Spectral library generation for hyperspectral archaeological validation

    NASA Astrophysics Data System (ADS)

    Canham, Kelly; Middleton, William; Messinger, David; Raqueno, Nina

    2012-06-01

    Fractional abundance maps have been produced from Hyperion hyperspectral data over Oaxaca, Mexico, by applying a new spatially adaptive spectral unmixing algorithm. The goal of this research is to produce land-use maps for aiding archaeologists studying the Zapotec civilization. However, to correlate the fractional abundance maps generated from the HSI image processing, a relationship between the known materials located in Oaxaca, Mexico, and the spectral profiles of these materials must be established. A field campaign during December 2011, (the dry season in Oaxaca) took place for the explicit task of obtaining spectral profiles of the most common materials found in the region. Ground-truth information was collected for three Oaxaca valleys (Tlacolula, Yanhuitlan, and Ycuitla). Common materials and associated regions were recorded and material samples were collected at many of these locations. Laboratory reflectance spectral profiles of the collected material samples are measured after the field campaign using a FieldSpec Pro. Wavelength ranges of the FieldSpec Pro spanned 350-2500nm matching that of the hyperspectral imagery collected from the Hyperion sensor on board the EO-1 satellite. GIS maps of the three valleys in Oaxaca, Mexico, are used to identify where these samples were collected and correspond to the laboratory measured material samples. The spectral library entries obtained correspond to bare soils, senescent agricultural vegetation, senescent natural vegetation, and terra cotta tile.

  7. Radiometric cross-calibration of EO-1 ALI with L7 ETM+ and Terra MODIS sensors using near-simultaneous desert observations

    USGS Publications Warehouse

    Chander, Gyanesh; Angal, Amit; Choi, Taeyoung; Xiong, Xiaoxiong

    2013-01-01

    The Earth Observing-1 (EO-1) satellite was launched on November 21, 2000, as part of a one-year technology demonstration mission. The mission was extended because of the value it continued to add to the scientific community. EO-1 has now been operational for more than a decade, providing both multispectral and hyperspectral measurements. As part of the EO-1 mission, the Advanced Land Imager (ALI) sensor demonstrates a potential technological direction for the next generation of Landsat sensors. To evaluate the ALI sensor capabilities as a precursor to the Operational Land Imager (OLI) onboard the Landsat Data Continuity Mission (LDCM, or Landsat 8 after launch), its measured top-of-atmosphere (TOA) reflectances were compared to the well-calibrated Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors in the reflective solar bands (RSB). These three satellites operate in a near-polar, sun-synchronous orbit 705 km above the Earth's surface. EO-1 was designed to fly one minute behind L7 and approximately 30 minutes in front of Terra. In this configuration, all the three sensors can view near-identical ground targets with similar atmospheric, solar, and viewing conditions. However, because of the differences in the relative spectral response (RSR), the measured physical quantities can be significantly different while observing the same target. The cross-calibration of ALI with ETM+ and MODIS was performed using near-simultaneous surface observations based on image statistics from areas observed by these sensors over four desert sites (Libya 4, Mauritania 2, Arabia 1, and Sudan 1). The differences in the measured TOA reflectances due to RSR mismatches were compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of each sensor. For this study, the spectral profile of the target comes from the near-simultaneous EO-1

  8. Mapping Regolith and Gossan for Mineral Exploration in the Eastern Kumaon Himalaya, India using hyperion data and object oriented image classification

    NASA Astrophysics Data System (ADS)

    Farooq, S.; Govil, H.

    2014-06-01

    Crystalline in the Kumaon Himalaya, India near Askot area is a prominent site of the base metal mineralization and gossanised surface. This area is hosted by the sulphides and sulphates of Cu, Pb, Zn and Au and Ag mineralization with the altered rocks like sericite chlorite schist, gneiss etc. Due to the deep weathering this area is also a good illustration site of the gossanised outcrop. Regolith mapping through the multispectral remotely sensed data using different parametric and nonparametric classification algorithm has been used for many years. In recent years, object oriented classification for classification of object rather than pixel has gained a good success within the geospatial community. On the other hand, space borne hyperspectral remote sensing has gained a great success in identification of the minerals from space. The narrow contiguous bands of this hyperspectral remote sensing data can provide more information of the chemical content of the different minerals. In this study EO1 (Earth Observation) Hyperion hyperspectral sensor data has been evaluated for regolith and gossan mapping using the object oriented image classification technique. The efficacy of the hyperion data is evaluated in and around the Askot base metal mineral deposits for hydrothermal alteration and base metal minerals. Three sites were selected by regolith mapping using object oriented image classification method and were evaluated by the aid of hyperspectral data for alteration minerals. During the field verification it was found that the mineralization within these sites was associated with the dolomite, gneiss and schists. Strong hydrothermal activity and shearing were dominated at these sites. Minerals like carbonates, sulphates and sulphides of copper, lead, zinc and silver, magnetite along with the altered minerals like, mica, chlorite, talc etc. were found at the target sites. eCognition™ and ENVI® software's were used for the object based classification and for the

  9. Hyperspectral image analysis for the determination of alteration minerals in geothermal fields: Çürüksu (Denizli) Graben, Turkey

    NASA Astrophysics Data System (ADS)

    Uygur, Merve; Karaman, Muhittin; Kumral, Mustafa

    2016-04-01

    Çürüksu (Denizli) Graben hosts various geothermal fields such as Kızıldere, Yenice, Gerali, Karahayıt, and Tekkehamam. Neotectonic activities, which are caused by extensional tectonism, and deep circulation in sub-volcanic intrusions are heat sources of hydrothermal solutions. The temperature of hydrothermal solutions is between 53 and 260 degree Celsius. Phyllic, argillic, silicic, and carbonatization alterations and various hydrothermal minerals have been identified in various research studies of these areas. Surfaced hydrothermal alteration minerals are one set of potential indicators of geothermal resources. Developing the exploration tools to define the surface indicators of geothermal fields can assist in the recognition of geothermal resources. Thermal and hyperspectral imaging and analysis can be used for defining the surface indicators of geothermal fields. This study tests the hypothesis that hyperspectral image analysis based on EO-1 Hyperion images can be used for the delineation and definition of surfaced hydrothermal alteration in geothermal fields. Hyperspectral image analyses were applied to images covering the geothermal fields whose alteration characteristic are known. To reduce data dimensionality and identify spectral endmembers, Kruse's multi-step process was applied to atmospherically and geometrically-corrected hyperspectral images. Minimum Noise Fraction was used to reduce the spectral dimensions and isolate noise in the images. Extreme pixels were identified from high order MNF bands using the Pixel Purity Index. n-Dimensional Visualization was utilized for unique pixel identification. Spectral similarities between pixel spectral signatures and known endmember spectrum (USGS Spectral Library) were compared with Spectral Angle Mapper Classification. EO-1 Hyperion hyperspectral images and hyperspectral analysis are sensitive to hydrothermal alteration minerals, as their diagnostic spectral signatures span the visible and shortwave

  10. Synergetic Use of Multispectral and Hyperspectral Spaceborne Sensors for the Mapping of Natural Resources with the Sensor Pairs: Landsat-8 and Hyperion, Sentinel-2 and EnMAP

    NASA Astrophysics Data System (ADS)

    Mielke, Christian; Rogass, Christian; Papenfuss, Anne; Boesche, Nina; Segl, Karl

    2016-08-01

    Multispectral and hyperspectral spaceborne data are increasingly used by the geoscientific community. They represent unique assets for screening large arid and semi- arid areas for their mineral resource potential. Here a new link between multispectral and hyperspectral spaceborne data is presented termed the Normalized Iron Feature Depth (NIFD). It is calculated for at ground reflectance data and at sensor radiance data from Sentinel-2 and Landsat-8 OLI data to highlight zones of iron bearing minerals such as goethite hematite and jarosite. These minerals are characteristic for so called gossan zones, which may indicate the presence of weathering ore minerals, especially metal sulphides. The normalized iron feature depth is calculated for Sentinel-2 and Landsat-8 data from the Bushmanland base metal deposits in South Africa and the Haib River porphyry copper-molybdenum deposit in Namibia. Comparison to hyperspectral spaceborne data, shows that the zones with high normalized iron feature depth values coincide with the gossan zones characterized from hyperspectral spaceborne data and data from fieldwork.

  11. Super-resolution reconstruction of hyperspectral images using empirical mode decomposition and compressed sensing

    NASA Astrophysics Data System (ADS)

    Ziyong, Zhou

    2016-10-01

    Hyperspectral remote sensing provides the possibility of direct detection of material information; however, coarse spatial resolution can restrict the scope of its application. The super-resolution (SR) technique can overcome this problem, but the separate application of SR reconstruction to each spectral band is computationally intensive. We proposed an approach that combines empirical mode decomposition (EMD), single-image SR reconstruction using compressed sensing (CS), and principal component analysis (PCA). EMD was used to extract details from within the images, whereas PCA was implemented to reduce the spectral dimensions of the hyperspectral image cube and to retain meaningful spectral information. The CS-based single-image SR reconstruction involved the use of both the K-SVD algorithm for learning and obtaining an over-complete dictionary, and the orthogonal matching pursuit algorithm for the image reconstruction. Experimental results obtained using an EO-1 hyperion image were used to validate the proposed approach.

  12. Urban land cover classification using hyperspectral data

    NASA Astrophysics Data System (ADS)

    Hegde, G.; Ahamed, J. Mohammed; Hebbar, R.; Raj, U.

    2014-11-01

    Urban land cover classification using remote sensing data is quite challenging due to spectrally and spatially complex urban features. The present study describes the potential use of hyperspectral data for urban land cover classification and its comparison with multispectral data. EO-1 Hyperion data of October 05, 2012 covering parts of Bengaluru city was analyzed for land cover classification. The hyperspectral data was initially corrected for atmospheric effects using MODTRAN based FLAASH module and Minimum Noise Fraction (MNF) transformation was applied to reduce data dimensionality. The threshold Eigen value of 1.76 in VNIR region and 1.68 in the SWIR region was used for selection of 145 stable bands. Advanced per pixel classifiers viz., Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) were used for general urban land cover classification. Accuracy assessment of the classified data revealed that SVM was quite superior (82.4 per cent) for urban land cover classification as compared to SAM (67.1 per cent). Selecting training samples using end members significantly improved the classification accuracy by 20.1 per cent in SVM. The land cover classification using multispectral LISS-III data using SVM showed lower accuracy mainly due to limitation of spectral resolution. The study indicated the requirement of additional narrow bands for achieving reasonable classification accuracy of urban land cover. Future research is focused on generating hyperspectral library for different urban features.

  13. Fire Characterization and Fire-Related Land Cover Classification Using Hyperion Data over Selected Alaskan Boreal Forest Fires

    NASA Astrophysics Data System (ADS)

    Waigl, C. F.; Prakash, A.; Stuefer, M.; Dennison, P. E.

    2014-12-01

    In this study, NIR and SWIR EO-1 Hyperion data acquired over two large Alaskan forest fires are used to detect active fires, map their immediate vicinity, and retrieve fire temperatures. The study sites are located in black spruce stands within the 2004 Boundary fire (215,000 ha total affected area) and the 2009 Wood River 1 fire (50,000 ha). Even though fires in the North American boreal forest ecosystem contribute greatly to global carbon cycling and large-scale air pollution, they have been less studied so far using satellite-borne imaging spectroscopy. We adapted the Hyperspectral Fire Detection Index (HFDI) so that it worked well for the high-latitude Hyperion data. This involved selecting suitable bands which best separated fire from non-fire pixels and averaging them to further improve the detection signal. Resulting fire detection maps compare favorably to uniform radiance thresholding of the Hyperion data and are consistent with fires detected on near-simultaneous Landsat 7 ETM+ data. Unsupervised classification of the vicinity of the active fire zones served to delineate 5 to 6 well separated classes: high- and low-intensity fire, various unburnt vegetation classes, recent fire scar, and a transitional zone ahead of the active fire front that shows evidence of fire impact but no emitted radiance component. Furthermore, MODTRAN5 was used for atmospheric correction to retrieve fire temperatures by modeling a mixture of emitted and reflected radiance signatures of the fire and background areas, respectively. As most of the carbon consumption and subsequent emissions in boreal forest fires stem from the combustion of dead plant material on the forest floor, estimates on fire intensities and high/low intensity burn areas provide valuable insight into the amount of carbon cycling in the system. Imaging spectroscopy can therefore contribute an important step forward in quantitative studies of boreal fires and their impacts. These techniques are set to advance

  14. Validating the autonomous EO-1 science agent

    NASA Technical Reports Server (NTRS)

    Cichy, Benjamin; Chien, Steve; Rabideau, Gregg; Tran, Daniel

    2004-01-01

    This paper describes the validation process for the Autonomous Science Agent, a software agent that is currently flying onboard NASA EO-1 spacecraft. The agent autonomously collects, analyzes, and reacts to onboard science data. The Autonomous Science Agent has been designed using a layered architectural approach with specific redundant safeguards to reduce the risk of an agent malfunction to the EO-1 spacecraft. This safe design has been thoroughly validated by informal validation methods supplemented by sub-system and system-level testing. This paper describes the analysis used to define agent safety, elements of the design that increase the safety of the agent, and the process used to validate agent safety.

  15. Chaos at Hyperion

    NASA Image and Video Library

    2016-12-05

    The moon Hyperion tumbles as it orbits Saturn. Hyperion's (168 miles or 270 kilometers across) spin axis has a chaotic orientation in time, meaning that it is essentially impossible to predict how the moon will be spinning in the future. So far, scientists only know of a few bodies with such chaotic spins. The image was taken in green light with the Cassini spacecraft narrow-angle camera on Aug. 22, 2016. The view was acquired at a distance of approximately 203,000 miles (326,000 kilometers) from Hyperion and at a Sun-Hyperion-spacecraft, or phase, angle of 10 degrees. Image scale is 1 mile (2 kilometers) per pixel. http://photojournal.jpl.nasa.gov/catalog/PIA20512

  16. Autonomous Science on the EO-1 Mission

    NASA Technical Reports Server (NTRS)

    Chien, S.; Sherwood, R.; Tran, D.; Castano, R.; Cichy, B.; Davies, A.; Rabideau, G.; Tang, N.; Burl, M.; Mandl, D.; hide

    2003-01-01

    In mid-2003, we will fly software to detect science events that will drive autonomous scene selectionon board the New Millennium Earth Observing 1 (EO-1) spacecraft. This software will demonstrate the potential for future space missions to use onboard decision-making to detect science events and respond autonomously to capture short-lived science events and to downlink only the highest value science data.

  17. Autonomous Science on the EO-1 Mission

    NASA Technical Reports Server (NTRS)

    Chien, S.; Sherwood, R.; Tran, D.; Castano, R.; Cichy, B.; Davies, A.; Rabideau, G.; Tang, N.; Burl, M.; Mandl, D.; Frye, S.; Hengemihle, J.; Agostino, J. D.; Bote, R.; Trout, B.; Shulman, S.; Ungar, S.; Gaasbeck, J. Van; Boyer, D.; Griffin, M.; Burke, H.; Greeley, R.; Doggett, T.; Williams, K.; Baker, V.

    2003-01-01

    In mid-2003, we will fly software to detect science events that will drive autonomous scene selectionon board the New Millennium Earth Observing 1 (EO-1) spacecraft. This software will demonstrate the potential for future space missions to use onboard decision-making to detect science events and respond autonomously to capture short-lived science events and to downlink only the highest value science data.

  18. Use of EO-1 Hyperion Data for Inter-Sensor Calibration of Vegetation Indices

    NASA Technical Reports Server (NTRS)

    Huete, Alfredo; Miura, Tomoaki; Kim, HoJin; Yoshioka, Hiroki

    2004-01-01

    Numerous satellite sensor systems useful in terrestrial Earth observation and monitoring have recently been launched and their derived products are increasingly being used in regional and global vegetation studies. The increasing availability of multiple sensors offer much opportunity for vegetation studies aimed at understanding the terrestrial carbon cycle, climate change, and land cover conversions. Potential applications include improved multiresolution characterization of the surface (scaling); improved optical-geometric characterization of vegetation canopies; improved assessments of surface phenology and ecosystem seasonal dynamics; and improved maintenance of long-term, inter-annual, time series data records. The Landsat series of sensors represent one group of sensors that have produced a long-term, archived data set of the Earth s surface, at fine resolution and since 1972, capable of being processed into useful information for global change studies (Hall et al., 1991).

  19. Mapping advanced argillic alteration zones with ASTER and Hyperion data in the Andes Mountains of Peru

    NASA Astrophysics Data System (ADS)

    Ramos, Yuddy; Goïta, Kalifa; Péloquin, Stéphane

    2016-04-01

    This study evaluates Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Hyperion hyperspectral sensor datasets to detect advanced argillic minerals. The spectral signatures of some alteration clay minerals, such as dickite and alunite, have similar absorption features; thus separating them using multispectral satellite images is a complex challenge. However, Hyperion with its fine spectral bands has potential for good separability of features. The Spectral Angle Mapper algorithm was used in this study to map three advanced argillic alteration minerals (alunite, kaolinite, and dickite) in a known alteration zone in the Peruvian Andes. The results from ASTER and Hyperion were analyzed, compared, and validated using a Portable Infrared Mineral Analyzer field spectrometer. The alterations corresponding to kaolinite and alunite were detected with both ASTER and Hyperion (80% to 84% accuracy). However, the dickite mineral was identified only with Hyperion (82% accuracy).

  20. Jeffries Matusita based mixed-measure for improved spectral matching in hyperspectral image analysis

    NASA Astrophysics Data System (ADS)

    Padma, S.; Sanjeevi, S.

    2014-10-01

    This paper proposes a novel hyperspectral matching technique by integrating the Jeffries-Matusita measure (JM) and the Spectral Angle Mapper (SAM) algorithm. The deterministic Spectral Angle Mapper and stochastic Jeffries-Matusita measure are orthogonally projected using the sine and tangent functions to increase their spectral ability. The developed JM-SAM algorithm is implemented in effectively discriminating the landcover classes and cover types in the hyperspectral images acquired by PROBA/CHRIS and EO-1 Hyperion sensors. The reference spectra for different land-cover classes were derived from each of these images. The performance of the proposed measure is compared with the performance of the individual SAM and JM approaches. From the values of the relative spectral discriminatory probability (RSDPB) and relative discriminatory entropy value (RSDE), it is inferred that the hybrid JM-SAM approach results in a high spectral discriminability than the SAM and JM measures. Besides, the use of the improved JM-SAM algorithm for supervised classification of the images results in 92.9% and 91.47% accuracy compared to 73.13%, 79.41%, and 85.69% of minimum-distance, SAM and JM measures. It is also inferred that the increased spectral discriminability of JM-SAM measure is contributed by the JM distance. Further, it is seen that the proposed JM-SAM measure is compatible with varying spectral resolutions of PROBA/CHRIS (62 bands) and Hyperion (242 bands).

  1. 2016 Mission Operations Working Group: Earth Observing-1 (EO-1)

    NASA Technical Reports Server (NTRS)

    Frye, Stuart

    2016-01-01

    EO-1 Mission Status for the Constellation Mission Operations Working Group to discuss the EO-1 flight systems, mission enhancements, debris avoidance maneuver, orbital information, 5-year outlook, and new ground stations.

  2. Detection of neolithic settlements in thessaly (Greece) through multispectral and hyperspectral satellite imagery.

    PubMed

    Alexakis, Dimitrios; Sarris, Apostolos; Astaras, Theodoros; Albanakis, Konstantinos

    2009-01-01

    Thessaly is a low relief region in Greece where hundreds of Neolithic settlements/tells called magoules were established from the Early Neolithic period until the Bronze Age (6,000 - 3,000 BC). Multi-sensor remote sensing was applied to the study area in order to evaluate its potential to detect Neolithic settlements. Hundreds of sites were geo-referenced through systematic GPS surveying throughout the region. Data from four primary sensors were used, namely Landsat ETM, ASTER, EO1 - HYPERION and IKONOS. A range of image processing techniques were originally applied to the hyperspectral imagery in order to detect the settlements and validate the results of GPS surveying. Although specific difficulties were encountered in the automatic classification of archaeological features composed by a similar parent material with the surrounding landscape, the results of the research suggested a different response of each sensor to the detection of the Neolithic settlements, according to their spectral and spatial resolution.

  3. Detection of Neolithic Settlements in Thessaly (Greece) Through Multispectral and Hyperspectral Satellite Imagery

    PubMed Central

    Alexakis, Dimitrios; Sarris, Apostolos; Astaras, Theodoros; Albanakis, Konstantinos

    2009-01-01

    Thessaly is a low relief region in Greece where hundreds of Neolithic settlements/tells called magoules were established from the Early Neolithic period until the Bronze Age (6,000 – 3,000 BC). Multi-sensor remote sensing was applied to the study area in order to evaluate its potential to detect Neolithic settlements. Hundreds of sites were geo-referenced through systematic GPS surveying throughout the region. Data from four primary sensors were used, namely Landsat ETM, ASTER, EO1 - HYPERION and IKONOS. A range of image processing techniques were originally applied to the hyperspectral imagery in order to detect the settlements and validate the results of GPS surveying. Although specific difficulties were encountered in the automatic classification of archaeological features composed by a similar parent material with the surrounding landscape, the results of the research suggested a different response of each sensor to the detection of the Neolithic settlements, according to their spectral and spatial resolution. PMID:22399961

  4. Deep Feature Learning for Hyperspectral Image Classification and Land Cover Estimation

    NASA Astrophysics Data System (ADS)

    Tsagkatakis, Grigorios; Tsakalides, Panagiotis

    2016-08-01

    The differences in spatial sampling between field measurements and remote-sensing imagery can hinder the exploitation of contemporary data. When the field-based sampling is higher than airborne and spaceborne imagery, each pixel is naturally associated with multiple pixels due to the multiplexing of the reflectances of different materials. To address this scale inconsistency, we propose the introduction of the multi-label classification framework where classifiers are trained to predict multiple labels per pixel. Furthermore, instead of relying on raw hyperspectral measurements for the classification process, we investigate the Stacked Sparse Autoencoders framework, an example of a deep learning network, for descriptive feature extraction. To validate the merits of the proposed scheme, we consider real data from the Hyperion instrument on-board the EO-1 and NYC land cover data from 2010.

  5. Surface composition of Hyperion.

    PubMed

    Cruikshank, D P; Dalton, J B; Dalle Ore, C M; Bauer, J; Stephan, K; Filacchione, G; Hendrix, A R; Hansen, C J; Coradini, A; Cerroni, P; Tosi, F; Capaccioni, F; Jaumann, R; Buratti, B J; Clark, R N; Brown, R H; Nelson, R M; McCord, T B; Baines, K H; Nicholson, P D; Sotin, C; Meyer, A W; Bellucci, G; Combes, M; Bibring, J-P; Langevin, Y; Sicardy, B; Matson, D L; Formisano, V; Drossart, P; Mennella, V

    2007-07-05

    Hyperion, Saturn's eighth largest icy satellite, is a body of irregular shape in a state of chaotic rotation. The surface is segregated into two distinct units. A spatially dominant high-albedo unit having the strong signature of H2O ice contrasts with a unit that is about a factor of four lower in albedo and is found mostly in the bottoms of cup-like craters. Here we report observations of Hyperion's surface in the ultraviolet and near-infrared spectral regions with two optical remote sensing instruments on the Cassini spacecraft at closest approach during a fly-by on 25-26 September 2005. The close fly-by afforded us the opportunity to obtain separate reflectance spectra of the high- and low-albedo surface components. The low-albedo material has spectral similarities and compositional signatures that link it with the surface of Phoebe and a hemisphere-wide superficial coating on Iapetus.

  6. Capability of Hyperspectral data in Spatial Variability Distribution of Chlorophyll and Water Stress in Rice Agriculture System

    NASA Astrophysics Data System (ADS)

    Moharana, S.; Dutta, S.

    2016-12-01

    Abstract : The mapping and analysis of spatial variability within the field is a challenging task. However, field variability of a single vegetation cover does not give satisfactory results mainly due to low spectral resolution and non-availability of remote sensing data. From the NASA Earth Observing-1 (EO-1) satellite data, spatial distribution of biophysical parameters like chlorophyll and relative water content in a rice agriculture system is carried out in the present study. Hyperion L1R product composed of 242 spectral bands with 30m spatial resolution was acquired for Assam, India. This high dimensional data is allowed for pre-processing to get an atmospherically corrected imagery. Moreover, ground based hyperspectral measurements are collected from experimental rice fields from the study site using hand held ASD spectroradiometer (350-1050 nm). Published indices specifically designed for chlorophyll (OASVI, mSR, and MTCI indices) and water content (WI and WBI indices) are selected based on stastical performance of the in-situ hyperspectral data. Index models are established for the respective biophysical parameters and observed that the aforementioned indices followed different linear and nonlinear relationships which are completely different from the published indices. By employing the presently developed relationships, spatial variation of total chlorophyll and water stress are mapped for a rice agriculture system from Hyperion imagery. The findings showed that, the variation of chlorophyll and water content ranged from 1.77-10.61mg/g and 40-90% respectively for the studied rice agriculture system. The spatial distribution of these parameters resulted from presently developed index models are well captured from Hyperion imagery and they have good agreement with observed field based chlorophyll (1.14-7.26 mg/g) and water content (60-95%) of paddy crop. This study can be useful in providing essential information to assess the paddy field heterogeneity in an

  7. Hyperspectral remote sensing for water quality applications in Guatemala

    NASA Astrophysics Data System (ADS)

    Flores Cordova, A. I.; Christopher, S. A.; Irwin, D.

    2013-12-01

    Water quality measurements are relevant to control and prevent the pollution of surface water essential for human use. Previous studies have used standard methods of water sampling to estimate water quality parameters. Nevertheless those methods are extremely expensive and time-consuming and do not provide information for an entire water body. Hence it is important to implement techniques that allow for the monitoring of water quality parameters in a timely and cost-effective manner, and remote sensing represents a feasible alternative. This study focuses on the largest algal bloom affecting Lake Atitlan, located in Guatemala, by using the hyperspectral sensor Hyperion on board the EO-1 satellite. This algal bloom had a life span that extended for a little more than a month and had a maximum coverage of approximately 40% of the lake's 137 square kilometer surface. This algal bloom occurred at the end of the year 2009, with November being the most critical month. Different satellite sensors were used to monitor the extent of the algal bloom, including Landsat Enhanced Thematic Mapper Plus (ETM+), the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Advanced Land Imager (ALI). However, Hyperion images were used to distinguish the characteristics of the vegetation populating the algal bloom. Hyperion satellite images provided a more complete spectral profile of the algal bloom affecting the lake due to its high spectral resolution characteristics. This enabled the identification of unique peaks of reflectance and absorption features of the spectral signature obtained from the algal bloom. The algal bloom was formed mainly by the cyanobacteria Lyngbya robusta. Hyperion satellite images were used to characterize the algal bloom and the unique pigments of cyanobacteria such as phycocyanin. Atmospheric correction was critical to obtain the pure reflectance of the algal bloom and differentiate the spectral features unique to the cyanobacteria

  8. The chaotic rotation of Hyperion

    NASA Technical Reports Server (NTRS)

    Wisdom, J.; Peale, S. J.; Mignard, F.

    1984-01-01

    Under the assumption that the satellite is rotating about a principal axis that is normal to its orbit plane, a plot of spin rate-versus-orientation for Hyperion at the pericenter of its orbit has revealed a large, chaotic zone surrounding Hyperion's synchronous spin-orbit state. The chaotic zone is so large that it surrounds the 1/2 and 2 states, and libration in the 3/2 state is not possible. Rotation in the chaotic zone is also attitude-unstable. As tidal dissipation drives Hyperion's spin toward a nearly synchronous value, Hyperion necessarily enters the large chaotic zone, becoming attitude-unstable and tumbling. It is therefore predicted that Hyperion will be found to be tumbling chaotically.

  9. Chaotic rotation of Hyperion?

    NASA Technical Reports Server (NTRS)

    Binzel, R. P.; Green, J. R.; Opal, C. B.

    1986-01-01

    Thomas et al. (1984) analyzed 14 Voyager 2 images of Saturn's satellite Hyperion and interpreted them to be consistent with a coherent (nonchaotic) rotation period of 13.1 days. This interpretation was criticized by Peale and Wisdom (1984), who argued that the low sampling frequency of Voyager data does not allow chaotic or nonchaotic rotation to be distinguished. New observations obtained with a higher sampling frequency are reported here which conclusively show that the 13.1 day period found by Thomas et al. was not due to coherent rotation.

  10. Earth Orbiter 1 (EO-1): Wideband Advanced Recorder and Processor (WARP)

    NASA Technical Reports Server (NTRS)

    Smith, Terry; Kessler, John

    1999-01-01

    An overview of the Earth Orbitor 1 (EO1) Wideband Advanced Recorder and Processor (WARP) is presented in viewgraph form. The WARP is a spacecraft component that receives, stores, and processes high rate science data and its associated ancillary data from multispectral detectors, hyperspectral detectors, and an atmospheric corrector, and then transmits the data via an X-band or S-band transmitter to the ground station. The WARP project goals are: (1) Pathfinder for next generation LANDSAT mission; (2) Flight prove architectures and technologies; and (3) Identify future technology needs.

  11. DEMO: The autonomous sciencecraft experiment onboard the EO-1 spacecraft

    NASA Technical Reports Server (NTRS)

    Tran, Daniel; Chien, Steve; Sherwood, Rob; Castano, Rebecca; Cichy, Benjamin; Davies, Ashley; Rabideau, Gregg

    2005-01-01

    The Autonomous Sciencecraft Experiment (ASE), currently flying onboard the Earth Observing-1 (EO-1) spacecraft, integrates several autonomy software technologies enabling autonomous science analysis and mission planning.

  12. Mapping and Assessing Surface Morphology of Holocene Lava Field in Krafla (NE Iceland) Using Hyperspectral Remote Sensing

    NASA Astrophysics Data System (ADS)

    Aufaristama, M.; Höskuldsson, A.; Jónsdóttir, I.; Ólafsdóttir, R.

    2016-01-01

    Iceland is well known for its volcanic activity due to its location on the spreading Mid Atlantic Ridge and one of the earth's hot spot. In the past 1000 years there were about 200 eruptions occurring in Iceland, meaning volcanic eruptions occurred every four to five years, on average. Iceland currently has 30 active volcano systems, distributed evenly throughout the so- called Neovolcanic Zone. One of these volcanic systems is the Krafla central volcano, which is located in the northern Iceland at latitude 65°42'53'' N and longitude 16°43'40'' W. Krafla has produced two volcanic events in historic times: 1724-1729 (Myvatn Fires) and 1975-1984 (Krafla Fires). The Krafla Fires began in December 1975 and lasted until September 1984. This event covered about 36-km2 surrounding area with lava, having a total volume of 0.25-0.3 km3. Previous studies of lava surface morphology at Krafla focused on an open channel area by remote sensing are essential as a complementary tool to the previous investigations and to extend the area of mapping. Using Spectral Angle Mapper (SAM) classification approach by selecting spectral reflectance end members, this study has successfully produced a detailed map of the surface morphology in Krafla lava field EO-1 Hyperion (Hyperspectral) satellite images. The overall accuracy of lava morphology map is 61.33% (EO-1 Hyperion). These results show that hyperspectral remote sensing is an acceptable alternative to field mapping and assessing the lava surface morphology in the Krafla lava field. In order to get validation of the satellite image's spectral reflectance, in-situ measurements of the lava field's spectral reflectance using ASD FieldSpec3 is essential.

  13. Evaluation of Algorithms for Compressing Hyperspectral Data

    NASA Technical Reports Server (NTRS)

    Cook, Sid; Harsanyi, Joseph; Faber, Vance

    2003-01-01

    With EO-1 Hyperion in orbit NASA is showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI spectral compression and Mapping Science (MSI) for JPEG 2000 spatial compression expertise, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor > 100, while retaining the necessary spectral and spatial fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our compression algorithms leverage commercial-off-the-shelf (COTS) spectral and spatial exploitation algorithms. We are currently in the process of evaluating these compression algorithms using statistical analysis and NASA scientists. We are also developing special purpose processors for executing these algorithms onboard a spacecraft.

  14. Hyperion: Rotational dynamics.

    NASA Astrophysics Data System (ADS)

    Black, G. J.; Nicholson, P. D.; Thomas, P. C.

    1995-09-01

    We have numerically integrated the full three dimensional rotation of Hyperion using as initial conditions the moments of inertia, pole position, and spin rate from a solution based on fitting control points, limb, and terminator positions in high-resolution Voyager 2 images (P. C. Thomas et al. 1995, Icarus ). These images were taken over a 38-hr period and cover ˜114° of rotation. From this solution, it is found that at the time of the Voyager 2 encounter (23 August 1981) the instantaneous spin axis was tilted ˜60° from the orbit normal and was roughly aligned with the axis of minimum moment of inertia. In addition, the instantaneous spin rate is found to have been 72° +3-4 per day, or about 4.2 times the synchronous rate. The integrated dynamical model using this solution provides an excellent fit to the lightcurve obtained from earlier low resolution Voyager 2 images, whereas a fit assuming a constant rotation pole and spin rate clearly does not. The largest amplitude component in the lightcurve is due to the free precession (wobble) rather than to the rotation itself. Previous work by J. Wisdom, S. J. Peale, and F. Mignard (1984, Icarus 58, 137-152) showed that it was likely that Hyperion would be in a chaotically tumbling state, and groundbased observations by J. J. Klavetter (1989, Astron. J. 97, 570-579; 98, 1855-1874) in 1987 could not be explained by any simply periodic rotation and are consistent with a chaotic state. Although Hyperion's rotation state is indeed formally chaotic, with the shortest Lyapunov time on the order of the orbital period or less (J. Wisdom et al. 1984, Astron. J. 94, 1350-1360), the short-term motion of the spin axis in 1981 appears "quasi-regular," undergoing forced precession with a period of ˜300 days and wobbling with a period of ˜7 days. Our integrations show that the unusual spin state seen by Voyager 2 can persist for several thousand years, although the chaotic nature of the motion limits the predictability of our

  15. Improved Classification of Mangroves Health Status Using Hyperspectral Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Vidhya, R.; Vijayasekaran, D.; Ahamed Farook, M.; Jai, S.; Rohini, M.; Sinduja, A.

    2014-11-01

    Mangrove ecosystem plays a crucial role in costal conservation and provides livelihood supports to humans. It is seriously affected by the various climatic and anthropogenic induced changes. The continuous monitoring is imperative to protect this fragile ecosystem. In this study, the mangrove area and health status has been extracted from Hyperspectral remote sensing data (EO- 1Hyperion) using support vector machine classification (SVM). The principal component transformation (PCT) technique is used to perform the band reduction in Hyperspectral data. The soil adjusted vegetation Indices (SAVI) were used as additional parameters. The mangroves are classified into three classes degraded, healthy and sparse. The SVM classification is generated overall accuracy of 73 % and kappa of 0.62. The classification results were compared with the results of spectral angle mapper classification (SAM). The SAVI also included in SVM classification and the accuracy found to be improved to 82 %. The sparse and degraded mangrove classes were well separated. The results indicate that the mapping of mangrove health is accurate when the machine learning classifier like SVM combined with different indices derived from hyperspectral remote sensing data.

  16. Detection of Chlorophyll and Leaf Area Index Dynamics from Sub-weekly Hyperspectral Imagery

    NASA Technical Reports Server (NTRS)

    Houborg, Rasmus; McCabe, Matthew F.; Angel, Yoseline; Middleton, Elizabeth M.

    2016-01-01

    Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense time series of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.

  17. Detection of chlorophyll and leaf area index dynamics from sub-weekly hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Houborg, Rasmus; McCabe, Matthew F.; Angel, Yoseline; Middleton, Elizabeth M.

    2016-10-01

    Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense timeseries of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.

  18. Mapping the distribution of mangrove species in the Core Zone of Mai Po Marshes Nature Reserve, Hong Kong, using hyperspectral data and high-resolution data

    NASA Astrophysics Data System (ADS)

    Jia, Mingming; Zhang, Yuanzhi; Wang, Zongming; Song, Kaishan; Ren, Chunying

    2014-12-01

    Mangrove species compositions and distributions are essential for conservation and restoration efforts. In this study, hyperspectral data of EO-1 HYPERION sensor and high spatial resolution data of SPOT-5 sensor were used in Mai Po mangrove species mapping. Objected-oriented method was used in mangrove species classification processing. Firstly, mangrove objects were obtained via segmenting high spatial resolution data of SPOT-5. Then the objects were classified into different mangrove species based on the spectral differences of HYPERION image. The classification result showed that in the top canopy, Kandelia obovata and Avicennia marina dominated Mai Po Marshes Natural Reserve, with area of 196.8 ha and 110.8 ha, respectively, Acanthus ilicifolius and Aegiceras corniculatum were mixed together and living at the edge of channels with an area of 11.7 ha. Additionally, mangrove species shows clearly zonations and associations in the Mai Po Core Zone. The overall accuracy of our mangrove map was 88% and the Kappa confidence was 0.83, which indicated great potential of using hyperspectral and high-resolution data for distinguishing and mapping mangrove species.

  19. Rotation of Hyperion. I - Observations

    NASA Technical Reports Server (NTRS)

    Klavetter, James Jay

    1989-01-01

    Precise and well sampled observations of Hyperion over a long period of time have been performed to test the prediction of Wisdom et al. (1984) that the satellite is in a state of chaotic rotation. CCD data for a 13-week period were obtained in Chile and in Arizona. A phase-dispersion-minimization analysis of the light curve indicates that Hyperion is not in a periodic rotational state, thus suggesting that it is chaotic.

  20. Automated endmember extraction for subpixel classification of multispectral and hyperspectral data

    NASA Astrophysics Data System (ADS)

    Shrivastava, Deepali; Kumar, Vinay; Sharma, Richa U.

    2016-04-01

    Most of the multispectral sensors acquire data in several broad wavelength bands and are capable of extracting different Land Cover features while hyperspectral sensors contain ample spectral data in narrow bandwidth (10- 20nm). The spectrally rich data enable the extraction of useful quantitative information from earth surface features. Endmembers are the pure spectral components extracted from the remote sensing datasets. Most approaches for Endmember extraction (EME) are manual and have been designed from a spectroscopic viewpoint, thus neglecting the spatial arrangement of the pixels. Therefore, EME techniques which can consider both spectral and spatial aspects are required to find more accurate Endmembers for Subpixel classification. Multispectral (EO-1 ALI and Landsat 8 OLI) and Hyperspectral (EO-1 Hyperion) datasets of Udaipur region, Rajasthan is used in this study. All the above mentioned datasets are preprocessed and converted to surface reflectance using Fast Line-of-sight Atmospheric Analysis of Spectral Hypercube (FLAASH). Further Automated Endmember extraction and Subpixel classification is carried out using Multiple Endmember Spectral Mixture Analysis (MESMA). Endmembers are selected from spectral libraries to be given as input to MESMA. To optimize these spectral libraries three techniques are deployed i.e. Count based Endmember selection (CoB), Endmember Average RMSE (EAR) and Minimum Average Spectral Angle (MASA) for endmember selection. Further identified endmembers are used for classifying multispectral and hyperspectral data using MESMA and SAM. It was observed from the obtained classified results that diverse features, spread over a pixel, which are spectrally same are well classified by MESMA whereas SAM was unable to do so.

  1. ASPEN: EO-1 Mission Activity Planning Made Easy

    NASA Technical Reports Server (NTRS)

    Sherwood, Rob; Govindjee, Anita; Yan, David; Rabideau, Gregg; Chien, Steve; Fukunaga, Alex

    1997-01-01

    This paper describes the application of an automated planning and scheduling system to the NASA Earth Orbitin 1 (EO-1) missions. The planning system, ASPEN, is used to autonomously schedule the daily activites of the satellite.

  2. Comparing Hyperion Lunar Observation with model calculations in support of GOES-R Advanced Baseline Imager (ABI) calibration

    NASA Astrophysics Data System (ADS)

    Shao, Xi; Cao, Changyong; Uprety, Sirish; Padula, Frank; Choi, Taeyoung

    2014-09-01

    Radiometric stability of the lunar surface and its smooth reflectance spectrum makes the moon an attractive candidate for calibrating satellite-based hyper/multi-band visible and infrared imagers. Long-term performance monitoring of satellite instrument using Moon can reveal the degradation of instruments. In this paper, analysis of Hyperion lunar observations and comparison with lunar model are performed in support of Cal/Val activities for satellite photometric imager such as GOES-R Advanced Baseline Imager (ABI) instrument. Hyperion makes hyper-spectral observations of the moon regularly with moon phase mostly at 7 degree and it covers visible and shirt-wavelength infrared (SWIR) channels with 10 nm spectral resolution. Five Hyperion lunar observations are analyzed. Lunar reflectance is derived from Hyperion observation and the mean absolute lunar spectral reflectance difference between Hyperion derivation and lunar model is 4.0 ± 2.62%. Through reflectance comparison, over-compensation of two strong atmospheric water absorption bands in Hyperion calibration is identified. The radiometric variance and degradation of Hyperion are assessed. To support the calibration of GOES-R ABI, hyper-spectral data of Hyperion lunar observation is convoluted with ABI spectral response functions for reflective solar bands to synthesize predicted lunar images to be observed by ABI. Lunar irradiances are derived from these synthesized lunar images for ABI and compared with lunar model predictions to quantify spectral biases. Long-term lunar imaging window of opportunities for GOES-R ABI are also assessed. The ability of using lunar model and Hyperion observation to calibrate satellite VNIR/SWIR sensors and reduce the measurement uncertainties is essential to support post-launch Cal/Val activities of GOES-R ABI.

  3. The Integration, Testing and Flight of the EO-1 GPS

    NASA Technical Reports Server (NTRS)

    Quinn, David A.; Sanneman, Paul A.; Shulman, Seth E.; Sager, Jennifer A.

    2001-01-01

    The Global Positioning System has long been hailed as the wave of the future for autonomous on-board navigation of low Earth orbiting spacecraft despite the fact that relatively few spacecraft have actually employed it for this purpose. While several missions operated out of the Goddard Space Flight Center have flown GPS receivers on board, the New Millenium Program (NMP) Earth Orbiting-1 (EO-1) spacecraft is the first to employ GPS for active, autonomous on-board navigation. Since EO-1 was designed to employ GPS as its primary source of the navigation ephemeris, special care had to be taken during the integration phase of spacecraft construction to assure proper performance. This paper is a discussion of that process: a brief overview of how the GPS works, how it fits into the design of the EO-1 Attitude Control System (ACS), the steps taken to integrate the system into the EO-1 spacecraft, the ultimate on-orbit performance during launch and early operations of the EO-1 mission and the performance of the on-board GPS ephemeris versus the ground based ephemeris. Conclusions will include a discussion of the lessons learned.

  4. Soil sail content estimation in the yellow river delta with satellite hyperspectral data

    USGS Publications Warehouse

    Weng, Yongling; Gong, Peng; Zhu, Zhi-Liang

    2008-01-01

    Soil salinization is one of the most common land degradation processes and is a severe environmental hazard. The primary objective of this study is to investigate the potential of predicting salt content in soils with hyperspectral data acquired with EO-1 Hyperion. Both partial least-squares regression (PLSR) and conventional multiple linear regression (MLR), such as stepwise regression (SWR), were tested as the prediction model. PLSR is commonly used to overcome the problem caused by high-dimensional and correlated predictors. Chemical analysis of 95 samples collected from the top layer of soils in the Yellow River delta area shows that salt content was high on average, and the dominant chemicals in the saline soil were NaCl and MgCl2. Multivariate models were established between soil contents and hyperspectral data. Our results indicate that the PLSR technique with laboratory spectral data has a strong prediction capacity. Spectral bands at 1487-1527, 1971-1991, 2032-2092, and 2163-2355 nm possessed large absolute values of regression coefficients, with the largest coefficient at 2203 nm. We obtained a root mean squared error (RMSE) for calibration (with 61 samples) of RMSEC = 0.753 (R2 = 0.893) and a root mean squared error for validation (with 30 samples) of RMSEV = 0.574. The prediction model was applied on a pixel-by-pixel basis to a Hyperion reflectance image to yield a quantitative surface distribution map of soil salt content. The result was validated successfully from 38 sampling points. We obtained an RMSE estimate of 1.037 (R2 = 0.784) for the soil salt content map derived by the PLSR model. The salinity map derived from the SWR model shows that the predicted value is higher than the true value. These results demonstrate that the PLSR method is a more suitable technique than stepwise regression for quantitative estimation of soil salt content in a large area. ?? 2008 CASI.

  5. Hyperspectral Systems Increase Imaging Capabilities

    NASA Technical Reports Server (NTRS)

    2010-01-01

    In 1983, NASA started developing hyperspectral systems to image in the ultraviolet and infrared wavelengths. In 2001, the first on-orbit hyperspectral imager, Hyperion, was launched aboard the Earth Observing-1 spacecraft. Based on the hyperspectral imaging sensors used in Earth observation satellites, Stennis Space Center engineers and Institute for Technology Development researchers collaborated on a new design that was smaller and used an improved scanner. Featured in Spinoff 2007, the technology is now exclusively licensed by Themis Vision Systems LLC, of Richmond, Virginia, and is widely used in medical and life sciences, defense and security, forensics, and microscopy.

  6. DEMO: the Autonomous Sciencecraft Experiment onboard the EO-1 spacecraft

    NASA Technical Reports Server (NTRS)

    Tran, Daniel; Chien, Steve; Sherwood, Rob; Castano, Rebecca; Cichy, Benjamin; Davies, Ashley; Rabideau, Gregg

    2004-01-01

    The Autonomous Sciencececraft Experiment (ASE), currently flying onboard the Earth Observing-1 (EO-1) spacecraft, integrates several autnomoy software technologies enabling autnomous science analysis and mission planning. The experiment demonstrates the potential for future space missions to use onboard decision-making to respond autonomously to capture short-lived science phenomena. The AAAI software demonstration will consist of two sections: a real-time display of an ASE-commanded ground contact from the EO-1 spacecraft, and a simulation of the full ASE autonomous science-response scenario.

  7. The information of oil and gas micro-seepage in Dongsheng region of inner Mongolia based on the airborne hyperspectral remote sensing image

    NASA Astrophysics Data System (ADS)

    Tian, Shu-Fang; Chen, Jian-Ping; Zhou, Mi

    2008-11-01

    The technology of hyper-spectral remote sensing which has higher spatial resolution characteristic, and optimizes the qualification of identifying and extracting salt mines, not only enhances the capacity of natural scenes detection and recognition, but also advances the level of quantitative remote sensing. It has important meaning for using the technology of hyper-spectral remote sensing to quantitative extraction. The paper investigate gas micro-seepage based on the Airborne Hyper-spectral Remote Sensing in Dongsheng of Inner Mongolia on the basis of gas micro-seepage theory using EO-1 Hyperion data collected by Satellite-Borne Sensor which has highest spatial resolution presently in the world. On the basis of data pretreated this paper adopts band math extracted the distribution of oil and gas micro-seepage using diagnostic assimilating spectrum of alteration minerals by the numbers. With eigenvector length model evaluates the research area comprehensive index, oil and gas micro-seepage information model of the research area is established and key regions of oil and gas micro-seepage are confirmed, which offers academic gist for oil and gas resource exploitation of Dongsheng.

  8. Water and Bottom Properties of a Coastal Environment Derived from Hyperion Data Measured from the EO-1 Spacecraft Platform

    DTIC Science & Technology

    2007-12-26

    246 (2002) [doi: 10. 1117/12.453346]. [9] H. R. Gordon and M. Wang, "Retrieval of water-leaving radiance and aerosol optical thickness over oceans with...Socleqv of Photo- Optical Instrumeniatwit rta,n-*-, ,,.,,,, . I Received 9 Mar 2007; accepted 5 Sep 2007: published 26 Dee 2007 ICCC: 10313195/2007...which is defined as ratio of water-leaving radiance (L.) to downwelling irradiance just above the surface (Ed)) and water optical properties were

  9. Integrating fAPARchl and PRInadir from EO-1/Hyperion to predict cornfield daily gross primary production (GPP)

    USDA-ARS?s Scientific Manuscript database

    Accurate estimates of terrestrial carbon sequestration is essential for evaluating changes in the carbon cycle due to global climate change. In a recent assessment of 26 carbon assimilation models at 39 FLUXNET tower sites across the United States and Canada, all models failed to adequately compute...

  10. Urban vegetation cover extraction from hyperspectral imagery and geographic information system spatial analysis techniques: case of Athens, Greece

    NASA Astrophysics Data System (ADS)

    Petropoulos, George P.; Kalivas, Dionissios P.; Georgopoulou, Iro A.; Srivastava, Prashant K.

    2015-01-01

    The present study aimed at evaluating the performance of two different pixel-based classifiers [spectral angle mapper (SAM) and support vector machines (SVMs)] in discriminating different land-cover classes in a typical urban setting, focusing particularly on urban vegetation cover by utilizing hyperspectral (EO-1 Hyperion) data. As a case study, the city of Athens, Greece, was used. Validation of urban vegetation predictions was based on the error matrix statistics. Additionally, the final urban vegetation cover maps were compared at a municipality level against reference urban vegetation cover estimates derived from the digitization of very high-resolution imagery. To ensure consistency and comparability of the results, the same training and validation points dataset were used to compare the different classifiers. The results showed that SVMs outperformed SAM in terms of both classification and urban vegetation cover mapping with an overall accuracy of 86.53% and Kappa coefficient 0.823, whereas for SAM classification, the accuracy statistics obtained were 75.13% and 0.673, respectively. Our results confirmed the ability of both techniques, when combined with Hyperion imagery, to extract urban vegetation cover for the case of a densely populated city with complex urban features, such as Athens. Our findings offer significant information at the local scale as regards to the presence of open green spaces in the urban environment of Athens. Such information is vital for successful infrastructure development, urban landscape planning, and improvement of urban environment. More widely, this study also contributes significantly toward an objective assessment of Hyperion in detecting and mapping urban vegetation cover.

  11. NASA EO-1 Spacecraft Images Chile Volcanic Eruption

    NASA Image and Video Library

    2011-06-17

    On June 14, 2011, NASA Earth Observing-1 EO-1 spacecraft obtained this image showing ash-rich volcanic plume billowing out of the vent, punching through a low cloud layer. The plume grey color is a reflection of its ash content.

  12. EO-1 Advanced Land Imager Technology Validation Report

    DTIC Science & Technology

    2007-11-02

    the Advanced Land Imager is intersatellite comparison. The EO-1 spacecraft is orbiting the Earth in a constellation of four spacecraft: Landsat 7 (10...events was as follows. The launch vehicle was changed from the Taurus to Delta 2 (28 Jan. 97) increasing mass allocations. The Project Office traded

  13. Mission Operations of EO-1 with Onboard Autonomy

    NASA Technical Reports Server (NTRS)

    Tran, Daniel Q.

    2006-01-01

    Space mission operations are extremely labor and knowledge-intensive and are driven by the ground and flight systems. Inclusion of an autonomy capability can have dramatic effects on mission operations. We describe the prior, labor and knowledge intensive mission operations flow for the Earth Observing-1 (EO-1) spacecraft as well as the new autonomous operations as part of the Autonomous Sciencecraft Experiment.

  14. Mission Operations of EO-1 with Onboard Autonomy

    NASA Technical Reports Server (NTRS)

    Tran, Daniel Q.

    2006-01-01

    Space mission operations are extremely labor and knowledge-intensive and are driven by the ground and flight systems. Inclusion of an autonomy capability can have dramatic effects on mission operations. We describe the prior, labor and knowledge intensive mission operations flow for the Earth Observing-1 (EO-1) spacecraft as well as the new autonomous operations as part of the Autonomous Sciencecraft Experiment.

  15. Rough and Tumble Hyperion Movie

    NASA Image and Video Library

    2006-02-03

    The tumbling and irregularly shaped moon Hyperion rotates away from the Cassini spacecraft in this movie taken during a distant encounter in Dec. 2005. A shadow closes over the large crater at bottom as the movie progresses. Hyperion (280 kilometers, or 174 miles across) is covered with closely packed and deeply etched pits. The warming action of the Sun on water ice lying beneath a darkened layer of surface material apparently has deepened and exaggerated the depressions already created by impacts. Cassini scientists now think that Hyperion’s unusual appearance can be attributed to the fact that it has an unusually low density for such a large object, giving it weak surface gravity and high porosity. These characteristics help preserve the original shapes of Hyperion’s craters by limiting the amount of impact ejecta coating the moon’s surface. Impactors tend to make craters by compressing the surface material, rather than blasting it out. Further, Hyperion’s weak gravity, and correspondingly low escape velocity, means that what little ejecta is produced has a good chance of escaping the moon altogether. The images were taken in visible light with the Cassini spacecraft narrow-angle camera on Dec. 23, 2005 at distances ranging from 228,000 kilometers (142,000 miles) to 238,000 kilometers (148,000 miles) from Hyperion and at a Sun-Hyperion-spacecraft, or phase, angle ranging from 77 to 86 degrees. Resolution in the original images was about 1.4 kilometers (0.9 mile) per pixel. The images have been magnified by a factor of two and contrast-enhanced to aid visibility. An animation is available at http://photojournal.jpl.nasa.gov/catalog/PIA07683

  16. Bathymetry and bottom albedo retrieval using Hyperion: a case study of Thitu Island and reef

    NASA Astrophysics Data System (ADS)

    Liu, Zhen

    2013-11-01

    The Spratly (Nansha) Islands in the South China Sea have considerable economic and important militarily strategic status. Ocean color remote sensing is an effective mean of surveying and research and especially it is useful for areas that are difficult to access, such as Thitu Island and its reef in the Spratly Islands. The Hyper-spectral Optimization Process Exemplar (HOPE) model, developed by Lee et al. (1999) is a rapid and robust bathymetry method that uses hyper-spectral remote sensing. In this study, using Hyperion hyper-spectral sensor data and HOPE, we derive bathymetry and bottom albedo measurements around Thitu Island and its reef. We compare the distribution of bottom depths from C-MAP with that derived from the Hyperion data. The retrieved bathymetry results correlate well with the distribution obtained from the bathymetry contour from 2.0 to 20 m. The average difference between Hyperion and C-MAP for two selected transects was 17.1% ( n=59, R=0.848, RMSE=2.342) and 10.9% ( n=59, R 2=0.834, RMSE=0.463). The retrieved bottom albedo is homogeneous in the lagoon and significantly non-homogeneous around the lagoon. These results indicate that HOPE could be very useful for bathymetry studies for the islands of the South China Sea.

  17. Intelligent systems in space : the EO-1 Autonomous Sciencecraft

    NASA Technical Reports Server (NTRS)

    Sherwood, Robert L.; Chien, Steve; Tran, Daniel; Cichy, Benjamin; Castano, Rebecca; Davies, Ashley; Rabideau, Gregg

    2005-01-01

    The Autonomous Sciencecraft Software (ASE) is currently flying onboard the Earth Observing One (EO-1) Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and runtime robust execution. Because of the deployment to the EO-1 spacecraft, the ASE software has stringent constraints of autonomy and limited computing resources. We describe these constraints and how they are reflected in our operations approach. A summary of the final results of the experiment is also included. This software has demonstrated the potential for space missions to use onboard decision-making to detect, analyze, and respond to science events, and to downlink only the highest value science data. As a result, ground-based mission planning and analysis functions have been greatly simplified, thus reducing operations cost.

  18. Multicopy suppression of oxidant-sensitive eos1 mutation by IZH2 in Saccharomyces cerevisiae and the involvement of Eos1 in zinc homeostasis.

