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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. Preprocessing of hyperspectral images: a comparative study of destriping algorithms for EO1-hyperion

    NASA Astrophysics Data System (ADS)

    Scheffler, Daniel; Karrasch, Pierre

    2013-10-01

    In this study, data from the EO-1 Hyperion instrument were used. Apart from atmospheric influences or topographic effects, the data represent a good choice in order to show different steps of the preprocessing process targeting sensorinternal sources of errors. These include the diffuse sensor noise, the striping effect, the smile effect, the keystone effect and the spatial misalignments between the detector arrays. For this research paper, the authors focus on the striping effect by comparing and evaluating different algorithms, methods and configurations to correct striping errors. The correction of striping effects becomes necessary due to the imprecise calibration of the detector array. This inaccuracy affects especially the first 12 visual and near infrared bands (VNIR) and also a large number of the bands in the short wave infrared array (SWIR). Altogether six destriping techniques were tested on the basis of a Hyperion dataset covering a test site in Central Europe. For the final evaluation, various analyses across all Hyperion channels were performed. The results show that some correction methods have almost no effect on the striping in the images. Other methods may eliminate the striping, but analyses show that these algorithms also alter pixel values in adjacent areas which originally had not been disturbed by the striping effect.

  4. Destriping of hyperspectral image data: an evaluation of different algorithms using EO-1 Hyperion data

    NASA Astrophysics Data System (ADS)

    Scheffler, Daniel; Karrasch, Pierre

    2014-01-01

    Data from the Earth Observing-1 Hyperion instrument were used. Apart from atmospheric influences or topographic effects, the data represent a good choice in order to show different steps of the preprocessing process targeting sensor-internal sources of errors. These include diffuse sensor noise, striping, smile-effect, keystone effect, and spatial misalignments between the detector arrays. For this research paper, the authors focus on the striping effect by comparing and evaluating different algorithms, methods, and configurations to correct striping errors. The correction of striping effects becomes necessary due to imprecise calibration of the detector array. This inaccuracy affects, especially, the first 12 visual and near-infrared bands and also a large number of bands in the short-wave infrared array. Altogether six destriping techniques were tested on the basis of a Hyperion dataset covering a test site in Central Europe. For the final evaluation, various analyses across all Hyperion channels were performed. The results show that some correction methods have almost no effect on the striping in the images. Other methods may eliminate the striping, but analyses show that these algorithms also alter pixel values in adjacent areas, which originally had not been disturbed by the striping effect. Being the first comprehensive comparison study of different destriping algorithms, this paper gives valuable recommendations on how to reach reliable results in further analyses of hyperspectral data.

  5. 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.

  6. Detection and Assessment of Abiotic Stress of Coniferous Landscapes Caused by Uranium Mining (Using Hyperspectral EO-1/Hyperion Data)

    NASA Astrophysics Data System (ADS)

    Filchev, Lachezar

    2013-12-01

    The paper presents the results from a study aiming at detecting and assessing abiotic stress in coniferous landscapes of Black pine monocultures (Pinus nigra L.) by using ground-based geochemical data, models of technogenic pollution, and satellite hyperspectral data from EO-1/Hyperion. Four vegetation indices (VIs), such as, MCARI, TCARI, MTVI 2, and PRI, as well as the shape and area attributes of the red-edge spectral features, have been studied in order to detect changes caused by the geochemical pollution. The analysis was performed on 4 test sites sized each 30m × 30 m, to correspond to EO-1/Hyperion pixel subspace, in homogenous coniferous landscapes in the Teyna River basin - a left tributary to Iskar River. In effect, the red-edge position index for unstressed coniferous landscapes (Black pine) was found to be at about λ=683 nm, whereas the stressed ones' red-edge position is at λ=671 nm. It was found that VIs, such as TCARI/MCARI and Zc has highest correlation (r2 =0.63; F: 5.20 at F: <0.1), followed by MTVI 2 and Zc (r2 =0.42; F: 2.48 at F: <0.21), and PRI and Zc (r2 =0.30; F: 1.34 at F: <0.33). Subsequently, the four test sites chosen were subdivided in two pairs, corresponding to the modeled Zc values after Inverse Multiquadratic Function (IMF) from the set of Radial Basis Function (RBF), into unstressed (test sites No. 2 and No. 5) and stressed coniferous landscapes (test sites No. 10 and No. 11). The hypothesis tested is that the clustering of EO-1/Hyperion VIs corresponds to Zc clustering using hierarchical clustering method (Ward). As a result, the MTVI 2 and TCARI/MCARI values group their first cluster relatively farther than Zc but the PRI does not reflect the Zc clusters. This lead to the conclusion that the satellite hyperspectral narrowband VIs are still not sensitive enough to study the geochemical background and vegetation stress of geochemically stressed coniferous landscapes by uranium mining without a priori ground based data.

  7. Detection and Assessment of Abiotic Stress of Coniferous Landscapes Caused By Uranium Mining (Using Hyperspectral EO-1/Hyperion Data)

    NASA Astrophysics Data System (ADS)

    Filchev, Lachezar

    2013-12-01

    The paper presents the results from a study aiming at detecting and assessing abiotic stress in coniferous landscapes of Black pine monocultures (Pinus nigra L.) by using ground-based geochemical data, models of technogenic pollution, and satellite hyperspectral data from EO-1/Hyperion. Four vegetation indices (VIs), such as, MCARI, TCARI, MTVI 2, and PRI, as well as the shape and area attributes of the red-edge spectral features, have been studied in order to detect changes caused by the geochemical pollution. The analysis was performed on 4 test sites sized each 30m × 30m, to correspond to EO-1/Hyperion pixel subspace, in homogenous coniferous landscapes in the Teyna River basin – a left tributary to Iskar River. In effect, the red-edge position index for unstressed coniferous landscapes (Black pine) was found to be at about λ=683 nm, whereas the stressed ones' red-edge position is at λ=671 nm. It was found that VIs, such as TCARI/MCARI and Zc has highest correlation (r2=0.63; F: 5.20 at F: <0.1), followed by MTVI 2 and Zc (r2=0.42; F: 2.48 at F: <0.21), and PRI and Zc (r2=0.30; F: 1.34 at F: <0.33). Subsequently, the four test sites chosen were subdivided in two pairs, corresponding to the modeled Zc values after Inverse Multiquadratic Function (IMF) from the set of Radial Basis Function (RBF), into unstressed (test sites No. 2 and No. 5) and stressed coniferous landscapes (test sites No. 10 and No. 11). The hypothesis tested is that the clustering of EO-1/Hyperion VIs corresponds to Zc clustering using hierarchical clustering method (Ward). As a result, the MTVI 2 and TCARI/MCARI values group their first cluster relatively farther than Zc but the PRI does not reflect the Zc clusters. This lead to the conclusion that the satellite hyperspectral narrowband VIs are still not sensitive enough to study the geochemical background and vegetation stress of geochemically stressed coniferous landscapes by uranium mining without a priori ground based data.

  8. 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.

  9. 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.

  10. 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% (

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. ASE Floodwater Classifier Development for EO-1 HYPERION Imagery

    NASA Astrophysics Data System (ADS)

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

    2004-03-01

    The objective of this investigation is to develop a prototype floodwater detection algorithm for Hyperion imagery. It will be run autonomously onboard the EO-1 spacecraft under the Autonomous Sciencecraft Experiment (ASE).

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Multiscale quantification of urban composition from EO-1/Hyperion data using object-based spectral unmixing

    NASA Astrophysics Data System (ADS)

    Zhang, Caiyun

    2016-05-01

    Quantification of the urban composition is important in urban planning and management. Previous research has primarily focused on unmixing medium-spatial resolution multispectral imagery using spectral mixture analysis (SMA) in order to estimate the abundance of urban components. For this study an object-based multiple endmember spectral mixture analysis (MESMA) approach was applied to unmix the 30-m Earth Observing-1 (EO-1)/Hyperion hyperspectral imagery. The abundance of two physical urban components (vegetation and impervious surface) was estimated and mapped at multiple scales and two defined geographic zones. The estimation results were validated by a reference dataset generated from fine spatial resolution aerial photography. The object-based MESMA approach was compared with its corresponding pixel-based one, and EO-1/Hyperion hyperspectral data was compared with the simulated EO-1/Advanced Land Imager (ALI) multispectral data in the unmixing modeling. The pros and cons of the object-based MESMA were evaluated. The result illustrates that the object-based MESMA is promising for unmixing the medium-spatial resolution hyperspectral imagery to quantify the urban composition, and it is an attractive alternative to the traditional pixel-based mixture analysis for various applications.

  3. Forest Species Differentiation and Mapping Using EO-1 Hyperion Imagery

    NASA Astrophysics Data System (ADS)

    Galidaki, G.; Gitas, I.; Katagis, T.

    2012-04-01

    This study addresses the problem of forest species differentiation and mapping using satellite EO-1 Hyperion imagery (30m, 196 bands). The study area is a part of the Greek island of Thassos which is covered with two conifer species, namely Pinus brutia and Pinus nigra. Two techniques were evaluated, namely Spectral Angle Mapper and Support Vector Machines while extensive field work provided reference data for the accuracy assessment of the maps produced by the classifications. Image preprocessing included the Cross Track Illumination Correction to account for the Smile effect, atmospheric correction using the FLAASH model and Lambertian topographic correction. The Minimum Noise Fraction transformation was used to separate the strong component of data noise and reduce data dimensionality. Both classification techniques, gave very promising results; SAM technique resulted in an overall accuracy (OA) of 94.3% and SVM technique yielded OA of 93.2%. This study showed that EO-1 Hyperion imagery can be used to differentiate and map the two main pine species, existing in Thassos.

  4. 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.

  5. 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.

  6. Discrimination of Sedimentary Lithologies Through Unmixing of EO-1 Hyperion Data: Melville Island, Canadian High Arctic

    NASA Astrophysics Data System (ADS)

    Leverington, D. W.

    2008-12-01

    The use of remote-sensing techniques in the discrimination of rock and soil classes in northern regions can help support a diverse range of activities including environmental characterization, mineral exploration, and the study of Quaternary paleoenvironments. Images of low spectral resolution can commonly be used in the mapping of lithological classes possessing distinct spectral characteristics, but hyperspectral databases offer greater potential for discrimination of materials distinguished by more subtle reflectance properties. Orbiting sensors offer an especially flexible and cost-effective means for acquisition of data to workers unable to conduct airborne surveys. In an effort to better constrain the utility of hyperspectral datasets in northern research, this study undertook to investigate the effectiveness of EO-1 Hyperion data in the discrimination and mapping of surface classes at a study area on Melville Island, Nunavut. Bedrock units in the immediate study area consist of late-Paleozoic clastic and carbonate sequences of the Sverdrup Basin. Weathered and frost-shattered felsenmeer, predominantly taking the form of boulder- to pebble-sized clasts that have accumulated in place and that mantle parent bedrock units, is the most common surface material in the study area. Hyperion data were converted from at-sensor radiance to reflectance, and were then linearly unmixed on the basis of end-member spectra measured from field samples. Hyperion unmixing results effectively portray the general fractional cover of six end members, although the fraction images of several materials contain background values that in some areas overestimate surface exposure. The best separated end members include the snow, green vegetation, and red-weathering sandstone classes, whereas the classes most negatively affected by elevated fraction values include the mudstone, limestone, and 'other' sandstone classes. Local overestimates of fractional cover are likely related to the

  7. 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.

  8. 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.

  9. 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.

  10. Spectral stability of the Libya 4 site using EO-1 Hyperion

    NASA Astrophysics Data System (ADS)

    Choi, Taeyoung (Jason); Xiong, Xiaoxiong (Jack); Angal, Amit; Chander, Gyanesh

    2013-06-01

    To assess the on-orbit radiometric stability of imaging sensors, pseudo-invariant calibration sites (PICS) have been utilized and recommended by the Committee on Earth Observation Satellites (CEOS). In the African continent, the Libya 4 test site has been frequently used to detect long-term changes because of its spatial uniformity, temporal stability, and low atmospheric aerosol loading. The nominal location of the Libya 4 test site is centered at the latitude and longitude of +28.55° and +23.99° with a suggested usable area of 75 x 75 km. Previous cross-calibration studies have used subset areas of the test site around the CEOS suggested center coordinate regardless of the spectral characteristic of the site. In this study, yearly hyper-spectral collections from 2004 to 2012 around day of the year 170 were used from Earth Observing One (EO-1) Hyperion sensor over the Libya 4 site. To evaluate the spectral stability over a broad range over the Libya 4 site, a series of Region of Interest (ROI) covering approximate areas of 3 by 3 km were selected in the along track direction from +28.07° to 29.55° of latitude (about 170 km long), which is also a subset of the CEOS reference site. The reflectance variations in other ROIs are initially estimated by average deviation and compared with the spectral angle mapper (SAM) method using ROI number `0' in year 2004 collection as a reference spectrum. To consider a practical application, SAM and average deviation metrics are limited by the wavelength ranges of Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) Relative Spectral Response (RSR), instead of using the entire range of the Hyperion spectrum. These ETM+ RSR's focused SAM values are considered to be the sensor specific spectral stability of the Libya 4 site. The Libya 4 CEOS test site is shown to be a spectrally stable target where SAM angles are less than 1.6 degrees and average deviations are less than 5% reflectance level based on the reference spectrum in

  11. 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

  12. 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).

  13. 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.

  14. Unsupervised multiple endmember spectral mixture analysis-based detection of opium poppy fields from an EO-1 Hyperion image in Helmand, Afghanistan.

    PubMed

    Wang, Jian-Jun; Zhang, Yun; Bussink, Coen

    2014-04-01

    Since 1992, Afghanistan has gradually become the primary illicit opium producer in the entire world. To efficiently eradicate the opium poppy, it is crucial for the United Nations Office on Drugs and Crime (UNODC) and Ministry of Counter Narcotics of Afghanistan to monitor opium poppy cultivation timely. In situ detection of opium fields, however, is often expensive, time-consuming and dangerous in Afghanistan. To overcome the constraints of inaccessibility of opium fields, high-resolution (≤1 m) images, like pan-sharpened IKONOS, have been applied in previous studies. Unfortunately, these high-resolution images are expensive when monitoring a large area. In contrast, EO-1 Hyperion imagery, the only source of spaceborne hyperspectral data, has a coarse resolution (30 m), but it is free of charge. Moreover, Hyperion's large number of channels may increase the detection capability of subpixel size targets. Until now, however, little research has been found that identified opium fields from spaceborne or aerial hyperspectral images. Therefore, this study attempts to detect opium fields from a Hyperion image covering a study area in Southwest Afghanistan in a situation where training samples were not available. A proposed methodology based on unsupervised endmember-selection and multiple-endmember spectral mixture analysis can detect opium fields directly from the Hyperion image. The number of poppy pixels was overestimated by 12%.

  15. 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.

  16. Evaluation of classifiers for processing Hyperion (EO-1) data of tropical vegetation

    NASA Astrophysics Data System (ADS)

    Vyas, Dhaval; Krishnayya, N. S. R.; Manjunath, K. R.; Ray, S. S.; Panigrahy, Sushma

    2011-04-01

    There is an urgent necessity to monitor changes in the natural surface features of earth. Compared to broadband multispectral data, hyperspectral data provides a better option with high spectral resolution. Classification of vegetation with the use of hyperspectral remote sensing generates a classical problem of high dimensional inputs. Complexity gets compounded as we move from airborne hyperspectral to Spaceborne technology. It is unclear how different classification algorithms will perform on a complex scene of tropical forests collected by spaceborne hyperspectral sensor. The present study was carried out to evaluate the performance of three different classifiers (Artificial Neural Network, Spectral Angle Mapper, Support Vector Machine) over highly diverse tropical forest vegetation utilizing hyperspectral (EO-1) data. Appropriate band selection was done by Stepwise Discriminant Analysis. The Stepwise Discriminant Analysis resulted in identifying 22 best bands to discriminate the eight identified tropical vegetation classes. Maximum numbers of bands came from SWIR region. ANN classifier gave highest OAA values of 81% with the help of 22 selected bands from SDA. The image classified with the help SVM showed OAA of 71%, whereas the SAM showed the lowest OAA of 66%. All the three classifiers were also tested to check their efficiency in classifying spectra coming from 165 processed bands. SVM showed highest OAA of 80%. Classified subset images coming from ANN (from 22 bands) and SVM (from 165 bands) are quite similar in showing the distribution of eight vegetation classes. Both the images appeared close to the actual distribution of vegetation seen in the study area. OAA levels obtained in this study by ANN and SVM classifiers identify the suitability of these classifiers for tropical vegetation discrimination.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. Hyperion

    SciTech Connect

    Prowell, Stacy; Sayre, Kirk; Willems, Richard; Pleszkoch, Mark; Lindberg, Steven; Reed, Joel; Testa, Kelly; Lamb, Logan; Heise, David

    2014-09-01

    The Hyperion system was designed to "look inside" an executable program and determine software's function or "behavior" without the use of the software's source code. Hyperion accomplishes this by generating associated program behaviors and the complete set of conditions under which they occur. These behaviors can be automatically checked for known malicious signatures and inspected by domain experts to assure correct operation and the absence of malicious content. Hyperion can also be used to check a program's security properties and to optimize a program.

  9. Hyperion

    2014-09-01

    The Hyperion system was designed to "look inside" an executable program and determine software's function or "behavior" without the use of the software's source code. Hyperion accomplishes this by generating associated program behaviors and the complete set of conditions under which they occur. These behaviors can be automatically checked for known malicious signatures and inspected by domain experts to assure correct operation and the absence of malicious content. Hyperion can also be used to checkmore » a program's security properties and to optimize a program.« less

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. Pulse Tube Cooler For The Hyperion Instrument

    NASA Astrophysics Data System (ADS)

    Chan, C. K.; Clancy, Pamela

    Hyperion is a hyperspectral imaging instrument on NMP EO-1 Spacecraft. The hyperspectral analysis derives from the use of contiguous spectral channels for space surveillance of forestry, minerals and coastal environments. The SWIR-FPA (wavelength spectrum from 0.9 to 2.5 _m) in the Grating Imaging Spectrometer is kept at the temperature of 110K by means of a TRW miniature pulse tube cooler system. The Mechanical Pulse Tube (MPT) cooler which is controlled by a free-standing Cooler Electronics Assembly (CEA) on the Hyperion Instrument Electronics panel, provides a nominal cooling load of 0.835W to the FPA via a cold thermal strap. The nominal operation of the cooler is at 75% stroke consuming 14.7W of electrical power at 300K heat reject temperature. This cooler can operate up to 90% stroke, thus having 92% performance margin for the Hyperion mission. Before the installation and operation on the instrument, both the mechanical and the electronics assemblies underwent the environmental tests of launch vibration, thermal vacuum cycling and burn-in. The cooling load lines, the temperature stability, the self-induced vibrational force, the ripple current and the magnetic radiated emission were measured. CK Hyperion PTC.DOC

  17. 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.

  18. 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

  19. An Exploration of Hyperion Hyperspectral Imagery Combined with Different Supervised Classification Approaches Towards Obtaining More Accurate Land Use/Cover Cartography

    NASA Astrophysics Data System (ADS)

    Igityan, Nune

    2014-05-01

    Land use and land cover (LULC) constitutes a key variable of the Earth's system that has in general shown a close correlation with human activities and the physical environment. Describing the pattern and the spatial distribution of LULC is traditionally based on remote sensing data analysis and, evidently, one of the most commonly techniques applied has been image classification. The main objective of the present study has been to evaluate the combined use of Hyperion hyperspectral imagery with a range of supervised classification algorithms widely available today for discriminating LULC classes in a typical Mediterranean setting. Accuracy assessment of the derived thematic maps was based on the analysis of the classification confusion matrix statistics computed for each classification map, using for consistency the same set of validation points. Those were selected on the basis of photo-interpretation of high resolution aerial imagery and of panchromatic imagery available for the studied region at the time of the Hyperion overpass. Results indicated close classification accuracy between the different classifiers with the SVMs outperforming the other classification approaches. The higher classification accuracy by SVMs was attributed principally to the ability of this classifier to identify an optimal separating hyperplane for classes' separation which allows a low generalisation error, thus producing the best possible classes' separation. Although all classifiers produced close results, SVMs generally appeared most useful in describing the spatial distribution and the cover density of each land cover category. All in all, this study demonstrated that, provided that a Hyperion hyperspectral imagery can be made available at regular time intervals over a given region, when combined with SVMs classifiers, can potentially enable a wider approach in land use/cover mapping. This can be of particular importance, especially for regions like in the Mediterranean basin

  20. 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.

  1. 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.

  2. 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%.

  3. 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.

  4. 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.

  5. Development of Bayesian-based transformation method of Landsat imagery into pseudo-hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Hoang, Nguyen Tien; Koike, Katsuaki

    2015-10-01

    It has been generally accepted that hyperspectral remote sensing is more effective and provides greater accuracy than multispectral remote sensing in many application fields. EO-1 Hyperion, a representative hyperspectral sensor, has much more spectral bands, while Landsat data has much wider image scene and longer continuous space-based record of Earth's land. This study aims to develop a new method, Pseudo-Hyperspectral Image Synthesis Algorithm (PHISA), to transform Landsat imagery into pseudo hyperspectral imagery using the correlation between Landsat and EO-1 Hyperion data. At first Hyperion scene was precisely pre-processed and co-registered to Landsat scene, and both data were corrected for atmospheric effects. Bayesian model averaging method (BMA) was applied to select the best model from a class of several possible models. Subsequently, this best model is utilized to calculate pseudo-hyperspectral data by R programming. Based on the selection results by BMA, we transform Landsat imagery into 155 bands of pseudo-hyperspectral imagery. Most models have multiple R-squared values higher than 90%, which assures high accuracy of the models. There are no significant differences visually between the pseudo- and original data. Most bands have Pearson's coefficients < 0.95, and only a small fraction has the coefficients < 0.93 like outliers in the data sets. In a similar manner, most Root Mean Square Error values are considerably low, smaller than 0.014. These observations strongly support that the proposed PHISA is valid for transforming Landsat data into pseudo-hyperspectral data from the outlook of statistics.

  6. 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.

  7. [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

  8. 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

  9. 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.

  10. 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.

  11. Efficient Spectral Endmember Detection Onboard the EO-1 Spacecraft

    NASA Technical Reports Server (NTRS)

    Bornstein, Ben; Thompson, David R.; Tran, Daniel; Bue, Brian; Chien, Steve; Castano, Rebecca

    2011-01-01

    Spaceflight and planetary exploration place severe constraints on the available bandwidth for downlinking large hyperspectral images. In addition, communications with spacecraft often occur intermittently, so mission-relevant hyperspectral data must wait for analysis on the ground before it can inform spacecraft activity planning. Onboard endmember detection can help alleviate these problems. It enables novelty detection and target identification for scheduling follow-up activities such as additional observation by narrow field of view instruments. Additionally, endmember analysis can facilitate data summary for downlink. This work describes a planned experiment of selective downlink by the EO-1 autonomous spacecraft. Here an efficient superpixel endmember detection algorithm keeps to the limited computational constraints of the flight processor. Tests suggest the procedure could enable significant improvements in downlink efficiency.

  12. Revolutionising Science-Driven Deep Space Mission Operations Using Autonomously-Operating Spacecraft as Demonstrated with ASE on EO-1.

    NASA Astrophysics Data System (ADS)

    Davies, A. G.; Chien, S.; Doggett, T. C.; Ip, F.; Dohm, J.; Greeley, R.; Baker, V.; Castano, R.; Sherwood, R.; Wagstaff, K.

    2005-12-01

    Until now, deep-space missions, separated from Earth by long communication times, have not had the capacity to quickly react to dynamic, ephemeral events that are of high science value. The capability of a spacecraft to react on a short time scale to such events is now a reality. The New Millennium Program Autonomous Sciencecraft Experiment (ASE) has successfully demonstrated autonomous, science-driven spacecraft operations. This flight-proven technology consists of (1) data classifiers, used to detect features of scientific interest; (2) an onboard planner than allocates available resources and creates observation sequences; and (3) a spacecraft command language that operates the spacecraft and instruments. ASE is flying on the Earth Observing 1 (EO-1) spacecraft in Earth orbit and autonomously detects active cloud cover, volcanism, changes in the cryosphere and flood events. Data are processed on-board EO-1. The spacecraft and Hyperion hyperspectral imager are then re-tasked to obtain further observations of the target. So far, this process has been executed over 300 times on-board EO-1. Additionally, in the special case of active volcanism, a data subset containing spectra of hot pixels is extracted and preferentially returned. This technology can enhance science return per returned byte by orders of magnitude. ASE technology is being infused onto Mars Odyssey to process THEMIS thermal imager data, with the goal of autonomously detecting thermal anomalies (hot spots), dust storms, and tracking the advance and retreat of seasonal ice caps. ASE allows THEMIS to collect a large volume of additional data, more than can be transmitted due to bandwidth constraints, and quickly analyze it to determine which images are of the highest priority (such as an image containing a thermal anomaly) or to transmit only the essential information, such as the location of a detection (such as the edge of the polar cap). Spacecraft autonomy is a requirement on certain deep

  13. 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

  14. 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

  15. 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.

  16. 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

  17. 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).

  18. Mapping intertidal surface sediment type distribution with retrieved sedimental components using EO-1 Hyperion data

    NASA Astrophysics Data System (ADS)

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

    2010-11-01

    Sediment type was one of the most important parameters of intertidal zone. The hydrodynamics and morphological changes could be indicated by sediment types very well, and the understanding of their distribution and stability could provide an important insight into littoral marine ecology. The way of conventional survey for sediment types was expensive and time-consuming. The objective of this study was to develop a method to distinguish sediment types using remote sensing, and enable which to be an alternative to traditional methods. Intertidal zone sediments were sampled at the south of Dafeng port, Yancheng city, Jiangsu province, China. Samples were collected from the upper 3cm surface of intertidal zone. The laboratory spectral reflectance data were obtained using a spectrometer. Particle-size of sediment samples were measured by Mastersizer 2000. Through analyzing characteristics of spectral reflectance for sediment samples, we found that two bands were sensitive to content of sediment components (sand, silt and clay) with central wavelengths at 864 and 1034 nm. However, the position of sensitive bands changed as moisture varied. In order to eliminate the impact of moisture on sediment spectral reflectance, moisture was introduced as a crucial factor to build regression equations with reflectance of sensitive bands to get contents of different sediment components, and then Shepard classification system was applied to acquire spatial distribution of sediment types. This way provided a quick, non-destructive and nonpolluting survey method. Meanwhile, this intelligent way of extracting information from muddy coastal zone will contribute to constructing digital earth, the huge system which benefits human beings.

  19. Mapping intertidal surface sediment type distribution with retrieved sedimental components using EO-1 Hyperion data

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

    Sediment type was one of the most important parameters of intertidal zone. The hydrodynamics and morphological changes could be indicated by sediment types very well, and the understanding of their distribution and stability could provide an important insight into littoral marine ecology. The way of conventional survey for sediment types was expensive and time-consuming. The objective of this study was to develop a method to distinguish sediment types using remote sensing, and enable which to be an alternative to traditional methods. Intertidal zone sediments were sampled at the south of Dafeng port, Yancheng city, Jiangsu province, China. Samples were collected from the upper 3cm surface of intertidal zone. The laboratory spectral reflectance data were obtained using a spectrometer. Particle-size of sediment samples were measured by Mastersizer 2000. Through analyzing characteristics of spectral reflectance for sediment samples, we found that two bands were sensitive to content of sediment components (sand, silt and clay) with central wavelengths at 864 and 1034 nm. However, the position of sensitive bands changed as moisture varied. In order to eliminate the impact of moisture on sediment spectral reflectance, moisture was introduced as a crucial factor to build regression equations with reflectance of sensitive bands to get contents of different sediment components, and then Shepard classification system was applied to acquire spatial distribution of sediment types. This way provided a quick, non-destructive and nonpolluting survey method. Meanwhile, this intelligent way of extracting information from muddy coastal zone will contribute to constructing digital earth, the huge system which benefits human beings.

  20. 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.

  1. 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).

  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. 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. PMID:22399961

  5. 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

  6. 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.

  7. 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.

  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. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Advancing Glaciological Applications of Remote Sensing with EO-1: (1) Mapping Snow Grain Size and Albedo on the Greenland Ice Sheet Using an Imaging Spectrometer, and (2) ALI Evaluation for Subtle Surface Topographic Mapping via Shape-from Shading

    NASA Technical Reports Server (NTRS)

    2003-01-01

    The Hyperion sensor, onboard NASA's Earth Observing-1 (EO-1) satellite,is an imaging spectroradiometer with 220 spectral bands over the spectral range from 0.4 - 2.5 microns. Over the course of summer 2001, the instrument acquired numerous images over the Greenland ice sheet. Our main motivation is to develop an accurate and robust approach for measuring the broadband albedo of snow from satellites. Satellite-derived estimates of broadband have typically been plagued with three problems: errors resulting from inaccurate atmospheric correction, particularly in the visible wavelengths from the conversion of reflectance to albedo (accounting for snow BRDE); and errors resulting from regression-based approaches used to convert narrowband albedo to broadband albedo. A typerspectral method has been developed that substantially reduces these three main sources of error and produces highly accurate estimates of snow albedo. This technique uses hyperspectral data from 0.98 - 1.06 microns, spanning a spectral absorption feature centered at 1.03 microns. A key aspect of this work is that this spectral range is within an atmospheric transmission window and reflectances are largely unaffected by atmospheric aerosols, water vapor, or ozone. In this investigation, we make broadband albedo measurements at four sites on the Greenland ice sheet: Summit, a high altitude station in central Greenland; the ETH/CU camp, a camp on the equilibrium line in western Greenland; Crawford Point, a site located between Summit and the ETH/CU camp; and Tunu, a site located in northeastern Greenland at 2000 m. altitude. Each of these sites has an automated weather station (AWS) that continually measures broadband albedo thereby providing validation data.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  1. 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.

  2. 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. PMID:25674434

  3. Using multispectral and hyperspectral satellite data for early detection of mountain pine beetle damage

    NASA Astrophysics Data System (ADS)

    Sharma, Rajeev

    Mountain pine beetle [MPB] (Dendroctonous ponderosae Hopk.) is the most serious pest of mature lodgepole pine ( Pinus contorta) in western North America. Three key research issues important in developing satellite-based methods for early MPB damage detection and mapping are examined in this thesis. Relevant questions relating to these issues are: (i) is it possible to provide information on MPB-attacked stands using satellite imagery at an earlier date than conventional methods; (ii) is spectral variability in mature lodgepole pine stands significant enough to warrant consideration in MPB attack detection at a landscape level; and (iii) are satellite-based hyperspectral bands useful in forest tree species discrimination and early detection of MPB-attacked stands. The first two questions were investigated using multispectral Landsat-7 ETM+ data; the third question was investigated using EO-1 Hyperion hyperspectral data. Using a multi-step deductive approach, MPB-attacked stands were identified with an accuracy of 69% using the Landsat imagery, approximately four months earlier than would be possible with conventional surveys. Significant spectral variability was found in mature stands of lodgepole pine, Douglas-fir ( Pseudotsuga menziesii) and spruce (Picea spp.) at the landscape level. Among the three variables examined (stand age, site index and site ecology), site ecology (BEC subzone/variants) had the largest influence on the spectral signatures of the three species. Douglas-fir, lodgepole pine and spruce could be identified with an identification accuracy of 81.8%, 82.1% and 78.9%, respectively, using a subset of nine narrow bands from the Hyperion sensor, mainly distributed in the 1500--1800 nm spectral region. Corresponding accuracies using Landsat data were 66.1%, 74.3% and 67.6%. Another set of nine spectral bands, optimized to identify MPB attack and distributed mainly in the 900--1100 nm spectral region, resulted in identification accuracies of 81.7% and

  4. Striping noise mitigation: performance evaluation on real and simulated hyperspectral images

    NASA Astrophysics Data System (ADS)

    Lastri, Cinzia; Guzzi, Donatella; Barducci, Alessandro; Pippi, Ivan; Nardino, Vanni; Raimondi, Valentina

    2015-10-01

    Striping noise is a phenomenon intrinsic to the process of image acquisition by means of scanning or pushbroom systems, caused by a poor radiometric calibration of the sensor. Although in-flight calibration has been performed, residual spatially and spectrally coherent noise may perturb the quantitative analysis of images and the extraction of physical parameters. Destriping methods can be classified in three main groups: statistical-based methods, digital-filtering methods and radiometric-equalisation methods. Their performances depend both on the scene under investigation and on the type and intensity of noise to be treated. Availability of simulated data at each step of the digital image formation process, including that one before the introduction of the striping effect, is particularly useful since it offers the opportunity to test and adjust a variety of image processing and calibration algorithms. This paper presents the performance of a statistical-based destriping method applied to a set of simulated and to images acquired by the EO-1 Hyperion hyperspectral sensor. The set of simulated data with different intensities of coherent and random noise was generated using an image simulator implemented for the PRISMA mission. Algorithm's performance was tested by evaluating most commonly used quality indexes. For the same purpose, a statistical evaluation based on image correlation and image differences between the corrected and ideal images was carried out. Results of the statistical analysis were compared with the outcome of the quality indexes-based analysis.

  5. 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.

  6. 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.

  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. 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.

  9. Follow That Satellite: EO-1 Maneuvers into Closed Formation With Landsat-7

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

    As the Landsat-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 Landsat-7 instruments. The validation method for these instruments was to have EO-1 fly in a close formation behind Landsat-7 on the same World Reference System 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 Landsat-7 where instrument validation was to occur plus a summary of completing the formation acquisition. EO-1 is required to operate one minute +/- 6 seconds behind Landsat-7 during the period of co-fly imaging with a cross track separation of within + 3 kilometers. This separation time can also be stated as a one minute +/- 6 seconds time difference in the Mean Local Time (MLT) at the descending nodes. Achieving the required MLT is heavily dependent on the time of launch. The EO-1 launch window, which had to accommodate the dual payloads of EO-1 and SAC-C, was very limited ranging from 0 to 22 seconds over the 16 day Landsat-7 WRS repeat cycle during which EO-1 was launched. Each EO-1 launch opportunity that occurred on a different day of a Landsat-7 16 day repeat cycle required a separate and distinct maneuver profile. These profiles varied significantly in duration and amount of onboard propellant required to achieve them. EO-1 launched on a day judged to have "medium" resource requirements for achieving the formation with Landsat-7. To phase EO-1 one minute behind Landsat-7 in the along track direction, a series of altitude adjusts separated by specific drift intervals were executed. Additional maneuvers slightly changed the EO-1 inclination to maintain the MLT requirements. Orbit maneuvers were planned and executed within errors of less

  10. 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.

