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Sample records for airborne lwir hyperspectral

  1. DETECTION AND IDENTIFICATION OF TOXIC AIR POLLUTANTS USING AIRBORNE LWIR HYPERSPECTRAL IMAGING

    EPA Science Inventory

    Airborne longwave infrared LWIR) hyperspectral imagery was utilized to detect and identify gaseous chemical release plumes at sites in sourthern Texzas. The Airborne Hysperspectral Imager (AHI), developed by the University of Hawaii was flown over a petrochemical facility and a ...

  2. Detection of abandoned mines/caves using airborne LWIR hyperspectral data

    NASA Astrophysics Data System (ADS)

    Shen, Sylvia S.; Roettiger, Kurt A.

    2012-09-01

    The detection of underground structures, both natural and man-made, continues to be an important requirement in both the military/intelligence and civil communities. There are estimates that as many as 70,000 abandoned mines/caves exist across the nation. These mines represent significant hazards to public health and safety, and they are of concern to Government agencies at the local, state, and federal levels. NASA is interested in the detection of caves on Mars and the Moon in anticipation of future manned space missions. And, the military/ intelligence community is interested in detecting caves, mines, and other underground structures that may be used to conceal the production of weapons of mass destruction or to harbor insurgents or other persons of interest by the terrorists. Locating these mines/caves scattered over millions of square miles is an enormous task, and limited resources necessitate the development of an efficient and effective broad area search strategy using remote sensing technologies. This paper describes an internally-funded research project of The Aerospace Corporation (Aerospace) to assess the feasibility of using airborne hyperspectral data to detect abandoned cave/mine entrances in a broad-area search application. In this research, we have demonstrated the potential utility of using thermal contrast between the cave/mine entrance and the ambient environment as a discriminatory signature. We have also demonstrated the use of a water vapor absorption line at12.55 μm and a quartz absorption feature at 9.25 μm as discriminatory signatures. Further work is required to assess the broader applicability of these signatures.

  3. Comparative analysis of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and Hyperspectral Thermal Emission Spectrometer (HyTES) longwave infrared (LWIR) hyperspectral data for geologic mapping

    NASA Astrophysics Data System (ADS)

    Kruse, Fred A.

    2015-05-01

    Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and spatially coincident Hyperspectral Thermal Emission Spectrometer (HyTES) data were used to map geology and alteration for a site in northern Death Valley, California and Nevada, USA. AVIRIS, with 224 bands at 10 nm spectral resolution over the range 0.4 - 2.5 μm at 3-meter spatial resolution were converted to reflectance using an atmospheric model. HyTES data with 256 bands at approximately 17 nm spectral resolution covering the 8 - 12 μm range at 4-meter spatial resolution were converted to emissivity using a longwave infrared (LWIR) radiative transfer atmospheric compensation model and a normalized temperature-emissivity separation approach. Key spectral endmembers were separately extracted for each wavelength region and identified, and the predominant material at each pixel was mapped for each range using Mixture-Tuned-Matched Filtering (MTMF), a partial unmixing approach. AVIRIS mapped iron oxides, clays, mica, and silicification (hydrothermal alteration); and the difference between calcite and dolomite. HyTES separated and mapped several igneous phases (not possible using AVIRIS), silicification, and validated separation of calcite from dolomite. Comparison of the material maps from the different modes, however, reveals complex overlap, indicating that multiple materials/processes exist in many areas. Combined and integrated analyses were performed to compare individual results and more completely characterize occurrences of multiple materials. Three approaches were used 1) integrated full-range analysis, 2) combined multimode classification, and 3) directed combined analysis in geologic context. Results illustrate that together, these two datasets provide an improved picture of the distribution of geologic units and subsequent alteration.

  4. Compressive hyperspectral sensor for LWIR gas detection

    NASA Astrophysics Data System (ADS)

    Russell, Thomas A.; McMackin, Lenore; Bridge, Bob; Baraniuk, Richard

    2012-06-01

    Focal plane arrays with associated electronics and cooling are a substantial portion of the cost, complexity, size, weight, and power requirements of Long-Wave IR (LWIR) imagers. Hyperspectral LWIR imagers add significant data volume burden as they collect a high-resolution spectrum at each pixel. We report here on a LWIR Hyperspectral Sensor that applies Compressive Sensing (CS) in order to achieve benefits in these areas. The sensor applies single-pixel detection technology demonstrated by Rice University. The single-pixel approach uses a Digital Micro-mirror Device (DMD) to reflect and multiplex the light from a random assortment of pixels onto the detector. This is repeated for a number of measurements much less than the total number of scene pixels. We have extended this architecture to hyperspectral LWIR sensing by inserting a Fabry-Perot spectrometer in the optical path. This compressive hyperspectral imager collects all three dimensions on a single detection element, greatly reducing the size, weight and power requirements of the system relative to traditional approaches, while also reducing data volume. The CS architecture also supports innovative adaptive approaches to sensing, as the DMD device allows control over the selection of spatial scene pixels to be multiplexed on the detector. We are applying this advantage to the detection of plume gases, by adaptively locating and concentrating target energy. A key challenge in this system is the diffraction loss produce by the DMD in the LWIR. We report the results of testing DMD operation in the LWIR, as well as system spatial and spectral performance.

  5. 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.

  6. Characterization of gaseous effluents from modeling of LWIR hyperspectral measurements

    NASA Astrophysics Data System (ADS)

    Griffin, Michael K.; Kerekes, John P.; Farrar, Kristine E.; Burke, Hsiao-hua K.

    2001-08-01

    Longwave Infrared (LWIR) radiation comprising atmospheric and surface emissions provides information for a number of applications including atmospheric profiling, surface temperature and emissivity estimation, and cloud depiction and characterization. The LWIR spectrum also contains absorption lines for numerous molecular species which can be utilized in quantifying species amounts. Modeling the absorption and emission from gaseous species using various radiative transfer codes such as MODTRAN-4 and FASE (a follow-on to the line-by-line radiative transfer code FASCODE) provides insight into the radiative signature of these elements as viewed from an airborne or space-borne platform and provides a basis for analysis of LWIR hyperspectral measurements. In this study, a model platform was developed for the investigation of the passive outgoing radiance from a scene containing an effluent plume layer. The effects of various scene and model parameters including ambient and plume temperatures, plume concentration, as well as the surface temperature and emissivity on the outgoing radiance were estimated. A simple equation relating the various components of the outgoing radiance was used to study the scale of the component contributions. A number of examples were given depicting the spectral radiance from plumes composed of single or multiple effluent gases as would be observed by typical airborne sensors. The issue of detectability and spectral identification was also discussed.

  7. Advances in hyperspectral LWIR pushbroom imagers

    NASA Astrophysics Data System (ADS)

    Holma, Hannu; Mattila, Antti-Jussi; Hyvärinen, Timo; Weatherbee, Oliver

    2011-06-01

    Two long-wave infrared (LWIR) hyperspectral imagers have been under extensive development. The first one utilizes a microbolometer focal plane array (FPA) and the second one is based on an Mercury Cadmium Telluride (MCT) FPA. Both imagers employ a pushbroom imaging spectrograph with a transmission grating and on-axis optics. The main target has been to develop high performance instruments with good image quality and compact size for various industrial and remote sensing application requirements. A big challenge in realizing these goals without considerable cooling of the whole instrument is to control the instrument radiation. The challenge is much bigger in a hyperspectral instrument than in a broadband camera, because the optical signal from the target is spread spectrally, but the instrument radiation is not dispersed. Without any suppression, the instrument radiation can overwhelm the radiation from the target even by 1000 times. The means to handle the instrument radiation in the MCT imager include precise instrument temperature stabilization (but not cooling), efficient optical background suppression and the use of background-monitoring-on-chip (BMC) method. This approach has made possible the implementation of a high performance, extremely compact spectral imager in the 7.7 to 12.4 μm spectral range. The imager performance with 84 spectral bands and 384 spatial pixels has been experimentally verified and an excellent NESR of 14 mW/(m2srμm) at 10 μm wavelength with a 300 K target has been achieved. This results in SNR of more than 700. The LWIR imager based on a microbolometer detector array, first time introduced in 2009, has been upgraded. The sensitivity of the imager has improved drastically by a factor of 3 and SNR by about 15 %. It provides a rugged hyperspectral camera for chemical imaging applications in reflection mode in laboratory and industry.

  8. 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.

  9. LWIR hyperspectral change detection for target acquisition and situation awareness in urban areas

    NASA Astrophysics Data System (ADS)

    Dekker, Rob J.; Schwering, Piet B. W.; Benoist, Koen W.; Pignatti, Stefano; Santini, Federico; Friman, Ola

    2013-05-01

    This paper studies change detection of LWIR (Long Wave Infrared) hyperspectral imagery. Goal is to improve target acquisition and situation awareness in urban areas with respect to conventional techniques. Hyperspectral and conventional broadband high-spatial-resolution data were collected during the DUCAS trials in Zeebrugge, Belgium, in June 2011. LWIR data were acquired using the ITRES Thermal Airborne Spectrographic Imager TASI-600 that operates in the spectral range of 8.0-11.5 μm (32 band configuration). Broadband data were acquired using two aeroplanemounted FLIR SC7000 MWIR cameras. Acquisition of the images was around noon. To limit the number of false alarms due to atmospheric changes, the time interval between the images is less than 2 hours. Local co-registration adjustment was applied to compensate for misregistration errors in the order of a few pixels. The targets in the data that will be analysed in this paper are different kinds of vehicles. Change detection algorithms that were applied and evaluated are Euclidean distance, Mahalanobis distance, Chronochrome (CC), Covariance Equalisation (CE), and Hyperbolic Anomalous Change Detection (HACD). Based on Receiver Operating Characteristics (ROC) we conclude that LWIR hyperspectral has an advantage over MWIR broadband change detection. The best hyperspectral detector is HACD because it is most robust to noise. MWIR high spatial-resolution broadband results show that it helps to apply a false alarm reduction strategy based on spatial processing.

  10. First results of ground-based LWIR hyperspectral imaging remote gas detection

    NASA Astrophysics Data System (ADS)

    Zheng, Wei-jian; Lei, Zheng-gang; Yu, Chun-chao; Wang, Hai-yang; Fu, Yan-peng; Liao, Ning-fang; Su, Jun-hong

    2014-11-01

    The new progress of ground-based long-wave infrared remote sensing is presented. The LWIR hyperspectral imaging by using the windowing spatial and temporal modulation Fourier spectroscopy, and the results of outdoor ether gas detection, verify the features of LWIR hyperspectral imaging remote sensing and technical approach. It provides a new technical means for ground-based gas remote sensing.

  11. Analysis of multispectral and hyperspectral longwave infrared (LWIR) data for geologic mapping

    NASA Astrophysics Data System (ADS)

    Kruse, Fred A.; McDowell, Meryl

    2015-05-01

    Multispectral MODIS/ASTER Airborne Simulator (MASTER) data and Hyperspectral Thermal Emission Spectrometer (HyTES) data covering the 8 - 12 μm spectral range (longwave infrared or LWIR) were analyzed for an area near Mountain Pass, California. Decorrelation stretched images were initially used to highlight spectral differences between geologic materials. Both datasets were atmospherically corrected using the ISAC method, and the Normalized Emissivity approach was used to separate temperature and emissivity. The MASTER data had 10 LWIR spectral bands and approximately 35-meter spatial resolution and covered a larger area than the HyTES data, which were collected with 256 narrow (approximately 17nm-wide) spectral bands at approximately 2.3-meter spatial resolution. Spectra for key spatially-coherent, spectrally-determined geologic units for overlap areas were overlain and visually compared to determine similarities and differences. Endmember spectra were extracted from both datasets using n-dimensional scatterplotting and compared to emissivity spectral libraries for identification. Endmember distributions and abundances were then mapped using Mixture-Tuned Matched Filtering (MTMF), a partial unmixing approach. Multispectral results demonstrate separation of silica-rich vs non-silicate materials, with distinct mapping of carbonate areas and general correspondence to the regional geology. Hyperspectral results illustrate refined mapping of silicates with distinction between similar units based on the position, character, and shape of high resolution emission minima near 9 μm. Calcite and dolomite were separated, identified, and mapped using HyTES based on a shift of the main carbonate emissivity minimum from approximately 11.3 to 11.2 μm respectively. Both datasets demonstrate the utility of LWIR spectral remote sensing for geologic mapping.

  12. Detection of chemical pollutants by passive LWIR hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Lavoie, Hugo; Thériault, Jean-Marc; Bouffard, François; Puckrin, Eldon; Dubé, Denis

    2012-09-01

    Toxic industrial chemicals (TICs) represent a major threat to public health and security. Their detection constitutes a real challenge to security and first responder's communities. One promising detection method is based on the passive standoff identification of chemical vapors emanating from the laboratory under surveillance. To investigate this method, the Department of National Defense and Public Safety Canada have mandated Defense Research and Development Canada (DRDC) - Valcartier to develop and test passive Long Wave Infrared (LWIR) hyperspectral imaging (HSI) sensors for standoff detection. The initial effort was focused to address the standoff detection and identification of toxic industrial chemicals (TICs) and precursors. Sensors such as the Multi-option Differential Detection and Imaging Fourier Spectrometer (MoDDIFS) and the Improved Compact ATmospheric Sounding Interferometer (iCATSI) were developed for this application. This paper describes the sensor developments and presents initial results of standoff detection and identification of TICs and precursors. The standoff sensors are based on the differential Fourier-transform infrared (FTIR) radiometric technology and are able to detect, spectrally resolve and identify small leak plumes at ranges in excess of 1 km. Results from a series of trials in asymmetric threat type scenarios will be presented. These results will serve to establish the potential of the method for standoff detection of TICs precursors and surrogates.

  13. Research on ground-based LWIR hyperspectral imaging remote gas detection

    NASA Astrophysics Data System (ADS)

    Yang, Zhixiong; Yu, Chunchao; Zheng, Weijian; Lei, Zhenggang; Yan, Min; Yuan, Xiaochun; Zhang, Peizhong

    2015-10-01

    The new progress of ground-based long-wave infrared remote sensing is presented, which describes the windowing spatial and temporal modulation Fourier spectroscopy imaging in details. The prototype forms the interference fringes based on the corner-cube of spatial modulation of Michelson interferometer, using cooled long-wave infrared photovoltaic staring FPA (focal plane array) detector. The LWIR hyperspectral imaging is achieved by the process of collection, reorganization, correction, apodization, FFT etc. from data cube. Noise equivalent sensor response (NESR), which is the sensitivity index of CHIPED-1 LWIR hyperspectral imaging prototype, can reach 5.6×10-8W/(cm-1.sr.cm2) at single sampling. Hyperspectral imaging is used in the field of organic gas VOC infrared detection. Relative to wide band infrared imaging, it has some advantages. Such as, it has high sensitivity, the strong anti-interference ability, identify the variety, and so on.

  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 imaging using novel LWIR OPO for hazardous material detection and identification

    NASA Astrophysics Data System (ADS)

    Ruxton, Keith; Robertson, Gordon; Miller, Bill; Malcolm, Graeme P. A.; Maker, Gareth T.

    2014-05-01

    Current stand-off hyperspectral imaging detection solutions that operate in the mid-wave infrared (MWIR), nominally 2.5 - 5 μm spectral region, are limited by the number of absorption bands that can be addressed. This issue is most apparent when evaluating a scene with multiple absorbers with overlapping spectral features making accurate material identification challenging. This limitation can be overcome by moving to the long wave IR (LWIR) region, which is rich in characteristic absorption features, which can provide ample molecular information in order to perform presumptive identification relative to a spectral library. This work utilises an instrument platform to perform negative contrast imaging using a novel LWIR optical parametric oscillator (OPO) as the source. The OPO offers continuous tuning in the region 5.5 - 9.5 μm, which includes a number of molecular vibrations associated with the target material compositions. Scanning the scene of interest whilst sweeping the wavelength of the OPO emission will highlight the presence of a suspect material and by analysing the resulting absorption spectrum, presumptive identification is possible. This work presents a selection of initial results using the LWIR hyperspectral imaging platform on a range of white powder materials to highlight the benefit operating in the LWIR region compared to the MWIR.

  16. Airborne midwave and longwave infrared hyperspectral imaging of gases

    NASA Astrophysics Data System (ADS)

    Gagnon, Marc-André; Tremblay, Pierre; Savary, Simon; Duval, Marc; Farley, Vincent; Chamberland, Martin

    2014-05-01

    Characterization of gas clouds are challenging situations to address due to the large and uneven distribution of these fast moving entities. Whether gas characterization is carried out for gas leaks surveys or environmental monitoring purposes, explosives and/or toxic chemicals are often involved. In such situations, airborne measurements present distinct advantages over ground based-techniques since large areas can be covered efficiently from a safe distance. In order to illustrate the potential of airborne thermal infrared hyperspectral imaging for gas cloud characterization, measurements were carried out above smokestacks and a ground-based gas release experiment. Quantitative airborne chemical images of carbon monoxide (CO) and ethylene (C2H4) were obtained from measurements carried out using a midwave (MWIR, 3-5 μm) and a longwave (LWIR, 8-12 μm) airborne infrared hyperspectral sensor respectively. Scattering effects were observed in the MWIR experiments on smokestacks as a result of water condensation upon rapid cool down of the hot emission gases. Airborne measurements were carried out using both mapping and targeting acquisition modes. The later provides unique time-dependent information such as the gas cloud direction and velocity.

  17. Airborne midwave and longwave infrared hyperspectral imaging of gases

    NASA Astrophysics Data System (ADS)

    Gagnon, Marc-André; Tremblay, Pierre; Savary, Simon; Duval, Marc; Farley, Vincent; Chamberland, Martin

    2014-11-01

    Characterization of gas clouds are challenging situations to address due to the large and uneven distribution of these fast moving entities. Whether gas characterization is carried out for gas leaks surveys or environmental monitoring purposes, explosives and/or toxic chemicals are often involved. In such situations, airborne measurements present distinct advantages over ground based-techniques since large areas can be covered efficiently from a safe distance. In order to illustrate the potential of airborne thermal infrared hyperspectral imaging for gas cloud characterization, measurements were carried out above smokestacks and a ground-based gas release experiment. Quantitative airborne chemical images of carbon monoxide (CO) and ethylene (C2H4) were obtained from measurements carried out using a midwave (MWIR, 3-5 μm) and a longwave (LWIR, 8-12 μm) airborne infrared hyperspectral sensor respectively. Scattering effects were observed in the MWIR experiments on smokestacks as a result of water condensation upon rapid cool down of the hot emission gases. Airborne measurements were carried out using both mapping and targeting acquisition modes. The later provides unique time-dependent information such as the gas cloud direction and velocity.

  18. Airborne midwave and longwave infrared hyperspectral imaging of gases

    NASA Astrophysics Data System (ADS)

    Gagnon, Marc-André; Tremblay, Pierre; Savary, Simon; Duval, Marc; Farley, Vincent; Guyot, Éric; Chamberland, Martin

    2014-10-01

    Characterization of gas clouds are challenging situations to address due to the large and uneven distribution of these fast moving entities. Whether gas characterization is carried out for gas leaks surveys or environmental monitoring purposes, explosives and/or toxic chemicals are often involved. In such situations, airborne measurements present distinct advantages over ground based-techniques since large areas can be covered efficiently from a safe distance. In order to illustrate the potential of airborne thermal infrared hyperspectral imaging for gas cloud characterization, measurements were carried out above smokestacks and a ground-based gas release experiment. Quantitative airborne chemical images of carbon monoxide (CO) and ethylene (C2H4) were obtained from measurements carried out using a midwave (MWIR, 3-5 μm) and a longwave (LWIR, 8-12 μm) airborne infrared hyperspectral sensor respectively. Scattering effects were observed in the MWIR experiments on smokestacks as a result of water condensation upon rapid cool down of the hot emission gases. Airborne measurements were carried out using both mapping and targeting acquisition modes. The later provides unique time-dependent information such as the gas cloud direction and velocity.

  19. Research on Ground-Based LWIR Hyperspectral Imaging Remote Gas Detection.

    PubMed

    Zheng, Wei-jian; Lei, Zheng-gang; Yu, Chun-chao; Yang, Zhi-xiong; Wang, Hai-yangi; Fu, Yan-peng; Li, Xun-niu; Liao, Ning-fang; Su, Jun-hong

    2016-02-01

    The new progress of ground-based long-wave infrared remote sensing is presented, which describes the windowing spatial and temporal modulation Fourier spectroscopy imaging in details. The prototype forms the interference fringes based on the corner-cube of spatial modulation of Michelson interferometer, using cooled long-wave infrared photovoltaic staring FPA (focal plane array) detector. The LWIR hyperspectral imaging is achieved by the process of collection, reorganization, correction, apodization, FFT etc. from data cube. Noise equivalent spectral radiance (NESR), which is the sensitivity index of CHIPED-1 LWIR hyperspectral imaging prototype, can reach 5.6 x 10⁻⁸ W · (cm⁻¹ · sr · cm²)⁻¹ at single sampling. The data is the same as commercial temporal modulation hyperspectral imaging spectrometer. It can prove the advantage of this technique. This technique still has space to be improved. For instance, spectral response range of CHIPED-1 LWIR hyperspectral imaging prototype can reach 11. 5 µm by testing the transmission curve of polypropylene film. In this article, choosing the results of outdoor high-rise and diethyl ether gas experiment as an example, the authors research on the detecting method of 2D distribution chemical gas VOC by infrared hyperspectral imaging. There is no observed diethyl ether gas from the infrared spectral slice of the same wave number in complicated background and low concentration. By doing the difference spectrum, the authors can see the space distribution of diethyl ether gas clearly. Hyperspectral imaging is used in the field of organic gas VOC infrared detection. Relative to wide band infrared imaging, it has some advantages. Such as, it has high sensitivity, the strong anti-interference ability, identify the variety, and so on. PMID:27209776

  20. Extraction of incident irradiance from LWIR hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Lahaie, Pierre

    2014-10-01

    The atmospheric correction of thermal hyperspectral imagery can be separated in two distinct processes: Atmospheric Compensation (AC) and Temperature and Emissivity separation (TES). TES requires for input at each pixel, the ground leaving radiance and the atmospheric downwelling irradiance, which are the outputs of the AC process. The extraction from imagery of the downwelling irradiance requires assumptions about some of the pixels' nature, the sensor and the atmosphere. Another difficulty is that, often the sensor's spectral response is not well characterized. To deal with this unknown, we defined a spectral mean operator that is used to filter the ground leaving radiance and a computation of the downwelling irradiance from MODTRAN. A user will select a number of pixels in the image for which the emissivity is assumed to be known. The emissivity of these pixels is assumed to be smooth and that the only spectrally fast varying variable in the downwelling irradiance. Using these assumptions we built an algorithm to estimate the downwelling irradiance. The algorithm is used on all the selected pixels. The estimated irradiance is the average on the spectral channels of the resulting computation. The algorithm performs well in simulation and results are shown for errors in the assumed emissivity and for errors in the atmospheric profiles. The sensor noise influences mainly the required number of pixels.

  1. LWIR hyperspectral imaging application and detection of chemical precursors

    NASA Astrophysics Data System (ADS)

    Lavoie, Hugo; Thériault, Jean-Marc; Bouffard, François; Puckrin, Eldon; Dubé, Denis

    2012-10-01

    Detection and identification of Toxic industrial chemicals (TICs) represent a major challenge to protect and sustain first responder and public security. In this context, passive Hyperspectral Imaging (HSI) is a promising technology for the standoff detection and identification of chemical vapors emanating from a distant location. To investigate this method, the Department of National Defense and Public Safety Canada have mandated Defense Research and Development Canada (DRDC) - Valcartier to develop and test Very Long Wave Infrared (VLWIR) HSI sensors for standoff detection. The initial effort was focused to address the standoff detection and identification of toxic industrial chemicals (TICs), surrogates and precursors. Sensors such as the Improved Compact ATmospheric Sounding Interferometer (iCATSI) and the Multi-option Differential Detection and Imaging Fourier Spectrometer (MoDDIFS) were developed for this application. This paper presents the sensor developments and preliminary results of standoff detection and identification of TICs and precursors. The iCATSI and MoDDIFS sensors are based on the optical differential Fourier-transform infrared (FTIR) radiometric technology and are able to detect, spectrally resolve and identify small leak at ranges in excess of 1 km. Results from a series of trials in asymmetric threat type scenarios are reported. These results serve to establish the potential of passive standoff HSI detection of TICs, precursors and surrogates.

  2. Statistical models for LWIR hyperspectral backgrounds and their applications in chemical agent detection

    NASA Astrophysics Data System (ADS)

    Manolakis, D.; Jairam, L. G.; Zhang, D.; Rossacci, M.

    2007-04-01

    Remote detection of chemical vapors in the atmosphere has a wide range of civilian and military applications. In the past few years there has been significant interest in the detection of effluent plumes using hyperspectral imaging spectroscopy in the 8-13μm atmospheric window. A major obstacle in the full exploitation of this technology is the fact that everything in the infrared is a source of radiation. As a result, the emission from the gases of interest is always mixed with emission by the more abundant atmospheric constituents and by other objects in the sensor field of view. The radiance fluctuations in this background emission constitute an additional source of interference which is much stronger than the detector noise. In this paper we develop and evaluate parametric models for the statistical characterization of LWIR hyperspectral backgrounds. We consider models based on the theory of elliptically contoured distributions. Both models can handle heavy tails, which is a key stastical feature of hyperspectral imaging backgrounds. The paper provides a concise description of the underlying models, the algorithms used to estimate their parameters from the background spectral measurements, and the use of the developed models in the design and evaluation of chemical warfare agent detection algorithms.

  3. Standoff chemical D and Id with extended LWIR hyperspectral imaging spectroradiometer

    NASA Astrophysics Data System (ADS)

    Prel, Florent; Moreau, Louis; Lavoie, Hugo; Bouffard, François; Thériault, Jean-Marc; Vallieres, Christian; Roy, Claude; Dubé, Denis

    2013-05-01

    Standoff detection and identification (D and Id) of unknown volatile chemicals such as chemical pollutants and consequences of industrial incidents has been increasingly desired for first responders and for environmental monitoring. On site gas detection sensors are commercially available and several of them can even detect more than one chemical species, however only few of them have the capabilities of detecting a wide variety of gases at long and safe distances. The ABB Hyperspectral Imaging Spectroradiometer (MR-i), configured for gas detection detects and identifies a wide variety of chemical species including toxic industrial chemicals (TICs) and surrogates several kilometers away from the sensor. This configuration is called iCATSI for improved Compact Atmospheric Sounding Interferometer. iCATSI is a standoff passive system. The modularity of the MR-i platform allows optimization of the detection configuration with a 256 x 256 Focal Plane Array imager or a line scanning imager both covering the long wave IR atmospheric window up to 14 μm. The uniqueness of its extended LWIR cut off enables to detect more chemicals as well as provide higher probability of detection than usual LWIR sensors.

  4. Real time standoff gas detection and environmental monitoring with LWIR hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Prel, Florent; Moreau, Louis; Lavoie, Hugo; Bouffard, François; Thériault, Jean-Marc; Vallieres, Christian; Roy, Claude; Dubé, Denis

    2012-10-01

    MR-i is a dual band Hyperspectral Imaging Spectro-radiometer. This field instrument generates spectral datacubes in the MWIR and LWIR. MR-i is modular and can be configured in different ways. One of its configurations is optimized for the standoff measurements of gases in differential mode. In this mode, the instrument is equipped with a dual-input telescope to perform optical background subtraction. The resulting signal is the differential between the spectral radiance entering each input port. With that method, the signal from the background is automatically removed from the signal of the target of interest. The spectral range of this configuration extends in the VLWIR (cut-off near 14 μm) to take full advantage of the LW atmospheric window.

  5. Mapping Waterhyacinth Infestations Using Airborne Hyperspectral Imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Waterhyacinth [Eichhornia crassipes (Mart.) Solms] is an exotic aquatic weed that often invades and clogs waterways in many tropical and subtropical regions of the world. The objective of this study was to evaluate airborne hyperspectral imagery and different image classification techniques for mapp...

  6. Airborne infrared hyperspectral imager for intelligence, surveillance and reconnaissance applications

    NASA Astrophysics Data System (ADS)

    Lagueux, Philippe; Puckrin, Eldon; Turcotte, Caroline S.; Gagnon, Marc-André; Bastedo, John; Farley, Vincent; Chamberland, Martin

    2012-09-01

    Persistent surveillance and collection of airborne intelligence, surveillance and reconnaissance information is critical in today's warfare against terrorism. High resolution imagery in visible and infrared bands provides valuable detection capabilities based on target shapes and temperatures. However, the spectral resolution provided by a hyperspectral imager adds a spectral dimension to the measurements, leading to additional tools for detection and identification of targets, based on their spectral signature. The Telops Hyper-Cam sensor is an interferometer-based imaging system that enables the spatial and spectral analysis of targets using a single sensor. It is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides datacubes of up to 320×256 pixels at spectral resolutions as fine as 0.25 cm-1. The LWIR version covers the 8.0 to 11.8 μm spectral range. The Hyper-Cam has been recently used for the first time in two compact airborne platforms: a bellymounted gyro-stabilized platform and a gyro-stabilized gimbal ball. Both platforms are described in this paper, and successful results of high-altitude detection and identification of targets, including industrial plumes, and chemical spills are presented.

  7. Airborne infrared hyperspectral imager for intelligence, surveillance, and reconnaissance applications

    NASA Astrophysics Data System (ADS)

    Puckrin, Eldon; Turcotte, Caroline S.; Gagnon, Marc-André; Bastedo, John; Farley, Vincent; Chamberland, Martin

    2012-06-01

    Persistent surveillance and collection of airborne intelligence, surveillance and reconnaissance information is critical in today's warfare against terrorism. High resolution imagery in visible and infrared bands provides valuable detection capabilities based on target shapes and temperatures. However, the spectral resolution provided by a hyperspectral imager adds a spectral dimension to the measurements, leading to additional tools for detection and identification of targets, based on their spectral signature. The Telops Hyper-Cam sensor is an interferometer-based imaging system that enables the spatial and spectral analysis of targets using a single sensor. It is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides datacubes of up to 320×256 pixels at spectral resolutions as fine as 0.25 cm-1. The LWIR version covers the 8.0 to 11.8 μm spectral range. The Hyper-Cam has been recently used for the first time in two compact airborne platforms: a belly-mounted gyro-stabilized platform and a gyro-stabilized gimbal ball. Both platforms are described in this paper, and successful results of high-altitude detection and identification of targets, including industrial plumes, and chemical spills are presented.

  8. Software algorithms for false alarm reduction in LWIR hyperspectral chemical agent detection

    NASA Astrophysics Data System (ADS)

    Manolakis, D.; Model, J.; Rossacci, M.; Zhang, D.; Ontiveros, E.; Pieper, M.; Seeley, J.; Weitz, D.

    2008-04-01

    The long-wave infrared (LWIR) hyperpectral sensing modality is one that is often used for the problem of detection and identification of chemical warfare agents (CWA) which apply to both military and civilian situations. The inherent nature and complexity of background clutter dictates a need for sophisticated and robust statistical models which are then used in the design of optimum signal processing algorithms that then provide the best exploitation of hyperspectral data to ultimately make decisions on the absence or presence of potentially harmful CWAs. This paper describes the basic elements of an automated signal processing pipeline developed at MIT Lincoln Laboratory. In addition to describing this signal processing architecture in detail, we briefly describe the key signal models that form the foundation of these algorithms as well as some spatial processing techniques used for false alarm mitigation. Finally, we apply this processing pipeline to real data measured by the Telops FIRST hyperspectral (FIRST) sensor to demonstrate its practical utility for the user community.

  9. Development of the second generation Hyperspectral Airborne Terrestrial Imager (HATI): HATI - 2500

    NASA Astrophysics Data System (ADS)

    Sandor-Leahy, S.; Thordarson, S.; Baldauf, B.; Figueroa, M.; Helmlinger, M.; Miller, H.; Reynolds, T.; Shepanski, J.

    2010-08-01

    Northrop Grumman Aerospace Systems (NGAS) has a long legacy developing and fielding hyperspectral sensors, including airborne and space based systems covering the visible through Long Wave Infrared (LWIR) wavelength ranges. Most recently NGAS has developed the Hyperspectral Airborne Terrestrial Instrument (HATI) family of hyperspectral sensors, which are compact airborne hyperspectral imagers designed to fly on a variety of platforms and be integrated with other sensors in NGAS's instrument suite. The current sensor under development is the HATI-2500, a full range Visible Near Infrared (VNIR) through Short Wave Infrared (SWIR) instrument covering the 0.4 - 2.5 micron wavelength range with high spectral resolution (3nm). The system includes a framing camera integrated with a GPS/INS to provide high-resolution multispectral imagery and precision geolocation. Its compact size and flexible acquisition parameters allow HATI-2500 to be integrated on a large variety of aerial platforms. This paper describes the HATI-2500 sensor and subsystems and its expected performance specifications.

  10. 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.

  11. Airborne hyperspectral detection of small changes.

    PubMed

    Eismann, Michael T; Meola, Joseph; Stocker, Alan D; Beaven, Scott G; Schaum, Alan P

    2008-10-01

    Hyperspectral change detection offers a promising approach to detect objects and features of remotely sensed areas that are too difficult to find in single images, such as slight changes in land cover and the insertion, deletion, or movement of small objects, by exploiting subtle differences in the imagery over time. Methods for performing such change detection, however, must effectively maintain invariance to typically larger image-to-image changes in illumination and environmental conditions, as well as misregistration and viewing differences between image observations, while remaining sensitive to small differences in scene content. Previous research has established predictive algorithms to overcome such natural changes between images, and these approaches have recently been extended to deal with space-varying changes. The challenges to effective change detection, however, are often exacerbated in an airborne imaging geometry because of the limitations in control over flight conditions and geometry, and some of the recent change detection algorithms have not been demonstrated in an airborne setting. We describe the airborne implementation and relative performance of such methods. We specifically attempt to characterize the effects of spatial misregistration on change detection performance, the efficacy of class-conditional predictors in an airborne setting, and extensions to the change detection approach, including physically motivated shadow transition classifiers and matched change filtering based on in-scene atmospheric normalization. PMID:18830283

  12. Citrus greening detection using airborne hyperspectral and multispectral imaging techniques

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging can provide unique spectral signatures for diseased vegetation. Airborne multispectral and hyperspectral imaging can be used to detect potentially infected trees over a large area for rapid detection of infected zones. This paper proposes a method to detect the citrus greening...

  13. Citrus greening disease detection using airborne multispectral and hyperspectral imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging can provide unique spectral signatures for diseased vegetation. Airborne hyperspectral imaging can be used to detect potentially infected trees over a large area for rapid detection of infected zones. Ground inspection and management can be focused on these infected zones rath...

  14. Evaluating Airborne Hyperspectral imagery for mapping waterhyacinth infestations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Waterhyacinth [Eichhornia crassipes (Mart.) Solms] is an exotic aquatic weed that often invades and clogs waterways in many tropical and subtropical regions of the world. The objective of this study was to evaluate airborne hyperspectral imagery and different image classification techniques for mapp...

  15. 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.

  16. 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...

  17. 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.

  18. Endmember signature based detection of flammable gases in LWIR hyperspectral images

    NASA Astrophysics Data System (ADS)

    Omruuzun, Fatih; Yardimci Cetin, Yasemin

    2005-05-01

    Segmentation and identification of compounds or materials existing in a scene is a crucial process. Hyperspectral sensors operating in different regions of the electromagnetic spectrum are able to quantify spectral characteristics of materials in different states. Due to the fact that some chemical compounds in gas state have insignificant light reflectance characteristics in visible region of the spectrum, imaging sensors operating in infrared regions are needed to sense energy absorbency characteristics of these compositions. The present study proposes a novel method for detection of flammable gases in long-wave infrared hyperspectral images. Proposed method begins with Black-Body radiation curve compensation. Since a priori information regarding the compounds in the scene is not always available, endmember spectral signatures are extracted with VCA hyperspectral unmixing algorithm. Afterwards, endmember signatures are matched with infrared energy absorbance signature of the target gas obtained from NIST (National Institute of Standards and Technology) Material Measurement Laboratory. Finally, concentration of target signature at each image pixel is detected by means of endmember abundance maps. The performance of the approach is compared with that of similarity measure based gas detection methods. It is observed that the proposed technique removes the need for an external threshold setting while providing better resolvability of the gasses.

  19. Detection and tracking of gas plumes in LWIR hyperspectral video sequence data

    NASA Astrophysics Data System (ADS)

    Gerhart, Torin; Sunu, Justin; Lieu, Lauren; Merkurjev, Ekaterina; Chang, Jen-Mei; Gilles, Jérôme; Bertozzi, Andrea L.

    2013-05-01

    Automated detection of chemical plumes presents a segmentation challenge. The segmentation problem for gas plumes is difficult due to the diffusive nature of the cloud. The advantage of considering hyperspectral images in the gas plume detection problem over the conventional RGB imagery is the presence of non-visual data, allowing for a richer representation of information. In this paper we present an effective method of visualizing hyperspectral video sequences containing chemical plumes and investigate the effectiveness of segmentation techniques on these post-processed videos. Our approach uses a combination of dimension reduction and histogram equalization to prepare the hyperspectral videos for segmentation. First, Principal Components Analysis (PCA) is used to reduce the dimension of the entire video sequence. This is done by projecting each pixel onto the first few Principal Components resulting in a type of spectral filter. Next, a Midway method for histogram equalization is used. These methods redistribute the intensity values in order to reduce icker between frames. This properly prepares these high-dimensional video sequences for more traditional segmentation techniques. We compare the ability of various clustering techniques to properly segment the chemical plume. These include K-means, spectral clustering, and the Ginzburg-Landau functional.

  20. 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.

  1. Airborne hyperspectral systems for solving remote sensing problems

    NASA Astrophysics Data System (ADS)

    Rodionov, I. D.; Rodionov, A. I.; Vedeshin, L. A.; Vinogradov, A. N.; Egorov, V. V.; Kalinin, A. P.

    2014-12-01

    A retrospective of airborne hyperspectrometer projects carried out in the ZAO Reagent Scientific Technical Center is presented. Hyperspectral devices developed during the period since the end of 1990s to the present day are described. The line of hyperspectrometers designed in recent times covers the ranges from ultraviolet (0.2 μm) to near infrared (1.0 μm). These devices can be mounted on airborne and automobile carriers, including small-size ones. By now, the developments of hyperspectral devices in ZAO Reagent have reached the finished state and have been prepared for serial production. Their technical characteristics permit one to speak of the creation of wide-range high-aperture ultraspectral high spatial resolution equipment with a possibility of real-time data processing on board.

  2. Real-time airborne hyperspectral imaging of land mines

    NASA Astrophysics Data System (ADS)

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

    2007-04-01

    DRDC Suffeld and Itres Research have jointly investigated the use of visible and infrared hyperspectral imaging (HSI) for surface and buried land mine detection since 1989. These studies have demonstrated reliable passive HSI detection of surface-laid mines, based on their reflectance spectra, from airborne and ground-based platforms. Commercial HSI instruments collect and store image data at aircraft speeds, but the data are analysed off- line. This is useful for humanitarian demining, but unacceptable for military countermine operations. We have developed a hardware and software system with algorithms that can process the raw hyperspectral data in real time to detect mines. The custom algorithms perform radiometric correction of the raw data, then classify pixels of the corrected data, referencing a spectral signature library. The classification results are stored and displayed in real time, that is, within a few frame times of the data acquisition. Such real-time mine detection was demonstrated for the first time from a slowly moving land vehicle in March 2000. This paper describes an improved system which can achieve real-time detection of mines from an airborne platform, with its commensurately higher data rates. The system is presently compatible with the Itres family of visible/near infrared, short wave infrared and thermal infrared pushbroom hyperspectral imagers and its broadband thermal infrared pushbroom imager. Experiments to detect mines from an airborne platform in real time were conducted at DRDC Suffield in November 2006. Surface-laid land mines were detected in real time from a slowly moving helicopter with generally good detection rates and low false alarm rates. To the authors' knowledge, this is the first time that land mines have been detected from an airborne platform in real time using hyperspectral imaging.

  3. Statistics for the Relative Detectability of Chemicals in Weak Gaseous Plumes in LWIR Hyperspectral Imagery

    SciTech Connect

    Metoyer, Candace N.; Walsh, Stephen J.; Tardiff, Mark F.; Chilton, Lawrence

    2008-10-30

    The detection and identification of weak gaseous plumes using thermal imaging data is complicated by many factors. These include variability due to atmosphere, ground and plume temperature, and background clutter. This paper presents an analysis of one formulation of the physics-based model that describes the at-sensor observed radiance. The motivating question for the analyses performed in this paper is as follows. Given a set of backgrounds, is there a way to predict the background over which the probability of detecting a given chemical will be the highest? Two statistics were developed to address this question. These statistics incorporate data from the long-wave infrared band to predict the background over which chemical detectability will be the highest. These statistics can be computed prior to data collection. As a preliminary exploration into the predictive ability of these statistics, analyses were performed on synthetic hyperspectral images. Each image contained one chemical (either carbon tetrachloride or ammonia) spread across six distinct background types. The statistics were used to generate predictions for the background ranks. Then, the predicted ranks were compared to the empirical ranks obtained from the analyses of the synthetic images. For the simplified images under consideration, the predicted and empirical ranks showed a promising amount of agreement. One statistic accurately predicted the best and worst background for detection in all of the images. Future work may include explorations of more complicated plume ingredients, background types, and noise structures.

  4. 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.

  5. 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.

  6. Quantitative study of detection performance for LWIR hyperspectral imagers as a function of number of spectral bands

    NASA Astrophysics Data System (ADS)

    Mayer, Rulon R.; Priest, Richard G.

    2001-08-01

    Remote passive sensors can collect data that depict both the spatial distribution of objects in the scene and the spectral distributions for those objects within the scene. Target search techniques, such as matched filter algorithms, use highly resolved wavelength spectra (large number of bands) to help detect fine features in the spectrum in order to discriminate objects from the background. The use of a large number of bands during the target search, however, significantly slows image collection and area coverage rates. This study quantitatively examines how binning or integrating bands can affect target detection. Our study examines the long-wave infrared spectra of man-made targets and natural backgrounds obtained with the SEBASS (8-12 micrometers ) imager as part of the Dark HORSE 2 exercise during the HYDRA data collection in November, 1998. In this collection, at least 30 bands of data were obtained, but they were then binned to as few as 2 bands. This study examines the effect on detection performance of reducing the number of bands, through computation of the signal to clutter ratio (SCR) for a variety of target types. In addition, this study examines how band reduction affects the receiver operator curves (ROC) i.e. the target detection probability versus false alarm rate, for matched filter algorithms using in-scene target signatures and hyperspectral images. Target detection, as measured by SCR, for a variety of target types, improves with increasing number of bands. The enhancement in SCR levels off at approximately 10 bands, with only a small increase in SCR obtained from 10 to 30 bands. Variable number of bands within a bin (for fixed number of bins), generated by a genetic algorithm, increases SCR and ROC curve performance for multi-temporal studies. Thus, optimal selection of bands derived from one mission, may be robust and stable, and provide enhanced target detection for data collected on subsequent days. This investigation is confined to the

  7. Airborne Hyperspectral Imagery for the Detection of Agricultural Crop Stress

    NASA Technical Reports Server (NTRS)

    Cassady, Philip E.; Perry, Eileen M.; Gardner, Margaret E.; Roberts, Dar A.

    2001-01-01

    Multispectral digital imagery from aircraft or satellite is presently being used to derive basic assessments of crop health for growers and others involved in the agricultural industry. Research indicates that narrow band stress indices derived from hyperspectral imagery should have improved sensitivity to provide more specific information on the type and cause of crop stress, Under funding from the NASA Earth Observation Commercial Applications Program (EOCAP) we are identifying and evaluating scientific and commercial applications of hyperspectral imagery for the remote characterization of agricultural crop stress. During the summer of 1999 a field experiment was conducted with varying nitrogen treatments on a production corn-field in eastern Nebraska. The AVIRIS (Airborne Visible-Infrared Imaging Spectrometer) hyperspectral imager was flown at two critical dates during crop development, at two different altitudes, providing images with approximately 18m pixels and 3m pixels. Simultaneous supporting soil and crop characterization included spectral reflectance measurements above the canopy, biomass characterization, soil sampling, and aerial photography. In this paper we describe the experiment and results, and examine the following three issues relative to the utility of hyperspectral imagery for scientific study and commercial crop stress products: (1) Accuracy of reflectance derived stress indices relative to conventional measures of stress. We compare reflectance-derived indices (both field radiometer and AVIRIS) with applied nitrogen and with leaf level measurement of nitrogen availability and chlorophyll concentrations over the experimental plots (4 replications of 5 different nitrogen levels); (2) Ability of the hyperspectral sensors to detect sub-pixel areas under crop stress. We applied the stress indices to both the 3m and 18m AVIRIS imagery for the entire production corn field using several sub-pixel areas within the field to compare the relative

  8. Automation of hyperspectral airborne remote sensing data processing

    NASA Astrophysics Data System (ADS)

    Kozoderov, V. V.; Egorov, V. D.

    2014-12-01

    An automated system is proposed for discriminating the spectral radiances registered by the hyperspectral airborne instruments based on average spectra and their interclass variability while distinguishing pixels related to the illuminated and shaded elements of the crown trees for various species and ages. Maps of the ground-based inventory for the selected area of airborne remote sensing are used as prior information. The system automatically forms databases of the selected classes of objects using the contours of these objects drawn on the image under processing. An opportunity to distinguish these classes is demonstrated in the red edge region of the spectra transition from the chlorophyll spectral band to the maximum of the spectral vegetation reflectivity.

  9. Evaluating airborne hyperspectral imagery for mapping saltcedar infestations in west Texas

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Rio Grande of west Texas contains by far the largest infestation of saltcedar (Tamarix spp.) in Texas. The objective of this study was to evaluate airborne hyperspectral imagery and different classification techniques for mapping saltcedar infestations. Hyperspectral imagery with 102 usable band...

  10. Using airborne hyperspectral imagery for mapping saltcedar infestations in west Texas

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Rio Grande of west Texas contains, by far, the largest infestation of saltcedar (Tamarix spp.) in Texas. The objective of this study was to evaluate airborne hyperspectral imagery and different classification techniques for mapping saltcedar infestations. Hyperspectral imagery with 102 usable ba...

  11. Spectral Unmixing of airborne hyperspectral imagery for mapping giant reed infestations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spectral unmixing techniques applied to hyperspectral imagery were examined for mapping giant reed (Arundo donax L.), an invasive weed that presents a severe threat to agroecosystems and riparian areas throughout the southern United States and northern Mexico. Airborne hyperspectral imagery with 102...

  12. Detection of single graves by airborne hyperspectral imaging.

    PubMed

    Leblanc, G; Kalacska, M; Soffer, R

    2014-12-01

    Airborne hyperspectral imaging (HSI) was assessed as a potential tool to locate single grave sites. While airborne HSI has shown to be useful to locate mass graves, it is expected the location of single graves would be an order of magnitude more difficult due to the smaller size and reduced mass of the targets. Two clearings were evaluated (through a blind test) as potential sites for containing at least one set of buried remains. At no time prior to submitting the locations of the potential burial sites from the HSI were the actual locations of the sites released or shared with anyone from the analysis team. The two HSI sensors onboard the aircraft span the range of 408-2524nm. A range of indicators that exploit the narrow spectral and spatial resolutions of the two complimentary HSI sensors onboard the aircraft were calculated. Based on the co-occurrence of anomalous pixels within the expected range of the indicators three potential areas conforming to our underlying assumptions of the expected spectral responses (and spatial area) were determined. After submission of the predicted burial locations it was revealed that two of the targets were located within GPS error (10m) of the true burial locations. Furthermore, due to the history of the TPOF site for burial work, investigation of the third target is being considered in the near future. The results clearly demonstrate promise for hyperspectral imaging to aid in the detection of buried remains, however further work is required before these results can justifiably be used in routine scenarios. PMID:25447169

  13. DETECTION AND IDENTIFICATION OF TOXIC AIR POLLUTANTS USING AIRBORNE LWIR HYPERSPECTRAL IMAGING

    EPA Science Inventory

    Gaseous releases from petrochemical, refinery, and electrical production facilities can contribute to regional air quality problems. Fugitive emissions or leaks can be costly to industry in terms of lost materials and products. Ground-based sampling and monitoring for leaks are t...

  14. Determination of pasture quality using airborne hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Pullanagari, R. R.; Kereszturi, G.; Yule, Ian J.; Irwin, M. E.

    2015-10-01

    Pasture quality is a critical determinant which influences animal performance (live weight gain, milk and meat production) and animal health. Assessment of pasture quality is therefore required to assist farmers with grazing planning and management, benchmarking between seasons and years. Traditionally, pasture quality is determined by field sampling which is laborious, expensive and time consuming, and the information is not available in real-time. Hyperspectral remote sensing has potential to accurately quantify biochemical composition of pasture over wide areas in great spatial detail. In this study an airborne imaging spectrometer (AisaFENIX, Specim) was used with a spectral range of 380-2500 nm with 448 spectral bands. A case study of a 600 ha hill country farm in New Zealand is used to illustrate the use of the system. Radiometric and atmospheric corrections, along with automatized georectification of the imagery using Digital Elevation Model (DEM), were applied to the raw images to convert into geocoded reflectance images. Then a multivariate statistical method, partial least squares (PLS), was applied to estimate pasture quality such as crude protein (CP) and metabolisable energy (ME) from canopy reflectance. The results from this study revealed that estimates of CP and ME had a R2 of 0.77 and 0.79, and RMSECV of 2.97 and 0.81 respectively. By utilizing these regression models, spatial maps were created over the imaged area. These pasture quality maps can be used for adopting precision agriculture practices which improves farm profitability and environmental sustainability.

  15. Relating Hyperspectral Airborne Data to Ground Measurements in a Complex and Discontinuous Canopy

    NASA Astrophysics Data System (ADS)

    Calleja, Javier F.; Hellmann, Christine; Mendiguren, Gorka; Punalekar, Suvarna; Peón, Juanjo; MacArthur, Alasdair; Alonso, Luis

    2015-12-01

    The work described in this paper is aimed at validating hyperspectral airborne reflectance data collected during the Regional Experiments For Land-atmosphere EXchanges (REFLEX) campaign. Ground reflectance data measured in a vineyard were compared with airborne reflectance data. A sampling strategy and subsequent ground data processing had to be devised so as to capture a representative spectral sample of this complex crop. A linear model between airborne and ground data was tried and statistically tested. Results reveal a sound correspondence between ground and airborne reflectance data (R2 > 0.97), validating the atmospheric correction of the latter.

  16. Comparison of different detection methods for citrus greening disease based on airborne multispectral and hyperspectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Citrus greening or Huanglongbing (HLB) is a devastating disease spread in many citrus groves since first found in 2005 in Florida. Multispectral (MS) and hyperspectral (HS) airborne images of citrus groves in Florida were taken to detect citrus greening infected trees in 2007 and 2010. Ground truthi...

  17. Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil hyperspectral reflectance imagery was obtained from an airborne imaging spectrometer (400 to 2450 nm with ~10 nm resolution, 2.5 m spatial resolution) flown over six tilled (bare soil) agricultural fields on the Eastern Shore of the Chesapeake Bay (Queen Anne’s county, MD). Surface soil samples...

  18. Detection of soil properties with airborne hyperspectral measurements of bare fields.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Airborne remote sensing data, using a hyperspectral (HSI) camera, were collected for a flight over two fields with a total of 128 ha. of recently seeded and nearly bare soil. The within-field spatial distribution of several soil properties was found by using multiple linear regression to select the ...

  19. Applying linear spectral unmixing to airborne hyperspectral imagery for mapping crop yield variability.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study evaluated linear spectral unmixing techniques for mapping the variation in crop yield. Both unconstrained and constrained linear spectral unmixing models were applied to airborne hyperspectral imagery recorded from one grain sorghum field and a cotton field. A pair of plant and soil spect...

  20. A Synergistic Approach to Atmospheric Compensation of Neon's Airborne Hyperspectral Imagery Utilizing an Airborne Solar Spectral Irradiance Radiometer

    NASA Astrophysics Data System (ADS)

    Wright, L.; Karpowicz, B. M.; Kindel, B. C.; Schmidt, S.; Leisso, N.; Kampe, T. U.; Pilewskie, P.

    2014-12-01

    A wide variety of critical information regarding bioclimate, biodiversity, and biogeochemistry is embedded in airborne hyperspectral imagery. Most, if not all of the primary signal relies upon first deriving the surface reflectance of land cover and vegetation from measured hyperspectral radiance. This places stringent requirements on terrain, and atmospheric compensation algorithms to accurately derive surface reflectance properties. An observatory designed to measure bioclimate, biodiversity, and biogeochemistry variables from surface reflectance must take great care in developing an approach which chooses algorithms with the highest accuracy, along with providing those algorithms with data necessary to describe the physical mechanisms that affect the measured at sensor radiance. The Airborne Observation Platform (AOP) part of the National Ecological Observatory Network (NEON) is developing such an approach. NEON is a continental-scale ecological observation platform designed to collect and disseminate data to enable the understanding and forecasting of the impacts of climate change, land use change, and invasive species on ecology. The instrumentation package used by the AOP includes a visible and shortwave infrared hyperspectral imager, waveform LiDAR, and high resolution (RGB) digital camera. In addition to airborne measurements, ground-based CIMEL sun photometers will be used to help characterize atmospheric aerosol loading, and ground validation measurements with field spectrometers will be made at select NEON sites. While the core instrumentation package provides critical information to derive surface reflectance of land surfaces and vegetation, the addition of a Solar Spectral Irradiance Radiometer (SSIR) is being investigated as an additional source of data to help identify and characterize atmospheric aerosol, and cloud contributions contributions to the radiance measured by the hyperspectral imager. The addition of the SSIR provides the opportunity to

  1. 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.

  2. Comparison of Airborne Multispectral and Hyperspectral Imagery for Yield Estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multispectral and hyperspectral imagery is being used to monitor crop conditions and map yield variability. However, limited research has been conducted to compare the differences between these two types of imagery for assessing crop growth and yield. The objective of this study was to compare airbo...

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

    NASA Astrophysics Data System (ADS)

    Pang, Yong; Li, Zengyuan

    2016-06-01

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

  4. Classification of the forest cover of Tver oblast using hyperspectral airborne imagery

    NASA Astrophysics Data System (ADS)

    Dmitriev, E. V.

    2014-12-01

    Recent research efforts have been focused on building a system of hyperspectral aerial sounding of forest vegetation on regional scales. The components of this system are developed using data obtained in the course of measurement campaigns in Tver forestry test sites. Hyperspectral airborne surveys are conducted using a Russian video spectrometer produced by the NPO Lepton company. The technique for recognizing ground-based objects is based on Bayesian classification principles with the feature space optimization. The choice of the most informative spectral channels is based on the step-up method. We propose an approach allowing the choice of channels to be more stable. We compare the classification of timber stands on the basis of hyperspectral imagery with ground-based data to demonstrate the consistency of the system developed.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  6. Application research of using CASI/SASI airborne hyperspectral remote sensing on lithology identification

    NASA Astrophysics Data System (ADS)

    Zhou, Jiajing; Qin, Kai

    2016-04-01

    Remote sensing provides an advanced method for lithology identification, which is one of the important research fields in geological prospecting. In theory, each lithology is of individual spectrum characteristics. Based on the spectral differences between them, we can identify different lithologies by remote sensing images. At present, the studies on lithology identification by remote sensing are primarily conducted on the multispectral images, such as Landsat 7 ETM+, SPOT-5, QuickBird and WorldView-2. Hyperspectral remote sensing images provide richer information, making it easier to identify the lithologies, but studied rarely. CASI/SASI is an airborne hyperspectral system covering a wavelength range of 0.38-2.45μm. With hundreds of bands, the hyperspectral images are useful to identify the spectrum characteristics of lithology. In addition, images are of high spatial resolution, with CASI of about 1m and SASI of about 2-2.5m, which make lithology identification more accurate. CASI/SASI hyperspectral data was collected in Beishan metallogenic belt in northwest China, as same as the ground spectral data of the lithologies. After data preprocessing, we divided different lithologies using CASI/SASI hyperspectral images and lithology spectrum, identified some important lithologies related to mineralization, and successfully found a few new ore clues.

  7. Measured performance of an airborne Fourier-transform hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Otten, Leonard John, III; Meigs, Andrew D.; Sellar, R. Glenn; Rafert, Bruce

    1996-11-01

    A new hyperspectral imager has recently been developed by Kestrel Corporation for use in light aircraft platforms. The instrument provides 256 spectral channels with 87 cm-1 spectral bandwidth over the 450 nm to 1000 nm portion of the spectrum. Operated as a pushbroom imager, the FTVHSI has been shown to have a IFOV of 0.75 mrad, and a FOV of 0.23 rad. The sensor includes an internal spectral/radiometric calibration source, a self contained spectrally resolved downwelling sensor, and complete line of sight and GPS positioning information. The instrument is now operating from a Cessna TU-206 single engine aircraft.

  8. MTU-Kestrel airborne hyperspectral imaging campaigns of the Lake Superior ecosystem

    NASA Astrophysics Data System (ADS)

    Rafert, J. Bruce; Slough, William J.; Rohde, Charles A.; Pilant, Andrew; Otten, Leonard J.; Meigs, Andrew D.; Jones, Al; Butler, Eugene W.

    1999-10-01

    The clear waters of Lake Superior constitute the heart of one of the most significant fresh water ecosystems in the world. Lake Superior is the world's largest lake by surface area (82,100 km2) holding approximately 10% of the earth's freshwater (12,230 km3) that is not locked into glaciers or ice caps. Although Superior is arguably the most significant fresh water ecosystem on earth, questions relating to the lake and its watershed remain unanswered, including the effects of human habitation, exploitation, and economic potential of the region. There is a great diversity of scientific disciplines with a common interest in remote sensing of the Lake Superior ecosystem which have the need for data at all spatial, spectral, and temporal scales-from scales supplied by satellites, ships or aircraft at low spatial, spectral or temporal resolution, to a requirement for synoptic high resolution spatial (approximately 1 meter)/spectral (1 - 10 nm) data. During May and August of 1998, two week-long data collection campaigns were performed using the Kestrel airborne visible hyperspectral imager to acquire hyperspectral data of a broad taxonomy of ecologically significant targets, including forests, urban areas, lakeshore zones and rivers, mining industry tailing basins, and the Lake itself. We will describe the Kestrel airborne hyperspectral sensor, the collection and data reduction methodology, and flight imagery from both campaigns.

  9. Retrieval of cloud optical properties using airborne hyperspectral cameras during the VOCALS campaign.

    NASA Astrophysics Data System (ADS)

    Labrador, L.; Vaughan, G.

    2009-09-01

    A set of two hyperspectral imaging sensors have been used to analyze the optical properties of stratocumulus cloud off the coast of Northern Chile within the framework of the VAMOS Ocean Clouds Atmosphere Land Study (VOCALS) during September-October 2008. The SPECIM Aisa Eagle & Hawk are tandem pushbroom-type hyperspectral imagers scanning in the 400-970 and 970-2500 nm range, respectively. The instruments were mounted onboard the National Environmental Research Council's (NERC) Dornier DO-228 aircraft, based in Arica, northern Chile during the campaign. An area approximately 600 x 200 km was surveyed off the northern coast of Chile and a total of 14 science flights were carried out where hyperspectral data were successfully collected over the stratocumulus deck at altitudes varying between 10000 and 15000 ft. Cloud optical properties, such as cloud optical thickness, cloud effective radius and liquid water path can be retrieved which can then be compared with space-borne hyperspectral imagers' retrievals. Atmospheric corrections have been applied to enable the comparison between the different type of sensors and the analysis requires, amongst other, solving the back-scattering problems associated with off-nadir views. The high resolution, both spatial and temporal, of these airborne sensors makes them ideal to validate satellite retrievals of cloud optical properties.

  10. An analysis task comparison of uncorrected vs. geo-registered airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Sun, Yihang; Kerekes, John

    2015-05-01

    Geo-registration is the task of assigning geospatial coordinates to the pixels of an image and placing them in a geographic coordinate system. However, the process of geo-registration can impair the quality of the image. This paper studies this topic by applying a comparison methodology to uncorrected and geo-registered airborne hyperspectral images obtained from the RIT SHARE 2012 data set. The uncorrected image was analyzed directly as collected by the sensor without being treated, while the geo-registered image was corrected using the nearest neighbor resampling approach. A comparison of performance was done for the analysis tasks of spectral unmixing and subpixel target detection, which can represent a measure of utility. The comparison demonstrates that the geo-registration process can affect the utility of hyperspectral imagery to a limited extent.

  11. Airborne Hyperspectral Survey of Afghanistan 2007: Flight Line Planning and HyMap Data Collection

    USGS Publications Warehouse

    Kokaly, Raymond F.; King, Trude V.V.; Livo, K. Eric

    2008-01-01

    Hyperspectral remote sensing data were acquired over Afghanistan with the HyMap imaging spectrometer (Cocks and others, 1998) operating on the WB-57 high altitude NASA research aircraft (http://jsc-aircraft-ops.jsc.nasa.gov/wb57/index.html). These data were acquired during the interval of August 22, 2007 to October 2, 2007, as part of the United States Geological Survey (USGS) project 'Oil and Gas Resources Assessment of the Katawaz and Helmand Basins'. A total of 218 flight lines of hyperspectral remote sensing data were collected over the country. This report describes the planning of the airborne survey and the flight lines that were flown. Included with this report are digital files of the nadir tracks of the flight lines, including a map of the labeled flight lines and corresponding vector shape files for geographic information systems (GIS).

  12. Airborne surveillance of water basins with hyperspectral FLS-LiDAR

    NASA Astrophysics Data System (ADS)

    Babichenko, S.; Alekseyev, V.; Lapimaa, J.; Lisin, A.; Poryvkina, L.; Shchemelyov, S.; Sobolev, I.; Vint, L.

    2010-10-01

    The airborne FLS-Lidars are based on the method of Laser Induced Fluorescence (LIF) and aimed at the analytical remote sensing of water objects. Scanning the laser beam across the flight trajectory and recording the comprehensive LIF spectrum with hyperspectral detector per every laser pulse provide detail maps of spectral properties of the water basins. A multi-tier model for integrated environmental assessment is applied for further analysis of this information to combine the benefits of "big-picture" capability of remote sensing techniques and GIS solutions with localized on-theground environmental data gathering. In this concept far looking satellite and airborne systems provide the highest tier information. The airborne data acquisition with FLS-Lidar is considered as the middle tier characterized by vast amount of LIF data with high spatial (less than 10 m) and spectral (less than 5 nm in UV/VIS spectral ranges) resolution. The lower tier is anchored with the geographical locations of important findings detected at the middle tier. Taken water samples are analyzed with fastscreening technology of Spectral Fluorescence Signatures (SFS) giving more analytical qualitative and quantitative results. And the base tier includes detail laboratory analysis of characteristic samples selected at the lower tier. Precisely geo-referenced LIF data of hyperspectral FLS-Lidar anchored to and calibrated by the ground SFS data allows detection of pollution incidents and mapping of environmental trends over vast water systems like coastal zone, lakes and rivers.r

  13. Mapping mine tailings using airborne geophysical and hyperspectral remote sensing data

    NASA Astrophysics Data System (ADS)

    Shang, Jiali

    Mine tailings are the waste products from mining operations. Most mine tailings contain a considerable amount of reactive sulphides which can cause acid mine drainage (AMD) when exposed to air and water. AMD constitutes a threat both to the environment and to public health. Increased awareness of AMD has led to growing activities in mine-tailing monitoring and reclamation worldwide. Mining companies in Canada are required to provide information to provincial governments about their waste disposal and control activities. There is an urgent need to develop new automated ways to provide information on short- to long-term evolution of tailings, thus enabling the mining companies to monitor their tailings more effectively. The overall goal of the thesis is to explore the potential of hyperspectral remote sensing and geophysical techniques for mapping variations within and immediately outside of the tailings. Data used for this study are from three sources: airborne geophysical data, hyperspectral casi and Probe-1 data, and field data. This study has contributed to both the remote sensing data analysis techniques and the understanding of mine-tailing surface and subsurface processes. Specifically, this study has the following important findings: (1) Airborne magnetic and electromagnetic data can provide information regarding the subsurface distribution of mine tailings on the basis of sulphide mineral content. A procedure has been developed in this study to use these data sources for rapidly surveying large tailings areas. This procedure can minimize expenditures for mining companies when designing remedial plans for the closure of the mines. This study has also identified regions of enhanced conductivity that extend beyond the tailing containment area. This information indicates seepage pathways, and is important for monitoring the effectiveness of tailing containment structures. (2) High-spatial-resolution hyperspectral casi (Compact Airborne Spectrographic Imagery

  14. Extraction, modelling, and use of linear features for restitution of airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Lee, Changno; Bethel, James S.

