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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 and identification of toxic air pollutants using airborne LWIR hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Williams, David J.; Feldman, Barry L.; Williams, Tim J.; Pilant, Drew; Lucey, Paul G.; Worthy, L. D.

    2005-01-01

    Airborne longwave infrared (LWIR) hyperspectral imagery was utilized to detect and identify gaseous chemical release plumes at sites in southern Texas. The Airborne Hyperspectral Imager (AHI), developed by the University of Hawai"i, was flown over a petrochemical facility and a confined animal feeding operation on a modified DC-3 during April, 2004. Data collected by the AHI system was successfully used to detect and identify numerous plumes at both sites. Preliminary results indicate the presence of benzene and ammonia and several other organic compounds. Emissions were identified using regression analysis on atmospherically compensated data. Data validation was conducted using facility emission inventories. This technology has great promise for monitoring and inventorying facility emissions, and may be used as means to assist ground inspection teams to focus on actual fugitive emission points.

  3. 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.

  4. 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.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Dombrowski, Mark S.; Willson, Paul

    1999-10-01

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

  7. 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.

  8. 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.

  9. Detection of gaseous plumes in airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Airborne measurements in the longwave infrared using an imaging hyperspectral sensor

    NASA Astrophysics Data System (ADS)

    Allard, Jean-Pierre; Chamberland, Martin; Farley, Vincent; Marcotte, Frédérick; Rolland, Matthias; Vallières, Alexandre; Villemaire, André

    2008-07-01

    Emerging applications in Defense and Security require sensors with state-of-the-art sensitivity and capabilities. Among these sensors, the imaging spectrometer is an instrument yielding a large amount of rich information about the measured scene. Standoff detection, identification and quantification of chemicals in the gaseous state is one important application. Analysis of the surface emissivity as a means to classify ground properties and usage is another one. Imaging spectrometers have unmatched capabilities to meet the requirements of these applications. Telops has developed the FIRST, a LWIR hyperspectral imager. The FIRST is based on the Fourier Transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. The FIRST, a man portable sensor, provides datacubes of up to 320×256 pixels at 0.35mrad spatial resolution over the 8-12 μm spectral range at spectral resolutions of up to 0.25cm-1. The FIRST has been used in several field campaigns, including the demonstration of standoff chemical agent detection [http://dx.doi.org/10.1117/12.788027.1]. More recently, an airborne system integrating the FIRST has been developed to provide airborne hyperspectral measurement capabilities. The airborne system and its capabilities are presented in this paper. The FIRST sensor modularity enables operation in various configurations such as tripod-mounted and airborne. In the airborne configuration, the FIRST can be operated in push-broom mode, or in staring mode with image motion compensation. This paper focuses on the airborne operation of the FIRST sensor.

  20. 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.

  1. 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...

  2. 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.

  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. 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.

  5. 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.

  6. 1994-1995 CNR LARA project airborne hyperspectral campaigns

    SciTech Connect

    Bianchi, R.; Cavalli, R.M.; Fiumi, L.

    1996-08-01

    CNR established a new laboratory for airborne hyperspectral imaging devoted to environmental problems and since the end of last June 1994 the project (LARA Project) is fully operative to provide hyperspectral data to the national and international scientific community. The Daedalus AA5000 MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) instrument, acquired by CNR (Italian National Research Council) in the framework of its LARA (Airborne Laboratory for Environmental Studies) Project, has been intensively operative. A number of MIVIS deployments have been carried out in Italy and Europe in cooperation with national and international institutions on a variety of sites, including active volcanoes, coastlines, lagoons and ocean, vegetated and cultivated areas, oil polluted surfaces, waste discharges, and archeological sites. One year of activity has shown the high system efficiency, from the survey to data preprocessing and dissemination.

  7. 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.

  8. Novel compact airborne platform for remote sensing applications using the Hyper-Cam infrared hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Turcotte, Caroline S.; Puckrin, Eldon; Aube, Françoys; Farley, Vincent; Savary, Simon; Chamberland, Martin

    2013-05-01

    High resolution broad-band imagery in the 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, which leads to an additional means of detecting and identifying 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, which yields high spectral resolution and enables a 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 integrated and flown on a novel airborne gyro-stabilized platform inside a fixed-wing aircraft. The new platform, more compact and more advanced than its predecessor, is described in this paper. The first results of target detection and identification are also presented.

  9. 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.

  10. 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.

  11. Two-dimensional focal plane detector arrays for LWIR/VLWIR space and airborne sounding missions

    NASA Astrophysics Data System (ADS)

    Hanna, S.; Bauer, A.; Bitterlich, H.; Bruder, M.; Haas, L.-D.; Haiml, M.; Hofmann, K.; Mahlein, K.-M.; Nothaft, H.-P.; Schallenberg, T.; Weber, A.; Wendler, J.; Wollrab, R.; Ziegler, J.

    2010-10-01

    An increasing need for high-precision atmospheric data especially in the long wavelength infrared (LWIR) and very long wavelength infrared (VLWIR) spectral ranges has arisen in the past years not only for the analysis of climate change and its effect on the earth's ecosystem, but also for weather forecast and atmospheric monitoring purposes. Spatially and spectrally resolved atmospheric emission data are advantageously gathered through limb or nadir sounding using an imaging Fourier transform (FT) interferometer with a two-dimensional (2D) high-speed focal plane detector array (FPA). In this paper, AIM reports on its latest results on MCT VLWIR FPAs for Fourier transform infrared sounding applications in the 8-15μm spectral range. The performance of a (112x112) pixel photodiode array with a 40μm pixel pitch incorporating extrinsic p-doping for low dark current, a technique for linearity improvement at high photon fluxes, pixel guards, pixel select/de-select, and a (2x2) super-pixel architecture is discussed. The customized read-out integrated circuit (ROIC) supporting integrate while-read (IWR) operation has a buffered direct injection (BDI) input stage and a full well capacity (FWC) of 143 Megaelectrons per super-pixel. It consists of two independently operating halves with two analog video outputs each. The full frame rate is typically 4k frames/sec, making it suitable for use with rapid scan FT infrared spectrometers. At a 55K operating temperature and an ~14.4μm cut-off wavelength, a photo response of 12.1mV/K and a noise equivalent temperature difference of 24.8mK at half well filling are demonstrated for a 286K reference scene. The nonlinearity error is <0.5%.

  12. 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

  13. 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.

  14. 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...

  15. 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...

  16. 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...

  17. 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

  18. 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.

  19. 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.

  20. [Research on airborne hyperspectral identification of red tide organism dominant species based on SVM].

    PubMed

    Ma, Yi; Zhang, Jie; Cui, Ting-wei

    2006-12-01

    Airborne hyperspectral identification of red tide organism dominant species can provide technique for distinguishing red tide and its toxin, and provide support for scaling the disaster. Based on support vector machine(SVM), the present paper provides an identification model of red tide dominant species. Utilizing this model, the authors accomplished three identification experiments with the hyperspectral data obtained on 16th July, and 19th and 25th August, 2001. It is shown from the identification results that the model has a high precision and is not restricted by high dimension of the hyperspectral data.

  1. 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.

  2. 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...

  3. 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 ...

  4. 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.

  5. 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.

  6. 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.

  7. Airborne measurements in the infrared using FTIR-based imaging hyperspectral sensors

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

    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. Push-broom dispersive sensors have been typically used for airborne hyperspectral mapping. However, extending the spectral range towards the mid-wave and long-wave infrared brings performance limitations due to the self emission of the sensor itself. The Fourier-transform spectrometer technology has been extensively used in the infrared spectral range due to its high transmittance as well as throughput and multiplex advantages, thereby reducing the sensor self-emission problem. Telops has developed the Hyper-Cam, a rugged and compact infrared hyperspectral imager. The Hyper-Cam is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides passive signature measurement capability, with up to 320x256 pixels at spectral resolutions of up to 0.25 cm-1. The Hyper-Cam 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. A special pointing module was designed to compensate for airplane attitude and forward motion. To our knowledge, the Hyper-Cam is the first commercial airborne hyperspectral imaging sensor based on Fourier-transform infrared technology. The first airborne measurements and some preliminary performance criteria for the Hyper-Cam are presented in

  8. Airborne measurements in the infrared using FTIR-based imaging hyperspectral sensors

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

    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. Push-broom dispersive sensors have been typically used for airborne hyperspectral mapping. However, extending the spectral range towards the mid-wave and long-wave infrared brings performance limitations due to the self emission of the sensor itself. The Fourier-transform spectrometer technology has been extensively used in the infrared spectral range due to its high transmittance as well as throughput and multiplex advantages, thereby reducing the sensor self-emission problem. Telops has developed the Hyper-Cam, a rugged and compact infrared hyperspectral imager. The Hyper-Cam is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides passive signature measurement capability, with up to 320x256 pixels at spectral resolutions of up to 0.25 cm-1. The Hyper-Cam 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. A special pointing module was designed to compensate for airplane attitude and forward motion. To our knowledge, the Hyper-Cam is the first commercial airborne hyperspectral imaging sensor based on Fourier-transform infrared technology. The first airborne measurements and some preliminary performance criteria for the Hyper-Cam are presented in

  9. 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.

  10. 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.

  11. Solid target spectral variability in LWIR

    NASA Astrophysics Data System (ADS)

    Rosario, Dalton; Borel, Christoph; Romano, Joao

    2016-05-01

    We continue to highlight the pattern recognition challenges associated with solid target spectral variability in the longwave infrared (LWIR) region of the electromagnetic spectrum for a persistent imaging experiment. The experiment focused on the collection and exploitation of LWIR hyperspectral imagery. We propose two methods for target detection, one based on the repeated-random-sampling trial adaptation to a single-class version of support vector machine, and the other based on a longitudinal data model. The defining characteristic of a longitudinal study is that objects are measured repeatedly through time and, as a result, data are dependent. This is in contrast to cross-sectional studies in which the outcomes of a specific event are observed by randomly sampling from a large population of relevant objects in which data are assumed independent. Researchers in the remote sensing community generally assume the problem of object recognition to be cross-sectional. Performance contrast is quantified using a LWIR hyperspectral dataset acquired during three consecutive diurnal cycles, and results reinforce the need for using data models that are more realistic to LWIR spectral data.

  12. Object-oriented and pixel-based classification approach for land cover using airborne long-wave infrared hyperspectral data

    NASA Astrophysics Data System (ADS)

    Marwaha, Richa; Kumar, Anil; Kumar, Arumugam Senthil

    2015-01-01

    Our primary objective was to explore a classification algorithm for thermal hyperspectral data. Minimum noise fraction is applied to thermal hyperspectral data and eight pixel-based classifiers, i.e., constrained energy minimization, matched filter, spectral angle mapper (SAM), adaptive coherence estimator, orthogonal subspace projection, mixture-tuned matched filter, target-constrained interference-minimized filter, and mixture-tuned target-constrained interference minimized filter are tested. The long-wave infrared (LWIR) has not yet been exploited for classification purposes. The LWIR data contain emissivity and temperature information about an object. A highest overall accuracy of 90.99% was obtained using the SAM algorithm for the combination of thermal data with a colored digital photograph. Similarly, an object-oriented approach is applied to thermal data. The image is segmented into meaningful objects based on properties such as geometry, length, etc., which are grouped into pixels using a watershed algorithm and an applied supervised classification algorithm, i.e., support vector machine (SVM). The best algorithm in the pixel-based category is the SAM technique. SVM is useful for thermal data, providing a high accuracy of 80.00% at a scale value of 83 and a merge value of 90, whereas for the combination of thermal data with a colored digital photograph, SVM gives the highest accuracy of 85.71% at a scale value of 82 and a merge value of 90.

  13. 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).

  14. 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.

  15. 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

  16. Biodiversity Mapping in a Tropical West African Forest with Airborne Hyperspectral Data

    PubMed Central

    Vaglio Laurin, Gaia; Chan, Jonathan Cheung-Wai; Chen, Qi; Lindsell, Jeremy A.; Coomes, David A.; Guerriero, Leila; Frate, Fabio Del; Miglietta, Franco; Valentini, Riccardo

    2014-01-01

    Tropical forests are major repositories of biodiversity, but are fast disappearing as land is converted to agriculture. Decision-makers need to know which of the remaining forests to prioritize for conservation, but the only spatial information on forest biodiversity has, until recently, come from a sparse network of ground-based plots. Here we explore whether airborne hyperspectral imagery can be used to predict the alpha diversity of upper canopy trees in a West African forest. The abundance of tree species were collected from 64 plots (each 1250 m2 in size) within a Sierra Leonean national park, and Shannon-Wiener biodiversity indices were calculated. An airborne spectrometer measured reflectances of 186 bands in the visible and near-infrared spectral range at 1 m2 resolution. The standard deviations of these reflectance values and their first-order derivatives were calculated for each plot from the c. 1250 pixels of hyperspectral information within them. Shannon-Wiener indices were then predicted from these plot-based reflectance statistics using a machine-learning algorithm (Random Forest). The regression model fitted the data well (pseudo-R2 = 84.9%), and we show that standard deviations of green-band reflectances and infra-red region derivatives had the strongest explanatory powers. Our work shows that airborne hyperspectral sensing can be very effective at mapping canopy tree diversity, because its high spatial resolution allows within-plot heterogeneity in reflectance to be characterized, making it an effective tool for monitoring forest biodiversity over large geographic scales. PMID:24937407

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. [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.

  4. [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

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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. ...

  10. 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.

  11. Radiometric calibration of multiple Earth observation sensors using airborne hyperspectral data at the Newell County rangeland test site

    NASA Astrophysics Data System (ADS)

    Teillet, Phil M.; Fedosejevs, Gunar; Gauthier, Robert P.; Shin, Raymond T.; O'Neill, Norman T.; Thome, Kurtis J.; Biggar, Stuart F.; Ripley, Herb T.; Meygret, Aime

    1999-09-01

    A single data set of spatially extensive hyperspectral imagery is used to carry out vicarious calibrations for multiple Earth observation sensors. Results are presented based on a data acquisition campaign at the newell County rangeland test site in Alberta in October 1998, which included ground-based measurements, satellite imagery, and airborne casi hyperspectral data. This paper present new calibration monitoring obtained for NOAA-14 AVHRR, OrbView-2 SeaWiFS, SPOT-4 VGT, Landsat-5 TM, and SPOT-2 HRV.

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. Remote estimation of canopy nitrogen content in winter wheat using airborne hyperspectral reflectance measurements

    NASA Astrophysics Data System (ADS)

    Zhou, Xianfeng; Huang, Wenjiang; Kong, Weiping; Ye, Huichun; Luo, Juhua; Chen, Pengfei

    2016-11-01

    Timely and accurate assessment of canopy nitrogen content (CNC) provides valuable insight into rapid and real-time nitrogen status monitoring in crops. A semi-empirical approach based on spectral index was extensively used for nitrogen content estimation. However, in many cases, due to specific vegetation types or local conditions, the applicability and robustness of established spectral indices for nitrogen retrieval were limited. The objective of this study was to investigate the optimal spectral index for winter wheat (Triticum aestivum L.) CNC estimation using Pushbroom Hyperspectral Imager (PHI) airborne hyperspectral data. Data collected from two different field experiments that were conducted during the major growth stages of winter wheat in 2002 and 2003 were used. Our results showed that a significant linear relationship existed between nitrogen and chlorophyll content at the canopy level, and it was not affected by cultivars, growing conditions and nutritional status of winter wheat. Nevertheless, it varied with growth stages. Periods around heading stage mainly worsened the relationship and CNC estimation, and CNC assessment for growth stages before and after heading could improve CNC retrieval accuracy to some extent. CNC assessment with PHI airborne hyperspectra suggested that spectral indices based on red-edge band including narrowband and broadband CIred-edge, NDVI-like and ND705 showed convincing results in CNC retrieval. NDVI-like and ND705 were sensitive to detect CNC changes less than 5 g/m2, narrowband and broadband CIred-edge were sensitive to a wide range of CNC variations. Further evaluation of CNC retrieval using field measured hyperspectra indicated that NDVI-like was robust and exhibited the highest accuracy in CNC assessment, and spectral indices (CIred-edge and CIgreen) that established on narrow or broad bands showed no obvious difference in CNC assessment. Overall, our study suggested that NDVI-like was the optimal indicator for winter

  17. 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

  18. Land cover mapping in Latvia using hyperspectral airborne and simulated Sentinel-2 data

    NASA Astrophysics Data System (ADS)

    Jakovels, Dainis; Filipovs, Jevgenijs; Brauns, Agris; Taskovs, Juris; Erins, Gatis

    2016-08-01

    Land cover mapping in Latvia is performed as part of the Corine Land Cover (CLC) initiative every six years. The advantage of CLC is the creation of a standardized nomenclature and mapping protocol comparable across all European countries, thereby making it a valuable information source at the European level. However, low spatial resolution and accuracy, infrequent updates and expensive manual production has limited its use at the national level. As of now, there is no remote sensing based high resolution land cover and land use services designed specifically for Latvia which would account for the country's natural and land use specifics and end-user interests. The European Space Agency launched the Sentinel-2 satellite in 2015 aiming to provide continuity of free high resolution multispectral satellite data thereby presenting an opportunity to develop and adapted land cover and land use algorithm which accounts for national enduser needs. In this study, land cover mapping scheme according to national end-user needs was developed and tested in two pilot territories (Cesis and Burtnieki). Hyperspectral airborne data covering spectral range 400-2500 nm was acquired in summer 2015 using Airborne Surveillance and Environmental Monitoring System (ARSENAL). The gathered data was tested for land cover classification of seven general classes (urban/artificial, bare, forest, shrubland, agricultural/grassland, wetlands, water) and sub-classes specific for Latvia as well as simulation of Sentinel-2 satellite data. Hyperspectral data sets consist of 122 spectral bands in visible to near infrared spectral range (356-950 nm) and 100 bands in short wave infrared (950-2500 nm). Classification of land cover was tested separately for each sensor data and fused cross-sensor data. The best overall classification accuracy 84.2% and satisfactory classification accuracy (more than 80%) for 9 of 13 classes was obtained using Support Vector Machine (SVM) classifier with 109 band

  19. A Bayesian approach to identification of gaseous effluents in passive LWIR imagery

    NASA Astrophysics Data System (ADS)

    Higbee, Shawn

    Typically a regression approach is applied in order to identify the gaseous constituents present in a hyperspectral image, and the task of species identification amounts to choosing the best regression model. Common model selection approaches (stepwise and criterion based methods) have well known multiple comparisons problems, and they do not allow the user to control the experiment-wise error rate, or allow the user to include scene-specific knowledge in the inference process. A Bayesian model selection technique called Gibbs Variable Selection (GVS) that better handles these issues is presented and implemented via Markov chain monte carlo (MCMC). GVS can be used to simultaneously conduct inference on the optical path depth and probability of inclusion in a pixel for a each species in a library. This method flexibly accommodates an analyst's prior knowledge of the species present in a scene, as well as mixtures of species of any arbitrary complexity. A modified version of GVS with fast convergence properties that is tailored to unsupervised use in hyperspectral image analysis will be presented. Additionally a series of automated diagnostic measures have been developed to monitor convergence of the MCMC with minimal operator intervention. Finally, the applicability of aggregating inference from adjacent pixels will be discussed. This method is compared against stepwise regression for model selection and results from LWIR data from the Airborne Hyperspectral Imager (AHI) are presented. Finally, the applicability of this method to operational scenarios and various sensors will be discussed.