  11. 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

  12. 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.

  13. Assessment of the spectral stability of Libya 4, Libya 1, and Mauritania 2 sites using Earth Observing One Hyperion

    NASA Astrophysics Data System (ADS)

    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 1σ 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 5. VICTORY MEMORIAL, SOUT SIDE OF HYPERION BOULEVARD VIADUCT LOCATED ...

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

    5. VICTORY MEMORIAL, SOUT SIDE OF HYPERION BOULEVARD VIADUCT LOCATED IN MIDDLE OF VIADUCT BETWEEN LOS ANGELES RIVER CROSSING AND INTERSTATE I-5 CROSSING. LOOKING NORTHWEST. SEE PHOTO CA-275-3 FOR CONTEXTUAL VIEW. - Glendale-Hyperion Viaduct, Spanning Golden State Freeway (I-5) & Los Angeles River at Glendale Boulevard, Los Angeles, Los Angeles County, CA

  2. 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

  3. 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).

  4. 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.

  5. On-orbit characterization of hyperspectral imagers

    NASA Astrophysics Data System (ADS)

    McCorkel, Joel

    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 tests sites are not always successful due to weather and funding availability. Therefore, RSG has also employed 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 dissertation presents a method for determining the radiometric calibration of a hyperspectral imager using multispectral imagery. The work relies on a multispectral sensor, Moderate-resolution Imaging Spectroradiometer (MODIS), 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. A method to predict hyperspectral surface reflectance using a combination of MODIS data and spectral shape information is developed and applied for the characterization of Hyperion. Spectral shape information is based on RSG's historical in situ data for the Railroad Valley test site and spectral library data for the Libyan test site. Average atmospheric parameters, also based on historical measurements, are used in reflectance prediction and transfer to space. Results of several cross-calibration scenarios that differ in image acquisition coincidence, test site, and reference sensor are found for the characterization of Hyperion. These are compared with results from the reflectance-based approach of vicarious calibration, a well-documented method developed by the RSG that serves as a baseline for calibration performance for the cross-calibration method developed here. Cross-calibration provides results that are within 2% of those of reflectance-based results in most spectral regions. Larger disagreements exist

  6. 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

  7. Detection and correction of spectral and spatial misregistrations for hyperspectral data using phase correlation method.

    PubMed

    Yokoya, Naoto; Miyamura, Norihide; Iwasaki, Akira

    2010-08-20

    Hyperspectral imaging sensors suffer from spectral and spatial misregistrations due to optical-system aberrations and misalignments. These artifacts distort spectral signatures that are specific to target objects and thus reduce classification accuracy. The main objective of this work is to detect and correct spectral and spatial misregistrations of hyperspectral images. The Hyperion visible near-infrared subsystem is used as an example. An image registration method based on phase correlation demonstrates the accurate detection of the spectral and spatial misregistrations. Cubic spline interpolation using estimated properties makes it possible to modify the spectral signatures. The accuracy of the proposed postlaunch estimation of the Hyperion characteristics is comparable to that of the prelaunch measurements, which enables the accurate onboard calibration of hyperspectral sensors. PMID:20733628

  8. Detection and correction of spectral and spatial misregistrations for hyperspectral data using phase correlation method.

    PubMed

    Yokoya, Naoto; Miyamura, Norihide; Iwasaki, Akira

    2010-08-20

    Hyperspectral imaging sensors suffer from spectral and spatial misregistrations due to optical-system aberrations and misalignments. These artifacts distort spectral signatures that are specific to target objects and thus reduce classification accuracy. The main objective of this work is to detect and correct spectral and spatial misregistrations of hyperspectral images. The Hyperion visible near-infrared subsystem is used as an example. An image registration method based on phase correlation demonstrates the accurate detection of the spectral and spatial misregistrations. Cubic spline interpolation using estimated properties makes it possible to modify the spectral signatures. The accuracy of the proposed postlaunch estimation of the Hyperion characteristics is comparable to that of the prelaunch measurements, which enables the accurate onboard calibration of hyperspectral sensors.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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%.

  19. 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.

  20. A synthetic theory for the perturbations of Titan on Hyperion

    NASA Astrophysics Data System (ADS)

    Taylor, D. B.

    1992-11-01

    A theory for Hyperion is developed in which the perturbations by Titan have been developed synthetically. These perturbations were derived by fitting a sum of periodic terms to the numerical integration of Sinclair and Taylor (1985) extended to +/- 25 yr from the epoch used, 1973.87. A theory for Hyperion, constructed by adding the solar perturbations to the synthetic theory and including expressions for the motion of the orbit plane, was, together with the theories for the other major satellites of Saturn fitted to observations from 1967 to 1983.

  1. 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.

  2. Pulse tube cooler for flight hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Chan, C. K.; Clancy, Pamela; Godden, John

    A new version of TRW's miniature pulse tube cooler system maintains the short wave infrared-focal plane array (SWIR-FPA) (with wavelength spectrum of 0.9-2.5 μm in the hyperspectral imaging spectrometer for the Hyperion Instrument) interface at a temperature of 110 K. The cooler provides the nominally required cooling load of 0.84W to the FPA via a cold thermal strap, at 72% stroke consuming 14.7 W of electrical power, when the heat reject temperature is at 300 K. This cooler can operate up to 90% stroke, having 1.5 W cooling load, thus having 79% performance margin for the Hyperion mission. Before the installation and operation of the cooler onto the instrument, both the mechanical and the electronics assemblies underwent the environmental tests of launch vibration, thermal vacuum cycling, and burn-in. The cooler performance in terms of mechanical efficiency, electronics efficiency, load lines, temperature stability, self-induced vibrational force reduction, ripple current reduction, and magnetic radiated emission was measured and are reported here.

  3. 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.

  4. 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%.

  5. Radiometric calibration stability of the EO-1 Advanced Land Imager: 5 years on-orbit

    NASA Astrophysics Data System (ADS)

    Markham, Brian L.; Ong, Lawrence; Barsi, Julia A.; Mendenhall, Jeffrey A.; Lencioni, Donald E.; Helder, Dennis L.; Hollaren, Douglas M.; Morfitt, Ron

    2006-09-01

    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 ALI'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%.

  6. Possibility of Using a Hyperion Power Module in Mongolia

    NASA Astrophysics Data System (ADS)

    Sambuu, Odmaa; Nanzad, Norov

    2011-06-01

    A Hyperion power module is the compact, inherent safety, self-regulating and its all mechanical components are not movable. Unlike conventional nuclear designs, it has uranium hydride fuel which serves as a combination fuel and moderator. The mobility of the hydrogen contained in the hydride fuel depends on the temperature. If the core temperature increases over the set point, the hydrogen is driven out of the core, the moderation drops and the power production decreases. If the temperature drops, the hydrogen returns and the process is reversed. The design requires only minimal human oversight. The compact nature and inherent safety opens the possibility for low-cost mass production and operation of the reactors [1,2]. In the paper, we will discuss about the possibility of using the Hyperion power module in Mongolia.

  7. 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).

  8. 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.

  9. 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

  10. [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. PMID:20101973

  11. 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.

  12. 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.

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

    NASA Astrophysics Data System (ADS)

    Cruikshank, D. P.; Dalle Ore, C. M.; Pendleton, Y. J.; Clark, R. N.

    2012-12-01

    We present a quantitative analysis of the hydrocarbon spectral bands measured on three of Saturn's satellites, Phoebe, Iapetus, and Hyperion. These bands, measured with the Cassini Visible-Infrared Mapping Spectrometer on close fly-bys of these satellites, are the C-H stretching modes of aromatic hydrocarbons at ~3.28 μm (~3050 cm-1), and the are four blended bands of aliphatic -CH2- and -CH3 in the range ~3.36-3.52 μm (~2980-2840 cm-1). In these data, the aromatic band, probably indicating the presence of polycyclic aromatic hydrocarbons (PAH), is unusually strong in comparison to the aliphatic bands, resulting in a unique signature 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 ~24; for Hyperion the value is ~12, while Iapetus 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 ~2.2 in the spectrum of low-albedo material on Iapetus; 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.

  14. 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.

  15. Hyperspectral image processing methods

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. Nonlinear time-series analysis of Hyperion's lightcurves

    NASA Astrophysics Data System (ADS)

    Tarnopolski, M.

    2015-06-01

    Hyperion is a satellite of Saturn that was predicted to remain in a chaotic rotational state. This was confirmed to some extent by Voyager 2 and Cassini series of images and some ground-based photometric observations. The aim of this article is to explore conditions for potential observations to meet in order to estimate a maximal Lyapunov Exponent (mLE), which being positive is an indicator of chaos and allows to characterise it quantitatively. Lightcurves existing in literature as well as numerical simulations are examined using standard tools of theory of chaos. It is found that existing datasets are too short and undersampled to detect a positive mLE, although its presence is not rejected. Analysis of simulated lightcurves leads to an assertion that observations from one site should be performed over a year-long period to detect a positive mLE, if present, in a reliable way. Another approach would be to use 2-3 telescopes spread over the world to have observations distributed more uniformly. This may be achieved without disrupting other observational projects being conducted. The necessity of time-series to be stationary is highly stressed.

  3. Multipurpose hyperspectral imaging system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  4. Requirements on optical sensors for quantitative definition of surface parameters multispectral - hyperspectral

    NASA Astrophysics Data System (ADS)

    Bodechtel, Johann

    2001-01-01

    New sensors allow a significant progress in remote sensing from qualitative interpretation of data to quantitative assessment and characterisation of the status of surface targets and phenomena. Gathered knowledge of band positioning, bandwidth and number of spectral bands in optical remote sensing allowed to improve the physical characteristics of existing and future sensors: SPOT 4/5, MOMS 02/2P, IRS-1C, LANDSAT 7, hyperspectral sensors on EO-1 HRST and HYMAP/ARIES etc. Improvements in radiometric sensor calibration, atmospheric corrections and digital evaluation methodology widen the possibilities for quantitative analysis of the data for different applications.

  5. [An algorithm of spectral minimum shannon entropy on extracting endmember of hyperspectral image].

    PubMed

    Yang, Ke-ming; Liu, Shi-wen; Wang, Lin-wei; Yang, Jie; Sun, Yang-yang; He, Dan-dan

    2014-08-01

    It's significant to study the algorithm of endmember extraction, which is the key for pixel unmixing,in the fields of feature identification, abundance inversion, quantitative remote sensing and so on. Based on the theory of shannon entropy and Gaussian distribution function, a new algorithm, named spectral minimum shannon entropy (SMSE) method for extracting end-members of hyperspectral images, is proposed in the present paper after analyzing the characteristics of spectra of the hyperspectral images. This algorithm was applied to extract the endmembers of an AVRIRS hyperspectral image, it was found that these extracted endmember spectra have higher precision by matching with the spectral library of United States Geological Survey (USGS). At the same time, it was also found that the SMSE algorithm has better efficiency and accuracy for extracting endmember spectra through comparing and analyzing comprehensively the results of endmember extraction of the experimental data by using the methods of SMSE, pixel purity index (PPI), sequential maximum angle convex cone (SMACC) and so on. In addition, the SMACC and SMSE are used to extract the endmembers in a Hyperion hyperspectral image, and it is concluded that the results of the SMSE is better than the SMACC's. Thus, the SMSE algorithm can be thought to have a certain degree of universal applicability.

  6. A hyperspectral image projector for hyperspectral imagers

    NASA Astrophysics Data System (ADS)

    Rice, Joseph P.; Brown, Steven W.; Neira, Jorge E.; Bousquet, Robert R.

    2007-04-01

    We have developed and demonstrated a Hyperspectral Image Projector (HIP) intended for system-level validation testing of hyperspectral imagers, including the instrument and any associated spectral unmixing algorithms. HIP, based on the same digital micromirror arrays used in commercial digital light processing (DLP*) displays, is capable of projecting any combination of many different arbitrarily programmable basis spectra into each image pixel at up to video frame rates. We use a scheme whereby one micromirror array is used to produce light having the spectra of endmembers (i.e. vegetation, water, minerals, etc.), and a second micromirror array, optically in series with the first, projects any combination of these arbitrarily-programmable spectra into the pixels of a 1024 x 768 element spatial image, thereby producing temporally-integrated images having spectrally mixed pixels. HIP goes beyond conventional DLP projectors in that each spatial pixel can have an arbitrary spectrum, not just arbitrary color. As such, the resulting spectral and spatial content of the projected image can simulate realistic scenes that a hyperspectral imager will measure during its use. Also, the spectral radiance of the projected scenes can be measured with a calibrated spectroradiometer, such that the spectral radiance projected into each pixel of the hyperspectral imager can be accurately known. Use of such projected scenes in a controlled laboratory setting would alleviate expensive field testing of instruments, allow better separation of environmental effects from instrument effects, and enable system-level performance testing and validation of hyperspectral imagers as used with analysis algorithms. For example, known mixtures of relevant endmember spectra could be projected into arbitrary spatial pixels in a hyperspectral imager, enabling tests of how well a full system, consisting of the instrument + calibration + analysis algorithm, performs in unmixing (i.e. de-convolving) the

  7. 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.

  8. Detection of Amazonian Black Earth Sites using Hyperspectral Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Braswell, B. H.; Palace, M.; Bush, M. B.; Neves, E.; Mcmichael, C.; Czarnecki, C.; Moraes, B.; Raczka, M.

    2012-12-01

    The pre-Columbian indigenous population estimates of the Amazon Basin lowlands are highly uncertain and the subject of considerable controversy. One of the archaeological sources used in reconstruction of Amazonian societies are Amazonian black earths (ABE) or terra preta soils. The immense size of Amazonia, remoteness of many areas, forest vegetation, and lack of archaeological field surveys, make remote sensing beneficial to archaeological studies in this region. Remote sensing allows for comparison and analysis of vegetation across vast areas. Previous research has shown that hyperspectral image data can detect vegetation canopy chemistry differences, associated with soil nutrients and chemistry anomalies at ABE locations. We conducted a preliminary analysis that indicates nine portions of the spectrum where three ABE sites are completely separable from the three non-ABE sites. A discriminant function analysis using stepwise variable selection indicated that five bands were adequate in distinguishing between ABE and non-ABE sites. These five bands ranged between the 2000-2400 nm, indicating that canopy moisture is useful in remotely sensing terra preta. The wealth of site locations we are compiling from numerous sources provides a unique opportunity to develop algorithms for the classification of ABE and non-ABE sites. Our current data holdings include over 1600 Hyperion images and a database of ABE/ non-ABE field observations at approximately 2900 sites. The distribution and number of ABE sites provides information useful for both archaeological research and has consequences for the interpretation of Amazonian forest ecology. Knowledge of the disturbance history of the Amazonian forest provides a context and framework for the placement of all environmental research in the region. This presentation reports results of statistical modeling using extracted spectra from about 400 sites that are within Hyperion scenes.

  9. Hyperspectral light field imaging

    NASA Astrophysics Data System (ADS)

    Leitner, Raimund; Kenda, Andreas; Tortschanoff, Andreas

    2015-05-01

    A light field camera acquires the intensity and direction of rays from a scene providing a 4D representation L(x,y,u,v) called the light field. The acquired light field allows to virtually change view point and selectively re-focus regions algorithmically, an important feature for many applications in imaging and microscopy. The combination with hyperspectral imaging provides the additional advantage that small objects (beads, cells, nuclei) can be categorised using their spectroscopic signatures. Using an inverse fluorescence microscope, a LCTF tuneable filter and a light field setup as a test-bed, fluorescence-marked beads have been imaged and reconstructed into a 4D hyper-spectral image cube LHSI(x,y,z,λ). The results demonstrate the advantages of the approach for fluorescence microscopy providing extended depth of focus (DoF) and the fidelity of hyper-spectral imaging.

  10. 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.

  11. Miniaturized handheld hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Wu, Huawen; Haibach, Frederick G.; Bergles, Eric; Qian, Jack; Zhang, Charlie; Yang, William

    2014-05-01

    A miniaturized hyperspectral 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 hyperspectral 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Hyperspectral holographic Fourier-microscopy

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    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.

  18. 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.

  19. 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.

  20. Hyperspectral confocal microscope.

    PubMed

    Sinclair, Michael B; Haaland, David M; Timlin, Jerilyn A; Jones, Howland D T

    2006-08-20

    We have developed a new, high performance, hyperspectral microscope for biological and other applications. For each voxel within a three-dimensional specimen, the microscope simultaneously records the emission spectrum from 500 nm to 800 nm, with better than 3 nm spectral resolution. The microscope features a fully confocal design to ensure high spatial resolution and high quality optical sectioning. Optical throughput and detection efficiency are maximized through the use of a custom prism spectrometer and a backside thinned electron multiplying charge coupled device (EMCCD) array. A custom readout mode and synchronization scheme enable 512-point spectra to be recorded at a rate of 8300 spectra per second. In addition, the EMCCD readout mode eliminates curvature and keystone artifacts that often plague spectral imaging systems. The architecture of the new microscope is described in detail, and hyperspectral images from several specimens are presented.

  1. 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.

  2. Snapshot Hyperspectral Volumetric Microscopy.

    PubMed

    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

  3. Hyperspectral confocal microscope

    NASA Astrophysics Data System (ADS)

    Sinclair, Michael B.; Haaland, David M.; Timlin, Jerilyn A.; Jones, Howland D. T.

    2006-08-01

    We have developed a new, high performance, hyperspectral microscope for biological and other applications. For each voxel within a three-dimensional specimen, the microscope simultaneously records the emission spectrum from 500 nm to 800 nm, with better than 3 nm spectral resolution. The microscope features a fully confocal design to ensure high spatial resolution and high quality optical sectioning. Optical throughput and detection efficiency are maximized through the use of a custom prism spectrometer and a backside thinned electron multiplying charge coupled device (EMCCD) array. A custom readout mode and synchronization scheme enable 512-point spectra to be recorded at a rate of 8300 spectra per second. In addition, the EMCCD readout mode eliminates curvature and keystone artifacts that often plague spectral imaging systems. The architecture of the new microscope is described in detail, and hyperspectral images from several specimens are presented.

  4. Hyperspectral confocal microscope.

    PubMed

    Sinclair, Michael B; Haaland, David M; Timlin, Jerilyn A; Jones, Howland D T

    2006-08-20

    We have developed a new, high performance, hyperspectral microscope for biological and other applications. For each voxel within a three-dimensional specimen, the microscope simultaneously records the emission spectrum from 500 nm to 800 nm, with better than 3 nm spectral resolution. The microscope features a fully confocal design to ensure high spatial resolution and high quality optical sectioning. Optical throughput and detection efficiency are maximized through the use of a custom prism spectrometer and a backside thinned electron multiplying charge coupled device (EMCCD) array. A custom readout mode and synchronization scheme enable 512-point spectra to be recorded at a rate of 8300 spectra per second. In addition, the EMCCD readout mode eliminates curvature and keystone artifacts that often plague spectral imaging systems. The architecture of the new microscope is described in detail, and hyperspectral images from several specimens are presented. PMID:16892134

  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. 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.

  7. Hyperspectral imagery and segmentation

    NASA Astrophysics Data System (ADS)

    Wellman, Mark C.; Nasrabadi, Nasser M.

    2002-07-01

    Hyperspectral imagery (HSI), a passive infrared imaging technique which creates images of fine resolution across the spectrum is currently being considered for Army tactical applications. An important tactical application of infra-red (IR) hyperspectral imagery is the detection of low contrast targets, including those targets that may employ camouflage, concealment and deception (CCD) techniques [1,2]. Spectral reflectivity characteristics were used for efficient segmentation between different materials such as painted metal, vegetation and soil for visible to near IR bands in the range of 0.46-1.0 microns as shown previously by Kwon et al [3]. We are currently investigating the HSI where the wavelength spans from 7.5-13.7 microns. The energy in this range of wavelengths is almost entirely emitted rather than reflected, therefore, the gray level of a pixel is a function of the temperature and emissivity of the object. This is beneficial since light level and reflection will not need to be considered in the segmentation. We will present results of a step-wise segmentation analysis on the long-wave infrared (LWIR) hyperspectrum utilizing various classifier architectures applied to both the full-band, broad-band and narrow-band features derived from the Spatially Enhanced Broadband Array Spectrograph System (SEBASS) data base. Stepwise segmentation demonstrates some of the difficulties in the multi-class case. These results give an indication of the added capability the hyperspectral imagery and associated algorithms will bring to bear on the target acquisition problem.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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).

  13. 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.

  14. 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

  15. 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

  16. 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

  17. Hyperspectral image projector applications

    NASA Astrophysics Data System (ADS)

    Rice, Joseph P.; Brown, Steven W.; Allen, David W.; Yoon, Howard W.; Litorja, Maritoni; Hwang, Jeeseong C.

    2012-03-01

    For the past several years NIST has been developing, along with several collaborators, a Hyperspectral Image Projector (HIP). This scene projector produces high-resolution programmable spectra and projects them into dynamic two-dimensional images. The current digital micromirror device (DMD) based HIP prototype has a spatial resolution of 1024 x 768 pixels and a spectral range of 450 nm to 2400 nm, with spectral resolution from 2 nm in the visible to 5 nm in the short-wave infrared. It disperses light from a supercontinuum fiber source across two DMDs to produce the programmable spectra, which then globally-illuminate a third DMD to form the spatial images. The HIP can simulate top-of-the atmosphere spectral radiance over a 10 mm x 14 mm, f/3 image, and this can be collimated to stimulate remote sensing instruments. Also, the spectral radiance of the projected scenes can be measured with a NIST-calibrated spectroradiometer, such that the spectral radiance projected into each pixel can be accurately known. The HIP was originally developed for applications in multi-spectral and hyperspectral imager testing, calibration, and performance validation, and examples of this application will be reviewed. Conceivable applications for the HIP in photovoltaic device characterization and optical medical imaging will also be discussed.

  18. Multi- and hyperspectral remote-sensing retrieval of floodplain-forest aboveground biomass using machine learning

    NASA Astrophysics Data System (ADS)

    Filippi, A. M.; Guneralp, I.; Randall, J.

    2014-12-01

    Forests within dynamic floodplain landscapes, such as meandering-river landscapes, are composed of uneven-aged trees and entail high spatial variability, which results from intersecting hydrological, fluvial, and ecological processes. Floodplain forests are an important carbon sink relative to other terrestrial ecosystems and thus serve a critical role in the global carbon cycle. Accurate, quantitative aboveground biomass (AGB) retrieval within floodplain forests is urgently needed for improved carbon-pool estimates in such areas and enhanced process understanding of river-floodplain biomorphodynamics. We perform remote AGB retrieval for a meander-bend bottomland hardwood forest, based on utilization of stochastic gradient boosting (SGB), multivariate adaptive regression splines (MARS), and Cubist algorithms and multi- and hyperspectral image-based data sets. For multispectral experiments, we use 30-m and 10-m image bands (Landsat 7 ETM+ and SPOT 5, respectively) and ancillary input vectors; for hyperspectral-based experiments, we use 30-m Hyperion bands and other input variables. Results indicate that for both the multispectral and hyperspectral experimental trials, SGB- and MARS-derived AGB are significantly more accurate than Cubist estimates. (Cubist is used for U.S. national-scale forest biomass mapping.) For the multispectral results, across all data-experiments and algorithms, at 10-m spatial resolution, SGB gives the most accurate estimates (RMSE = 22.49 tonnes/ha; coefficient of determination (R2) = 0.96) when geomorphometric data are also included. For 30-m multispectral data trials, MARS performs the best (RMSE = 29.2 tonnes/ha; R2 = 0.94) when image-derived data are also incorporated. For the hyperspectral experiments, the most accurate MARS- and SGB-based retrievals have R2 of 0.97 and 0.95, respectively; the most accurate Cubist AGB retrieval has R2 of 0.85. MARS and SGB AGB are not significantly different though for the hyperspectral experiments. The

  19. Development and implementation of a multiscale biomass model using hyperspectral vegetation indices for winter wheat in the North China Plain

    NASA Astrophysics Data System (ADS)

    Gnyp, Martin L.; Bareth, Georg; Li, Fei; Lenz-Wiedemann, Victoria I. S.; Koppe, Wolfgang; Miao, Yuxin; Hennig, Simon D.; Jia, Liangliang; Laudien, Rainer; Chen, Xinping; Zhang, Fusuo

    2014-12-01

    Crop monitoring during the growing season is important for regional management decisions and biomass prediction. The objectives of this study were to develop, improve and validate a scale independent biomass model. Field studies were conducted in Huimin County, Shandong Province of China, during the 2006-2007 growing season of winter wheat (Triticum aestivum L.). The field design had a multiscale set-up with four levels which differed in their management, such as nitrogen fertilizer inputs and cultivars, to create different biomass conditions: small experimental fields (L1), large experimental fields (L2), small farm fields (L3), and large farm fields (L4). L4, planted with different winter wheat varieties, was managed according to farmers' practice while L1 through L3 represented controlled field experiments. Multitemporal spectral measurements were taken in the fields, and biomass was sampled for each spectral campaign. In addition, multitemporal Hyperion data were obtained in 2006 and 2007. L1 field data were used to develop biomass models based on the relation between the winter wheat spectra and biomass: several published vegetation indices, including NRI, REP, OSAVI, TCI, and NDVI, were investigated. A new hyperspectral vegetation index, which uses a four-band combination in the NIR and SWIR domains, named GnyLi, was developed. Following the multiscale concept, the data of higher levels (L2 through L4) were used stepwise to validate and improve the models of the lower levels, and to transfer the improved models to the next level. Lastly, the models were transferred and validated at the regional scale using Hyperion images of 2006 and 2007. The results showed that the GnyLi and NRI models, which were based on the NIR and SWIR domains, performed best with R2 > 0.74. All the other indices explained less than 60% model variability. Using the Hyperion data for regionalization, GnyLi and NRI explained 81-89% of the biomass variability. These results highlighted

  20. 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. PMID:23423869

  1. Corrections to the theory of the orbit of Saturn's satellite Hyperion

    NASA Astrophysics Data System (ADS)

    Taylor, D. B.; Sinclair, A. T.; Message, P. J.

    1987-07-01

    A spectral analysis has been made of the residuals obtained from fitting Woltjer's theory of Hyperion to the numerical integration of Sinclair and Taylor (1985) extended to ±25 yr from epoch. The major correction found was to the phase of the libration argument and is probably due to a slightly inaccurate value of the frequency of this argument. The new theory now includes all perturbations corresponding to an observed displacement of 0.arcsec07 or more at the opposition distance of 8.5 AU. The new amplitudes of the long-period perturbations are in broad agreement with those obtained from recent analytical work by Message. The new theory fitted to observations from 1967 to 1983 gave a root-mean-square residual of 0.arcsec28 compared to 0.arcsec44 for the fit of the old theory given in Taylor (1984) to observations in the same period.

  2. 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.

  3. 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.

  4. Development of hyperspectral image projectors

    NASA Astrophysics Data System (ADS)

    Rice, J. P.; Brown, S. W.; Neira, J. E.

    2006-08-01

    We present design concepts for calibrated hyperspectral image projectors (HIP) and related sources intended for system-level testing of instruments ranging from complex hyperspectral or multispectral imagers to simple filter radiometers. HIP, based on the same digital mirror arrays used in commercial digital light processing (DLP) displays, is capable of projecting any combination of many different arbitrarily programmable basis spectra into each pixel of the unit under test (UUT) at video frame rates. The resulting spectral and spatial content of the image entering the UUT can simulate, at typical video frame rates and integration times, realistic scenes to which the UUT will be exposed during use. Also, its spectral radiance can be measured with a calibrated spectroradiometer, such that the hyperspectral photon field entering the UUT is well known. Use of such generated scenes in a controlled laboratory setting would alleviate expensive field testing, allow better separation of environmental effects from instrument effects, and enable system-level performance testing and validation. Example potential applications include system-level testing of complex hyperspectral imaging instruments as implemented with data reduction algorithms when viewing realistic scenes, testing the performance of simple fighter-fighter infrared cameras under simulated adverse conditions, and hardware-in-the-loop testing of multispectral and hyperspectral systems.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices

    NASA Astrophysics Data System (ADS)

    Hamzeh, S.; Naseri, A. A.; AlaviPanah, S. K.; Mojaradi, B.; Bartholomeus, H. M.; Clevers, J. G. P. W.; Behzad, M.

    2013-04-01

    The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R2 = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.

  11. 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

  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. 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.

  14. 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.

  15. Bayesian segmentation of hyperspectral images

    NASA Astrophysics Data System (ADS)

    Mohammadpour, Adel; Féron, Olivier; Mohammad-Djafari, Ali

    2004-11-01

    In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.

  16. Hyperspectral imaging system for UAV

    NASA Astrophysics Data System (ADS)

    Zhang, Da; Zheng, Yuquan

    2015-10-01

    Hyperspectral imaging system for Unmanned Aerial Vehicle (UAV) is proposed under airborne remote sensing application background. By the application of Offner convex spherical grating spectral imaging system and using large area array detector push-broom imaging, hyperspectral imaging system with the indicators of 0.4μm to 1.0μm spectral range, 120 spectral bands, 5nm spectral resolution and 1m ground sampling interval (flight altitude 5km) is developed and completed. The Offner convex grating spectral imaging system is selected to achieve non-spectral line bending and colorless distortion design results. The diffraction efficiency is 15%-30% in the range of 0.4μm to 1.0μm wavelength. The system performances are tested by taking spectral and radiometric calibration methods in the laboratory. Based on monochromatic collimated light method for spectral performance parameters calibration of hyperspectral optical remote sensor, the analysis results of spectral calibration data show that the calibration test repeatability is less than 0.2 nm within one hour. The spectral scaling results show that the average spectral resolution of hyperspectral optical remote sensor is 4.94 nm, and the spatial dimension of the high-spectral optical remote sensor spectral resolution is less than 5 nm, the average of the typical spectral bandwidth is about 6 nm, the system average signal-to-noise ratio (SNR) is up to 43dB under typical operating conditions. Finally the system functionalities and performance indicators are verified by the aviation flight tests, which it's equipped on UAV. The actual image quality is good, and the spectral position is stable.

  17. 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.

  18. 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.

  19. 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.

  20. Hyperspectral image compressive projection algorithm

    NASA Astrophysics Data System (ADS)

    Rice, Joseph P.; Allen, David W.

    2009-05-01

    We describe a compressive projection algorithm and experimentally assess its performance when used with a Hyperspectral Image Projector (HIP). The HIP is being developed by NIST for system-level performance testing of hyperspectral and multispectral imagers. It projects a two-dimensional image into the unit under test (UUT), whereby each pixel can have an independently programmable arbitrary spectrum. To efficiently project a single frame of dynamic realistic hyperspectral imagery through the collimator into the UUT, a compression algorithm has been developed whereby the series of abundance images and corresponding endmember spectra that comprise the image cube of that frame are first computed using an automated endmember-finding algorithm such as the Sequential Maximum Angle Convex Cone (SMACC) endmember model. Then these endmember spectra are projected sequentially on the HIP spectral engine in sync with the projection of the abundance images on the HIP spatial engine, during the singleframe exposure time of the UUT. The integrated spatial image captured by the UUT is the endmember-weighted sum of the abundance images, which results in the formation of a datacube for that frame. Compressive projection enables a much smaller set of broadband spectra to be projected than monochromatic projection, and thus utilizes the inherent multiplex advantage of the HIP spectral engine. As a result, radiometric brightness and projection frame rate are enhanced. In this paper, we use a visible breadboard HIP to experimentally assess the compressive projection algorithm performance.

  1. 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.

  2. Skin detection in hyperspectral images

    NASA Astrophysics Data System (ADS)

    Sanchez, Stephanie M.; Velez-Reyes, Miguel

    2015-05-01

    Hyperspectral imagers collect information of the scene being imaged at close contiguous bands in the electromagnetic spectrum at high spectral resolutions. The number of applications for these imagers has grown over the years as they are now used in various fields. Many algorithms are described in the literature for skin detection in color imagery. However increased detection accuracy, in particularly over cluttered backgrounds, and of small targets and in low spatial resolution systems can be achieved by taking advantage of the spectral information that can be collected with multi/hyperspectral imagers. The ultimate goal of our research work is the development of a human presence detection system over different backgrounds using hyperspectral imaging in the 400-1000nm region of the spectrum that can be used in the context of search and rescue operations, and surveillance in defense and security applications. The 400-1000 nm region is chosen because of availability of low cost imagers in this region of the spectrum. This paper presents preliminary results in the use of combinations of normalized difference indices that can be used to detect regions of interest in a scene that can be used as a pre-processor in a human detection system. A new normalized difference ratio, the Skin Normalized Difference Index (SNDI) is proposed. Experimental results show that a combination the NDGRI+NDVI+SNDI results in a probability of detection similar to that of the NDGRI. However, the combination of features results in a much lower probability of false alarm.

  3. Hyperspectral imaging for nondestructive evaluation of tomatoes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  4. 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.

  5. 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.