    This paper presents an approach for the restitution of airborne hyperspectral imagery with linear features. The approach consisted of semi-automatic line extraction and mathematical modelling of the linear features. First, the line was approximately determined manually and refined using dynamic programming. The extracted lines could then be used as control data with the ground information of the lines, or as constraints with simple assumption for the ground information of the line. The experimental results are presented numerically in tables of RMS residuals of check points as well as visually in ortho-rectified images.

  15. Diffused Matrix Format: A New Storage and Processing Format for Airborne Hyperspectral Sensor Images

    PubMed Central

    Martínez, Pablo; Cristo, Alejandro; Koch, Magaly; Pérez, Rosa Mª.; Schmid, Thomas; Hernández, Luz M.

    2010-01-01

    At present, hyperspectral images are mainly obtained with airborne sensors that are subject to turbulences while the spectrometer is acquiring the data. Therefore, geometric corrections are required to produce spatially correct images for visual interpretation and change detection analysis. This paper analyzes the data acquisition process of airborne sensors. The main objective is to propose a new data format called Diffused Matrix Format (DMF) adapted to the sensor's characteristics including its spectral and spatial information. The second objective is to compare the accuracy of the quantitative maps derived by using the DMF data structure with those obtained from raster images based on traditional data structures. Results show that DMF processing is more accurate and straightforward than conventional image processing of remotely sensed data with the advantage that the DMF file structure requires less storage space than other data formats. In addition the data processing time does not increase when DMF is used. PMID:22399919

  16. Data processing of remotely sensed airborne hyperspectral data using the Airborne Processing Library (APL): Geocorrection algorithm descriptions and spatial accuracy assessment

    NASA Astrophysics Data System (ADS)

    Warren, Mark A.; Taylor, Benjamin H.; Grant, Michael G.; Shutler, Jamie D.

    2014-03-01

    Remote sensing airborne hyperspectral data are routinely used for applications including algorithm development for satellite sensors, environmental monitoring and atmospheric studies. Single flight lines of airborne hyperspectral data are often in the region of tens of gigabytes in size. This means that a single aircraft can collect terabytes of remotely sensed hyperspectral data during a single year. Before these data can be used for scientific analyses, they need to be radiometrically calibrated, synchronised with the aircraft's position and attitude and then geocorrected. To enable efficient processing of these large datasets the UK Airborne Research and Survey Facility has recently developed a software suite, the Airborne Processing Library (APL), for processing airborne hyperspectral data acquired from the Specim AISA Eagle and Hawk instruments. The APL toolbox allows users to radiometrically calibrate, geocorrect, reproject and resample airborne data. Each stage of the toolbox outputs data in the common Band Interleaved Lines (BILs) format, which allows its integration with other standard remote sensing software packages. APL was developed to be user-friendly and suitable for use on a workstation PC as well as for the automated processing of the facility; to this end APL can be used under both Windows and Linux environments on a single desktop machine or through a Grid engine. A graphical user interface also exists. In this paper we describe the Airborne Processing Library software, its algorithms and approach. We present example results from using APL with an AISA Eagle sensor and we assess its spatial accuracy using data from multiple flight lines collected during a campaign in 2008 together with in situ surveyed ground control points.

  17. Great Lakes Hyperspectral Water Quality Instrument Suite for Airborne Monitoring of Algal Blooms

    NASA Technical Reports Server (NTRS)

    Lekki, John; Leshkevich, George; Nguyen, Quang-Viet; Flatico, Joseph; Prokop, Norman; Kojima, Jun; Anderson, Robert; Demers, James; Krasowski, Michael

    2007-01-01

    NASA Glenn Research Center and NOAA Great Lakes Environmental Research Lab are collaborating to utilize an airborne hyperspectral imaging sensor suite to monitor Harmful Algal Blooms (HABs) in the western basin of Lake Erie. The HABs are very dynamic events as they form, spread and then disappear within a 4 to 8 week time period in late summer. They are a concern for human health, fish and wildlife because they can contain blue green toxic algae. Because of this toxicity there is a need for the blooms to be continually monitored. This situation is well suited for aircraft based monitoring because the blooms are a very dynamic event and they can spread over a large area. High resolution satellite data is not suitable by itself because it will not give the temporal resolution due to the infrequent overpasses of the quickly changing blooms. A custom designed hyperspectral imager and a point spectrometer mounted on aT 34 aircraft have been used to obtain data on an algal bloom that formed in the western basin of Lake Erie during September 2006. The sensor suite and operations will be described and preliminary hyperspectral data of this event will be presented

  18. Field-Based and Airborne Hyperspectral Imaging for Applied Research in the State of Alaska

    NASA Astrophysics Data System (ADS)

    Prakash, A.; Buchhorn, M.; Cristobal, J.; Kokaly, R. F.; Graham, P. R.; Waigl, C. F.; Hampton, D. L.; Werdon, M.; Guldager, N.; Bertram, M.; Stuefer, M.

    2015-12-01

    Hyperspectral imagery acquired using Hyspex VNIR-1800 and SWIR-384 camera systems have provided unique information on terrestrial and aquatic biogeochemical parameters, and diagnostic mineral properties in exposed outcrops in selected sites in the state of Alaska. The Hyspex system was configured for in-situ and field scanning by attaching it to a gimbal-mounted rotational stage on a robust tripod. Scans of vertical faces of vegetation and rock outcrops were made close to the campus of the University of Alaska Fairbanks, in an abandoned mine near Fairbanks, and on exposures of Orange Hill in Wrangell-St. Elias National Park. Atmospherically corrected integrated VNIR_SWIR spectra were extracted which helped to study varying nitrogen content in the vegetation, and helped to distinguish the various micas. Processed imagery helped to pull out carbonates, clays, sulfates, and alteration-related minerals. The same instrument was also mounted in airborne configuration on two different aircrafts, a DeHavilland Beaver and a Found Bush Hawk. Test flights were flown over urban and wilderness areas that presented a variety of landcover types. Processed imagery shows promise in mapping man-made surfaces, phytoplankton, and dissolved materials in inland water bodies. Sample data and products are available on the University of Alaska Fairbanks Hyperspectral Imaging Laboratory (HyLab) website at http://hyperspectral.alaska.edu.

  19. Application of high spatial resolution airborne hyperspectral remote sensing data in thematic information extraction

    NASA Astrophysics Data System (ADS)

    Xu, Hong-gen; Ma, Hong-chao; Li, De-ren; Song, Yan

    2006-10-01

    The airborne hyperspectral remote sensing data, such as PHI, OMIS, has the virtues of high spatial and spectral resolution. Hence, from the view of target classification we can consider that it can provide the ability of discriminating targets more detailedly than other data. So it's important to extract thematic information and update database using this kind of data. Whereas, the hyperspectral data has abundant bands and high between-band correlation, the traditional classification methods such as maximum likelihood classifier (MLC) and spectral angle mapper (SAM) have performed poorly in thematic information extraction. For this reason, we present a new method for thematic information extraction with hyperspectral remote sensing data. We perform classification by means of combining the self-organizing map (SOM) neural network which is considered as full-pixel technique with linear spectral mixture analysis (LSMA) which is considered as mixed-pixel technique. The SOM neural network is improved from some aspects to classify the pure data and find the mixed data. And then the mixed data are unmixed and classified by LSMA. The result of experiment shows that we can have the better performance in thematic information extraction with PHI by this means.

  20. The design and the development of a hyperspectral and multispectral airborne mapping system

    NASA Astrophysics Data System (ADS)

    Gorsevski, Pece V.; Gessler, Paul E.

    Flexible and cost-effective tools for rapid image acquisition and natural resource mapping are needed by land managers. This paper describes the hardware and software architecture of a low-cost system that can be deployed on a light aircraft for rapid data acquisition. The Hyperspectral and Multispectral Cameras for Airborne Mapping (HAMCAM) was designed and developed in the Geospatial Laboratory for Environmental Dynamics at the University of Idaho as a student-learning tool, and to enhance the existing curriculum currently offered. The system integrates a hyperspectral sensor with four multispectral cameras, an Inertial Navigation System (INS), a Wide Area Augmentation System (WAAS)-capable Global Positioning System (GPS), a data acquisition computer, and custom software for running the sensors in a variety of different modes. The outputs include very high resolution imagery obtained in four adjustable visible and near-infrared bands from the multispectral imager. The hyperspectral sensor acquires 240 spectral bands along 2.7 nm intervals within the 445-900 nm range. The INS provides aircraft pitch, roll and yaw information for rapid geo-registration of the imagery. This paper will discuss the challenges associated with the development of the system and the integration of components and software for implementation of this system for natural resource management applications. In addition, sample imagery acquired by the sensor will be presented.

  1. First Use of an Airborne Thermal Infrared Hyperspectral Scanner for Compositional Mapping

    NASA Technical Reports Server (NTRS)

    Kirkland, Laurel; Herr, Kenneth; Keim, Eric; Adams, Paul; Salisbury, John; Hackwell, John; Treiman, Allan

    2002-01-01

    In May 1999, the airborne thermal infrared hyperspectral imaging system, Spatially Enhanced Broadband Array Spectrograph System (SEBASS), was flown over Mon-non Mesa, NV, to provide the first test of such a system for geological mapping. Several types of carbonate deposits were identified using the 11.25 microns band. However, massive calcrete outcrops exhibited weak spectral contrast, which was confirmed by field and laboratory measurements. Because the weathered calcrete surface appeared relatively smooth in hand specimen, this weak spectral contrast was unexpected. Here we show that microscopic roughness not readily apparent to the eye has introduced both a cavity effect and volume scattering to reduce spectral contrast. The macroroughness of crevices and cobbles may also have a significant cavity effect. The diminished spectral contrast is important because it places higher signal-to-noise ratio (SNR) requirements for spectroscopic detection and identification. This effect should be factored into instrumentation planning and interpretations, especially interpretations without benefit of ground truth. SEBASS had the required high SNR and spectral resolution to allow us to demonstrate for the first time the ability of an airborne hyperspectral thermal infrared scanner to detect and identify spectrally subtle materials.

  2. Airborne infrared-hyperspectral mapping for detection of gaseous and solid targets

    NASA Astrophysics Data System (ADS)

    Puckrin, E.; Turcotte, C. S.; Lahaie, P.; Dubé, D.; Farley, V.; Lagueux, P.; Marcotte, F.; Chamberland, M.

    2010-04-01

    Airborne hyperspectral ground mapping is being used in an ever-increasing extent for numerous applications in the military, geology and environmental fields. The different regions of the electromagnetic spectrum help produce information of differing nature. The visible, near-infrared and short-wave infrared radiation (400 nm to 2.5 μm) has been mostly used to analyze reflected solar light, while the mid-wave (3 to 5 μm) and long-wave (8 to 12 μm or thermal) infrared senses the self-emission of molecules directly, enabling the acquisition of data during night time. The Telops Hyper-Cam is a rugged and compact infrared hyperspectral imager based on the Fourier-transform technology. It has been used on the ground in several field campaigns, including the demonstration of standoff chemical agent detection. More recently, the Hyper-Cam has been integrated into an airplane to provide airborne measurement capabilities. The technology offers fine spectral resolution (up to 0.25 cm-1) and high accuracy radiometric calibration (better than 1 degree Celsius). Furthermore, the spectral resolution, spatial resolution, swath width, integration time and sensitivity are all flexible parameters that can be selected and optimized to best address the specific objectives of each mission. The system performance and a few measurements have been presented in previous publications. This paper focuses on analyzing additional measurements in which detection of fertilizer and Freon gas has been demonstrated.

  3. Retrieval of Topsoil Properties of Vegetation-Covered Terrain Using Airborne Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Liu, Lanfa; Buchroithner, Manfred

    2016-04-01

    Soil spectroscopy is a promising technique for topsoil analysis, and has been successfully utilized in the laboratory. When it is applied from airborne platforms, the presence of vegetation significantly affects imaging spectroscopy or hyperspectral imaging when retrieving topsoil properties. A Forced Invariance Approach has been proved to be able to effectively suppress the vegetation signal in mixed pixels. However, the approach is still mainly limited to lithological mapping. In this paper, we attempted to apply it to the retrieval of topsoil properties (soil moisture and soil salinity at depths 4 cm and 10 cm) using airborne hyperspectral data. The corresponding ground truth data was obtained from an eco-hydrological wireless sensing network in the Zhangye Oasis in the middle stream of the Heihe River Basin, China. The General Linear Model with Logit Link Function was adopted to model the relationships between measured soil properties and the spectra. The vegetation suppression result demonstrates that the spectral response curves of hyperspectral image pixels are flattened and the shapes are rather similar to the soil endmenber spectrum. From the modelling results it can be seen that the Forced Invariance Approach is more effective for soil moisture than for soil salinity at depth 10 cm, as the salt content is comparatively lower than the water content in soil, and the corresponding spectral response is weaker. This approach did not work for soil at a depth of 4 cm. The reason for this is that surface soil is significantly influenced by exterior factors like irrigation and wind, and landscape fragmentation and cultivation activities also contribute to the high spatial heterogeneity of the surface soil properties.

  4. A methodology for luminance map retrieval using airborne hyperspectral and photogrammetric data

    NASA Astrophysics Data System (ADS)

    Pipia, Luca; Alamús, Ramon; Tardà, Anna; Pérez, Fernando; Palà, Vicenç; Corbera, Jordi

    2014-10-01

    This paper puts forward a methodology developed at the Institut Cartogràfic i Geològic de Catalunya (ICGC) to quantify upwelling light flux using hyperspectral and photogrammetric airborne data. The work was carried out in the frame of a demonstrative study requested by the municipality of Sant Cugat del Vallès, in the vicinity of Barcelona (Spain), and aimed to envisage a new approach to assess artificial lighting policies and actions as alternative to field campaigns. Hyperspectral and high resolution multispectral/panchromatic data were acquired simultaneously over urban areas. In order to avoid moon light contributions, data were acquired during the first days of new moon phase. Hyperspectral data were radiometrically calibrated. Then, National Center for Environmental Prediction (NCEP) atmospheric profiles were employed to estimate the actual Column Water Vapor (CWV) to be passed to ModTran5.0 for the atmospheric transmissivity τ calculation. At-the-ground radiance was finally integrated using the photopic sensitivity curve to generate a luminance map (cdm-2) of the flown area by mosaicking the different flight tracks. In an attempt to improve the spatial resolution and enhance the dynamic range of the luminance map, a sensor-fusion strategy was finally looked into. DMC Photogrammetric data acquired simultaneously to hyperspectral information were converted into at-the-ground radiance and upscaled to CASI spatial resolution. High-resolution (HR) luminance maps with enhanced dynamic range were finally generated by linearly fitting up-scaled DMC mosaics to the CASI-based luminance information. In the end, a preliminary assessment of the methodology is carried out using non-simultaneous in-situ measurements.

  5. Applying linear spectral unmixing to airborne hyperspectral imagery for mapping yield variability in grain sorghum and cotton fields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study examined linear spectral unmixing techniques for mapping the variation in crop yield for precision agriculture. Both unconstrained and constrained linear spectral unmixing models were applied to airborne hyperspectral imagery collected from a grain sorghum field and a cotton field. A pair...

  6. Detection of European Corn Borer Infestation in Iowa Corn Plots using Spectral Vegetation Indices Derived from Airborne Hyperspectral Imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing technology was used to distinguish corn infested with European corn borers, Ostrinia nubilalis, from corn that was not infested. In 2004 and 2005, eleven spectral vegetation indices that emphasize foliar plant pigments were calculated using airborne hyperspectral imagery. Manual inocu...

  7. Estimating leaf area index and aboveground biomass of an invasive weed (yellow starthistle, Centaurea solstitalis L.) using airborne hyperspectral data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral remote sensed data was obtained via a Compact Airborne Spectrographic Imager (CASI) and used to estimate leaf area index (LAI) and aboveground biomass of a highly invasive weed species, yellow starthistle (Centaurea solstitialis L.). In parallel, 34 ground-based field plots were used t...

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  9. [Remote sensing of chlorophyll fluorescence at airborne level based on unmanned airship platform and hyperspectral sensor].

    PubMed

    Yang, Pei-Qi; Liu, Zhi-Gang; Ni, Zhuo-Ya; Wang, Ran; Wang, Qing-Shan

    2013-11-01

    The solar-induced chlorophyll fluorescence (ChlF) has a close relationship with photosynthetic and is considered as a probe of plant photosynthetic activity. In this study, an airborne fluorescence detecting system was constructed by using a hyperspectral imager on board an unmanned airship. Both Fraunhofer Line Discriminator (FLD) and 3FLD used to extract ChlF require the incident solar irradiance, which is always difficult to receive at airborne level. Alternative FLD (aFLD) can overcome the problem by selecting non-fluorescent emitter in the image. However, aFLD is based on the assumption that reflectance is identical around the Fraunhofer line, which is not realistic. A new method, a3FLD, is proposed, which assumes that reflectance varies linearly with the wavelength around Fraunhofer line. The result of simulated data shows that ChlF retrieval error of a3FLD is significantly lower than that of aFLD when vegetation reflectance varies near the Fraunhofer line. The results of hyperspectral remote sensing data with the airborne fluorescence detecting system show that the relative values of retrieved ChlF of 5 kinds of plants extracted by both aFLD and a3FLD are consistent with vegetation growth stage and the ground-level ChlF. The ChlF values of aFLD are about 15% greater than a3FLD. In addition, using aFLD, some non-fluorescent objects have considerable ChlF value, while a3FLD can effectively overcome the problem. PMID:24555390

  10. Bayesian classifier applications of airborne hyperspectral imagery processing for forested areas

    NASA Astrophysics Data System (ADS)

    Kozoderov, Vladimir; Kondranin, Timofei; Dmitriev, Egor; Kamentsev, Vladimir

    2015-06-01

    Pattern recognition problem is outlined in the context of textural and spectral analysis of remote sensing imagery processing. Main attention is paid to Bayesian classifier that can be used to realize the processing procedures based on parallel machine-learning algorithms and high-productive computers. We consider the maximum of the posterior probability principle and the formalism of Markov random fields for the neighborhood description of the pixels for the related classes of objects with the emphasis on forests of different species and ages. The energy category of the selected classes serves to account for the likelihood measure between the registered radiances and the theoretical distribution functions approximating remotely sensed data. Optimization procedures are undertaken to solve the pattern recognition problem of the texture description for the forest classes together with finding thin nuances of their spectral distribution in the feature space. As a result, possible redundancy of the channels for imaging spectrometer due to their correlations is removed. Difficulties are revealed due to different sampling data while separating pixels, which characterize the sunlit tops, shaded space and intermediate cases of the Sun illumination conditions on the hyperspectral images. Such separation of pixels for the forest classes is maintained to enhance the recognition accuracy, but learning ensembles of data need to be agreed for these categories of pixels. We present some results of the Bayesian classifier applicability for recognizing airborne hyperspectral images using the relevant improvements in separating such pixels for the forest classes on a test area of the 4 × 10 km size encompassed by 13 airborne tracks, each forming the images by 500 pixels across the track and from 10,000 to 14,000 pixels along the track. The spatial resolution of each image is near to 1 m from the altitude near to 2 km above the ground level. The results of the hyperspectral imagery

  11. Airborne hyperspectral and LiDAR data integration for weed detection

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  12. Airborne Hyperspectral Infrared Imaging Survey of the Southern San Andreas Fault

    NASA Astrophysics Data System (ADS)

    Lynch, D. K.; Tratt, D. M.; Buckland, K. N.; Johnson, P. D.

    2014-12-01

    The San Andreas Fault (SAF) between Desert Hot Springs and Bombay Beach has been surveyed with Mako, an airborne hyperspectral imager operating across the wavelength range 7.6-13.2 μm in the thermal-infrared (TIR) spectral region. The data were acquired with a 4-km swath width centered on the SAF, and many tectonic features are recorded in the imagery. Spectral analysis using diagnostic features of minerals can identify rocks, soils and vegetation. Mako imagery can also locate rupture zones and measure slip distances. Designed and built by The Aerospace Corporation, the innovative and highly capable airborne imaging spectrometer used for this work enables low-noise performance (NEΔT ≲ 0.1 K @ 10 μm) at small pixel IFOV (0.55 mrad) and high frame rates, making possible an area-coverage rate of 20 km2 per minute with 2-m ground resolution from 12,500 ft (3.8 km) above-ground altitude. Since its commissioning in 2010, Mako has been used in numerous studies involving other earthquake fault systems (Hector Mine, S. Bristol Mts.), mapping of surface geology, geothermal sources (fumaroles near the Salton Sea), urban surveys, and the detection, quantification, and tracking of natural and anthropogenic gaseous emission plumes. Mako is available for airborne field studies and new applications are of particular interest. It can be flown at any altitude below 20,000 ft to achieve the desired GSD.

  13. Use of spectral vegetation indices derived from airborne hyperspectral imagery for detection of European corn borer infestation in Iowa corn plots

    EPA Science Inventory

    Eleven spectral vegetation indices that emphasize foliar plant pigments were calculated using airborne hyperspectral imagery and evaluated in 2004 and 2005 for their ability to detect experimental plots of corn manually inoculated with Ostrinia nubilalis (Hübner) neonate larvae. ...

  14. Temperature and emissivity separation and mineral mapping based on airborne TASI hyperspectral thermal infrared data

    NASA Astrophysics Data System (ADS)

    Cui, Jing; Yan, Bokun; Dong, Xinfeng; Zhang, Shimin; Zhang, Jingfa; Tian, Feng; Wang, Runsheng

    2015-08-01

    Thermal infrared remote sensing (8-12 μm) (TIR) has great potential for geologic remote sensing studies. TIR has been successfully used for terrestrial and planetary geologic studies to map surface materials. However, the complexity of the physics and the lack of hyperspectral data make the studies under-investigated. A new generation of commercial hyperspectral infrared sensors, known as Thermal Airborne Spectrographic Imager (TASI), was used for image analysis and mineral mapping in this study. In this paper, a combined method integrating normalized emissivity method (NEM), ratio algorithm (RATIO) and maximum-minimum apparent emissivity difference (MMD), being applied in multispectral data, has been modified and used to determine whether this method is suitable for retrieving emissivity from TASI hyperspectral data. MODTRAN 4 has been used for the atmospheric correction. The retrieved emissivity spectra matched well with the field measured spectra except for bands 1, 2, and 32. Quartz, calcite, diopside/hedenbergite, hornblende and microcline have been mapped by the emissivity image. Mineral mapping results agree with the dominant minerals identified by laboratory X-ray powder diffraction and spectroscopic analyses of field samples. Both of the results indicated that the atmospheric correction method and the combined temperature-emissivitiy method are suitable for TASI image. Carbonate skarnization was first found in the study area by the spatial extent of diopside. Chemical analyses of the skarn samples determined that the Au content was 0.32-1.74 g/t, with an average Au content of 0.73 g/t. This information provides an important resource for prospecting for skarn type gold deposits. It is also suggested that TASI is suitable for prospect and deposit scale exploration.

  15. Urban land-cover classification based on airborne hyperspectral data and field observation

    NASA Astrophysics Data System (ADS)

    Yamazaki, Fumio; Hara, Konomi; Liu, Wen

    2014-10-01

    Using a dataset from the 2013 IEEE data fusion contest, a basic study to classify urban land-cover was carried out. The spectral reflectance characteristics of surface materials were investigated from the airborne hyperspectral (HS) data acquired by CASI-1500 imager over Houston, Texas, USA. The HS data include 144 spectral bands in the visible to near-infrared (380 nm to 1050 nm) regions. A multispectral (MS) image acquired by WorldView-2 satellite was also introduced in order to compare it with the HS image. A field measurement in the Houston's test site was carried out using a handheld spectroradiometer by the present authors. The reflectance of surface materials obtained by the measurement was also compared with the pseudo-reflectance of the HS data and they showed good agreement. Finally a principal component analysis was conducted for the HS and MS data and the result was discussed.

  16. High Resolution Airborne Laser Scanning and Hyperspectral Imaging with a Small Uav Platform

    NASA Astrophysics Data System (ADS)

    Gallay, Michal; Eck, Christoph; Zgraggen, Carlo; Kaňuk, Ján; Dvorný, Eduard

    2016-06-01

    The capabilities of unmanned airborne systems (UAS) have become diverse with the recent development of lightweight remote sensing instruments. In this paper, we demonstrate our custom integration of the state-of-the-art technologies within an unmanned aerial platform capable of high-resolution and high-accuracy laser scanning, hyperspectral imaging, and photographic imaging. The technological solution comprises the latest development of a completely autonomous, unmanned helicopter by Aeroscout, the Scout B1-100 UAV helicopter. The helicopter is powered by a gasoline two-stroke engine and it allows for integrating 18 kg of a customized payload unit. The whole system is modular providing flexibility of payload options, which comprises the main advantage of the UAS. The UAS integrates two kinds of payloads which can be altered. Both payloads integrate a GPS/IMU with a dual GPS antenna configuration provided by OXTS for accurate navigation and position measurements during the data acquisition. The first payload comprises a VUX-1 laser scanner by RIEGL and a Sony A6000 E-Mount photo camera. The second payload for hyperspectral scanning integrates a push-broom imager AISA KESTREL 10 by SPECIM. The UAS was designed for research of various aspects of landscape dynamics (landslides, erosion, flooding, or phenology) in high spectral and spatial resolution.

  17. Detection of Extreme Climate Event Impacts to Terrestrial Productivity From Airborne Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Desai, A. R.; DuBois, S.; Singh, A.; Serbin, S.; Goulden, M.; Baldocchi, D. D.; Oechel, W. C.; Kruger, E. L.; Townsend, P. A.

    2015-12-01

    Changes in drought frequency and intensity are likely to be some of the largest climate anomalies to influence the net productivity of ecosystems, especially in already water-limited regions. However, the physiological mechanisms that drive this response are limited by primarily infrequent and small-scale leaf-level measurements. Here, we integrated eddy covariance flux tower estimates of gross primary productivity (GPP) across an elevation-gradient in California with airborne imagery from the NASA HyspIRI Preparatory campaign to evaluate the potential of hyperspectral imagery to detect responses of GPP to prolonged drought. We observed a number of spectral features in the visible, infrared, and shortwave infrared regions that yielded stronger linkages than traditional broadband indices with space and time variation in GPP across a range of ecosystems in California experiencing water stress in the past three years. Further, partial least squares regression (PLSR) modeling offers the ability to generate predictive models of GPP from narrowband hyperspectral remote sensing that directly links plant chemistry and spectral properties to productivity, and could serve as a significant advance over broadband remote sensing of GPP anomalies.

  18. Design and modeling of spectral-thermal unmixing targets for airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Clare, Phil

    2006-05-01

    Techniques to determine the proportions of constituent materials within a single pixel spectrum are well documented in the reflective (0.4-2.5μm) domain. The same capability is also desirable for the thermal (7-14μm) domain, but is complicated by the thermal contributions to the measured spectral radiance. Atmospheric compensation schemes for the thermal domain have been described along with methods for estimating the spectral emissivity from a spectral radiance measurement and hence the next stage to be tackled is the unmixing of thermal spectral signatures. In order to pursue this goal it is necessary to collect data of well-calibrated targets which will expose the limits of the available techniques and enable more robust methods to be designed. This paper describes the design of a set of ground targets for an airborne hyperspectral imager, which will test the effectiveness of available methods. The set of targets include panels to explore a number of difficult scenarios such as isothermal (different materials at identical temperature), isochromal (identical materials, but at differing temperatures), thermal adjacency and thermal point sources. Practical fabrication issues for heated targets and selection of appropriate materials are described. Mathematical modelling of the experiments has enabled prediction of at-sensor measured radiances which are used to assess the design parameters. Finally, a number of useful lessons learned during the fielding of these actual targets are presented to assist those planning future trials of thermal hyperspectral sensors.

  19. Performance of three reflectance calibration methods for airborne hyperspectral spectrometer data.

    PubMed

    Miura, Tomoaki; Huete, Alfredo R

    2009-01-01

    In this study, the performances and accuracies of three methods for converting airborne hyperspectral spectrometer data to reflectance factors were characterized and compared. The "reflectance mode (RM)" method, which calibrates a spectrometer against a white reference panel prior to mounting on an aircraft, resulted in spectral reflectance retrievals that were biased and distorted. The magnitudes of these bias errors and distortions varied significantly, depending on time of day and length of the flight campaign. The "linear-interpolation (LI)" method, which converts airborne spectrometer data by taking a ratio of linearly-interpolated reference values from the preflight and post-flight reference panel readings, resulted in precise, but inaccurate reflectance retrievals. These reflectance spectra were not distorted, but were subject to bias errors of varying magnitudes dependent on the flight duration length. The "continuous panel (CP)" method uses a multi-band radiometer to obtain continuous measurements over a reference panel throughout the flight campaign, in order to adjust the magnitudes of the linear-interpolated reference values from the preflight and post-flight reference panel readings. Airborne hyperspectral reflectance retrievals obtained using this method were found to be the most accurate and reliable reflectance calibration method. The performances of the CP method in retrieving accurate reflectance factors were consistent throughout time of day and for various flight durations. Based on the dataset analyzed in this study, the uncertainty of the CP method has been estimated to be 0.0025 ± 0.0005 reflectance units for the wavelength regions not affected by atmospheric absorptions. The RM method can produce reasonable results only for a very short-term flight (e.g., < 15 minutes) conducted around a local solar noon. The flight duration should be kept shorter than 30 minutes for the LI method to produce results with reasonable accuracies. An important

  20. Performance of Three Reflectance Calibration Methods for Airborne Hyperspectral Spectrometer Data

    PubMed Central

    Miura, Tomoaki; Huete, Alfredo R.

    2009-01-01

    In this study, the performances and accuracies of three methods for converting airborne hyperspectral spectrometer data to reflectance factors were characterized and compared. The “reflectance mode (RM)” method, which calibrates a spectrometer against a white reference panel prior to mounting on an aircraft, resulted in spectral reflectance retrievals that were biased and distorted. The magnitudes of these bias errors and distortions varied significantly, depending on time of day and length of the flight campaign. The “linear-interpolation (LI)” method, which converts airborne spectrometer data by taking a ratio of linearly-interpolated reference values from the preflight and post-flight reference panel readings, resulted in precise, but inaccurate reflectance retrievals. These reflectance spectra were not distorted, but were subject to bias errors of varying magnitudes dependent on the flight duration length. The “continuous panel (CP)” method uses a multi-band radiometer to obtain continuous measurements over a reference panel throughout the flight campaign, in order to adjust the magnitudes of the linear-interpolated reference values from the preflight and post-flight reference panel readings. Airborne hyperspectral reflectance retrievals obtained using this method were found to be the most accurate and reliable reflectance calibration method. The performances of the CP method in retrieving accurate reflectance factors were consistent throughout time of day and for various flight durations. Based on the dataset analyzed in this study, the uncertainty of the CP method has been estimated to be 0.0025 ± 0.0005 reflectance units for the wavelength regions not affected by atmospheric absorptions. The RM method can produce reasonable results only for a very short-term flight (e.g., < 15 minutes) conducted around a local solar noon. The flight duration should be kept shorter than 30 minutes for the LI method to produce results with reasonable accuracies

  1. Estimating Leaf Water Potential of Giant Sequoia Trees from Airborne Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Francis, E. J.; Asner, G. P.

    2015-12-01

    Recent drought-induced forest dieback events have motivated research on the mechanisms of tree survival and mortality during drought. Leaf water potential, a measure of the force exerted by the evaporation of water from the leaf surface, is an indicator of plant water stress and can help predict tree mortality in response to drought. Scientists have traditionally measured water potentials on a tree-by-tree basis, but have not been able to produce maps of tree water potential at the scale of a whole forest, leaving forest managers unaware of forest drought stress patterns and their ecosystem-level consequences. Imaging spectroscopy, a technique for remote measurement of chemical properties, has been used to successfully estimate leaf water potentials in wheat and maize crops and pinyon-pine and juniper trees, but these estimates have never been scaled to the canopy level. We used hyperspectral reflectance data collected by the Carnegie Airborne Observatory (CAO) to map leaf water potentials of giant sequoia trees (Sequoiadendron giganteum) in an 800-hectare grove in Sequoia National Park. During the current severe drought in California, we measured predawn and midday leaf water potentials of 48 giant sequoia trees, using the pressure bomb method on treetop foliage samples collected with tree-climbing techniques. The CAO collected hyperspectral reflectance data at 1-meter resolution from the same grove within 1-2 weeks of the tree-level measurements. A partial least squares regression was used to correlate reflectance data extracted from the 48 focal trees with their water potentials, producing a model that predicts water potential of giant sequoia trees. Results show that giant sequoia trees can be mapped in the imagery with a classification accuracy of 0.94, and we predicted the water potential of the mapped trees to assess 1) similarities and differences between a leaf water potential map and a canopy water content map produced from airborne hyperspectral data, 2

  2. CASI/SASI airborne hyperspectral remote sensing anomaly extraction of metallogenic prediction research in Gansu Beishan South Beach area

    NASA Astrophysics Data System (ADS)

    Che, Yongfei; Zhao, Yingjun

    2014-11-01

    Hyperspectral remote sensing has one of the technical advantages atlas. The known deposits of Gansu Beishan South Beach deposits as the study area, based on the theory of wall rock alteration, using airborne hyperspectral remote sensing data (CASI/SASI), extracted mineralization alteration information and analysis. Based on airborne hyperspectral remote sensing mineral mapping results in the study area, Combining analysising of possible mineral formation fluid properties, spatial distribution characteristics and time evolution with analysising of mineral formation environment (lithology and tectonic environment), construction of the South Beach gold deposit location model, the deposit location model as a guide, comprehensive analysis of mineralization geological background and surface geochemical data, delineated mineralization favorable areas. The field investigation showed that signs of altered development of strong in the delineation of the mineralization favorable areas and metallogenic potential of better, is worth paying attention to the prospecting target area. Further explanation that the hyperspectral remote sensing can provide accurate and reliable information for the prospecting, and is worthy of further mining the ore prospecting potential.

  3. Estimation of green grass/herb biomass from airborne hyperspectral imagery using spectral indices and partial least squares regression

    NASA Astrophysics Data System (ADS)

    Cho, Moses Azong; Skidmore, Andrew; Corsi, Fabio; van Wieren, Sipke E.; Sobhan, Istiak

    2007-12-01

    The main objective was to determine whether partial least squares (PLS) regression improves grass/herb biomass estimation when compared with hyperspectral indices, that is normalised difference vegetation index (NDVI) and red-edge position (REP). To achieve this objective, fresh green grass/herb biomass and airborne images (HyMap) were collected in the Majella National Park, Italy in the summer of 2005. The predictive performances of hyperspectral indices and PLS regression models were then determined and compared using calibration ( n = 30) and test ( n = 12) data sets. The regression model derived from NDVI computed from bands at 740 and 771 nm produced a lower standard error of prediction (SEP = 264 g m -2) on the test data compared with the standard NDVI involving bands at 665 and 801 nm (SEP = 331 g m -2), but comparable results with REPs determined by various methods (SEP = 261 to 295 g m -2). PLS regression models based on original, derivative and continuum-removed spectra produced lower prediction errors (SEP = 149 to 256 g m -2) compared with NDVI and REP models. The lowest prediction error (SEP = 149 g m -2, 19% of mean) was obtained with PLS regression involving continuum-removed bands. In conclusion, PLS regression based on airborne hyperspectral imagery provides a better alternative to univariate regression involving hyperspectral indices for grass/herb biomass estimation in the Majella National Park.

  4. Extracting Roof Parameters and Heat Bridges Over the City of Oldenburg from Hyperspectral, Thermal, and Airborne Laser Scanning Data

    NASA Astrophysics Data System (ADS)

    Bannehr, L.; Luhmann, Th.; Piechel, J.; Roelfs, T.; Schmidt, An.

    2011-09-01

    Remote sensing methods are used to obtain different kinds of information about the state of the environment. Within the cooperative research project HiReSens, funded by the German BMBF, a hyperspectral scanner, an airborne laser scanner, a thermal camera, and a RGB-camera are employed on a small aircraft to determine roof material parameters and heat bridges of house tops over the city Oldenburg, Lower Saxony. HiReSens aims to combine various geometrical highly resolved data in order to achieve relevant evidence about the state of the city buildings. Thermal data are used to obtain the energy distribution of single buildings. The use of hyperspectral data yields information about material consistence of roofs. From airborne laser scanning data (ALS) digital surface models are inferred. They build the basis to locate the best orientations for solar panels of the city buildings. The combination of the different data sets offers the opportunity to capitalize synergies between differently working systems. Central goals are the development of tools for the collection of heat bridges by means of thermal data, spectral collection of roofs parameters on basis of hyperspectral data as well as 3D-capture of buildings from airborne lasers scanner data. Collecting, analyzing and merging of the data are not trivial especially not when the resolution and accuracy is aimed in the domain of a few decimetre. The results achieved need to be regarded as preliminary. Further investigations are still required to prove the accuracy in detail.

  5. An oil film information retrieval method overcoming the influence of sun glitter, based on AISA+ airborne hyper-spectral image

    NASA Astrophysics Data System (ADS)

    Zhan, Yuanzeng; Mao, Tianming; Gong, Fang; Wang, Difeng; Chen, Jianyu

    2010-10-01

    As an effective survey tool for oil spill detection, the airborne hyper-spectral sensor affords the potentiality for retrieving the quantitative information of oil slick which is useful for the cleanup of spilled oil. But many airborne hyper-spectral images are affected by sun glitter which distorts radiance values and spectral ratios used for oil slick detection. In 2005, there's an oil spill event leaking at oil drilling platform in The South China Sea, and an AISA+ airborne hyper-spectral image recorded this event will be selected for studying in this paper, which is affected by sun glitter terribly. Through a spectrum analysis of the oil and water samples, two features -- "spectral rotation" and "a pair of fixed points" can be found in spectral curves between crude oil film and water. Base on these features, an oil film information retrieval method which can overcome the influence of sun glitter is presented. Firstly, the radiance of the image is converted to normal apparent reflectance (NormAR). Then, based on the features of "spectral rotation" (used for distinguishing oil film and water) and "a pair of fixed points" (used for overcoming the effect of sun glitter), NormAR894/NormAR516 is selected as an indicator of oil film. Finally, by using a threshold combined with the technologies of image filter and mathematic morphology, the distribution and relative thickness of oil film are retrieved.

  6. Remote Sensing of Vegetation Species Diversity: The Utility of Integrated Airborne Hyperspectral and Lidar Data

    NASA Astrophysics Data System (ADS)

    Krause, Keith Stuart

    The change, reduction, or extinction of species is a major issue currently facing the Earth. Efforts are underway to measure, monitor, and protect habitats that contain high species diversity. Remote sensing technology shows extreme value for monitoring species diversity by mapping ecosystems and using those land cover maps or other derived data as proxies to species number and distribution. The National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) consists of remote sensing instruments such as an imaging spectrometer, a full-waveform lidar, and a high-resolution color camera. AOP collected data over the Ordway-Swisher Biological Station (OSBS) in May 2014. A majority of the OSBS site is covered by the Sandhill ecosystem, which contains a very high diversity of vegetation species and is a native habitat for several threatened fauna species. The research presented here investigates ways to analyze the AOP data to map ecosystems at the OSBS site. The research attempts to leverage the high spatial resolution data and study the variability of the data within a ground plot scale along with integrating data from the different sensors. Mathematical features are derived from the data and brought into a decision tree classification algorithm (rpart), in order to create an ecosystem map for the site. The hyperspectral and lidar features serve as proxies for chemical, functional, and structural differences in the vegetation types for each of the ecosystems. K-folds cross validation shows a training accuracy of 91%, a validation accuracy of 78%, and a 66% accuracy using independent ground validation. The results presented here represent an important contribution to utilizing integrated hyperspectral and lidar remote sensing data for ecosystem mapping, by relating the spatial variability of the data within a ground plot scale to a collection of vegetation types that make up a given ecosystem.

  7. Use of field reflectance data for crop mapping using airborne hyperspectral image

    NASA Astrophysics Data System (ADS)

    Nidamanuri, Rama Rao; Zbell, Bernd

    2011-09-01

    Recent developments in hyperspectral remote sensing technologies enable acquisition of image with high spectral resolution, which is typical to the laboratory or in situ reflectance measurements. There has been an increasing interest in the utilization of in situ reference reflectance spectra for rapid and repeated mapping of various surface features. Here we examined the prospect of classifying airborne hyperspectral image using field reflectance spectra as the training data for crop mapping. Canopy level field reflectance measurements of some important agricultural crops, i.e. alfalfa, winter barley, winter rape, winter rye, and winter wheat collected during four consecutive growing seasons are used for the classification of a HyMAP image acquired for a separate location by (1) mixture tuned matched filtering (MTMF), (2) spectral feature fitting (SFF), and (3) spectral angle mapper (SAM) methods. In order to answer a general research question "what is the prospect of using independent reference reflectance spectra for image classification", while focussing on the crop classification, the results indicate distinct aspects. On the one hand, field reflectance spectra of winter rape and alfalfa demonstrate excellent crop discrimination and spectral matching with the image across the growing seasons. On the other hand, significant spectral confusion detected among the winter barley, winter rye, and winter wheat rule out the possibility of existence of a meaningful spectral matching between field reflectance spectra and image. While supporting the current notion of "non-existence of characteristic reflectance spectral signatures for vegetation", results indicate that there exist some crops whose spectral signatures are similar to characteristic spectral signatures with possibility of using them in image classification.

  8. Land surface emissivity retrieval from airborne hyperspectral scanner thermal infrared data over urban surfaces

    NASA Astrophysics Data System (ADS)

    Gao, C. X.; Qian, Y. G.; Wang, N.; Ma, L. L.; Jiang, X. G.

    2015-12-01

    Land surface emissivity (LSE) is a key parameter for characterizing the land surface, and is vital for a wide variety of surface-atmosphere studies. This paper retrieved LSEs of land surfaces over the city of Madrid, Spain from airborne hyperspectral scanner (AHS) thermal infrared data using temperature emissivity separation (TES) method. Six different kinds of urban surfaces: asphalt, bare soil, granite, pavement, shrub and grass pavement, were selected to evaluate the performance of the TES method in urban areas. The results demonstrate that the TES method can be successfully applied to retrieve LSEs in urban area. The six urban surfaces have similar curve shape of emissivity spectra, with the lowest emissivity in band 73, and highest in band 78; the LSE for bare soil varies significantly with spectra, approximately from 0.90 in band 72 to 0.98 in band 78, whereas the LSE for grass has the smallest spectral variation, approximately from 0.965 in band 72 to 0.974 in band 78, and the shrub presents higher LSE than other surfaces in bands 72, 73, 75-77, but a little lower in bands 78 and 79. Furthermore, it is worth noting that band 73 is suitable for discriminating different urban surfaces because large LSE differences exist in this channel for different urban surfaces.

  9. Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data

    PubMed Central

    Stratoulias, Dimitris; Balzter, Heiko; Sykioti, Olga; Zlinszky, András; Tóth, Viktor R.

    2015-01-01

    Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution (i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite’s Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds. PMID:26378538

  10. [Inversion of vegetation canopy's chlorophyll content based on airborne hyperspectral image].

    PubMed

    Li, Ming-Ze; Zhao, Xiao-Hong; Liu, Yue; Lu, Wei; Dong, Shuai; Meng, Lu

    2013-01-01

    By using the airborne hyperspectral remote sensing data of Liangshui National Nature Reserve in Yichun of Heilongjiang Province, Northeast China, 15 spectral parameters including red edge area, triangular vegetation index, and normalized difference vegetation index, etc. were extracted, and in combining with 5 geographical parameters including slope, aspect, elevation, canopy density and total vegetation coverage, and by using SPAD-502, the vegetation canopy's relative chlorophyll content in the reserve were measured, with the correlations of the leaf spectral reflectivity, its first-order derivative and other deformations with the SPAD value analyzed. A prediction model for relative chlorophyll content was established by adopting the kernel-based partial least-squares regression, and a quantitative estimation of the vegetation canopy's relative chlorophyll content in the study area was carried out with the established model. The results showed that the model performed best when the sections were three and the principle components were ten. The co-efficient of determination of the model was R2 = 0.855, the mean absolute percent error was 9.6%, and the prediction precision was 89.7%. PMID:23718007

  11. Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data.

    PubMed

    Stratoulias, Dimitris; Balzter, Heiko; Sykioti, Olga; Zlinszky, András; Tóth, Viktor R

    2015-01-01

    Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution (i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite's Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds. PMID:26378538

  12. Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

    USGS Publications Warehouse

    Hively, W. Dean; McCarty, Gregory W.; Reeves, James B., III; Lang, Megan W.; Oesterling, Robert A.; Delwiche, Stephen R.

    2011-01-01

    Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm, ~10 nm resolution, 2.5 m spatial resolution). Surface soil samples (n = 315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted with R2 > 0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a 3 × 3 low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

  13. New hyperspectral difference water index for the extraction of urban water bodies by the use of airborne hyperspectral images

    NASA Astrophysics Data System (ADS)

    Xie, Huan; Luo, Xin; Xu, Xiong; Tong, Xiaohua; Jin, Yanmin; Pan, Haiyan; Zhou, Bingzhong

    2014-01-01

    Extracting surface land-cover types and analyzing changes are among the most common applications of remote sensing. One of the most basic tasks is to identify and map surface water boundaries. Spectral water indexes have been successfully used in the extraction of water bodies in multispectral images. However, directly applying a water index method to hyperspectral images disregards the abundant spectral information and involves difficulty in selecting appropriate spectral bands. It is also a challenge for a spectral water index to distinguish water from shadowed regions. The purpose of this study is therefore to develop an index that is suitable for water extraction by the use of hyperspectral images, and with the capability to mitigate the effects of shadow and low-albedo surfaces, especially in urban areas. Thus, we introduce a new hyperspectral difference water index (HDWI) to improve the water classification accuracy in areas that include shadow over water, shadow over other ground surfaces, and low-albedo ground surfaces. We tested the new method using PHI-2, HyMAP, and ROSIS hyperspectral images of Shanghai, Munich, and Pavia. The performance of the water index was compared with the normalized difference water index (NDWI) and the Mahalanobis distance classifier (MDC). With all three test images, the accuracy of HDWI was significantly higher than that of NDWI and MDC. Therefore, HDWI can be used for extracting water with a high degree of accuracy, especially in urban areas, where shadow caused by high buildings is an important source of classification error.

  14. Alteration mineral mapping and metallogenic prediction using CASI/SASI airborne hyperspectral data in Mingshujing area of Gansu Province, NW China

    NASA Astrophysics Data System (ADS)

    Sun, Yu; Zhao, Yingjun; Qin, Kai; Tian, Feng

    2016-04-01

    Hyperspectral remote sensing is a frontier of remote sensing. Due to its advantage of integrated image with spectrum, it can realize objects identification, superior to objects classification of multispectral remote sensing. Taken the Mingshujing area in Gansu Province of China as an example, this study extracted the alteration minerals and thus to do metallogenic prediction using CASI/SASI airborne hyperspectral data. The Mingshujing area, located in Liuyuan region of Gansu Province, is dominated by middle Variscan granites and Indosinian granites, with well developed EW- and NE-trending faults. In July 2012, our project team obtained the CASI/SASI hyperspectral data of Liuyuan region by aerial flight. The CASI hyperspectral data have 32 bands and the SASI hyperspectral data have 88 bands, with spectral resolution of 15nm for both. The hyperspectral raw data were first preprocessed, including radiometric correction and geometric correction. We then conducted atmospheric correction using empirical line method based on synchronously measured ground spectra to obtain hyperspectral reflectance data. Spectral dimension of hyperspectral data was reduced by the minimum noise fraction transformation method, and then purity pixels were selected. After these steps, image endmember spectra were obtained. We used the endmember spectrum election method based on expert knowledge to analyze the image endmember spectra. Then, the mixture tuned matched filter (MTMF) mapping method was used to extract mineral information, including limonite, Al-rich sericite, Al-poor sericite and chlorite. Finally, the distribution of minerals in the Mingshujing area was mapped. According to the distribution of limonite and Al-rich sericite mapped by CASI/SASI hyperspectral data, we delineated five gold prospecting areas, and further conducted field verification in these areas. It is shown that there are significant gold mineralized anomalies in surface in the Baixianishan and Xitan prospecting

  15. How Cities Breathe: Ground-Referenced, Airborne Hyperspectral Imaging Precursor Measurements To Space-Based Monitoring

    NASA Technical Reports Server (NTRS)

    Leifer, Ira; Tratt, David; Quattrochi, Dale; Bovensmann, Heinrich; Gerilowski, Konstantin; Buchwitz, Michael; Burrows, John

    2013-01-01

    Methane's (CH4) large global warming potential (Shindell et al., 2012) and likely increasing future emissions due to global warming feedbacks emphasize its importance to anthropogenic greenhouse warming (IPCC, 2007). Furthermore, CH4 regulation has far greater near-term climate change mitigation potential versus carbon dioxide CO2, the other major anthropogenic Greenhouse Gas (GHG) (Shindell et al., 2009). Uncertainties in CH4 budgets arise from the poor state of knowledge of CH4 sources - in part from a lack of sufficiently accurate assessments of the temporal and spatial emissions and controlling factors of highly variable anthropogenic and natural CH4 surface fluxes (IPCC, 2007) and the lack of global-scale (satellite) data at sufficiently high spatial resolution to resolve sources. Many important methane (and other trace gases) sources arise from urban and mega-urban landscapes where anthropogenic activities are centered - most of humanity lives in urban areas. Studying these complex landscape tapestries is challenged by a wide and varied range of activities at small spatial scale, and difficulty in obtaining up-to-date landuse data in the developed world - a key desire of policy makers towards development of effective regulations. In the developing world, challenges are multiplied with additional political access challenges. As high spatial resolution satellite and airborne data has become available, activity mapping applications have blossomed - i.e., Google maps; however, tap a minute fraction of remote sensing capabilities due to limited (three band) spectral information. Next generation approaches that incorporate high spatial resolution hyperspectral and ultraspectral data will allow detangling of the highly heterogeneous usage megacity patterns by providing diagnostic identification of chemical composition from solids (refs) to gases (refs). To properly enable these next generation technologies for megacity include atmospheric radiative transfer modeling

  16. Regional prediction of soil organic carbon content over croplands using airborne hyperspectral data

    NASA Astrophysics Data System (ADS)

    Vaudour, Emmanuelle; Gilliot, Jean-Marc; Bel, Liliane; Lefebvre, Josias; Chehdi, Kacem

    2015-04-01

    This study was carried out in the framework of the Prostock-Gessol3 and the BASC-SOCSENSIT projects, dedicated to the spatial monitoring of the effects of exogenous organic matter land application on soil organic carbon storage. It aims at identifying the potential of airborne hyperspectral AISA-Eagle data for predicting the topsoil organic carbon (SOC) content of bare cultivated soils over a large peri-urban area (221 km2) with both contrasted soils and SOC contents, located in the western region of Paris, France. Soils comprise hortic or glossic luvisols, calcaric, rendzic cambisols and colluvic cambisols. Airborne AISA-Eagle data (400-1000 nm, 126 bands) with 1 m-resolution were acquired on 17 April 2013 over 13 tracks which were georeferenced. Tracks were atmospherically corrected using a set of 22 synchronous field spectra of both bare soils, black and white targets and impervious surfaces. Atmospherically corrected track tiles were mosaicked at a 2 m-resolution resulting in a 66 Gb image. A SPOT4 satellite image was acquired the same day in the framework of the SPOT4-Take Five program of the French Space Agency (CNES) which provided it with atmospheric correction. The land use identification system layer (RPG) of 2012 was used to mask non-agricultural areas, then NDVI calculation and thresholding enabled to map agricultural fields with bare soil. All 18 sampled sites known to be bare at this very date were correctly included in this map. A total of 85 sites sampled in 2013 or in the 3 previous years were identified as bare by means of this map. Predictions were made from the mosaic spectra which were related to topsoil SOC contents by means of partial least squares regression (PLSR). Regression robustness was evaluated through a series of 1000 bootstrap data sets of calibration-validation samples. The use of the total sample including 27 sites under cloud shadows led to non-significant results. Considering 43 sites outside cloud shadows only, median

  17. Analysis of Coincident HICO and Airborne Hyperspectral Images Over Lake Erie Western Basin HABs

    NASA Astrophysics Data System (ADS)

    Cline, M., Jr.; Becker, R.; Lekki, J.; Bridgeman, T. B.; Tokars, R. P.; Anderson, R. C.

    2015-12-01

    Harmful algal blooms (HABs) produce waterborne toxins that pose a significant threat to people, livestock, and wildlife. 40 million people in both Canada and the U.S. depend on Great Lakes water. In the summer of 2014, in the Lake Erie Western Basin, an HAB of the cyanobacteria Microsystis was so severe that a water-use ban was in effect for the greater Toledo area, Ohio. This shut off the water supply to over 400,000 people from a single water intake. We investigated bloom intensity, composition, and spatial variability by comparing hyperspectral data from NASA's HICO, multispectral data from MODIS spaceborne imagers and NASA GRC's HSI imagers to on-lake ASD radiometer measurements using in situ water quality testing as ground reference data, all acquired on a single day during the bloom in 2014. HICO imagery acquired on Aug 15, 2014 was spatially georeferenced and atmospherically corrected using empirical line method utilizing on-lake ASD spectra. HSI imagery were processed in a similar way. Cyanobacteria Index (CI) images were created from processed images using the Wynne (2010) algorithm, previously used for MODIS and MERIS imagery. This algorithm-generated CI images provide reliable results for both ground level (R²=0.7784), and satellite imagery (R²=0.7794) for seven sampling points in Lake Erie's western basin. Spatial variability in the bloom was high, and was not completely characterized by the lower spatial resolution MODIS data. The ability to robustly atmospherically correct and generate useful CI maps from airborne and satellite sensors can provide a time- and cost-effective method for HABs analysis. Timely processing of these high spatial and spectral resolution remote sensing data can aid in management of water intake resources.

  18. Mapping of macro and micro nutrients of mixed pastures using airborne AisaFENIX hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Pullanagari, R. R.; Kereszturi, Gábor; Yule, I. J.

    2016-07-01

    On-farm assessment of mixed pasture nutrient concentrations is important for animal production and pasture management. Hyperspectral imaging is recognized as a potential tool to quantify the nutrient content of vegetation. However, it is a great challenge to estimate macro and micro nutrients in heterogeneous mixed pastures. In this study, canopy reflectance data was measured by using a high resolution airborne visible-to-shortwave infrared (Vis-SWIR) imaging spectrometer measuring in the wavelength region 380-2500 nm to predict nutrient concentrations, nitrogen (N) phosphorus (P), potassium (K), sulfur (S), zinc (Zn), sodium (Na), manganese (Mn) copper (Cu) and magnesium (Mg) in heterogeneous mixed pastures across a sheep and beef farm in hill country, within New Zealand. Prediction models were developed using four different methods which are included partial least squares regression (PLSR), kernel PLSR, support vector regression (SVR), random forest regression (RFR) algorithms and their performance compared using the test data. The results from the study revealed that RFR produced highest accuracy (0.55 ⩽ R2CV ⩽ 0.78; 6.68% ⩽ nRMSECV ⩽ 26.47%) compared to all other algorithms for the majority of nutrients (N, P, K, Zn, Na, Cu and Mg) described, and the remaining nutrients (S and Mn) were predicted with high accuracy (0.68 ⩽ R2CV ⩽ 0.86; 13.00% ⩽ nRMSECV ⩽ 14.64%) using SVR. The best training models were used to extrapolate over the whole farm with the purpose of predicting those pasture nutrients and expressed through pixel based spatial maps. These spatially registered nutrient maps demonstrate the range and geographical location of often large differences in pasture nutrient values which are normally not measured and therefore not included in decision making when considering more effective ways to utilized pasture.

  19. [Estimating Leaf Area Index of Crops Based on Hyperspectral Compact Airborne Spectrographic Imager (CASI) Data].

    PubMed

    Tang, Jian-min; Liao, Qin-hong; Liu, Yi-qing; Yang, Gui-jun; Feng, Hai-kuanr; Wang, Ji-hua

    2015-05-01

    The fast estimation of leaf area index (LAI) is significant for learning the crops growth, monitoring the disease and insect, and assessing the yield of crops. This study used the hyperspectral compact airborne spectrographic imager (CASI) data of Zhangye city, in Heihe River basin, on July 7, 2012, and extracted the spectral reflectance accurately. The potential of broadband and red-edge vegetation index for estimating the LAI of crops was comparatively investigated by combined with the field measured data. On this basis, the sensitive wavebands for estimating the LAI of crops were selected and two new spectral indexes (NDSI and RSI) were constructed, subsequently, the spatial distribution of LAI in study area was analyzed. The result showed that broadband vegetation index NDVI had good effect for estimating the LAI when the vegetation coverage is relatively lower, the R2 and RMSE of estimation model were 0. 52, 0. 45 (p<0. 01) , respectively. For red-edge vegetation index, CIred edge took the different crop types into account fully, thus it gained the same estimation accuracy with NDVI. NDSI(569.00, 654.80) and RSI(597.60, 654.80) were constructed by using waveband combination algorithm, which has superior estimation results than NDVI and CIred edge. The R2 of estimation model used NDSI(569.00, 654.80) was 0. 77(p<0. 000 1), it mainly used the wavebands near the green peak and red valley of vegetation spectrum. The spatial distribution map of LAI was made according to the functional relationship between the NDSI(569.00, 654.80) and LAI. After analyzing this map, the LAI values were lower in the northwest of study area, this indicated that more fertilizer should be increased in this area. This study can provide technical support for the agricultural administrative department to learn the growth of crops quickly and make a suitable fertilization strategy. PMID:26415459

  20. Airborne hyperspectral imaging for sensing phosphorus concentration in the Lake Okeechobee drainage basin

    NASA Astrophysics Data System (ADS)

    Bogrekci, Ismail; Lee, Won Suk; Jordan, Jonathan D.

    2005-05-01

    Eutrophication disturbs the ecological balance in the Lake Okeechobee due to high concentration of phosphorus emanated from the regions in the lake's drainage basin. Ability of measuring phosphorus (P) concentrations of water in the Lake Okeechobee itself is very important. Furthermore, monitoring P in its drainage basins is crucial in order to find the cause of P loading and contributing regions. Also, inexpensive real-time sensing capability for a large area in a short time would help scientist, government agents, and civilians to understand the causes, spot the high-risk areas, and develop management practices for restoring the natural equilibrium. In order to measure P concentrations in the Lake Okeechobee drainage basin, airborne hyperspectral images were taken from five representative target sites by deploying a modified queen air twin engine aircraft. Each flight line covered a swath of approximately 365 m wide. Spatial resolution was about 1 m. Spectral range covered was between 412.65 and 991.82 nm with an approximate of 5 nm spectral resolution. Ground truthing was conducted to collect soil and vegetation samples, GPS coordinates of each location, and reflectance measurement of each sample. On the ground, spectral reflectance was measured using a handheld spectrometer in 400-2500 nm. The samples were sent to a laboratory for chemical analysis. Also diffuse reflectance of the samples was measured in a laboratory setting using a spectrophotometer with an integrating sphere. Images were geocorrected and rectified to reduce geometric effect. Calibration of images was conducted to obtain actual reflectance of the target area. Score, SAM (Spectral Angle Mapping), SFF (Spectral Feature Fitting) were computed for spectral matching with image derived spectral library.

  1. An algorithm for simultaneous inversion of aerosol properties and surface reflectance from airborne GeoTASO hyperspectral data

    NASA Astrophysics Data System (ADS)

    Hou, W.; Wang, J.; Xu, X.; Ding, S.; Han, D.; Leitch, J. W.; Delker, T.; Chen, G.

    2014-12-01

    This paper presents an inversion method to retrieve aerosol properties from the hyperspectral data collected by airborne GeoTASO (Geostationary Trance gas and Aerosol Sensor Optimization). Mounted on the NASA HU-25C aircraft, GeoTASO measures radiation in 1000 spectral bands from 415 nm to 696 nm, and is a prototype for the TEMPO (Tropospheric Emissions: Monitoring of Pollution) instrument. It flew over Houston during September 2013 and gathered several days' of airborne hyperspectral remote sensing data for our research. Our inversion method, which is based on the optimization theory and different from the traditional lookup table (LUT) retrieval technique, can simultaneously retrieve parameters of atmospheric aerosols such as the aerosol optical depth and other aerosol parameters, as well as the surface reflectance albedo. To provide constraints of hyperspectral surface reflectance in the inversion, we first conduct principal component analysis (PCA) using 46 reflectance spectra of various plants and vegetation to identify the most influential components. With the first six principal components and the corresponding calculated weight vector, the spectra could be reconstructed with an accuracy of 1%. UNL-VRTM (UNified Linearized Radiative Transfer Model) is employed for forward model calculation, and its outputs include not only the Stokes 4-vector elements, but also their sensitivities (Jacobians) with respect to the aerosol properties parameters and the principal components of surface spectral reflectance. The inversion is carried out with optimization algorithm L-BFGS-B (Large scale BFGS Bound constrained), and is conducted iteratively until the modeled spectral radiance fits with GeoTASO measurements. Finally, the retrieval results of aerosol optical depth and other aerosol parameters are compared against those retrieved by AEROENT and/or in situ measurements during the aircraft campaign.

  2. Fusion of full waveform Laserscanning and airborne hyperspectral remote sensing data for the characterization of forest stands

    NASA Astrophysics Data System (ADS)

    Buddenbaum, Henning

    2010-05-01

    Hyperspectral data offer the maximum spectral reflectance information available from remote sensing. A continuous spectrum of narrow bands with near-laboratory quality is recorded for each pixel. This data can be used for difficult classification tasks or detailed quantitative analyses, e.g. determination of chlorophyll or water content in leaves. But in forested areas, discerning between different age classes of the same tree species is still error-prone. Airborne Laserscanning measures the three-dimensional position of every reflecting object and can be used to map tree heights and crown volumes. These are highly correlated with tree age and timber volume. In addition, Laserscanner data can be used to differentiate between coniferous and deciduous trees either by analysing crown shapes that lead to different surface roughness or by exploiting the intensity information of laser echoes from the crowns. But a more detailed determination of tree species is not possible using Laserscanning alone. The combination of hyperspectral and Laserscanning data promises the possibility to map both tree species and age classes. We used a HyMap data set with 122 bands recorded in 2003 and a full waveform Laserscanning recorded in 2005 in the same area, Idarwald Forest in South-western Germany. To combine both datasets, we defined voxels above the HyMap pixels, containing the mean laser intensity in slices of 50 cm height. These voxels form a second hyperspectral dataset of 76 bands with the same geometry as the HyMap image, so that they could be fused into a 198 band image. The joined image performed better in a classification of tree species and age classes than each of the single images and also better than a dataset consisting of the hyperspectral image and a tree height map. Apart from classification, it can also be used to derive tree heights and crown base heights and to estimate biomass, leaf area index and timber volume and to characterize the vertical forest structure.