  20. Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data.

    PubMed

    Moses, Wesley J; Gitelson, Anatoly A; Perk, Richard L; Gurlin, Daniela; Rundquist, Donald C; Leavitt, Bryan C; Barrow, Tadd M; Brakhage, Paul

    2012-03-15

    Algorithms based on red and near infra-red (NIR) reflectances measured using field spectrometers have been previously shown to yield accurate estimates of chlorophyll-a concentration in turbid productive waters, irrespective of variations in the bio-optical characteristics of water. The objective of this study was to investigate the performance of NIR-red models when applied to multi-temporal airborne reflectance data acquired by the hyperspectral sensor, Airborne Imaging Spectrometer for Applications (AISA), with non-uniform atmospheric effects across the dates of data acquisition. The results demonstrated the capability of the NIR-red models to capture the spatial distribution of chlorophyll-a in surface waters without the need for atmospheric correction. However, the variable atmospheric effects did affect the accuracy of chlorophyll-a retrieval. Two atmospheric correction procedures, namely, Fast Line-of-sight Atmospheric Adjustment of Spectral Hypercubes (FLAASH) and QUick Atmospheric Correction (QUAC), were applied to AISA data and their results were compared. QUAC produced a robust atmospheric correction, which led to NIR-red algorithms that were able to accurately estimate chlorophyll-a concentration, with a root mean square error of 5.54 mg m(-3) for chlorophyll-a concentrations in the range 2.27-81.17 mg m(-3). PMID:22209281

  1. Overview of hyperspectral remote sensing for mapping marine benthic habitats from airborne and underwater sensors

    NASA Astrophysics Data System (ADS)

    Dierssen, Heidi M.

    2013-09-01

    The seafloor, with its diverse and dynamic benthic habitats varying on meter to centimeter scales, is difficult to accurately monitor with traditional techniques. The technology used to build imaging spectrometers has rapidly advanced in recent years with the advent of smaller sensors and better signal-to-noise capabilities that has facilitated their use in mapping fine-scale benthic features. Here, the use of such sensors for hyperspectral remote sensing of the seafloor from both airborne and underwater platforms is discussed. Benthic constituents provide a so-called optical fingerprint with spectral properties that are often too subtle to be discerned with simple color photographs or multichannel spectrometers. Applications include the recent field validation of the airborne Portable Remote Imaging SpectroMeter (PRISM), a new imaging sensor package optimized for coastal ocean processes in Elkorn Slough California. In these turbid sediment-laden waters, only subtle spectral differences differentiate seafloor with sediment from that with eelgrass. The ultimate goal is to provide robust radiometric approaches that accurately consider light attenuation by the water column and are able to be applied to diverse habitats without considerable foreknowledge.

  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. 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.

  4. 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.

  5. 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.

  6. SYSIPHE system: a state of the art airborne hyperspectral imaging system: initial results from the first airborne campaign

    NASA Astrophysics Data System (ADS)

    Rousset-Rouviere, Laurent; Coudrain, Christophe; Fabre, Sophie; Poutier, Laurent; Løke, Trond; Fridman, Andrei; Blaaberg, Søren; Baarstad, Ivar; Skauli, Torbjorn; Mocoeur, Isabelle

    2014-10-01

    SYSIPHE is an airborne hyperspectral imaging system, result of a cooperation between France (Onera and DGA) and Norway (NEO and FFI). It is a unique system by its spatial sampling -0.5m with a 500m swath at a ground height of 2000m- combined with its wide spectral coverage -from 0.4μm to 11.5μm in the atmospheric transmission bands. Its infrared component, named SIELETERS, consists in two high étendue imaging static Fourier transform spectrometers, one for the midwave infrared and one for the longwave infrared. These two imaging spectrometers are closely similar in design, since both are made of a Michelson interferometer, a refractive imaging system, and a large IRFPA (1016x440 pixels). Moreover, both are cryogenically cooled and mounted on their own stabilization platform which allows the line of sight to be controlled and recorded. These data are useful to reconstruct and to georeference the spectral image from the raw interferometric images. The visible and shortwave infrared component, named Hyspex ODIN-1024, consists of two spectrographs for VNIR and SWIR based on transmissive gratings. These share a common fore-optics and a common slit, to ensure perfect registration between the VNIR and the SWIR images. The spectral resolution varies from 5nm in the visible to 6nm in the shortwave infrared. In addition, the STAD, the post processing and archiving system, is developed to provide spectral reflectance and temperature products (SRT products) from calibrated georeferenced and inter-band registered spectral images at the sensor level acquired and pre-processed by SIELETERS and Hyspex ODIN-1024 systems.

  7. 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.; 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.

  8. 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

  9. Sunglint effects on the characterization of optically active substances in high spatial resolution airborne hyperspectral images

    NASA Astrophysics Data System (ADS)

    Streher, A. S.; Faria Barbosa, C. Clemente; Soares Galvão, L.; Goodman, J. A.; Silva, T. S.

    2013-05-01

    Sunglint, also known as the specular reflection of light from water surfaces, is a component of sensor-received radiance that represents a confounding factor on the characterization of water bodies by remote sensing. In airborne remote sensing images, the effect of sunglint can be minimized by optimizing the flight paths, directing the sensor towards or away from the Sun, and by keeping solar zenith angles between 30° and 60°. However, these guidelines cannot always be applied, often due to the irregular spatial pattern of lakes, estuaries and coastlines. The present study assessed the impact of sunglint on the relationship between the optically active substances (OAS) concentration, in optically complex waters, and the spectral information provided by an airborne high spatial resolution hyperspectral sensor (SpecTIR). The Ibitinga reservoir, located in southeastern Brazil (state of São Paulo), was selected as the study area because of its meandering shape. As a result, there is demanding constant changes in data acquisition geometry to achieve complete coverage, therefore not allowing sunglint conditions to be minimized during image acquisition. Field data collection was carried out on October 23 and 24, 2011. During these two days, 15 water stations along the reservoir were sampled, concurrently with the SpecTIR image acquisition in 357 bands (398-2455 nm) and at 3 m spatial resolution. Chlorophyll, pheophytin, total suspended solids, organic and inorganic suspended solids and colored dissolved matter were determined in laboratory. The images were corrected for the atmospheric effects using the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm and then geometrically corrected. In order to evaluate the sunglint effects on the OAS characterization, the images were corrected for such effects using the deglint algorithm from Goodman et al. (2008). The SpecTIR 662-nm band reflectance was selected to be correlated to the OAS due to

  10. 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

  11. Airborne LiDAR and hyperspectral mapping of snow depth and albedo in the Upper Colorado River Basin, Colorado, USA by the NASA JPL Airborne Snow Observatory

    NASA Astrophysics Data System (ADS)

    Deems, J. S.; Painter, T. H.

    2014-12-01

    Operational hydrologic simulation and forecasting in snowmelt-dominated watersheds currently relies on indices of snow accumulation and melt from measurements at a small number of point locations or geographically-limited manual surveys. These data sources cannot adequately characterize the spatial distribution of snow depth/water equivalent, which is the primary determinant of snowpack volume and runoff rates. The NASA JPL Airborne Snow Observatory's airborne laser scanning system maps snow depth at high spatial and temporal resolutions, and is paired with a hyperspectral imager to provide an unprecedented snowpack monitoring capability and enabling a new operational paradigm. We present the initial results from this new application of multi-temporal LiDAR and hyperspectral mapping. During the snowmelt seasons of 2013 and 2014, the ASO mapped snow depth and albedo in the Uncompahgre River Basin in Colorado's Upper Colorado River Basin on a nominally monthly basis. These products enable an assessment and comparison of spatial snow accumulation and melt processes in two years with very different snowmelt hydrographs.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. [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

  17. Assessment of chlorophyll-a concentration in the Gulf of Riga using hyperspectral airborne and simulated Sentinel-3 OLCI data

    NASA Astrophysics Data System (ADS)

    Jakovels, Dainis; Brauns, Agris; Filipovs, Jevgenijs; Taskovs, Juris; Fedorovicha, Dagnija; Paavel, Birgot; Ligi, Martin; Kutser, Tiit

    2016-08-01

    Remote sensing has proved to be an accurate and reliable tool in clear water environments like oceans or the Mediterranean Sea. However, the current algorithms and methods usually fail on optically complex waters like coastal and inland waters. The whole Baltic Sea can be considered as optically complex coastal waters. Remote assessment of water quality parameters (eg., chlorophyll-a concentration) is of interest for monitoring of marine environment, but hasn't been used as a routine approach in Latvia. In this study, two simultaneous hyperspectral airborne data and in situ measurement campaigns were performed in the Gulf of Riga near the River Daugava mouth in summer 2015 to simulate Sentinel-3 data and test existing algorithms for retrieval of Level 2 Water products. Comparison of historical data showed poor overall correlation between in situ measurements and MERIS chlorophyll-a data products. Better correlation between spectral chl-a data products and in situ water sampling measurements was achieved during simultaneous airborne and field campaign resulting in R2 up to 0.94 for field spectral data, R2 of 0.78 for airborne data. Test of all two band ratio combinations showed that R2 could be improved from 0.63 to 0.94 for hyperspectral airborne data choosing 712 and 728 nm bands instead of 709 and 666 nm, and R2 could be improved from 0.61 to 0.83 for simulated Sentinel-3 OLCI data choosing Oa10 and Oa8 bands instead of Oa11 and Oa8. Repeated campaigns are planned during spring and summer blooms 2016 in the Gulf of Riga to get larger data set for validation and evaluate repeatability. The main challenges remain to acquire as good data as possible within rapidly changing environment and often cloudy weather conditions.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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

  8. 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...

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Validation of Satellite Ammonia Retrievals using Airborne Hyperspectral Thermal-Infrared Spectrometry

    NASA Astrophysics Data System (ADS)

    Tratt, D. M.; Hall, J. L.; Chang, C. S.; Qian, J.; Clarisse, L.; Van Damme, M.; Clerbaux, C.; Hurtmans, D.; Coheur, P.

    2011-12-01

    We demonstrate the utility of a new airborne sensor with the requisite spatial, spectral, and radiometric resolution to characterize "point" sources of ammonia emission. Flights were conducted over California's San Joaquin Valley, which is a region of intensive agriculture and animal husbandry that has been identified as one of the single largest sources of atmospheric free ammonia worldwide. Airborne data acquisition operations were coordinated with daytime overpasses of the Infrared Atmospheric Sounding Interferometer (IASI) aboard the European Space Agency's MetOp-A platform. IASI is capable of measuring total columns of ammonia and the primary purpose of this investigation was to compare and validate the IASI ammonia product against high-spatial-resolution airborne retrievals acquired contemporaneously over the same footprint. The ~12-km pixel size of the IASI satellite measurements cannot resolve the local-scale variability of ammonia abundance and consequently cannot characterize the often compact source emissions. The nominal 2-m pixel size of the airborne data revealed variability of ammonia concentration at several different scales within the IASI footprint. At this pixel size, well-defined plumes issuing from individual dairy facilities could be imaged and their dispersion characteristics resolved. Retrieved ammonia concentrations in excess of 50 ppb were inferred for some of the strongest discrete plumes.

  14. 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.

  15. 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.

  16. The use of airborne hyperspectral data for tree species classification in a species-rich Central European forest area

    NASA Astrophysics Data System (ADS)

    Richter, Ronny; Reu, Björn; Wirth, Christian; Doktor, Daniel; Vohland, Michael

    2016-10-01

    The success of remote sensing approaches to assess tree species diversity in a heterogeneously mixed forest stand depends on the availability of both appropriate data and suitable classification algorithms. To separate the high number of in total ten broadleaf tree species in a small structured floodplain forest, the Leipzig Riverside Forest, we introduce a majority based classification approach for Discriminant Analysis based on Partial Least Squares (PLS-DA), which was tested against Random Forest (RF) and Support Vector Machines (SVM). The classifier performance was tested on different sets of airborne hyperspectral image data (AISA DUAL) that were acquired on single dates in August and September and also stacked to a composite product. Shadowed gaps and shadowed crown parts were eliminated via spectral mixture analysis (SMA) prior to the pixel-based classification. Training and validation sets were defined spectrally with the conditioned Latin hypercube method as a stratified random sampling procedure. In the validation, PLS-DA consistently outperformed the RF and SVM approaches on all datasets. The additional use of spectral variable selection (CARS, "competitive adaptive reweighted sampling") combined with PLS-DA further improved classification accuracies. Up to 78.4% overall accuracy was achieved for the stacked dataset. The image recorded in August provided slightly higher accuracies than the September image, regardless of the applied classifier.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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...

  2. 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.

  3. 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

  4. 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

  5. Semi-Blind Source Separation for Estimation of Clay Content Over Semi-Vegetated Areas, from Vnir/swir Hyperspectral Airborne Data

    NASA Astrophysics Data System (ADS)

    Ouerghemmi, W.; Gomez, C.; Nacer, S.; Lagacherie, P.

    2015-08-01

    The applicability of Visible, Near-Infrared and Short Wave Infrared (VNIR/SWIR) hyperspectral imagery for soil property mapping decreases when surfaces are partially covered by vegetation. The objective of this research was to develop and evaluate a methodology based on the "double-extraction" technique, for clay content estimation over semi-vegetated surfaces using VNIR/SWIR hyperspectral airborne data. The "double-extraction" technique initially proposed by Ouerghemmi et al. (2011) consists of 1) an extraction of a soil reflectance spectrum ssoil from semi-vegetated spectra using a Blind Source Separation technique, and 2) an extraction of clay content from the soil reflectance spectrum ssoil, using a multivariate regression method. In this paper, the Source Separation approach is Semi-Blind thanks to the integration of field knowledge in Source Separation model. And the multivariate regression method is a partial least squares regression (PLSR) model. This study employed VNIR/SWIR HyMap airborne data acquired in a French Mediterranean region over an area of 24 km2. Our results showed that our methodology based on the "double-extraction" technique is accurate for clay content estimation when applied to pixels under a specific Cellulose Absorption Index threshold. Finally the clay content can be estimated over around 70% of the semi-vegetated pixels of our study area, which may offer an extension of soil properties mapping, at the moment restricted to bare soils.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Evaluation of the spatial distribution, in percent coverage of the oil spilled during the Trecate blow-out, based on the analysis of airborne hyperspectral MIVIS data

    SciTech Connect

    Bianchi, R.; Cavalli, R.M.; Marino, C.M.

    1996-07-01

    On February 1994 a large area close to the Trecate town has been interested by an oil blow-out from an AGIP rig located within the Ticino Regional Park. One month later an airborne survey has been carried out in the framework of the CNR Lara Project, by utilizing the Daedalus AA5000 MIVIS spectrometer with 102 channels from Visible to Thermal Infrared. Different authors stress, for oil slicks discrimination, the utility of laser and microwaves based techniques, but the high spatial and spectral MIVIS resolutions can improve the detection of the relative coverage by spilled oil. This task has been performed by applying hyperspectral unmixing methods to the MIVIS calibrated data, obtaining an oil fractional image with respect to other chosen end-members. The analysis has shown a good agreement between the results of the unconstrained unmixing technique applied to MIVIS data and the ground truths, offering a tool useful to quantify in a synoptic overview the effects of oil spills over land, by relating the ppm of oil with the oil hyperspectral information gathered by MIVIS.

  12. 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.

  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. 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

  15. 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.

  16. 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

  17. Thermal Infrared Airborne Hyperspectral Detection of Fumarolic Ammonia Venting on the Calipatria Fault in the Salton Sea Geothermal Field, Imperial County, California

    NASA Astrophysics Data System (ADS)

    Lynch, D. K.; Tratt, D. M.; Buckland, K. N.; Hall, J. L.; Kasper, B. P.; Martino, M. G.; Ortega, L. J.; Westberg, K. R.; Young, S. J.; Johnson, P. D.