  6. Efficient detection in hyperspectral imagery.

    PubMed

    Schweizer, S M; Moura, J F

    2001-01-01

    Hyperspectral sensors collect hundreds of narrow and contiguously spaced spectral bands of data. Such sensors provide fully registered high resolution spatial and spectral images that are invaluable in discriminating between man-made objects and natural clutter backgrounds. The price paid for this high resolution data is extremely large data sets, several hundred of Mbytes for a single scene, that make storage and transmission difficult, thus requiring fast onboard processing techniques to reduce the data being transmitted. Attempts to apply traditional maximum likelihood detection techniques for in-flight processing of these massive amounts of hyperspectral data suffer from two limitations: first, they neglect the spatial correlation of the clutter by treating it as spatially white noise; second, their computational cost renders them prohibitive without significant data reduction like by grouping the spectral bands into clusters, with a consequent loss of spectral resolution. This paper presents a maximum likelihood detector that successfully confronts both problems: rather than ignoring the spatial and spectral correlations, our detector exploits them to its advantage; and it is computationally expedient, its complexity increasing only linearly with the number of spectral bands available. Our approach is based on a Gauss-Markov random field (GMRF) modeling of the clutter, which has the advantage of providing a direct parameterization of the inverse of the clutter covariance, the quantity of interest in the test statistic. We discuss in detail two alternative GMRF detectors: one based on a binary hypothesis approach, and the other on a "single" hypothesis formulation. We analyze extensively with real hyperspectral imagery data (HYDICE and SEBASS) the performance of the detectors, comparing them to a benchmark detector, the RX-algorithm. Our results show that the GMRF "single" hypothesis detector outperforms significantly in computational cost the RX

  7. The Hyperspectral Stereo Camera Project

    NASA Astrophysics Data System (ADS)

    Griffiths, A. D.; Coates, A. J.

    2006-12-01

    The MSSL Hyperspectral Stereo Camera (HSC) is developed from Beagle2 stereo camera heritage. Replaceing filter wheels with liquid crystal tuneable filters (LCTF) turns each eye into a compact hyperspectral imager. Hyperspectral imaging is defined here as acquiring 10s-100s of images in 10-20 nm spectral bands. Combined together these bands form an image `cube' (with wavelength as the third dimension) allowing a detailed spectrum to be extracted at any pixel position. A LCTF is conceptually similar to the Fabry-Perot tuneable filter design but instead of physical separation, the variable refractive index of the liquid crystal etalons is used to define the wavelength of interest. For 10 nm bandwidths, LCTFs are available covering the 400-720 nm and 650-1100 nm ranges. The resulting benefits include reduced imager mechanical complexity, no limitation on the number of filter wavelengths available and the ability to change the wavelengths of interest in response to new findings as the mission proceeds. LCTFs are currently commercially available from two US companies - Scientific Solutions Inc. and Cambridge Research Inc. (CRI). CRI distribute the `Varispec' LCTFs used in the HSC. Currently, in Earth orbit hyperspectral imagers can prospect for minerals, detect camouflaged military equipment and determine the species and state of health of crops. Therefore, we believe this instrument shows great promise for a wide range of investigations in the planetary science domain (below). MSSL will integrate and test at representative Martian temperatures the HSC development model (to determine power requirements to prevent the liquid crystals freezing). Additionally, a full radiometric calibration is required to determine the HSC sensitivity. The second phase of the project is to demonstrate (in a ground based lab) the benefit of much higher spectral resolution to the following Martian scientific investigations: - Determination of the mineralogy of rocks and soil - Detection of

  8. 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.

  9. False alarm recognition in hyperspectral gas plume identification

    DOEpatents

    Conger, James L.; Lawson, Janice K.; Aimonetti, William D.

    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.

  10. Hyperspectral imaging camera using wavefront division interference.

    PubMed

    Bahalul, Eran; Bronfeld, Asaf; Epshtein, Shlomi; Saban, Yoram; Karsenty, Avi; Arieli, Yoel

    2016-03-01

    An approach for performing hyperspectral imaging is introduced. The hyperspectral imaging is based on Fourier transform spectroscopy, where the interference is performed by wavefront division interference rather than amplitude division interference. A variable phase delay between two parts of the wavefront emanating from each point of an object is created by a spatial light modulator (SLM) to obtain variable interference patterns. The SLM is placed in the exit pupil of an imaging system, thus enabling conversion of a general imaging optical system into an imaging hyperspectral optical system. The physical basis of the new approach is introduced, and an optical apparatus is built. PMID:26974085

  11. Is there a best hyperspectral detection algorithm?

    NASA Astrophysics Data System (ADS)

    Manolakis, D.; Lockwood, R.; Cooley, T.; Jacobson, J.

    2009-05-01

    A large number of hyperspectral detection algorithms have been developed and used over the last two decades. Some algorithms are based on highly sophisticated mathematical models and methods; others are derived using intuition and simple geometrical concepts. The purpose of this paper is threefold. First, we discuss the key issues involved in the design and evaluation of detection algorithms for hyperspectral imaging data. Second, we present a critical review of existing detection algorithms for practical hyperspectral imaging applications. Finally, we argue that the "apparent" superiority of sophisticated algorithms with simulated data or in laboratory conditions, does not necessarily translate to superiority in real-world applications.

  12. 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.

  13. 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

  14. Quality assessment for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Shen, Weimin

    2014-11-01

    Image quality assessment is an essential value judgement approach for many applications. Multi & hyper spectral imaging has more judging essentials than grey scale or RGB imaging and its image quality assessment job has to cover up all-around evaluating factors. This paper presents an integrating spectral imaging quality assessment project, in which spectral-based, radiometric-based and spatial-based statistical behavior for three hyperspectral imagers are jointly executed. Spectral response function is worked out based on discrete illumination images and its spectral performance is deduced according to its FWHM and spectral excursion value. Radiometric response ability of different spectral channel under both on-ground and airborne imaging condition is judged by SNR computing based upon local RMS extraction and statistics method. Spatial response evaluation of the spectral imaging instrument is worked out by MTF computing with slanted edge analysis method. Reported pioneering systemic work in hyperspectral imaging quality assessment is carried out with the help of several domestic dominating work units, which not only has significance in the development of on-ground and in-orbit instrument performance evaluation technique but also takes on reference value for index demonstration and design optimization for instrument development.

  15. 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

  16. Using hyperspectral data in precision farming applications

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  17. Constructing satellite-derived hyperspectral indices sensitive to canopy structure variables of a Cordilleran Cypress (Austrocedrus chilensis) forest

    NASA Astrophysics Data System (ADS)

    Peña, Marco A.; Brenning, Alexander; Sagredo, Ariel

    2012-11-01

    Satellite hyperspectral data were used to construct empirical spectral indices related to the canopy structure of a Cordilleran Cypress (Austrocedrus chilensis) forest located in the Andes of central Chile. Measurements of tree diameter at breast height (DBH) and tree height (TH) were performed for a set of plots located within a pure and unevenly aged stand of A. chilensis with moderate cover. Normalized difference vegetation indices (NDIs) related to DBH and TH were constructed from the corresponding hyperspectral data in Hyperion imagery. NDIs construction utilized the original spectral reflectance curve, its first derivative, and the continuum-removed reflectance in a two-step procedure that ranks NDIs based on their Spearman correlation with the response variable while controlling the false discovery rate. Several reflectance-based NDIs as well as a larger group of derivative-based NDIs were significantly related to DBH or TH (ρ > 0.70). The NDIs most strongly related to the field variables were based on derivative bands located within the same spectral regions used by the broadband greenness index known as green normalized difference vegetation index. Most other significant NDIs used NIR bands, which are well-known for their sensitivity to foliage amount changes. The results obtained in this exploratory study mostly agreed with the spectral regions expected to be most sensitive to changes in the canopy structure of vegetation. Further research in other A. chilensis forests subject to different site and environmental conditions is needed in order to assess the applicability of the NDIs over a wider range of this endemic species.

  18. 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.

  19. 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.

  20. Hyperspectral imaging of atherosclerotic plaques in vitro

    NASA Astrophysics Data System (ADS)

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

    2011-02-01

    Vulnerable plaques constitute a risk for serious heart problems, and are difficult to identify using existing methods. Hyperspectral imaging combines spectral- and spatial information, providing new possibilities for precise optical characterization of atherosclerotic lesions. Hyperspectral data were collected from excised aorta samples (n = 11) using both white-light and ultraviolet illumination. Single lesions (n = 42) were chosen for further investigation, and classified according to histological findings. The corresponding hyperspectral images were characterized using statistical image analysis tools (minimum noise fraction, K-means clustering, principal component analysis) and evaluation of reflectance/fluorescence spectra. Image analysis combined with histology revealed the complexity and heterogeneity of aortic plaques. Plaque features such as lipids and calcifications could be identified from the hyperspectral images. Most of the advanced lesions had a central region surrounded by an outer rim or shoulder-region of the plaque, which is considered a weak spot in vulnerable lesions. These features could be identified in both the white-light and fluorescence data. Hyperspectral imaging was shown to be a promising tool for detection and characterization of advanced atherosclerotic plaques in vitro. Hyperspectral imaging provides more diagnostic information about the heterogeneity of the lesions than conventional single point spectroscopic measurements.

  1. 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.

  2. Thermal characterization of a NIR hyperspectral camera

    NASA Astrophysics Data System (ADS)

    Parra, Francisca; Meza, Pablo; Pezoa, Jorge E.; Torres, Sergio N.

    2011-11-01

    The accuracy achieved by applications employing hyperspectral data collected by hyperspectral cameras depends heavily on a proper estimation of the true spectral signal. Beyond question, a proper knowledge about the sensor response is key in this process. It is argued here that the common first order representation for hyperspectral NIR sensors does not represent accurately their thermal wavelength-dependent response, hence calling for more sophisticated and precise models. In this work, a wavelength-dependent, nonlinear model for a near infrared (NIR) hyperspectral camera is proposed based on its experimental characterization. Experiments have shown that when temperature is used as the input signal, the camera response is almost linear at low wavelengths, while as the wavelength increases the response becomes exponential. This wavelength-dependent behavior is attributed to the nonlinear responsivity of the sensors in the NIR spectrum. As a result, the proposed model considers different nonlinear input/output responses, at different wavelengths. To complete the representation, both the nonuniform response of neighboring detectors in the camera and the time varying behavior of the input temperature have also been modeled. The experimental characterization and the proposed model assessment have been conducted using a NIR hyperspectral camera in the range of 900 to 1700 [nm] and a black body radiator source. The proposed model was utilized to successfully compensate for both: (i) the nonuniformity noise inherent to the NIR camera, and (ii) the stripping noise induced by the nonuniformity and the scanning process of the camera while rendering hyperspectral images.

  3. 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.

  4. Hyperspectral remote sensing applied for hydrogeological mapping in a hard-rock terrain for water resource management

    NASA Astrophysics Data System (ADS)

    Singh, Amit; Mukherjee, Saumitra

    2011-11-01

    This study aimed at studying the whole of geological environment associated with a semi-arid, hard-rock terrain utilizing hyperspectral satellite data, topographic analysis and 3D visualization techniques to infer hydrological regime in form of GIS outputs. The study area selected has a rapidly changing land use pattern and subjected to mining activity. Several natural lakes have dried up and few abandoned mining pits have turned up into lakes. Efforts are being made to restore the landscape and protect any further degradation. Availability of water is prime decisive factor in all such efforts. In this study, Hyperion data has been utilized in a unique and elaborated methodology designed to effectively isolate the intruding urban cover and extract maximum information in an unmixing approach. This has been coupled with ground surveys as well as analysis of soil / sediment, rock and water samples. ASTER DEM has been used for topographic analysis using TauDEM to infer watershed and drainage pattern. Apart from geological endmembers, available pockets of vegetation have been identified as these are themselves an indicator of groundwater availability. This also resulted in identification of sites suitable for future geophysical surveys to determine the nature of sub-surface fractures. This whole exercise in detail has been helpful in obtaining a synoptic view of water resource in the region and then subsequent planning for integrated water resource management.

  5. 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.

  6. 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.

  7. Quantitative retrieving of soil organic matter using field spectrometer and hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    Zhuo, Luo; Liu, Yaolin; Chen, Jie; Hu, Changji; Wu, Jian

    2008-12-01

    As the important component of soil, soil organic matter not only provides every nutrient element for crop, but also has determinant effect for forming of soil structure and melioration the soil physical character. Mapping and dating soil organic matter is of great importance in soil use and evaluation. In this study we examine the feasibility of soil organic matter content by using Hyperspectrally reflective remote sensing methodology. This technique was tested in Xiaochang County located in Hubei province. The soil reflectance properties of samples were measured in the laboratory by ASD field spectrometer. The correlation analysis related with organic matter content was processed from three factors: the spectral reflectance parameter ((lgρ)', ρ/ ρ450-750 and (1/lgρ623)'/ (1/lgρ564)'). The results show that the correlation coefficients of r values were: organic matter identification index (ρ/ ρ450-750) > logarithmic first derivative of reflectivity ((lgρ)') > organic matter mix identification index ((1/lgρ623)'/(1/lgρ564)'). Knowing these correlations we were able to use the best prominence correlation of organic matter identification index of 1850nm wavelength as the variable regression to build up statistical regression analysis. We used five model types (Linear Function, Logarithmic Function, Quadratic Function, Power Function and Exponential Function) to forecast the soil organic matter content Hyperion model. The accuracy assessment (R2= 0.8484) by relating forecasted organic matter values with Quadratic Function regression showed that the model is reliable and significantly correlative with known stabilization processes throughout the study area. The quantitative methodology developed in this study for refutations soil organic matter content can be adapted to other regions throughout the world.

  8. Unsupervised linear unmixing of hyperspectral image for crop yield estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multispectral and hyperspectral imagery are often used for estimating crop yield. This paper describes an unsupervised unmixing scheme of hyperspectral images to estimate crop yield. From the hyperspectral images, the endmembers and their abundance maps are computed by unsupervised unmixing. The abu...

  9. Research on hyperspectral dynamic infrared scene simulation technology

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Hu, Yu; Ding, Na; Sun, Kefeng; Sun, Dandan; Xie, Junhu; Wu, Wenli; Gao, Jiaobo

    2015-02-01

    The paper presents a hardware in loop dynamic IR scene simulation technology for IR hyperspectral imaging system. Along with fleetly development of new type EO detecting, remote sensing and hyperspectral imaging technique, not only static parameters' calibration of hyperspectral IR imaging system but also dynamic parameters' testing and evaluation are required, thus hyperspectral dynamic IR simulation and evaluation become more and more important. Hyperspectral dynamic IR scene projector utilizes hyperspectral space and time domain features controlling spectrum and time synchronously to realize hardware in loop simulation. Hyperspectral IR target and background simulating image can be gained by the accomplishment of 3D model and IR characteristic romancing, hyperspectral dynamic IR scene is produced by image converting device. The main parameters of a developed hyperspectral dynamic IR scene projector: wave band range is 3~5μm, 8~12μm Field of View (FOV) is 8°; spatial resolution is 1024×768 spectrum resolution is 1%~2%. IR source and simulating scene features should be consistent with spectrum characters of target, and different spectrum channel's images can be gotten from calibration. A hyperspectral imaging system splits light with dispersing type grating, pushbrooms and collects the output signal of dynamic IR scene projector. With hyperspectral scene spectrum modeling, IR features romancing, atmosphere transmission feature modeling and IR scene projecting, target and scene in outfield can be simulated ideally, simulation and evaluation of IR hyperspectral imaging system's dynamic features are accomplished in laboratory.

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. [Validation of feasibility of virtual hyperspectral technology].

    PubMed

    Lin, Ling; Wu, Hong-jie; Li, Zhe; Li, Gang; Zhang, Bao-ju; Wu, Jin-cheng

    2011-12-01

    To verify the virtual hyperspectral technology for acquiring the internal composition and structure information, the virtual hyperspectral system, which took apples as the test materials, was built. First, we detected the virtual hyperspectral system of the normal apples and ill apples. Then, the virtual hyperspectral of apple slices and apple slices with a piece of red optical filter embedded was detected. Finally, the reflection spectrum of normal apple, ill apple, apple slice and slice with a piece of red filter embedded was detected. The results showed that virtual hyperspectral, which can gain more information than reflection spectrum, could be used for detecting the variation of internal composition and structure. It is a strong evidence that this technology can be used in human body in the future. Virtual hpyerspectral is a new path applied to detecting the biological information, and it can be used for the multi-information and cross-information detection simultaneously and systematically. More foundation for quick disease check-up in vivo was expected to be provided by this technology. PMID:22295793

  15. 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.

  16. 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.

  17. Military applications of hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Briottet, X.; Boucher, Y.; Dimmeler, A.; Malaplate, A.; Cini, A.; Diani, M.; Bekman, H.; Schwering, P.; Skauli, T.; Kasen, I.; Renhorn, I.; Klasén, L.; Gilmore, M.; Oxford, D.

    2006-05-01

    Optical imaging, including infrared imaging, generally has many important applications, both civilian and military. In recent years, technological advances have made multi- and hyperspectral imaging a viable technology in many demanding military application areas. The aim of the CEPA JP 8.10 program has been to evaluate the potential benefit of spectral imaging techniques in tactical military applications. This unclassified executive summary describes the activities in the program and outlines some of the results. More specific results are given in classified reports and presentations. The JP 8.10 program started in March 2002 and ended in February 2005. The participating nations were France, Germany, Italy, Netherlands, Norway, Sweden and United-Kingdom, each with a contribution of 2 man-years per year. Essential objectives of the program were to: 1) analyze the available spectral information in the optronic landscape from visible to infrared; 2) analyze the operational utility of multi- and hyperspectral imaging for detection, recognition and identification of targets, including low-signature targets; 3) identify applications where spectral imaging can provide a strong gain in performance; 4) propose technical recommendations of future spectral imaging systems and critical components. Finally, a stated objective of the JP 8.10 program is to "ensure the proper link with the image processing community". The presentation is organized as follows. In a first step, the two trials (Pirrene and Kvarn) are presented including a summary of the acquired optical properties of the different landscape materials and of the spectral images. Then, a phenomenology study is conducted analyzing the spectral behavior of the optical properties, understanding the signal at the sensor and, by processing spectroradiometric measurements evaluating the potential to discriminate spectral signatures. Cameo-Sim simulation software is presented including first validation results and the

  18. 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).

  19. Hyperspectral and broadband FLIR data fusion

    NASA Astrophysics Data System (ADS)

    Nicholas, Mike; James, Matt; Nothard, Jo

    2005-10-01

    Future targeting systems aim to extend the range of air-ground target search, acquisition, temporal tracking and identification exceeding those currently afforded by forward looking infrared sensors. One technology option that has the potential to fulfil this requirement is hyperspectral imaging. Therefore a solution to detection and identification at longer ranges is the fusion of data from broadband and hyperspectral sensors. QinetiQ, under the Data & Information Fusion Defense Technology Centre, aims to develop a fully integrated spatial/spectral and temporal target detection/ identification air- ground tracking environment. This will build upon current capabilities in target tracking, synthetic scene generation, sensor modelling, hyperspectral and broadband target detection and identification algorithms into a tool that can be used to evaluate data fusion architectures.

  20. Real-time snapshot hyperspectral imaging endoscope.

    PubMed

    Kester, Robert T; Bedard, Noah; Gao, Liang; Tkaczyk, Tomasz S

    2011-05-01

    Hyperspectral imaging has tremendous potential to detect important molecular biomarkers of early cancer based on their unique spectral signatures. Several drawbacks have limited its use for in vivo screening applications: most notably the poor temporal and spatial resolution, high expense, and low optical throughput of existing hyperspectral imagers. We present the development of a new real-time hyperspectral endoscope (called the image mapping spectroscopy endoscope) based on an image mapping technique capable of addressing these challenges. The parallel high throughput nature of this technique enables the device to operate at frame rates of 5.2 frames per second while collecting a (x, y, λ) datacube of 350 × 350 × 48. We have successfully imaged tissue in vivo, resolving a vasculature pattern of the lower lip while simultaneously detecting oxy-hemoglobin. PMID:21639573

  1. 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.

  2. Dynamical Spectral Unmixing of Multitemporal Hyperspectral Images

    NASA Astrophysics Data System (ADS)

    Henrot, Simon; Chanussot, Jocelyn; Jutten, Christian

    2016-07-01

    In this paper, we consider the problem of unmixing a time series of hyperspectral images. We propose a dynamical model based on linear mixing processes at each time instant. The spectral signatures and fractional abundances of the pure materials in the scene are seen as latent variables, and assumed to follow a general dynamical structure. Based on a simplified version of this model, we derive an efficient spectral unmixing algorithm to estimate the latent variables by performing alternating minimizations. The performance of the proposed approach is demonstrated on synthetic and real multitemporal hyperspectral images.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Hyperspectral exploitation with plant sentinels

    NASA Astrophysics Data System (ADS)

    Shaw, Arnab K.; Medford, June; Antunes, Mauricio; McCormick, William S.; Wicker, Devert

    2007-04-01

    The primary goal of this paper is to develop Hyperspectral algorithms for early detection of a readout system used in conjunction with plants designed to de-green or discolor after detection of explosives, harmful chemicals, and environmental pollutants. Work in progress is aimed to develop a new class of biosensors or Plant Sentinels that can serve as inexpensive plant-based biological early-warning systems capable of detecting substances that are harmful to human or the environment [LoHe03]. The de-greening circuits in the laboratory plant, Arabidopsis, have been shown to induce rapid chlorophyll loss, thereby change color under the influence of synthetic estrogens. However, as of now, the bio de-greening phenomenon is detectable by human eyes or with a system (chlorophyll fluorescence) that works best in laboratory conditions. In order to make the plant sentinel system practically viable, we have developed automated monitoring scheme for early detection of the de-greening phenomenon. The automated detection capability would lead to practical applicability and wider usage. This paper presents novel and effective HSI-based algorithms for early detection of de-greening of plants and vegetation due to explosives or chemical agents. The image processing based automated degreening detector, presented in this paper will be capable of 24/7 monitoring of the plant sentinels and to detect minutest possible discoloration of the plant-sensors to serve as an early-warning system. We also present preliminary results on estimating the length of time that the explosive or chemical agent has been present.

  9. 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.

  10. Landmine detection using passive hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    McFee, John E.; Anger, Cliff; Achal, Steve; Ivanco, Tyler

    2007-04-01

    Airborne hyperspectral imaging has been studied since the late 1980s as a tool to detect minefields for military countermine operations and for level I clearance for humanitarian demining. Hyperspectral imaging employed on unmanned ground vehicles may also be used to augment or replace broadband imagers to detect individual mines. This paper will discuss the ability of different optical wavebands - the visible/near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) - to detect surface-laid and buried mines. The phenomenology that determines performance in the different bands is discussed. Hyperspectral imagers have usually been designed and built for general purpose remote sensing applications and often do not meet the requirements of mine detection. The DRDC mine detection research program has sponsored the development by Itres Research of VNIR, SWIR and TIR instruments specifically intended for mine detection. The requirements for such imagers are described, as well as the instruments. Some results of mine detection experiments are presented. To date, reliable day time detection of surface-laid mines in non-real-time, independent of solar angle, time of day and season has been demonstrated in the VNIR and SWIR. Real-time analysis, necessary for military applications, has been demonstrated from low speed ground vehicles and recently from airborne platforms. Reliable, repeatable detection of buried mines has yet to be demonstrated, although a recently completed TIR hyperspectral imager will soon be tested for such a capability.

  11. Quality evaluation of fruit by hyperspectral imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This chapter presents new applications of hyperspectral imaging for measuring the optical properties of fruits and assessing their quality attributes. A brief overview is given of current techniques for measuring optical properties of turbid and opaque biological materials. Then a detailed descripti...

  12. 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.

  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. 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.

  15. 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.

  16. Convex geometry analysis method of hyperspectral data

    NASA Astrophysics Data System (ADS)

    Gong, Yanjun; Wang, XiChang; Qi, Hongxing; Yu, BingXi

    2003-06-01

    We present matrix expression of convex geometry analysis method of hyperspectral data by linear mixing model and establish a mathematic model of endmembers. A 30-band remote sensing image is applied to testify the model. The results of analysis reveal that the method can analyze mixed pixel questions. The targets that are smaller than earth surface pixel can be identified by applying the method.

  17. 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

  18. 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

  19. Compression of hyperspectral data for automated analysis

    NASA Astrophysics Data System (ADS)

    Linderhed, Anna; Wadströmer, Niclas; Stenborg, K.-G.; Nautsch, Harald

    2009-09-01

    State of the art and coming hyperspectral optical sensors generate large amounts of data and automatic analysis is necessary. One example is Automatic Target Recognition (ATR), frequently used in military applications and a coming technique for civilian surveillance applications. When sensors communicate in networks, the capacity of the communication channel defines the limit of data transferred without compression. Automated analysis may have different demands on data quality than a human observer, and thus standard compression methods may not be optimal. This paper presents results from testing how the performance of detection methods are affected by compressing input data with COTS coders. A standard video coder has been used to compress hyperspectral data. A video is a sequence of still images, a hybrid video coder use the correlation in time by doing block based motion compensated prediction between images. In principle only the differences are transmitted. This method of coding can be used on hyperspectral data if we consider one of the three dimensions as the time axis. Spectral anomaly detection is used as detection method on mine data. This method finds every pixel in the image that is abnormal, an anomaly compared to the surroundings. The purpose of anomaly detection is to identify objects (samples, pixels) that differ significantly from the background, without any a priori explicit knowledge about the signature of the sought-after targets. Thus the role of the anomaly detector is to identify "hot spots" on which subsequent analysis can be performed. We have used data from Imspec, a hyperspectral sensor. The hyperspectral image, or the spectral cube, consists of consecutive frames of spatial-spectral images. Each pixel contains a spectrum with 240 measure points. Hyperspectral sensor data was coded with hybrid coding using a variant of MPEG2. Only I- and P- frames was used. Every 10th frame was coded as I frame. 14 hyperspectral images was coded in 3

  20. Hyperspectral Data Classification Using Factor Graphs

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

    Accurate classification of hyperspectral data is still a competitive task and new classification methods are developed to achieve desired tasks of hyperspectral data use. The objective of this paper is to develop a new method for hyperspectral data classification ensuring the classification model properties like transferability, generalization, probabilistic interpretation, etc. While factor graphs (undirected graphical models) are unfortunately not widely employed in remote sensing tasks, these models possess important properties such as representation of complex systems to model estimation/decision making tasks. In this paper we present a new method for hyperspectral data classification using factor graphs. Factor graph (a bipartite graph consisting of variables and factor vertices) allows factorization of a more complex function leading to definition of variables (employed to store input data), latent variables (allow to bridge abstract class to data), and factors (defining prior probabilities for spectral features and abstract classes; input data mapping to spectral features mixture and further bridging of the mixture to an abstract class). Latent variables play an important role by defining two-level mapping of the input spectral features to a class. Configuration (learning) on training data of the model allows calculating a parameter set for the model to bridge the input data to a class. The classification algorithm is as follows. Spectral bands are separately pre-processed (unsupervised clustering is used) to be defined on a finite domain (alphabet) leading to a representation of the data on multinomial distribution. The represented hyperspectral data is used as input evidence (evidence vector is selected pixelwise) in a configured factor graph and an inference is run resulting in the posterior probability. Variational inference (Mean field) allows to obtain plausible results with a low calculation time. Calculating the posterior probability for each class

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. Quantification and threshold detection in real-time hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Driver, Richard D.

    2009-05-01

    The technical challenges of applying hyperspectral imaging techniques to on-line real-time food monitoring is discussed. System optimization must be applied to the design of the hyperspectral imaging spectrograph, the choice and operation of the imaging detector, the design of the illumination system and finally the development of software algorithms to correctly quantify the hyperspectral images. The signal to noise limitation of hyperspectral detection is discussed with particular emphasis on the detection of moving objects at high measurement bandwidths. An example is given of the development of a simple but accurate algorithm for the detection and discrimination of rust particles on leaves.

  6. Evaluation of thermophilic anaerobic digestion processes for full-scale Class A biosolids disinfection at Hyperion Treatment Plant.

    PubMed

    Iranpour, R; Cox, H H J

    2007-05-01

    This paper describes 5 phases of full-scale testing at the City of Los Angeles Hyperion Treatment Plant (HTP) for producing Class A biosolids (U.S. EPA Part 503 Biosolids Rule) by thermophilic anaerobic digestion. Phases I and II were tests with a two-stage continuous-batch process in a thermophilic battery of six digesters and a designated post-digestion train that was isolated from mesophilic operations. These tests demonstrated that digester outflow biosolids met the Class A limits for fecal coliforms and Salmonella sp. However, fecal coliform densities sharply increased during post-digestion. The recurrence was possibly related to a combination of a large drop of the biosolids temperature after the dewatering centrifuges and contamination of thermophilically digested biosolids from mesophilic operations. Phase III was conducted after insulation and electrical heat-tracing of the post-digestion train to maintain a biosolids temperature throughout post-digestion at about the same level as in the digester outflow. Biosolids monitoring at the last points of plant control (silos at Truck Loading Facility and farm for land application) indicated that fecal coliform recurrence was prevented. After completing the conversion of HTP to thermophilic operation, certification tests of Phases IV and V demonstrated Class A compliance of a two-stage continuous-batch process under Alternatives 1 and 3 of the Part 503 Biosolids Rule, respectively. HTP received the permit for Class A (indeed exceptional quality) biosolids land application in Kern County, California, in December 2002 under Alternative 3. Since 2003, HTP has consistently complied with the federal and local standards for Class A biosolids, indicating that Class A limits can be met under conditions less stringent than defined by the Alternative 1 time-temperature requirement for batch treatment. PMID:17054113

  7. Hyperspectral face recognition under variable outdoor illumination

    NASA Astrophysics Data System (ADS)

    Pan, Zhihong; Healey, Glenn E.; Prasad, Manish; Tromberg, Bruce J.

    2004-08-01

    We examine the performance of illumination-invariant face recognition in outdoor hyperspectral images using a database of 200 subjects. The hyperspectral camera acquires 31 bands over the 700-1000nm spectral range. Faces are represented by local spectral information for several tissue types. Illumination variation is modeled by low-dimensional spectral radiance subspaces. Invariant subspace projection over multiple tissue types is used for recognition. The experiments consider various face orientations and expressions. The analysis includes experiments for images synthesized using face reflectance images of 200 subjects and a database of over 7,000 outdoor illumination spectra. We also consider experiments that use a set of face images that were acquired under outdoor illumination conditions.

  8. Hyperspectral imaging of polymer/fullerene blends

    NASA Astrophysics Data System (ADS)

    Torreggiani, Armida; Tinti, Francesca; Savoini, Alberto; Melchiorre, Michele; Po, Riccardo; Camaioni, Nadia

    2014-10-01

    The effectiveness of a hyperspectral imaging system integrated on an enhanced dark-field microscope for probing the microscale morphology of model poly(3- hexylthiopene): [6,6]-phenyl-C61- butyric acid methyl ester (P3HT:PCBM) blends is demonstrated. This non-contact technique provides both spectral and spatial information in one measurement, providing an effective mapping of the presence and location of the component materials in the investigated P3HT:PCBM blends spincoated over different substrates (zinc oxide, poly(3,4- ethylenedioxythiophene):poly(styrenesulfonate). The hyperspectral analysis accounts for the micro-scale morphology of P3HT:PCBM blends, even in case of high film roughness, and the quantitative determination of blend components reveals a preferential accumulation of the lowenergy material (P3HT) at the interface with air, confirming the findings reported with other mapping techniques

  9. 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.

  10. 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.

  11. 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.

  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

    2012-12-01

    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. PMID:23262713

  13. Hyperspectral target detection using sequential approach

    NASA Astrophysics Data System (ADS)

    Haskett, Hanna T.; Sood, Arun K.; Habib, Mohammad K.

    1999-08-01

    This paper describes an automatic target detection algorithm based on the sequential multi-stage approach. Each stage of the algorithm uses more spectral bands than the previous stage. To ensure high probability of detection and low false alarm rate, Chebyshev's inequality test is applied. The sequential approach enables a significant reduction in computational time of a hyperspectral detection system. The Forest Radiance I database collected with the HYDICE hyperspectral sensor at the U.S. Army Proving Ground in Aberdeen, Maryland is utilized. Scenarios include targets in the open, with footprints of 1 m and different times of day. The total area coverage and the number of targets used in this evaluation are approximately 6 km2 and 126, respectively.

  14. 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

    2012-12-01

    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.

  15. 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.

  16. 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.

  17. A parallel unmixing algorithm for hyperspectral images

    NASA Astrophysics Data System (ADS)

    Robila, Stefan A.; Maciak, Lukasz G.

    2006-10-01

    We present a new algorithm for feature extraction in hyperspectral images based on source separation and parallel computing. In source separation, given a linear mixture of sources, the goal is to recover the components by producing an unmixing matrix. In hyperspectral imagery, the mixing transform and the separated components can be associated with endmembers and their abundances. Source separation based methods have been employed for target detection and classification of hyperspectral images. However, these methods usually involve restrictive conditions on the nature of the results such as orthogonality (in Principal Component Analysis - PCA and Orthogonal Subspace Projection - OSP) of the endmembers or statistical independence (in Independent Component Analysis - ICA) of the abundances nor do they fully satisfy all the conditions included in the Linear Mixing Model. Compared to this, our approach is based on the Nonnegative Matrix Factorization (NMF), a less constraining unmixing method. NMF has the advantage of producing positively defined data, and, with several modifications that we introduce also ensures addition to one. The endmember vectors and the abundances are obtained through a gradient based optimization approach. The algorithm is further modified to run in a parallel environment. The parallel NMF (P-NMF) significantly reduces the time complexity and is shown to also easily port to a distributed environment. Experiments with in-house and Hydice data suggest that NMF outperforms ICA, PCA and OSP for unsupervised endmember extraction. Coupled with its parallel implementation, the new method provides an efficient way for unsupervised unmixing further supporting our efforts in the development of a real time hyperspectral sensing environment with applications to industry and life sciences.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. Unsupervised data fusion for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Jimenez-Rodriguez, Luis O.; Velez-Reyes, Miguel; Rivera-Medina, Jorge; Velasquez, Hector

    2002-01-01

    Hyperspectral images contain a great amount of information in terms of hundreds of narrowband channels. This should lead to better parameter estimation and to more accurate classifications. However, traditional classification methods based on multispectral analysis fail to work properly on this type of data. High dimensional space poses a difficulty in obtaining accurate parameter estimates and as a consequence this makes unsupervised classification a challenge that requires new techniques. Thus, alternative methods are needed to take advantage of the information provided by the hyperdimensional data. Data fusion is an alternative when dealing with such large data sets in order to improve classification accuracy. Data fusion is an important process in the areas of environmental systems, surveillance, automation, medical imaging, and robotics. The uses of this technique in Remote Sensing have been recently expanding. A relevant application is to adapt the data fusion approaches to be used on hyperspectral imagery taking into consideration the special characteristics of such data. The approach of this paper is to presents a scheme that integrates information from most of the hyperspectral narrow-bands in order to increase the discrimination accuracy in unsupervised classification.