    PubMed

    Nakamura, Toshihide; Takahashi, Shunsuke; Takagi, Hiroshi; Shima, Jun

    2010-05-01

    EOS1 is required for tolerance to oxidative stress in Saccharomyces cerevisiae; mutants are defective in the gene sensitive to hydrogen peroxide and tolerant to tunicamycin. To clarify the function of Eos1, we screened yeast genomic DNA libraries for heterologous genes that, when overexpressed from a plasmid, can suppress the hydrogen peroxide-sensitive eos1 mutation. We identified one such gene, IZH2, which has previously been reported to be a Zap1-regulated gene. However, the EOS1 and IZH2 genes do not themselves appear to be functionally interchangeable. Double disruption of the EOS1 and IZH2 genes yielded a slow-growth phenotype, suggesting that the two proteins are involved in related cellular processes. DNA microarray analysis revealed decreased expression of Zap1-regulated genes in the eos1-deletion mutant (Deltaeos1). Thus, it is likely that Eos1 is involved in zinc homeostasis.

  19. Development of a PPT for the EO-1 Spacecraft

    NASA Technical Reports Server (NTRS)

    Benson, Scott W.; Arrington, Lynn A.; Hoskins, W. Andrew; Meckel, Nicole J.

    2000-01-01

    A Pulsed Plasma Thruster (PPT) has been developed for use in a technology demonstration flight experiment on the Earth Observing 1 (EO-1) New Millennium Program mission. The thruster replaces the spacecraft pitch axis momentum wheel for control and momentum management during an experiment of a minimum three-day duration. The EO-1 PPT configuration is a combination of new technology and design heritage from similar systems flown in the 1970's and 1980's. Acceptance testing of the protoflight unit has validated readiness for flight, and integration with the spacecraft, including initial combined testing, has been completed. The thruster provides a range of capability from 90 microN-sec impulse bit at 650 sec specific impulse for 12 W input power, through 860 microN-sec impulse bit at 1400 see specific impulse for 70 W input power. Development of this thruster reinitiates technology research and development and re-establishes an industry base for production of flight hardware. This paper reviews the EO-1 PPT development, including technology selection, design and fabrication, acceptance testing, and initial spacecraft integration and test.

  20. ASTER, ALI and Hyperion sensors data for lithological mapping and ore minerals exploration.

    PubMed

    Beiranvand Pour, Amin; Hashim, Mazlan

    2014-01-01

    This paper provides a review of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), and Hyperion data and applications of the data as a tool for ore minerals exploration, lithological and structural mapping. Spectral information extraction from ASTER, ALI, and Hyperion data has great ability to assist geologists in all disciplines to map the distribution and detect the rock units exposed at the earth's surface. The near coincidence of Earth Observing System (EOS)/Terra and Earth Observing One (EO-1) platforms allows acquiring ASTER, ALI, and Hyperion imagery of the same ground areas, resulting accurate information for geological mapping applications especially in the reconnaissance stages of hydrothermal copper and gold exploration, chromite, magnetite, massive sulfide and uranium ore deposits, mineral components of soils and structural interpretation at both regional and district scales. Shortwave length infrared and thermal infrared bands of ASTER have sufficient spectral resolution to map fundamental absorptions of hydroxyl mineral groups and silica and carbonate minerals for regional mapping purposes. Ferric-iron bearing minerals can be discriminated using six unique wavelength bands of ALI spanning the visible and near infrared. Hyperion visible and near infrared bands (0.4 to 1.0 μm) and shortwave infrared bands (0.9 to 2.5 μm) allowed to produce image maps of iron oxide minerals, hydroxyl-bearing minerals, sulfates and carbonates in association with hydrothermal alteration assemblages, respectively. The techniques and achievements reviewed in the present paper can further introduce the efficacy of ASTER, ALI, and Hyperion data for future mineral and lithological mapping and exploration of the porphyry copper, epithermal gold, chromite, magnetite, massive sulfide and uranium ore deposits especially in arid and semi-arid territory.

  1. Hyperspectral Imaging of River Systems

    DTIC Science & Technology

    2012-09-30

    derivatives, to target products --- sediment, chlorophyll, or sampled pixels know to contain pigments of interest, such as phycocyanin commonly found in...from 400 at 450 nm to 200 at 850 nm. The Hyperion SNR is approximately ¼ of the HICO SNR.] IMPACT/ APPLICATIONS The long term goal of this work...Tufillaro, M. Corson, B-C. Gao, and R. Lucke, 2012, “Hyperspectral Imager for the Coastal Ocean (HICO): overview and Coastal Ocean Applications

  2. The Fate of Ejecta from Hyperion

    NASA Technical Reports Server (NTRS)

    Lissauer, Jack J.; Dobrovolskis, Anthony R.; DeVincenzi, Donald (Technical Monitor)

    2002-01-01

    Ejecta from Saturn's moon Hyperion is subject to powerful perturbations from nearby Titan, which control its ultimate fate. We have performed numerical integrations to simulate a simplified system consisting of Saturn (including oblateness), Tethys, Dione, Titan, Hyperion, Iapetus, and the Sun (treated simply as a massive satellite). In addition, 1050 massless particles were ejected from Hyperion at five different points in its orbit. These particles started more or less evenly distributed over latitude and longitude, 1 km above Hyperion's mean radius, and were ejected radially outward at speeds 10\\% faster than its escape speed. Only about 4\\% of the particles survived for the 100,000-year course of the integration, while $\\sim$8/% escaped from the Saturnian system. Titan accreted $\\sim$77\\% of all the particles, while Hyperion reaccreted only $\\sim$5\\%. This may help to account for Hyperion's rugged shape. Three particles hit Rhea and 2 hit Dione, but $\\sim$5\\% of the particles were removed when they penetrated within 150,000 km of Saturn. Most removals occurred within the first few thousand years. In general, ejecta from Hyperion are much more widely scattered than previously thought, and cross the orbits of all of the other classical satellites.

  3. Retrieving vegetation cover types in the complex natural ecosystem of the Pollino National Park (South Italy) through Hyperion data

    NASA Astrophysics Data System (ADS)

    Fusilli, Lorenzo; Bassani, Cristiana; Pascucci, Simone; Pignatti, Stefano

    2007-10-01

    In this paper the potential of the Hyperion spaceborne hyperspectral data in discriminating land covers in complex natural ecosystems was evaluated according to the hierarchical structure of the European standard legend (CORINE Land Cover 2000). Furthermore, the ability of the Hyperion data in retrieving land cover information at sub-pixel level was assessed by exploiting the vegetation classes' distribution as obtained by aerial-photos. Four standard supervised classifiers have been compared in terms of algorithm performance and class accuracy by applying statistical metric; the best results were achieved with the Minimum Distance (MD) classifier. In those areas exhibiting mixed pixels at the Hyperion spatial resolution a Linear Spectral Unmixing technique was applied for deriving abundance fractions of the endmembers (i.e. land covers) previously identified. Accuracy of the un-mixing analysis was evaluated using a Residual Error index calculated by relating Hyperion fractional abundances and reference aerial-photos. Results show the capability of Hyperion data to map land covers and vegetation diversity even at sub-pixel level within a complex natural landscape.

  4. Satellite-based land use mapping: comparative analysis of Landsat-8, Advanced Land Imager, and big data Hyperion imagery

    NASA Astrophysics Data System (ADS)

    Pervez, Wasim; Uddin, Vali; Khan, Shoab Ahmad; Khan, Junaid Aziz

    2016-04-01

    Until recently, Landsat technology has suffered from low signal-to-noise ratio (SNR) and comparatively poor radiometric resolution, which resulted in limited application for inland water and land use/cover mapping. The new generation of Landsat, the Landsat Data Continuity Mission carrying the Operational Land Imager (OLI), has improved SNR and high radiometric resolution. This study evaluated the utility of orthoimagery from OLI in comparison with the Advanced Land Imager (ALI) and hyperspectral Hyperion (after preprocessing) with respect to spectral profiling of classes, land use/cover classification, classification accuracy assessment, classifier selection, study area selection, and other applications. For each data source, the support vector machine (SVM) model outperformed the spectral angle mapper (SAM) classifier in terms of class discrimination accuracy (i.e., water, built-up area, mixed forest, shrub, and bare soil). Using the SVM classifier, Hyperion hyperspectral orthoimagery achieved higher overall accuracy than OLI and ALI. However, OLI outperformed both hyperspectral Hyperion and multispectral ALI using the SAM classifier, and with the SVM classifier outperformed ALI in terms of overall accuracy and individual classes. The results show that the new generation of Landsat achieved higher accuracies in mapping compared with the previous Landsat multispectral satellite series.

  5. Quantitative analysis of alteration mineral content and characteristic spectra of Hyperion image at oil and gas microseepage area

    NASA Astrophysics Data System (ADS)

    Liu, Na; Chen, Xiaomei; Li, Qianqian

    2015-08-01

    With Sanhu region of Qaidam Basin as the test area and the mineral compositions and hyperspectral remote sensing images as test data, the present paper sets up the quantitative relationships between clay and carbonate of altered minerals caused by oil and gas microseepage and the characteristic parameters from hyperspectral remote sensing image. To get the quantitative relationships between these characteristic parameters and contents, the statistical regression method is used after the spectral characteristics extraction from Hyperion image. The research results show the contents of clay and carbonate have a high degree fitting with the depth of spectral absorption peak, while there are low correlations between other characteristic parameters and the contents. This conclusion provides references for using the hyperspectral remote sensing information to explore the oil and gas direct and lessening or even getting rid of the groundwork, and provides a statistical basis for inversing the surface mineral contents with the hyperspectral remote sensing image.

  6. Spectral matching in Hyperion images for improved characterization of Mangrove ecosystems in southern India

    NASA Astrophysics Data System (ADS)

    Padma, S.; Sanjeevi, S.

    2014-11-01

    Mangrove ecosystem study is one of the main beneficiaries of the application of hyperspectral data and spectral matching techniques. Diversity and density of mangrove species leads to complexity of the ecosystem. Hence, species level mapping becomes difficult. Though hyperspectral images are appropriate for such a mapping, different mangrove species with closely matching spectra pose a challenge. This paper proposes a novel hyperspectral matching algorithm by integrating the stochastic Jeffries-Matusita measure (JM) and deterministic Spectral Angle Mapper (SAM) to accurately map most species of the mangrove ecosystem. The JM-SAM algorithm signifies the combination of an quantitative angle measure (SAM) and an qualitative distance measure (JM). The spectral capabilities of both the measures are orthogonally projected using tangent and sine functions to result in the combined algorithm. The developed JM-SAM algorithm is implemented to discriminate the mangrove species and the landcover classes of Pichavaram and Muthupet mangrove forests of southern India using the Hyperion datasets. The developed algorithm is extended in a supervised framework for improved classification of the Hyperion image. The reference spectra of the mangrove species and other cover types are extracted from the Hyperion image. From the values of relative spectral discriminatory probability and relative discriminatory entropy value, it can be inferred that hybrid JM-SAM matching measure results in improved discriminability than the individual SAM and JM algorithms. This performance is reflected in the classification results where the JM-SAM (TAN) and JM-SAM (SIN) matching algorithms yielded an improved accuracy of (86.25%,85%) and (88.10%, 86.96) for both the study sites.

  7. Addressing EO-1 Spacecraft Pulsed Plasma Thruster EMI Concerns

    NASA Technical Reports Server (NTRS)

    Zakrzwski, C. M.; Davis, Mitch; Sarmiento, Charles; Bauer, Frank H. (Technical Monitor)

    2001-01-01

    The Pulsed Plasma Thruster (PPT) Experiment on the Earth Observing One (EO-1) spacecraft has been designed to demonstrate the capability of a new generation PPT to perform spacecraft attitude control. Results from PPT unit level radiated electromagnetic interference (EMI) tests led to concerns about potential interference problems with other spacecraft subsystems. Initial plans to address these concerns included firing the PPT at the spacecraft level both in atmosphere, with special ground support equipment. and in vacuum. During the spacecraft level tests, additional concerns where raised about potential harm to the Advanced Land Imager (ALI). The inadequacy of standard radiated emission test protocol to address pulsed electromagnetic discharges and the lack of resources required to perform compatibility tests between the PPT and an ALI test unit led to changes in the spacecraft level validation plan. An EMI shield box for the PPT was constructed and validated for spacecraft level ambient testing. Spacecraft level vacuum tests of the PPT were deleted. Implementation of the shield box allowed for successful spacecraft level testing of the PPT while eliminating any risk to the ALI. The ALI demonstration will precede the PPT demonstration to eliminate any possible risk of damage of ALI from PPT operation.

  8. Design and performance of the EO-1 Advanced Land Imager

    NASA Astrophysics Data System (ADS)

    Lencioni, Donald E.; Digenis, Constantine J.; Bicknell, William E.; Hearn, David R.; Mendenhall, Jeffrey A.

    1999-12-01

    An Advanced Land Imager (ALI) will be flown on the first Earth Observing mission (EO-1) under NASA's New Millennium Program (NMP). The ALI contains a number of key NMP technologies. These include a 15 degree wide field-of-view, push-broom instrument architecture with a 12.5 cm aperture diameter, compact multispectral detector arrays, non-cryogenic HgCdTe for the short wave infrared bands, silicon carbide optics, and a multi-level solar calibration technique. The focal plane contains multispectral and panchromatic (MS/Pan) detector arrays with a total of 10 spectral bands spanning the 0.4 to 2.5 micrometer wavelength region. Seven of these correspond to the heritage Landsat bands. The instantaneous fields of view of the detectors are 14.2 (mu) rad for the Pan band and 42.6 (mu) rad for the MS bands. The partially populated focal plane provides a 3 degree cross-track coverage corresponding to 37 km on the ground. The focal plane temperature is maintained at 220 K by means of a passive radiator. The instrument environmental and performance testing has been completed. Preliminary data analysis indicates excellent performance. This paper presents an overview of the instrument design, the calibration strategy, and results of the pre-flight performance measurements. It also discusses the potential impact of ALI technologies to future Landsat-like instruments.

  9. 16. LIGHTING AND PILLAR DETAIL VIEW ON HYPERION BOULEVARD VIADUCT ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    16. LIGHTING AND PILLAR DETAIL VIEW ON HYPERION BOULEVARD VIADUCT AT OVERCROSSING OF RIVERSIDE DRIVE. LOOKING NORTH. - Glendale-Hyperion Viaduct, Spanning Golden State Freeway (I-5) & Los Angeles River at Glendale Boulevard, Los Angeles, Los Angeles County, CA

  10. 9. NORTHSIDE OF HYPERION BOULEVARD VIADUCT OVERCROSSING OF LOS ANGELES ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    9. NORTHSIDE OF HYPERION BOULEVARD VIADUCT OVERCROSSING OF LOS ANGELES RIVER. LOOKING EAST/SOUTHEAST. HYPERION BOULEVARD OVERCROSSING OF LOS ANGELES RIVER IS UPPER SECTION OF VIADUCT. GLENDALE BOULEVARD IS LOWER SECTION OF RIVER OVERCROSSING. - Glendale-Hyperion Viaduct, Spanning Golden State Freeway (I-5) & Los Angeles River at Glendale Boulevard, Los Angeles, Los Angeles County, CA

  11. Surface Features Analysis in Salt-Affected Area Using Hyperspectral Data: A Case Study in the Zone of Chotts, Tunisia

    NASA Astrophysics Data System (ADS)

    Bouaziz, Moncef; Liesenberg, Veraldo; Bouaziz, Samir; Gloaguen, Richard

    2010-12-01

    Arid and semi-arid regions are most affected by Salinity. Chotts regions in southern Tunisia are such an area, where the excessive content of salt in the soil is a hard faced problem. Soil salinity in this area enforces several environmental problems such as limiting plant growth, reducing crop productivity, degrading soil quality and leads to accelerated rates rill and gully erosion . Remote sensing analysis by the mean of spectral analysis, geomorphologic aspect from digital elevation models and distribution of rainfall intensity from satellite data are used in this study to discern features and patterns of areas affected by salt. Correlation between these remote sensing indicators is made in order to assess the contribution of each indicator to identify the salt-affected area. The approach followed in this study was applied on Hyperspectral data from EO-1 Mission. Hyperion data are promoted due to their very high spectral resolution and wide enhanced spatial information. The present study highlighted the high correlation between the flat surfaces and the high content of salt in the soil (from soil salinity indices) on one hand and a low correlation between the high intensity of rainfall distribution and indicators of low salt content in the soil on the other hand.

  12. The Effectiveness of Hydrothermal Alteration Mapping based on Hyperspectral Data in Tropical Region

    NASA Astrophysics Data System (ADS)

    Muhammad, R. R. D.; Saepuloh, A.

    2016-09-01

    Hyperspectral remote sensing could be used to characterize targets at earth's surface based on their spectra. This capability is useful for mapping and characterizing the distribution of host rocks, alteration assemblages, and minerals. Contrary to the multispectral sensors, the hyperspectral identifies targets with high spectral resolution. The Wayang Windu Geothermal field in West Java, Indonesia was selected as the study area due to the existence of surface manifestation and dense vegetation environment. Therefore, the effectiveness of hyperspectral remote sensing in tropical region was targeted as the study objective. The Spectral Angle Mapper (SAM) method was used to detect the occurrence of clay minerals spatially from Hyperion data. The SAM references of reflectance spectra were obtained from field observation at altered materials. To calculate the effectiveness of hyperspectral data, we used multispectral data from Landsat-8. The comparison method was conducted by comparing the SAM's rule images from Hyperion and Landsat-8, resulting that hyperspectral was more accurate than multispectral data. Hyperion SAM's rule images showed lower value compared to Landsat-8, the significant number derived from using Hyperion was about 24% better. This inferred that the hyperspectral remote sensing is preferable for mineral mapping even though vegetation covered study area.

  13. Follow That Satellite: EO-1 Maneuvers Into Close Formation With Landsat-7

    NASA Technical Reports Server (NTRS)

    DeFazio, Robert L.; Owens, Skip; Good, Susan; Bauer, Frank H. (Technical Monitor)

    2001-01-01

    As the Landsat-7 (LS-7) spacecraft continued NASA's historic program of earth imaging begun over three decades ago, NASA launched the Earth Observing-1 (EO-1) spacecraft carrying examples of the next generation of LS instruments. The validation method for these instruments was to have EO-1 fly in a close formation behind LS-7 on the same World Reference System (WRS) path. From that formation hundreds of near-coincident images would be taken by each spacecraft and compared to evaluate improvements in the EO-1 instruments. This paper will address the mission analysis required to launch and maneuver EO-1 into the formation with LS-7 where instrument validation was to occur plus a summary of completing the formation acquisition. Each EO-1 launch opportunity that occurred on a different day of a LS-7 16-day repeat cycle required a separate and distinct maneuver profile.

  14. Successful Detection of Floods in Real Time Onboard EO1 Through NASA's ST6 Autonomous Sciencecraft Experiment (ASE)

    NASA Astrophysics Data System (ADS)

    Ip, F.; Dohm, J. M.; Baker, V. R.; Castano, R.; Cichy, B.; Chien, S.; Davies, A.; Doggett, T.; Greeley, R.

    2004-12-01

    For the first time, a spacecraft has the ability to autonomously detect and react to flood events. Flood detection and the investigation of flooding dynamics in real time from space have never been done before at least not until now. Part of the challenge for the hydrological community has been the difficulty of obtaining cloud-free scenes from orbit at sufficient temporal and spatial resolutions to accurately assess flooding. In addition, the large spatial extent of drainage networks coupled with the size of the data sets necessary to be downlinked from satellites add to the difficulty of monitoring flooding from space. Technology developed as part of the Autonomous Sciencecraft Experiment (ASE) creates the new capability to autonomously detect, assess, and react to dynamic events, thereby enabling the monitoring of transient processes such as flooding in real time. In addition to being able to autonomously process the imaged data onboard the spacecraft for the first time and search the data for specific spectral features, the ASE Science Team has developed and tested change detection algorithms for the Hyperion spectrometer on EO-1. For flood events, if a change is detected in the onboard processed image (i.e. an increase in the number of ¡wet¡" pixels relative to a baseline image where the system is in normal flow condition or relatively dry), the spacecraft is autonomously retasked to obtain additional scenes. For instance, in February 2004 a rare flooding of the Australian Diamantina River was captured by EO-1. In addition, in August during ASE onboard testing a Zambezi River scene in Central Africa was successfully triggered by the classifier to autonomously take another observation. Yet another successful trigger-response flooding test scenario of the Yellow River in China was captured by ASE on 8/18/04. These exciting results pave the way for future smart reconnaissance missions of transient processes on Earth and beyond. Acknowledgments: We are grateful

  15. Assessment of the Spectral Stability of Libya 4, Libya 1, and Mauritania 2 Sites Using Earth Observing One Hyperion

    NASA Technical Reports Server (NTRS)

    Choi, Taeyoung; Xiong, Xiaoxiong; Angal, Amit; Chander, Gyanesh; Qu, John J.

    2014-01-01

    The objective of this paper is to formulate a methodology to assess the spectral stability of the Libya 4, Libya 1, and Mauritania 2 pseudo-invariant calibration sites (PICS) using Earth Observing One (EO-1) Hyperion sensor. All the available Hyperion collections, downloaded from the Earth Explorer website, were utilized for the three PICS. In each site, a reference spectrum is selected at a specific day in the vicinity of the region of interest (ROI) defined by Committee on Earth Observation Satellites (CEOS). A series of ROIs are predefined in the along-track direction with 196 spectral top-of-atmosphere reflectance values in each ROI. Based on the reference ROI spectrum, the spectral stability of these ROIs is evaluated by average deviations (ADs) and spectral angle mapper (SAM) methods in the specific ranges of time and geo-spatial locations. Time and ROI location-dependent SAM and AD results are very stable within +/- 2 deg and +/-1.7% of 1sigma standard deviations. Consequently, the Libya 4, Mauritania 2, and Libya 1 CEOS selected PICS are spectrally stable targets within the time and spatial swath ranges of the Hyperion collections.

  16. Ecological site classification of semiarid rangelands: Synergistic use of Landsat and Hyperion imagery

    NASA Astrophysics Data System (ADS)

    Blanco, Paula D.; del Valle, Héctor F.; Bouza, Pablo J.; Metternicht, Graciela I.; Hardtke, Leonardo A.

    2014-06-01

    Ecological sites are the basic entity used in rangeland health assessment. This study evaluates the synergistic use of multi- and hyper-spectral satellite imagery for sub-pixel classification of ecological sites in semiarid rangelands. Hyperion and Landsat enhanced thematic mapper (ETM) data are included in a two-step procedure to mapping ecological sites in Patagonian rangelands of Argentina. Firstly, mixture tuned matched filtering and logistic regression analyses are used for Hyperion data processing to obtain ecological site probability images in the area covered by hyperspectral imagery. Secondly, artificial neural networks are applied to model the relationships between the spectral response patterns of Landsat and the probability images from Hyperion, and used to map ecological sites over the entire study area. Overall classification accuracy was 81% (kappa = 0.77) with relatively high accuracies for all ecological sites demonstrating that their spectral signatures are sufficiently distinct to be detectable. Better accuracies were obtained for shrub steppes with desert pavement (producer's and user's accuracies of 89% and 84%, respectively), and shrub-grass steppes associated to tertiary calcareous outcrops (producer's and user's accuracies of 100% and 86%, respectively), while poorer accuracies resulted for shrub-grass steppes on old alluvial plains (producer's and user's accuracies of 75% and 56%, respectively). Fuzzy maps of ecological sites as presented in this research can provide rangeland managers with a tool to stratify the landscape and organize ecological information for rangeland health assessment and monitoring, prioritizing and selecting appropriate management actions, and promoting the recovery of areas degraded in these environments.

  17. Spatial resolution enhancement of EO-1 ALI bands

    NASA Astrophysics Data System (ADS)

    Nikolakopoulos, Konstantinos G.

    2006-09-01

    spectral characteristics, they do not take into account the resolution ratio of the input images. Usually the spatial resolution of the panchromatic image is two (Landsat 7, Spot 1-4) or four times (Ikonos, Quickbird) better than the size of the multispectral images. This paper is an attempt to fuse high-resolution panchromatic and low-resolution multispectral bands of the EO-1 ALI sensor. ALI collects nine multispectral bands with 30m resolution and a panchromatic band with 3 times better resolution (10m). ALI has a panchromatic band narrower than the respective band of Landsat7. It has also two narrower bands in the spectral range of Landsat7 band 4. It has also an extra narrower band near the spectral range of Landsat7 band 1. In this study we compare the efficiency of seven fusion techniques and more especially the efficiency of Gram Schmidt, Modified IHS, PCA, Pansharp, Wavelet and LMM (Local Mean Matching) LMVM (Local Mean and Variance Matching) fusion techniques for the fusion of ALI data. Two ALI images collected over the same area have been used. In order to quantitatively measure the quality of the fused images we have made the following controls: Firstly, we have examined the optical qualitative result. Then, we examined the correlation between the original multispectral and the fused images and all the statistical parameters of the histograms of the various frequency bands. All the fusion techniques improve the resolution and the optical result. In contrary to the fusion of other data (ETM, Spot5, Ikonos and Quickbird) all the algorithms provoke small changes to the statistical parameters.

  18. Characterization of Permafrost Degradation and Plant Communities Using Hyperspectral Reflectance

    NASA Astrophysics Data System (ADS)

    Garnello, A.; Finnell, D.; Palace, M. W.; Wu, J.; Lepine, L. C.; Crill, P. M.; Varner, R. K.

    2014-12-01

    spp. (R2 .92), and Open Water (R2 .79). Results indicate the usefulness of hyperspectral measurements for estimating vegetative composition. Continued work will examine field spectrometer measurements with those from the EO-1 Hyperion sensor in an effort to scale-up permafrost degradation monitoring.

  19. Active Volcano Monitoring using a Space-based Hyperspectral Imager

    NASA Astrophysics Data System (ADS)

    Cipar, J. J.; Dunn, R.; Cooley, T.

    2010-12-01

    Active volcanoes occur on every continent, often in close proximity to heavily populated areas. While ground-based studies are essential for scientific research and disaster mitigation, remote sensing from space can provide rapid and continuous monitoring of active and potentially active volcanoes [Ramsey and Flynn, 2004]. In this paper, we report on hyperspectral measurements of Kilauea volcano, Hawaii. Hyperspectral images obtained by the US Air Force TacSat-3/ARTEMIS sensor [Lockwood et al, 2006] are used to obtain estimates of the surface temperatures for the volcano. ARTEMIS measures surface-reflected light in the visible, near-infrared, and short-wave infrared bands (VNIR-SWIR). The SWIR bands are known to be sensitive to thermal radiation [Green, 1996]. For example, images from the NASA Hyperion hyperspectral sensor have shown the extent of wildfires and active volcanoes [Young, 2009]. We employ the methodology described by Dennison et al, (2006) to obtain an estimate of the temperature of the active region of Kilauea. Both day and night-time images were used in the analysis. To improve the estimate, we aggregated neighboring pixels. The active rim of the lava lake is clearly discernable in the temperature image, with a measured temperature exceeding 1100o C. The temperature decreases markedly on the exterior of the summit crater. While a long-wave infrared (LWIR) sensor would be ideal for volcano monitoring, we have shown that the thermal state of an active volcano can be monitored using the SWIR channels of a reflective hyperspectral imager. References: Dennison, Philip E., Kraivut Charoensiri, Dar A. Roberts, Seth H. Peterson, and Robert O. Green (2006). Wildfire temperature and land cover modeling using hyperspectral data, Remote Sens. Environ., vol. 100, pp. 212-222. Green, R. O. (1996). Estimation of biomass fire temperature and areal extent from calibrated AVIRIS spectra, in Summaries of the 6th Annual JPL Airborne Earth Science Workshop, Pasadena, CA

  20. The radius and albedo of Hyperion

    NASA Technical Reports Server (NTRS)

    Cruikshank, D. P.

    1979-01-01

    A measurement of the 20-micron thermal flux from Hyperion is reported, and the radius and surface geometric albedo of this outer satellite of Saturn are computed by the photometric/radiometric method. A corrected and normalized 20-micron thermal flux of 0.033 + or - 0.012 Jy is determined. A radius of 112 + or - 15 km and a surface geometric albedo of 0.47 + or - 0.11 are obtained by assuming values of unity for the phase integral, emissivity, and bolometric/visual geometric-albedo ratio. The sensitivity of the photometric/radiometric method to the assumed values of the parameters involved is discussed, and the results are compared with similar studies of Triton. It is concluded that neither Hyperion nor Triton appears to have a geometric albedo in the lower end of the distribution of small bodies in the solar system.

  1. Progress of Icelandic Lava Flows Charted by NASA EO-1 Spacecraft

    NASA Image and Video Library

    2014-09-09

    On the night of Sept. 6, 2014 NASA Earth Observing 1 EO-1 spacecraft observed the ongoing eruption at Holuhraun, Iceland. Partially covered by clouds, this scene shows the extent of the lava flows that have been erupting.

  2. Hyperion 5113/GP Infrasound Sensor Evaluation.

    SciTech Connect

    Merchant, Bion J.

    2015-08-01

    Sandia National Laboratories has tested and evaluated an infrasound sensor, the 5113/GP manufactured by Hyperion. These infrasound sensors measure pressure output by a methodology developed by the University of Mississippi. The purpose of the infrasound sensor evaluation was to determine a measured sensitivity, transfer function, power, self-noise, dynamic range, and seismic sensitivity. These sensors are being evaluated prior to deployment by the U.S. Air Force.

  3. The Titan-Hyperion orbital resonance

    NASA Technical Reports Server (NTRS)

    Peale, S. J.

    1991-01-01

    Considerable effort was spent investigating the applicability of a Hamiltonian averaged over high frequency terms, where long period and secular terms up to second order in eccentricity were kept. The Hamiltonian that is given from the planar, elliptic, restricted three body problem applied to Titan-Hyperion, when the Kepler terms are also expanded to second order in small quantities and several conical transformations are carried out, is presented and discussed.

  4. Lead-bismuth eutectic technology for Hyperion reactor

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Kapernick, R. J.; McClure, P. R.; Trapp, T. J.

    2013-10-01

    A small lead-bismuth eutectic-cooled reactor concept (referred to as the Hyperion reactor concept) is being studied at Los Alamos National Laboratory and Hyperion Power Generation. In this report, a critical assessment of the lead-bismuth eutectic technology for Hyperion reactor is presented based on currently available knowledge. Included are: material compatibility, oxygen control, thermal hydraulics, polonium control. The key advances in the technology and their applications to Hyperion reactor design are analyzed. Also, the near future studies in main areas of the technology are recommended for meeting the design requirements.

  5. Evaluation and effect of various noise reduction techniques used before atmospheric correction of Hyperion data

    NASA Astrophysics Data System (ADS)

    Panda, Chinmaya; Kumar, Vinay; Pandey, Kamal; Jyothi, G.

    2016-04-01

    Remote sensing, in recent days, has seen the emergence of hyperspectral sensors as the helping aspect to numerous applications. Hyperspectral remote sensing often contains data with narrow spectral bandwidth (10nm) that enables the feature identification and distinction of spectral similar features. Hyperion L1R data consists of 242 bands and out of which some bands contain noise (a pattern reorganization that hinders information). After removal of these sensor errors like bad bands and dropped line error, atmospheric correction using Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) is carried out to get true ground reflectance. It was observed in the spectral reflectance curve of the obtained product is still affected with several noise and in order to remove this noise some corrections are required before atmospheric correction. In this study various noise reduction techniques like Minimum Noise Fraction (MNF), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) are implemented to observe their effect on sensor error removed Hyperion data before carrying out atmospheric correction. At first noise reduction techniques (MNF, PCA and ICA) are applied separately to the Hyperion sensor error corrected product and then inverse of (MNF, PCA and ICA) are carried out respectively. It was observed that applying atmospheric correction after applying MNF & inverse MNF was giving better spectral profiles of the features (i.e. with less noise). From the above spectral profiles we can conclude that the data which is atmospherically corrected after applying MNF & inverse MNF is giving better results i.e. the spectral profiles of vegetation, water, urban and coal field is smooth and less noisy in comparison with the spectral profiles obtained by directly applying atmospheric correction and the spectral profiles obtained by applying PCA & inverse PCA and ICA &inverse ICA. After applying PCA & inverse PCA and then atmospheric correction the

  6. MultiSpec—a tool for multispectral hyperspectral image data analysis

    NASA Astrophysics Data System (ADS)

    Biehl, Larry; Landgrebe, David

    2002-12-01

    MultiSpec is a multispectral image data analysis software application. It is intended to provide a fast, easy-to-use means for analysis of multispectral image data, such as that from the Landsat, SPOT, MODIS or IKONOS series of Earth observational satellites, hyperspectral data such as that from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) and EO-1 Hyperion satellite system or the data that will be produced by the next generation of Earth observational sensors. The primary purpose for the system was to make new, otherwise complex analysis tools available to the general Earth science community. It has also found use in displaying and analyzing many other types of non-space related digital imagery, such as medical image data and in K-12 and university level educational activities. MultiSpec has been implemented for both the Apple Macintosh ® and Microsoft Windows ® operating systems (OS). The effort was first begun on the Macintosh OS in 1988. The GLOBE ( http://www.globe.gov) program supported the development of a subset of MultiSpec for the Windows OS in 1995. Since then most (but not all) of the features in the Macintosh OS version have been ported to the Windows OS version. Although copyrighted, MultiSpec with its documentation is distributed without charge. The Macintosh and Windows versions and documentation on its use are available from the World Wide Web at URL: http://dynamo.ecn.purdue.edu/˜biehl/MultiSpec/ MultiSpec is copyrighted (1991-2001) by Purdue Research Foundation, West Lafayette, Indiana 47907.

  7. 15. LIGHTING DETAIL ON WAVERLY DRIVE OVERCROSSING HYPERION BOULEVARD. LAMPS ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    15. LIGHTING DETAIL ON WAVERLY DRIVE OVERCROSSING HYPERION BOULEVARD. LAMPS ALSO SEEN IN CA-272-13. LOOKING EAST/SOUTHEAST. - Glendale-Hyperion Viaduct, Spanning Golden State Freeway (I-5) & Los Angeles River at Glendale Boulevard, Los Angeles, Los Angeles County, CA

  8. Spectral Ratio Imaging with Hyperion Satellite Data for Geological Mapping

    NASA Technical Reports Server (NTRS)

    Vincent, Robert K.; Beck, Richard A.

    2005-01-01

    Since the advent of LANDSAT I in 1972, many different multispectral satellites have been orbited by the U.S. and other countries. These satellites have varied from 4 spectral bands in LANDSAT I to 14 spectral bands in the ASTER sensor aboard the TERRA space platform. Hyperion is a relatively new hyperspectral sensor with over 220 spectral bands. The huge increase in the number of spectral bands offers a substantial challenge to computers and analysts alike when it comes to the task of mapping features on the basis of chemical composition, especially if little or no ground truth is available beforehand from the area being mapped. One approach is the theoretical approach of the modeler, where all extraneous information (atmospheric attenuation, sensor electronic gain and offset, etc.) is subtracted off and divided out, and laboratory (or field) spectra of materials are used as training sets to map features in the scene of similar composition. This approach is very difficult to keep accurate because of variations in the atmosphere, solar illumination, and sensor electronic gain and offset that are not always perfectly recorded or accounted for. For instance, to apply laboratory or field spectra of materials as data sets from the theoretical approach, the header information of the files must reflect the correct, up-to-date sensor electronic gain and offset and the analyst must pick the exact atmospheric model that is appropriate for the day of data collection in order for classification procedures to accurately match pixels in the scene with the laboratory or field spectrum of a desired target on the basis of the hyperspectral data. The modeling process is so complex that it is difficult to tell when it is operating well or determine how to fix it when it is incorrect. Recently RSI has announced that the latest version of their ENVI software package is not performing atmospheric corrections correctly with the FLAASH atmospheric model. It took a long time to determine

  9. Hyperion 5113/A Infrasound Sensor Evaluation

    SciTech Connect

    Merchant, Bion John

    2015-09-01

    Sandia National Laboratories has tested and evaluated an infrasound sensor, the 5113/A manufactured by Hyperion. These infrasound sensors measure pressure output by a methodology developed by the University of Mississippi. The purpose of the infrasound sensor evaluation was to determine a measured sensitivity, transfer function, power, self-noise, and dynamic range. The 5113/A infrasound sensor is a new revision of the 5000 series intended to meet the infrasound application requirements for use in the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO).

  10. The hyperion particle-γ detector array

    DOE PAGES

    Hughes, R. O.; Burke, J. T.; Casperson, R. J.; ...

    2017-03-08

    Hyperion is a new high-efficiency charged-particle γ-ray detector array which consists of a segmented silicon telescope for charged-particle detection and up to fourteen high-purity germanium clover detectors for the detection of coincident γ rays. The array will be used in nuclear physics measurements and Stockpile Stewardship studies and replaces the STARLiTeR array. In conclusion, this article discusses the features of the array and presents data collected with the array in the commissioning experiment.

  11. The hyperion particle-γ detector array

    NASA Astrophysics Data System (ADS)

    Hughes, R. O.; Burke, J. T.; Casperson, R. J.; Ota, S.; Fisher, S.; Parker, J.; Beausang, C. W.; Dag, M.; Humby, P.; Koglin, J.; McCleskey, E.; McIntosh, A. B.; Saastamoinen, A.; Tamashiro, A. S.; Wilson, E.; Wu, T. C.

    2017-06-01

    Hyperion is a new high-efficiency charged-particle γ-ray detector array which consists of a segmented silicon telescope for charged-particle detection and up to fourteen high-purity germanium clover detectors for the detection of coincident γ rays. The array will be used in nuclear physics measurements and Stockpile Stewardship studies and replaces the STARLiTeR array. This article discusses the features of the array and presents data collected with the array in the commissioning experiment.

  12. Tree Canopy Characterization for EO-1 Reflective and Thermal Infrared Validation Studies: Rochester, New York

    NASA Technical Reports Server (NTRS)

    Ballard, Jerrell R., Jr.; Smith, James A.

    2002-01-01

    The tree canopy characterization presented herein provided ground and tree canopy data for different types of tree canopies in support of EO-1 reflective and thermal infrared validation studies. These characterization efforts during August and September of 2001 included stem and trunk location surveys, tree structure geometry measurements, meteorology, and leaf area index (LAI) measurements. Measurements were also collected on thermal and reflective spectral properties of leaves, tree bark, leaf litter, soil, and grass. The data presented in this report were used to generate synthetic reflective and thermal infrared scenes and images that were used for the EO-1 Validation Program. The data also were used to evaluate whether the EO-1 ALI reflective channels can be combined with the Landsat-7 ETM+ thermal infrared channel to estimate canopy temperature, and also test the effects of separating the thermal and reflective measurements in time resulting from satellite formation flying.

  13. SensorWeb Evolution Using the Earth Observing One (EO-1) Satellite as a Test Platform

    NASA Technical Reports Server (NTRS)

    Mandl, Daniel; Frye, Stuart; Cappelaere, Pat; Ly, Vuong; Handy, Matthew; Chien, Steve; Grossman, Robert; Tran, Daniel

    2012-01-01

    The Earth Observing One (EO-1) satellite was launched in November 2000 as a one year technology demonstration mission for a variety of space technologies. After the first year, in addition to collecting science data from its instruments, the EO-1 mission has been used as a testbed for a variety of technologies which provide various automation capabilities and which have been used as a pathfinder for the creation of SensorWebs. A SensorWeb is the integration of variety of space, airborne and ground sensors into a loosely coupled collaborative sensor system that automatically provides useful data products. Typically, a SensorWeb is comprised of heterogeneous sensors tied together with a messaging architecture and web services. This paper provides an overview of the various technologies that were tested and eventually folded into normal operations. As these technologies were folded in, the nature of operations transformed. The SensorWeb software enables easy connectivity for collaboration with sensors, but the side benefit is that it improved the EO-1 operational efficiency. This paper presents the various phases of EO-1 operation over the past 12 years and also presents operational efficiency gains demonstrated by some metrics.

  14. Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

    NASA Technical Reports Server (NTRS)

    Ross, Kenton W.; Russell, Jeffrey; Ryan, Robert E.

    2006-01-01

    The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion

  15. Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

    NASA Astrophysics Data System (ADS)

    Ross, K. W.; Ryan, R. E.; Russell, J.

    2006-12-01

    The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments--400 m versus 250 m--at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB® that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ("real") or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system's actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion data will be used

  16. Topological analysis of chaotic orbits: Revisiting Hyperion

    NASA Technical Reports Server (NTRS)

    Boyd, Patricia T.; Mindlin, Gabriel B.; Gilmore, Robert; Solari, Hernan G.

    1994-01-01

    There is emerging interest in the possibility of chaotic evolution in astrophysical systems. To mention just one example, recent well-sampled ground-based observations of the Saturian satellite Hyperion strongly suggest that it is exhibiting chaotic behavior. We present a general technique, the method of close returns, for the analysis of data from astronomical objects believed to be exhibiting chaotic motion. The method is based on the extraction of pieces of the evolution that exhibit nearly periodic behavior-episodes during which the object stays near in phase space to some unstable periodic orbit. Such orbits generally act as skeletal features, tracing the topological organization of the manifold on which the chaotic dynamics takes place. This method does not require data sets as lengthy as other nonlinear analysis techniques do and is therefore well suited to many astronomical observing programs. Well sampled data covering between twenty and forty characteristic periods of the system have been found to be sufficient for the application of this technique. Additional strengths of this method are its robustness in the presence of noise and the ability for a user to clearly distinguish between periodic, random, and chaotic behavior by inspection of the resulting two-dimensional image. As an example of its power, we analyze close returns in a numerically generated data set, based on a model for Hyperion extensively studied in the literature, corresponding to nightly observations of the satellite. We show that with a small data set, embedded unstable periodic orbits can be extracted and that these orbits can be responsible for nearly periodic behavior lasting a substantial fraction of the observing run.

  17. Infrared reflectance spectra of Hyperion, Titania, and Triton

    NASA Technical Reports Server (NTRS)

    Lebofsky, L. A.; Lebofsky, M. J.; Rieke, G. H.

    1981-01-01

    Medium-resolution infrared (1-2.5 microns; Delta-lambda/lambda = 0.05) photometry of Triton, Titania, and Hyperion and medium-resolution (1.5-2.4 microns; Delta-lambda/lambda not greater than 0.01) spectroscopy of Triton are presented. Hyperion and Titania have spectra roughly similar to the laboratory spectrum of water frost, while the spectrum of Triton is inconsistent with the spectra of frosts likely to be major surface constituents.

  18. Results of NASA's First Autonomous Formation Flying Experiment: Earth Observing-1 (EO-1)

    NASA Technical Reports Server (NTRS)

    Folta, David C.; Hawkins, Albin; Bauer, Frank H. (Technical Monitor)

    2001-01-01

    NASA's first autonomous formation flying mission completed its primary goal of demonstrating an advanced technology called enhanced formation flying. To enable this technology, the Guidance, Navigation, and Control center at the Goddard Space Flight Center (GSFC) implemented a universal 3-axis formation flying algorithm in an autonomous executive flight code onboard the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft. This paper describes the mathematical background of the autonomous formation flying algorithm and the onboard flight design and presents the validation results of this unique system. Results from functionality assessment through fully autonomous maneuver control are presented as comparisons between the onboard EO-1 operational autonomous control system called AutoCon(tm), its ground-based predecessor, and a standalone algorithm.

  19. Preliminary Results of NASA's First Autonomous Formation Flying Experiment: Earth Observing-1 (EO-1)

    NASA Technical Reports Server (NTRS)

    Folta, David; Hawkins, Albin

    2001-01-01

    NASA's first autonomous formation flying mission is completing a primary goal of demonstrating an advanced technology called enhanced formation flying. To enable this technology, the Guidance, Navigation, and Control center at the Goddard Space Flight Center has implemented an autonomous universal three-axis formation flying algorithm in executive flight code onboard the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft. This paper describes the mathematical background of the autonomous formation flying algorithm and the onboard design and presents the preliminary validation results of this unique system. Results from functionality assessment and autonomous maneuver control are presented as comparisons between the onboard EO-1 operational autonomous control system called AutoCon(tm), its ground-based predecessor, and a stand-alone algorithm.

  20. A geometric performance assessment of the EO-1 advanced land imager

    USGS Publications Warehouse

    Storey, J.C.; Choate, M.J.; Meyer, D.J.

    2004-01-01

    The Earth Observing 1 (EO-1) Advanced Land Imager (ALI) demonstrates technology applicable to a successor system to the Landsat Thematic Mapper series. A study of the geometric performance characteristics of the ALI was conducted under the auspices of the EO-1 Science Validation Team. This study evaluated ALI performance with respect to absolute pointing knowledge, focal plane sensor chip assembly alignment, and band-to-band registration for purposes of comparing this new technology to the heritage Landsat systems. On-orbit geometric calibration procedures were developed that allowed the generation of ALI geometrically corrected products that compare favorably with their Landsat 7 counterparts with respect to absolute geodetic accuracy, internal image geometry, and band registration.

  1. Results of NASA's First Autonomous Formation Flying Experiment: Earth Observing-1 (EO-1)

    NASA Technical Reports Server (NTRS)

    Folta, David; Hawkins, Albin; Bauer, Frank (Technical Monitor)

    2002-01-01

    NASA's first autonomous formation flying mission completed its primary goal of demonstrating an advanced technology called enhanced formation flying. To enable this technology, the Flight Dynamics Analysis Branch at the Goddard Space Flight Center implemented a universal 3-axis formation flying algorithm in an autonomous executive flight code onboard the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft. This paper describes the mathematical background of the autonomous formation flying algorithm, the onboard flight design and the validation results of this unique system. Results from fully autonomous maneuver control are presented as comparisons between the onboard EO-1 operational autonomous control system called AutoCon, its ground-based predecessor used in operations, and the original standalone algorithm. Maneuvers discussed encompass reactionary, routine formation maintenance, and inclination control. Orbital data is also examined to verify that all formation flying requirements were met.

  2. Results Of NASA's First Autonomous Formation Flying Experiment: Earth Observing-1 (EO-1)

    NASA Technical Reports Server (NTRS)

    Folta, David; Hawkins, Albin

    2002-01-01

    NASA's first autonomous formation flying mission completed its primary goal of demonstrating an advanced technology called Enhanced Formation Flying. To enable this technology, a team at the Goddard Space Flight Center implemented a universal 3-axis formation flying algorithm in an autonomous executive flight code onboard the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft. This paper describes the mathematical background of the autonomous formation flying algorithm, the onboard flight design and the validation results of this unique system. Results from fully autonomous maneuver control are presented as comparisons between the onboard EO-1 operational autonomous control system called AutoCon(trademark), its ground-based predecessor used in operations, and the original standalone algorithm. Maneuvers discussed encompass reactionary, routine formation maintenance, and inclination control. Orbital data is also examined to verify that all formation flying requirements were met.

  3. Results of NASA's First Autonomous Formation Flying Experiment: Earth Observing-1 (EO-1)

    NASA Technical Reports Server (NTRS)

    Folta, David; Hawkins, Albin; Bauer, Frank (Technical Monitor)

    2002-01-01

    NASA's first autonomous formation flying mission completed its primary goal of demonstrating an advanced technology called enhanced formation flying. To enable this technology, the Flight Dynamics Analysis Branch at the Goddard Space Flight Center implemented a universal 3-axis formation flying algorithm in an autonomous executive flight code onboard the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft. This paper describes the mathematical background of the autonomous formation flying algorithm, the onboard flight design and the validation results of this unique system. Results from fully autonomous maneuver control are presented as comparisons between the onboard EO-1 operational autonomous control system called AutoCon, its ground-based predecessor used in operations, and the original standalone algorithm. Maneuvers discussed encompass reactionary, routine formation maintenance, and inclination control. Orbital data is also examined to verify that all formation flying requirements were met.

  4. Results Of NASA's First Autonomous Formation Flying Experiment: Earth Observing-1 (EO-1)

    NASA Technical Reports Server (NTRS)

    Folta, David; Hawkins, Albin

    2002-01-01

    NASA's first autonomous formation flying mission completed its primary goal of demonstrating an advanced technology called Enhanced Formation Flying. To enable this technology, a team at the Goddard Space Flight Center implemented a universal 3-axis formation flying algorithm in an autonomous executive flight code onboard the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft. This paper describes the mathematical background of the autonomous formation flying algorithm, the onboard flight design and the validation results of this unique system. Results from fully autonomous maneuver control are presented as comparisons between the onboard EO-1 operational autonomous control system called AutoCon(trademark), its ground-based predecessor used in operations, and the original standalone algorithm. Maneuvers discussed encompass reactionary, routine formation maintenance, and inclination control. Orbital data is also examined to verify that all formation flying requirements were met.

  5. Integration and Test Flight Validation Plans for the Pulsed Plasma Thruster Experiment on EO- 1

    NASA Technical Reports Server (NTRS)

    Zakrzwski, Charles; Benson, Scott; Sanneman, Paul; Hoskins, Andy; Bauer, Frank H. (Technical Monitor)

    2002-01-01

    The Pulsed Plasma Thruster (PPT) Experiment on the Earth Observing One (EO-1) spacecraft has been designed to demonstrate the capability of a new generation PPT to perform spacecraft attitude control. The PPT is a small, self-contained pulsed electromagnetic propulsion system capable of delivering high specific impulse (900-1200 s), very small impulse bits (10-1000 uN-s) at low average power (less than 1 to 100 W). Teflon fuel is ablated and slightly ionized by means of a capacitative discharge. The discharge also generates electromagnetic fields that accelerate the plasma by means of the Lorentz Force. EO-1 has a single PPT that can produce thrust in either the positive or negative pitch direction. The flight validation has been designed to demonstrate of the ability of the PPT to provide precision pointing accuracy, response and stability, and confirmation of benign plume and EMI effects. This paper will document the success of the flight validation.

  6. Nicaragua Eruption Lava Threat Closely Monitored by NASA EO-1 Spacecraft

    NASA Image and Video Library

    2015-12-07

    Momotombo volcano, Nicaragua, began erupting on Dec. 1, 2015, after more than a century of inactivity. On Dec. 4, 2015, the Advanced Land Imager (ALI) on NASA's Earth Observing 1 (EO-1) spacecraft observed the new eruption. This image is created from infrared data, and shows the incandescent active vent at the summit of the volcano and lava flowing down the side of the volcano. These data are being examined by scientists to determine where lava will flow, allowing assessment of possible threats to local infrastructure. The EO-1 data were obtained at an altitude of 438 miles (705 kilometers) and at a resolution of 98 feet (30 meters) per pixel at different visible and infrared wavelengths. The ALI image is 23 miles (37 kilometers) wide. http://photojournal.jpl.nasa.gov/catalog/PIA20203

  7. Design of the EO-1 Pulsed Plasma Thruster Attitude Control Experiment

    NASA Technical Reports Server (NTRS)

    Zakrzwski, Charles; Sanneman, Paul; Hunt, Teresa; Blackman, Kathie; Bauer, Frank H. (Technical Monitor)

    2001-01-01

    The Pulsed Plasma Thruster (PPT) Experiment on the Earth Observing 1 (EO-1) spacecraft has been designed to demonstrate the capability of a new generation PPT to perform spacecraft attitude control. The PPT is a small, self-contained pulsed electromagnetic Propulsion system capable of delivering high specific impulse (900-1200 s), very small impulse bits (10-1000 micro N-s) at low average power (less than 1 to 100 W). EO-1 has a single PPT that can produce torque in either the positive or negative pitch direction. For the PPT in-flight experiment, the pitch reaction wheel will be replaced by the PPT during nominal EO-1 nadir pointing. A PPT specific proportional-integral-derivative (PID) control algorithm was developed for the experiment. High fidelity simulations of the spacecraft attitude control capability using the PPT were conducted. The simulations, which showed PPT control performance within acceptable mission limits, will be used as the benchmark for on-orbit performance. The flight validation will demonstrate the ability of the PPT to provide precision pointing resolution. response and stability as an attitude control actuator.

  8. Flora: A Proposed Hyperspectral Mission

    NASA Technical Reports Server (NTRS)

    Ungar, Stephen; Asner, Gregory; Green, Robert; Knox, Robert

    2006-01-01

    In early 2004, one of the authors (Stephen Ungar, NASA GSFC) presented a mission concept called "Spectrasat" at the AVIRIS Workshop in Pasadena, CA. This mission concept grew out of the lessons learned from the Earth Observing-One (EO-1) Hyperion Imaging Spectrometer and was structured to more effectively accomplish the types of studies conducted with Hyperion. The Spectrasat concept represented an evolution of the technologies and operation strategies employed on EO-I. The Spectrasat concept had been preceded by two community-based missions proposed by Susan Ustin, UC Davis and Robert Green, NASA JPL. As a result of community participation, starting at this AVIRIS Workshop, the Spectrasat proposal evolved into the Flora concept which now represents the combined visions of Gregory Asner (Carnegie Institute), Stephen Ungar, Robert Green and Robert Knox, NASA GSFC. Flora is a proposed imaging spectrometer mission, designed to address global carbon cycle science issues. This mission centers on measuring ecological disturbance for purposes of ascertaining changes in global carbon stocks and draws heavily on experience gained through AVIRIS airborne flights and Hyperion space born flights. The observing strategy exploits the improved ability of imaging spectrometers, as compared with multi-spectral observing systems, to identify vegetation functional groups, detect ecosystem response to disturbance and assess the related discovery. Flora will be placed in a sun synchronous orbit, with a 45 meter pixel size, a 90 km swath width and a 31 day repeat cycle. It covers the spectral range from 0.4 to 2.5 micrometers with a spectral sampling interval of 10 nm. These specifications meet the needs of the Flora science team under the leadership of Gregory Asner. Robert Green, has introduced a spectrometer design for Flora which is expected to have a SNR of 600: 1 in the VNIR and 450: 1 in the SWIR. The mission team at NASA GSFC is designing an Intelligent Payload Module (IPM

  9. Flora: A Proposed Hyperspectral Mission

    NASA Technical Reports Server (NTRS)

    Ungar, Stephen; Asner, Gregory; Green, Robert; Knox, Robert

    2006-01-01

    In early 2004, one of the authors (Stephen Ungar, NASA GSFC) presented a mission concept called "Spectrasat" at the AVIRIS Workshop in Pasadena, CA. This mission concept grew out of the lessons learned from the Earth Observing-One (EO-1) Hyperion Imaging Spectrometer and was structured to more effectively accomplish the types of studies conducted with Hyperion. The Spectrasat concept represented an evolution of the technologies and operation strategies employed on EO-I. The Spectrasat concept had been preceded by two community-based missions proposed by Susan Ustin, UC Davis and Robert Green, NASA JPL. As a result of community participation, starting at this AVIRIS Workshop, the Spectrasat proposal evolved into the Flora concept which now represents the combined visions of Gregory Asner (Carnegie Institute), Stephen Ungar, Robert Green and Robert Knox, NASA GSFC. Flora is a proposed imaging spectrometer mission, designed to address global carbon cycle science issues. This mission centers on measuring ecological disturbance for purposes of ascertaining changes in global carbon stocks and draws heavily on experience gained through AVIRIS airborne flights and Hyperion space born flights. The observing strategy exploits the improved ability of imaging spectrometers, as compared with multi-spectral observing systems, to identify vegetation functional groups, detect ecosystem response to disturbance and assess the related discovery. Flora will be placed in a sun synchronous orbit, with a 45 meter pixel size, a 90 km swath width and a 31 day repeat cycle. It covers the spectral range from 0.4 to 2.5 micrometers with a spectral sampling interval of 10 nm. These specifications meet the needs of the Flora science team under the leadership of Gregory Asner. Robert Green, has introduced a spectrometer design for Flora which is expected to have a SNR of 600: 1 in the VNIR and 450: 1 in the SWIR. The mission team at NASA GSFC is designing an Intelligent Payload Module (IPM

  10. Radiometric Characterization of Hyperspectral Imagers using Multispectral Sensors

    NASA Technical Reports Server (NTRS)

    McCorkel, Joel; Kurt, Thome; Leisso, Nathan; Anderson, Nikolaus; Czapla-Myers, Jeff

    2009-01-01

    The Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne and satellite based sensors. Often, ground-truth measurements at these test sites are not always successful due to weather and funding availability. Therefore, RSG has also automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor, This work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral a imagery. The work relies on the Moderate Resolution Imaging Spectroradiometer (M0DIS) as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of M0DlS. The results compare cross-calibration scenarios that differ in image acquisition coincidence, test site used for the calibration, and reference sensor. Cross-calibration results are presented that show agreement between the use of coincident and non-coincident image pairs within 2% in most brands as well as similar agreement between results that employ the different MODIS sensors as a reference.