  3. Practical example for use of the supervised vicarious calibration (SVC) method on multisource hyperspectral imagery data - ValCalHyp airborne hyperspectral campaign under the EUFAR framework

    NASA Astrophysics Data System (ADS)

    Brook, A.; Ben Dor, E.

    2014-09-01

    A novel approach for radiometric calibration and atmospheric correction of airborne hyperspectral (HRS) data, termed supervised vicarious calibration (SVC) was proposed by Brook and Ben-Dor in 2010. The present study was aimed at validating this SVC approach by simultaneously using several different airborne HSR sensors that acquired HSR data over several selected sites at the same time. The general goal of this study was to apply a cross-calibration approach to examine the capability and stability of the SVC method and to examine its validity. This paper reports the result of the multi sensors campaign took place over Salon de Provenance, France on behalf of the ValCalHyp project took place in 2011. The SVC method enabled the rectification of the radiometric drift of each sensor and improves their performance significantly. The flight direction of the SVC targets was found to be a critical issue for such correction and recommendations have been set for future utilization of this novel method. The results of the SVC method were examined by comparing ground-truth spectra of several selected validation targets with the image spectra as well as by comparing the classified water quality images generated from all sensors over selected water bodies.

  4. Longwave infrared compressive hyperspectral imager

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  5. Mapping beech ( Fagus sylvatica L.) forest structure with airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Cho, Moses Azong; Skidmore, Andrew K.; Sobhan, Istiak

    2009-06-01

    Estimating forest structural attributes using multispectral remote sensing is challenging because of the saturation of multispectral indices at high canopy cover. The objective of this study was to assess the utility of hyperspectral data in estimating and mapping forest structural parameters including mean diameter-at-breast height (DBH), mean tree height and tree density of a closed canopy beech forest ( Fagus sylvatica L.). Airborne HyMap images and data on forest structural attributes were collected from the Majella National Park, Italy in July 2004. The predictive performances of vegetation indices (VI) derived from all possible two-band combinations (VI ( i, j) = ( Ri - Rj)/( Ri + Rj), where Ri and Rj = reflectance in any two bands) were evaluated using calibration ( n = 33) and test ( n = 20) data sets. The potential of partial least squares (PLS) regression, a multivariate technique involving several bands was also assessed. New VIs based on the contrast between reflectance in the red-edge shoulder (756-820 nm) and the water absorption feature centred at 1200 nm (1172-1320 nm) were found to show higher correlations with the forest structural parameters than standard VIs derived from NIR and visible reflectance (i.e. the normalised difference vegetation index, NDVI). PLS regression showed a slight improvement in estimating the beech forest structural attributes (prediction errors of 27.6%, 32.6% and 46.4% for mean DBH, height and tree density, respectively) compared to VIs using linear regression models (prediction errors of 27.8%, 35.8% and 48.3% for mean DBH, height and tree density, respectively). Mean DBH was the best predicted variable among the stand parameters (calibration R2 = 0.62 for an exponential model fit and standard error of prediction = 5.12 cm, i.e. 25% of the mean). The predicted map of mean DBH revealed high heterogeneity in the beech forest structure in the study area. The spatial variability of mean DBH occurs at less than 450 m. The DBH

  6. Urban forest ecosystem analysis using fused airborne hyperspectral and lidar data

    NASA Astrophysics Data System (ADS)

    Alonzo, Mike Gerard

    Urban trees are strategically important in a city's effort to mitigate their carbon footprint, heat island effects, air pollution, and stormwater runoff. Currently, the most common method for quantifying urban forest structure and ecosystem function is through field plot sampling. However, taking intensive structural measurements on private properties throughout a city is difficult, and the outputs from sample inventories are not spatially explicit. The overarching goal of this dissertation is to develop methods for mapping urban forest structure and function using fused hyperspectral imagery and waveform lidar data at the individual tree crown scale. Urban forest ecosystem services estimated using the USDA Forest Service's i-Tree Eco (formerly UFORE) model are based largely on tree species and leaf area index (LAI). Accordingly, tree species were mapped in my Santa Barbara, California study area for 29 species comprising >80% of canopy. Crown-scale discriminant analysis methods were introduced for fusing Airborne Visible Infrared Imaging Spectrometry (AVIRIS) data with a suite of lidar structural metrics (e.g., tree height, crown porosity) to maximize classification accuracy in a complex environment. AVIRIS imagery was critical to achieving an overall species-level accuracy of 83.4% while lidar data was most useful for improving the discrimination of small and morphologically unique species. LAI was estimated at both the field-plot scale using laser penetration metrics and at the crown scale using allometry. Agreement of the former with photographic estimates of gap fraction and the latter with allometric estimates based on field measurements was examined. Results indicate that lidar may be used reasonably to measure LAI in an urban environment lacking in continuous canopy and characterized by high species diversity. Finally, urban ecosystem services such as carbon storage and building energy-use modification were analyzed through combination of aforementioned

  7. AN ECOLOGICAL ASSESSMENT OF OPPORTUNISTIC PLANT SPECIES IN GREAT LAKES COASTAL WETLANDS USING AIRBORNE HYPERSPECTRAL DATE

    EPA Science Inventory

    Airbome hyperspectral data were used to detect dense patches of Phragmites australis, a native opportunist plant species, at the Pointe Mouillee coastal wetland complex (Wayne and Monroe Counties, Michigan). This study provides initial results from one of thirteen coastal wetland...

  8. Airborne Multi-Angle Hyper-Spectral Measurements of White Caps on the Open Ocean

    NASA Astrophysics Data System (ADS)

    Laveigne, J.; Cairns, B.; Diner, D. J.

    2004-05-01

    The influence of whitecaps on the atmospheric correction of ocean color measurements is highly dependent on the spectral variation of albedo that is assumed for the whitecaps. Field measurements of breaking waves in the surf zone indicate a strong spectral variation in whitecap reflectance with the reflectance at 1650 nm nm decreasing by 95% relative to that at 440 nm. The cause of this spectral variation is thought to be the strong absorption by water at longer wavelengths that attenuates light reflected from submerged bubbles. Measurements made during an ocean cruise suggest that the magnitude of this decrease is typically less in the open ocean where the wave breaking is less violent and bubbles are not injected as deep into the water. Nonetheless, even in the open ocean, when whitecaps are large and bright similar decreases in reflectance from 440 nm to 860 nm to those observed in the surf zone are seen. Unfortunately, although measurements in the vicinity of 1600 and 2200 nm are important for remote sensing of aerosols and the atmospheric correction of ocean color measurements, the longest wavelength used for the open ocean measurements was 860 nm. Information about typical reflectance decreases from 440 nm to these longer wavelengths is therefore missing. One approach to remedying this absence of information about the spectral variation of white cap albedo across the solar spectrum is to use an airborne imaging spectrometer. However, a significant difficulty in using airborne, or ship-borne, instrumentation to measure the spectral albedo of whitecaps is the contamination of data by sun glitter. It is usually much more difficult than anticipated to filter data to reject glitter, even for ship-borne measurements with a television camera that provides a visual reference. This means that most data that is reported is obtained under overcast conditions. One approach to alleviating the problems caused by sun glitter is to using multi-angle remote sensing. If

  9. VNIR-SWIR-TIR hyperspectral airborne campaign for soil and sediment mapping in semi-arid south african environments

    NASA Astrophysics Data System (ADS)

    Milewski, Robert; Chabrillat, Sabine; Eisele, Andreas

    2016-04-01

    Airborne hyperspectral remote sensing techniques has been proven to offer efficient procedures for soil and sediment mineralogical mapping in arid areas on larger scales. Optical methods based on traditional remote sensing windows using the solar reflective spectral wavelength range from the visible-near infrared (VNIR: 0.4-1.1 μm) to the short-wave infrared region (SWIR: 1.1-2.5 μm) allow mapping of common soil properties such as iron oxides, textural characteristics and organic carbon. However, soil mapping in semi-arid environments using VNIR-SWIR is currently limited due to specific spectral characteristics. Challenges appear in such environments due to the common presence of sandy soils (coarse textured) which grain size distribution is driven by the dominant mineral, quartz (SiO2), and which lacks any distinctive Si-O bond related spectral features within the VNIR-SWIR. Furthermore, another challenge is represented by the common presence of other specific spectral features due to different salts (gypsum, halite) or coatings of different forms (cyanobacteria, iron-oxides and/or -oxyhydroxides) for which few studies exists or that oft prevent detection of any other potential spectral feature of e.g. soil organics. In this context, more methodological developments are needed to overcome current limitations of hyperspectral remote sensing for arid areas, and to extent its scope using the thermal infrared (TIR) wavelength region within the atmospheric window between 8 and 14 μm (longwave infrared). In 2015 an extensive VNIR-SWIR-TIR airborne hyperspectral dataset consisting of HySpex-VNIR, HySpex-SWIR (NEO) and Hyper-Cam (TELOPS) data has been acquired in various Namibian and South African landscapes part of the Dimap/GFZ campaign in the frame of the BMBF-SPACES Geoarchive project. Research goals are 1) to demonstrate the capabilities to extract information from such a dataset and 2) to demonstrate the potential of advanced hyperspectral remote sensing

  10. Mapping tree health using airborne full-waveform laser scans and hyperspectral imagery: a case study for floodplain eucalypt forest

    NASA Astrophysics Data System (ADS)

    Shendryk, I.; Tulbure, M. G.; Broich, M.

    2014-12-01

    Barmah-Millewa Forest (BMF), the largest River Red Gum forest in the world, located in south-eastern Australia is suffering from severe dieback, thus diminishing its ecological and economical value. Previous research showed that dieback is a good predictor of the forest health and stressed the need for BMF health mapping and change monitoring. In this respect, airborne laser scanning and hyperspectral imaging offer extensive spatial and spectral coverage of measurements and represent an ideal tool for forest health mapping at individual tree scale. The aim of this project is to quantify the health of individual, structurally complex floodplain eucalypt trees by integrating airborne hyperspectral imagery, full-waveform laser scans and field measurements. An aerial survey, conducted in May 2014, was designed to provide a representative sample of BMF tree health. The positioning of 17 flight lines aimed to capture the heterogeneity of the forest health and flood frequency. Preliminary analysis of the aerial remote sensing data with regards to chlorophyll concentrations, dieback levels and canopy densities allowed us to target our field campaign (conducted in June 2014). Field measurements included accurate position measurements, LAI, visual assessment, spectral measurement and mensuration of individual trees in 30 m2 plots. For detection of individual tree trunks from airborne laser scans we used a novel approach based on Euclidean distance clustering, taking advantage of the intensity and pulse width difference between woody and leaf tree compartments. The detected trunks were used to seed a minimum cut algorithm for tree crown delineation. In situ measurements confirmed the high structural diversity of the forest and allowed the calibration of the tree detection algorithm. An overall accuracy of the tree detection of 54% and 67% was achieved for trees with circumference over 40 cm and over 100 cm respectively. As a further step, 3D point clusters representing

  11. Automatic Extraction of Optimal Endmembers from Airborne Hyperspectral Imagery Using Iterative Error Analysis (IEA) and Spectral Discrimination Measurements

    PubMed Central

    Song, Ahram; Chang, Anjin; Choi, Jaewan; Choi, Seokkeun; Kim, Yongil

    2015-01-01

    Pure surface materials denoted by endmembers play an important role in hyperspectral processing in various fields. Many endmember extraction algorithms (EEAs) have been proposed to find appropriate endmember sets. Most studies involving the automatic extraction of appropriate endmembers without a priori information have focused on N-FINDR. Although there are many different versions of N-FINDR algorithms, computational complexity issues still remain and these algorithms cannot consider the case where spectrally mixed materials are extracted as final endmembers. A sequential endmember extraction-based algorithm may be more effective when the number of endmembers to be extracted is unknown. In this study, we propose a simple but accurate method to automatically determine the optimal endmembers using such a method. The proposed method consists of three steps for determining the proper number of endmembers and for removing endmembers that are repeated or contain mixed signatures using the Root Mean Square Error (RMSE) images obtained from Iterative Error Analysis (IEA) and spectral discrimination measurements. A synthetic hyperpsectral image and two different airborne images such as Airborne Imaging Spectrometer for Application (AISA) and Compact Airborne Spectrographic Imager (CASI) data were tested using the proposed method, and our experimental results indicate that the final endmember set contained all of the distinct signatures without redundant endmembers and errors from mixed materials. PMID:25625907

  12. Selectable Hyperspectral Airborne Remote-sensing Kit (SHARK) on the Vision II turbine rotorcraft UAV over the Florida Keys

    NASA Astrophysics Data System (ADS)

    Holasek, R. E.; Nakanishi, K.; Swartz, B.; Zacaroli, R.; Hill, B.; Naungayan, J.; Herwitz, S.; Kavros, P.; English, D. C.

    2013-12-01

    As part of the NASA ROSES program, the NovaSol Selectable Hyperspectral Airborne Remote-sensing Kit (SHARK) was flown as the payload on the unmanned Vision II helicopter. The goal of the May 2013 data collection was to obtain high resolution visible and near-infrared (visNIR) hyperspectral data of seagrasses and coral reefs in the Florida Keys. The specifications of the SHARK hyperspectral system and the Vision II turbine rotorcraft will be described along with the process of integrating the payload to the vehicle platform. The minimal size, weight, and power (SWaP) specifications of the SHARK system is an ideal match to the Vision II helicopter and its flight parameters. One advantage of the helicopter over fixed wing platforms is its inherent ability to take off and land in a limited area and without a runway, enabling the UAV to be located in close proximity to the experiment areas and the science team. Decisions regarding integration times, waypoint selection, mission duration, and mission frequency are able to be based upon the local environmental conditions and can be modified just prior to take off. The operational procedures and coordination between the UAV pilot, payload operator, and scientist will be described. The SHARK system includes an inertial navigation system and digital elevation model (DEM) which allows image coordinates to be calculated onboard the aircraft in real-time. Examples of the geo-registered images from the data collection will be shown. SHARK mounted below VTUAV. SHARK deployed on VTUAV over water.

  13. Detection of spatio-temporal changes of Norway spruce forest stands in Ore Mountains using airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Misurec, J.; Kopačková, V.; Lhotáková, Z.; Albrechtova, J.; Campbell, P. K. E.

    2015-12-01

    The Ore Mountains are an example of the region that suffered from severe environmental pollution caused by long-term coal mining and heavy industry leading to massive dieback of the local Norway spruce forests between the 1970's and 1990's. The situation became getting better at the end of 1990's after pollution loads significantly decreased. In 1998 and 2013, airborne hyperspectral data (with sensor ASAS and APEX, respectively) were used to study recovery of the originally damaged forest stands and compared them with those that have been less affected by environmental pollution. The field campaign (needle biochemical analysis, tree defoliation etc.) accompanied hyperspectral imagery acquisition. An analysis was conducted assessing a set of 16 vegetation indices providing complex information on foliage, biochemistry and canopy biophysics and structure. Five of them (NDVI, NDVI705, VOG1, MSR and TCARI/OSAVI) showing the best results were employed to study spatial gradients as well as temporal changes. The detected gradients are in accordance with ground truth data on representative trees. The obtained results indicate that the original significant differences between the damaged and undamaged stands have been generally levelled until 2013, although it is still possible to detect signs of the previous damages in several cases.

  14. Aerosol, Cloud and Trace Gas Observations Derived from Airborne Hyperspectral Radiance and Direct Beam Measurements in Recent Field Campaigns

    NASA Technical Reports Server (NTRS)

    Redemann, J.; Flynn, C. J.; Shinozuka, Y.; Kacenelenbogen, M.; Segal-Rosenheimer, M.; LeBlanc, S.; Russell, P. B.; Livingston, J. M.; Schmid, B.; Dunagan, S. E.; Johnson, R. R.

    2014-01-01

    The AERONET (AErosol RObotic NETwork) ground-based suite of sunphotometers provides measurements of spectral aerosol optical depth (AOD), precipitable water and spectral sky radiance, which can be inverted to retrieve aerosol microphysical properties that are critical to assessments of aerosol-climate interactions. Because of data quality criteria and sampling constraints, there are significant limitations to the temporal and spatial coverage of AERONET data and their representativeness for global aerosol conditions. The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument, jointly developed by NASA Ames and PNNL with NASA Goddard collaboration, combines airborne sun tracking and AERONET-like sky scanning with spectroscopic detection. Being an airborne instrument, 4STAR has the potential to fill gaps in the AERONET data set. Dunagan et al. [2013] present results establishing the performance of the instrument, along with calibration, engineering flight test, and preliminary scientific field data. The 4STAR instrument operated successfully in the SEAC4RS [Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys] experiment in Aug./Sep. 2013 aboard the NASA DC-8 and in the DoE [Department of Energy]-sponsored TCAP [Two Column Aerosol Project, July 2012 & Feb. 2013] experiment aboard the DoE G-1 aircraft (Shinozuka et al., 2013), and acquired a wealth of data in support of mission objectives on all SEAC4RS and TCAP research flights. 4STAR provided direct beam measurements of hyperspectral AOD, columnar trace gas retrievals (H2O, O3, NO2; Segal-Rosenheimer et al., 2014), and the first ever airborne hyperspectral sky radiance scans, which can be inverted to yield the same products as AERONET ground-based observations. In addition, 4STAR measured zenith radiances underneath cloud decks for retrievals of cloud optical depth and effective diameter. In this presentation, we provide an overview of the new

  15. ESTIMATING WITHIN-FIELD VARIATIONS IN SOIL PROPERTIES FROM AIRBORNE HYPERSPECTRAL IMAGES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The ability of hyperspectral image (HSI) data to provide estimates of soil electrical conductivity (EC) and soil fertility levels without requiring extensive field data collection was investigated. Bare soil images were acquired using a prism grating pushbroom scanner in April 2000 and May 2001 for ...

  16. Comparison of airborne multispectral and hyperspectral imagery for estimating grain sorghum yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Both multispectral and hyperspectral images are being used to monitor crop conditions and map yield variability, but limited research has been conducted to compare the differences between these two types of imagery for assessing crop growth and yields. The objective of this study was to compare airb...

  17. Spectral angle mapper (SAM) based citrus greening disease detection using airborne hyperspectral imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Over the past two decades, hyperspectral (HS) imaging has provided remarkable performance in ground object classification and disease identification, due to its high spectral resolution. In this paper, a novel method named “extended spectral angle mapping (ESAM)” is proposed to detect citrus greenin...

  18. Prediction of senescent rangeland canopy structural attributes with airborne hyperspectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Canopy structural and chemical data are needed for senescent, mixed-grass prairie landscapes in autumn, yet models driven by image data are lacking for rangelands dominated by non-photosynthetically active vegetation (NPV). Here, we report how aerial hyperspectral imagery might be modeled to predic...

  19. LWIR polarimeter calibration

    NASA Astrophysics Data System (ADS)

    Blumer, Robert V.; Miller, Miranda A.; Howe, James D.; Stevens, Mark A.

    2002-01-01

    Performance reported efforts to calibrate a MWIR imaging polarimeter met with moderate success. Recent efforts to calibrate a LWIR sensor using a different technique have been much more fruitful. For our sensor, which is based on a rotating retarder, we have improved system calibration substantially be including nonuniformity correction at all measurement positions of the retarder in our polarization data analysis. This technique can account for effects such as spurious optical reflections within a camera system that had been masquerading as false polarization in our previous data analysis methodology. Our techniques will be described and our calibration results will be quantified. Data from field-testing will be presented.

  20. Mapping Ungulate Habitats in Yellowstone National Park with Airborne Hyperspectral Data

    NASA Technical Reports Server (NTRS)

    Terrie, Gregory; Warner, Amanda; Spruce, Joseph

    2001-01-01

    Mapping vegetation habitats of ungulates (e.g., bison, elk, and deer) is critical to the development of efficient wildlife management and monitoring practices in Yellowstone National Park. Image endmembers were chosen using the ENVI minimum noise fraction, pixel purity index, N-dimensional visualizer approach. The spectral angle mapper algorithm was used to classify the image. This process was applied to low altitude AVIRIS and Probe-1 hyperspectral imagery of the Lamar River/Soda Butte Creek confluence to map several ungulate habitats (e.g., grasses, sedge, sage, aspen, willow, and cottonwood. The results are being compared to field measurements and large-scale color infrared aerial photography to assess mapping accuracy. The use of AVIRIS and Probe-1 data enabled the examination of hyperspectral data collected at different spatial and spectral resolutions.

  1. Airborne Demonstration of FPGA Implementation of Fast Lossless Hyperspectral Data Compression System

    NASA Technical Reports Server (NTRS)

    Keymeulen, D.; Aranki, N.; Bakhshi, A.; Luong, H.; Sartures, C.; Dolman, D.

    2014-01-01

    Efficient on-board lossless hyperspectral data compression reduces data volume in order to meet NASA and DoD limited downlink capabilities. The technique also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware.

  2. Concept and integration of an on-line quasi-operational airborne hyperspectral remote sensing system

    NASA Astrophysics Data System (ADS)

    Schilling, Hendrik; Lenz, Andreas; Gross, Wolfgang; Perpeet, Dominik; Wuttke, Sebastian; Middelmann, Wolfgang

    2013-10-01

    Modern mission characteristics require the use of advanced imaging sensors in reconnaissance. In particular, high spatial and high spectral resolution imaging provides promising data for many tasks such as classification and detecting objects of military relevance, such as camouflaged units or improvised explosive devices (IEDs). Especially in asymmetric warfare with highly mobile forces, intelligence, surveillance and reconnaissance (ISR) needs to be available close to real-time. This demands the use of unmanned aerial vehicles (UAVs) in combination with downlink capability. The system described in this contribution is integrated in a wing pod for ease of installation and calibration. It is designed for the real-time acquisition and analysis of hyperspectral data. The main component is a Specim AISA Eagle II hyperspectral sensor, covering the visible and near-infrared (VNIR) spectral range with a spectral resolution up to 1.2 nm and 1024 pixel across track, leading to a ground sampling distance below 1 m at typical altitudes. The push broom characteristic of the hyperspectral sensor demands an inertial navigation system (INS) for rectification and georeferencing of the image data. Additional sensors are a high resolution RGB (HR-RGB) frame camera and a thermal imaging camera. For on-line application, the data is preselected, compressed and transmitted to the ground control station (GCS) by an existing system in a second wing pod. The final result after data processing in the GCS is a hyperspectral orthorectified GeoTIFF, which is filed in the ERDAS APOLLO geographical information system. APOLLO allows remote access to the data and offers web-based analysis tools. The system is quasi-operational and was successfully tested in May 2013 in Bremerhaven, Germany.

  3. Estimation of aerosol type from airborne hyperspectral data: a new technique designed for industrial plume characterization

    NASA Astrophysics Data System (ADS)

    Deschamps, A.; Marion, R.; Foucher, P.-Y.; Briottet, X.

    2012-11-01

    The determination of the aerosol type in a plume from remotely sensed data without any a priori knowledge is a challenging task. If several methods have already been developed to characterize the aerosols from multi or hyperspectral data, they are not suited for industrial particles, which have specific physical and optical properties, changing quickly and in a complex way with the distance from the source emission. From radiative transfer equations, we have developed an algorithm, based on a Look-Up Table approach, enabling the determination of the type of this kind of particles from hyperspectral data. It consists in the selection of pixels pairs, located at the transitions between two kinds of grounds (or between an illuminated and a shadow area), then in the comparison between normalized estimated Aerosol Optical Thicknesses (AOTs) and pre-calculated AOTs. The application of this algorithm to simulated data leads to encouraging results: the selection of only six pixels pairs allows the algorithm to differentiate aerosols emitted by a metallurgical plant from biomass burning particles, urban aerosols and particles from an oil depot explosion, regardless the size and the aerosol concentration. The algorithm performances are better for a relatively high AOT but the single scattering approximation does not enable the characterization of thick plumes (AOT above 2.0). However, the choice of transitions (type of grounds) does not seem to significantly affect the results.

  4. Data products of NASA Goddard's LiDAR, hyperspectral, and thermal airborne imager (G-LiHT)

    NASA Astrophysics Data System (ADS)

    Corp, Lawrence A.; Cook, Bruce D.; McCorkel, Joel; Middleton, Elizabeth M.

    2015-06-01

    Scientists in the Biospheric Sciences Laboratory at NASA's Goddard Space Flight Center have undertaken a unique instrument fusion effort for an airborne package that integrates commercial off the shelf LiDAR, Hyperspectral, and Thermal components. G-LiHT is a compact, lightweight and portable system that can be used on a wide range of airborne platforms to support a number of NASA Earth Science research projects and space-based missions. G-LiHT permits simultaneous and complementary measurements of surface reflectance, vegetation structure, and temperature, which provide an analytical framework for the development of new algorithms for mapping plant species composition, plant functional types, biodiversity, biomass, carbon stocks, and plant growth. G-LiHT and its supporting database are designed to give scientists open access to the data that are needed to understand the relationship between ecosystem form and function and to stimulate the advancement of synergistic algorithms. This system will enhance our ability to design new missions and produce data products related to biodiversity and climate change. G-LiHT has been operational since 2011 and has been used to collect data for a number of NASA and USFS sponsored studies, including NASA's Carbon Monitoring System (CMS) and the American ICESat/GLAS Assessment of Carbon (AMIGA-Carb). These acquisitions target a broad diversity of forest communities and ecoregions across the United States and Mexico. Here, we will discuss the components of G-LiHT, their calibration and performance characteristics, operational implementation, and data processing workflows. We will also provide examples of higher level data products that are currently available.

  5. High spatial resolution imaging of methane and other trace gases with the airborne Hyperspectral Thermal Emission Spectrometer (HyTES)

    NASA Astrophysics Data System (ADS)

    Hulley, Glynn C.; Duren, Riley M.; Hopkins, Francesca M.; Hook, Simon J.; Vance, Nick; Guillevic, Pierre; Johnson, William R.; Eng, Bjorn T.; Mihaly, Jonathan M.; Jovanovic, Veljko M.; Chazanoff, Seth L.; Staniszewski, Zak K.; Kuai, Le; Worden, John; Frankenberg, Christian; Rivera, Gerardo; Aubrey, Andrew D.; Miller, Charles E.; Malakar, Nabin K.; Sánchez Tomás, Juan M.; Holmes, Kendall T.

    2016-06-01

    Currently large uncertainties exist associated with the attribution and quantification of fugitive emissions of criteria pollutants and greenhouse gases such as methane across large regions and key economic sectors. In this study, data from the airborne Hyperspectral Thermal Emission Spectrometer (HyTES) have been used to develop robust and reliable techniques for the detection and wide-area mapping of emission plumes of methane and other atmospheric trace gas species over challenging and diverse environmental conditions with high spatial resolution that permits direct attribution to sources. HyTES is a pushbroom imaging spectrometer with high spectral resolution (256 bands from 7.5 to 12 µm), wide swath (1-2 km), and high spatial resolution (˜ 2 m at 1 km altitude) that incorporates new thermal infrared (TIR) remote sensing technologies. In this study we introduce a hybrid clutter matched filter (CMF) and plume dilation algorithm applied to HyTES observations to efficiently detect and characterize the spatial structures of individual plumes of CH4, H2S, NH3, NO2, and SO2 emitters. The sensitivity and field of regard of HyTES allows rapid and frequent airborne surveys of large areas including facilities not readily accessible from the surface. The HyTES CMF algorithm produces plume intensity images of methane and other gases from strong emission sources. The combination of high spatial resolution and multi-species imaging capability provides source attribution in complex environments. The CMF-based detection of strong emission sources over large areas is a fast and powerful tool needed to focus on more computationally intensive retrieval algorithms to quantify emissions with error estimates, and is useful for expediting mitigation efforts and addressing critical science questions.

  6. Design of an airborne Fourier transform visible hyperspectral imaging system for light aircraft environmental remote sensing

    NASA Astrophysics Data System (ADS)

    Otten, Leonard John, III; Butler, Eugene W.; Rafert, Bruce; Sellar, R. Glenn

    1995-06-01

    Kestrel Corporation and the Florida Institute of Technology have designed, and are now manufacturing, a Fourier transform visible hyperspectral imager system for use in a single engine light aircraft. The system is composed of a Sagnac-based interferometer optical subsystem, a data management system, and an aircraft attitude and current position sybsystem. The system is designed to have better than 5 nm spectral resolution at 450 nm, operates over the 440 nm to 1150 nm spectral band and has a 2D spatial resolution of 0.8 mrad. An internal calibration source is recorded with every frame of data to retain radiometric accuracy. The entire system fits into a Cessna 206 and uses a conventional downward looking view port located in the baggage compartment. During operation, data are collected at a rate of 15 Mbytes per second and stored direct to a disk array. Data storage has been sized to accommodate 56 minutes of observations. Designed for environmental mapping, this Fourier transform imager has uses in emergency response and military operations.

  7. Airborne hyperspectral imaging for the detection of powdery mildew in wheat

    NASA Astrophysics Data System (ADS)

    Franke, Jonas; Mewes, Thorsten; Menz, Gunter

    2008-08-01

    Plant stresses, in particular fungal diseases, show a high variability in spatial and temporal dimension with respect to their impact on the host. Recent "Precision Agriculture"-techniques allow for a spatially and temporally adjusted pest control that might reduce the amount of cost-intensive and ecologically harmful agrochemicals. Conventional stressdetection techniques such as random monitoring do not meet demands of such optimally placed management actions. The prerequisite is an accurate sensor-based detection of stress symptoms. The present study focuses on a remotely sensed detection of the fungal disease powdery mildew (Blumeria graminis) in wheat, Europe's main crop. In a field experiment, the potential of hyperspectral data for an early detection of stress symptoms was tested. A sophisticated endmember selection procedure was used and, additionally, a linear spectral mixture model was applied to a pixel spectrum with known characteristics, in order to derive an endmember representing 100% powdery mildew-infected wheat. Regression analyses of matched fraction estimates of this endmember and in-field-observed powdery mildew severities showed promising results (r=0.82 and r2=0.67).

  8. Detection of a buoyant coastal wastewater discharge using airborne hyperspectral and infrared imagery

    NASA Astrophysics Data System (ADS)

    Marmorino, George O.; Smith, Geoffrey B.; Miller, W. D.; Bowles, Jeffrey H.

    2010-01-01

    Municipal wastewater discharged into the ocean through a submerged pipe, or outfall, can rise buoyantly to the sea surface, resulting in a near-field mixing zone and, in the presence of an ambient ocean current, an extended surface plume. In this paper, data from a CASI (Compact Airborne Spectrographic Imager) and an airborne infrared (IR) camera are shown to detect a municipal wastewater discharge off the southeast coast of Florida, U.S.A., through its elevated levels of chromophoric dissolved organic matter plus detrital material (CDOM) and cooler sea surface temperatures. CDOM levels within a ~15-m-diameter surface 'boil' are found to be about twice those in the ambient shelf water, and surface temperatures near the boil are lower by ~0.4°C, comparable to the vertical temperature difference across the ambient water column. The CASI and IR imagery show a nearly identically shaped buoyant plume, consistent with a fully surfacing discharge, but the IR data more accurately delineate the area of most rapid dilution as compared with previous in-situ measurements. The imagery also allows identification of ambient oceanographic processes that affect dispersion and transport in the far field. This includes an alongshore front, which limits offshore dispersion of the discharge, and shoreward-propagating nonlinear internal waves, which may be responsible for an enhanced onshore transport of the discharge.

  9. Mapping tree health using airborne laser scans and hyperspectral imagery: a case study for a floodplain eucalypt forest

    NASA Astrophysics Data System (ADS)

    Shendryk, Iurii; Tulbure, Mirela; Broich, Mark; McGrath, Andrew; Alexandrov, Sergey; Keith, David

    2016-04-01

    Airborne laser scanning (ALS) and hyperspectral imaging (HSI) are two complementary remote sensing technologies that provide comprehensive structural and spectral characteristics of forests over large areas. In this study we developed two algorithms: one for individual tree delineation utilizing ALS and the other utilizing ALS and HSI to characterize health of delineated trees in a structurally complex floodplain eucalypt forest. We conducted experiments in the largest eucalypt, river red gum forest in the world, located in the south-east of Australia that experienced severe dieback over the past six decades. For detection of individual trees from ALS we developed a novel bottom-up approach based on Euclidean distance clustering to detect tree trunks and random walks segmentation to further delineate tree crowns. Overall, our algorithm was able to detect 67% of tree trunks with diameter larger than 13 cm. We assessed the accuracy of tree delineations in terms of crown height and width, with correct delineation of 68% of tree crowns. The increase in ALS point density from ~12 to ~24 points/m2 resulted in tree trunk detection and crown delineation increase of 11% and 13%, respectively. Trees with incorrectly delineated crowns were generally attributed to areas with high tree density along water courses. The accurate delineation of trees allowed us to classify the health of this forest using machine learning and field-measured tree crown dieback and transparency ratios, which were good predictors of tree health in this forest. ALS and HSI derived indices were used as predictor variables to train and test object-oriented random forest classifier. Returned pulse width, intensity and density related ALS indices were the most important predictors in the tree health classifications. At the forest level in terms of tree crown dieback, 77% of trees were classified as healthy, 14% as declining and 9% as dying or dead with 81% mapping accuracy. Similarly, in terms of tree

  10. Using airborne hyperspectral data to characterize the surface pH and mineralogy of pyrite mine tailings

    NASA Astrophysics Data System (ADS)

    Zabcic, N.; Rivard, B.; Ong, C.; Mueller, A.

    2014-10-01

    Acid mine drainage (AMD) is a key concern of the mining industry due to its impact on the quality of water and soils surrounding mine waste deposits. Acid mine drainage derives from the oxidation of metal sulphides, e.g. pyrite (FeS2), exposed to oxygen and water. The leachate acidity is capable of releasing heavy metals contained in the mining waste rock, which can affect water quality and lead to metal enrichment in sediments and potentially resulting in ecosystem degradation. Predicting tailings leachate pH is key to the management of sulfide-bearing mine wastes and is an emerging remote sensing application with limited studies having been realized. Such a capability would supplement traditional methods (i.e. ground surveys) that are challenging to implement due to the extent and large volume of mine waste. This study reports regional scale tailings mineral maps generated from airborne hyperspectral information of the Sotiel-Migollas complex in Spain and pinpoints sources of AMD. The extraction of spectral endmembers from imagery revealed twenty six endmembers for tailings material that represent mostly mineral mixtures. From these, eleven spectral groups were defined, each encompassing minor variations in mineral mixtures. The mineral maps resulting from the use of these endmembers for the detailed investigation of four tailings serve as indicators of the metal, sulphate, and pH levels of the AMD solution at the time of mineral precipitation. Predicted mineralogy was assessed using spectra from samples collected in the field and associated X-ray diffraction measurements. We also discuss the relative merits of the minerals maps of this study and soil leachate pH maps that we previously reported for the same locality using the same airborne data. The pH maps tend to provide predictions consistent with the mineralogy predicted from the mineral maps and the field and laboratory evidence. The pH maps offer information on the pH conditions of the tailings thus giving

  11. Airborne multispectral and hyperspectral remote sensing: Examples of applications to the study of environmental and engineering problems

    SciTech Connect

    Bianchi, R.; Marino, C.M.

    1997-10-01

    The availability of a new aerial survey capability carried out by the CNR/LARA (National Research Council - Airborne Laboratory for the Environmental Research) by a new spectroradiometer AA5000 MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) on board a CASA 212/200 aircraft, enable the scientists to obtain innovative data sets, for different approach to the definitions and the understanding of a variety of environmental and engineering problems. The 102 MIVIS channels spectral bandwidths are chosen to meet the needs of scientific research for advanced applications of remote sensing data. In such configuration MIVIS can offer significant contributions to problem solving in wide sectors such as geologic exploration, agricultural crop studies, forestry, land use mapping, idrogeology, oceanography and others. LARA in 1994-96 has been active over different test-sites in joint-venture with JPL, Pasadena, different European Institutions and Italian University and Research Institutes. These aerial surveys allow the national and international scientific community to approach the use of Hyperspectral Remote Sensing in environmental problems of very large interest. The sites surveyed in Italy, France and Germany include a variety of targets such as quarries, landfills, karst cavities areas, landslides, coastlines, geothermal areas, etc. The deployments gathered up to now more than 300 GBytes of MIVIS data in more than 30 hours of VLDS data recording. The purpose of this work is to present and to comment the procedures and the results at research and at operational level of the past campaigns with special reference to the study of environmental and engineering problems.

  12. Hyperspectral laboratory and airborne measurements as tools for local mapping of swelling soils in Orléans area (France)

    NASA Astrophysics Data System (ADS)

    Grandjean, Gilles; Dufrechou, Gregory; Hohmann, Audrey

    2013-04-01

    Swelling soils contain clay minerals that change volume with water content and cause extensive and expensive damage on infrastructures. Based on spatial distribution of infrastructure damages and existing geological maps, the Bureau de Recherches Géologiques et Minières (BRGM, the French Geological Survey) published in 2010 a 1:50 000 swelling hazard map of France. This map indexes the territory to low, intermediate, or high swell susceptibility, but does not display smallest and isolated clays lithologies. At local scale, identification of clay minerals and characterization of swell potential of soils using conventional soil analysis (DRX, chemical, and geotechnical analysis) are slow, expensive, and does not permit integrated measurements. Shortwave infrared (SWIR: 1100-2500 nm) spectral domains are characterized by significant spectral absorption bands that provide an underused tool for estimate the swell potential of soils. Reflectance spectroscopy, using an ASD Fieldspec Pro spectrometer, permits a rapid and less expensive measurement of soil reflectance spectra in the field and laboratory. In order to produce high precision map of expansive soils, the BRGM aims to optimize laboratory reflectance spectroscopy for mapping swelling soils. Geotechnical use of laboratory reflectance spectroscopy for local characterization of swell potential of soils could be assessable from an economical point of view. A new high resolution airborne hyperspectral survey (covering ca. 280 km², 380 channels ranging from 400 to 2500 nm) located at the W of Orléans (Loiret, France) will also be combined with field and laboratory measurements to detect and map swelling soils.

  13. 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...

  14. Hyperspectral Observations of Land Surfaces Using Ground-based, Airborne, and Satellite Sensors

    NASA Astrophysics Data System (ADS)

    Knuteson, R. O.; Best, F. A.; Revercomb, H. E.; Tobin, D. C.

    2006-12-01

    The University of Wisconsin-Madison Space Science and Engineering Center (UW-SSEC) has helped pioneer the use of high spectral resolution infrared spectrometers for application to atmospheric and surface remote sensing. This paper is focused on observations of land surface infrared emission from high spectral resolution measurements collected over the past 15 years using airborne, ground-based, and satellite platforms. The earliest data was collected by the High-resolution Interferometer Sounder (HIS), an instrument designed in the 1980s for operation on the NASA ER-2 high altitude aircraft. The HIS was replaced in the late 1990s by the Scanning-HIS instrument which has flown on the NASA ER-2, WB-57, DC-8, and Scaled Composites Proteus aircraft and continues to support field campaigns, such as those for EOS Terra, Aqua, and Aura validation. Since 1995 the UW-SSEC has fielded a ground-based Atmospheric Emitted Radiance Interferometer (AERI) in a research vehicle (the AERIBAGO) which has allowed for direct field measurements of land surface emission from a height of about 16 ft above the ground. Several ground-based and aircraft campaigns were conducted to survey the region surrounding the ARM Southern Great Plains site in north central Oklahoma. The ground- based AERIBAGO has also participated in surface emissivity campaigns in the Western U.S.. Since 2002, the NASA Atmospheric InfraRed Sounder (AIRS) has provided similar measurements from the Aqua platform in an afternoon sun-synchronous polar orbit. Ground-based and airborne observations are being used to validate the land surface products derived from the AIRS observations. These cal/val activities are in preparation for similar measurements anticipated from the operational Cross-track InfraRed Sounder (CrIS) on the NPOESS Preparatory Platform (NPP), expected to be launched in 2008. Moreover, high spectral infrared observations will soon be made by the Infrared Atmospheric Sounder Interferometer (IASI) on the

  15. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  17. First observations using SPICE hyperspectral dataset

    NASA Astrophysics Data System (ADS)

    Rosario, Dalton; Romano, Joao; Borel, Christoph

    2014-06-01

    Our first observations using the longwave infrared (LWIR) hyperspectral data subset of the Spectral and Polarimetric Imagery Collection Experiment (SPICE) database are summarized in this paper, focusing on the inherent challenges associated with using this sensing modality for the purpose of object pattern recognition. Emphases are also put on data quality, qualitative validation of expected atmospheric spectral features, and qualitative comparison against another dataset of the same site using a different LWIR hyperspectral sensor. SPICE is a collaborative effort between the Army Research Laboratory, U.S. Army Armament RDEC, and more recently the Air Force Institute of Technology. It focuses on the collection and exploitation of longwave and midwave infrared (LWIR and MWIR) hyperspectral and polarimetric imagery. We concluded from this work that the quality of SPICE hyperspectral LWIR data is categorically comparable to other datasets recorded by a different sensor of similar specs; and adequate for algorithm research, given the scope of SPICE. The scope was to conduct a long-term infrared data collection of the same site with targets, using both sensing modalities, under various weather and non-ideal conditions. Then use the vast dataset and associated ground truth information to assess performance of the state of the art algorithms, while determining performance degradation sources. The expectation is that results from these assessments will spur new algorithmic ideas with the potential to augment pattern recognition performance in remote sensing applications. Over time, we are confident the SPICE database will prove to be an asset to the wide open remote sensing community.

  18. Miniaturized Airborne Imaging Central Server System

    NASA Technical Reports Server (NTRS)

    Sun, Xiuhong

    2011-01-01

    In recent years, some remote-sensing applications require advanced airborne multi-sensor systems to provide high performance reflective and emissive spectral imaging measurement rapidly over large areas. The key or unique problem of characteristics is associated with a black box back-end system that operates a suite of cutting-edge imaging sensors to collect simultaneously the high throughput reflective and emissive spectral imaging data with precision georeference. This back-end system needs to be portable, easy-to-use, and reliable with advanced onboard processing. The innovation of the black box backend is a miniaturized airborne imaging central server system (MAICSS). MAICSS integrates a complex embedded system of systems with dedicated power and signal electronic circuits inside to serve a suite of configurable cutting-edge electro- optical (EO), long-wave infrared (LWIR), and medium-wave infrared (MWIR) cameras, a hyperspectral imaging scanner, and a GPS and inertial measurement unit (IMU) for atmospheric and surface remote sensing. Its compatible sensor packages include NASA s 1,024 1,024 pixel LWIR quantum well infrared photodetector (QWIP) imager; a 60.5 megapixel BuckEye EO camera; and a fast (e.g. 200+ scanlines/s) and wide swath-width (e.g., 1,920+ pixels) CCD/InGaAs imager-based visible/near infrared reflectance (VNIR) and shortwave infrared (SWIR) imaging spectrometer. MAICSS records continuous precision georeferenced and time-tagged multisensor throughputs to mass storage devices at a high aggregate rate, typically 60 MB/s for its LWIR/EO payload. MAICSS is a complete stand-alone imaging server instrument with an easy-to-use software package for either autonomous data collection or interactive airborne operation. Advanced multisensor data acquisition and onboard processing software features have been implemented for MAICSS. With the onboard processing for real time image development, correction, histogram-equalization, compression, georeference, and

  19. Commercial tree species discrimination using airborne AISA Eagle hyperspectral imagery and partial least squares discriminant analysis (PLS-DA) in KwaZulu-Natal, South Africa

    NASA Astrophysics Data System (ADS)

    Peerbhay, Kabir Yunus; Mutanga, Onisimo; Ismail, Riyad

    2013-05-01

    Discriminating commercial tree species using hyperspectral remote sensing techniques is critical in monitoring the spatial distributions and compositions of commercial forests. However, issues related to data dimensionality and multicollinearity limit the successful application of the technology. The aim of this study was to examine the utility of the partial least squares discriminant analysis (PLS-DA) technique in accurately classifying six exotic commercial forest species (Eucalyptus grandis, Eucalyptus nitens, Eucalyptus smithii, Pinus patula, Pinus elliotii and Acacia mearnsii) using airborne AISA Eagle hyperspectral imagery (393-900 nm). Additionally, the variable importance in the projection (VIP) method was used to identify subsets of bands that could successfully discriminate the forest species. Results indicated that the PLS-DA model that used all the AISA Eagle bands (n = 230) produced an overall accuracy of 80.61% and a kappa value of 0.77, with user's and producer's accuracies ranging from 50% to 100%. In comparison, incorporating the optimal subset of VIP selected wavebands (n = 78) in the PLS-DA model resulted in an improved overall accuracy of 88.78% and a kappa value of 0.87, with user's and producer's accuracies ranging from 70% to 100%. Bands located predominantly within the visible region of the electromagnetic spectrum (393-723 nm) showed the most capability in terms of discriminating between the six commercial forest species. Overall, the research has demonstrated the potential of using PLS-DA for reducing the dimensionality of hyperspectral datasets as well as determining the optimal subset of bands to produce the highest classification accuracies.

  20. Thermal remote sensing from Airborne Hyperspectral Scanner data in the framework of the SPARC and SEN2FLEX projects: an overview

    NASA Astrophysics Data System (ADS)

    Sobrino, J. A.; Jiménez-Muñoz, J. C.; Zarco-Tejada, P. J.; Sepulcre-Cantó, G.; de Miguel, E.; Sòria, G.; Romaguera, M.; Julien, Y.; Cuenca, J.; Hidalgo, V.; Franch, B.; Mattar, C.; Morales, L.; Gillespie, A.; Sabol, D.; Balick, L.; Su, Z.; Jia, L.; Gieske, A.; Timmermans, W.; Olioso, A.; Nerry, F.; Guanter, L.; Moreno, J.; Shen, Q.

    2009-06-01

    The AHS (Airborne Hyperspectral Scanner) instrument has 80 spectral bands covering the visible and near infrared (VNIR), short wave infrared (SWIR), mid infrared (MIR) and thermal infrared (TIR) spectral range. The instrument is operated by Instituto Nacional de Técnica Aerospacial (INTA), and it has been involved in several field campaigns since 2004. This paper presents an overview of the work performed with the AHS thermal imagery provided in the framework of the SPARC and SEN2FLEX campaigns, carried out respectively in 2004 and 2005 over an agricultural area in Spain. The data collected in both campaigns allowed for the first time the development and testing of algorithms for land surface temperature and emissivity retrieval as well as the estimation of evapotranspiration from AHS data. Errors were found to be around 1.5 K for land surface temperature and 1 mm/day for evapotranspiration.

  1. Thermal remote sensing from Airborne Hyperspectral Scanner data in the framework of the SPARC and SEN2FLEX projects: an overview

    NASA Astrophysics Data System (ADS)

    Sobrino, J. A.; Jiménez-Muñoz, J. C.; Zarco-Tejada, P. J.; Sepulcre-Cantó, G.; de Miguel, E.; Sòria, G.; Romaguera, M.; Julien, Y.; Cuenca, J.; Hidalgo, V.; Franch, B.; Mattar, C.; Morales, L.; Gillespie, A.; Sabol, D.; Balick, L.; Su, Z.; Jia, L.; Gieske, A.; Timmermans, W.; Olioso, A.; Nerry, F.; Guanter, L.; Moreno, J.; Shen, Q.

    2009-11-01

    The AHS (Airborne Hyperspectral Scanner) instrument has 80 spectral bands covering the visible and near infrared (VNIR), short wave infrared (SWIR), mid infrared (MIR) and thermal infrared (TIR) spectral range. The instrument is operated by Instituto Nacional de Técnica Aerospacial (INTA), and it has been involved in several field campaigns since 2004. This paper presents an overview of the work performed with the AHS thermal imagery provided in the framework of the SPARC and SEN2FLEX campaigns, carried out respectively in 2004 and 2005 over an agricultural area in Spain. The data collected in both campaigns allowed for the first time the development and testing of algorithms for land surface temperature and emissivity retrieval as well as the estimation of evapotranspiration from AHS data. Errors were found to be around 1.5 K for land surface temperature and 1 mm/day for evapotranspiration.

  2. Using TerraSAR-X and hyperspectral airborne data to monitor surface deformation and physical properties of the Barrow permafrost landscape, Alask

    NASA Astrophysics Data System (ADS)

    Haghshenas-Haghighi, M.; Motagh, M.; Heim, B.; Sachs, T.; Kohnert, K.; Streletskiy, D. A.

    2014-12-01

    In this study, we assess seasonal subsidence/heaving due to thawing/freezing of the permafrost in Barrow (71.3 N, 156.5 W) at the northernmost point of Alaska. The topographic relief in this area is low. Thick Permafrost underlies the entire area, with large ice volumes in its upper layer. With a large collection of field measurements during the past decades at the Barrow Environmental Observatory (BEO), it is an ideal site for permafrost investigation. There are long term systematic geocryological investigations within the Global Terrestrial Network (GTN-P) of the Circumpolar Active Layer Monitoring (CALM) programme. We use 28 TerraSAR-X images, acquired between December 2012 and December 2013 and analyze them using the Small BAseline Subset (SBAS) technique to extract time-series of ground surface deformation. We also analyze hyperspectral images acquired by the airborne AISA sensor over Barrow area, within the AIRMETH2013 programme, to assess physical characteristics such as vegetation biomass and density, surface moisture, and water bodies. Finally, we combine the information derived from both InSAR and hyperspectral analysis, with field measurements to investigate the link between physical characteristics of the permafrost and surface displacement.

  3. SIELETERS, an airborne infrared dual-band spectro-imaging system for measurement of scene spectral signatures.

    PubMed

    Coudrain, Christophe; Bernhardt, Sylvie; Caes, Marcel; Domel, Roland; Ferrec, Yann; Gouyon, Rémi; Henry, Didier; Jacquart, Marc; Kattnig, Alain; Perrault, Philippe; Poutier, Laurent; Rousset-Rouvière, Laurent; Tauvy, Michel; Thétas, Sophie; Primot, Jérôme

    2015-06-15

    More and more, hyperspectral images are envisaged to improve the aerial reconnaissance capability of airborne systems, both for civilian and military applications. To confirm the hopes put in this new way of imaging a scene, it is necessary to develop airborne systems allowing the measurement of the spectral signatures of objects of interest in real conditions, with high spectral and spatial resolutions. The purpose of this paper is to present the design and the first in-flight results of the dual-band infrared spectro-imaging system called Sieleters. This system has demonstrated simultaneously a ground sampling distance of 0.5m, associated with a spectral resolution of 11 cm(-1) for the Mid-Wave InfraRed (MWIR) and 5 cm(-1) for the Long-Wave InfraRed (LWIR). PMID:26193589

  4. Prediction of soil stability and erosion in semiarid regions using numerical hydrological model (MCAT) and airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Brook, Anna; Wittenberg, Lea

    2015-04-01

    promising models is the MCAT, which is a MATLAB library of visual and numerical analysis tools for the evaluation of hydrological and environmental models. The model applied in this paper presents an innovative infrastructural system for predicting soil stability and erosion impacts. This integrated model is applicable to mixed areas with spatially varying soil properties, landscape, and land-cover characteristics. Data from a semiarid site in southern Israel was used to evaluate the model and analyze fundamental erosion mechanisms. The findings estimate the sensitivity of the suggested model to the physical parameters and encourage the use of hyperspectral remote sensing imagery (HSI). The proposed model is integrated according to the following stages: 1. The soil texture, aggregation, soil moisture estimated via airborne HSI data, including soil surface clay and calcium carbonate erosions; 2. The mechanical stability of soil assessed via pedo-transfer function corresponding to load dependent changes in soil physical properties due to pre-compression stress (set of equations study shear strength parameters take into account soil texture, aggregation, soil moisture and ecological soil variables); 3. The precipitation-related runoff model program (RMP) satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation; 4. The Monte Carlo Analysis Toolbox (MCAT), a library of visual and numerical analysis tools for the evaluation of hydrological and environmental models, is proposed as a tool for integrate all the approaches to an applicable model. The presented model overcomes the limitations of existing modeling methods by integrating physical data produced via HSI and yet stays generic in terms of space and time independency.

  5. Evaluation of multi-scale hyperspectral reflectance and emittance image data for remote mineral mapping in northeastern Death Valley National Park, California and Oasis Valley, Nevada

    NASA Astrophysics Data System (ADS)

    Aslett, Zan

    This dissertation focuses upon the analyses of hyperspectral reflectance and thermal emission image data to remotely detect and map surficial mineralogy in an arid environment in southern Nevada and southeastern California. It includes four manuscripts prepared for submission to peer-reviewed journals, which are presented as single chapters. The research involves the use of longwave-infrared (LWIR) hyper- and multi-spectral measurements made from ground, aerial, and spaceborne perspectives of sedimentary and meta-sedimentary geologic units in northeastern Death Valley National Park, California and both shortwave-infrared (SWIR) and LWIR hyperspectral measurements in an area of diverse Paleozoic and Tertiary geology in Oasis Valley, Nevada. In Chapter 1, a brief overview of the dissertation is provided, including background on reflected and thermal-infrared mineral spectroscopy; remote sensing; the impacts of spatial and spectral resolution upon the ability to detect, identify, and map minerals using remote sensing image data; and the use of combined reflectance and emittance image data to better map minerals. In Chapter 2, ground-based SEBASS LWIR hyperspectral image data is analyzed in order to determine the utility of very high resolution remotely-sensed emittance measurements to delineate late-Proterozoic and Paleozoic sedimentary lithologies of an outcrop at Hell's Gate, Death Valley. In Chapter 3, airborne SEBASS image data over Boundary Canyon are analyzed in conjunction with moderate-scale geologic maps and laboratory measurements to map minerals associated with sedimentary and meta-sedimentary rocks and important in recognizing a detachment fault structure, as well as metamorphic facies. In Chapter 4, ground-based and aerial SEBASS, aerial MASTER, and spaceborne ASTER emittance measurements are compared over two study sites to determine what repercussions viewing perspective and spatial, spectral, and radiometric resolutions have upon remote identification

  6. Stokes vector analysis of LWIR polarimetric in adverse weather

    NASA Astrophysics Data System (ADS)

    Michalson, Jacob L.; Romano, Joao M.; Roth, Luz

    2011-10-01

    It is understood that Long Wave Infrared (LWIR) polarimetric imagery has the potential for detecting man-made objects in natural clutter backgrounds. Unlike Spectral and conventional broadband, polarimetric imagery takes advantage of the polarized signals emitted by the smooth surfaces of man-made materials. Studying the effect of how meteorological conditions affect polarization signals is imperative in order to understand where and how polarimetric technology can be beneficial to the war fighter. In this paper we intend to demonstrate the effects of weather on the performance of Stokes vector components, S0, S1, S2, and the Degree of Linear Polarization (DOLP) as detectors of man-made materials. Using the Hyperspectral Polarimetric Image Collection Experiment (SPICE) data collection, we analyze approximately one thousand images and correlate the performance of each of the detection metrics to individual meteorological measurements.

  7. 3D-FFT for Signature Detection in LWIR Images

    SciTech Connect

    Medvick, Patricia A.; Lind, Michael A.; Mackey, Patrick S.; Nuffer, Lisa L.; Foote, Harlan P.

    2007-11-20

    Improvements in analysis detection exploitation are possible by applying whitened matched filtering within the Fourier domain to hyperspectral data cubes. We describe an implementation of a Three Dimensional Fast Fourier Transform Whitened Matched Filter (3DFFTMF) approach and, using several example sets of Long Wave Infra Red (LWIR) data cubes, compare the results with those from standard Whitened Matched Filter (WMF) techniques. Since the variability in shape of gaseous plumes precludes the use of spatial conformation in the matched filtering, the 3DFFTMF results were similar to those of two other WMF methods. Including a spatial low-pass filter within the Fourier space can improve signal to noise ratios and therefore improve detection limit by facilitating the mitigation of high frequency clutter. The improvement only occurs if the low-pass filter diameter is smaller than the plume diameter.

  8. Staring MWIR, LWIR and 2-color and scanning LWIR polarimetry technology

    NASA Astrophysics Data System (ADS)

    Malone, Neil R.; Kennedy, Adam; Graham, Roger; Thai, Yen; Stark, Justin; Sienicki, Joe; Fest, Eric

    2011-09-01

    Polarimetry sensor development has been in work for some time to determine the best use of polarimetry to differentiate between manmade objects and objects made by nature. Both MWIR and LWIR and 2-color staring Focal Plane Arrays (FPAs) and LWIR scanning FPAs have been built at Raytheon Vision Systems each with exceedingly higher performance. This paper presents polarimetric performance comparisons between staring 2562 MWIR, 2562 LWIR, 5122 LWIR/LWIR staring FPAs and scanning LWIR FPAs. LWIR polarimetry has the largest polarimetric signal level and a larger emissive polarimetric signature than MWIR which makes LWIR less dependent on sun angles. Polished angled glass and metal objects are easily detected using LWIR polarimetry. While single band 9-11 um LWIR polarimetry has advantages adding another band between 3 and 7 um improves the capability of the sensor for polarization and spectral phenomenology. In addition the 3-7 um band has improved NEDT over the 9-11 um band due to the shorter detector cutoff reducing the Noise Equivalent Degree of Linear Polarization. (NEDOLP). To gain acceptance polarimetric sensors must provide intelligence signatures that are better than existing nonpolarimetric Infrared sensors. This paper shows analysis indicating the importance of NEDOLP and Extinction ratios.

  9. From HYSOMA to ENSOMAP - A new open source tool for quantitative soil properties mapping based on hyperspectral imagery from airborne to spaceborne applications

    NASA Astrophysics Data System (ADS)

    Chabrillat, Sabine; Guillaso, Stephane; Rabe, Andreas; Foerster, Saskia; Guanter, Luis

    2016-04-01

    Soil spectroscopy from the visible-near infrared to the short wave infrared has been shown to be a proven method for the quantitative prediction of key soil surface properties in the laboratory, field, and up to airborne studies for exposed soils in appropriate surface conditions. With the upcoming launch of the next generation of spaceborne hyperspectral sensors within the next 3 to 5 years (EnMAP, HISUI, PRISMA, SHALOM), a great potential for the global mapping and monitoring of soil properties is appearing. This potential can be achieved only if adequate software tools are available, as shown by the increasing demand for the availability/accessibility of hyperspectral soil products from the geoscience community that have neither the capacity nor the expertise to deliver these soil products. In this context, recently many international efforts were tuned toward the development of robust and easy-to-access soil algorithms to allow non-remote sensing experts to obtain geoscience information based on non-expensive software packages where repeatability of the results is an important prerequisite. In particular, several algorithms for geological and mineral mapping were recently released such as the U.S. Geological Survey Processing Routines in IDL for Spectroscopic Measurements (PRISM) software, or the GFZ EnMAP Geological Mapper. For quantitative soil mapping and monitoring, the HYSOMA (Hyperspectral Soil Mapper) software interface was developed at GFZ under the EUFAR (www.eufar.net) and the EnMAP (www.enmap.org) programs. HYSOMA was specifically oriented toward digital soil mapping applications and has been distributed since 2012 for free as IDL plug-ins under the IDL-virtual machine at www.gfz-potsdam.de/hysoma under a close source license. The HYSOMA interface focuses on fully automatic generation of semi-quantitative soil maps such as soil moisture, soil organic matter, iron oxide, clay content, and carbonate content. With more than 100 users around the world

  10. Mapping grassland leaf area index with airborne hyperspectral imagery: A comparison study of statistical approaches and inversion of radiative transfer models

    NASA Astrophysics Data System (ADS)

    Darvishzadeh, Roshanak; Atzberger, Clement; Skidmore, Andrew; Schlerf, Martin

    2011-11-01

    Statistical and physical models have seldom been compared in studying grasslands. In this paper, both modeling approaches are investigated for mapping leaf area index (LAI) in a Mediterranean grassland (Majella National Park, Italy) using HyMap airborne hyperspectral images. We compared inversion of the PROSAIL radiative transfer model with narrow band vegetation indices (NDVI-like and SAVI2-like) and partial least squares regression (PLS). To assess the performance of the investigated models, the normalized RMSE (nRMSE) and R2 between in situ measurements of leaf area index and estimated parameter values are reported. The results of the study demonstrate that LAI can be estimated through PROSAIL inversion with accuracies comparable to those of statistical approaches ( R2 = 0.89, nRMSE = 0.22). The accuracy of the radiative transfer model inversion was further increased by using only a spectral subset of the data ( R2 = 0.91, nRMSE = 0.18). For the feature selection wavebands not well simulated by PROSAIL were sequentially discarded until all bands fulfilled the imposed accuracy requirements.

  11. Use of spectral vegetation indices derived from airborne hyperspectral imagery for detection of European corn borer infestation in Iowa corn plots.

    PubMed

    Carroll, Matthew W; Glaser, John A; Hellmich, Richard L; Hunt, Thomas E; Sappington, Thomas W; Calvin, Dennis; Copenhaver, Ken; Fridgen, John

    2008-10-01

    Eleven spectral vegetation indices that emphasize foliar plant pigments were calculated using airborne hyperspectral imagery and evaluated in 2004 and 2005 for their ability to detect experimental plots of corn manually inoculated with Ostrinia nubilalis (Hübner) neonate larvae. Manual inoculations were timed to simulate infestation of corn, Zea mays L., by first and second flights of adult O. nubilalis. The ability of spectral vegetation indices to detect O. nubilalis-inoculated plots improved as the growing season progressed, with multiple spectral vegetation indices able to identify infested plots in late August and early September. Our findings also indicate that for detecting O. nubilalis-related plant stress in corn, spectral vegetation indices targeting carotenoid and anthocyanin pigments are not as effective as those targeting chlorophyll. Analysis of image data suggests that feeding and stem boring by O. nubilalis larvae may increase the rate of plant senescence causing detectable differences in plant biomass and vigor when compared with control plots. Further, we identified an approximate time frame of 5-6 wk postinoculation, when spectral differences of manually inoculated "second" generation O. nubilalis plots seem to peak. PMID:18950044

  12. New heterojunction LWIR detector options

    NASA Technical Reports Server (NTRS)

    Maserjian, Joseph

    1990-01-01

    Researchers investigate the heterojunction internal photoemission (HIP) approach that potentially offers long wavelength infrared (LWIR) photovoltaic detector performance (single pixel) that is competitive with the best of other approaches being considered. Most significantly, this approach offers a relatively simple device technology that promises producible and uniform FPA's. Researchers emphasize an exciting process based on intervalence band absorption. They investigate both III-V and Si-based heterojunctions grown by molecular beam epitaxy (MBE) in which the barrier can be tailored to the desired cutoff wavelength. In addition, MBE allows one to optimize the device structure with precise control of doping profiles and layer thicknesses, and perform band structure engineering by control of composition and heterojunction strain. Researchers also consider free carrier absorption in heterojunctions. Acceptable absorption coefficients can be achieved in very heavily n(exp +) doped semiconductor layers (approx. equals 10(exp 20)cm(exp -3). However, in this case the appreciable filling of conduction band states leads to a Schottky-like photoresponse with a gradual (quadratic) turn-on above threshold. A more satisfactory approach would be to use p(exp +) doping so that with the higher density of states in the heavy hole valence band there would be a narrow band of occupied states. This gives the desirable effect of a more rapid (linear) turn-on above threshold. Unfortunately, the higher hole effective mass also reduces (inversely) the free carrier absorption. For this and other reasons, the intervalence band absorption process looks much more promising.