  3. 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. PMID:24727909

  4. Benthic habitat mapping using hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    Vélez-Reyes, Miguel; Goodman, James A.; Castrodad-Carrau, Alexey; Jiménez-Rodriguez, Luis O.; Hunt, Shawn D.; Armstrong, Roy

    2006-09-01

    Benthic habitats are the different bottom environments as defined by distinct physical, geochemical, and biological characteristics. Remote sensing is increasingly being used to map and monitor the complex dynamics associated with estuarine and nearshore benthic habitats. Advantages of remote sensing technology include both the qualitative benefits derived from a visual overview, and more importantly, the quantitative abilities for systematic assessment and monitoring. Advancements in instrument capabilities and analysis methods are continuing to expand the accuracy and level of effectiveness of the resulting data products. Hyperspectral sensors in particular are rapidly emerging as a more complete solution, especially for the analysis of subsurface shallow aquatic systems. The spectral detail offered by hyperspectral instruments facilitates significant improvements in the capacity to differentiate and classify benthic habitats. This paper reviews two techniques for mapping shallow coastal ecosystems that both combine the retrieval of water optical properties with a linear unmixing model to obtain classifications of the seafloor. Example output using AVIRIS hyperspectral imagery of Kaneohe Bay, Hawaii is employed to demonstrate the application potential of the two approaches and compare their respective results.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. Information efficiency in hyperspectral imaging systems

    NASA Astrophysics Data System (ADS)

    Reichenbach, Stephen E.; Cao, Luyin; Narayanan, Ram M.

    2002-07-01

    In this work we develop a method for assessing the information density and efficiency of hyperspectral imaging systems that have spectral bands of nonuniform width. Imaging system designs with spectral bands of nonuniform width can efficiently gather information about a scene by allocating bandwidth among the bands according to their information content. The information efficiency is the ratio of information density to data density and is a function of the scene's spectral radiance, hyperspectral system design, and signal-to-noise ratio. The assessment can be used to produce an efficient system design. For example, one approach to determining the number and width of the spectral bands for an information-efficient design is to begin with a design that has a single band and then to iteratively divide a band into two bands until no further division improves the system's efficiency. Two experiments illustrate this approach, one using a simple mathematical model for the scene spectral-radiance autocorrelation function and the other using the deterministic spectral-radiance autocorrelation function of a hyperspectral image from NASA's Advanced Solid-State Array Spectroradiometer. The approach could be used either to determine a fixed system design or to dynamically control a system with variable-width spectral bands (e.g., using on-board processing in a satellite system).

  11. 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

  12. 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

    2016-01-01

    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

  13. 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.

  14. 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.

  15. 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

    2016-01-01

    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.

  16. Morphology-based fusion method of hyperspectral image

    NASA Astrophysics Data System (ADS)

    Yue, Song; Zhang, Zhijie; Ren, Tingting; Wang, Chensheng; Yu, Hui

    2014-11-01

    Hyperspectral image analysis method is widely used in all kinds of application including agriculture identification and forest investigation and atmospheric pollution monitoring. In order to accurately and steadily analyze hyperspectral image, considering the spectrum and spatial information which is provided by hyperspectral data together is necessary. The hyperspectral image has the characteristics of large amount of wave bands and information. Corresponding to the characteristics of hyperspectral image, a fast image fusion method that can fuse the hyperspectral image with high fidelity is studied and proposed in this paper. First of all, hyperspectral image is preprocessed before the morphological close operation. The close operation is used to extract wave band characteristic to reduce dimensionality of hyperspectral image. The spectral data is smoothed at the same time to avoid the discontinuity of the data by combination of spatial information and spectral information. On this basis, Mean-shift method is adopted to register key frames. Finally, the selected key frames by fused into one fusing image by the pyramid fusion method. The experiment results show that this method can fuse hyper spectral image in high quality. The fused image's attributes is better than the original spectral images comparing to the spectral images and reach the objective of fusion.

  17. Hyperspectral microscopy to identify foodborne bacteria with optimum lighting source

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  18. Online Unmixing of Multitemporal Hyperspectral Images Accounting for Spectral Variability.

    PubMed

    Thouvenin, Pierre-Antoine; Dobigeon, Nicolas; Tourneret, Jean-Yves

    2016-09-01

    Hyperspectral unmixing is aimed at identifying the reference spectral signatures composing a hyperspectral image and their relative abundance fractions in each pixel. In practice, the identified signatures may vary spectrally from an image to another due to varying acquisition conditions, thus inducing possibly significant estimation errors. Against this background, the hyperspectral unmixing of several images acquired over the same area is of considerable interest. Indeed, such an analysis enables the endmembers of the scene to be tracked and the corresponding endmember variability to be characterized. Sequential endmember estimation from a set of hyperspectral images is expected to provide improved performance when compared with methods analyzing the images independently. However, the significant size of the hyperspectral data precludes the use of batch procedures to jointly estimate the mixture parameters of a sequence of hyperspectral images. Provided that each elementary component is present in at least one image of the sequence, we propose to perform an online hyperspectral unmixing accounting for temporal endmember variability. The online hyperspectral unmixing is formulated as a two-stage stochastic program, which can be solved using a stochastic approximation. The performance of the proposed method is evaluated on synthetic and real data. Finally, a comparison with independent unmixing algorithms illustrates the interest of the proposed strategy.

  19. Video-rate visible to LWIR hyperspectral image generation exploitation

    NASA Astrophysics Data System (ADS)

    Dombrowski, Mark S.; Willson, Paul

    1999-10-01

    Hyperspectral imaging is the latest advent in imaging technology, providing the potential to extract information about the objects in a scene that is unavailable to panchromatic imagers. This increased utility, however, comes at the cost of tremendously increased data. The ultimate utility of hyperspectral imagery is in the information that can be gleaned from the spectral dimension, rather than in the hyperspectral imagery itself. To have the broadest range of applications, extraction of this information must occur in real-time. Attempting to produce and exploit complete cubes of hyperspectral imagery at video rates, however, presents unique problems for both the imager and the processor, since data rates are scaled by the number of spectral planes in the cube. MIDIS, the Multi-band Identification and Discrimination Imaging Spectroradiometer, allows both real-time collection and processing of hyperspectral imagery over the range of 0.4 micrometer to 12 micrometer. Presented here are the major design challenges and solutions associated with producing high-speed, high-sensitivity hyperspectral imagers operating in the Vis/NIR, SWIR/MWIR and LWIR, and of the electronics capable of handling data rates up to 160 mega-pixels per second, continuously. Beyond design and performance issues associated with producing and processing hyperspectral imagery at such high speeds, this paper also discusses applications of real-time hyperspectral imaging technology. Example imagery includes such problems as buried mine detection, inspecting surfaces, and countering CCD (camouflage, concealment, and deception).

  20. Online Unmixing of Multitemporal Hyperspectral Images Accounting for Spectral Variability.

    PubMed

    Thouvenin, Pierre-Antoine; Dobigeon, Nicolas; Tourneret, Jean-Yves

    2016-09-01

    Hyperspectral unmixing is aimed at identifying the reference spectral signatures composing a hyperspectral image and their relative abundance fractions in each pixel. In practice, the identified signatures may vary spectrally from an image to another due to varying acquisition conditions, thus inducing possibly significant estimation errors. Against this background, the hyperspectral unmixing of several images acquired over the same area is of considerable interest. Indeed, such an analysis enables the endmembers of the scene to be tracked and the corresponding endmember variability to be characterized. Sequential endmember estimation from a set of hyperspectral images is expected to provide improved performance when compared with methods analyzing the images independently. However, the significant size of the hyperspectral data precludes the use of batch procedures to jointly estimate the mixture parameters of a sequence of hyperspectral images. Provided that each elementary component is present in at least one image of the sequence, we propose to perform an online hyperspectral unmixing accounting for temporal endmember variability. The online hyperspectral unmixing is formulated as a two-stage stochastic program, which can be solved using a stochastic approximation. The performance of the proposed method is evaluated on synthetic and real data. Finally, a comparison with independent unmixing algorithms illustrates the interest of the proposed strategy. PMID:27305679

  1. Hyperspectral Imaging for Defect Detection of Pickling Cucumber

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  2. Online Unmixing of Multitemporal Hyperspectral Images Accounting for Spectral Variability

    NASA Astrophysics Data System (ADS)

    Thouvenin, Pierre-Antoine; Dobigeon, Nicolas; Tourneret, Jean-Yves

    2016-09-01

    Hyperspectral unmixing is aimed at identifying the reference spectral signatures composing an hyperspectral image and their relative abundance fractions in each pixel. In practice, the identified signatures may vary spectrally from an image to another due to varying acquisition conditions, thus inducing possibly significant estimation errors. Against this background, hyperspectral unmixing of several images acquired over the same area is of considerable interest. Indeed, such an analysis enables the endmembers of the scene to be tracked and the corresponding endmember variability to be characterized. Sequential endmember estimation from a set of hyperspectral images is expected to provide improved performance when compared to methods analyzing the images independently. However, the significant size of hyperspectral data precludes the use of batch procedures to jointly estimate the mixture parameters of a sequence of hyperspectral images. Provided that each elementary component is present in at least one image of the sequence, we propose to perform an online hyperspectral unmixing accounting for temporal endmember variability. The online hyperspectral unmixing is formulated as a two-stage stochastic program, which can be solved using a stochastic approximation. The performance of the proposed method is evaluated on synthetic and real data. A comparison with independent unmixing algorithms finally illustrates the interest of the proposed strategy.

  3. 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.

  4. 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

  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. 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.

  7. 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

  8. 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.

  9. Hyperspectral Imaging for Cancer Surgical Margin Delineation: Registration of Hyperspectral and Histological Images.

    PubMed

    Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

    2014-03-12

    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

  10. Monitoring Earth's Climate with Shortwave Hyperspectral Reflectance

    NASA Astrophysics Data System (ADS)

    Pilewskie, Peter

    The Sun provides nearly all the energy that fuels the dynamical, chemical, and biological processes in the Earth system. Absorbed solar radiation, the difference between incoming and reflected sunlight, defines Earth’s equilibrium temperature and, along with the emitted infrared radiation, determines the climate state of the planet. The transfer of solar radiation through the atmosphere is modulated by wavelength-specific interactions that are unique for given surface types and the intervening atmospheric gases and condensed species. Reflected radiation that exits the Earth’s atmosphere carries with it the complex fingerprint of the Earth system state. How this signal varies temporally, spatially, and spectrally is a measure of those processes within the Earth system that affect climate change. Despite its importance to the basic energy balance between Earth and the solar-terrestrial environment in which it resides, a precise record of the nature of reflected solar spectral radiation over all climate-relevant time scales remains elusive. A primary goal of a climate observing system is to obtain climate benchmark data records with sufficient accuracy for identifying climate variability on decadal time scales and longer, and with sufficient information content to attribute change to underlying causes. Until recently, detecting climate change signatures in reflected solar radiance has been hindered by instrument accuracy and stability, insufficient spectral coverage and resolution, and inherent sampling limitations from low-Earth orbit observations. This talk will discuss the challenges to monitoring the shortwave energy budget from space. I will present new studies on methods to separate the various contributions in the top-of-atmosphere outgoing shortwave radiance using existing satellite (SCIAMACHY) data and explore methods to enhance trend detection in hyperspectral reflectance time series. Finally, I look ahead to the requirements for a climate observing

  11. 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.

  12. Performance and application of real-time hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Dombrowski, Mark S.; Willson, Paul D.; LaBaw, Clayton C.

    1998-10-01

    Hyperspectral imaging is the latest advent in imaging technology, providing the potential to extract information about the objects in a scene that is unavailable to panchromatic imagers. This increased utility, however, comes at the cost of tremendously increased data. The ultimate utility of hyperspectral imagery is in the information that can be gleaned from the spectral dimension, rather than in the hyperspectral imagery itself. To have the broadest range of applications, extraction of this information must occur in real-time. Attempting to produce and exploit complete cubes of hyperspectral imagery at video rates, however, present unique problems for both the imager and the processor, since data rates are scaled by the number of spectral planes in the cube. MIDIS, the Multi-band Identification and Discrimination Imaging Spectroradiometer, allows both real-time here are the major design innovations associated with producing high-speed, high-sensitivity hyperspectral imagers operating in the SWIR and LWIR, and of the electronics capable of handling data rates up to 160 megapixels per second, continuously. Discussion of real-time algorithms capable of exploiting the spectral dimension of the imagery is also included. Beyond design and performance issues associated with producing and processing hyperspectral imagery at such high speeds, this paper also discusses applications of real-time hyperspectral imaging technology. Example imagery includes such problems as detecting counterfeit money, inspecting surfaces, and countering CCD.

  13. Dimensionality reduction of hyperspectral images using kernel ICA

    NASA Astrophysics Data System (ADS)

    Khan, Asif; Kim, Intaek; Kong, Seong G.

    2009-05-01

    Computational burden due to high dimensionality of Hyperspectral images is an obstacle in efficient analysis and processing of Hyperspectral images. In this paper, we use Kernel Independent Component Analysis (KICA) for dimensionality reduction of Hyperspectraql images based on band selection. Commonly used ICA and PCA based dimensionality reduction methods do not consider non linear transformations and assumes that data has non-gaussian distribution. When the relation of source signals (pure materials) and observed Hyperspectral images is nonlinear then these methods drop a lot of information during dimensionality reduction process. Recent research shows that kernel-based methods are effective in nonlinear transformations. KICA is robust technique of blind source separation and can even work on near-gaussina data. We use Kernel Independent Component Analysis (KICA) for the selection of minimum number of bands that contain maximum information for detection in Hyperspectral images. The reduction of bands is basd on the evaluation of weight matrix generated by KICA. From the selected lower number of bands, we generate a new spectral image with reduced dimension and use it for hyperspectral image analysis. We use this technique as preprocessing step in detection and classification of poultry skin tumors. The hyperspectral iamge samples of chicken tumors used contain 65 spectral bands of fluorescence in the visible region of the spectrum. Experimental results show that KICA based band selection has high accuracy than that of fastICA based band selection for dimensionality reduction and analysis for Hyperspectral images.

  14. 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.

  15. 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

  16. Small satellite's role in future hyperspectral Earth observation missions

    NASA Astrophysics Data System (ADS)

    Guelman, M.; Ortenberg, F.

    2009-06-01

    Along with various advanced satellite onboard sensors, an important place in the near future will belong to hyperspectral instruments, considered as suitable for different scientific, commercial and military missions. As was demonstrated over the last decade, hyperspectral Earth observations can be provided by small satellites at considerably lower costs and shorter timescales, even though with some limitations on resolution, spectral response, and data rate. In this work the requirements on small satellites with imaging hyperspectral sensors are studied. Physical and technological limitations of hyperspectral imagers are considered. A mathematical model of a small satellite with a hyperspectral imaging spectrometer system is developed. The ability of the small satellites of different subclasses (micro- and mini-) to obtain hyperspectral images with a given resolution and quality is examined. As a result of the feasibility analysis, the constraints on the main technical parameters of hyperspectral instruments suitable for application onboard the small satellites are outlined. Comparison of the data for designed and planned instruments with simulation results validates the presented approach to the estimation of the small satellite size limitations. Presented analysis was carried out for sensors with conventional filled aperture optics.

  17. Hyperspectral confocal fluorescence imaging of cells

    NASA Astrophysics Data System (ADS)

    Haaland, David M.; Jones, Howland D. T.; Sinclair, Michael B.; Carson, Bryan; Branda, Catherine; Poschet, Jens F.; Rebeil, Roberto; Tian, Bing; Liu, Ping; Brasier, Allan R.

    2007-09-01

    Confocal fluorescence imaging of biological systems is an important method by which researchers can investigate molecular processes occurring in live cells. We have developed a new 3D hyperspectral confocal fluorescence microscope that can further enhance the usefulness of fluorescence microscopy in studying biological systems. The new microscope can increase the information content obtained from the image since, at each voxel, the microscope records 512 wavelengths from the emission spectrum (490 to 800 nm) while providing optical sectioning of samples with diffraction-limited spatial resolution. When coupled with multivariate curve resolution (MCR) analyses, the microscope can resolve multiple spatially and spectrally overlapped emission components, thereby greatly increasing the number of fluorescent labels, relative to most commercial microscopes, that can be monitored simultaneously. The MCR algorithm allows the "discovery" of all emitting sources and estimation of their relative concentrations without cross talk, including those emission sources that might not have been expected in the imaged cells. In this work, we have used the new microscope to obtain time-resolved hyperspectral images of cellular processes. We have quantitatively monitored the translocation of the GFP-labeled RelA protein (without interference from autofluorescence) into and out of the nucleus of live HeLa cells in response to continuous stimulation by the cytokine, TNFα. These studies have been extended to imaging live mouse macrophage cells with YFP-labeled RelA and GFP-labeled IRF3 protein. Hyperspectral imaging coupled with MCR analysis makes possible, for the first time, quantitative analysis of GFP, YFP, and autofluorescence without concern for cross-talk between emission sources. The significant power and quantitative capabilities of the new hyperspectral imaging system are further demonstrated with the imaging of a simple fluorescence dye (SYTO 13) traditionally used to stain the

  18. 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.

  19. A grid service-based tool for hyperspectral imaging analysis

    NASA Astrophysics Data System (ADS)

    Carvajal, Carmen L.; Lugo, Wilfredo; Rivera, Wilson; Sanabria, John

    2005-06-01

    This paper outlines the design and implementation of Grid-HSI, a Service Oriented Architecture-based Grid application to enable hyperspectral imaging analysis. Grid-HSI provides users with a transparent interface to access computational resources and perform remotely hyperspectral imaging analysis through a set of Grid services. Grid-HSI is composed by a Portal Grid Interface, a Data Broker and a set of specialized Grid services. Grid based applications, contrary to other clientserver approaches, provide the capabilities of persistence and potential transient process on the web. Our experimental results on Grid-HSI show the suitability of the prototype system to perform efficiently hyperspectral imaging analysis.

  20. 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.

  1. 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

  2. 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.

  3. Dried fruits quality assessment by hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Serranti, Silvia; Gargiulo, Aldo; Bonifazi, Giuseppe

    2012-05-01

    Dried fruits products present different market values according to their quality. Such a quality is usually quantified in terms of freshness of the products, as well as presence of contaminants (pieces of shell, husk, and small stones), defects, mould and decays. The combination of these parameters, in terms of relative presence, represent a fundamental set of attributes conditioning dried fruits humans-senses-detectable-attributes (visual appearance, organolectic properties, etc.) and their overall quality in terms of marketable products. Sorting-selection strategies exist but sometimes they fail when a higher degree of detection is required especially if addressed to discriminate between dried fruits of relatively small dimensions and when aiming to perform an "early detection" of pathogen agents responsible of future moulds and decays development. Surface characteristics of dried fruits can be investigated by hyperspectral imaging (HSI). In this paper, specific and "ad hoc" applications addressed to propose quality detection logics, adopting a hyperspectral imaging (HSI) based approach, are described, compared and critically evaluated. Reflectance spectra of selected dried fruits (hazelnuts) of different quality and characterized by the presence of different contaminants and defects have been acquired by a laboratory device equipped with two HSI systems working in two different spectral ranges: visible-near infrared field (400-1000 nm) and near infrared field (1000-1700 nm). The spectra have been processed and results evaluated adopting both a simple and fast wavelength band ratio approach and a more sophisticated classification logic based on principal component (PCA) analysis.

  4. 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 Eastern Shore and is owned by the DuPont Corporation.

  5. Separability between pedestrians in hyperspectral imagery.

    PubMed

    Herweg, Jared; Kerekes, John; Eismann, Michael

    2013-02-20

    The popularity of hyperspectral imaging (HSI) in remote sensing continues to lead to it being adapted in novel ways to overcome challenging imaging problems. This paper reports on research efforts exploring the phenomenology of using HSI as an aid in detecting and tracking human pedestrians. An assessment of the likelihood of distinguishing between pedestrians based on the measured spectral reflectance of observable materials and the presence of noise is presented. The assessments included looking at the spectral separation between pedestrian material subregions using different spectral-reflectance regions within the full range (450-2500 nm), as well as when the spectral content of the pedestrian subregions are combined. In addition to the pedestrian spectral-reflectance data analysis, the separability of pedestrian subregions in remotely sensed hyperspectral images was assessed using a unique data set garnered as part of this work. Results indicated that skin was the least distinguishable material between pedestrians using the spectral Euclidean distance metric. The clothing, especially the shirt, offered the most salient feature for distinguishing the pedestrian. Additionally, significant spectral separability performance is realized when combining the reflectance information of two or more subregions.

  6. Hyperspectral imaging applied to forensic medicine

    NASA Astrophysics Data System (ADS)

    Malkoff, Donald B.; Oliver, William R.

    2000-03-01

    Remote sensing techniques now include the use of hyperspectral infrared imaging sensors covering the mid-and- long wave regions of the spectrum. They have found use in military surveillance applications due to their capability for detection and classification of a large variety of both naturally occurring and man-made substances. The images they produce reveal the spatial distributions of spectral patterns that reflect differences in material temperature, texture, and composition. A program is proposed for demonstrating proof-of-concept in using a portable sensor of this type for crime scene investigations. It is anticipated to be useful in discovering and documenting the affects of trauma and/or naturally occurring illnesses, as well as detecting blood spills, tire patterns, toxic chemicals, skin injection sites, blunt traumas to the body, fluid accumulations, congenital biochemical defects, and a host of other conditions and diseases. This approach can significantly enhance capabilities for determining the circumstances of death. Potential users include law enforcement organizations (police, FBI, CIA), medical examiners, hospitals/emergency rooms, and medical laboratories. Many of the image analysis algorithms already in place for hyperspectral remote sensing and crime scene investigations can be applied to the interpretation of data obtained in this program.

  7. SWIR hyperspectral imaging detector for surface residues

    NASA Astrophysics Data System (ADS)

    Nelson, Matthew P.; Mangold, Paul; Gomer, Nathaniel; Klueva, Oksana; Treado, Patrick

    2013-05-01

    ChemImage has developed a SWIR Hyperspectral Imaging (HSI) sensor which uses hyperspectral imaging for wide area surveillance and standoff detection of surface residues. Existing detection technologies often require close proximity for sensing or detecting, endangering operators and costly equipment. Furthermore, most of the existing sensors do not support autonomous, real-time, mobile platform based detection of threats. The SWIR HSI sensor provides real-time standoff detection of surface residues. The SWIR HSI sensor provides wide area surveillance and HSI capability enabled by liquid crystal tunable filter technology. Easy-to-use detection software with a simple, intuitive user interface produces automated alarms and real-time display of threat and type. The system has potential to be used for the detection of variety of threats including chemicals and illicit drug substances and allows for easy updates in the field for detection of new hazardous materials. SWIR HSI technology could be used by law enforcement for standoff screening of suspicious locations and vehicles in pursuit of illegal labs or combat engineers to support route-clearance applications- ultimately to save the lives of soldiers and civilians. In this paper, results from a SWIR HSI sensor, which include detection of various materials in bulk form, as well as residue amounts on vehicles, people and other surfaces, will be discussed.

  8. 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.

  9. Pork grade evaluation using hyperspectral imaging techniques

    NASA Astrophysics Data System (ADS)

    Zhou, Rui; Cai, Bo; Wang, Shoubing; Ji, Huihua; Chen, Huacai

    2011-11-01

    The method to evaluate the grade of the pork based on hyperspectral imaging techniques was studied. Principal component analysis (PCA) was performed on the hyperspectral image data to extract the principal components which were used as the inputs of the evaluation model. By comparing the different discriminating rates in the calibration set and the validation set under different information, the choice of the components can be optimized. Experimental results showed that the classification evaluation model was the optimal when the principal of component (PC) of spectra was 3, while the corresponding discriminating rate was 89.1% in the calibration set and 84.9% in the validation set. It was also good when the PC of images was 9, while the corresponding discriminating rate was 97.2% in the calibration set and 91.1% in the validation set. The evaluation model based on both information of spectra and images was built, in which the corresponding PCs of spectra and images were used as the inputs. This model performed very well in grade classification evaluation, and the discriminating rates of calibration set and validation set were 99.5% and 92.7%, respectively, which were better than the two evaluation models based on single information of spectra or images.

  10. 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.

  11. Hyper-spectral scanner design and analysis

    SciTech Connect

    Canavan, G.; Moses, J.; Smith, R.

    1996-06-01

    This is the final report of a two-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). An earlier project produced rough designs for key components of a compact hyper-spectral sensor for environmental and ecological measurements. Such sensors could be deployed on unmanned vehicles, aircraft, or satellites for measurements important to agriculture, the environment, and ecologies. This represents an important advance in remote sensing. Motorola invited us to propose an add-on, proof-of-principle sensor for their Comet satellite, whose primary mission is to demonstrate a channel of the IRIDIUM satellite communications system. Our project converted the preliminary designs from the previous effort into final designs for the telescope, camera, computer and interfaces that constitute the hyper-spectral scanning sensor. The work concentrated on design, fabrication, preliminary integration, and testing of the electronic circuit boards for the computer, data compression board, and interface board for the camera-computer and computer-modulator (transmitter) interfaces.

  12. Onboard Image Processing System for Hyperspectral Sensor

    PubMed Central

    Hihara, Hiroki; Moritani, Kotaro; Inoue, Masao; Hoshi, Yoshihiro; Iwasaki, Akira; Takada, Jun; Inada, Hitomi; Suzuki, Makoto; Seki, Taeko; Ichikawa, Satoshi; Tanii, Jun

    2015-01-01

    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. PMID:26404281

  13. [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.

  14. Separability between pedestrians in hyperspectral imagery.

    PubMed

    Herweg, Jared; Kerekes, John; Eismann, Michael

    2013-02-20

    The popularity of hyperspectral imaging (HSI) in remote sensing continues to lead to it being adapted in novel ways to overcome challenging imaging problems. This paper reports on research efforts exploring the phenomenology of using HSI as an aid in detecting and tracking human pedestrians. An assessment of the likelihood of distinguishing between pedestrians based on the measured spectral reflectance of observable materials and the presence of noise is presented. The assessments included looking at the spectral separation between pedestrian material subregions using different spectral-reflectance regions within the full range (450-2500 nm), as well as when the spectral content of the pedestrian subregions are combined. In addition to the pedestrian spectral-reflectance data analysis, the separability of pedestrian subregions in remotely sensed hyperspectral images was assessed using a unique data set garnered as part of this work. Results indicated that skin was the least distinguishable material between pedestrians using the spectral Euclidean distance metric. The clothing, especially the shirt, offered the most salient feature for distinguishing the pedestrian. Additionally, significant spectral separability performance is realized when combining the reflectance information of two or more subregions. PMID:23435007

  15. APEX - the Hyperspectral ESA Airborne Prism Experiment

    PubMed Central

    Itten, Klaus I.; Dell'Endice, Francesco; Hueni, Andreas; Kneubühler, Mathias; Schläpfer, Daniel; Odermatt, Daniel; Seidel, Felix; Huber, Silvia; Schopfer, Jürg; Kellenberger, Tobias; Bühler, Yves; D'Odorico, Petra; Nieke, Jens; Alberti, Edoardo; Meuleman, Koen

    2008-01-01

    The airborne ESA-APEX (Airborne Prism Experiment) hyperspectral mission simulator is described with its distinct specifications to provide high quality remote sensing data. The concept of an automatic calibration, performed in the Calibration Home Base (CHB) by using the Control Test Master (CTM), the In-Flight Calibration facility (IFC), quality flagging (QF) and specific processing in a dedicated Processing and Archiving Facility (PAF), and vicarious calibration experiments are presented. A preview on major applications and the corresponding development efforts to provide scientific data products up to level 2/3 to the user is presented for limnology, vegetation, aerosols, general classification routines and rapid mapping tasks. BRDF (Bidirectional Reflectance Distribution Function) issues are discussed and the spectral database SPECCHIO (Spectral Input/Output) introduced. The optical performance as well as the dedicated software utilities make APEX a state-of-the-art hyperspectral sensor, capable of (a) satisfying the needs of several research communities and (b) helping the understanding of the Earth's complex mechanisms.

  16. Detection of explosives by differential hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Dubroca, Thierry; Brown, Gregory; Hummel, Rolf E.

    2014-02-01

    Our team has pioneered an explosives detection technique based on hyperspectral imaging of surfaces. Briefly, differential reflectometry (DR) shines ultraviolet (UV) and blue light on two close-by areas on a surface (for example, a piece of luggage on a moving conveyer belt). Upon reflection, the light is collected with a spectrometer combined with a charge coupled device (CCD) camera. A computer processes the data and produces in turn differential reflection spectra taken from these two adjacent areas on the surface. This differential technique is highly sensitive and provides spectroscopic data of materials, particularly of explosives. As an example, 2,4,6-trinitrotoluene displays strong and distinct features in differential reflectograms near 420 and 250 nm, that is, in the near-UV region. Similar, but distinctly different features are observed for other explosives. Finally, a custom algorithm classifies the collected spectral data and outputs an acoustic signal if a threat is detected. This paper presents the complete DR hyperspectral imager which we have designed and built from the hardware to the software, complete with an analysis of the device specifications.

  17. 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.

  18. 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

    2015-01-01

    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. PMID:26404281

  19. Hyperspectral Technique for Detecting Soil Parameters

    NASA Astrophysics Data System (ADS)

    Garfagnoli, F.; Ciampalini, A.; Moretti, S.; Chiarantini, L.

    2011-12-01

    In satellite and airborne remote sensing, hyperspectral technique has become a very powerful tool, due to the possibility of rapidly realizing chemical/mineralogical maps of the studied areas. Many studies are trying to customize the algorithms to identify several geo-physical soil properties. The specific objective of this study is to investigate those soil characteristics, such as clay mineral content, influencing degradation processes (soil erosion and shallow landslides), by means of correlation analysis, in order to examine the possibility of predicting the selected property using high-resolution reflectance spectra and images. The study area is located in the Mugello basin, about 30 km north of Firenze (Tuscany, Italy). Agriculturally suitable terrains are assigned mainly to annual crops, marginally to olive groves, vineyards and orchards. Soils mostly belong to Regosols and Cambisols orders. An ASD FieldSpec spectroradiometer was used to obtain reflectance spectra from about 80 dried, crushed and sieved samples under controlled laboratory conditions. Samples were collected simultaneously with the flight of SIM.GA hyperspectral camera from Selex Galileo, over an area of about 5 km2 and their positions were recorded with a differential GPS. The quantitative determination of clay minerals content was performed by means of XRD and Rietveld refinement. Different chemometric techniques were preliminarily tested to correlate mineralogical records with reflectance data. A one component partial least squares regression model yielded a preliminary R2 value of 0.65. A slightly better result was achieved by plotting the absorption peak depth at 2210 versus total clay content (band-depth analysis). The complete SIM.GA hyperspectral geocoded row dataset, with an approximate pixel resolution of 0.6 m (VNIR) and 1.2 m (SWIR), was firstly transformed into at sensor radiance values, by applying calibration coefficients and parameters from laboratory measurements to non

  20. FAPEC-based lossless and lossy hyperspectral data compression

    NASA Astrophysics Data System (ADS)

    Portell, Jordi; Artigues, Gabriel; Iudica, Riccardo; García-Berro, Enrique

    2015-10-01

    Data compression is essential for remote sensing based on hyperspectral sensors owing to the increasing amount of data generated by modern instrumentation. CCSDS issued the 123.0 standard for lossless hyperspectral compression, and a new lossy hyperspectral compression recommendation is being prepared. We have developed multispectral and hyperspectral pre-processing stages for FAPEC, a data compression algorithm based on an entropy coder. We can select a prediction-based lossless stage that offers excellent results and speed. Alternatively, a DWT-based lossless and lossy stage can be selected, which offers excellent results yet obviously requiring more compression time. Finally, a lossless stage based on our HPA algorithm can also be selected, only lossless for now but with the lossy option in preparation. Here we present the overall design of these data compression systems and the results obtained on a variety of real data, including ratios, speed and quality.

  1. Unsupervised hyperspectral image analysis using independent component analysis (ICA)

    SciTech Connect

    S. S. Chiang; I. W. Ginsberg

    2000-06-30

    In this paper, an ICA-based approach is proposed for hyperspectral image analysis. It can be viewed as a random version of the commonly used linear spectral mixture analysis, in which the abundance fractions in a linear mixture model are considered to be unknown independent signal sources. It does not require the full rank of the separating matrix or orthogonality as most ICA methods do. More importantly, the learning algorithm is designed based on the independency of the material abundance vector rather than the independency of the separating matrix generally used to constrain the standard ICA. As a result, the designed learning algorithm is able to converge to non-orthogonal independent components. This is particularly useful in hyperspectral image analysis since many materials extracted from a hyperspectral image may have similar spectral signatures and may not be orthogonal. The AVIRIS experiments have demonstrated that the proposed ICA provides an effective unsupervised technique for hyperspectral image classification.

  2. Hyperspectral stimulated emission depletion microscopy and methods of use thereof

    DOEpatents

    Timlin, Jerilyn A; Aaron, Jesse S

    2014-04-01

    A hyperspectral stimulated emission depletion ("STED") microscope system for high-resolution imaging of samples labeled with multiple fluorophores (e.g., two to ten fluorophores). The hyperspectral STED microscope includes a light source, optical systems configured for generating an excitation light beam and a depletion light beam, optical systems configured for focusing the excitation and depletion light beams on a sample, and systems for collecting and processing data generated by interaction of the excitation and depletion light beams with the sample. Hyperspectral STED data may be analyzed using multivariate curve resolution analysis techniques to deconvolute emission from the multiple fluorophores. The hyperspectral STED microscope described herein can be used for multi-color, subdiffraction imaging of samples (e.g., materials and biological materials) and for analyzing a tissue by Forster Resonance Energy Transfer ("FRET").