  11. On-orbit test results from the EO-1 Advanced Land Imager

    NASA Astrophysics Data System (ADS)

    Evans, Jenifer B.; Digenis, Constantine J.; Gibbs, Margaret D.; Hearn, David R.; Lencioni, Donald E.; Mendenhall, Jeffrey A.; Welsh, Ralph D.

    2002-01-01

    The Advanced Land Imager (ALI) is the primary instrument flown on the first Earth Observing mission (EO-1), launched on November 21, 2000. It was developed under NASA's New Millennium Program (NMP). The NMP mission objective is to flight-validate advanced technologies that will enable dramatic improvements in performance, cost, mass, and schedule for future, Landsat-like, Earth Science Enterprise instruments. ALI contains a number of innovative features designed to achieve this objective. These include the basic instrument architecture which employs a push-broom data collection mode, a wide field of view optical design, compact multi-spectral detector arrays, non-cryogenic HgCdTe for the short wave infrared bands, silicon carbide optics, and a multi-level solar calibration technique. During the first ninety days on orbit, the instrument performance was evaluated by collecting several Earth scenes and comparing them to identical scenes obtained by Landsat7. In addition, various on-orbit calibration techniques were exercised. This paper will present an overview of the EO-1 mission activities during the first ninety days on-orbit, details of the ALI instrument performance and a comparison with the ground calibration measurements.

  12. NASA's Autonomous Formation Flying Technology Demonstration, Earth Observing-1(EO-1)

    NASA Technical Reports Server (NTRS)

    Folta, David; Bristow, John; Hawkins, Albin; Dell, Greg

    2002-01-01

    NASA's first autonomous formation flying mission, the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft, recently completed its principal goal of demonstrating advanced formation control technology. This paper provides an overview of the evolution of an onboard system that was developed originally as a ground mission planning and operations tool. We discuss the Goddard Space Flight Center s formation flying algorithm, the onboard flight design and its implementation, the interface and functionality of the onboard system, and the implementation of a Kalman filter based GPS data smoother. A number of safeguards that allow the incremental phasing in of autonomy and alleviate the potential for mission-impacting anomalies from the on- board autonomous system are discussed. A comparison of the maneuvers planned onboard using the EO-1 autonomous control system to those from the operational ground-based maneuver planning system is presented to quantify our success. The maneuvers discussed encompass reactionary and routine formation maintenance. Definitive orbital data is presented that verifies all formation flying requirements.

  13. Cross calibration of the Landsat-7 ETM+ and EO-1 ALI sensor

    USGS Publications Warehouse

    Chander, G.; Meyer, D.J.; Helder, D.L.

    2004-01-01

    As part of the Earth Observer 1 (EO-1) Mission, the Advanced Land Imager (ALI) demonstrates a potential technological direction for Landsat Data Continuity Missions. To evaluate ALI's capabilities in this role, a cross-calibration methodology has been developed using image pairs from the Landsat-7 (L7) Enhanced Thematic Mapper Plus (ETM+) and EO-1 (ALI) to verify the radiometric calibration of ALI with respect to the well-calibrated L7 ETM+ sensor. Results have been obtained using two different approaches. The first approach involves calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors. The second approach uses vicarious calibration techniques to compare the predicted top-of-atmosphere radiance derived from ground reference data collected during the overpass to the measured radiance obtained from the sensor. The results indicate that the relative sensor chip assemblies gains agree with the ETM+ visible and near-infrared bands to within 2% and the shortwave infrared bands to within 4%.

  14. On-Orbit Testing of the EO-1 Pulsed Plasma Thruster

    NASA Technical Reports Server (NTRS)

    Zakrzwski, Charles; Benson, Scott; Sanneman, Paul; Hoskins, Andrew

    2002-01-01

    The Pulsed Plasma Thruster (PPT) Experiment on the Earth Observing 1 (EO-1) spacecraft has demonstrated the capability of a new generation PPT to perform spacecraft attitude control. The PPT is a small, self-contained pulsed electromagnetic propulsion system capable of delivering high specific impulse (900-1200 s) and very small impulse bits (10-1000 microN-s) at low average power (4 to 100 W). EO-1 has a single PPT that can produce torque in the positive or negative pitch direction and replace the function of the spacecraft s pitch reaction wheel. The flight validation experiment was designed to demonstrate the ability of the PPT to provide precision pointing accuracy, response and stability, and to confirm that the thruster plume and EMI effects on the spacecraft and instruments were benign. The PPT has been successfully used for pitch attitude control accumulating over 26 hours of operational time with over 96,000 pulses. Thruster performance has been nominal and all spacecraft subsystems and instruments continue to show no detrimental effects from PPT operation.

  15. Evolving EO-1 Sensor Web Testbed Capabilities in Pursuit of GEOSS

    NASA Technical Reports Server (NTRS)

    Mandi, Dan; Ly, Vuong; Frye, Stuart; Younis, Mohamed

    2006-01-01

    A viewgraph presentation to evolve sensor web capabilities in pursuit of capabilities to support Global Earth Observing System of Systems (GEOSS) is shown. The topics include: 1) Vision to Enable Sensor Webs with "Hot Spots"; 2) Vision Extended for Communication/Control Architecture for Missions to Mars; 3) Key Capabilities Implemented to Enable EO-1 Sensor Webs; 4) One of Three Experiments Conducted by UMBC Undergraduate Class 12-14-05 (1 - 3); 5) Closer Look at our Mini-Rovers and Simulated Mars Landscae at GSFC; 6) Beginning to Implement Experiments with Standards-Vision for Integrated Sensor Web Environment; 7) Goddard Mission Services Evolution Center (GMSEC); 8) GMSEC Component Catalog; 9) Core Flight System (CFS) and Extension for GMSEC for Flight SW; 10) Sensor Modeling Language; 11) Seamless Ground to Space Integrated Message Bus Demonstration (completed December 2005); 12) Other Experiments in Queue; 13) Acknowledgements; and 14) References.

  16. The Hyperion Project: Partnership for an Advaned Technology Cluster Testbed

    SciTech Connect

    Seager, M; Leininger, M

    2008-04-28

    The Hyperion project offers a unique opportunity to participate in a community-driven testing and development resource at a scale beyond what can be accomplished by one entity alone. Hyperion is a new strategic technology partnership intended to support the member-driven development and testing at scale. This partnership will allow commodity clusters to scale up to meet the growing demands of customers multi-core petascale simulation environments. Hyperion will tightly couple together the outstanding research and development capabilities of Lawrence Livermore National Laboratory with leading technology companies, including Cisco, Data Direct Networks, Dell, Intel, LSI, Mellanox, Qlogic, RedHat, SuperMicro and Sun. The end goal of this project is to revolutionize cluster computing in fundamental ways by providing the critical software and hardware components for a highly scalable simulation environment. This environment will include support for high performance networking, parallel file systems, operating system, and cluster management. This goal will be achieved by building a scalable technology cluster testbed that will be fully dedicated to the partners and provide: (1) A scalable development testing and benchmarking environment for critical enabling Linux cluster technologies; (2) An evaluation testbed for new hardware and software technologies; and (3) A vehicle for forming long term collaborations.

  17. Particle-gamma studies with the new Hyperion array

    NASA Astrophysics Data System (ADS)

    Hughes, R. O.; Burke, J. T.; Fisher, S.; Parker, J.; Ota, S.; Ting, A.; Casperson, R. J.; McCleskey, E.; McIntosh, A. B.; Beausang, C. W.; Wilson, E.; Humby, P.

    2015-10-01

    Hyperion is a charged-particle and γ-ray spectroscopy array for low energy nuclear physics studies consisting of a highly segmented silicon telescope for charged particle detection surrounded by up to 14 HPGe ``clover'' γ-ray detectors. Hyperion was designed and built between March 2014 and May 2015 as a significant upgrade to the existing STARLiTeR array currently at Texas A&M University Cyclotron Institute. The array was installed in May 2015 in preparation for its commissioning runs scheduled for September 2015. Hyperion will offer high particle-gamma and particle-gamma-gamma detection efficiencies and is intended to be used both for low energy structure studies and indirect measurements of neutron cross sections via the surrogate method. Details of the new array and the commissioning experiment focusing on 167 , 168 , 169Tm studies will be presented. This work was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344. Supported by DoE grant numbers DE-FG52-09NA29467 (TAMU), DE-NA0001801, DE-FG02-05ER41379 (UofR).

  18. Carbon-Carbon Composite Radiator Development for the EO-1 Spacecraft

    NASA Technical Reports Server (NTRS)

    Vaughn, Wallace; Shinn, Elizabeth; Rawal, Suraj; Wright, Joe

    2004-01-01

    The Carbon-Carbon Space Radiator Partnership (CSRP), an informal partnership of Government and industrial personnel, was formed to promote the use of Carbon-carbon composites (C-C) as engineering materials for spacecraft thermal management applications . As a part of this effort the partnership has built a structural radiator for the Earth Orbiter - 1 (EO-1) spacecraft. This radiator, using C-C face-sheets with an aluminum honeycomb core, will demonstrate both the thermal and structural properties of C-C under actual service conditions as well as provide performance data from space flight. This paper will present results from the design of the radiator, the thermal/mechanical tests of the facesheet materials, and sub-component test results on the C-C/Al honeycomb sandwich material. The 29- by 28-inch radiator was designed to support two electronics boxes with a combined heat output of 60 watts maximum and a weight of 58 lbs. The analysis of the radiator design shows that the radiator constructed with 20-mil-thick facesheets of a P30-fiber-reinforced C-C from BFGoodrich is able to meet or exceed all the required thermal and mechanical requirements.

  19. Radiometric calibration stability of the EO-1 advanced land imager: 5 years on-orbit

    USGS Publications Warehouse

    Markham, B.L.; Ong, L.; Barsi, J.A.; Mendenhall, J.A.; Lencioni, D.E.; Helder, D.L.; Hollaren, D.M.; Morfitt, R.

    2006-01-01

    The Advanced Land Imager (ALI) was developed as a prototype sensor for follow on missions to Landsat-7. It was launched in November 2000 on the Earth Observing One (EO-1) satellite as a nominal one-year technology demonstration mission. As of this writing, the sensor has continued to operate in excess of 5 years. Six of the ALl's nine multi-spectral (MS) bands and the panchromatic band have similar spectral coverage as those on the Landsat-7 ETM+. In addition to on-board lamps, which have been significantly more stable than the lamps on ETM+, the ALI has a solar diffuser and has imaged the moon monthly since launch. This combined calibration dataset allows understanding of the radiometric stability of the ALI system, its calibrators and some differentiation of the sources of the changes with time. The solar dataset is limited as the mechanism controlling the aperture to the solar diffuser failed approximately 18 months after launch. Results over 5 years indicate that: the shortest wavelength band (443 nm) has degraded in response about 2%; the 482 nm and 565 nm bands decreased in response about 1%; the 660 nm, 790 nm and 868 nm bands each degraded about 5%; the 1250 nm and 1650 nm bands did not change significantly and the 2215 nm band increased in response about 2%.

  20. Enhanced Formation Flying for the Earth Observing-1 (EO-1) New Millennium Mission

    NASA Technical Reports Server (NTRS)

    Folta, David; Quinn, David

    1997-01-01

    With scientific objectives for Earth observation programs becoming more ambitious and spacecraft becoming more autonomous, the need for new technical approaches on the feasibility of achieving and maintaining formations of spacecraft has come to the forefront. The trend to develop small low cost spacecraft has led many scientists to recognize the advantage of flying several spacecraft in formation, an example of which is shown in the figure below, to achieve the correlated instrument measurements formerly possible only by flying many instruments on a single large platform. Yet, formation flying imposes additional complications on orbit maintenance, especially when each spacecraft has its own orbit requirements. However, advances in automation proposed by GSFC Codes 550 and 712 allow more of the burden in maneuver planning and execution to be placed onboard the spacecraft, mitigating some of the associated operational concerns. The purpose of this analysis is to develop the fundamentals of formation flying mechanics, concepts for understanding the relative motion of free flying spacecraft, and an operational control theory for formation maintenance of the Earth Observing-1 (EO-l) spacecraft that is part of the New Millennium. Results of this development can be used to determine the appropriateness of formation flying for a particular case as well as the operational impacts. Applications to the Mission to Planet Earth (MTPE) Earth Observing System (EOS) and New Millennium (NM) were highly considered in analysis and applications. This paper presents the proposed methods for the guidance and control of the EO-1 spacecraft to formation fly with the Landsat-7 spacecraft using an autonomous closed loop three axis navigation control, GPS, and Cross link navigation support. Simulation results using various fidelity levels of modeling, algorithms developed and implemented in MATLAB, and autonomous 'fuzzy logic' control using AutoCon will be presented. The results of these

  1. Hyperspectral analysis of clay minerals

    NASA Astrophysics Data System (ADS)

    Janaki Rama Suresh, G.; Sreenivas, K.; Sivasamy, R.

    2014-11-01

    A study was carried out by collecting soil samples from parts of Gwalior and Shivpuri district, Madhya Pradesh in order to assess the dominant clay mineral of these soils using hyperspectral data, as 0.4 to 2.5 μm spectral range provides abundant and unique information about many important earth-surface minerals. Understanding the spectral response along with the soil chemical properties can provide important clues for retrieval of mineralogical soil properties. The soil samples were collected based on stratified random sampling approach and dominant clay minerals were identified through XRD analysis. The absorption feature parameters like depth, width, area and asymmetry of the absorption peaks were derived from spectral profile of soil samples through DISPEC tool. The derived absorption feature parameters were used as inputs for modelling the dominant soil clay mineral present in the unknown samples using Random forest approach which resulted in kappa accuracy of 0.795. Besides, an attempt was made to classify the Hyperion data using Spectral Angle Mapper (SAM) algorithm with an overall accuracy of 68.43 %. Results showed that kaolinite was the dominant mineral present in the soils followed by montmorillonite in the study area.

  2. Retrieval of chlorophyll in Hangzhou Bay based on hyperspectral satellite

    NASA Astrophysics Data System (ADS)

    Zhu, Qiankun; Huang, Haiqing; Mao, Feng; Hu, Qiliang; Cheng, Qian

    2016-10-01

    Chlorophyll concentration is one of the important parameters of water quality assessment, and the quantitative retrieval of chlorophyll concentration and its distribution is one of the main applications of remote sensing in the coastal waters. Because of its unique geographical position and economic value, Hangzhou Bay has a very important research significance. By hyperspectral remote sensing technology effectively overcomes the effect of turbid coastal for chlorophyll concentration estimates, the researchers by accurate measurement of chlorophyll spectral characteristics of chlorophyll concentration for quantitative retrieval possible. The Hyperion hyperspectral imager for Hangzhou Bay estuary area of chlorophyll remote sensing monitoring data were chlorophyll a concentration in remote sensing inversion model is constructed, and combined with pretreated Hyperion high image data inversion of regional chlorophyll a concentration, and then analyzes the uneven distribution of Hangzhou Bay Estuary chlorophyll content space, near the Yangtze River Estuary and Hangzhou Bay estuarine research area of chlorophyll concentration is lower than that far from the coast in the study area, and the conclusion of regional autumn average CHL concentration is higher than in winter.

  3. [Estimation of canopy chlorophyll content using hyperspectral data].

    PubMed

    Dong, Jing-Jing; Wang, Li; Niu, Zheng

    2009-11-01

    Many researches have developed models to estimate chlorophyl content at leaf and canopy level, but they were species-specific. The objective of the present paper was to develop a new model. First, canopy reflectance was simulated for different species and different canopy architecture using radiative transfer models. Based on the simulated canopy reflectance, the relationship between canopy reflectance and canopy chlorophyll content was studied, and then a chlorophyll estimation model was built using the method of spectral index. The coefficient of determination (R2) between spectral index based model and canopy chlorophyll content reached 0.75 for simulated data. To investigate the applicability of this chlorophyll model, the authors chose a field sample area in Gansu Province to carry out the measurement of leaf chlorophyll content, canopy reflectance and other parameters. Besides, the authors also ordered the synchronous Hyperion data, a hyperspectral image with a spatial resolution of 30 m. Canopy reflectance from field measurment and reflectance from Hyperion image were respectively used as the input parameter for the chlorophyll estimation model. Both of them got good results, which indicated that the model could be used for accurate canopy chlorophyll estimation using canopy reflectance. However, while using spaceborne hyperspectral data to estimate canopy chlorophyll content, good atmospheric correction is required.

  4. [Hyperspectral image classification based on 3-D gabor filter and support vector machines].

    PubMed

    Feng, Xiao; Xiao, Peng-feng; Li, Qi; Liu, Xiao-xi; Wu, Xiao-cui

    2014-08-01

    A three-dimensional Gabor filter was developed for classification of hyperspectral remote sensing image. This method is based on the characteristics of hyperspectral image and the principle of texture extraction with 2-D Gabor filters. Three-dimensional Gabor filter is able to filter all the bands of hyperspectral image simultaneously, capturing the specific responses in different scales, orientations, and spectral-dependent properties from enormous image information, which greatly reduces the time consumption in hyperspectral image texture extraction, and solve the overlay difficulties of filtered spectrums. Using the designed three-dimensional Gabor filters in different scales and orientations, Hyperion image which covers the typical area of Qi Lian Mountain was processed with full bands to get 26 Gabor texture features and the spatial differences of Gabor feature textures corresponding to each land types were analyzed. On the basis of automatic subspace separation, the dimensions of the hyperspectral image were reduced by band index (BI) method which provides different band combinations for classification in order to search for the optimal magnitude of dimension reduction. Adding three-dimensional Gabor texture features successively according to its discrimination to the given land types, supervised classification was carried out with the classifier support vector machines (SVM). It is shown that the method using three-dimensional Gabor texture features and BI band selection based on automatic subspace separation for hyperspectral image classification can not only reduce dimensions; but also improve the classification accuracy and efficiency of hyperspectral image.

  5. Lunar and Planetary Science XXXV: Image Processing and Earth Observations

    NASA Technical Reports Server (NTRS)

    2004-01-01

    The titles in this section include: 1) Expansion in Geographic Information Services for PIGWAD; 2) Modernization of the Integrated Software for Imagers and Spectrometers; 3) Science-based Region-of-Interest Image Compression; 4) Topographic Analysis with a Stereo Matching Tool Kit; 5) Central Avra Valley Storage and Recovery Project (CAVSARP) Site, Tucson, Arizona: Floodwater and Soil Moisture Investigations with Extraterrestrial Applications; 6) ASE Floodwater Classifier Development for EO-1 HYPERION Imagery; 7) Autonomous Sciencecraft Experiment (ASE) Operations on EO-1 in 2004; 8) Autonomous Vegetation Cover Scene Classification of EO-1 Hyperion Hyperspectral Data; 9) Long-Term Continental Areal Reduction Produced by Tectonic Processes.

  6. Lunar and Planetary Science XXXV: Image Processing and Earth Observations

    NASA Technical Reports Server (NTRS)

    2004-01-01

    The titles in this section include: 1) Expansion in Geographic Information Services for PIGWAD; 2) Modernization of the Integrated Software for Imagers and Spectrometers; 3) Science-based Region-of-Interest Image Compression; 4) Topographic Analysis with a Stereo Matching Tool Kit; 5) Central Avra Valley Storage and Recovery Project (CAVSARP) Site, Tucson, Arizona: Floodwater and Soil Moisture Investigations with Extraterrestrial Applications; 6) ASE Floodwater Classifier Development for EO-1 HYPERION Imagery; 7) Autonomous Sciencecraft Experiment (ASE) Operations on EO-1 in 2004; 8) Autonomous Vegetation Cover Scene Classification of EO-1 Hyperion Hyperspectral Data; 9) Long-Term Continental Areal Reduction Produced by Tectonic Processes.

  7. The Uranian satellites and Hyperion - New spectrophotometry and compositional implications

    NASA Technical Reports Server (NTRS)

    Brown, R. H.

    1983-01-01

    New reflectance spectra at 3.5 percent resolution have been obtained for Ariel, Titania, Oberon, and Hyperion in the 0.8 to 1.6-micron spectrum region. The new spectra show no absorptions other than the 1.5 micron water-ice feature (within the precision of the data), and demonstrate extension into the 0.8- to 1.6 micron region of the 1.5- to 2.5 micron spectral similarity ofo Ariel to Hyperion (Brown and Cruikshank, 1983). The new data confirm the presence of a dark, spectrally bland component on/in the water-ice surfaces of the Uranian satellites, which, with some reservations, has spectral similarities to the dark substance on the leading side of lapetus and the dark material on/in the surface of Hyperion, as well as other dark, spectrally neutral substances such as charcoal. Attempts were made to match the spectra of Ariel, Titania, and Oberon with additive reflectance mixes (aeral coverage) of fine-grained water frost and various dark components such as charcoal, lampblack, and charcoal-water-ice mixtures. The results were broad limits on the amounts of possible areal coverage of a charcoal-like spectral component on the surfaces of the Uranian satellites, but the data are not of sufficient precision to conclusively determine whether the dominant mode of contaminant dispersal is areal or voluminal. The effect of highly variegated albedos on the diameters derived by Brown, Cruikshank, and Morrison (1982) is found to be small.

  8. Hydrocarbons on Phoebe, Iapetus, and Hyperion: Quantitative Analysis

    NASA Technical Reports Server (NTRS)

    Cruikshank, Dale P.; MoreauDalleOre, Cristina; Pendleton, Yvonne J.; Clark, Roger Nelson

    2012-01-01

    We present a quantitative analysis of the hydrocarbon spectral bands measured on three of Saturn's satellites, Phoebe, Iaperus, and Hyperion. These bands, measured with the Cassini Visible-Infrared Mapping Spectrometer on close fly-by's of these satellites, are the C-H stretching modes of aromatic hydrocarbons at approximately 3.28 micrometers (approximately 3050 per centimeter), and the are four blended bands of aliphatic -CH2- and -CH3 in the range approximately 3.36-3.52 micrometers (approximately 2980- 2840 per centimeter) bably indicating the presence of polycyclic aromatic hydrocarbons (PAH), is unusually strong in comparison to the aliphatic bands, resulting in a unique signarure among Solar System bodies measured so far, and as such offers a means of comparison among the three satellites. The ratio of the C-H bands in aromatic molecules to those in aliphatic molecules in the surface materials of Phoebe, NAro:NAliph approximately 24; for Hyperion the value is approximately 12, while laperus shows an intermediate value. In view of the trend of the evolution (dehydrogenation by heat and radiation) of aliphatic complexes toward more compact molecules and eventually to aromatics, the relative abundances of aliphatic -CH2- and -CH3- is an indication of the lengths of the molecular chain structures, hence the degree of modification of the original material. We derive CH2:CH3 approximately 2.2 in the spectrum of low-albedo material on laperus; this value is the same within measurement errors to the ratio in the diffuse interstellar medium. The similarity in the spectral signatures of the three satellites, plus the apparent weak trend of aromatic/aliphatic abundance from Phoebe to Hyperion, is consistent with, and effectively confirms that the source of the hydrocarbon-bearing material is Phoebe, and that the appearance of that material on the other two satellites arises from the deposition of the inward-spiraling dust that populates the Phoebe ring.

  9. Hyperion and its Cousins: Sponges, Landslides, Layers, and Ridges

    NASA Astrophysics Data System (ADS)

    Thomas, P. C.

    2007-12-01

    Cassini's exploration of the Saturn system has given detailed views of small, irregularly-shaped satellites from ~10 to 135 km-mean radius that orbit within the rings to Phoebe nearly 100 times further from Saturn. The spongy appearance of Hyperion, reflecting a high density of well-preserved 2-10 km craters, may derive from a combination of effects of low porosity and Hyperion's size on the generation of impact crater ejecta. Smaller, porous moons in the Saturn system do not show similar effects with available data. Low gravity is not a deterrent to downlsope processes: these dominate the surface of Telesto which is essentially self-buried in debris. Ring- related satellite Atlas and (probably Pan) shows a distinct two-component surface that may represent different stages of accretion. These satellites, and other ring-related ones are shaped such that parts of their surfaces have almost zero escape velocity and thus may retard further accretion, leaving them in balance with hyper velocity impact effects. Phoebe is distinct from the more icy inner satellites, with higher density, probably much lower porosity, and some layering of icy and rocky components. Comparison to recent data on comets and small asteroids suggests much remains to be learned regarding crater formation and removal on low-gravity objects.

  10. Hyperspectral image processing methods

    USDA-ARS?s Scientific Manuscript database

    Hyperspectral image processing refers to the use of computer algorithms to extract, store and manipulate both spatial and spectral information contained in hyperspectral images across the visible and near-infrared portion of the electromagnetic spectrum. A typical hyperspectral image processing work...

  11. Water Quality Measurements from Hyperspectral Remote Sensing: The Case of the River Ganga

    NASA Astrophysics Data System (ADS)

    Baruch, A.; Carbonneau, P.; Sinha, R.; Scott, S.

    2014-12-01

    Water pollution is a major challenge in large river systems such as the Ganga (i.e. Ganges). With a population of 400 million, widespread agriculture and a heavy industrial base, this river basin is facing multiple stressors and as a result, is now notorious for poor water quality. One of the key issues in addressing this problem remains basic water quality monitoring with systematic and reliable methods. Currently, water quality datasets in the River Ganga are highly fragmented and inadequate for most investigations. Given the sub-continental scale of the system, remote sensing could offer a plausible solution if capable of producing holistic assessments of water quality with a standardised methodology. Specifically, the development of hyperspectral remote sensing, capable of detecting very small changes in incident radiation, offers the potential to mimic laboratory spectroscopy and thus identify the chemicals polluting a body of water, and perhaps, even measure their concentration. However, the use of hyperspectral remote sensing in order to measure water quality is not yet established and remains a very challenging problem. In this study, laboratory experiments, ancillary field data and hyperspectral imagery from the Hyperion sensor were used to explore the feasibility of using remote sensing to detect chromium pollution in the River Ganga. The laboratory experiments demonstrated that field spectroscopy was indeed capable of detecting chromium in concentrations that can currently be found in the Ganga. Furthermore, the analysis of the Hyperion images of the River Ganga shows some promising results which suggest that chromium compounds can be detected using hyperspectral satellite imagery. However, the results confirm that measuring water quality from spaceborne hyperspectral imagery is extremely challenging and further research is required to improve the confidence of these results and refine this methodology.

  12. Hyperspectral Sensor Data Capability for Retrieving Complex Urban Land Cover in Comparison with Multispectral Data: Venice City Case Study (Italy)

    PubMed Central

    Cavalli, Rosa Maria; Fusilli, Lorenzo; Pascucci, Simone; Pignatti, Stefano; Santini, Federico

    2008-01-01

    This study aims at comparing the capability of different sensors to detect land cover materials within an historical urban center. The main objective is to evaluate the added value of hyperspectral sensors in mapping a complex urban context. In this study we used: (a) the ALI and Hyperion satellite data, (b) the LANDSAT ETM+ satellite data, (c) MIVIS airborne data and (d) the high spatial resolution IKONOS imagery as reference. The Venice city center shows a complex urban land cover and therefore was chosen for testing the spectral and spatial characteristics of different sensors in mapping the urban tissue. For this purpose, an object-oriented approach and different common classification methods were used. Moreover, spectra of the main anthropogenic surfaces (i.e. roofing and paving materials) were collected during the field campaigns conducted on the study area. They were exploited for applying band-depth and sub-pixel analyses to subsets of Hyperion and MIVIS hyperspectral imagery. The results show that satellite data with a 30m spatial resolution (ALI, LANDSAT ETM+ and HYPERION) are able to identify only the main urban land cover materials. PMID:27879879

  13. Unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization

    NASA Astrophysics Data System (ADS)

    Masalmah, Yahya M.; Vélez-Reyes, Miguel

    2006-04-01

    This paper presents an approach for simultaneous determination of endmembers and their abundances in hyperspectral imagery unmixing using a constrained positive matrix factorization (PMF). The algorithm presented here solves the constrained PMF using Gauss-Seidel method. This algorithm alternates between the endmembers matrix updating step and the abundance estimation step until convergence is achieved. Preliminary results using a subset of a HYPERION image taken in SW Puerto Rico are presented. These results show the potential of the proposed method to solve the unsupervised unmixing problem.

  14. Use of the Earth Observing One (EO-1) Satellite for the Namibia SensorWeb Flood Early Warning Pilot

    NASA Technical Reports Server (NTRS)

    Mandl, Daniel; Frye, Stuart; Cappelaere, Pat; Handy, Matthew; Policelli, Fritz; Katjizeu, McCloud; Van Langenhove, Guido; Aube, Guy; Saulnier, Jean-Francois; Sohlberg, Rob; Silva, Julie; Kussul, Nataliia; Skakun, Sergii; Ungar, Stephen; Grossman, Robert

    2012-01-01

    The Earth Observing One (EO-1) satellite was launched in November 2000 as a one year technology demonstration mission for a variety of space technologies. After the first year, it was used as a pathfinder for the creation of SensorWebs. A SensorWeb is the integration of variety of space, airborne and ground sensors into a loosely coupled collaborative sensor system that automatically provides useful data products. Typically, a SensorWeb is comprised of heterogeneous sensors tied together with a messaging architecture and web services. Disasters are the perfect arena to use SensorWebs. One SensorWeb pilot project that has been active since 2009 is the Namibia Early Flood Warning SensorWeb pilot project. The Pilot Project was established under the auspices of the Namibian Ministry of Agriculture Water and Forestry (MAWF)/Department of Water Affairs, the Committee on Earth Observing Satellites (CEOS)/Working Group on Information Systems and Services (WGISS) and moderated by the United Nations Platform for Space-based Information for Disaster Management and Emergency Response (UN-SPIDER). The effort began by identifying and prototyping technologies which enabled the rapid gathering and dissemination of both space-based and ground sensor data and data products for the purpose of flood disaster management and water-borne disease management. This was followed by an international collaboration to build small portions of the identified system which was prototyped during that past few years during the flood seasons which occurred in the February through May timeframe of 2010 and 2011 with further prototyping to occur in 2012. The SensorWeb system features EO-1 data along with other data sets from such satellites as Radarsat, Terra and Aqua. Finally, the SensorWeb team also began to examine the socioeconomic component to determine the impact of the SensorWeb technology and how best to assist in the infusion of this technology in lesser affluent areas with low levels of basic

  15. Assessing the accuracy of hyperspectral and multispectral satellite imagery for categorical and Quantitative mapping of salinity stress in sugarcane fields

    NASA Astrophysics Data System (ADS)

    Hamzeh, Saeid; Naseri, Abd Ali; AlaviPanah, Seyed Kazem; Bartholomeus, Harm; Herold, Martin

    2016-10-01

    This study evaluates the feasibility of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields located in the southwest of Iran. For this purpose a Hyperion image acquired on September 2, 2010 and a Landsat7 ETM+ image acquired on September 7, 2010 were used as hyperspectral and multispectral satellite imagery. Field data including soil salinity in the sugarcane root zone was collected at 191 locations in 25 fields during September 2010. In the first section of the paper, based on the yield potential of sugarcane as influenced by different soil salinity levels provided by FAO, soil salinity was classified into three classes, low salinity (1.7-3.4 dS/m), moderate salinity (3.5-5.9 dS/m) and high salinity (6-9.5) by applying different classification methods including Support Vector Machine (SVM), Spectral Angle Mapper (SAM), Minimum Distance (MD) and Maximum Likelihood (ML) on Hyperion and Landsat images. In the second part of the paper the performance of nine vegetation indices (eight indices from literature and a new developed index in this study) extracted from Hyperion and Landsat data was evaluated for quantitative mapping of salinity stress. The experimental results indicated that for categorical classification of salinity stress, Landsat data resulted in a higher overall accuracy (OA) and Kappa coefficient (KC) than Hyperion, of which the MD classifier using all bands or PCA (1-5) as an input performed best with an overall accuracy and kappa coefficient of 84.84% and 0.77 respectively. Vice versa for the quantitative estimation of salinity stress, Hyperion outperformed Landsat. In this case, the salinity and water stress index (SWSI) has the best prediction of salinity stress with an R2 of 0.68 and RMSE of 1.15 dS/m for Hyperion followed by Landsat data with an R2 and RMSE of 0.56 and 1.75 dS/m respectively. It was concluded that categorical mapping of salinity stress is the best option

  16. Estimating Spatial Variations in Soil Organic Carbon Using Hyperspectral Data and Map Algebra

    NASA Astrophysics Data System (ADS)

    Jaber, S.; Lant, C.

    2009-04-01

    Soil organic carbon (SOC) sequestration is a component of larger strategies to control the accumulation of greenhouse gases that are causing global warming. To implement this approach, it is necessary to improve the methods of measuring SOC content under normal field conditions. Among these methods are indirect remote sensing and geographic information systems (GIS) techniques that are required to provide non-intrusive, low cost, and spatially continuous information that cover large areas on a repetitive basis. This study evaluates the effectiveness of hyperspectral data in improving existing remote sensing methodologies for measuring SOC content. The study area is Big Creek Watershed (BCW) in Southern Illinois, USA. Composite soil samples were collected from 303 representative pixels along the Hyperion coverage area of the watershed. Two linear multiple regression models predicting SOC were calibrated and validated: an all-variables model and a raster-variables only model. Map algebra was implemented to extrapolate the raster variables only model and produce a SOC map for the BCW. Hyperion data improved the predictability of SOC compared to multispectral satellite remote sensing sensors with a correlation coefficient (R) of 0.37 and a root mean square error (RMSE) of 3.19 metric tons per hectare to a 15-cm depth in the validation sample. Hyperspectral data cannot capture small annual variations in SOC, but can measure decadal variations associated with changes in tillage or crop rotation with fair accuracy; RMSEs are as low as 34 percent of field-measured changes in SOC due to changes in tillage and as low as 59 percent for changes in crop rotation. These ranges of error likely need to be reduced further if hyperspectral data were to be used as the basis of carbon sequestration credit programs. Hyperspectral data combined with map algebra can measure total SOC pools in various ecosystem or soil types to within a few percent error.

  17. Oil and gas reservoir exploration based on hyperspectral remote sensing and super-low-frequency electromagnetic detection

    NASA Astrophysics Data System (ADS)

    Qin, Qiming; Zhang, Zili; Chen, Li; Wang, Nan; Zhang, Chengye

    2016-01-01

    This paper proposes a method that combined hyperspectral remote sensing with super-low-frequency (SLF) electromagnetic detection to extract oil and gas reservoir characteristics from surface to underground, for the purpose of determining oil and gas exploration target regions. The study area in Xinjiang Karamay oil-gas field, China, was investigated. First, a Hyperion dataset was used to extract altered minerals (montmorillonite, chlorite, and siderite), which were comparatively verified by field survey and spectral measurement. Second, the SLF electromagnetic datasets were then acquired where the altered minerals were distributed. An inverse distance weighting method was utilized to acquire two-dimensional profiles of the electrical feature distribution of different formations on the subsurface. Finally, existing geological data, field work, and the results derived from Hyperion images and SLF electromagnetic datasets were comprehensively analyzed to confirm the oil and gas exploration target region. The results of both hyperspectral remote sensing and SLF electromagnetic detection had a good consistency with the geological materials in this study. This paper demonstrates that the combination of hyperspectral remote sensing and SLF electromagnetic detection is suitable for the early exploration of oil and gas reservoirs, which is characterized by low exploration costs, large exploration areas, and a high working efficiency.

  18. Stress Monitoring of Mulberry Plants by Finding Rep Using Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Bhosle, K.; Musande, V.

    2017-05-01

    Stressed on crop can be monitored using different indices. Red Edge position is good estimator for stress monitoring. The red edge position (REP) is strongly correlated with foliar chlorophyll content. Strong chlorophyll absorption causes the abrupt change in the 680-800 nm region of reflectance spectra of green vegetation. The red edge consist the point of maximum slope between red and near-infrared wavelengths. REP can be used to recognize green zone of the observation area. The REP is present in spectra for vegetation recorded by remote sensing methods. REP is clearer and significant in hyper spectral data as hyper spectral consist of more and continuous bands data. In this paper experiments were carried out for mulberry crop using USGS EO-1 Hyperion data. Atmospheric corrected data is used for classification. Classification is carried out on small cluster of 14 field samples. Ground truth is verified and classified by comparing with Hyperion data. REP is different for different stressed condition of crops and shows healthy and diseased crop condition. Nutritional stresses, diseases, drought of plants are detected using REP. Stressed and healthy field of mulberry are estimated by calculating REP using maximum first derivative, linear interpolation, linear extrapolation method. Finally REP is compared using above methods. It is noticeable difference of REP for healthy and stressed crop. The research indicates that overall accuracy using maximum first derivative was 92.85 % and it was more compared to other methods. Linear extrapolation gives less accuracy compared to linear interpolation method.

  19. Hyperspectral Remote Sensing of Vegetation:Knowledge Gain and Knowledge Gap after 40 years of research

    NASA Astrophysics Data System (ADS)

    Thenkabail, P. S.; Huete, A. R.

    2012-12-01

    This presentation summarizes the advances made over 40+ years in understanding, modeling, and mapping terrestrial vegetation as reported in the new book on "Hyperspectral Remote Sensing of Vegetation" (Publisher: Taylor and Francis inc.). The advent of spaceborne hyperspectral sensors or imaging spectroscopy (e.g., NASA's Hyperion, ESA's PROBA, and upcoming Italy's ASI's Prisma, Germany's DLR's EnMAP, Japanese HIUSI, NASA's HyspIRI) as well as the advancements in processing large volumes of hyperspectral data have generated tremendous interest in expanding the hyperspectral applications' knowledge base to large areas. Advances made in using hyperspectral data, relative to broadband spectral data, include: (a) significantly improved characterization and modeling of a wide array of biophysical and biochemical properties of vegetation, (b) the ability to discriminate plant species and vegetation types with high degree of accuracy, (c) reduced uncertainty in determining net primary productivity or carbon assessments from terrestrial vegetation, (d) improved crop productivity and water productivity models, (e) the ability to assess stress resulting from causes such as management practices, pests and disease, water deficit or water excess, and (f) establishing wavebands and indices with greater sensitivity for analyzing vegetation characteristics. Current state of knowledge on hyperspectral narrowbands (HNBs) for agricultural and vegetation studies inferred from the Book entitled hyperspectral remote sensing of vegetation by Thenkabail et al., 2011. Six study areas of the World for which we have extensive data from field spectroradiometers for 8 major world crops (wheat, corn, rice, barley, soybeans, pulses, and cotton). Approx. 10,500 such data points will be used in crop modeling and in building spectral libraries.

  20. View-illumination effects on hyperspectral vegetation indices in the Amazonian tropical forest

    NASA Astrophysics Data System (ADS)

    Galvão, Lênio Soares; Breunig, Fábio Marcelo; Santos, João Roberto dos; Moura, Yhasmin Mendes de

    2013-04-01

    Because of the pointing capability of the Hyperion/Earth Observing-One (EO-1) to improve the revisit time of the scene, temporal series of narrowband vegetation indices (VIs) can be generated to study the phenology of the Amazonian tropical forests. In this study, 10 selected narrowband VIs calculated from Hyperion nadir and off-nadir data and from different view directions (forward scattering and backscattering) were analyzed for their sensitivity to view-illumination effects along the dry season on the Seasonal Semi-deciduous Forest. Data analysis was also supported by PROSAIL modeling to simulate the spectral response of this forest type in both directions. Hyperion and PROSAIL results showed that the Enhanced Vegetation Index (EVI) and Photochemical Reflectance Index (PRI) were the two more anisotropic VIs, whereas the Normalized Difference Vegetation Index (NDVI), Structure Insensitive Pigment Index (SIPI) and the Vogelmann Red Edge Index (VOG) were comparatively less sensitive to view-illumination effects. When compared to the other VIs and because of the greater dependence on the near-infrared (NIR) reflectance, EVI showed a different spectral behavior. EVI increased from forward scattering to backscattering and with decreasing solar zenith angle (SZA) towards the end of the local dry season, due to reduction in shading and enhancement of the illumination effects. On the other hand, PRI was higher with increasing shading in the forward scattering direction, as deduced from the PROSAIL simulation. Results emphasized the importance of taking into account bidirectional effects when analyzing temporal series of VIs collected over tropical forests by imaging spectrometers with pointing capability or even by multispectral sensors with large field-of-view (FOV).

  1. Multipurpose hyperspectral imaging system

    USDA-ARS?s Scientific Manuscript database

    A hyperspectral imaging system of high spectral and spatial resolution that incorporates several innovative features has been developed to incorporate a focal plane scanner (U.S. Patent 6,166,373). This feature enables the system to be used for both airborne/spaceborne and laboratory hyperspectral i...

  2. Dimensionality reduction of hyperspectral data: band selection using curve fitting

    NASA Astrophysics Data System (ADS)

    Pal, Mahendra K.; Porwal, Alok

    2016-04-01

    Hyperspectral sensors offer narrow spectral bandwidth facilitating better discrimination of various ground materials. However, high spectral resolutions of these sensors result in larger data volumes, and thus pose computation challenges. The increased computational complexity limit the use of hyperspectral data, where applications demands moderate accuracies but economy of processing and execution time. Also the high dimensionality of the feature space adversely affect classification accuracies when the number of training samples is limited - a consequence of Hughes' effect. A reduction in the number of dimensions lead to the Hughes effect, thus improving classification accuracies. Dimensionality reduction can be accomplished by: (i) feature selection, that is, selection of sub-optimal subset of the original set of features and (ii) feature extraction, that is, projection of the original feature space into a lower dimensional subspace that preserves most of Information. In this contribution, we propose a novel method of feature section by identifying and selecting the optimal bands based on spectral decorrelation using a local curve fitting technique. The technique is implemented on the Hyperion data of a study area from Western India. The results shows that the proposed algorithm is efficient and effective in preserving the useful original information for better classification with reduced data size and dimension.

  3. Band selection for change detection from hyperspectral images

    NASA Astrophysics Data System (ADS)

    Liu, Sicong; Du, Qian; Tong, Xiaohua

    2017-05-01

    In this paper, we propose to apply unsupervised band selection to improve the performance of change detection in multitemporal hyperspectral images (HSI-CD). By reducing data dimensionality through finding the most distinctive and informative bands in the difference image, foreground changes may be better detected. Band selection-based dimensionality reduction (BS-DR) technique is considered to investigate in details the following sub-problems in HSI-CD including: 1) the estimated number of multi-class changes; 2) the binary CD; 3) the multiple CD; 4) the change discriminability; 5) the optimal number of selected bands. Thus it contributes at first time a quantitative analysis of the BS-DR approach impacting on the HSI-CD performance. Due to the difficulty of having training samples in an unknown environment, unsupervised band selection and change detection are considered. A pair of real multitemporal hyperspectral Hyperion data set has been used to validate the proposed approach. Experimental results confirmed the effectiveness of selecting a band subset to obtain a satisfactory CD result, comparing with the one using original full bands. In addition, the results also demonstrated that the reduced feature space is capable to maintain sufficient information for detecting the occurred spectrally significant changes. CD performance is enhanced with respect to the increasing of change representative and discriminable capabilities.

  4. Alteration mineral mapping using ETM+ and hyperion remote sensing data at Bau Gold Field, Sarawak, Malaysia

    NASA Astrophysics Data System (ADS)

    Pour, A. B.; Hashim, M.

    2014-02-01

    The area under investigation is the Bau gold mining district in the State of Sarawak, East Malaysia, on the island of Borneo. It has tropical climate with limited bedrock exposures. Bau is a gold field similar to Carlin style gold deposits. Geological analyses coupled with remote sensing data were used to detect hydrothermally altered rocks associated with gold mineralization. The Landsat Enhanced Thematic Mapper+ (ETM+) and Hyperion data were used to carry out mineral mapping of mineralized zones in the study area and surrounding terrain. Directed Principal Components Analysis (DPCA) transformation of four appropriate ETM+ band ratios were applied to produce DPC images, allowing the removal of the effects of vegetation from ETM+ data and the detection of separate mineral images at a regional scale. Linear Spectral Unmixing (LSU) was used to produce image maps of hydroxyl-bearing minerals using Hyperion data at a district scale. Results derived from the visible and near infrared and shortwave infrared bands of Hyperion represented iron oxide/hydroxide and clay minerals rich zones associated with the known gold prospects in the Bau district. The results show that the known gold prospects and potentially interesting areas are recognizable by the methods used, despite limited bedrock exposure in this region and the constraints imposed by the tropical environment. The approach used in this study can be more broadly applicable to provide an opportunity for detecting potentially interesting areas of gold mineralization using the ETM+ and Hyperion data in the tropical/sub-tropical regions.

  5. Comparison of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Earth Observing One (EO-1) Advanced Land Imager

    NASA Technical Reports Server (NTRS)

    Pedelty, Jeffrey A.; Morisette, Jeffrey T.; Smith, James A.

    2004-01-01

    We compare images from the Enhanced Thematic Mapper Plus (ETM+) sensor on Landsat-7 and the Advanced Land Imager (ALI) instrument on Earth Observing One (EO-1) over a test site in Rochester, New York. The site contains a variety of features, ranging from water of varying depths, deciduous/coniferous forest, and grass fields, to urban areas. Nearly coincident cloud-free images were collected one minute apart on 25 August 2001. We also compare images of a forest site near Howland, Maine, that were collected on 7 September, 2001. We atmospherically corrected each pair of images with the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmosphere model, using aerosol optical thickness and water vapor column density measured by in situ Cimel sun photometers within the Aerosol Robotic Network (AERONET), along with ozone density derived from the Total Ozone Mapping Spectrometer (TOMS) on the Earth Probe satellite. We present true-color composites from each instrument that show excellent qualitative agreement between the multispectral sensors, along with grey-scale images that demonstrate a significantly improved ALI panchromatic band. We quantitatively compare ALI and ETM+ reflectance spectra of a grassy field in Rochester and find < or equal to 6% differences in the visible/near infrared and approx. 2% differences in the short wave infrared. Spectral comparisons of forest sites in Rochester and Howland yield similar percentage agreement except for band 1, which has very low reflectance. Principal component analyses and comparison of normalized difference vegetation index histograms for each sensor indicate that the ALI is able to reproduce the information content in the ETM+ but with superior signal-to-noise performance due to its increased 12-bit quantization.

  6. [Interpretation of spatial distribution pattern for dissolved inorganic nitrogen concentration in coastal estuary using hyperspectral data].

    PubMed

    Zhang, Dong; Xu, Yong; Zhang, Ying; Li, Huan

    2010-06-01

    Choosing dissolved inorganic nitrogen (DIN) as one of the representative nutritional salt monitoring indexes, a hyperspectral remotely sensed inversion model was built and applied to quantitatively retrieve water quality parameters with its spatial distribution patterns in coastal estuary with high suspended sediment concentration (SSC). It was found that when SSC was larger than 0.1 kg/m3, DIN concentration had a notable inverse correlation with SSC and the correlation coefficient R2 reached 0.617. Based on this conclusion, firstly the in-situ observed water surface remote sensing reflectance was resampled according to the spectral response characters of Hyperion sensor. And then, statistical correlation analysis between reflectance and DIN concentration was carried out. The results showed that band reflectance of R804 and R630 representing the second and first reflectance peak of water spectrum curve were sensitive to the variation of DIN concentration. And then, a pseudo remotely sensed sand parameter index R804 x R630/(R804 - R630) was calculated for the construction of the nonlinear DIN quantitative reversion model. Correlation coefficient R2 between observed and simulated DIN concentrations for 29 calibrating samples and 10 validating samples were 0.746 and 0.67, while their mean absolute errors reached 109.07 and 147.58 microg/L, respectively. The model was then applied on Hyperion hyperspectral image to get the spatial distribution character of DIN concentration in Sheyanghe river estuary and the DIN concentration was between 52 to 513 microg/L. Results indicated that in coastal estuary which was dominated by suspended sediments, the diffusive trends of DIN concentration reversed by remote sensing techniques had an intimate relationship with motions of tidal current and transportation attributes of SSC. As the hydrodynamic conditions were unclear, hyperspectral remote sensing technique was an effective technical way for dynamic survey of DIN concentration.

  7. 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.

  8. Hyperspectral remote sensing of vegetation: knowledge gain and knowledge gap after 50 years of research (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Thenkabail, Prasad S.

    2017-04-01

    This presentation summarizes the advances made over 40+ years in understanding, modeling, and mapping terrestrial vegetation as reported in the new book on "Hyperspectral Remote Sensing of Vegetation" (Publisher:Taylor and Francis inc.). The advent of spaceborne hyperspectral sensors or imaging spectroscopy (e.g., NASA's Hyperion, ESA's PROBA, and upcoming Italy's ASI's Prisma, Germany's DLR's EnMAP, Japanese HIUSI, NASA's HyspIRI) as well as the advances made in processing when handling large volumes of hyperspectral data have generated tremendous interest in advancing the hyperspectral applications' knowledge base to large areas. Advances made in using hyperspectral data, relative to broadband data, include: (a) significantly improved characterization and modeling of a wide array of biophysical and biochemical properties of vegetation, (b) ability to discriminate plant species and vegetation types with high degree of accuracy, (c) reducing uncertainties in determining net primary productivity or carbon assessments from terrestrial vegetation, (d) improved crop productivity and water productivity models, (e) ability to assess stress resulting from causes such as management practices, pests and disease, water deficit or water excess, and (f) establishing more sensitive wavebands and indices to study vegetation characteristics. The presentation will discuss topics such as: (1) hyperspectral sensors and their characteristics, (2) methods of overcoming the Hughes phenomenon, (3) characterizing biophysical and biochemical properties, (4) advances made in using hyperspectral data in modeling evapotranspiration or actual water use by plants, (5) study of phenology, light use efficiency, and gross primary productivity, (5) improved accuracies in species identification and land cover classifications, and (6) applications in precision farming.

  9. Hyperspectral observation of anthropogenic and biogenic pollution in coastal zone

    NASA Astrophysics Data System (ADS)

    Lavrova, Olga; Loupian, Evgeny; Mityagina, Marina; Uvarov, Ivan

    The work presents results of anthropogenic and biogenic pollution detection in coastal zones of the Black and Caspian Seas based on satellite hyperspetral data provided by the Hyperion and HICO instruments. Techniques developed on the basis of the analysis of spectral characteristics calculated in special points were employed to address the following problems: (a) assessment of the blooming intensity of cyanobacteria and their distribution in bays of western Crimea and discrimination between anthropogenic pollutant discharge events and algae bloom; (b) detection of anthropogenic pollution in Crimean lakes utilized as industrial liquid discharge reservoirs; (c) detection of oil pollution in areas of shelf oil production in the Caspian Sea. Information values of different spectral bands and their composites were estimated in connection with the retrieval of the main sea water components: phytoplankton, suspended matter and colored organic matter, and also various anthropogenic pollutants, including oil. Software tools for thematic hyperspectral data processing in application to the investigation of sea coastal zones and internal water bodies were developed on the basis of the See the Sea geoportal created by the Space Research Institute RAS. The geoportal is focused on the study of processes in the world ocean with the emphasis on the advantages of satellite systems of observation. The tools that were introduced into the portal allow joint analysis of quasi-simultaneous satellite data, in particular data from the Hyperion, HICO, OLI Landsat-8, ETM Landsat-7 and TM Landsat-5 instruments. Results of analysis attempts combining data from different sensors are discussed. Their strong and weak points are highlighted. The study was completed with partial financial support from The Russian Foundation for Basic Research grants # 14-05-00520-a and 13-07-12017.

  10. Mapping of Biophysical Parameters of Rice Agriculture System from Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Moharana, Shreedevi; Duta, Subashisa

    2017-04-01

    Chlorophyll, nitrogen and leaf water content are the most essential parameters for paddy crop growth. Ground hyperspectral observations were collected at canopy level during critical growth period of rice by using hand held Spectroradiometer. Chemical analysis was carried out to quantify the total chlorophyll, nitrogen and leaf water content. By exploiting the in-situ hyperspectral measurements, regression models were established between each of the crop growth parameters and the spectral indices specifically designed for chlorophyll, nitrogen and water stress. Narrow band vegetation index models were developed for mapping these parameters from Hyperion imagery in an agriculture system. It was inferred that the modified simple ratio (SR) and leaf nitrogen concentration (LNC) predictive index models, which followed a linear and nonlinear relationship respectively, produced satisfactory results in predicting rice nitrogen content from hyperspectral imagery. The presently developed model was compared with other models proposed by researchers. It was ascertained that, nitrogen content varied widely from 1-4 percentage and only 2-3 percentage for paddy crop using present modified index models and well-known predicted Tian et al. (2011) model respectively. The modified present LNC index model performed better than the established Tian et al. (2011) model as far as the estimated nitrogen content from Hyperion imagery was concerned. Moreover, within the observed chlorophyll range attained from the rice genotypes cultivated in the studied rice agriculture system, the index models (LNC, OASVI, Gitelson, mSR and MTCI) accomplished satisfactory results in the spatial distribution of rice chlorophyll content from Hyperion imagery. Spatial distribution of total chlorophyll content widely varied from 1.77-5.81 mg/g (LNC), 3.0-13 mg/g (OASVI) and 2.90-5.40 mg/g (MTCI). Following the similar guideline, it was found that normalized difference water index (NDWI) and normalized

  11. Detection of a strongly negative surface potential at Saturn's moon Hyperion

    PubMed Central

    Nordheim, T A; Jones, G H; Roussos, E; Leisner, J S; Coates, A J; Kurth, W S; Khurana, K K; Krupp, N; Dougherty, M K; Waite, J H

    2014-01-01

    On 26 September 2005, Cassini conducted its only close targeted flyby of Saturn's small, irregularly shaped moon Hyperion. Approximately 6 min before the closest approach, the electron spectrometer (ELS), part of the Cassini Plasma Spectrometer (CAPS) detected a field-aligned electron population originating from the direction of the moon's surface. Plasma wave activity detected by the Radio and Plasma Wave instrument suggests electron beam activity. A dropout in energetic electrons was observed by both CAPS-ELS and the Magnetospheric Imaging Instrument Low-Energy Magnetospheric Measurement System, indicating that the moon and the spacecraft were magnetically connected when the field-aligned electron population was observed. We show that this constitutes a remote detection of a strongly negative (∼ −200 V) surface potential on Hyperion, consistent with the predicted surface potential in regions near the solar terminator. PMID:26074639

  12. Detection of a strongly negative surface potential at Saturn's moon Hyperion

    NASA Astrophysics Data System (ADS)

    Nordheim, T. A.; Jones, G. H.; Roussos, E.; Leisner, J. S.; Coates, A. J.; Kurth, W. S.; Khurana, K. K.; Krupp, N.; Dougherty, M. K.; Waite, J. H.

    2014-10-01

    On 26 September 2005, Cassini conducted its only close targeted flyby of Saturn's small, irregularly shaped moon Hyperion. Approximately 6 min before the closest approach, the electron spectrometer (ELS), part of the Cassini Plasma Spectrometer (CAPS) detected a field-aligned electron population originating from the direction of the moon's surface. Plasma wave activity detected by the Radio and Plasma Wave instrument suggests electron beam activity. A dropout in energetic electrons was observed by both CAPS-ELS and the Magnetospheric Imaging Instrument Low-Energy Magnetospheric Measurement System, indicating that the moon and the spacecraft were magnetically connected when the field-aligned electron population was observed. We show that this constitutes a remote detection of a strongly negative (~ -200 V) surface potential on Hyperion, consistent with the predicted surface potential in regions near the solar terminator.