    2009-12-01

    An airborne hyperspectral imaging survey was conducted along the Calipatria Fault in the vicinity of the Salton Sea in Southern California. In addition to strong thermal hotspots associated with active fumaroles along the fault, a number of discrete and distributed sources of ammonia were detected. Mullet Island, some recently exposed areas of sea floor, and a shallow-water fumarolic geothermal vent all indicated ammonia emissions, presumed to originate from the eutrophic reduction of nitrate fertilizer in agricultural runoff and the decay (oxidation) of organic matter, probably algae. All emission sources detected lay along the putative Calipatria Fault, one of a number of en echelon faults in the Brawley Seismic Zone that is part of the northern-most spreading center of the East Pacific Rise. The techniques developed during this field experiment suggest a potential methodology for monitoring certain of the toxic episodes that are a known source of mass aquatic fauna kills within the Salton Sea ecosystem. The imagery was acquired at ~0.05 micron spectral resolution across the 7.6-13.5 micron thermal-infrared spectral region with a ground sample distance of approximately 1 m using the SEBASS (Spatially Enhanced Broadband Array Spectrograph System) sensor.

  18. Hyperspectral imagery and segmentation

    NASA Astrophysics Data System (ADS)

    Wellman, Mark C.; Nasrabadi, Nasser M.

    2002-07-01

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

  19. 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.

  20. 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

  1. Use of airborne hyperspectral imagery to investigate the influence of soil nitrogen supplies and variable-rate fertilization to winter wheat growth

    NASA Astrophysics Data System (ADS)

    Song, Xiaoyu; Yan, Guangjian; Wang, Jihua; Liu, Liangyun; Xue, Xuzhang; Li, Cunjun; Huang, Wenjiang

    2007-10-01

    Advanced technology in airborne detection of crop growth can help optimize the strategies of fertilization, and help maximize the grain output by adjusting field inputs. In this study, Push-broom Hyperspectral Image sensor (PHI) was used to investigate the influence of soil nitrogen supplied and variable-rate fertilization to the growth of winter wheat. The objective was to determine to what extent the reflectance obtained in the 80 visible and near-infrared (NIR) wavebands (from 410nm to 832nm) might be related to differences of variance of soil nitrogen and variable-rate fertilization. Management plots were arranged at Beijing Precision Farming Experimental Station. Three flights were made during the wheat growing season. Several field experiments, including the crop sampling, soil sampling and variable-rate fertilization were carried out in the field. Data were analyzed for each flight and each band separately. Some spectrum indices were derived from PHI images and statistical correlation analysis were carried out among the spectrum indices and soil nitrogen, variable-rate fertilization amount. In addition, the spectrum indices difference between elongation stage and grain filling stage are calculated and the correlation analysis was also carried out. The analysis results indicated that the reflectance of winter wheat is significantly influenced at certain wavelength by the soil nitrogen and the variable-rate fertilization. The soil nitrogen effect was detectable in all the three flights. Differences in response due to soil nitrogen variance were most evident at spectrum indices, such as dλ red, INFLEX, Green/Red, NIRness, DVI and RDVI. Furthermore, analysis results also indicated that the variable fertilization can reduce the growth difference of winter wheat caused by spatial distribution difference of soil nitrogen.

  2. 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.

  3. A unique, accurate LWIR optics measurement system

    NASA Astrophysics Data System (ADS)

    Fantone, Stephen D.; Orband, Daniel G.

    2011-05-01

    A compact low-cost LWIR test station has been developed that provides real time MTF testing of IR optical systems and EO imaging systems. The test station is intended to be operated by a technician and can be used to measure the focal length, blur spot size, distortion, and other metrics of system performance. The challenges and tradeoffs incorporated into this instrumentation will be presented. The test station performs the measurement of an IR lens or optical system's first order quantities (focal length, back focal length) including on and off-axis imaging performance (e.g., MTF, resolution, spot size) under actual test conditions to enable the simulation of their actual use. Also described is the method of attaining the needed accuracies so that derived calculations like focal length (EFL = image shift/tan(theta)) can be performed to the requisite accuracy. The station incorporates a patented video capture technology and measures MTF and blur characteristics using newly available lowcost LWIR cameras. This allows real time determination of the optical system performance enabling faster measurements, higher throughput and lower cost results than scanning systems. Multiple spectral filters are also accommodated within the test stations which facilitate performance evaluation under various spectral conditions.

  4. Performance and application of real-time hyperspectral imaging

    NASA Astrophysics Data System (ADS)

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

    1998-10-01

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

  5. 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

  6. 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.

  7. 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.

  8. 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...

  9. 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.

  10. Spacecraft Line-of-Sight Stabilization Using LWIR Earth Signature

    NASA Technical Reports Server (NTRS)

    Quadrelli, Marco B.; Piazzolla, Sabino

    2012-01-01

    The objective of this study is to investigate the potential of using the bright and near-uniform Earth infrared (or wavelength infrared, LWIR) signature as a stable reference for accurate (micro-rad or less) inertial pointing and tracking on-board an space vehicle, including the determination of the fundamental limits of applicability of the proposed method for space missions. We demonstrate sub-micro radian level pointing accuracy under a representative set of disturbances experienced by the spacecraft in orbit.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. Analysis for signal-to-noise ratio of hyper-spectral imaging FTIR interferometer

    NASA Astrophysics Data System (ADS)

    Li, Xun-niu; Zheng, Wei-jian; Lei, Zheng-gang; Wang, Hai-yang; Fu, Yan-peng

    2013-08-01

    Signal-to-noise Ratio of hyper-spectral imaging FTIR interferometer system plays a decisive role on the performance of the instrument. It is necessary to analyze them in the development process. Based on the simplified target/background model, the energy transfer model of the LWIR hyper-spectral imaging interferometer has been discussed. The noise equivalent spectral radiance (NESR) and its influencing factors of the interferometer system was analyzed, and the signal-to-noise(SNR) was calculated by using the properties of NESR and incident radiance. In a typical application environment, using standard atmospheric model of USA(1976 COESA) as a background, and set a reasonable target/background temperature difference, and take Michelson spatial modulation Fourier Transform interferometer as an example, the paper had calculated the NESR and the SNR of the interferometer system which using the commercially LWIR cooled FPA and UFPA detector. The system noise sources of the instrument were also analyzed in the paper. The results of those analyses can be used to optimize and pre-estimate the performance of the interferometer system, and analysis the applicable conditions of use different detectors. It has important guiding significance for the LWIR interferometer spectrometer design.

  17. 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...

  18. 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...

  19. Modelling the Spatial Distribution of CO2 Fluxes in a Subalpine Grassland Plateau of the Italian Alps Using Multiple Airborne AISA Eagle Hyperspectral Sensor Observations and Sentinel-2 Simulated Data.

    NASA Astrophysics Data System (ADS)

    Sakowska, K.; Vescovo, L.; Gianelle, D.; Rossini, M.; Alberti, G.; Dalponte, M.; Fava, F.; Gioli, B.; Julitta, T.; Meggio, F.; Pitacco, A.; Mac Arthur, A.

    2015-12-01

    ESA's satellite Sentinel-2 provides images of high spatial, spectral and temporal resolution, providing a high potential for biophysical parameter characteristics monitoring and for products validation at the Eddy Covariance (EC) towers. A set of 13 spectral bands is available ranging from the visible and NIR to SWIR, featuring four bands at 10 m, six bands at 20 m and three bands at 60 m spatial resolution. Depending on the presence of clouds, satellite data will be available every 10-15 days. In comparison to the last sensors, Sentinel-2 incorporates three new spectral bands in the red-edge region which are particularly important for the retrieval and monitoring of biophysical parameter characteristics of dynamic ecosystems such as crops and grasslands. Under the umbrella of the COST Action ES0903, a hyperspectral flight campaign was organised at Viote del Monte Bondone (Trento, Italy) and five EC towers were installed on subalpine grasslands characterised by extreme variability of ecosystem structural parameters. The aim of the campaign was to compare the performance of different vegetation indices (simulating Sentinel-2 bands) in estimating NEE of these grassland ecosystems and to explore the structural and radiation controls on CO2 fluxes. The predictive capacity of partial least squares regression (PLSR) models using the full range of spectral data from different sites and from different airborne acquisitions was also assessed, and the appropriateness of the Sentinel-2 spatial resolution for ground-based flux upscaling was tested. The high structural heterogeneity of the investigated canopies resulted in high NEE fluxes spatial variability within the 5 investigated towers, indicating that, within the same grassland vegetation type, there is an evident control of structural traits on photosynthesis. Including PAR into the model resulted in a general increase in the performance of the linear regression. Also, the high predictive capacity of PLSR models

  20. Pupil imaging with a high sensitivity, LWIR focal plane array

    NASA Astrophysics Data System (ADS)

    LeVan, Paul D.; Hubbs, John E.; Pratt, Quinn T.

    2014-10-01

    We describe an integrated sensor assembly serving as both a component technology demonstration and a potential means of detecting distant point sources of infrared radiation. The objective of the demonstration was to show that usefully long integration times could be achieved with a low-background and well capacity, LWIR focal plane array optimized for use with cooled optics in space. The system controls extraneous background radiation with a small (150 μm) cooled pinhole that nevertheless transmits all the radiation of a point source collected by the fore-optic. Broad waveband response (~3 to 12 μm) results from optimization of the fore-optic for both MW and LWIR, as well as from a broadband anti-reflection coating on the field lens that is used at the pinhole to reimage the entrance aperture and its surrounding cold stop. Integration times in excess of 10 msec have been achieved for room temperature backgrounds with the FPA cold stage operated at 50 Kelvin, and noise performance has been bracketed with single frames of data collected over several integration times and over several minutes duration. However, anomalous signal behavior has been observed as the temperature of a remote blackbody increases. Although operation to date has been with a lower operability, engineering grade FPA, plans are to eventually upgrade to a higher quality device.

  1. 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.

  2. 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.

  3. 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

  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. Antenna-coupled unbiased detectors for LW-IR regime

    NASA Astrophysics Data System (ADS)

    Tiwari, Badri Nath

    At room temperature (300K), the electromagnetic (EM) radiation emitted by humans and other living beings peaks mostly in the long-wavelength infrared (LW-IR) regime. And since the atmosphere shows relatively little absorption in this band, applications such as target detection, tracking, active homing, and navigation in autonomous vehicles extensively use the LW-IR frequency range. The present research work is focused on developing antenna-based, uncooled, and unbiased detectors for the LW-IR regime. In the first part of this research, antenna-coupled metal-oxide-metal diodes (ACMOMD) are investigated. In response to the EM radiation, high-frequency antenna currents are induced in the antenna. An asymmetric-barrier Al-Al2O3-Pt MOM diode rectifies the antenna currents. Two different types of fabrication processes have been developed for ACMOMDs namely one-step lithography and two-step lithography. The major drawbacks of MOM-based devices include hard-to-control fabrication processes, generally very high zero-biased resistances, and vulnerability to electrostatic discharges, leading to unstable electrical characteristics. The second part of this research focuses on the development of unbiased LW-IR sensors based on the Seebeck effect. If two different metals are joined together at one end and their other ends are open-circuited, and if a non-zero temperature difference exists between the joined end and the open ends, then a non-zero open-circuit voltage can be measured between the open ends of the wires. Based on this effect, we have developed antenna-coupled nano-thermocouples (ACNTs) in which radiation-induced antenna currents produce polarization-dependent heating of the joined end of the two metals whereas the open ends remain at substrate temperature. This polarization-dependent heating induces polarization-dependent temperature difference between the joined end and the open ends of the metals leading to a polarization-dependent open-circuit voltage between the

  7. 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.

  8. 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.

  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. 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.

  13. 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.

  14. Temperature-emissivity separation for LWIR sensing using MCMC

    NASA Astrophysics Data System (ADS)

    Ash, Joshua N.; Meola, Joseph

    2016-05-01

    Signal processing for long-wave infrared (LWIR) sensing is made complicated by unknown surface temperatures in a scene which impact measured radiance through temperature-dependent black-body radiation of in-scene objects. The unknown radiation levels give rise to the temperature-emissivity separation (TES) problem describing the intrinsic ambiguity between an object's temperature and emissivity. In this paper we present a novel Bayesian TES algorithm that produces a probabilistic posterior estimate of a material's unknown temperature and emissivity. The statistical uncertainty characterization provided by the algorithm is important for subsequent signal processing tasks such as classification and sensor fusion. The algorithm is based on Markov chain Monte Carlo (MCMC) methods and exploits conditional linearity to achieve efficient block-wise Gibbs sampling for rapid inference. In contrast to existing work, the algorithm optimally incorporates prior knowledge about inscene materials via Bayesian priors which may optionally be learned using training data and a material database. Examples demonstrate up to an order of magnitude reduction in error compared to classical filter-based TES methods.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Comparative study of spectral diffuse-only and diffuse-specular radiative transfer models and field-collected data in the LWIR

    NASA Astrophysics Data System (ADS)

    Stoyanov, Dimitar M.; Marciniak, Michael A.; Meola, Joseph

    2015-09-01

    The sensitivity of hyper-spectral remote sensing to the directional reflectance of surfaces was studied using both laboratory and field measurements. Namely, the effects of the specular- and diffuse-reflectance properties of a set of eight samples, ranging from high to low in both total reflectance and specularity, on diffuse-only and diffusespecular radiative transfer models in the long-wave infrared (LWIR, 7-14-μm wavelength) were studied. The samples were measured in the field as a set of eight panels, each in two orientations, with surface normal pointing toward zenith and tipped at 45° from zenith. The field-collected data also included down-welling spectral sky radiance at several angles from zenith to the horizon, ground spectral radiance, panel spectral radiances in both orientations, Infragold® spectral radiances in both orientations near each panel location, and panel temperatures. Laboratory measurements included spectral hemispherical, specular and diffuse directional reflectance (HDR, SDR and DDR) for each sample for several reflectance angles with respect to the surface normal. The diffuse-only radiative transfer model used the HDR data, while the diffuse-specular model used the SDR and DDR data. Both calculated spectral reflected and self-emitted radiances for each panel, using the field-collected sky radiance data to avoid uncertainties associated with atmospheric models. The modeled spectral radiances were then compared to the field-collected values to quantify differences in moving from an HDR-based model to an SDR/DDR model in the LWIR for a variety of surface-reflectance types.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Characterization of barrier effects in superlattice LWIR detectors

    NASA Astrophysics Data System (ADS)

    Rhiger, David R.; Kvaas, Robert E.; Harris, Sean F.; Kolasa, Borys P.; Hill, Cory J.; Ting, David Z.

    2010-04-01

    Improved LWIR sensors are needed for defense applications. We report an advance in sensor technology based on diodes in type-II strained layer superlattice structures built in the InAs/GaSb/AlSb materials system. A key feature of the devices is a pair of complementary barriers, namely, an electron barrier and a hole barrier formed at different depths in the growth sequence. The structure is known as CBIRD. This work is a collaborative effort between Raytheon Vision Systems and Jet Propulsion Laboratory, with design and growth being performed at JPL, and processing and testing at RVS. We have analyzed the current-voltage characteristics as functions of temperature and junction area, and have measured the spectral response and quantum efficiency as functions of bias voltage. From the temperature dependence of the dark current in a typical case, we infer that the effective barrier height is 0.175 eV. This indicates that dark current is limited by the barriers rather than diffusion or GR mechanisms occurring within the absorber region where the bandgap is 0.13 eV. The barriers prove to be very effective in suppressing the dark current. In the case of a detector having a cutoff wavelength of 9.24 μm, we find R0A > 105 ohm cm2 at 78 K, as compared with about 100 ohm cm2 for an InAs/GaSb homojunction of the same cutoff. For good photo response, the device must be biased to typically -200 or -250 mV. In this condition we find the internal quantum efficiency to be greater than 50%, while the RA remains above 104 ohm cm2. Thus, the device shows both high RA and good quantum efficiency at the same operating bias. We have also measured the capacitance of the CBIRD device as functions of bias and frequency to help characterize the behavior of the barriers. A 256×256 focal plane array was fabricated with this structure which showed at 78K a responsivity operability of more than 99%.

  5. 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.

  6. A hyperspectral image projector for hyperspectral imagers

    NASA Astrophysics Data System (ADS)

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

    2007-04-01

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

  7. 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.

  8. 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

  9. 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

  10. 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.

  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. 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.

  13. Fast, electrically tunable filters for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  14. Linking goniometer measurements to hyperspectral and multisensor imagery for retrieval of beach properties and coastal characterization

    NASA Astrophysics Data System (ADS)

    Bachmann, Charles M.; Gray, Deric; Abelev, Andrei; Philpot, William; Montes, Marcos J.; Fusina, Robert; Musser, Joseph; Li, Rong-Rong; Vermillion, Michael; Smith, Geoffrey; Korwan, Daniel; Snow, Charlotte; Miller, W. David; Gardner, Joan; Sletten, Mark; Georgiev, Georgi; Truitt, Barry; Killmon, Marcus; Sellars, Jon; Woolard, Jason; Parrish, Christopher; Schwarzscild, Art

    2012-06-01

    In June 2011, a multi-sensor airborne remote sensing campaign was flown at the Virginia Coast Reserve Long Term Ecological Research site with coordinated ground and water calibration and validation (cal/val) measurements. Remote sensing imagery acquired during the ten day exercise included hyperspectral imagery (CASI-1500), topographic LiDAR, and thermal infra-red imagery, all simultaneously from the same aircraft. Airborne synthetic aperture radar (SAR) data acquisition for a smaller subset of sites occurred in September 2011 (VCR'11). Focus areas for VCR'11 were properties of beaches and tidal flats and barrier island vegetation and, in the water column, shallow water bathymetry. On land, cal/val emphasized tidal flat and beach grain size distributions, density, moisture content, and other geotechnical properties such as shear and bearing strength (dynamic deflection modulus), which were related to hyperspectral BRDF measurements taken with the new NRL Goniometer for Outdoor Portable Hyperspectral Earth Reflectance (GOPHER). This builds on our earlier work at this site in 2007 related to beach properties and shallow water bathymetry. A priority for VCR'11 was to collect and model relationships between hyperspectral imagery, acquired from the aircraft at a variety of different phase angles, and geotechnical properties of beaches and tidal flats. One aspect of this effort was a demonstration that sand density differences are observable and consistent in reflectance spectra from GOPHER data, in CASI hyperspectral imagery, as well as in hyperspectral goniometer measurements conducted in our laboratory after VCR'11.