  13. Dead pixel replacement in LWIR microgrid polarimeters.

    PubMed

    Ratliff, Bradley M; Tyo, J Scott; Boger, James K; Black, Wiley T; Bowers, David L; Fetrow, Matthew P

    2007-06-11

    LWIR imaging arrays are often affected by nonresponsive pixels, or "dead pixels." These dead pixels can severely degrade the quality of imagery and often have to be replaced before subsequent image processing and display of the imagery data. For LWIR arrays that are integrated with arrays of micropolarizers, the problem of dead pixels is amplified. Conventional dead pixel replacement (DPR) strategies cannot be employed since neighboring pixels are of different polarizations. In this paper we present two DPR schemes. The first is a modified nearest-neighbor replacement method. The second is a method based on redundancy in the polarization measurements.We find that the redundancy-based DPR scheme provides an order-of-magnitude better performance for typical LWIR polarimetric data. PMID:19547086

  14. Dead pixel replacement in LWIR microgrid polarimeters

    NASA Astrophysics Data System (ADS)

    Ratliff, Bradley M.; Tyo, J. Scott; Boger, James K.; Black, Wiley T.; Bowers, David L.; Fetrow, Matthew P.

    2007-06-01

    LWIR imaging arrays are often affected by nonresponsive pixels, or “dead pixels.” These dead pixels can severely degrade the quality of imagery and often have to be replaced before subsequent image processing and display of the imagery data. For LWIR arrays that are integrated with arrays of micropolarizers, the problem of dead pixels is amplified. Conventional dead pixel replacement (DPR) strategies cannot be employed since neighboring pixels are of different polarizations. In this paper we present two DPR schemes. The first is a modified nearest-neighbor replacement method. The second is a method based on redundancy in the polarization measurements.We find that the redundancy-based DPR scheme provides an order-of-magnitude better performance for typical LWIR polarimetric data.

  15. Gas plume quantification in downlooking hyperspectral longwave infrared images

    NASA Astrophysics Data System (ADS)

    Turcotte, Caroline S.; Davenport, Michael R.

    2010-10-01

    Algorithms have been developed to support quantitative analysis of a gas plume using down-looking airborne hyperspectral long-wave infrared (LWIR) imagery. The resulting gas quantification "GQ" tool estimates the quantity of one or more gases at each pixel, and estimates uncertainty based on factors such as atmospheric transmittance, background clutter, and plume temperature contrast. GQ uses gas-insensitive segmentation algorithms to classify the background very precisely so that it can infer gas quantities from the differences between plume-bearing pixels and similar non-plume pixels. It also includes MODTRAN-based algorithms to iteratively assess various profiles of air temperature, water vapour, and ozone, and select the one that implies smooth emissivity curves for the (unknown) materials on the ground. GQ then uses a generalized least-squares (GLS) algorithm to simultaneously estimate the most likely mixture of background (terrain) material and foreground plume gases. Cross-linking of plume temperature to the estimated gas quantity is very non-linear, so the GLS solution was iteratively assessed over a range of plume temperatures to find the best fit to the observed spectrum. Quantification errors due to local variations in the camera-topixel distance were suppressed using a subspace projection operator. Lacking detailed depth-maps for real plumes, the GQ algorithm was tested on synthetic scenes generated by the Digital Imaging and Remote Sensing Image Generation (DIRSIG) software. Initial results showed pixel-by-pixel gas quantification errors of less than 15% for a Freon 134a plume.

  16. Regional prediction of soil organic carbon content over temperate croplands using visible near-infrared airborne hyperspectral imagery and synchronous field spectra

    NASA Astrophysics Data System (ADS)

    Vaudour, E.; Gilliot, J. M.; Bel, L.; Lefevre, J.; Chehdi, K.

    2016-07-01

    This study aimed at identifying the potential of Vis-NIR airborne hyperspectral AISA-Eagle data for predicting the topsoil organic carbon (SOC) content of bare cultivated soils over a large peri-urban area (221 km2) with both contrasted soils and SOC contents, located in the western region of Paris, France. Soil types comprised haplic luvisols, calcaric cambisols and colluvic cambisols. Airborne AISA-Eagle data (400-1000 nm, 126 bands) with 1 m-resolution were acquired on 17 April 2013 over 13 tracks. Tracks were atmospherically corrected then mosaicked at a 2 m-resolution using a set of 24 synchronous field spectra of bare soils, black and white targets and impervious surfaces. The land use identification system layer (RPG) of 2012 was used to mask non-agricultural areas, then calculation and thresholding of NDVI from an atmospherically corrected SPOT image acquired the same day enabled to map agricultural fields with bare soil. A total of 101 sites sampled either in 2013 or in the 3 previous years and in 2015 were identified as bare by means of this map. Predictions were made from the mosaic AISA spectra which were related to topsoil SOC contents by means of partial least squares regression (PLSR). Regression robustness was evaluated through a series of 1000 bootstrap data sets of calibration-validation samples, considering 74 sites outside cloud shadows only, and different sampling strategies for selecting calibration samples. Validation root-mean-square errors (RMSE) were comprised between 3.73 and 4.49 g Kg-1 and were ∼4 g Kg-1 in median. The most performing models in terms of coefficient of determination (R2) and Residual Prediction Deviation (RPD) values were the calibration models derived either from Kennard-Stone or conditioned Latin Hypercube sampling on smoothed spectra. The most generalizable model leading to lowest RMSE value of 3.73 g Kg-1 at the regional scale and 1.44 g Kg-1 at the within-field scale and low bias was the cross-validated leave

  17. Regional-scale mineral mapping using ASTER VNIR/SWIR data and validation of reflectance and mineral map products using airborne hyperspectral CASI/SASI data

    NASA Astrophysics Data System (ADS)

    Jing, Cui; Bokun, Yan; Runsheng, Wang; Feng, Tian; Yingjun, Zhao; Dechang, Liu; Suming, Yang; Wei, Shen

    2014-12-01

    ASTER data have been widely and successfully used in lithological mapping and mineral exploration for decades. The errors due to atmospheric water vapor and the characteristics of the photoelectric sensor could lead to the anomalous characteristics of band 5 and 9 in the ASTER standard reflectivity product. These anomalies could result in the spectroscopic misidentification of minerals. This study proposed a simple method of atmospheric correction for converting radiance-at-sensor to ground reflectance. The ASTER VNIR/SWIR reflectance correction factor was derived to correct the spectral shape bias resulting from the radiometric calibration error using airborne hyperspectral CASI_SASI data. The ASTER VNIR/SWIR reflectance correction factor was derived to correct the spectral shape bias resulting from the radiometric calibration error. After applying the reflectance factor to the atmospheric-corrected ASTER L1B data, a band combination mapping method was proposed for identifying minerals more quickly and accurately. The results indicate that this method for atmospheric correction of ASTER data produces very good results in the arid and bare areas. It is still unknown whether the method is suitable for humid and rainy areas where atmospheric water vapor varies spatially more than in arid and bare areas. After applying the reflectance factor to the atmospheric-corrected ASTER L1B data, the mean error of all reflectance bands decreased from 0.0256 to 0.002, and the standard deviation decreased from 0.04251 to 0.0007. The errors of the 2/1, 5/6 and 9/8 band ratios decreased from 2.38%, 4.102%, and 4.28% to 1.26%, -0.162%, and 0.31%, respectively. The radiometric calibration error of the ASTER band 1-9 data can lead to the overestimation of kaolinite. A band index of 2/1 for retrieving Fe3+ cannot produce a reliable Fe3+ distribution map, and a new index should be developed.

  18. Uncooled LWIR imaging: applications and market analysis

    NASA Astrophysics Data System (ADS)

    Takasawa, Satomi

    2015-05-01

    The evolution of infrared (IR) imaging sensor technology for defense market has played an important role in developing commercial market, as dual use of the technology has expanded. In particular, technologies of both reduction in pixel pitch and vacuum package have drastically evolved in the area of uncooled Long-Wave IR (LWIR; 8-14 μm wavelength region) imaging sensor, increasing opportunity to create new applications. From the macroscopic point of view, the uncooled LWIR imaging market is divided into two areas. One is a high-end market where uncooled LWIR imaging sensor with sensitivity as close to that of cooled one as possible is required, while the other is a low-end market which is promoted by miniaturization and reduction in price. Especially, in the latter case, approaches towards consumer market have recently appeared, such as applications of uncooled LWIR imaging sensors to night visions for automobiles and smart phones. The appearance of such a kind of commodity surely changes existing business models. Further technological innovation is necessary for creating consumer market, and there will be a room for other companies treating components and materials such as lens materials and getter materials and so on to enter into the consumer market.

  19. On the retrieval of water-related canopy biochemistry from airborne hyperspectral data and its comparison to MODIS spectral response

    NASA Astrophysics Data System (ADS)

    Casas Planes; Riaño, D.; Ustin, S.; Dennison, P. E.; Salas, J.

    2013-12-01

    Quantification of states and rates of water content in vegetation is critical in plant ecology. This work aims to assess the performance of a wide range of methodologies for the retrieval of vegetation biochemical and biophysical properties related to water, including: (i) foliar water content (FWC, cm), (ii) canopy water content (CWC, cm), (iii) fuel moisture content (FMC) and several interrelated variables: (iv) leaf mass per area (LMA, g/cm2), (v) foliar biomass (FB, g/m2), and (vi) leaf area index (LAI, m2/m2). Methods are applied to Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data collected over Stanford University's Jasper Ridge Biological Preserve, California, USA, and derived Moderate Resolution Imaging Spectrometer (MODIS)-like data, within a multitemporal frame and stratified by cover type (i.e. grassland, shrubland and forest). Assessed methods are: (i) spectral fitting techniques applied to AVIRIS data, ii) the use of standard and recently designed indices, iii) AVIRIS PROSAIL and MODIS CWC PROSAIL inversion; and iv) the estimation of best band combination indices calibrated with the experimental dataset. This work shows how CWC retrieved from spectral fitting techniques proved relatively inaccurate. RTM simulations were significantly improved with the incorporation of a soil spectrum particularly in the case of grasslands and only for LAI in forests. Spectral indices provided higher accuracy; however, the most accurate index differed by variable and by cover types. Empirical calibration of indices improved the retrievals significantly in the case of FMC, LMA and FB using bands in the longer wavelength SWIR region.

  20. Unsupervised hyperspectral image classification

    NASA Astrophysics Data System (ADS)

    Jiao, Xiaoli; Chang, Chein-I.

    2007-09-01

    Two major issues encountered in unsupervised hyperspectral image classification are (1) how to determine the number of spectral classes in the image and (2) how to find training samples that well represent each of spectral classes without prior knowledge. A recently developed concept, Virtual dimensionality (VD) is used to estimate the number of spectral classes of interest in the image data. This paper proposes an effective algorithm to generate an appropriate training set via a recently developed Prioritized Independent Component Analysis (PICA). Two sets of hyperspectral data, Airborne Visible Infrared Imaging Spectrometer (AVIRIS) Cuprite data and HYperspectral Digital Image Collection Experiment (HYDICE) data are used for experiments and performance analysis for the proposed method.

  1. Longwave infrared (LWIR) coded aperture dispersive spectrometer.

    PubMed

    Fernandez, C; Guenther, B D; Gehm, M E; Brady, D J; Sullivan, M E

    2007-04-30

    We describe a static aperture-coded, dispersive longwave infrared (LWIR) spectrometer that uses a microbolometer array at the detector plane. The two-dimensional aperture code is based on a row-doubled Hadamard mask with transmissive and opaque openings. The independent column code nature of the matrix makes for a mathematically well-defined pattern that spatially and spectrally maps the source information to the detector plane. Post-processing techniques on the data provide spectral estimates of the source. Comparative experimental results between a slit and coded aperture for emission spectroscopy from a CO(2) laser are demonstrated. PMID:19532832

  2. Discriminative imaging using a LWIR polarimeter

    NASA Astrophysics Data System (ADS)

    Connor, Barry; Carrie, Iain; Craig, Robert; Parsons, John

    2008-10-01

    The phenomenon of polarisation causes smooth man-made objects, such as metal and glass, to have a different polarisation signature to that of natural vegetation. Therefore, polarisation has the potential to discriminate man-made objects from background clutter. Polarimetric information, combined with conventional thermal imaging, provides a powerful means of reducing false alarms in applications such as situational awareness, detection of low signature targets and disturbed earth. The paper presents results of discriminative imaging algorithms that were designed to augment polarimetric signatures. Recent results from a LWIR polarimetric imager are presented and these show the merit of discriminative imaging techniques when applied to polarimetric thermal imagers.

  3. Hole-Impeded-Doping-Superlattice LWIR Detectors

    NASA Technical Reports Server (NTRS)

    Maserjian, Joseph

    1991-01-01

    Hole-Impeded-Doping-Superlattice (HIDS) InAs devices proposed for use as photoconductive or photovoltaic detectors of radiation in long-wavelength infrared (LWIR) range of 8 to 17 micrometers. Array of HIDS devices fabricated on substrates GaAs or Si. Radiation incident on black surface, metal contacts for picture elements serve as reactors, effectively doubling optical path and thereby increasing absorption of photons. Photoconductive detector offers advantages of high gain and high impedance; photovoltaic detector offers lower noise and better interface to multiplexer readouts.

  4. SPECTRAL PROPERTIES OF TREE CHOLLA AND YUCCA MEASURED BY AN AIRBORNE HYPERSPECTRAL SENSOR AND THE RESULTING MAXIMUM LIKELIHOOD CLASSIFICATION OF RANGELANDS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral remote sensing is an emerging technology with the potential to identify plant species, delineate vegetation and habitat characteristics, differentiate causes of vegetation stress, and characterize soil properties. This technology can be used in range management as a tool to map variou...

  5. A method for quantification of gas plumes in thermal hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Messinger, David W.

    2005-06-01

    Several commercial and environmental applications require the detection and quantification of gaseous plumes from airborne platforms. Unlike active LIDAR imaging in a DIAL system, the signal received by a passive sensor depends not only on the gas concentration pathlength, but the temperature contrast between the gas column and the background as well. Further complicating the problem, the at-sensor radiance is a function of a non-linear combination of the gas concentration and temperature, both inherently unknown. A method is presented to estimate the gas concentration pathlength and temperature from LWIR Hyperspectral Imagery (HSI) without any assumptions about the gas properties or background radiance. A non-linear model is fit to the data using a Levenberg-Marquardt fitting procedure. This technique requires only a priori knowledge of the gas species present in the pixel of interest to reduce the complexity of the model. The resulting concentration pathlength and temperature are reported on a per-pixel basis. Results are shown for application to synthetic imagery created with the DIRSIG simulation. Concentration pathlength results are promising for a gas with strong, moderately broad features (Freon) but less so for a gas with weaker, narrow features (NH3). In neither case is the solution to the gas temperature satisfactory. This is further demonstrated through examination of the residual space in which the minimization is performed where it is shown that a unique minimum is not present in the space.

  6. Simulation of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

  7. Detection comparisons between LWIR and MWIR polarimetric sensors

    NASA Astrophysics Data System (ADS)

    Malone, Neil R.; Hampp, Andreas; Gordon, Eli E.; Liguori, Michael V.; Thai, Yen; Vodicka, Jim; Bangs, James W.

    2008-04-01

    Polarimetry sensor development has been in work for some time to determine the best use of polarimetry to differentiate between manmade objects and objects made by nature. Both MWIR and LWIR Focal Plane Arrays (FPAs) have been built at Raytheon Vision Systems each with exceedingly higher extinction ratios. This paper compares field imagery between MWIR and LWIR micro-grid polarimetric sensors independently and during simultaneous image collects. LWIR polarimetry has the largest polarimetric signal level and an emissive polarimetric signature which allows detection at thermal crossover and is less dependent on sun angles. Polished angled glass and metal objects are easily detected using LWIR polarimetry. While LWIR polarimetry has many advantages its resolution is not as good as MWIR. MWIR polarimetry has higher resolution than LWIR. With good sun angles plastic drums, and wet surfaces provide good polarization signatures. With poor sun angles detection can be challenging. To gain acceptance polarimetric sensors must provide intelligence signatures that are better than existing nonpolarimetric Infrared sensors. This paper shows several examples of images without polarimetric processing and identical images with MWIR and/or LWIR polarimetric fusion onto the non-polarized images to show the improvement of detection using polarimetric sensors. It is the author's belief that the fastest way to gain acceptance of polarimetric remote sensing is through field demonstration as shown in Figure 1.

  8. 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

  9. LWIR thermal imaging through dust obscuration

    NASA Astrophysics Data System (ADS)

    Smith, Forrest A.; Jacobs, Eddie L.; Chari, Srikant; Brooks, Jason

    2011-05-01

    The physical model for long wave infrared (LWIR) thermal imaging through a dust obscurant incorporates transmission loss as well as an additive path radiance term, both of which are dependent on an obscurant density along the imaging path. When the obscurant density varies in time and space, the desired signal is degraded by two anti-correlated atmospheric noise components-the transmission (multiplicative) and the path radiance (additive)-which are not accounted for by a single transmission parameter. This research introduces an approach to modeling the performance impact of dust obscurant variations. Effective noise terms are derived for obscurant variations detected by a sensor via a forward radiometric analysis of the imaging context. The noise parameters derived here provide a straightforward approach to predicting imager performance with existing NVESD models such as NVThermIP.

  10. 2-Cam LWIR imaging Stokes polarimeter

    NASA Astrophysics Data System (ADS)

    Kudenov, Michael W.; Dereniak, Eustace L.; Pezzaniti, Larry; Gerhart, Grant R.

    2008-04-01

    A 2-Cam micro-bolometer imaging polarimeter operating in the LWIR is presented. The system is capable of snapshot imaging Stokes polarimetry in any one channel (S I, S II, or S 3) by taking two simultaneous measurements of a scene. For measurements of S I or S II, the instrument relies on a specially optimized wire-grid beam-splitter. For measurements of S 3, a form birefringent quarter-wave retarder is inserted into the optical path. Specifics associated with the design of the wire-grid beam-splitter and the form birefringent quarter-wave retarder will be overviewed, with inclusion of RCWA simulations. Calibration and simulation procedures, as well as calibration targets, will be highlighted, and initial data from the instrument are presented.

  11. Status of LWIR HgCdTe infrared detector technology

    NASA Technical Reports Server (NTRS)

    Reine, M. B.

    1990-01-01

    The performance requirements that today's advanced Long Wavelength Infrared (LWIR) focal plane arrays place on the HgCdTe photovoltaic detector array are summarized. The theoretical performance limits for intrinsic LWIR HgCdTe detectors are reviewed as functions of cutoff wavelength and operating temperature. The status of LWIR HgCdTe photovoltaic detectors is reviewed and compared to the focal plane array (FPA) requirements and to the theoretical limits. Emphasis is placed on recent data for two-layer HgCdTe PLE heterojunction photodiodes grown at Loral with cutoff wavelengths ranging between 10 and 19 microns at temperatures of 70 to 80 K. Development trends in LWIR HgCdTe detector technology are outlined, and conclusions are drawn about the ability for photovoltaic HgCdTe detector arrays to satisfy a wide variety of advanced FPA array applications.

  12. PRELIMINARY INVESTIGATION OF SUBMERGED AQUATIC VEGETATION MAPPING USING HYPERSPECTRAL REMOTE SENSING

    EPA Science Inventory

    The use of airborne hyperspectral remote sensing imagery for automated mapping of submersed aquatic vegetation in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery, together with in-situ spectral refl...

  13. Long-wavelength infrared hyperspectral data "mining" at Cuprite, NV

    NASA Astrophysics Data System (ADS)

    Sundberg, Robert; Adler-Golden, Steven; Conforti, Patrick

    2015-09-01

    In recent years long-wavelength infrared (LWIR) hyperspectral imagery has significantly improved in quality and become much more widely available, sparking interest in a variety of applications involving remote sensing of surface composition. This in turn has motivated the development and study of LWIR-focused algorithms for atmospheric retrieval, temperature-emissivity separation (TES) and material detection and identification. In this paper we evaluate some LWIR algorithms for atmospheric retrieval, TES, endmember-finding and rare material detection for their utility in characterizing mineral composition in SEBASS hyperspectral imagery taken near Cuprite, NV. Atmospheric correction results using the In-Scene Atmospheric Correction (ISAC) method are compared with those from the first-principles, MODTRAN©-based FLAASH-IR method. Covariance-whitened endmember-finding methods are observed to be sensitive to image artifacts. However, with clean data and all-natural terrain they can automatically locate and distinguish many minor mineral components, with especially high sensitivity to varieties of calcite. Not surprisingly, the major scene materials, including silicates, are best located using unwhitened techniques. Minerals that we identified in the data include calcite, quartz, alunite and (tentatively) kaolinite.

  14. Fiber optic snapshot hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Mansur, David J.; Rentz Dupuis, Julia; Vaillancourt, Robert

    2012-06-01

    OPTRA is developing a snapshot hyperspectral imager (HSI) employing a fiber optic bundle and dispersive spectrometer. The fiber optic bundle converts a broadband spatial image to an array of fiber columns which serve as multiple entrance slits to a prism spectrometer. The dispersed spatially resolved spectra are then sampled by a two-dimensional focal plane array (FPA) at a greater than 30 Hz update rate, thereby qualifying the system as snapshot. Unlike snapshot HSI systems based on computed tomography or coded apertures, our approach requires only the remapping of the FPA frame into hyperspectral cubes rather than a complex reconstruction. Our system has high radiometric efficiency and throughput supporting sufficient signal to noise for hyperspectral imaging measurements made over very short integration times (< 33 ms). The overall approach is compact, low cost, and contains no moving parts, making it ideal for unmanned airborne surveillance. In this paper we present a preliminary design for the fiber optic snapshot HSI system.

  15. Exploration of integrated visible to near-, shortwave-, and longwave-infrared (full range) hyperspectral data analysis

    NASA Astrophysics Data System (ADS)

    Cone, Shelli R.; Kruse, Fred A.; McDowell, Meryl L.

    2015-05-01

    Visible to near-, shortwave-, and longwave-infrared (VNIR, SWIR, LWIR) hyperspectral data were integrated using a variety of approaches to take advantage of complementary wavelength-specific spectral characteristics for improved material classification. The first approach applied separate minimum noise fraction (MNF) transforms to the three regions and combined only non-noise transformed bands. A second approach integrated the VNIR, SWIR, and LWIR data before using MNF analysis to isolate linear band combinations containing high signal to noise. Spectral endmembers extracted from each integrated dataset were unmixed and spatially mapped using a partial unmixing approach. Integrated results were compared to baseline analyses of the separate spectral regions. Outcomes show that analyzing across the full VNIR-SWIR-LWIR spectrum improves material characterization and identification.

  16. 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.

  17. Recent trial results of an LWIR polarimeter

    NASA Astrophysics Data System (ADS)

    Connor, Barry; Carrie, Iain

    2009-05-01

    The aim of this paper is to describe the results of various trials involving a high-resolution thermal imager that has been designed to be sensitive to polarised radiation. Polarisation has the potential to discriminate man-made objects and disturbed earth from background clutter. Polarisation combined with conventional thermal imaging within the one camera offers the potential to significantly reduce false alarms in surveillance and detection applications. The camera used during the trials is a technology demonstrator developed by Thales Optronics, UK. The camera operates in the longwave infra red and has a QWIP polarisation-sensitive detector. The results presented in this paper include recent trials in the UK and USA. The aim of the trials was to assess the utility in using a LWIR polarimeter for detection of difficult objects from background clutter. Thermal and polarised images were captured and processed in order to detect anomalies. Several polarisation-based discriminative imaging techniques are applied to trials imagery. The effect of the diurnal cycle on the effectiveness of polarisation for object discrimination will be assessed.

  18. Spectral optimization studies and schemes to enhance target detection and display for a three-band staring LWIR sensor

    NASA Astrophysics Data System (ADS)

    Mayer, Rulon R.; Waterman, James; Schuler, Jonathon; Scribner, Dean

    2003-12-01

    To achieve enhanced target discrimination, prototype three- band long wave infrared (LWIR) focal plane arrays (FPA) for missile defense applications have recently been constructed. The cutoff wavelengths, widths, and spectral overlap of the bands are critical parameters for the multicolor sensor design. Previous calculations for sensor design did not account for target and clutter spectral features in determining the optimal band characteristics. The considerable spectral overlap and correlation between the bands and attendant reduction in color contrast is another unexamined issue. To optimize and simulate the projected behavior of three-band sensors, this report examined a hyperspectral LWIR image cube. Our study starts with 30 bands of the LWIR spectra of three man-made targets and natural backgrounds that were binned to 3 bands using weighted band binning. This work achieves optimal binning by using a genetic algorithm approach and the target-to-clutter-ratio (TCR) as the optimization criterion. Another approach applies a genetic algorithm to maximize discrimination among the spectral reflectivities in the Non-conventional Exploitation Factors Data System (NEFDS) library. Each candidate band was weighted using a Fermi function to represent four interacting band edges for three- bands. It is found that choice of target can significantly influence the optimal choice of bands as expressed through the TCR and the Receiver Operator Characteristic curve. This study shows that whitening the image data prominently displays targets relative to backgrounds by increasing color contrast and also maintains color constancy. Three-color images are displayed by assigning red, green, blue colors directly to the whitened data set. Achieving constant colors of targets and backgrounds over time can greatly aid human viewers in the interpretation of the images and discriminate targets.

  19. Spectral optimization studies and schemes to enhance target detection and display for a three-band staring LWIR sensor

    NASA Astrophysics Data System (ADS)

    Mayer, Rulon R.; Waterman, James; Schuler, Jonathon; Scribner, Dean

    2004-01-01

    To achieve enhanced target discrimination, prototype three- band long wave infrared (LWIR) focal plane arrays (FPA) for missile defense applications have recently been constructed. The cutoff wavelengths, widths, and spectral overlap of the bands are critical parameters for the multicolor sensor design. Previous calculations for sensor design did not account for target and clutter spectral features in determining the optimal band characteristics. The considerable spectral overlap and correlation between the bands and attendant reduction in color contrast is another unexamined issue. To optimize and simulate the projected behavior of three-band sensors, this report examined a hyperspectral LWIR image cube. Our study starts with 30 bands of the LWIR spectra of three man-made targets and natural backgrounds that were binned to 3 bands using weighted band binning. This work achieves optimal binning by using a genetic algorithm approach and the target-to-clutter-ratio (TCR) as the optimization criterion. Another approach applies a genetic algorithm to maximize discrimination among the spectral reflectivities in the Non-conventional Exploitation Factors Data System (NEFDS) library. Each candidate band was weighted using a Fermi function to represent four interacting band edges for three- bands. It is found that choice of target can significantly influence the optimal choice of bands as expressed through the TCR and the Receiver Operator Characteristic curve. This study shows that whitening the image data prominently displays targets relative to backgrounds by increasing color contrast and also maintains color constancy. Three-color images are displayed by assigning red, green, blue colors directly to the whitened data set. Achieving constant colors of targets and backgrounds over time can greatly aid human viewers in the interpretation of the images and discriminate targets.

  20. Operational multi-angle hyperspectral remote sensing for feature detection

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R.; Brooks, Donald K.

    2013-10-01

    Remote sensing results of land and water surfaces from airborne and satellite platforms are dependent upon the illumination geometry and the sensor viewing geometry. Correction of pushbroom hyperspectral imagery can be achieved using bidirectional reflectance factors (BRF's) image features based upon their multi-angle hyperspectral signatures. Ground validation of features and targets utilize non-imaging sensors such as hemispherical goniometers. In this paper, a new linear translation based hyperspectral imaging goniometer system is described. Imagery and hyperspectral signatures obtained from a rotation stage platform and the new linear non-hemispherical goniometer system shows applications and a multi-angle correction approach for multi-angle hyperspectral pushbroom imagery corrections. Results are presented in a manner in order to describe how ground, vessel and airborne based multi-angle hyperspectral signatures can be applied to operational hyperspectral image acquisition by the calculation of hyperspectral anisotropic signature imagery. The results demonstrate the analysis framework from the systems to water and coastal vegetation for exploitation of surface and subsurface feature or target detection based using the multi-angle radiative transfer based BRF's. The hyperspectral pushbroom multi-angle analysis methodology forms a basis for future multi-sensor based multi-angle change detection algorithms.

  1. Type II superlattice technology for LWIR detectors

    NASA Astrophysics Data System (ADS)

    Klipstein, P. C.; Avnon, E.; Azulai, D.; Benny, Y.; Fraenkel, R.; Glozman, A.; Hojman, E.; Klin, O.; Krasovitsky, L.; Langof, L.; Lukomsky, I.; Nitzani, M.; Shtrichman, I.; Rappaport, N.; Snapi, N.; Weiss, E.; Tuito, A.

    2016-05-01

    SCD has developed a range of advanced infrared detectors based on III-V semiconductor heterostructures grown on GaSb. The XBn/XBp family of barrier detectors enables diffusion limited dark currents, comparable with MCT Rule-07, and high quantum efficiencies. This work describes some of the technical challenges that were overcome, and the ultimate performance that was finally achieved, for SCD's new 15 μm pitch "Pelican-D LW" type II superlattice (T2SL) XBp array detector. This detector is the first of SCD's line of high performance two dimensional arrays working in the LWIR spectral range, and was designed with a ~9.3 micron cut-off wavelength and a format of 640 x 512 pixels. It contains InAs/GaSb and InAs/AlSb T2SLs, engineered using k • p modeling of the energy bands and photo-response. The wafers are grown by molecular beam epitaxy and are fabricated into Focal Plane Array (FPA) detectors using standard FPA processes, including wet and dry etching, indium bump hybridization, under-fill, and back-side polishing. The FPA has a quantum efficiency of nearly 50%, and operates at 77 K and F/2.7 with background limited performance. The pixel operability of the FPA is above 99% and it exhibits a stable residual non uniformity (RNU) of better than 0.04% of the dynamic range. The FPA uses a new digital read-out integrated circuit (ROIC), and the complete detector closely follows the interfaces of SCD's MWIR Pelican-D detector. The Pelican- D LW detector is now in the final stages of qualification and transfer to production, with first prototypes already integrated into new electro-optical systems.

  2. Hyperspectral forest monitoring and imaging implications

    NASA Astrophysics Data System (ADS)

    Goodenough, David G.; Bannon, David

    2014-05-01

    The forest biome is vital to the health of the earth. Canada and the United States have a combined forest area of 4.68 Mkm2. The monitoring of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of improved information products to land managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory (major forest species), forest health, foliar biochemistry, biomass, and aboveground carbon. Operationally there is a requirement for a mix of airborne and satellite approaches. This paper surveys some methods and results in hyperspectral sensing of forests and discusses the implications for space initiatives with hyperspectral sensing

  3. Spatial patterns of vegetation biomass and soil organic carbon acquired from airborne lidar and hyperspectral imagery at Reynolds Creek Critical Zone Observatory

    NASA Astrophysics Data System (ADS)

    Will, R. M.; Li, A.; Glenn, N. F.; Benner, S. G.; Spaete, L.; Ilangakoon, N. T.

    2015-12-01

    Soil organic carbon distribution and the factors influencing this distribution are important for understanding carbon stores, vegetation dynamics, and the overall carbon cycle. Linking soil organic carbon (SOC) with aboveground vegetation biomass may provide a method to better understand SOC distribution in semiarid ecosystems. The Reynolds Creek Critical Zone Observatory (RC CZO) in Idaho, USA, is approximately 240 square kilometers and is situated in the semiarid Great Basin of the sagebrush-steppe ecosystem. Full waveform airborne lidar data and Next-Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-ng) collected in 2014 across the RC CZO are used to map vegetation biomass and SOC and then explore the relationships between them. Vegetation biomass is estimated by identifying vegetation species, and quantifying distribution and structure with lidar and integrating the field-measured biomass. Spectral data from AVIRIS-ng are used to differentiate non-photosynthetic vegetation (NPV) and soil, which are commonly confused in semiarid ecosystems. The information from lidar and AVIRIS-ng are then used to predict SOC by partial least squares regression (PLSR). An uncertainty analysis is provided, demonstrating the applicability of these approaches to improving our understanding of the distribution and patterns of SOC across the landscape.

  4. Within-field and regional-scale accuracies of topsoil organic carbon content prediction from an airborne visible near-infrared hyperspectral image combined with synchronous field spectra for temperate croplands

    NASA Astrophysics Data System (ADS)

    Vaudour, Emmanuelle; Gilliot, Jean-Marc; Bel, Liliane; Lefevre, Josias; Chehdi, Kacem

    2016-04-01

    This study was carried out in the framework of the TOSCA-PLEIADES-CO of the French Space Agency and benefited data from the earlier PROSTOCK-Gessol3 project supported by the French Environment and Energy Management Agency (ADEME). It aimed at identifying the potential of airborne hyperspectral visible near-infrared AISA-Eagle data for predicting the topsoil organic carbon (SOC) content of bare cultivated soils over a large peri-urban area (221 km2) with intensive annual crop cultivation and both contrasted soils and SOC contents, located in the western region of Paris, France. Soils comprise hortic or glossic luvisols, calcaric, rendzic cambisols and colluvic cambisols. Airborne AISA-Eagle images (400-1000 nm, 126 bands) with 1 m-resolution were acquired on 17 April 2013 over 13 tracks. Tracks were atmospherically corrected then mosaicked at a 2 m-resolution using a set of 24 synchronous field spectra of bare soils, black and white targets and impervious surfaces. The land use identification system layer (RPG) of 2012 was used to mask non-agricultural areas, then calculation and thresholding of NDVI from an atmospherically corrected SPOT4 image acquired the same day enabled to map agricultural fields with bare soil. A total of 101 sites, which were sampled either at the regional scale or within one field, were identified as bare by means of this map. Predictions were made from the mosaic AISA spectra which were related to SOC contents by means of partial least squares regression (PLSR). Regression robustness was evaluated through a series of 1000 bootstrap data sets of calibration-validation samples, considering those 75 sites outside cloud shadows only, and different sampling strategies for selecting calibration samples. Validation root-mean-square errors (RMSE) were comprised between 3.73 and 4.49 g. Kg-1 and were ~4 g. Kg-1 in median. The most performing models in terms of coefficient of determination (R²) and Residual Prediction Deviation (RPD) values were the

  5. Detecting Sirex noctilio grey-attacked and lightning-struck pine trees using airborne hyperspectral data, random forest and support vector machines classifiers

    NASA Astrophysics Data System (ADS)

    Abdel-Rahman, Elfatih M.; Mutanga, Onisimo; Adam, Elhadi; Ismail, Riyad

    2014-02-01

    The visual progression of sirex (Sirex noctilio) infestation symptoms has been categorized into three distinct infestation phases, namely the green, red and grey stages. The grey stage is the final stage which leads to almost complete defoliation resulting in dead standing trees or snags. Dead standing pine trees however, could also be due to the lightning damage. Hence, the objective of the present study was to distinguish amongst healthy, sirex grey-attacked and lightning-damaged pine trees using AISA Eagle hyperspectral data, random forest (RF) and support vector machines (SVM) classifiers. Our study also presents an opportunity to look at the possibility of separating amongst the previously mentioned pine trees damage classes and other landscape classes on the study area. The results of the present study revealed the robustness of the two machine learning classifiers with an overall accuracy of 74.50% (total disagreement = 26%) for RF and 73.50% (total disagreement = 27%) for SVM using all the remaining AISA Eagle spectral bands after removing the noisy ones. When the most useful spectral bands as measured by RF were exploited, the overall accuracy was considerably improved; 78% (total disagreement = 22%) for RF and 76.50% (total disagreement = 24%) for SVM. There was no significant difference between the performances of the two classifiers as demonstrated by the results of McNemar's test (chi-squared; χ2 = 0.14, and 0.03 when all the remaining ASIA Eagle wavebands, after removing the noisy ones and the most important wavebands were used, respectively). This study concludes that AISA Eagle data classified using RF and SVM algorithms provide relatively accurate information that is important to the forest industry for making informed decision regarding pine plantations health protocols.

  6. Detection of disturbed earth using passive LWIR polarimetric imaging

    NASA Astrophysics Data System (ADS)

    Gurton, Kristan P.; Felton, Melvin

    2009-08-01

    We report test results of a study to assess the applicability for using passive polarimetric imaging in the long-wave infrared (LWIR) to detect regions of recently altered road-type surfaces, e.g., soil, gravel, asphalt, etc. The field test was conducted at the U.S. Army Research Laboratory, Adelphi, MD, on a test surface best described as a well traveled dirt road consisting of a gravel clay-soil mixture that was well compacted. During this initial proof-of-concept test, a LWIR polarimetric camera system was positioned at a slant-path of 10 degrees with respect to the line-of-site (LOS) and the natural lay of the surface, approximately 15 meters from the target test-bed. Stokes images, S0, S1, and S2, were recorded using the LWIR polarimeter that utilizes a spinning achromatic retarder design mated to Mercury Cadmium Telluride (MCT) focal plane array (FPA). Various surrogate targets were buried near the surface and great care was taken to camouflage the area to eliminate any "visible" signs of disturbance. Thermal gradients resulting from the unearthing of cool soil were allowed to dissipate. Two metrics were used to evaluate performance, i.e., conventional receiver operating characteristic (ROC) curve analysis and an effective contrast ratio between the target and background. Results showed particularly good detectability in the S2 imagery, with less in S1, and no detectability in S0, i.e., the conventional LWIR thermal image.

  7. Development of a visible-NIR/LWIR QWIP sensor

    NASA Astrophysics Data System (ADS)

    Cho, Eric; McQuiston, Barbara K.; Lim, Wah; Rafol, B., , Sir; Hanson, Cynthia; Nguyen, Richard; Hutchinson, Andy

    2003-09-01

    Quantum Well Infrared Photodetectors (QWIPs) based infrared focal plane arrays (FPAs) have been widely researched and investigated in the 3-5 μm and 6-20 μm wavelength ranges. The demonstrations of QWIP FPAs include single-color, dual-color and even multiple-color, as well as varieties of physical formats in the infrared range. In this paper, we discuss the research and development efforts currently undergoing at QWIP Technologies on dual-color, visible-NIR/LWIR FPAs, as an interim step for a project sponsored by DARPA (Defense Advanced Research Project Agency) to develop a four-color QWIP-based FPA. To the best of our knowledge, this is the first reported result on visible/LWIR QWIP imager, as well as the first reported GaAs PIN diode-based FPA. This device consists of a GaAs/AlGaAs based PIN diode grown on a GaAs substrate, and subsequently a stack of multiple quantum wells (MQWs), epitaxially grown on top of the PIN structure. This VISA (visible/infrared sensor array) structure is sensitive in the 500nm-890nm as well as in the 8um-12 um wavelength ranges. Very high sensitivities are observed from both visible PIN diode and LWIR QWIP; both visible and LWIR images obtained from this device are presented in this paper.

  8. MidIR and LWIR polarimetric sensor comparison study

    NASA Astrophysics Data System (ADS)

    Gurton, Kristan; Felton, Melvin; Mack, Robert; LeMaster, Daniel; Farlow, Craig; Kudenov, Michael; Pezzaniti, Larry

    2010-04-01

    We present a comparative study involving five distinctly different polarimetric imaging platforms that are designed to record calibrated Stokes images (and associated polarimetric products) in either the MidIR or LWIR spectral regions. The data set used in this study was recorded during April 14-18, 2008, at the Russell Tower Measurement Facility, Redstone Arsenal, Huntsville, AL. Four of the five camera systems were designed to operate in the LWIR (approx. 8-12μm), and used either cooled mercury cadmium telluride (MCT) focal-plane-arrays (FPA), or a near-room temperature microbolometer. The lone MidIR polarimetric sensor was based on a liquid nitrogen (LN2) cooled indium antimonide (InSb) FPA, resulting in an approximate wavelength response of 3-5μm. The selection of cameras was comprised of the following optical designs: a LWIR "super-pixel," or division-of-focal plane (DoFP) sensor; two LWIR spinning-achromatic-retarder (SAR) based sensors; one LWIR division-of-amplitude (DoAM) sensor; and one MidIR division-of-aperture (DoA) sensor. Cross-sensor comparisons were conducted by examining calibrated Stokes images (e.g., S0, S1, S2, and degree-of-linear polarization (DOLP)) recorded by each sensor for a given target at approximately the same test periods to ensure that data sets were recorded under similar atmospheric conditions. Target detections are applied to the image set for each polarimetric sensor for further comparison, i.e., conventional receiver operating characteristic (ROC) curve analysis and an effective contrast ratio are considered.

  9. 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.

  10. Hyperspectral IR polarimetry with applications in demining and unexploded ordnance detection

    NASA Astrophysics Data System (ADS)

    Scott, Herman E.; Jones, Stephen H.; Iannarilli, Frank J., Jr.; Annen, Kurt D.

    1999-02-01

    Several years of effort in IR polarimetry have brought us convincing evidence of its effectiveness in differentiating man made objects from natural backgrounds. Adding modern focal plane array (FPA) technology (either cooled or uncooled) makes it possible to combine the benefits of polarimetry with the power of hyperspectral imaging. Aerodyne Research is embarked on a stepwise, controlled-risk development program with the objective of fielding an innovative and affordable hyperspectral imaging IR polarimeter. Proof-of-concept demonstrations are conducted for each significant technology increment as part of the prototype development effort. These steps, two demonstrated and two yet to be demonstrated, are: (1) LWIR (non-imaging) Spectral Polarimeter to demonstrate the effectiveness of combined polarimetric and hyperspectral discriminating capabilities in observations on static scenes; (2) LWIR Uncooled FPA Imaging (broadband) Polarimeter to test the sensitivity of an affordable Uncooled FPA in a broadband configuration against static scenes; (3) Multispectral Imaging Polarimeter to quantify clutter rejection performance improvements to be realized in multispectral polarimetry; and (4) Hyperspectral Imaging IR Polarimeter designed with optimal spatial and spectral resolution and sufficient throughput to achieve the reliable performance required in surface mine and UXO detection applications. Results from the ongoing proof-of- concept demonstrations in simulated surface mine detection will be presented.

  11. Calibration methodology and performance characterization of a polarimetric hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Holder, Joel G.; Martin, Jacob A.; Pitz, Jeremey; Pezzaniti, Joseph L.; Gross, Kevin C.

    2014-05-01

    Polarimetric hyperspectral imaging (P-HSI) has the potential to improve target detection, material identification, and background characterization over conventional hyperspectral imaging and polarimetric imaging. To fully exploit the spectro-polarimetric signatures captured by such an instrument, a careful calibration process is required to remove the spectrally- and polarimetrically-dependent system response (gain). Calibration of instruments operating in the long-wave infrared (LWIR, 8μm to 12 μm) is further complicated by the polarized spectral radiation generated within the instrument (offset). This paper presents a calibration methodology developed for a LWIR Telops Hyper-Cam modified for polarimetry by replacing the entrance window with a rotatable holographic wire-grid polarizer (4000 line/mm, ZnSe substrate, 350:1 extinction ratio). A standard Fourier-transform spectrometer (FTS) spectro-radiometric calibration is modified to include a Mueller-matrix approach to account for polarized transmission through and polarized selfemission from each optical interface. It is demonstrated that under the ideal polarizer assumption, two distinct blackbody measurements at polarizer angles of 0°, 45°, 90°, and 135° are sufficient to calibrate the system for apparent degree-of-linear-polarization (DoLP) measurements. Noise-equivalent s1, s2, and DoLP are quantified using a wide-area blackbody. A polarization-state generator is used to determine the Mueller deviation matrix. Finally, a realistic scene involving buildings, cars, sky radiance, and natural vegetation is presented.

  12. Tracking long-range transported upper-tropospheric pollution layers with a newly developed airborne Hyperspectral Sun/Sky spectrometer (4STAR): Results from the TCAP 2012 campaign

    NASA Astrophysics Data System (ADS)

    Segal-Rosenhaimer, M.; Russell, P. B.; Schmid, B.; Redemann, J.; Livingston, J. M.; Flynn, C. J.; Johnson, R.; Dunagan, S.; Shinozuka, Y.; Herman, J. R.; Cede, A.; Abuhassan, N.; Comstock, J. M.; Hubbe, J.

    2013-12-01

    TCAP, the Two Column Aerosol Project, was aimed at providing a detailed set of observations to investigate topics related to radiation and aerosol-cloud interactions, and to learn about aging and transport of atmospheric aerosols and gaseous constituents that are related to tropospheric pollution events. During the year-long campaign, an intensive airborne deployment was held in the summer of 2012 based at the Hyannis airport, Cape-Cod, MA. In the course of the campaign, the newly developed Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) flew onboard the DOE Gulfstream 1 (G-1) aircraft, together with a suite of in-situ instruments to measure atmospheric state parameters and aerosol and cloud characteristics. One of the unique features of the 4STAR instrument, stemming from its design using grating spectrometers that cover the UV-VIS-SWIR spectral range (i.e. 350-1700nm), is its capability to measure atmospheric trace gases such as water vapor, O3 and NO2 concurrently with spectrally resolved aerosol optical depth (AOD). Here, we utilize the 4STAR measurements above the planetary boundary layer (PBL) (i.e. above 3000 meters) to investigate atmospheric composition of elevated pollution layers transported from the continental US and Canada during the TCAP summer phase. The 4STAR-retrieved values of AOD at 500 nm, Ångstrom exponent (AE) at 500 nm, columnar water vapor (CWV), and NO2 are used as variables in a k-means clustering algorithm to determine the atmospheric composition characteristics of the observed elevated polluted layers during the July flights. We found that, compared to AOD, NO2 displays less variability in plumes that are related to biomass-burning (BB) emissions over the course of several days. HYSPLIT back-trajectory analysis has confirmed our clustering results of two major air-mass sources: a relatively dry and clean upper tropospheric source and a humid, polluted one. Our clustering analysis, resulting in different ocean

  13. Small object hyperspectral detection from a low-flying UAV

    NASA Astrophysics Data System (ADS)

    Murray-Krezan, J.; Neumann, J. G.; Leathers, R. A.

    2008-04-01

    Small object detection with a low false alarm rate remains a challenge for automated hyperspectral detection algorithms when the background environment is cluttered. In order to approach this problem we are developing a compact hyperspectral sensor that can be fielded from a small unmanned airborne platform. This platform is capable of flying low and slow, facilitating the collection of hyperspectral imagery that has a small ground-sample distance (GSD) and small atmospheric distortion. Using high-resolution hyperspectral imagery we simulate various ranges between the sensor and the objects of interest. This numerical study aids in analysis of the effects of stand-off distance on detection versus false alarm rates when using standard hyperspectral detection algorithms. Preliminary experimental evidence supports our simulation results.

  14. Evaluating AISA+ hyperspectral imagery for mapping black mangrove along the South Texas Gulf Coast

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Mangrove wetlands are economically and ecologically important ecosystems and accurate assessment of these wetlands with remote sensing can assist in their management and conservation. This study was conducted to evaluate airborne AISA+ hyperspectral imagery and image transformation and classificatio...

  15. Mapping Black Mangrove Along the South Texas Gulf Coast Using AISA+ Hyperspectral Imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Mangrove wetlands are economically and ecologically important ecosystems and accurate assessment of these wetlands with remote sensing can assist in their management and conservation. This study was conducted to evaluate airborne hyperspectral imagery and image compression and classification techniq...

  16. MWIR and LWIR Megapixel QWIP Focal Plane Arrays

    NASA Technical Reports Server (NTRS)

    Gunapala, Sarath D.; Bandara, S. V.; Liu, J. K.; Rafol, S. B.; Thang, J.; Mumolo, Jason; Tidrow, M.; LeVan, P. D.; Hill, C.

    2004-01-01

    A mid-wavelength infrared (MWIR) and long-wavelength infrared (LWIR) 1024x1024 pixel quantum well infrared photodetector (QWIP) focal plane array has been demonstrated with excellent imagery. MWIR focal plane has given noise equivalent differential temperature (NETD) of 19 mK at 95K operating temperature with f/2.5 optics at 300K background and LWIR focal plane has given NEDT of 13 mK at 70K operating temperature with same optical and background conditions as MWIR array. Both of these focal plane arrays have shown background limited performance (BLIP) at 90K and 70K operating temperatures with the same optics and background conditions. In this paper, we will discuss their performance in quantum efficiency, NETD, uniformity, and operability.

  17. Achromatic phase retarder applied to MWIR & LWIR dual-band.

    PubMed

    Kang, Guoguo; Tan, Qiaofeng; Wang, Xiaoling; Jin, Guofan

    2010-01-18

    The development of the dual-band IR imaging polarimetry creates the need for achromatic phase retarder used in dual-band. Dielectric grating with the period smaller than the illuminating wavelength presents a strong form-birefringence. With this feature, the combination of several subwavelength gratings can be used as achromatic phase retarders. We proposed a combination of 4 subwavelength structured gratings (SWGs) used as an achromatic quarter-wave plate (QWP) applied to MWIR & LWIR bandwidths. Design method using effective medium theory and optimization algorithms is described in detail. The simulation results led to the possibility of an dual-band achromatic QWP whose retardance deviates from 90 degrees by <+/-0.75 degrees with the fast axis unfixed and by <+/-1.35 degrees with the fast axis fixed over MWIR(3-5microm) & LWIR(8-12microm) bandwiths. PMID:20173997

  18. Refractive lens design for simultaneous SWIR and LWIR imaging

    NASA Astrophysics Data System (ADS)

    Sparrold, Scott; Herman, Eric; Czajkowski, Amber; O'Shea, Kevin

    2011-06-01

    Infrared detector technology has progressed to include many fused wavebands. This has been driven by the need of military systems to image over diverse spectrums. Imaging systems can now operate in both the short wave infrared (SWIR) as well as the long wave infrared (LWIR). Reflective optics seems like a natural solution to such a large waveband, but they will have more restrictive size and field of view constraints. This paper will demonstrate the steps to achieve a Petzval lens with fast aperture and moderate field that is achromatic in the SWIR and has low axial color in the LWIR. The lens achieves a high resolution solution in terms of modulation transfer function (MTF).

  19. Folded path LWIR system for SWAP constrained platforms

    NASA Astrophysics Data System (ADS)

    Fleet, Erin F.; Wilson, Michael L.; Linne von Berg, Dale; Giallorenzi, Thomas; Mathieu, Barry

    2014-06-01

    Folded path reflection and catadioptric optics are of growing interest, especially in the long wave infrared (LWIR), due to continuing demands for reductions in imaging system size, weight and power (SWAP). We present the optical design and laboratory data for a 50 mm focal length low f/# folded-path compact LWIR imaging system. The optical design uses 4 concentric aspheric mirrors, each of which is described by annular aspheric functions well suited to the folded path design space. The 4 mirrors are diamond turned onto two thin air-spaced aluminum plates which can be manually focused onto the uncooled LWIR microbolometer array detector. Stray light analysis will be presented to show how specialized internal baffling can be used to reduce stray light propagation through the folded path optical train. The system achieves near diffraction limited performance across the FOV with a 15 mm long optical train and a 5 mm back focal distance. The completed system is small enough to reside within a 3 inch diameter ball gimbal.

  20. Characterization of a C-QWIP LWIR camera

    NASA Astrophysics Data System (ADS)

    Forrai, David P.; Sempsrott, Mark; Fischer, Robert; Choi, Kwong-Kit; Devitt, John W.

    2007-04-01

    Large format corrugated quantum well infrared photodetector (C-QWIP) focal plane arrays (FPAs) have been developed over the past two years. The results of this development have demonstrated the potential for this technology to satisfy requirements for very large format high performance long-wave infrared (LWIR) imaging systems. One particular C-QWIP design has focused on developing an FPA that operates in the 8 to 10 μm spectrum with integration times in the millisecond regime when used against warm backgrounds. This FPA is very suitable for many LWIR applications and has been integrated into a camera system. The specifications of that camera are described in this paper. The characterization of this camera system includes standard electro-optical tests and compares the results of those tests to theoretical models for the FPA. This paper concludes by describing the ongoing effort to tailor the system specifically for the C-QWIP. This includes design features of the read-out integrated circuit (ROIC), dewar-cooler design and interfacing electronics, and video processing. This thorough characterization of the camera has demonstrated the utility of the C-QWIP FPA for LWIR imaging and has established a path forward to further improve the performance of imaging systems implementing this technology.

  1. Hyperspectral anomaly detection method based on auto-encoder

    NASA Astrophysics Data System (ADS)

    Bati, Emrecan; ćalışkan, Akın.; Koz, Alper; Alatan, A. A.

    2015-10-01

    A major drawback of most of the existing hyperspectral anomaly detection methods is the lack of an efficient background representation, which can successfully adapt to the varying complexity of hyperspectral images. In this paper, we propose a novel anomaly detection method which represents the hyperspectral scenes of different complexity with the state-of-the-art representation learning method, namely auto-encoder. The proposed method first encodes the spectral image into a sparse code, then decodes the coded image, and finally, assesses the coding error at each pixel as a measure of anomaly. Predictive Sparse Decomposition Auto-encoder is utilized in the proposed anomaly method due to its efficient joint learning for the encoding and decoding functions. The performance of the proposed anomaly detection method is both tested on visible-near infrared (VNIR) and long wave infrared (LWIR) hyperspectral images and compared with the conventional anomaly detection method, namely Reed-Xiaoli (RX) detector.1 The experiments has verified the superiority of the proposed anomaly detection method in terms of receiver operating characteristics (ROC) performance.

  2. Fractal Characterization of Hyperspectral Imagery

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  3. 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.

  4. 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.

  5. 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.

  6. Detection of industrial gaseous chemical plumes using hyperspectral imagery in the emissive regime

    NASA Astrophysics Data System (ADS)

    Farrell, Michael D., Jr.; Mersereau, Russell M.

    2005-08-01

    For the past ten years, much of the research in hyperspectral image data exploitation techniques has been focused on detection of ground targets. As a passive remote sensing technique, hyperspectral imagers have performed reasonably well in detecting the presence of a variety of objects; from crop species to land mines to mineral deposits to vehicles under camouflage. These often promising results have prompted new studies of hyperspectral remote sensing for other applications - including atmospheric monitoring. Should technologies like hyperspectral imaging prove effective in emission source monitoring, organizations interested in environmental assessment could transition from inspection using hand-held analytical instruments to a truly standoff technique. In this paper, we evaluate the utility of a set of hyperspectral exploitation techniques applied to the task of gas detection. This set of techniques is a sampling of approaches that have appeared in the literature, and all of the methods discussed have demonstrated utility in the reflective regime. Specifically, we look at signature-based detection, anomaly detection, transformations (i.e. rotations) of the spectral space, and even dedicated band combinations and scatter plots. Using real LWIR hyperspectral data recently collected on behalf of the US Environmental Protection Agency, we compare performance in detecting three different industrial gases.

  7. 1024x1024 Pixel MWIR and LWIR QWIP Focal Plane Arrays and 320x256 MWIR:LWIR Pixel Colocated Simultaneous Dualband QWIP Focal Plane Arrays

    NASA Technical Reports Server (NTRS)

    Gunapala, Sarath D.; Bandara, Sumith V.; Liu, John K.; Hill, Cory J.; Rafol, S. B.; Mumolo, Jason M.; Trinh, Joseph T.; Tidrow, M. Z.; Le Van, P. D.

    2005-01-01

    Mid-wavelength infrared (MWIR) and long-wavelength infrared (LWIR) 1024x1024 pixel quantum well infrared photodetector (QWIP) focal planes have been demonstrated with excellent imaging performance. The MWIR QWIP detector array has demonstrated a noise equivalent differential temperature (NE(Delta)T) of 17 mK at a 95K operating temperature with f/2.5 optics at 300K background and the LWIR detector array has demonstrated a NE(Delta)T of 13 mK at a 70K operating temperature with the same optical and background conditions as the MWIR detector array after the subtraction of system noise. Both MWIR and LWIR focal planes have shown background limited performance (BLIP) at 90K and 70K operating-temperatures respectively, with similar optical and background conditions. In addition, we are in the process of developing MWIR and LWIR pixel collocated simultaneously readable dualband QWIP focal plane arrays.

  8. Hyperspectral image processing

    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...

  9. 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...

  10. Mapping invasive weeds using airborne hyperspectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Invasive plant species present a serious problem to the natural environment and have adverse ecological and economic impacts on both terrestrial and aquatic ecosystems they invade. This article provides a brief overview on the use of remote sensing for mapping invasive plant species in both terrestr...

  11. HYPERSPECTRAL CHANNEL SELECTION FOR WATER QUALITY MONITORING ON THE GREAT MIAMI RIVER, OHIO

    EPA Science Inventory

    During the summer of 1999, spectral data were collected with a hand-held spectroradiometer, a laboratory spectrometer and airborne hyperspectral sensors from the Great Miami River (GMR), Ohio. Approximately 80 km of the GMR were imaged during a flyover with a Compact Airborne Sp...

  12. LWIR polarimetry for enhanced facial recognition in thermal imagery

    NASA Astrophysics Data System (ADS)

    Gurton, Kristan P.; Yuffa, Alex J.; Videen, Gorden

    2014-05-01

    We present a series of long-wave-infrared (LWIR) polarimetric-based thermal images of facial profiles in which polarization-state information of the image forming radiance is retained and displayed. The resultant polarimetric images show enhanced facial features, additional texture, and details that are not present in the corresponding conventional thermal imagery. It has been generally thought that conventional thermal imagery (MidiR or LWIR) could not produce the detailed spatial information required for reliable human identification due to the so-called "ghosting" effect often seen in thermal imagery of human subjects. By using polarimetric information, we are able to extract subtle surface features of the human face, thus improving subject identification. The considered polarimetric image sets include the conventional thermal intensity image, S0 , the two Stokes images, S1 and S2, and a Stokes image product called the degree-of-linear-polarization (DoLP) image. Finally, Stokes imagery is combined with Fresnel relations to extract additional 3D surface information.

  13. Hyperspectral cytometry.

    PubMed

    Grégori, Gérald; Rajwa, Bartek; Patsekin, Valery; Jones, James; Furuki, Motohiro; Yamamoto, Masanobu; Paul Robinson, J

    2014-01-01

    Hyperspectral cytometry is an emerging technology for single-cell analysis that combines ultrafast optical spectroscopy and flow cytometry. Spectral cytometry systems utilize diffraction gratings or prism-based monochromators to disperse fluorescence signals from multiple labels (organic dyes, nanoparticles, or fluorescent proteins) present in each analyzed bioparticle onto linear detector arrays such as multianode photomultipliers or charge-coupled device sensors. The resultant data, consisting of a series of characterizing every analyzed cell, are not compensated by employing the traditional cytometry approach, but rather are spectrally unmixed utilizing algorithms such as constrained Poisson regression or non-negative matrix factorization. Although implementations of spectral cytometry were envisioned as early as the 1980s, only recently has the development of highly sensitive photomultiplier tube arrays led to design and construction of functional prototypes and subsequently to introduction of commercially available systems. This chapter summarizes the historical efforts and work in the field of spectral cytometry performed at Purdue University Cytometry Laboratories and describes the technology developed by Sony Corporation that resulted in release of the first commercial spectral cytometry system-the Sony SP6800. A brief introduction to spectral data analysis is also provided, with emphasis on the differences between traditional polychromatic and spectral cytometry approaches. PMID:24271566

  14. Low dark current MCT-based focal plane detector arrays for the LWIR and VLWIR developed at AIM

    NASA Astrophysics Data System (ADS)

    Gassmann, Kai Uwe; Eich, Detlef; Fick, Wolfgang; Figgemeier, Heinrich; Hanna, Stefan; Thöt, Richard

    2015-10-01

    For nearly 40 years AIM develops, manufactures and delivers photo-voltaic and photo-conductive infrared sensors and associated cryogenic coolers which are mainly used for military applications like pilotage, weapon sights, UAVs or vehicle platforms. In 2005 AIM started to provide the competences also for space applications like IR detector units for the SLSTR instrument on board of the Sentinel 3 satellite, the hyperspectral SWIR Imager for EnMAP or pushbroom detectors for high resolution Earth observation satellites. Meanwhile AIM delivered more than 25 Flight Models for several customers. The first European pulse-tube cooler ever operating on-board of a satellite is made by AIM. AIM homes the required infrared core capabilities such as design and manufacturing of focal plane assemblies, detector housing technologies, development and manufacturing of cryocoolers and also data processing for thermal IR cameras under one roof which enables high flexibility to react to customer needs and assures economical solutions. Cryogenically cooled Hg(1-x)CdxTe (MCT) quantum detectors are unequalled for applications requiring high imaging as well as high radiometric performance in the infrared spectral range. Compared with other technologies, they provide several advantages, such as the highest quantum efficiency, lower power dissipation compared to photoconductive devices and fast response times, hence outperforming micro-bolometer arrays. However, achieving an excellent MCT detector performance at long (LWIR) and very long (VLWIR) infrared wavelengths is challenging due to the exponential increase in the thermally generated photodiode dark current with increasing cut-off wavelength and / or operating temperature. Dark current is a critical design driver, especially for LWIR / VLWIR multi-spectral imagers with moderate signal levels or hyper-spectral Fourier spectrometers operating deep into the VLWIR spectral region. Consequently, low dark current (LDC) technologies are the

  15. Comparing a MWIR and LWIR polarimetric imager for surface swimmer detection

    NASA Astrophysics Data System (ADS)

    Harchanko, John S.; Pezzaniti, Larry; Chenault, David; Eades, Graham

    2008-04-01

    Previously, we have investigated the use of Long-Wave Infra-Red (LWIR) polarimetric imaging for the detection of surface swimmers in a maritime environment. While better contrast and longer range are expected with Mid-Wave Infra-Red (MWIR) polarimetric imaging, the cost of such a system is higher than a polarimetric imager operating in the LWIR due to the advent of higher-performance micro-bolometer imaging arrays. The actual performance of a MWIR polarimetric imager to detect a person in the water is presented. A comparative analysis of system cost between MWIR and LWIR systems is also discussed.

  16. Comparing a MWIR and LWIR polarimetric imaging for surface swimmer detection

    NASA Astrophysics Data System (ADS)

    Harchanko, John S.; Pezzaniti, Larry; Chenault, David; Eades, Graham

    2008-04-01

    Previously, we have investigated the use of Long-Wave Infra-Red (LWIR) polarimetric imaging for the detection of surface swimmers in a maritime environment. While better contrast and longer range are expected with Mid-Wave Infra-Red (MWIR) polarimetric imaging, the cost of such a system is higher than a polarimetric imager operating in the LWIR due to the advent of higher-performance micro-bolometer imaging arrays. The actual performance of a MWIR polarimetric imager to detect a person in the water is presented. A comparative analysis of system cost between MWIR and LWIR systems is also discussed.

  17. 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.

  18. 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.

  19. 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.