  13. Detection of a strongly negative surface potential at Saturn's moon Hyperion.

    PubMed

    Nordheim, T A; Jones, G H; Roussos, E; Leisner, J S; Coates, A J; Kurth, W S; Khurana, K K; Krupp, N; Dougherty, M K; Waite, J H

    2014-10-28

    On 26 September 2005, Cassini conducted its only close targeted flyby of Saturn's small, irregularly shaped moon Hyperion. Approximately 6 min before the closest approach, the electron spectrometer (ELS), part of the Cassini Plasma Spectrometer (CAPS) detected a field-aligned electron population originating from the direction of the moon's surface. Plasma wave activity detected by the Radio and Plasma Wave instrument suggests electron beam activity. A dropout in energetic electrons was observed by both CAPS-ELS and the Magnetospheric Imaging Instrument Low-Energy Magnetospheric Measurement System, indicating that the moon and the spacecraft were magnetically connected when the field-aligned electron population was observed. We show that this constitutes a remote detection of a strongly negative (∼ -200 V) surface potential on Hyperion, consistent with the predicted surface potential in regions near the solar terminator.

  14. Forming The Surfaces Of Hyperion, Atlas, And Telesto: Nature Versus Nurture

    NASA Astrophysics Data System (ADS)

    Thomas, Peter C.; Burns, J.; Charnoz, S.; Brahic, A.; Porco, C.; Weiss, J.

    2007-10-01

    Hyperion, Atlas and Telesto present three radically different faces: Hyperion has a sponge-like topography at the 2-10 km scale; Telesto is buried in debris, and Atlas has a smooth equatorial ridge contrasting with rugged polar regions. Are these the result of materials (nature) or environment (nurture), and what implications do these greatly differing forms have for other satellites and other icy objects in the outer solar system? Porosity may play a crucial role in Hyperion's sponge-like appearance, this satellite differing from other porous ones in its size and lack of processes competing with cratering. Recent Cassini images (Porco et al. 2007) show Atlas's flying-saucer shape to reflect two distinct regions: rough polar and smooth equatorial. These may be a reflection of ring-related particle accretion (Charnoz et . al. 2007). Telesto, partly buried in (its own?) debris, appears a stochastic result of its environment: perhaps similar to Deimos’ self-covering. Irregular objects do not yield easily to correlation of surface appearance and shape parameters such as axial ratios or gravitational relief relative to object size. Only the presence of a wide range of surface acceleration seems to qualitatively affect surface processes. We discuss the implications for other small satellites of outer planets and for small KBOs. Porco, C. et al. (2007) , submitted to Science. Charnoz, S. et al. (2007) Submitted to Science.

  15. Hyperspectral remote sensing of vegetation and agricultural crops: knowledge gain and knowledge gap after 40 years of research

    USGS Publications Warehouse

    Thenkabail, Prasad S.; Lyon, John G.; Huete, Alfredo; Edited by Thenkabail, Prasad S.; Lyon, John G.; Huete, Alfredo

    2011-01-01

    The focus of this chapter was to summarize the advances made over last 40+ years, as reported in various chapters of this book, in understanding, modeling, and mapping terrestrial vegetation using hyperspectral remote sensing (or imaging spectroscopy) using sensors that are ground-based, truck-mounted, airborne, and spaceborne. As we have seen in various chapters of this book and synthesized in this chapter, the advances made include: (a) significantly improved characterization and modeling of a wide array of biophysical and biochemical properties of vegetation, (b) ability to discriminate plant species and vegetation types with high degree of accuracies (c) reducing uncertainties in determining net primary productivity or carbon assessments from terrestrial vegetation, (d) improved crop productivity and water productivity models, (b), (e) ability to access stress resulting from causes such as management practices, pests and disease, water deficit or excess; , and (f) establishing more sensitive wavebands and indices to detect plant water\\moisture content. The advent of spaceborne hyperspectral sensors (e.g., NASA’s Hyperion, ESA’s PROBA, and upcoming NASA’s HyspIRI) and numerous methods and techniques espoused in this book to overcome Hughes phenomenon or data redundancy when handling large volumes of hyperspectral data have generated tremendous interest in advancing our hyperspectral applications knowledge base over larger spatial extent such as region, nation, continent, and globe.

  16. Hyperspectral remote sensing of evaporate minerals and associated sediments in Lake Magadi area, Kenya

    NASA Astrophysics Data System (ADS)

    Kodikara, Gayantha R. L.; Woldai, Tsehaie; van Ruitenbeek, Frank J. A.; Kuria, Zack; van der Meer, Freek; Shepherd, Keith D.; van Hummel, G. J.

    2012-02-01

    Pleistocene to present evaporitic lacustrine sediments in Lake Magadi, East African Rift Valley, Kenya were studied and mapped using spectral remote sensing methods. This approach incorporated surface mineral mapping using space-borne hyperspectral Hyperion imagery together with laboratory analysis, including visible, near-infrared diffuse reflectance spectroscopy (VNIR) measurements and X-ray diffraction for selected rock and soil samples of the study area. The spectral signatures of Magadiite and Kenyaite, which have not been previously reported, were established and the spectral signatures of trona, chert series, volcanic tuff and the High Magadi bed were also analyzed. Image processing techniques, MNF (Minimum Noise Fraction) and MTMF (Mixture Tuned Matched Filtering) using a stratified approach (image analysis with and without the lake area), were used to enhance the mapping of evaporates. High Magadi beds, chert series and volcanic tuff were identified from the Hyperion image with an overall mapping accuracy of 84.3%. Even though, the spatial distribution of evaporites and sediments in Lake Magadi area change in response to climate variations, the mineralogy of this area has not been mapped recently. The results of this study shows the usefulness of the hypersspectral remote sensing to map the surface geology of this kind of environment and to locate promising sites for industrial open-pit trona mining in a qualitative and quantitative manner.

  17. Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images.

    PubMed

    Arellano, Paul; Tansey, Kevin; Balzter, Heiko; Boyd, Doreen S

    2015-10-01

    The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI705) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest.

  18. Determining the intrinsic dimension of a hyperspectral image using random matrix theory.

    PubMed

    Cawse-Nicholson, Kerry; Damelin, Steven B; Robin, Amandine; Sears, Michael

    2013-04-01

    Determining the intrinsic dimension of a hyperspectral image is an important step in the spectral unmixing process and under- or overestimation of this number may lead to incorrect unmixing in unsupervised methods. In this paper, we discuss a new method for determining the intrinsic dimension using recent advances in random matrix theory. This method is entirely unsupervised, free from any user-determined parameters and allows spectrally correlated noise in the data. Robustness tests are run on synthetic data, to determine how the results were affected by noise levels, noise variability, noise approximation, and spectral characteristics of the endmembers. Success rates are determined for many different synthetic images, and the method is tested on two pairs of real images, namely a Cuprite scene taken from Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) and SpecTIR sensors, and a Lunar Lakes scene taken from AVIRIS and Hyperion, with good results.

  19. Hyperspectral fundus imager

    NASA Astrophysics Data System (ADS)

    Truitt, Paul W.; Soliz, Peter; Meigs, Andrew D.; Otten, Leonard John, III

    2000-11-01

    A Fourier Transform hyperspectral imager was integrated onto a standard clinical fundus camera, a Zeiss FF3, for the purposes of spectrally characterizing normal anatomical and pathological features in the human ocular fundus. To develop this instrument an existing FDA approved retinal camera was selected to avoid the difficulties of obtaining new FDA approval. Because of this, several unusual design constraints were imposed on the optical configuration. Techniques to calibrate the sensor and to define where the hyperspectral pushbroom stripe was located on the retina were developed, including the manufacturing of an artificial eye with calibration features suitable for a spectral imager. In this implementation the Fourier transform hyperspectral imager can collect over a hundred 86 cm-1 spectrally resolved bands with 12 micro meter/pixel spatial resolution within the 1050 nm to 450 nm band. This equates to 2 nm to 8 nm spectral resolution depending on the wavelength. For retinal observations the band of interest tends to lie between 475 nm and 790 nm. The instrument has been in use over the last year successfully collecting hyperspectral images of the optic disc, retinal vessels, choroidal vessels, retinal backgrounds, and macula diabetic macular edema, and lesions of age-related macular degeneration.

  20. Hyperspectral holographic Fourier-microscopy

    SciTech Connect

    Kalenkov, G S; Kalenkov, S G; Shtan'ko, A E

    2015-04-30

    A detailed theory of the method of holographic recording of hyperspectral wave fields is developed. New experimentally obtained hyperspectral holographic images of microscopic objects are presented. The possibilities of the method are demonstrated experimentally using the examples of urgent microscopy problems: speckle noise suppression, obtaining hyperspectral image of a microscopic object, as well as synthesis of a colour image and obtaining an optical profile of a phase object. (holography)

  1. Vega-Constellation Tools to Analize Hyperspectral Images

    NASA Astrophysics Data System (ADS)

    Savorskiy, V.; Loupian, E.; Balashov, I.; Kashnitskii, A.; Konstantinova, A.; Tolpin, V.; Uvarov, I.; Kuznetsov, O.; Maklakov, S.; Panova, O.; Savchenko, E.

    2016-06-01

    Creating high-performance means to manage massive hyperspectral data (HSD) arrays is an actual challenge when it is implemented to deal with disparate information resources. Aiming to solve this problem the present work develops tools to work with HSD in a distributed information infrastructure, i.e. primarily to use those tools in remote access mode. The main feature of presented approach is in the development of remotely accessed services, which allow users both to conduct search and retrieval procedures on HSD sets and to provide target users with tools to analyze and to process HSD in remote mode. These services were implemented within VEGA-Constellation family information systems that were extended by adding tools oriented to support the studies of certain classes of natural objects by exploring their HSD. Particular developed tools provide capabilities to conduct analysis of such objects as vegetation canopies (forest and agriculture), open soils, forest fires, and areas of thermal anomalies. Developed software tools were successfully tested on Hyperion data sets.

  2. Chlorophyll content retrieval from hyperspectral remote sensing imagery.

    PubMed

    Yang, Xiguang; Yu, Ying; Fan, Wenyi

    2015-07-01

    Chlorophyll content is the essential parameter in the photosynthetic process determining leaf spectral variation in visible bands. Therefore, the accurate estimation of the forest canopy chlorophyll content is a significant foundation in assessing forest growth and stress affected by diseases. Hyperspectral remote sensing with high spatial resolution can be used for estimating chlorophyll content. In this study, the chlorophyll content was retrieved step by step using Hyperion imagery. Firstly, the spectral curve of the leaf was analyzed, 25 spectral characteristic parameters were identified through the correlation coefficient matrix, and a leaf chlorophyll content inversion model was established using a stepwise regression method. Secondly, the pixel reflectance was converted into leaf reflectance by a geometrical-optical model (4-scale). The three most important parameters of reflectance conversion, including the multiple scattering factor (M 0 ), and the probability of viewing the sunlit tree crown (P T ) and the background (P G ), were estimated by leaf area index (LAI), respectively. The results indicated that M 0 , P T , and P G could be described as a logarithmic function of LAI, with all R (2) values above 0.9. Finally, leaf chlorophyll content was retrieved with RMSE = 7.3574 μg/cm(2), and canopy chlorophyll content per unit ground surface area was estimated based on leaf chlorophyll content and LAI. Chlorophyll content mapping can be useful for the assessment of forest growth stage and diseases.

  3. Crater numbers and geological histories of Iapetus, Enceladus, Tethys and Hyperion

    NASA Technical Reports Server (NTRS)

    Plescia, J. B.; Boyce, J. M.

    1983-01-01

    The surfaces of the Saturn satellites Tethys, Iapetus and Encedalus display surfaces which indicate active geological processes and therefore suggest a degree of internal evolution. By contrast, the Saturn satellite Hyperion and the coorbitals 1980S1 and 1980S3 show no trace of geological activity and may be fragments of once-larger bodies. Activity on Iapetus appears to have been confined to the dark terrain, and offers no clue as to its timing and extent. The widest terrain type and crater number variations are those of Encedalus, which indicate the most prolonged period of geological activity of any of the satellites studied.

  4. Simulation of the hyperspectral data from multispectral data using Python programming language

    NASA Astrophysics Data System (ADS)

    Tiwari, Varun; Kumar, Vinay; Pandey, Kamal; Ranade, Rigved; Agarwal, Shefali

    2016-04-01

    Multispectral remote sensing (MRS) sensors have proved their potential in acquiring and retrieving information of Land Use Land (LULC) Cover features in the past few decades. These MRS sensor generally acquire data within limited broad spectral bands i.e. ranging from 3 to 10 number of bands. The limited number of bands and broad spectral bandwidth in MRS sensors becomes a limitation in detailed LULC studies as it is not capable of distinguishing spectrally similar LULC features. On the counterpart, fascinating detailed information available in hyperspectral (HRS) data is spectrally over determined and able to distinguish spectrally similar material of the earth surface. But presently the availability of HRS sensors is limited. This is because of the requirement of sensitive detectors and large storage capability, which makes the acquisition and processing cumbersome and exorbitant. So, there arises a need to utilize the available MRS data for detailed LULC studies. Spectral reconstruction approach is one of the technique used for simulating hyperspectral data from available multispectral data. In the present study, spectral reconstruction approach is utilized for the simulation of hyperspectral data using EO-1 ALI multispectral data. The technique is implemented using python programming language which is open source in nature and possess support for advanced imaging processing libraries and utilities. Over all 70 bands have been simulated and validated using visual interpretation, statistical and classification approach.

  5. Snapshot Hyperspectral Volumetric Microscopy

    PubMed Central

    Wu, Jiamin; Xiong, Bo; Lin, Xing; He, Jijun; Suo, Jinli; Dai, Qionghai

    2016-01-01

    The comprehensive analysis of biological specimens brings about the demand for capturing the spatial, temporal and spectral dimensions of visual information together. However, such high-dimensional video acquisition faces major challenges in developing large data throughput and effective multiplexing techniques. Here, we report the snapshot hyperspectral volumetric microscopy that computationally reconstructs hyperspectral profiles for high-resolution volumes of ~1000 μm × 1000 μm × 500 μm at video rate by a novel four-dimensional (4D) deconvolution algorithm. We validated the proposed approach with both numerical simulations for quantitative evaluation and various real experimental results on the prototype system. Different applications such as biological component analysis in bright field and spectral unmixing of multiple fluorescence are demonstrated. The experiments on moving fluorescent beads and GFP labelled drosophila larvae indicate the great potential of our method for observing multiple fluorescent markers in dynamic specimens. PMID:27103155

  6. Simulation of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

    Richsmeier, Steven C.; Singer-Berk, Alexander; Bernstein, Lawrence S.

    2004-01-01

    A software package generates simulated hyperspectral imagery for use in validating algorithms that generate estimates of Earth-surface spectral reflectance from hyperspectral images acquired by airborne and spaceborne instruments. This software is based on a direct simulation Monte Carlo approach for modeling three-dimensional atmospheric radiative transport, as well as reflections from surfaces characterized by spatially inhomogeneous bidirectional reflectance distribution functions. In this approach, "ground truth" is accurately known through input specification of surface and atmospheric properties, and it is practical to consider wide variations of these properties. The software can treat both land and ocean surfaces, as well as the effects of finite clouds with surface shadowing. The spectral/spatial data cubes computed by use of this software can serve both as a substitute for, and a supplement to, field validation data.

  7. Snapshot Hyperspectral Volumetric Microscopy

    NASA Astrophysics Data System (ADS)

    Wu, Jiamin; Xiong, Bo; Lin, Xing; He, Jijun; Suo, Jinli; Dai, Qionghai

    2016-04-01

    The comprehensive analysis of biological specimens brings about the demand for capturing the spatial, temporal and spectral dimensions of visual information together. However, such high-dimensional video acquisition faces major challenges in developing large data throughput and effective multiplexing techniques. Here, we report the snapshot hyperspectral volumetric microscopy that computationally reconstructs hyperspectral profiles for high-resolution volumes of ~1000 μm × 1000 μm × 500 μm at video rate by a novel four-dimensional (4D) deconvolution algorithm. We validated the proposed approach with both numerical simulations for quantitative evaluation and various real experimental results on the prototype system. Different applications such as biological component analysis in bright field and spectral unmixing of multiple fluorescence are demonstrated. The experiments on moving fluorescent beads and GFP labelled drosophila larvae indicate the great potential of our method for observing multiple fluorescent markers in dynamic specimens.

  8. Toward hyperspectral face recognition

    NASA Astrophysics Data System (ADS)

    Robila, Stefan A.

    2008-02-01

    Face recognition continues to meet significant challenges in reaching accurate results and still remains one of the activities where humans outperform technology. An attractive approach in improving face identification is provided by the fusion of multiple imaging sources such as visible and infrared images. Hyperspectral data, i.e. images collected over hundreds of narrow contiguous light spectrum intervals constitute a natural choice for expanding face recognition image fusion, especially since it may provide information beyond the normal visible range, thus exceeding the normal human sensing. In this paper we investigate the efficiency of hyperspectral face recognition through an in house experiment that collected data in over 120 bands within the visible and near infrared range. The imagery was produced using an off the shelf sensor in both indoors and outdoors with the subjects being photographed from various angles. Further processing included spectra collection and feature extraction. Human matching performance based on spectral properties is discussed.

  9. Planetary Hyperspectral Imager (PHI)

    NASA Technical Reports Server (NTRS)

    Silvergate, Peter

    1996-01-01

    A hyperspectral imaging spectrometer was breadboarded. Key innovations were use of a sapphire prism and single InSb focal plane to cover the entire spectral range, and a novel slit optic and relay optics to reduce thermal background. Operation over a spectral range of 450 - 4950 nm (approximately 3.5 spectral octaves) was demonstrated. Thermal background reduction by a factor of 8 - 10 was also demonstrated.

  10. Quantitative Hyperspectral Reflectance Imaging.

    PubMed

    Klein, Marvin E; Aalderink, Bernard J; Padoan, Roberto; De Bruin, Gerrit; Steemers, Ted A G

    2008-09-11

    Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultural heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of environmental conditions on the object. We describe the basic concept, working principles, construction and performance of a laboratory instrument specifically developed for the analysis of historical documents. The instrument measures calibrated spectral reflectance images at 70 wavelengths ranging from 365 to 1100 nm (near-ultraviolet, visible and near-infrared). By using a wavelength tunable narrow-bandwidth light-source, the light energy used to illuminate the measured object is minimal, so that any light-induced degradation can be excluded. Basic analysis of the hyperspectral data includes a qualitative comparison of the spectral images and the extraction of quantitative data such as mean spectral reflectance curves and statistical information from user-defined regions-of-interest. More sophisticated mathematical feature extraction and classification techniques can be used to map areas on the document, where different types of ink had been applied or where one ink shows various degrees of degradation. The developed quantitative hyperspectral imager is currently in use by the Nationaal Archief (National Archives of The Netherlands) to study degradation effects of artificial samples and original documents, exposed in their permanent exhibition area or stored in their deposit rooms.

  11. Hyperspectral data discrimination methods

    NASA Astrophysics Data System (ADS)

    Casasent, David P.; Chen, Xuewen

    2000-12-01

    Hyperspectral data provides spectral response information that provides detailed chemical, moisture, and other description of constituent parts of an item. These new sensor data are useful in USDA product inspection. However, such data introduce problems such as the curse of dimensionality, the need to reduce the number of features used to accommodate realistic small training set sizes, and the need to employ discriminatory features and still achieve good generalization (comparable training and test set performance). Several two-step methods are compared to a new and preferable single-step spectral decomposition algorithm. Initial results on hyperspectral data for good/bad almonds and for good/bad (aflatoxin infested) corn kernels are presented. The hyperspectral application addressed differs greatly from prior USDA work (PLS) in which the level of a specific channel constituent in food was estimated. A validation set (separate from the test set) is used in selecting algorithm parameters. Threshold parameters are varied to select the best Pc operating point. Initial results show that nonlinear features yield improved performance.

  12. Hyperspectral Biofilm Classification Analysis for Carrying Capacity of Migratory Birds in the South Bay Salt Ponds

    NASA Technical Reports Server (NTRS)

    Hsu, Wei-Chen; Kuss, Amber Jean; Ketron, Tyler; Nguyen, Andrew; Remar, Alex Covello; Newcomer, Michelle; Fleming, Erich; Debout, Leslie; Debout, Brad; Detweiler, Angela; Skiles, Joseph

    2011-01-01

    Tidal marshes are highly productive ecosystems that support migratory birds as roosting and over-wintering habitats on the Pacific Flyway. Microphytobenthos, or more commonly 'biofilms' contribute significantly to the primary productivity of wetland ecosystems, and provide a substantial food source for macroinvertebrates and avian communities. In this study, biofilms were characterized based on taxonomic classification, density differences, and spectral signatures. These techniques were then applied to remotely sensed images to map biofilm densities and distributions in the South Bay Salt Ponds and predict the carrying capacity of these newly restored ponds for migratory birds. The GER-1500 spectroradiometer was used to obtain in situ spectral signatures for each density-class of biofilm. The spectral variation and taxonomic classification between high, medium, and low density biofilm cover types was mapped using in-situ spectral measurements and classification of EO-1 Hyperion and Landsat TM 5 images. Biofilm samples were also collected in the field to perform laboratory analyses including chlorophyll-a, taxonomic classification, and energy content. Comparison of the spectral signatures between the three density groups shows distinct variations useful for classification. Also, analysis of chlorophyll-a concentrations show statistically significant differences between each density group, using the Tukey-Kramer test at an alpha level of 0.05. The potential carrying capacity in South Bay Salt Ponds is estimated to be 250,000 birds.

  13. Hyperspectral Biofilm Classification Analysis for Carrying Capacity of Migratory Birds in the South Bay Salt Ponds

    NASA Astrophysics Data System (ADS)

    Ketron, T.; Hsu, W.; Kuss, A. M.; Nguyen, A.; Remar, A. C.; Newcomer, M. E.; Fleming, E.; Bebout, L.; Bebout, B.; Detweiler, A. M.; Skiles, J. W.

    2011-12-01

    Tidal marshes are highly productive ecosystems that support migratory birds as roosting and over-wintering habitats on the Pacific Flyway. Microphytobenthos, or more commonly 'biofilms' contribute significantly to the primary productivity of wetland ecosystems, and provide a substantial food source for macroinvertebrates and avian communities. In this study, biofilms were characterized based on taxonomic classification, density differences, and spectral signatures. These techniques were then applied to remotely sensed images to map biofilm densities and distributions in the South Bay Salt Ponds and predict the carrying capacity of these newly restored ponds for migratory birds. The GER-1500 spectroradiometer was used to obtain in situ spectral signatures for each density-class of biofilm. The spectral variation and taxonomic classification between high, medium, and low density biofilm cover types was mapped using in-situ spectral measurements and classification of EO-1 Hyperion and Landsat TM 5 images. Biofilm samples were also collected in the field to perform laboratory analyses including chlorophyll-a, taxonomic classification, and energy content. Comparison of the spectral signatures between the three density groups shows distinct variations useful for classification. Also, analysis of chlorophyll-a concentrations show statistically significant differences between each density group, using the Tukey-Kramer test at an alpha level of 0.05. The potential carrying capacity in South Bay Salt Ponds is estimated to be 250,000 birds.

  14. Rapid Prototyping of Hyperspectral Image Analysis Algorithms for Improved Invasive Species Decision Support Tools

    NASA Astrophysics Data System (ADS)

    Bruce, L. M.; Ball, J. E.; Evangilista, P.; Stohlgren, T. J.

    2006-12-01

    as Hyperion imagery), and low spectral/spatial resolution images (such as MODIS imagery). These algorithms include hyperspectral exploitation methods such as stepwise-LDA band selection, optimized spectral band grouping, and stepwise PCA component selection. The PIs have extensive experience with combining these recently- developed methods with conventional classifiers to form an end-to-end automated target recognition (ATR) system for detecting invasive species. The outputs of these systems can be invasive prediction maps, as well as quantitative accuracy assessments like confusion matrices, user accuracies, and producer accuracies. For all of these research endeavors, the PIs have developed numerous advanced signal and image processing methodologies, as well a suite of associated software modules. However, the use of the prototype software modules has been primarily contained to Mississippi State University. The project described in this presentation and paper will enable future systematic inclusion of these software modules into a DSS with national scope.

  15. Multi-pass encoding of hyperspectral imagery with spectral quality control

    NASA Astrophysics Data System (ADS)

    Wasson, Steven; Walker, William

    2015-05-01

    Multi-pass encoding is a technique employed in the field of video compression that maximizes the quality of an encoded video sequence within the constraints of a specified bit rate. This paper presents research where multi-pass encoding is extended to the field of hyperspectral image compression. Unlike video, which is primarily intended to be viewed by a human observer, hyperspectral imagery is processed by computational algorithms that generally attempt to classify the pixel spectra within the imagery. As such, these algorithms are more sensitive to distortion in the spectral dimension of the image than they are to perceptual distortion in the spatial dimension. The compression algorithm developed for this research, which uses the Karhunen-Loeve transform for spectral decorrelation followed by a modified H.264/Advanced Video Coding (AVC) encoder, maintains a user-specified spectral quality level while maximizing the compression ratio throughout the encoding process. The compression performance may be considered near-lossless in certain scenarios. For qualitative purposes, this paper presents the performance of the compression algorithm for several Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Hyperion datasets using spectral angle as the spectral quality assessment function. Specifically, the compression performance is illustrated in the form of rate-distortion curves that plot spectral angle versus bits per pixel per band (bpppb).

  16. Hyperspectral Feature Detection Onboard the Earth Observing One Spacecraft using Superpixel Segmentation and Endmember Extraction

    NASA Technical Reports Server (NTRS)

    Thompson, David R.; Bornstein, Benjamin; Bue, Brian D.; Tran, Daniel Q.; Chien, Steve A.; Castano, Rebecca

    2012-01-01

    We present a demonstration of onboard hyperspectral image processing with the potential to reduce mission downlink requirements. The system detects spectral endmembers and then uses them to map units of surface material. This summarizes the content of the scene, reveals spectral anomalies warranting fast response, and reduces data volume by two orders of magnitude. We have integrated this system into the Autonomous Science craft Experiment for operational use onboard the Earth Observing One (EO-1) Spacecraft. The system does not require prior knowledge about spectra of interest. We report on a series of trial overflights in which identical spacecraft commands are effective for autonomous spectral discovery and mapping for varied target features, scenes and imaging conditions.

  17. Hyperspectral Feature Detection Onboard the Earth Observing One Spacecraft using Superpixel Segmentation and Endmember Extraction

    NASA Technical Reports Server (NTRS)

    Thompson, David R.; Bornstein, Benjamin; Bue, Brian D.; Tran, Daniel Q.; Chien, Steve A.; Castano, Rebecca

    2012-01-01

    We present a demonstration of onboard hyperspectral image processing with the potential to reduce mission downlink requirements. The system detects spectral endmembers and then uses them to map units of surface material. This summarizes the content of the scene, reveals spectral anomalies warranting fast response, and reduces data volume by two orders of magnitude. We have integrated this system into the Autonomous Science craft Experiment for operational use onboard the Earth Observing One (EO-1) Spacecraft. The system does not require prior knowledge about spectra of interest. We report on a series of trial overflights in which identical spacecraft commands are effective for autonomous spectral discovery and mapping for varied target features, scenes and imaging conditions.

  18. Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission

    USGS Publications Warehouse

    Mariotto, Isabella; Thenkabail, Prasad S.; Huete, Alfredo; Slonecker, E. Terrence; Platonov, Alexander

    2013-01-01

    Precise monitoring of agricultural crop biomass and yield quantities is critical for crop production management and prediction. The goal of this study was to compare hyperspectral narrowband (HNB) versus multispectral broadband (MBB) reflectance data in studying irrigated cropland characteristics of five leading world crops (cotton, wheat, maize, rice, and alfalfa) with the objectives of: 1. Modeling crop productivity, and 2. Discriminating crop types. HNB data were obtained from Hyperion hyperspectral imager and field ASD spectroradiometer, and MBB data were obtained from five broadband sensors: Landsat-7 Enhanced Thematic Mapper Plus (ETM +), Advanced Land Imager (ALI), Indian Remote Sensing (IRS), IKONOS, and QuickBird. A large collection of field spectral and biophysical variables were gathered for the 5 crops in Central Asia throughout the growing seasons of 2006 and 2007. Overall, the HNB and hyperspectral vegetation index (HVI) crop biophysical models explained about 25% greater variability when compared with corresponding MBB models. Typically, 3 to 7 HNBs, in multiple linear regression models of a given crop variable, explained more than 93% of variability in crop models. The evaluation of λ1 (400–2500 nm) versus λ2 (400–2500 nm) plots of various crop biophysical variables showed that the best two-band normalized difference HVIs involved HNBs centered at: (i) 742 nm and 1175 nm (HVI742-1175), (ii) 1296 nm and 1054 nm (HVI1296-1054), (iii) 1225 nm and 697 nm (HVI1225-697), and (iv) 702 nm and 1104 nm (HVI702-1104). Among the most frequently occurring HNBs in various crop biophysical models, 74% were located in the 1051–2331 nm spectral range, followed by 10% in the moisture sensitive 970 nm, 6% in the red and red-edge (630–752 nm), and the remaining 10% distributed between blue (400–500 nm), green (501–600 nm), and NIR (760–900 nm). Discriminant models, used for discriminating 3 or 4 or 5 crop types, showed significantly higher accuracies

  19. Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission

    USGS Publications Warehouse

    Mariotto, Isabella; Thenkabail, Prasad S.; Huete, Alfredo; Slonecker, E. Terrence; Platonov, Alexander

    2013-01-01

    Precise monitoring of agricultural crop biomass and yield quantities is critical for crop production management and prediction. The goal of this study was to compare hyperspectral narrowband (HNB) versus multispectral broadband (MBB) reflectance data in studying irrigated cropland characteristics of five leading world crops (cotton, wheat, maize, rice, and alfalfa) with the objectives of: 1. Modeling crop productivity, and 2. Discriminating crop types. HNB data were obtained from Hyperion hyperspectral imager and field ASD spectroradiometer, and MBB data were obtained from five broadband sensors: Landsat-7 Enhanced Thematic Mapper Plus (ETM +), Advanced Land Imager (ALI), Indian Remote Sensing (IRS), IKONOS, and QuickBird. A large collection of field spectral and biophysical variables were gathered for the 5 crops in Central Asia throughout the growing seasons of 2006 and 2007. Overall, the HNB and hyperspectral vegetation index (HVI) crop biophysical models explained about 25% greater variability when compared with corresponding MBB models. Typically, 3 to 7 HNBs, in multiple linear regression models of a given crop variable, explained more than 93% of variability in crop models. The evaluation of λ1 (400–2500 nm) versus λ2 (400–2500 nm) plots of various crop biophysical variables showed that the best two-band normalized difference HVIs involved HNBs centered at: (i) 742 nm and 1175 nm (HVI742-1175), (ii) 1296 nm and 1054 nm (HVI1296-1054), (iii) 1225 nm and 697 nm (HVI1225-697), and (iv) 702 nm and 1104 nm (HVI702-1104). Among the most frequently occurring HNBs in various crop biophysical models, 74% were located in the 1051–2331 nm spectral range, followed by 10% in the moisture sensitive 970 nm, 6% in the red and red-edge (630–752 nm), and the remaining 10% distributed between blue (400–500 nm), green (501–600 nm), and NIR (760–900 nm). Discriminant models, used for discriminating 3 or 4 or 5 crop types, showed significantly higher accuracies

  20. Spatial Field Variability Mapping of Rice Crop using Clustering Technique from Space Borne Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Moharana, S.; Dutta, S.

    2015-12-01

    Precision farming refers to field-specific management of an agricultural crop at a spatial scale with an aim to get the highest achievable yield and to achieve this spatial information on field variability is essential. The difficulty in mapping of spatial variability occurring within an agriculture field can be revealed by employing spectral techniques in hyperspectral imagery rather than multispectral imagery. However an advanced algorithm needs to be developed to fully make use of the rich information content in hyperspectral data. In the present study, potential of hyperspectral data acquired from space platform was examined to map the field variation of paddy crop and its species discrimination. This high dimensional data comprising 242 spectral narrow bands with 30m ground resolution Hyperion L1R product acquired for Assam, India (30th Sept and 3rd Oct, 2014) were allowed for necessary pre-processing steps followed by geometric correction using Hyperion L1GST product. Finally an atmospherically corrected and spatially deduced image consisting of 112 band was obtained. By employing an advanced clustering algorithm, 12 different clusters of spectral waveforms of the crop were generated from six paddy fields for each images. The findings showed that, some clusters were well discriminated representing specific rice genotypes and some clusters were mixed treating as a single rice genotype. As vegetation index (VI) is the best indicator of vegetation mapping, three ratio based VI maps were also generated and unsupervised classification was performed for it. The so obtained 12 clusters of paddy crop were mapped spatially to the derived VI maps. From these findings, the existence of heterogeneity was clearly captured in one of the 6 rice plots (rice plot no. 1) while heterogeneity was observed in rest of the 5 rice plots. The degree of heterogeneous was found more in rice plot no.6 as compared to other plots. Subsequently, spatial variability of paddy field was

  1. Implementation of spot scanning dose optimization and dose calculation for helium ions in Hyperion.

    PubMed

    Fuchs, Hermann; Alber, Markus; Schreiner, Thomas; Georg, Dietmar

    2015-09-01

    Helium ions ((4)He) may supplement current particle beam therapy strategies as they possess advantages in physical dose distribution over protons. To assess potential clinical advantages, a dose calculation module accounting for relative biological effectiveness (RBE) was developed and integrated into the treatment planning system Hyperion. Current knowledge on RBE of (4)He together with linear energy transfer considerations motivated an empirical depth-dependent "zonal" RBE model. In the plateau region, a RBE of 1.0 was assumed, followed by an increasing RBE up to 2.8 at the Bragg-peak region, which was then kept constant over the fragmentation tail. To account for a variable proton RBE, the same model concept was also applied to protons with a maximum RBE of 1.6. Both RBE models were added to a previously developed pencil beam algorithm for physical dose calculation and included into the treatment planning system Hyperion. The implementation was validated against Monte Carlo simulations within a water phantom using γ-index evaluation. The potential benefits of (4)He based treatment plans were explored in a preliminary treatment planning comparison (against protons) for four treatment sites, i.e., a prostate, a base-of-skull, a pediatric, and a head-and-neck tumor case. Separate treatment plans taking into account physical dose calculation only or using biological modeling were created for protons and (4)He. Comparison of Monte Carlo and Hyperion calculated doses resulted in a γ mean of 0.3, with 3.4% of the values above 1 and γ 1% of 1.5 and better. Treatment plan evaluation showed comparable planning target volume coverage for both particles, with slightly increased coverage for (4)He. Organ at risk (OAR) doses were generally reduced using (4)He, some by more than to 30%. Improvements of (4)He over protons were more pronounced for treatment plans taking biological effects into account. All OAR doses were within tolerances specified in the QUANTEC report. The

  2. Implementation of spot scanning dose optimization and dose calculation for helium ions in Hyperion

    SciTech Connect

    Fuchs, Hermann; Schreiner, Thomas; Georg, Dietmar

    2015-09-15

    Purpose: Helium ions ({sup 4}He) may supplement current particle beam therapy strategies as they possess advantages in physical dose distribution over protons. To assess potential clinical advantages, a dose calculation module accounting for relative biological effectiveness (RBE) was developed and integrated into the treatment planning system Hyperion. Methods: Current knowledge on RBE of {sup 4}He together with linear energy transfer considerations motivated an empirical depth-dependent “zonal” RBE model. In the plateau region, a RBE of 1.0 was assumed, followed by an increasing RBE up to 2.8 at the Bragg-peak region, which was then kept constant over the fragmentation tail. To account for a variable proton RBE, the same model concept was also applied to protons with a maximum RBE of 1.6. Both RBE models were added to a previously developed pencil beam algorithm for physical dose calculation and included into the treatment planning system Hyperion. The implementation was validated against Monte Carlo simulations within a water phantom using γ-index evaluation. The potential benefits of {sup 4}He based treatment plans were explored in a preliminary treatment planning comparison (against protons) for four treatment sites, i.e., a prostate, a base-of-skull, a pediatric, and a head-and-neck tumor case. Separate treatment plans taking into account physical dose calculation only or using biological modeling were created for protons and {sup 4}He. Results: Comparison of Monte Carlo and Hyperion calculated doses resulted in a γ{sub mean} of 0.3, with 3.4% of the values above 1 and γ{sub 1%} of 1.5 and better. Treatment plan evaluation showed comparable planning target volume coverage for both particles, with slightly increased coverage for {sup 4}He. Organ at risk (OAR) doses were generally reduced using {sup 4}He, some by more than to 30%. Improvements of {sup 4}He over protons were more pronounced for treatment plans taking biological effects into account. All

  3. Airborne Hyperspectral Imaging System

    NASA Technical Reports Server (NTRS)

    Behar, Alberto E.; Cooper, Moogega; Adler, John; Jacobson, Tobias

    2012-01-01

    A document discusses a hyperspectral imaging instrument package designed to be carried aboard a helicopter. It was developed to map the depths of Greenland's supraglacial lakes. The instrument is capable of telescoping to twice its original length, allowing it to be retracted with the door closed during takeoff and landing, and manually extended in mid-flight. While extended, the instrument platform provides the attached hyperspectral imager a nadir-centered and unobstructed view of the ground. Before flight, the instrument mount is retracted and securely strapped down to existing anchor points on the floor of the helicopter. When the helicopter reaches the destination lake, the door is opened and the instrument mount is manually extended. Power to the instrument package is turned on, and the data acquisition computer is commanded via a serial cable from an onboard user-operated laptop to begin data collection. After data collection is complete, the instrument package is powered down and the mount retracted, allowing the door to be closed in preparation for landing. The present design for the instrument mount consists of a three-segment telescoping cantilever to allow for a sufficient extended length to see around the landing struts and provide a nadir-centered and unobstructed field of view for the hyperspectral imager. This instrument works on the premise that water preferentially absorbs light with longer wavelengths on the red side of the visible spectrum. This property can be exploited in order to remotely determine the depths of bodies of pure freshwater. An imager flying over such a lake receives light scattered from the surface, the bulk of the water column, and from the lake bottom. The strength of absorption of longer-wavelength light depends on the depth of the water column. Through calibration with in situ measurements of the water depths, a depth-determining algorithm may be developed to determine lake depth from these spectral properties of the

  4. Multipurpose Hyperspectral Imaging System

    NASA Technical Reports Server (NTRS)

    Mao, Chengye; Smith, David; Lanoue, Mark A.; Poole, Gavin H.; Heitschmidt, Jerry; Martinez, Luis; Windham, William A.; Lawrence, Kurt C.; Park, Bosoon

    2005-01-01

    A hyperspectral imaging system of high spectral and spatial resolution that incorporates several innovative features has been developed to incorporate a focal plane scanner (U.S. Patent 6,166,373). This feature enables the system to be used for both airborne/spaceborne and laboratory hyperspectral imaging with or without relative movement of the imaging system, and it can be used to scan a target of any size as long as the target can be imaged at the focal plane; for example, automated inspection of food items and identification of single-celled organisms. The spectral resolution of this system is greater than that of prior terrestrial multispectral imaging systems. Moreover, unlike prior high-spectral resolution airborne and spaceborne hyperspectral imaging systems, this system does not rely on relative movement of the target and the imaging system to sweep an imaging line across a scene. This compact system (see figure) consists of a front objective mounted at a translation stage with a motorized actuator, and a line-slit imaging spectrograph mounted within a rotary assembly with a rear adaptor to a charged-coupled-device (CCD) camera. Push-broom scanning is carried out by the motorized actuator which can be controlled either manually by an operator or automatically by a computer to drive the line-slit across an image at a focal plane of the front objective. To reduce the cost, the system has been designed to integrate as many as possible off-the-shelf components including the CCD camera and spectrograph. The system has achieved high spectral and spatial resolutions by using a high-quality CCD camera, spectrograph, and front objective lens. Fixtures for attachment of the system to a microscope (U.S. Patent 6,495,818 B1) make it possible to acquire multispectral images of single cells and other microscopic objects.

  5. Quantitative Hyperspectral Reflectance Imaging

    PubMed Central

    Klein, Marvin E.; Aalderink, Bernard J.; Padoan, Roberto; de Bruin, Gerrit; Steemers, Ted A.G.

    2008-01-01

    Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultural heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of environmental conditions on the object. We describe the basic concept, working principles, construction and performance of a laboratory instrument specifically developed for the analysis of historical documents. The instrument measures calibrated spectral reflectance images at 70 wavelengths ranging from 365 to 1100 nm (near-ultraviolet, visible and near-infrared). By using a wavelength tunable narrow-bandwidth light-source, the light energy used to illuminate the measured object is minimal, so that any light-induced degradation can be excluded. Basic analysis of the hyperspectral data includes a qualitative comparison of the spectral images and the extraction of quantitative data such as mean spectral reflectance curves and statistical information from user-defined regions-of-interest. More sophisticated mathematical feature extraction and classification techniques can be used to map areas on the document, where different types of ink had been applied or where one ink shows various degrees of degradation. The developed quantitative hyperspectral imager is currently in use by the Nationaal Archief (National Archives of The Netherlands) to study degradation effects of artificial samples and original documents, exposed in their permanent exhibition area or stored in their deposit rooms. PMID:27873831

  6. Sublimation-driven erosion on Hyperion: Topographic analysis and landform simulation model tests

    NASA Astrophysics Data System (ADS)

    Howard, Alan D.; Moore, Jeffrey M.; Schenk, Paul M.; White, Oliver L.; Spencer, John

    2012-07-01

    The unique appearance of Hyperion can be explained in part by the loss to space of ballistic ejecta during impact events, as was proposed by Thomas et al. (Thomas, P.C. et al. [2007a]. Icarus 190, 573-584). We conclude that such loss is a partial explanation, accounting for the lack of appreciable intercrater plains on a saturation-cratered surface. In order to create the smooth surfaces and the reticulate, honeycomb pattern of narrow divides between old craters, appreciable subsequent modification of crater morphology must occur through mass-wasting processes accompanied by sublimation, probably facilitated by the loss of CO2 as a component of the relief-supporting matrix of the bedrock. During early stages of crater degradation, steep, crenulate bedrock slopes occupy the upper crater walls with abrupt transitions downslope onto smooth slopes near the angle of repose mantled by mass wasting debris, as can be seen within young craters. Long-continued mass wasting eventually results in slopes totally mantled with particulate debris. This mass wasting effectively destroys small craters, at least in part accounting for the paucity of sub-kilometer craters on Hyperion. Surface temperatures measured by Cassini CIRS range from 58 K to 127 K and imply a surface thermal inertia of 11 ± 2 J m-2 K-1 s-1/2 and bolometric albedo ranging from 0.05 to 0.33. Resulting H2O sublimation rates are only tens of cm per billion years for most of the surface, so the evolution of the observed landforms is likely to require sublimation of more volatile species such as CO2.

  7. New Thermal Infrared Hyperspectral Imagers

    DTIC Science & Technology

    2009-10-01

    ANSI Std Z39-18 New Thermal Infrared Hyperspectral Imagers 4 - 2 RTO-MP-SET-151 UNCLASSIFIED/UNLIMITED uncooled microbolometer detector , has...temperature does not affect on the temperature of the focal plane array, which is in constant New Thermal Infrared Hyperspectral Imagers RTO-MP-SET...Boreman, G.D., Infrared Detectors and Systems, John Wiley & Sons, (1996). [5] Kruse, P.W., Uncooled Thermal Imaging, SPIE Tutorial Texts in Optical

  8. Use of EO-1 Advanced Land Imager (ALI) multispectral image data and real-time field sampling for water quality mapping in the Hirfanlı Dam Lake, Turkey.

    PubMed

    Kavurmacı, Murat; Ekercin, Semih; Altaş, Levent; Kurmaç, Yakup

    2013-08-01

    This paper focuses on the evaluation of water quality variations in Hirfanlı Water Reservoir, which is one of the most important water resources in Turkey, through EO-1 (Earth Observing-1) Advanced Land Imager (ALI) multispectral data and real-time field sampling. The study was materialized in 20 different sampling points during the overpass of the EO-1 ALI sensor over the study area. A multi-linear regression technique was used to explore the relationships between radiometrically corrected EO-1 ALI image data and water quality parameters: chlorophyll a, turbidity, and suspended solids. The retrieved and verified results show that the measured and estimated values of water quality parameters are in good agreement (R (2) >0.93). The resulting thematic maps derived from EO-1 multispectral data for chlorophyll a, turbidity, and suspended solids show the spatial distribution of the water quality parameters. The results indicate that the reservoir has average nutrient values. Furthermore, chlorophyll a, turbidity, and suspended solids values increased at the upstream reservoir and shallow coast of the Hirfanlı Water Reservoir.

  9. Hyperspectral, photogrammetric and morphological characterization of surface impurities over the Greenland ice sheet from remote sensing observations

    NASA Astrophysics Data System (ADS)

    Tedesco, M.; Alexander, P. M.; Briggs, K.; Linares, M.; Mote, T. L.

    2016-12-01

    The spatial and temporal evolution of surface impurities over the Greenland ice sheet plays a crucial role in modulating the meltwater production in view of the associated feedback on albedo. Recent studies have pointed to a `darkening' of the west portion of the ice sheet with this reduction in albedo likely associated with the increasing presence of surface impurities (e.g., soot, dust) and biological activity (e.g., cryoconite holes, algae, bacteria). Regional climate models currently do not account for the presence, evolution and impact on albedo of such impurities, mostly because the underlying processes driving the spectral and morphological evolution of impurities are poorly known. One for the reasons for this is the lack of hyperspectral and high-spatial resolution data over specific regions of the Greenland ice sheet. To put things in perspective: there is more hyperspectral data at high spatial resolution for the planet Mars than for the Greenland ice sheet. In this presentation, we report the results of an analysis using the few available hyperspectral data collected over Greenland by the HYPERION and AVIRIS sensors, in conjunction with visible (RGB) helicopter-based high resolution images and LANDSAT/WorldView data for characterizing the spectral and morphological evolution of surface impurities and cryoconite holes over western Greenland. The hyperspectral data is used to characterize the abundance of different `endmembers' and the temporal evolution (inter-seasonal and intra-seasonal) of surface impurities composition and concentration. Digital photographs from helicopter are used to characterize the size and distribution of cryoconite holes as a function of elevation and, lastly, LANDSAT/WV images are used to study the evolution of `mysterious' shapes that form as a consequence of the accumulation of impurities and the ice flow.

  10. Hyperspectral Imager-Tracker

    NASA Technical Reports Server (NTRS)

    Agurok, Llya

    2013-01-01

    The Hyperspectral Imager-Tracker (HIT) is a technique for visualization and tracking of low-contrast, fast-moving objects. The HIT architecture is based on an innovative and only recently developed concept in imaging optics. This innovative architecture will give the Light Prescriptions Innovators (LPI) HIT the possibility of simultaneously collecting the spectral band images (hyperspectral cube), IR images, and to operate with high-light-gathering power and high magnification for multiple fast- moving objects. Adaptive Spectral Filtering algorithms will efficiently increase the contrast of low-contrast scenes. The most hazardous parts of a space mission are the first stage of a launch and the last 10 kilometers of the landing trajectory. In general, a close watch on spacecraft operation is required at distances up to 70 km. Tracking at such distances is usually associated with the use of radar, but its milliradian angular resolution translates to 100- m spatial resolution at 70-km distance. With sufficient power, radar can track a spacecraft as a whole object, but will not provide detail in the case of an accident, particularly for small debris in the onemeter range, which can only be achieved optically. It will be important to track the debris, which could disintegrate further into more debris, all the way to the ground. Such fragmentation could cause ballistic predictions, based on observations using high-resolution but narrow-field optics for only the first few seconds of the event, to be inaccurate. No optical imager architecture exists to satisfy NASA requirements. The HIT was developed for space vehicle tracking, in-flight inspection, and in the case of an accident, a detailed recording of the event. The system is a combination of five subsystems: (1) a roving fovea telescope with a wide 30 field of regard; (2) narrow, high-resolution fovea field optics; (3) a Coude optics system for telescope output beam stabilization; (4) a hyperspectral

  11. Modeling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands

    NASA Astrophysics Data System (ADS)

    Anne, Naveen J. P.; Abd-Elrahman, Amr H.; Lewis, David B.; Hewitt, Nicole A.

    2014-12-01

    Developing spectral models of soil properties is an important frontier in remote sensing and soil science. Several studies have focused on modeling soil properties such as total pools of soil organic matter and carbon in bare soils. We extended this effort to model soil parameters in areas densely covered with coastal vegetation. Moreover, we investigated soil properties indicative of soil functions such as nutrient and organic matter turnover and storage. These properties include the partitioning of mineral and organic soil between particulate (>53 μm) and fine size classes, and the partitioning of soil carbon and nitrogen pools between stable and labile fractions. Soil samples were obtained from Avicennia germinans mangrove forest and Juncus roemerianus salt marsh plots on the west coast of central Florida. Spectra corresponding to field plot locations from Hyperion hyperspectral image were extracted and analyzed. The spectral information was regressed against the soil variables to determine the best single bands and optimal band combinations for the simple ratio (SR) and normalized difference index (NDI) indices. The regression analysis yielded levels of correlation for soil variables with R2 values ranging from 0.21 to 0.47 for best individual bands, 0.28 to 0.81 for two-band indices, and 0.53 to 0.96 for partial least-squares (PLS) regressions for the Hyperion image data. Spectral models using Hyperion data adequately (RPD > 1.4) predicted particulate organic matter (POM), silt + clay, labile carbon (C), and labile nitrogen (N) (where RPD = ratio of standard deviation to root mean square error of cross-validation [RMSECV]). The SR (0.53 μm, 2.11 μm) model of labile N with R2 = 0.81, RMSECV= 0.28, and RPD = 1.94 produced the best results in this study. Our results provide optimism that remote-sensing spectral models can successfully predict soil properties indicative of ecosystem nutrient and organic matter turnover and storage, and do so in areas with dense

  12. Contextual Detection of Anomalies within Hyperspectral Images

    DTIC Science & Technology

    2011-03-01

    Hyperspectral Imagery (HSI), Unsupervised Target Detection, Target Identification, Contextual Anomaly Detection 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...processing. Hyperspectral imaging has a wide range of applications within remote sensing, not limited to terrain classification , environmental monitoring...Johnson, R. J. (2008). Improved feature extraction, feature selection, and identification techniques that create a fast unsupervised hyperspectral

  13. Hyperspectral imaging polarimeter design and calibration

    NASA Astrophysics Data System (ADS)

    Loe, Richard S.; Duggin, Michael J.

    2002-01-01

    The integration and calibration of a hyperspectral imaging polarimeter is described. The system was designed to exploit subtle spectral details in visible and near-IR hyperspectral polarimetric images. All of the system components were commercial-off-the-shelf. This device uses a tunable liquid crystal filter and 16-bit cooled CCD camera. The challenges of calibrating a hyperspectral polarimeter are discussed.

  14. Compact hyperspectral image sensor based on a novel hyperspectral encoder

    NASA Astrophysics Data System (ADS)

    Hegyi, Alex N.; Martini, Joerg

    2015-06-01

    A novel hyperspectral imaging sensor is demonstrated that can enable breakthrough applications of hyperspectral imaging in domains not previously accessible. Our technology consists of a planar hyperspectral encoder combined with a traditional monochrome image sensor. The encoder adds negligibly to the sensor's overall size, weight, power requirement, and cost (SWaP-C); therefore, the new imager can be incorporated wherever image sensors are currently used, such as in cell phones and other consumer electronics. In analogy to Fourier spectroscopy, the technique maintains a high optical throughput because narrow-band spectral filters are unnecessary. Unlike conventional Fourier techniques that rely on Michelson interferometry, our hyperspectral encoder is robust to vibration and amenable to planar integration. The device can be viewed within a computational optics paradigm: the hardware is uncomplicated and serves to increase the information content of the acquired data, and the complexity of the system, that is, the decoding of the spectral information, is shifted to computation. Consequently, system tradeoffs, for example, between spectral resolution and imaging speed or spatial resolution, are selectable in software. Our prototype demonstration of the hyperspectral imager is based on a commercially-available silicon CCD. The prototype encoder was inserted within the camera's ~1 cu. in. housing. The prototype can image about 49 independent spectral bands distributed from 350 nm to 1250 nm, but the technology may be extendable over a wavelength range from ~300 nm to ~10 microns, with suitable choice of detector.

  15. Selecting optimum base wavelet for extracting spectral alteration features associated with porphyry copper mineralization using hyperspectral images

    NASA Astrophysics Data System (ADS)

    Abdolmaleki, Mehdi; Tabaei, Morteza; Fathianpour, Nader; Gorte, Ben G. H.

    2017-06-01

    Extracting a set of meaningful spectral features could enhance the classification performance. This is particularly important in hyperspectral images where the dataset are very large and time consuming to process. Wavelet transform as a powerful decomposition tool in both low and high frequency components could play an essential role in extracting spectral features of target minerals. Selecting the optimum base wavelet is an important step in wavelet transform. In this research, two criteria to select optimum base wavelet were implemented on three wavelet series including Daubechie (db), symlet (sym) and coiflet (coif). Energy criterion involves entropy factor and energy-to-Shannon entropy ratio while matching shape criterion operates according to correlation coefficients. High ranking base wavelets in both energy and shape criteria, coif1, db3 and db7, are recommended to be utilized in hyperspectral image classification. Neural Network technique was used for classification and trained by means of mineral spectral features related to typical porphyry copper deposits. Non-Linear wavelet feature extraction was employed to select the efficient features as input data. The study area covered by Hyperion data contains two well-known porphyry copper deposits, Darrehzar and Sarcheshmeh, located in the Iranian copper belt. Based on classification error matrix, it is concluded that db7 through 12 selected features exhibits the maximum consistency with the field measured data and can be recommended as an appropriate base wavelet for detecting porphyry copper deposits.

  16. Space-borne hyperspectral remote sensing imagery noise eliminating based on CFFT self-adapted by optimal SNR

    NASA Astrophysics Data System (ADS)

    Liu, Qingjie; Lin, Qizhong; Wang, Liming; Wang, Qinjun; Miao, Fengxian

    2010-09-01

    Space-borne hyperspectral remote sensing imagery, supplying both spatial and spectral information for quantitative remote sensing monitoring, is easily polluted by noises from atmosphere, terrain etc. Based on spectral continuum removing and recovering, traditional fast Fourier Transform (FFT) was extended to Continuum Fast Fourier Transform (CFFT) to separate noise from target information in frequency domain (FD). Thus, low-pass filter for reserving useful information was designed for eliminating noise, with its cut-off frequency selected self-adaptively by optimal signal-tonoise ratio (SNR). Hyperion hyperspectral imageries of Beijing and Xinjiang China were singled out for noise removing to validate the filtering ability of the Continuum Fast Fourier Transform self-adapted by Optimal Signal-noise Ratio(CFFTOSNR) method with qualitative description and quantificational indexs, including mean, variance, entropy, definition and SNR etc. Experiment result shows that CFFTOSNR does well in reducing the gauss white noises in spectral domain and stripe and band-subtracting noise in spatial domain respectively, while the quantificational indexs of filtered imagery are all improved, with entropy of post-processed image obviously increased by 5 db.

  17. Bitcoin, Blockchains and Efficient Distributed Spacecraft Mission Control

    NASA Technical Reports Server (NTRS)

    Mandl, Dan

    2017-01-01

    Earth Observing 1 (E0-1) satellite has an imaging spectrometer (hyperspectral) instrument called Hyperion. The satellite is able to image any spot on Earth in the nadir looking direction every 16 days. With slewing of the satellite and allowing for up to a 23 degree view angle, any spot on the Earth can be imaged approximately every 2 to 3 days. EO-1 has been used to track many natural hazards such as wildfires, volcanoes and floods. An enhanced capability that is sought is the ability to image natural hazards in a daily time series for space based imaging spectrometers. The Hyperion can not provide this capability on EO-1 with the present polar orbit. However, a constellation of cubesats each powered with Intelligent Payload Modules, and each with copies of a commercial imaging spectrometer, positioned strategically in the same orbit, can be used to provide daily coverage, cost-effectively.