  3. Dental caries imaging using hyperspectral stimulated Raman scattering microscopy

    NASA Astrophysics Data System (ADS)

    Wang, Zi; Zheng, Wei; Jian, Lin; Huang, Zhiwei

    2016-03-01

    We report the development of a polarization-resolved hyperspectral stimulated Raman scattering (SRS) imaging technique based on a picosecond (ps) laser-pumped optical parametric oscillator system for label-free imaging of dental caries. In our imaging system, hyperspectral SRS images (512×512 pixels) in both fingerprint region (800-1800 cm-1) and high-wavenumber region (2800-3600 cm-1) are acquired in minutes by scanning the wavelength of OPO output, which is a thousand times faster than conventional confocal micro Raman imaging. SRS spectra variations from normal enamel to caries obtained from the hyperspectral SRS images show the loss of phosphate and carbonate in the carious region. While polarization-resolved SRS images at 959 cm-1 demonstrate that the caries has higher depolarization ratio. Our results demonstrate that the polarization resolved-hyperspectral SRS imaging technique developed allows for rapid identification of the biochemical and structural changes of dental caries.

  4. System and method for progressive band selection for hyperspectral images

    NASA Technical Reports Server (NTRS)

    Fisher, Kevin (Inventor)

    2013-01-01

    Disclosed herein are systems, methods, and non-transitory computer-readable storage media for progressive band selection for hyperspectral images. A system having module configured to control a processor to practice the method calculates a virtual dimensionality of a hyperspectral image having multiple bands to determine a quantity Q of how many bands are needed for a threshold level of information, ranks each band based on a statistical measure, selects Q bands from the multiple bands to generate a subset of bands based on the virtual dimensionality, and generates a reduced image based on the subset of bands. This approach can create reduced datasets of full hyperspectral images tailored for individual applications. The system uses a metric specific to a target application to rank the image bands, and then selects the most useful bands. The number of bands selected can be specified manually or calculated from the hyperspectral image's virtual dimensionality.

  5. Black Beauty's Rainbow: Hyperspectral Imaging of Northwest Africa 7034

    NASA Astrophysics Data System (ADS)

    Cannon, K. M.; Mustard, J. F.; Agee, C. B.; Wilson, J. H.; Greenberger, R. N.

    2014-07-01

    Hyperspectral imaging is used to characterize the first basaltic breccia from Mars, Northwest Africa 7034. Initial results show the spectral character of NWA 7034 is unlike other SNC meteorites and may be more representative of average martian crust.

  6. Hyperspectral image classification for mapping agricultural tillage practices

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An efficient classification framework for mapping agricultural tillage practice using hyperspectral remote sensing imagery is proposed, which has the potential to be implemented practically to provide rapid, accurate, and objective surveying data for precision agricultural management and appraisal f...

  7. High spectral resolution airborne short wave infrared hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Wei, Liqing; Yuan, Liyin; Wang, Yueming; Zhuang, Xiaoqiong

    2016-05-01

    Short Wave InfraRed(SWIR) spectral imager is good at detecting difference between materials and penetrating fog and mist. High spectral resolution SWIR hyperspectral imager plays a key role in developing earth observing technology. Hyperspectral data cube can help band selections that is very important for multispectral imager design. Up to now, the spectral resolution of many SWIR hyperspectral imagers is about 10nm. A high sensitivity airborne SWIR hyperspectral imager with narrower spectral band will be presented. The system consists of TMA telescope, slit, spectrometer with planar blazed grating and high sensitivity MCT FPA. The spectral sampling interval is about 3nm. The IFOV is 0.5mrad. To eliminate the influence of the thermal background, a cold shield is designed in the dewar. The pixel number of spatial dimension is 640. Performance measurement in laboratory and image analysis for flight test will also be presented.

  8. Physical Retrieval of Surface Emissivity Spectrum from Hyperspectral Infrared Radiances

    NASA Technical Reports Server (NTRS)

    Li, Jun; Weisz, Elisabeth; Zhou, Daniel K.

    2007-01-01

    Retrieval of temperature, moisture profiles and surface skin temperature from hyperspectral infrared (IR) radiances requires spectral information about the surface emissivity. Using constant or inaccurate surface emissivities typically results in large retrieval errors, particularly over semi-arid or arid areas where the variation in emissivity spectrum is large both spectrally and spatially. In this study, a physically based algorithm has been developed to retrieve a hyperspectral IR emissivity spectrum simultaneously with the temperature and moisture profiles, as well as the surface skin temperature. To make the solution stable and efficient, the hyperspectral emissivity spectrum is represented by eigenvectors, derived from the laboratory measured hyperspectral emissivity database, in the retrieval process. Experience with AIRS (Atmospheric InfraRed Sounder) radiances shows that a simultaneous retrieval of the emissivity spectrum and the sounding improves the surface skin temperature as well as temperature and moisture profiles, particularly in the near surface layer.

  9. Hyperspectral characterization of fluorophore diffusion in human skin using a sCMOS based hyperspectral camera

    NASA Astrophysics Data System (ADS)

    Hernandez-Palacios, J.; Haug, I. J.; Grimstad, Ø.; Randeberg, L. L.

    2011-07-01

    Hyperspectral fluorescence imaging is a modality combining high spatial and spectral resolution with increased sensitivity for low photon counts. The main objective of the current study was to investigate if this technique is a suitable tool for characterization of diffusion properties in human skin. This was done by imaging fluorescence from Alexa 488 in ex vivo human skin samples using an sCMOS based hyperspectral camera. Pre-treatment with acetone, DMSO and mechanical micro-needling of the stratum corneum created variation in epidermal permeability between the measured samples. Selected samples were also stained using fluorescence labelled biopolymers. The effect of fluorescence enhancers on transdermal diffusion could be documented from the collected data. Acetone was found to have an enhancing effect on the transport, and the results indicate that the biopolymers might have a similar effect, The enhancement from these compounds were not as prominent as the effect of mechanical penetration of the sample using a micro-needling device. Hyperspectral fluorescence imaging has thus been proven to be an interesting tool for characterization of fluorophore diffusion in ex vivo skin samples. Further work will include repetition of the measurements in a shorter time scale and mathematical modeling of the diffusion process to determine the diffusivity in skin for the compounds in question.

  10. Hyperspectral shooting apparatus for the Resurs-P spacecraft

    NASA Astrophysics Data System (ADS)

    Arkhipov, S. A.; Baklanov, A. I.; Linko, V. M.

    2014-12-01

    A hyperspectral shooting apparatus (HSA) was installed on the Resurs-P spacecraft. The HSA receives hyperspectral Earth's remote sounding data with a spatial resolution of 30 m in 130 spectral channels in field-of-view of 30 km. The basic specifications of HSA, structure, design, optical scheme, features of photogrammetric and radiometric calibration of HSA, and functions and structures of the ground-based software for apparatus operation are described.

  11. Design and Analysis of a Hyperspectral Microwave Receiver Subsystem

    NASA Technical Reports Server (NTRS)

    Blackwell, W.; Galbraith, C.; Hancock, T.; Leslie, R.; Osaretin, I.; Shields, M.; Racette, P.; Hillard, L.

    2012-01-01

    Hyperspectral microwave (HM) sounding has been proposed to achieve unprecedented performance. HM operation is achieved using multiple banks of RF spectrometers with large aggregate bandwidth. A principal challenge is Size/Weight/Power scaling. Objectives of this work: 1) Demonstrate ultra-compact (100 cm3) 52-channel IF processor (enabler); 2) Demonstrate a hyperspectral microwave receiver subsystem; and 3) Deliver a flight-ready system to validate HM sounding.

  12. Development of practical thermal infrared hyperspectral imaging system

    NASA Astrophysics Data System (ADS)

    Wang, Jianyu; Li, Chunlai; Lv, Gang; Yuan, Liyin; Liu, Enguang; Jin, Jian; Ji, Hongzhen

    2014-11-01

    As an optical remote sensing equipment, the thermal infrared hyperspectral imager operates in the thermal infrared spectral band and acquires about 180 wavebands in range of 8.0~12.5μm. The field of view of this imager is 13° and the spatial resolution is better than 1mrad. Its noise equivalent temperature difference (NETD) is less than 0.2K@300K(average). 1 The influence of background radiation of the thermal infrared hyperspectral imager,and a simulation model of simplified background radiation is builded. 2 The design and implementationof the Cryogenic Optics. 3 Thermal infrared focal plane array (FPA) and special dewar component for the thermal infrared hyperspectral imager. 4 Parts of test results of the thermal infrared hyperspectral imager.The hyperspectral imaging system is China's first success in developing this type of instrument, whose flight validation experiments have already been embarked on. The thermal infrared hyperspectral data acquired will play an important role in fields such as geological exploration and air pollutant identification.

  13. Hyperspectral imaging for safety inspection of food and agricultural products

    NASA Astrophysics Data System (ADS)

    Lu, Renfu; Chen, Yud-Ren

    1999-01-01

    Development of effective food inspection systems is critical in successful implementation of the hazard analysis and critical control points (HACCP) program. Hyperspectral imaging or imaging spectroscopy, which combines techniques of imaging and spectroscopy to acquire spatial and spectral information simultaneously, has great potential in food quality and safety inspection. This paper reviewed the basic principle and features of hyperspectral imaging and its hardware and software implementation. The potential areas of application for hyperspectral imaging in food quality and safety inspection were identified and its limitations were discussed. A hyperspectral imaging system developed for research in food quality and safety inspection was described. Experiments were performed to acquire hyperspectral images from four classes of poultry carcasses: normal, cadaver, septicemia, and tumor. Noticeable differences in the spectra of the relative reflectance and its second difference in the wavelengths between 430 nm and 900 nm were observed between wholesome and unwholesome carcasses. Differences among the three classes of unwholesome carcasses were also observed from their respective spectra. These results showed that hyperspectral imaging can be an effective tool for safety inspection of poultry carcasses.

  14. Supercontinuum-source-based facility for evaluation of hyperspectral imagers

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Yu; Yamada, Yoshiro; Ishii, Juntaro

    2013-10-01

    The next Japanese earth observing hyperspectral/multispectral imager mission, the HISUI (Hyper-spectral Imager SUIte) mission, is currently underway. In order to guarantee the hyperspectral images with a high spatial and wavelength resolution, it is necessary to evaluate the difference of the spectral sensitivities among the detector devices arrayed twodimensionally and correct spectral and spatial misregistrations and the effect of stray light. Since there are tens of thousands of detectors in the two-dimensional-array sensor, they have to be evaluated in parallel, instead of point by point, with the special technique for hyperspectral imagers. Hence, the new calibration system which has high radiance with the spatial uniformity and widely tunable wavelength range is required instead of conventional lamp systems which have poor power to calibrate arrayed devices at once. In this presentation, a supercontinuum-source-based system for calibration of hyperspectral imagers and its preliminary performance are described. Supercontinuum light is white light with continuous and broad spectra, which is generated by nonlinear optical effects of ultrashort pulse lasers in photonic crystal fibers. Using the system, the relative spectral responsivity and spectral misregistration of the hyperspectral imager, which is consist of a polychromator and twodimensionally arrayed CCD, are measured.

  15. Sofradir SWIR hyperspectral detectors for space applications

    NASA Astrophysics Data System (ADS)

    Nowicki-Bringuier, Yoanna-Reine; Chorier, Philippe

    2009-09-01

    The field of SWIR detectors for space applications is strongly growing those last years, mainly because of the increasing need for environmental missions in the SWIR detection range. For now more than 10 years, Sofradir is involved in that field, developing and improving its SWIR detectors technology, leading to a mature technology that enable to address most of missions needs in term of performances, but also with respect to hard environmental constraints. SWIR detection range at Sofradir has been qualified for space applications thanks to various programs already run (APEX or Bepi-Colombo programs) or currently running (Sentinel 2, PRISMA mission). For Sentinel 2, a 1280x3 with a 15μm pitch in the SWIR range (CTIA) has been developed and is currently being validated. 1000x256 or 500x256 arrays 30 μm pitch (called Saturn or Neptune detectors) have already been validated in terms of irradiation behavior, thermal cycling, and ageing. Specific package designs have been validated in terms of high levels of shocks and vibrations. In particular, for both Sentinel 2 and PRISMA programs, Sofradir has developed reliable packaging compatible with passive cooling. Recently, for PRISMA mission, Sofradir is extending its VISible to Short wave Infra-Red technology, called VISIR, to 1000x256 hyperspectral arrays. This technology has the huge advantage to enable detection in both visible and short wave detection range (0.4μm up to 2.5μm), thus limiting the number of needed channels for hyperspectral applications but also outshining the classical limitation of Silicon Visible detectors, for which the sensitivity is dramatically dropping above 0.9 μm. In this paper, we will focus on hyperspectral detectors available at Sofradir. Main general performances will be first described, with emphasize on the VISIR technology that has been recently developed and which enable to cover simultaneously the Visible and SWIR ranges [0.4-2.5μm] with a single detector. Then some complete

  16. A hyperspectral imaging prototype for online quality evaluation of pickling cucumbers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A hyperspectral imaging prototype was developed for online evaluation of external and internal quality of pickling cucumbers. The prototype had several new, unique features including simultaneous reflectance and transmittance imaging and inline, real time calibration of hyperspectral images of each ...

  17. [Advances in researches on hyperspectral remote sensing forestry information-extracting technology].

    PubMed

    Wu, Jian; Peng, Dao-Li

    2011-09-01

    The hyperspectral remote sensing technology has become one of the leading technologies in forestry remote sensing domain. In the present review paper, the advances in researches on hyperspectral remote sensing technology in forestry information extraction both at home and abroad were reviewed, and the five main research aspects including the hyperspectral classification and recognition of forest tree species, the hyperspectral inversion and extraction of forest ecological physical parameters, the hyperspectral monitoring and diagnosis of forest nutrient element, the forest crown density information extraction and the hyperspectral monitoring of forest disasters were summarized. The unresolved problems of hyperspectral technology in the forestry remote sensing applications were pointed out and the possible ways to solve these problems were expounded. Finally, the application prospect of hyperspectral remote sensing technology in forestry was analyzed.

  18. Hyperspectral image reconstruction for diffuse optical tomography

    PubMed Central

    Larusson, Fridrik; Fantini, Sergio; Miller, Eric L.

    2011-01-01

    We explore the development and performance of algorithms for hyperspectral diffuse optical tomography (DOT) for which data from hundreds of wavelengths are collected and used to determine the concentration distribution of chromophores in the medium under investigation. An efficient method is detailed for forming the images using iterative algorithms applied to a linearized Born approximation model assuming the scattering coefficient is spatially constant and known. The L-surface framework is employed to select optimal regularization parameters for the inverse problem. We report image reconstructions using 126 wavelengths with estimation error in simulations as low as 0.05 and mean square error of experimental data of 0.18 and 0.29 for ink and dye concentrations, respectively, an improvement over reconstructions using fewer specifically chosen wavelengths. PMID:21483616

  19. Recent applications of hyperspectral imaging in microbiology.

    PubMed

    Gowen, Aoife A; Feng, Yaoze; Gaston, Edurne; Valdramidis, Vasilis

    2015-05-01

    Hyperspectral chemical imaging (HSI) is a broad term encompassing spatially resolved spectral data obtained through a variety of modalities (e.g. Raman scattering, Fourier transform infrared microscopy, fluorescence and near-infrared chemical imaging). It goes beyond the capabilities of conventional imaging and spectroscopy by obtaining spatially resolved spectra from objects at spatial resolutions varying from the level of single cells up to macroscopic objects (e.g. foods). In tandem with recent developments in instrumentation and sampling protocols, applications of HSI in microbiology have increased rapidly. This article gives a brief overview of the fundamentals of HSI and a comprehensive review of applications of HSI in microbiology over the past 10 years. Technical challenges and future perspectives for these techniques are also discussed.

  20. Metric Learning for Hyperspectral Image Segmentation

    NASA Technical Reports Server (NTRS)

    Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

    2011-01-01

    We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

  1. Hyper-spectral Atmospheric Sounding. Appendixes 1

    NASA Technical Reports Server (NTRS)

    Smith, W. L.; Zhou, D. K.; Revercomb, H. E.; Huang, H. L.; Antonelli, P.; Mango, S. A.

    2002-01-01

    The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) is the first hyper-spectral remote sounding system to be orbited aboard a geosynchronous satellite. The GETS is designed to obtain revolutionary observations of the four dimensional atmospheric temperature, moisture, and wind structure as well as the distribution of the atmospheric trace gases, CO and O3. Although GIFTS will not be orbited until 2006-2008, a glimpse at the its measurement capabilities has been obtained by analyzing data from the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Test-bed-Interferometer (NAST-I) and Aqua satellite Atmospheric Infrared Sounder (AIRS). In this paper we review the GIFTS experiment and empirically assess measurement expectations based on meteorological profiles retrieved from the NAST aircraft and Aqua satellite AIRS spectral radiances.

  2. Hyperspectral image projector for advanced sensor characterization

    NASA Astrophysics Data System (ADS)

    Brown, S. W.; Rice, J. P.; Neira, J. E.; Bousquet, R.; Johnson, B. C.

    2006-08-01

    In this work, we describe radiometric platforms able to produce realistic spectral distributions and spatial scenes for the development of application-specific metrics to quantify the performance of sensors and systems. Using these platforms, sensor and system performance may be quantified in terms of the accuracy of measurements of standardized sets of complex source distributions. The same platforms can also serve as a basis for algorithm testing and instrument comparison. The platforms consist of spectrally tunable light sources (STS's) coupled with spatially programmable projection systems. The resultant hyperspectral image projectors (HIP) can generate complex spectral distributions with high spectral fidelity; that is, scenes with realistic spectral content. Using the same fundamental technology, platforms can be developed for the ultraviolet, visible, and infrared regions. These radiometric platforms will facilitate advanced sensor characterization testing, enabling a pre-flight validation of the pre-flight calibration.

  3. Food quality assessment by NIR hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Whitworth, Martin B.; Millar, Samuel J.; Chau, Astor

    2010-04-01

    Near infrared reflectance (NIR) spectroscopy is well established in the food industry for rapid compositional analysis of bulk samples. NIR hyperspectral imaging provides new opportunities to measure the spatial distribution of components such as moisture and fat, and to identify and measure specific regions of composite samples. An NIR hyperspectral imaging system has been constructed for food research applications, incorporating a SWIR camera with a cooled 14 bit HgCdTe detector and N25E spectrograph (Specim Ltd, Finland). Samples are scanned in a pushbroom mode using a motorised stage. The system has a spectral resolution of 256 pixels covering a range of 970-2500 nm and a spatial resolution of 320 pixels covering a swathe adjustable from 8 to 300 mm. Images are acquired at a rate of up to 100 lines s-1, enabling samples to be scanned within a few seconds. Data are captured using SpectralCube software (Specim) and analysed using ENVI and IDL (ITT Visual Information Solutions). Several food applications are presented. The strength of individual absorbance bands enables the distribution of particular components to be assessed. Examples are shown for detection of added gluten in wheat flour and to study the effect of processing conditions on fat distribution in chips/French fries. More detailed quantitative calibrations have been developed to study evolution of the moisture distribution in baguettes during storage at different humidities, to assess freshness of fish using measurements of whole cod and fillets, and for prediction of beef quality by identification and separate measurement of lean and fat regions.

  4. Space View Issues for Hyperspectral Sounders

    NASA Technical Reports Server (NTRS)

    Manning, Evan M.; Aumann, Hartmut H.; Broberg, Steven E.

    2013-01-01

    The expectation for climate quality measurements from hyperspectral sounders is absolute calibration accuracy at the 100 mK level and stability at the < 40 mK/decade level. The Atmospheric InfraRed Sounder (AIRS)1, Cross-track Infrared Sounder (CrIS), and Infrared Atmospheric Sounding Interferometer (IASI) hyperspectral sounders currently in orbit have been shown to agree well over most of their brightness temperature range. Some larger discrepancies are seen, however, at the coldest scene temperatures, such as those seen in Antarctic winter and deep convective clouds. A key limiting factor for the calibrated scene radiance accuracy for cold scenes is how well the effective radiance of the cold space view pertains to the scene views. The space view signal is composed of external sources and instrument thermal emission at about 270 K from the scan mirror, external baffles, etc. Any difference in any of these contributions between space views and scene views will impact the absolute calibration accuracy, and the impact can be critical for cold scenes. Any change over time in these will show up as an apparent trend in calibrated radiances. We use AIRS data to investigate the validity of the space view assumption in view of the 100 mK accuracy and 40 mK/decade trend expectations. We show that the space views used for the cold calibration point for AIRS v5 Level-1B products meet these standards except under special circumstances and that AIRS v6 Level-1B products will meet them under all circumstances. This analysis also shows the value of having multiple distinct space views to give operational redundancy and analytic data, and that reaching climate quality requires continuing monitoring of aging instruments and adjustment of calibration.

  5. Experience in the use of hyperspectral data for the detection of vegetation containing narcotic substances

    NASA Astrophysics Data System (ADS)

    Sedelnikov, V. P.; Lukashevich, E. L.; Karpukhina, O. A.

    2014-12-01

    This paper provides the characteristics of an experimental sample of a hyperspectral videospectrometer Sokol-SCP and presents examples of the hyperspectral data received as a result of flight tests. The results of the detection of vegetation containing narcotic substances by spectral attributes using the obtained hyperspectral information are considered. The opportunity for using the hyperspectral data for detection of cannabis and papaver sites, including those in mixed crops with masking vegetation, is confirmed.

  6. Analysis of hyperspectral scattering images using a moment method for apple firmness prediction

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This article reports on using a moment method to extract features from the hyperspectral scattering profiles for apple fruit firmness prediction. Hyperspectral scattering images between 500 nm and 1000 nm were acquired online, using a hyperspectral scattering system, for ‘Golden Delicious’, ’Jonagol...

  7. Target detection algorithm for airborne thermal hyperspectral data

    NASA Astrophysics Data System (ADS)

    Marwaha, R.; Kumar, A.; Raju, P. L. N.; Krishna Murthy, Y. V. N.

    2014-11-01

    Airborne hyperspectral imaging is constantly being used for classification purpose. But airborne thermal hyperspectral image usually is a challenge for conventional classification approaches. The Telops Hyper-Cam sensor is an interferometer-based imaging system that helps in the spatial and spectral analysis of targets utilizing a single sensor. It is based on the technology of Fourier-transform which yields high spectral resolution and enables high accuracy radiometric calibration. The Hypercam instrument has 84 spectral bands in the 868 cm-1 to 1280 cm-1 region (7.8 μm to 11.5 μm), at a spectral resolution of 6 cm-1 (full-width-half-maximum) for LWIR (long wave infrared) range. Due to the Hughes effect, only a few classifiers are able to handle high dimensional classification task. MNF (Minimum Noise Fraction) rotation is a data dimensionality reducing approach to segregate noise in the data. In this, the component selection of minimum noise fraction (MNF) rotation transformation was analyzed in terms of classification accuracy using constrained energy minimization (CEM) algorithm as a classifier for Airborne thermal hyperspectral image and for the combination of airborne LWIR hyperspectral image and color digital photograph. On comparing the accuracy of all the classified images for airborne LWIR hyperspectral image and combination of Airborne LWIR hyperspectral image with colored digital photograph, it was found that accuracy was highest for MNF component equal to twenty. The accuracy increased by using the combination of airborne LWIR hyperspectral image with colored digital photograph instead of using LWIR data alone.

  8. Measurement of Sun Induced Chlorophyll Fluorescence Using Hyperspectral Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Irteza, S. M.; Nichol, J. E.

    2016-06-01

    Solar Induced Chlorophyll Fluorescence (SIF), can be used as an indicator of stress in vegetation. Several scientific approaches have been made and there is considerable evidence that steady state Chlorophyll fluorescence is an accurate indicator of plant stress hence a reliable tool to monitor vegetation health status. Retrieval of Chlorophyll fluorescence provides an insight into photochemical and carbon sequestration processes within vegetation. Detection of Chlorophyll fluorescence has been well understood in the laboratory and field measurement. Fluorescence retrieval methods were applied in and around the atmospheric absorption bands 02B (Red wavelength) approximately 690 nm and 02A (Far red wavelengths) 740 nm. Hyperion satellite images were acquired for the years 2012 to 2015 in different seasons. Atmospheric corrections were applied using the 6S Model. The Fraunhofer Line Discrimanator (FLD) method was applied for retrieval of SIF from the Hyperion images by measuring the signal around the absorption bands in both vegetated and non vegetated land cover types. Absorption values were extracted in all the selected bands and the fluorescence signal was detected. The relationships between NDVI and Fluorescence derived from the satellite images are investigated to understand vegetation response within the absorption bands.

  9. In vivo and in vitro hyperspectral imaging of cervical neoplasia

    NASA Astrophysics Data System (ADS)

    Wang, Chaojian; Zheng, Wenli; Bu, Yanggao; Chang, Shufang; Tong, Qingping; Zhang, Shiwu; Xu, Ronald X.

    2014-02-01

    Cervical cancer is a prevalent disease in many developing countries. Colposcopy is the most common approach for screening cervical intraepithelial neoplasia (CIN). However, its clinical efficacy heavily relies on the examiner's experience. Spectroscopy is a potentially effective method for noninvasive diagnosis of cervical neoplasia. In this paper, we introduce a hyperspectral imaging technique for noninvasive detection and quantitative analysis of cervical neoplasia. A hyperspectral camera is used to collect the reflectance images of the entire cervix under xenon lamp illumination, followed by standard colposcopy examination and cervical tissue biopsy at both normal and abnormal sites in different quadrants. The collected reflectance data are calibrated and the hyperspectral signals are extracted. Further spectral analysis and image processing works are carried out to classify tissue into different types based on the spectral characteristics at different stages of cervical intraepithelial neoplasia. The hyperspectral camera is also coupled with a lab microscope to acquire the hyperspectral transmittance images of the pathological slides. The in vivo and the in vitro imaging results are compared with clinical findings to assess the accuracy and efficacy of the method.

  10. Quantum computation in the analysis of hyperspectral data

    NASA Astrophysics Data System (ADS)

    Gomez, Richard B.; Ghoshal, Debabrata; Jayanna, Anil

    2004-08-01

    Recent research on the topic of quantum computation provides us with some quantum algorithms with higher efficiency and speedup compared to their classical counterparts. In this paper, it is our intent to provide the results of our investigation of several applications of such quantum algorithms - especially the Grover's Search algorithm - in the analysis of Hyperspectral Data. We found many parallels with Grover's method in existing data processing work that make use of classical spectral matching algorithms. Our efforts also included the study of several methods dealing with hyperspectral image analysis work where classical computation methods involving large data sets could be replaced with quantum computation methods. The crux of the problem in computation involving a hyperspectral image data cube is to convert the large amount of data in high dimensional space to real information. Currently, using the classical model, different time consuming methods and steps are necessary to analyze these data including: Animation, Minimum Noise Fraction Transform, Pixel Purity Index algorithm, N-dimensional scatter plot, Identification of Endmember spectra - are such steps. If a quantum model of computation involving hyperspectral image data can be developed and formalized - it is highly likely that information retrieval from hyperspectral image data cubes would be a much easier process and the final information content would be much more meaningful and timely. In this case, dimensionality would not be a curse, but a blessing.

  11. A compressive sensing and unmixing scheme for hyperspectral data processing.

    PubMed

    Li, Chengbo; Sun, Ting; Kelly, Kevin F; Zhang, Yin

    2012-03-01

    Hyperspectral data processing typically demands enormous computational resources in terms of storage, computation, and input/output throughputs, particularly when real-time processing is desired. In this paper, a proof-of-concept study is conducted on compressive sensing (CS) and unmixing for hyperspectral imaging. Specifically, we investigate a low-complexity scheme for hyperspectral data compression and reconstruction. In this scheme, compressed hyperspectral data are acquired directly by a device similar to the single-pixel camera based on the principle of CS. To decode the compressed data, we propose a numerical procedure to compute directly the unmixed abundance fractions of given endmembers, completely bypassing high-complexity tasks involving the hyperspectral data cube itself. The reconstruction model is to minimize the total variation of the abundance fractions subject to a preprocessed fidelity equation with a significantly reduced size and other side constraints. An augmented Lagrangian-type algorithm is developed to solve this model. We conduct extensive numerical experiments to demonstrate the feasibility and efficiency of the proposed approach, using both synthetic data and hardware-measured data. Experimental and computational evidences obtained from this paper indicate that the proposed scheme has a high potential in real-world applications. PMID:21914570

  12. A global shutter CMOS image sensor for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Stefanov, Konstantin D.; Dryer, Ben J.; Hall, David J.; Holland, Andrew D.; Pratlong, Jérôme; Fryer, Martin; Pike, Andrew

    2015-09-01

    Hyperspectral imaging has been providing vital information on the Earth landscape in response to the changing environment, land use and natural phenomena. While conventional hyperspectral imaging instruments have typically used rows of linescan CCDs, CMOS image sensors (CIS) have been slowly penetrating space instrumentation for the past decade, and Earth observation (EO) is no exception. CIS provide distinct advantages over CCDs that are relevant to EO hyperspectral imaging. The lack of charge transfer through the array allows the reduction of cross talk usually present in CCDs due to imperfect charge transfer efficiency, and random pixel addressing makes variable integration time possible, and thus improves the camera sensitivity and dynamic range. We have developed a 10T pixel design that integrates a pinned photodiode with global shutter and in-pixel correlated double sampling (CDS) to increase the signal to noise ratio in less intense spectral regimes, allowing for both high resolution and low noise hyperspectral imaging for EO. This paper details the characterization of a test device, providing baseline performance measurements of the array such as noise, responsivity, dark current and global shutter efficiency, and also discussing benchmark hyperspectral imaging requirements such as dynamic range, pixel crosstalk, and image lag.

  13. a Diversified Deep Belief Network for Hyperspectral Image Classification

    NASA Astrophysics Data System (ADS)

    Zhong, P.; Gong, Z. Q.; Schönlieb, C.

    2016-06-01

    In recent years, researches in remote sensing demonstrated that deep architectures with multiple layers can potentially extract abstract and invariant features for better hyperspectral image classification. Since the usual real-world hyperspectral image classification task cannot provide enough training samples for a supervised deep model, such as convolutional neural networks (CNNs), this work turns to investigate the deep belief networks (DBNs), which allow unsupervised training. The DBN trained over limited training samples usually has many "dead" (never responding) or "potential over-tolerant" (always responding) latent factors (neurons), which decrease the DBN's description ability and thus finally decrease the hyperspectral image classification performance. This work proposes a new diversified DBN through introducing a diversity promoting prior over the latent factors during the DBN pre-training and fine-tuning procedures. The diversity promoting prior in the training procedures will encourage the latent factors to be uncorrelated, such that each latent factor focuses on modelling unique information, and all factors will be summed up to capture a large proportion of information and thus increase description ability and classification performance of the diversified DBNs. The proposed method was evaluated over the well-known real-world hyperspectral image dataset. The experiments demonstrate that the diversified DBNs can obtain much better results than original DBNs and comparable or even better performances compared with other recent hyperspectral image classification methods.

  14. Geographical classification of apple based on hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Guo, Zhiming; Huang, Wenqian; Chen, Liping; Zhao, Chunjiang; Peng, Yankun

    2013-05-01

    Attribute of apple according to geographical origin is often recognized and appreciated by the consumers. It is usually an important factor to determine the price of a commercial product. Hyperspectral imaging technology and supervised pattern recognition was attempted to discriminate apple according to geographical origins in this work. Hyperspectral images of 207 Fuji apple samples were collected by hyperspectral camera (400-1000nm). Principal component analysis (PCA) was performed on hyperspectral imaging data to determine main efficient wavelength images, and then characteristic variables were extracted by texture analysis based on gray level co-occurrence matrix (GLCM) from dominant waveband image. All characteristic variables were obtained by fusing the data of images in efficient spectra. Support vector machine (SVM) was used to construct the classification model, and showed excellent performance in classification results. The total classification rate had the high classify accuracy of 92.75% in the training set and 89.86% in the prediction sets, respectively. The overall results demonstrated that the hyperspectral imaging technique coupled with SVM classifier can be efficiently utilized to discriminate Fuji apple according to geographical origins.

  15. Hyperspectral anomaly detection using sparse kernel-based ensemble learning

    NASA Astrophysics Data System (ADS)

    Gurram, Prudhvi; Han, Timothy; Kwon, Heesung

    2011-06-01

    In this paper, sparse kernel-based ensemble learning for hyperspectral anomaly detection is proposed. The proposed technique is aimed to optimize an ensemble of kernel-based one class classifiers, such as Support Vector Data Description (SVDD) classifiers, by estimating optimal sparse weights. In this method, hyperspectral signatures are first randomly sub-sampled into a large number of spectral feature subspaces. An enclosing hypersphere that defines the support of spectral data, corresponding to the normalcy/background data, in the Reproducing Kernel Hilbert Space (RKHS) of each respective feature subspace is then estimated using regular SVDD. The enclosing hypersphere basically represents the spectral characteristics of the background data in the respective feature subspace. The joint hypersphere is learned by optimally combining the hyperspheres from the individual RKHS, while imposing the l1 constraint on the combining weights. The joint hypersphere representing the most optimal compact support of the local hyperspectral data in the joint feature subspaces is then used to test each pixel in hyperspectral image data to determine if it belongs to the local background data or not. The outliers are considered to be targets. The performance comparison between the proposed technique and the regular SVDD is provided using the HYDICE hyperspectral images.

  16. Hybrid tenso-vectorial compressive sensing for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Li, Qun; Bernal, Edgar A.