  20. Miniaturization of sub-meter resolution hyperspectral imagers on unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Hill, Samuel L.; Clemens, Peter

    2014-05-01

    Traditional airborne environmental monitoring has frequently deployed hyperspectral imaging as a leading tool for characterizing and analyzing a scene's critical spectrum-based signatures for applications in agriculture genomics and crop health, vegetation and mineral monitoring, and hazardous material detection. As the acceptance of hyperspectral evaluation grows in the airborne community, there has been a dramatic trend in moving the technology from use on midsize aircraft to Unmanned Aerial Systems (UAS). The use of UAS accomplishes a number of goals including the reduction in cost to run multiple seasonal evaluations over smaller but highly valuable land-areas, the ability to use frequent data collections to make rapid decisions on land management, and the improvement of spatial resolution by flying at lower altitudes (< 150 m). Despite this trend, there are several key parameters affecting the use of traditional hyperspectral instruments in UAS with payloads less than 0.5 kg (~1lb) where size, weight and power (SWaP) are critical to how high and how far a given UAS can fly. Additionally, on many of the light-weight UAS, users are frequently trying to capture data from one or more instruments to augment the hyperspectral data collection, thus reducing the amount of SWaP available to the hyperspectral instrumentation. The following manuscript will provide an analysis on a newly-developed miniaturized hyperspectral imaging platform that provides full hyperspectral resolution and traditional hyperspectral capabilities without sacrificing performance to accommodate the decreasing SWaP of smaller and smaller UAS platforms.

  1. LWIR and VLWIR detectors development at SOFRADIR for space applications

    NASA Astrophysics Data System (ADS)

    Terrier, Bertrand; Delannoy, Anne; Chorier, Philippe; Maillard, Magalie; Rubaldo, Laurent

    2010-10-01

    SOFRADIR is one of the leading companies involved in the development and manufacturing of infrared detectors. Its offer covers the infrared spectrum from visible range (0.4 μm) up to very long wavelength range (15 μm). The need in this last field is driven by space activities, especially by meteorological instruments using imagery or spectrometry. In the frame of Meteosat Third Generation mission, ESA has launched pre-development activities to address the critical equipments for risk reduction. VLWIR detectors for FCI and IRS have been considered as challenging ones and thus SOFRADIR has been involved for manufacturing and testing 2D arrays with long cut-off wavelength (14.9μm at 50K) in order to evaluate their compliance to MTG requirements as far as dark current behaviour, quantum efficiency, photoresponse uniformity, spatial response, operability and reliability are concerned. In parallel, trends of space and tactical applications call for dark current reduction technology in order to improve systems performances in terms of operating temperature and signal to noise ratio. In the frame of its common laboratory DEFIR with CEA-LETI, Sofradir has developed a new MCT p on n technology to answer this need. First demonstrations were made with success (640x512, pitch 15μm and cut-off 9.5μm) and Sofradir is now industrializing this technology in particular for tactical application. Thanks to the communality between space and tactical activity at Sofradir, these results will benefit advantageously also to space activity. In this paper, we present a review of latest Sofradir results concerning LWIR and VLWIR technology. In particular, latest data, concerning development and characterization of generic VLWIR technology up to 15 μm cut-off wavelength, are presented as well as data concerning the promising p on n LWIR technology.

  2. Deep transfer learning for automatic target classification: MWIR to LWIR

    NASA Astrophysics Data System (ADS)

    Ding, Zhengming; Nasrabadi, Nasser; Fu, Yun

    2016-05-01

    Publisher's Note: This paper, originally published on 5/12/2016, was replaced with a corrected/revised version on 5/18/2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. When dealing with sparse or no labeled data in the target domain, transfer learning shows its appealing performance by borrowing the supervised knowledge from external domains. Recently deep structure learning has been exploited in transfer learning due to its attractive power in extracting effective knowledge through multi-layer strategy, so that deep transfer learning is promising to address the cross-domain mismatch. In general, cross-domain disparity can be resulted from the difference between source and target distributions or different modalities, e.g., Midwave IR (MWIR) and Longwave IR (LWIR). In this paper, we propose a Weighted Deep Transfer Learning framework for automatic target classification through a task-driven fashion. Specifically, deep features and classifier parameters are obtained simultaneously for optimal classification performance. In this way, the proposed deep structures can extract more effective features with the guidance of the classifier performance; on the other hand, the classifier performance is further improved since it is optimized on more discriminative features. Furthermore, we build a weighted scheme to couple source and target output by assigning pseudo labels to target data, therefore we can transfer knowledge from source (i.e., MWIR) to target (i.e., LWIR). Experimental results on real databases demonstrate the superiority of the proposed algorithm by comparing with others.

  3. Hyperspectral sensing of forests

    NASA Astrophysics Data System (ADS)

    Goodenough, David G.; Dyk, Andrew; Chen, Hao; Hobart, Geordie; Niemann, K. Olaf; Richardson, Ash

    2007-11-01

    Canada contains 10% of the world's forests covering an area of 418 million hectares. The sustainable management of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of new and improved information products to resource managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory, forest health, foliar biochemistry, biomass, and aboveground carbon than are currently available. This paper surveys recent methods and results in hyperspectral sensing of forests and describes space initiatives for hyperspectral sensing.

  4. NIR/LWIR dual-band infrared photodetector with optical addressing

    NASA Astrophysics Data System (ADS)

    Cellek, O. O.; Kim, H. S.; Reno, J. L.; Zhang, Y.-H.

    2012-06-01

    A near infrared (NIR) and long-wavelength infrared (LWIR) dual-band infrared photodetector, which can switch detection bands with light bias, is demonstrated at 77 K. The demonstrated scheme consists of series connected photodetectors for different bands. The basic operating principle of the scheme is that without light bias, shorter wavelength detector limits the total current and thus the device operates in NIR mode. With light bias on the NIR detector, the LWIR detector becomes the current limiting device and the device then operates in LWIR mode. Proposed design allows single indium-bump per pixel focal plane arrays, and in principle allows covering all tactical bands such as UV, visible, NIR, SWIR, MWIR and LWIR bands with a single pixel.

  5. Radiometric consistency assessment of hyperspectral infrared sounders

    NASA Astrophysics Data System (ADS)

    Wang, L.; Han, Y.; Jin, X.; Chen, Y.; Tremblay, D. A.

    2015-07-01

    The radiometric and spectral consistency among the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared Sounder (CrIS) is fundamental for the creation of long-term infrared (IR) hyperspectral radiance benchmark datasets for both inter-calibration and climate-related studies. In this study, the CrIS radiance measurements on Suomi National Polar-orbiting Partnership (SNPP) satellite are directly compared with IASI on MetOp-A and -B at the finest spectral scale and with AIRS on Aqua in 25 selected spectral regions through one year of simultaneous nadir overpass (SNO) observations to evaluate radiometric consistency of these four hyperspectral IR sounders. The spectra from different sounders are paired together through strict spatial and temporal collocation. The uniform scenes are selected by examining the collocated Visible Infrared Imaging Radiometer Suite (VIIRS) pixels. Their brightness temperature (BT) differences are then calculated by converting the spectra onto common spectral grids. The results indicate that CrIS agrees well with IASI on MetOp-A and IASI on MetOp-B at the longwave IR (LWIR) and middle-wave IR (MWIR) bands with 0.1-0.2 K differences. There are no apparent scene-dependent patterns for BT differences between CrIS and IASI for individual spectral channels. CrIS and AIRS are compared at the 25 spectral regions for both Polar and Tropical SNOs. The combined global SNO datasets indicate that, the CrIS-AIRS BT differences are less than or around 0.1 K among 21 of 25 comparison spectral regions and they range from 0.15 to 0.21 K in the remaining 4 spectral regions. CrIS-AIRS BT differences in some comparison spectral regions show weak scene-dependent features.

  6. Radiometric consistency assessment of hyperspectral infrared sounders

    NASA Astrophysics Data System (ADS)

    Wang, L.; Han, Y.; Jin, X.; Chen, Y.; Tremblay, D. A.

    2015-11-01

    The radiometric and spectral consistency among the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared Sounder (CrIS) is fundamental for the creation of long-term infrared (IR) hyperspectral radiance benchmark data sets for both intercalibration and climate-related studies. In this study, the CrIS radiance measurements on Suomi National Polar-orbiting Partnership (SNPP) satellite are directly compared with IASI on MetOp-A and MetOp-B at the finest spectral scale and with AIRS on Aqua in 25 selected spectral regions through simultaneous nadir overpass (SNO) observations in 2013, to evaluate radiometric consistency of these four hyperspectral IR sounders. The spectra from different sounders are paired together through strict spatial and temporal collocation. The uniform scenes are selected by examining the collocated Visible Infrared Imaging Radiometer Suite (VIIRS) pixels. Their brightness temperature (BT) differences are then calculated by converting the spectra onto common spectral grids. The results indicate that CrIS agrees well with IASI on MetOp-A and IASI on MetOp-B at the long-wave IR (LWIR) and middle-wave IR (MWIR) bands with 0.1-0.2 K differences. There are no apparent scene-dependent patterns for BT differences between CrIS and IASI for individual spectral channels. CrIS and AIRS are compared at the 25 spectral regions for both polar and tropical SNOs. The combined global SNO data sets indicate that the CrIS-AIRS BT differences are less than or around 0.1 K among 21 of 25 spectral regions and they range from 0.15 to 0.21 K in the remaining four spectral regions. CrIS-AIRS BT differences in some comparison spectral regions show weak scene-dependent features.

  7. Software for Simulation of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  8. Implications and mitigation of model mismatch and covariance contamination for hyperspectral chemical agent detection

    NASA Astrophysics Data System (ADS)

    Niu, Sidi; Golowich, Steven E.; Ingle, Vinay K.; Manolakis, Dimitris G.

    2013-02-01

    Most chemical gas detection algorithms for long-wave infrared hyperspectral images assume a gas with a perfectly known spectral signature. In practice, the chemical signature is either imperfectly measured and/or exhibits spectral variability due to temperature variations and Beers law. The performance of these detection algorithms degrades further as a result of unavoidable contamination of the background covariance by the plume signal. The objective of this work is to explore robust matched filters that take the uncertainty and/or variability of the target signatures into account and mitigate performance loss resulting from different factors. We introduce various techniques that control the selectivity of the matched filter and we evaluate their performance in standoff LWIR hyperspectral chemical gas detection applications.

  9. Comparison of the inversion periods for MidIR and LWIR polarimetric and conventional thermal imagery

    NASA Astrophysics Data System (ADS)

    Felton, M.; Gurton, K. P.; Pezzaniti, J. L.; Chenault, D. B.; Roth, L. E.

    2010-04-01

    We report the results of a diurnal study in which radiometrically calibrated polarimetric and conventional thermal imagery are recorded in the MidIR and LWIR to identify and compare the respective time periods in which minimum target contrast is achieved. The MidIR polarimetric sensor is based on a division-of-aperture approach and has a 640x512 InSb focal-plane array, while the LWIR polarimetric sensor uses a spinning achromatic retarder to perform the polarimetric filtering and has a 324x256 microbolometer focal-plane array. The images used in this study include the S0 and S1 Stokes images of a scene containing a military vehicle and the natural background. In addition, relevant meteorological parameters measured during the test period include air temperature, ambient loading in the LWIR, relative humidity, cloud cover, height, and density. The data shows that the chief factors affecting polarimetric contrast in both wavebands are the amount of thermal emission from the objects in the scene and the abundance of MidIR and LWIR sources in the optical background. In particular, it has been observed that the MidIR polarimetric contrast was positively correlated to the presence of MidIR sources in the optical background, while the LWIR polarimetric contrast was negatively correlated to the presence of LWIR sources in the optical background.

  10. Performance Evaluation of Hyperspectral Chemical Detection Systems

    NASA Astrophysics Data System (ADS)

    Truslow, Eric

    Remote sensing of chemical vapor plumes is a difficult but important task with many military and civilian applications. Hyperspectral sensors operating in the long wave infrared (LWIR) regime have well demonstrated detection capabilities. However, the identification of a plume's chemical constituents, based on a chemical library, is a multiple hypothesis-testing problem that standard detection metrics do not fully describe. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and an identification metric based on the Dice index. Using the developed metrics, we demonstrate that using a detector bank followed by an identifier can achieve superior performance relative to either algorithm individually. Performance of the cascaded system relies on the first pass reliably detecting the plume. However, detection performance is severely hampered by the inclusion of plume pixels in estimates of background quantities. We demonstrate that this problem, known as contamination, can be mitigated by iteratively applying a spatial filter to the detected pixels. Multiple detection and filtering passes can remove nearly all contamination from the background estimates, a vast improvement over single-pass techniques.

  11. Hyperspectral image segmentation using active contours

    NASA Astrophysics Data System (ADS)

    Lee, Cheolha P.; Snyder, Wesley E.

    2004-08-01

    Multispectral or hyperspectral image processing has been studied as a possible approach to automatic target recognition (ATR). Hundreds of spectral bands may provide high data redundancy, compensating the low contrast in medium wavelength infrared (MWIR) and long wavelength infrared (LWIR) images. Thus, the combination of spectral (image intensity) and spatial (geometric feature) information analysis could produce a substantial improvement. Active contours provide segments with continuous boundaries, while edge detectors based on local filtering often provide discontinuous boundaries. The segmentation by active contours depends on geometric feature of the object as well as image intensity. However, the application of active contours to multispectral images has been limited to the cases of simply textured images with low number of frames. This paper presents a supervised active contour model, which is applicable to vector-valued images with non-homogeneous regions and high number of frames. In the training stage, histogram models of target classes are estimated from sample vector-pixels. In the test stage, contours are evolved based on two different metrics: the histogram models of the corresponding segments and the histogram models estimated from sample target vector-pixels. The proposed segmentation method integrates segmentation and model-based pattern matching using supervised segmentation and multi-phase active contour model, while traditional methods apply pattern matching only after the segmentation. The proposed algorithm is implemented with both synthetic and real multispectral images, and shows desirable segmentation and classification results even in images with non-homogeneous regions.

  12. Evaluating the Potential of Satellite Hyperspectral Resurs-P Data for Forest Species Classification

    NASA Astrophysics Data System (ADS)

    Brovkina, O.; Hanuš, J.; Zemek, F.; Mochalov, V.; Grigorieva, O.; Pikla, M.

    2016-06-01

    Satellite-based hyperspectral sensors provide spectroscopic information in relatively narrow contiguous spectral bands over a large area which can be useful in forestry applications. This study evaluates the potential of satellite hyperspectral Resurs-P data for forest species mapping. Firstly, a comparative study between top of canopy reflectance obtained from the Resurs-P, from the airborne hyperspectral scanner CASI and from field measurement (FieldSpec ASD 4) on selected vegetation cover types is conducted. Secondly, Resurs-P data is tested in classification and verification of different forest species compartments. The results demonstrate that satellite hyperspectral Resurs-P sensor can produce useful informational and show good performance for forest species classification comparable both with forestry map and classification from airborne CASI data, but also indicate that developments in pre-processing steps are still required to improve the mapping level.

  13. Compact high-resolution VIS/NIR hyperspectral sensor

    NASA Astrophysics Data System (ADS)

    Hyvärinen, Timo; Herrala, Esko; Procino, Wes; Weatherbee, Oliver

    2011-06-01

    Current hyperspectral imagers are either bulky with good performance, or compact with only moderate performance. This paper presents a new hyperspectral technology which overcomes this drawback, and makes it possible to integrate extremely compact and high performance push-broom hyperspectral imagers for Unmanned Aerial Vehicles (UAV) and other demanding applications. Hyperspectral imagers in VIS/NIR, SWIR, MWIR and LWIR spectral ranges have been implemented. This paper presents the measured performance attributes for a VIS/NIR imager which covers 350 to 1000 nm with spectral resolution of 3 nm. The key innovation is a new imaging spectrograph design which employs both transmissive and reflective optics in order to achieve high light throughput and large spatial image size in an extremely compact format. High light throughput is created by numerical aperture of F/2.4 and high diffraction efficiency. Image distortions are negligible, keystone being <2 um and smile 0.13 nm across the full focal plane image size of 24 mm (spatially) x 6 m (spectrally). The spectrograph is integrated with an advanced camera which provides 1300 spatial pixels and image rate of 160 Hz. A higher resolution version with 2000 spatial pixels will produce up to 100 images/s. The camera achieves, with spectral binning, an outstanding signal-to-noise ratio of 800:1, orders of magnitude higher than any current compact VIS/NIR imager. The imager weighs only 1.4 kg, including fore optics, imaging spectrograph with shutter and camera, in a format optimized for installation in small payload compartments and gimbals. In addition to laboratory characterization, results from a flight test mission are presented.

  14. 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.

  15. A simultaneous dual-band infrared hyperspectral imager for standoff detection

    NASA Astrophysics Data System (ADS)

    Gupta, Neelam; Smith, Dale

    2005-11-01

    A novel dual-band hyperspectral imager has been developed to collect 128-band hyperspectral image cubes simultaneously in both 4-5.25 μm (mid wave IR, MWIR) and 8-10.5 μm (long wave IR, LWIR) bands for both target detection and standoff detection of chemical and biological agents. The imager uses a specially designed diffractive optics Ge lens with a dual-band 320×240 HgCdTe infrared (IR) focal plane array (FPA) cooled with a closed cycle Sterling-cooler. The diffractive optics lens acts both as a focusing as well as a dispersive device. The imager simultaneously collects a single-color full scene image with a narrow band in the LWIR region (e.g., at 8 μm) using the first order diffraction and corresponding single-color image in the MWIR region (e.g., at 4 μm) using the second order diffraction. Images at different wavelengths are obtained by moving the lens along its optical axis to focus the corresponding wavelengths. Contributions of out of focus wavelengths are removed in post processing. In this paper we will briefly discuss the imager and present data and results from a recent field test.

  16. Hyperspectral Image Classification using a Self-Organizing Map

    NASA Technical Reports Server (NTRS)

    Martinez, P.; Gualtieri, J. A.; Aguilar, P. L.; Perez, R. M.; Linaje, M.; Preciado, J. C.; Plaza, A.

    2001-01-01

    The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

  17. Preliminary investigation of submerged aquatic vegetation mapping using hyperspectral remote sensing.

    PubMed

    William, David J; Rybicki, Nancy B; Lombana, Alfonso V; O'Brien, Tim M; Gomez, Richard B

    2003-01-01

    The use of airborne hyperspectral remote sensing imagery for automated mapping of submerged aquatic vegetation (SAV) in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery and field spectrometer measurements were obtained in October of 2000. A spectral library database containing selected ground-based and airborne sensor spectra was developed for use in image processing. The spectral library is used to automate the processing of hyperspectral imagery for potential real-time material identification and mapping. Field based spectra were compared to the airborne imagery using the database to identify and map two species of SAV (Myriophyllum spicatum and Vallisneria americana). Overall accuracy of the vegetation maps derived from hyperspectral imagery was determined by comparison to a product that combined aerial photography and field based sampling at the end of the SAV growing season. The algorithms and databases developed in this study will be useful with the current and forthcoming space-based hyperspectral remote sensing systems. PMID:12620030

  18. Preliminary investigation of submerged aquatic vegetation mapping using hyperspectral remote sensing

    USGS Publications Warehouse

    Williams, D.J.; Rybicki, N.B.; Lombana, A.V.; O'Brien, T. M.; Gomez, R.B.

    2003-01-01

    The use of airborne hyperspectral remote sensing imagery for automated mapping of submerged aquatic vegetation (SAV) in the tidal Potomac River was investigated for near to realtime resource assessment and monitoring. Airborne hyperspectral imagery and field spectrometer measurements were obtained in October of 2000. A spectral library database containing selected ground-based and airborne sensor spectra was developed for use in image processing. The spectral library is used to automate the processing of hyperspectral imagery for potential real-time material identification and mapping. Field based spectra were compared to the airborne imagery using the database to identify and map two species of SAV (Myriophyllum spicatum and Vallisneria americana). Overall accuracy of the vegetation maps derived from hyperspectral imagery was determined by comparison to a product that combined aerial photography and field based sampling at the end of the SAV growing season. The algorithms and databases developed in this study will be useful with the current and forthcoming space-based hyperspectral remote sensing systems.

  19. 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

  20. Comparison of objects detection capabilities in LWIR and THz ranges

    NASA Astrophysics Data System (ADS)

    Kowalski, Marcin; Kastek, Mariusz; Szustakowski, Mieczyslaw

    2015-10-01

    Multispectral systems for detection of concealed dangerous objects are becoming more popular because of their higher effectiveness compared to mono-spectral systems. So far, the problem of detecting objects hidden under clothing was considered only in the case of airports but it is becoming more important for public places like metro stations, and government buildings. Exploration of new spectral bands as well as development of technology result in introduction of new solutions - both mono and multispectral. It has been proved that objects hidden under clothing can be detected and visualized using terahertz (THz) cameras. However, passive THz cameras still offer too low image resolution for objects recognition. Limited range is another issue of passive imagers. On the other hand new infrared cameras offer sufficient parameters to detect objects covered with fabrics in some conditions, as well as high image quality and big pixel resolutions. The purpose of the studies is to investigate and compare the possibilities of using passive cameras operating in long wavelength infrared (LWIR) and THz spectral ranges for detection of concealed objects. For the purpose of investigations, commercial imagers operating in 6.5-11.7 μm and 250GHz (1.25mm) were used. In the article, we present the measurement setup and the results of measurements in various operating conditions. Theoretical studies of both spectral bands focused on detection of objects with passive imagers are also presented.

  1. LWIR pupil imaging and prospects for background compensation

    NASA Astrophysics Data System (ADS)

    LeVan, Paul; Sakoglu, Ünal; Stegall, Mark; Pierce, Greg

    2015-08-01

    A previous paper described LWIR Pupil Imaging with a sensitive, low-flux focal plane array, and behavior of this type of system for higher flux operations as understood at the time. We continue this investigation, and report on a more detailed characterization of the system over a broad range of pixel fluxes. This characterization is then shown to enable non-uniformity correction over the flux range, using a standard approach. Since many commercial tracking platforms include a "guider port" that accepts pulse width modulation (PWM) error signals, we have also investigated a variation on the use of this port to "dither" the tracking platform in synchronization with the continuous collection of infrared images. The resulting capability has a broad range of applications that extend from generating scene motion in the laboratory for quantifying performance of "realtime, scene-based non-uniformity correction" approaches, to effectuating subtraction of bright backgrounds by alternating viewing aspect between a point source and adjacent, source-free backgrounds.

  2. Imaging polarimetry in the LWIR with microgrid polarimeters

    NASA Astrophysics Data System (ADS)

    Tyo, J. S.

    2010-06-01

    Microgrid polarimeters have emerged over the past decade as a viable tool for performing real-time, highly accurate polarimetric imagery. A microgrid polarimeter operates by integrating a focal plane array (FPA) with an array of micropolarizing optics. Mircrogrids have the advantage of being relatively compact, rugged, and inherently spatiotemporally aligned. However, they have the single disadvantage that the various polarization measurements that go into estimating the Stokes parameters at a particular pixel are actually coming from separate locations in the field. Hence, a microgrid polarimeter performs best where there is no image information, obviating the need for an imaging polarimeter! Recently we have been working with a LWIR microgrid polarimeter at the College of Optical Sciences. Our instrument is a DRS Sensors & Targeting Systems 640 x 480 HgCdTe FPA with linear polarizers at 0°, 45°, 90°, and 135° [1]. In this paper we will review our recent results that derive methods for artifact-free reconstruction of band limited imagery.

  3. Polarization visual enhancement technique for LWIR microgrid polarimeter imagery

    NASA Astrophysics Data System (ADS)

    Ratliff, Bradley M.; Tyo, J. Scott; Black, Wiley T.; Boger, James K.; Bowers, David L.

    2008-04-01

    Division of focal plane (DoFP) polarimeters are a particular class of imaging device that consists of an array of micropolarizers integrated upon a focal plane array sensor (FPA). Such devices are also called microgrid polarimeters and have been studied over the past decade with systems being designed and built in all regions of the optical spectrum. These systems are advantageous due to their rugged, compact design and ability to obtain a complete set of polarimetric measurements during a single frame capture. One inherent disadvantage of DoFP systems is that each pixel of the FPA sensor makes a polarized intensity measurement of a different scene point. These spatial measurements are then used to estimate the Stokes vectors across the scene. Since each polarized intensity measurement has a different instantaneous field-of-view (IFOV), artifacts are introduced that can degrade the quality of estimated polarization imagery. Here we develop and demonstrate a visual enhancement technique that is able to reduce false polarization caused by IFOV error while preserving true polarization content within the Stokes parameter images. The technique is straight-forward conceptually and is computationally efficient. All results are presented using data acquired from an actual LWIR microgrid sensor.

  4. Estimation and discrimination of aerosols using multiple wavelength LWIR lidar

    NASA Astrophysics Data System (ADS)

    Warren, Russell E.; Vanderbeek, Richard G.; Ahl, Jeffrey L.

    2010-04-01

    This paper presents an overview of recent work by the Edgewood Chemical Biological Center (ECBC) in algorithm development for parameter estimation and classification of localized atmospheric aerosols using data from rapidly tuned multiple-wavelength range-resolved LWIR lidar. The motivation for this work is the need to detect, locate, and discriminate biological threat aerosols in the atmosphere from interferent materials such as dust and smoke at safe standoff ranges using time-series data collected at a discrete set of CO2 laser wavelengths. The goals of the processing are to provide real-time aerosol detection, localization, and discrimination. Earlier work by the authors has produced an efficient Kalman filter-based algorithm for estimating the range-dependent aerosol concentration and wavelength-dependent backscatter signatures. The latter estimates are used as feature vectors for training support vector machines classifiers for performing the discrimination. Several years of field testing under the Joint Biological Standoff Detection System program at Dugway Proving Ground, UT, Eglin Air Force Base, FL, and other locations have produced data and backscatter estimates from a broad range of biological and interferent aerosol materials for the classifier development. The results of this work are summarized in our presentation.

  5. Polarization in the LWIR: a method to improve target aquisition

    NASA Astrophysics Data System (ADS)

    Aron, Y.; Gronau, Y.

    2005-05-01

    We have shown a method of target acquisition with a high Probability of Detection (Pd), extremely low False Alarm Rate (FAR), which can be implemented in real time hardware existing in most of ELOP's FLIRs. This target acquisition method is based on sensing the linear polarized radiation of the scene and is based on the phenomenon that facets found on most man made targets show a high degree of linear polarization while natural background elements do not. Using this phenomenon (after fixing all the engineering hurdles such as polarizer wobble, etc) can give us a powerful tool for acquiring targets in cluttered backgrounds, where "regular FLIRs", even the most sensitive ones, fail to acquire targets. This phenomenon is most successful where the limiting factor for detection is the clutter, so although lowering scenes SNR (Signal to Noise Ratio), by introducing the polarizer, we get higher SCR (Signal to Clutter Ratio) which is often the real limiting factor in real life. The phenomenon was found to be very robust over different targets and backgrounds in the LWIR and much weaker in the MWIR.

  6. Digital pixel readout integrated circuit architectures for LWIR

    NASA Astrophysics Data System (ADS)

    Shafique, Atia; Yazici, Melik; Kayahan, Huseyin; Ceylan, Omer; Gurbuz, Yasar

    2015-06-01

    This paper presents and discusses digital pixel readout integrated circuit architectures for long wavelength infrared (LWIR) in CMOS technology. Presented architectures are designed for scanning and staring arrays type detectors respectively. For scanning arrays, digital time delay integration (TDI) is implemented on 8 pixels with sampling rate up to 3 using CMOS 180nm technology. Input referred noise of ROIC is below 750 rms electron meanwhile power dissipation is appreciably under 30mW. ROIC design is optimized to perform at room as well as cryogenic temperatures. For staring type arrays, a digital pixel architecture relying on coarse quantization with pulse frequency modulation (PFM) and novel approach of extended integration is presented. It can achieve extreme charge handling capacity of 2.04Ge- with 20 bit output resolution and power dissipation below 350 nW in CMOS 90nm technology. Efficient mechanism of measuring the time to estimate the remaining charge on integration capacitor in order to achieve low SNR has employed.

  7. False-alarm characterization in hyperspectral gas-detection applications

    NASA Astrophysics Data System (ADS)

    DiPietro, Robert S.; Truslow, Eric; Manolakis, Dimitris G.; Golowich, Steven E.; Lockwood, Ronald B.

    2012-09-01

    Chemical cloud detection using long-wave infrared (LWIR) hyperspectral-imaging sensors has many civilian and military applications, including chemical warfare threat mitigation, environmental monitoring, and emergency response. Current capabilities are limited by variation in background clutter as opposed to the physics of photon detection, and this makes the statistical characterization of clutter and clutter-induced false alarms essential to the design of practical systems. In this exploratory work, we use hyperspectral data collected both on the ground and in the air to spectrally and spatially characterize false alarms. Focusing on two widely-used detectors, the matched filter (MF) and the adaptive cosine estimator (ACE), we compare empirical false-alarm rates to their theoretical counterparts - detector output under Gaussian, t and t-mixture distributed data - and show that these models often underestimate false-alarm rates. Next, we threshold real detection maps and show that true detections and false alarms often exhibit very different spatial behavior. To exploit this difference and understand how spatial processing affects performance, the spatial behavior of false alarms must be understood. We take a first step in this direction by showing that, although the behavior may `look' quite random, it is not well captured by the complete-spatial-randomness model. Finally, we describe how our findings impact the design of real detection systems.

  8. Hyperspectral data compression using a Wiener filter predictor

    NASA Astrophysics Data System (ADS)

    Villeneuve, Pierre V.; Beaven, Scott G.; Stocker, Alan D.

    2013-09-01

    The application of compression to hyperspectral image data is a significant technical challenge. A primary bottleneck in disseminating data products to the tactical user community is the limited communication bandwidth between the airborne sensor and the ground station receiver. This report summarizes the newly-developed "Z-Chrome" algorithm for lossless compression of hyperspectral image data. A Wiener filter prediction framework is used as a basis for modeling new image bands from already-encoded bands. The resulting residual errors are then compressed using available state-of-the-art lossless image compression functions. Compression performance is demonstrated using a large number of test data collected over a wide variety of scene content from six different airborne and spaceborne sensors .

  9. 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.

  10. Hyper-Cam automated calibration method for continuous hyperspectral imaging measurements

    NASA Astrophysics Data System (ADS)

    Gagnon, Jean-Philippe; Habte, Zewdu; George, Jacks; Farley, Vincent; Tremblay, Pierre; Chamberland, Martin; Romano, Joao; Rosario, Dalton

    2010-04-01

    The midwave and longwave infrared regions of the electromagnetic spectrum contain rich information which can be captured by hyperspectral sensors thus enabling enhanced detection of targets of interest. A continuous hyperspectral imaging measurement capability operated 24/7 over varying seasons and weather conditions permits the evaluation of hyperspectral imaging for detection of different types of targets in real world environments. Such a measurement site was built at Picatinny Arsenal under the Spectral and Polarimetric Imagery Collection Experiment (SPICE), where two Hyper-Cam hyperspectral imagers are installed at the Precision Armament Laboratory (PAL) and are operated autonomously since Fall of 2009. The Hyper-Cam are currently collecting a complete hyperspectral database that contains the MWIR and LWIR hyperspectral measurements of several targets under day, night, sunny, cloudy, foggy, rainy and snowy conditions. The Telops Hyper-Cam sensor is an imaging spectrometer that enables the spatial and spectral analysis capabilities using a single sensor. It is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides datacubes of up to 320x256 pixels at spectral resolutions of up to 0.25 cm-1. The MWIR version covers the 3 to 5 μm spectral range and the LWIR version covers the 8 to 12 μm spectral range. This paper describes the automated operation of the two Hyper-Cam sensors being used in the SPICE data collection. The Reveal Automation Control Software (RACS) developed collaboratively between Telops, ARDEC, and ARL enables flexible operating parameters and autonomous calibration. Under the RACS software, the Hyper-Cam sensors can autonomously calibrate itself using their internal blackbody targets, and the calibration events are initiated by user defined time intervals and on internal beamsplitter temperature monitoring. The RACS software is the first software developed for

  11. Miniaturization of high spectral spatial resolution hyperspectral imagers on unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Hill, Samuel L.; Clemens, Peter

    2015-06-01

    Traditional airborne environmental monitoring has frequently deployed hyperspectral imaging as a leading tool for characterizing and analyzing a scene's critical spectrum-based signatures for applications in agriculture genomics and crop health, vegetation and mineral monitoring, and hazardous material detection. As the acceptance of hyperspectral evaluation grows in the airborne community, there has been a dramatic trend in moving the technology from use on midsize aircraft to Unmanned Aerial Systems (UAS). The use of UAS accomplishes a number of goals including the reduction in cost to run multiple seasonal evaluations over smaller but highly valuable land-areas, the ability to use frequent data collections to make rapid decisions on land management, and the improvement of spatial resolution by flying at lower altitudes (<500 ft.). Despite this trend, there are several key parameters affecting the use of traditional hyperspectral instruments in UAS with payloads less than 10 lbs. where size, weight and power (SWAP) are critical to how high and how far a given UAS can fly. Additionally, on many of the light-weight UAS, users are frequently trying to capture data from one or more instruments to augment the hyperspectral data collection, thus reducing the amount of SWAP available to the hyperspectral instrumentation. The following manuscript will provide an analysis on a newly-developed miniaturized hyperspectral imaging platform, the Nano-Hyperspec®, which provides full hyperspectral resolution and traditional hyperspectral capabilities without sacrificing performance to accommodate the decreasing SWAP of smaller and smaller UAS platforms. The analysis will examine the Nano-Hyperspec flown in several UAS airborne environments and the correlation of the systems data with LiDAR and other GIS datasets.

  12. The effects of thermal equilibrium and contrast in LWIR polarimetric images.

    PubMed

    Tyo, J Scott; Ratliff, Bradley M; Boger, James K; Black, Wiley T; Bowers, David L; Fetrow, Matthew P

    2007-11-12

    Long-wave infrared (LWIR) polarimetric signatures provide the potential for day-night detection and identification of objects in remotely sensed imagery. The source of optical energy in the LWIR is usually due to thermal emission from the object in question, which makes the signature dependent primarily on the target and not on the external environment. In this paper we explore the impact of thermal equilibrium and the temperature of (unseen) background objects on LWIR polarimetric signatures. We demonstrate that an object can completely lose its polarization signature when it is in thermal equilibrium with its optical background, even if it has thermal contrast with the objects that appear behind it in the image. PMID:19550799

  13. High-g launch testing of a low-cost un-cooled LWIR imager

    NASA Astrophysics Data System (ADS)

    Tiffany, Jason; Brown, F. Christophe; Manning, Kyle; Kellermeyer, William; King, Don; Drewry, David

    2014-06-01

    Unmanned aerial vehicles (UAVs) and smart munitions require low-cost IR sensors that fit within very small volumes, yet offer acceptable performance and landing/launch survivability. The LWIR band provides unique contrast for specific applications in both UAVs and smart munitions, with smart munitions presenting an additional challenge of high g-loads during launch. These high g-loads are not typically a design target of low-cost, un-cooled commercial off the shelf (COTS) LWIR sensors. This work addresses the challenges of adapting a COTS un-cooled LWIR imager for launch survivability. The sensor was modeled for mechanical stability and weaknesses identified. Modifications were made to improve launch survivability and multiple units were tested. Data is presented on the optical performance as measured through the modulation transfer function (MTF) both before and after launches for multiple locations across the lens.

  14. 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.

  15. Ore minerals textural characterization by hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Bonifazi, Giuseppe; Picone, Nicoletta; Serranti, Silvia

    2013-02-01

    The utilization of hyperspectral detection devices, for natural resources mapping/exploitation through remote sensing techniques, dates back to the early 1970s. From the first devices utilizing a one-dimensional profile spectrometer, HyperSpectral Imaging (HSI) devices have been developed. Thus, from specific-customized devices, originally developed by Governmental Agencies (e.g. NASA, specialized research labs, etc.), a lot of HSI based equipment are today available at commercial level. Parallel to this huge increase of hyperspectral systems development/manufacturing, addressed to airborne application, a strong increase also occurred in developing HSI based devices for "ground" utilization that is sensing units able to play inside a laboratory, a processing plant and/or in an open field. Thanks to this diffusion more and more applications have been developed and tested in this last years also in the materials sectors. Such an approach, when successful, is quite challenging being usually reliable, robust and characterised by lower costs if compared with those usually associated to commonly applied analytical off- and/or on-line analytical approaches. In this paper such an approach is presented with reference to ore minerals characterization. According to the different phases and stages of ore minerals and products characterization, and starting from the analyses of the detected hyperspectral firms, it is possible to derive useful information about mineral flow stream properties and their physical-chemical attributes. This last aspect can be utilized to define innovative process mineralogy strategies and to implement on-line procedures at processing level. The present study discusses the effects related to the adoption of different hardware configurations, the utilization of different logics to perform the analysis and the selection of different algorithms according to the different characterization, inspection and quality control actions to apply.

  16. Mitigation of image artifacts in LWIR microgrid polarimeter images

    NASA Astrophysics Data System (ADS)

    Ratliff, Bradley M.; Tyo, J. Scott; Boger, James K.; Black, Wiley T.; Bowers, David M.; Kumar, Rakesh

    2007-09-01

    Microgrid polarimeters, also known as division of focal plane (DoFP) polarimeters, are composed of an integrated array of micropolarizing elements that immediately precedes the FPA. The result of the DoFP device is that neighboring pixels sense different polarization states. The measurements made at each pixel can be combined to estimate the Stokes vector at every reconstruction point in a scene. DoFP devices have the advantage that they are mechanically rugged and inherently optically aligned. However, they suffer from the severe disadvantage that the neighboring pixels that make up the Stokes vector estimates have different instantaneous fields of view (IFOV). This IFOV error leads to spatial differencing that causes false polarization signatures, especially in regions of the image where the scene changes rapidly in space. Furthermore, when the polarimeter is operating in the LWIR, the FPA has inherent response problems such as nonuniformity and dead pixels that make the false polarization problem that much worse. In this paper, we present methods that use spatial information from the scene to mitigate two of the biggest problems that confront DoFP devices. The first is a polarimetric dead pixel replacement (DPR) scheme, and the second is a reconstruction method that chooses the most appropriate polarimetric interpolation scheme for each particular pixel in the image based on the scene properties. We have found that these two methods can greatly improve both the visual appearance of polarization products as well as the accuracy of the polarization estimates, and can be implemented with minimal computational cost.

  17. Swap intensified WDR CMOS module for I2/LWIR fusion

    NASA Astrophysics Data System (ADS)

    Ni, Yang; Noguier, Vincent

    2015-05-01

    The combination of high resolution visible-near-infrared low light sensor and moderate resolution uncooled thermal sensor provides an efficient way for multi-task night vision. Tremendous progress has been made on uncooled thermal sensors (a-Si, VOx, etc.). It's possible to make a miniature uncooled thermal camera module in a tiny 1cm3 cube with <1W power consumption. For silicon based solid-state low light CCD/CMOS sensors have observed also a constant progress in terms of readout noise, dark current, resolution and frame rate. In contrast to thermal sensing which is intrinsic day&night operational, the silicon based solid-state sensors are not yet capable to do the night vision performance required by defense and critical surveillance applications. Readout noise, dark current are 2 major obstacles. The low dynamic range at high sensitivity mode of silicon sensors is also an important limiting factor, which leads to recognition failure due to local or global saturations & blooming. In this context, the image intensifier based solution is still attractive for the following reasons: 1) high gain and ultra-low dark current; 2) wide dynamic range and 3) ultra-low power consumption. With high electron gain and ultra low dark current of image intensifier, the only requirement on the silicon image pickup device are resolution, dynamic range and power consumption. In this paper, we present a SWAP intensified Wide Dynamic Range CMOS module for night vision applications, especially for I2/LWIR fusion. This module is based on a dedicated CMOS image sensor using solar-cell mode photodiode logarithmic pixel design which covers a huge dynamic range (> 140dB) without saturation and blooming. The ultra-wide dynamic range image from this new generation logarithmic sensor can be used directly without any image processing and provide an instant light accommodation. The complete module is slightly bigger than a simple ANVIS format I2 tube with <500mW power consumption.

  18. Development of a Random Field Model for Gas Plume Detection in Multiple LWIR Images.

    SciTech Connect

    Heasler, Patrick G.

    2008-09-30

    This report develops a random field model that describes gas plumes in LWIR remote sensing images. The random field model serves as a prior distribution that can be combined with LWIR data to produce a posterior that determines the probability that a gas plume exists in the scene and also maps the most probable location of any plume. The random field model is intended to work with a single pixel regression estimator--a regression model that estimates gas concentration on an individual pixel basis.

  19. Handheld hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Saari, Heikki; Aallos, Ville-Veikko; Holmlund, Christer; Malinen, Jouko; Mäkynen, Jussi

    2010-04-01

    VTT Technical Research Centre of Finland has developed a new low cost hand-held staring hyperspectral imager for applications previously blocked by high cost of the instrumentation. The system is compatible with standard video and microscope lenses. The instrument can record 2D spatial images at several wavelength bands simultaneously. The concept of the hyperspectral imager has been published in SPIE Proc. 7474. The prototype fits in an envelope of 100 mm x 60 mm x 40 mm and its weight is ca. 300 g. The benefits of the new device compared to Acousto-Optic Tunable filter (AOTF) or Liquid Crystal Tunable Filter (LCTF) devices are small size and weight, speed of wavelength tuning, high optical throughput, independence of polarization state of incoming light and capability to record three wavelengths simultaneously. The operational wavelength range with Silicon-based CCD or CMOS sensors is 200 - 1100 nm and spectral resolution is 2 - 10 nm @ FWHM. Similar IR imagers can be built using InGaAs, InSb or MCT imaging sensors. The spatial resolution of the prototype is 480 x 750 pixels. It contains control system and memory for the image data acquisition. It operates either autonomously recording hyperspectral data cubes continuously or controlled by a laptop computer. The prototype was configured as a hyperspectral microscope for the spectral range 400 - 700 nm. The design of the hyperspectral imager, characterization results and sample measurement results are presented.

  20. Bobcat 2013: a hyperspectral data collection supporting the development and evaluation of spatial-spectral algorithms

    NASA Astrophysics Data System (ADS)

    Kaufman, Jason; Celenk, Mehmet; White, A. K.; Stocker, Alan D.

    2014-06-01

    The amount of hyperspectral imagery (HSI) data currently available is relatively small compared to other imaging modalities, and what is suitable for developing, testing, and evaluating spatial-spectral algorithms is virtually nonexistent. In this work, a significant amount of coincident airborne hyperspectral and high spatial resolution panchromatic imagery that supports the advancement of spatial-spectral feature extraction algorithms was collected to address this need. The imagery was collected in April 2013 for Ohio University by the Civil Air Patrol, with their Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) sensor. The target materials, shapes, and movements throughout the collection area were chosen such that evaluation of change detection algorithms, atmospheric compensation techniques, image fusion methods, and material detection and identification algorithms is possible. This paper describes the collection plan, data acquisition, and initial analysis of the collected imagery.

  1. COUPLING HYPERSPECTRAL REMOTE SENSING WITH FIELD SPECTROMETRY TO MONITOR INLAND WATER QUALITY PARAMETERS

    EPA Science Inventory

    Visible to near-infrared, airborne hyperspectral data were successfully used to estimate water quality parameters such as chlorophyll a, turbidity and total phosphorus from the Great Miami River, Ohio. During the summer of 1999, spectral data were collected with a hand-held fiel...

  2. Comparison of hyperspectral imagery with aerial photography and multispectral imagery for mapping broom snakeweed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Broom snakeweed [Gutierrezia sarothrae (Pursh.) Britt. and Rusby] is one of the most widespread and abundant rangeland weeds in western North America. The objectives of this study were to evaluate airborne hyperspectral imagery and compare it with aerial color-infrared (CIR) photography and multispe...

  3. Characterization of forest crops with a range of nutrient and water treatments using AISA Hyperspectral Imagery.

    SciTech Connect

    Gong, Binglei; Im, Jungho; Jensen, John, R.; Coleman, Mark; Rhee, Jinyoung; Nelson, Eric

    2012-07-01

    This research examined the utility of Airborne Imaging Spectrometer for Applications (AISA) hyperspectral imagery for estimating the biomass of three forest crops---sycamore, sweetgum and loblolly pine--planted in experimental plots with a range of fertilization and irrigation treatments on the Savannah River Site near Aiken, South Carolina.

  4. Hyperspectral remote sensing and geospatial modeling for monitoring invasive plant species

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing is used to show the actual distribution of distinctive invasive weeds such as leafy spurge (Euphorbia esula L.), whereas landscape modeling can show the potential distribution over an area. Geographic information system data and hyperspectral imagery [NASA JPL’s Airborne Visible Infra...

  5. Comparative performance of large-format MWIR and LWIR systems in NV-IPM

    NASA Astrophysics Data System (ADS)

    Burdette, Edward M.; Teague, James R.; Dobbins, Christopher L.; Wood, Samuel B.

    2015-05-01

    This report describes tasks comparing the simulated performance levels of infrared (IR) sensing systems in detecting, recognizing, and identifying (DRI) targets using the Night Vision Integrated Performance Model (NV-IPM) version 1.1. Both mid-wave infrared (MWIR) and long-wave infrared (LWIR) systems, chosen to represent the current state-of-the-art, were analyzed across various environmental conditions. These states included a range of both man-made and natural obscurants, selected to simulate atmospheric conditions commonly experienced throughout the world. This report investigates the validity of the NV-IPM, down-selects top-performing systems from an original set, and provides detailed performance analysis of these best-of-breed systems in various environmental scenarios. Six sensing systems, Indium-Antimonide (InSb) MWIR, Mercury-Cadmium-Telluride (MCT) MWIR, nBn InSb MWIR, Quantum Well Infrared Photodetector (QWIP) LWIR, uncooled LWIR, and dual-band MCT MWIR/LWIR system, were evaluated against a variety of environmental variations. Specifications for the IR systems were obtained from manufacturers or relevant published literature. Simulation results indicated the nBn InSb MWIR system as the strongest-performing system in many of the tests.

  6. 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.

  7. Hyperspectral bands prediction based on inter-band spectral correlation structure

    NASA Astrophysics Data System (ADS)

    Ahmed, Ayman M.; Sharkawy, Mohamed El.; Elramly, Salwa H.

    2013-02-01

    Hyperspectral imaging has been widely studied in many applications; notably in climate changes, vegetation, and desert studies. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and spaceborne imaging. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we analyze the spectral cross correlation between bands for AVIRIS and Hyperion hyperspectral data; spectral cross correlation matrix is calculated, assessing the strength of the spectral matrix, we propose new technique to find highly correlated groups of bands in the hyperspectral data cube based on "inter band correlation square", and finally, we propose a new technique of band regrouping based on correlation values weights for different group of bands as network of correlation.

  8. Research on method of geometry and spectral calibration of pushbroom dispersive hyperspectral imager

    NASA Astrophysics Data System (ADS)

    He, Zhiping; Shu, Rong; Wang, Jianyu

    2012-11-01

    Development and application of airborne and aerospace hyperspectral imager press for high precision geometry and spectral calibration of pixels of image cube. The research of geometry and spectral calibration of pushbroom hyperspectral imager, its target is giving the coordinate of angle field of view and center wavelength of each detect unit in focal plane detector of hyperspectral imager, and achieves the high precision, full field of view, full channel geometry and spectral calibration. It is importance for imaging quantitative and deep application of hyperspectal imager. The paper takes the geometry and spectral calibration of pushbroom dispersive hyperspectral imager as case study, and research on the constitution and analysis of imaging mathematical model. Aimed especially at grating-dispersive hyperspectral imaging, the specialty of the imaging mode and dispersive method has been concretely analyzed. Based on the analysis, the theory and feasible method of geometry and spectral calibration of dispersive hyperspectral imager is set up. The key technique has been solved is As follows: 1). the imaging mathematical model and feasible method of geometry and spectral calibration for full pixels of image cube has been set up, the feasibility of the calibration method has been analyzed. 2). the engineering model and method of the geometry and spectral calibration of pushbroom dispersive hyperspectral imager has been set up and the calibration equipment has been constructed, and the calibration precision has been analyzed.

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. Airborne change detection system for the detection of route mines

    NASA Astrophysics Data System (ADS)

    Donzelli, Thomas P.; Jackson, Larry; Yeshnik, Mark; Petty, Thomas E.

    2003-09-01

    The US Army is interested in technologies that will enable it to maintain the free flow of traffic along routes such as Main Supply Routes (MSRs). Mines emplaced in the road by enemy forces under cover of darkness represent a major threat to maintaining a rapid Operational Tempo (OPTEMPO) along such routes. One technique that shows promise for detecting enemy mining activity is Airborne Change Detection, which allows an operator to detect suspicious day-to-day changes in and around the road that may be indicative of enemy mining. This paper presents an Airborne Change Detection that is currently under development at the US Army Night Vision and Electronic Sensors Directorate (NVESD). The system has been tested using a longwave infrared (LWIR) sensor on a vertical take-off and landing unmanned aerial vehicle (VTOL UAV) and a midwave infrared (MWIR) sensor on a fixed wing aircraft. The system is described and results of the various tests conducted to date are presented.

  14. a Comparison of LIDAR Reflectance and Radiometrically Calibrated Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Roncat, A.; Briese, C.; Pfeifer, N.

    2016-06-01

    In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration. While this calibration, aiming at the derivation of physically meaningful surface attributes such as a reflectance value, is quite cumbersome for passively sensed data and relies on a number of external parameters, the situation is by far less complicated for active remote sensing techniques such as lidar. This fact motivates the investigation of the suitability of full-waveform lidar as a "single-wavelength reflectometer" to support radiometric calibration of hyperspectral imagery. In this paper, this suitability was investigated by means of an airborne hyperspectral imagery campaign and an airborne lidar campaign recorded over the same area. Criteria are given to assess diffuse reflectance behaviour; the distribution of reflectance derived by the two techniques were found comparable in four test areas where these criteria were met. This is a promising result especially in the context of current developments of multi-spectral lidar systems.

  15. 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.

  16. Effectiveness of airborne multispectral thermal data for karst groundwater resources recognition in coastal areas

    NASA Astrophysics Data System (ADS)

    Pignatti, Stefano; Fusilli, Lorenzo; Palombo, Angelo; Santini, Federico; Pascucci, Simone

    2013-04-01

    attitude system data and public domain GPS stream (ASI-GeoDAF). Annals of Geophysics, 49 (1), pp. 11-19. Pascucci S., Bassani C., Palombo A., Poscolieri M., Cavalli R. 2008. Road Asphalt Pavements Analyzed by Airborne Thermal Remote Sensing: Preliminary Results of the Venice Highway. Sensors 2008, 8(2), 1278-1296; doi:10.3390/s8021278. Pignatti, S.; Lapenna, V.; Palombo, A.; Pascucci, S.; Pergola, N.; Cuomo, V. 2011. An advanced tool of the CNR IMAA EO facilities: Overview of the TASI-600 hyperspectral thermal spectrometer. 3rd Hyperspectral Image and Signal Processing: Evolution in Remote Sensing Conference (WHISPERS), 2011; DOI 10.1109/WHISPERS.2011.6080890. Johnson, B. R. and S. J. Young, 1998. In-Scene Atmospheric Compensation: Application to SEBASS Data Collected at the ARM Site. Technical Report, Space and Environment Technology Center, The Aerospace Corporation, May 1998. Z.L. Li, F. Becker, M.P Stoll and Z. Wan. 1999. Evaluation of six methods for extracting relative emissivity spectra from thermal infrared images. Remote Sensing of Environment, vol. 69, 197-214.

  17. FPGA-based architecture for hyperspectral endmember extraction

    NASA Astrophysics Data System (ADS)

    Rosário, João.; Nascimento, José M. P.; Véstias, Mário

    2014-10-01

    Hyperspectral instruments have been incorporated in satellite missions, providing data of high spectral resolution of the Earth. This data can be used in remote sensing applications, such as, target detection, hazard prevention, and monitoring oil spills, among others. In most of these applications, one of the requirements of paramount importance is the ability to give real-time or near real-time response. Recently, onboard processing systems have emerged, in order to overcome the huge amount of data to transfer from the satellite to the ground station, and thus, avoiding delays between hyperspectral image acquisition and its interpretation. For this purpose, compact reconfigurable hardware modules, such as field programmable gate arrays (FPGAs) are widely used. This paper proposes a parallel FPGA-based architecture for endmember's signature extraction. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data sets collected by the NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Cuprite mining district in Nevada. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems, opening new perspectives for onboard hyperspectral image processing.

  18. 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.

  19. Hyperspectral trace gas detection using the wavelet packet transform

    NASA Astrophysics Data System (ADS)

    Salvador, Mark Z.; Resmini, Ronald G.; Gomez, Richard B.

    2008-04-01

    A method for trace gas detection in hyperspectral data is demonstrated using the wavelet packet transform. This new method, the Wavelet Packet Subspace (WPS), applies the wavelet packet transform and selects a best basis for pattern matching. The wavelet packet transform is an extension of the wavelet transform, which fully decomposes a signal into a library of wavelet packet bases. Application of the wavelet packet transform to hyperspectral data for the detection of trace gases takes advantage of the ability of the wavelet transform to locate spectral features in both scale and location. By analyzing the wavelet packet tree of specific gas, nodes of the tree are selected which represent an orthogonal best basis. The best basis represents the significant spectral features of that gas. This is then used to identify pixels in the scene using existing matching algorithms such as spectral angle or matched filter. Using data from the Airborne Hyperspectral Imager (AHI), this method is compared to traditional matched filter detection methods. Initial results demonstrate a promising wavelet packet subspace technique for hyperspectral trace gas detection applications.

  20. Nonlinear Bayesian Algorithms for Gas Plume Detection and Estimation from Hyper-spectral Thermal Image Data

    PubMed Central

    Heasler, Patrick; Posse, Christian; Hylden, Jeff; Anderson, Kevin

    2007-01-01

    This paper presents a nonlinear Bayesian regression algorithm for detecting and estimating gas plume content from hyper-spectral data. Remote sensing data, by its very nature, is collected under less controlled conditions than laboratory data. As a result, the physics-based model that is used to describe the relationship between the observed remote-sensing spectra, and the terrestrial (or atmospheric) parameters that are estimated is typically littered with many unknown “nuisance” parameters. Bayesian methods are well-suited for this context as they automatically incorporate the uncertainties associated with all nuisance parameters into the error estimates of the parameters of interest. The nonlinear Bayesian regression methodology is illustrated on simulated data from a three-layer model for longwave infrared (LWIR) measurements from a passive instrument. The generated LWIR scenes contain plumes of varying intensities, and this allows estimation uncertainty and probability of detection to be quantified. The results show that this approach should permit more accurate estimation as well as a more reasonable description of estimate uncertainty. Specifically, the methodology produces a standard error that is more realistic than that produced by matched filter estimation.

  1. 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

  2. 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.

  3. Hyperspectral air-to-air seeker

    NASA Astrophysics Data System (ADS)

    Gat, Nahum; Barhen, Jacob; Gulati, Sandeep; Steiner, Todd D.

    1994-07-01

    Synthetic hyperspectral signatures representing an airborne target engine radiation, a decoy flare, and the engine plume radiation are used to demonstrate computational techniques for the discrimination between such objects. Excellent discrimination is achieved for a `single look' at SNR of -10 dB. Since the atmospheric transmittance perturbs the signature of all objects in an identical fashion, the transmittance is equivalent to a modulation of the target radiance (in the spectral domain). The proper spectral signal decomposition may, therefore, recover the original unperturbed signature accurately enough to allow discrimination. The algorithms described here, and in two accompanying papers, have been tested over the spectral range that includes the VNIR and MWIR and are most appropriate for an intelligent, autonomous, air-to-air or surface-to-air guided munitions. With additional enhancements, the techniques apply to ground targets and other dual-use applications.

  4. A new hyperspectral dataset and some challenges

    NASA Astrophysics Data System (ADS)

    Wadströmer, Niclas; Ahlberg, Jörgen; Svensson, Thomas

    2010-04-01

    We present a new hyperspectral data set that FOI will keep publicly available. The hyperspectral data set was collected in an airborne measurement over the countryside. The spectral resolution was about 10 nm which allowed registrations in 60 spectral bands in the visual and near infrared range (390-960 nm). Objects with various signature properties were placed in three areas: the edge of a wood, an open field and a rough open terrain. Several overflights were performed over the areas. Between the overflights some of the objects were moved, representing different scenarios. Our interest is primarily in anomaly detection of man-made objects placed in nature where no such objects are expected. The objects in the trial were military and civilian vehicles, boards of different size and a camouflage net. The size of the boards range from multipixel to subpixel size. Due to wind and cloud conditions the stability and the flight height of the airplane vary between the overflights, which makes the analysis extra challenging.

  5. 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.

  6. The Hyperspectral Thermal Emission Spectrometer (HyTES): Preliminary Results

    NASA Technical Reports Server (NTRS)

    Hook, Simon; Johnson, William R.; Eng, Bjorn T.; Gunapala, Sarah D.; Lamborn, Andrew U.; Mouroulis, Pantazis, Z.; Mouroulis, Pantazis, Z.; Paine, Christopher G.; Soibel, Alexander; Wilson, Daniel W.

    2011-01-01

    The Hyperspectral Thermal Emission Spectrometer (HyTES) is being developed as part of the risk reduction activities associated with the Hyperspectral Infrared Imager (HyspIRI). HyspIRI is one of the Tier 2 Decadal Survey Missions. HyTES will provide information on how to place the filters on the HyspIRI Thermal Infrared Instrument (TIR) as well as provide antecedent science data. The pushbroom design has 512 spatial pixels over a 50-degree field of view and 256 spectral channels between 7.5 micrometers to 12 micrometers. HyTES includes many key enabling state-of-the-art technologies including a high performance convex diffraction grating, a quantum well infrared photodetector (QWIP) focal plane array, and a compact Dyson-inspired optical design. The Dyson optical design allows for a very compact and optically fast system (F/1.6). It also minimizes cooling requirements due to the fact it has a single monolithic prism-like grating design which allows baffling for stray light suppression. The monolithic configuration eases mechanical tolerancing requirements which are a concern since the complete optical assembly is operated at cryogenic temperatures ((is) approximately 100K). The QWIP allows for optimum spatial and spectral uniformity and provides adequate responsivity or D-star to allow 200mK noise equivalent temperature difference (NEDT) operation across the LWIR passband. Assembly of the system is nearly complete. After completion, alignment results will be presented which show low keystone and smile distortion. This is required to minimize spatial-spectral mixing between adjacent spectral channels and spatial positions. Predictions show the system will have adequate signal to noise for laboratory calibration targets.

  7. A low cost thermal infrared hyperspectral imager for small satellites

    NASA Astrophysics Data System (ADS)

    Crites, S. T.; Lucey, P. G.; Wright, R.; Garbeil, H.; Horton, K. A.

    2011-06-01

    The traditional model for space-based earth observations involves long mission times, high cost, and long development time. Because of the significant time and monetary investment required, riskier instrument development missions or those with very specific scientific goals are unlikely to successfully obtain funding. However, a niche for earth observations exploiting new technologies in focused, short lifetime missions is opening with the growth of the small satellite market and launch opportunities for these satellites. These low-cost, short-lived missions provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off the shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCOR), to demonstrate the ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power efficient thermal hyperspectral imager with electronics contained in a pressure vessel to enable the use of COTS electronics, and will be compatible with small satellite platforms. The sensor, called Thermal Hyperspectral Imager (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230-meter pixels with 20 wavenumber spectral resolution from a 400-km orbit.

  8. Fourth Airborne Geoscience Workshop

    NASA Technical Reports Server (NTRS)

    1991-01-01

    The focus of the workshop was on how the airborne community can assist in achieving the goals of the Global Change Research Program. The many activities that employ airborne platforms and sensors were discussed: platforms and instrument development; airborne oceanography; lidar research; SAR measurements; Doppler radar; laser measurements; cloud physics; airborne experiments; airborne microwave measurements; and airborne data collection.

  9. Multiple Spectral-Spatial Classification Approach for Hyperspectral Data

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

    A .new multiple classifier approach for spectral-spatial classification of hyperspectral images is proposed. Several classifiers are used independently to classify an image. For every pixel, if all the classifiers have assigned this pixel to the same class, the pixel is kept as a marker, i.e., a seed of the spatial region, with the corresponding class label. We propose to use spectral-spatial classifiers at the preliminary step of the marker selection procedure, each of them combining the results of a pixel-wise classification and a segmentation map. Different segmentation methods based on dissimilar principles lead to different classification results. Furthermore, a minimum spanning forest is built, where each tree is rooted on a classification -driven marker and forms a region in the spectral -spatial classification: map. Experimental results are presented for two hyperspectral airborne images. The proposed method significantly improves classification accuracies, when compared to previously proposed classification techniques.

  10. Low-Complexity Adaptive Lossless Compression of Hyperspectral Imagery

    NASA Technical Reports Server (NTRS)

    Klimesh, Matthew

    2006-01-01

    A low-complexity, adaptive predictive technique for lossless compression of hyperspectral imagery is described. This technique is designed to be suitable for implementation in hardware such as a field programmable gate array (FPGA); such an implementation could be used for high-speed compression of hyperspectral imagery onboard a spacecraft. The predictive step of the technique makes use of the sign algorithm, which is a relative of the least mean square (LMS) algorithm from the field of low-complexity adaptive filtering. The compressed data stream consists of prediction residuals encoded using a method similar to that of the JPEG-LS lossless image compression standard. Compression results are presented for several datasets including some raw Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS) datasets and raw Atmospheric Infrared Sounder (AIRS) datasets. The compression effectiveness obtained with the technique is competitive with that of the best of previously described techniques with similar complexity.