  18. New generation handheld hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Wu, Huawen (Owen); Li, Hui; Tang, Shengjun

    2016-10-01

    A miniaturized hyper-spectral imager is enabled with image sensor integrated with dispersing elements in a very compact form factor, removing the need for expensive, moving, bulky and complex optics that have been used in conventional hyper-spectral imagers for decades. The result is a handheld spectral imager that can be installed on miniature UAV drones or conveyor belts in production lines. Eventually, small handhelds can be adapted for use in outpatient medical clinics for point-of-care diagnostics and other in-field applications.

  19. Medical hyperspectral imaging: a review.

    PubMed

    Lu, Guolan; Fei, Baowei

    2014-01-01

    Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.

  20. Medical hyperspectral imaging: a review

    PubMed Central

    Lu, Guolan; Fei, Baowei

    2014-01-01

    Abstract. Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. PMID:24441941

  1. A Data Transfer Fusion Method for Discriminating Similar Spectral Classes

    PubMed Central

    Wang, Qingyan; Zhang, Junping

    2016-01-01

    Hyperspectral data provide new capabilities for discriminating spectrally similar classes, but such class signatures sometimes will be difficult to analyze. To incorporate reliable useful information could help, but at the same time, may also lead increased dimensionality of the feature vector making the hyperspectral data larger than expected. It is challenging to apply discriminative information from these training data to testing data that are not in the same feature space and with different data distributions. A data fusion method based on transfer learning is proposed, in which transfer learning is introduced into boosting algorithm, and other out-date data are used to instruct hyperspectral image classification. In order to validate the method, experiments are conducted on EO-1 Hyperion hyperspectral data and ROSIS hyperspectral data. Significant improvements have been achieved in terms of accuracy compared to the results generated by conventional classification approaches. PMID:27854238

  2. Hyperspectral Mapping of the Invasive Species Pepperweed and the Development of a Habitat Suitability Model

    NASA Technical Reports Server (NTRS)

    Nguyen, Andrew; Gole, Alexander; Randall, Jarom; Dlott, Glade; Zhang, Sylvia; Alfaro, Brian; Schmidt, Cindy; Skiles, J. W.

    2011-01-01

    Mapping and predicting the spatial distribution of invasive plant species is central to habitat management, however difficult to implement at landscape and regional scales. Remote sensing techniques can reduce the impact field campaigns have on these ecologically sensitive areas and can provide a regional and multi-temporal view of invasive species spread. Invasive perennial pepperweed (Lepidium latifolium) is now widespread in fragmented estuaries of the South San Francisco Bay, and is shown to degrade native vegetation in estuaries and adjacent habitats, thereby reducing forage and shelter for wildlife. The purpose of this study is to map the present distribution of pepperweed in estuarine areas of the South San Francisco Bay Salt Pond Restoration Project (Alviso, CA), and create a habitat suitability model to predict future spread. Pepperweed reflectance data were collected in-situ with a GER 1500 spectroradiometer along with 88 corresponding pepperweed presence and absence points used for building the statistical models. The spectral angle mapper (SAM) classification algorithm was used to distinguish the reflectance spectrum of pepperweed and map its distribution using an image from EO-1 Hyperion. To map pepperweed, we performed a supervised classification on an ASTER image with a resulting classification accuracy of 71.8%. We generated a weighted overlay analysis model within a geographic information system (GIS) framework to predict areas in the study site most susceptible to pepperweed colonization. Variables for the model included propensity for disturbance, status of pond restoration, proximity to water channels, and terrain curvature. A Generalized Additive Model (GAM) was also used to generate a probability map and investigate the statistical probability that each variable contributed to predict pepperweed spread. Results from the GAM revealed distance to channels, distance to ponds and curvature were statistically significant (p < 0.01) in determining

  3. Hyperspectral Mapping of the Invasive Species Pepperweed and the Development of a Habitat Suitability Model

    NASA Astrophysics Data System (ADS)

    Nguyen, A.; Gole, A.; Randall, J.; Dlott, G. A.; Zhang, S.; Alfaro, B.; Schmidt, C.; Skiles, J. W.

    2011-12-01

    Mapping and predicting the spatial distribution of invasive plant species is central to habitat management, however difficult to implement at landscape and regional scales. Remote sensing techniques can reduce the cost of field campaigns and can provide a regional and multi-temporal view of invasive species spread. Invasive perennial pepperweed (Lepidium latifolium) is now widespread in fragmented estuaries of the South San Francisco Bay, and is shown to degrade native vegetation in estuaries and adjacent habitats, thereby reducing forage and shelter for wildlife. The purpose of this study is to map the current distribution of pepperweed in estuarine areas of the South San Francisco Bay Salt Pond Restoration Project, and create a habitat suitability model to predict future spread. Pepperweed reflectance data were collected in-situ with a GER 1500 spectroradiometer along with 88 corresponding pepperweed presence and absence points used for building the statistical models. The spectral angle mapper (SAM) classification algorithm was used to distinguish the reflectance spectrum of pepperweed and map its distribution using an EO-1 Hyperion satellite image. To map pepperweed, a supervised classification was performed on an ASTER image with a resulting classification accuracy of 71.8%. We generated a weighted overlay analysis model within a geographic information system (GIS) framework to predict areas in the study site most susceptible to pepperweed colonization. Variables for the model included propensity for disturbance, status of pond restoration, proximity to water channels, and terrain curvature. A Generalized Additive Model (GAM) was also used to generate a probability map and investigate the statistical probability that each variable contributed to predict pepperweed spread. Results from the GAM revealed distance to channels, distance to ponds and curvature were statistically significant (p < 0.01) in determining the locations of suitable pepperweed habitats.

  4. Hyperspectral characterization of atherosclerotic plaques

    NASA Astrophysics Data System (ADS)

    Randeberg, Lise L.; Larsen, Eivind L. P.; Aksnes, Astrid; Haugen, Olav A.; Svaasand, Lars O.

    2009-07-01

    Imaging modalities like hyperspectral imaging create large amounts of data. Time efficient, automated analytic techniques are therefore required to enjoy the power of such methods. In this study it was investigated if hyperspectral imaging followed by automated noise filtering and statistical image analysis is a suitable method for characterization of the macroscopic structure of atherosclerotic lesions. Ten human aorta samples (6×8 cm) were collected during autopsy. Hyperspectral white light and fluorescence images and 5 - 6 biopsies were collected from each sample. The biopsies were stained (HES, Sudan red), and grouped according to histology. All images were noise filtered and normalized. Fluorescence spectra were collected from all biopsied regions, and used to compute average spectra for each histological group. Supervised classification was performed using Spectral angle mapping (SAM) with the average spectra as endmembers. K-means- and ISO-data clustering was used for unsupervised classification. The results show that noise filtering and normalization is essential for reliable classification. Supervised classification was in general found to perform better than unsupervised classification. However, the SAM results strongly depend on the variation in the spectra used to compute the average endmember spectra. The analysis show that fatty deposits, calcifications, connective tissue and hemoglobin can be identified. The lesions were found to have a complex structure where vulnerable regions could be found next to stabile regions within the same lesion. In conclusion hyperspectral imaging, automated filtering and -analysis was found to be a suitable tool to classify advanced atherosclerotic lesions.

  5. Estimation of a genetically viable population for multigenerational interstellar voyaging: Review and data for project Hyperion

    NASA Astrophysics Data System (ADS)

    Smith, Cameron M.

    2014-04-01

    Designing interstellar starships for human migration to exoplanets requires establishing the starship population, which factors into many variables including closed-ecosystem design, architecture, mass and propulsion. I review the central issues of population genetics (effects of mutation, migration, selection and drift) for human populations on such voyages, specifically referencing a roughly 5-generation (c. 150-year) voyage currently in the realm of thought among Icarus Interstellar's Project Hyperion research group. I present several formulae as well as concrete numbers that can be used to help determine populations that could survive such journeys in good health. I find that previously proposed such populations, on the order of a few hundred individuals, are significantly too low to consider based on current understanding of vertebrate (including human) genetics and population dynamics. Population genetics theory, calculations and computer modeling determine that a properly screened and age- and sex-structured total founding population (Nc) of anywhere from roughly 14,000 to 44,000 people would be sufficient to survive such journeys in good health. A safe and well-considered Nc figure is 40,000, an Interstellar Migrant Population (IMP) composed of an Effective Population [Ne] of 23,400 reproductive males and females, the rest being pre- or post-reproductive individuals. This number would maintain good health over five generations despite (a) increased inbreeding resulting from a relatively small human population, (b) depressed genetic diversity due to the founder effect, (c) demographic change through time and (d) expectation of at least one severe population catastrophe over the 5-generation voyage.

  6. Multi range spectral feature fitting for hyperspectral imagery in extracting oilseed rape planting area

    NASA Astrophysics Data System (ADS)

    Pan, Zhuokun; Huang, Jingfeng; Wang, Fumin

    2013-12-01

    Spectral feature fitting (SFF) is a commonly used strategy for hyperspectral imagery analysis to discriminate ground targets. Compared to other image analysis techniques, SFF does not secure higher accuracy in extracting image information in all circumstances. Multi range spectral feature fitting (MRSFF) from ENVI software allows user to focus on those interesting spectral features to yield better performance. Thus spectral wavelength ranges and their corresponding weights must be determined. The purpose of this article is to demonstrate the performance of MRSFF in oilseed rape planting area extraction. A practical method for defining the weighted values, the variance coefficient weight method, was proposed to set up criterion. Oilseed rape field canopy spectra from the whole growth stage were collected prior to investigating its phenological varieties; oilseed rape endmember spectra were extracted from the Hyperion image as identifying samples to be used in analyzing the oilseed rape field. Wavelength range divisions were determined by the difference between field-measured spectra and image spectra, and image spectral variance coefficient weights for each wavelength range were calculated corresponding to field-measured spectra from the closest date. By using MRSFF, wavelength ranges were classified to characterize the target's spectral features without compromising spectral profile's entirety. The analysis was substantially successful in extracting oilseed rape planting areas (RMSE ≤ 0.06), and the RMSE histogram indicated a superior result compared to a conventional SFF. Accuracy assessment was based on the mapping result compared with spectral angle mapping (SAM) and the normalized difference vegetation index (NDVI). The MRSFF yielded a robust, convincible result and, therefore, may further the use of hyperspectral imagery in precision agriculture.

  7. Hyperspectral Remote Sensing Techniques in Predicting Phycocyanin Concentrations in Cyanobacteria: A Comprehensive Study

    NASA Astrophysics Data System (ADS)

    Mishra, S.; Mishra, D. R.; Schluchter, W. M.

    2009-12-01

    The purpose of this research was to evaluate the performance of existing spectral band ratio algorithms and develop a novel algorithm to quantify phycocyanin (PC) in cyanobacteria using hyperspectral remotely-sensed data. We performed four spectroscopic experiments on two different laboratory cultured cyanobacterial species and found that the existing band ratio algorithms are highly sensitive to chlorophylls, making them inaccurate in predicting cyanobacterial abundance in the presence of other chlorophyll-containing organisms. Our results also show that the widely used 654 nm reflectance peak in existing algorithms is highly sensitive to changes in chlorophyll-a concentration and offers poor PC predictive ability. We present a novel spectral band ratio algorithm that is least sensitive to the presence of chlorophyll. The newly developed band ratio model showed promising results by yielding low root mean squared error (RMSE, 15,260 cells mL-1) and significantly low relative root mean squared error (RMS, 101%) as compared to the existing band ratio algorithms. Natural logarithmic transformation of the new model yielded the lowest RMSE (13,885 cells mL-1) and a high coefficient of determination (0.95) between measured and predicted PC concentration. We also show that the new algorithm is species independent and accurately retrieves PC concentration in the presence of varying amount of chlorophyll-a in the system. Band setting of the model confirms that it can be used for retrieval of PC using hyperspectral sensors such as Hyperion as well as data acquired by other airborne sensors. Figure (A, B, C) Percent reflectance spectra of Synechocystis PCC 6803 from Exp I, II, III respectively. (D) Percent reflectance spectra of Anabaena from Exp IV. Data collected from these experiments were included in the evaluation of existing PC predictive models and the calibration and validation of the new spectral band ratio model.

  8. Analyses of the soil surface dynamic of South African Kalahari salt pans based on hyperspectral and multitemporal data

    NASA Astrophysics Data System (ADS)

    Milewski, Robert; Chabrillat, Sabine; Behling, Robert; Mielke, Christian; Schleicher, Anja Maria; Guanter, Luis

    2016-04-01

    The consequences of climate change represent a major threat to sustainable development and growth in Southern Africa. Understanding the impact on the geo- and biosphere is therefore of great importance in this particular region. In this context the Kalahari salt pans (also known as playas or sabkhas) and their peripheral saline and alkaline habitats are an ecosystem of major interest. They are very sensitive to environmental conditions, and as thus hydrological, mineralogical and ecological responses to climatic variations can be analysed. Up to now the soil composition of salt pans in this area have been only assessed mono-temporally and on a coarse regional scale. Furthermore, the dynamic of the salt pans, especially the formation of evaporites, is still uncertain and poorly understood. High spectral resolution remote sensing can estimate evaporite content and mineralogy of soils based on the analyses of the surface reflectance properties within the Visible-Near InfraRed (VNIR 400-1000 nm) and Short-Wave InfraRed (SWIR 1000-2500 nm) regions. In these wavelength regions major chemical components of the soil interact with the electromagnetic radiation and produce characteristic absorption features that can be used to derive the properties of interest. Although such techniques are well established for the laboratory and field scale, the potential of current (Hyperion) and upcoming spaceborne sensors such as EnMAP for quantitative mineralogical and salt spectral mapping is still to be demonstrated. Combined with hyperspectral methods, multitemporal remote sensing techniques allow us to derive the recent dynamic of these salt pans and link the mineralogical analysis of the pan surface to major physical processes in these dryland environments. In this study we focus on the analyses of the Namibian Omongwa salt pans based on satellite hyperspectral imagery and multispectral time-series data. First, a change detection analysis is applied using the Iterative

  9. [Estimation of sparse vegetation coverage in arid region based on hyperspectral mixed pixel decomposition].

    PubMed

    Li, Xiao-Song; Gao, Zhi-Hai; Li, Zeng-Yuan; Bai, Li-Na; Wang, Beng-Yu

    2010-01-01

    Based on Hyperion hyperspectral image data, the image-derived shifting sand, false-Gobi spectra, and field-measured sparse vegetation spectra were taken as endmembers, and the sparse vegetation coverage (< 40%) in Minqin oasis-desert transitional zone of Gansu Province was estimated by using fully constrained linear spectral mixture model (LSMM) and non-constrained LSMM, respectively. The results showed that the sparse vegetation fraction based on fully constrained LSMM described the actual sparse vegetation distribution. The differences between sparse vegetation fraction and field-measured vegetation coverage were less than 5% for all samples, and the RMSE was 3.0681. However, the sparse vegetation fraction based on non-constrained LSMM was lower than the field-measured vegetation coverage obviously, and the correlation between them was poor, with a low R2 of 0.5855. Compared with McGwire's corresponding research, the sparse vegetation coverage estimation in this study was more accurate and reliable, having expansive prospect for application in the future.

  10. Application of Gibbs sampling in efficient hyperspectral unmixing based on the mixtures of Dirichlet components

    NASA Astrophysics Data System (ADS)

    Babakan, Solmaz; Oskouei, Majid Mohammady

    2015-01-01

    The independent component analysis has been commonly employed in hyperspectral unmixing. However, the success of this method is highly dependent on the independency of its sources assumption. Dependent component analysis (DECA) algorithm, which utilizes a Dirichlet mixture model, was developed to provide more adequate spectral unmixing of dependent sources. Estimation of the unknown model parameters using the expectation maximization algorithm in DECA resulted in some insufficiencies. DECAGibbs algorithm is introduced to improve unmixing accuracy by applying the Gibbs sampling method to the parameter estimation process of DECA, which is conducted in different manners of modeling the observations. Functionality of the DECAGibbs algorithm is examined through the artificial datasets and an AVIRIS image of Cuprite, Nevada, indicating better decomposition of mixed observations. Finally, the best performing model was employed in mineralogical mapping of the Lahroud region, northwest Iran, by a Hyperion image. The results represent the high reliability of the proposed method according to the geological studies of the area. Since the practical application of the mixture models relies upon the efficient estimation of their involved parameters, the performance of the DECA algorithm is improved by employing the Bayesian parameter estimation approaches in this research.

  11. Hyperspectral clustering and unmixing for studying the ecology of state formation and complex societies

    NASA Astrophysics Data System (ADS)

    Kwong, Justin D.; Messinger, David W.; Middleton, William D.

    2009-08-01

    This project is an application of hyperspectral classification and unmixing in support of an ongoing archaeological study. The study region is the Oaxaca Valley located in the state of Oaxaca, Mexico on the southern coast. This was the birthplace of the Zapotec civilization which grew into a complex state level society. Hyperion imagery is being collected over a 30,000 km2 area. Classification maps of regions of interest are generated using K-means clustering and a novel algorithm called Gradient Flow. Gradient Flow departs from conventional stochastic or deterministic approaches, using graph theory to cluster spectral data. Spectral unmixing is conducted using the RIT developed algorithm Max-D to automatically find end members. Stepwise unmixing is performed to better model the data using the end members found be Max-D. Data are efficiently shared between imaging scientists and archaeologists using Google Earth to stream images over the internet rather than downloading them. The overall goal of the project is to provide archaeologists with useful information maps without having to interpret the raw data.

  12. Combination of Biochemical and Hyperspectral Remote Sensing Methods for Detection of Heavy Metal Pollutions in Eucalyptus Leaves (case Study: the City of Bam)

    NASA Astrophysics Data System (ADS)

    Khalili, R.; Anvari, S.; Honarmand, M.

    2015-12-01

    Environmental pollution may be caused due to mines and mineral deposits. The accumulation of the associated heavy metals in soil and especially at the root zone of plants would result in plant contamination. This paper aims to detect the dominant heavy metals in Eucalyptus leaves using both biochemical and hyperspectral techniques for northern part of Bam in Iran. In this regards, using biochemical approach, some Eucalyptus leaf samples were collected, and their laboratory data containing the concentration of heavy metals were measured by Graphite Furnace Atomic Absorption Spectrometry (GF-AAS). Using ASD FieldSpec3 Pro spectrometer (Analytical Spectral Devices) also, the spectral profile of leaf samples was measured and compared with healthy ones namely control samples. Finally, using supervised classification methods, the spatial distribution of heavy metals was determined by combination of biochemical results, spectral measurements of samples and hyperspectral images of EO-1 satellite. Results showed that Eucalyptus trees accumulates the heavy metals of As and Pb with the average concentrations equalling 9.98 and 14.31 ppb while compared with the relevant control samples equalling 2.32 and 8.98 ppb, respectively. Combination of biochemical and hyperspectral data analysis also proved by increasing heavy metals concentrations in all samples, their spectral profiles for the visible and near infrared regions will be changed in comparison with those obtained from the control sample.

  13. Analysis of hyperspectral data for estimation of temperate forest canopy nitrogen concentration: comparison between an airborne (AVIRIS) and a spaceborne (Hyperion) sensor

    Treesearch

    Marie-Louise Smith; Mary E. Martin; Lucie Plourde; Scott V. Ollinger

    2003-01-01

    Field studies among diverse biomes demonstrate that mass-based nitrogen concentration at leaf and canopy scales is strongly related to carbon uptake and cycling. Combined field and airborne imaging spectrometry studies demonstrate the capacity for accurate empirical estimation of forest canopy N concentration and other biochemical constituents at scales from forest...

  14. Modelling of moon surface charging in the Saturn system - comparison with Cassini observations at Rhea and Hyperion

    NASA Astrophysics Data System (ADS)

    Nordheim, T.; Jones, G. H.; Roussos, E.; Coates, A. J.

    2013-12-01

    Electrical surface charging is thought to be a ubiquitous process in the Solar System, affecting objects embedded in magnetospheric as well as solar wind plasma. In the Saturn system, previous studies (Roussos et al, 2010) have predicted strongly negative surface potentials on several of its moons under certain conditions, and recently, such negatively charged surfaces have been remotely detected at the Moons Rhea (Jones et al, in prep) and Hyperion (Nordheim et al, in prep) using the CAPS-ELS instrument on Cassini. Surface charging has also been implicated in dust levitation and transport on the Moon and asteroids, and observations of Saturn's small icy moon Atlas has revealed a surface texture that may be partially explained by motion of electrostatically charged dust grains (Hirato & Miyamoto, 2012). Furthermore, faint ring arcs have been detected around several of Saturn's small moons (Anthe, Methone) and it has been suggested that these are in fact created by electrostatic acceleration and ejection of dust grains. Using a modified version of the method employed by (Roussos et al, 2010) and appropriate plasma parameters for the relevant moon encounters, we compare the predicted and remotely sensed surface potentials at Rhea and Hyperion for a range of simulation parameters, including secondary electron emission yield and incident electron and ion flux. In addition, the potential for submicron dust grain acceleration and ejection at Saturn's moons will be investigated using a simple model for dust grain levitation.

  15. Hyperspectral remote sensing of vegetation

    USGS Publications Warehouse

    Thenkabail, Prasad S.; Lyon, John G.; Huete, Alfredo

    2011-01-01

    Hyperspectral narrow-band (or imaging spectroscopy) spectral data are fast emerging as practical solutions in modeling and mapping vegetation. Recent research has demonstrated the advances in and merit of hyperspectral data in a range of applications including quantifying agricultural crops, modeling forest canopy biochemical properties, detecting crop stress and disease, mapping leaf chlorophyll content as it influences crop production, identifying plants affected by contaminants such as arsenic, demonstrating sensitivity to plant nitrogen content, classifying vegetation species and type, characterizing wetlands, and mapping invasive species. The need for significant improvements in quantifying, modeling, and mapping plant chemical, physical, and water properties is more critical than ever before to reduce uncertainties in our understanding of the Earth and to better sustain it. There is also a need for a synthesis of the vast knowledge spread throughout the literature from more than 40 years of research.

  16. Compositional analysis of Hyperion with the Cassini Visual and Infrared Mapping Spectrometer

    NASA Astrophysics Data System (ADS)

    Brad Dalton, J.; Cruikshank, Dale P.; Clark, Roger N.

    2012-08-01

    Compositional mapping of the surface of Hyperion using Cassini Visual and Infrared Mapping Spectrometer (VIMS) observations reveals a heterogeneous surface dominated by water ice accompanied by additional materials. Carbon dioxide, as evidenced by a prominent absorption band centered at 4.26 μm, is distributed over most of the surface, including icy regions. This does not represent exposures of pure CO2 ice, but concentrations of CO2 molecules adsorbed on other materials or complexed in H2O, perhaps as a clathrate (Cruikshank, D.P., Meyer, A.W., Brown, R.H., Clark, R.N., Jaumann, R., Stephan, K., Hibbitts, C.A., Sandford, S.A., Mastrapa, R., Filacchione, G., Dalle Ore, C.M., Nicholson, P.D., Buratti, B.J., McCord, T.B., Nelson, R.M., Dalton, J.B., Baines, K.H., Matson, D.L., The VIMS Team [2010]. Icarus 206, 561-572). Localized deposits of low-albedo material in subcircular depressions exhibit spectral absorptions indicative of C-H in aromatic (3.29 μm) and aliphatic (3.35-3.50 μm) hydrocarbons. An absorption band at 2.42 μm that is also seen on other saturnian satellites, tentatively identified as H2 (Clark, R.N. et al. [2011]. In: Proc. AAS-DPS Meeting, 43, 1563; Clark et al., in preparation, 2012) adsorbed on dark material grains, is also prominent. Our best spectral models included H2O and CO2 ice, with small amounts of nanophase Fe and Fe2O3. Weaker and more spatially scattered absorption features are also found at 4.48, 4.60, and 4.89 μm, although no clear molecular identifications have yet been made. While strongest in the low-albedo deposits, the CO2, hydrocarbon and putative H2 bands vary in strength throughout the icy regions, as do the 4.48-, 4.60- and 4.89-μm bands, suggesting that this background ice is laced with a complex mixture of non-ice compounds.

  17. Wide area Hyperspectral Motion Imaging

    DTIC Science & Technology

    2017-02-03

    interest . However, traditional kinematic data based tracking algorithms have challenges in wide area motion imagery due to a relatively low...sampling rate , low spatial resolution, occlusions, changes in lighting, and multiple confusers. Recent studies have shown that incorporating hyperspectral...For example, to cover 64 km2 at a ground sampling distance of 0.5m, an update rate of 1Hz, and up to 256 spectral bands, a dispersive grating

  18. Hyperspectral-Augmented Target Tracking

    DTIC Science & Technology

    2008-03-01

    Simulation of Sensor Data Measurement Forma - tion . . . . . . . . . . . . . . . . . . . . . . . . 3-5 3.1.2.1 Hyperspectral Sensor . . . . . . . . . . . 3-5...interaction between these system elements is shown in Fig. 2.1. 2.3.1 Panchromatic Video Sensor Data Processing and Measurement Forma - tion. Similar...metric” distance measures. This research evaluates distance metrics (Eu- clidean, Manhattan /cityblock, Chebyshev, and Canberra) and other non-metric

  19. Single-pixel hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Suo, Jinli; Wang, Yuwang; Bian, Liheng; Dai, Qionghai

    2016-10-01

    Conventional multispectral imaging methods detect photons of a 3D hyperspectral data cube separately either in the spatial or spectral dimension using array detectors, and are thus photon inefficient and spectrum range limited. Besides, they are usually bulky and highly expensive. To address these issues, this paper presents single-pixel multispectral imaging techniques, which are of high sensitivity, wide spectrum range, low cost and light weight. Two mechanisms are proposed, and experimental validation are also reported.

  20. Hyperspectral Imaging of River Systems

    DTIC Science & Technology

    2010-09-30

    plume. The 300 m MERIS pixels do a much better job of imaging the river mouth. 3 The Hyperspectral Imager for the Coastal Ocean (HICO; Corson et...radiances, L1B data is supplied by NRL’s HICOTM team [ Corson 2010]. (b) At-sensor radiance for black pixel in Fig. 1 (a). The raw data is indicated...that goal. RELATED PROJECTS I continue to collaborate regularly with colleagues at the NRL Remote Sensing Division (Code 7200; Mike Corson and

  1. Hyperspectral imaging of bruised skin

    NASA Astrophysics Data System (ADS)

    Randeberg, Lise L.; Baarstad, Ivar; Løke, Trond; Kaspersen, Peter; Svaasand, Lars O.

    2006-02-01

    Bruises can be important evidence in legal medicine, for example in cases of child abuse. Optical techniques can be used to discriminate and quantify the chromophores present in bruised skin, and thereby aid dating of an injury. However, spectroscopic techniques provide only average chromophore concentrations for the sampled volume, and contain little information about the spatial chromophore distribution in the bruise. Hyperspectral imaging combines the power of imaging and spectroscopy, and can provide both spectroscopic and spatial information. In this study a hyperspectral imaging system developed by Norsk Elektro Optikk AS was used to measure the temporal development of bruised skin in a human volunteer. The bruises were inflicted by paintball bullets. The wavelength ranges used were 400 - 1000 nm (VNIR) and 900 - 1700 nm (SWIR), and the spectral sampling intervals were 3.7 and 5 nm, respectively. Preliminary results show good spatial discrimination of the bruised areas compared to normal skin. Development of a white spot can be seen in the central zone of the bruises. This central white zone was found to resemble the shape of the object hitting the skin, and is believed to develop in areas where the impact caused vessel damage. These results show that hyperspectral imaging is a promising technique to evaluate the temporal and spatial development of bruises on human skin.

  2. Fractal Characterization of Hyperspectral Imagery

    NASA Technical Reports Server (NTRS)

    Qiu, Hon-Iie; Lam, Nina Siu-Ngan; Quattrochi, Dale A.; Gamon, John A.

    1999-01-01

    Two Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral images selected from the Los Angeles area, one representing urban and the other, rural, were used to examine their spatial complexity across their entire spectrum of the remote sensing data. Using the ICAMS (Image Characterization And Modeling System) software, we computed the fractal dimension values via the isarithm and triangular prism methods for all 224 bands in the two AVIRIS scenes. The resultant fractal dimensions reflect changes in image complexity across the spectral range of the hyperspectral images. Both the isarithm and triangular prism methods detect unusually high D values on the spectral bands that fall within the atmospheric absorption and scattering zones where signature to noise ratios are low. Fractal dimensions for the urban area resulted in higher values than for the rural landscape, and the differences between the resulting D values are more distinct in the visible bands. The triangular prism method is sensitive to a few random speckles in the images, leading to a lower dimensionality. On the contrary, the isarithm method will ignore the speckles and focus on the major variation dominating the surface, thus resulting in a higher dimension. It is seen where the fractal curves plotted for the entire bandwidth range of the hyperspectral images could be used to distinguish landscape types as well as for screening noisy bands.

  3. Hyperspectral imaging of ischemic wounds

    NASA Astrophysics Data System (ADS)

    Gnyawali, Surya C.; Elgharably, Haytham; Melvin, James; Huang, Kun; Bergdall, Valerie; Allen, David W.; Hwang, Jeeseong; Litorja, Maritoni; Shirley, Eric; Sen, Chandan K.; Xu, Ronald

    2012-03-01

    Optical imaging has the potential to achieve high spatial resolution and high functional sensitivity in wound assessment. However, clinical acceptance of many optical imaging devices is hampered by poor reproducibility, low accuracy, and lack of biological interpretation. We developed an in vivo model of ischemic flap for non-contact assessment of wound tissue functional parameters and spectral characteristics. The model was created by elevating the bipedicle skin flaps of a domestic pig from the underlying vascular bed and inhibiting graft bed reperfusion by a silastic sheet. Hyperspectral imaging was carried out on the ischemic flap model and compared with transcutaneous oxygen tension and perfusion measurements at different positions of the wound. Hyperspectral images have also been captured continuously during a post-occlusive reactive hyperemia (PORH) procedure. Tissue spectral characteristics obtained by hyperspectral imaging correlated well with cutaneous tissue oxygen tension, blood perfusion, and microscopic changes of tissue morphology. Our experiments not only demonstrated the technical feasibility for quantitative assessment of chronic wound but also provided a potential digital phantom platform for quantitative characterization and calibration of medical optical devices.

  4. Longwave infrared compressive hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Dupuis, Julia R.; Kirby, Michael; Cosofret, Bogdan R.

    2015-06-01

    Physical Sciences Inc. (PSI) is developing a longwave infrared (LWIR) compressive sensing hyperspectral imager (CS HSI) based on a single pixel architecture for standoff vapor phase plume detection. The sensor employs novel use of a high throughput stationary interferometer and a digital micromirror device (DMD) converted for LWIR operation in place of the traditional cooled LWIR focal plane array. The CS HSI represents a substantial cost reduction over the state of the art in LWIR HSI instruments. Radiometric improvements for using the DMD in the LWIR spectral range have been identified and implemented. In addition, CS measurement and sparsity bases specifically tailored to the CS HSI instrument and chemical plume imaging have been developed and validated using LWIR hyperspectral image streams of chemical plumes. These bases enable comparable statistics to detection based on uncompressed data. In this paper, we present a system model predicting the overall performance of the CS HSI system. Results from a breadboard build and test validating the system model are reported. In addition, the measurement and sparsity basis work demonstrating the plume detection on compressed hyperspectral images is presented.

  5. Hyperspectral imaging for nondestructive evaluation of tomatoes

    USDA-ARS?s Scientific Manuscript database

    Machine vision methods for quality and defect evaluation of tomatoes have been studied for online sorting and robotic harvesting applications. We investigated the use of a hyperspectral imaging system for quality evaluation and defect detection for tomatoes. Hyperspectral reflectance images were a...

  6. Progressive band processing for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Schultz, Robert C.

    Hyperspectral imaging has emerged as an image processing technique in many applications. The reason that hyperspectral data is called hyperspectral is mainly because the massive amount of information provided by the hundreds of spectral bands that can be used for data analysis. However, due to very high band-to-band correlation much information may be also redundant. Consequently, how to effectively and best utilize such rich spectral information becomes very challenging. One general approach is data dimensionality reduction which can be performed by data compression techniques, such as data transforms, and data reduction techniques, such as band selection. This dissertation presents a new area in hyperspectral imaging, to be called progressive hyperspectral imaging, which has not been explored in the past. Specifically, it derives a new theory, called Progressive Band Processing (PBP) of hyperspectral data that can significantly reduce computing time and can also be realized in real-time. It is particularly suited for application areas such as hyperspectral data communications and transmission where data can be communicated and transmitted progressively through spectral or satellite channels with limited data storage. Most importantly, PBP allows users to screen preliminary results before deciding to continue with processing the complete data set. These advantages benefit users of hyperspectral data by reducing processing time and increasing the timeliness of crucial decisions made based on the data such as identifying key intelligence information when a required response time is short.

  7. A hyperspectral approach to estimating biomass and plant production in a heterogeneous restored temperate peatland

    NASA Astrophysics Data System (ADS)

    Byrd, K. B.; Schile, L. M.; Windham-Myers, L.; Kelly, M.; Hatala, J.; Baldocchi, D. D.

    2012-12-01

    inundation and NPV. fAPAR values were combined with GPP estimates at the field scale from eddy correlation flux measurements to develop a LUE model of plant production. To compare the effectiveness of broadband vs. narrowband indices in predicting biomass and fAPAR, we simulated eight multispectral World View-2 (WV-2) bands and 164 hyperspectral Hyperion bands with the field spectroradiometer data. We calculated NDVI-type two band vegetation indices (TBVI) using all possible band combinations, with a total of 28 WV-2 indices and 13,366 Hyperion indices. Biomass estimation was affected by water depth; regression of cattail biomass to TBVI680,910 produced a R2 that was 47% higher (R2 = 0.53) when water levels were under 50 cm compared to when water levels were over 50 cm (R2 = 0.28). fAPAR estimation was affected by the density of NPV; regression of fAPAR to TBVI539,1114 when PARtransmitted was measured above thatch was 49% higher (R2 = 0.50) than when PARtransmitted was measured below thatch (R2 = 0.20, TBVI1286,1266). Accounting for background effects in this heterogeneous environment will aid in the development of robust indices that can be applied to other wetland sites for estimates of carbon storage potential across large extents.

  8. Oil spill detection using hyperspectral infrared camera

    NASA Astrophysics Data System (ADS)

    Yu, Hui; Wang, Qun; Zhang, Zhen; Zhang, Zhi-jie; Tang, Wei; Tang, Xin; Yue, Song; Wang, Chen-sheng

    2016-11-01

    Oil spill pollution is a severe environmental problem that persists in the marine environment and in inland water systems around the world. Remote sensing is an important part of oil spill response. The hyperspectral images can not only provide the space information but also the spectral information. Pixels of interests generally incorporate information from disparate component that requires quantitative decomposition of these pixels to extract desired information. Oil spill detection can be implemented by applying hyperspectral camera which can collect the hyperspectral data of the oil. By extracting desired spectral signature from hundreds of band information, one can detect and identify oil spill area in vast geographical regions. There are now numerous hyperspectral image processing algorithms developed for target detection. In this paper, we investigate several most widely used target detection algorithm for the identification of surface oil spills in ocean environment. In the experiments, we applied a hyperspectral camera to collect the real life oil spill. The experimental results shows the feasibility of oil spill detection using hyperspectral imaging and the performance of hyperspectral image processing algorithms were also validated.

  9. Inverse Problems in Hyperspectral Imaging

    NASA Astrophysics Data System (ADS)

    Berisha, Sebastian

    In hyperpsectral imaging, multiple images of the same scene are obtained over a contiguous range of wavelengths in the electromagnetic spectrum. Hyperspectral images represent observations of a scene at many different wavelengths and most importantly associate to each pixel in the imaged scene a full spectral vector or spectral signature. However, due to the presence of spectral mixtures (at different scales) in the scene and/or low spatial resolution of the hyperspectral sensor, the acquired spectral vectors of each pixel are actually a mixture of the spectra of the various materials present in the spatial coverage area of the corresponding pixel, and they also contain additional degradations caused by atmospheric blurring.We present a numerical approach for deblurring and sparse unmixing of space objects taken by ground based telescopes. A major challenge for deblurring hyperspectral images is that of estimating the overall blurring operator, taking into account the fact that the blurring operator point spread function (PSF) can be wavelength dependent and depend on the imaging system as well as the effects of atmospheric turbulence. We formulate the PSF estimation as a nonlinear least squares problem, which is solved using a variable projection Gauss-Newton method. Our analysis shows that the Jacobian can be potentially very ill-conditioned. To deal with this ill-conditioning, we use a combination of subset selection and regularization. We then incorporate the PSF estimation scheme with a preconditioned alternating direction method of multipliers to solve the deblurring and sparse unmixing problem. Experimental results illustrate the effectiveness of the resulting numerical schemes.

  10. Use of Reflectance Ratios as a Proxy for Coastal Water Constituent Monitoring in the Pearl River Estuary

    PubMed Central

    Fang, Li-Gang; Chen, Shui-Sen; Li, Dong; Li, Hong-Li

    2009-01-01

    Spectra, salinity, total suspended solids (TSS, in mg/L) and colored dissolved organic matter (CDOM, ag(400) at 400 nm) sampled in stations in 44 different locations on December 18, 19 and 21, in 2006 were measured and analyzed. The studied field covered a large variety of optically different waters, the absorption coefficient of CDOM ([ag(400)] in m-1) varied between 0.488 and 1.41 m-1, and the TSS concentrations (mg/L) varied between 7.0 and 241.1 mg/L. In order to detect salinity of the Pearl River Estuary, we analyzed the spectral properties of TSS and CDOM, and the relationships between field water reflectance spectra and water constituents' concentrations based on the synchronous in-situ and satellite hyper-spectral image analysis. A good correlation was discovered (the positive correlation by linear fit), between in-situ reflectance ratio R680/R527 and TSS concentrations (R2 = 0.65) for the salinity range of 1.74-22.12. However, the result also showed that the absorption coefficient of CDOM was not tightly correlated with reflectance. In addition, we also observed two significant relationships (R2 > 0.77), one between TSS concentrations and surface salinity and the other between the absorption coefficient of CDOM and surface salinity. Finally, we develop a novel method to understand surface salinity distribution of estuarine waters from the calibrated EO-1 Hyperion reflectance data in the Pearl River Estuary, i.e. channels with high salinity and shoals with low salinity. The EO-1 Hyperion derived surface salinity and TSS concentrations were validated using in-situ data that were collected on December 21, 2006, synchronous with EO-1 Hyperion satellite imagery acquisition. The results showed that the semi-empirical relationships are capable of predicting salinity from EO-1 Hyperion imagery in the Pearl River Estuary (RMSE < 2‰). PMID:22389623

  11. False alarm recognition in hyperspectral gas plume identification

    DOEpatents

    Conger, James L [San Ramon, CA; Lawson, Janice K [Tracy, CA; Aimonetti, William D [Livermore, CA

    2011-03-29

    According to one embodiment, a method for analyzing hyperspectral data includes collecting first hyperspectral data of a scene using a hyperspectral imager during a no-gas period and analyzing the first hyperspectral data using one or more gas plume detection logics. The gas plume detection logic is executed using a low detection threshold, and detects each occurrence of an observed hyperspectral signature. The method also includes generating a histogram for all occurrences of each observed hyperspectral signature which is detected using the gas plume detection logic, and determining a probability of false alarm (PFA) for all occurrences of each observed hyperspectral signature based on the histogram. Possibly at some other time, the method includes collecting second hyperspectral data, and analyzing the second hyperspectral data using the one or more gas plume detection logics and the PFA to determine if any gas is present. Other systems and methods are also included.

  12. Hyperspectral Imaging of human arm

    NASA Technical Reports Server (NTRS)

    2003-01-01

    ProVision Technologies, a NASA research partnership center at Sternis Space Center in Mississippi, has developed a new hyperspectral imaging (HSI) system that is much smaller than the original large units used aboard remote sensing aircraft and satellites. The new apparatus is about the size of a breadbox. Health-related applications of HSI include non-invasive analysis of human skin to characterize wounds and wound healing rates (especially important for space travelers who heal more slowly), determining if burns are first-, second-, or third degree (rather than painful punch biopsies). The work is sponsored under NASA's Space Product Development (SPD) program.

  13. Hyperspectral Imaging of human arm

    NASA Technical Reports Server (NTRS)

    2003-01-01

    ProVision Technologies, a NASA research partnership center at Sternis Space Center in Mississippi, has developed a new hyperspectral imaging (HSI) system that is much smaller than the original large units used aboard remote sensing aircraft and satellites. The new apparatus is about the size of a breadbox. Health-related applications of HSI include non-invasive analysis of human skin to characterize wounds and wound healing rates (especially important for space travelers who heal more slowly), determining if burns are first-, second-, or third degree (rather than painful punch biopsies). The work is sponsored under NASA's Space Product Development (SPD) program.

  14. Hyperspectral remote sensing for terrestrial applications

    USGS Publications Warehouse

    Thenkabail, Prasad S.; Teluguntla, Pardhasaradhi G.; Murali Krishna Gumma,; Venkateswarlu Dheeravath,

    2015-01-01

    Remote sensing data are considered hyperspectral when the data are gathered from numerous wavebands, contiguously over an entire range of the spectrum (e.g., 400–2500 nm). Goetz (1992) defines hyperspectral remote sensing as “The acquisition of images in hundreds of registered, contiguous spectral bands such that for each picture element of an image it is possible to derive a complete reflectance spectrum.” However, Jensen (2004) defines hyperspectral remote sensing as “The simultaneous acquisition of images in many relatively narrow, contiguous and/or non contiguous spectral bands throughout the ultraviolet, visible, and infrared portions of the electromagnetic spectrum.

  15. Correction and use of inflight hyperspectral data

    NASA Astrophysics Data System (ADS)

    Killey, Ainsley

    2010-10-01

    Pushbroom hyperspectral imagers (HSIs) are being increasingly used for aerial vegetative and/or geological ground mapping1. There is also considerable interest in using hyperspectral imagers for aerial surveillance and military targeting2. The Optics and Lasers Department of the Advanced Technology Centre (ATC) of BAE Systems has been working on these problems for several years3. To this end a number of spatial and spectral detection algorithms have been developed, based on change detection, matched filtering and anomaly detection4. The department owns several visible (VIS) and short wave infrared (SWIR) hyperspectral cameras systems, with different resolutions, field of views, and operational speeds.

  16. Hyperspectral Shack–Hartmann test

    PubMed Central

    Birch, Gabriel C.; Descour, Michael R.; Tkaczyk, Tomasz S.

    2011-01-01

    A hyperspectral Shack–Hartmann test bed has been developed to characterize the performance of miniature optics across a wide spectral range, a necessary first step in developing broadband achromatized all-polymer endomicroscopes. The Shack–Hartmann test bed was used to measure the chromatic focal shift (CFS) of a glass singlet lens and a glass achromatic lens, i.e., lenses representing the extrema of CFS magnitude in polymer elements to be found in endomicroscope systems. The lenses were tested from 500 to 700 nm in 5 and 10 nm steps, respectively. In both cases, we found close agreement between test results obtained from a ZEMAX model of the test bed and test lens and those obtained by experiment (maximum error of 12 μm for the singlet lens and 5 μm for the achromatic triplet lens). Future applications of the hyperspectral Shack–Hartmann test include measurements of aberrations as a function of wavelength, characterization of manufactured plastic endomicroscope elements and systems, and reverse optimization. PMID:20885478

  17. Common hyperspectral image database design

    NASA Astrophysics Data System (ADS)

    Tian, Lixun; Liao, Ningfang; Chai, Ali

    2009-11-01

    This paper is to introduce Common hyperspectral image database with a demand-oriented Database design method (CHIDB), which comprehensively set ground-based spectra, standardized hyperspectral cube, spectral analysis together to meet some applications. The paper presents an integrated approach to retrieving spectral and spatial patterns from remotely sensed imagery using state-of-the-art data mining and advanced database technologies, some data mining ideas and functions were associated into CHIDB to make it more suitable to serve in agriculture, geological and environmental areas. A broad range of data from multiple regions of the electromagnetic spectrum is supported, including ultraviolet, visible, near-infrared, thermal infrared, and fluorescence. CHIDB is based on dotnet framework and designed by MVC architecture including five main functional modules: Data importer/exporter, Image/spectrum Viewer, Data Processor, Parameter Extractor, and On-line Analyzer. The original data were all stored in SQL server2008 for efficient search, query and update, and some advance Spectral image data Processing technology are used such as Parallel processing in C#; Finally an application case is presented in agricultural disease detecting area.

  18. Using hyperspectral data in precision farming applications

    USDA-ARS?s Scientific Manuscript database

    Precision farming practices such as variable rate applications of fertilizer and agricultural chemicals require accurate field variability mapping. This chapter investigated the value of hyperspectral remote sensing in providing useful information for five applications of precision farming: (a) Soil...

  19. Hyperspectral Imaging of the Coastal Ocean

    DTIC Science & Technology

    2008-01-01

    only 30% of the variance is resolved at 300 m for the data from the 15th. This well mixed case is more typical for many coastal regions. 1 (A) 710...demonstrated that spaceborne hyperspectral remote sensing is the best approach to covertly acquire data on shallow water bathymetry, bottom types, hazards...a hyperspectral imager in space to demonstrate the ability to covertly acquire data on shallow water bathymetry, bottom types, hazards to navigation

  20. Discriminative Sparse Representations in Hyperspectral Imagery

    DTIC Science & Technology

    2010-03-01

    classification , and unsupervised labeling (clustering) [2, 3, 4, 5, 6, 7, 8]. Recently, a non-parametric (Bayesian) approach to sparse modeling and com...DISCRIMINATIVE SPARSE REPRESENTATIONS IN HYPERSPECTRAL IMAGERY By Alexey Castrodad, Zhengming Xing John Greer, Edward Bosch Lawrence Carin and...00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Discriminative Sparse Representations in Hyperspectral Imagery 5a. CONTRACT NUMBER 5b. GRANT

  1. Segmentation in dermatological hyperspectral images: dedicated methods.

    PubMed

    Koprowski, Robert; Olczyk, Paweł

    2016-08-17

    Segmentation of hyperspectral medical images is one of many image segmentation methods which require profiling. This profiling involves either the adjustment of existing, known image segmentation methods or a proposal of new dedicated methods of hyperspectral image segmentation. Taking into consideration the size of analysed data, the time of analysis is of major importance. Therefore, the authors proposed three new dedicated methods of hyperspectral image segmentation with special reference to the time of analysis. The segmentation methods presented in this paper were tested and profiled to the images acquired from different hyperspectral cameras including SOC710 Hyperspectral Imaging System, Specim sCMOS-50-V10E. Correct functioning of the method was tested for over 10,000 2D images constituting the sequence of over 700 registrations of the areas of the left and right hand and the forearm. As a result, three new methods of hyperspectral image segmentation have been proposed: fast analysis of emissivity curves (SKE), 3D segmentation (S3D) and hierarchical segmentation (SH). They have the following features: are fully automatic; allow for implementation of fast segmentation methods; are profiled to hyperspectral image segmentation; use emissivity curves in the model form, can be applied in any type of objects not necessarily biological ones, are faster (SKE-2.3 ms, S3D-1949 ms, SH-844 ms for the computer with Intel(®) Core i7 4960X CPU 3.6 GHz) and more accurate (SKE-accuracy 79 %, S3D-90 %, SH-92 %) in comparison with typical methods known from the literature. Profiling and/or proposing new methods of hyperspectral image segmentation is an indispensable element of developing software. This ensures speed, repeatability and low sensitivity of the algorithm to changing parameters.

  2. Uncooled long-wave infrared hyperspectral imaging

    NASA Technical Reports Server (NTRS)

    Lucey, Paul G. (Inventor)

    2006-01-01

    A long-wave infrared hyperspectral sensor device employs a combination of an interferometer with an uncooled microbolometer array camera to produce hyperspectral images without the use of bulky, power-hungry motorized components, making it suitable for UAV vehicles, small mobile platforms, or in extraterrestrial environments. The sensor device can provide signal-to-noise ratios near 200 for ambient temperature scenes with 33 wavenumber resolution at a frame rate of 50 Hz, with higher results indicated by ongoing component improvements.

  3. Mapping Alteration Caused by Hydrocarbon Microseepages in Patrick Draw area Southwest Wyoming Using Image Spectroscopy and Hyperspectral Remote Sensing

    SciTech Connect

    Shuhab D. Khan

    2008-06-21

    Detection of underlying reservoir accumulations using remote sensing techniques had its inception with the identification of macroseeps. However, today we find ourselves relying on the detection of more subtle characteristics associated with petroleum reservoirs, such as microseeps. Microseepages are the result of vertical movement of light hydrocarbons from the reservoir to the surface through networks of fractures, faults, and bedding planes that provide permeable routes within the overlying rock. Microseepages express themselves at the surface in an array of alterations and anomalies, such as chemical or mineralogical changes in overlying soils and sediments. Using NASA's Hyperion hyperspectral imaging sensors, this project has developed spectral and geochemical ground truthing techniques to identify and map alterations caused by hydrocarbon microseepages and to determine their relationships to the underlying geology in the Patrick Draw area of Southwest Wyoming. Training the classification of satellite imagery with spectral inputs of samples collected over previously defined areas of hydrocarbon microseepage resulted in the successful identification of an anomalous zone. Geochemical characteristics of samples that defined this anomalous zone were then compared to the remaining non-anomalous samples using XRD, ICP, spectroscopy and carbon isotope techniques.

  4. Spatial mapping of leaf area index using hyperspectral remote sensing for hydrological applications with a particular focus on canopy interception

    NASA Astrophysics Data System (ADS)

    Bulcock, H. H.; Jewitt, G. P. W.

    2010-02-01

    The establishment of commercial forestry plantations in natural grassland vegetation, results in increased transpiration and interception which in turn, results in a streamflow reduction. Methods to quantify this impact typically require LAI as an input into the various equations and process models that are applied. The use of remote sensing technology as a tool to estimate leaf area index (LAI) for use in estimating canopy interception is described in this paper. Remote sensing provides a potential solution to effectively monitor the spatial and temporal variability of LAI. This is illustrated using Hyperion hyperspectral imagery and three vegetation indices, namely the normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI) and Vogelmann index 1 to estimate LAI in a catchment afforested with Eucalyptus, Pinus and Acacia genera in the KwaZulu-Natal midlands of South Africa. Of the three vegetation indices used in this study, it was found that the Vogelmann index 1 was the most robust index with an R2 and root mean square error (RMSE) values of 0.7 and 0.3 respectively. However, both NDVI and SAVI could be used to estimate the LAI of 12 year old Pinus patula accurately. If the interception component is to be quantified independently, estimates of maximum storage capacity and canopy interception are required. Thus, the spatial distribution of LAI in the catchment is used to estimate maximum canopy storage capacity in the study area.

  5. A new method for spatial resolution enhancement of hyperspectral images using sparse coding and linear spectral unmixing

    NASA Astrophysics Data System (ADS)

    Hashemi, Nezhad Z.; Karami, A.

    2015-10-01

    Hyperspectral images (HSI) have high spectral and low spatial resolutions. However, multispectral images (MSI) usually have low spectral and high spatial resolutions. In various applications HSI with high spectral and spatial resolutions are required. In this paper, a new method for spatial resolution enhancement of HSI using high resolution MSI based on sparse coding and linear spectral unmixing (SCLSU) is introduced. In the proposed method (SCLSU), high spectral resolution features of HSI and high spatial resolution features of MSI are fused. In this case, the sparse representation of some high resolution MSI and linear spectral unmixing (LSU) model of HSI and MSI is simultaneously used in order to construct high resolution HSI (HRHSI). The fusion process of HSI and MSI is formulated as an ill-posed inverse problem. It is solved by the Split Augmented Lagrangian Shrinkage Algorithm (SALSA) and an orthogonal matching pursuit (OMP) algorithm. Finally, the proposed algorithm is applied to the Hyperion and ALI datasets. Compared with the other state-of-the-art algorithms such as Coupled Nonnegative Matrix Factorization (CNMF) and local spectral unmixing, the SCLSU has significantly increased the spatial resolution and in addition the spectral content of HSI is well maintained.

  6. Hyperspectral imaging utility for transportation systems

    NASA Astrophysics Data System (ADS)

    Bridgelall, Raj; Rafert, J. Bruce; Tolliver, Denver

    2015-03-01

    The global transportation system is massive, open, and dynamic. Existing performance and condition assessments of the complex interacting networks of roadways, bridges, railroads, pipelines, waterways, airways, and intermodal ports are expensive. Hyperspectral imaging is an emerging remote sensing technique for the non-destructive evaluation of multimodal transportation infrastructure. Unlike panchromatic, color, and infrared imaging, each layer of a hyperspectral image pixel records reflectance intensity from one of dozens or hundreds of relatively narrow wavelength bands that span a broad range of the electromagnetic spectrum. Hence, every pixel of a hyperspectral scene provides a unique spectral signature that offers new opportunities for informed decision-making in transportation systems development, operations, and maintenance. Spaceborne systems capture images of vast areas in a short period but provide lower spatial resolution than airborne systems. Practitioners use manned aircraft to achieve higher spatial and spectral resolution, but at the price of custom missions and narrow focus. The rapid size and cost reduction of unmanned aircraft systems promise a third alternative that offers hybrid benefits at affordable prices by conducting multiple parallel missions. This research formulates a theoretical framework for a pushbroom type of hyperspectral imaging system on each type of data acquisition platform. The study then applies the framework to assess the relative potential utility of hyperspectral imaging for previously proposed remote sensing applications in transportation. The authors also introduce and suggest new potential applications of hyperspectral imaging in transportation asset management, network performance evaluation, and risk assessments to enable effective and objective decision- and policy-making.

  7. Compression technique for plume hyperspectral images

    NASA Astrophysics Data System (ADS)

    Feather, B. K.; Fulkerson, S. A.; Jones, J. H.; Reed, R. A.; Simmons, M. A.; Swann, D. G.; Taylor, W. E.; Bernstein, L. S.

    2005-06-01

    The authors recently developed a hyperspectral image output option for a standardized government code designed to predict missile exhaust plume infrared signatures. Typical predictions cover the 2- to 5-m wavelength range (2000 to 5000 cm-1) at 5 cm-1 spectral resolution, and as a result the hyperspectral images have several hundred frequency channels. Several hundred hyperspectral plume images are needed to span the full operational envelope of missile altitude, Mach number, and aspect angle. Since the net disk storage space can be as large as 100 GB, a Principal Components Analysis is used to compress the spectral dimension, reducing the volume of data to just a few gigabytes. The principal challenge was to specify a robust default setting for the data compression routine suitable for general users, who are not necessarily specialists in data compression. Specifically, the objective was to provide reasonable data compression efficiency of the hyperspectral imagery while at the same time retaining sufficient accuracy for infrared scene generation and hardware-in-the-loop test applications over a range of sensor bandpasses and scenarios. In addition, although the end users of the code do not usually access the detailed spectral information contained in these hyperspectral images, this information must nevertheless be of sufficient fidelity so that atmospheric transmission losses between the missile plume and the sensor could be reliably computed as a function of range. Several metrics were used to determine how far the plume signature hyperspectral data could be safely compressed while still meeting these end-user requirements.

  8. Reflectance and fluorescence hyperspectral elastic image registration

    NASA Astrophysics Data System (ADS)

    Lange, Holger; Baker, Ross; Hakansson, Johan; Gustafsson, Ulf P.