  15. DLC/BP ultra durable LWIR protective coatings for ZnS windows

    NASA Astrophysics Data System (ADS)

    Li, Qiantao; Liu, Shijun; Xiong, Changxin

    2007-12-01

    DLC/BP ultra durable LWIR (long wave infrared) protective coatings have been designed and prepared on ZnS (Zinc Sulphide) windows successfully. Both of BP and DLC coatings are deposited by RF-PECVD (radio frequency enhanced plasma chemical vapor deposition) process, but in different chamber. The transmittance, micro-hardness and durability of DLC/BP coatings have been investigated, which are measured by FTIR spectroscopy, micro-hardness tester and simulative harsh environmental test system. The ZnS window outer face coated with DLC/BP coatings and inner face coated with high efficient antireflection coatings is also fabricated. In the band of 8~11.5μm, the measured maximum transmittance is above 93% and the average transmittance is about 89%. The coated ZnS windows meet with the demands of LWIR electro-optics systems workable in battlefield environment.

  16. Direct optimization of LWIR systems for maximized detection range and minimized size and weight

    NASA Astrophysics Data System (ADS)

    Bates, Rob; Kubala, Kenneth

    2014-05-01

    With reductions in microbolometer size and cost, long-wave infrared (LWIR) systems are increasingly being developed for platforms with challenging size, weight, power, and cost (SWAP-C) constraints, such as helmet-mounted systems and unmanned vehicles. Past optimization of imaging systems toward the simultaneous objectives of improved stand-off detection and low size, weight, and power required an iterative, multi-disciplinary design process. Here we demonstrate the direct optimization of the full LWIR system model including the optics, sensor, signal processing, and display degrees of freedom with system level metrics including SWAP-C and detection range. The end result is a system with superior size and weight for a given detection range.

  17. 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.

  18. Hyperspectral Technique for Detecting Soil Parameters

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  19. 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.

  20. Characterization of LWIR diodes on InAs/GaSb Type-II superlattice material

    NASA Astrophysics Data System (ADS)

    Rhiger, David R.; Kvaas, Robert E.; Harris, Sean F.; Hill, Cory J.

    2009-11-01

    Long wavelength infrared (LWIR) focal plane arrays (FPAs) built on Type-II strained layer InAs/GaSb superlattice materials are emerging as an alternative to LWIR HgCdTe. We have made progress in the development of this technology in a collaborative effort between Raytheon Vision Systems and Jet Propulsion Laboratory, resulting in successful devices with LWIR cutoff wavelengths. We report here two investigations related to wafer processing and superlattice material characteristics. The critical interface between the superlattice and the silicon dioxide passivation was examined at the atomic scale by high resolution transmission electron microscopy (HRTEM), showing a conformal coating on an InAs/GaSb mesa sidewall, which undulates with the superlattice periodicity due to differential etching. Electron energy loss spectroscopy (EELS) showed that oxides of the superlattice elements were present but minimal, and some occasional arsenic precipitates were observed at the passivation interface. Our previous analysis of the current-voltage curves was extended further to reveal the minority carrier lifetimes responsible for producing the generation-recombination (GR) and the diffusion dark currents. Lifetimes at 78 K were found to be 6 and 20 ns in the GR and diffusion processes, respectively. Lifetimes from both mechanisms track together with temperature. A HgCdTe diode was analyzed in the same manner for comparison.

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. Airborne Transparencies.

    ERIC Educational Resources Information Center

    Horne, Lois Thommason

    1984-01-01

    Starting from a science project on flight, art students discussed and investigated various means of moving in space. Then they made acetate illustrations which could be used as transparencies. The projection phenomenon made the illustrations look airborne. (CS)

  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. 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

  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. 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

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Hyperspectral holographic Fourier-microscopy

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  3. Hyperspectral data collection for the assessment of target detection algorithms: the Viareggio 2013 trial

    NASA Astrophysics Data System (ADS)

    Rossi, Alessandro; Acito, Nicola; Diani, Marco; Corsini, Giovanni; De Ceglie, Sergio Ugo; Riccobono, Aldo; Chiarantini, Leandro

    2014-10-01

    Airborne hyperspectral imagery is valuable for military and civilian applications, such as target identification, detection of anomalies and changes within multiple acquisitions. In target detection (TD) applications, the performance assessment of different algorithms is an important and critical issue. In this context, the small number of public available hyperspectral data motivated us to perform an extensive measurement campaign including various operating scenarios. The campaign was organized by CISAM in cooperation with University of Pisa, Selex ES and CSSN-ITE, and it was conducted in Viareggio, Italy in May, 2013. The Selex ES airborne hyperspectral sensor SIM.GA was mounted on board of an airplane to collect images over different sites in the morning and afternoon of two subsequent days. This paper describes the hyperspectral data collection of the trial. Four different sites were set up, representing a complex urban scenario, two parking lots and a rural area. Targets with dimensions comparable to the sensor ground resolution were deployed in the sites to reproduce different operating situations. An extensive ground truth documentation completes the data collection. Experiments to test anomalous change detection techniques were set up changing the position of the deployed targets. Search and rescue scenarios were simulated to evaluate the performance of anomaly detection algorithms. Moreover, the reflectance signatures of the targets were measured on the ground to perform spectral matching in varying atmospheric and illumination conditions. The paper presents some preliminary results that show the effectiveness of hyperspectral data exploitation for the object detection tasks of interest in this work.

  4. QCL as a game changer in MWIR and LWIR military and homeland security applications

    NASA Astrophysics Data System (ADS)

    Patel, C. Kumar N.; Lyakh, Arkadiy; Maulini, Richard; Tsekoun, Alexei; Tadjikov, Boris

    2012-06-01

    QCLs represent an important advance in MWIR and LWIR laser technology. With the demonstration of CW/RT QCLs, large number applications for QCLs have opened up, some of which represent replacement of currently used laser sources such as OPOs and OPSELs, and others being new uses which were not possible using earlier MWIR/LWIR laser sources, namely OPOs, OPSELs and CO2 lasers. Pranalytica has made significant advances in CW/RT power and WPE of QCLs and through its invention of a new QCL structure design, the non-resonant extraction, has demonstrated single emitter power of >4.7 W and WPE of >17% in the 4.4μm-5.0μm region. Pranalytica has also been commercially supplying the highest power MWIR QCLs with high WPEs. The NRE design concept now has been extended to the shorter wavelengths (3.8μm-4.2μm) with multiwatt power outputs and to longer wavelengths (7μm-10μm) with >1 W output powers. The high WPE of the QCLs permits RT operation of QCLs without using TECs in quasi-CW mode where multiwatt average powers are obtained even in ambient T>70°C. The QCW uncooled operation is particularly attractive for handheld, battery-operated applications where electrical power is limited. This paper describes the advances in QCL technology and applications of the high power MWIR and LWIR QCLs for defense applications, including protection of aircraft from MANPADS, standoff detection of IEDs, insitu detection of CWAs and explosives, infrared IFF beacons and target designators. We see that the SWaP advantages of QCLs are game changers.

  5. Remote sensing applications with NH hyperspectral portable video camera

    NASA Astrophysics Data System (ADS)

    Takara, Yohei; Manago, Naohiro; Saito, Hayato; Mabuchi, Yusaku; Kondoh, Akihiko; Fujimori, Takahiro; Ando, Fuminori; Suzuki, Makoto; Kuze, Hiroaki

    2012-11-01

    Recent advances in image sensor and information technologies have enabled the development of small hyperspectral imaging systems. EBA JAPAN (Tokyo, Japan) has developed a novel grating-based, portable hyperspectral imaging camera NH-1 and NH-7 that can acquire a 2D spatial image (640 x 480 and 1280 x 1024 pixels, respectively) with a single exposure using an internal self-scanning system. The imagers cover a wavelength range of 350 - 1100 nm, with a spectral resolution of 5 nm. Because of their small weight of 750 g, the NH camera systems can easily be installed on a small UAV platform. We show the results from the analysis of data obtained by remote sensing applications including land vegetation and atmospheric monitoring from both ground- and airborne/UAV-based observations.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. Recent progress in LWIR HOT photoconductors based on MOCVD grown (100) HgCdTe

    NASA Astrophysics Data System (ADS)

    Gawron, W.; Kębłowski, A.; Kopytko, M.; Madejczyk, P.; Martyniuk, P.; Pędzińska, M.; Piotrowski, A.; Piotrowski, J.; Rogalski, A.; Romanis, M.; Sosna, A.

    2016-10-01

    Hg1-x Cd x Te photoconductors grown in (100) crystallographic orientation are prone to demonstrating high crystalline quality, which results in a lower number of generation-recombination centers, lower noise and high responsivity. This work presents the optimum growth conditions and results of the characterization both of layers and high operating temperature (HOT) long wavelength infrared (LWIR) photoconductive devices based on them. The (100) HgCdTe photoconductor attains D*(13 μm) equal to 6.5 × 109 cmHz1/2W-1 at 200 K and therefore outperforms its (111)B counterpart.

  11. 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

  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. Airborne Imagery

    NASA Technical Reports Server (NTRS)

    1983-01-01

    ATM (Airborne Thematic Mapper) was developed for NSTL (National Space Technology Companies) by Daedalus Company. It offers expanded capabilities for timely, accurate and cost effective identification of areas with prospecting potential. A related system is TIMS, Thermal Infrared Multispectral Scanner. Originating from Landsat 4, it is also used for agricultural studies, etc.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. 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

  1. Toward hyperspectral face recognition

    NASA Astrophysics Data System (ADS)

    Robila, Stefan A.

    2008-02-01

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

  2. 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.

  3. 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.

  4. 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 ...

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. Long-wavelength infrared (LWIR) quantum-dot infrared photodetector (QDIP) focal plane array

    NASA Astrophysics Data System (ADS)

    Gunapala, S. D.; Bandara, S. V.; Hill, C. J.; Ting, D. Z.; Liu, J. K.; Rafol, S. B.; Blazejewski, E. R.; Mumolo, J. M.; Keo, S. A.; Krishna, S.; Chang, Y. C.; Shott, C. A.

    2006-05-01

    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 QDIPs. Subsequent material and device improvements have demonstrated an absorption quantum efficiency (QE) of ~ 3%. Dot-in-the-well (DWELL) QDIPs were also experimentally shown to absorb both 45o 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 8.1μm devices has reached ~ 1 x 1010 Jones at 77 K. Furthermore

  16. 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

  17. The use of hyperspectral data to estimate soil properties

    NASA Astrophysics Data System (ADS)

    Wu, Yong

    Recently there has been a significant increase in the amount of satellite and airborne remotely sensed data (e.g., multi- and hyperspectral) available for use in engineering. The use of these types of data for the assessment of soil properties requires the identification and quantitative estimate of key parameters from soil spectral measurement. This study focuses on soil water content and soil composition. Spectral response of soils with different water content was studied. Artificial neural networks were developed to predict water content of soils from their spectral response. The predicted water contents are in good agreement with the actual water contents. The study could serve as an initial step for developing in-situ water content determination techniques. Spectral un-mixing was also discussed in this study. The N-FINDER algorithm was adapted to find the end-members in a hyperspectral data set. The linear mixture model and the Orthogonal Subspace Projection (OSP) algorithm were used to calculate the fractions of end-members. It is shown that the linear model and OSP can give a fairly good estimate of the end-member abundances. A hyperspectral imaging software tool was used to analyze an AVIRIS data set following a proposed processing routine. The abundance maps of end-members were generated. It is expected that the spectrally determined soil information can be used along with other soil engineering correlations to help engineers characterize a site.

  18. 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.

  19. 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.

  20. LWIR passive perception system for stealthy unmanned ground vehicle night operations

    NASA Astrophysics Data System (ADS)

    Lee, Daren; Rankin, Arturo; Huertas, Andres; Nash, Jeremy; Ahuja, Gaurav; Matthies, Larry

    2016-05-01

    Resupplying forward-deployed units in rugged terrain in the presence of hostile forces creates a high threat to manned air and ground vehicles. An autonomous unmanned ground vehicle (UGV) capable of navigating stealthily at night in off-road and on-road terrain could significantly increase the safety and success rate of such resupply missions for warfighters. Passive night-time perception of terrain and obstacle features is a vital requirement for such missions. As part of the ONR 30 Autonomy Team, the Jet Propulsion Laboratory developed a passive, low-cost night-time perception system under the ONR Expeditionary Maneuver Warfare and Combating Terrorism Applied Research program. Using a stereo pair of forward looking LWIR uncooled microbolometer cameras, the perception system generates disparity maps using a local window-based stereo correlator to achieve real-time performance while maintaining low power consumption. To overcome the lower signal-to-noise ratio and spatial resolution of LWIR thermal imaging technologies, a series of pre-filters were applied to the input images to increase the image contrast and stereo correlator enhancements were applied to increase the disparity density. To overcome false positives generated by mixed pixels, noisy disparities from repeated textures, and uncertainty in far range measurements, a series of consistency, multi-resolution, and temporal based post-filters were employed to improve the fidelity of the output range measurements. The stereo processing leverages multi-core processors and runs under the Robot Operating System (ROS). The night-time passive perception system was tested and evaluated on fully autonomous testbed ground vehicles at SPAWAR Systems Center Pacific (SSC Pacific) and Marine Corps Base Camp Pendleton, California. This paper describes the challenges, techniques, and experimental results of developing a passive, low-cost perception system for night-time autonomous navigation.

  1. Dislocations as a Noise Source in LWIR HgCdTe Photodiodes

    NASA Astrophysics Data System (ADS)

    Jóźwikowski, Krzysztof; Jóźwikowska, Alina; Martyniuk, Andrzej

    2016-10-01

    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. 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.

  3. 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.

  4. Hyperspectral image projector applications

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

  5. Hyperspectral low altitude flashtube illuminator system for visible and near-infrared remote sensing

    SciTech Connect

    Kalshoven, J.E.

    1996-10-01

    A high energy flashtube is integrated with an airborne spectrometer system for hyperspectral remote sensing of the Earth`s surface. The system, called AVIS (Airborne Vegetation Index Sensor) and currently mounted on a NASA helicopter, is flown at a nominal altitude of 500 feet (150 m). The flashtube is a two joule Xenon lamp pulsed at a 2 Hz rate. The transmitting optics give a 15 x 35 mrad beam output. The receiver is a grating spectrometer with a 512 element CCD linear array which provides a high resolution output of the backscattered visible and infrared spectrum. The system is currently used for forest canopy studies. 5 figs., 2 tabs.

  6. The Northwest of china hyperspectral mineral mapping project

    NASA Astrophysics Data System (ADS)

    ZHAO, yingjun; QIN, kai

    2015-04-01

    This five year collaborative project was established in September 2010 with the overall aim of developing, validating, evaluating and delivering a suite of publicly available, pre-competitive mineral mapping products from airborne CASI/SASI/TASI hyperspectral imagery. Moreover, it was important to establish whether these mineral maps would complement other precompetitive geological and geophysical data and provide valuable new information for enhanced mineral exploration by the china resources community. The project acquisition and generation of a suite of 21 mineral abundance and mineral composition maps derived from airborne CASI/SASI/TASI hyperspectral imagery (171 flight-lines) covering covering12000 km2 in northwest china. A mineral analysis approach was used to appreciate the value of these mineral maps for exploration. That is, mineral products need to be selected on the basis of critical parameters, such as what minerals are expected to develop as fluids migrate from source rocks to depositional sites and then to outflow zones with each associated with different physicochemical conditions (e.g. metasomatic metal budget, nature of the fluids, water-rock ratios, lithostatic pressure, pore fluid pressure, REDOX, pH, and temperature). In summary, this project has shown that it is possible to generate accurate, large area mineral maps that provide new information about mineral system footprints not seen in other precompetitive geoscience data and that the vision of a mineral map of china is achievable and of potential value for the resources industry.

  7. 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.

  8. Detection and monitoring of oil spills using hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Sanchez, Glenda; Roper, William E.; Gomez, Richard B.

    2003-08-01

    Oil pollution is a very important aspect in the environmental field. Oil pollution is an important subject due to its capacity to adversely affect animals, aquatic life, vegetation and drinking water. The movement of open water oil spills can be affected by mind, waves and tides. Land based oil spills are often affected by rain and temperature. It is important to have an accurate management of the cleanup. Remote sensing and in particular hyper-spectral capabilities, are being use to identify oil spills and prevent worse problems. In addition to this capability, this technology can be used for federal and state compliance of petroleum related companies. There are several hyper-spectral sensors used in the identification of oil spills. One commonly use sensor is the Airborne Imaging Spectroradiometer for Applications (AISA). The main concern associated with the use of these sensors is the potential for false identification of oil spills. The use of AISA to identify an oil spill over the Patuxent River is an example of how this tool can assist with investigating an oil pipeline accident, and its potential to affect the surrounding environment. A scenario like this also serves as a good test of the accuracy with which spills may be identified using new airborne sensors.