  11. Application of hyperspectral infrared analysis of hydrothermal alteration on Earth and Mars.

    PubMed

    Thomas, Matilda; Walter, Malcolm R

    2002-01-01

    An integrated analysis of both airborne and field short-wave infrared hyperspectral measurements was used in conjunction with conventional field mapping techniques to map hydrothermal alteration in the central portion of the Mount Painter Inlier in the Flinders Ranges, South Australia. The airborne hyperspectral data show the spatial distribution of spectrally distinct minerals occurring as primary minerals and as weathering and alteration products. Field spectral measurements, taken with a portable infrared mineral analyzer spectrometer and supported by thin-section analyses, were used to verify the mineral maps and enhance the level of information obtainable from the airborne data. Hydrothermal alteration zones were identified and mapped separately from the background weathering signals. A main zone of alteration, coinciding with the Paralana Fault zone, was recognized, and found to contain kaolinite, muscovite, biotite, and K-feldspar. A small spectral variation associated with a ring-like feature around Mount Painter was tentatively determined to be halloysite and interpreted to represent a separate hydrothermal fluid and fluid source, and probably a separate system. The older parts of the alteration system are tentatively dated as Permo-Carboniferous. The remote sensing of alteration at Mount Painter confirms that hyperspectral imaging techniques can produce accurate mineralogical maps with significant details that can be used to identify and map hydrothermal activity. Application of hyperspectral surveys such as that conducted at Mount Painter would be likely to provide similar detail about putative hydrothermal deposits on Mars. PMID:12530243

  12. Hyperspectral sensors and the conservation of monumental buildings

    NASA Astrophysics Data System (ADS)

    Camaiti, Mara; Benvenuti, Marco; Chiarantini, Leandro; Costagliola, Pilar; Moretti, Sandro; Paba, Francesca; Pecchioni, Elena; Vettori, Silvia

    2010-05-01

    The continuous control of the conservation state of outdoor materials is a good practice for timely planning conservative interventions and therefore to preserve historical buildings. The monitoring of surfaces composition, in order to characterize compounds of neo-formation and deposition, by traditional diagnostic campaigns, although gives accurate results, is a long and expensive method, and often micro-destructive analyses are required. On the other hand, hyperspectral analysis in the visible and near infrared (VNIR) region is a very common technique for determining the characteristics and properties of soils, air, and water in consideration of its capability to give information in a rapid, simultaneous and not-destructive way. VNIR Hypespectral analysis, which discriminate materials on the basis of their different patterns of absorption at specific wavelengths, are in fact successfully used for identifying minerals and rocks (1), as well as for detecting soil properties including moisture, organic content and salinity (2). Among the existing VNIR techniques (Laboratory Spectroscopy - LS, Portable Spectroscopy - PS and Imaging Spectroscopy - IS), PS and IS can play a crucial role in the characterization of components of exposed stone surfaces. In particular, the Imaging Spectroscopic (remote sensing), which uses sensors placed both on land or airborne, may contribute to the monitoring of large areas in consideration of its ability to produce large areal maps at relatively low costs. In this presentation the application of hyperspectral instruments (mainly PS and IS, not applied before in the field of monumental building diagnostic) to quantify the degradation of carbonate surfaces will be discussed. In particular, considering gypsum as the precursor symptom of damage, many factors which may affect the estimation of gypsum content on the surface will be taken into consideration. Two hyperspectral sensors will be considered: 1) A portable radiometer (ASD

  13. Hyperspectral sensors and the conservation of monumental buildings

    NASA Astrophysics Data System (ADS)

    Camaiti, Mara; Benvenuti, Marco; Chiarantini, Leandro; Costagliola, Pilar; Moretti, Sandro; Paba, Francesca; Pecchioni, Elena; Vettori, Silvia

    2010-05-01

    The continuous control of the conservation state of outdoor materials is a good practice for timely planning conservative interventions and therefore to preserve historical buildings. The monitoring of surfaces composition, in order to characterize compounds of neo-formation and deposition, by traditional diagnostic campaigns, although gives accurate results, is a long and expensive method, and often micro-destructive analyses are required. On the other hand, hyperspectral analysis in the visible and near infrared (VNIR) region is a very common technique for determining the characteristics and properties of soils, air, and water in consideration of its capability to give information in a rapid, simultaneous and not-destructive way. VNIR Hypespectral analysis, which discriminate materials on the basis of their different patterns of absorption at specific wavelengths, are in fact successfully used for identifying minerals and rocks (1), as well as for detecting soil properties including moisture, organic content and salinity (2). Among the existing VNIR techniques (Laboratory Spectroscopy - LS, Portable Spectroscopy - PS and Imaging Spectroscopy - IS), PS and IS can play a crucial role in the characterization of components of exposed stone surfaces. In particular, the Imaging Spectroscopic (remote sensing), which uses sensors placed both on land or airborne, may contribute to the monitoring of large areas in consideration of its ability to produce large areal maps at relatively low costs. In this presentation the application of hyperspectral instruments (mainly PS and IS, not applied before in the field of monumental building diagnostic) to quantify the degradation of carbonate surfaces will be discussed. In particular, considering gypsum as the precursor symptom of damage, many factors which may affect the estimation of gypsum content on the surface will be taken into consideration. Two hyperspectral sensors will be considered: 1) A portable radiometer (ASD

  14. Correlation of environmental data measurements with polarimetric LWIR sensor measurements of manmade objects in natural clutter

    NASA Astrophysics Data System (ADS)

    McCarthy, James; Woolley, Mark; Roth, Luz

    2010-04-01

    In recent years there has been an increased interest in using polarimetric imaging sensors for terrestrial remote sensing applications because of their ability to discriminate manmade objects in a natural clutter background. However, adverse weather limits the performance of these sensors. Long Wave Infrared (LWIR) polarimetric sensor data of a scene containing manmade objects in a natural clutter background is compared with simultaneously collected environmental data. In this paper, a metric is constructed from the Stokes parameter S1 and is correlated with some environmental channels. There are differences in the correlation outputs, with the sensor data metric positively correlated with some environmental channels, negatively correlated with some channels and uncorrelated with other channels. Results from real data measurements are presented and interpreted. An uncooled LWIR sensor using an achromatic retarder to capture the polarimetric states performed the data collection. The environmental channels include various meteorological channels, radiation loading and soil properties.

  15. Variation in MidIR and LWIR polarimetric imagery due to diurnal and meteorological impacts

    NASA Astrophysics Data System (ADS)

    Gurton, Kristan P.; Felton, Melvin

    2008-04-01

    We present radiometric and polarimetric calibrated imagery recorded in both the mid-wave IR (MidIR) and long wave IR (LWIR) as a function diurnal variation over several multiday periods. We compare differences in polarimetric and conventional thermal imagry for both IR atmospheric transmission windows, i.e., 3-5μm and 8-12 μm regions. Meteorological parameters measured during the study include temperature, relative-humidity, wind-speed/direction, precipitation, and ambient atmospheric IR loading. The two camera systems used in the study differed significantly in design. The LWIR polarimetric sensor utilizes a spinning achromatic retarder and is best suited for static scenes, while the MidIR system is based on a division-of-aperture design and is capable of recording polarimetric imagery of targets that are rapidly moving. Examples of both S0 (conventional thermal) and degree-of-linear polarization (DOLP) imagery are presented and compared.

  16. MICROCARD: a micro-camera based on a circular diffraction grating for MWIR and LWIR imagery

    NASA Astrophysics Data System (ADS)

    Druart, Guillaume; Guérineau, Nicolas; Tauvy, Michel; Rommeluère, Sylvain; Primot, Jérôme; Deschamps, Joël; Fendler, Manuel; Cigna, Jean-Charles; Taboury, Jean

    2008-09-01

    Circular diffraction gratings (also called diffractive axicons) are optical components producing achromatic non-diffracting beams. They thus produce a focal line rather than a focal point for classical lenses. We have recently shown in the visible spectral range that this property can be used to design a simple imaging system with a long depth of focus and a linear variable zoom by using and translating a diffractive axicon as the only component. We have then adapted this principle for the mid-wavelength infrared (MWIR) spectral range and the long-wavelength infrared (LWIR) spectral range. A LWIR low-cost micro-camera, called MICROCARD, has been designed and realized. First images from this camera will be shown. Moreover a way to design a compact MWIR micro-camera with moveable parts integrated directly into the cryostat will be presented.

  17. Airborne laser

    NASA Astrophysics Data System (ADS)

    Lamberson, Steven E.

    2002-06-01

    The US Air Force Airborne Laser (ABL) is an airborne, megawatt-class laser system with a state-of-the-art atmospheric compensation system to destroy enemy ballistic missiles at long ranges. This system will provide both deterrence and defense against the use of such weapons during conflicts. This paper provides an overview of the ABL weapon system including: the notional operational concept, the development approach and schedule, the overall aircraft configuration, the technologies being incorporated in the ABL, and the risk reduction approach being utilized to ensure program success.

  18. PtSi/Si LWIR Detectors Made With p+ Doping Spikes

    NASA Technical Reports Server (NTRS)

    Lin, True-Lon; Park, Jin S.; George, Thomas; Fathauer, Robert W.; Jones, Eric W.; Maserjian, Joseph

    1996-01-01

    PtSi/Si Schottky-barrier devices detecting long-wavelength infrared (LWIR) photons demonstrated. Essential feature of one of these devices is p+ "doping spike"; layer of Si about 10 Angstrom thick, located at PtSi/Si interface, and doped with electron acceptors (boron atoms) at concentration between 5 x 10(19) and 2 x 10(20) cm(-3). Doping spikes extend cutoff wavelengths of devices to greater values than otherwise possible.

  19. The civil air patrol ARCHER hyperspectral sensor system

    NASA Astrophysics Data System (ADS)

    Stevenson, Brian; O'Connor, Rory; Kendall, William; Stocker, Alan; Schaff, William; Holasek, Rick; Even, Detlev; Alexa, Drew; Salvador, John; Eismann, Michael; Mack, Robert; Kee, Pat; Harris, Steve; Karch, Barry; Kershenstein, John

    2005-05-01

    The Civil Air Patrol (CAP) is procuring Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) systems to increase their search-and-rescue mission capability. These systems are being installed on a fleet of Gippsland GA-8 aircraft, and will position CAP to gain realworld mission experience with the application of hyperspectral sensor and processing technology to search and rescue. The ARCHER system design, data processing, and operational concept leverage several years of investment in hyperspectral technology research and airborne system demonstration programs by the Naval Research Laboratory (NRL) and Air Force Research Laboratory (AFRL). Each ARCHER system consists of a NovaSol-designed, pushbroom, visible/near-infrared (VNIR) hyperspectral imaging (HSI) sensor, a co-boresighted visible panchromatic high-resolution imaging (HRI) sensor, and a CMIGITS-III GPS/INS unit in an integrated sensor assembly mounted inside the GA-8 cabin. ARCHER incorporates an on-board data processing system developed by Space Computer Corporation (SCC) to perform numerous real-time processing functions including data acquisition and recording, raw data correction, target detection, cueing and chipping, precision image geo-registration, and display and dissemination of image products and target cue information. A ground processing station is provided for post-flight data playback and analysis. This paper describes the requirements and architecture of the ARCHER system, including design, components, software, interfaces, and displays. Key sensor performance characteristics and real-time data processing features are discussed in detail. The use of the system for detecting and geo-locating ground targets in real-time is demonstrated using test data collected in Southern California in the fall of 2004.

  20. Remote detection of buried land-mines and IEDs using LWIR polarimetric imaging.

    PubMed

    Gurton, Kristan P; Felton, Melvin

    2012-09-24

    We report results of an ongoing study designed to assess the ability for enhanced detection of recently buried land-mines and/or improvised explosive devices (IED) devices using passive long-wave infrared (LWIR) polarimetric imaging. Polarimetric results are presented for a series of field tests conducted at various locations and soil types. Well-calibrated Stokes images, S0, S1, S2, and the degree-of-linear-polarization (DoLP) are recorded for different line-of-sight (LOS) slant paths at varying distances. Results span a three-year time period in which three different LWIR polarimetric camera systems are used. All three polarimetric imaging platforms used a spinning-achromatic-retarder (SAR) design capable of achieving high polarimetric frame rates and good radiometric throughput without the loss of spatial resolution inherent in other optical designs. Receiver-operating-characteristic (ROC) analysis and a standardized contrast parameter are used to compare detectability between conventional LWIR thermal and polarimetric imagery. Results suggest improved detectability, regardless of geographic location or soil type. PMID:23037383

  1. LWIR and VLWIR MCT technologies and detectors development at SOFRADIR for space applications

    NASA Astrophysics Data System (ADS)

    Leroy, Cédric; Chorier, Philippe; Destefanis, Gérard

    2012-06-01

    SOFRADIR is one of the leading companies involved in the development and manufacturing of MCT (Mercury Cadmium Telluride) infrared detectors for space programs. The panel of space applications in which SOFRADIR is involved is wide and covers a large spectrum ranging from visible up to very long wavelength infrared (VLWIR). The last mission requirements for space applications, in particular for imagers and sounders, have brought new specifications for LWIR and VLWIR infrared detectors with cut-off wavelength of more than 15 μm. These requirements call for technology and design optimizations in order to find the best trade-off between detector performances and operational constraints such as operating temperature. In this paper, we present first a review of the different needs for current and future LWIR and VWLIR space applications in terms of detector architectures and requirements. Then, a presentation is made of the latest MCT technology optimizations for LWIR and VLWIR spectral bandwidths to meet these needs (n-onp and p-on-n technologies). Finally, different read-out circuit architectures are discussed to improve operability and performances in these bandwidths. Anyway, as mission requirements are always different depending on applications, a trade-off between the different solutions proposed in this paper is necessary in the early phases of the programs to find the best compromise to comply with customer needs.

  2. Moving beyond flat earth: dense 3D scene reconstruction from a single FL-LWIR camera

    NASA Astrophysics Data System (ADS)

    Stone, K.; Keller, J. M.; Anderson, D. T.

    2013-06-01

    In previous work an automatic detection system for locating buried explosive hazards in forward-looking longwave infrared (FL-LWIR) and forward-looking ground penetrating radar (FL-GPR) data was presented. This system consists of an ensemble of trainable size-contrast filters prescreener coupled with a secondary classification step which extracts cell-structured image space features, such as local binary patterns (LBP), histogram of oriented gradients (HOG), and edge histogram descriptors (EHD), from multiple looks and classifies the resulting feature vectors using a support vector machine. Previously, this system performed image space to UTM coordinate mapping under a flat earth assumption. This limited its applicability to flat terrain and short standoff distances. This paper demonstrates a technique for dense 3D scene reconstruction from a single vehicle mounted FL-LWIR camera. This technique utilizes multiple views and standard stereo vision algorithms such as polar rectification and optimal correction. Results for the detection algorithm using this 3D scene reconstruction approach on data from recent collections at an arid US Army test site are presented. These results are compared to those obtained under the flat earth assumption, with special focus on rougher terrain and longer standoff distance than in previous experiments. The most recent collection also allowed comparison between uncooled and cooled FL-LWIR cameras for buried explosive hazard detection.

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. Compressed hyperspectral sensing

    NASA Astrophysics Data System (ADS)

    Tsagkatakis, Grigorios; Tsakalides, Panagiotis

    2015-03-01

    Acquisition of high dimensional Hyperspectral Imaging (HSI) data using limited dimensionality imaging sensors has led to restricted capabilities designs that hinder the proliferation of HSI. To overcome this limitation, novel HSI architectures strive to minimize the strict requirements of HSI by introducing computation into the acquisition process. A framework that allows the integration of acquisition with computation is the recently proposed framework of Compressed Sensing (CS). In this work, we propose a novel HSI architecture that exploits the sampling and recovery capabilities of CS to achieve a dramatic reduction in HSI acquisition requirements. In the proposed architecture, signals from multiple spectral bands are multiplexed before getting recorded by the imaging sensor. Reconstruction of the full hyperspectral cube is achieved by exploiting a dictionary of elementary spectral profiles in a unified minimization framework. Simulation results suggest that high quality recovery is possible from a single or a small number of multiplexed frames.

  8. 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

  9. Planetary Hyperspectral Imager (PHI)

    NASA Technical Reports Server (NTRS)

    Silvergate, Peter

    1996-01-01

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

  10. Mapping Geology and Vegetation using Hyperspectral Data in Antarctica: Current Challenges, New Solutions and Looking to the Future

    NASA Astrophysics Data System (ADS)

    Black, M.; Riley, T. R.; Fleming, A. H.; Ferrier, G.; Fretwell, P.; Casanovas, P.

    2015-12-01

    Antarctica is a unique and geographically remote environment. Traditional field campaigns investigating geology and vegetation in the region encounter numerous challenges including the harsh polar climate, the invasive nature of the work, steep topography and high infrastructure costs. Additionally, such field campaigns are often limited in terms of spatial and temporal resolution, and particularly, the topographical challenges presented in the Antarctic mean that many areas remain inaccessible. Remote Sensing, particularly hyperspectral imaging, may provide a solution to overcome the difficulties associated with field based mapping in the Antarctic. Planned satellite launches, such as EnMAP and HyspIRI, if successful, will yield large-scale, repeated hyperspectral imagery of Antarctica. Hyperspectral imagery has proven mapping capabilities and can yield greater information than can be attained using multispectral data. As a precursor to future satellite imagery, we utilise hyperspectral imagery from the first known airborne hyperspectral survey carried out in the Antarctic by the British Antarctic Survey and partners in 2011. Multiple imaging spectrometers were simultaneously deployed covering the visible, shortwave and thermal infrared regions of the electromagnetic spectrum. Additional data was generated during a field campaign deploying multiple ground spectrometers covering the same wavelengths as the airborne imagers. We utilise this imagery to assess the current challenges and propose some new solutions for mapping vegetation and geology, which may be directly applicable to future satellite hyperspectral imagery in the Antarctic.

  11. 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.

  12. Comparison of support vector machine-based processing chains for hyperspectral image classification

    NASA Astrophysics Data System (ADS)

    Rojas, Marta; Dópido, Inmaculada; Plaza, Antonio; Gamba, Paolo

    2010-08-01

    Many different approaches have been proposed in recent years for remotely sensed hyperspectral image classification. Despite the variety of techniques designed to tackle the aforementioned problem, the definition of standardized processing chains for hyperspectral image classification is a difficult objective, which may ultimately depend on the application being addressed. Generally speaking, a hyperspectral image classification chain may be defined from two perspectives: 1) the provider's viewpoint, and 2) the user's viewpoint, where the first part of the chain comprises activities such as data calibration and geo-correction aspects, while the second part of the chain comprises information extraction processes from the collected data. The modules in the second part of the chain (which constitutes our main focus in this paper) should be ideally flexible enough to be accommodated not only to different application scenarios, but also to different hyperspectral imaging instruments with varying characteristics, and spatial and spectral resolutions. In this paper, we evaluate the performance of different processing chains resulting from combinations of modules for dimensionality reduction, feature extraction/ selection, image classification, and spatial post-processing. The support vector machine (SVM) classifier is adopted as a baseline due to its ability to classify hyperspectral data sets using limited training samples. A specific classification scenario is investigated, using a reference hyperspectral data set collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Indian Pines region in Indiana, USA.

  13. The French proposal for a high spatial resolution Hyperspectral mission

    NASA Astrophysics Data System (ADS)

    Carrère, Véronique; Briottet, Xavier; Jacquemoud, Stéphane; Marion, Rodolphe; Bourguignon, Anne; Chami, Malik; Chanussot, Jocelyn; Chevrel, Stéphane; Deliot, Philippe; Dumont, Marie; Foucher, Pierre-Yves; Gomez, Cécile; Roman-Minghelli, Audrey; Sheeren, David; Weber, Christiane; Lefèvre, Marie-José; Mandea, Mioara

    2014-05-01

    More than 25 years of airborne imaging spectroscopy and spaceborne sensors such as Hyperion or HICO have clearly demonstrated the ability of such a remote sensing technique to produce value added information regarding surface composition and physical properties for a large variety of applications. Scheduled missions such as EnMAP and PRISMA prove the increased interest of the scientific community for such a type of remote sensing data. In France, a group of Science and Defence users of imaging spectrometry data (Groupe de Synthèse Hyperspectral, GSH) established an up-to-date review of possible applications, define instrument specifications required for accurate, quantitative retrieval of diagnostic parameters, and identify fields of application where imaging spectrometry is a major contribution. From these conclusions, CNES (French Space Agency) decided a phase 0 study for an hyperspectral mission concept, named at this time HYPXIM (HYPerspectral-X IMagery), the main fields of applications are vegetation biodiversity, coastal and inland waters, geosciences, urban environment, atmospheric sciences, cryosphere and Defence. Results pointed out applications where high spatial resolution was necessary and would not be covered by the other foreseen hyperspectral missions. The phase A started at the beginning of 2013 based on the following HYPXIM characteristics: a hyperspectral camera covering the [0.4 - 2.5 µm] spectral range with a 8 m ground sampling distance (GSD) and a PAN camera with a 1.85 m GSD, onboard a mini-satellite platform. This phase A is currently stopped due to budget constraints. Nevertheless, the Science team is currently focusing on the preparation for the next CNES prospective meeting (March, 2014), an important step for the future of the mission. This paper will provide an update of the status of this mission and of new results obtained by the Science team.

  14. Automated optical testing of LWIR objective lenses using focal plane array sensors

    NASA Astrophysics Data System (ADS)

    Winters, Daniel; Erichsen, Patrik; Domagalski, Christian; Peter, Frank; Heinisch, Josef; Dumitrescu, Eugen

    2012-10-01

    The image quality of today's state-of-the-art IR objective lenses is constantly improving while at the same time the market for thermography and vision grows strongly. Because of increasing demands on the quality of IR optics and increasing production volumes, the standards for image quality testing increase and tests need to be performed in shorter time. Most high-precision MTF testing equipment for the IR spectral bands in use today relies on the scanning slit method that scans a 1D detector over a pattern in the image generated by the lens under test, followed by image analysis to extract performance parameters. The disadvantages of this approach are that it is relatively slow, it requires highly trained operators for aligning the sample and the number of parameters that can be extracted is limited. In this paper we present lessons learned from the R and D process on using focal plane array (FPA) sensors for testing of long-wave IR (LWIR, 8-12 m) optics. Factors that need to be taken into account when switching from scanning slit to FPAs are e.g.: the thermal background from the environment, the low scene contrast in the LWIR, the need for advanced image processing algorithms to pre-process camera images for analysis and camera artifacts. Finally, we discuss 2 measurement systems for LWIR lens characterization that we recently developed with different target applications: 1) A fully automated system suitable for production testing and metrology that uses uncooled microbolometer cameras to automatically measure MTF (on-axis and at several o-axis positions) and parameters like EFL, FFL, autofocus curves, image plane tilt, etc. for LWIR objectives with an EFL between 1 and 12mm. The measurement cycle time for one sample is typically between 6 and 8s. 2) A high-precision research-grade system using again an uncooled LWIR camera as detector, that is very simple to align and operate. A wide range of lens parameters (MTF, EFL, astigmatism, distortion, etc.) can be

  15. Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified ...

  16. Estimating Yellow Starthistle (Centaurea solstitialis) Leaf Area Index and Aboveground Biomass with the Use of Hyperspectral Data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral remote-sensed data were obtained via a Compact Airborne Spectrographic Imager-II (CASI-II) and used to estimate leaf-area index (LAI) and aboveground biomass of a highly invasive weed species, yellow starthistle (YST). In parallel, 34 ground-based field plots were used to measure abov...

  17. An airborne thematic thermal infrared and electro-optical imaging system

    NASA Astrophysics Data System (ADS)

    Sun, Xiuhong; Shu, Peter

    2011-08-01

    This paper describes an advanced Airborne Thematic Thermal InfraRed and Electro-Optical Imaging System (ATTIREOIS) and its potential applications. ATTIREOIS sensor payload consists of two sets of advanced Focal Plane Arrays (FPAs) - a broadband Thermal InfraRed Sensor (TIRS) and a four (4) band Multispectral Electro-Optical Sensor (MEOS) to approximate Landsat ETM+ bands 1,2,3,4, and 6, and LDCM bands 2,3,4,5, and 10+11. The airborne TIRS is 3-axis stabilized payload capable of providing 3D photogrammetric images with a 1,850 pixel swathwidth via pushbroom operation. MEOS has a total of 116 million simultaneous sensor counts capable of providing 3 cm spatial resolution multispectral orthophotos for continuous airborne mapping. ATTIREOIS is a complete standalone and easy-to-use portable imaging instrument for light aerial vehicle deployment. Its miniaturized backend data system operates all ATTIREOIS imaging sensor components, an INS/GPS, and an e-Gimbal™ Control Electronic Unit (ECU) with a data throughput of 300 Megabytes/sec. The backend provides advanced onboard processing, performing autonomous raw sensor imagery development, TIRS image track-recovery reconstruction, LWIR/VNIR multi-band co-registration, and photogrammetric image processing. With geometric optics and boresight calibrations, the ATTIREOIS data products are directly georeferenced with an accuracy of approximately one meter. A prototype ATTIREOIS has been configured. Its sample LWIR/EO image data will be presented. Potential applications of ATTIREOIS include: 1) Providing timely and cost-effective, precisely and directly georeferenced surface emissive and solar reflective LWIR/VNIR multispectral images via a private Google Earth Globe to enhance NASA's Earth science research capabilities; and 2) Underflight satellites to support satellite measurement calibration and validation observations.

  18. Uas Based Tree Species Identification Using the Novel FPI Based Hyperspectral Cameras in Visible, NIR and SWIR Spectral Ranges

    NASA Astrophysics Data System (ADS)

    Näsi, R.; Honkavaara, E.; Tuominen, S.; Saari, H.; Pölönen, I.; Hakala, T.; Viljanen, N.; Soukkamäki, J.; Näkki, I.; Ojanen, H.; Reinikainen, J.

    2016-06-01

    Unmanned airborne systems (UAS) based remote sensing offers flexible tool for environmental monitoring. Novel lightweight Fabry-Perot interferometer (FPI) based, frame format, hyperspectral imaging in the spectral range from 400 to 1600 nm was used for identifying different species of trees in a forest area. To the best of the authors' knowledge, this was the first research where stereoscopic, hyperspectral VIS, NIR, SWIR data is collected for tree species identification using UAS. The first results of the analysis based on fusion of two FPI-based hyperspectral imagers and RGB camera showed that the novel FPI hyperspectral technology provided accurate geometric, radiometric and spectral information in a forested scene and is operational for environmental remote sensing applications.

  19. Geometric and Reflectance Signature Characterization of Complex Canopies Using Hyperspectral Stereoscopic Images from Uav and Terrestrial Platforms

    NASA Astrophysics Data System (ADS)

    Honkavaara, E.; Hakala, T.; Nevalainen, O.; Viljanen, N.; Rosnell, T.; Khoramshahi, E.; Näsi, R.; Oliveira, R.; Tommaselli, A.

    2016-06-01

    Light-weight hyperspectral frame cameras represent novel developments in remote sensing technology. With frame camera technology, when capturing images with stereoscopic overlaps, it is possible to derive 3D hyperspectral reflectance information and 3D geometric data of targets of interest, which enables detailed geometric and radiometric characterization of the object. These technologies are expected to provide efficient tools in various environmental remote sensing applications, such as canopy classification, canopy stress analysis, precision agriculture, and urban material classification. Furthermore, these data sets enable advanced quantitative, physical based retrieval of biophysical and biochemical parameters by model inversion technologies. Objective of this investigation was to study the aspects of capturing hyperspectral reflectance data from unmanned airborne vehicle (UAV) and terrestrial platform with novel hyperspectral frame cameras in complex, forested environment.

  20. Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA)

    USGS Publications Warehouse

    Kokaly, R.F.; King, T.V.V.; Hoefen, T.M.

    2011-01-01

    Identifying materials by measuring and analyzing their reflectance spectra has been an important method in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow scientists to detect materials and map their distributions across the landscape. With new satellite-borne hyperspectral sensors planned for the future, for example, HYSPIRI (HYPerspectral InfraRed Imager), robust methods are needed to fully exploit the information content of hyperspectral remote sensing data. A method of identifying and mapping materials using spectral-feature based analysis of reflectance data in an expert-system framework called MICA (Material Identification and Characterization Algorithm) is described in this paper. The core concepts and calculations of MICA are presented. A MICA command file has been developed and applied to map minerals in the full-country coverage of the 2007 Afghanistan HyMap hyperspectral data. ?? 2011 IEEE.

  1. High-Performance M/LWIR Dual-Band HgCdTe/Si Focal-Plane Arrays

    NASA Astrophysics Data System (ADS)

    Vilela, M. F.; Olsson, K. R.; Norton, E. M.; Peterson, J. M.; Rybnicek, K.; Rhiger, D. R.; Fulk, C. W.; Bangs, J. W.; Lofgreen, D. D.; Johnson, S. M.

    2013-11-01

    Mercury cadmium telluride (HgCdTe) grown on large-area silicon (Si) substrates allows for larger array formats and potentially reduced focal-plane array (FPA) cost compared with smaller, more expensive cadmium zinc telluride (CdZnTe) substrates. In this work, the use of HgCdTe/Si for mid- wavelength/long-wavelength infrared (M/LWIR) dual-band FPAs is evaluated for tactical applications. A number of M/LWIR dual-band HgCdTe triple-layer n- P- n heterojunction device structures were grown by molecular-beam epitaxy (MBE) on 100-mm (211)Si substrates. Wafers exhibited low macrodefect densities (< 300 cm-2). Die from these wafers were mated to dual-band readout integrated circuits to produce FPAs. The measured 81-K cutoff wavelengths were 5.1 μm for band 1 (MWIR) and 9.6 μm for band 2 (LWIR). The FPAs exhibited high pixel operability in each band with noise-equivalent differential temperature operability of 99.98% for the MWIR band and 98.7% for the LWIR band at 81 K. The results from this series are compared with M/LWIR FPAs from 2009 to address possible methods for improvement. Results obtained in this work suggest that MBE growth defects and dislocations present in devices are not the limiting factor for detector operability, with regards to infrared detection for tactical applications.

  2. Hyperspectral Soil Mapper (HYSOMA) software interface: Review and future plans

    NASA Astrophysics Data System (ADS)

    Chabrillat, Sabine; Guillaso, Stephane; Eisele, Andreas; Rogass, Christian

    2014-05-01

    With the upcoming launch of the next generation of hyperspectral satellites that will routinely deliver high spectral resolution images for the entire globe (e.g. EnMAP, HISUI, HyspIRI, HypXIM, PRISMA), an increasing demand for the availability/accessibility of hyperspectral soil products is coming from the geoscience community. Indeed, many robust methods for the prediction of soil properties based on imaging spectroscopy already exist and have been successfully used for a wide range of soil mapping airborne applications. Nevertheless, these methods require expert know-how and fine-tuning, which makes them used sparingly. More developments are needed toward easy-to-access soil toolboxes as a major step toward the operational use of hyperspectral soil products for Earth's surface processes monitoring and modelling, to allow non-experienced users to obtain new information based on non-expensive software packages where repeatability of the results is an important prerequisite. In this frame, based on the EU-FP7 EUFAR (European Facility for Airborne Research) project and EnMAP satellite science program, higher performing soil algorithms were developed at the GFZ German Research Center for Geosciences as demonstrators for end-to-end processing chains with harmonized quality measures. The algorithms were built-in into the HYSOMA (Hyperspectral SOil MApper) software interface, providing an experimental platform for soil mapping applications of hyperspectral imagery that gives the choice of multiple algorithms for each soil parameter. The software interface focuses on fully automatic generation of semi-quantitative soil maps such as soil moisture, soil organic matter, iron oxide, clay content, and carbonate content. Additionally, a field calibration option calculates fully quantitative soil maps provided ground truth soil data are available. Implemented soil algorithms have been tested and validated using extensive in-situ ground truth data sets. The source of the HYSOMA

  3. Airborne Visible / Infrared Imaging Spectrometer AVIS: Design, Characterization and Calibration

    PubMed Central

    Oppelt, Natascha; Mauser, Wolfram

    2007-01-01

    The Airborne Visible / Infrared imaging Spectrometer AVIS is a hyperspectral imager designed for environmental monitoring purposes. The sensor, which was constructed entirely from commercially available components, has been successfully deployed during several experiments between 1999 and 2007. We describe the instrument design and present the results of laboratory characterization and calibration of the system's second generation, AVIS-2, which is currently being operated. The processing of the data is described and examples of remote sensing reflectance data are presented.

  4. Design and fabrication of diffraction grating for application in hyperspectral imaging for the long-wavelength infrared spectral region

    NASA Astrophysics Data System (ADS)

    Vojtíšek, Petr; Possolt, Martin; Doleček, Roman; Steiger, Kateřina; Pintr, Pavel; Václavík, Jan

    2015-01-01

    Hyperspectral imaging as an instrument for obtaining a wide range of information on the world around us is a fast developing area of modern technology. In such systems, the desired information is obtained via the processing of stored spectral information of a measured scene. One of the main advantages of hyperspectral imaging over conventional imaging methods is the use of a broad spectral range, which is not restricted to just the visible range but can extend to adjacent regions and further, for example, deeply into the infrared region. The main element in such hyperspectral systems is the spectral separating system, which can be based on a wide variety of spectral dependent physical processes - birefringence, refraction, diffraction, etc. In this contribution, we would like to present the design and fabrication process of such a spectral separating system based on diffraction grating. The main requirements for this system were - operation in the long-wavelength infrared region (LWIR, 7-14 um), the highest possible diffraction efficiency in this spectral region with respect to the black body radiation of a temperature of 350 K, and the avoidance of restrictions inherent to fabrication. The design was carried out with the use of Scalar theory of transmission gratings, which is based on the idea of thin grating. The obtained results were compared to the designs produced via the Rigorous coupled wave theory (RCWA) and Finite Element Method (FEM). Fabrication of the designed grating was done in germanium with the use of single-point diamond turning.

  5. Hyperspectral data recognition and mapping of soil salinization in arid environment

    NASA Astrophysics Data System (ADS)

    Lu, Ning; Zhang, Zhi; Gao, Yang

    2005-10-01

    Hyperspectral imagery of airborne imaging spectrometer (Pushbroom Hyperspectral Imager (PHI)) was acquired over KeLaMaYi, which situated in arid region of northwestern China. In situ hyperspectral data obtained with FieldSpec HandHeld spectrometer (ASD) simultaneously were analyzed for recognition of soil salinization. Some types of transformation were applied to the reflectance data of 60 soil samples, which preprocessed with a simple smoothing followed by band merging. A comparative study among these methods was made to ascertain their applicability for recognition accuracies. After multivariate analysis between ion concentration and reflectance data or their derivatives, a best statistical model was then extracted to predict the soil salinity and PH. Using this prediction model, subpixel classification applied to the corrected imagery helped to yield quantitative maps of soil salinity and PH. Such maps contributed to suggesting soil distribution and aggregation, estimating the spatial controls of erosion, and consequently, helping to plan soil improvement and soil conservation schemes.

  6. Accumulating pyramid spatial-spectral collaborative coding divergence for hyperspectral anomaly detection

    NASA Astrophysics Data System (ADS)

    Sun, Hao; Zou, Huanxin; Zhou, Shilin

    2016-03-01

    Detection of anomalous targets of various sizes in hyperspectral data has received a lot of attention in reconnaissance and surveillance applications. Many anomaly detectors have been proposed in literature. However, current methods are susceptible to anomalies in the processing window range and often make critical assumptions about the distribution of the background data. Motivated by the fact that anomaly pixels are often distinctive from their local background, in this letter, we proposed a novel hyperspectral anomaly detection framework for real-time remote sensing applications. The proposed framework consists of four major components, sparse feature learning, pyramid grid window selection, joint spatial-spectral collaborative coding and multi-level divergence fusion. It exploits the collaborative representation difference in the feature space to locate potential anomalies and is totally unsupervised without any prior assumptions. Experimental results on airborne recorded hyperspectral data demonstrate that the proposed methods adaptive to anomalies in a large range of sizes and is well suited for parallel processing.

  7. Spectral-spatial classification of hyperspectral data based on a stochastic minimum spanning forest approach.

    PubMed

    Bernard, Kévin; Tarabalka, Yuliya; Angulo, Jesús; Chanussot, Jocelyn; Benediktsson, Jón Atli

    2012-04-01

    In this paper, a new method for supervised hyperspectral data classification is proposed. In particular, the notion of stochastic minimum spanning forest (MSF) is introduced. For a given hyperspectral image, a pixelwise classification is first performed. From this classification map, M marker maps are generated by randomly selecting pixels and labeling them as markers for the construction of MSFs. The next step consists in building an MSF from each of the M marker maps. Finally, all the M realizations are aggregated with a maximum vote decision rule in order to build the final classification map. The proposed method is tested on three different data sets of hyperspectral airborne images with different resolutions and contexts. The influences of the number of markers and of the number of realizations M on the results are investigated in experiments. The performance of the proposed method is compared to several classification techniques (both pixelwise and spectral-spatial) using standard quantitative criteria and visual qualitative evaluation. PMID:22086502

  8. Challenges in collecting hyperspectral imagery of coastal waters using Unmanned Aerial Vehicles (UAVs)

    NASA Astrophysics Data System (ADS)

    English, D. C.; Herwitz, S.; Hu, C.; Carlson, P. R., Jr.; Muller-Karger, F. E.; Yates, K. K.; Ramsewak, D.

    2013-12-01

    Airborne multi-band remote sensing is an important tool for many aquatic applications; and the increased spectral information from hyperspectral sensors may increase the utility of coastal surveys. Recent technological advances allow Unmanned Aerial Vehicles (UAVs) to be used as alternatives or complements to manned aircraft or in situ observing platforms, and promise significant advantages for field studies. These include the ability to conduct programmed flight plans, prolonged and coordinated surveys, and agile flight operations under difficult conditions such as measurements made at low altitudes. Hyperspectral imagery collected from UAVs should allow the increased differentiation of water column or shallow benthic communities at relatively small spatial scales. However, the analysis of hyperspectral imagery from airborne platforms over shallow coastal waters differs from that used for terrestrial or oligotrophic ocean color imagery, and the operational constraints and considerations for the collection of such imagery from autonomous platforms also differ from terrestrial surveys using manned aircraft. Multispectral and hyperspectral imagery of shallow seagrass and coral environments in the Florida Keys were collected with various sensor systems mounted on manned and unmanned aircrafts in May 2012, October 2012, and May 2013. The imaging systems deployed on UAVs included NovaSol's Selectable Hyperspectral Airborne Remote-sensing Kit (SHARK), a Tetracam multispectral imaging system, and the Sunflower hyperspectal imager from Galileo Group, Inc. The UAVs carrying these systems were Xtreme Aerial Concepts' Vision-II Rotorcraft UAV, MLB Company's Bat-4 UAV, and NASA's SIERRA UAV, respectively. Additionally, the Galileo Group's manned aircraft also surveyed the areas with their AISA Eagle hyperspectral imaging system. For both manned and autonomous flights, cloud cover and sun glint (solar and viewing angles) were dominant constraints on retrieval of quantitatively

  9. Trade-off studies of a hyperspectral infrared sounder on a geostationary satellite.

    PubMed

    Wang, Fang; Li, Jun; Schmit, Timothy J; Ackerman, Steven A

    2007-01-10

    Trade-off studies on spectral coverage, signal-to-noise ratio (SNR), and spectral resolution for a hyperspectral infrared (IR) sounder on a geostationary satellite are summarized. The data density method is applied for the vertical resolution analysis, and the rms error between true and retrieved profiles is used to represent the retrieval accuracy. The effects of spectral coverage, SNR, and spectral resolution on vertical resolution and retrieval accuracy are investigated. The advantages of IR and microwave sounder synergy are also demonstrated. When focusing on instrument performance and data processing, the results from this study show that the preferred spectral coverage combines long-wave infrared (LWIR) with the shorter middle-wave IR (SMidW). Using the appropriate spectral coverage, a hyperspectral IR sounder with appropriate SNR can achieve the required science performance (1 km vertical resolution, 1 K temperature, and 10% relative humidity retrieval accuracy). The synergy of microwave and IR sounders can improve the vertical resolution and retrieval accuracy compared to either instrument alone. PMID:17268565

  10. 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.

  11. Spectral difference analysis and airborne imaging classification for citrus greening infected trees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Citrus greening, also called Huanglongbing (HLB), became a devastating disease spread through citrus groves in Florida, since it was first found in 2005. Multispectral (MS) and hyperspectral (HS) airborne images of citrus groves in Florida were acquired to detect citrus greening infected trees in 20...

  12. Geometric correction of airborne remote sensing data: An operational procedure to geocode MIVIS data

    SciTech Connect

    Avanzi, G.; Bianchi, R.; Cavalli, R.M.

    1996-11-01

    Study to develop a software methodology to geocode MIVIS hyperspectral images collected by the CNR LARA Project. Gol of the study is to integrate the airborne Position and Attitude System with the image data to obtain geoceded images at a medium-small scale (1: 15000 - 1: 10000). 4 refs., 4 figs.

  13. Fusion of remotely sensed data from airborne and ground-based sensors for cotton regrowth study

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The study investigated the use of aerial multispectral imagery and ground-based hyperspectral data for the discrimination of different crop types and timely detection of cotton plants over large areas. Airborne multispectral imagery and ground-based spectral reflectance data were acquired at the sa...

  14. ASPIS, A Flexible Multispectral System for Airborne Remote Sensing Environmental Applications

    PubMed Central

    Papale, Dario; Belli, Claudio; Gioli, Beniamino; Miglietta, Franco; Ronchi, Cesare; Vaccari, Francesco Primo; Valentini, Riccardo

    2008-01-01

    Airborne multispectral and hyperspectral remote sensing is a powerful tool for environmental monitoring applications. In this paper we describe a new system (ASPIS) composed by a 4-CCD spectral sensor, a thermal IR camera and a laser altimeter that is mounted on a flexible Sky-Arrow airplane. A test application of the multispectral sensor to estimate durum wheat quality is also presented.

  15. 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

  16. GPU Lossless Hyperspectral Data Compression System for Space Applications

    NASA Technical Reports Server (NTRS)

    Keymeulen, Didier; Aranki, Nazeeh; Hopson, Ben; Kiely, Aaron; Klimesh, Matthew; Benkrid, Khaled

    2012-01-01

    On-board lossless hyperspectral data compression reduces data volume in order to meet NASA and DoD limited downlink capabilities. At JPL, a novel, adaptive and predictive technique for lossless compression of hyperspectral data, named the Fast Lossless (FL) algorithm, was recently developed. This technique uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. Because of its outstanding performance and suitability for real-time onboard hardware implementation, the FL compressor is being formalized as the emerging CCSDS Standard for Lossless Multispectral & Hyperspectral image compression. The FL compressor is well-suited for parallel hardware implementation. A GPU hardware implementation was developed for FL targeting the current state-of-the-art GPUs from NVIDIA(Trademark). The GPU implementation on a NVIDIA(Trademark) GeForce(Trademark) GTX 580 achieves a throughput performance of 583.08 Mbits/sec (44.85 MSamples/sec) and an acceleration of at least 6 times a software implementation running on a 3.47 GHz single core Intel(Trademark) Xeon(Trademark) processor. This paper describes the design and implementation of the FL algorithm on the GPU. The massively parallel implementation will provide in the future a fast and practical real-time solution for airborne and space applications.

  17. Postfire soil burn severity mapping with hyperspectral image unmixing

    USGS Publications Warehouse

    Robichaud, P.R.; Lewis, S.A.; Laes, D.Y.M.; Hudak, A.T.; Kokaly, R.F.; Zamudio, J.A.

    2007-01-01

    Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after the 2002 Hayman Fire in Colorado to assess the application of high resolution imagery for burn severity mapping and to compare it to standard burn severity mapping methods. Mixture Tuned Matched Filtering (MTMF), a partial spectral unmixing algorithm, was used to identify the spectral abundance of ash, soil, and scorched and green vegetation in the burned area. The overall performance of the MTMF for predicting the ground cover components was satisfactory (r2 = 0.21 to 0.48) based on a comparison to fractional ash, soil, and vegetation cover measured on ground validation plots. The relationship between Landsat-derived differenced Normalized Burn Ratio (dNBR) values and the ground data was also evaluated (r2 = 0.20 to 0.58) and found to be comparable to the MTMF. However, the quantitative information provided by the fine-scale hyperspectral imagery makes it possible to more accurately assess the effects of the fire on the soil surface by identifying discrete ground cover characteristics. These surface effects, especially soil and ash cover and the lack of any remaining vegetative cover, directly relate to potential postfire watershed response processes. ?? 2006 Elsevier Inc. All rights reserved.

  18. Algorithm for Lossless Compression of Calibrated Hyperspectral Imagery

    NASA Technical Reports Server (NTRS)

    Kiely, Aaron B.; Klimesh, Matthew A.

    2010-01-01

    A two-stage predictive method was developed for lossless compression of calibrated hyperspectral imagery. The first prediction stage uses a conventional linear predictor intended to exploit spatial and/or spectral dependencies in the data. The compressor tabulates counts of the past values of the difference between this initial prediction and the actual sample value. To form the ultimate predicted value, in the second stage, these counts are combined with an adaptively updated weight function intended to capture information about data regularities introduced by the calibration process. Finally, prediction residuals are losslessly encoded using adaptive arithmetic coding. Algorithms of this type are commonly tested on a readily available collection of images from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imager. On the standard calibrated AVIRIS hyperspectral images that are most widely used for compression benchmarking, the new compressor provides more than 0.5 bits/sample improvement over the previous best compression results. The algorithm has been implemented in Mathematica. The compression algorithm was demonstrated as beneficial on 12-bit calibrated AVIRIS images.

  19. An optimized hybrid encode based compression algorithm for hyperspectral image

    NASA Astrophysics Data System (ADS)

    Wang, Cheng; Miao, Zhuang; Feng, Weiyi; He, Weiji; Chen, Qian; Gu, Guohua

    2013-12-01

    Compression is a kernel procedure in hyperspectral image processing due to its massive data which will bring great difficulty in date storage and transmission. In this paper, a novel hyperspectral compression algorithm based on hybrid encoding which combines with the methods of the band optimized grouping and the wavelet transform is proposed. Given the characteristic of correlation coefficients between adjacent spectral bands, an optimized band grouping and reference frame selection method is first utilized to group bands adaptively. Then according to the band number of each group, the redundancy in the spatial and spectral domain is removed through the spatial domain entropy coding and the minimum residual based linear prediction method. Thus, embedded code streams are obtained by encoding the residual images using the improved embedded zerotree wavelet based SPIHT encode method. In the experments, hyperspectral images collected by the Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS) were used to validate the performance of the proposed algorithm. The results show that the proposed approach achieves a good performance in reconstructed image quality and computation complexity.The average peak signal to noise ratio (PSNR) is increased by 0.21~0.81dB compared with other off-the-shelf algorithms under the same compression ratio.

  20. PHIRST light: a liquid crystal tunable filter hyperspectral sensor

    NASA Astrophysics Data System (ADS)

    Stevenson, Brian P.; Kendall, William B.; Stellman, Christopher M.; Olchowski, Frederick M.

    2003-09-01

    PHIRST Light is a visible and near-infrared (VNIR) hyperspectral imaging sensor that has been assembled at the Naval Research Laboratory (NRL) using off-the-shelf components. It consists of a Dalsa 1M60 camera mated to a CRI VariSpec liquid crystal tunable filter (LCTF) and a conventional 75mm Pentax lens. This system can be thought of as the modern equivalent of a filter-wheel sensor. Historically, the problem with such sensors has been that images for different wavelengths are collected at different times. This causes spectral correlation problems when the camera is not perfectly still during the collection time for all bands (such as when it is deployed on an airborne platform). However, the PHIRST Light sensor is hard mounted in a Twin Otter aircraft, and is mated to a TrueTime event capture board, which records the precise GPS time of each image frame. Combining this information with the output of a CMIGITS INS/GPS unit permits precise coregistration of images from multiple wavelengths, and allows the formation of a conventional hyperspectral image cube. In this paper we present an overview of the sensor and its deployment, describe the processing steps required to produce coregistered hyperspectral cubes, and show detection results for targets viewed during the Aberdeen Collection Experiment (ACE).

  1. A Field Portable Hyperspectral Goniometer for Coastal Characterization

    NASA Technical Reports Server (NTRS)

    Bachmann, Charles M.; Gray, Deric; Abelev, Andrei; Philpot, William; Fusina, Robert A.; Musser, Joseph A.; Vermillion, Michael; Doctor, Katarina; White, Maurice; Georgiev, Georgi

    2012-01-01

    During an airborne multi-sensor remote sensing experiment at the Virginia Coast Reserve (VCR) Long Term Ecological Research (LTER) site in June 2011 (VCR '11), first measurements were taken with the new NRL Goniometer for Outdoor Portable Hyperspectral Earth Reflectance (GOPHER). GOPHER measures the angular distribution of hyperspectral reflectance. GOPHER was constructed for NRL by Spectra Vista Corporation (SVC) and the University of Lethbridge through a capital equipment purchase in 2010. The GOPHER spectrometer is an SVC HR -1024, which measures hyperspectral reflectance over the range from 350 -2500 nm, the visible, near infrared, and short-wave infrared. During measurements, the spectrometer travels along a zenith quarter -arc track that can rotate in azimuth, allowing for measurement of the bi-directional reflectance distribution function (BRDF) over the whole hemisphere. The zenith arc has a radius of approximately 2m, and the spectrometer scan pattern can be programmed on the fly during calibration and validation efforts. The spectrometer and zenith arc assembly can be raised and lowered along a mast to allow for measurement of uneven terrain or vegetation canopies of moderate height. Hydraulics on the chassis allow for leveling of the instrument in the field. At just over 400 lbs, GOPHER is a field portable instrument and can be transformed into a compact trailer assembly for movement over long distances in the field.

  2. Hyperspectral sensor for analysis of gases in the atmosphere (HYGAS)

    NASA Astrophysics Data System (ADS)

    Harig, R.; Keens, A.; Rusch, P.; Gerhard, J.; Sabbah, S.

    2010-04-01

    Remote sensing by infrared spectroscopy allows identification and quantification of atmospheric gases as well as airborne pollutants. An application of the method that has gained increased interest in recent years is remote sensing of hazardous gases. If hazardous compounds are released into the atmosphere, for example in the case of a chemical accident, emergency response forces require information about the released compounds immediately in order to take appropriate measures to protect workers, residents, and the environment. A hyperspectral sensor allows identification and visualisation of hazardous clouds in the atmosphere from long distances. The image of a cloud allows an assessment of the dimensions and the dispersion of a cloud. In addition, the source of a cloud may be located. A hyperspectral sensor based on an imaging Fourier-transform spectrometer with a focal plane array detector is currently being developed for this application. Compared to conventional spectrometers, hyperspectral systems allow the use of spatial information in addition to spectral information. In addition to the application of remote sensing of hazardous gases, the system may be applied in other fields of research such as the detection of liquids and atmospheric measurements. In this work, the HYGAS system and first results of measurements are presented.

  3. Hyperspectral and thermal methodologies applied to landslide monitoring

    NASA Astrophysics Data System (ADS)

    Vellico, Michela; Sterzai, Paolo; Pietrapertosa, Carla; Mora, Paolo; Berti, Matteo; Corsini, Alessandro; Ronchetti, Francesco; Giannini, Luciano; Vaselli, Orlando

    2010-05-01

    Landslide monitoring is a very actual topic. Landslides are a widespread phenomenon over the European territory and these phenomena have been responsible of huge economic losses. The aim of the WISELAND research project (Integrated Airborne and Wireless Sensor Network systems for Landslide Monitoring), funded by the Italian Government, is to test new monitoring techniques capable to rapidly and successfully characterize large landslides in fine soils. Two active earthflows in the Northern Italian Appenines have been chosen as test sites and investigated: Silla (Bologna Province) and Valoria (Modena Province). The project implies the use of remote sensing methodologies, with particular focus on the joint use of airborne Lidar, hyperspectral and thermal systems. These innovative techniques give promising results, since they allow to detect the principal landslide components and to evaluate the spatial distribution of parameters relevant to landslide dynamics such as surface water content and roughness. In this paper we put the attention on the response of the terrain related to the use of a hyperspectral system and its integration with the complementary information obtained using a thermal sensor. The potentiality of a hyperspectral dataset acquired in the VNIR (Visible Near Infrared field) and of the spectral response of the terrain could be high since they give important information both on the soil and on the vegetation status. Several significant indexes can be calculated, such as NDVI, obtained considering a band in the Red field and a band in the Infrared field; it gives information on the vegetation health and indirectly on the water content of soils. This is a key point that bridges hyperspectral and thermal datasets. Thermal infrared data are closely related to soil moisture, one of the most important parameter affecting surface stability in soil slopes. Effective stresses and shear strength in unsaturated soils are directly related to water content, and

  4. Littoral assessment of mine burial signatures (LAMBS): buried-landmine hyperspectral data collections

    NASA Astrophysics Data System (ADS)

    Kenton, Arthur C.; Geci, Duane M.; McDonald, James A.; Ray, Kristofer J.; Thomas, Clayton M.; Holloway, John H., Jr.; Petee, Danny A.; Witherspoon, Ned H.

    2003-09-01

    The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies project's Littoral Assessment of Mine Burial Signatures (LAMBS) contract is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines located in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 μm) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. The LAMBS program further expands the hyperspectral database previously collected and analyzed on the U.S. Army's Hyperspectral Mine Detection Phenomenology program [see "Detection of Land Mines with Hyperspectral Data," and "Hyperspectral Mine Detection Phenomenology Program," Proc. SPIE Vol. 3710, pp 917-928 and 819-829, AeroSense April 1999] to littoral areas where tidal, surf, and wind action can additionally modify spectral signatures. This work summarizes the LAMBS buried mine collections conducted at three beach sites - an inland bay beach site (Eglin AFB, FL, Site A-22), an Atlantic beach site (Duck, NC), and a Gulf beach site (Eglin AFB, FL, Site A-15). Characteristics of the spectral signatures of the various dry and damp beach sands are presented. These are then compared to buried land mine signatures observed for the tested background types, burial ages, and environmental conditions experienced.

  5. Hyperspectral imaging with liquid-crystal tunable filter for biological and agricultural assessment

    NASA Astrophysics Data System (ADS)

    Mao, Chengye; Heitschmidt, Jerry

    1999-01-01

    A hyperspectral imaging system has been developed to provide the capability of both airborne and ground/laboratory data acquisitions. The system consists of modular front imaging optics with a liquid crystal tunable filter (LCTF), a CCD video camera, a frame grabber and a portable computer system. The spectral range is form 450 nm to 750 nm with a 10 nm bandpass for each band acquired. The system can capture different spectral images at a rate up to 14 images per second. Hyperspectral imaging with an LCTF provides a new method for hyperspectral image acquisition. The system allows the user to define a wavelength sequence of up to thirty-two spectrums specifically required for individual application, and can quickly switch from the current wavelength to the next during automated image acquisition. Hyperspectral images of crop fields, vegetation, fruits, and meat were successfully captured during laboratory experiments and airborne image acquisition. The constructed spectral image cube not only shows the spatial features of the target, but also reveals the individual pixels with unique spectral signatures. The imaging system with LCTF is, therefore, very useful in biological and agricultural assessment for detecting variations in crop fields, or defects in samples and products.

  6. A practical approach to LWIR wafer-level optics for thermal imaging systems

    NASA Astrophysics Data System (ADS)

    Symmons, Alan; Pini, Ray

    2013-06-01

    The development and implementation of wafer level packaging for commercial microbolometers has opened the pathway towards full wafer-based thermal imaging systems. The next challenge in development is moving from discrete element LWIR imaging systems to a wafer based optical system, similar to lens assemblies found in cell phone cameras. This paper will compare a typical high volume thermal imaging design manufactured from discrete lens elements to a similar design optimized for manufacture through a wafer based approach. We will explore both performance and cost tradeoffs as well as review the manufacturability of all designs.

  7. Potential of Airborne Imaging Spectroscopy at Czechglobe

    NASA Astrophysics Data System (ADS)

    Hanuš, J.; Fabiánek, T.; Fajmon, L.

    2016-06-01

    Ecosystems, their services, structures and functions are affected by complex environmental processes, which are both natural and human-induced and globally changing. In order to understand how ecosystems behave in globally changing environment, it is important to monitor the current status of ecosystems and their structural and functional changes in time and space. An essential tool allowing monitoring of ecosystems is remote sensing (RS). Many ecosystems variables are being translated into a spectral response recorded by RS instruments. It is however important to understand the complexity and synergies of the key ecosystem variables influencing the reflected signal. This can be achieved by analysing high resolution RS data from multiple sources acquired simultaneously from the same platform. Such a system has been recently built at CzechGlobe - Global Change Research Institute (The Czech Academy of Sciences). CzechGlobe has been significantly extending its research infrastructure in the last years, which allows advanced monitoring of ecosystem changes at hierarchical levels spanning from molecules to entire ecosystems. One of the CzechGlobe components is a laboratory of imaging spectroscopy. The laboratory is now operating a new platform for advanced remote sensing observations called FLIS (Flying Laboratory of Imaging Spectroscopy). FLIS consists of an airborne carrier equipped with passive RS systems. The core instrument of FLIS is a hyperspectral imaging system provided by Itres Ltd. The hyperspectral system consists of three spectroradiometers (CASI 1500, SASI 600 and TASI 600) that cover the reflective spectral range from 380 to 2450 nm, as well as the thermal range from 8 to 11.5 μm. The airborne platform is prepared for mounting of full-waveform laser scanner Riegl-Q780 as well, however a laser scanner is not a permanent part of FLIS. In 2014 the installation of the hyperspectral scanners was completed and the first flights were carried out with all

  8. Hyperspectral mapping of crop and soils for precision agriculture

    NASA Astrophysics Data System (ADS)

    Whiting, Michael L.; Ustin, Susan L.; Zarco-Tejada, Pablo; Palacios-Orueta, Alicia; Vanderbilt, Vern C.

    2006-08-01

    Precision agriculture requires high spectral and spatial resolution imagery for advanced analyses of crop and soil conditions to increase environmental protection and producers' sustainability. GIS models that anticipate crop responses to nutrients, water, and pesticides require high spatial detail to generate application prescription maps. While the added precision of geo-spatial interpolation to field scouting generates improved zone maps and are an improvement over field-wide applications, it is limited in detail due to expense, and lacks the high precision required for pixel level applications. Multi-spectral imagery gives the spatial detail required, but broad band indexes are not sensitive to many variables in the crop and soil environment. Hyperspectral imagery provides both the spatial detail of airborne imagery and spectral resolution for spectroscopic and narrow band analysis techniques developed over recent decades in the laboratory that will advance precise determination of water and bio-physical properties of crops and soils. For several years, we have conducted remote sensing investigations to improve cotton production through field spectrometer measurements, and plant and soil samples in commercial fields and crop trials. We have developed spectral analyses techniques for plant and soil conditions through determination of crop water status, effectiveness of pre-harvest defoliant applications, and soil characterizations. We present the most promising of these spectroscopic absorption and narrow band index techniques, and their application to airborne hyperspectral imagery in mapping the variability in crops and soils.

  9. Hyperspectral digital holography of microobjects

    NASA Astrophysics Data System (ADS)

    Kalenkov, Sergey G.; Kalenkov, Georgy S.; Shtanko, Alexander E.

    2015-03-01

    Novel method is suggested for a hyperspectral wave field holographic recording, based on asymmetrical Fourier spectrometer with a flat microobject placed in one of its arms. The output signal, which is the interference of the reference field with the field diffracted by the object, is registered by CCD. The process of recording is reduced to consecutive registration of two-dimensional interferograms by changing the optical length of the reference arm of the interferometer. One-dimensional Fourier transform of the interferogram in each pixel gives a spatial distribution of the complex amplitude for all spectral components of a hyperspectral object field. Inverse Fresnel transform of this field gives a hyperspectral object field in the object plane. Hyperspectral amplitude and average-phase profile images of standard microscope samples obtained experimentally are presented. Coloring, Fellgett's advantage and speckle noise reduction are discussed.

  10. Hyperspectral image analysis. A tutorial.

    PubMed

    Amigo, José Manuel; Babamoradi, Hamid; Elcoroaristizabal, Saioa

    2015-10-01

    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case. PMID:26481986

  11. Multisensor airborne imagery collection and processing onboard small unmanned systems

    NASA Astrophysics Data System (ADS)

    Linne von Berg, Dale; Anderson, Scott A.; Bird, Alan; Holt, Niel; Kruer, Melvin; Walls, Thomas J.; Wilson, Michael L.

    2010-04-01

    FEATHAR (Fusion, Exploitation, Algorithms, and Targeting for High-Altitude Reconnaissance) is an ONR funded effort to develop and test new tactical sensor systems specifically designed for small manned and unmanned platforms (payload weight < 50 lbs). This program is being directed and executed by the Naval Research Laboratory (NRL) in conjunction with the Space Dynamics Laboratory (SDL). FEATHAR has developed and integrated EyePod, a combined long-wave infrared (LWIR) and visible to near infrared (VNIR) optical survey & inspection system, with NuSAR, a combined dual band synthetic aperture radar (SAR) system. These sensors are being tested in conjunction with other ground and airborne sensor systems to demonstrate intelligent real-time cross-sensor cueing and in-air data fusion. Results from test flights of the EyePod and NuSAR sensors will be presented.

  12. Assessment of target detection limits in hyperspectral data

    NASA Astrophysics Data System (ADS)

    Gross, W.; Boehler, J.; Schilling, H.; Middelmann, W.; Weyermann, J.; Wellig, P.; Oechslin, R.; Kneubuehler, M.

    2015-10-01

    Hyperspectral remote sensing data can be used for civil and military applications to detect and classify target objects that cannot be reliably separated using broadband sensors. The comparably low spatial resolution is compensated by the fact that small targets, even below image resolution, can still be classified. The goal of this paper is to determine the target size to spatial resolution ratio for successful classification of different target and background materials. Airborne hyperspectral data is used to simulate data with known mixture ratios and to estimate the detection threshold for given false alarm rates. The data was collected in July 2014 over Greding, Germany, using airborne aisaEAGLE and aisaHAWK hyperspectral sensors. On the ground, various target materials were placed on natural background. The targets were four quadratic molton patches with an edge length of 7 meters in the colors black, white, grey and green. Also, two different types of polyethylene (camouflage nets) with an edge length of approximately 5.5 meters were deployed. Synthetic data is generated from the original data using spectral mixtures. Target signatures are linearly combined with different background materials in specific ratios. The simulated mixtures are appended to the original data and the target areas are removed for evaluation. Commonly used classification algorithms, e.g. Matched Filtering, Adaptive Cosine Estimator are used to determine the detection limit. Fixed false alarm rates are employed to find and analyze certain regions where false alarms usually occur first. A combination of 18 targets and 12 backgrounds is analyzed for three VNIR and two SWIR data sets of the same area.

  13. Airborne hyperspectral imagery for mapping crop yield variability

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information concerning the spatial variation in crop yield has become necessary for site-specific crop management. Traditional satellite imagery has long been used to monitor crop growing conditions and to estimate crop yields over large geographic areas. However, this type of imagery has limited us...

  14. Testing different classification methods in airborne hyperspectral imagery processing.

    PubMed

    Kozoderov, Vladimir V; Dmitriev, Egor V

    2016-05-16

    To enhance the efficiency of machine-learning algorithms of optical remote sensing imagery processing, optimization techniques are evolved of the land surface objects pattern recognition. Different methods of supervised classification are considered for these purposes, including the metrical classifier operating with Euclidean distance between any points of the multi-dimensional feature space given by registered spectra, the K-nearest neighbors classifier based on a majority vote for neighboring pixels of the recognized objects, the Bayesian classifier of statistical decision making, the Support Vector Machine classifier dealing with stable solutions of the mini-max optimization problem and their different modifications. We describe the related techniques applied for selected test regions to compare the listed classifiers. PMID:27409968

  15. AIRBORNE HYPERSPECTRAL IDENTIFICATION OF INVASIVE AND OPPORTUNISTIC WETLANDS PLANT SPECIES

    EPA Science Inventory

    Coastal wetlands are among the most fragmented and disturbed ecosystems and the Great Lakes are no exception. One possible result is the observed increase in the presence and dominance of invasive and other opportunistic plant species, such as the common reed (Phragmites australi...

  16. The Thermal Infrared Compact Imaging Spectrometer (TIRCIS): a follow-on to the Space Ultra Compact Hyperspectral Imager (SUCHI)

    NASA Astrophysics Data System (ADS)

    Crites, S. T.; Wright, R.; Lucey, P. G.; Chan, J.; Gabrieli, A.; Garbeil, H.; Horton, K. A.; Imai-Hong, A. K. R.; Pilger, E. J.; Wood, M.; Yoneshige, L.

    2015-05-01

    The Thermal Infrared Compact Imaging Spectrometer (TIRCIS) is a long wave infrared (LWIR, 8-14 microns) hyperspectral imager designed as the follow-on to the University of Hawaii's SUCHI (Space Ultra Compact Hyperspectral Imager). SUCHI is a low-mass (<9kg), low-volume (10x12x40cm3) LWIR spectrometer designed as the primary payload on the University of Hawaii-built 'HiakaSat' microsatellite. SUCHI is based on a variable-gap Fabry Perot interferometer employed as a Fourier transform spectrometer with images collected by a commercial off-the-shelf microbolometer contained inside a 1-atm sealed vessel. The sensor has been fully integrated with the HiakaSat microsatellite and is awaiting launch in 2015. The TIRCIS instrument is based on the same principles but takes lessons learned from SUCHI and applies them to a new design with improvements in spatial resolution, spectral resolution and spectral responsivity. The TIRCIS instrument is based on an uncooled microbolometer array with custom detector coatings to enhance responsivity towards 7 microns. Like SUCHI, TIRCIS utilizes a variable-gap Fabry Perot interferometer to create the spectra, but three different interferometer wedges with varying slopes resulting in spectral resolution ranging from 44 cm-1 to 6.5 cm-1 will be tested to explore tradeoffs between spectral resolution and sensitivity. TIRCIS is designed to achieve 120 m spatial resolution, compared with 230 m for SUCHI, from a theoretical 500 km orbit. It will be used for ground and aircraft data collection but will undergo environmental testing to demonstrate its relevance to the space environment. TIRCIS has been fully designed and is entering fabrication, with an operational instrument to be delivered in October, 2015.