    2004-05-01

    Science and Technology International (STI) presents a novel multi-modal elastic image registration approach for a new hyperspectral medical imaging modality. STI's HyperSpectral Diagnostic Imaging (HSDI) cervical instrument is used for the early detection of uterine cervical cancer. A Computer-Aided-Diagnostic (CAD) system is being developed to aid the physician with the diagnosis of pre-cancerous and cancerous tissue regions. The CAD system uses the fusion of multiple data sources to optimize its performance. The key enabling technology for the data fusion is image registration. The difficulty lies in the image registration of fluorescence and reflectance hyperspectral data due to the occurrence of soft tissue movement and the limited resemblance of these types of imagery. The presented approach is based on embedding a reflectance image in the fluorescence hyperspectral imagery. Having a reflectance image in both data sets resolves the resemblance problem and thereby enables the use of elastic image registration algorithms required to compensate for soft tissue movements. Several methods of embedding the reflectance image in the fluorescence hyperspectral imagery are described. Initial experiments with human subject data are presented where a reflectance image is embedded in the fluorescence hyperspectral imagery.

  9. Retrieval Lesson Learned from NAST-I Hyperspectral Data

    NASA Technical Reports Server (NTRS)

    Zhou, Daniel K.; Smith, William L.; Liu, Xu; Larar, Allen M.; Mango, Stephen A.

    2007-01-01

    The retrieval lesson learned is important to many current and future hyperspectral remote sensors. Validated retrieval algorithms demonstrate the advancement of hyperspectral remote sensing capabilities to be achieved with current and future satellite instruments.

  10. New Application of Hyperspectral Imaging for Bacterial Cell Classification

    USDA-ARS?s Scientific Manuscript database

    Hyperspectral microscopy has shown potential as a method for rapid detection of foodborne pathogenic bacteria with spectral characteristics from bacterial cells. Hyperspectral microscope images (HMIs) are collected from broiler chicken isolates of Salmonella serotypes Enteritidis, Typhimurium, Infa...

  11. Naval EarthMap Observer (NEMO) Hyperspectral Remote Sensing Program

    DTIC Science & Technology

    2000-10-01

    The NEMO hyperspectral remote sensing program will provide unclassified, space-based hyperspectral passive imagery at moderate resolution that offers substantial potential for direct use by Naval forces and the Civil Sector.

  12. Multi- and hyperspectral scene modeling

    NASA Astrophysics Data System (ADS)

    Borel, Christoph C.; Tuttle, Ronald F.

    2011-06-01

    This paper shows how to use a public domain raytracer POV-Ray (Persistence Of Vision Raytracer) to render multiand hyper-spectral scenes. The scripting environment allows automatic changing of the reflectance and transmittance parameters. The radiosity rendering mode allows accurate simulation of multiple-reflections between surfaces and also allows semi-transparent surfaces such as plant leaves. We show that POV-Ray computes occlusion accurately using a test scene with two blocks under a uniform sky. A complex scene representing a plant canopy is generated using a few lines of script. With appropriate rendering settings, shadows cast by leaves are rendered in many bands. Comparing single and multiple reflection renderings, the effect of multiple reflections is clearly visible and accounts for 25% of the overall apparent canopy reflectance in the near infrared.

  13. Hyperspectral imaging using RGB color for foodborne pathogen detection

    USDA-ARS?s Scientific Manuscript database

    This paper reports the latest development of a color vision technique for detecting colonies of foodborne pathogens grown on agar plates with a hyperspectral image classification model that was developed using full hyperspectral data. The hyperspectral classification model depended on reflectance sp...

  14. 1D hyperspectral images of a light emitting diodes array

    NASA Astrophysics Data System (ADS)

    Urzica (Iordache), I.; Damian, V.; Logofatu, P. C.; Apostol, D.; Vasile, T.; Udrea, C.

    2015-02-01

    The paper present our first steps to realize a hyperspectral imaging system. Preliminary experiments in the domain have as purpose to test the capability of a monochromator with a 2D linear CCD camera, to create hyperspectral images. Using a Sciencetech 9055 model monochromator with a Hamamatsu CCD, we have analyzed an array of three LEDs of various colors, obtaining 1D hyperspectral images.

  15. Innovative Statistical Inference for Anomaly Detection in Hyperspectral Imagery

    DTIC Science & Technology

    2004-09-01

    Innovative Statistical Inference for Anomaly Detection in Hyperspectral Imagery by Dalton Rosario ARL-TR-3339 September 2004...2004 Innovative Statistical Inference for Anomaly Detection in Hyperspectral Imagery Dalton Rosario Sensors and Electron Devices...the effectiveness of both algorithms. 15. SUBJECT TERMS Hyperspectral anomaly detection , large sample theory 16. SECURITY CLASSIFICATION OF: 19a

  16. Observing the 2010 Eyjafjallajökull, Iceland, Eruptions with NASA's Earth Observing-1 Spacecraft - Improving Data Flow In a Volcanic Crisis Through Use of Autonomy

    NASA Astrophysics Data System (ADS)

    Chien, S.; Davies, A. G.; Doubleday, J.; Tran, D. Q.; Gudmundsson, M. T.; Jónsdóttir, I.; Hoskuldsson, A.; Thordarson, T.; Jakobsdottir, S.; Wright, R.

    2010-12-01

    Eyjafjallajökull volcano, Iceland, erupted from 20 March to 12 April 2010 (a flank eruption) and again from 14 April to 23 May 2010. The latter eruption heavily impacted air travel across much of northern Europe, and highlighted the need to monitor and quickly react to new eruptions. The NASA Earth Observing 1 spacecraft (EO-1), which is managed by the NASA Goddard Space Flight Center, obtained over 50 observation pairs with the Hyperion hyperspectral imager and ALI (Advanced Land Imager) multispectral camera. EO-1 is the remote-sensing asset of a globe-spanning Volcano Sensor Web [1], where low spatial resolution data (e.g., MODIS) or alerts of ongoing or possible volcanic activity are used to trigger requests for high resolution EO-1 data. Advanced resource management software, developed in part for flight onboard EO-1 as part of the Autonomous Sciencecraft [2, 3] is now used to task EO-1. This system allowed rapid re-tasking of EO-1 to obtain both day and night data at high temporal resolution (on average every 2 days), unusual for such high spatial resolution imagers (Hyperion and ALI at 30 m/pixel, with an ALI panchromatic band at 10 m/pixel). About 50% of the data were impacted by cloud. Advances in data handling and communications during the last two years means that Hyperion and ALI data are typically on the ground and ready for analysis within a few hours of data acquisition. Automatic data processing systems at the NASA’s Jet Propulsion Laboratory process Hyperion data to (1) correct for atmospheric adsorption; (2) remove the sunlight component in daytime data; (3) identify hot pixels; (4) fit unsaturated data to determine temperature and area of sub-pixel thermal sources; (5) calculate total thermal emission and, from this, an effusion rate; (6) generate geo-located data products. The entire process is autonomous. Data products, as well as images generated, were sent to volcanologists in the field to aid in eruption assessment. The JPL group is now

  17. Wavelet compression techniques for hyperspectral data

    NASA Technical Reports Server (NTRS)

    Evans, Bruce; Ringer, Brian; Yeates, Mathew

    1994-01-01

    Hyperspectral sensors are electro-optic sensors which typically operate in visible and near infrared bands. Their characteristic property is the ability to resolve a relatively large number (i.e., tens to hundreds) of contiguous spectral bands to produce a detailed profile of the electromagnetic spectrum. In contrast, multispectral sensors measure relatively few non-contiguous spectral bands. Like multispectral sensors, hyperspectral sensors are often also imaging sensors, measuring spectra over an array of spatial resolution cells. The data produced may thus be viewed as a three dimensional array of samples in which two dimensions correspond to spatial position and the third to wavelength. Because they multiply the already large storage/transmission bandwidth requirements of conventional digital images, hyperspectral sensors generate formidable torrents of data. Their fine spectral resolution typically results in high redundancy in the spectral dimension, so that hyperspectral data sets are excellent candidates for compression. Although there have been a number of studies of compression algorithms for multispectral data, we are not aware of any published results for hyperspectral data. Three algorithms for hyperspectral data compression are compared. They were selected as representatives of three major approaches for extending conventional lossy image compression techniques to hyperspectral data. The simplest approach treats the data as an ensemble of images and compresses each image independently, ignoring the correlation between spectral bands. The second approach transforms the data to decorrelate the spectral bands, and then compresses the transformed data as a set of independent images. The third approach directly generalizes two-dimensional transform coding by applying a three-dimensional transform as part of the usual transform-quantize-entropy code procedure. The algorithms studied all use the discrete wavelet transform. In the first two cases, a wavelet

  18. Dehazing method for hyperspectral remote sensing imagery with hyperspectral linear unmixing

    NASA Astrophysics Data System (ADS)

    Gan, Yuquan; Hu, Bingliang; Wen, Desheng; Wang, Shuang

    2016-10-01

    Haze always exists in hyper-spectral remote sensing imagery, and it is a key reason that influences the effective information extraction of hyper-spectral images. Specially, when the faint haze covers part of the target in remote sensing images, the target still can be detected but not clear. So, how to remove the influence of the haze and improve the applicable efficiency of hyper-spectral images is a popular research point. This paper proposes a dehazing method for hyper-spectral images based on linear unmixing. First, a popular hyper-spectral unmixing method called FUN is used to get the signature of all the end-members and their corresponding abundance. And then, the abundance of the haze end-member is removed and the abundances of the rest end-members are adjusted to satisfy the sum-to-one and non-negative constraint. Lastly, the new abundance and the signature of the end-members are linearly mixed to get the dehazed hyper-spectral images. The experiment result shows that the dehazed hyper-spectral images exhibit better target information and details. The method is effective and available.

  19. Maintenance of Ecosystem Nitrogen Limitation by Ephemeral Forest Disturbance: An Assessment using MODIS, Hyperion, and Landsat ETM+

    NASA Technical Reports Server (NTRS)

    McNeil, Brenden E.; deBeurs, Kirsten M.; Eshleman, Keith N.; Foster, Jane R.; Townsend, Philip A.

    2007-01-01

    Ephemeral disturbances, such as non-lethal insect defoliations and crown damage from meteorological events, can significantly affect the delivery of ecosystem services by helping maintain nitrogen (N) limitation in temperate forest ecosystems. However, the impacts of these disturbances are difficult to observe across the broad-scales at which they affect ecosystem function. Using remotely sensed measures and field data, we find support for the hypothesis that ephemeral disturbances help maintain landscape-wide ecosystem N limitation. Specifically, a phenology-based defoliation index derived from daily MODIS satellite imagery predicts three ecosystem responses from oak-dominated forested watersheds: elevated stream water N export (R(exp 2) = 0.48), decreased foliar N (R(exp 2) = 0.69, assessed with Hyperion imagery), and reduced vegetation growth vigor (R(exp 2) = 0.49, assessed with Landsat ETM+ imagery). The results indicate that ephemeral disturbances and other forest stressors may sustain N limitation by reducing the ability of trees to compete for--and retain--soil available N.

  20. Maintenance of ecosystem nitrogen limitation by ephemeral forest disturbance: An assessment using MODIS, Hyperion, and Landsat ETM+

    NASA Astrophysics Data System (ADS)

    McNeil, Brenden E.; de Beurs, Kirsten M.; Eshleman, Keith N.; Foster, Jane R.; Townsend, Philip A.

    2007-10-01

    Ephemeral disturbances, such as non-lethal insect defoliations and crown damage from meteorological events, can significantly affect the delivery of ecosystem services by helping maintain nitrogen (N) limitation in temperate forest ecosystems. However, the impacts of these disturbances are difficult to observe across the broad-scales at which they affect ecosystem function. Using remotely sensed measures and field data, we find support for the hypothesis that ephemeral disturbances help maintain landscape-wide ecosystem N limitation. Specifically, a phenology-based defoliation index derived from daily MODIS satellite imagery predicts three ecosystem responses from oak-dominated forested watersheds: elevated stream water N export (R2 = 0.48), decreased foliar N (R2 = 0.69, assessed with Hyperion imagery), and reduced vegetation growth vigor (R2 = 0.49, assessed with Landsat ETM+ imagery). The results indicate that ephemeral disturbances and other forest stressors may sustain N limitation by reducing the ability of trees to compete for -and retain- soil available N.

  1. Maintenance of Ecosystem Nitrogen Limitation by Ephemeral Forest Disturbance: An Assessment using MODIS, Hyperion, and Landsat ETM+

    NASA Technical Reports Server (NTRS)

    McNeil, Brenden E.; deBeurs, Kirsten M.; Eshleman, Keith N.; Foster, Jane R.; Townsend, Philip A.

    2007-01-01

    Ephemeral disturbances, such as non-lethal insect defoliations and crown damage from meteorological events, can significantly affect the delivery of ecosystem services by helping maintain nitrogen (N) limitation in temperate forest ecosystems. However, the impacts of these disturbances are difficult to observe across the broad-scales at which they affect ecosystem function. Using remotely sensed measures and field data, we find support for the hypothesis that ephemeral disturbances help maintain landscape-wide ecosystem N limitation. Specifically, a phenology-based defoliation index derived from daily MODIS satellite imagery predicts three ecosystem responses from oak-dominated forested watersheds: elevated stream water N export (R(exp 2) = 0.48), decreased foliar N (R(exp 2) = 0.69, assessed with Hyperion imagery), and reduced vegetation growth vigor (R(exp 2) = 0.49, assessed with Landsat ETM+ imagery). The results indicate that ephemeral disturbances and other forest stressors may sustain N limitation by reducing the ability of trees to compete for--and retain--soil available N.

  2. Odor and volatile organic compound treatment by biotrickling filters: pilot-scale studies at hyperion treatment plant.

    PubMed

    Cox, H H J; Deshusses, M A; Converse, B M; Schroeder, E D; Iranpour, R

    2002-01-01

    A pilot-scale biotrickling filter was installed at the Hyperion Treatment Plant in Los Angeles, California, to study hydrogen sulfide (odor) and volatile organic compound (VOC) removal from headworks waste air. The performance of the reactor was continuously monitored during a 10-month period. At an average empty bed gas residence time of 24 seconds, 10 to 50 ppm of hydrogen sulfide was consistently removed at greater than 98% efficiency, corresponding to an average volumetric elimination capacity of 5.2 g/m3 x h. Concentration profiles over the height of the reactor indicated nearly complete removal in the first section of the reactor, suggesting that elimination capacities up to 30 g/m3 x h could be obtained. The odor reduction (as dilution to threshold) was 98%, which correlated with the efficiency of removal of hydrogen sulfide as the primary pollutant. Volatile organic compounds were present at concentrations up to 225 ppb. Moderate but significant removal of toluene and benzene was observed when the biotrickling filter was operated with pH control to neutralize sulfuric acid production from hydrogen sulfide oxidation. Xylenes and chlorinated VOCs were not removed regardless of experimental conditions in the reactor. The results led to the conclusion that VOC removal is the limiting process in biotrickling filters for the simultaneous removal of hydrogen sulfide and VOCs at publicly owned treatment works.

  3. Maintenance of Ecosystem Nitrogen Limitation by Ephemeral Forest Disturbance: An Assessment using MODIS, Hyperion, and Landsat ETM+

    NASA Technical Reports Server (NTRS)

    McNeil, Brenden E.; deBeurs, Kirsten M.; Eshleman, Keith N.; Foster, Jane R.; Townsend, Philip A.

    2007-01-01

    Ephemeral disturbances, such as non-lethal insect defoliations and crown damage from meteorological events, can significantly affect the delivery of ecosystem services by helping maintain nitrogen (N) limitation in temperate forest ecosystems. However, the impacts of these disturbances are difficult to observe across the broad-scales at which they affect ecosystem function. Using remotely sensed measures and field data, we find support for the hypothesis that ephemeral disturbances help maintain landscape-wide ecosystem N limitation. Specifically, a phenology-based defoliation index derived from daily MODIS satellite imagery predicts three ecosystem responses from oak-dominated forested watersheds: elevated stream water N export (R(exp 2) = 0.48), decreased foliar N (R(exp 2) = 0.69, assessed with Hyperion imagery), and reduced vegetation growth vigor (R(exp 2) = 0.49, assessed with Landsat ETM+ imagery). The results indicate that ephemeral disturbances and other forest stressors may sustain N limitation by reducing the ability of trees to compete for--and retain--soil available N.

  4. Portable Hyperspectral Imaging Broadens Sensing Horizons

    NASA Technical Reports Server (NTRS)

    2007-01-01

    Broadband multispectral imaging can be very helpful in showing differences in energy being radiated and is often employed by NASA satellites to monitor temperature and climate changes. In addition, hyperspectral imaging is ideal for advanced laboratory uses, biomedical imaging, forensics, counter-terrorism, skin health, food safety, and Earth imaging. Lextel Intelligence Systems, LLC, of Jackson, Mississippi purchased Photon Industries Inc., a spinoff company of NASA's Stennis Space Center and the Institute for Technology Development dedicated to developing new hyperspectral imaging technologies. Lextel has added new features to and expanded the applicability of the hyperspectral imaging systems. It has made advances in the size, usability, and cost of the instruments. The company now offers a suite of turnkey hyperspectral imaging systems based on the original NASA groundwork. It currently has four lines of hyperspectral imaging products: the EagleEye VNIR 100E, the EagleEye SWIR 100E, the EagleEye SWIR 200E, and the EagleEye UV 100E. These Lextel instruments are used worldwide for a wide variety of applications including medical, military, forensics, and food safety.

  5. Parallel hyperspectral image reconstruction using random projections

    NASA Astrophysics Data System (ADS)

    Sevilla, Jorge; Martín, Gabriel; Nascimento, José M. P.

    2016-10-01

    Spaceborne sensors systems are characterized by scarce onboard computing and storage resources and by communication links with reduced bandwidth. Random projections techniques have been demonstrated as an effective and very light way to reduce the number of measurements in hyperspectral data, thus, the data to be transmitted to the Earth station is reduced. However, the reconstruction of the original data from the random projections may be computationally expensive. SpeCA is a blind hyperspectral reconstruction technique that exploits the fact that hyperspectral vectors often belong to a low dimensional subspace. SpeCA has shown promising results in the task of recovering hyperspectral data from a reduced number of random measurements. In this manuscript we focus on the implementation of the SpeCA algorithm for graphics processing units (GPU) using the compute unified device architecture (CUDA). Experimental results conducted using synthetic and real hyperspectral datasets on the GPU architecture by NVIDIA: GeForce GTX 980, reveal that the use of GPUs can provide real-time reconstruction. The achieved speedup is up to 22 times when compared with the processing time of SpeCA running on one core of the Intel i7-4790K CPU (3.4GHz), with 32 Gbyte memory.

  6. MEMS FPI-based smartphone hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Rissanen, Anna; Saari, Heikki; Rainio, Kari; Stuns, Ingmar; Viherkanto, Kai; Holmlund, Christer; Näkki, Ismo; Ojanen, Harri

    2016-05-01

    This paper demonstrates a mobile phone- compatible hyperspectral imager based on a tunable MEMS Fabry-Perot interferometer. The realized iPhone 5s hyperspectral imager (HSI) demonstrator utilizes MEMS FPI tunable filter for visible-range, which consist of atomic layer deposited (ALD) Al2O3/TiO2-thin film Bragg reflectors. Characterization results for the mobile phone hyperspectral imager utilizing MEMS FPI chip optimized for 500 nm is presented; the operation range is λ = 450 - 550 nm with FWHM between 8 - 15 nm. Also a configuration of two cascaded FPIs (λ = 500 nm and λ = 650 nm) combined with an RGB colour camera is presented. With this tandem configuration, the overall wavelength tuning range of MEMS hyperspectral imagers can be extended to cover a larger range than with a single FPI chip. The potential applications of mobile hyperspectral imagers in the vis-NIR range include authentication, counterfeit detection and potential health/wellness and food sensing applications.

  7. Characterizing Hyperspectral Imagery (AVIRIS) Using Fractal Technique

    NASA Technical Reports Server (NTRS)

    Qiu, Hong-Lie; Lam, Nina Siu-Ngan; Quattrochi, Dale

    1997-01-01

    With the rapid increase in hyperspectral data acquired by various experimental hyperspectral imaging sensors, it is necessary to develop efficient and innovative tools to handle and analyze these data. The objective of this study is to seek effective spatial analytical tools for summarizing the spatial patterns of hyperspectral imaging data. In this paper, we (1) examine how fractal dimension D changes across spectral bands of hyperspectral imaging data and (2) determine the relationships between fractal dimension and image content. It has been documented that fractal dimension changes across spectral bands for the Landsat-TM data and its value [(D)] is largely a function of the complexity of the landscape under study. The newly available hyperspectral imaging data such as that from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) which has 224 bands, covers a wider spectral range with a much finer spectral resolution. Our preliminary result shows that fractal dimension values of AVIRIS scenes from the Santa Monica Mountains in California vary between 2.25 and 2.99. However, high fractal dimension values (D > 2.8) are found only from spectral bands with high noise level and bands with good image quality have a fairly stable dimension value (D = 2.5 - 2.6). This suggests that D can also be used as a summary statistics to represent the image quality or content of spectral bands.

  8. Characterizing Hyperspectral Imagery (AVIRIS) Using Fractal Technique

    NASA Technical Reports Server (NTRS)

    Qiu, Hong-Lie; Lam, Nina Siu-Ngan; Quattrochi, Dale

    1997-01-01

    With the rapid increase in hyperspectral data acquired by various experimental hyperspectral imaging sensors, it is necessary to develop efficient and innovative tools to handle and analyze these data. The objective of this study is to seek effective spatial analytical tools for summarizing the spatial patterns of hyperspectral imaging data. In this paper, we (1) examine how fractal dimension D changes across spectral bands of hyperspectral imaging data and (2) determine the relationships between fractal dimension and image content. It has been documented that fractal dimension changes across spectral bands for the Landsat-TM data and its value [(D)] is largely a function of the complexity of the landscape under study. The newly available hyperspectral imaging data such as that from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) which has 224 bands, covers a wider spectral range with a much finer spectral resolution. Our preliminary result shows that fractal dimension values of AVIRIS scenes from the Santa Monica Mountains in California vary between 2.25 and 2.99. However, high fractal dimension values (D > 2.8) are found only from spectral bands with high noise level and bands with good image quality have a fairly stable dimension value (D = 2.5 - 2.6). This suggests that D can also be used as a summary statistics to represent the image quality or content of spectral bands.

  9. Novel hyperspectral imager for lightweight UAVs

    NASA Astrophysics Data System (ADS)

    Saari, Heikki; Aallos, Ville-Veikko; Holmlund, Christer; Mäkynen, Jussi; Delauré, Bavo; Nackaerts, Kris; Michiels, Bart

    2010-04-01

    VTT Technical Research Centre of Finland has developed a new miniaturized staring hyperspectral imager with a weight of 350 g making the system compatible with lightweight UAS platforms. The instrument is able to record 2D spatial images at the selected wavelength bands simultaneously. The concept of the hyperspectral imager has been published in the SPIE Proc. 74741. The operational wavelength range of the imager can be tuned in the range 400 - 1100 nm and spectral resolution is in the range 5 - 10 nm @ FWHM. Presently the spatial resolution is 480 × 750 pixels but it can be increased simply by changing the image sensor. The field of view of the system is 20 × 30 degrees and ground pixel size at 100 m flying altitude is around 7.5 cm. The system contains batteries, image acquisition control system and memory for the image data. It can operate autonomously recording hyperspectral data cubes continuously or controlled by the autopilot system of the UAS. The new hyperspectral imager prototype was first tried in co-operation with the Flemish Institute for Technological Research (VITO) on their UAS helicopter. The instrument was configured for the spectral range 500 - 900 nm selected for the vegetation and natural water monitoring applications. The design of the UAS hyperspectral imager and its characterization results together with the analysis of the spectral data from first test flights will be presented.

  10. A new hyperspectral image compression paradigm based on fusion

    NASA Astrophysics Data System (ADS)

    Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

    2016-10-01

    The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

  11. Hyperspectral vital sign signal analysis for medical data

    NASA Astrophysics Data System (ADS)

    Gao, Cheng; Li, Yao; Li, Hsiao-Chi; Chang, Chein-I.; Hu, Peter; Mackenzie, Colin

    2015-05-01

    This paper develops a completely new technology,) from a hyperspectral imaging perspective, called Hyperspectral Vital Sign Signal Analysis (HyVSSA. A hyperspectral image is generally acquired by hundreds of contiguous spectral bands, each of which is an optical sensor specified by a particular wavelength. In medical application, we can consider a patient with different vital sign signals as a pixel vector in hyperspectral image and each vital sign signal as a particular band. In light of this interpretation, a revolutionary concept is developed, which translates medical data to hyperspectral data in such a way that hyperspectral technology can be readily applied to medical data analysis. One of most useful techniques in hyperspectral data processing is, Anomaly Detection (AD) which in this medical application is used to predict outcomes such as transfusion, length of stay (LOS) and mortality using various vital signs. This study compared transfusion prediction performance of Anomaly Detection (AD) and Logistic Regression (LR).

  12. Hyperspectral imaging and its applications

    NASA Astrophysics Data System (ADS)

    Serranti, S.; Bonifazi, G.

    2016-04-01

    Hyperspectral imaging (HSI) is an emerging technique that combines the imaging properties of a digital camera with the spectroscopic properties of a spectrometer able to detect the spectral attributes of each pixel in an image. For these characteristics, HSI allows to qualitatively and quantitatively evaluate the effects of the interactions of light with organic and/or inorganic materials. The results of this interaction are usually displayed as a spectral signature characterized by a sequence of energy values, in a pre-defined wavelength interval, for each of the investigated/collected wavelength. Following this approach, it is thus possible to collect, in a fast and reliable way, spectral information that are strictly linked to chemical-physical characteristics of the investigated materials and/or products. Considering that in an hyperspectral image the spectrum of each pixel can be analyzed, HSI can be considered as one of the best nondestructive technology allowing to perform the most accurate and detailed information extraction. HSI can be applied in different wavelength fields, the most common are the visible (VIS: 400-700 nm), the near infrared (NIR: 1000-1700 nm) and the short wave infrared (SWIR: 1000-2500 nm). It can be applied for inspections from micro- to macro-scale, up to remote sensing. HSI produces a large amount of information due to the great number of continuous collected spectral bands. Such an approach, when successful, is quite challenging being usually reliable, robust and characterized by lower costs, if compared with those usually associated to commonly applied analytical off-line and/or on-line analytical approaches. More and more applications have been thus developed and tested, in these last years, especially in food inspection, with a large range of investigated products, such as fruits and vegetables, meat, fish, eggs and cereals, but also in medicine and pharmaceutical sector, in cultural heritage, in material characterization and in

  13. The EO-1 Autonomous Science Agent Architecture

    NASA Technical Reports Server (NTRS)

    Chien, Steve; Sherwood, Rob; Tran, Daniel; Cichy, Benjamin; Rabideau, Gregg; Castano, Rebecca; Davies, Ashley; Lee, Rachel; Mandl, Dan; Frye, Stuart; hide

    2004-01-01

    An Autonomous Science Agent is currently flying onboard the Earth Observing One Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and run-time robust execution. Because of the deployment to a remote spacecraft, this Autonomous Science Agent has stringent constraints of autonomy, reliability, and limited computing resources. We describe these constraints and how they are reflected in our agent architecture.

  14. The EO-1 Autonomous Science Agent Architecture

    NASA Technical Reports Server (NTRS)

    Chien, Steve; Sherwood, Rob; Tran, Daniel; Cichy, Benjamin; Rabideau, Gregg; Castano, Rebecca; Davies, Ashley; Lee, Rachel; Mandl, Dan; Frye, Stuart; Trout, Bruce; Hengemihle, Jerry; D'Agostino, Jeff; Shulman, Seth; Ungar, Stephen; Brakke, Thomas; Boyer, Darrell; Van Gaasbeck, Jim; Greeley, Ronald; Doggett, Thomas; Baker, Victor; Dohm, James; Ip, Felipe

    2004-01-01

    An Autonomous Science Agent is currently flying onboard the Earth Observing One Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and run-time robust execution. Because of the deployment to a remote spacecraft, this Autonomous Science Agent has stringent constraints of autonomy, reliability, and limited computing resources. We describe these constraints and how they are reflected in our agent architecture.

  15. Hyperspectral Image Sharpening Based on Ehlers Fusion

    NASA Astrophysics Data System (ADS)

    Xu, S.; Ehlers, M.

    2017-09-01

    As the application of hyperspectral images is increasing, many researchers attempt to extend existing pansharpening techniques to hyperspectral images. This paper focuses on the application of Ehlers fusion to hyperspectral image sharpening. Ehlers fusion involves two crucial algorithms: filter technique in the frequency domain and intensity transform. In this study, different filter types and intensity transform methods were analysed separately. With a combination of filter types and intensity transforms, the fusion procedure was implemented to test data sets. The spectral profiles of the pixels of the images were then used as a tool to control the quality of the fused image. Finally, the performance of Ehlers fusion is compared with Principle Component (PC) analysis, Gram-Schmidt transform (Gram-Schmidt), High-Pass Filtering in the spatial domain (HPF), and Wavelet Principal Component (Wavelet-PC) analysis using the same input data. The comparison shows that Ehlers high-pass filter fusion shows outstanding performance both on spatial enhancement and colour preservation.

  16. Designing microarray phantoms for hyperspectral imaging validation

    PubMed Central

    Clarke, Matthew L.; Lee, Ji Youn; Samarov, Daniel V.; Allen, David W.; Litorja, Maritoni; Nossal, Ralph; Hwang, Jeeseong

    2012-01-01

    The design and fabrication of custom-tailored microarrays for use as phantoms in the characterization of hyperspectral imaging systems is described. Corresponding analysis methods for biologically relevant samples are also discussed. An image-based phantom design was used to program a microarrayer robot to print prescribed mixtures of dyes onto microscope slides. The resulting arrays were imaged by a hyperspectral imaging microscope. The shape of the spots results in significant scattering signals, which can be used to test image analysis algorithms. Separation of the scattering signals allowed elucidation of individual dye spectra. In addition, spectral fitting of the absorbance spectra of complex dye mixtures was performed in order to determine local dye concentrations. Such microarray phantoms provide a robust testing platform for comparisons of hyperspectral imaging acquisition and analysis methods. PMID:22741076

  17. Toward Improved Hyperspectral Analysis in Semiarid Systems

    NASA Astrophysics Data System (ADS)

    Glenn, N. F.; Mitchell, J.

    2012-12-01

    Idaho State University's Boise Center Aerospace Laboratory (BCAL) has processed and applied hyperspectral data for a variety of biophysical sciences in semiarid systems over the past 10 years. HyMap hyperspectral data have been used in most of these studies, along with AVIRIS, CASI, and PIKA-II data. Our studies began with the detection of individual weed species, such as leafy spurge, corroborated with extensive field analysis, including spectrometer data. Early contributions to the field of hyperspectral analysis included the use of: time-series datasets and classification threshold methods for target detection, and subpixel analysis for characterizing weed invasions and post-fire vegetation and soil conditions. Subsequent studies optimized subpixel unmixing performance using spectral subsetting and vegetation abundance investigations. More recent studies have extended the application of hyperspectral data from individual plant species detection to identification of biochemical constituents. We demonstrated field and airborne hyperspectral Nitrogen absorption in sagebrush using combinations of data reduction and spectral transformation techniques (i.e., continuum removal, derivative analysis, partial least squares regression). In spite of these and many other successful demonstrations, gaps still exist in effective species level discrimination due to the high complexity of soil and nonlinear mixing in semiarid shrubland. BCAL studies are currently focusing on complimenting narrowband vegetation indices with LiDAR (light detection and ranging, both airborne and ground-based) derivatives to improve vegetation cover predictions. Future combinations of LiDAR and hyperspectral data will involve exploring the full range spectral information and serve as an integral step in scaling shrub biomass estimates from plot to landscape and regional scales.

  18. Identification of coral reef feature using hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    Mohanty, P. C.; Panditrao, Satej; Mahendra, R. S.; Shiva Kumar, H.; Kumar, T. Srinivasa

    2016-04-01

    Present study employs reef-up approach to map coral reef zones along the Sentinel Island of Andaman using high spectral resolution offered by hyper spectral imagery by Hyperion mission of NASA. This data consisting of 242 spectral bands, provide a unique ability to identify Coral substrate based on their spectral properties. We applied atmospheric correction with the help of Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) module of ENVI software. This atmospherically corrected was used to extract Coral Reef Zones (CRZ) based on specific threshold limits after subtracting data of 782.95nm band from 579.45nm band of Hyperion imagery. Both of these bands were chosen due to their property of exhibiting maximum spectral contrast that determines threshold limits to distinguish a coral area from its non-coral counterpart. These CRZs were compared with the coral reef zones base map developed using LISS-III data by INCOIS, Hyderabad and SAC, Ahmadabad under CZS project. We observed that extracted CRZ area was 85.25 m2 and 110.1 m2 using LISS-III and Hyperion Data respectively. Despite the overestimation of CRZ by Hyperion data as compared to LISS-III, the spatial distribution of CRZ showed reasonable similarity in both.

  19. Cross-calibration of the Terra MODIS, Landsat 7 ETM+ and EO-1 ALI sensors using near-simultaneous surface observation over the Railroad Valley Playa, Nevada, test site

    USGS Publications Warehouse

    Chander, G.; Angal, A.; Choi, T.; Meyer, D.J.; Xiong, X.; Teillet, P.M.

    2007-01-01

    A cross-calibration methodology has been developed using coincident image pairs from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS), the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Earth Observing EO-1 Advanced Land Imager (ALI) to verify the absolute radiometric calibration accuracy of these sensors with respect to each other. To quantify the effects due to different spectral responses, the Relative Spectral Responses (RSR) of these sensors were studied and compared by developing a set of "figures-of-merit." Seven cloud-free scenes collected over the Railroad Valley Playa, Nevada (RVPN), test site were used to conduct the cross-calibration study. This cross-calibration approach was based on image statistics from near-simultaneous observations made by different satellite sensors. Homogeneous regions of interest (ROI) were selected in the image pairs, and the mean target statistics were converted to absolute units of at-sensor reflectance. Using these reflectances, a set of cross-calibration equations were developed giving a relative gain and bias between the sensor pair.

  20. Hyperspectral photometric stereo for a single capture.

    PubMed

    Ozawa, Keisuke; Sato, Imari; Yamaguchi, Masahiro

    2017-03-01

    We present a single-capture photometric stereo method using a hyperspectral camera. A spectrally and spatially designed illumination enables a point-wise estimation of reflectance spectra and surface normals from a single hyperspectral image. The illumination works as a reflectance probe in wide spectral regions where reflectance spectra are measured, and the full spectra are estimated by interpolation. It also works as the resource for shadings in other spectral regions. The accuracy of estimation is evaluated in a simulation. Also, we prepare an experimental setup and demonstrate a surface reconstruction against a real scene.

  1. Hyperspectral Thermal Emission Spectrometer: Engineering Flight Campaign

    NASA Technical Reports Server (NTRS)

    Johnson, William R.; Hook, Simon J.; Shoen, Steven S.; Eng, Bjorn T.

    2013-01-01

    The Hyperspectral Thermal Emission Spectrometer (HyTES) successfully completed its first set of engineering test flights. HyTES was developed in support of the Hyperspectral Infrared Imager (HyspIRI). HyspIRI is one of the Tier II Decadal Survey missions. HyTES currently provides both high spectral resolution (17 nm) and high spatial resolution (2-5m) data in the thermal infrared (7.5-12 micron) part of the electromagnetic spectrum. HyTES data will be used to help determine the optimum band positions for the HyspIRI Thermal Infrared (TIR) sensor and provide antecedent data for HyspIRI related studies.

  2. Tongue Tumor Detection in Medical Hyperspectral Images

    PubMed Central

    Liu, Zhi; Wang, Hongjun; Li, Qingli

    2012-01-01

    A hyperspectral imaging system to measure and analyze the reflectance spectra of the human tongue with high spatial resolution is proposed for tongue tumor detection. To achieve fast and accurate performance for detecting tongue tumors, reflectance data were collected using spectral acousto-optic tunable filters and a spectral adapter, and sparse representation was used for the data analysis algorithm. Based on the tumor image database, a recognition rate of 96.5% was achieved. The experimental results show that hyperspectral imaging for tongue tumor diagnosis, together with the spectroscopic classification method provide a new approach for the noninvasive computer-aided diagnosis of tongue tumors. PMID:22368462

  3. Nonnegative Matrix Factorization for Efficient Hyperspectral Image Projection

    NASA Technical Reports Server (NTRS)

    Iacchetta, Alexander S.; Fienup, James R.; Leisawitz, David T.; Bolcar, Matthew R.

    2015-01-01

    Hyperspectral imaging for remote sensing has prompted development of hyperspectral image projectors that can be used to characterize hyperspectral imaging cameras and techniques in the lab. One such emerging astronomical hyperspectral imaging technique is wide-field double-Fourier interferometry. NASA's current, state-of-the-art, Wide-field Imaging Interferometry Testbed (WIIT) uses a Calibrated Hyperspectral Image Projector (CHIP) to generate test scenes and provide a more complete understanding of wide-field double-Fourier interferometry. Given enough time, the CHIP is capable of projecting scenes with astronomically realistic spatial and spectral complexity. However, this would require a very lengthy data collection process. For accurate but time-efficient projection of complicated hyperspectral images with the CHIP, the field must be decomposed both spectrally and spatially in a way that provides a favorable trade-off between accurately projecting the hyperspectral image and the time required for data collection. We apply nonnegative matrix factorization (NMF) to decompose hyperspectral astronomical datacubes into eigenspectra and eigenimages that allow time-efficient projection with the CHIP. Included is a brief analysis of NMF parameters that affect accuracy, including the number of eigenspectra and eigenimages used to approximate the hyperspectral image to be projected. For the chosen field, the normalized mean squared synthesis error is under 0.01 with just 8 eigenspectra. NMF of hyperspectral astronomical fields better utilizes the CHIP's capabilities, providing time-efficient and accurate representations of astronomical scenes to be imaged with the WIIT.

  4. Recent development of hyperspectral LiDAR using supercontinuum laser

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  5. Nonnegative matrix factorization for efficient hyperspectral image projection

    NASA Astrophysics Data System (ADS)

    Iacchetta, Alexander S.; Fienup, James R.; Leisawitz, David T.; Bolcar, Matthew R.

    2015-09-01

    Hyperspectral imaging for remote sensing has prompted development of hyperspectral image projectors that can be used to characterize hyperspectral imaging cameras and techniques in the lab. One such emerging astronomical hyperspectral imaging technique is wide-field double-Fourier interferometry. NASA's current, state-of-the-art, Wide-field Imaging Interferometry Testbed (WIIT) uses a Calibrated Hyperspectral Image Projector (CHIP) to generate test scenes and provide a more complete understanding of wide-field double-Fourier interferometry. Given enough time, the CHIP is capable of projecting scenes with astronomically realistic spatial and spectral complexity. However, this would require a very lengthy data collection process. For accurate but time-efficient projection of complicated hyperspectral images with the CHIP, the field must be decomposed both spectrally and spatially in a way that provides a favorable trade-off between accurately projecting the hyperspectral image and the time required for data collection. We apply nonnegative matrix factorization (NMF) to decompose hyperspectral astronomical datacubes into eigenspectra and eigenimages that allow time-efficient projection with the CHIP. Included is a brief analysis of NMF parameters that affect accuracy, including the number of eigenspectra and eigenimages used to approximate the hyperspectral image to be projected. For the chosen field, the normalized mean squared synthesis error is under 0.01 with just 8 eigenspectra. NMF of hyperspectral astronomical fields better utilizes the CHIP's capabilities, providing time-efficient and accurate representations of astronomical scenes to be imaged with the WIIT.

  6. Hyperspectral remote sensing of postfire soil properties

    Treesearch

    Sarah A. Lewis; Peter R. Robichaud; William J. Elliot; Bruce E. Frazier; Joan Q. Wu

    2004-01-01

    Forest fires may induce changes in soil organic properties that often lead to water repellent conditions within the soil profile that decrease soil infiltration capacity. The remote detection of water repellent soils after forest fires would lead to quicker and more accurate assessment of erosion potential. An airborne hyperspectral image was acquired over the Hayman...

  7. First observations using SPICE hyperspectral dataset

    NASA Astrophysics Data System (ADS)

    Rosario, Dalton; Romano, Joao; Borel, Christoph

    2014-06-01

    Our first observations using the longwave infrared (LWIR) hyperspectral data subset of the Spectral and Polarimetric Imagery Collection Experiment (SPICE) database are summarized in this paper, focusing on the inherent challenges associated with using this sensing modality for the purpose of object pattern recognition. Emphases are also put on data quality, qualitative validation of expected atmospheric spectral features, and qualitative comparison against another dataset of the same site using a different LWIR hyperspectral sensor. SPICE is a collaborative effort between the Army Research Laboratory, U.S. Army Armament RDEC, and more recently the Air Force Institute of Technology. It focuses on the collection and exploitation of longwave and midwave infrared (LWIR and MWIR) hyperspectral and polarimetric imagery. We concluded from this work that the quality of SPICE hyperspectral LWIR data is categorically comparable to other datasets recorded by a different sensor of similar specs; and adequate for algorithm research, given the scope of SPICE. The scope was to conduct a long-term infrared data collection of the same site with targets, using both sensing modalities, under various weather and non-ideal conditions. Then use the vast dataset and associated ground truth information to assess performance of the state of the art algorithms, while determining performance degradation sources. The expectation is that results from these assessments will spur new algorithmic ideas with the potential to augment pattern recognition performance in remote sensing applications. Over time, we are confident the SPICE database will prove to be an asset to the wide open remote sensing community.

  8. Parallel hyperspectral compressive sensing method on GPU

    NASA Astrophysics Data System (ADS)

    Bernabé, Sergio; Martín, Gabriel; Nascimento, José M. P.

    2015-10-01

    Remote hyperspectral sensors collect large amounts of data per flight usually with low spatial resolution. It is known that the bandwidth connection between the satellite/airborne platform and the ground station is reduced, thus a compression onboard method is desirable to reduce the amount of data to be transmitted. This paper presents a parallel implementation of an compressive sensing method, called parallel hyperspectral coded aperture (P-HYCA), for graphics processing units (GPU) using the compute unified device architecture (CUDA). This method takes into account two main properties of hyperspectral dataset, namely the high correlation existing among the spectral bands and the generally low number of endmembers needed to explain the data, which largely reduces the number of measurements necessary to correctly reconstruct the original data. Experimental results conducted using synthetic and real hyperspectral datasets on two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN, reveal that the use of GPUs can provide real-time compressive sensing performance. The achieved speedup is up to 20 times when compared with the processing time of HYCA running on one core of the Intel i7-2600 CPU (3.4GHz), with 16 Gbyte memory.

  9. Mine detection experiments using hyperspectral sensors

    NASA Astrophysics Data System (ADS)

    Winter, Edwin M.; Miller, Miranda A.; Simi, Christopher G.; Hill, Anthony B.; Williams, Timothy J.; Hampton, David; Wood, Mark; Zadnick, Jerry; Sviland, Marc D.

    2004-09-01

    Hyperspectral imaging is an important technology for the detection of surface and buried land mines from an airborne platform. For this reason, hyperspectral was included with SAR sensors in the two deployments that were executed by the CECOM RDEC Night Vision and Electronic Systems Directorate (NVESD) in Fall 2002 and in Spring 2003. The purpose of these deployments was to bring together a wide variety of airborne sensors for the detection of mines, with well ground-truthed targets. The hyperspectral sensors included the Airborne Hyperspectral Imager (AHI), a University of Hawaii LWIR HSI sensor and the Compact Airborne Spectral Sensor (COMPASS), an NVESD VNIR/SWIR sensor. Both a high frequency SAR and a ground penetrating radar were also flown. These experiments were carried out at sites where an extensive array of buried and surface mines were deployed. At the first location, on the east coast, the mines were deployed against several different backgrounds ranging from bare dirt to long grass. At the second location in the desert southwest, the mines were placed on backgrounds ranging from loose sand to mixed sand and vegetation. The COMPASS and AHI sensors were both placed on the Twin Otter aircraft, and data was collected with the airplane as low as 700 ft and as high as 4000 ft. In this paper, the data collected on surface mines will be reviewed, and specific examples from each background type presented. Spectral detection algorithms will be applied to the data and the results of the algorithm processing will be presented.

  10. GPU Lossless Hyperspectral Data Compression System

    NASA Technical Reports Server (NTRS)

    Aranki, Nazeeh I.; Keymeulen, Didier; Kiely, Aaron B.; Klimesh, Matthew A.

    2014-01-01

    Hyperspectral imaging systems onboard aircraft or spacecraft can acquire large amounts of data, putting a strain on limited downlink and storage resources. Onboard data compression can mitigate this problem but may require a system capable of a high throughput. In order to achieve a high throughput with a software compressor, a graphics processing unit (GPU) implementation of a compressor was developed targeting the current state-of-the-art GPUs from NVIDIA(R). The implementation is based on the fast lossless (FL) compression algorithm reported in "Fast Lossless Compression of Multispectral-Image Data" (NPO- 42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which operates on hyperspectral data and achieves excellent compression performance while having low complexity. The FL compressor uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. The new Consultative Committee for Space Data Systems (CCSDS) Standard for Lossless Multispectral & Hyperspectral image compression (CCSDS 123) is based on the FL compressor. The software makes use of the highly-parallel processing capability of GPUs to achieve a throughput at least six times higher than that of a software implementation running on a single-core CPU. This implementation provides a practical real-time solution for compression of data from airborne hyperspectral instruments.

  11. Hyperspectral signature analysis of skin parameters

    NASA Astrophysics Data System (ADS)

    Vyas, Saurabh; Banerjee, Amit; Garza, Luis; Kang, Sewon; Burlina, Philippe

    2013-02-01

    The temporal analysis of changes in biological skin parameters, including melanosome concentration, collagen concentration and blood oxygenation, may serve as a valuable tool in diagnosing the progression of malignant skin cancers and in understanding the pathophysiology of cancerous tumors. Quantitative knowledge of these parameters can also be useful in applications such as wound assessment, and point-of-care diagnostics, amongst others. We propose an approach to estimate in vivo skin parameters using a forward computational model based on Kubelka-Munk theory and the Fresnel Equations. We use this model to map the skin parameters to their corresponding hyperspectral signature. We then use machine learning based regression to develop an inverse map from hyperspectral signatures to skin parameters. In particular, we employ support vector machine based regression to estimate the in vivo skin parameters given their corresponding hyperspectral signature. We build on our work from SPIE 2012, and validate our methodology on an in vivo dataset. This dataset consists of 241 signatures collected from in vivo hyperspectral imaging of patients of both genders and Caucasian, Asian and African American ethnicities. In addition, we also extend our methodology past the visible region and through the short-wave infrared region of the electromagnetic spectrum. We find promising results when comparing the estimated skin parameters to the ground truth, demonstrating good agreement with well-established physiological precepts. This methodology can have potential use in non-invasive skin anomaly detection and for developing minimally invasive pre-screening tools.

  12. Hyperspectral image analysis for plant stress detection

    USDA-ARS?s Scientific Manuscript database

    Abiotic and disease-induced stress significantly reduces plant productivity. Automated on-the-go mapping of plant stress allows timely intervention and mitigating of the problem before critical thresholds are exceeded, thereby, maximizing productivity. A hyperspectral camera analyzed the spectral ...

  13. Biometric study using hyperspectral imaging during stress

    NASA Astrophysics Data System (ADS)

    Nagaraj, Sheela; Quoraishee, Shafik; Chan, Gabriel; Short, Kenneth R.

    2010-04-01

    To the casual observer, transient stress results in a variety of physiological changes that can be seen in the face. Although the conditions can be seen visibly, the conditions affect the emissivity and absorption properties of the skin, which imaging spectrometers, commonly referred to as Hyperspectral (HS) cameras, can quantify at every image pixel. The study reported on in this paper, using Hyperspectral cameras, provides a basis for continued study of HS imaging to eventually quantify biometric stress. This study was limited to the visible to near infrared (VNIR) spectral range. Signal processing tools and algorithms have been developed and are described for using HS face data from human subjects. The subjects were placed in psychologically stressful situations and the camera data were analyzed to detect stress through changes in dermal reflectance and emissivity. Results indicate that hyperspectral imaging may potentially serve as a non-invasive tool to measure changes in skin emissivity indicative of a stressful incident. Particular narrow spectral bands in the near-infrared region of the electromagnetic spectrum seem especially important. Further studies need to be performed to determine the optimal spectral bands and to generalize the conclusions. The enormous information available in hyperspectral imaging needs further analysis and more spectral regions need to be exploited. Non-invasive stress detection is a prominent area of research with countless applications for both military and commercial use including border patrol, stand-off interrogation, access control, surveillance, and non-invasive and un-attended patient monitoring.

  14. Structured Sparse Method for Hyperspectral Unmixing

    NASA Astrophysics Data System (ADS)

    Zhu, Feiyun; Wang, Ying; Xiang, Shiming; Fan, Bin; Pan, Chunhong

    2014-02-01

    Hyperspectral Unmixing (HU) has received increasing attention in the past decades due to its ability of unveiling information latent in hyperspectral data. Unfortunately, most existing methods fail to take advantage of the spatial information in data. To overcome this limitation, we propose a Structured Sparse regularized Nonnegative Matrix Factorization (SS-NMF) method based on the following two aspects. First, we incorporate a graph Laplacian to encode the manifold structures embedded in the hyperspectral data space. In this way, the highly similar neighboring pixels can be grouped together. Second, the lasso penalty is employed in SS-NMF for the fact that pixels in the same manifold structure are sparsely mixed by a common set of relevant bases. These two factors act as a new structured sparse constraint. With this constraint, our method can learn a compact space, where highly similar pixels are grouped to share correlated sparse representations. Experiments on real hyperspectral data sets with different noise levels demonstrate that our method outperforms the state-of-the-art methods significantly.

  15. Novel hyperspectral prediction method and apparatus

    NASA Astrophysics Data System (ADS)

    Kemeny, Gabor J.; Crothers, Natalie A.; Groth, Gard A.; Speck, Kathy A.; Marbach, Ralf

    2009-05-01

    Both the power and the challenge of hyperspectral technologies is the very large amount of data produced by spectral cameras. While off-line methodologies allow the collection of gigabytes of data, extended data analysis sessions are required to convert the data into useful information. In contrast, real-time monitoring, such as on-line process control, requires that compression of spectral data and analysis occur at a sustained full camera data rate. Efficient, high-speed practical methods for calibration and prediction are therefore sought to optimize the value of hyperspectral imaging. A novel method of matched filtering known as science based multivariate calibration (SBC) was developed for hyperspectral calibration. Classical (MLR) and inverse (PLS, PCR) methods are combined by spectroscopically measuring the spectral "signal" and by statistically estimating the spectral "noise." The accuracy of the inverse model is thus combined with the easy interpretability of the classical model. The SBC method is optimized for hyperspectral data in the Hyper-CalTM software used for the present work. The prediction algorithms can then be downloaded into a dedicated FPGA based High-Speed Prediction EngineTM module. Spectral pretreatments and calibration coefficients are stored on interchangeable SD memory cards, and predicted compositions are produced on a USB interface at real-time camera output rates. Applications include minerals, pharmaceuticals, food processing and remote sensing.

  16. Model-based Hyperspectral Exploitation Algorithm Development

    DTIC Science & Technology

    2006-01-01

    pixels, and an iterative constrained optimization using generalized reduced gradients ( GRG ). Sample results are shown in Figure 5. Much progress has...in-water optical parameters from remote observations involved a non-linear optimization that required observations of several regions of interests...retrieval from long wave infrared airborne hyperspectral imagery. The optimized land surface temperature and emissivity retrieval (OLSTER) algorithm

  17. Model-based Hyperspectral Exploitation Algorithm Development

    DTIC Science & Technology

    2007-09-30

    near- blackbody pixels, and an iterative constrained optimization using generalized reduced gradients ( GRG ). Sample results are shown in Figure 5...derive the spectral in-water optical parameters from remote observations involved a non-linear optimization that required observations of several...and emissivity retrieval from long wave infrared airborne hyperspectral imagery. The optimized land surface temperature and emissivity retrieval

  18. Mapping Waterhyacinth Infestations Using Airborne Hyperspectral Imagery

    USDA-ARS?s Scientific Manuscript database

    Waterhyacinth [Eichhornia crassipes (Mart.) Solms] is an exotic aquatic weed that often invades and clogs waterways in many tropical and subtropical regions of the world. The objective of this study was to evaluate airborne hyperspectral imagery and different image classification techniques for mapp...

  19. Mapping Soil Organic Matter with Hyperspectral Imaging

    NASA Astrophysics Data System (ADS)

    Moni, Christophe; Burud, Ingunn; Flø, Andreas; Rasse, Daniel

    2014-05-01

    Soil organic matter (SOM) plays a central role for both food security and the global environment. Soil organic matter is the 'glue' that binds soil particles together, leading to positive effects on soil water and nutrient availability for plant growth and helping to counteract the effects of erosion, runoff, compaction and crusting. Hyperspectral measurements of samples of soil profiles have been conducted with the aim of mapping soil organic matter on a macroscopic scale (millimeters and centimeters). Two soil profiles have been selected from the same experimental site, one from a plot amended with biochar and another one from a control plot, with the specific objective to quantify and map the distribution of biochar in the amended profile. The soil profiles were of size (30 x 10 x 10) cm3 and were scanned with two pushbroomtype hyperspectral cameras, one which is sensitive in the visible wavelength region (400 - 1000 nm) and one in the near infrared region (1000 - 2500 nm). The images from the two detectors were merged together into one full dataset covering the whole wavelength region. Layers of 15 mm were removed from the 10 cm high sample such that a total of 7 hyperspectral images were obtained from the samples. Each layer was analyzed with multivariate statistical techniques in order to map the different components in the soil profile. Moreover, a 3-dimensional visalization of the components through the depth of the sample was also obtained by combining the hyperspectral images from all the layers. Mid-infrared spectroscopy of selected samples of the measured soil profiles was conducted in order to correlate the chemical constituents with the hyperspectral results. The results show that hyperspectral imaging is a fast, non-destructive technique, well suited to characterize soil profiles on a macroscopic scale and hence to map elements and different organic matter quality present in a complete pedon. As such, we were able to map and quantify biochar in our

  20. ICER-3D Hyperspectral Image Compression Software

    NASA Technical Reports Server (NTRS)

    Xie, Hua; Kiely, Aaron; Klimesh, matthew; Aranki, Nazeeh

    2010-01-01

    Software has been developed to implement the ICER-3D algorithm. ICER-3D effects progressive, three-dimensional (3D), wavelet-based compression of hyperspectral images. If a compressed data stream is truncated, the progressive nature of the algorithm enables reconstruction of hyperspectral data at fidelity commensurate with the given data volume. The ICER-3D software is capable of providing either lossless or lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The compression algorithm, which was derived from the ICER image compression algorithm, includes wavelet-transform, context-modeling, and entropy coding subalgorithms. The 3D wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of sets of hyperspectral image data, while facilitating elimination of spectral ringing artifacts, using a technique summarized in "Improving 3D Wavelet-Based Compression of Spectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. Correlation is further exploited by a context-modeling subalgorithm, which exploits spectral dependencies in the wavelet-transformed hyperspectral data, using an algorithm that is summarized in "Context Modeler for Wavelet Compression of Hyperspectral Images" (NPO-43239), which follows this article. An important feature of ICER-3D is a scheme for limiting the adverse effects of loss of data during transmission. In this scheme, as in the similar scheme used by ICER, the spatial-frequency domain is partitioned into rectangular error-containment regions. In ICER-3D, the partitions extend through all the wavelength bands. The data in each partition are compressed independently of those in the other partitions, so that loss or corruption of data from any partition does not affect the other partitions. Furthermore, because compression is progressive within each partition, when data are lost, any data from that partition received

  1. Earth Observing-1 Extended Mission

    USGS Publications Warehouse

    ,

    2003-01-01

    From its beginning in November 2000, the NASA Earth Observing-1 (EO-1) mission demonstrated the feasibility and performance of a dozen innovative sensor, spacecraft, and operational technologies. The 1-year mission tested a variety of technologies, some of which may be included on the planned 2007 Landsat Data Continuity Mission. Onboard the spacecraft are two land remote sensing instruments: the Advanced Land Imager (ALI), which acquires data in spectral bands and at resolutions similar to Landsat, and Hyperion, which acquires data in 220 10-nanometer-wide bands covering the visible, near-, and shortwave-infrared bands. Recognizing the remarkable performance of the satellite's instruments and the exceptional value of the data, the U.S. Geological Survey (USGS) and NASA agreed in December 2001 to share responsibility for operating EO-1 on a cost-reimbursable basis as long as customer sales are sufficient to recover flight and ground operations costs. The EO-1 extended mission operates within constraints imposed by its technology-pioneering origins, but it also provides unique and valuable capabilities. The spacecraft can acquire a target scene three times in a 16-day period. The ALI instrument has additional spectral coverage and greater radiometric dynamic range compared with the sensors on Landsat 7. Hyperion is the first civilian spaceborne hyperspectral imager. As of January 2003, more than 5,000 scenes had been acquired, indexed, and archived.