  9. Sofradir SWIR hyperspectral detectors for space applications

    NASA Astrophysics Data System (ADS)

    Nowicki-Bringuier, Yoanna-Reine; Chorier, Philippe

    2009-09-01

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

  10. 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...

  11. 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

  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. 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.

  14. 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.

  15. 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

  16. State of the art of AIM LWIR and VLWIR MCT 2D focal plane detector arrays for higher operating temperatures

    NASA Astrophysics Data System (ADS)

    Figgemeier, H.; Hanna, S.; Eich, D.; Mahlein, K.-M.; Fick, W.; Schirmacher, W.; Thöt, R.

    2016-05-01

    In this paper AIM presents its latest results on both n-on-p and p-on-n low dark current planar MCT photodiode technology LWIR and VLWIR two-dimensional focal plane detector arrays with a cut-off wavelength >11μm at 80K and a 640x512 pixel format at a 20μm pitch. Thermal dark currents significantly reduced as compared to `Tennant's Rule 07' at a yet good detection efficiency >60% as well as results from NETD and photo response performance characterization are presented. The demonstrated detector performance paces the way for a new generation of higher operating temperature LWIR MCT FPAs with a <30mK NETD up to a 110K detector operating temperature and with good operability.

  17. 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.

  18. 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.

  19. 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.

  20. Informed Source Separation of Atmospheric and Surface Signal Contributions in Shortwave Hyperspectral Imagery using Non-negative Matrix Factorization

    NASA Astrophysics Data System (ADS)

    Wright, L.; Coddington, O.; Pilewskie, P.

    2015-12-01

    Current challenges in Earth remote sensing require improved instrument spectral resolution, spectral coverage, and radiometric accuracy. Hyperspectral instruments, deployed on both aircraft and spacecraft, are a growing class of Earth observing sensors designed to meet these challenges. They collect large amounts of spectral data, allowing thorough characterization of both atmospheric and surface properties. The higher accuracy and increased spectral and spatial resolutions of new imagers require new numerical approaches for processing imagery and separating surface and atmospheric signals. One potential approach is source separation, which allows us to determine the underlying physical causes of observed changes. Improved signal separation will allow hyperspectral instruments to better address key science questions relevant to climate change, including land-use changes, trends in clouds and atmospheric water vapor, and aerosol characteristics. In this work, we investigate a Non-negative Matrix Factorization (NMF) method for the separation of atmospheric and land surface signal sources. NMF offers marked benefits over other commonly employed techniques, including non-negativity, which avoids physically impossible results, and adaptability, which allows the method to be tailored to hyperspectral source separation. We adapt our NMF algorithm to distinguish between contributions from different physically distinct sources by introducing constraints on spectral and spatial variability and by using library spectra to inform separation. We evaluate our NMF algorithm with simulated hyperspectral images as well as hyperspectral imagery from several instruments including, the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), NASA Hyperspectral Imager for the Coastal Ocean (HICO) and National Ecological Observatory Network (NEON) Imaging Spectrometer.

  1. Hyperspectral range imaging for transportation systems evaluation

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  2. Development of hyperspectral image projectors

    NASA Astrophysics Data System (ADS)

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

    2006-08-01

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

  3. Design of a concise Féry-prism hyperspectral imaging system based on multi-configuration

    NASA Astrophysics Data System (ADS)

    Dong, Wei; Nie, Yun-feng; Zhou, Jin-song

    2013-08-01

    In order to meet the needs of space borne and airborne hyperspectral imaging system for light weight, simplification and high spatial resolution, a novel design of Féry-prism hyperspectral imaging system based on Zemax multi-configuration method is presented. The novel structure is well arranged by analyzing optical monochromatic aberrations theoretically, and the optical structure of this design is concise. The fundamental of this design is Offner relay configuration, whereas the secondary mirror is replaced by Féry-prism with curved surfaces and a reflective front face. By reflection, the light beam passes through the Féry-prism twice, which promotes spectral resolution and enhances image quality at the same time. The result shows that the system can achieve light weight and simplification, compared to other hyperspectral imaging systems. Composed of merely two spherical mirrors and one achromatized Féry-prism to perform both dispersion and imaging functions, this structure is concise and compact. The average spectral resolution is 6.2nm; The MTFs for 0.45~1.00um spectral range are greater than 0.75, RMSs are less than 2.4um; The maximal smile is less than 10% pixel, while the keystones is less than 2.8% pixel; image quality approximates the diffraction limit. The design result shows that hyperspectral imaging system with one modified Féry-prism substituting the secondary mirror of Offner relay configuration is feasible from the perspective of both theory and practice, and possesses the merits of simple structure, convenient optical alignment, and good image quality, high resolution in space and spectra, adjustable dispersive nonlinearity. The system satisfies the requirements of airborne or space borne hyperspectral imaging system.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. Buried mine detection using fractal geometry analysis to the LWIR successive line scan data image

    NASA Astrophysics Data System (ADS)

    Araki, Kan

    2012-06-01

    We have engaged in research on buried mine/IED detection by remote sensing method using LWIR camera. A IR image of a ground, containing buried objects can be assumed as a superimposed pattern including thermal scattering which may depend on the ground surface roughness, vegetation canopy, and effect of the sun light, and radiation due to various heat interaction caused by differences in specific heat, size, and buried depth of the objects and local temperature of their surrounding environment. In this cumbersome environment, we introduce fractal geometry for analyzing from an IR image. Clutter patterns due to these complex elements have oftentimes low ordered fractal dimension of Hausdorff Dimension. On the other hand, the target patterns have its tendency of obtaining higher ordered fractal dimension in terms of Information Dimension. Random Shuffle Surrogate method or Fourier Transform Surrogate method is used to evaluate fractional statistics by applying shuffle of time sequence data or phase of spectrum. Fractal interpolation to each line scan was also applied to improve the signal processing performance in order to evade zero division and enhance information of data. Some results of target extraction by using relationship between low and high ordered fractal dimension are to be presented.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. [Progress in leaf area index retrieval based on hyperspectral remote sensing and retrieval models].

    PubMed

    Zhang, Jia-Hua; Du, Yu-Zhang; Liu, Xu-Feng; He, Zhen-Ming; Yang, Li-Min

    2012-12-01

    The leaf area index (LAI) is a very important parameter affecting land-atmosphere exchanges in land-surface processes; LAI is one of the basic feature parameters of canopy structure, and one of the most important biophysical parameters for modeling ecosystem processes such as carbon and water fluxes. Remote sensing provides the only feasible option for mapping LAI continuously over landscapes, but existing methodologies have significant limitations. To detect LAI accurately and quickly is one of tasks in the ecological and agricultural crop yield estimation study, etc. Emerging hyperspectral remote sensing sensor and techniques can complement existing ground-based measurement of LAI. Spatially explicit measurements of LAI extracted from hyperspectral remotely sensed data are component necessary for simulation of ecological variables and processes. This paper firstly summarized LAI retrieval method based on different level hyperspectral remote sensing platform (i. e., airborne, satelliteborne and ground-based); and secondly different kinds of retrieval model were summed up both at home and abroad in recent years by using hyperspectral remote sensing data; and finally the direction of future development of LAI remote sensing inversion was analyzed.

  5. 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%.

  6. Estimation of leaf nitrogen and silicon using hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    Mokhele, Tholang A.; Ahmed, Fethi B.

    2010-11-01

    The potential to estimate the nutrient status in important agricultural crops such as maize and sugarcane is of significant interest. In South African sugarcane agriculture, just like in global ecosystem, the estimation of Nitrogen (N) and Silicon (Si) is very important. These nutrients are one of the factors influencing the prevalence of the stalk borer Eldana saccharina Walker (Lepidoptera: Pyralidae). Therefore, the researchers aim at estimating leaf N and Si concentration as well as their ratio in sugarcane using hyperspectral remote sensing (spectroradiometry) for monitoring E. saccharina. A hand-held Analytical Spectral Devices (ASD) Field Spec® 3 spectroradiometer was used to take leaf spectral measurements of sugarcane plants from a potted-plant trial taking place under shade house conditions. In this trial, nitrogen and silicon nutrient applications as well as varieties used were known. In addition, watering regimes and artificial infestation of E. saccharina were carefully controlled. The study results indicate that the Red-edge Index (R740/R720) is linearly related to N concentration (R2 = 0.81, Root Mean Square Error (RMSE) = 0.103) for N37 with the highest correlation coefficient. For Si, the index (R750-R560)/(R750+R560) was linearly related to Si concentration (R2 = 0.53, RMSE = 0.118) for N25. Finally, the N:Si ratio was linearly correlated to the index (R1075-R730)/(R1075+R730) (R2 = 0.67, RMSE = 1.508) for N37, hence this index can be used for early detection of E. saccharina damage or for identifying sugarcane that is prone to attack by E. saccharina. It was concluded that hyperspectral remote sensing has potential for use in estimating the N:Si ratio and E. saccharina potential infestations can be monitored rapidly and nondestructively in sugarcane under controlled conditions. It is recommended that an advanced study be conducted in field conditions using airborne and/or spaceborne hyperspectral sensors.

  7. 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.

  8. 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.

  9. Measuring Radiant Emissions from Entire Prescribed Fires with Ground, Airborne and Satellite Sensors RxCADRE 2012

    NASA Technical Reports Server (NTRS)

    Dickinson, Matthew B.; Hudak, Andrew T.; Zajkowski, Thomas; Loudermilk, E. Louise; Schroeder, Wilfrid; Ellison, Luke; Kremens, Robert L.; Holley, William; Martinez, Otto; Paxton, Alexander; Bright, Benjamin C.; O'Brien, Joseph J.; Hornsby, Benjamin; Ichoku, Charles; Faulring, Jason; Gerace, Aaron; Peterson, David; Mauceri, Joseph

    2015-01-01

    Characterising radiation from wildland fires is an important focus of fire science because radiation relates directly to the combustion process and can be measured across a wide range of spatial extents and resolutions. As part of a more comprehensive set of measurements collected during the 2012 Prescribed Fire Combustion and Atmospheric Dynamics Research (RxCADRE) field campaign, we used ground, airborne and spaceborne sensors to measure fire radiative power (FRP) from whole fires, applying different methods to small (2 ha) and large (.100 ha) burn blocks. For small blocks (n1/46), FRP estimated from an obliquely oriented long-wave infrared (LWIR) camera mounted on a boom lift were compared with FRP derived from combined data from tower-mounted radiometers and remotely piloted aircraft systems (RPAS). For large burn blocks (n1/43), satellite FRP measurements from the Moderate-resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors were compared with near-coincident FRP measurements derived from a LWIR imaging system aboard a piloted aircraft. We describe measurements and consider their strengths and weaknesses. Until quantitative sensors exist for small RPAS, their use in fire research will remain limited. For oblique, airborne and satellite sensors, further FRP measurement development is needed along with greater replication of coincident measurements, which we show to be feasible.

  10. 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.

  11. 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.

  12. Hyperspectral target detection using manifold learning and multiple target spectra

    DOE PAGES

    Ziemann, Amanda K.; Theiler, James; Messinger, David W.

    2016-03-31

    Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform these detection analyses. For a d-dimensional hyperspectral image, however, where d is the number of spectral bands, it is common for the data to inherently occupy an m-dimensional space with m << d. In the remote sensing community, this has led to recent interestmore » in the use of manifold learning, which seeks to characterize the embedded lower-dimensional, nonlinear manifold that the data discretely approximate. The research presented in this paper focuses on a graph theory and manifold learning approach to target detection, using an adaptive version of locally linear embedding that is biased to separate target pixels from background pixels. Finally, this approach incorporates multiple target signatures for a particular material, accounting for the spectral variability that is often present within a solid material of interest.« less

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. Exploration of geothermal systems using hyperspectral thermal infrared remote sensing

    NASA Astrophysics Data System (ADS)

    Reath, Kevin A.; Ramsey, Michael S.

    2013-09-01

    Visible near infrared (VNIR), short-wave infrared (SWIR), and thermal infrared (TIR) remote sensing has long been used for geothermal exploration. Specific focus on the TIR region (8-12 μm) has resulted in major-rock-forming mineral classes being identified and their areal percentages to be more easily mapped due in part to the linear mixing behavior of TIR emission. To understand the mineral compositional and thermal distribution of active geothermal surfaces systems, hyperspectral TIR data from the Spatially Enhanced Broadband Array Spectrograph System (SEBASS) airborne sensor were acquired over the Salton Sea, CA geothermal fields by The Aerospace Corporation on March 26, 2009 and April 6, 2010. SEBASS collects 128 wavelength channels at ~ 1 m spatial resolution. Such high resolution data are rarely available for this type of scientific analysis and enabled the identification of rare mineral assemblages associated with the geothermally-active areas. One surface unit with a unique spectrum, believed to be a magnesium sulfate of unknown hydration state, was identified for the first time in the SEBASS data. The abundance and distribution of this mineral varied between 2009 and 2010 likely due to the precipitation conditions. Data obtained by the SEBASS sensor were also regressed to the 32 channel spectral resolution of the Mineral and Gas Identifier (MAGI) airborne sensor in order to test sensitivity limits. At this lower spectral resolution, all surface minerals were still effectively identified and therefore validated data at MAGI resolution are still very effective for accurate surface compositional mapping. A similar approach used at active geothermal areas in other semi-arid regions around the world has the potential to better characterize transient mineralogy, identify "indicators minerals", understand the influence of surface and ground water, and ultimately to locate new geothermal targets for future exploration. Furthermore, new Mineral and Gas

  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 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.

  20. MAP estimation for hyperspectral image resolution enhancement using an auxiliary sensor.

    PubMed

    Hardie, Russell C; Eismann, Michael T; Wilson, Gregory L

    2004-09-01

    This paper presents a novel maximum a posteriori estimator for enhancing the spatial resolution of an image using co-registered high spatial-resolution imagery from an auxiliary sensor. Here, we focus on the use of high-resolution panchomatic data to enhance hyperspectral imagery. However, the estimation framework developed allows for any number of spectral bands in the primary and auxiliary image. The proposed technique is suitable for applications where some correlation, either localized or global, exists between the auxiliary image and the image being enhanced. To exploit localized correlations, a spatially varying statistical model, based on vector quantization, is used. Another important aspect of the proposed algorithm is that it allows for the use of an accurate observation model relating the "true" scene with the low-resolutions observations. Experimental results with hyperspectral data derived from the airborne visible-infrared imaging spectrometer are presented to demonstrate the efficacy of the proposed estimator.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. Characterisation methods for the hyperspectral sensor HySpex at DLR's calibration home base

    NASA Astrophysics Data System (ADS)

    Baumgartner, Andreas; Gege, Peter; Köhler, Claas; Lenhard, Karim; Schwarzmaier, Thomas

    2012-09-01

    The German Aerospace Center's (DLR) Remote Sensing Technology Institute (IMF) operates a laboratory for the characterisation of imaging spectrometers. Originally designed as Calibration Home Base (CHB) for the imaging spectrometer APEX, the laboratory can be used to characterise nearly every airborne hyperspectral system. Characterisation methods will be demonstrated exemplarily with HySpex, an airborne imaging spectrometer system from Norsk Elektro Optikks A/S (NEO). Consisting of two separate devices (VNIR-1600 and SWIR-320me) the setup covers the spectral range from 400 nm to 2500 nm. Both airborne sensors have been characterised at NEO. This includes measurement of spectral and spatial resolution and misregistration, polarisation sensitivity, signal to noise ratios and the radiometric response. The same parameters have been examined at the CHB and were used to validate the NEO measurements. Additionally, the line spread functions (LSF) in across and along track direction and the spectral response functions (SRF) for certain detector pixels were measured. The high degree of lab automation allows the determination of the SRFs and LSFs for a large amount of sampling points. Despite this, the measurement of these functions for every detector element would be too time-consuming as typical detectors have 105 elements. But with enough sampling points it is possible to interpolate the attributes of the remaining pixels. The knowledge of these properties for every detector element allows the quantification of spectral and spatial misregistration (smile and keystone) and a better calibration of airborne data. Further laboratory measurements are used to validate the models for the spectral and spatial properties of the imaging spectrometers. Compared to the future German spaceborne hyperspectral Imager EnMAP, the HySpex sensors have the same or higher spectral and spatial resolution. Therefore, airborne data will be used to prepare for and validate the spaceborne system

  7. 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

  8. 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.

  9. Detection in urban scenario using combined airborne imaging sensors

    NASA Astrophysics Data System (ADS)

    Renhorn, Ingmar; Axelsson, Maria; Benoist, Koen; Bourghys, Dirk; Boucher, Yannick; Briottet, Xavier; De Ceglie, Sergio; Dekker, Rob; Dimmeler, Alwin; Dost, Remco; Friman, Ola; Kåsen, Ingebjørg; Maerker, Jochen; van Persie, Mark; Resta, Salvatore; Schwering, Piet; Shimoni, Michal; Haavardsholm, Trym Vegard

    2012-06-01

    The EDA project "Detection in Urban scenario using Combined Airborne imaging Sensors" (DUCAS) is in progress. The aim of the project is to investigate the potential benefit of combined high spatial and spectral resolution airborne imagery for several defense applications in the urban area. The project is taking advantage of the combined resources from 7 contributing nations within the EDA framework. An extensive field trial has been carried out in the city of Zeebrugge at the Belgian coast in June 2011. The Belgian armed forces contributed with platforms, weapons, personnel (soldiers) and logistics for the trial. Ground truth measurements with respect to geometrical characteristics, optical material properties and weather conditions were obtained in addition to hyperspectral, multispectral and high resolution spatial imagery. High spectral/spatial resolution sensor data are used for detection, classification, identification and tracking.

  10. 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.

  11. 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

  12. 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

  13. Hyperspectral imaging of ischemic wounds

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

  14. 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.