    2016-05-01

    Hyperspectral imaging has a wide range of applications relying on remote material identification, including astronomy, mineralogy, and agriculture; however, due to the large volume of data involved, the complexity and cost of hyperspectral imagers can be prohibitive. The exploitation of redundancies along the spatial and spectral dimensions of a hyperspectral image of a scene has created new paradigms that overcome the limitations of traditional imaging systems. While compressive sensing (CS) approaches have been proposed and simulated with success on already acquired hyperspectral imagery, most of the existing work relies on the capability to simultaneously measure the spatial and spectral dimensions of the hyperspectral cube. Most real-life devices, however, are limited to sampling one or two dimensions at a time, which renders a significant portion of the existing work unfeasible. We propose a new variant of the recently proposed serial hybrid vectorial and tensorial compressive sensing (HCS-S) algorithm that, like its predecessor, is compatible with real-life devices both in terms of the acquisition and reconstruction requirements. The newly introduced approach is parallelizable, and we abbreviate it as HCS-P. Together, HCS-S and HCS-P comprise a generalized framework for hybrid tenso-vectorial compressive sensing, or HCS for short. We perform a detailed analysis that demonstrates the uniqueness of the signal reconstructed by both the original HCS-S and the proposed HCS-P algorithms. Last, we analyze the behavior of the HCS reconstruction algorithms in the presence of measurement noise, both theoretically and experimentally.

  17. Hyperspectral characterization of an in vitro wound model

    NASA Astrophysics Data System (ADS)

    Randeberg, Lise L.; Hegstad, Janne-Lise; Paluchowski, Lukasz; Milanič, Matija; Pukstad, Brita S.

    2014-03-01

    Wound healing is a complex process not fully understood. There is a need of better methods to evaluate the different stages of healing, and optical characterization is a promising tool in this respect. In this study hyperspectral imaging was employed to characterize an in vitro wound model. The wound model was established by first cutting circular patches of human abdominal skin using an 8mm punch biopsy tool, and then creating dermal wounds in the center of the skin patches using a 5mm tool. The wounds were incubated in medium with 10% serum and antibiotics. Hyperspectral images were collected every three days using a push broom hyper spectral camera (Hyspex VNIR1600). The camera had a spectral resolution of 3.7 nm and was fitted with a close up lens giving a FOV of 2.5 cm and a spatial resolution of 29 micrometer. Samples for histology were collected throughout the measurement period, which was 21 days in total. Data were processed in ENVI and Matlab. A successful classification based on hyperspectral imaging of the implemented model is presented. It was not possible to see the healing zone in the in vitro model with the naked eye without dying. The hyperspectral results showed that newly formed epithelium could be imaged without any additional contrast agents or dyes. It was also possible to detect non-viable tissue. In vitro wound models and hyperspectral imaging can thus be employed to gain further insight in the complicated process of healing in different kinds of wounds.

  18. Hyperspectral Fluorescence and Reflectance Imaging Instrument

    NASA Technical Reports Server (NTRS)

    Ryan, Robert E.; O'Neal, S. Duane; Lanoue, Mark; Russell, Jeffrey

    2008-01-01

    The system is a single hyperspectral imaging instrument that has the unique capability to acquire both fluorescence and reflectance high-spatial-resolution data that is inherently spatially and spectrally registered. Potential uses of this instrument include plant stress monitoring, counterfeit document detection, biomedical imaging, forensic imaging, and general materials identification. Until now, reflectance and fluorescence spectral imaging have been performed by separate instruments. Neither a reflectance spectral image nor a fluorescence spectral image alone yields as much information about a target surface as does a combination of the two modalities. Before this system was developed, to benefit from this combination, analysts needed to perform time-consuming post-processing efforts to co-register the reflective and fluorescence information. With this instrument, the inherent spatial and spectral registration of the reflectance and fluorescence images minimizes the need for this post-processing step. The main challenge for this technology is to detect the fluorescence signal in the presence of a much stronger reflectance signal. To meet this challenge, the instrument modulates artificial light sources from ultraviolet through the visible to the near-infrared part of the spectrum; in this way, both the reflective and fluorescence signals can be measured through differencing processes to optimize fluorescence and reflectance spectra as needed. The main functional components of the instrument are a hyperspectral imager, an illumination system, and an image-plane scanner. The hyperspectral imager is a one-dimensional (line) imaging spectrometer that includes a spectrally dispersive element and a two-dimensional focal plane detector array. The spectral range of the current imaging spectrometer is between 400 to 1,000 nm, and the wavelength resolution is approximately 3 nm. The illumination system consists of narrowband blue, ultraviolet, and other discrete

  19. Estimation of tissue optical parameters with hyperspectral imaging and spectral unmixing

    NASA Astrophysics Data System (ADS)

    Lu, Guolan; Qin, Xulei; Wang, Dongsheng; Chen, Zhuo G.; Fei, Baowei

    2015-03-01

    Early detection of oral cancer and its curable precursors can improve patient survival and quality of life. Hyperspectral imaging (HSI) holds the potential for noninvasive early detection of oral cancer. The quantification of tissue chromophores by spectral unmixing of hyperspectral images could provide insights for evaluating cancer progression. In this study, non-negative matrix factorization has been applied for decomposing hyperspectral images into physiologically meaningful chromophore concentration maps. The approach has been validated by computer-simulated hyperspectral images and in vivo tumor hyperspectral images from a head and neck cancer animal model.

  20. Estimation of Tissue Optical Parameters with Hyperspectral Imaging and Spectral Unmixing

    PubMed Central

    Lu, Guolan; Qin, Xulei; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

    2015-01-01

    Early detection of oral cancer and its curable precursors can improve patient survival and quality of life. Hyperspectral imaging (HSI) holds the potential for noninvasive early detection of oral cancer. The quantification of tissue chromophores by spectral unmixing of hyperspectral images could provide insights for evaluating cancer progression. In this study, non-negative matrix factorization has been applied for decomposing hyperspectral images into physiologically meaningful chromophore concentration maps. The approach has been validated by computer-simulated hyperspectral images and in vivo tumor hyperspectral images from a head and neck cancer animal model. PMID:26855467

  1. Hyperspectral Image Super-Resolution via Non-Negative Structured Sparse Representation.

    PubMed

    Dong, Weisheng; Fu, Fazuo; Shi, Guangming; Cao, Xun; Wu, Jinjian; Li, Guangyu; Li, Guangyu

    2016-05-01

    Hyperspectral imaging has many applications from agriculture and astronomy to surveillance and mineralogy. However, it is often challenging to obtain high-resolution (HR) hyperspectral images using existing hyperspectral imaging techniques due to various hardware limitations. In this paper, we propose a new hyperspectral image super-resolution method from a low-resolution (LR) image and a HR reference image of the same scene. The estimation of the HR hyperspectral image is formulated as a joint estimation of the hyperspectral dictionary and the sparse codes based on the prior knowledge of the spatial-spectral sparsity of the hyperspectral image. The hyperspectral dictionary representing prototype reflectance spectra vectors of the scene is first learned from the input LR image. Specifically, an efficient non-negative dictionary learning algorithm using the block-coordinate descent optimization technique is proposed. Then, the sparse codes of the desired HR hyperspectral image with respect to learned hyperspectral basis are estimated from the pair of LR and HR reference images. To improve the accuracy of non-negative sparse coding, a clustering-based structured sparse coding method is proposed to exploit the spatial correlation among the learned sparse codes. The experimental results on both public datasets and real LR hypspectral images suggest that the proposed method substantially outperforms several existing HR hyperspectral image recovery techniques in the literature in terms of both objective quality metrics and computational efficiency. PMID:27019486

  2. D Hyperspectral Frame Imager Camera Data in Photogrammetric Mosaicking

    NASA Astrophysics Data System (ADS)

    Mäkeläinen, A.; Saari, H.; Hippi, I.; Sarkeala, J.; Soukkamäki, J.

    2013-08-01

    A new 2D hyperspectral frame camera system has been developed by VTT (Technical Research Center of Finland) and Rikola Ltd. It contains frame based and very light camera with RGB-NIR sensor and it is suitable for light weight and cost effective UAV planes. MosaicMill Ltd. has converted the camera data into proper format for photogrammetric processing, and camera's geometrical accuracy and stability are evaluated to guarantee required accuracies for end user applications. MosaicMill Ltd. has also applied its' EnsoMOSAIC technology to process hyperspectral data into orthomosaics. This article describes the main steps and results on applying hyperspectral sensor in orthomosaicking. The most promising results as well as challenges in agriculture and forestry are also described.

  3. Diagnosis method of cucumber downy mildew with NIR hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Tian, Youwen; Li, Tianlai; Zhang, Lin; Zhang, Xiaodong

    2011-11-01

    This study was carried out to develop a hyperspectral imaging system in the near infrared (NIR) region (900-1700 nm) to diagnose cucumber downy mildew. Hyperspectral images were acquired from each diseased cucumber leaf samples with downy mildew and then their spectral data were extracted. Spectral data were analyzed using principal component analysis (PCA) to reduce the high dimensionality of the data and for selecting some important wavelengths. Out of 256 wavelengths, only two wavelengths (1426 and 1626nm) of first PC were selected as the optimum wavelengths for the diagnosis of cucumber downy mildew. The data analysis showed that it is possible to diagnose cucumber downy mildew with few numbers of wavelengths on the basis of their statistical image features and histogram features. The results revealed the potentiality of NIR hyperspectral imaging as an objective and non-destructive method for the authentication and diagnosis of cucumber downy mildew.

  4. Hyperspectral retinal imaging with a spectrally tunable light source

    NASA Astrophysics Data System (ADS)

    Francis, Robert P.; Zuzak, Karel J.; Ufret-Vincenty, Rafael

    2011-03-01

    Hyperspectral retinal imaging can measure oxygenation and identify areas of ischemia in human patients, but the devices used by current researchers are inflexible in spatial and spectral resolution. We have developed a flexible research prototype consisting of a DLP®-based spectrally tunable light source coupled to a fundus camera to quickly explore the effects of spatial resolution, spectral resolution, and spectral range on hyperspectral imaging of the retina. The goal of this prototype is to (1) identify spectral and spatial regions of interest for early diagnosis of diseases such as glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy (DR); and (2) define required specifications for commercial products. In this paper, we describe the challenges and advantages of using a spectrally tunable light source for hyperspectral retinal imaging, present clinical results of initial imaging sessions, and describe how this research can be leveraged into specifying a commercial product.

  5. Parallel computation for blood cell classification in medical hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Li, Wei; Wu, Lucheng; Qiu, Xianbo; Ran, Qiong; Xie, Xiaoming

    2016-09-01

    With the advantage of fine spectral resolution, hyperspectral imagery provides great potential for cell classification. This paper provides a promising classification system including the following three stages: (1) band selection for a subset of spectral bands with distinctive and informative features, (2) spectral-spatial feature extraction, such as local binary patterns (LBP), and (3) followed by an effective classifier. Moreover, these three steps are further implemented on graphics processing units (GPU) respectively, which makes the system real-time and more practical. The GPU parallel implementation is compared with the serial implementation on central processing units (CPU). Experimental results based on real medical hyperspectral data demonstrate that the proposed system is able to offer high accuracy and fast speed, which are appealing for cell classification in medical hyperspectral imagery.

  6. [Nondestructive discrimination of waxed apples based on hyperspectral imaging technology].

    PubMed

    Gao, Jun-Feng; Zhang, Hai-Liang; Kong, Wen-Wen; He, Yong

    2013-07-01

    The potential of hyperspectral imaging technology was evaluated for discriminating three types of waxed apples. Three types of apples smeared with fruit wax, with industrial wax, and not waxed respectively were imaged by a hyperspectral imaging system with a spectral range of 308-1 024 nm. ENVI software processing platform was used for extracting hyperspectral image object of diffuse reflection spectral response characteristics. Eighty four of 126 apple samples were selected randomly as calibration set and the rest were prediction set. After different preprocess, the related mathematical models were established by using the partial least squares (PLS), the least squares support vector machine (LS-SVM) and BP neural network methods and so on. The results showed that the model of MSC-SPA-LSSVM was the best to discriminate three kinds of waxed apples with 100%, 100% and 92.86% correct prediction respectively.

  7. Workflow for Building a Hyperspectral Uav: Challenges and Opportunities

    NASA Astrophysics Data System (ADS)

    Proctor, C.; He, Y.

    2015-08-01

    Owing to the limited payload capacities of most UAV platforms within an academic research budget, many UAV systems utilize commercial RGB cameras or modified sensors with some capacity for sensing in the NIR. However, many applications require higher spectral fidelity that only hyperspectral sensors can offer. For instance, the Photochemical Reflectance Index relies upon the narrow band absorbance of xanthophyll pigments at 531 and 570nm to quantify photosynthetic light use efficiency which are important indicators of productivity and stress in agricultural and forest ecosystems. Thus, our research group has been working on building a research paradigm around a commercial off-the-shelf hyperspectral sensor and UAV. This paper discusses some of the key decisions made regarding selection of equipment and navigating the regulatory and logistical landmines. The imagery collected to date and the options available to process and utilize hyperspectral data are discussed at the end.

  8. Classification of Korla fragrant pears using NIR hyperspectral imaging analysis

    NASA Astrophysics Data System (ADS)

    Rao, Xiuqin; Yang, Chun-Chieh; Ying, Yibin; Kim, Moon S.; Chao, Kuanglin

    2012-05-01

    Korla fragrant pears are small oval pears characterized by light green skin, crisp texture, and a pleasant perfume for which they are named. Anatomically, the calyx of a fragrant pear may be either persistent or deciduous; the deciduouscalyx fruits are considered more desirable due to taste and texture attributes. Chinese packaging standards require that packed cases of fragrant pears contain 5% or less of the persistent-calyx type. Near-infrared hyperspectral imaging was investigated as a potential means for automated sorting of pears according to calyx type. Hyperspectral images spanning the 992-1681 nm region were acquired using an EMCCD-based laboratory line-scan imaging system. Analysis of the hyperspectral images was performed to select wavebands useful for identifying persistent-calyx fruits and for identifying deciduous-calyx fruits. Based on the selected wavebands, an image-processing algorithm was developed that targets automated classification of Korla fragrant pears into the two categories for packaging purposes.

  9. Application of Hyperspectral Methods in Hydrothermal Mineral System Studies

    NASA Astrophysics Data System (ADS)

    Laukamp, Carsten; Cudahy, Thomas; Gessner, Klaus; Haest, Maarten; Cacetta, Mike; Rodger, Andrew; Jones, Mal; Thomas, Matilda

    2010-05-01

    Hyperspectral infrared reflectance spectra are used to identify abundances and compositional differences of mineral groups and single mineral phases. 3D mineral maps are derived from surface (airborne and satellite sensed) and sub-surface (drill core) mineralogical data and integrated with geological, geochemical and geophysical datasets, enabling a quantitative mineral systems analysis. The Western Australian Centre of Excellence for 3D Mineral Mapping is working on a variety of mineral deposits to showcase the emerging applications of hyperspectral techniques in mineral system studies. Applied remote sensing technologies comprise hyperspectral airborne surveys (HyMap) covering 126 bands in the visible and shortwave infrared, as well as satellite-based multispectral surveys (ASTER) featuring 14 bands from the visible to thermal infrared. Drill cores were scanned with CSIRO's HyLoggingTM systems, which allow a fast acquisition of mineralogical data in cm-spacing and thereby providing statistically significant datasets. Building on procedures developed for public Australian geosurvey data releases for north Queensland, Broken Hill and Kalgoorlie (http://c3dmm.csiro.au), the ultimate goal is to develop sensor-independent scalars based on the position, depth and shape of selected absorption features in the visible-near (VNIR), shortwave (SWIR) and thermal infrared (TIR), which can be applied to a wide range of mineral deposit types. In the Rocklea Dome Channel Iron Ore deposits of the Pilbara (Western Australia) for example, hyperspectral drill core data were processed into 3D mineral maps to delineate major ore zones by identifying various ore types and possible contaminants. Vitreous (silica-rich) iron ore was successfully separated from ochreous goethitic ore, with both of them requiring different metallurgical processing. The silicified vitreous iron ore as well as outlined carbonate-rich zones are presumably related to overprinting groundwater effects. The

  10. Fault tolerance of SVM algorithm for hyperspectral image

    NASA Astrophysics Data System (ADS)

    Cui, Yabo; Yuan, Zhengwu; Wu, Yuanfeng; Gao, Lianru; Zhang, Hao

    2015-10-01

    One of the most important tasks in analyzing hyperspectral image data is the classification process[1]. In general, in order to enhance the classification accuracy, a data preprocessing step is usually adopted to remove the noise in the data before classification. But for the time-sensitive applications, we hope that even the data contains noise the classifier can still appear to execute correctly from the user's perspective, such as risk prevention and response. As the most popular classifier, Support Vector Machine (SVM) has been widely used for hyperspectral image classification and proved to be a very promising technique in supervised classification[2]. In this paper, two experiments are performed to demonstrate that for the hyperspectral data with noise, if the noise of the data is within a certain range, SVM algorithm is still able to execute correctly from the user's perspective.

  11. Embedded GPU implementation of anomaly detection for hyperspectral images

    NASA Astrophysics Data System (ADS)

    Wu, Yuanfeng; Gao, Lianru; Zhang, Bing; Yang, Bin; Chen, Zhengchao

    2015-10-01

    Anomaly detection is one of the most important techniques for remotely sensed hyperspectral data interpretation. Developing fast processing techniques for anomaly detection has received considerable attention in recent years, especially in analysis scenarios with real-time constraints. In this paper, we develop an embedded graphics processing units based parallel computation for streaming background statistics anomaly detection algorithm. The streaming background statistics method can simulate real-time anomaly detection, which refer to that the processing can be performed at the same time as the data are collected. The algorithm is implemented on NVIDIA Jetson TK1 development kit. The experiment, conducted with real hyperspectral data, indicate the effectiveness of the proposed implementations. This work shows the embedded GPU gives a promising solution for high-performance with low power consumption hyperspectral image applications.

  12. Spatial and temporal variability of hyperspectral signatures of terrain

    NASA Astrophysics Data System (ADS)

    Jones, K. F.; Perovich, D. K.; Koenig, G. G.

    2008-04-01

    Electromagnetic signatures of terrain exhibit significant spatial heterogeneity on a range of scales as well as considerable temporal variability. A statistical characterization of the spatial heterogeneity and spatial scaling algorithms of terrain electromagnetic signatures are required to extrapolate measurements to larger scales. Basic terrain elements including bare soil, grass, deciduous, and coniferous trees were studied in a quasi-laboratory setting using instrumented test sites in Hanover, NH and Yuma, AZ. Observations were made using a visible and near infrared spectroradiometer (350 - 2500 nm) and hyperspectral camera (400 - 1100 nm). Results are reported illustrating: i) several difference scenes; ii) a terrain scene time series sampled over an annual cycle; and iii) the detection of artifacts in scenes. A principal component analysis indicated that the first three principal components typically explained between 90 and 99% of the variance of the 30 to 40-channel hyperspectral images. Higher order principal components of hyperspectral images are useful for detecting artifacts in scenes.

  13. Spectral-Spatial Classification of Hyperspectral Images Using Hierarchical Optimization

    NASA Technical Reports Server (NTRS)

    Tarabalka, Yuliya; Tilton, James C.

    2011-01-01

    A new spectral-spatial method for hyperspectral data classification is proposed. For a given hyperspectral image, probabilistic pixelwise classification is first applied. Then, hierarchical step-wise optimization algorithm is performed, by iteratively merging neighboring regions with the smallest Dissimilarity Criterion (DC) and recomputing class labels for new regions. The DC is computed by comparing region mean vectors, class labels and a number of pixels in the two regions under consideration. The algorithm is converged when all the pixels get involved in the region merging procedure. Experimental results are presented on two remote sensing hyperspectral images acquired by the AVIRIS and ROSIS sensors. The proposed approach improves classification accuracies and provides maps with more homogeneous regions, when compared to previously proposed classification techniques.

  14. Hyperspectral Imaging and Related Field Methods: Building the Science

    NASA Technical Reports Server (NTRS)

    Goetz, Alexander F. H.; Steffen, Konrad; Wessman, Carol

    1999-01-01

    The proposal requested funds for the computing power to bring hyperspectral image processing into undergraduate and graduate remote sensing courses. This upgrade made it possible to handle more students in these oversubscribed courses and to enhance CSES' summer short course entitled "Hyperspectral Imaging and Data Analysis" provided for government, industry, university and military. Funds were also requested to build field measurement capabilities through the purchase of spectroradiometers, canopy radiation sensors and a differential GPS system. These instruments provided systematic and complete sets of field data for the analysis of hyperspectral data with the appropriate radiometric and wavelength calibration as well as atmospheric data needed for application of radiative transfer models. The proposed field equipment made it possible to team-teach a new field methods course, unique in the country, that took advantage of the expertise of the investigators rostered in three different departments, Geology, Geography and Biology.

  15. An airborne real-time hyperspectral target detection system

    NASA Astrophysics Data System (ADS)

    Skauli, Torbjorn; Haavardsholm, Trym V.; Kåsen, Ingebjørg; Arisholm, Gunnar; Kavara, Amela; Opsahl, Thomas Olsvik; Skaugen, Atle

    2010-04-01

    An airborne system for hyperspectral target detection is described. The main sensor is a HySpex pushbroom hyperspectral imager for the visible and near-infrared spectral range with 1600 pixels across track, supplemented by a panchromatic line imager. An optional third sensor can be added, either a SWIR hyperspectral camera or a thermal camera. In real time, the system performs radiometric calibration and georeferencing of the images, followed by image processing for target detection and visualization. The current version of the system implements only spectral anomaly detection, based on normal mixture models. Image processing runs on a PC with a multicore Intel processor and an Nvidia graphics processing unit (GPU). The processing runs in a software framework optimized for large sustained data rates. The platform is a Cessna 172 aircraft based close to FFI, modified with a camera port in the floor.

  16. The new hyperspectral microscopic system for cancer diagnosis

    NASA Astrophysics Data System (ADS)

    Hsieh, Yao-Fang; Mang, Ou-Yang; Chiou, Jin-Chern; Lin, Yung-Jiun; Tsai, Ming-Hsui; Bau, Da-Tian; Chiu, Chang-Fang; Teseng, Guan-Chin; Chang, Nai-Wen; Kao, Wen-Chung; Wu, Shun-De

    2011-02-01

    Until now, the cancer was examined by diagnosing the pathological changes of tumor. If the examination of cancer can diagnose the tumor before the cell occur the pathological changes, the cure rate of cancer will increase. This research develops a human-machine interface for hyper-spectral microscope. The hyper-spectral microscope can scan the specific area of cell and records the data of spectrum and intensity. These data is helpful to diagnose tumor. This research aims to develop a new system and a human-machine interface to control the hyper-spectral microscope. The interface can control the moving speed of motor, the exposure-time of hyper-spectrum, real-time focus, image of fluorescence, and record the data of spectral intensity and position.

  17. Hyperspectral characterization of the adjustable nano-coating systems

    NASA Astrophysics Data System (ADS)

    Murzina, Marina V. A.; Farrell, J. Paul; Aktsipetrov, Oleg A.; Murzina, Tatyana V.

    2005-05-01

    Nano-coatings with adjustable optical features is one of the revolutionary technologies of today. In this work, we investigate how hyperspectral imaging can detect adjustable nano-surfaces used, for example, for active camouflage. The distinct attributes of the nano-coating spectra are discussed. Fast algorithms of utilizing hyperspectral information for recognizing these attributes are suggested. The research applies to both recognizing the camouflaged objects and to building unrecognizable camouflage technology. In the context of tracking active camouflage, the identification of characteristic spectral attributes is especially important. Active spectra can constantly change, therefore confusing traditional hyperspectral classification. In contrast, the identified general spectral attributes stay the same allowing for robust identification and reliable tracking of the camouflaged objects.

  18. Hyperspectral Cubesat Constellation for Rapid Natural Hazard Response

    NASA Astrophysics Data System (ADS)

    Mandl, D.; Huemmrich, K. F.; Ly, V. T.; Handy, M.; Ong, L.; Crum, G.

    2015-12-01

    With the advent of high performance space networks that provide total coverage for Cubesats, the paradigm for low cost, high temporal coverage with hyperspectral instruments becomes more feasible. The combination of ground cloud computing resources, high performance with low power consumption onboard processing, total coverage for the cubesats and social media provide an opprotunity for an architecture that provides cost-effective hyperspectral data products for natural hazard response and decision support. This paper provides a series of pathfinder efforts to create a scalable Intelligent Payload Module(IPM) that has flown on a variety of airborne vehicles including Cessna airplanes, Citation jets and a helicopter and will fly on an Unmanned Aerial System (UAS) hexacopter to monitor natural phenomena. The IPM's developed thus far were developed on platforms that emulate a satellite environment which use real satellite flight software, real ground software. In addition, science processing software has been developed that perform hyperspectral processing onboard using various parallel processing techniques to enable creation of onboard hyperspectral data products while consuming low power. A cubesat design was developed that is low cost and that is scalable to larger consteallations and thus can provide daily hyperspectral observations for any spot on earth. The design was based on the existing IPM prototypes and metrics that were developed over the past few years and a shrunken IPM that can perform up to 800 Mbps throughput. Thus this constellation of hyperspectral cubesats could be constantly monitoring spectra with spectral angle mappers after Level 0, Level 1 Radiometric Correction, Atmospheric Correction processing. This provides the opportunity daily monitoring of any spot on earth on a daily basis at 30 meter resolution which is not available today.

  19. Content-based hyperspectral image retrieval using spectral unmixing

    NASA Astrophysics Data System (ADS)

    Plaza, Antonio J.

    2011-11-01

    The purpose of content-based image retrieval (CBIR) is to retrieve, from real data stored in a database, information that is relevant to a query. A major challenge for the development of efficient CBIR systems in the context of hyperspectral remote sensing applications is how to deal with the extremely large volumes of data produced by current Earth-observing (EO) imaging spectrometers. The data resulting from EO campaigns often comprises many Gigabytes per flight. When multiple instruments or timelines are combined, this leads to the collection of massive amounts of data coming from heterogeneous sources, and these data sets need to be effectively stored, managed, shared and retrieved. Furthermore, the growth in size and number of hyperspectral data archives demands more sophisticated search capabilities to allow users to locate and reuse data acquired in the past. In this paper we develop a new strategy to effectively retrieve hyperspectral image data sets using spectral unmixing concepts. Spectral unmixing is a very important task for hyperspectral data exploitation since the spectral signatures collected in natural environments are invariably a mixture of the pure signatures of the various materials found within the spatial extent of the ground instantaneous field view of the imaging instrument. In this work, we use the information provided by spectral unmixing (i.e. the spectral endmembers and their corresponding abundances in the scene) as effective meta-data to develop a new CBIR system that can assist users in the task of efficiently searching hyperspectral image instances in large data repositories. The proposed approach is validated using a collection of 154 hyperspectral data sets (comprising seven full flightlines) gathered by NASA using the Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the World Trade Center (WTC) area in New York City during the last two weeks of September, 2001, only a few days after the terrorist attacks that

  20. Hyperspectral sensor HSC3000 for nano-satellite TAIKI

    NASA Astrophysics Data System (ADS)

    Satori, S.; Aoyanagi, Y.; Hara, U.; Mitsuhashi, R.; Takeuchi, Y.

    2008-12-01

    Hokkaido Satellite Project was kicked off at April in 2003 by the volunteer group that consists of students, researchers and engineers in order to demonstrate the space business models using nanosatellites of 15kg/50kg in Japan. The Hokkaido satellite named "TAIKI" is characterized by a hyperspectral sensor with a VNIR (visible and near infrared range) and a laser communication instrument for data downlink communication. At the beginning of 2008 we started to develop a space qualified hyperspectral sensor HSC3000 based on the optical design of HSC1700. Last year we developed the hyperspectral camera HSC-3000 BBM funded by New Energy Development Organization (NEDO) as the position of the breadboard model of HSC3000. HSC-3000 BBM is specified by the spectral range from 400nm to 1000nm, 81 spectral bands, image size of 640 x 480 pixels, radiometric resolution of 10 bits and data transfer rate of 200 f/s. By averaging outputs of several adjacent pixels to increase S/N, HSC3000 of the spaceborne is targeted at the specification of 30 m spatial resolution, 61 spectral bands, 10 nm spectral resolution and S/N300. Spin-off technology of the hyperspectral imager is also introduced. We have succeeded to develop a hyperspectral camera as the spin-off product named HSC1700 which installs both the hyperspectral sensor unit and a scanning mechanism inside. The HSC1700 is specified by the spectral range from 400nm to 800nm, 81 spectral bands, image size of 640 x 480 pixels, radiometric resolution of 8 bits and data transfer rate of 30 f/s.

  1. Hyperspectral range imaging for transportation systems evaluation

    NASA Astrophysics Data System (ADS)

    Bridgelall, Raj; Rafert, J. B.; Atwood, Don; Tolliver, Denver D.

    2016-04-01

    Transportation agencies expend significant resources to inspect critical infrastructure such as roadways, railways, and pipelines. Regular inspections identify important defects and generate data to forecast maintenance needs. However, cost and practical limitations prevent the scaling of current inspection methods beyond relatively small portions of the network. Consequently, existing approaches fail to discover many high-risk defect formations. Remote sensing techniques offer the potential for more rapid and extensive non-destructive evaluations of the multimodal transportation infrastructure. However, optical occlusions and limitations in the spatial resolution of typical airborne and space-borne platforms limit their applicability. This research proposes hyperspectral image classification to isolate transportation infrastructure targets for high-resolution photogrammetric analysis. A plenoptic swarm of unmanned aircraft systems will capture images with centimeter-scale spatial resolution, large swaths, and polarization diversity. The light field solution will incorporate structure-from-motion techniques to reconstruct three-dimensional details of the isolated targets from sequences of two-dimensional images. A comparative analysis of existing low-power wireless communications standards suggests an application dependent tradeoff in selecting the best-suited link to coordinate swarming operations. This study further produced a taxonomy of specific roadway and railway defects, distress symptoms, and other anomalies that the proposed plenoptic swarm sensing system would identify and characterize to estimate risk levels.

  2. Hyperspectral grating optimization and manufacturing considerations

    NASA Astrophysics Data System (ADS)

    Ziph-Schatzberg, Leah; Swartz, Barry; Warren, Chris; Santman, Jeff; Saleh, Mohammad; Wiggins, Richard; Crifasi, Joe; Comstock, Lovell; Taylor, Kevan

    2015-06-01

    Hyperspectral imaging systems are finding broader applications in both the commercial and aerospace markets. It is becoming clear that to optimize the performance of these systems, their instrument transfer function needs to be tailored for each application. Vis-SWIR systems in the full 400nm to 2500nm waveband present particular design and manufacturing challenges. A single blazed grating is inadequate for a system operating in the full vis-SWIR wavelength range. In addition, optical materials and broad band coatings present a challenge for non-reflective systems. An understanding of the application and wavelengths of interest, combined with a judicious choice of a focal plane array, can then lead to an optimized system for the specific application. The ability to tailor the grating and manufacture a wide variety of grating profiles and substrate shapes becomes a significant performance enabler. This paper will discuss how the use of optical, coating, and grating design/analysis software, combined with grating manufacturing techniques assure meeting high performance requirements for different applications.

  3. Infrared hyperspectral imaging polarimeter using birefringent prisms.

    PubMed

    Craven-Jones, Julia; Kudenov, Michael W; Stapelbroek, Maryn G; Dereniak, Eustace L

    2011-03-10

    A compact short-wavelength and middle-wavelength infrared hyperspectral imaging polarimeter (IHIP) is introduced. The sensor includes a pair of sapphire Wollaston prisms and several high-order retarders to form an imaging Fourier transform spectropolarimeter. The Wollaston prisms serve as a birefringent interferometer with reduced sensitivity to vibration versus an unequal path interferometer, such as a Michelson. Polarimetric data are acquired through the use of channeled spectropolarimetry to modulate the spectrum with the Stokes parameter information. The collected interferogram is Fourier filtered and reconstructed to recover the spatially and spectrally varying Stokes vector data across the image. The IHIP operates over a ±5° field of view and implements a dual-scan false signature reduction technique to suppress polarimetric aliasing artifacts. In this paper, the optical layout and operation of the IHIP sensor are presented in addition to the radiometric, spectral, and polarimetric calibration techniques used with the system. Spectral and spectropolarimetric results from the laboratory and outdoor tests with the instrument are also presented. PMID:21394189

  4. Hyperspectral monitoring of chemically sensitive plant sensors

    NASA Astrophysics Data System (ADS)

    Simmons, Danielle A.

    Current events clearly demonstrate that chemical and biological threats against the public are very real. Automated detection of chemical threats is a necessary component of a system that provides early warning of an attack. Plant biologists are currently developing genetically engineered plants that de-green in the presence of explosives (i.e. TNT) in their environment. The objectives of this thesis are to study the spectral reflectance phenomenology of the plant sensors and to propose requirements for an operational monitoring system using spectral imaging technology. Hyperspectral data were collected under laboratory conditions to determine the key spectral regions in the reflectance spectra associated with the de-greening phenomenon. The collected reflectance spectra were then entered into simulated imagery created using the Rochester Institute of Technology's Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. System performance was studied as a function of pixel size, radiometric noise, spectral waveband dependence and spectral resolution. It was found that a framing array sensor with 40nm wide bands centered at 645 nm, 690 nm, 875 nm, a ground sample distance of 11cm or smaller, and an signal to noise ratio of 250 or better would be sufficient for monitoring bio-sensors deployed under conditions similar to those simulated for this work.

  5. Compressive hyperspectral and multispectral imaging fusion

    NASA Astrophysics Data System (ADS)

    Espitia, Óscar; Castillo, Sergio; Arguello, Henry

    2016-05-01

    Image fusion is a valuable framework which combines two or more images of the same scene from one or multiple sensors, allowing to improve the resolution of the images and increase the interpretable content. In remote sensing a common fusion problem consists of merging hyperspectral (HS) and multispectral (MS) images that involve large amount of redundant data, which ignores the highly correlated structure of the datacube along the spatial and spectral dimensions. Compressive HS and MS systems compress the spectral data in the acquisition step allowing to reduce the data redundancy by using different sampling patterns. This work presents a compressed HS and MS image fusion approach, which uses a high dimensional joint sparse model. The joint sparse model is formulated by combining HS and MS compressive acquisition models. The high spectral and spatial resolution image is reconstructed by using sparse optimization algorithms. Different fusion spectral image scenarios are used to explore the performance of the proposed scheme. Several simulations with synthetic and real datacubes show promising results as the reliable reconstruction of a high spectral and spatial resolution image can be achieved by using as few as just the 50% of the datacube.