  2. Chromotomosynthesis for high speed hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Bostick, Randall L.; Perram, Glen P.

    2012-09-01

    A rotating direct vision prism, chromotomosynthetic imaging (CTI) system operating in the visible creates hyperspectral imagery by collecting a set of 2D images with each spectrally projected at a different rotation angle of the prism. Mathematical reconstruction techniques that have been well tested in the field of medical physics are used to reconstruct the data to produce the 3D hyperspectral image. The instrument operates with a 100 mm focusing lens in the spectral range of 400-900 nm with a field of view of 71.6 mrad and angular resolution of 0.8-1.6 μrad. The spectral resolution is 0.6 nm at the shortest wavelengths, degrading to over 10 nm at the longest wavelengths. Measurements using a pointlike target show that performance is limited by chromatic aberration. The accuracy and utility of the instrument is assessed by comparing the CTI results to spatial data collected by a wideband image and hyperspectral data collected using a liquid crystal tunable filter (LCTF). The wide-band spatial content of the scene reconstructed from the CTI data is of same or better quality as a single frame collected by the undispersed imaging system with projections taken at every 1°. Performance is dependent on the number of projections used, with projections at 5° producing adequate results in terms of target characterization. The data collected by the CTI system can provide spatial information of equal quality as a comparable imaging system, provide high-frame rate slitless 1-D spectra, and generate 3-D hyperspectral imagery which can be exploited to provide the same results as a traditional multi-band spectral imaging system. While this prototype does not operate at high speeds, components exist which will allow for CTI systems to generate hyperspectral video imagery at rates greater than 100 Hz. The instrument has considerable potential for characterizing bomb detonations, muzzle flashes, and other battlefield combustion events.

  3. Spectral Reconstruction for Obtaining Virtual Hyperspectral Images

    NASA Astrophysics Data System (ADS)

    Perez, G. J. P.; Castro, E. C.

    2016-12-01

    Hyperspectral sensors demonstrated its capabalities in identifying materials and detecting processes in a satellite scene. However, availability of hyperspectral images are limited due to the high development cost of these sensors. Currently, most of the readily available data are from multi-spectral instruments. Spectral reconstruction is an alternative method to address the need for hyperspectral information. The spectral reconstruction technique has been shown to provide a quick and accurate detection of defects in an integrated circuit, recovers damaged parts of frescoes, and it also aids in converting a microscope into an imaging spectrometer. By using several spectral bands together with a spectral library, a spectrum acquired by a sensor can be expressed as a linear superposition of elementary signals. In this study, spectral reconstruction is used to estimate the spectra of different surfaces imaged by Landsat 8. Four atmospherically corrected surface reflectance from three visible bands (499 nm, 585 nm, 670 nm) and one near-infrared band (872 nm) of Landsat 8, and a spectral library of ground elements acquired from the United States Geological Survey (USGS) are used. The spectral library is limited to 420-1020 nm spectral range, and is interpolated at one nanometer resolution. Singular Value Decomposition (SVD) is used to calculate the basis spectra, which are then applied to reconstruct the spectrum. The spectral reconstruction is applied for test cases within the library consisting of vegetation communities. This technique was successful in reconstructing a hyperspectral signal with error of less than 12% for most of the test cases. Hence, this study demonstrated the potential of simulating information at any desired wavelength, creating a virtual hyperspectral sensor without the need for additional satellite bands.

  4. Illumination compensation in ground based hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Wendel, Alexander; Underwood, James

    2017-07-01

    Hyperspectral imaging has emerged as an important tool for analysing vegetation data in agricultural applications. Recently, low altitude and ground based hyperspectral imaging solutions have come to the fore, providing very high resolution data for mapping and studying large areas of crops in detail. However, these platforms introduce a unique set of challenges that need to be overcome to ensure consistent, accurate and timely acquisition of data. One particular problem is dealing with changes in environmental illumination while operating with natural light under cloud cover, which can have considerable effects on spectral shape. In the past this has been commonly achieved by imaging known reference targets at the time of data acquisition, direct measurement of irradiance, or atmospheric modelling. While capturing a reference panel continuously or very frequently allows accurate compensation for illumination changes, this is often not practical with ground based platforms, and impossible in aerial applications. This paper examines the use of an autonomous unmanned ground vehicle (UGV) to gather high resolution hyperspectral imaging data of crops under natural illumination. A process of illumination compensation is performed to extract the inherent reflectance properties of the crops, despite variable illumination. This work adapts a previously developed subspace model approach to reflectance and illumination recovery. Though tested on a ground vehicle in this paper, it is applicable to low altitude unmanned aerial hyperspectral imagery also. The method uses occasional observations of reference panel training data from within the same or other datasets, which enables a practical field protocol that minimises in-field manual labour. This paper tests the new approach, comparing it against traditional methods. Several illumination compensation protocols for high volume ground based data collection are presented based on the results. The findings in this paper are

  5. Hyperspectral analysis of columbia spotted frog habitat

    USGS Publications Warehouse

    Shive, J.P.; Pilliod, D.S.; Peterson, C.R.

    2010-01-01

    Wildlife managers increasingly are using remotely sensed imagery to improve habitat delineations and sampling strategies. Advances in remote sensing technology, such as hyperspectral imagery, provide more information than previously was available with multispectral sensors. We evaluated accuracy of high-resolution hyperspectral image classifications to identify wetlands and wetland habitat features important for Columbia spotted frogs (Rana luteiventris) and compared the results to multispectral image classification and United States Geological Survey topographic maps. The study area spanned 3 lake basins in the Salmon River Mountains, Idaho, USA. Hyperspectral data were collected with an airborne sensor on 30 June 2002 and on 8 July 2006. A 12-year comprehensive ground survey of the study area for Columbia spotted frog reproduction served as validation for image classifications. Hyperspectral image classification accuracy of wetlands was high, with a producer's accuracy of 96 (44 wetlands) correctly classified with the 2002 data and 89 (41 wetlands) correctly classified with the 2006 data. We applied habitat-based rules to delineate breeding habitat from other wetlands, and successfully predicted 74 (14 wetlands) of known breeding wetlands for the Columbia spotted frog. Emergent sedge microhabitat classification showed promise for directly predicting Columbia spotted frog egg mass locations within a wetland by correctly identifying 72 (23 of 32) of known locations. Our study indicates hyperspectral imagery can be an effective tool for mapping spotted frog breeding habitat in the selected mountain basins. We conclude that this technique has potential for improving site selection for inventory and monitoring programs conducted across similar wetland habitat and can be a useful tool for delineating wildlife habitats. ?? 2010 The Wildlife Society.

  6. Hyperspectral imager development at Army Research Laboratory

    NASA Astrophysics Data System (ADS)

    Gupta, Neelam

    2008-04-01

    Development of robust compact optical imagers that can acquire both spectral and spatial features from a scene of interest is of utmost importance for standoff detection of chemical and biological agents as well as targets and backgrounds. Spectral features arise due to the material properties of objects as a result of the emission, reflection, and absorption of light. Using hyperspectral imaging one can acquire images with narrow spectral bands and take advantage of the characteristic spectral signatures of different materials making up the scene in detection of objects. Traditional hyperspectral imaging systems use gratings and prisms that acquire one-dimensional spectral images and require relative motion of sensor and scene in addition to data processing to form a two-dimensional image cube. There is much interest in developing hyperspectral imagers using tunable filters that acquire a two-dimensional spectral image and build up an image cube as a function of time. At the Army Research Laboratory (ARL), we are developing hyperspectral imagers using a number of novel tunable filter technologies. These include acousto-optic tunable filters (AOTFs) that can provide adaptive no-moving-parts imagers from the UV to the long wave infrared, diffractive optics technology that can provide image cubes either in a single spectral region or simultaneously in different spectral regions using a single moving lens or by using a lenslet array, and micro-electromechanical systems (MEMS)-based Fabry-Perot (FP) tunable etalons to develop miniature sensors that take advantage of the advances in microfabrication and packaging technologies. New materials are being developed to design AOTFs and a full Stokes polarization imager has been developed, diffractive optics lenslet arrays are being explored, and novel FP tunable filters are under fabrication for the development of novel miniature hyperspectral imagers. Here we will brief on all the technologies being developed and present

  7. Perceptual Based Image Fusion with Applications to Hyperspectral Image Data.

    DTIC Science & Technology

    1994-12-01

    spectral bands from the AVIRIS hyperspectral sensor will be evaluated. 1.4 Approach/ Thesis Organization Chapter one described data processing problems...Based Image Fusion with Applications to Hyperspectral Image Data THESIS A o .:or \\Terry Allen Wilson NTS _ Captain, USAF DTIC Tf-, LI Unannou!c<ej LI...Applications to Hyperspectral Image Data THESIS Presented to the Faculty of the Graduate School of Engineering of the Air Force Institute of

  8. Spatial and Temporal Point Tracking in Real Hyperspectral Images

    DTIC Science & Technology

    2006-08-26

    Principle Components Analysis PDF - Probability Density Function PDF - Probability Density Function ROC - Receiver Operating Characteristics RX - Reed...HYPERCUBE CREATION 85 5.4.1 THE BACKGROUND HYPERCUBE 85 5.4.2 TARGET IMPLANTATION 86 5.4.3 NOISE ADDITION 87 5.4.4 EXAMPLES OF HYPERSPECTRAL MOVIE ...cubes or, simply put, a hyperspectral movie . Our research incorporates algorithms from two different areas – target detection in hyperspectral imagery

  9. Fusion Schemes for Ensembles of Hyperspectral Anomaly Detection Algorithms

    DTIC Science & Technology

    2011-03-01

    9] Robert J. Johnson, "Improved Feature Extraction, Feature Selection, and Identification Techniques that Create a Fast Unsupervised Hyperspectral ...FUSION SCHEMES FOR ENSEMBLES OF  HYPERSPECTRAL  ANOMALY DETECTION  ALGORITHMS...SCHEMES FOR ENSEMBLES OF  HYPERSPECTRAL  ANOMALY DETECTION  ALGORITHMS    THESIS          Presented to the Faculty     Department of Operational

  10. Statistical Modeling of Natural Backgrounds in Hyperspectral LWIR Data

    DTIC Science & Technology

    2016-09-06

    Statistical Modeling of Natural Backgrounds in Hyperspectral LWIR Data Eric Truslowa, Dimitris Manolakisa, Thomas Cooleyb, and Joseph Meolac aMIT...87117 cSensors Directorate, Air Force Research Laboratory, Wright-Patterson AFB, OH 45433 Hyperspectral sensors operating in the long wave infrared (LWIR...investigated. In this paper, we investigate modeling hyperspectral LWIR data using a statistical mixture model for the emissivity and surface

  11. See the Sea: multi-user information system for investigating processes and phenomena in coastal zones via satellite remotely sensed data, particularly hyperspectral data

    NASA Astrophysics Data System (ADS)

    Mityagina, Marina I.; Lavrova, Olga Yu.; Uvarov, Ivan A.

    2014-10-01

    The functionality, the goals and the current state of the distributed information system "See the Sea" (STS) are presented and discussed. This system is designed for investigating various processes and phenomena in the ocean and marine atmosphere using different types of satellite remotely sensed data. The STS system provides researchers with the possibilities to deal with the satellite remote sensing data as well as with the result of its analysis. The key feature of STS is the ability to work simultaneously with satellite information of different types. STS provides tools for joint analysis of different types of satellite data, as well as data of ground meteorological stations, cartographic data etc. This paper gives an overview of the system and data processing use cases. Some example cases are described including processing and joint analysis of various satellite data. The data from different sensors (obtained by Envisat ASAR, Landsat-8 OLI, Landsat-7 ETM+, Landsat-5 TM, Terra/Aqua MODIS as well as Hyperion and HICO hyperspectral data) was analyzed jointly for differentiation between different types of coastal waters, and for reconstruction of suspended matter distribution in the test areas of the Azov and Black Seas.

  12. Removal of clouds, dust and shadow pixels from hyperspectral imagery using a non-separable and stationary spatio-temporal covariance model

    NASA Astrophysics Data System (ADS)

    Angel, Yoseline; Houborg, Rasmus; McCabe, Matthew F.

    2016-10-01

    Hyperspectral remote sensing images are usually affected by atmospheric conditions such as clouds and their shadows, which represents a contamination of reflectance data and complicates the extraction of biophysical variables to monitor phenological cycles of crops. This paper explores a cloud removal approach based on reflectance prediction using multitemporal data and spatio-temporal statistical models. In particular, a covariance model that captures the behavior of spatial and temporal components in data simultaneously (i.e. non-separable) is considered. Eight weekly images collected from the Hyperion hyper-spectrometer instrument over an agricultural region of Saudi Arabia were used to reconstruct a scene with the presence of cloudy affected pixels over a center-pivot crop. A subset of reflectance values of cloud-free pixels from 50 bands in the spectral range from 426.82 to 884.7 nm at each date, were used as input to fit a parametric family of non-separable and stationary spatio-temporal covariance functions. Applying simple kriging as an interpolator, cloud affected pixels were replaced by cloud-free predicted values per band, obtaining their respective predicted spectral profiles at the same time. An exercise of reconstructing simulated cloudy pixels in a different swath was conducted to assess the model accuracy, achieving root mean square error (RMSE) values per band less than or equal to 3%. The spatial coherence of the results was also checked through absolute error distribution maps demonstrating their consistency.

  13. Improved spatial mapping of leaf area index using hyperspectral remote sensing for hydrological applications with a particular focus on canopy interception

    NASA Astrophysics Data System (ADS)

    Bulcock, H. H.; Jewitt, G. P. W.

    2009-09-01

    The use of remote sensing technology as a tool to estimate leaf area index (LAI) for use in estimating canopy interception is described in this paper. The establishment of commercial forestry plantations in natural grassland vegetation, results in increased transpiration and interception which in turn, results in a streamflow reduction. Methods to quantify this impact typically require LAI as an input into the various equations and process models that are applied. Remote sensing provides a potential solution to effectively monitor the spatial and temporal variability of LAI. This is illustrated using Hyperion hyperspectral imagery and three vegetation indices, namely the normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI) and Vogelmann index 1 to estimate LAI in a catchment afforested with Eucalyptus, Pinus and Acacia genera in the KwaZulu-Natal midlands of South Africa. Of the three vegetation indices used in this study, it was found that the Vogelmann index 1 was the most robust index with an R2 and root mean square error (RMSE) values of 0.7 and 0.3 respectively. However, both NDVI and SAVI could be used to estimate the LAI of 12 year old Pinus patula accurately. If the interception component is to be quantified independently, estimates of maximum storage capacity and canopy interception are required. Thus, the spatial distribution of LAI in the catchment is used to estimate maximum canopy storage capacity in the study area.

  14. Study on data mining technology in hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    Su, Hongjun; Sheng, Yehua; Wen, Yongning; Tao, Hong

    2007-06-01

    In this paper, the problems rise in hyperspectral data mining and some key issues should pay attention to were proposed based on the analysis on the state-of-art of hyperspectral data mining. The problems are as follows: data mining precision, mining algorithm efficiency, new hyperspectral data mining algorithms, the uncertainty in hyperspectral data mining, visualization in hyperspectral data mining process, and knowledge presentation, interpretation, estimation and management etc.. Some key issues should emphasize in the future are: systematic hyperspectral data mining theory, dimensionality reduction, mining spatial and temporal knowledge from images, and mining distributed data and mining multi-agent data. Also the framework and architecture of hyperspectral data mining were put forward in this paper. Hyperspectral data mining framework includes some subparts as follows: data selection, data preprocessing, data transfer, data mining and pattern estimation. And the architecture is composed of database, data warehouse, database management system, repository, mining process, user interface etc.. At last, an algorithm which named Relational perspective map (RPM) was introduced into the field of hyperspectral data mining. By the experiment on the spectra data from USGS spectral library, it proves that this algorithm is suitable to discover those spectral features and to identify and discriminate object classes based on their spectra.

  15. Multiview hyperspectral topography of tissue structural and functional characteristics

    NASA Astrophysics Data System (ADS)

    Zhang, Shiwu; Liu, Peng; Huang, Jiwei; Xu, Ronald

    2012-12-01

    Accurate and in vivo characterization of structural, functional, and molecular characteristics of biological tissue will facilitate quantitative diagnosis, therapeutic guidance, and outcome assessment in many clinical applications, such as wound healing, cancer surgery, and organ transplantation. However, many clinical imaging systems have limitations and fail to provide noninvasive, real time, and quantitative assessment of biological tissue in an operation room. To overcome these limitations, we developed and tested a multiview hyperspectral imaging system. The multiview hyperspectral imaging system integrated the multiview and the hyperspectral imaging techniques in a single portable unit. Four plane mirrors are cohered together as a multiview reflective mirror set with a rectangular cross section. The multiview reflective mirror set was placed between a hyperspectral camera and the measured biological tissue. For a single image acquisition task, a hyperspectral data cube with five views was obtained. The five-view hyperspectral image consisted of a main objective image and four reflective images. Three-dimensional topography of the scene was achieved by correlating the matching pixels between the objective image and the reflective images. Three-dimensional mapping of tissue oxygenation was achieved using a hyperspectral oxygenation algorithm. The multiview hyperspectral imaging technique is currently under quantitative validation in a wound model, a tissue-simulating blood phantom, and an in vivo biological tissue model. The preliminary results have demonstrated the technical feasibility of using multiview hyperspectral imaging for three-dimensional topography of tissue functional properties.

  16. Comparative alteration mineral mapping using visible to shortwave infrared (0.4-2.4 μm) Hyperion, ALI, and ASTER imagery

    USGS Publications Warehouse

    Hubbard, B.E.; Crowley, J.K.; Zimbelman, D.R.

    2003-01-01

    Advanced Land Imager (ALI), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Hyperion imaging spectrometer data covering an area in the Central Andes between Volcan Socompa and Salar de Llullaillaco were used to map hydrothermally altered rocks associated with several young volcanic systems. Six ALI channels in the visible and near-infrared wavelength range (0.4-1.0 ??m) were useful for discriminating between ferric-iron alteration minerals based on the spectral shapes of electronic absorption features seen in continuum-removed spectra. Six ASTER channels in the short wavelength infrared (1.0-2.5 ??m) enabled distinctions between clay and sulfate mineral types based on the positions of band minima related to Al-OH vibrational absorption features. Hyperion imagery embedded in the broader image coverage of ALI and ASTER provided essential leverage for calibrating and improving the mapping accuracy of the multispectral data. This capability is especially valuable in remote areas of the earth where available geologic and other ground truth information is limited.

  17. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    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.

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

    PubMed

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

    2016-02-25

    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.

  20. Thermophilic-anaerobic digestion to produce class A biosolids: initial full-scale studies at Hyperion Treatment Plant.

    PubMed

    Iranpour, R; Cox, H H J; Oh, S; Fan, S; Kearney, R J; Abkian, V; Haug, R T

    2006-02-01

    The highest quality of biosolids is called exceptional quality. To qualify for this classification, biosolids must comply with three criteria: (1) metal concentrations, (2) vector-attraction reduction, and (3) the Class A pathogen-density requirements. The City of Los Angeles Bureau of Sanitation Hyperion Treatment Plant (HTP) (Playa del Rey, California) meets the first two requirements. Thus, the objective of this study was to ensure that HTP's biosolids production would meet the Class A pathogen-reduction requirements following the time-temperature regimen for batch processing (U.S. EPA, 1993; Subsection 32, Alternative 1). Because regulations require the pathogen limits to be met at the last point of plant control, biosolids sampling was not limited to immediately after the digesters, i.e., the digester outflows. The sampling extended to several locations in HTP's postdigestion train, in particular, the last points of plant control, i.e., the truck loading facility and the farm for land application. A two-stage, thermophilic-continuous-batch process, consisting of a battery of six egg-shaped digesters, was established in late 2001 for phase I of this study and modified in early 2002 for phase II. As the biosolids were discharged from the second-stage digesters, the Salmonella sp. (pathogen) and fecal-coliform (indicator) densities were well below the limits for Class A biosolids, even though the second-stage-digester temperatures were a few degrees below the temperature required by Alternative 1. Salmonella sp. densities remained below the Class A limit at all postdigestion sampling locations. Fecal-coliform densities were also below the Class A limit at postdigestion-sampling locations, except the truck-loading facility (phases I and II) and the farm for final use of the biosolids (phase II). Although federal regulations require one of the limits for either fecal coliforms or Salmonella sp. to be met, local regulations in Kern County, California, where the

  1. Anomaly Detection and Comparative Analysis of Hydrothermal Alteration Materials Trough Hyperspectral Multisensor Data in the Turrialba Volcano

    NASA Astrophysics Data System (ADS)

    Rejas, J. G.; Martínez-Frías, J.; Bonatti, J.; Martínez, R.; Marchamalo, M.

    2012-07-01

    The aim of this work is the comparative study of the presence of hydrothermal alteration materials in the Turrialba volcano (Costa Rica) in relation with computed spectral anomalies from multitemporal and multisensor data adquired in spectral ranges of the visible (VIS), short wave infrared (SWIR) and thermal infrared (TIR). We used for this purposes hyperspectral and multispectral images from the HyMAP and MASTER airborne sensors, and ASTER and Hyperion scenes in a period between 2002 and 2010. Field radiometry was applied in order to remove the atmospheric contribution in an empirical line method. HyMAP and MASTER images were georeferenced directly thanks to positioning and orientation data that were measured at the same time in the acquisition campaign from an inertial system based on GPS/IMU. These two important steps were allowed the identification of spectral diagnostic bands of hydrothermal alteration minerals and the accuracy spatial correlation. Enviromental impact of the volcano activity has been studied through different vegetation indexes and soil patterns. Have been mapped hydrothermal materials in the crater of the volcano, in fact currently active, and their surrounding carrying out a principal components analysis differentiated for a high and low absorption bands to characterize accumulations of kaolinite, illite, alunite and kaolinite+smectite, delimitating zones with the presence of these minerals. Spectral anomalies have been calculated on a comparative study of methods pixel and subpixel focused in thermal bands fused with high-resolution images. Results are presented as an approach based on expert whose main interest lies in the automated identification of patterns of hydrothermal altered materials without prior knowledge or poor information on the area.

  2. Metric Learning to Enhance Hyperspectral Image Segmentation

    NASA Technical Reports Server (NTRS)

    Thompson, David R.; Castano, Rebecca; Bue, Brian; Gilmore, Martha S.

    2013-01-01

    Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy.

  3. Hyperspectral image data compression based on DSP

    NASA Astrophysics Data System (ADS)

    Fan, Jiming; Zhou, Jiankang; Chen, Xinhua; Shen, Weimin

    2010-11-01

    The huge data volume of hyperspectral image challenges its transportation and store. It is necessary to find an effective method to compress the hyperspectral image. Through analysis and comparison of current various algorithms, a mixed compression algorithm based on prediction, integer wavelet transform and embedded zero-tree wavelet (EZW) is proposed in this paper. We adopt a high-powered Digital Signal Processor (DSP) of TMS320DM642 to realize the proposed algorithm. Through modifying the mixed algorithm and optimizing its algorithmic language, the processing efficiency of the program was significantly improved, compared the non-optimized one. Our experiment show that the mixed algorithm based on DSP runs much faster than the algorithm on personal computer. The proposed method can achieve the nearly real-time compression with excellent image quality and compression performance.

  4. Classification of High Spatial Resolution, Hyperspectral ...

    EPA Pesticide Factsheets

    EPA announced the availability of the final report,Hyperspectral Remote Sensing Imagery of the Little Miami River Watershed in Southwest Ohio, USA . This report and associated land use/land cover (LULC) coverage is the result of a collaborative effort among an interdisciplinary team of scientists with the U.S. Environmental Protection Agency's (U.S. EPA's) Office of Research and Development in Cincinnati, Ohio. A primary goal of this project is to enhance the use of geography and spatial analytic tools in risk assessment, and to improve the scientific basis for risk management decisions affecting drinking water and water quality. The land use/land cover classification is derived from 82 flight lines of Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery acquired from July 24 through August 9, 2002 via fixed-wing aircraft.

  5. Software for Simulation of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

    Richtsmeier, Steven C.; Singer-Berk, Alexander; Bernstein, Lawrence S.

    2002-01-01

    A package of software generates simulated hyperspectral images for use in validating algorithms that generate estimates of Earth-surface spectral reflectance from hyperspectral images acquired by airborne and spaceborne instruments. This software is based on a direct simulation Monte Carlo approach for modeling three-dimensional atmospheric radiative transport as well as surfaces characterized by spatially inhomogeneous bidirectional reflectance distribution functions. In this approach, 'ground truth' is accurately known through input specification of surface and atmospheric properties, and it is practical to consider wide variations of these properties. The software can treat both land and ocean surfaces and the effects of finite clouds with surface shadowing. The spectral/spatial data cubes computed by use of this software can serve both as a substitute for and a supplement to field validation data.

  6. Estimating physiological skin parameters from hyperspectral signatures

    NASA Astrophysics Data System (ADS)

    Vyas, Saurabh; Banerjee, Amit; Burlina, Philippe

    2013-05-01

    We describe an approach for estimating human skin parameters, such as melanosome concentration, collagen concentration, oxygen saturation, and blood volume, using hyperspectral radiometric measurements (signatures) obtained from in vivo skin. We use a computational model based on Kubelka-Munk theory and the Fresnel equations. This model forward maps the skin parameters to a corresponding multiband reflectance spectra. Machine-learning-based regression is used to generate the inverse map, and hence estimate skin parameters from hyperspectral signatures. We test our methods using synthetic and in vivo skin signatures obtained in the visible through the short wave infrared domains from 24 patients of both genders and Caucasian, Asian, and African American ethnicities. Performance validation shows promising results: good agreement with the ground truth and well-established physiological precepts. These methods have potential use in the characterization of skin abnormalities and in minimally-invasive prescreening of malignant skin cancers.

  7. Estimating physiological skin parameters from hyperspectral signatures.

    PubMed

    Vyas, Saurabh; Banerjee, Amit; Burlina, Philippe

    2013-05-01

    We describe an approach for estimating human skin parameters, such as melanosome concentration, collagen concentration, oxygen saturation, and blood volume, using hyperspectral radiometric measurements (signatures) obtained from in vivo skin. We use a computational model based on Kubelka-Munk theory and the Fresnel equations. This model forward maps the skin parameters to a corresponding multiband reflectance spectra. Machine-learning-based regression is used to generate the inverse map, and hence estimate skin parameters from hyperspectral signatures. We test our methods using synthetic and in vivo skin signatures obtained in the visible through the short wave infrared domains from 24 patients of both genders and Caucasian, Asian, and African American ethnicities. Performance validation shows promising results: good agreement with the ground truth and well-established physiological precepts. These methods have potential use in the characterization of skin abnormalities and in minimally-invasive prescreening of malignant skin cancers.

  8. Field deployable pushbroom hyperspectral imagining polarimeter

    NASA Astrophysics Data System (ADS)

    Lowenstern, Mariano; Kudenov, Michael W.

    2016-05-01

    Hyperspectral polarimetry is demonstrated to measure the spectrum and polarization state of a scene. This information is important to identify material properties for applications such as remote sensing and agricultural monitoring, among others. We report the design and performance of a ruggedized, field deployable Hyperspectral Polarimeter Imaging (HPI) system over the VIS to NIR range (450-800 nm). An entrance slit was used to sample a scene in a pushbroom scanning mode, sampling over a 30 degree vertical by 110 degree horizontal field of view. Furthermore, athermalized achromatic retarders were implemented in a channel spectrum generator to measure the linear Stoke vectors. This paper reports the mechanical and optical layout of the system and its peripherals. We present preliminary spectral and polarimetry calibration techniques as well as testing results in field environments.

  9. Supervised Classification Techniques for Hyperspectral Data

    NASA Technical Reports Server (NTRS)

    Jimenez, Luis O.

    1997-01-01

    The recent development of more sophisticated remote sensing systems enables the measurement of radiation in many mm-e spectral intervals than previous possible. An example of this technology is the AVIRIS system, which collects image data in 220 bands. The increased dimensionality of such hyperspectral data provides a challenge to the current techniques for analyzing such data. Human experience in three dimensional space tends to mislead one's intuition of geometrical and statistical properties in high dimensional space, properties which must guide our choices in the data analysis process. In this paper high dimensional space properties are mentioned with their implication for high dimensional data analysis in order to illuminate the next steps that need to be taken for the next generation of hyperspectral data classifiers.

  10. Albedo recovery for hyperspectral image classification

    NASA Astrophysics Data System (ADS)

    Zhan, Kun; Wang, Haibo; Xie, Yuange; Zhang, Chutong; Min, Yufang

    2017-07-01

    Image intensity value is determined by both the albedo component and the shading component. The albedo component describes the physical nature of different objects at the surface of the earth, and land-cover classes are different from each other because of their intrinsic physical materials. We, therefore, recover the intrinsic albedo feature of the hyperspectral image to exploit the spatial semantic information. Then, we use the support vector machine (SVM) to classify the recovered intrinsic albedo hyperspectral image. The SVM tries to maximize the minimum margin to achieve good generalization performance. Experimental results show that the SVM with the intrinsic albedo feature method achieves a better classification performance than the state-of-the-art methods in terms of visual quality and three quantitative metrics.

  11. Piecewise flat embeddings for hyperspectral image analysis

    NASA Astrophysics Data System (ADS)

    Hayes, Tyler L.; Meinhold, Renee T.; Hamilton, John F.; Cahill, Nathan D.

    2017-05-01

    Graph-based dimensionality reduction techniques such as Laplacian Eigenmaps (LE), Local Linear Embedding (LLE), Isometric Feature Mapping (ISOMAP), and Kernel Principal Components Analysis (KPCA) have been used in a variety of hyperspectral image analysis applications for generating smooth data embeddings. Recently, Piecewise Flat Embeddings (PFE) were introduced in the computer vision community as a technique for generating piecewise constant embeddings that make data clustering / image segmentation a straightforward process. In this paper, we show how PFE arises by modifying LE, yielding a constrained ℓ1-minimization problem that can be solved iteratively. Using publicly available data, we carry out experiments to illustrate the implications of applying PFE to pixel-based hyperspectral image clustering and classification.

  12. Hyperspectral all-sky imaging of auroras.

    PubMed

    Sigernes, Fred; Ivanov, Yuriy; Chernouss, Sergey; Trondsen, Trond; Roldugin, Alexey; Fedorenko, Yury; Kozelov, Boris; Kirillov, Andrey; Kornilov, Ilia; Safargaleev, Vladimir; Holmen, Silje; Dyrland, Margit; Lorentzen, Dag; Baddeley, Lisa

    2012-12-03

    A prototype auroral hyperspectral all-sky camera has been constructed and tested. It uses electro-optical tunable filters to image the night sky as a function of wavelength throughout the visible spectrum with no moving mechanical parts. The core optical system includes a new high power all-sky lens with F-number equal to f/1.1. The camera has been tested at the Kjell Henriksen Observatory (KHO) during the auroral season of 2011/2012. It detects all sub classes of aurora above ~½ of the sub visual 1kR green intensity threshold at an exposure time of only one second. Supervised classification of the hyperspectral data shows promise as a new method to process and identify auroral forms.

  13. Miniaturization of a SWIR hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Warren, Christopher P.; Pfister, William; Even, Detlev; Velasco, Arleen; Yee, Selwyn; Breitwieser, David; Naungayan, Joseph

    2011-05-01

    A new approach for the design and fabrication of a miniaturized SWIR Hyperspectral imager is described. Previously, good results were obtained with a VNIR Hyperspectral imager, by use of light propagation within bonded solid blocks of fused silica. These designs use the Offner design form, providing excellent, low distortion imaging. The same idea is applied to the SWIR Hyperspectral imager here, resulting in a microHSITM SWIR Hyperspectral sensor, capable of operating in the 850-1700 nm wavelength range. The microHSI spectrometer weighs 910 g from slit input to camera output. This spectrometer can accommodate custom foreoptics to adapt to a wide range of fields-of-view (FOV). The current application calls for a 15 degree FOV, and utilizes an InGaAs image sensor with a spatial format of 640 x 25 micron pixels. This results in a slit length of 16 mm, and a foreoptics focal length of 61 mm, operating at F# = 2.8. The resulting IFOV is 417 μrad for this application, and a spectral dispersion of 4.17 nm/pixel. A prototype SWIR microHSI was fabricated, and the blazed diffraction grating was embedded within the optical blocks, resulting in a 72% diffraction efficiency at the wavelength of 1020 nm. This spectrometer design is capable of accommodating slit lengths of up to 25.6 mm, which opens up a wide variety of applications. The microHSI concepts can be extended to other wavelength regions, and a miniaturized LWIR microHSI sensor is in the conceptual design stage.

  14. Compressive Hyperspectral Imaging and Anomaly Detection

    DTIC Science & Technology

    2010-02-01

    the desired jointly sparse a"s, one shall adjust a and b. 4.4 Hyperspectral Image Reconstruction and Denoising We apply the model x* = Da’ + e! to...iteration for compressive sensing and sparse denoising ,’" Communications in Mathematical Sciences , 2008. W. Yin, "Analysis and generalizations of...Aharon, M. Elad, and A. Bruckstein, "K- SVD : An algorithm for designing overcomplete dictionaries for sparse representation,’" IEEE Transactions on Signal

  15. Neural Network-Based Hyperspectral Algorithms

    DTIC Science & Technology

    2016-06-07

    Neural Network -Based Hyperspectral Algorithms Walter F. Smith, Jr. and Juanita Sandidge Naval Research Laboratory Code 7340, Bldg 1105 Stennis Space...combination of in-situ and model data of water column variables (IOP’s, depth, bottom type, upwelling radiance, etc.) a neural network non-linear... network (Lippman, 1987). Neural network -based algorithms have been demonstrated by the investigators for retrieval of water depth from Airborne Visible

  16. Processing and analyzing advanced hyperspectral imagery data

    NASA Astrophysics Data System (ADS)

    El-Nahry, A. H.

    2006-09-01

    The main objective of the current work is to recognize the dominant and predominant clay minerals of South Port Said plain soils, Egypt using the high advanced remote sensing techniques of hyperspectral data. Spectral analyses as one of the most advanced remote sensing techniques were used for the aforementioned purpose. Different spectral processes have been used to execute the prospective spectral analyses. These processes include 1-The reflectance calibration of hyperspectral data belonging to the studied area, 2- Using the minimum noise fraction (MNF) transformation. 3 -Creating the pixel purity index (PPI) which used as a mean of finding the most "spectrally pure", extreme, pixel in hyperspectral images. Making conjunction between the Minimum Noise Fraction Transform (MNF) and Pixel Purity Index (PPI) tools through 3-D visualization offered capabilities to locate, identify, and cluster the purest pixels and most extreme spectral responses in a data set. To identify the clay minerals of the studied area the extracted unknown spectra of the purest pixels was matched to pre-defined (library) spectra providing score with respect to the library spectra. Three methods namely, Spectral Feature Fitting (SFF),Spectral Angle Mapper (SAM) and Binary Encoding (BE) were used to produce score between 0 and 1, where the value of I equal a perfect match showing exactly the mineral type. In the investigated area four clay minerals could be identified i.e. Vermiculite, Kaolinite, Montmorillinite, and Illite recording different scores related to their abundance in the soils. In order to check the validity and accuracy of the obtained results, X-ray diffraction analysis was applied on surface soil samples covering the same locations of the end-members that derived from hyperspectral image. Highly correlated and significant results were obtained using the two approaches (spectral signatures and x-ray diffraction).

  17. Synergetics Framework for Hyperspectral Image Classification

    NASA Astrophysics Data System (ADS)

    Müller, R.; Cerra, D.; Reinartz, P.

    2013-05-01

    In this paper a new classification technique for hyperspectral data based on synergetics theory is presented. Synergetics - originally introduced by the physicist H. Haken - is an interdisciplinary theory to find general rules for pattern formation through selforganization and has been successfully applied in fields ranging from biology to ecology, chemistry, cosmology, and thermodynamics up to sociology. Although this theory describes general rules for pattern formation it was linked also to pattern recognition. Pattern recognition algorithms based on synergetics theory have been applied to images in the spatial domain with limited success in the past, given their dependence on the rotation, shifting, and scaling of the images. These drawbacks can be discarded if such methods are applied to data acquired by a hyperspectral sensor in the spectral domain, as each single spectrum, related to an image element in the hyperspectral scene, can be analysed independently. The classification scheme based on synergetics introduces also methods for spatial regularization to get rid of "salt and pepper" classification results and for iterative parameter tuning to optimize class weights. The paper reports an experiment on a benchmark data set frequently used for method comparisons. This data set consists of a hyperspectral scene acquired by the Airborne Visible Infrared Imaging Spectrometer AVIRIS sensor of the Jet Propulsion Laboratory acquired over the Salinas Valley in CA, USA, with 15 vegetation classes. The results are compared to state-of-the-art methodologies like Support Vector Machines (SVM), Spectral Information Divergence (SID), Neural Networks, Logistic Regression, Factor Graphs or Spectral Angle Mapper (SAM). The outcomes are promising and often outperform state-of-the-art classification methodologies.

  18. Compressive hyperspectral sensor for LWIR gas detection

    NASA Astrophysics Data System (ADS)

    Russell, Thomas A.; McMackin, Lenore; Bridge, Bob; Baraniuk, Richard

    2012-06-01

    Focal plane arrays with associated electronics and cooling are a substantial portion of the cost, complexity, size, weight, and power requirements of Long-Wave IR (LWIR) imagers. Hyperspectral LWIR imagers add significant data volume burden as they collect a high-resolution spectrum at each pixel. We report here on a LWIR Hyperspectral Sensor that applies Compressive Sensing (CS) in order to achieve benefits in these areas. The sensor applies single-pixel detection technology demonstrated by Rice University. The single-pixel approach uses a Digital Micro-mirror Device (DMD) to reflect and multiplex the light from a random assortment of pixels onto the detector. This is repeated for a number of measurements much less than the total number of scene pixels. We have extended this architecture to hyperspectral LWIR sensing by inserting a Fabry-Perot spectrometer in the optical path. This compressive hyperspectral imager collects all three dimensions on a single detection element, greatly reducing the size, weight and power requirements of the system relative to traditional approaches, while also reducing data volume. The CS architecture also supports innovative adaptive approaches to sensing, as the DMD device allows control over the selection of spatial scene pixels to be multiplexed on the detector. We are applying this advantage to the detection of plume gases, by adaptively locating and concentrating target energy. A key challenge in this system is the diffraction loss produce by the DMD in the LWIR. We report the results of testing DMD operation in the LWIR, as well as system spatial and spectral performance.

  19. Alternative Asymmetric Hypothesis Tests for Hyperspectral Imagery

    DTIC Science & Technology

    2006-02-01

    This report focuses on the development of statistical anomaly detection techniques aimed at accentuating the presence of meaningful objects, e.g., a...significant improvement in anomaly detection performance via a principle of indirect comparison, where samples are not compared to each other as individual...development of four unconventional techniques for hyperspectral (HS) anomaly detection . The first technique is based on some of the advances made on

  20. Hyperspectral Ocean Color Science: Santa Barbara Channel

    DTIC Science & Technology

    2016-06-07

    HYPERSPECTRAL OCEAN COLOR SCIENCE: SANTA BARBARA CHANNEL David A. Siegel Institute of Computational Earth System Science University of California at...University of California at Santa Barbara,Institute of Computational Earth System Science,Santa Barbara,CA,93106 8. PERFORMING ORGANIZATION REPORT...correction term required for the above-water Rrs + ( )λ estimates limits the utility of this technique to very calm days . Ours is one of the first

  1. LIFTERS-hyperspectral imaging at LLNL

    SciTech Connect

    Fields, D.; Bennett, C.; Carter, M.

    1994-11-15

    LIFTIRS, the Livermore Imaging Fourier Transform InfraRed Spectrometer, recently developed at LLNL, is an instrument which enables extremely efficient collection and analysis of hyperspectral imaging data. LIFTIRS produces a spatial format of 128x128 pixels, with spectral resolution arbitrarily variable up to a maximum of 0.25 inverse centimeters. Time resolution and spectral resolution can be traded off for each other with great flexibility. We will discuss recent measurements made with this instrument, and present typical images and spectra.

  2. Ore minerals textural characterization by hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Bonifazi, Giuseppe; Picone, Nicoletta; Serranti, Silvia

    2013-02-01

    The utilization of hyperspectral detection devices, for natural resources mapping/exploitation through remote sensing techniques, dates back to the early 1970s. From the first devices utilizing a one-dimensional profile spectrometer, HyperSpectral Imaging (HSI) devices have been developed. Thus, from specific-customized devices, originally developed by Governmental Agencies (e.g. NASA, specialized research labs, etc.), a lot of HSI based equipment are today available at commercial level. Parallel to this huge increase of hyperspectral systems development/manufacturing, addressed to airborne application, a strong increase also occurred in developing HSI based devices for "ground" utilization that is sensing units able to play inside a laboratory, a processing plant and/or in an open field. Thanks to this diffusion more and more applications have been developed and tested in this last years also in the materials sectors. Such an approach, when successful, is quite challenging being usually reliable, robust and characterised by lower costs if compared with those usually associated to commonly applied analytical off- and/or on-line analytical approaches. In this paper such an approach is presented with reference to ore minerals characterization. According to the different phases and stages of ore minerals and products characterization, and starting from the analyses of the detected hyperspectral firms, it is possible to derive useful information about mineral flow stream properties and their physical-chemical attributes. This last aspect can be utilized to define innovative process mineralogy strategies and to implement on-line procedures at processing level. The present study discusses the effects related to the adoption of different hardware configurations, the utilization of different logics to perform the analysis and the selection of different algorithms according to the different characterization, inspection and quality control actions to apply.

  3. Polarimetric Hyperspectral Imaging Systems and Applications

    NASA Technical Reports Server (NTRS)

    Cheng, Li-Jen; Mahoney, Colin; Reyes, George; Baw, Clayton La; Li, G. P.

    1996-01-01

    This paper reports activities in the development of AOTF Polarimetric Hyperspectral Imaging (PHI) Systems at JPL along with field observation results for illustrating the technology capabilities and advantages in remote sensing. In addition, the technology was also used to measure thickness distribution and structural imperfections of silicon-on-silicon wafers using white light interference phenomenon for demonstrating the potential in scientific and industrial applications.

  4. Excitation-scanning hyperspectral imaging microscope.

    PubMed

    Favreau, Peter F; Hernandez, Clarissa; Heaster, Tiffany; Alvarez, Diego F; Rich, Thomas C; Prabhat, Prashant; Leavesley, Silas J

    2014-04-01

    Hyperspectral imaging is a versatile tool that has recently been applied to a variety of biomedical applications, notably live-cell and whole-tissue signaling. Traditional hyperspectral imaging approaches filter the fluorescence emission over a broad wavelength range while exciting at a single band. However, these emission-scanning approaches have shown reduced sensitivity due to light attenuation from spectral filtering. Consequently, emission scanning has limited applicability for time-sensitive studies and photosensitive applications. In this work, we have developed an excitation-scanning hyperspectral imaging microscope that overcomes these limitations by providing high transmission with short acquisition times. This is achieved by filtering the fluorescence excitation rather than the emission. We tested the efficacy of the excitation-scanning microscope in a side-by-side comparison with emission scanning for detection of green fluorescent protein (GFP)-expressing endothelial cells in highly autofluorescent lung tissue. Excitation scanning provided higher signal-to-noise characteristics, as well as shorter acquisition times (300  ms/wavelength band with excitation scanning versus 3  s/wavelength band with emission scanning). Excitation scanning also provided higher delineation of nuclear and cell borders, and increased identification of GFP regions in highly autofluorescent tissue. These results demonstrate excitation scanning has utility in a wide range of time-dependent and photosensitive applications.

  5. Matching pursuit analysis of hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Alparone, Luciano; Argenti, Fabrizio; Dionisio, Michele

    2003-11-01

    Aim of this paper is investigating the use of overcomplete bases for the representation of hyperspectral image data. The idea is building an overcomplete basis starting from several orthogonal or non-orthogonal bases and picking the subset of such vectors best matching pixel spectra. A common technique to select the most representative elements of a signal is Matching Pursuit (MP). An iterative approach is used to find the coefficients of the linear combination of vectors, so that the residual function has minimum energy. The computational cost is extremely high when a large set of data is to be processed. Therefore, a reduced data set (RDS) is produced by applying the projection pursuit (PP) technique to each of the segments in which the hyperspectral image is partitioned based on a spatial homogeneity criterion of pixel spectra. Then MP is applied to the RDS to find a non-orthogonal frame capable to represent such data through waveforms selected to best match spectral features. Experimental results carried out on the hyperspectral data AVIRIS Moffett Field '97 compare a dictionary of wavelet functions with a dictionary of endmembers spectra. Although the former is preferable in terms of energy compaction, the latter is superior for physical significance of the resulting components.

  6. PET and PVC separation with hyperspectral imagery.

    PubMed

    Moroni, Monica; Mei, Alessandro; Leonardi, Alessandra; Lupo, Emanuela; Marca, Floriana La

    2015-01-20

    Traditional plants for plastic separation in homogeneous products employ material physical properties (for instance density). Due to the small intervals of variability of different polymer properties, the output quality may not be adequate. Sensing technologies based on hyperspectral imaging have been introduced in order to classify materials and to increase the quality of recycled products, which have to comply with specific standards determined by industrial applications. This paper presents the results of the characterization of two different plastic polymers--polyethylene terephthalate (PET) and polyvinyl chloride (PVC)--in different phases of their life cycle (primary raw materials, urban and urban-assimilated waste and secondary raw materials) to show the contribution of hyperspectral sensors in the field of material recycling. This is accomplished via near-infrared (900-1700 nm) reflectance spectra extracted from hyperspectral images acquired with a two-linear-spectrometer apparatus. Results have shown that a rapid and reliable identification of PET and PVC can be achieved by using a simple two near-infrared wavelength operator coupled to an analysis of reflectance spectra. This resulted in 100% classification accuracy. A sensor based on this identification method appears suitable and inexpensive to build and provides the necessary speed and performance required by the recycling industry.

  7. Hyperspectral image classification using Support Vector Machine

    NASA Astrophysics Data System (ADS)

    Moughal, T. A.

    2013-06-01

    Classification of land cover hyperspectral images is a very challenging task due to the unfavourable ratio between the number of spectral bands and the number of training samples. The focus in many applications is to investigate an effective classifier in terms of accuracy. The conventional multiclass classifiers have the ability to map the class of interest but the considerable efforts and large training sets are required to fully describe the classes spectrally. Support Vector Machine (SVM) is suggested in this paper to deal with the multiclass problem of hyperspectral imagery. The attraction to this method is that it locates the optimal hyper plane between the class of interest and the rest of the classes to separate them in a new high-dimensional feature space by taking into account only the training samples that lie on the edge of the class distributions known as support vectors and the use of the kernel functions made the classifier more flexible by making it robust against the outliers. A comparative study has undertaken to find an effective classifier by comparing Support Vector Machine (SVM) to the other two well known classifiers i.e. Maximum likelihood (ML) and Spectral Angle Mapper (SAM). At first, the Minimum Noise Fraction (MNF) was applied to extract the best possible features form the hyperspectral imagery and then the resulting subset of the features was applied to the classifiers. Experimental results illustrate that the integration of MNF and SVM technique significantly reduced the classification complexity and improves the classification accuracy.

  8. Hyperspectral surveying for mineral resources in Alaska

    USGS Publications Warehouse

    Kokaly, Raymond F.; Graham, Garth E.; Hoefen, Todd M.; Kelley, Karen D.; Johnson, Michaela R.; Hubbard, Bernard E.

    2016-07-07

    Alaska is a major producer of base and precious metals and has a high potential for additional undiscovered mineral resources. However, discovery is hindered by Alaska’s vast size, remoteness, and rugged terrain. New methods are needed to overcome these obstacles in order to fully evaluate Alaska’s geology and mineral resource potential. Hyperspectral surveying is one method that can be used to rapidly acquire data about the distributions of surficial materials, including different types of bedrock and ground cover. In 2014, the U.S. Geological Survey began the Alaska Hyperspectral Project to assess the applicability of this method in Alaska. The primary study area is a remote part of the eastern Alaska Range where porphyry deposits are exposed. In collaboration with the Alaska Division of Geological and Geophysical Surveys, the University of Alaska Fairbanks, and the National Park Service, the U.S. Geological Survey is collecting and analyzing hyperspectral data with the goals of enhancing geologic mapping and developing methods to identify and characterize mineral deposits elsewhere in Alaska.

  9. Infrared hyperspectral imaging for chemical vapour detection

    NASA Astrophysics Data System (ADS)

    Ruxton, K.; Robertson, G.; Miller, W.; Malcolm, G. P. A.; Maker, G. T.; Howle, C. R.

    2012-10-01

    Active hyperspectral imaging is a valuable tool in a wide range of applications. One such area is the detection and identification of chemicals, especially toxic chemical warfare agents, through analysis of the resulting absorption spectrum. This work presents a selection of results from a prototype midwave infrared (MWIR) hyperspectral imaging instrument that has successfully been used for compound detection at a range of standoff distances. Active hyperspectral imaging utilises a broadly tunable laser source to illuminate the scene with light at a range of wavelengths. While there are a number of illumination methods, the chosen configuration illuminates the scene by raster scanning the laser beam using a pair of galvanometric mirrors. The resulting backscattered light from the scene is collected by the same mirrors and focussed onto a suitable single-point detector, where the image is constructed pixel by pixel. The imaging instrument that was developed in this work is based around an IR optical parametric oscillator (OPO) source with broad tunability, operating in the 2.6 to 3.7 μm (MWIR) and 1.5 to 1.8 μm (shortwave IR, SWIR) spectral regions. The MWIR beam was primarily used as it addressed the fundamental absorption features of the target compounds compared to the overtone and combination bands in the SWIR region, which can be less intense by more than an order of magnitude. We show that a prototype NCI instrument was able to locate hydrocarbon materials at distances up to 15 metres.

  10. PET and PVC Separation with Hyperspectral Imagery

    PubMed Central

    Moroni, Monica; Mei, Alessandro; Leonardi, Alessandra; Lupo, Emanuela; La Marca, Floriana

    2015-01-01

    Traditional plants for plastic separation in homogeneous products employ material physical properties (for instance density). Due to the small intervals of variability of different polymer properties, the output quality may not be adequate. Sensing technologies based on hyperspectral imaging have been introduced in order to classify materials and to increase the quality of recycled products, which have to comply with specific standards determined by industrial applications. This paper presents the results of the characterization of two different plastic polymers—polyethylene terephthalate (PET) and polyvinyl chloride (PVC)—in different phases of their life cycle (primary raw materials, urban and urban-assimilated waste and secondary raw materials) to show the contribution of hyperspectral sensors in the field of material recycling. This is accomplished via near-infrared (900–1700 nm) reflectance spectra extracted from hyperspectral images acquired with a two-linear-spectrometer apparatus. Results have shown that a rapid and reliable identification of PET and PVC can be achieved by using a simple two near-infrared wavelength operator coupled to an analysis of reflectance spectra. This resulted in 100% classification accuracy. A sensor based on this identification method appears suitable and inexpensive to build and provides the necessary speed and performance required by the recycling industry. PMID:25609050

  11. Illumination system characterization for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Katrašnik, Jaka; Pernuš, Franjo; Likar, Boštjan

    2011-03-01

    Near-infrared hyperspectral imaging is becoming a popular tool in the biomedical field, especially for detection and analysis of different types of cancers, analysis of skin burns and bruises, imaging of blood vessels and for many other applications. As in all imaging systems, proper illumination is crucial to attain optimal image quality that is needed for best performance of image analysis algorithms. In hyperspectral imaging based on filters (AOTF, LCTF and filter wheel) the acquired spectral signature has to be representative in all parts of the imaged object. Therefore, the whole object must be equally well illuminated - without shadows and specular reflections. As there are no restrictions imposed on the material and geometry of the object, the desired object illumination can only be achieved with completely diffuse illumination. In order to minimize shadows and specular reflections in diffuse illumination the light illuminating the object must be spatially, angularly and spectrally uniform. We present and test two diffuse illumination system designs that try to achieve optimal uniformity of the above mentioned properties. The illumination uniformity properties were measured with an AOTF based hyperspectral imaging system utilizing a standard white diffuse reflectance target and a specially designed calibration target for estimating the spatial and angular illumination uniformity.

  12. Broadband QWIP FPAs for hyperspectral applications

    NASA Astrophysics Data System (ADS)

    Reisinger, Axel; Dennis, Richard; Patnaude, Kelly; Burrows, Douglas; Bundas, Jason; Beech, Kim; Faska, Ross; Sundaram, Mani

    2013-07-01

    Is a quantum well infrared photodetector (QWIP) suitable for hyperspectral applications? Yes, provided its spectral response is broad enough, the signal-to-noise ratio in narrow spectral slices across the entire response band is high enough, and the operating temperature is reasonable. We present the performance of a 640 × 512 QWIP focal plane array (FPA) with nearly uniform spectral response from 8 to 12 μm that achieves temporal noise equivalent temperature difference (NETD) lower than 200 mK in 20 nm wide spectral slices across the entire 8-12 μm band with the FPA operating at a temperature of 50 K or colder. A hyperspectral camera would feature a grating or prism to disperse 8-12 μm light across such a FPA or a hyperspectral filter on top of the FPA. Operating in pushbroom mode on an earth-observing satellite, the camera can be used for spectral mapping of vegetation, crops and forests, for pollution monitoring, and for studies in atmospheric chemistry.

  13. Fast compression implementation for hyperspectral sensor

    NASA Astrophysics Data System (ADS)

    Hihara, Hiroki; Yoshida, Jun; Ishida, Juro; Takada, Jun; Senda, Yuzo; Suzuki, Makoto; Seki, Taeko; Ichikawa, Satoshi; Ohgi, Nagamitsu

    2010-11-01

    Fast and small foot print lossless image compressors aiming at hyper-spectral sensor for the earth observation satellite have been developed. Since more than one hundred channels are required for hyper-spectral sensors on optical observation satellites, fast compression algorithm with small foot print implementation is essential for reducing encoder size and weight resulting in realizing light-weight and small-size sensor system. The image compression method should have low complexity in order to reduce size and weight of the sensor signal processing unit, power consumption and fabrication cost. Coding efficiency and compression speed enables enlargement of the capacity of signal compression channels, which resulted in reducing signal compression channels onboard by multiplexing sensor signal channels into reduced number of compression channels. The employed method is based on FELICS1, which is hierarchical predictive coding method with resolution scaling. To improve FELICS's performance of image decorrelation and entropy coding, we applied two-dimensional interpolation prediction and adaptive Golomb-Rice coding, which enables small footprint. It supports progressive decompression using resolution scaling, whilst still delivering superior performance as measured by speed and complexity. The small footprint circuitry is embedded into the hyper-spectral sensor data formatter. In consequence, lossless compression function has been added without additional size and weight.