  15. Hyperspectral image compressive projection algorithm

    NASA Astrophysics Data System (ADS)

    Rice, Joseph P.; Allen, David W.

    2009-05-01

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

  16. Skin detection in hyperspectral images

    NASA Astrophysics Data System (ADS)

    Sanchez, Stephanie M.; Velez-Reyes, Miguel

    2015-05-01

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

  17. 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.

  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. 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

  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. 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).

  2. 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.

  3. Comparative study on atmospheric correction methods of visible and near-infrared hyperspectral image

    NASA Astrophysics Data System (ADS)

    He, Qian; Wu, Jingli; Wang, Guangping; Liu, Chang; Tao, Tao

    2015-03-01

    Currently, common atmospheric correction methods usually based on the statistical information of image itself for relative reflectance calculation, or make use of the radiative transfer model and meteorological parameters for accurate calculations. In order to compare the advantages and disadvantages of these methods, we carried out some atmospheric correction experiments based on AVIRIS Airborne Visible and Near-Infrared hyperspectral data. It proved that, the statistical method is simple and convenient, but not wide adaptability, that can only get the relative reflectance; while the radiative transfer model method is very complex and require the support of auxiliary information, but it can get the precise absolute reflectance of surface features.

  4. 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.

  5. 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.

  6. Efficient detection in hyperspectral imagery.

    PubMed

    Schweizer, S M; Moura, J F

    2001-01-01

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

  7. Solid state temperature-dependent NUC (non-uniformity correction) in uncooled LWIR (long-wave infrared) imaging system

    NASA Astrophysics Data System (ADS)

    Cao, Yanpeng; Tisse, Christel-Loic

    2013-06-01

    In uncooled LWIR microbolometer imaging systems, temperature fluctuations of FPA (Focal Plane Array) as well as lens and mechanical components placed along the optical path result in thermal drift and spatial non-uniformity. These non-idealities generate undesirable FPN (Fixed-Pattern-Noise) that is difficult to remove using traditional, individual shutterless and TEC-less (Thermo-Electric Cooling) techniques. In this paper we introduce a novel single-image based processing approach that marries the benefits of both statistical scene-based and calibration-based NUC algorithms, without relying neither on extra temperature reference nor accurate motion estimation, to compensate the resulting temperature-dependent non-uniformities. Our method includes two subsequent image processing steps. Firstly, an empirical behavioral model is derived by calibrations to characterize the spatio-temporal response of the microbolometric FPA to environmental and scene temperature fluctuations. Secondly, we experimentally establish that the FPN component caused by the optics creates a spatio-temporally continuous, low frequency, low-magnitude variation of the image intensity. We propose to make use of this property and learn a prior on the spatial distribution of natural image gradients to infer the correction function for the entire image. The performance and robustness of the proposed temperature-adaptive NUC method are demonstrated by showing results obtained from a 640×512 pixels uncooled LWIR microbolometer imaging system operating over a broad range of temperature and with rapid environmental temperature changes (i.e. from -5°C to 65°C within 10 minutes).

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. Filtering high resolution hyperspectral imagery and analyzing it for quantification of water quality parameters and aquatic vegetation

    NASA Astrophysics Data System (ADS)

    Pande-Chhetri, Roshan

    High resolution hyperspectral imagery (airborne or ground-based) is gaining momentum as a useful analytical tool in various fields including agriculture and aquatic systems. These images are often contaminated with stripes and noise resulting in lower signal-to-noise ratio, especially in aquatic regions where signal is naturally low. This research investigates effective methods for filtering high spatial resolution hyperspectral imagery and use of the imagery in water quality parameter estimation and aquatic vegetation classification. The striping pattern of the hyperspectral imagery is non-parametric and difficult to filter. In this research, a de-striping algorithm based on wavelet analysis and adaptive Fourier domain normalization was examined. The result of this algorithm was found superior to other available algorithms and yielded highest Peak Signal to Noise Ratio improvement. The algorithm was implemented on individual image bands and on selected bands of the Maximum Noise Fraction (MNF) transformed images. The results showed that image filtering in the MNF domain was efficient and produced best results. The study investigated methods of analyzing hyperspectral imagery to estimate water quality parameters and to map aquatic vegetation in case-2 waters. Ground-based hyperspectral imagery was analyzed to determine chlorophyll-a (Chl-a) concentrations in aquaculture ponds. Two-band and three-band indices were implemented and the effect of using submerged reflectance targets was evaluated. Laboratory measured values were found to be in strong correlation with two-band and three-band spectral indices computed from the hyperspectral image. Coefficients of determination (R2) values were found to be 0.833 and 0.862 without submerged targets and stronger values of 0.975 and 0.982 were obtained using submerged targets. Airborne hyperspectral images were used to detect and classify aquatic vegetation in a black river estuarine system. Image normalization for water

  15. 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

  16. 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.

  17. Optimization of spectral bands for hyperspectral remote sensing of forest vegetation

    NASA Astrophysics Data System (ADS)

    Dmitriev, Egor V.; Kozoderov, Vladimir V.

    2013-10-01

    Optimization principles of accounting for the most informative spectral channels in hyperspectral remote sensing data processing serve to enhance the efficiency of the employed high-productive computers. The problem of pattern recognition of the remotely sensed land surface objects with the accent on the forests is outlined from the point of view of the spectral channels optimization on the processed hyperspectral images. The relevant computational procedures are tested using the images obtained by the produced in Russia hyperspectral camera that was installed on a gyro-stabilized platform to conduct the airborne flight campaigns. The Bayesian classifier is used for the pattern recognition of the forests with different tree species and age. The probabilistically optimal algorithm constructed on the basis of the maximum likelihood principle is described to minimize the probability of misclassification given by this classifier. The classification error is the major category to estimate the accuracy of the applied algorithm by the known holdout cross-validation method. Details of the related techniques are presented. Results are shown of selecting the spectral channels of the camera while processing the images having in mind radiometric distortions that diminish the classification accuracy. The spectral channels are selected of the obtained subclasses extracted from the proposed validation techniques and the confusion matrices are constructed that characterize the age composition of the classified pine species as well as the broad age-class recognition for the pine and birch species with the fully illuminated parts of their crowns.

  18. 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.

  19. Development of an imaging hyperspectral camera using the ultraviolet and visible wavelength AOTF

    NASA Astrophysics Data System (ADS)

    Kurosaki, Hirohisa; Shingu, Hirokimi; Enkyo, Shigeharu; Suzuki, Takao; Tanioka, Kenkichi; Takefuji, Yoshiyasu

    2003-04-01

    A spectroscopic camera has been developed which has spectral resolution of less than 1.5nm in the ultraviolet (UV) and visible wavelength bands (320-580 nm). Its main components are a specially coated UV objective lens, a UV Acousto-Optic Tunable Filter (AOTF) with a thermo-electric cooling system, and a imaging system based on a high-gain avalanche rushing amorphous photoconductor (HARP) developed by NHK Science and Technical Research Laboratories. Research is currently under way to develop the hyperspectral camera into a sensor package for airborne and ultimately space-based remote sensing applications. This paper presents the basic principle and configuration of the hyperspectral camera, and gives details of tests to measure its performance. The results of spectral resolution tests analyzing very close two spectra from a helium-discharge lamp demonstrate the camera's high spectral resolution performance. Full color and spectral images obtained by a spectrometry experiment are also presented to demonstrate the camera's hyperspectral capabilities.

  20. 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.

  1. 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.

  2. 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.

  3. Ningaloo Reef: Shallow Marine Habitats Mapped Using a Hyperspectral Sensor

    PubMed Central

    Kobryn, Halina T.; Wouters, Kristin; Beckley, Lynnath E.; Heege, Thomas

    2013-01-01

    Research, monitoring and management of large marine protected areas require detailed and up-to-date habitat maps. Ningaloo Marine Park (including the Muiron Islands) in north-western Australia (stretching across three degrees of latitude) was mapped to 20 m depth using HyMap airborne hyperspectral imagery (125 bands) at 3.5 m resolution across the 762 km2 of reef environment between the shoreline and reef slope. The imagery was corrected for atmospheric, air-water interface and water column influences to retrieve bottom reflectance and bathymetry using the physics-based Modular Inversion and Processing System. Using field-validated, image-derived spectra from a representative range of cover types, the classification combined a semi-automated, pixel-based approach with fuzzy logic and derivative techniques. Five thematic classification levels for benthic cover (with probability maps) were generated with varying degrees of detail, ranging from a basic one with three classes (biotic, abiotic and mixed) to the most detailed with 46 classes. The latter consisted of all abiotic and biotic seabed components and hard coral growth forms in dominant or mixed states. The overall accuracy of mapping for the most detailed maps was 70% for the highest classification level. Macro-algal communities formed most of the benthic cover, while hard and soft corals represented only about 7% of the mapped area (58.6 km2). Dense tabulate coral was the largest coral mosaic type (37% of all corals) and the rest of the corals were a mix of tabulate, digitate, massive and soft corals. Our results show that for this shallow, fringing reef environment situated in the arid tropics, hyperspectral remote sensing techniques can offer an efficient and cost-effective approach to mapping and monitoring reef habitats over large, remote and inaccessible areas. PMID:23922921

  4. 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.

  5. 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

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

    USGS Publications Warehouse

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

    2011-01-01

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

  7. Mars Airborne Prospecting Spectrometer

    NASA Astrophysics Data System (ADS)

    Steinkraus, J. M.; Wright, M. W.; Rheingans, B. E.; Steinkraus, D. E.; George, W. P.; Aljabri, A.; Hall, J. L.; Scott, D. C.

    2012-06-01

    One novel approach towards addressing the need for innovative instrumentation and investigation approaches is the integration of a suite of four spectrometer systems to form the Mars Airborne Prospecting Spectrometers (MAPS) for prospecting on Mars.

  8. Hyperspectral Data Processing and Mapping of Soil Parameters: Preliminary Data from Tuscany (Italy)

    NASA Astrophysics Data System (ADS)

    Garfagnoli, F.; Moretti, S.; Catani, F.; Innocenti, L.; Chiarantini, L.

    2010-12-01

    Hyperspectral imaging has become a very powerful remote sensing tool for its capability of performing chemical and physical analysis of the observed areas. The objective of this study is to retrieve and characterize clay mineral content of the cultivated layer of soils, from both airborne hyperspectral and field spectrometry surveys in the 400-2500 nm spectral range. Correlation analysis is used to examine the possibility to predict the selected property using high-resolution reflectance spectra and images. The study area is located in the Mugello basin, about 30 km north of Firenze (Tuscany, Italy). Agriculturally suitable terrains are assigned mainly to annual crops, marginally to olive groves, vineyards and orchards. Soils mostly belong to Regosols and Cambisols orders. About 80 topsoil samples scattered all over the area were collected simultaneously with the flight of SIM.GA hyperspectral camera from Selex Galileo. The quantitative determination of clay minerals content in soil samples was performed by means of XRD and Rietveld refinement. An ASD FieldSpec spectroradiometer was used to obtain reflectance spectra from dried, crushed and sieved samples under controlled laboratory conditions. Different chemometric techniques (multiple linear regression, vertex component analysis, partial least squares regression and band depth analysis) were preliminarily tested to correlate mineralogical records with reflectance data. A one component partial least squares regression model yielded a preliminary R2 value of 0.65. A similar result was achieved by plotting the absorption peak depth at 2210 versus total clay mineral content (band-depth analysis). A complete hyperspectral geocoded reflectance dataset was collected using SIM.GA hyperspectral image sensor from Selex-Galileo, mounted on board of the University of Firenze ultra light aircraft. The approximate pixel resolution was 0.6 m (VNIR) and 1.2 m (SWIR). Airborne SIM.GA row data were firstly transformed into at

  9. Optimal band selection in hyperspectral remote sensing of aquatic benthic features: a wavelet filter window approach

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R., Jr.

    2006-09-01

    This paper describes a wavelet based approach to derivative spectroscopy. The approach is utilized to select, through optimization, optimal channels or bands to use as derivative based remote sensing algorithms. The approach is applied to airborne and modeled or synthetic reflectance signatures of environmental media and features or objects within such media, such as benthic submerged vegetation canopies. The technique can also applied to selected pixels identified within a hyperspectral image cube obtained from an board an airborne, ground based, or subsurface mobile imaging system. This wavelet based image processing technique is an extremely fast numerical method to conduct higher order derivative spectroscopy which includes nonlinear filter windows. Essentially, the wavelet filter scans a measured or synthetic signature in an automated sequential manner in order to develop a library of filtered spectra. The library is utilized in real time to select the optimal channels for direct algorithm application. The unique wavelet based derivative filtering technique makes us of a translating, and dilating derivative spectroscopy signal processing (TDDS-SP (R)) approach based upon remote sensing science and radiative transfer processes unlike other signal processing techniques applied to hyperspectral signatures.

  10. Abundance quantification by independent component analysis of hyperspectral imagery for oil spill coverage calculation

    NASA Astrophysics Data System (ADS)

    Han, Zhongzhi; Wan, Jianhua; Zhang, Jie; Zhang, Hande

    2016-08-01

    The estimation of oil spill coverage is an important part of monitoring of oil spills at sea. The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills and the accuracy of estimates of their size. We consider at-sea oil spills with zonal distribution in this paper and improve the traditional independent component analysis algorithm. For each independent component we added two constraint conditions: non-negativity and constant sum. We use priority weighting by higher-order statistics, and then the spectral angle match method to overcome the order nondeterminacy. By these steps, endmembers can be extracted and abundance quantified simultaneously. To examine the coverage of a real oil spill and correct our estimate, a simulation experiment and a real experiment were designed using the algorithm described above. The result indicated that, for the simulation data, the abundance estimation error is 2.52% and minimum root mean square error of the reconstructed image is 0.030 6. We estimated the oil spill rate and area based on eight hyper-spectral remote sensing images collected by an airborne survey of Shandong Changdao in 2011. The total oil spill area was 0.224 km2, and the oil spill rate was 22.89%. The method we demonstrate in this paper can be used for the automatic monitoring of oil spill coverage rates. It also allows the accurate estimation of the oil spill area.

  11. Unsupervised hierarchical partitioning of hyperspectral images: application to marine algae identification

    NASA Astrophysics Data System (ADS)

    Chen, B.; Chehdi, K.; De Oliveria, E.; Cariou, C.; Charbonnier, B.

    2015-10-01

    In this paper a new unsupervised top-down hierarchical classification method to partition airborne hyperspectral images is proposed. The unsupervised approach is preferred because the difficulty of area access and the human and financial resources required to obtain ground truth data, constitute serious handicaps especially over large areas which can be covered by airborne or satellite images. The developed classification approach allows i) a successive partitioning of data into several levels or partitions in which the main classes are first identified, ii) an estimation of the number of classes automatically at each level without any end user help, iii) a nonsystematic subdivision of all classes of a partition Pj to form a partition Pj+1, iv) a stable partitioning result of the same data set from one run of the method to another. The proposed approach was validated on synthetic and real hyperspectral images related to the identification of several marine algae species. In addition to highly accurate and consistent results (correct classification rate over 99%), this approach is completely unsupervised. It estimates at each level, the optimal number of classes and the final partition without any end user intervention.

  12. Hyperspectral Geobotanical Remote Sensing for CO2 Storage Monitoring

    SciTech Connect

    Pickles, W; Cover, W

    2004-05-14

    This project's goal is to develop remote sensing methods for early detection and spatial mapping, over whole regions simultaneously, of any surface areas under which there are significant CO2 leaks from deep underground storage formations. If large amounts of CO2 gas percolated up from a storage formation below to within plant root depth of the surface, the CO2 soil concentrations near the surface would become elevated and would affect individual plants and their local plant ecologies. Excessive soil CO2 concentrations are observed to significantly affect local plant and animal ecologies in our geothermal exploration, remote sensing research program at Mammoth Mountain CA USA. We also know from our geothermal exploration remote sensing programs, that we can map subtle hidden faults by spatial signatures of altered minerals and of plant species and health distributions. Mapping hidden faults is important because in our experience these highly localized (one to several centimeters) spatial pathways are good candidates for potentially significant CO2 leaks from deep underground formations. The detection and discrimination method we are developing uses primarily airborne hyperspectral, high spatial (3 meter) with 128 band wavelength resolution, visible and near infrared reflected light imagery. We also are using the newly available ''Quickbird'' satellite imagery that has high spatial resolution (0.6 meter for panchromatic images, 2.4 meters for multispectral). We have a commercial provider, HyVista Corp of Sydney Australia, of airborne hyperspectral imagery acquisitions and very relevant image data post processing, so that eventually the ongoing surveillance of CO2 storage fields can be contracted for commercially. In this project we have imaged the Rangely Colorado Oil field and surrounding areas with an airborne hyperspectral visible and near infrared reflected light sensor. The images were analyzed by several methods using the suite of tools available in the ENVI

  13. Hyperspectral and photogrammetric helicopter-based measurements over western Greenland

    NASA Astrophysics Data System (ADS)

    Tedesco, M.; Mote, T. L.; Smith, L. C.; Rennermalm, A. K.; Lampkin, D. J.