  6. Virtual dimensionality analysis for hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Chang, Chein-I.; Lee, Li-Chien; Paylor, Drew

    2015-05-01

    Virtual dimensionality (VD) has been widely used to estimate number of endmembers in the past. Unfortunately, the original idea of VD was developed to specify the number of spectrally distinct signatures in hyperspectral data where there is no provided specific definition of what "spectrally distinct signatures" are. As a result, many techniques developed to estimate VD have produced various values for VD. This paper addresses this issue by develops a target specified VD (TSVD) theory where the value of VD is completely determined by targets of interest. In particular, the VD techniques can be categorized according to targets characterized by eigenvalues/eigenvectors and real target signal sources which are used for a binary composite hypothesis testing problem. For the latter case the Automatic Target Generation Process (ATGP) is particularly used to generate real target signal sources to replace eigenvalues/eigenvectors as signal sources to be used for the binary hypothesis testing problem. In order to find probability distributions under each hypothesis the extreme theory used by Maximum Orthogonal Complement Algorithm (MOCA) is used for their derivations. As a result, VD can be estimated by two types of signals sources, eigenvalues/eigenvectors along with two types of detectors, maximum likelihood detector and Neyman-Pearson detector.

  7. Hyperspectral fluorescence microscopy based on compressed sensing

    NASA Astrophysics Data System (ADS)

    Studer, Vincent; Bobin, Jérome; Chahid, Makhlad; Mousavi, Hamed; Candes, Emmanuel; Dahan, Maxime

    2012-03-01

    In fluorescence microscopy, one can distinguish two kinds of imaging approaches, wide field and raster scan microscopy, differing by their excitation and detection scheme. In both imaging modalities the acquisition is independent of the information content of the image. Rather, the number of acquisitions N, is imposed by the Nyquist-Shannon theorem. However, in practice, many biological images are compressible (or, equivalently here, sparse), meaning that they depend on a number of degrees of freedom K that is smaller that their size N. Recently, the mathematical theory of compressed sensing (CS) has shown how the sensing modality could take advantage of the image sparsity to reconstruct images with no loss of information while largely reducing the number M of acquisition. Here we present a novel fluorescence microscope designed along the principles of CS. It uses a spatial light modulator (DMD) to create structured wide field excitation patterns and a sensitive point detector to measure the emitted fluorescence. On sparse fluorescent samples, we could achieve compression ratio N/M of up to 64, meaning that an image can be reconstructed with a number of measurements of only 1.5 % of its pixel number. Furthemore, we extend our CS acquisition scheme to an hyperspectral imaging system.

  8. Finding archaeological cropmarks: a hyperspectral approach

    NASA Astrophysics Data System (ADS)

    Aqdus, Syed A.; Hanson, William S.; Drummond, Jane

    2007-10-01

    Aerial photography has made the single most important contribution to our improved appreciation of the density, diversity and distribution of archaeological sites in Britain since WWII. This is particularly the case for areas of intensive lowland agriculture where ploughed-out sites are known only from marks in the crops growing above them. However, reconnaissance for such cropmarks is not equally effective throughout the lowlands because of the particular conditions of drier weather, well-drained soils and arable agriculture required before they become visible. In Scotland, for example, there is considerable bias in the discovery and, consequently, known distribution of archaeological sites in favour of the drier eastern side of the country, with its higher percentage of arable agriculture, as opposed to the west with its wetter climate and greater proportion of grazing land. Given that the appearance of cropmarks is linked to moisture stress in growing plants, they are potentially detectable at bandwidths outside the visible and before they become apparent therein. Using a range of imagery (CASI 2, ATM and digital vertical photographic data) from two case study sites in Lowland Scotland to facilitate comparisons, one in the east and one in the west, this paper considers the extent to which hyperspectral imagery can enhance the identification of otherwise invisible archaeological sites.

  9. Anisotropic representations for superresolution of hyperspectral data

    NASA Astrophysics Data System (ADS)

    Bosch, Edward H.; Czaja, Wojciech; Murphy, James M.; Weinberg, Daniel

    2015-05-01

    We develop a method for superresolution based on anisotropic harmonic analysis. Our ambition is to efficiently increase the resolution of an image without blurring or introducing artifacts, and without integrating additional information, such as sub-pixel shifts of the same image at lower resolutions or multimodal images of the same scene. The approach developed in this article is based on analysis of the directional features present in the image that is to be superesolved. The harmonic analytic technique of shearlets is implemented in order to efficiently capture the directional information present in the image, which is then used to provide smooth, accurate images at higher resolutions. Our algorithm is compared to both a recent anisotropic technique based on frame theory and circulant matrices,1 as well as to the standard superresolution method of bicubic interpolation. We evaluate our algorithm on synthetic test images, as well as a hyperspectral image. Our results indicate the superior performance of anisotropic methods, when compared to standard bicubic interpolation.

  10. Unmixing hyperspectral images using Markov random fields

    SciTech Connect

    Eches, Olivier; Dobigeon, Nicolas; Tourneret, Jean-Yves

    2011-03-14

    This paper proposes a new spectral unmixing strategy based on the normal compositional model that exploits the spatial correlations between the image pixels. The pure materials (referred to as endmembers) contained in the image are assumed to be available (they can be obtained by using an appropriate endmember extraction algorithm), while the corresponding fractions (referred to as abundances) are estimated by the proposed algorithm. Due to physical constraints, the abundances have to satisfy positivity and sum-to-one constraints. The image is divided into homogeneous distinct regions having the same statistical properties for the abundance coefficients. The spatial dependencies within each class are modeled thanks to Potts-Markov random fields. Within a Bayesian framework, prior distributions for the abundances and the associated hyperparameters are introduced. A reparametrization of the abundance coefficients is proposed to handle the physical constraints (positivity and sum-to-one) inherent to hyperspectral imagery. The parameters (abundances), hyperparameters (abundance mean and variance for each class) and the classification map indicating the classes of all pixels in the image are inferred from the resulting joint posterior distribution. To overcome the complexity of the joint posterior distribution, Markov chain Monte Carlo methods are used to generate samples asymptotically distributed according to the joint posterior of interest. Simulations conducted on synthetic and real data are presented to illustrate the performance of the proposed algorithm.

  11. Hyperspectral anomaly detection using enhanced global factors

    NASA Astrophysics Data System (ADS)

    Paciencia, Todd J.; Bauer, Kenneth W.

    2016-05-01

    Dimension reduction techniques have become one popular unsupervised approach used towards detecting anomalies in hyperspectral imagery. Although demonstrating promising results in the literature on specific images, these methods can become difficult to directly interpret and often require tuning of their parameters to achieve high performance on a specific set of images. This lack of generality is also compounded by the need to remove noise and atmospheric absorption spectral bands from the image prior to detection. Without a process for this band selection and to make the methods adaptable to different image compositions, performance becomes difficult to maintain across a wider variety of images. Here, we present a framework that uses factor analysis to provide a robust band selection and more meaningful dimension reduction with which to detect anomalies in the imagery. Measurable characteristics of the image are used to create an automated decision process that allows the algorithm to adjust to a particular image, while maintaining high detection performance. The framework and its algorithms are detailed, and results are shown for forest, desert, sea, rural, urban, anomaly-sparse, and anomaly-dense imagery types from different sensors. Additionally, the method is compared to current state-of-the-art methods and is shown to be computationally efficient.

  12. Food inspection using hyperspectral imaging and SVDD

    NASA Astrophysics Data System (ADS)

    Uslu, Faruk Sukru; Binol, Hamidullah; Bal, Abdullah

    2016-05-01

    Nowadays food inspection and evaluation is becoming significant public issue, therefore robust, fast, and environmentally safe methods are studied instead of human visual assessment. Optical sensing is one of the potential methods with the properties of being non-destructive and accurate. As a remote sensing technology, hyperspectral imaging (HSI) is being successfully applied by researchers because of having both spatial and detailed spectral information about studied material. HSI can be used to inspect food quality and safety estimation such as meat quality assessment, quality evaluation of fish, detection of skin tumors on chicken carcasses, and classification of wheat kernels in the food industry. In this paper, we have implied an experiment to detect fat ratio in ground meat via Support Vector Data Description which is an efficient and robust one-class classifier for HSI. The experiments have been implemented on two different ground meat HSI data sets with different fat percentage. Addition to these implementations, we have also applied bagging technique which is mostly used as an ensemble method to improve the prediction ratio. The results show that the proposed methods produce high detection performance for fat ratio in ground meat.

  13. Infrared hyperspectral imaging polarimeter using birefringent prisms.

    PubMed

    Craven-Jones, Julia; Kudenov, Michael W; Stapelbroek, Maryn G; Dereniak, Eustace L

    2011-03-10

    A compact short-wavelength and middle-wavelength infrared hyperspectral imaging polarimeter (IHIP) is introduced. The sensor includes a pair of sapphire Wollaston prisms and several high-order retarders to form an imaging Fourier transform spectropolarimeter. The Wollaston prisms serve as a birefringent interferometer with reduced sensitivity to vibration versus an unequal path interferometer, such as a Michelson. Polarimetric data are acquired through the use of channeled spectropolarimetry to modulate the spectrum with the Stokes parameter information. The collected interferogram is Fourier filtered and reconstructed to recover the spatially and spectrally varying Stokes vector data across the image. The IHIP operates over a ±5° field of view and implements a dual-scan false signature reduction technique to suppress polarimetric aliasing artifacts. In this paper, the optical layout and operation of the IHIP sensor are presented in addition to the radiometric, spectral, and polarimetric calibration techniques used with the system. Spectral and spectropolarimetric results from the laboratory and outdoor tests with the instrument are also presented.

  14. Raman Hyperspectral Imaging of Microfossils: Potential Pitfalls

    PubMed Central

    Olcott Marshall, Alison

    2013-01-01

    Abstract Initially, Raman spectroscopy was a specialized technique used by vibrational spectroscopists; however, due to rapid advancements in instrumentation and imaging techniques over the last few decades, Raman spectrometers are widely available at many institutions, allowing Raman spectroscopy to become a widespread analytical tool in mineralogy and other geological sciences. Hyperspectral imaging, in particular, has become popular due to the fact that Raman spectroscopy can quickly delineate crystallographic and compositional differences in 2-D and 3-D at the micron scale. Although this rapid growth of applications to the Earth sciences has provided great insight across the geological sciences, the ease of application as the instruments become increasingly automated combined with nonspecialists using this techique has resulted in the propagation of errors and misunderstandings throughout the field. For example, the literature now includes misassigned vibration modes, inappropriate spectral processing techniques, confocal depth of laser penetration incorrectly estimated into opaque crystalline solids, and a misconstrued understanding of the anisotropic nature of sp2 carbons. Key Words: Raman spectroscopy—Raman imaging—Confocal Raman spectroscopy—Disordered sp2 carbons—Hematite—Microfossils. Astrobiology 13, 920–931. PMID:24088070

  15. Comparison of hyperspectral change detection algorithms

    NASA Astrophysics Data System (ADS)

    Pieper, M.; Manolakis, D.; Truslow, E.; Cooley, T.; Brueggeman, M.; Weisner, A.; Jacobson, J.

    2015-09-01

    There are a multitude of civilian and military applications for the detection of anomalous changes in hyper-spectral images. Anomalous changes occur when the material within a pixel is replaced. Environmental factors that change over time, such as illumination, will affect the radiance of all the pixels in a scene, despite the materials within remaining constant. The goal of an anomalous change detection algorithm is to suppress changes caused by the environment, and detect pixels where the materials within have changed. Anomalous change detection is a two step process. Two co-registered images of a scene are first transformed to maximize the overall correlation between the images, then an anomalous change detector (ACD) is applied to the transformed images. The transforms maximize the correlation between the two images to attenuate the environmental differences that distract from the anomalous changes of importance. Several categories of transforms with different optimization parameters are discussed and compared. One of two types of ACDs are then applied to the transformed images. The first ACD uses the difference of the two transformed images. The second concatenates the spectra of two images and uses an aggregated ACD. A comparison of the two ACD methods and their effectiveness with the different transforms is done for the first time.

  16. Visible-Infrared Hyperspectral Image Projector

    NASA Technical Reports Server (NTRS)

    Bolcar, Matthew

    2013-01-01

    The VisIR HIP generates spatially-spectrally complex scenes. The generated scenes simulate real-world targets viewed by various remote sensing instruments. The VisIR HIP consists of two subsystems: a spectral engine and a spatial engine. The spectral engine generates spectrally complex uniform illumination that spans the wavelength range between 380 nm and 1,600 nm. The spatial engine generates two-dimensional gray-scale scenes. When combined, the two engines are capable of producing two-dimensional scenes with a unique spectrum at each pixel. The VisIR HIP can be used to calibrate any spectrally sensitive remote-sensing instrument. Tests were conducted on the Wide-field Imaging Interferometer Testbed at NASA s Goddard Space Flight Center. The device is a variation of the calibrated hyperspectral image projector developed by the National Institute of Standards and Technology in Gaithersburg, MD. It uses Gooch & Housego Visible and Infrared OL490 Agile Light Sources to generate arbitrary spectra. The two light sources are coupled to a digital light processing (DLP(TradeMark)) digital mirror device (DMD) that serves as the spatial engine. Scenes are displayed on the DMD synchronously with desired spectrum. Scene/spectrum combinations are displayed in rapid succession, over time intervals that are short compared to the integration time of the system under test.

  17. Bayesian fusion of hyperspectral astronomical images

    NASA Astrophysics Data System (ADS)

    Jalobeanu, André; Petremand, Matthieu; Collet, Christophe

    2011-03-01

    The new integral-field spectrograph MUSE will acquire hyperspectral images of the deep sky, requiring huge amounts of raw data to be processed, posing a challenge to modern algorithms and technologies. In order to achieve the required sensitivity to observe very faint objects, many observations need to be reconstructed and co-added into a single data cube. In this paper, we propose a new fusion method to combine all raw observations while removing most of the instrumental and observational artifacts such as blur or cosmic rays. Thus, the results can be accurately and consistently analyzed by astronomers. We use a Bayesian framework allowing for optimal data fusion and uncertainty estimation. The knowledge of the instrument allows to write the direct problem (data acquisition on the detector matrix) and then to invert it through Bayesian inference, assuming a smoothness prior for the data cube to be reconstructed. Compared to existing methods, the originality of the new technique is in the propagation of errors throughout the fusion pipeline and the ability to deal with various acquisition parameters for each input image. For this paper, we focus on small-size, simulated astronomical observations with varying parameters to validate the image formation model, the reconstruction algorithm and the predicted uncertainties.

  18. Hyperspectral Imaging of fecal contamination on chickens

    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 scanning chickens during processing to help prevent contaminated food from getting to the table. ProVision is working with Sanderson Farms of Mississippi and the U.S. Department of Agriculture. ProVision has a record in its spectral library of the unique spectral signature of fecal contamination, so chickens can be scanned and those with a positive reading can be separated. HSI sensors can also determine the quantity of surface contamination. Research in this application is quite advanced, and ProVision is working on a licensing agreement for the technology. The potential for future use of this equipment in food processing and food safety is enormous.

  19. Directly Estimating Endmembers for Compressive Hyperspectral Images

    PubMed Central

    Xu, Hongwei; Fu, Ning; Qiao, Liyan; Peng, Xiyuan

    2015-01-01

    The large volume of hyperspectral images (HSI) generated creates huge challenges for transmission and storage, making data compression more and more important. Compressive Sensing (CS) is an effective data compression technology that shows that when a signal is sparse in some basis, only a small number of measurements are needed for exact signal recovery. Distributed CS (DCS) takes advantage of both intra- and inter- signal correlations to reduce the number of measurements needed for multichannel-signal recovery. HSI can be observed by the DCS framework to reduce the volume of data significantly. The traditional method for estimating endmembers (spectral information) first recovers the images from the compressive HSI and then estimates endmembers via the recovered images. The recovery step takes considerable time and introduces errors into the estimation step. In this paper, we propose a novel method, by designing a type of coherent measurement matrix, to estimate endmembers directly from the compressively observed HSI data via convex geometry (CG) approaches without recovering the images. Numerical simulations show that the proposed method outperforms the traditional method with better estimation speed and better (or comparable) accuracy in both noisy and noiseless cases. PMID:25905699

  20. Standoff midwave infrared hyperspectral imaging of ship plumes

    NASA Astrophysics Data System (ADS)

    Gagnon, Marc-André; Gagnon, Jean-Philippe; Tremblay, Pierre; Savary, Simon; Farley, Vincent; Guyot, Éric; Lagueux, Philippe; Chamberland, Martin; Marcotte, Frédérick

    2016-05-01

    Characterization of ship plumes is very challenging due to the great variety of ships, fuel, and fuel grades, as well as the extent of a gas plume. In this work, imaging of ship plumes from an operating ferry boat was carried out using standoff midwave (3-5 μm) infrared hyperspectral imaging. Quantitative chemical imaging of combustion gases was achieved by fitting a radiative transfer model. Combustion efficiency maps and mass flow rates are presented for carbon monoxide (CO) and carbon dioxide (CO2). The results illustrate how valuable information about the combustion process of a ship engine can be successfully obtained using passive hyperspectral remote sensing imaging.

  1. Detection of gaseous plumes in airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Agassi, Eyal; Hirsch, Eitan; Chamberland, Martin; Gagnon, Marc-André; Eichstaedt, Holger

    2016-05-01

    The thermal hyperspectral sensor Hyper-Cam was mounted on a light aircraft and measured continuous releases of several atmospheric tracers from a height of 2 km. A unique detection algorithm that eliminates the need for clear background estimation was operated over the acquired data with excellent detection results. The data-cubes were acquired in a "target mode", which is a unique method of operation of the Hyper-Cam sensor. This method provides multiple views of the plume which can be exploited to enhance the detection performance. These encouraging results demonstrate the utility of airborne LWIR hyperspectral imaging for efficient detection and mapping of effluent gases for environmental monitoring.

  2. Emissivity retrieval from indoor hyperspectral imaging of mineral grains

    NASA Astrophysics Data System (ADS)

    Yousefi, Bardia; Sojasi, Saeed; Ibarra Castanedo, Clemente; Beaudoin, Georges; Huot, François; Maldague, Xavier P. V.; Chamberland, Martin; Lalonde, Erik

    2016-05-01

    The proposed approach addresses the problem of retrieving the emissivity of hyperspectral data in the spectroscopic imageries from indoor experiments. This methodology was tested on experimental data that have been recorded with hyperspectral images working in visible/near infrared and long-wave infrared bands. The proposed technique provides a framework for computing down-welling spectral radiance applying non-negative matrix factorization (NMF) analysis. It provides the necessary means for the non-uniform correction of active thermographical experiments. The obtained results indicate promising accuracy. In addition, the application of the proposed technique is not limited to non-uniform heating spectroscopy but to uniform spectroscopy as well.

  3. Hyperspectral imaging in the infrared using LIFTIRS. Revision 1

    SciTech Connect

    Bennett, C.L.; Carter, M.R.; Fields, D.J.

    1995-10-01

    In this article the ideal performance for various possible designs for imaging spectrometers is discussed. Recent characterization measurements made with LIFTIRS, the Livermore Imaging Fourier Transform InfraRed Spectrometer are also presented. Hyperspectral imagers, characterized by having a large number of spectral channels, enable definitive identification and quantitative measurement of the composition of objects in the field of view. Infrared hyperspectral imagers are particularly useful for remote chemical analysis, since almost all molecules have characteristic rotation-vibration spectra in the infrared, and a broad portion of the so-called fingerprint region of the infrared spectrum lies where the atmosphere is relatively transparent, between 8 and 13 {micro}m.

  4. Methodology for hyperspectral image classification using novel neural network

    SciTech Connect

    Subramanian, S., Gat, N., Sheffield, M.,; Barhen, J.; Toomarian, N.

    1997-04-01

    A novel feed forward neural network is used to classify hyperspectral data from the AVIRIS sector. The network applies an alternating direction singular value decomposition technique to achieve rapid training times (few seconds per class). Very few samples (10-12) are required for training. 100% accurate classification is obtained using test data sets. The methodology combines this rapid training neural network together with data reduction and maximal feature separation techniques such as principal component analysis and simultaneous diagonalization of covariance matrices, for rapid and accurate classification of large hyperspectral images. The results are compared to those of standard statistical classifiers. 21 refs., 3 figs., 5 tabs.

  5. Hyperspectral imagery classification based on relevance vector machines

    NASA Astrophysics Data System (ADS)

    Yang, Guopeng; Yu, Xuchu; Feng, Wufa; Xu, Weixiao; Zhang, Pengqiang

    2009-10-01

    The relevance vector machine is sparse model in the Bayesian framework, its mathematics model doesn't have regularization coefficient and its kernel functions don't need to satisfy Mercer's condition. RVM present the good generalization performance, and its predictions are probabilistic. In this paper, a hyperspectral imagery classification method based on the relevance machine is brought forward. We introduce the sparse Bayesian classification model, regard the RVM learning as the maximization of marginal likelihood, and select the fast sequential sparse Bayesian learning algorithm. Through the experiment of PHI imagery classification, the advantages of the relevance machine used in hyperspectral imagery classification are given out.

  6. Assessing the capabilities of hyperspectral remote sensing to map oil films on waters

    NASA Astrophysics Data System (ADS)

    Liu, Bingxin; Li, Ying; Zhu, Xueyuan

    2014-11-01

    The harm of oil spills has caused extensive public concern. Remote sensing technology has become one of the most effective means of monitoring oil spill. However, how to evaluate the information extraction capabilities of various sensors and choose the most effective one has become an important issue. The current evaluation of sensors to detect oil films was mainly using in-situ measured spectra as a reference to determine the favorable band, but ignoring the effects of environmental noise and spectral response function. To understand the precision and accuracy of environment variables acquired from remote sensing, it is important to evaluate the target detection sensitivity of the entire sensor-air-target system corresponding to the change of reflectivity. The measurement data associated with the evaluation is environmental noise equivalent reflectance difference (NEΔRE ), which depends on the instrument signal to noise ratio(SNR) and other image data noise (such as atmospheric variables, scattered sky light scattering and direct sunlight, etc.). Hyperion remote sensing data is taken as an example for evaluation of its oil spill detection capabilities with the prerequisite that the impact of the spatial resolution is ignored. In order to evaluate the sensor's sensitivity of the film of water, the reflectance spectral data of light diesel and crude oil film were used. To obtain Hyperion reflectance data, we used FLAASH to do the atmospheric correction. The spectral response functions of Hyperion sensor was used for filtering the measured reflectance of the oil films to the theoretic spectral response. Then, these spectral response spectra were normalized to NEΔRE, according to which, the sensitivity of the sensor in oil film detecting could be evaluated. For crude oil, the range for Hyperion sensor to identify the film is within the wavelength from 518nm to 610nm (Band 17 to Band 26 of Hyperion sensors), within which the thin film and thick film can also be

  7. Hyperspectral image reconstruction using RGB color for foodborne pathogen detection on agar plates

    NASA Astrophysics Data System (ADS)

    Yoon, Seung-Chul; Shin, Tae-Sung; Park, Bosoon; Lawrence, Kurt C.; Heitschmidt, Gerald W.

    2014-03-01

    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 spectra measured in the visible and near-infrared spectral range from 400 and 1,000 nm (473 narrow spectral bands). Multivariate regression methods were used to estimate and predict hyperspectral data from RGB color values. The six representative non-O157 Shiga-toxin producing Eschetichia coli (STEC) serogroups (O26, O45, O103, O111, O121, and O145) were grown on Rainbow agar plates. A line-scan pushbroom hyperspectral image sensor was used to scan 36 agar plates grown with pure STEC colonies at each plate. The 36 hyperspectral images of the agar plates were divided in half to create training and test sets. The mean Rsquared value for hyperspectral image estimation was about 0.98 in the spectral range between 400 and 700 nm for linear, quadratic and cubic polynomial regression models and the detection accuracy of the hyperspectral image classification model with the principal component analysis and k-nearest neighbors for the test set was up to 92% (99% with the original hyperspectral images). Thus, the results of the study suggested that color-based detection may be viable as a multispectral imaging solution without much loss of prediction accuracy compared to hyperspectral imaging.

  8. Improved Scanners for Microscopic Hyperspectral Imaging

    NASA Technical Reports Server (NTRS)

    Mao, Chengye

    2009-01-01

    Improved scanners to be incorporated into hyperspectral microscope-based imaging systems have been invented. Heretofore, in microscopic imaging, including spectral imaging, it has been customary to either move the specimen relative to the optical assembly that includes the microscope or else move the entire assembly relative to the specimen. It becomes extremely difficult to control such scanning when submicron translation increments are required, because the high magnification of the microscope enlarges all movements in the specimen image on the focal plane. To overcome this difficulty, in a system based on this invention, no attempt would be made to move either the specimen or the optical assembly. Instead, an objective lens would be moved within the assembly so as to cause translation of the image at the focal plane: the effect would be equivalent to scanning in the focal plane. The upper part of the figure depicts a generic proposed microscope-based hyperspectral imaging system incorporating the invention. The optical assembly of this system would include an objective lens (normally, a microscope objective lens) and a charge-coupled-device (CCD) camera. The objective lens would be mounted on a servomotor-driven translation stage, which would be capable of moving the lens in precisely controlled increments, relative to the camera, parallel to the focal-plane scan axis. The output of the CCD camera would be digitized and fed to a frame grabber in a computer. The computer would store the frame-grabber output for subsequent viewing and/or processing of images. The computer would contain a position-control interface board, through which it would control the servomotor. There are several versions of the invention. An essential feature common to all versions is that the stationary optical subassembly containing the camera would also contain a spatial window, at the focal plane of the objective lens, that would pass only a selected portion of the image. In one version

  9. Hyperspectral image analysis using artificial color

    NASA Astrophysics Data System (ADS)

    Fu, Jian; Caulfield, H. John; Wu, Dongsheng; Tadesse, Wubishet

    2010-03-01

    By definition, HSC (HyperSpectral Camera) images are much richer in spectral data than, say, a COTS (Commercial-Off-The-Shelf) color camera. But data are not information. If we do the task right, useful information can be derived from the data in HSC images. Nature faced essentially the identical problem. The incident light is so complex spectrally that measuring it with high resolution would provide far more data than animals can handle in real time. Nature's solution was to do irreversible POCS (Projections Onto Convex Sets) to achieve huge reductions in data with minimal reduction in information. Thus we can arrange for our manmade systems to do what nature did - project the HSC image onto two or more broad, overlapping curves. The task we have undertaken in the last few years is to develop this idea that we call Artificial Color. What we report here is the use of the measured HSC image data projected onto two or three convex, overlapping, broad curves in analogy with the sensitivity curves of human cone cells. Testing two quite different HSC images in that manner produced the desired result: good discrimination or segmentation that can be done very simply and hence are likely to be doable in real time with specialized computers. Using POCS on the HSC data to reduce the processing complexity produced excellent discrimination in those two cases. For technical reasons discussed here, the figures of merit for the kind of pattern recognition we use is incommensurate with the figures of merit of conventional pattern recognition. We used some force fitting to make a comparison nevertheless, because it shows what is also obvious qualitatively. In our tasks our method works better.

  10. Fast, electrically tunable filters for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Liberman, V.; Parameswaran, L.; Gear, C.; Cabral, A.; Rothschild, M.

    2014-06-01

    Tunable, narrow-wavelength spectral filters with a ms response in the mid-wave/long-wave infrared (MW/LWIR) are an enabling technology for hyperspectral imaging systems. Few commercial off-the-shelf (COTS) components for this application exist, including filter wheels, movable gratings, and Fabry-Perot (FP) etalon-based devices. These devices can be bulky, fragile and often do not have the required response speed. Here, we present a fundamentally different approach for tunable reflective IR filters, based on coupling subwavelength plasmonic antenna arrays with liquid crystals (LCs). Our device operates in reflective mode and derives its narrow bandwidth from diffractive coupling of individual antenna elements. The wavelength tunability of the device arises from electrically-induced re-orientation of the LC material in intimate contact with antenna array. This re-orientation, in turn, induces a change in the local dielectric environment of the antenna array, leading to a wavelength shift. We will first present results of full-field optimization of micron-size antenna geometries to account for complex 3D LC anisotropy. We have fabricated these antenna arrays on IR-transparent CaF2 substrates utilizing electron beam lithography, and have demonstrated tunability using 5CB, a commercially available LC. However, the design can be extended to high-birefringence liquid crystals for an increased tuning range. Our initial results demonstrate <60% peak reflectance in the 4- 6 μm wavelength range with a tunability of 0.2 μm with re-orientation of the surface alignment layers. Preliminary electrical switching has been demonstrated and is being optimized.

  11. Infrared hyperspectral imaging sensor for gas detection

    NASA Astrophysics Data System (ADS)

    Hinnrichs, Michele

    2000-11-01

    A small light weight man portable imaging spectrometer has many applications; gas leak detection, flare analysis, threat warning, chemical agent detection, just to name a few. With support from the US Air Force and Navy, Pacific Advanced Technology has developed a small man portable hyperspectral imaging sensor with an embedded DSP processor for real time processing that is capable of remotely imaging various targets such as gas plums, flames and camouflaged targets. Based upon their spectral signature the species and concentration of gases can be determined. This system has been field tested at numerous places including White Mountain, CA, Edwards AFB, and Vandenberg AFB. Recently evaluation of the system for gas detection has been performed. This paper presents these results. The system uses a conventional infrared camera fitted with a diffractive optic that images as well as disperses the incident radiation to form spectral images that are collected in band sequential mode. Because the diffractive optic performs both imaging and spectral filtering, the lens system consists of only a single element that is small, light weight and robust, thus allowing man portability. The number of spectral bands are programmable such that only those bands of interest need to be collected. The system is entirely passive, therefore, easily used in a covert operation. Currently Pacific Advanced Technology is working on the next generation of this camera system that will have both an embedded processor as well as an embedded digital signal processor in a small hand held camera configuration. This will allow the implementation of signal and image processing algorithms for gas detection and identification in real time. This paper presents field test data on gas detection and identification as well as discuss the signal and image processing used to enhance the gas visibility. Flow rates as low as 0.01 cubic feet per minute have been imaged with this system.

  12. Hyperspectral remote sensing of wild oyster reefs

    NASA Astrophysics Data System (ADS)

    Le Bris, Anthony; Rosa, Philippe; Lerouxel, Astrid; Cognie, Bruno; Gernez, Pierre; Launeau, Patrick; Robin, Marc; Barillé, Laurent

    2016-04-01

    The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generated changes in the structure and functioning of intertidal ecosystems. Considered as an invasive species and a trophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmers following recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wild oyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map two contrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs in muddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library, collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral Angle Mapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOT satellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontal oysters in the rocky area were correctly classified but the detection was less efficient for vertical oysters in muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrally degraded HySpex data, it was clear that the spectral resolution was more important than the spatial resolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining the misclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps of oyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remote sensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers. This work highlights the interest of developing remote sensing techniques for aquaculture applications in coastal

  13. Airborne Hyperspectral Imaging of Seagrass and Coral Reef

    NASA Astrophysics Data System (ADS)

    Merrill, J.; Pan, Z.; Mewes, T.; Herwitz, S.

    2013-12-01

    This talk presents the process of project preparation, airborne data collection, data pre-processing and comparative analysis of a series of airborne hyperspectral projects focused on the mapping of seagrass and coral reef communities in the Florida Keys. As part of a series of large collaborative projects funded by the NASA ROSES program and the Florida Fish and Wildlife Conservation Commission and administered by the NASA UAV Collaborative, a series of airborne hyperspectral datasets were collected over six sites in the Florida Keys in May 2012, October 2012 and May 2013 by Galileo Group, Inc. using a manned Cessna 172 and NASA's SIERRA Unmanned Aerial Vehicle. Precise solar and tidal data were used to calculate airborne collection parameters and develop flight plans designed to optimize data quality. Two independent Visible and Near-Infrared (VNIR) hyperspectral imaging systems covering 400-100nm were used to collect imagery over six Areas of Interest (AOIs). Multiple collections were performed over all sites across strict solar windows in the mornings and afternoons. Independently developed pre-processing algorithms were employed to radiometrically correct, synchronize and georectify individual flight lines which were then combined into color balanced mosaics for each Area of Interest. The use of two different hyperspectral sensor as well as environmental variations between each collection allow for the comparative analysis of data quality as well as the iterative refinement of flight planning and collection parameters.

  14. Hyperspectral Imaging Sensors and the Marine Coastal Zone

    NASA Technical Reports Server (NTRS)

    Richardson, Laurie L.

    2000-01-01

    Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum, in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.

  15. Models of formation and some algorithms of hyperspectral image processing

    NASA Astrophysics Data System (ADS)

    Achmetov, R. N.; Stratilatov, N. R.; Yudakov, A. A.; Vezenov, V. I.; Eremeev, V. V.

    2014-12-01

    Algorithms and information technologies for processing Earth hyperspectral imagery are presented. Several new approaches are discussed. Peculiar properties of processing the hyperspectral imagery, such as multifold signal-to-noise reduction, atmospheric distortions, access to spectral characteristics of every image point, and high dimensionality of data, were studied. Different measures of similarity between individual hyperspectral image points and the effect of additive uncorrelated noise on these measures were analyzed. It was shown that these measures are substantially affected by noise, and a new measure free of this disadvantage was proposed. The problem of detecting the observed scene object boundaries, based on comparing the spectral characteristics of image points, is considered. It was shown that contours are processed much better when spectral characteristics are used instead of energy brightness. A statistical approach to the correction of atmospheric distortions, which makes it possible to solve the stated problem based on analysis of a distorted image in contrast to analytical multiparametric models, was proposed. Several algorithms used to integrate spectral zonal images with data from other survey systems, which make it possible to image observed scene objects with a higher quality, are considered. Quality characteristics of hyperspectral data processing were proposed and studied.