  17. Commodity cluster and hardware-based massively parallel implementations of hyperspectral imaging algorithms

    NASA Astrophysics Data System (ADS)

    Plaza, Antonio; Chang, Chein-I.; Plaza, Javier; Valencia, David

    2006-05-01

    The incorporation of hyperspectral sensors aboard airborne/satellite platforms is currently producing a nearly continual stream of multidimensional image data, and this high data volume has soon introduced new processing challenges. The price paid for the wealth spatial and spectral information available from hyperspectral sensors is the enormous amounts of data that they generate. Several applications exist, however, where having the desired information calculated quickly enough for practical use is highly desirable. High computing performance of algorithm analysis is particularly important in homeland defense and security applications, in which swift decisions often involve detection of (sub-pixel) military targets (including hostile weaponry, camouflage, concealment, and decoys) or chemical/biological agents. In order to speed-up computational performance of hyperspectral imaging algorithms, this paper develops several fast parallel data processing techniques. Techniques include four classes of algorithms: (1) unsupervised classification, (2) spectral unmixing, and (3) automatic target recognition, and (4) onboard data compression. A massively parallel Beowulf cluster (Thunderhead) at NASA's Goddard Space Flight Center in Maryland is used to measure parallel performance of the proposed algorithms. In order to explore the viability of developing onboard, real-time hyperspectral data compression algorithms, a Xilinx Virtex-II field programmable gate array (FPGA) is also used in experiments. Our quantitative and comparative assessment of parallel techniques and strategies may help image analysts in selection of parallel hyperspectral algorithms for specific applications.

  18. Real-time lossy compression of hyperspectral images using iterative error analysis on graphics processing units

    NASA Astrophysics Data System (ADS)

    Sánchez, Sergio; Plaza, Antonio

    2012-06-01

    Hyperspectral image compression is an important task in remotely sensed Earth Observation as the dimensionality of this kind of image data is ever increasing. This requires on-board compression in order to optimize the donwlink connection when sending the data to Earth. A successful algorithm to perform lossy compression of remotely sensed hyperspectral data is the iterative error analysis (IEA) algorithm, which applies an iterative process which allows controlling the amount of information loss and compression ratio depending on the number of iterations. This algorithm, which is based on spectral unmixing concepts, can be computationally expensive for hyperspectral images with high dimensionality. In this paper, we develop a new parallel implementation of the IEA algorithm for hyperspectral image compression on graphics processing units (GPUs). The proposed implementation is tested on several different GPUs from NVidia, and is shown to exhibit real-time performance in the analysis of an Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) data sets collected over different locations. The proposed algorithm and its parallel GPU implementation represent a significant advance towards real-time onboard (lossy) compression of hyperspectral data where the quality of the compression can be also adjusted in real-time.

  19. Analysis of hyper-spectral AVIRIS image data over a mixed-conifer forest in Maine

    NASA Technical Reports Server (NTRS)

    Lawrence, William T.; Shimabukuro, Yosio E.; Gao, Bo-Cai

    1993-01-01

    An introduction to some of the potential uses of hyperspectral data for ecosystem analysis is presented. The examples given are derived from a digital dataset acquired over a sub-boreal forest in central Maine in 1990 by the NASA-JPL Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument gathers data from 400 to 2500 nm in 224 channels at bandwidths of approximately 10 nm. As a preview to the uses of the hyperspectral data, several products from this dataset were extracted. They range from the traditional false color composite made from simulated Thematic Mapper bands and the well known normalized difference vegetation index to much more exotic products such as fractions of vegetation, soil and shade based on linear spectral mixing models and estimates of the leaf water content at the landscape level derived using spectrum-matching techniques. Our research and that of many others indicates that the hyperspectral datasets carry much important information which is only beginning to be understood. This analysis gives an initial indication of the utility of hyperspectral data. Much work still remains to be done in algorithm development and in understanding the physics behind the complex information signal carried in the hyperspectral datasets. This work must be carried out to provide the fullest science support for high spectral resolution data to be acquired by many of the instruments to be launched as part of the Earth Observing System program in the mid-1990's.

  20. Hyperspectral data application for peat forest monitoring in Central Kalimantan, Indonesia

    NASA Astrophysics Data System (ADS)

    Ohki, Takashi; Yoshida, Keigo; Sekine, Hozuma; Takayama, Taichi; Takeda, Tomomi; Hirose, Kazuyo; Evri, Muhammad; Osaki, Mitsuru

    2012-11-01

    Peatland is a large CO2 reservoir which accumulates 2000Gt of CO2, which is equal to 30% of global soil carbon. However, it has been becoming a large CO2 emission source because of peat decomposition and fire due to drainage water. This is caused by social activities such as canalizing. Especially, in Indonesia, peat swamp forests cover considerable portions of Kalimantan and 37.5% of CO2 emission source is peatland (DNPI, 2010). To take measures, it is necessary to conduct appropriate assessment of CO2 emission in broad peat swamp forest. Because hyperspectral data possess higher spectral resolutions, it is expected to evaluate the detailed forest conditions. We develop a method to assess carbon emission from peat swamp forest by using hyperspectral data in Central Kalimantan, Indonesia. Specifically, we estimate 1) forestry biomass and 2) underground water level expected as an indicator of CO2 emission from peat. In this research, we use the image taken by HyMAP which is one of the airborne hyperspectral sensors. Since the research area differs in forest types and conditions due to the past forest fire and disturbance, forest types are classified with the sparse linear discriminant analysis. Then, we conduct a biomass estimation using Normalized Difference Spectral Index (NDSI). We also analyze the relationship between underground water level and Normalized Difference Water Index (NDWI), and find the possibility of underground water level estimation with hyperspectral data. We plan to establish a highly developed method to apply hyperspectral sensor to peatland monitoring system.

  1. WAR HORSE (wide-area reconnaissance: hyperspectral overhead real-time surveillance experiment)

    NASA Astrophysics Data System (ADS)

    Stellman, Christopher M.; Olchowski, Frederick M.; Michalowicz, Joseph V.

    2001-10-01

    In recent years the Optical Sciences Division, Naval Research Laboratory (NRL) has been involved in the development of real-time hyperspectral detection, cueing, target location, and target designation capabilities. Under the Dark HORSE program it was demonstrated that a hyperspectral sensor could be used for the autonomous, real- time detection of airborne and military ground targets. This work has culminated in WAR HORSE, an autonomous real-time visible hyperspectral target detection system that has been configured for us on a Predator Unmanned Air Vehicle (UAV). The sensor system provides Predator with the ability to detect manmade objects in areas of natural background. The system consists of a visible hyperspectral imaging sensor, a real-time signal processor, a high-resolution visible line scan camera, an interface and control software application, and a data storage medium. The system is coupled to an on- board GPS/INS to provide target geo-location information and relevant data is transmitted to a ground station using line- of-sight down-link capabilities. The presented paper will provide an overview of the WAR HORSE sensor system hardware components and their integration aboard a Predator UAV. In addition, the results of a recently completed demonstration aboard the Predator UAV will be provided. This demonstration represents the first autonomous real-time hyperspectral target detection system to flown aboard a Predator UAV.

  2. Hyperspectral Imager-Tracker

    NASA Technical Reports Server (NTRS)

    Agurok, Llya

    2013-01-01

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

  3. Clusters versus FPGAs for spectral mixture analysis-based lossy hyperspectral data compression

    NASA Astrophysics Data System (ADS)

    Plaza, Antonio J.

    2008-08-01

    The increasing number of airborne and satellite platforms that incorporate hyperspectral imaging spectrometers has soon created the need for efficient storage, transmission and data compression methodologies. In particular, hyperspectral data compression is expected to play a crucial role in many remote sensing applications. Many efforts have been devoted to designing and developing lossless and lossy algorithms for hyperspectral imagery. However, most available lossy compression approaches have largely overlooked the impact of mixed pixels and subpixel targets, which can be accurately modeled and uncovered by resorting to the wealth of spectral information provided by hyperspectral image data. In this paper, we develop a simple lossy compression technique which relies on the concept of spectral unmixing, one of the most popular approaches to deal with mixed pixels and subpixel targets in hyperspectral analysis. The proposed method uses a two-stage approach in which the purest spectral signatures (also called endmembers) are first extracted from the input data, and then used to express mixed pixels as linear combinations of endmembers. Analytical and experimental results are presented in the context of a real application, using hyperspectral data collected by NASA's Jet Propulsion Laboratory over the World Trade Center area in New York City, right after the terrorist attacks of September 11th. These data are used in this work to evaluate the impact of compression using different methods on spectral signature quality for accurate detection of hot spot fires. Two parallel implementations are developed for the proposed lossy compression algorithm: a multiprocessor implementation tested on Thunderhead, a massively parallel Beowulf cluster at NASA's Goddard Space Flight Center, and a hardware implementation developed on a Xilinx Virtex-II FPGA device. Combined, these parts offer a thoughtful perspective on the potential and emerging challenges of incorporating parallel

  4. Hyperspectral band selection based on parallel particle swarm optimization and impurity function band prioritization schemes

    NASA Astrophysics Data System (ADS)

    Chang, Yang-Lang; Liu, Jin-Nan; Chen, Yen-Lin; Chang, Wen-Yen; Hsieh, Tung-Ju; Huang, Bormin

    2014-01-01

    In recent years, satellite imaging technologies have resulted in an increased number of bands acquired by hyperspectral sensors, greatly advancing the field of remote sensing. Accordingly, owing to the increasing number of bands, band selection in hyperspectral imagery for dimension reduction is important. This paper presents a framework for band selection in hyperspectral imagery that uses two techniques, referred to as particle swarm optimization (PSO) band selection and the impurity function band prioritization (IFBP) method. With the PSO band selection algorithm, highly correlated bands of hyperspectral imagery can first be grouped into modules to coarsely reduce high-dimensional datasets. Then, these highly correlated band modules are analyzed with the IFBP method to finely select the most important feature bands from the hyperspectral imagery dataset. However, PSO band selection is a time-consuming procedure when the number of hyperspectral bands is very large. Hence, this paper proposes a parallel computing version of PSO, namely parallel PSO (PPSO), using a modern graphics processing unit (GPU) architecture with NVIDIA's compute unified device architecture technology to improve the computational speed of PSO processes. The natural parallelism of the proposed PPSO lies in the fact that each particle can be regarded as an independent agent. Parallel computation benefits the algorithm by providing each agent with a parallel processor. The intrinsic parallel characteristics embedded in PPSO are, therefore, suitable for parallel computation. The effectiveness of the proposed PPSO is evaluated through the use of airborne visible/infrared imaging spectrometer hyperspectral images. The performance of PPSO is validated using the supervised K-nearest neighbor classifier. The experimental results demonstrate that the proposed PPSO/IFBP band selection method can not only improve computational speed, but also offer a satisfactory classification performance.

  5. Improving the detection task performance of a LWIR imaging system through the use of wavefront coding

    NASA Astrophysics Data System (ADS)

    Gross, Kevin A.; Kubala, Kenny

    2007-04-01

    In a traditional optical system the imaging performance is maximized at a single point in the operational space. This characteristic leads to maximizing the probability of detection if the object is on axis, at the designed conjugate, with the designed operational temperature and if the system components are manufactured without error in form and alignment. Due to the many factors that influence the system's image quality the probability of detection will decrease away from this peak value. An infrared imaging system is presented that statistically creates a higher probability of detection over the complete operational space for the Hotelling observer. The system is enabled through the use of wavefront coding, a computational imaging technology in which optics, mechanics, detection and signal processing are combined to enable LWIR imaging systems to be realized with detection task performance that is difficult or impossible to obtain in the optical domain alone. The basic principles of statistical decision theory will be presented along with a specific example of how wavefront coding technology can enable improved performance and reduced sensitivity to some of the fundamental constraints inherent in LWIR systems.

  6. Modeling precision and accuracy of a LWIR microgrid array imaging polarimeter

    NASA Astrophysics Data System (ADS)

    Boger, James K.; Tyo, J. Scott; Ratliff, Bradley M.; Fetrow, Matthew P.; Black, Wiley T.; Kumar, Rakesh

    2005-08-01

    Long-wave infrared (LWIR) imaging is a prominent and useful technique for remote sensing applications. Moreover, polarization imaging has been shown to provide additional information about the imaged scene. However, polarization estimation requires that multiple measurements be made of each observed scene point under optically different conditions. This challenging measurement strategy makes the polarization estimates prone to error. The sources of this error differ depending upon the type of measurement scheme used. In this paper, we examine one particular measurement scheme, namely, a simultaneous multiple-measurement imaging polarimeter (SIP) using a microgrid polarizer array. The imager is composed of a microgrid polarizer masking a LWIR HgCdTe focal plane array (operating at 8.3-9.3 μm), and is able to make simultaneous modulated scene measurements. In this paper we present an analytical model that is used to predict the performance of the system in order to help interpret real results. This model is radiometrically accurate and accounts for the temperature of the camera system optics, spatial nonuniformity and drift, optical resolution and other sources of noise. This model is then used in simulation to validate it against laboratory measurements. The precision and accuracy of the SIP instrument is then studied.

  7. High Performance MWIR and LWIR (Hg,Cd)Te Heterostructure Photodiodes

    NASA Astrophysics Data System (ADS)

    Vydyanath, H. R.; Ward, P. B.; Hampton, S. R.; Fishman, L.; Slawinski, J.; Devaney, C.; Ellsworth, J.; Krueger, T.

    1986-11-01

    (Hg,Cd)Te heterostructures have been grown liquid phase epitaxially from tellurium rich solutions on CdTe and (Cd,Zn)Te substrates. Both MWIR detectors sensitive in the 3-5 μm spectral region and LWIR detectors sensitive in the 8-14 µm spectral region have been fabricated in the heterostructures. Detectors with high RoA (low noise) and high quantum efficiency (high signal) have been fabricated. For the MWIR detectors, quantum efficiency in excess of 75 percent and RoA values in excess of 107 ohm cm2 at 80K have been demonstrated for λCo ~ 5.5 µm. For the LWIR detectors RoA values of ~ 106 ohm cm2 have been demonstrated at 40K for λCo ~ 11 μm. A correlation of the trap energies established via carrier lifetime and DLTS measurements with the depletion width - capacitance data indicates the p-n junction to be located at the heterostructure interface.

  8. Temperature dependence characteristics of dark current for arsenic doped LWIR HgCdTe detectors

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Chen, Xiaoshuang; Hu, Weida; Ye, Zhenghua; Lin, Chun; Hu, Xiaoning; Guo, Jin; Xie, Feng; Zhou, Jie; Liang, Jian; Wang, Xiaofang; Lu, Wei

    2013-11-01

    Resistance-voltage (R-V) curves of arsenic doped long-wavelength infrared (LWIR) Mercury Cadmium Telluride (HgCdTe) photodiodes were measured in the temperature range of 59-92 K. The dark current characteristics of HgCdTe junction diode are presented by using a simultaneous-mode nonlinear fitting method. The observed R-V characteristics have been shown in agreement with the theoretical calculation by taking into account the contributions: (i) diffusion mechanism (Rdiff), (ii) generation-recombination mechanism (Rgr) in the depletion region, (iii) trap-assisted tunneling mechanism (Rtat), and (iv) band-to-band tunneling mechanism (Rbbt). Six characteristic parameters as function of temperature are extracted from the measured current-voltage (I-V) curves by considering the dominant current mechanisms under different bias levels. The fitted current components under different temperatures show that, as the temperature rises, the contribution to the dominant dark current component around maximum dynamic resistance range is changed from the trap-assisted tunneling and diffusion currents to the generation recombination effect. This change indicates that the dark current component may mainly be caused by the generation recombination current, which limits the performance of arsenic doped LWIR HgCdTe detectors.

  9. Convolutional neural network approach for buried target recognition in FL-LWIR imagery

    NASA Astrophysics Data System (ADS)

    Stone, K.; Keller, J. M.

    2014-05-01

    A convolutional neural network (CNN) approach to recognition of buried explosive hazards in forward-looking long-wave infrared (FL-LWIR) imagery is presented. The convolutional filters in the first layer of the network are learned in the frequency domain, making enforcement of zero-phase and zero-dc response characteristics much easier. The spatial domain representations of the filters are forced to have unit l2 norm, and penalty terms are added to the online gradient descent update to encourage orthonormality among the convolutional filters, as well smooth first and second order derivatives in the spatial domain. The impact of these modifications on the generalization performance of the CNN model is investigated. The CNN approach is compared to a second recognition algorithm utilizing shearlet and log-gabor decomposition of the image coupled with cell-structured feature extraction and support vector machine classification. Results are presented for multiple FL-LWIR data sets recently collected from US Army test sites. These data sets include vehicle position information allowing accurate transformation between image and world coordinates and realistic evaluation of detection and false alarm rates.

  10. 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.

  11. Signal processing algorithms for staring single pixel hyperspectral sensors

    NASA Astrophysics Data System (ADS)

    Manolakis, Dimitris; Rossacci, Michael; O'Donnell, Erin; D'Amico, Francis M.

    2006-08-01

    Remote sensing of chemical warfare agents (CWA) with stand-off hyperspectral sensors has a wide range of civilian and military applications. These sensors exploit the spectral changes in the ambient photon flux produced thermal emission or absorption after passage through a region containing the CWA cloud. In this work we focus on (a) staring single-pixel sensors that sample their field of view at regular intervals of time to produce a time series of spectra and (b) scanning single or multiple pixel sensors that sample their FOV as they scan. The main objective of signal processing algorithms is to determine if and when a CWA enters the FOV of the sensor. We shall first develop and evaluate algorithms for staring sensors following two different approaches. First, we will assume that no threat information is available and we design an adaptive anomaly detection algorithm to detect a statistically-significant change in the observed spectrum. The algorithm processes the observed spectra sequentially-in-time, estimates adaptively the background, and checks whether the next spectrum differs significantly from the background based on the Mahalanobis distance or the distance from the background subspace. In the second approach, we will assume that we know the spectral signature of the CWA and develop sequential-in-time adaptive matched filter detectors. In both cases, we assume that the sensor starts its operation before the release of the CWA; otherwise, staring at a nearby CWA-free area is required for background estimation. Experimental evaluation and comparison of the proposed algorithms is accomplished using data from a long-wave infrared (LWIR) Fourier transform spectrometer.

  12. Experimental results from an airborne static Fourier transform imaging spectrometer.

    PubMed

    Ferrec, Yann; Taboury, Jean; Sauer, Hervé; Chavel, Pierre; Fournet, Pierre; Coudrain, Christophe; Deschamps, Joël; Primot, Jérôme

    2011-10-20

    A high étendue static Fourier transform spectral imager has been developed for airborne use. This imaging spectrometer, based on a Michelson interferometer with rooftop mirrors, is compact and robust and benefits from a high collection efficiency. Experimental airborne images were acquired in the visible domain. The processing chain to convert raw images to hyperspectral data is described, and airborne spectral images are presented. These experimental results show that the spectral resolution is close to the one expected, but also that the signal to noise ratio is limited by various phenomena (jitter, elevation fluctuations, and one parasitic image). We discuss the origin of those limitations and suggest solutions to circumvent them. PMID:22015418

  13. 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.

  14. Geometric correction of synchronous scanned Operational Modular Imaging Spectrometer II hyperspectral remote sensing images using spatial positioning data of an inertial navigation system

    NASA Astrophysics Data System (ADS)

    Zhou, Xiaohu; Neubauer, Franz; Zhao, Dong; Xu, Shichao

    2015-01-01

    The high-precision geometric correction of airborne hyperspectral remote sensing image processing was a hard nut to crack, and conventional methods of remote sensing image processing by selecting ground control points to correct the images are not suitable in the correction process of airborne hyperspectral image. The optical scanning system of an inertial measurement unit combined with differential global positioning system (IMU/DGPS) is introduced to correct the synchronous scanned Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing images. Posture parameters, which were synchronized with the OMIS II, were first obtained from the IMU/DGPS. Second, coordinate conversion and flight attitude parameters' calculations were conducted. Third, according to the imaging principle of OMIS II, mathematical correction was applied and the corrected image pixels were resampled. Then, better image processing results were achieved.

  15. Development of Hyperspectral Remote Sensing Capability For the Early Detection and Monitoring of Harmful Algal Blooms (HABs) in the Great Lakes

    NASA Technical Reports Server (NTRS)

    Lekki, John; Anderson, Robert; Nguyen, Quang-Viet; Demers, James; Leshkevich, George; Flatico, Joseph; Kojima, Jun

    2013-01-01

    Hyperspectral imagers have significant capability for detecting and classifying waterborne constituents. One particularly appropriate application of such instruments in the Great Lakes is to detect and monitor the development of potentially Harmful Algal Blooms (HABs). Two generations of small hyperspectral imagers have been built and tested for aircraft based monitoring of harmful algal blooms. In this paper a discussion of the two instruments as well as field studies conducted using these instruments will be presented. During the second field study, in situ reflectance data was obtained from the Research Vessel Lake Guardian in conjunction with reflectance data obtained with the hyperspectral imager from overflights of the same locations. A comparison of these two data sets shows that the airborne hyperspectral imager closely matches measurements obtained from instruments on the lake surface and thus positively supports its utilization for detecting and monitoring HABs.

  16. LWIR HgCdTe barrier photodiode with Auger-suppression

    NASA Astrophysics Data System (ADS)

    Kopytko, M.; Kębłowski, A.; Gawron, W.; Pusz, W.

    2016-03-01

    This paper reports on advanced metalorganic chemical vapor deposition (MOCVD) grown HgCdTe barrier photodiodes for long wave infrared (LWIR) application. The n+p+Bp πN+ device is a concept of a specific barrier bandgap architecture integrated with Auger-suppression as a good solution for high operating temperature (HOT) infrared detectors with high detectivity and sub-nanosecond time constant. The design approach, growth aspects and detector characterization of HgCdTe n+p+Bp πN+ barrier photodiodes operated with thermoelectric cooling (230 K) have been discussed in the paper. The influence of absorber thickness on the device’s properties has been analyzed in the experiment.

  17. Long-Wavelength Infrared (LWIR) Quantum Dot Infrared Photodetector (QDIP) Focal Plane Array

    NASA Technical Reports Server (NTRS)

    Gunapala, Sarath D.; Bandara, S. V.; Liu, J. K.; Hill, C. J.; Rafol, S. B.; Mumolo, J. M.; Shott, C. A.

    2006-01-01

    We have exploited the artificial atomlike properties of epitaxially self-assembled quantum dots for the development of high operating temperature long wavelength infrared (LWIR) focal plane arrays. Quantum dots are nanometer-scale islands that form spontaneously on a semiconductor substrate due to lattice mismatch. QDIPs are expected to outperform quantum well infrared detectors (QWIPs) and are expected to offer significant advantages over II-VI material based focal plane arrays. QDIPs are fabricated using robust wide bandgap III-V materials which are well suited to the production of highly uniform LWIR arrays. We have used molecular beam epitaxy (MBE) technology to grow multi-layer LWIR quantum dot structures based on the InAs/InGaAs/GaAs material system. JPL is building on its significant QWIP experience and is basically building a Dot-in-the-Well (DWELL) device design by embedding InAs quantum dots in a QWIP structure. This hybrid quantum dot/quantum well device offers additional control in wavelength tuning via control of dot-size and/or quantum well sizes. In addition the quantum wells can trap electrons and aide in ground state refilling. Recent measurements have shown a 10 times higher photoconductive gain than the typical QWIP device, which indirectly confirms the lower relaxation rate of excited electrons (photon bottleneck) in QDPs. Subsequent material and device improvements have demonstrated an absorption quantum efficiency (QE) of approx. 3%. Dot-in-the-well (DWELL) QDIPs were also experimentally shown to absorb both 45 deg. and normally incident light. Thus we have employed a reflection grating structure to further enhance the quantum efficiency. JPL has demonstrated wavelength control by progressively growing material and fabricating devices structures that have continuously increased in LWIR response. The most recent devices exhibit peak responsivity out to 8.1 microns. Peak detectivity of the 8.1 micrometer devices has reached approx. 1 x 10(exp 10

  18. Satellite Hyperspectral Imaging Simulation

    NASA Technical Reports Server (NTRS)

    Zanoni, Vicki; Stanley, Tom; Blonski, Slawomir; Cao, Changyong; Gasser, Jerry; Ryan, Robert

    1999-01-01

    Simulation of generic pushbroom satellite hyperspectral sensors have been performed to evaluate the potential performance and validation techniques for satellite systems such as COIS(NEMO), Warfighter-1(OrbView-4) and Hyperion(EO-1). The simulations start with a generation of synthetic scenes from material maps of studied terrain. Scene-reflected radiance is corrected for atmospheric effects and convolved with sensor spectral response using MODTRAN 4 radiance and transmissions calculations. Scene images are further convolved with point spread functions derived from Optical Transfer Functions (OTF's) of the sensor system. Photon noise and etectorr/electronics noise are added to the simulated images, which are also finally quantized to the sensor bit resolution. Studied scenes include bridges and straight roads used for evaluation of sensor spatial resolution, as well as fields of minerals, vegetation and manmade materials used for evaluation of sensor radiometric response and sensitivity. The scenes are simulated with various seasons and weather conditions. Signal-to-noise ratios and expected performance are estimated for typical satellite system specifications and are discussed for all the scenes.

  19. Medical hyperspectral imaging: a review

    NASA Astrophysics Data System (ADS)

    Lu, Guolan; Fei, Baowei

    2014-01-01

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

  20. Medical hyperspectral imaging: a review

    PubMed Central

    Lu, Guolan; Fei, Baowei

    2014-01-01

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

  1. Dislocations as a Noise Source in LWIR HgCdTe Photodiodes

    NASA Astrophysics Data System (ADS)

    Jóźwikowski, Krzysztof; Jóźwikowska, Alina; Martyniuk, Andrzej

    2016-02-01

    The effect of dislocation on the 1/f noise current in long-wavelength infrared (LWIR) reverse biased HgCdTe photodiodes working at liquid nitrogen (LN) temperature was analyzed theoretically by using a phenomenological model of dislocations as an additional Shockley-Read-Hall (SRH) generation-recombination (G-R) channel in heterostructure. Numerical analysis was involved to solve the set of transport equations in order to find a steady state values of physical parameters of the heterostructure. Next, the set of transport equations for fluctuations (TEFF) was formulated and solved to obtain the spectral densities (SD) of the fluctuations of electrical potential, quasi-Fermi levels, and temperature. The SD of mobility fluctuations, shot G-R noise, and thermal noise were also taken into account in TEFF. Additional expressions for SD of 1/f fluctuations of the G-R processes were derived. Numerical values of the SD of noise current were compared with the experimental results of Johnson et al. Theoretical analysis has shown that the dislocations increase the G-R processes and this way cause the growth of G-R dark current. Despite the fact that dislocations increase both shot G-R noise and 1/f G-R noise, the main cause of 1/f current noise in LN cooled LWIR photodiodes are fluctuations of the carriers mobility determined by 1/f fluctuations of relaxation times. As the noise current is proportional to the total diode current, growth of G-R dark current caused by dislocations leads to the growth of noise current.

  2. Fusion of remotely sensed data from airborne and ground-based sensors to enhance detection of cotton plants

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The study investigated the use of aerial multispectral imagery and ground-based hyperspectral data for the discrimination of different crop types and timely detection of cotton plants over large areas. Airborne multispectral imagery and ground-based spectral reflectance data were acquired at the sa...

  3. A new morphological anomaly detection algorithm for hyperspectral images and its GPU implementation

    NASA Astrophysics Data System (ADS)

    Paz, Abel; Plaza, Antonio

    2011-10-01

    Anomaly detection is considered a very important task for hyperspectral data exploitation. It is now routinely applied in many application domains, including defence and intelligence, public safety, precision agriculture, geology, or forestry. Many of these applications require timely responses for swift decisions which depend upon high computing performance of algorithm analysis. However, with the recent explosion in the amount and dimensionality of hyperspectral imagery, this problem calls for the incorporation of parallel computing techniques. In the past, clusters of computers have offered an attractive solution for fast anomaly detection in hyperspectral data sets already transmitted to Earth. However, these systems are expensive and difficult to adapt to on-board data processing scenarios, in which low-weight and low-power integrated components are essential to reduce mission payload and obtain analysis results in (near) real-time, i.e., at the same time as the data is collected by the sensor. An exciting new development in the field of commodity computing is the emergence of commodity graphics processing units (GPUs), which can now bridge the gap towards on-board processing of remotely sensed hyperspectral data. In this paper, we develop a new morphological algorithm for anomaly detection in hyperspectral images along with an efficient GPU implementation of the algorithm. The algorithm is implemented on latest-generation GPU architectures, and evaluated with regards to other anomaly detection algorithms using hyperspectral data collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the World Trade Center (WTC) in New York, five days after the terrorist attacks that collapsed the two main towers in the WTC complex. The proposed GPU implementation achieves real-time performance in the considered case study.

  4. Incorporating multiresolution analysis with multiclassifiers and decision fusion for hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    West, Terrance R.

    The ongoing development and increased affordability of hyperspectral sensors are increasing their utilization in a variety of applications, such as agricultural monitoring and decision making. Hyperspectral Automated Target Recognition (ATR) systems typically rely heavily on dimensionality reduction methods, and particularly intelligent reduction methods referred to as feature extraction techniques. This dissertation reports on the development, implementation, and testing of new hyperspectral analysis techniques for ATR systems, including their use in agricultural applications where ground truthed observations available for training the ATR system are typically very limited. This dissertation reports the design of effective methods for grouping and down-selecting Discrete Wavelet Transform (DWT) coefficients and the design of automated Wavelet Packet Decomposition (WPD) filter tree pruning methods for use within the framework of a Multiclassifiers and Decision Fusion (MCDF) ATR system. The efficacy of the DWT MCDF and WPD MCDF systems are compared to existing ATR methods commonly used in hyperspectral remote sensing applications. The newly developed methods' sensitivity to operating conditions, such as mother wavelet selection, decomposition level, and quantity and quality of available training data are also investigated. The newly developed ATR systems are applied to the problem of hyperspectral remote sensing of agricultural food crop contaminations either by airborne chemical application, specifically Glufosinate herbicide at varying concentrations applied to corn crops, or by biological infestation, specifically soybean rust disease in soybean crops. The DWT MCDF and WPD MCDF methods significantly outperform conventional hyperspectral ATR methods. For example, when detecting and classifying varying levels of soybean rust infestation, stepwise linear discriminant analysis, results in accuracies of approximately 30%-40%, but WPD MCDF methods result in accuracies

  5. Method for Retrieving Leaf Biochemical Parameters from Hyperspectral Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Chen, J. M.; Li, Y.; Zhang, Y.

    2002-05-01

    Retrieving biophysical and biochemical parameters is one of the most important and promising applications of hyperspectral remote sensing and will contribute greatly to the understanding of terrestrial ecosystems. We developed a mathematical inversion method for deriving leaf chlorophyll and water contents, which are potentially very useful as inputs to photosynthesis and carbon cycle models. From hyperspectral data cubes, global absorption coefficients for these parameters have been derived from two leaf spectral models named LIBERTY and PROSPECT. Taking into account the various factors affecting the coefficients such as the cellular structure of leaves and concentrations of other substances (lignin, protein, etc.), we have successfully retrieved chlorophyll and water concentrations of leaves. The inversion model is tested by comparing these parameters used in the forward calculations of leaf spectra and the same parameters retrieved from these forward-calculated spectra. Excellent agreement is found between the inverse and forward results, the difference being generally less than 1%. Atmospherically corrected airborne hyperspectral CASI (Compact Airborne Spectrographic Imager) images over a boreal forest are chosen for further model test. Through the model inversion, the data cube with 72 spectral bands and 405x2852 pixels is used to produce maps of the chlorophyll and water concentrations for the forest. The influence of canopy architecture on the inversion results is yet to be investigated using a geometrical optical model.

  6. CNR LARA project, Italy: Airborne laboratory for environmental research

    NASA Technical Reports Server (NTRS)

    Bianchi, R.; Cavalli, R. M.; Fiumi, L.; Marino, C. M.; Pignatti, S.

    1995-01-01

    The increasing interest for the environmental problems and the study of the impact on the environment due to antropic activity produced an enhancement of remote sensing applications. The Italian National Research Council (CNR) established a new laboratory for airborne hyperspectral imaging, the LARA Project (Laboratorio Aero per Ricerche Ambientali - Airborne Laboratory for Environmental Research), equipping its airborne laboratory, a CASA-212, mainly with the Daedalus AA5000 MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) instrument. MIVIS's channels, spectral bandwidths, and locations are chosen to meet the needs of scientific research for advanced applications of remote sensing data. MIVIS can make significant contributions to solving problems in many diverse areas such as geologic exploration, land use studies, mineralogy, agricultural crop studies, energy loss analysis, pollution assessment, volcanology, forest fire management and others. The broad spectral range and the many discrete narrow channels of MIVIS provide a fine quantization of spectral information that permits accurate definition of absorption features from a variety of materials, allowing the extraction of chemical and physical information of our environment. The availability of such a hyperspectral imager, that will operate mainly in the Mediterranean area, at the present represents a unique opportunity for those who are involved in environmental studies and land-management to collect systematically large-scale and high spectral-spatial resolution data of this part of the world. Nevertheless, MIVIS deployments will touch other parts of the world, where a major interest from the international scientific community is present.

  7. Clusters versus GPUs for Parallel Target and Anomaly Detection in Hyperspectral Images

    NASA Astrophysics Data System (ADS)

    Paz, Abel; Plaza, Antonio

    2010-12-01

    Remotely sensed hyperspectral sensors provide image data containing rich information in both the spatial and the spectral domain, and this information can be used to address detection tasks in many applications. In many surveillance applications, the size of the objects (targets) searched for constitutes a very small fraction of the total search area and the spectral signatures associated to the targets are generally different from those of the background, hence the targets can be seen as anomalies. In hyperspectral imaging, many algorithms have been proposed for automatic target and anomaly detection. Given the dimensionality of hyperspectral scenes, these techniques can be time-consuming and difficult to apply in applications requiring real-time performance. In this paper, we develop several new parallel implementations of automatic target and anomaly detection algorithms. The proposed parallel algorithms are quantitatively evaluated using hyperspectral data collected by the NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) system over theWorld Trade Center (WTC) in New York, five days after the terrorist attacks that collapsed the two main towers in theWTC complex.

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

    PubMed

    Varga, Timothy A; Asner, Gregory P

    2008-04-01

    Alien invasive grasses threaten to transform Hawaiian ecosystems through the alteration of ecosystem dynamics, especially the creation or intensification of a fire cycle. Across sub-montane ecosystems of Hawaii Volcanoes National Park on Hawaii Island, we quantified fine fuels and fire spread potential of invasive grasses using a combination of airborne hyperspectral and light detection and ranging (LiDAR) measurements. Across a gradient from forest to savanna to shrubland, automated mixture analysis of hyperspectral data provided spatially explicit fractional cover estimates of photosynthetic vegetation, non-photosynthetic vegetation, and bare substrate and shade. Small-footprint LiDAR provided measurements of vegetation height along this gradient of ecosystems. Through the fusion of hyperspectral and LiDAR data, a new fire fuel index (FFI) was developed to model the three-dimensional volume of grass fuels. Regionally, savanna ecosystems had the highest volumes of fire fuels, averaging 20% across the ecosystem and frequently filling all of the three-dimensional space represented by each image pixel. The forest and shrubland ecosystems had lower FFI values, averaging 4.4% and 8.4%, respectively. The results indicate that the fusion of hyperspectral and LiDAR remote sensing can provide unique information on the three-dimensional properties of ecosystems, their flammability, and the potential for fire spread. PMID:18488621

  9. Evaluating the feasibility of multitemporal hyperspectral remote sensing for monitoring bioremediation

    NASA Astrophysics Data System (ADS)

    Noomen, Marleen; Hakkarainen, Annika; van der Meijde, Mark; van der Werff, Harald

    2015-02-01

    In recent years, several studies focused on the detection of hydrocarbon pollution in the environment using hyperspectral remote sensing. Particularly the indirect detection of hydrocarbon pollution, using vegetation reflectance in the red edge region, has been studied extensively. Bioremediation is one of the methods that can be applied to clean up polluted sites. So far, there have been no studies on monitoring of bioremediation using (hyperspectral) remote sensing. This study evaluates the feasibility of hyperspectral remote sensing for monitoring the effect of bioremediation over time. Benzene leakage at connection points along a pipeline was monitored by comparing the red edge position (REP) in 2005 and 2008 using HyMap airborne hyperspectral images. REP values were normalized in order to enhance local variations caused by a change in benzene concentrations. 11 out of 17 locations were classified correctly as remediated, still polluted, or still clean, with a total accuracy of 65%. When only polluted locations that were remediated were taken into account, the (user's) accuracy was 71%.

  10. Alignment of Hyperspectral Imagery and Full-Waveform LIDAR Data for Visualisation and Classification Purposes

    NASA Astrophysics Data System (ADS)

    Miltiadou, M.; Warren, M. A.; Grant, M.; Brown, M.

    2015-04-01

    The overarching aim of this paper is to enhance the visualisations and classifications of airborne remote sensing data for remote forest surveys. A new open source tool is presented for aligning hyperspectral and full-waveform LiDAR data. The tool produces coloured polygon representations of the scanned areas and aligned metrics from both datasets. Using data provided by NERC ARSF, tree coverage maps are generated and projected into the polygons. The 3D polygon meshes show well-separated structures and are suitable for direct rendering with commodity 3D-accelerated hardware allowing smooth visualisation. The intensity profile of each wave sample is accumulated into a 3D discrete density volume building a 3D representation of the scanned area. The 3D volume is then polygonised using the Marching Cubes algorithm. Further, three user-defined bands from the hyperspectral images are projected into the polygon mesh as RGB colours. Regarding the classifications of full-waveform LiDAR data, previous work used extraction of point clouds while this paper introduces a new approach of deriving information from the 3D volume representation and the hyperspectral data. We generate aligned metrics of multiple resolutions, including the standard deviation of the hyperspectral bands and width of the reflected waveform derived from the volume. Tree coverage maps are then generated using a Bayesian probabilistic model and due to the combination of the data, higher accuracy classification results are expected.

  11. A comparison of real and simulated airborne multisensor imagery

    NASA Astrophysics Data System (ADS)

    Bloechl, Kevin; De Angelis, Chris; Gartley, Michael; Kerekes, John; Nance, C. Eric

    2014-06-01

    This paper presents a methodology and results for the comparison of simulated imagery to real imagery acquired with multiple sensors hosted on an airborne platform. The dataset includes aerial multi- and hyperspectral imagery with spatial resolutions of one meter or less. The multispectral imagery includes data from an airborne sensor with three-band visible color and calibrated radiance imagery in the long-, mid-, and short-wave infrared. The airborne hyperspectral imagery includes 360 bands of calibrated radiance and reflectance data spanning 400 to 2450 nm in wavelength. Collected in September 2012, the imagery is of a park in Avon, NY, and includes a dirt track and areas of grass, gravel, forest, and agricultural fields. A number of artificial targets were deployed in the scene prior to collection for purposes of target detection, subpixel detection, spectral unmixing, and 3D object recognition. A synthetic reconstruction of the collection site was created in DIRSIG, an image generation and modeling tool developed by the Rochester Institute of Technology, based on ground-measured reflectance data, ground photography, and previous airborne imagery. Simulated airborne images were generated using the scene model, time of observation, estimates of the atmospheric conditions, and approximations of the sensor characteristics. The paper provides a comparison between the empirical and simulated images, including a comparison of achieved performance for classification, detection and unmixing applications. It was found that several differences exist due to the way the image is generated, including finite sampling and incomplete knowledge of the scene, atmospheric conditions and sensor characteristics. The lessons learned from this effort can be used in constructing future simulated scenes and further comparisons between real and simulated imagery.

  12. 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.

  13. Hyperspectral image classifier based on beach spectral feature

    NASA Astrophysics Data System (ADS)

    Liang, Zhang; Lianru, Gao; Bing, Zhang

    2014-03-01

    The seashore, especially coral bank, is sensitive to human activities and environmental changes. A multispectral image, with coarse spectral resolution, is inadaptable for identify subtle spectral distinctions between various beaches. To the contrary, hyperspectral image with narrow and consecutive channels increases our capability to retrieve minor spectral features which is suit for identification and classification of surface materials on the shore. Herein, this paper used airborne hyperspectral data, in addition to ground spectral data to study the beaches in Qingdao. The image data first went through image pretreatment to deal with the disturbance of noise, radiation inconsistence and distortion. In succession, the reflection spectrum, the derivative spectrum and the spectral absorption features of the beach surface were inspected in search of diagnostic features. Hence, spectra indices specific for the unique environment of seashore were developed. According to expert decisions based on image spectrums, the beaches are ultimately classified into sand beach, rock beach, vegetation beach, mud beach, bare land and water. In situ surveying reflection spectrum from GER1500 field spectrometer validated the classification production. In conclusion, the classification approach under expert decision based on feature spectrum is proved to be feasible for beaches.

  14. Construction of a small and lightweight hyperspectral imaging system

    NASA Astrophysics Data System (ADS)

    Vogel, Britta; Hünniger, Dirk; Bastian, Georg

    2014-05-01

    The analysis of the reflected sunlight offers great opportunity to gain information about the environment, including vegetation and soil. In the case of plants the wavelength ratio of the reflected light usually undergoes a change if the state of growth or state of health changes. So the measurement of the reflected light allows drawing conclusions about the state of, amongst others, vegetation. Using a hyperspectral imaging system for data acquisition leads to a large dataset, which can be evaluated with respect to several different questions to obtain various information by one measurement. Based on commercially available plain optical components we developed a small and lightweight hyperspectral imaging system within the INTERREG IV A-Project SMART INSPECTORS. The project SMART INSPECTORS [Smart Aerial Test Rigs with Infrared Spectrometers and Radar] deals with the fusion of airborne visible and infrared imaging remote sensing instruments and wireless sensor networks for precision agriculture and environmental research. A high performance camera was required in terms of good signal, good wavelength resolution and good spatial resolution, while severe constraints of size, proportions and mass had to be met due to the intended use on small unmanned aerial vehicles. The detector was chosen to operate without additional cooling. The refractive and focusing optical components were identified by supporting works with an optical raytracing software and a self-developed program. We present details of design and construction of our camera system, test results to confirm the optical simulation predictions as well as our first measurements.

  15. Spectral Band Characterization for Hyperspectral Monitoring of Water Quality

    NASA Technical Reports Server (NTRS)

    Vermillion, Stephanie C.; Raqueno, Rolando; Simmons, Rulon

    2001-01-01

    A method for selecting the set of spectral characteristics that provides the smallest increase in prediction error is of interest to those using hyperspectral imaging (HSI) to monitor water quality. The spectral characteristics of interest to these applications are spectral bandwidth and location. Three water quality constituents of interest that are detectable via remote sensing are chlorophyll (CHL), total suspended solids (TSS), and colored dissolved organic matter (CDOM). Hyperspectral data provides a rich source of information regarding the content and composition of these materials, but often provides more data than an analyst can manage. This study addresses the spectral characteristics need for water quality monitoring for two reasons. First, determination of the greatest contribution of these spectral characteristics would greatly improve computational ease and efficiency. Second, understanding the spectral capabilities of different spectral resolutions and specific regions is an essential part of future system development and characterization. As new systems are developed and tested, water quality managers will be asked to determine sensor specifications that provide the most accurate and efficient water quality measurements. We address these issues using data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and a set of models to predict constituent concentrations.

  16. Radiometric characterization of hyperspectral imagers using multispectral sensors

    NASA Astrophysics Data System (ADS)

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

    2009-08-01

    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 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 work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral imagery. The work relies on the 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. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of MODIS. 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 bands as well as similar agreement between results that employ the different MODIS sensors as a reference.

  17. Drawbacks of using linear mixture modeling on hyperspectral images

    NASA Astrophysics Data System (ADS)

    Rodricks, Neena; Kirkland, Laurel E.

    2004-10-01

    Hyperspectral spectroscopy can be used remotely to measure emitted radiation from minerals and rocks at a series of narrow and continuous wavelength bands resulting in a continuous spectrum for each pixel, thereby providing ample spectral information to identify and distinguish spectrally unique materials. Linear mixture modeling ("spectral unmixing"), a commonly used method, is based on the theory that the radiance in the thermal infrared region (8-12 μm) from a multi-mineral surface can be modeled as a linear combination of the endmembers. A linear mixture model can thus potentially model the minerals present on planetary surfaces. It works by scaling the endmember spectra so that the sum of the scaled endmember spectra matches the measured spectrum with the smallest "error" (difference). But one of the drawbacks of this established method is that mathematically, a fit with an inverted spectrum is valid, which effectively returns a negative abundance of a material. Current models usually address the problem by elimination of endmembers that have negative scale factors. Eliminating the negative abundance problem is not a major issue when the endmembers are known. However, identifying unknown target composition (like on Mars) can be a problem. The goal of this study is to improve the understanding and find a subsequent solution of the negative abundance problem for Mars analog field data obtained from airborne and ground spectrometers. We are using a well-defined library of spectra to test the accuracy of hyperspectral analysis for the identification of minerals on planetary surfaces.

  18. Evaluation of hyperspectral imagery for detecting hydrocarbon microseepage

    SciTech Connect

    Zhikang Chen; Ahl, D.; Albasini, J.

    1996-07-01

    Loark Producing Company (Loark) of Jackson, Mississippi, is a small consulting organization providing services for hydrocarbon exploration. Current methods used for {open_quotes}finding oil{close_quotes} include geophysics, geochemistry, geobotany, and surface mapping, but these techniques are not definitive. The oil and gas industries primary goal is to minimize the initial economic risk associated with hydrocarbon exploration. Loark is participating in a Visiting Investigator Program (VIP) project at Stennis Space Center in cooperation with the Mississippi Office of Geology to explore the use of hyperspectral imaging to detect hydrocarbon microseepage. Extensive evidence in favor of vertical migration of hydrocarbon from subsurface petroleum reservoirs has been presented during the past 30 years. Migrating volatiles from reservoirs can alter surface rocks, thus changing their weathering characteristics or producing soil environments containing higher concentrations of iron and manganese that can in turn contaminate surface vegetation or alter growth patterns. The ability to detect indicator species, vegetation stress, and/or forest structure dynamics provides a potential methodology for hydrocarbon detection and exploration. The effects of vegetation stress from microseepage are subtle in nature and are not readily apparent using broad-band sensors, such as TM or SPOT. It is hypothesized that hyperspectral airborne sensors, having narrower spectral bandwidths and higher spatial resolutions, may provide improved discriminatory ability for detecting vegetation stress due to microseepage. In this study, geochemical data are being utilized for preliminary determination of microseepage sites. High spectral resolution GER Mark V data of both control and microseepage sites have been acquired and analyzed to examine hydrocarbon microseepage evidence. High spectral and high spatial resolution airborne TRWIS-B sensor data of these sites have also been acquired.

  19. An automatic detection system for buried explosive hazards in FL-LWIR and FL-GPR data

    NASA Astrophysics Data System (ADS)

    Stone, K.; Keller, J. M.; Anderson, D. T.; Barclay, D. B.

    2012-06-01

    Improvements to an automatic detection system for locating buried explosive hazards in forward-looking longwave infrared (FL-LWIR) imagery, as well as the system's application to detection in confidence maps and forwardlooking ground penetrating radar (FL-GPR) data, are discussed. The detection system, described in previous work, utilizes an ensemble of trainable size-contrast filters and the mean-shift algorithm in Universal Transverse Mercator (UTM) coordinates. Improvements of the raw detection algorithm include weighted mean-shift within the individual size-contrast filters and a secondary classification step which exacts cell structured image space features, including local binary patterns (LBP), histogram of oriented gradients (HOG), edge histogram descriptor (EHD), and maximally stable extremal regions (MSER) segmentation based shape information, from one or more looks and classifies the resulting feature vector using a support vector machine (SVM). FL-LWIR specific improvements include elimination of the need for multiple models due to diurnal temperature variation. The improved algorithm is assessed on FL-LWIR and FL-GPR data from recent collections at a US Army test site.

  20. Measured comparison of the inversion periods for polarimetric and conventional thermal long-wave IR (LWIR) imagery

    NASA Astrophysics Data System (ADS)

    Felton, M.; Gurton, K. P.; Roth, L. E.; Pezzaniti, J. L.; Chenault, D. B.

    2009-08-01

    We report the results of a multi-day diurnal study in which radiometrically calibrated polarimetric and conventional thermal imagery is recorded in the LWIR to identify/compare the respective time periods in which minimum target contrast is achieved, e.g., thermal inversion periods are typically experienced during dusk and dawn. Imagery is recorded with a polarimetric IR sensor employing a 324x256 microbolometer array using a spinning achromatic retarder to perform the polarimetric filtering. The images used in this study include the S0, normalized S1, and normalized S2 Stokes images and the degree of linear polarization (DOLP) images of a scene containing military vehicles and the natural background. In addition, relevant meteorological parameters measured during the test period include air temperature, ambient loading in the LWIR, relative humidity, and cloud cover, height and density. The data shows that the chief factors affecting polarimetric contrast are the amount of thermal emission from the objects in the scene and the abundance of LWIR sources in the optical background. In addition, we found that contrast between targets and background within polarimetric images often remains relatively high during periods of low thermal contrast.

  1. MCT-Based LWIR and VLWIR 2D Focal Plane Detector Arrays for Low Dark Current Applications at AIM

    NASA Astrophysics Data System (ADS)

    Hanna, S.; Eich, D.; Mahlein, K.-M.; Fick, W.; Schirmacher, W.; Thöt, R.; Wendler, J.; Figgemeier, H.

    2016-09-01

    We present our latest results on n-on- p as well as on p-on- n low dark current planar mercury cadmium telluride (MCT) photodiode technology long wavelength infrared (LWIR) and very long wavelength infrared (VLWIR) two-dimensional focal plane arrays (FPAs) with quantum efficiency (QE) cut-off wavelength >11 μm at 80 K and a 512 × 640 pixel format FPA at 20 μm pitch stitched from two 512 × 320 pixel photodiode arrays. Significantly reduced dark currents as compared with Tennant's "Rule 07" are demonstrated in both polarities while retaining good detection efficiency ≥60% for operating temperatures between 30 K and 100 K. This allows for the same dark current performance at 20 K higher operating temperature than with previous AIM INFRAROT-MODULE GmbH (AIM) technology. For p-on- n LWIR MCT FPAs, broadband photoresponse nonuniformity of only about 1.2% is achieved at 55 K with low defective pixel numbers. For an n-on- p VLWIR MCT FPA with 13.6 μm cut-off at 55 K, excellent photoresponse nonuniformity of about 3.1% is achieved at moderate defective pixel numbers. This advancement in detector technology paves the way for outstanding signal-to-noise ratio performance infrared detection, enabling cutting-edge next-generation LWIR/VLWIR detectors for space instruments and devices with higher operating temperature and low size, weight, and power for field applications.

  2. MCT-Based LWIR and VLWIR 2D Focal Plane Detector Arrays for Low Dark Current Applications at AIM

    NASA Astrophysics Data System (ADS)

    Hanna, S.; Eich, D.; Mahlein, K.-M.; Fick, W.; Schirmacher, W.; Thöt, R.; Wendler, J.; Figgemeier, H.

    2016-04-01

    We present our latest results on n-on-p as well as on p-on-n low dark current planar mercury cadmium telluride (MCT) photodiode technology long wavelength infrared (LWIR) and very long wavelength infrared (VLWIR) two-dimensional focal plane arrays (FPAs) with quantum efficiency (QE) cut-off wavelength >11 μm at 80 K and a 512 × 640 pixel format FPA at 20 μm pitch stitched from two 512 × 320 pixel photodiode arrays. Significantly reduced dark currents as compared with Tennant's "Rule 07" are demonstrated in both polarities while retaining good detection efficiency ≥60% for operating temperatures between 30 K and 100 K. This allows for the same dark current performance at 20 K higher operating temperature than with previous AIM INFRAROT-MODULE GmbH (AIM) technology. For p-on-n LWIR MCT FPAs, broadband photoresponse nonuniformity of only about 1.2% is achieved at 55 K with low defective pixel numbers. For an n-on-p VLWIR MCT FPA with 13.6 μm cut-off at 55 K, excellent photoresponse nonuniformity of about 3.1% is achieved at moderate defective pixel numbers. This advancement in detector technology paves the way for outstanding signal-to-noise ratio performance infrared detection, enabling cutting-edge next-generation LWIR/VLWIR detectors for space instruments and devices with higher operating temperature and low size, weight, and power for field applications.

  3. An Integrated Method for Mapping Impervious and Pervious Areas in Urban Environments Using Hyperspectral and LiDAR Data

    NASA Astrophysics Data System (ADS)

    Hashemi Beni, L.; McArdle, S.; Khayer, Y.

    2014-11-01

    As urbanization continues to increase and extreme climatic events become more prevalent, urban planners and engineers are actively implementing adaptive measures to protect urban assets and communities. To support the urban planning adaptation process, mapping of impervious and pervious areas is essential to understanding the hydrodynamic environment within urban areas for flood risk planning. The application of advance geospatial data and analytical techniques using remote sensing and GIS can improve land surface characterization to better quantify surface run-off and infiltration. This study presents a method to combine airborne hyperspectral and LiDAR data for classifying pervious (e.g. vegetation, gravel, and soil) and impervious (e.g. asphalt and concrete) areas within road allowance areas for the City of Surrey, British Columbia, Canada. Hyperspectral data was acquired using the Compact Airborne Spectrographic Imager (CASI) at 1 m ground spatial resolution, consisting of 72 spectral bands, and LiDAR data acquired from Leica Airborne LiDAR system at a density of 20 points/m2. A spectral library was established using 10 cm orthophotography and GIS data to identify surface features. In addition to spectral functions such as mean and standard deviation, several spectral indices were developed to discriminate between asphalt, concrete, gravel, vegetation, and shadows respectively. A spectral analysis of selected endmembers was conducted and an initial classification technique was applied using Spectral Angle Mapper (SAM). The classification results (i.e. shadows) were improved by integrating LIDAR data with the hyperspectral data.

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  5. Predicting the detectability of thin gaseous plumes in hyperspectral images using basis vectors

    SciTech Connect

    Anderson, Kevin K.; Tardiff, Mark F.; Chilton, Lawrence

    2010-09-01

    This paper describes a new method for predicting the detectability of thin gaseous plumes in hyperspectral images. The novelty of this method is the use of basis vectors for each of the spectral channels of a collection instrument to calculate noise-equivalent concentration-pathlengths instead of matching scene pixels to absorbance spectra of gases in a library. This method provides insight into regions of the spectrum where gas detection will be relatively easier or harder, as influenced by ground emissivity, temperature contrast, and the atmosphere. We relate a three-layer physics-based radiance model to basis vector noise-equivalent concentration-pathlengths, to signal-to-noise ratios, and finally to minimum detectable concentration-pathlengths. We illustrate the method using an Airborne Hyperspectral Imager image. Our results show that data collection planning could be in°uenced by information about when potential plumes are likely to be over background segments that are most conducive to detection.

  6. New progress in study on vegetation models for hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    Tong, Qingxi; Zhao, Yongchao; Zhang, Xia; Zhang, Bing; Zheng, Lanfen

    2001-02-01

    Some new vegetation models for hyperspectral remote sensing are provided in this paper. They are Derivative Spectral Model (DSM), Multi-temporal Index Image Cube Model (MIIC), Hybrid Decision Tree Model (HDT) and Correlation Simulating Analysis Model (CSAM). All models are developed and used to process the images acquired by Airborne Pushbroom Hyperspectral Imager (PHI) in Changzhou area, China, 1999. Some successful applications are provided and evaluated. The results show that DSM has the ability of eliminating the background interference of vegetation analysis. MIIC is a viable method for monitoring dynamic change of land cover and vegetation growth stages. HDT is effective in precise classification of rice land while CSAM provide a possibility and theoretical basis for crop identification, breed classification, and land information extraction especially for rice.

  7. An infrared hyperspectral sensor for remote sensing of gases in the atmosphere

    NASA Astrophysics Data System (ADS)

    Sabbah, Samer; Rusch, Peter; Gerhard, Jõrn-Hinnrich; Harig, Roland

    2010-10-01

    Remote sensing by infrared spectroscopy allows identification and quantification of atmospheric gases as well as airborne pollutants. Infrared hyperspectral sensors deliver high spectral and spatial resolution images of a scene. By analyzing the spectra, gas emissions, for example from industrial plants, chemical accidents, or ships can be identified and quantified from long distances. The image of the cloud can be used to pinpoint the source of the gas as well as to assess the dimension and the dispersion of the cloud. A hyperspectral sensor based on the method of Fourier-transform spectroscopy has been developed. A cube corner Michelson interferometer with large optical apertures has been designed specifically for the task. In addition, the system encompasses a cooled infrared focal plane array detector, a calibration source, and a video camera. The system is compact and field portable. Field measurements were conducted on ship exhausts. Gas clouds were successfully visualized and identified.

  8. Derivative Analysis of AVIRIS Hyperspectral Data for the Detection of Plant Stress

    NASA Technical Reports Server (NTRS)

    Estep, Lee; Berglund, Judith

    2001-01-01

    A remote sensing campaign was conducted over a U.S. Department of Agriculture test site at Shelton, Nebraska. The test field was set off in blocks that were differentially treated with nitrogen. Four replicates of 0-kg/ha to 200-kg/ha, in 50-kg/ha increments, were present. Low-altitude AVIRIS hyperspectral data were collected over the site in 224 spectral bands. Simultaneously, ground data were collected to support the airborne imagery. In an effort to evaluate published, derivative-based algorithms for the detection of plant stress, different derivative-based approaches were applied to the collected AVIRIS image cube. The results indicate that, given good quality hyperspectral imagery, derivative techniques compare favorably with simple, well known band ratio algorithms for detection of plant stress.

  9. 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

  10. Design and performance of the Civil Air Patrol ARCHER hyperspectral processing system

    NASA Astrophysics Data System (ADS)

    Stevenson, Brian; O'Connor, Rory; Kendall, William; Stocker, Alan; Schaff, William; Alexa, Drew; Salvador, John; Eismann, Michael; Barnard, Kenneth; Kershenstein, John

    2005-06-01

    The Civil Air Patrol (CAP) is procuring Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) systems to increase their search-and-rescue mission capability. These systems are being installed on a fleet of Gippsland GA-8 aircraft, and will position CAP to gain realworld mission experience with the application of hyperspectral sensor and processing technology to search and rescue. The ARCHER system design, data processing, and operational concept leverage several years of investment in hyperspectral technology research and airborne system demonstration programs by the Naval Research Laboratory (NRL) and Air Force Research Laboratory (AFRL). Each ARCHER system consists of a NovaSol-designed, pushbroom, visible/near-infrared (VNIR) hyperspectral imaging (HSI) sensor, a co-boresighted visible panchromatic high-resolution imaging (HRI) sensor, and a CMIGITS-III GPS/INS unit in an integrated sensor assembly mounted inside the GA-8 cabin. ARCHER incorporates an on-board data processing system developed by Space Computer Corporation (SCC) to perform numerous real-time processing functions including data acquisition and recording, raw data correction, target detection, cueing and chipping, precision image geo-registration, and display and dissemination of image products and target cue information. A ground processing station is provided for post-flight data playback and analysis. This paper describes the requirements and architecture of the ARCHER system, with emphasis on data processor design, components, software, interfaces, and displays. Key sensor performance characteristics and real-time data processing features are discussed. The use of the system for detecting and geo-locating ground targets in real-time is demonstrated using test data collected in Southern California in the fall of 2004.

  11. Building spectral libraries for wetlands land cover classification and hyperspectral remote sensing.

    PubMed

    Zomer, R J; Trabucco, A; Ustin, S L

    2009-05-01

    Recent advances in remote sensing provide opportunities to map plant species and vegetation within wetlands at management relevant scales and resolutions. Hyperspectral imagers, currently available on airborne platforms, provide increased spectral resolution over existing space-based sensors that can document detailed information on the distribution of vegetation community types, and sometimes species. Development of spectral libraries of wetland species is a key component needed to facilitate advanced analytical techniques to monitor wetlands. Canopy and leaf spectra at five sites in California, Texas, and Mississippi were sampled to create a common spectral library for mapping wetlands from remotely sensed data. An extensive library of spectra (n=1336) for coastal wetland communities, across a range of bioclimatic, edaphic, and disturbance conditions were measured. The wetland spectral libraries were used to classify and delineate vegetation at a separate location, the Pacheco Creek wetland in the Sacramento Delta, California, using a PROBE-1 airborne hyperspectral data set (5m pixel resolution, 128 bands). This study discusses sampling and collection methodologies for building libraries, and illustrates the potential of advanced sensors to map wetland composition. The importance of developing comprehensive wetland spectral libraries, across diverse ecosystems is highlighted. In tandem with improved analytical tools these libraries provide a physical basis for interpretation that is less subject to conditions of specific data sets. To facilitate a global approach to the application of hyperspectral imagers to mapping wetlands, we suggest that criteria for and compilation of wetland spectral libraries should proceed today in anticipation of the wider availability and eventual space-based deployment of advanced hyperspectral high spatial resolution sensors. PMID:18395960

  12. Hyperspectral remote sensing for soil organic carbon mapping

    NASA Astrophysics Data System (ADS)

    Stevens, A.; van Wesemael, B.

    2009-04-01

    Satellite and airborne hyperspectral remote sensing is increasingly investigated as a fast and convenient tool to map soil properties. However, several research have pointed out the difficulty to obtain good calibration results over large areas due to spatial variation in soil types and surface soil conditions (moisture content, roughness, vegetation cover). These effects induce a spectral variability not directly related to the property studied and decrease the accuracy of predictions. A flight campaign was organized on 4-9th October 2007 using the AHS-160 airborne spectrometer to predict Soil Organic Carbon (SOC) in bare cropland soils in Grand-Duchy of Luxembourg. The study area consisted in a north-south transect of ~7 km width and ~60 km length and crossed 4 of the 5 agro-geological regions of Luxembourg, characterized by various soil types such as Cambisols, Luvisols, Arenosols and Calcisols. After collecting more than 300 soil samples of the soil surface, spectral data was related with SOC content using several standard multivariate calibration techniques (Partial Least Square Regression, Penalized-spline Regression, Support Vector Machine). It is shown that calibrations yield reasonably accurate predictions over large areas as long as secondary information (e.g. soil types, agro-pedological regions) are included in the models (Root Mean Square Error of Prediction: ~3 g C kg-1). Such calibration models could be applied to every soil pixel of the hyperspectral image to produce a SOC map of the area. However, predictions have been realized using statistical relationships based on a set of calibration randomly chosen from a set of samples collected during a field campaign, the rest being used for validation purposes. It means that the validation set is not completely independent from the calibration set. As a consequence, a true independent validation (over fields not covered by the calibration/validation sets) would probably give lower accuracies than the ones

  13. Nonlinear Bayesian Algorithms for Gas Plume Detection and Estimation from Hyper-spectral Thermal Image Data

    SciTech Connect

    Heasler, Patrick G.; Posse, Christian; Hylden, Jeff L.; Anderson, Kevin K.