    2015-12-01

    We discuss the setup and results of an experiment aimed at collecting helicopter-based hyperspectral and photogrammetry measurements over the western Greenland ice sheet (GrIS) for studying the evolution of surface albedo and surface hydrological features. Data were collected during three days at the end of July 2015 concurrently with in-situ hydrological measurements of runoff and discharge of a supraglacial stream (Rio Behar) and along the K-transect up to an elevation of ~ 1500 m a.s.l. Hyperspectral measurements of incoming and outgoing radiation collected at a radiometric resolution of 10 nm were acquired in conjunction with geo-located images by means of a digital camera mounted on the same platform. Gyroscopes and 3-D accelerometers were also used to estimate the relative orientation of the sensors collecting the incoming and outgoing solar radiation. To our knowledge, despite their importance, it is the first time that such measurements have been collected over the Greenland ice sheet from an airborne platform. The sensors were installed inside a pod that was specifically modified for our purpose. The impact of the helicopter on the recorded incoming radiation was characterized by collecting measurements in the absence and presence of the helicopter when the rotors were either off or on. Moreover, the effect of the relative position of the helicopter with respect to the sun's position was also quantified by ad-hoc maneuvers during take off and landing with the helicopter spinning around the main rotor axis. The geo-referenced images collected by our instrument provide an unprecedented ground spatial resolution of ~ 6 cm, hence allowing us to study the spatial distribution of surface hydrological features, such as cryoconite holes, small order streams and cracks developing into larger moulins. Such images were also used to evaluate the application of RGB data to estimate streams and lakes surface area and depths. Our helicopter-based hyperspectral and

  14. Data correction techniques for the airborne large-aperture static image spectrometer based on image registration

    NASA Astrophysics Data System (ADS)

    Zhang, Geng; Shi, Dalian; Wang, Shuang; Yu, Tao; Hu, Bingliang

    2015-01-01

    We propose an approach to correct the data of the airborne large-aperture static image spectrometer (LASIS). LASIS is a kind of stationary interferometer which compromises flux output and device stability. It acquires a series of interferograms to reconstruct the hyperspectral image cube. Reconstruction precision of the airborne LASIS data suffers from the instability of the plane platform. Usually, changes of plane attitudes, such as yaws, pitches, and rolls, can be precisely measured by the inertial measurement unit. However, the along-track and across-track translation errors are difficult to measure precisely. To solve this problem, we propose a co-optimization approach to compute the translation errors between the interferograms using an image registration technique which helps to correct the interferograms with subpixel precision. To demonstrate the effectiveness of our approach, experiments are run on real airborne LASIS data and our results are compared with those of the state-of-the-art approaches.

  15. Using hyperspectral data in precision farming applications

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. Canopy Spectral Invariants. Part 2; Application to Classification of Forest Types from Hyperspectral Data

    NASA Technical Reports Server (NTRS)

    Schull, M. A.; Knyazikhin, Y.; Xu, L.; Samanta, A.; Carmona, P. L.; Lepine, L.; Jenkins, J. P.; Ganguly, S.; Myneni, R. B.

    2011-01-01

    Many studies have been conducted to demonstrate the ability of hyperspectral data to discriminate plant dominant species. Most of them have employed the use of empirically based techniques, which are site specific, requires some initial training based on characteristics of known leaf and/or canopy spectra and therefore may not be extendable to operational use or adapted to changing or unknown land cover. In this paper we propose a physically based approach for separation of dominant forest type using hyperspectral data. The radiative transfer theory of canopy spectral invariants underlies the approach, which facilitates parameterization of the canopy reflectance in terms of the leaf spectral scattering and two spectrally invariant and structurally varying variables - recollision and directional escape probabilities. The methodology is based on the idea of retrieving spectrally invariant parameters from hyperspectral data first, and then relating their values to structural characteristics of three-dimensional canopy structure. Theoretical and empirical analyses of ground and airborne data acquired by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over two sites in New England, USA, suggest that the canopy spectral invariants convey information about canopy structure at both the macro- and micro-scales. The total escape probability (one minus recollision probability) varies as a power function with the exponent related to the number of nested hierarchical levels present in the pixel. Its base is a geometrical mean of the local total escape probabilities and accounts for the cumulative effect of canopy structure over a wide range of scales. The ratio of the directional to the total escape probability becomes independent of the number of hierarchical levels and is a function of the canopy structure at the macro-scale such as tree spatial distribution, crown shape and size, within-crown foliage density and ground cover. These properties allow for the natural

  17. Uncooled long-wave infrared hyperspectral imaging

    NASA Technical Reports Server (NTRS)

    Lucey, Paul G. (Inventor)

    2006-01-01

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

  18. a New Control Points Based Geometric Correction Algorithm for Airborne Push Broom Scanner Images Without On-Board Data

    NASA Astrophysics Data System (ADS)

    Strakhov, P.; Badasen, E.; Shurygin, B.; Kondranin, T.

    2016-06-01

    Push broom scanners, such as video spectrometers (also called hyperspectral sensors), are widely used in the present. Usage of scanned images requires accurate geometric correction, which becomes complicated when imaging platform is airborne. This work contains detailed description of a new algorithm developed for processing of such images. The algorithm requires only user provided control points and is able to correct distortions caused by yaw, flight speed and height changes. It was tested on two series of airborne images and yielded RMS error values on the order of 7 meters (3-6 source image pixels) as compared to 13 meters for polynomial-based correction.

  19. Reflectance and fluorescence hyperspectral elastic image registration

    NASA Astrophysics Data System (ADS)

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

    2004-05-01

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

  20. Hyperspectral imaging of atherosclerotic plaques in vitro

    NASA Astrophysics Data System (ADS)

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

    2011-02-01

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

  1. Thermal characterization of a NIR hyperspectral camera

    NASA Astrophysics Data System (ADS)

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

    2011-11-01

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

  2. Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

    NASA Astrophysics Data System (ADS)

    Clark, M. L.; Kilham, N. E.

    2015-12-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

  3. Retrieval Lesson Learned from NAST-I Hyperspectral Data

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

  4. Development of Research Infrastructure in Nevada for the Exploitation of Hyperspectral Image Data to Address Proliferation and Detection of Chemical and Biological Materials.

    SciTech Connect

    James V. Taranik

    2007-12-31

    This research was to exploit hyperspectral reflectance imaging technology for the detection and mapping variability (clutter) of the natural background against which gases in the atmosphere are imaged. The natural background consists of landscape surface cover composed of consolidated rocks, unconsolidated rock weathering products, soils, coatings on rock materials, vegetation, water, materials constructed by humans, and mixtures of the above. Human made gases in the atmosphere may indicate industrial processes important to detecting non-nuclear chemical and biological proliferation. Our research was to exploit the Visible and Near-Infrared (NIR) and the Short-wave Infrared (SWIR) portions of the electromagnetic spectrum to determine the properties of solid materials on the earth’s surface that could influence the detection of gases in the Long-Wave Infrared (LWIR). We used some new experimental hyperspectral imaging technologies to collect data over the Non-Proliferation Test and Evaluation Center (NPTEC) located on the Nevada Test Site (NTS). The SpecTIR HyperSpecTIR (HST) and Specim Dual hyperspectral sensors were used to understand the variability in the imaged background (clutter), that detected, measured, identified and mapped with operational commercial hyperspectral techniques. The HST sensors were determined to be more experimental than operational because of problems with radiometric and atmospheric data correction. However the SpecTIR Dual system, developed by Specim in Finland, eventually was found to provide cost-effective hyperspectral image data collection and it was possible to correct the Dual system’s data for specific areas. Batch processing of long flightlines was still complex, and if comparison to laboratory spectra was desired, the Dual system data still had to be processed using the empirical line method. This research determined that 5-meter spatial resolution was adequate for mapping natural background variations. Furthermore, this

  5. A highly strained InAs/GaSb type II superlattice for LWIR detection

    NASA Astrophysics Data System (ADS)

    Chen, Yiqiao; Moy, Aaron; Mi, Kan; Lu, Wentao; Chow, Peter

    2013-09-01

    IR photo detectors are in high demand for various military and civilian applications, such as airborne surveillance, remote sensing, environmental monitoring, and spectrometry. Recently InAs/GaSb type II superlattice (T2SL) has attracted numerous R and D interest since SLS is the only IR material that has a theoretical prediction of higher performance than HgCdTe. Here we report the improvement of SL photo diodes through a new design with highly-strained type-II superlattice (HS-T2SL). The HS-T2SL consists of a highly compressively strained thick InSb layer at InAs/GaSb interfaces. The presence of coherent strain shifts the band edges such that the SL energy gap is reduced. This reduced band gap is advantageous to photodetectors because longer cut-off wavelengths can be obtained with reduced layer thickness in the strained SL. The highly compressive strain in HS-T2SL also leads to an even higher optical absorption coefficient and lower dark current. Applying this new design resistance-area product (R0A) is measured as high as 2.1 Ohm-cm2 at 85K for 14.8-μm-cutoff photo diodes without any dark current suppression barriers. The fabricated 14.5μm-cutoff photo diode shows Johnson-noiselimited peak detectivity of 8.4×1010 cmHz1/2/W at zero bias at 85K.

  6. Ecohydrological Characterization of a Floodplain Mire by Hyperspectral Remote Sensing

    NASA Astrophysics Data System (ADS)

    Batelaan, O.; Verbeiren, B.; Hung, L. Q.

    2010-12-01

    For the emerging field of ecohydrology it is essential to be able to estimate spatially distributed water and energy balances in different types of ecosystems. This information is a prerequisite for predicting the occurrence of vegetation species in dependence of site specific conditions. In this contribution the results of a field and airborne imaging spectroscopy campaign in the Doode Bemde floodplain mire (Belgium) are presented. Vegetation is characterized and water and energy balance components are estimated on a scale, which allows the discrimination of local wetness and vegetation heterogeneity in relation to differences in soil and vegetation condition. Among the common vegetation indices, the red-edge index proved to separate the phreatophytic vegetation types and showed to be linearly correlated with the maximum groundwater depth of the vegetation types. Since evapotranspiration is the largest component of the water and energy fluxes, we combine high resolution thermal airborne sensor data (ATM) with hyperspectral CASI imagery to enable derivation of ecological relevant observation of evapotranspiration at a resolution of 1-10 m. The evapotranspiration is simulated with the Surface Energy Balance Algorithm for Land (SEBAL). The estimated evapotranspiration values are statistically related to measured soil moisture conditions via the evaporative fraction. The evaporative fraction shows a non-linear relationship with soil moisture, and its level is dependent on the general wetness of the area. It appears feasible to map spatially detailed soil moisture on basis of estimation of the evaporative fraction. The results contribute to an increased understanding of the ecohydrological functioning of the study area.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. Research on hyperspectral dynamic infrared scene simulation technology

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  9. Wavelet compression techniques for hyperspectral data

    NASA Technical Reports Server (NTRS)

    Evans, Bruce; Ringer, Brian; Yeates, Mathew

    1994-01-01

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

  10. Airborne data acquisition techniques

    SciTech Connect

    Arro, A.A.

    1980-01-01

    The introduction of standards on acceptable procedures for assessing building heat loss has created a dilemma for the contractor performing airborne thermographic surveys. These standards impose specifications on instrumentation, data acquisition, recording, interpretation, and presentation. Under the standard, the contractor has both the obligation of compliance and the requirement of offering his services at a reasonable price. This paper discusses the various aspects of data acquisition for airborne thermographic surveys and various techniques to reduce the costs of this operation. These techniques include the calculation of flight parameters for economical data acquisition, the selection and use of maps for mission planning, and the use of meteorological forecasts for flight scheduling and the actual execution of the mission. The proper consideration of these factors will result in a cost effective data acquisition and will place the contractor in a very competitive position in offering airborne thermographic survey services.

  11. Prediction Metrics for Chemical Detection in Long-Wave Infrared Hyperspectral Imagery

    SciTech Connect

    Chilton, Marie C.; Walsh, Stephen J.; Daly, Don S.

    2009-01-29

    A natural or anthropogenic process often generates a signature gas plume whose chemical constituents may be identified using hyperspectral imagery. A hyperspectral image is a pixel-indexed set of spectra where each spectrum reflects the chemical constituents of the plume, the atmosphere, the bounding background surface, and instrument noise. This study explored the relationship between gas absorbance and background emissivity across the long-wave infrared (LWIR) spectrum and how they affect relative gas detection sensitivity. The physics-based model for the observed radiance shows that high gas absorbance coupled with low background emissivity at a single wavenumber results in a stronger recorded radiance. Two sensitivity measures were developed to predict relative probability of detection using chemical absorbance and background emissivity: one focused on a single wavenumber while another accounted for the entire spectrum. The predictive abilities of these measures were compared to synthetic image analysis. This study simulated images with 499 distinct gases at each of 6 concentrations over 6 different background surfaces with the atmosphere and level of instrument noise held constant. The Whitened Matched Filter was used to define gas detection from an image spectrum. The estimate of a chemical’s probability of detection at a given concentration over a specific background was the proportion of detections in 500 trials. Of the 499 chemicals used in the images, 276 had estimated probabilities of detection below 0.2 across all backgrounds and concentrations; these chemicals were removed from the study. For 92.8 percent of the remaining chemicals, the single channel measure correctly predicted the background over which the chemical had the largest relative probability of detection. Further, the measure which accounted for information across all wavenumbers predicted the background over which the chemical had the largest relative probability of detection for 93

  12. Performance portability study of an automatic target detection and classification algorithm for hyperspectral image analysis using OpenCL

    NASA Astrophysics Data System (ADS)

    Bernabe, Sergio; Igual, Francisco D.; Botella, Guillermo; Garcia, Carlos; Prieto-Matias, Manuel; Plaza, Antonio

    2015-10-01

    Recent advances in heterogeneous high performance computing (HPC) have opened new avenues for demanding remote sensing applications. Perhaps one of the most popular algorithm in target detection and identification is the automatic target detection and classification algorithm (ATDCA) widely used in the hyperspectral image analysis community. Previous research has already investigated the mapping of ATDCA on graphics processing units (GPUs) and field programmable gate arrays (FPGAs), showing impressive speedup factors that allow its exploitation in time-critical scenarios. Based on these studies, our work explores the performance portability of a tuned OpenCL implementation across a range of processing devices including multicore processors, GPUs and other accelerators. This approach differs from previous papers, which focused on achieving the optimal performance on each platform. Here, we are more interested in the following issues: (1) evaluating if a single code written in OpenCL allows us to achieve acceptable performance across all of them, and (2) assessing the gap between our portable OpenCL code and those hand-tuned versions previously investigated. Our study includes the analysis of different tuning techniques that expose data parallelism as well as enable an efficient exploitation of the complex memory hierarchies found in these new heterogeneous devices. Experiments have been conducted using hyperspectral data sets collected by NASA's Airborne Visible Infra- red Imaging Spectrometer (AVIRIS) and the Hyperspectral Digital Imagery Collection Experiment (HYDICE) sensors. To the best of our knowledge, this kind of analysis has not been previously conducted in the hyperspectral imaging processing literature, and in our opinion it is very important in order to really calibrate the possibility of using heterogeneous platforms for efficient hyperspectral imaging processing in real remote sensing missions.

  13. An algorithm for hyperspectral remote sensing of aerosols: theoretical framework, information content analysis and application to GEO-TASO

    NASA Astrophysics Data System (ADS)

    Hou, W.; Wang, J.; Xu, X.; Leitch, J. W.; Delker, T.; Chen, G.

    2015-12-01

    This paper includes a series of studies that aim to develop a hyperspectral remote sensing technique for retrieving aerosol properties from a newly developed instrument GEO-TASO (Geostationary Trance gas and Aerosol Sensor Optimization) that measures the radiation at 0.4-0.7 wavelengths at spectral resolution of 0.02 nm. GEOS-TASO instrument is a prototype instrument of TEMPO (Tropospheric Emissions: Monitoring of Pollution), which will be launched in 2022 to measure aerosols, O3, and other trace gases from a geostationary orbit over the N-America. The theoretical framework of optimized inversion algorithm and the information content analysis such as degree of freedom for signal (DFS) will be discussed for hyperspectral remote sensing in visible bands, as well as the application to GEO-TASO, which has mounted on the NASA HU-25C aircraft and gathered several days' of airborne hyperspectral data for our studies. Based on the optimization theory and different from the traditional lookup table (LUT) retrieval technique, our inversion method intends to retrieve the aerosol parameters and surface reflectance simultaneously, in which UNL-VRTM (UNified Linearized Radiative Transfer Model) is employed for forward model and Jacobians calculation, meanwhile, principal component analysis (PCA) is used to constrain the hyperspectral surface reflectance.The information content analysis provides the theoretical analysis guidance about what kind of aerosol parameters could be retrieved from GeoTASO hyperspectral remote sensing to the practical inversion study. Besides, the inversion conducted iteratively until the modeled spectral radiance fits with GeoTASO measurements by a Quasi-Newton method called L-BFGS-B (Large scale BFGS Bound constrained). Finally, the retrieval results of aerosol optical depth and other aerosol parameters are compared against those retrieved by AEROENT and/or in situ measurements such as DISCOVER-AQ during the aircraft campaign.

  14. Airborne oceanographic lidar system

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Specifications and preliminary design of an Airborne Oceanographic Lidar (AOL) system, which is to be constructed for installation and used on a NASA Wallops Flight Center (WFC) C-54 research aircraft, are reported. The AOL system is to provide an airborne facility for use by various government agencies to demonstrate the utility and practicality of hardware of this type in the wide area collection of oceanographic data on an operational basis. System measurement and performance requirements are presented, followed by a description of the conceptual system approach and the considerations attendant to its development. System performance calculations are addressed, and the system specifications and preliminary design are presented and discussed.

  15. Airborne rain mapping radar

    NASA Technical Reports Server (NTRS)

    Wilson, W. J.; Parks, G. S.; Li, F. K.; Im, K. E.; Howard, R. J.

    1988-01-01

    An airborne scanning radar system for remote rain mapping is described. The airborne rain mapping radar is composed of two radar frequency channels at 13.8 and 24.1 GHz. The radar is proposed to scan its antenna beam over + or - 20 deg from the antenna boresight; have a swath width of 7 km; a horizontal spatial resolution at nadir of about 500 m; and a range resolution of 120 m. The radar is designed to be applicable for retrieving rainfall rates from 0.1-60 mm/hr at the earth's surface, and for measuring linear polarization signatures and raindrop's fall velocity.