  14. Hyperspectral Anomaly Detection in Urban Scenarios

    NASA Astrophysics Data System (ADS)

    Rejas Ayuga, J. G.; Martínez Marín, R.; Marchamalo Sacristán, M.; Bonatti, J.; Ojeda, J. C.

    2016-06-01

    We have studied the spectral features of reflectance and emissivity in the pattern recognition of urban materials in several single hyperspectral scenes through a comparative analysis of anomaly detection methods and their relationship with city surfaces with the aim to improve information extraction processes. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of AHS sensor and HyMAP and MASTER of two cities, Alcalá de Henares (Spain) and San José (Costa Rica) respectively, have been used. In this research it is assumed no prior knowledge of the targets, thus, the pixels are automatically separated according to their spectral information, significantly differentiated with respect to a background, either globally for the full scene, or locally by image segmentation. Several experiments on urban scenarios and semi-urban have been designed, analyzing the behaviour of the standard RX anomaly detector and different methods based on subspace, image projection and segmentation-based anomaly detection methods. A new technique for anomaly detection in hyperspectral data called DATB (Detector of Anomalies from Thermal Background) based on dimensionality reduction by projecting targets with unknown spectral signatures to a background calculated from thermal spectrum wavelengths is presented. First results and their consequences in non-supervised classification and extraction information processes are discussed.

  15. Excitation-scanning hyperspectral imaging microscope

    PubMed Central

    Favreau, Peter F.; Hernandez, Clarissa; Heaster, Tiffany; Alvarez, Diego F.; Rich, Thomas C.; Prabhat, Prashant; Leavesley, Silas J.

    2014-01-01

    Abstract. Hyperspectral imaging is a versatile tool that has recently been applied to a variety of biomedical applications, notably live-cell and whole-tissue signaling. Traditional hyperspectral imaging approaches filter the fluorescence emission over a broad wavelength range while exciting at a single band. However, these emission-scanning approaches have shown reduced sensitivity due to light attenuation from spectral filtering. Consequently, emission scanning has limited applicability for time-sensitive studies and photosensitive applications. In this work, we have developed an excitation-scanning hyperspectral imaging microscope that overcomes these limitations by providing high transmission with short acquisition times. This is achieved by filtering the fluorescence excitation rather than the emission. We tested the efficacy of the excitation-scanning microscope in a side-by-side comparison with emission scanning for detection of green fluorescent protein (GFP)-expressing endothelial cells in highly autofluorescent lung tissue. Excitation scanning provided higher signal-to-noise characteristics, as well as shorter acquisition times (300  ms/wavelength band with excitation scanning versus 3  s/wavelength band with emission scanning). Excitation scanning also provided higher delineation of nuclear and cell borders, and increased identification of GFP regions in highly autofluorescent tissue. These results demonstrate excitation scanning has utility in a wide range of time-dependent and photosensitive applications. PMID:24727909

  16. Hyperspectral imaging of skin and lung cancers

    NASA Astrophysics Data System (ADS)

    Zherdeva, Larisa A.; Bratchenko, Ivan A.; Alonova, Marina V.; Myakinin, Oleg O.; Artemyev, Dmitry N.; Moryatov, Alexander A.; Kozlov, Sergey V.; Zakharov, Valery P.

    2016-04-01

    The problem of cancer control requires design of new approaches for instrumental diagnostics, as the accuracy of cancer detection on the first step of diagnostics in clinics is slightly more than 50%. In this study, we present a method of visualization and diagnostics of skin and lung tumours based on registration and processing of tissues hyperspectral images. In a series of experiments registration of hyperspectral images of skin and lung tissue samples is carried out. Melanoma, basal cell carcinoma, nevi and benign tumours are studied in skin ex vivo and in vivo experiments; adenocarcinomas and squamous cell carcinomas are studied in ex vivo lung experiments. In a series of experiments the typical features of diffuse reflection spectra for pathological and normal tissues were found. Changes in tissues morphology during the tumour growth lead to the changes of blood and pigments concentration, such as melanin in skin. That is why tumours and normal tissues maybe differentiated with information about spectral response in 500-600 nm and 600 - 670 nm areas. Thus, hyperspectral imaging in the visible region may be a useful tool for cancer detection as it helps to estimate spectral properties of tissues and determine malignant regions for precise resection of tumours.

  17. Hyperspectral Anomaly Detection by Graph Pixel Selection.

    PubMed

    Yuan, Yuan; Ma, Dandan; Wang, Qi

    2016-12-01

    Hyperspectral anomaly detection (AD) is an important problem in remote sensing field. It can make full use of the spectral differences to discover certain potential interesting regions without any target priors. Traditional Mahalanobis-distance-based anomaly detectors assume the background spectrum distribution conforms to a Gaussian distribution. However, this and other similar distributions may not be satisfied for the real hyperspectral images. Moreover, the background statistics are susceptible to contamination of anomaly targets which will lead to a high false-positive rate. To address these intrinsic problems, this paper proposes a novel AD method based on the graph theory. We first construct a vertex- and edge-weighted graph and then utilize a pixel selection process to locate the anomaly targets. Two contributions are claimed in this paper: 1) no background distributions are required which makes the method more adaptive and 2) both the vertex and edge weights are considered which enables a more accurate detection performance and better robustness to noise. Intensive experiments on the simulated and real hyperspectral images demonstrate that the proposed method outperforms other benchmark competitors. In addition, the robustness of the proposed method has been validated by using various window sizes. This experimental result also demonstrates the valuable characteristic of less computational complexity and less parameter tuning for real applications.

  18. Ship classification in terrestrial hyperspectral data

    NASA Astrophysics Data System (ADS)

    Keskin, Göksu; Schilling, Hendrik; Lenz, Andreas; Groß, Wolfgang; Middelmann, Wolfgang

    2016-10-01

    This work analyzes the applicability of using hyperspectral data for ship classification in coastal or harbor environment. An approach for hyperspectral feature selection based on bag-of-words method was developed. Nearest neighbor and random forest classifiers were used for evaluating hyperspectral bag-of-words features. The evaluation dataset was self-acquired at the Kiel Harbor in Germany, using Aisa Eagle in VNIR and Aisa Hawk in SWIR sensors. The dataset included 547 samples of 72 objects ranging from passenger ferries to sailing boats in different illumination conditions. An object library was created from the dataset and bag-of-words features were extracted. Two different separation strategies for separating training and test sets were selected: Random subsets and chronologically separated subsets. Chronological separation was more challenging than the random separation for both classifiers. In order to allow a future sliding window operation for object detection, the training and the classification were performed additionally on rectangular windows including background pixels. The performance of nearest neighbor classifier dropped whereas the performance of random forest classifier slightly improved. Overall performance of random forest classifier is better than nearest neighbor classifier; however it requires a more comprehensive dataset for training. The evaluations indicated that the bag-of-words feature selection is feasible for the given application.

  19. Postfire soil burn severity mapping with hyperspectral image unmixing

    Treesearch

    Peter R. Robichaud; Sarah A. Lewis; Denise Y. M. Laes; Andrew T. Hudak; Raymond F. Kokaly; Joseph A. Zamudio

    2007-01-01

    Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after...

  20. Hyperspectral Imaging for Defect Detection of Pickling Cucumber

    USDA-ARS?s Scientific Manuscript database

    This book chapter reviews the recent progress on hyperspectral imaging technology for defect inspection of pickling cucumbers. The chapter first describes near-infrared hyperspectral reflectance imaging technique for the detection of bruises on pickling cucumbers. The technique showed good detection...

  1. Developing a portable GPU library for hyperspectral image processing

    NASA Astrophysics Data System (ADS)

    Pérez-Irizarry, Gabriel J.; De La Cruz-Sanchez, Francisco; Landrón-Rivera, Brian A.; Santiago, Nayda G.; Velez-Reyes, Miguel

    2012-06-01

    The increasing volume of data produced by hyperspectral image sensors have forced researches and developers to seek out new and more ecient ways of analyzing the data as quick as possible. Medical, scientic, and military applications present performance requirements for tools that perform operations on hyperspectral sensor data. By providing a hyperspectral image analysis library, we aim to accelerate hyperspectral image application development. Development of a cross-platform library, Libdect, with GPU support for hyperspectral image analysis is presented. Coupling library development with ecient hyperspectral algorithms escalates into a signicant time invest- ment in many projects or prototypes. Provided a solution to these issues, developers can implement hyperspectral image analysis applications in less time. Developers will not be focused on implementing target detection code and potential issues related to platform or GPU architecture dierences. Libdect's development team counts with previously implemented detection algorithms. By utilizing proven tools, such as CMake and CTest, to develop Libdect's infrastructure, we were able to develop and test a prototype library that provides target detection code with GPU support on Linux platforms. As a whole, Libdect is an early prototype of an open and documented example of Software Engineering practices and tools. They are put together in an eort to increase developer productivity and encourage new developers into the eld of hyperspectral image application development.

  2. Multiview hyperspectral topography of tissue structural and functional characteristics

    NASA Astrophysics Data System (ADS)

    Liu, Peng; Huang, Jiwei; Zhang, Shiwu; Xu, Ronald X.

    2016-01-01

    Accurate and in vivo characterization of structural, functional, and molecular characteristics of biological tissue will facilitate quantitative diagnosis, therapeutic guidance, and outcome assessment in many clinical applications, such as wound healing, cancer surgery, and organ transplantation. We introduced and tested a multiview hyperspectral imaging technique for noninvasive topographic imaging of cutaneous wound oxygenation. The technique integrated a multiview module and a hyperspectral module in a single portable unit. Four plane mirrors were cohered to form a multiview reflective mirror set with a rectangular cross section. The mirror set was placed between a hyperspectral camera and the target biological tissue. For a single image acquisition task, a hyperspectral data cube with five views was obtained. The five-view hyperspectral image consisted of a main objective image and four reflective images. Three-dimensional (3-D) topography of the scene was achieved by correlating the matching pixels between the objective image and the reflective images. 3-D mapping of tissue oxygenation was achieved using a hyperspectral oxygenation algorithm. The multiview hyperspectral imaging technique was validated in a wound model, a tissue-simulating blood phantom, and in vivo biological tissue. The experimental results demonstrated the technical feasibility of using multiview hyperspectral imaging for 3-D topography of tissue functional properties.

  3. Hyperspectral Imagery Classification Using a Backpropagation Neural Network

    DTIC Science & Technology

    1993-12-01

    A backpropagation neural network was developed and implemented for classifying AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) hyperspectral...imagery. It is a fully interconnected linkage of three layers of neural network . Fifty input layer neurons take in signals from Bands 41 to 90 of the...moderate AVIRIS pixel resolution of 20 meters by 20 meters. Backpropagation neural network , Hyperspectral imagery

  4. Hyperspectral microscopy to identify foodborne bacteria with optimum lighting source

    USDA-ARS?s Scientific Manuscript database

    Hyperspectral microscopy is an emerging technology for rapid detection of foodborne pathogenic bacteria. Since scattering spectral signatures from hyperspectral microscopic images (HMI) vary with lighting sources, it is important to select optimal lights. The objective of this study is to compare t...

  5. A Developed Spectral Identification Tree for Mineral Mapping using Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Gan, Fuping; Wang, Runsheng; Yan, Bokun; Shang, Kun

    2016-04-01

    The relationship between the spectral features and the composition of minerals are the basis of mineral identification using hyperspectral data. The reflectance spectrum of minerals results from the systematic combination of several modes of interaction between electromagnetic energy and mineral particles in the form of reflection and absorption. Minerals tend to have absorbing features at specific wavelengths with a characteristic shape, which can be used as diagnostic indicators for identification. The spectral identification tree (SIT) method for mineral identification is developed in our research to map minerals accurately and applied in some typical mineral deposits in China. The SIT method is based on the diagnostic absorption features of minerals through comparing and statistically analyzing characteristic spectral data of minerals. We establish several levels of identification rules for the type, group and species of minerals using IF-THEN rule according to the spectral identification criteria so that the developed SIT can be further used to map minerals at different levels of detail from mineral type to mineral species. Identifiable minerals can be grouped into six types: Fe2+-bearing, Fe3+-bearing, Mn2+-bearing, Al-OH-bearing, Mg-OH-bearing and carbonate minerals. Each type can be further divided into several mineral groups. Each group contains several mineral species or specific minerals. A mineral spectral series, therefore, can be constructed as "type-group-species-specific mineral (mineral variety)" for mineral spectral identification. It is noted that the mineral classification is based mainly on spectral reflectance characteristics of minerals which may not be consistent with the classification in mineralogy. We applied the developed SIT method to the datasets acquired at the Eastern Tianshan Mountains of Xinjiang (HyMap data) and the Qulong district of Xizang (Hyperion data). In Xinjiang, the two major classes of Al-OH and Mg-OH minerals were

  6. Using Hyperspectral Imagery to Identify Turfgrass Stresses

    NASA Technical Reports Server (NTRS)

    Hutto, Kendall; Shaw, David

    2008-01-01

    The use of a form of remote sensing to aid in the management of large turfgrass fields (e.g. golf courses) has been proposed. A turfgrass field of interest would be surveyed in sunlight by use of an airborne hyperspectral imaging system, then the raw observational data would be preprocessed into hyperspectral reflectance image data. These data would be further processed to identify turfgrass stresses, to determine the spatial distributions of those stresses, and to generate maps showing the spatial distributions. Until now, chemicals and water have often been applied, variously, (1) indiscriminately to an entire turfgrass field without regard to localization of specific stresses or (2) to visible and possibly localized signs of stress for example, browning, damage from traffic, or conspicuous growth of weeds. Indiscriminate application is uneconomical and environmentally unsound; the amounts of water and chemicals consumed could be insufficient in some areas and excessive in most areas, and excess chemicals can leak into the environment. In cases in which developing stresses do not show visible signs at first, it could be more economical and effective to take corrective action before visible signs appear. By enabling early identification of specific stresses and their locations, the proposed method would provide guidance for planning more effective, more economical, and more environmentally sound turfgrass-management practices, including application of chemicals and water, aeration, and mowing. The underlying concept of using hyperspectral imagery to generate stress maps as guides to efficient management of vegetation in large fields is not new; it has been applied in the growth of crops to be harvested. What is new here is the effort to develop an algorithm that processes hyperspectral reflectance data into spectral indices specific to stresses in turfgrass. The development effort has included a study in which small turfgrass plots that were, variously, healthy or

  7. Mapping pigment distribution in mud samples through hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Mehrübeoglu, Mehrube; Nicula, Cosmina; Trombley, Christopher; Smith, Shane W.; Smith, Dustin K.; Shanks, Elizabeth S.; Zimba, Paul V.

    2015-09-01

    Mud samples collected from bodies of water reveal information about the distribution of microorganisms in the local sediments. Hyperspectral imaging has been investigated as a technology to identify phototropic organisms living on sediments collected from the Texas Coastal Bend area based on their spectral pigment profiles and spatial arrangement. The top pigment profiles identified through high-performance liquid chromatography (HPLC) have been correlated with spectral signatures extracted from the hyperspectral data of mud using fast Fourier transform (FFT). Spatial distributions have also been investigated using 2D hyperspectral image processing. 2D pigment distribution maps have been created based on the correlation with pigment profiles in the FFT domain. Among the tested pigments, the results show match among four out of five pigment distribution trends between HPLC and hyperspectral data analysis. Differences are attributed mainly to the difference between area and volume of scale between the HPLC analysis and area covered by hyperspectral imaging.

  8. Spectral-Spatial Hyperspectral Image Classification Based on KNN

    NASA Astrophysics Data System (ADS)

    Huang, Kunshan; Li, Shutao; Kang, Xudong; Fang, Leyuan

    2016-12-01

    Fusion of spectral and spatial information is an effective way in improving the accuracy of hyperspectral image classification. In this paper, a novel spectral-spatial hyperspectral image classification method based on K nearest neighbor (KNN) is proposed, which consists of the following steps. First, the support vector machine is adopted to obtain the initial classification probability maps which reflect the probability that each hyperspectral pixel belongs to different classes. Then, the obtained pixel-wise probability maps are refined with the proposed KNN filtering algorithm that is based on matching and averaging nonlocal neighborhoods. The proposed method does not need sophisticated segmentation and optimization strategies while still being able to make full use of the nonlocal principle of real images by using KNN, and thus, providing competitive classification with fast computation. Experiments performed on two real hyperspectral data sets show that the classification results obtained by the proposed method are comparable to several recently proposed hyperspectral image classification methods.

  9. Massively parallel processing of remotely sensed hyperspectral images

    NASA Astrophysics Data System (ADS)

    Plaza, Javier; Plaza, Antonio; Valencia, David; Paz, Abel

    2009-08-01

    In this paper, we develop several parallel techniques for hyperspectral image processing that have been specifically designed to be run on massively parallel systems. The techniques developed cover the three relevant areas of hyperspectral image processing: 1) spectral mixture analysis, a popular approach to characterize mixed pixels in hyperspectral data addressed in this work via efficient implementation of a morphological algorithm for automatic identification of pure spectral signatures or endmembers from the input data; 2) supervised classification of hyperspectral data using multi-layer perceptron neural networks with back-propagation learning; and 3) automatic target detection in the hyperspectral data using orthogonal subspace projection concepts. The scalability of the proposed parallel techniques is investigated using Barcelona Supercomputing Center's MareNostrum facility, one of the most powerful supercomputers in Europe.

  10. Investigating coral hyperspectral properties across coral species and coral state using hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Mehrubeoglu, Mehrube; Smith, Dustin K.; Smith, Shane W.; Strychar, Kevin B.; McLauchlan, Lifford

    2013-09-01

    Coral reefs are one of the most diverse and threatened ecosystems in the world. Corals worldwide are at risk, and in many instances, dying due to factors that affect their environment resulting in deteriorating environmental conditions. Because corals respond quickly to the quality of the environment that surrounds them, corals have been identified as bioindicators of water quality and marine environmental health. The hyperspectral imaging system is proposed as a noninvasive tool to monitor different species of corals as well as coral state over time. This in turn can be used as a quick and non-invasive method to monitor environmental health that can later be extended to climate conditions. In this project, a laboratory-based hyperspectral imaging system is used to collect spectral and spatial information of corals. In the work presented here, MATLAB and ENVI software tools are used to view and process spatial information and coral spectral signatures to identify differences among the coral data. The results support the hypothesis that hyperspectral properties of corals vary among different coral species, and coral state over time, and hyperspectral imaging can be a used as a tool to document changes in coral species and state.

  11. Hyperspectral imaging for cancer surgical margin delineation: registration of hyperspectral and histological images

    NASA Astrophysics Data System (ADS)

    Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo G.; Fei, Baowei

    2014-03-01

    The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection.

  12. Hyperspectral Imaging for Cancer Surgical Margin Delineation: Registration of Hyperspectral and Histological Images

    PubMed Central

    Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

    2014-01-01

    The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection. PMID:25328640

  13. Entry-Level Spin Distributions of Sm Isotopes from the (p,t) Reaction at 25 MeV using Hyperion and STARLiTeR

    NASA Astrophysics Data System (ADS)

    Cooper, N.; Humby, P.; Beausang, C. W.; Wilson, E.; Hughes, R. O.; Ota, S.; Koglin, J.; Casperson, R. J.; Burke, J.; Simon, A.; Reingold, C.; McCleskey, M.; McCleskey, E.; Saastamoinen, A.; Chyzh, R.; Dag, M.; Hyperion Collaboration

    2016-09-01

    The surrogate method has proven to be a useful tool in determining neutron capture cross sections. However, differences in level properties populated in these experimental studies, which are currently being performed near stability, may have an impact on extracted cross sections. This talk will focus on an experiment performed at the Texas A&M Cyclotron Institute with the Hyperion Si telescope and HPGe detector array. Outgoing particles were detected following the reaction of 25 MeV protons incident on an enriched 150Sm target. Results from recently developed codes to extract the entry-level spin distributions from experimental data as well as predict this distribution will be presented for 148Sm as well as 150,152Sm using past experimental data from STARLiteR. This work was partly supported by DOE Grants No. DE-FG02-05ER41379 and No. DE-NA0001801.

  14. Comparing methods for analysis of biomedical hyperspectral image data

    NASA Astrophysics Data System (ADS)

    Leavesley, Silas J.; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter F.; Annamdevula, Naga S.; Rich, Thomas C.

    2017-02-01

    Over the past 2 decades, hyperspectral imaging technologies have been adapted to address the need for molecule-specific identification in the biomedical imaging field. Applications have ranged from single-cell microscopy to whole-animal in vivo imaging and from basic research to clinical systems. Enabling this growth has been the availability of faster, more effective hyperspectral filtering technologies and more sensitive detectors. Hence, the potential for growth of biomedical hyperspectral imaging is high, and many hyperspectral imaging options are already commercially available. However, despite the growth in hyperspectral technologies for biomedical imaging, little work has been done to aid users of hyperspectral imaging instruments in selecting appropriate analysis algorithms. Here, we present an approach for comparing the effectiveness of spectral analysis algorithms by combining experimental image data with a theoretical "what if" scenario. This approach allows us to quantify several key outcomes that characterize a hyperspectral imaging study: linearity of sensitivity, positive detection cut-off slope, dynamic range, and false positive events. We present results of using this approach for comparing the effectiveness of several common spectral analysis algorithms for detecting weak fluorescent protein emission in the midst of strong tissue autofluorescence. Results indicate that this approach should be applicable to a very wide range of applications, allowing a quantitative assessment of the effectiveness of the combined biology, hardware, and computational analysis for detecting a specific molecular signature.

  15. Thin-film tunable filters for hyperspectral fluorescence microscopy

    PubMed Central

    Favreau, Peter; Hernandez, Clarissa; Lindsey, Ashley Stringfellow; Alvarez, Diego F.; Rich, Thomas; Prabhat, Prashant

    2013-01-01

    Abstract. Hyperspectral imaging is a powerful tool that acquires data from many spectral bands, forming a contiguous spectrum. Hyperspectral imaging was originally developed for remote sensing applications; however, hyperspectral techniques have since been applied to biological fluorescence imaging applications, such as fluorescence microscopy and small animal fluorescence imaging. The spectral filtering method largely determines the sensitivity and specificity of any hyperspectral imaging system. There are several types of spectral filtering hardware available for microscopy systems, most commonly acousto-optic tunable filters (AOTFs) and liquid crystal tunable filters (LCTFs). These filtering technologies have advantages and disadvantages. Here, we present a novel tunable filter for hyperspectral imaging—the thin-film tunable filter (TFTF). The TFTF presents several advantages over AOTFs and LCTFs, most notably, a high percentage transmission and a high out-of-band optical density (OD). We present a comparison of a TFTF-based hyperspectral microscopy system and a commercially available AOTF-based system. We have characterized the light transmission, wavelength calibration, and OD of both systems, and have then evaluated the capability of each system for discriminating between green fluorescent protein and highly autofluorescent lung tissue. Our results suggest that TFTFs are an alternative approach for hyperspectral filtering that offers improved transmission and out-of-band blocking. These characteristics make TFTFs well suited for other biomedical imaging devices, such as ophthalmoscopes or endoscopes. PMID:24077519

  16. An Approach for Characterizing and Comparing Hyperspectral Microscopy Systems

    PubMed Central

    Annamdevula, Naga S.; Sweat, Brenner; Favreau, Peter; Lindsey, Ashley S.; Alvarez, Diego F.; Rich, Thomas C.; Leavesley, Silas J.

    2013-01-01

    Hyperspectral imaging and analysis approaches offer accurate detection and quantification of fluorescently-labeled proteins and cells in highly autofluorescent tissues. However, selecting optimum acquisition settings for hyperspectral imaging is often a daunting task. In this study, we compared two hyperspectral systems—a widefield system with acoustic optical tunable filter (AOTF) and charge coupled device (CCD) camera, and a confocal system with diffraction gratings and photomultiplier tube (PMT) array. We measured the effects of system parameters on hyperspectral image quality and linear unmixing results. Parameters that were assessed for the confocal system included pinhole diameter, laser power, PMT gain and for the widefield system included arc lamp intensity, and camera gain. The signal-to-noise ratio (SNR) and the root-mean-square error (RMS error) were measured to assess system performance. Photobleaching dynamics were studied. Finally, theoretical sensitivity studies were performed to estimate the incremental response (sensitivity) and false-positive detection rates (specificity). Results indicate that hyperspectral imaging assays are highly dependent on system parameters and experimental conditions. For detection of green fluorescent protein (GFP)-expressing cells in fixed lung tissues, a confocal pinhole of five airy disk units, high excitation intensity and low detector gain were optimal. The theoretical sensitivity studies revealed that widefield hyperspectral microscopy was able to detect GFP with fewer false positive occurrences than confocal microscopy, even though confocal microscopy offered improved signal and noise characteristics. These studies provide a framework for optimization that can be applied to a variety of hyperspectral imaging systems. PMID:23877125

  17. Hyperspectral face recognition with spatiospectral information fusion and PLS regression.

    PubMed

    Uzair, Muhammad; Mahmood, Arif; Mian, Ajmal

    2015-03-01

    Hyperspectral imaging offers new opportunities for face recognition via improved discrimination along the spectral dimension. However, it poses new challenges, including low signal-to-noise ratio, interband misalignment, and high data dimensionality. Due to these challenges, the literature on hyperspectral face recognition is not only sparse but is limited to ad hoc dimensionality reduction techniques and lacks comprehensive evaluation. We propose a hyperspectral face recognition algorithm using a spatiospectral covariance for band fusion and partial least square regression for classification. Moreover, we extend 13 existing face recognition techniques, for the first time, to perform hyperspectral face recognition.We formulate hyperspectral face recognition as an image-set classification problem and evaluate the performance of seven state-of-the-art image-set classification techniques. We also test six state-of-the-art grayscale and RGB (color) face recognition algorithms after applying fusion techniques on hyperspectral images. Comparison with the 13 extended and five existing hyperspectral face recognition techniques on three standard data sets show that the proposed algorithm outperforms all by a significant margin. Finally, we perform band selection experiments to find the most discriminative bands in the visible and near infrared response spectrum.

  18. Using hyperspectral imaging technology to identify diseased tomato leaves

    NASA Astrophysics Data System (ADS)

    Li, Cuiling; Wang, Xiu; Zhao, Xueguan; Meng, Zhijun; Zou, Wei

    2016-11-01

    In the process of tomato plants growth, due to the effect of plants genetic factors, poor environment factors, or disoperation of parasites, there will generate a series of unusual symptoms on tomato plants from physiology, organization structure and external form, as a result, they cannot grow normally, and further to influence the tomato yield and economic benefits. Hyperspectral image usually has high spectral resolution, not only contains spectral information, but also contains the image information, so this study adopted hyperspectral imaging technology to identify diseased tomato leaves, and developed a simple hyperspectral imaging system, including a halogen lamp light source unit, a hyperspectral image acquisition unit and a data processing unit. Spectrometer detection wavelength ranged from 400nm to 1000nm. After hyperspectral images of tomato leaves being captured, it was needed to calibrate hyperspectral images. This research used spectrum angle matching method and spectral red edge parameters discriminant method respectively to identify diseased tomato leaves. Using spectral red edge parameters discriminant method produced higher recognition accuracy, the accuracy was higher than 90%. Research results have shown that using hyperspectral imaging technology to identify diseased tomato leaves is feasible, and provides the discriminant basis for subsequent disease control of tomato plants.

  19. Evaluation of copyright protection schemes for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Minguillon, Julia; Herrera-Joancomarti, Jordi; Megias, David; Serra-Sagrista, Joan

    2004-02-01

    In this paper we evaluate the performance of several image watermarking schemes applied to hyperspectral imaging. An image watermarking scheme based on JPEG2000 which can be also used to store and manipulate hyperspectral images is also described. Different watermarking schemes are tested in order to determine the suitability of each one for a specific hyperspectral image environment. The impact of classical GIS operations (namely zooming, cropping and compression) on the performance of each watermarking scheme is measured in terms of capacity and robustness. In order to do so, we study several possibilities for watermarking hyperspectral images, as all hyperspectral image bands should be taken into account. We also study the impact of watermarking in image quality, measured as usual by PSNR, but also by the degradation of classification performance. Compression, classification and watermarking are closely related to each other as decisions taken in one subject have a large impact on the others. Our results show that the newcomer JPEG2000 standard is a useful tool for both hyperspectral imaging and copyright protection purposes. The proposed watermarking scheme, which takes advantage of JPEG2000 standard capabilities, can be considered to be robust under the constraints defined by the integration of hyperspectral imaging with geographical information systems. JPEG2000 extensions defined by the standard related to this work are also considered.

  20. Research on hyperspectral dynamic scene and image sequence simulation

    NASA Astrophysics Data System (ADS)

    Sun, Dandan; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei

    2016-10-01

    This paper presents a simulation method of hyper-spectral dynamic scene and image sequence for hyper-spectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyper-spectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyper-spectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyper-spectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyper-spectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyper-spectral images are consistent with the theoretical analysis results.

  1. Research on hyperspectral dynamic scene and image sequence simulation

    NASA Astrophysics Data System (ADS)

    Sun, Dandan; Liu, Fang; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei

    2016-10-01

    This paper presents a simulation method of hyperspectral dynamic scene and image sequence for hyperspectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyperspectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyperspectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyperspectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyperspectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyperspectral images are consistent with the theoretical analysis results.

  2. Compressive and classical hyperspectral systems: a fundamental comparison

    NASA Astrophysics Data System (ADS)

    Shay, Adi; August, Isaac Y.; Stern, Adrian

    2015-05-01

    Hyperspectral imagery involves capturing and processing a tremendous amount of data, which sets severe system resource requirements. This has motivated the application of compressive sensing for different spectroscopic and spectroscopic imager systems. Several new compressive hyperspectral architectures have been designed to stretch the common limitations of classical systems. However, the application of the compressive sensing framework involves design of system architectures that differ significantly from the conventional ones. Since compressive sensing differs essentially from conventional sensing, it cannot be implemented for hyperspectral imaging by simply modifying one of the components of a conventional hyperspectral system, rather it requires a complete new design. In this work we present a comparison between four compressive hyperspectral architectures to conventional architectures. The compressive hyperspectral sensing compared are: Coded Aperture Snapshot Spectral Imaging (CASSI), Compressive HS Imaging by Separable Spatial And Spectral Operators (CHISSS), (Liquid-crystal Compressive spectral Imager) LiCSI and (Spectral Single-Pixel) SSP systems. Those methods are compared to conventional spatial/spectral scanning hyperspectral such as pushbroom, whiskbroom and color filter techniques. A fundamental comparison between these architectures is presented in terms of optical system volume and radiometric efficiency.

  3. Adaptation of Industrial Hyperspectral Line Scanner for Archaeological Applications

    NASA Astrophysics Data System (ADS)

    Miljković, V.; Gajski, D.

    2016-06-01

    The spectral characteristic of the visible light reflected from any of archaeological artefact is the result of the interaction of its surface illuminated by incident light. Every particular surface depends on what material it is made of and/or which layers put on it has its spectral signature. Recent archaeometry recognises this information as very valuable data to extend present documentation of artefacts and as a new source for scientific exploration. However, the problem is having an appropriate hyperspectral imaging system available and adopted for applications in archaeology. In this paper, we present the new construction of the hyperspectral imaging system, made of industrial hyperspectral line scanner ImSpector V9 and CCD-sensor PixelView. The hyperspectral line scanner is calibrated geometrically, and hyperspectral data are geocoded and converted to the hyperspectral cube. The system abilities are evaluated for various archaeological artefacts made of different materials. Our experience in applications, visualisations, and interpretations of collected hyperspectral data are explored and presented.

  4. Pattern recognition in hyperspectral persistent imaging

    NASA Astrophysics Data System (ADS)

    Rosario, Dalton; Romano, Joao; Borel, Christoph

    2015-05-01

    We give updates on a persistent imaging experiment dataset, being considered for public release in a foreseeable future, and present additional observations analyzing a subset of the dataset. The experiment is a long-term collaborative effort among the Army Research Laboratory, Army Armament RDEC, and Air Force Institute of Technology that focuses on the collection and exploitation of longwave infrared (LWIR) hyperspectral imagery. We emphasize the inherent challenges associated with using remotely sensed LWIR hyperspectral imagery for material recognition, and show that this data type violates key data assumptions conventionally used in the scientific community to develop detection/ID algorithms, i.e., normality, independence, identical distribution. We treat LWIR hyperspectral imagery as Longitudinal Data and aim at proposing a more realistic framework for material recognition as a function of spectral evolution through time, and discuss limitations. The defining characteristic of a longitudinal study is that objects are measured repeatedly through time and, as a result, data are dependent. This is in contrast to cross-sectional studies in which the outcomes of a specific event are observed by randomly sampling from a large population of relevant objects in which data are assumed independent. Researchers in the remote sensing community generally assume the problem of object recognition to be cross-sectional. But through a longitudinal analysis of a fixed site with multiple material types, we quantify and argue that, as data evolve through a full diurnal cycle, pattern recognition problems are longitudinal in nature and that by applying this knowledge may lead to better algorithms.

  5. Atmospheric Correction Algorithm for Hyperspectral Imagery

    SciTech Connect

    R. J. Pollina

    1999-09-01

    In December 1997, the US Department of Energy (DOE) established a Center of Excellence (Hyperspectral-Multispectral Algorithm Research Center, HyMARC) for promoting the research and development of algorithms to exploit spectral imagery. This center is located at the DOE Remote Sensing Laboratory in Las Vegas, Nevada, and is operated for the DOE by Bechtel Nevada. This paper presents the results to date of a research project begun at the center during 1998 to investigate the correction of hyperspectral data for atmospheric aerosols. Results of a project conducted by the Rochester Institute of Technology to define, implement, and test procedures for absolute calibration and correction of hyperspectral data to absolute units of high spectral resolution imagery will be presented. Hybrid techniques for atmospheric correction using image or spectral scene data coupled through radiative propagation models will be specifically addressed. Results of this effort to analyze HYDICE sensor data will be included. Preliminary results based on studying the performance of standard routines, such as Atmospheric Pre-corrected Differential Absorption and Nonlinear Least Squares Spectral Fit, in retrieving reflectance spectra show overall reflectance retrieval errors of approximately one to two reflectance units in the 0.4- to 2.5-micron-wavelength region (outside of the absorption features). These results are based on HYDICE sensor data collected from the Southern Great Plains Atmospheric Radiation Measurement site during overflights conducted in July of 1997. Results of an upgrade made in the model-based atmospheric correction techniques, which take advantage of updates made to the moderate resolution atmospheric transmittance model (MODTRAN 4.0) software, will also be presented. Data will be shown to demonstrate how the reflectance retrieval in the shorter wavelengths of the blue-green region will be improved because of enhanced modeling of multiple scattering effects.

  6. Combined hyperspatial and hyperspectral imaging spectrometer concept

    NASA Technical Reports Server (NTRS)

    Burke, Ian; Zwick, Harold

    1995-01-01

    There is a user need for increasing spatial and spectral resolution in Earth Observation (EO) optical instrumentation. Higher spectral resolution will be achieved by the introduction of spaceborne imaging spectrometers. Higher spatial resolutions of 1 - 3m will be achieved also, but at the expense of sensor redesign, higher communications bandwidth, high data processing volumes, and therefore, at the risk of time delays due to large volume data-handling bottlenecks. This paper discusses a design concept whereby the hyperspectral properties of a spaceborne imaging spectrometer can be used to increase the image spatial resolution, without such adverse cost impact.

  7. Reconfigurable Hardware for Compressing Hyperspectral Image Data

    NASA Technical Reports Server (NTRS)

    Aranki, Nazeeh; Namkung, Jeffrey; Villapando, Carlos; Kiely, Aaron; Klimesh, Matthew; Xie, Hua

    2010-01-01

    High-speed, low-power, reconfigurable electronic hardware has been developed to implement ICER-3D, an algorithm for compressing hyperspectral-image data. The algorithm and parts thereof have been the topics of several NASA Tech Briefs articles, including Context Modeler for Wavelet Compression of Hyperspectral Images (NPO-43239) and ICER-3D Hyperspectral Image Compression Software (NPO-43238), which appear elsewhere in this issue of NASA Tech Briefs. As described in more detail in those articles, the algorithm includes three main subalgorithms: one for computing wavelet transforms, one for context modeling, and one for entropy encoding. For the purpose of designing the hardware, these subalgorithms are treated as modules to be implemented efficiently in field-programmable gate arrays (FPGAs). The design takes advantage of industry- standard, commercially available FPGAs. The implementation targets the Xilinx Virtex II pro architecture, which has embedded PowerPC processor cores with flexible on-chip bus architecture. It incorporates an efficient parallel and pipelined architecture to compress the three-dimensional image data. The design provides for internal buffering to minimize intensive input/output operations while making efficient use of offchip memory. The design is scalable in that the subalgorithms are implemented as independent hardware modules that can be combined in parallel to increase throughput. The on-chip processor manages the overall operation of the compression system, including execution of the top-level control functions as well as scheduling, initiating, and monitoring processes. The design prototype has been demonstrated to be capable of compressing hyperspectral data at a rate of 4.5 megasamples per second at a conservative clock frequency of 50 MHz, with a potential for substantially greater throughput at a higher clock frequency. The power consumption of the prototype is less than 6.5 W. The reconfigurability (by means of reprogramming) of

  8. Absolute measurement of hyperspectral and angular reflection.

    PubMed

    Hwang, Jisoo

    2014-09-20

    A new instrument for absolute measurement of hyperspectral and angular reflection is presented. The instrument determines absolute values of angular reflection quantities in a wavelength range from 380 to 780 nm with a 3 nm spectral resolution by using a white source and a CCD-based spectroradiometer. Through uncertainty evaluation, the measurement uncertainty is determined as 1.4%-2.9% (k=2) for white diffuse material of Spectralon. The gonioreflectometric determination and an integrating-sphere-based reflection measurement traceable to KRISS spectral reflectance scale are compared by determining hemispherical reflectance, which results in agreement in their uncertainties.

  9. Hyperspectral Image Turbulence Measurements of the Atmosphere

    NASA Technical Reports Server (NTRS)

    Lane, Sarah E.; West, Leanne L.; Gimmestad, Gary G.; Kireev, Stanislav; Smith, William L., Sr.; Burdette, Edward M.; Daniels, Taumi; Cornman, Larry

    2012-01-01

    A Forward Looking Interferometer (FLI) sensor has the potential to be used as a means of detecting aviation hazards in flight. One of these hazards is mountain wave turbulence. The results from a data acquisition activity at the University of Colorado s Mountain Research Station will be presented here. Hyperspectral datacubes from a Telops Hyper-Cam are being studied to determine if evidence of a turbulent event can be identified in the data. These data are then being compared with D&P TurboFT data, which are collected at a much higher time resolution and broader spectrum.

  10. Camouflage target reconnaissance based on hyperspectral imaging technology

    NASA Astrophysics Data System (ADS)

    Hua, Wenshen; Guo, Tong; Liu, Xun

    2015-08-01

    Efficient camouflaged target reconnaissance technology makes great influence on modern warfare. Hyperspectral images can provide large spectral range and high spectral resolution, which are invaluable in discriminating between camouflaged targets and backgrounds. Hyperspectral target detection and classification technology are utilized to achieve single class and multi-class camouflaged targets reconnaissance respectively. Constrained energy minimization (CEM), a widely used algorithm in hyperspectral target detection, is employed to achieve one class camouflage target reconnaissance. Then, support vector machine (SVM), a classification method, is proposed to achieve multi-class camouflage target reconnaissance. Experiments have been conducted to demonstrate the efficiency of the proposed method.

  11. Inline hyperspectral thickness determination of thin films using neural networks

    NASA Astrophysics Data System (ADS)

    Tremmel, Anton J.; Weiss, Roman; Schardt, Michael; Koch, Alexander W.

    2017-04-01

    Combining reflectometry and hyperspectral imaging allows mapping of thin film thickness. Therefore, layer thickness is calculated by comparing a dataset of simulated spectra with the measured data. Utilizing the maximum frame rate of the hyperspectral imager, the pixel wise spectra comparing procedure cannot be performed using a standard computer due to the processing load. In this work, a method using neural networks for calculating layer thickness is presented. By the use of the nonlinear equation as result of a trained neural network, thickness data can be determined with a measurement rate matching the maximum frame rate of the hyperspectral imager.

  12. Determining the dimensionality of hyperspectral imagery for unsupervised band selection

    NASA Astrophysics Data System (ADS)

    Umana-Diaz, Alejandra; Velez-Reyes, Miguel

    2003-09-01

    This paper addresses the problem of estimating the dimension of a hyperspectral image. Spanning and intrinsic dimension concepts are studied as ways to determine the number of degrees of freedom needed to represent a Hyperspectral Image. Algorithms for the estimation of spanning and intrinsic dimension are reviewed and applied to hyperspectral images. Estimators are evaluated and compared using simulated and AVIRIS data. The final objective of this work is to develop an algorithm to determine the number of bands to select in a band subset selection algorithm.

  13. Spatial Mutual Information Based Hyperspectral Band Selection for Classification

    PubMed Central

    2015-01-01

    The amount of information involved in hyperspectral imaging is large. Hyperspectral band selection is a popular method for reducing dimensionality. Several information based measures such as mutual information have been proposed to reduce information redundancy among spectral bands. Unfortunately, mutual information does not take into account the spatial dependency between adjacent pixels in images thus reducing its robustness as a similarity measure. In this paper, we propose a new band selection method based on spatial mutual information. As validation criteria, a supervised classification method using support vector machine (SVM) is used. Experimental results of the classification of hyperspectral datasets show that the proposed method can achieve more accurate results. PMID:25918742

  14. Post-processing for improving hyperspectral anomaly detection accuracy

    NASA Astrophysics Data System (ADS)

    Wu, Jee-Cheng; Jiang, Chi-Ming; Huang, Chen-Liang

    2015-10-01

    Anomaly detection is an important topic in the exploitation of hyperspectral data. Based on the Reed-Xiaoli (RX) detector and a morphology operator, this research proposes a novel technique for improving the accuracy of hyperspectral anomaly detection. Firstly, the RX-based detector is used to process a given input scene. Then, a post-processing scheme using morphology operator is employed to detect those pixels around high-scoring anomaly pixels. Tests were conducted using two real hyperspectral images with ground truth information and the results based on receiver operating characteristic curves, illustrated that the proposed method reduced the false alarm rates of the RXbased detector.

  15. Acceleration of tomographic hyperspectral restoration algorithms

    NASA Astrophysics Data System (ADS)

    Schau, Harvey C.

    2006-05-01

    Hyperspectral imaging spectrometers have proven to be both versatile and powerful instruments with applications in diverse areas such as medical diagnosis, land usage, military target detection, and art forgery. In many applications scanning systems cannot be effectively employed and true "flash" operation is necessary. Multiplex systems have been developed which can gather information in multispectral bands simultaneously, and then produce a datacube after mathematical restoration. Such system enjoy compact size, robust construction, inexpensive costs and zero moving parts at the cost of highly complex mathematical restoration operations. Currently the limiting feature of such tomographic hyperspectral imagers such as the FMDIS [1,2] is the speed of restoration. Due to the large sizes of the restoration kernel, restorations are typically recursive and require many iterations to achieve satisfactory results. Little can be done to make the systems smaller since the size is determined by the number of colors and pixel size of the focal plane arrays (FPA) employed. Thus, techniques must be investigated to speed up the restoration either by reducing the number of iterations or reducing the number of operations within an iteration. It is assumed that little can be done to reduce the number of operations in an iteration since the operations are done in sparse format, we therefore investigate reducing the number of iterations through mathematical accelerations. We assume this acceleration will work to advantage regardless of the mechanism (PC-based or dedicated processor such as a gate array) by which the restoration is implemented.

  16. Hyperspectral Aerosol Optical Depths from TCAP Flights

    SciTech Connect

    Shinozuka, Yohei; Johnson, Roy R.; Flynn, Connor J.; Russell, P. B.; Schmid, Beat; Redemann, Jens; Dunagan, Stephen; Kluzek, Celine D.; Hubbe, John M.; Segal-Rosenheimer, Michal; Livingston, J. M.; Eck, T.; Wagener, Richard; Gregory, L.; Chand, Duli; Berg, Larry K.; Rogers, Ray; Ferrare, R. A.; Hair, John; Hostetler, Chris A.; Burton, S. P.

    2013-11-13

    4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research), the world’s first hyperspectral airborne tracking sunphotometer, acquired aerosol optical depths (AOD) at 1 Hz during all July 2012 flights of the Two Column Aerosol Project (TCAP). Root-mean square differences from AERONET ground-based observations were 0.01 at wavelengths between 500-1020 nm, 0.02 at 380 and 1640 nm and 0.03 at 440 nm in four clear-sky fly-over events, and similar in ground side-by-side comparisons. Changes in the above-aircraft AOD across 3-km-deep spirals were typically consistent with integrals of coincident in situ (on DOE Gulfstream 1 with 4STAR) and lidar (on NASA B200) extinction measurements within 0.01, 0.03, 0.01, 0.02, 0.02, 0.02 at 355, 450, 532, 550, 700, 1064 nm, respectively, despite atmospheric variations and combined measurement uncertainties. Finer vertical differentials of the 4STAR measurements matched the in situ ambient extinction profile within 14% for one homogeneous column. For the AOD observed between 350-1660 nm, excluding strong water vapor and oxygen absorption bands, estimated uncertainties were ~0.01 and dominated by (then) unpredictable throughput changes, up to +/-0.8%, of the fiber optic rotary joint. The favorable intercomparisons herald 4STAR’s spatially-resolved high-frequency hyperspectral products as a reliable tool for climate studies and satellite validation.

  17. [Hyperspectral remote sensing monitoring of grassland degradation].

    PubMed

    Wang, Huan-jiong; Fan, Wen-jie; Cui, Yao-kui; Zhou, Lei; Yan, Bin-yan; Wu, Dai-hui; Xu, Xi-ru

    2010-10-01

    The distributing of China's grassland is abroad and the status of grassland degradation is in serious condition. So achieving real-time and exactly grassland ecological monitoring is significant for the carbon cycle, as well as for climate and on regional economies. With the field measured spectra data as data source, hyperspectral remote sensing monitoring of grassland degradation was researched in the present article. The warm meadow grassland in Hulunbeier was chosen as a study object. Reflectance spectra of leaves and pure canopies of some dominant grassland species such as Leymus chinensis, Stipa krylovii and Artemisia frigid, as well as reflectance spectra of mixed grass community were measured. Using effective spectral feature parametrization methods, the spectral feature of leaves and pure canopies were extracted, so the constructive species and degenerate indicator species can be exactly distinguished. Verification results showed that the accuracy of spectral identification was higher than 95%. Taking it as the foundation, the spectra of mixed grass community were unmixed using linear mixing models, and the proportion of all the components was calculated, and the errors were less than 5%. The research results of this article provided the evidence of hyperspectral remote sensing monitoring of grassland degradation.

  18. Modular hyperspectral imager enables multiple research applications

    NASA Astrophysics Data System (ADS)

    Hô, Nicolas; Prel, Florent; Moreau, Louis; Lavoie, Hugo; Bouffard, François; Dubé, Denis; Thériault, Jean-Marc; Vallières, Christian; Roy, Claude

    2012-09-01

    The MR-i spectroradiometer can support a wide range of applications from its architecture suited to multiple configurations. Its modular 4-port FTIR spectroradiometer architecture allows the simultaneous use of two different detector modules, direct or differential input(s) and multiple telescopes. In a given configuration, MR-i can combine a MWIR focal plane array and a LWIR focal plane array to provide an extended spectral range from the two imaging sensors. The two detector array modules are imaging the same scene allowing synchronized pixel-to-pixel spectral range combination. In another configuration, MR-i can combine two identical focal plane arrays with different attenuation factors and two interleaved integration times per detector array. This configuration generates four sets of hyperspectral data cubes with different dynamic ranges that can be combined to produce a single hyperspectral cube with unmatched dynamic range. This configuration is particularly well suited for high-speed, high-dynamic range characterization of targets such as aircrafts, flares, and explosions. In a third configuration, named iCATSI, the spectroradiometer is used in differential input configuration to provide efficient optical background subtraction. The iCATSI configuration features an MCT detectors array with spectral cutoff near 14 µm. This extended spectral range and high sensitivity allows the detection and identification of a wide range of chemicals.

  19. Regional lithology mapping using airborne hyperspectral data

    NASA Astrophysics Data System (ADS)

    Qin, Kai; Chen, Jianping; Zhao, Yingjun

    2015-04-01

    This paper proposed a new procedure for rock identifiction and mapping using airborne hyperspectral CASI/SASI data (wavelength: 380-2450 nm) for the Nanbaishiling in Liuyuan area, Gansu Province, NW China. Rocks in the study area include granite, diorite, marble, basalt and quartzite. In situ and laboratory reflectance spectra (400 to 2500 nm) show Al-OH absorption of muscovite, kaolinite, and illite in granite, granodiorite and quartz diorite, and Fe-OH, Mg-OH absorptions of biotite and chlorite .The absorption near 2.3µm caused by carbonate is most intense in marble reflectance spectra. Ferric-iron absorption is intense in most of the felsic rocks. CASI/SASI data with approximately 2-m spatial resolution were recorded in 149 narrow bands along a 1.2-km-wide swath. Correction of the data to spectral reflectance was performed by reference to in situ measurements of an extensive, alluvial plain. Five major rock types have been identified by using MNF and analysis of in situ and laboratory spectra. The lithoglogic map presented in this study were verified by field investigation, and was compared with previous lithologic map. The result show a reliable classification of lithology using Airborne Hyperspectral data.

  20. Parallax mitigation for hyperspectral change detection

    NASA Astrophysics Data System (ADS)

    Vongsy, Karmon; Eismann, Michael T.; Mendenhall, Michael J.; Velten, Vincent J.

    2014-06-01

    A pixel-level Generalized Likelihood Ratio Test (GLRT) statistic for hyperspectral change detection is developed to mitigate false change caused by image parallax. Change detection, in general, represents the difficult problem of discriminating significant changes opposed to insignificant changes caused by radiometric calibration, image registration issues, and varying view geometries. We assume that the images have been registered, and each pixel pair provides a measurement from the same spatial region in the scene. Although advanced image registration methods exist that can reduce mis-registration to subpixel levels; residual spatial mis-registration can still be incorrectly detected as significant changes. Similarly, changes in sensor viewing geometry can lead to parallax error in an urban cluttered scene where height structures, such as buildings, appear to move. Our algorithm looks to the inherent relationship between the image views and the theory of stereo vision to perform parallax mitigation leading to a search result in the assumed parallax direction. Mitigation of the parallax-induced false alarms is demonstrated using hyperspectral data in the experimental analysis. The algorithm is examined and compared to the existing chronochrome anomalous change detection algorithm to assess performance.

  1. Image visualization of hyperspectral spectrum for LWIR

    NASA Astrophysics Data System (ADS)

    Chong, Eugene; Jeong, Young-Su; Lee, Jai-Hoon; Park, Dong Jo; Kim, Ju Hyun

    2015-07-01

    The image visualization of a real-time hyperspectral spectrum in the long-wave infrared (LWIR) range of 900-1450 cm-1 by a color-matching function is addressed. It is well known that the absorption spectra of main toxic industrial chemical (TIC) and chemical warfare agent (CWA) clouds are detected in this spectral region. Furthermore, a significant spectral peak due to various background species and unknown targets are also present. However, those are dismissed as noise, resulting in utilization limit. Herein, we applied a color-matching function that uses the information from hyperspectral data, which is emitted from the materials and surfaces of artificial or natural backgrounds in the LWIR region. This information was used to classify and differentiate the background signals from the targeted substances, and the results were visualized as image data without additional visual equipment. The tristimulus value based visualization information can quickly identify the background species and target in real-time detection in LWIR.

  2. Onboard Image Processing System for Hyperspectral Sensor.

    PubMed

    Hihara, Hiroki; Moritani, Kotaro; Inoue, Masao; Hoshi, Yoshihiro; Iwasaki, Akira; Takada, Jun; Inada, Hitomi; Suzuki, Makoto; Seki, Taeko; Ichikawa, Satoshi; Tanii, Jun

    2015-09-25

    Onboard image processing systems for a hyperspectral sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS) sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS), which is a hierarchical predictive coding method with resolution scaling. To improve FELICS's performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the sensor system without adding size, weight, power consumption, and fabrication cost.

  3. Sparse Superpixel Unmixing for Hyperspectral Image Analysis

    NASA Technical Reports Server (NTRS)

    Castano, Rebecca; Thompson, David R.; Gilmore, Martha

    2010-01-01

    Software was developed that automatically detects minerals that are present in each pixel of a hyperspectral image. An algorithm based on sparse spectral unmixing with Bayesian Positive Source Separation is used to produce mineral abundance maps from hyperspectral images. A superpixel segmentation strategy enables efficient unmixing in an interactive session. The algorithm computes statistically likely combinations of constituents based on a set of possible constituent minerals whose abundances are uncertain. A library of source spectra from laboratory experiments or previous remote observations is used. A superpixel segmentation strategy improves analysis time by orders of magnitude, permitting incorporation into an interactive user session (see figure). Mineralogical search strategies can be categorized as supervised or unsupervised. Supervised methods use a detection function, developed on previous data by hand or statistical techniques, to identify one or more specific target signals. Purely unsupervised results are not always physically meaningful, and may ignore subtle or localized mineralogy since they aim to minimize reconstruction error over the entire image. This algorithm offers advantages of both methods, providing meaningful physical interpretations and sensitivity to subtle or unexpected minerals.

  4. Hyperspectral monitoring of chemically sensitive plant sentinels

    NASA Astrophysics Data System (ADS)

    Simmons, Danielle A.; Kerekes, John P.; Raqueno, Nina G.

    2009-08-01

    Automated detection of chemical threats is essential for an early warning of a potential attack. Harnessing plants as bio-sensors allows for distributed sensing without a power supply. Monitoring the bio-sensors requires a specifically tailored hyperspectral system. Tobacco plants have been genetically engineered to de-green when a material of interest (e.g. zinc, TNT) is introduced to their immediate vicinity. The reflectance spectra of the bio-sensors must be accurately characterized during the de-greening process for them to play a role in an effective warning system. Hyperspectral data have been collected under laboratory conditions to determine the key regions in the reflectance spectra associated with the degreening phenomenon. Bio-sensor plants and control (nongenetically engineered) plants were exposed to TNT over the course of two days and their spectra were measured every six hours. Rochester Institute of Technologys Digital Imaging and Remote Sensing Image Generation Model (DIRSIG) was used to simulate detection of de-greened plants in the field. The simulated scene contains a brick school building, sidewalks, trees and the bio-sensors placed at the entrances to the buildings. Trade studies of the bio-sensor monitoring system were also conducted using DIRSIG simulations. System performance was studied as a function of field of view, pixel size, illumination conditions, radiometric noise, spectral waveband dependence and spectral resolution. Preliminary results show that the most significant change in reflectance during the degreening period occurs in the near infrared region.

  5. Hyperspectral Imagery Data for Remote Sensing

    NASA Technical Reports Server (NTRS)

    Garegnani, Jerry; Gualtney, Lawrence

    1999-01-01

    In order for remotely sensed data to be useful in a practical application for agriculture, an information product must be made available to the land management decision maker within 24 to 48 hours of data acquisition. Hyperspectral imagery data is proving useful in differentiation of plant species potentially allowing identification of non-healthy areas and pest infestations within crop fields that may require the farm managers attention. Currently however, extracting the needed site-specific feature information from the vast spectral content of large hyperspectral image files is a labor intensive and time consuming task prohibiting the necessary fast turnaround from raw data to final product. We illustrate the methods, techniques and technologies necessary to produce field-level information products from imagery and other related spatial data that are useful to the farm manager for specific decisions that must be made throughout the growing season. We also propose to demonstrate the cost effectiveness of an integrated system, from acquisition to final product distribution, to utilize imagery for decisions on a working farm in conjunction with a commercial agricultural services company and their crop scouts. The demonstration farm is Chesapeake Farms, a 3000 acre research farm in Chestertown, Maryland on the Eas