  16. Detecting red blotch disease in grape leaves using hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Mehrubeoglu, Mehrube; Orlebeck, Keith; Zemlan, Michael J.; Autran, Wesley

    2016-05-01

    Red blotch disease is a viral disease that affects grapevines. Symptoms appear as irregular blotches on grape leaves with pink and red veins on the underside of the leaves. Red blotch disease causes a reduction in the accumulation of sugar in grapevines affecting the quality of grapes and resulting in delayed harvest. Detecting and monitoring this disease early is important for grapevine management. This work focuses on the use of hyperspectral imaging for detection and mapping red blotch disease in grape leaves. Grape leaves with known red blotch disease have been imaged with a portable hyperspectral imaging system both on and off the vine to investigate the spectral signature of red blotch disease as well as to identify the diseased areas on the leaves. Modified reflectance calculated at spectral bands corresponding to 566 nm (green) and 628 nm (red), and modified reflectance ratios computed at two sets of bands (566 nm / 628 nm, 680 nm / 738 nm) were selected as effective features to differentiate red blotch from healthy-looking and dry leaf. These two modified reflectance and two ratios of modified reflectance values were then used to train the support vector machine classifier in a supervised learning scheme. Once the SVM classifier was defined, two-class classification was achieved for grape leaf hyperspectral images. Identification of the red blotch disease on grape leaves as well as mapping different stages of the disease using hyperspectral imaging are presented in this paper.

  17. Advances in Hyperspectral and Multispectral Image Fusion and Spectral Unmixing

    NASA Astrophysics Data System (ADS)

    Lanaras, C.; Baltsavias, E.; Schindler, K.

    2015-08-01

    In this work, we jointly process high spectral and high geometric resolution images and exploit their synergies to (a) generate a fused image of high spectral and geometric resolution; and (b) improve (linear) spectral unmixing of hyperspectral endmembers at subpixel level w.r.t. the pixel size of the hyperspectral image. We assume that the two images are radiometrically corrected and geometrically co-registered. The scientific contributions of this work are (a) a simultaneous approach to image fusion and hyperspectral unmixing, (b) enforcing several physically plausible constraints during unmixing that are all well-known, but typically not used in combination, and (c) the use of efficient, state-of-the-art mathematical optimization tools to implement the processing. The results of our joint fusion and unmixing has the potential to enable more accurate and detailed semantic interpretation of objects and their properties in hyperspectral and multispectral images, with applications in environmental mapping, monitoring and change detection. In our experiments, the proposed method always improves the fusion compared to competing methods, reducing RMSE between 4% and 53%.

  18. Airborne Hyperspectral Remote Sensing for Identification Grassland Vegetation

    NASA Astrophysics Data System (ADS)

    Burai, P.; Tomor, T.; Bekő, L.; Deák, B.

    2015-08-01

    In our study we classified grassland vegetation types of an alkali landscape (Eastern Hungary), using different image classification methods for hyperspectral data. Our aim was to test the applicability of hyperspectral data in this complex system using various image classification methods. To reach the highest classification accuracy, we compared the performance of traditional image classifiers, machine learning algorithm, feature extraction (MNF-transformation) and various sizes of training dataset. Hyperspectral images were acquired by an AISA EAGLE II hyperspectral sensor of 128 contiguous bands (400-1000 nm), a spectral sampling of 5 nm bandwidth and a ground pixel size of 1 m. We used twenty vegetation classes which were compiled based on the characteristic dominant species, canopy height, and total vegetation cover. Image classification was applied to the original and MNF (minimum noise fraction) transformed dataset using various training sample sizes between 10 and 30 pixels. In the case of the original bands, both SVM and RF classifiers provided high accuracy for almost all classes irrespectively of the number of the training pixels. We found that SVM and RF produced the best accuracy with the first nine MNF transformed bands. Our results suggest that in complex open landscapes, application of SVM can be a feasible solution, as this method provides higher accuracies compared to RF and MLC. SVM was not sensitive for the size of the training samples, which makes it an adequate tool for cases when the available number of training pixels are limited for some classes.

  19. Hyperspectral radiance simulator: cloudy radiance modeling and beyond

    NASA Astrophysics Data System (ADS)

    Huang, Hung-Lung; Tobin, David C.; Li, Jun; Olson, Erik R.; Baggett, Kevin; Huang, Bormin; Mecikalski, John; Knuteson, Robert O.; Osborne, Brian; Posselt, Derek; Antonelli, Paolo B.; Revercomb, Henry E.; Smith, William L.; Yang, Ping

    2003-04-01

    Current and future advanced atmospheric profile sounding and imaging instruments are evolving to enable global or hemispherical hyperspectral resolution measurements from space. The NASA/Navy/NOAA Geosynchronous Imaging FTS (GIFTS) for EO-3, NOAA Hyperspectral Environmental Sounder (HES) for GOES-R, and the currently operational Atmospheric Infrared Sounder (AIRS) on the NASA's Aqua Spacecraft will collect infrared high-spectral resolution/hyperspectral radiance spectra for remote sensing of the atmosphere, clouds, land, and ocean surfaces. These semi-continuous infrared high spectral- resolution/hyperspectral radiances will provide unprecedented information in the infrared region that is highly sensitive to absorption and emission of clouds. For sounding the atmospheric profiles one must perform cloud clearing or model the radiative effects of cloud explicitly if sounding is desired under cloud-contaminated conditions. We will describe the approach for modeling cloud attenuation in a fast-parameterized forward model that treats clouds as an additional absorber. Together with the usual clear forward model spectroscopic inputs, cloud altitude, effective particle size and shape and its ice or liquid water content are required input variables. Based on this efficient cloudy radiative transfer model, the simulation of the spatial and temporal coherent radiance images in three dimensions becomes possible. We will further explain how these 3-D GIFTS radiance cubes are used as test bed for a variety of trade studies.

  20. The challenges of analysing blood stains with hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Kuula, J.; Puupponen, H.-H.; Rinta, H.; Pölönen, I.

    2014-06-01

    Hyperspectral imaging is a potential noninvasive technology for detecting, separating and identifying various substances. In the forensic and military medicine and other CBRNE related use it could be a potential method for analyzing blood and for scanning other human based fluids. For example, it would be valuable to easily detect whether some traces of blood are from one or more persons or if there are some irrelevant substances or anomalies in the blood. This article represents an experiment of separating four persons' blood stains on a white cotton fabric with a SWIR hyperspectral camera and FT-NIR spectrometer. Each tested sample includes standardized 75 _l of 100 % blood. The results suggest that on the basis of the amount of erythrocytes in the blood, different people's blood might be separable by hyperspectral analysis. And, referring to the indication given by erythrocytes, there might be a possibility to find some other traces in the blood as well. However, these assumptions need to be verified with wider tests, as the number of samples in the study was small. According to the study there also seems to be several biological, chemical and physical factors which affect alone and together on the hyperspectral analyzing results of blood on fabric textures, and these factors need to be considered before making any further conclusions on the analysis of blood on various materials.

  1. LED lighting for use in multispectral and hyperspectral imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Lighting for machine vision and hyperspectral imaging is an important component for collecting high quality imagery. However, it is often given minimal consideration in the overall design of an imaging system. Tungsten-halogens lamps are the most common source of illumination for broad spectrum appl...

  2. Hyperspectral imaging and quantitative analysis for prostate cancer detection

    PubMed Central

    Akbari, Hamed; Halig, Luma V.; Schuster, David M.; Osunkoya, Adeboye; Master, Viraj; Nieh, Peter T.; Chen, Georgia Z.

    2012-01-01

    Abstract. Hyperspectral imaging (HSI) is an emerging modality for various medical applications. Its spectroscopic data might be able to be used to noninvasively detect cancer. Quantitative analysis is often necessary in order to differentiate healthy from diseased tissue. We propose the use of an advanced image processing and classification method in order to analyze hyperspectral image data for prostate cancer detection. The spectral signatures were extracted and evaluated in both cancerous and normal tissue. Least squares support vector machines were developed and evaluated for classifying hyperspectral data in order to enhance the detection of cancer tissue. This method was used to detect prostate cancer in tumor-bearing mice and on pathology slides. Spatially resolved images were created to highlight the differences of the reflectance properties of cancer versus those of normal tissue. Preliminary results with 11 mice showed that the sensitivity and specificity of the hyperspectral image classification method are 92.8% to 2.0% and 96.9% to 1.3%, respectively. Therefore, this imaging method may be able to help physicians to dissect malignant regions with a safe margin and to evaluate the tumor bed after resection. This pilot study may lead to advances in the optical diagnosis of prostate cancer using HSI technology. PMID:22894488

  3. a Review of Hyperspectral Imaging in Close Range Applications

    NASA Astrophysics Data System (ADS)

    Kurz, T. H.; Buckley, S. J.

    2016-06-01

    Hyperspectral imaging is an established method for material mapping, which has been conventionally applied from airborne and spaceborne platforms for a range of applications, including mineral and vegetation mapping, change detection and environmental studies. The main advantage of lightweight hyperspectral imagers lies in the flexibility to deploy them from various platforms (terrestrial imaging and from unmanned aerial vehicles; UAVs), as well as the high spectral resolution to cover an expanding wavelength range. In addition, spatial resolution allows object sampling distances from micrometres to tens of centimetres - complementary to conventional nadir-looking systems. When this new type of imaging device was initially released, few instruments were available and the applicability and potential of the method was restricted. Today, a wider range of instruments, with a range of specifications, is available, with significant improvements over the first generation of technology. In this contribution, the state-of-the-art of hyperspectral imaging will be reviewed from a close range measurement perspective, highlighting how the method supplements geometric modelling techniques. An overview of the processing workflow, adjusted to the more complex close range imaging scenario will be given. This includes the integration with 3D laser scanning and photogrammetric models to provide a geometric framework and real world coordinate system for the hyperspectral imagery.

  4. CRSP Hyperspectral Stripe Array Targets: Preliminary Results and Analysis

    NASA Technical Reports Server (NTRS)

    Terrie, Gregory; Jenner, Jeff; Tate, Steve; Muston, Shaun; Schaefer, Jason; Grant, Brennan; Sellers, Richard

    2000-01-01

    Objectives of this program: Assess the capability of a spaceborne hyperspectral sensor/algorithm system to perform target detection; Provide information to guide the design and construction of surrogate targets and stripe arrays; Target development cost of less than 50,000.

  5. Hyperspectral Imaging of Forest Resources: The Malaysian Experience

    NASA Astrophysics Data System (ADS)

    Mohd Hasmadi, I.; Kamaruzaman, J.

    2008-08-01

    Remote sensing using satellite and aircraft images are well established technology. Remote sensing application of hyperspectral imaging, however, is relatively new to Malaysian forestry. Through a wide range of wavelengths hyperspectral data are precisely capable to capture narrow bands of spectra. Airborne sensors typically offer greatly enhanced spatial and spectral resolution over their satellite counterparts, and able to control experimental design closely during image acquisition. The first study using hyperspectral imaging for forest inventory in Malaysia were conducted by Professor Hj. Kamaruzaman from the Faculty of Forestry, Universiti Putra Malaysia in 2002 using the AISA sensor manufactured by Specim Ltd, Finland. The main objective has been to develop methods that are directly suited for practical tropical forestry application at the high level of accuracy. Forest inventory and tree classification including development of single spectral signatures have been the most important interest at the current practices. Experiences from the studies showed that retrieval of timber volume and tree discrimination using this system is well and some or rather is better than other remote sensing methods. This article reviews the research and application of airborne hyperspectral remote sensing for forest survey and assessment in Malaysia.

  6. Study on full-polarization hyperspectral imaging technology

    NASA Astrophysics Data System (ADS)

    Wei, Xiangyu; Zhou, Qiang; Zhong, Tenghui; Li, Yubo

    2014-02-01

    Since full-polarization parameter measurement can not be well combined with hyperspectral imaging technology yet , a new full-polarization hyperspectral imaging measurement structure using a dual optical path system was investigated. We utilized the hyperspectral1 interference imaging technology and polarization modulation technology based on electro-optic effect in our research. The polarization information, spectral information and spatial image information were acquired at the same time, which means the simultaneous measurement of hyperspectral information and full-polarization parameter was achieved. In this artical, the principle of the full-polarization parameter measurement was introduced at first. Then the experiment setup was shown and the optical elements were illustrated. Also,the detailed formula derivation steps of the full-Stokes vector was given. At last, some computer simulation data and experimental results were given. Through the combination of spectral imaging and full-polarization parameter measurement, the detecting information of the object is greatly enriched. This work will definitely be helpful to many optical remote sensing technology areas such as resources survey, environmental monitoring and military reconnaissan.

  7. Spectral gating in hyperspectral-augmented target tracking

    NASA Astrophysics Data System (ADS)

    Soliman, Neil A.; Mendenhall, Michael J.; Vasquez, Juan R.

    2008-04-01

    Hyperspectral images provide scientists and engineers with the capability of precise material identification in remote sensing applications. One can leverage this data for precise track identification (ID) and incorporate the high-confidence ID in the tracking process. Our previous work demonstrates that hyperspectral-aided tracking outperforms kinematic-only tracking where multiple ambiguous situations exist. We develop a novel gating concept for hyperspectral measurements, similar in concept to the gating of the Mahalanobis distance computed from the Kalman residuals. Our spectral gating definition is based on the distance between the spectral distribution of the class ID of a track and the spectral distribution of the class ID resulting from the classification of a measurement. We further incorporate the distance between each class distribution (in spectral space) in the track association portion of our hyperspectral-aided tracker. Since functional forms of the joint probability distribution function do not exist, similarity measures such as the Kullback-Leibler divergence or Bhattacharyya distance cannot be used. Instead, we compute all pair-wise distances between all samples of the two classes and then summarize these distances in a meaningful way. This article presents our novel spectral gating approach and its use in track association. It further explores different similarity measures and their effect on spectral gating and track association.

  8. Portable hyperspectral imager for assessment of skin disorders: preliminary measurements

    NASA Astrophysics Data System (ADS)

    Beach, James M.; Lanoue, Mark A.; Brabham, Kori; Khoobehi, Bahram

    2005-04-01

    Oxygenation of the facial skin was evaluated in rosacea using a hyperspectral camera. A portable imaging system utilizing crossed-polarization optics for illumination and recording is described. Relative oxygen saturation was determined from rosacea features and compared with normal skin. Saturation maps and light absorption spectra showed a significant increase in the oxygen saturation of the blood in rosacea-affected skin.

  9. Recent Advances in Techniques for Hyperspectral Image Processing

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; Benediktsson, Jon Atli; Boardman, Joseph W.; Brazile, Jason; Bruzzone, Lorenzo; Camps-Valls, Gustavo; Chanussot, Jocelyn; Fauvel, Mathieu; Gamba, Paolo; Gualtieri, Anthony; Marconcini, Mattia; Tilton, James C.; Trianni, Giovanna

    2009-01-01

    Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than 30 years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspectral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the highdimensional nature of the data, and to integrate the spatial and spectral information. Performance of the discussed techniques is evaluated in different analysis scenarios. To satisfy time-critical constraints in specific applications, we also develop efficient parallel implementations of some of the discussed algorithms. Combined, these parts provide an excellent snapshot of the state-of-the-art in those areas, and offer a thoughtful perspective on future potentials and emerging challenges in the design of robust hyperspectral imaging algorithms

  10. Identifying saltcedar with hyperspectral data and support vector machines

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Saltcedar (Tamarix spp.) are a group of dense phreatophytic shrubs and trees that are invasive to riparian areas throughout the United States. This study determined the feasibility of using hyperspectral data and a support vector machine (SVM) classifier to discriminate saltcedar from other cover t...

  11. Phase correction algorithms for a snapshot hyperspectral imaging system

    NASA Astrophysics Data System (ADS)

    Chan, Victoria C.; Kudenov, Michael; Dereniak, Eustace

    2015-09-01

    We present image processing algorithms that improve spatial and spectral resolution on the Snapshot Hyperspectral Imaging Fourier Transform (SHIFT) spectrometer. Final measurements are stored in the form of threedimensional datacubes containing the scene's spatial and spectral information. We discuss calibration procedures, review post-processing methods, and present preliminary results from proof-of-concept experiments.

  12. Hyperspectral imaging with a liquid crystal polarization interferometer.

    PubMed

    Hegyi, Alex; Martini, Joerg

    2015-11-01

    A novel hyperspectral imaging system has been developed that takes advantage of the tunable path delay between orthogonal polarization states of a liquid crystal variable retarder. The liquid crystal is placed in the optical path of an imaging system and the path delay between the polarization states is varied, causing an interferogram to be generated simultaneously at each pixel. A data set consisting of a series of images is recorded while varying the path delay; Fourier transforming the data set with respect to the path delay yields the hyperspectral data-cube. The concept is demonstrated with a prototype imager consisting of a liquid crystal variable retarder integrated into a commercial 640x480 pixel CMOS camera. The prototype can acquire a full hyperspectral data-cube in 0.4 s, and is sensitive to light over a 400 nm to 1100 nm range with a dispersion-dependent spectral resolution of 450 cm(-1) to 660 cm(-1). Similar to Fourier transform spectroscopy, the imager is spatially and spectrally multiplexed and therefore achieves high optical throughput. Additionally, the common-path nature of the polarization interferometer yields a vibration-insensitive device. Our concept allows for the spectral resolution, imaging speed, and spatial resolution to be traded off in software to optimally address a given application. The simplicity, compactness, potential low cost, and software adaptability of the device may enable a disruptive class of hyperspectral imaging systems with a broad range of applications. PMID:26561143

  13. Textural Analysis of Hyperspectral Images for Improving Contaminant Detection Accuracy

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Previous studies demonstrated a hyperspectral imaging system has a potential for poultry fecal contaminant detection by measuring reflectance intensity. The simple image ratio at 565 and 517-nm images with optimal thresholding was able to detect fecal contaminants on broiler carcasses with high acc...

  14. Hyperspectral image representation and processing with binary partition trees.

    PubMed

    Valero, Silvia; Salembier, Philippe; Chanussot, Jocelyn

    2013-04-01

    The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image-processing tools. This paper proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation relying on the binary partition tree (BPT). This hierarchical region-based representation can be interpreted as a set of hierarchical regions stored in a tree structure. Hence, the BPT succeeds in presenting: 1) the decomposition of the image in terms of coherent regions, and 2) the inclusion relations of the regions in the scene. Based on region-merging techniques, the BPT construction is investigated by studying the hyperspectral region models and the associated similarity metrics. Once the BPT is constructed, the fixed tree structure allows implementing efficient and advanced application-dependent techniques on it. The application-dependent processing of BPT is generally implemented through a specific pruning of the tree. In this paper, a pruning strategy is proposed and discussed in a classification context. Experimental results on various hyperspectral data sets demonstrate the interest and the good performances of the BPT representation.

  15. Identification of seedling cabbages and weeds using hyperspectral imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Target detectionis one of research focues for precision chemical application. This study developed a method to identify seedling cabbages and weeds using hyperspectral spectral imaging. In processing the image data, with ENVI software, after dimension reduction, noise reduction, de-correlation for h...

  16. Visible Hyperspectral Imaging for Standoff Detection of Explosives on Surfaces

    SciTech Connect

    Bernacki, Bruce E.; Blake, Thomas A.; Mendoza, Albert; Johnson, Timothy J.

    2010-11-01

    There is an ever-increasing need to be able to detect the presence of explosives, preferably from standoff distances. This paper presents an application of visible hyperspectral imaging using anomaly, polarization and spectral identification approaches for the standoff detection (13 meters) of nitroaromatic explosives on realistic painted surfaces based upon the colorimetric differences between tetryl and TNT which are enhanced by solar irradiation.

  17. Shortwave infrared hyperspectral Imaging for cotton foreign matter classification

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Various types of cotton foreign matter seriously reduce the commercial value of cotton lint and further degrade the quality of textile products for consumers. This research was aimed to investigate the potential of a non-contact technique, i.e., liquid crystal tunable filter (LCTF) hyperspectral ima...

  18. Hyperspectral image visualization using t-distributed stochastic neighbor embedding

    NASA Astrophysics Data System (ADS)

    Zhang, Biyin; Yu, Xin

    2015-12-01

    Hyperspectral image visualization reduces high-dimensional spectral bands to three color channels, which are sought in order to explain well the nonlinear data characteristics that are hidden in the high-dimensional spectral bands. Despite the surge in the linear visualization techniques, the development of nonlinear visualization has been limited. The paper presents a new technique for visualization of hyperspectral image using t-distributed stochastic neighbor embedding, called VHI-tSNE, which learns a nonlinear mapping between the high-dimensional spectral space and the three-dimensional color space. VHI-tSNE transforms hyperspectral data into bilateral probability similarities, and employs a heavy-tailed distribution in three-dimensional color space to alleviate the crowding problem and optimization problem in SNE technique. We evaluate the performance of VHI-tSNE in experiments on several hyperspectral imageries, in which we compare it to the performance of other state-of-art techniques. The results of experiments demonstrated the strength of the proposed technique.

  19. Advances in Spectral-Spatial Classification of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

    Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

    2012-01-01

    Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

  20. Identification of inflammation sites in arthritic joints using hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Paluchowski, Lukasz A.; Milanic, Matija; Bjorgan, Asgeir; Grandaunet, Berit; Dhainaut, Alvilde; Hoff, Mari; Randeberg, Lise L.

    2014-03-01

    Inflammatory arthritic diseases have prevalence between 2 and 3% and may lead to joint destruction and deformation resulting in a loss of function. Patient's quality of life is often severely affected as the disease attacks hands and finger joints. Pathology involved in arthritis includes angiogenesis, hyper-vascularization, hyper-metabolism and relative hypoxia. We have employed hyperspectral imaging to study the hemodynamics of affected- and non-affected joints and tissue. Two hyperspectral, push-broom cameras were used (VNIR-1600, SWIR-320i, Norsk Elektro Optikk AS, Norway). Optical spectra (400nm - 1700nm) of high spectral resolution were collected from 15 patients with visible symptoms of arthritic rheumatic diseases in at least one joint. The control group consisted of 10 healthy individuals. Concentrations of dominant chromophores were calculated based on analytical calculations of light transport in tissue. Image processing was used to analyze hyperspectral data and retrieve information, e.g. blood concentration and tissue oxygenation maps. The obtained results indicate that hyperspectral imaging can be used to quantify changes within affected joints and surrounding tissue. Further improvement of this method will have positive impact on diagnosis of arthritic joints at an early stage. Moreover it will enable development of fast, noninvasive and noncontact diagnostic tool of arthritic joints

  1. [Orthogonal projection divergence-based hyperspectral band selection].

    PubMed

    Su, Hong-jun; Sheng, Ye-hua; Yang, He; Du, Qian

    2011-05-01

    Due to the high data dimensionality of a hyperspectral image, dimensionality reduction algorithm has attracted much attention in hyperspectral image analysis. Band selection algorithm, which selects appropriate bands from the original set of spectral bands, can preserve original information from the data and is useful for image classification and recognition. In the present paper, a novel band selection algorithm based on orthogonal projection divergence (OPD) is proposed, it aims to discriminate the interesting objects from background and noise information, maximize the spectral similarity between different spectral vectors by projecting the original data to feature space. Two HYDICE Washington DC Mall images and an HYMAP Purdue campus image data were experimented, and support vector machine (SVM) classifier was used for classification. The selected band number varies from 5 to 40 in order to study the impacts of different band selection algorithms on different features. For the computation complex, the sequential floating forward search (SFFS) was used to get the appropriate bands. The experiments have proved that our proposed OPD algorithm can outperform other traditional band selection methods such as SAM, ED, SID, and LCMV-BCC for hyperspectral image analysis. It is proven that OPD band selection is effective and robust in hyperspectral remote sensing dimensionality reduction

  2. Band selection for viewing underwater objects using hyperspectral sensors

    NASA Astrophysics Data System (ADS)

    Stein, David W. J.; Stewart, Stephen E.; Gilbert, Gary D.; Schoonmaker, Jon S.

    1999-10-01

    Multispectral and hyperspectral sensors are being used for remote sensing and imaging of ocean waters. Many applications require the compression of hyperspectral data to achieve real-time transmission or exploitation. Hyperspectral data compression or reduction has been accomplished using techniques based upon principal component analysis or linear unmixing. Alternatively, data compression (reduction) may be performed by band selection, or band selection may be preliminary to either of the other compression techniques. Band selection also has implications for sensor design and the stability of estimates of processing parameters. In this study, we address the question of which bands are the most efficacious for imaging submerged objects, such as whales, using an anomaly detector, or a matched filter. Bands are selected by optimizing a detection criterion subject to a constraint on the number of bands. The technique is applied to give hyperspectral data sets, and the optimum bandwidths and centers are determined. The loss in performance from selecting reduced numbers of bands is tabulated and the need for adaptively selecting reduced numbers of bands is demonstrated.

  3. [Study on hyperspectral characteristics of apple florescence canopy].

    PubMed

    Zhu, Xi-Cun; Zhao, Geng-Xing; Lei, Tong; Li, Xi-Can; Chen, Zhi-Qiang

    2009-10-01

    The present study aims to systematically analyze the hyperspectral characteristics of apple florescence canopy and explore the sensitive spectra to provide the theoretical basis for large area apple information extracting and remote sensing retrieval for nutrition diagnosis. Based on the 120 hyperspectral data of apple florescence canopy acquired with ASD Field Spec 3 portable object spectrometer, the effects of different sample numbers on hyperspectral characteristics were analyzed. Using variance analysis method, the hyperspectral characteristics of apple florescence canopy and the sensitive wave bands were obtained. The results showed that with the increase in cumulative sample numbers, the hyperspectrum curves of apple florescence became stable and smooth. At the 550 nm green peak and the 760-1,300 nm reflection plateau, the reflection rate reduced with the increase in flowering amount, while in the red valley of 670 nm, the reflection rate increased with the increase in flowering amount; At the wave bands of 350-500, 600-680 and 760-1,300 nm, the variance analysis results showed very significant differences, indicating that they were sensitive wave bands of florescence canopy. With the increase in flowering amount, the red-edge position, the red-edge slope and red edge area tended to decrease gradually. PMID:20038043

  4. Remote sensing of soil moisture using airborne hyperspectral data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Institute for Technology Development (ITD) has developed an airborne hyperspectral sensor system that collects electromagnetic reflectance data of the terrain. The system consists of sensors for three different sections of the electromagnetic spectrum; the Ultra-Violet (UV), Visible/Near Infrare...

  5. Hyperspectral image classification by collaboration of spatial and spectral information

    NASA Astrophysics Data System (ADS)

    Yan, Yu-zhou; Zhao, Yongqiang; Xue, Hui-feng; Kou, Xiao-dong; Liu, Yuanzheng

    2009-07-01

    The classification of hyperspectral image data has drawn much attention in recent years. Consequently, it contains not only spectral information of objects, but also spatial arrangement of objects. The most established Hyperspectral classifiers are based on the observed spectral signal, and ignore the spatial relations among observations. Information captured in neighboring locations may provide useful supplementary knowledge for analysis. To combine the spectral and spatial information in the classification process, in this paper, a Multidimensional Local Spatial Autocorrelation (MLSA) is proposed for hyperspectral image data. Based on this measure, a collaborative classification method is proposed, which integrates the spectral and spatial autocorrelation during the decision-making process. The trials of our experiment are conducted on two scenes, one from HYDICE 210-band imagery collected over an area that contains a diverse range of terrain features and the other is toy car hyperspectral image captured at Instrumentation and Sensing Laboratory (ISL) at Beltsville Agricultural Research Center. Quantitative measures of local consistency (smoothness) and global labeling, along with class maps, demonstrate the benefits of applying this method for unsupervised and supervised classification.

  6. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

    Finn, Michael P.; Lewis, Mark (David); Bosch, David D.; Giraldo, Mario; Yamamoto, Kristina H.; Sullivan, Dana G.; Kincaid, Russell; Luna, Ronaldo; Allam, Gopala Krishna; Kvien, Craig; Williams, Michael S.

    2011-01-01

    Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R 2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

  7. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

    Finn, M.; Lewis, M.; Bosch, D.; Giraldo, Mario; Yamamoto, K.; Sullivan, D.; Kincaid, R.; Luna, R.; Allam, G.; Kvien, Craig; Williams, M.

    2011-01-01

    Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

  8. Study on classification of pork quality using hyperspectral imaging technique

    NASA Astrophysics Data System (ADS)

    Zeng, Shan; Bai, Jun; Wang, Haibin

    2015-12-01

    The relative problems' research of chilled meat, thawed meat and spoiled meat discrimination by hyperspectral image technique were proposed, such the section of feature wavelengths, et al. First, based on 400 ~ 1000nm range hyperspectral image data of testing pork samples, by K-medoids clustering algorithm based on manifold distance, we select 30 important wavelengths from 753 wavelengths, and thus select 8 feature wavelengths (454.4, 477.5, 529.3, 546.8, 568.4, 580.3, 589.9 and 781.2nm) based on the discrimination value. Then 8 texture features of each image under 8 feature wavelengths were respectively extracted by two-dimensional Gabor wavelets transform as pork quality feature. Finally, we build a pork quality classification model using the fuzzy C-mean clustering algorithm. Through the experiment of extracting feature wavelengths, we found that although the hyperspectral images between adjacent bands have a strong linear correlation, they show a significant non-linear manifold relationship from the entire band. K-medoids clustering algorithm based on manifold distance used in this paper for selecting the characteristic wavelengths, which is more reasonable than traditional principal component analysis (PCA). Through the classification result, we conclude that hyperspectral imaging technology can distinguish among chilled meat, thawed meat and spoiled meat accurately.

  9. ML detection in hyperspectral imagery: a GMRF modeling approach

    NASA Astrophysics Data System (ADS)

    Thornton, Susan M.; Moura, Jose M. F.

    1999-07-01

    The use of hyperspectral imagery for remote sensing detection applications has received attention recently due to the ability of the hyperspectral sensor to provide registered information in both space and frequency. In this paper we extend our work on the development of an efficient implementation of the Maximum Likelihood (ML) detector in which we use a 3D Gauss-Markov random field to model the clutter background in the hyperspectral data. We review the details of the optimal ML estimation approach for obtaining the Markov parameters and discuss a gradient based optimization scheme for obtaining these estimates. To improve the computational efficiency of the overall detection algorithm, we develop an estimation method based on some simple mathematical approximations that allows us to explicitly solve for the Markov parameters. In addition, we use a stochastic, rather than deterministic target model by implementing a single hypothesis test in place of the more traditional binary hypothesis paradigm. We compare the detection performance and the computational requirements of our updated model and detector implementation to the benchmark RX detection algorithm for hyperspectral imagery.

  10. Anomaly detection based on the statistics of hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Catterall, Stephen P.

    2004-10-01

    The purpose of this paper is to introduce a new anomaly detection algorithm for application to hyperspectral imaging (HSI) data. The algorithm uses characterisations of the joint (among wavebands) probability density function (pdf) of HSI data. Traditionally, the pdf has been assumed to be multivariate Gaussian or a mixture of multivariate Gaussians. Other distributions have been considered by previous authors, in particular Elliptically Contoured Distributions (ECDs). In this paper we focus on another distribution, which has only recently been defined and studied. This distribution has a more flexible and extensive set of parameters than the multivariate Gaussian does, yet the pdf takes on a relatively simple mathematical form. The result of all this is a model for the pdf of a hyperspectral image, consisting of a mixture of these distributions. Once a model for the pdf of a hyperspectral image has been obtained, it can be incorporated into an anomaly detector. The new anomaly detector is implemented and applied to some medium wave infra-red (MWIR) hyperspectral imagery. Comparison is made with a well-known anomaly detector, and it will be seen that the results are promising.

  11. Detection of lettuce discoloration using hyperspectral reflectance imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rapid visible/near-infrared (VNIR) hyperspectral imaging methods, employing both a single waveband algorithm and multi-spectral algorithms, were developed in order to classify the discoloration of lettuce. Reflectance spectra for sound and discolored lettuce surfaces were extracted from hyperspectra...

  12. Hyperspectral imaging system for whole corn ear surface inspection

    NASA Astrophysics Data System (ADS)

    Yao, Haibo; Kincaid, Russell; Hruska, Zuzana; Brown, Robert L.; Bhatnagar, Deepak; Cleveland, Thomas E.

    2013-05-01

    Aflatoxin is a mycotoxin produced mainly by Aspergillus flavus (A.flavus) and Aspergillus parasitiucus fungi that grow naturally in corn. Very serious health problems such as liver damage and lung cancer can result from exposure to high toxin levels in grain. Consequently, many countries have established strict guidelines for permissible levels in consumables. Conventional chemical-based analytical methods used to screen for aflatoxin such as thin-layer chromatography (TLC) and high performance liquid chromatography (HPLC) are time consuming, expensive, and require the destruction of samples as well as proper training for data interpretation. Thus, it has been a continuing effort within the research community to find a way to rapidly and non-destructively detect and possibly quantify aflatoxin contamination in corn. One of the more recent developments in this area is the use of spectral technology. Specifically, fluorescence hyperspectral imaging offers a potential rapid, and non-invasive method for contamination detection in corn infected with toxigenic A.flavus spores. The current hyperspectral image system is designed for scanning flat surfaces, which is suitable for imaging single or a group of corn kernels. In the case of a whole corn cob, it is preferred to be able to scan the circumference of the corn ear, appropriate for whole ear inspection. This paper discusses the development of a hyperspectral imaging system for whole corn ear imaging. The new instrument is based on a hyperspectral line scanner using a rotational stage to turn the corn ear.

  13. Earth Observing-1 Extended Mission

    USGS Publications Warehouse

    ,

    2005-01-01

    Since November 2000, the National Aeronautics and Space Administration (NASA) Earth Observing-1 (