    2007-06-13

    This paper presents a nonlinear Bayesian regression algorithm for the purpose of detecting and estimating gas plume content from hyper-spectral data. Remote sensing data, by its very nature, is collected under less controlled conditions than laboratory data. As a result, the physics-based model that is used to describe the relationship between the observed remotesensing spectra, and the terrestrial (or atmospheric) parameters that we desire to estimate, is typically littered with many unknown "nuisance" parameters (parameters that we are not interested in estimating, but also appear in the model). Bayesian methods are well-suited for this context as they automatically incorporate the uncertainties associated with all nuisance parameters into the error estimates of the parameters of interest. The nonlinear Bayesian regression methodology is illustrated on realistic simulated data from a three-layer model for longwave infrared (LWIR) measurements from a passive instrument. This shows that this approach should permit more accurate estimation as well as a more reasonable description of estimate uncertainty.

  14. 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.

  15. Fire detection from hyperspectral data using neural network approach

    NASA Astrophysics Data System (ADS)

    Piscini, Alessandro; Amici, Stefania

    2015-10-01

    This study describes an application of artificial neural networks for the recognition of flaming areas using hyper- spectral remote sensed data. Satellite remote sensing is considered an effective and safe way to monitor active fires for environmental and people safeguarding. Neural networks are an effective and consolidated technique for the classification of satellite images. Moreover, once well trained, they prove to be very fast in the application stage for a rapid response. At flaming temperature, thanks to its low excitation energy (about 4.34 eV), potassium (K) ionize with a unique doublet emission features. This emission features can be detected remotely providing a detection map of active fire which allows in principle to separate flaming from smouldering areas of vegetation even in presence of smoke. For this study a normalised Advanced K Band Difference (AKBD) has been applied to airborne hyper spectral sensor covering a range of 400-970 nm with resolution 2.9 nm. A back propagation neural network was used for the recognition of active fires affecting the hyperspectral image. The network was trained using all channels of sensor as inputs, and the corresponding AKBD indexes as target output. In order to evaluate its generalization capabilities, the neural network was validated on two independent data sets of hyperspectral images, not used during neural network training phase. The validation results for the independent data-sets had an overall accuracy round 100% for both image and a few commission errors (0.1%), therefore demonstrating the feasibility of estimating the presence of active fires using a neural network approach. Although the validation of the neural network classifier had a few commission errors, the producer accuracies were lower due to the presence of omission errors. Image analysis revealed that those false negatives lie in "smoky" portion fire fronts, and due to the low intensity of the signal. The proposed method can be considered

  16. 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.

  17. New target acquisition task for contemporary operating environments: personnel in MWIR, LWIR, and SWIR

    NASA Astrophysics Data System (ADS)

    Boettcher, Evelyn J.; Leonard, Kevin R.; Hodgkin, Van A.; Thompson, Roger; Miller, Brian; Hixson, Jon; Johnson, Sara; Godbolt, Tehran; Acton, David D.

    2010-04-01

    Operating environments that US Soldiers and Marines are in have changed, along with the types of tasks that they are required to perform. In addition, the potential imaging sensor options available have increased. These changes make it necessary to examine how these new tasks are affected by waveband and time of day. US Army Research, Development and Engineering Command, Communications Electronics Research Development and Engineering Center, Night Vision and Electronic Sensor Directorate (NVESD), investigated one such task for several wavebands (MWIR, LWIR, Visible, and SWIR) and during both day and night. This task involved identification of nine different personnel targets: US Soldier, US Marine, Eastern-European/Asian Soldier, Urban Insurgent, Rural Insurgent, Hostile Militia, Indigenous Inhabitant, Contract Laborer, and Reporter. These nine distinct targets were made up from three tactically significant categories: Friendly Force, Combatant and Neutral/Non-Combatant. A ten second video was taken of an actor dressed as one of these targets. The actors walk a square pattern, enabling all aspects to be seen in each video clip. Target characteristics were measured and characteristic dimension, target contrast tabulated. A nine-alternative, forced-choice human perception test was performed at NVESD. This test allowed NVESD to quantify the ability of observers to discriminate between personnel targets for each waveband and time of day. The task difficulty criterion, V50, was also calculated allowing for future modeling using the NVESD sensor performance model.

  18. VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity.

    PubMed

    Fernández, Roemi; Montes, Héctor; Salinas, Carlota

    2015-01-01

    Ground bearing capacity has become a relevant concept for site-specific management that aims to protect soil from the compaction and the rutting produced by the indiscriminate use of agricultural and forestry machines. Nevertheless, commonly known techniques for its estimation are cumbersome and time-consuming. In order to alleviate these difficulties, this paper introduces an innovative sensory system based on Visible-Near InfraRed (VIS-NIR), Short-Wave InfraRed (SWIR) and Long-Wave InfraRed (LWIR) imagery and a sequential algorithm that combines a registration procedure, a multi-class SVM classifier, a K-means clustering and a linear regression for estimating the ground bearing capacity. To evaluate the feasibility and capabilities of the presented approach, several experimental tests were carried out in a sandy-loam terrain. The proposed solution offers notable benefits such as its non-invasiveness to the soil, its spatial coverage without the need for exhaustive manual measurements and its real time operation. Therefore, it can be very useful in decision making processes that tend to reduce ground damage during agricultural and forestry operations. PMID:26083227

  19. FSR: a field portable spectral reflectometer to measure ground from NIR to LWIR

    NASA Astrophysics Data System (ADS)

    Moreau, Louis; Bourque, Hugo; Ouellet, Réal; Prel, Florent; Roy, Claude; Vallieres, Christian; Thériault, Guillaume

    2011-11-01

    ABB Bomem has recently designed a field-deployable reflectometer. The Full Spectrum Reflectometer (FSR) measures the diffuse reflectance of surfaces in the 0.7 μm to 13.5 μm spectral range. The spectral resolution is adjustable from 32 to 4 cm-1. The instrument is portable, battery-operated and designed for field usage in a single, lightweight and ruggedized package. In its simplest mode, the instrument is automated and can be operated by non-specialist personnel with minimal training. The FSR has a laboratory mode to measure targets brought to the instrument in a sampling cup and a field mode with automated measurement sequence. To facilitate the measurement of various ground surfaces, the instrument is packaged in a three-point mount for easy target access and stability. One of the mount is the sampling port. The instrument has its own built-in NIR and LWIR infrared sources to illuminate the ground area to be measured. The instrument includes two built-in references for calibration: a Spectralon diffuser and an Infragold diffuser. The first units were commissioned to build a spectral database of surfaces in various conditions (humidity, temperature, texture, mixing, etc.) and in the presence of interfering chemicals (oils, solvents, etc.) but the instrument can also serve other purposes such as the identification of unknown materials.

  20. Advanced computational sensors technology: testing and evaluation in visible, SWIR, and LWIR imaging

    NASA Astrophysics Data System (ADS)

    Rizk, Charbel G.; Wilson, John P.; Pouliquen, Philippe

    2015-05-01

    The Advanced Computational Sensors Team at the Johns Hopkins University Applied Physics Laboratory and the Johns Hopkins University Department of Electrical and Computer Engineering has been developing advanced readout integrated circuit (ROIC) technology for more than 10 years with a particular focus on the key challenges of dynamic range, sampling rate, system interface and bandwidth, and detector materials or band dependencies. Because the pixel array offers parallel sampling by default, the team successfully demonstrated that adding smarts in the pixel and the chip can increase performance significantly. Each pixel becomes a smart sensor and can operate independently in collecting, processing, and sharing data. In addition, building on the digital circuit revolution, the effective well size can be increased by orders of magnitude within the same pixel pitch over analog designs. This research has yielded an innovative class of a system-on-chip concept: the Flexible Readout and Integration Sensor (FRIS) architecture. All key parameters are programmable and/or can be adjusted dynamically, and this architecture can potentially be sensor and application agnostic. This paper reports on the testing and evaluation of one prototype that can support either detector polarity and includes sample results with visible, short-wavelength infrared (SWIR), and long-wavelength infrared (LWIR) imaging.

  1. Detection and tracking of RC model aircraft in LWIR microgrid polarimeter data

    NASA Astrophysics Data System (ADS)

    Ratliff, Bradley M.; LeMaster, Daniel A.; Mack, Robert T.; Villeneuve, Pierre V.; Weinheimer, Jeffrey J.; Middendorf, John R.

    2011-10-01

    The LWIR microgrid Polarized InfraRed Advanced Tactical Experiment (PIRATE) sensor was used to image several types of RC model aircraft at varying ranges and speeds under different background conditions. The data were calibrated and preprocessed using recently developed microgrid processing algorithms prior to estimation of the thermal (s0) and polarimetric (s1 and s2) Stokes vector images. The data were then analyzed to assess the utility of polarimetric information when the thermal s0 data is augmented with s1 and s2 information for several model aircraft detection and tracking scenarios. Multi-variate analysis tools were applied in conjunction with multi-hypothesis detection schemes to assess detection performance of the aircraft under different background clutter conditions. We find that polarization is able to improve detection performance when compared with the corresponding thermal data in nearly all cases. A tracking algorithm was applied to a sequence of s0 and corresponding degree of linear polarization (DoLP) images. An initial assessment was performed to determine whether polarization information can provide additional utility in these tracking scenarios.

  2. Robust person and object tracking in LWIR and VIS based on a new template matching method

    NASA Astrophysics Data System (ADS)

    Müller, Thomas

    2014-06-01

    Template matching is one of the oldest techniques in computer vision. It has been applied in a variety of different applications using cross correlation as distance measurement or derivates of it. But so far, the success of object tracking is very limited despite the promising structural similarity search that is done thereby. Based on an analysis of the underlying reasons, a new kind of measurement is proposed therefore to open up far more of the potential the structural search inherently offers. This new measurement does not sum up differences in color space like the cross correlation but outputs the number of matching pixels in percent. As a key feature, local color variations are considered in order to properly handle the different character of homogeneous and highly structured regions and to model the relations between them. Furthermore, relevant differences between templates are expatiated and stressed while irrelevant contributions to the measurement function are widely suppressed in order to avoid unnecessary distortions on the measurement and, therefore, on the search decision. The presented results document the advantages in comparison to the measurements known from the literature. Different objects and persons in LWIR and VIS image sequences are tracked to illustrate the performance and the benefit in a broad field of applications.

  3. BAE Systems' 17μm LWIR camera core for civil, commercial, and military applications

    NASA Astrophysics Data System (ADS)

    Lee, Jeffrey; Rodriguez, Christian; Blackwell, Richard

    2013-06-01

    Seventeen (17) µm pixel Long Wave Infrared (LWIR) Sensors based on vanadium oxide (VOx) micro-bolometers have been in full rate production at BAE Systems' Night Vision Sensors facility in Lexington, MA for the past five years.[1] We introduce here a commercial camera core product, the Airia-MTM imaging module, in a VGA format that reads out in 30 and 60Hz progressive modes. The camera core is architected to conserve power with all digital interfaces from the readout integrated circuit through video output. The architecture enables a variety of input/output interfaces including Camera Link, USB 2.0, micro-display drivers and optional RS-170 analog output supporting legacy systems. The modular board architecture of the electronics facilitates hardware upgrades allow us to capitalize on the latest high performance low power electronics developed for the mobile phones. Software and firmware is field upgradeable through a USB 2.0 port. The USB port also gives users access to up to 100 digitally stored (lossless) images.

  4. The side-passivation research on LWIR HgCdTe detector

    NASA Astrophysics Data System (ADS)

    Xu, Qinfei; Tang, Hengjing; Gong, Haimei

    2008-03-01

    In order to prevent Hg running over from the exposing side of HgCdTe LWIR detector with little photosensitive region, side-passivation detectors are fabricated. Then several experiments are done to characterize the side-passivation effect. Firstly, a SEM micrograph is shown, and it makes clear that wet etching and side-passivation can remove part of defect induced by IBE. Secondly, the performance measurement indicates that the performance of side-passivation detector is superior to the general one, especially for detectors with little photosensitive region. Thirdly, hot dipping is done to say that the thermal stability of side-passivation detectors is superior to general ones. And with the exception of this, the less the photosensitive region width is, the stronger the ability of protection is. Last but not the least, the detectivity of not only general detectors but also side-passivation ones increases obviously. As a whole, the performance of side-passivation detectors increases more largely than general ones. Above all, side-wall passivating film can passivate the sensitivity of detector's surface and block Hg out of the surface effectively. The results can provide experimental reference for IR semiconductor detector.

  5. A miniature low-cost LWIR camera with a 160×120 microbolometer FPA

    NASA Astrophysics Data System (ADS)

    Tepegoz, Murat; Kucukkomurler, Alper; Tankut, Firat; Eminoglu, Selim; Akin, Tayfun

    2014-06-01

    This paper presents the development of a miniature LWIR thermal camera, MSE070D, which targets value performance infrared imaging applications, where a 160x120 CMOS-based microbolometer FPA is utilized. MSE070D features a universal USB interface that can communicate with computers and some particular mobile devices in the market. In addition, it offers high flexibility and mobility with the help of its USB powered nature, eliminating the need for any external power source, thanks to its low-power requirement option. MSE070D provides thermal imaging with its 1.65 inch3 volume with the use of a vacuum packaged CMOS-based microbolometer type thermal sensor MS1670A-VP, achieving moderate performance with a very low production cost. MSE070D allows 30 fps thermal video imaging with the 160x120 FPA size while resulting in an NETD lower than 350 mK with f/1 optics. It is possible to obtain test electronics and software, miniature camera cores, complete Application Programming Interfaces (APIs) and relevant documentation with MSE070D, as MikroSens want to help its customers to evaluate its products and to ensure quick time-to-market for systems manufacturers.

  6. Design of a ROIC with high dynamic range for LWIR FPAs

    NASA Astrophysics Data System (ADS)

    Zhai, Yongcheng; Ding, Ruijun

    2014-11-01

    In this paper, a high performance readout integrated circuit (ROIC) designed for long wave infrared (LWIR) detectors is introduced, which has high dynamic range (HDR). To accommodate the wide scene dynamic range requirement, special circuit architecture is used to the input unit cell. A capacitive feedback transimpedance amplifier (CTIA) as input circuit is used to provide high injection efficiency, low input resistance, good linearity, precise voltage bias. Because of the restriction of the layout area, four unit cells will share an integration capacitor and each unit cell has a correlated double sampling (CDS) circuit, which allows the infrared focal plane arrays (IRFPA) to be operated in full frame snapshot mode and provides the maximum integration time available. The charge transfer circuit is used and we don't need to consider the drive ability of the unit cell. The simulation results confirm that the ROIC provides over a factor of 70dB dynamic range with the 5.0v power supply.

  7. VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity

    PubMed Central

    Fernández, Roemi; Montes, Héctor; Salinas, Carlota

    2015-01-01

    Ground bearing capacity has become a relevant concept for site-specific management that aims to protect soil from the compaction and the rutting produced by the indiscriminate use of agricultural and forestry machines. Nevertheless, commonly known techniques for its estimation are cumbersome and time-consuming. In order to alleviate these difficulties, this paper introduces an innovative sensory system based on Visible-Near InfraRed (VIS-NIR), Short-Wave InfraRed (SWIR) and Long-Wave InfraRed (LWIR) imagery and a sequential algorithm that combines a registration procedure, a multi-class SVM classifier, a K-means clustering and a linear regression for estimating the ground bearing capacity. To evaluate the feasibility and capabilities of the presented approach, several experimental tests were carried out in a sandy-loam terrain. The proposed solution offers notable benefits such as its non-invasiveness to the soil, its spatial coverage without the need for exhaustive manual measurements and its real time operation. Therefore, it can be very useful in decision making processes that tend to reduce ground damage during agricultural and forestry operations. PMID:26083227

  8. Internal and external stray radiation suppression for LWIR catadioptric telescope using non-sequential ray tracing

    NASA Astrophysics Data System (ADS)

    Zhu, Yang; Zhang, Xin; Liu, Tao; Wu, Yanxiong; Shi, Guangwei; Wang, Lingjie

    2015-07-01

    A long wave infrared imaging system operated for space exploration of faint target is highly sensitive to stray radiation. We present an integrative suppression process of internal and external stray radiation. A compact and re-imaging LWIR catadioptric telescope is designed as practical example and internal and external stray radiation is analyzed for this telescope. The detector is cryogenically cooled with 100% cold shield efficiency of Lyot stop. A non-sequential ray tracing technique is applied to investigate how the stray radiation propagates inside optical system. The simulation and optimization during initial design stage are proceeded to avoid subversive defect that the stray radiation disturbs the target single. The quantitative analysis of stray radiation irradiance emitted by lenses and structures inside is presented in detail. The optical elements, which operate at room-temperature due to the limitation of weight and size, turn to be the significant stray radiation sources. We propose a method combined infrared material selection and optical form optimization to reduce the internal stray radiation of lens. We design and optimize mechanical structures to achieve a further attenuation of internal stray radiation power. The point source transmittance (PST) is calculated to assess the external radiation which comes from the source out of view field. The ghost of bright target due to residual reflection of optical coatings is simulated. The results show that the performance of stray radiation suppression is dramatically improved by iterative optimization and modification of optomechanical configurations.

  9. Optical design of a static LWIR Fourier-transform imaging spectrometer with high throughput

    NASA Astrophysics Data System (ADS)

    Wang, Hai-yang; Fu, Yan-peng; Zheng, Wei-jian; Liao, Ning-fang; Jin, Wei-qi

    2013-08-01

    A LWIR Fourier-transform imaging spectrometer based on the static Michelson interferometer with high throughput is presented. Advantages and disadvantages of some common structures of imaging spectrometer are analyzed. Some selection of optimum configurations for imaging spectrometer is proceeded. The interferogram is acquired over the whole field of the camera while the scene of interest scans the path difference range, and vignetting should be strongly limited while keeping the size of the interferometer as small as possible for manufacturability and practicability reasons. The key point is to put the entrance pupil of the imaging lens inside the interferometer. The design of optical system is proposed. The field of view(FOV) is 10°.The operating wavelength range is from 8 to 12μm, F number is 2 and the working temperature range is -20°C~40°C. Optical system with 100% cold shield efficiency is good adaptability to wide environment temperature change. The spectrometer system has low utilization of solar energy in the infrared band, so to ensure its transmittance, and it is necessary to use a small amount of lenses as possible, so here the method of the active electromechanical athermalisation just uses four lenses in the system. Modulation transfer function (MTF), aberrant and distortion etc of optical system are analyzed. The results show that an excellent performance and image performance are obtained despite the simple structure.

  10. Focal plane readout for 2-D LWIR application implemented with current mode background suppression per pixel

    NASA Astrophysics Data System (ADS)

    Woo, Doo Hyung; Kang, Sang Gu; Lee, Hee Chul

    2004-02-01

    In this paper, a readout technique involving current mode background suppression is studied for 2-dimensional infrared focal plane arrays (IR FPA"s). This technique has a current memory per pixel, and the suppression current can be optimized per pixel element. Capacitive transimpedende amplifier (CTIA) and feedback amplifier structure are adopted for input circuit and background suppression circuit, respectively. Feedback amplifier structure can minimize skimming error due to channel length modulation. The area size of the pixel circuit is generally limited in the case of 2-D application. So, the amplifier used in the CTIA input circuit adopts timesharing for background suppression. To further improve the area limitation, a half circuit of the CTIA is shared in row circuit out of the pixel array. Because of the leakage of the current memory, the skimming data of the current memory in the pixel array is stored in SRAM array through ADC, and is refreshed periodically with SRAM data through DAC. The readout circuit was fabricated using 0.6um 2-poly 3-metal CMOS process for 64 x 64 LWIR HgCdTe IR array with the pixel size of 50um x 50um. The measurement performance of the skimming circuit exhibits about only 3% error for 100nA background current. The simulation results exhibit that skimming error can be reduced further to 0.3% when the ratioed current mirror scheme and/or multi step refresh scheme is adopted.

  11. LWIR HgCdTe: Innovative detectors in an incumbent technology

    NASA Technical Reports Server (NTRS)

    Tennant, William E.

    1990-01-01

    HgCdTe is the current material of choice for high performance imagers operating at relatively high temperatures. Its lack of technological maturity compared with silicon and wide-band gap III-V compounds is more than offset by its outstanding IR sensitivity and by the relatively benign effect of its materials defects. This latter property has allowed non-equilibrium growth techniques, metal oxide chemical vapor deposition (MOCVD) and molecular beam epitaxy (MBE), to produce device quality long wavelength infrared (LWIR) HgCdTe even on common substrates like GaAs and GaAs/Si. Detector performance in these exotic materials structures is comparable in many ways with devices in equilibrium-grown material. Lifetimes are similar. RoA values at 77K as high as several hundred have been seen in HgCdTe/GaAs/Si with 9.5 micron cut-off wavelength. HgCdTe/GaAs layers with approx. 15 micron cut-off wavelengths have given average 77K RoAs of greater than 2. Hybrid focal plane arrays have been evaluated with excellent operability.

  12. 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.

  13. A New Hyperspectral Designed for Small UAS Tested in Real World Applications

    NASA Astrophysics Data System (ADS)

    Marcucci, E.; Saiet, E., II; Hatfield, M. C.

    2014-12-01

    The ability to investigate landscape and vegetation from airborne instruments offers many advantages, including high resolution data, ability to deploy instruments over a specific area, and repeat measurements. The Alaska Center for Unmanned Aircraft Systems Integration (ACUASI) has recently integrated a hyperspectral imaging camera onto their Ptarmigan hexacopter. The Rikola Hyperspectral Camera manufactured by VTT and Rikola, Ltd. is capable of obtaining data within the 400-950 nm range with an accuracy of ~1 nm. Using the compact flash on the UAV limits the maximum number of channels to 24 this summer. The camera uses a single frame to sequentially record the spectral bands of interest in a 37° field-of-view. Because the camera collects data as single frames it takes a finite amount of time to compile the complete spectral. Although each frame takes only 5 nanoseconds, co-registration of frames is still required. The hovering ability of the hexacopter helps eliminate frame shift. GPS records data for incorporation into a larger dataset. Conservatively, the Ptarmigan can fly at an altitude of 400 feet, for 15 minutes, and 7000 feet away from the operator. The airborne hyperspectral instrument will be extremely useful to scientists as a platform that can provide data on-request. Since the spectral range of the camera is ideal for the study of vegetation, this study 1) examines seasonal changes of vegetation of the Fairbanks area, 2) ground-truths satellite measurements, and 3) ties vegetation conditions around a weather tower to the tower readings. Through this proof of concept, ACUASI provides a means for scientists to request the most up-to-date and location-specific data for their field sites. Additionally, the resolution of the airborne instruments is much higher than that of satellite data, these may be readily tasked, and they have the advantage over manned flights in terms of manpower and cost.

  14. Thermal infrared spectral imager for airborne science applications

    NASA Astrophysics Data System (ADS)

    Johnson, William R.; Hook, Simon J.; Mouroulis, Pantazis; Wilson, Daniel W.; Gunapala, Sarath D.; Hill, Cory J.; Mumolo, Jason M.; Realmuto, Vincent; Eng, Bjorn T.

    2009-05-01

    An airborne thermal hyperspectral imager is underdevelopment which utilizes the compact Dyson optical configuration and quantum well infrared photo detector (QWIP) focal plane array. The Dyson configuration uses a single monolithic prism-like grating design which allows for a high throughput instrument (F/1.6) with minimal ghosting, stray-light and large swath width. The configuration has the potential to be the optimal imaging spectroscopy solution unmanned aerial vehicles (UAV) due to its small form factor and relatively low power requirements. The planned instrument specifications are discussed as well as design trade-offs. Calibration testing results (noise equivalent temperature difference, spectral linearity and spectral bandwidth) and laboratory emissivity plots from samples are shown using an operational testbed unit which has similar specifications as the final airborne system. Field testing of the testbed unit was performed to acquire plots of emissivity for various known standard minerals (quartz). A comparison is made using data from the ASTER spectral library.

  15. Towards HyTES: an airborne thermal imaging spectroscopy instrument

    NASA Astrophysics Data System (ADS)

    Johnson, William R.; Hook, Simon J.; Mouroulis, Pantazis; Wilson, Daniel W.; Gunapala, Sarath D.; Hill, Cory J.; Mumolo, Jason M.; Realmuto, Vincent; Eng, Bjorn T.

    2009-08-01

    An airborne thermal hyperspectral imager is underdevelopment which utilizes the compact Dyson optical configuration and quantum well infrared photo detector (QWIP) focal plane array. The Dyson configuration uses a single monolithic prism-like grating design which allows for a high throughput instrument (F/1.6) with minimal ghosting, stray-light and large swath width. The configuration has the potential to be the optimal imaging spectroscopy solution unmanned aerial vehicles (UAV) due to its small form factor and relatively low power requirements. The planned instrument specifications are discussed as well as design trade-offs. Calibration testing results (noise equivalent temperature difference, spectral linearity and spectral bandwidth) and laboratory emissivity plots from samples are shown using an operational testbed unit which has similar specifications as the final airborne system. Field testing of the testbed unit was performed to acquire plots of emissivity for various known standard minerals (quartz). A comparison is made using data from the ASTER spectral library.

  16. Range-gated intensified spectrographic imager: an instrument for active hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Simard, Jean-Robert; Mathieu, Pierre; Fournier, Georges R.; Larochelle, Vincent; Babey, Stephen K.

    2000-09-01

    Hyperspectral imaging has demonstrated impressive capabilities in airborne surveys, particularly for mineral and biomass characterizations. Based on this success, it is believed that other applications like search and rescue operations, and detection/identification of various ground military targets could greatly benefit from this technology. The strength of hyperspectral imaging comes from the access to another dimension of information: the spectral content of the detected return signal for each spatial pixel. In the case of conventional hyperspectral imaging, the return signal depicts the spectral reflectance of the day irradiance from the scene within the field of view of each pixel. However, by inserting a range-gated intensifier into a hyperspectral camera and by combining the camera with selected pulsed lasers, it becomes possible to relate the returned spectral information to specific light/matter interactions like induced fluorescence. This new technique may be referred to as 'active hyperspectral imaging.' Among its advantages, this approach is independent of the ambient lighting conditions and can be customized in excitation wavelengths. Moreover, by using a range-gated intensified camera, it is possible to survey limited area with a significant increase in signal-to-noise ratio. A camera of this type has been built by our group in collaboration with private industry and is described in this paper. The internal design of the camera is discussed, new issues concerning the calibration of the camera are depicted and a model based on signal-to-noise ratio analysis is presented. From the fluorescent characteristics of surrogate land mines measured in the laboratory, this model is used to predict the capabilities of detecting surface-laid mines from an aerial platform based scenario.

  17. Differentiating aquatic plant communities in a eutrophic river using hyperspectral and multispectral remote sensing

    USGS Publications Warehouse

    Tian, Y.Q.; Yu, Q.; Zimmerman, M.J.; Flint, S.; Waldron, M.C.

    2010-01-01

    This study evaluates the efficacy of remote sensing technology to monitor species composition, areal extent and density of aquatic plants (macrophytes and filamentous algae) in impoundments where their presence may violate water-quality standards. Multispectral satellite (IKONOS) images and more than 500 in situ hyperspectral samples were acquired to map aquatic plant distributions. By analyzing field measurements, we created a library of hyperspectral signatures for a variety of aquatic plant species, associations and densities. We also used three vegetation indices. Normalized Difference Vegetation Index (NDVI), near-infrared (NIR)-Green Angle Index (NGAI) and normalized water absorption depth (DH), at wavelengths 554, 680, 820 and 977 nm to differentiate among aquatic plant species composition, areal density and thickness in cases where hyperspectral analysis yielded potentially ambiguous interpretations. We compared the NDVI derived from IKONOS imagery with the in situ, hyperspectral-derived NDVI. The IKONOS-based images were also compared to data obtained through routine visual observations. Our results confirmed that aquatic species composition alters spectral signatures and affects the accuracy of remote sensing of aquatic plant density. The results also demonstrated that the NGAI has apparent advantages in estimating density over the NDVI and the DH. In the feature space of the three indices, 3D scatter plot analysis revealed that hyperspectral data can differentiate several aquatic plant associations. High-resolution multispectral imagery provided useful information to distinguish among biophysical aquatic plant characteristics. Classification analysis indicated that using satellite imagery to assess Lemna coverage yielded an overall agreement of 79% with visual observations and >90% agreement for the densest aquatic plant coverages. Interpretation of biophysical parameters derived from high-resolution satellite or airborne imagery should prove to be a

  18. The Hyperspectral Satellite and Program EnMAP (Environmental Monitoring and Analysis Program)

    NASA Astrophysics Data System (ADS)

    Stuffler, T.; Kaufmann, C.; Hofer, S.; Förster, K. P.; Schreier, G.; Mueller, A.; Penné, B.

    2008-08-01

    In the upcoming generation of satellite sensors, hyperspectral instruments will play a significant role and are considered world-wide within different future planning. Our team has successfully finished the Phase B study for the advanced hyperspectral mission EnMAP. Routine operations shall start in 2012. The scientific lead of the mission is at the GFZ and the industrial prime ship at Kayser-Threde. The performance of the hyperspectral instrument allows for a detailed monitoring, characterisation and parameter extraction of rock/soil targets, vegetation, and inland and coastal waters on a global scale supporting a wide variety of applications in agriculture, forestry, water management and geology. The EnMAP instrument provides over 240 continuous spectral bands in the wavelength range between 420 - 2450 nm with a ground resolution of 30 m x 30 m. Thus, the broad science and application community can draw from an extensive and highly resolved pool of information supporting the modelling and optimisation process on their results. The operation of an airborne system (ARES) as an element in the HGF hyperspectral network and the ongoing evolution concerning data handling and extraction procedures, will support the later inclusion process of EnMAP into the growing scientist and user communities. As a scientific pathfinder mission a broad international science community has raised larger interest in the hyperspectral data sets as well as value adding companies investigating the commercial potential of EnMAP. The presented paper describes the instrument and mission highlighting the data application and the actual status in the EnMAP planning phase.

  19. Progressive band processing for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Schultz, Robert C.

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

  20. 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...

  1. Airborne oceanographic lidar system

    NASA Technical Reports Server (NTRS)

    Bressel, C.; Itzkan, I.; Nunes, J. E.; Hoge, F.

    1977-01-01

    The characteristics of an Airborne Oceanographic Lidar (AOL) are given. The AOL system is described and its potential for various measurement applications including bathymetry and fluorosensing is discussed.

  2. Exploitation of combined visible hyperspectral and infrared imagery

    NASA Astrophysics Data System (ADS)

    Smith, Geoffrey B.; Marmorino, George O.; Miller, W. David

    2008-11-01

    Natural and anthropogenic surfactants accumulate at the air-sea interface, forming microlayer films, slicks, and foam patches. The resulting enhanced viscoelasticity of the interface alters the small-scale wave spectrum and near-surface turbulence. These changes alter the surface thermal boundary layer and ``skin'' temperature, making infrared thermal imagery ideal for detecting/mapping/studying ocean slicks. Slicks are found under a range of conditions and can result from physical straining of the sea surface (e.g. internal waves) as well as from local biological processes (e.g. plankton blooms). Airborne datasets that combine simultaneous airborne infrared and visible wavelength hyperspectral remote sensing data are now available and provide new opportunities to investigate the physical and biological processes that result in ocean slicks. In addition to the multiple sensors, these datasets are at spatial and time scales much smaller than possible with available satellite remote sensors. This enables the study of a much broader range of phenomena. In particular we investigate the relationship between surface accumulations of vegetative material, ocean slicks and surface temperature changes. We also investigate the relationship between the presence of slicks and water column chromophoric dissolved organic matter (CDOM).

  3. Detecting leafy spurge in native grassland using hyperspectral image analysis

    NASA Astrophysics Data System (ADS)

    Kloppenburg, Catherine

    Leafy spurge (Euphoria esula L.) is a perennial noxious weed that has been encroaches on the native grassland regions of North America resulting in biological and economic impacts. Leafy spurge growth is most prevalent along river banks and in pasture areas. Due to poor accessibility and the cost and labour associated with data collection, estimates of number and size of leafy spurge infestations is poor. Remote sensing has the ability to cover large areas, providing an alternate means to ground surveys and will allow for the capability to create an accurate baseline of infestations. Airborne hyperspectral data were collected over the two test sites selected on the Blood Reserve in Southern Alberta using a combined Airborne Imaging Spectrometer for different Applications (AISA) Eagle and Hawk sensor systems in July, 2010. This study used advanced analysis tools, including spectral mixture analysis, spectral angle mapper and mixture-tuned matched filter techniques to evaluate the ability to detect leafy spurge patches. The results show that patches of leafy spurge with flowering stem density >40 stems m-2 were identified with 85 % accuracy while identification of lower density stems were less accurate (10 - 40 %). The results are promising with respect to quantifying areas of significant leafy spurge infestation and targeting biological control and potential insect release sites.

  4. Integration of thermal and hyperspectral VNIR imagery for architectural and artistic heritage analysis and monitoring

    NASA Astrophysics Data System (ADS)

    Cavalli, Rosa Maria; Masini, Nicola; Pascucci, Simone; Palombo, Angelo; Pignatti, Stefano

    2010-05-01

    The application of integrated hyperspectral VNIR and thermal data for analyzing and monitoring the architectural and artistic heritage status is becoming a remarkable tool to be combined with other non-destructive techniques (e.g. GPR), and prior to destructive checking, in order to extract appropriate information and make useful decisions [1]. As the analysis of some kind of damages (e.g. water infiltrations) or alterations is not always fulfilled with visible and thermographic imagery, the proposed study aims at integrating hyperspectral reflectances and temperature and apparent thermal inertia behaviours. Hyperspectral data is able to discriminate materials on the basis of their different patterns of wavelength-specific absorption; in fact, they are successfully used for identifying minerals and rocks, as well as detecting soil properties including moisture, organic content and salinity [2]. Moreover, the potential to find out alterations or damages and monitoring them through non-destructive sensors is particularly appreciated in structural analysis for restoration works such as water infiltrations in outdoor cultural assets and moisture penetration in a wall that is a major source of paint alteration [3, 4]. The jointly use of the reflective and infrared (emitted, absorbed, reflected and transmitted) radiation for this research study is encouraged by the technical and operative characteristics of the observation systems at disposal that can provide high spectral resolution and high-frequency images with low Ne?R e Ne?T values and able to observe the variables and physical and optical parameters in quasi real-time and connected to the cultural heritage status. The following portable field instruments are used for this study: (a) HYSPEX hyperspectral scanner working in the VNIR (0.4-1.0μm) spectral region, which is an imaging spectrometer with a very high spectral and spatial resolution, (b) 2 FLIR SC7000 Thermal cams working in the MWIR (3-5 micron) and LWIR

  5. Integration of thermal and hyperspectral VNIR imagery for architectural and artistic heritage analysis and monitoring

    NASA Astrophysics Data System (ADS)

    Cavalli, Rosa Maria; Masini, Nicola; Pascucci, Simone; Palombo, Angelo; Pignatti, Stefano

    2010-05-01

    The application of integrated hyperspectral VNIR and thermal data for analyzing and monitoring the architectural and artistic heritage status is becoming a remarkable tool to be combined with other non-destructive techniques (e.g. GPR), and prior to destructive checking, in order to extract appropriate information and make useful decisions [1]. As the analysis of some kind of damages (e.g. water infiltrations) or alterations is not always fulfilled with visible and thermographic imagery, the proposed study aims at integrating hyperspectral reflectances and temperature and apparent thermal inertia behaviours. Hyperspectral data is able to discriminate materials on the basis of their different patterns of wavelength-specific absorption; in fact, they are successfully used for identifying minerals and rocks, as well as detecting soil properties including moisture, organic content and salinity [2]. Moreover, the potential to find out alterations or damages and monitoring them through non-destructive sensors is particularly appreciated in structural analysis for restoration works such as water infiltrations in outdoor cultural assets and moisture penetration in a wall that is a major source of paint alteration [3, 4]. The jointly use of the reflective and infrared (emitted, absorbed, reflected and transmitted) radiation for this research study is encouraged by the technical and operative characteristics of the observation systems at disposal that can provide high spectral resolution and high-frequency images with low Ne?R e Ne?T values and able to observe the variables and physical and optical parameters in quasi real-time and connected to the cultural heritage status. The following portable field instruments are used for this study: (a) HYSPEX hyperspectral scanner working in the VNIR (0.4-1.0μm) spectral region, which is an imaging spectrometer with a very high spectral and spatial resolution, (b) 2 FLIR SC7000 Thermal cams working in the MWIR (3-5 micron) and LWIR

  6. NASA image-based geological expert system development project for hyperspectral image analysis

    NASA Technical Reports Server (NTRS)

    Chiou, W. C., Sr.

    1985-01-01

    The NASA image-based geological expert system was applied to analyze remotely sensed hyperspectral image data. The major objective is for geologists to identify the earth surface mineral properties directly from the airborne and spaceborne imaging spectrometer data. With certain constraints, it is shown that the system can identify correctly different classes of mineral. It has the built-in learning paradigm to enhance the confidence factor of mineral identification. A very powerful natural language system was incorporated as the user-friendly front end, and the concurrent processing efficiency of the frame-based knowledge representation in the hypercube microsupercomputer simulation was tested.

  7. Measured comparison of the crossover periods for mid- and long-wave IR (MWIR and LWIR) polarimetric and conventional thermal imagery.

    PubMed

    Felton, M; Gurton, K P; Pezzaniti, J L; Chenault, D B; Roth, L E

    2010-07-19

    We report the results of a multi-day diurnal study in which polarimetric and conventional thermal imagery is recorded in the mid- and long-wave IR to identify and compare the respective time periods in which minimum target contrast is achieved. The data shows that the chief factors affecting polarimetric contrast in both wavebands are the amount of thermal emission from the objects in the scene and the abundance of MWIR and LWIR sources in the optical background. In particular, it has been observed that the MWIR polarimetric contrast was positively correlated to the presence of MWIR sources in the optical background, while the LWIR polarimetric contrast was negatively correlated to the presence of LWIR sources in the optical background. PMID:20720953

  8. Identification of unknown waste sites using MIVIS hyperspectral images

    SciTech Connect

    Gomarasca, M.A.; Strobelt, S.

    1996-11-01

    This paper presents the results on the individuation of known and unknown (illegal) waste sites using Landsat TM satellite imagery and airborne MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) data for detailed analysis in Italy. Previous results with Landsat TM imagery were partially positive for large waste site identification and negative for small sites. Information acquired by the MIVIS hyperspectral system presents three main characteristics: local scale study, possibility to plan the proper period based on the objectives of the study, high number of spectral bands with high spectral and geometrical resolution. MIVIS airborne shootings were carried out on 7 July 1994 at noon with 4x4 m pixel resolution. The MIVIS 102 bands` sensors can distinguish even objects with similar spectral behavior, thanks to its high spectral resolution. Identification of degraded sites is obtained using traditional spectral and statistical operators (NDVI, Principal Component Analysis, Maximum Likelihood classifier) and innovative combination of filtered band ratios realized to extract specific waste elements (acid slimes or contaminated soils). One of the aims that concerns with this study is the definition of an operative program for the characterization, identification and classification of defined categories of waste disposal sites. The best schedule for the data collection by airborne MIVIS oriented to this target is defined. The planning of the proper flight, based on the waste sites features, is important to optimize this technology. One of the most efficient methods for detecting hidden waste sites is the thermal inertia so two images are necessary: one during low sun load and one with high sun load. The results obtained are operationally useful and winning. This instrument, supported by correct analysis techniques, may offer new interesting prospects in territorial management and environmental monitoring. 5 refs., 5 figs., 1 tab.

  9. Above ground biomass estimation from lidar and hyperspectral airbone data in West African moist forests.

    NASA Astrophysics Data System (ADS)

    Vaglio Laurin, Gaia; Chen, Qi; Lindsell, Jeremy; Coomes, David; Cazzolla-Gatti, Roberto; Grieco, Elisa; Valentini, Riccardo

    2013-04-01

    The development of sound methods for the estimation of forest parameters such as Above Ground Biomass (AGB) and the need of data for different world regions and ecosystems, are widely recognized issues due to their relevance for both carbon cycle modeling and conservation and policy initiatives, such as the UN REDD+ program (Gibbs et al., 2007). The moist forests of the Upper Guinean Belt are poorly studied ecosystems (Vaglio Laurin et al. 2013) but their role is important due to the drier condition expected along the West African coasts according to future climate change scenarios (Gonzales, 2001). Remote sensing has proven to be an effective tool for AGB retrieval when coupled with field data. Lidar, with its ability to penetrate the canopy provides 3D information and best results. Nevertheless very limited research has been conducted in Africa tropical forests with lidar and none to our knowledge in West Africa. Hyperspectral sensors also offer promising data, being able to evidence very fine radiometric differences in vegetation reflectance. Their usefulness in estimating forest parameters is still under evaluation with contrasting findings (Andersen et al. 2008, Latifi et al. 2012), and additional studies are especially relevant in view of forthcoming satellite hyperspectral missions. In the framework of the EU ERC Africa GHG grant #247349, an airborne campaign collecting lidar and hyperspectral data has been conducted in March 2012 over forests reserves in Sierra Leone and Ghana, characterized by different logging histories and rainfall patterns, and including Gola Rainforest National Park, Ankasa National Park, Bia and Boin Forest Reserves. An Optech Gemini sensor collected the lidar dataset, while an AISA Eagle sensor collected hyperspectral data over 244 VIS-NIR bands. The lidar dataset, with a point density >10 ppm was processed using the TIFFS software (Toolbox for LiDAR Data Filtering and Forest Studies)(Chen 2007). The hyperspectral dataset, geo

  10. Reconciling In Situ Foliar Nitrogen and Vegetation Structure Measurements with Airborne Imagery Across Ecosystems

    NASA Astrophysics Data System (ADS)

    Flagg, C.

    2015-12-01

    Over the next 30 years the National Ecological Observatory Network (NEON) will monitor environmental and ecological change throughout North America. NEON will provide a suite of standardized data from several ecological topics of interest, including net primary productivity and nutrient cycling, from 60+ sites across 20 eco-climatic domains when fully operational in 2017. The breadth of sampling includes ground-based measurements of foliar nitrogen and vegetation structure, ground-based spectroscopy, airborne LIDAR, and airborne hyperspectral surveys occurring within narrow overlapping time intervals once every five years. While many advancements have been made in linking and scaling in situ data with airborne imagery, establishing these relationships across dozens of highly variable sites poses significant challenges to understanding continental-wide processes. Here we study the relationship between foliar nitrogen content and airborne hyperspectral imagery at different study sites. NEON collected foliar samples from three sites in 2014 as part of a prototype study: Ordway Swisher Biological Station (pine-oak savannah, with active fire management), Jones Ecological Research Center (pine-oak savannah), and San Joaquin Experimental Range (grass-pine oak woodland). Leaf samples and canopy heights of dominant and co-dominant species were collected from trees located within 40 x 40 meter sampling plots within two weeks of aerial LIDAR and hyperspectral surveys. Foliar canopy samples were analyzed for leaf mass per area (LMA), stable isotopes of C and N, C/N content. We also examine agreement and uncertainty between ground based canopy height and airborne LIDAR derived digital surface models (DSM) for each site. Site-scale maps of canopy nitrogen and canopy height will also be presented.

  11. Possibilities for LWIR detectors using MBE-grown Si(/Si(1-x)Ge(x) structures

    NASA Technical Reports Server (NTRS)

    Hauenstein, Robert J.; Miles, Richard H.; Young, Mary H.

    1990-01-01

    Traditionally, long wavelength infrared (LWIR) detection in Si-based structures has involved either extrinsic Si or Si/metal Schottky barrier devices. Molecular beam epitaxially (MBE) grown Si and Si/Si(1-x)Ge(x) heterostructures offer new possibilities for LWIR detection, including sensors based on intersubband transitions as well as improved conventional devices. The improvement in doping profile control of MBE in comparison with conventional chemical vapor deposited (CVD) Si films has resulted in the successful growth of extrinsic Si:Ga, blocked impurity-band conduction detectors. These structures exhibit a highly abrupt step change in dopant profile between detecting and blocking layers which is extremely difficult or impossible to achieve through conventional epitaxial growth techniques. Through alloying Si with Ge, Schottky barrier infrared detectors are possible, with barrier height values between those involving pure Si or Ge semiconducting materials alone. For both n-type and p-type structures, strain effects can split the band edges, thereby splitting the Schottky threshold and altering the spectral response. Measurements of photoresponse of n-type Au/Si(1-x)Ge(x) Schottky barriers demonstrate this effect. For intersubband multiquntum well (MQW) LWIR detection, Si(1-x)Ge(x)/Si detectors grown on Si substrates promise comparable absorption coefficients to that of the Ga(Al)As system while in addition offering the fundamental advantage of response to normally incident light as well as the practical advantage of Si-compatibility. Researchers grew Si(1-x)Ge(x)/Si MQW structures aimed at sensitivity to IR in the 8 to 12 micron region and longer, guided by recent theoretical work. Preliminary measurements of n- and p-type Si(1-x)Ge(x)/Si MQW structures are given.

  12. Implementation of pixel level digital TDI for scanning type LWIR FPAs

    NASA Astrophysics Data System (ADS)

    Ceylan, Omer; Kayahan, Huseyin; Yazici, Melik; Afridi, Sohaib; Shafique, Atia; Gurbuz, Yasar

    2014-07-01

    Implementation of a CMOS digital readout integrated circuit (DROIC) based on pixel level digital time delay integration (TDI) for scanning type LWIR focal plane arrays (FPAs) is presented. TDI is implemented on 8 pixels with over sampling rate of 3. Analog signal integrated on integration capacitor is converted to digital domain in pixel, and digital data is transferred to TDI summation counters, where contributions of 8 pixels are added. Output data is 16 bit, where 8 bits are allocated for most significant bits and 8 bits for least significant bits. Control block of the ROIC, which is responsible of generating timing diagram for switches controlling the pixels and summation counters, is realized with VerilogHDL. Summation counters and parallel-to-serial converter to convert 16 bit parallel output data to single bit output are also realized with Verilog HDL. Synthesized verilog netlists are placed&routed and combined with analog under-pixel part of the design. Quantization noise of analog-to-digital conversion is less than 500e-. Since analog signal is converted to digital domain in-pixel, inaccuracies due to analog signal routing over large chip area is eliminated. ROIC is fabricated with 0.18μm CMOS process and chip area is 10mm2. Post-layout simulation results of the implemented design are presented. ROIC is programmable through serial or parallel interface. Input referred noise of ROIC is less than 750 rms electron, while power consumption is less than 30mW. ROIC is designed to perform in cryogenic temperatures.

  13. Implementation of electronic crosstalk correction for terra MODIS PV LWIR bands

    NASA Astrophysics Data System (ADS)

    Geng, Xu; Madhavan, Sriharsha; Chen, Na; Xiong, Xiaoxiong

    2015-09-01

    The MODerate-resolution Imaging Spectroradiometer (MODIS) is one of the primary instruments in the fleet of NASA's Earth Observing Systems (EOS) in space. Terra MODIS has completed 15 years of operation far exceeding its design lifetime of 6 years. The MODIS Level 1B (L1B) processing is the first in the process chain for deriving various higher level science products. These products are used mainly in understanding the geophysical changes occurring in the Earth's land, ocean, and atmosphere. The L1B code is designed to carefully calibrate the responses of all the detectors of the 36 spectral bands of MODIS and provide accurate L1B radiances (also reflectances in the case of Reflective Solar Bands). To fulfill this purpose, Look Up Tables (LUTs), that contain calibration coefficients derived from both on-board calibrators and Earth-view characterized responses, are used in the L1B processing. In this paper, we present the implementation mechanism of the electronic crosstalk correction in the Photo Voltaic (PV) Long Wave InfraRed (LWIR) bands (Bands 27-30). The crosstalk correction involves two vital components. First, a crosstalk correction modular is implemented in the L1B code to correct the on-board Blackbody and Earth-View (EV) digital number (dn) responses using a linear correction model. Second, the correction coefficients, derived from the EV observations, are supplied in the form of LUTs. Further, the LUTs contain time stamps reflecting to the change in the coefficients assessed using the Noise Equivalent difference Temperature (NEdT) trending. With the algorithms applied in the MODIS L1B processing it is demonstrated that these corrections indeed restore the radiometric balance for each of the affected bands and substantially reduce the striping noise in the processed images.

  14. MWIR/LWIR filter based on Liquid-Crystal Fabry-Perot structure for tunable spectral imaging detection

    NASA Astrophysics Data System (ADS)

    Zhang, Huaidong; Muhammad, Afzal; Luo, Jun; Tong, Qing; Lei, Yu; Zhang, Xinyu; Sang, Hongshi; Xie, Changsheng

    2015-03-01

    An electrically tunable medium-wave infrared (MWIR)/long-wave infrared (LWIR) filter based on the key structure of Liquid-Crystal (LC) Fabry-Perot (FP), which works in the wavelength range from 2.5 μm to 12 μm, is designed and fabricated successfully in this paper. According to the optical interference principle of the FP cavity and electrically controlled birefringence of nematic LC molecules, the particular functions including spectral selection and spectral staring and spectral adjustment, can be realized by the developed MWIR/LWIR filter driven and controlled electrically. As to the LC-FP filter, both planar reflective mirrors are shaped by depositing a layer of aluminum (Al) film (∼60 nm) over one side of double-side polished Zinc Selenide (ZnSe) wafer (∼1 mm), and then polyimide (PI) layer with the thickness of ∼100 nm is coated directly on Al film. With typical sandwich architecture, the depth of the cavity with nematic LC molecules sealed in is ∼7.5 μm. To make sure the LC molecules parallel aligned and twist regularly under voltage driving signal applied on Al film, which also acts as electrode, the V-grooves are formed in PI layer with the depth of ∼90 nm and the width of ∼350 nm at average by strong rubbing. The typical transmission spectrum in MWIR&LWIR wavelength range and several spectral images in MWIR wavelength range based on the fabricated LC-FP filter, have been obtained through applying a voltage driving-signal with different root-means-square (RMS) value over the electrodes of LC-FP filter in the selected voltage range from 0VRMS to 19.8VRMS. The testing result demonstrates a prospect of realization smart spectral imaging and further integrating the LC-FP filter with infrared focal plane arrays (FPAs) to achieve the purpose infrared multispectral imaging. The developed MWIR&LWIR LC-FP filters show some obvious advantages such as wide working wavelength range, electrically tunable spectral selection, ultra-compact, low cost, being

  15. 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

  16. 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.

  17. HRIS technology development results and their implementation in future hyperspectral imagers

    NASA Astrophysics Data System (ADS)

    Harnisch, Bernd; Fabbricotti, Marino; Meynart, Roland; Kunkel, Bernd P.; Posselt, Winfried; Schmidt, Elke; Davancens, Robert; Donnadieu, Olivier; Saint-Pe, Olivier; Charlton, Dave E.; Sankus, Liz; Basile, Giuseppe; Calamei, L.; Schweizer, Juergen; Juranek, Hans J.; Sand, Rolf; Schwarzer, Horst H.; Suemnich, Karl-Heinz; Slater, Philip N.

    1997-12-01

    The recent developments within the ESA funded HRIS (high resolution imaging spectrometer) technology program -- aiming at an airborne demonstrator model -- yielded rather successful subsystem developments. HRIS is designed as a true pushbroom hyperspectral imager with comparatively high spatial and spectral resolution, covering the spectral range from 450 to 2350 nm. The main breadboard units, with a space-near design, are essentially: a TMA (three mirro anastigmat, Carl Zeiss) front optics, a dual path spectrometer optics (Officine Galileo) with a novel in-field spectral separation unit, a 2-D SWIR CMT detector array with a dedicated CMOS readout multiplexer (GEC Marconi IR, MATRA MSF for testing), the signal processing electronics (DSS), some calibration elements (DLR + DSS), and the extensive testing of all units. The paper presents the essential results per unit, with possible exception of the front optics (which may not be completed at the conference paper presentation yet), including derived further development efforts. Also, the remaining steps towards an airborne test mission are outlined, together with a brief description of the envisaged high-altitude aircraft. We hope that this paper may also stir some potential users of later airborne HRIS test missions over dedicated target areas. Positive responses would support ESA to pursue the program. The technology units development under the HRIS contract have turned out useful for follow-on instrument developments such as the ESA Explorer mission candidate PRISM (processes research by an imaging space mission). This leads to the conclusion that the achieved development results are a sound basis for future airborne and spaceborne hyperspectral imager developments in Europe. A brief survey of the current PRISM baseline concept is added to the paper.

  18. 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.

  19. 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.

  20. Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment

    NASA Astrophysics Data System (ADS)

    Koch, Barbara

    2010-11-01

    This is a review of the latest developments in different fields of remote sensing for forest biomass mapping. The main fields of research within the last decade have focused on the use of small footprint airborne laser scanning systems, polarimetric synthetic radar interferometry and hyperspectral data. Parallel developments in the field of digital airborne camera systems, digital photogrammetry and very high resolution multispectral data have taken place and have also proven themselves suitable for forest mapping issues. Forest mapping is a wide field and a variety of forest parameters can be mapped or modelled based on remote sensing information alone or combined with field data. The most common information required about a forest is related to its wood production and environmental aspects. In this paper, we will focus on the potential of advanced remote sensing techniques to assess forest biomass. This information is especially required by the REDD (reducing of emission from avoided deforestation and degradation) process. For this reason, new types of remote sensing data such as fullwave laser scanning data, polarimetric radar interferometry (polarimetric systhetic aperture interferometry, PolInSAR) and hyperspectral data are the focus of the research. In recent times, a few state-of-the-art articles in the field of airborne laser scanning for forest applications have been published. The current paper will provide a state-of-the-art review of remote sensing with a particular focus on biomass estimation, including new findings with fullwave airborne laser scanning, hyperspectral and polarimetric synthetic aperture radar interferometry. A synthesis of the actual findings and an outline of future developments will be presented.

  1. 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

  2. Vessel contrast enhancement in hyperspectral images

    NASA Astrophysics Data System (ADS)

    Bjorgan, Asgeir; Denstedt, Martin; Milanič, Matija; Paluchowski, Lukasz A.; Randeberg, Lise L.

    2015-03-01

    Imaging of vessel structures can be useful for investigation of endothelial function, angiogenesis and hyper-vascularization. This can be challenging for hyperspectral tissue imaging due to photon scattering and absorption in other parts of the tissue. Real-time processing techniques for enhancement of vessel contrast in hyperspectral tissue images were investigated. Wavelet processing and an inverse diffusion model were employed, and compared to band ratio metrics and statistical methods. A multiscale vesselness filter was applied for further enhancement. The results show that vessel structures in hyperspectral images can be enhanced and characterized using a combination of statistical, numerical and more physics informed models.

  3. 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.

  4. Second International Airborne Remote Sensing Conference and Exhibition

    NASA Technical Reports Server (NTRS)

    1996-01-01

    The conference provided four days of displays and scientific presentations on applications, technology, a science of sub-orbital data gathering and analysis. The twelve displayed aircraft equipped with sophisticated instrumentation represented a wide range of environmental and reconnaissance missions,including marine pollution control, fire detection, Open Skies Treaty verification, thermal mapping, hydrographical measurements, military research, ecological and agricultural observations, geophysical research, atmospheric and meterological observations, and aerial photography. The U.S. Air Force and the On-Site Inspection Agency displayed the new Open Skies Treaty verification Boeing OC 135B that promotes international monitoring of military forces and activities. SRl's Jetstream uses foliage and ground penetrating SAR for forest inventories, toxic waste delineation, and concealed target and buried unexploded ordnance detection. Earth Search Sciences's Gulfstream 1 with prototype miniaturized airborne hyperspectral imaging equipment specializes in accurate mineral differentiation, low-cost hydrocarbon exploration, and nonproliferation applications. John E. Chance and the U.S. Army Corps of Engineers displayed the Bell 2 helicopter with SHOALS that performs hydrographic surveying of navigation projects, coastal environment assessment, and nautical charting surveys. Bechtel Nevada and U.S. DOE displayed both the Beech King AIR B-200 platform equipped to provide first response to nuclear accidents and routine environmental surveillance, and the MBB BO-105 helicopter used in spectral analysis for environmental assessment and military appraisal. NASA Ames Research Center's high-altitude Lockheed ER-2 assists in earth resources monitoring research in atmospheric chemistry, oceanography, and electronic sensors; ozone and greenhouse studies and satellite calibration and data validation. Ames also showcased the Learjet 24 Airborne Observatory that completed missions in Venus

  5. Bathymetry Mapping Using Hyperspectral Data: a Case Study of Yamada Bay, Northeast Japan

    NASA Astrophysics Data System (ADS)

    Ariyasu, E.; Kakuta, S.; Takeda, T.

    2016-06-01

    This study aims to examine if the inversion method using hyperspectral data is applicable in Japan. Nowadays, overseas researchers are mainly applied an inversion method for accurately estimating water depth. It is able to gain not only water depth, but also benthic spectral reflection and inherent optical properties (IOPs) at the same time, based on physics-based radiative transfer theory for hyperspectral data. It is highly significant to understand the possibility to develop the application in future for coastal zone of main island, which is a common water quality in Japan, but there is not any case study applied this method in Japan. The study site of Yamada bay in Iwate Prefecture is located in northeast of Japan. An existed analytical model was optimized for mapping water depth in Yamada bay using airborne hyperspectral image and ground survey data which were simultaneously acquired in December, 2015. The retrieved remote-sensing reflectance (Rrs) is basically qualitatively appropriate result. However, when compared with all ground survey points, the retrieved water depth showed low correlation, even though ground points which are selected sand bottom indicates high relationship. Overall, we could understand the inversion method is applicable in Japan. However, it needs to challenge to improve solving error-caused problems.

  6. Advanced hyperspectral imaging solutions for near real-time target detection

    NASA Astrophysics Data System (ADS)

    Weatherbee, Oliver; Janaskie, Justin; Hyvärinen, Timo

    2012-09-01

    AISA hyperspectral imagers have been utilized in airborne applications for various defense related Intelligence, Surveillance and Reconnaissance (ISR) applications. In expanding the utility and capabilities of hyperspectral imagers for defense related applications, the implementation in a ground scanning configuration for check-point and forensic purposes has been achieved. System specifications, design, and operational considerations for a fully automated, near real-time target detection capability are presented. The system utilizes modularized software architecture, combining C++ command, capture, calibration, and messaging functions with drop-in IDL exploitation module for detection algorithm and target set flexibility. Performance capability against known defense related targets of interest have been tested, verified, and are presented utilizing full 400-2450nm spectral range provided by combined AisaEAGLE and AisaHAWK hyperspectral imagers. Initial results are also described for a new extended InGaAs system, covering 585-1630nm to provide a similar capability for integrations which have size, weight, and power restrictions.

  7. Characterization and reduction of stochastic and periodic anomalies in a hyperspectral imaging sensor system

    NASA Astrophysics Data System (ADS)

    Shetler, Bruce V.; Kieffer, Hugh H.

    1996-11-01

    HYDICE, the HYperspectral Digital Imagery Collection Experiment, is an airborne hyperspectral imaging sensor operating in a pushbroom mode. HYDICE collects data simultaneously in 210 wavelength bands from 0.4 to 2.5 micrometers using a prism as the dispersing element. While the overall quality of HYDICE data is excellent, certain data stream anomalies have been identified, among which are a periodic offset in DN level related to the operation of the system cryocooler and a quasi-random variation in the spectral alignment between the dispersed image and the focal plane. In this paper we report on an investigation into the above two effects and the development of algorithms and software to correct or minimize their impact in a production data processing system. We find the periodic variation to have unexpected time and band-dependent characteristics which argues against the possibility of correction in post- processing, but to be relatively insensitive to signal and consequently of low impact on the operation of the system. We investigate spectral jitter through an algorithm which performs a least squares fit to several atmospheric spectral features to characterize both the time-dependent jitter motion and systematic spectral mis-registration. This method is also implemented to correct the anomalies in the production data stream. A comprehensive set of hyperspectral sensor calibration and correction algorithm is also presented.

  8. Trace gas detection in hyperspectral imagery using the wavelet packet subspace

    NASA Astrophysics Data System (ADS)

    Salvador, Mark A. Z.

    This dissertation describes research into a new remote sensing method to detect trace gases in hyperspectral and ultra-spectral data. This new method is based on the wavelet packet transform. It attempts to improve both the computational tractability and the detection of trace gases in airborne and spaceborne spectral imagery. Atmospheric trace gas research supports various Earth science disciplines to include climatology, vulcanology, pollution monitoring, natural disasters, and intelligence and military applications. Hyperspectral and ultra-spectral data significantly increases the data glut of existing Earth science data sets. Spaceborne spectral data in particular significantly increases spectral resolution while performing daily global collections of the earth. Application of the wavelet packet transform to the spectral space of hyperspectral and ultra-spectral imagery data potentially improves remote sensing detection algorithms. It also facilities the parallelization of these methods for high performance computing. This research seeks two science goals, (1) developing a new spectral imagery detection algorithm, and (2) facilitating the parallelization of trace gas detection in spectral imagery data.

  9. Subsurface detection of coral reefs in shallow waters using hyperspectral data

    NASA Astrophysics Data System (ADS)

    Rodriguez-Diaz, Eladio; Jimenez-Rodriguez, Luis O.; Velez-Reyes, Miguel; Gilbes, Fernando; DiMarzio, Charles A.

    2003-09-01

    Hyperspectral Remote Sensing has the potential to be used as an effective coral monitoring system from either space or airborne sensors. The problems to be addressed in hyperspectral imagery of coastal waters are related to the medium, which presents high scattering and absorption, and the object to be detected. The object to be detected, in this case coral reefs or different types of ocean floor, has a weak signal as a consequence of its interaction with the medium. The retrieval of information about these targets requires the development of mathematical models and processing tools in the area of inversion, image reconstruction and detection. This paper presents the development of algorithms that does not use labeled samples to detect coral reefs under coastal shallow waters. Synthetic data was generated to simulate data gathered using a high resolution imaging spectrometer (hyperspectral) sensor. A semi-analytic model that simplifies the radiative transfer equation was used to quantify the interaction between the object of interest, the medium and the sensor. Tikhonov method of regularization was used as a starting point in order to arrive at an inverse formulation that incorporates a priori information about the target. This expression will be used in an inversion process on a pixel by pixel basis to estimate the ocean floor signal. The a priori information is in the form of previously measured spectral signatures of objects of interest, such as sand, corals, and sea grass.

  10. 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

  11. 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.

  12. Hyperspectral imaging using compressed sensing

    NASA Astrophysics Data System (ADS)

    Ramirez I., Gabriel Eduardo; Manian, Vidya B.

    2012-06-01

    Compressed sensing (CS) has attracted a lot of attention in recent years as a promising signal processing technique that exploits a signal's sparsity to reduce its size. It allows for simple compression that does not require a lot of additional computational power, and would allow physical implementation at the sensor using spatial light multiplexers using Texas Instruments (TI) digital micro-mirror device (DMD). The DMD can be used as a random measurement matrix, reflecting the image off the DMD is the equivalent of an inner product between the images individual pixels and the measurement matrix. CS however is asymmetrical, meaning that the signals recovery or reconstruction from the measurements does require a higher level of computation. This makes the prospect of working with the compressed version of the signal in implementations such as detection or classification much more efficient. If an initial analysis shows nothing of interest, the signal need not be reconstructed. Many hyper-spectral image applications are precisely focused on these areas, and would greatly benefit from a compression technique like CS that could help minimize the light sensor down to a single pixel, lowering costs associated with the cameras while reducing the large amounts of data generated by all the bands. The present paper will show an implementation of CS using a single pixel hyper-spectral sensor, and compare the reconstructed images to those obtained through the use of a regular sensor.