  16. NASA Airborne Lidar July 1991

    Atmospheric Science Data Center

    2016-05-26

    NASA Airborne Lidar July 1991 Data from the 1991 NASA Langley Airborne Lidar flights following the eruption of Pinatubo in July ... and Osborn [1992a, 1992b]. Project Title:  NASA Airborne Lidar Discipline:  Field Campaigns ...

  17. NASA Airborne Lidar May 1992

    Atmospheric Science Data Center

    2016-05-26

    NASA Airborne Lidar May 1992 An airborne Nd:YAG (532 nm) lidar was operated by the NASA Langley Research Center about a year following the June 1991 eruption of ... Osborn [1992a, 1992b].  Project Title:  NASA Airborne Lidar Discipline:  Field Campaigns ...

  18. Hyperspectral MIVIS data to investigate the Lilybaeum (Marsala) Archaeological Park

    NASA Astrophysics Data System (ADS)

    Merola, P.; Allegrini, A.; Bajocco, S.

    2005-10-01

    In the last 20 years air photograph and remote sensing, both from airplane and satellite, allowed to gain, from the analysis of the superficial land unit characteristics, useful information for the location of buried archaeological structures. For this kind of investigation, hyperspectral MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) data revealed to be very useful, for example, since 1994, for the purpose CNR-LARA research project, many archaeological studies have been supported by MIVIS data on several italian archaeological sites: Selinunte, Arpi (Foggia), Villa Adriana (Tivoli) and Marsala. Marsala town, the ancient Lilybaeum, lies on the western coastline of Sicily, at about 30 km south of Trapani. Founded by the Phoenicians, it intensely lived during the Punic, Roman, Arab and Norman periods, whose dominations left many important remains. This archaeological area was investigated by means of several techniques, such as excavations, topographic studies based on airborne campaigns, etc. On this site the main archaeological information were provided by the analysis of the VIS-NIR spectral bands and by Thermal Capacity image.

  19. Shallow water substrate mapping using hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    Fearns, P. R. C.; Klonowski, W.; Babcock, R. C.; England, P.; Phillips, J.

    2011-08-01

    During April 2004 the airborne hyperspectral sensor, HyMap, collected data over a shallow coastal region of Western Australia. These data were processed by inversion of a semi-analytical shallow water optical model to classify the substrate. Inputs to the optical model include water column constituent specific inherent optical properties (SIOPs), view and illumination geometry, surface condition (based on wind speed) and normalised reflectance spectra of substrate types. A sub-scene of the HyMap data covering approximately 4 km 2 was processed such that each 3×3 m 2 pixel was classed as sand, seagrass, brown algae or various mixtures of these three components. Coincident video data were collected and used to estimate substrate types. We present comparisons of the habitat classifications determined by these two methods and show that the percentage validation of the remotely sensed habitat map may be optimised by selection of appropriate optical model parameters. The optical model was able to retrieve classes for approximately 80% of all pixels in the scene, with validation percentages of approximately 50% for sand and seagrass classification, and 90% for brown algae classification. The semi-analytical model inversion approach to classification can be expected to be applied to any shallow water region where substrate reflectance spectra and SIOPs are known or can be inferred.

  20. Quantifying structural physical habitat attributes using LIDAR and hyperspectral imagery.

    PubMed

    Hall, Robert K; Watkins, Russell L; Heggem, Daniel T; Jones, K Bruce; Kaufmann, Philip R; Moore, Steven B; Gregory, Sandra J

    2009-12-01

    Structural physical habitat attributes include indices of stream size, channel gradient, substrate size, habitat complexity, and riparian vegetation cover and structure. The Environmental Monitoring and Assessment Program (EMAP) is designed to assess the status and trends of ecological resources at different scales. High-resolution remote sensing provides unique capabilities in detecting a variety of features and indicators of environmental health and condition. LIDAR is an airborne scanning laser system that provides data on topography, channel dimensions (width, depth), slope, channel complexity (residual pools, volume, morphometric complexity, hydraulic roughness), riparian vegetation (height and density), dimensions of riparian zone, anthropogenic alterations and disturbances, and channel and riparian interaction. Hyperspectral aerial imagery offers the advantage of high spectral and spatial resolution allowing for the detection and identification of riparian vegetation and natural and anthropogenic features at a resolution not possible with satellite imagery. When combined, or fused, these technologies comprise a powerful geospatial data set for assessing and monitoring lentic and lotic environmental characteristics and condition. PMID:19165614

  1. MEMS FPI-based smartphone hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Rissanen, Anna; Saari, Heikki; Rainio, Kari; Stuns, Ingmar; Viherkanto, Kai; Holmlund, Christer; Näkki, Ismo; Ojanen, Harri

    2016-05-01

    This paper demonstrates a mobile phone- compatible hyperspectral imager based on a tunable MEMS Fabry-Perot interferometer. The realized iPhone 5s hyperspectral imager (HSI) demonstrator utilizes MEMS FPI tunable filter for visible-range, which consist of atomic layer deposited (ALD) Al2O3/TiO2-thin film Bragg reflectors. Characterization results for the mobile phone hyperspectral imager utilizing MEMS FPI chip optimized for 500 nm is presented; the operation range is λ = 450 - 550 nm with FWHM between 8 - 15 nm. Also a configuration of two cascaded FPIs (λ = 500 nm and λ = 650 nm) combined with an RGB colour camera is presented. With this tandem configuration, the overall wavelength tuning range of MEMS hyperspectral imagers can be extended to cover a larger range than with a single FPI chip. The potential applications of mobile hyperspectral imagers in the vis-NIR range include authentication, counterfeit detection and potential health/wellness and food sensing applications.

  2. Portable Hyperspectral Imaging Broadens Sensing Horizons

    NASA Technical Reports Server (NTRS)

    2007-01-01

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

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

    PubMed

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

    2011-12-01

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

  4. Novel hyperspectral imager for lightweight UAVs

    NASA Astrophysics Data System (ADS)

    Saari, Heikki; Aallos, Ville-Veikko; Holmlund, Christer; Mäkynen, Jussi; Delauré, Bavo; Nackaerts, Kris; Michiels, Bart

    2010-04-01

    VTT Technical Research Centre of Finland has developed a new miniaturized staring hyperspectral imager with a weight of 350 g making the system compatible with lightweight UAS platforms. The instrument is able to record 2D spatial images at the selected wavelength bands simultaneously. The concept of the hyperspectral imager has been published in the SPIE Proc. 74741. The operational wavelength range of the imager can be tuned in the range 400 - 1100 nm and spectral resolution is in the range 5 - 10 nm @ FWHM. Presently the spatial resolution is 480 × 750 pixels but it can be increased simply by changing the image sensor. The field of view of the system is 20 × 30 degrees and ground pixel size at 100 m flying altitude is around 7.5 cm. The system contains batteries, image acquisition control system and memory for the image data. It can operate autonomously recording hyperspectral data cubes continuously or controlled by the autopilot system of the UAS. The new hyperspectral imager prototype was first tried in co-operation with the Flemish Institute for Technological Research (VITO) on their UAS helicopter. The instrument was configured for the spectral range 500 - 900 nm selected for the vegetation and natural water monitoring applications. The design of the UAS hyperspectral imager and its characterization results together with the analysis of the spectral data from first test flights will be presented.

  5. Aerosol optical retrieval and surface reflectance from airborne remote sensing data over land.

    PubMed

    Bassani, Cristiana; Cavalli, Rosa Maria; Pignatti, Stefano

    2010-01-01

    Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550 nm (τ(550)) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ(550) with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ(550) and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ(550) retrieved by Module A (r(2) = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r(2) ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness. PMID:22163558

  6. Assessing canopy PRI from airborne imagery to map water stress in maize

    NASA Astrophysics Data System (ADS)

    Rossini, M.; Fava, F.; Cogliati, S.; Meroni, M.; Marchesi, A.; Panigada, C.; Giardino, C.; Busetto, L.; Migliavacca, M.; Amaducci, S.; Colombo, R.

    2013-12-01

    This paper presents a method for mapping water stress in a maize field using hyperspectral remote sensing imagery. An airborne survey using AISA (Specim, Finland) was performed in July 2008 over an experimental farm in Italy. Hyperspectral data were acquired over a maize field with three different irrigation regimes. An intensive field campaign was also conducted concurrently with imagery acquisition to measure relative leaf water content (RWC), active chlorophyll fluorescence (ΔF/Fm‧), leaf temperature (Tl) and Leaf Area Index (LAI). The analysis of the field data showed that at the time of the airborne overpass the maize plots with irrigation deficits were experiencing a moderate water stress, affecting the plant physiological status (ΔF/Fm‧, difference between Tl and air temperature (Tair), and RWC) but not the canopy structure (LAI). Among the different Vegetation Indices (VIs) computed from the airborne imagery the Photochemical Reflectance Index computed using the reflectance at 570 nm as the reference band (PRI570) showed the strongest relationships with ΔF/Fm‧ (r2 = 0.76), Tl - Tair (r2 = 0.82) and RWC (r2 = 0.64) and the red-edge Chlorophyll Index (CIred-edge) with LAI (r2 = 0.64). Thus PRI has been proven to be related to water stress at early stages, before structural changes occurred.

  7. Airborne multisensor pod system (AMPS) data: Multispectral data integration and processing hints

    SciTech Connect

    Leary, T.J.; Lamb, A.

    1996-11-01

    The Department of Energy`s Office of Arms Control and Non-Proliferation (NN-20) has developed a suite of airborne remote sensing systems that simultaneously collect coincident data from a US Navy P-3 aircraft. The primary objective of the Airborne Multisensor Pod System (AMPS) Program is {open_quotes}to collect multisensor data that can be used for data research, both to reduce interpretation problems associated with data overload and to develop information products more complete than can be obtained from any single sensor.{close_quotes} The sensors are housed in wing-mounted pods and include: a Ku-Band Synthetic Aperture Radar; a CASI Hyperspectral Imager; a Daedalus 3600 Airborne Multispectral Scanner; a Wild Heerbrugg RC-30 motion compensated large format camera; various high resolution, light intensified and thermal video cameras; and several experimental sensors (e.g. the Portable Hyperspectral Imager of Low-Light Spectroscopy (PHILLS)). Over the past year or so, the Coastal Marine Resource Assessment (CAMRA) group at the Florida Department of Environmental Protection`s Marine Research Institute (FMRI) has been working with the Department of Energy through the Naval Research Laboratory to develop applications and products from existing data. Considerable effort has been spent identifying image formats integration parameters. 2 refs., 3 figs., 2 tabs.

  8. Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land

    PubMed Central

    Bassani, Cristiana; Cavalli, Rosa Maria; Pignatti, Stefano

    2010-01-01

    Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550nm (τ550) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ550 with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ550 and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ550 retrieved by Module A (r2 = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r2 ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness. PMID:22163558

  9. Military applications of hyperspectral imagery

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

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

  10. Airborne Fraunhofer Line Discriminator

    NASA Technical Reports Server (NTRS)

    Gabriel, F. C.; Markle, D. A.

    1969-01-01

    Airborne Fraunhofer Line Discriminator enables prospecting for fluorescent materials, hydrography with fluorescent dyes, and plant studies based on fluorescence of chlorophyll. Optical unit design is the coincidence of Fraunhofer lines in the solar spectrum occurring at the characteristic wavelengths of some fluorescent materials.

  11. Recognizing Airborne Hazards.

    ERIC Educational Resources Information Center

    Schneider, Christian M.

    1990-01-01

    The heating, ventilating, and air conditioning (HVAC) systems in older buildings often do not adequately handle air-borne contaminants. Outlines a three-stage Indoor Air Quality (IAQ) assessment and describes a case in point at a Pittsburgh, Pennsylvania, school. (MLF)

  12. Airborne asbestos in buildings.

    PubMed

    Lee, R J; Van Orden, D R

    2008-03-01

    The concentration of airborne asbestos in buildings nationwide is reported in this study. A total of 3978 indoor samples from 752 buildings, representing nearly 32 man-years of sampling, have been analyzed by transmission electron microscopy. The buildings that were surveyed were the subject of litigation related to suits alleging the general building occupants were exposed to a potential health hazard as a result the presence of asbestos-containing materials (ACM). The average concentration of all airborne asbestos structures was 0.01structures/ml (s/ml) and the average concentration of airborne asbestos > or = 5microm long was 0.00012fibers/ml (f/ml). For all samples, 99.9% of the samples were <0.01 f/ml for fibers longer than 5microm; no building averaged above 0.004f/ml for fibers longer than 5microm. No asbestos was detected in 27% of the buildings and in 90% of the buildings no asbestos was detected that would have been seen optically (> or = 5microm long and > or = 0.25microm wide). Background outdoor concentrations have been reported at 0.0003f/ml > or = 5microm. These results indicate that in-place ACM does not result in elevated airborne asbestos in building atmospheres approaching regulatory levels and that it does not result in a significantly increased risk to building occupants.

  13. Feasibility Study of Radiometry for Airborne Detection of Aviation Hazards

    NASA Technical Reports Server (NTRS)

    Gimmestad, Gary G.; Papanicolopoulos, Chris D.; Richards, Mark A.; Sherman, Donald L.; West, Leanne L.; Johnson, James W. (Technical Monitor)

    2001-01-01

    Radiometric sensors for aviation hazards have the potential for widespread and inexpensive deployment on aircraft. This report contains discussions of three aviation hazards - icing, turbulence, and volcanic ash - as well as candidate radiometric detection techniques for each hazard. Dual-polarization microwave radiometry is the only viable radiometric technique for detection of icing conditions, but more research will be required to assess its usefulness to the aviation community. Passive infrared techniques are being developed for detection of turbulence and volcanic ash by researchers in this country and also in Australia. Further investigation of the infrared airborne radiometric hazard detection approaches will also be required in order to develop reliable detection/discrimination techniques. This report includes a description of a commercial hyperspectral imager for investigating the infrared detection techniques for turbulence and volcanic ash.

  14. Airborne imagery of a disintegrating Sargassum drift line

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

    Airborne hyperspectral and thermal infrared imagery collected over the Florida Current provide a view of the disintegration of a Sargassum drift line in 5 m s -1 winds. The drift line consists mostly of rafts 20-80 m 2 in size, though aggregations larger than 1000 m 2 also occur. Rafts tend to be elongated, curved in the upwind direction, and 0.1-0.5 °C warmer than the surrounding ocean surface. Long weed 'trails' extending upwind from the rafts are evidence of plants dropping out and being left behind more rapidly drifting rafts. The raft line may be a remnant of an earlier Sargassum frontal band, which is detectible as an upwind thermal front and areas of submerged weed. Issues are identified that require future field measurements.

  15. International Symposium on Airborne Geophysics

    NASA Astrophysics Data System (ADS)

    Mogi, Toru; Ito, Hisatoshi; Kaieda, Hideshi; Kusunoki, Kenichiro; Saltus, Richard W.; Fitterman, David V.; Okuma, Shigeo; Nakatsuka, Tadashi

    2006-05-01

    Airborne geophysics can be defined as the measurement of Earth properties from sensors in the sky. The airborne measurement platform is usually a traditional fixed-wing airplane or helicopter, but could also include lighter-than-air craft, unmanned drones, or other specialty craft. The earliest history of airborne geophysics includes kite and hot-air balloon experiments. However, modern airborne geophysics dates from the mid-1940s when military submarine-hunting magnetometers were first used to map variations in the Earth's magnetic field. The current gamut of airborne geophysical techniques spans a broad range, including potential fields (both gravity and magnetics), electromagnetics (EM), radiometrics, spectral imaging, and thermal imaging.

  16. Hyperspectral vital sign signal analysis for medical data

    NASA Astrophysics Data System (ADS)

    Gao, Cheng; Li, Yao; Li, Hsiao-Chi; Chang, Chein-I.; Hu, Peter; Mackenzie, Colin

    2015-05-01

    This paper develops a completely new technology,) from a hyperspectral imaging perspective, called Hyperspectral Vital Sign Signal Analysis (HyVSSA. A hyperspectral image is generally acquired by hundreds of contiguous spectral bands, each of which is an optical sensor specified by a particular wavelength. In medical application, we can consider a patient with different vital sign signals as a pixel vector in hyperspectral image and each vital sign signal as a particular band. In light of this interpretation, a revolutionary concept is developed, which translates medical data to hyperspectral data in such a way that hyperspectral technology can be readily applied to medical data analysis. One of most useful techniques in hyperspectral data processing is, Anomaly Detection (AD) which in this medical application is used to predict outcomes such as transfusion, length of stay (LOS) and mortality using various vital signs. This study compared transfusion prediction performance of Anomaly Detection (AD) and Logistic Regression (LR).

  17. Hyperspectral and broadband FLIR data fusion

    NASA Astrophysics Data System (ADS)

    Nicholas, Mike; James, Matt; Nothard, Jo

    2005-10-01

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

  18. Real-time snapshot hyperspectral imaging endoscope.

    PubMed

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

    2011-05-01

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

  19. Photoreactivation in Airborne Mycobacterium parafortuitum

    PubMed Central

    Peccia, Jordan; Hernandez, Mark

    2001-01-01

    Photoreactivation was observed in airborne Mycobacterium parafortuitum exposed concurrently to UV radiation (254 nm) and visible light. Photoreactivation rates of airborne cells increased with increasing relative humidity (RH) and decreased with increasing UV dose. Under a constant UV dose with visible light absent, the UV inactivation rate of airborne M. parafortuitum cells decreased by a factor of 4 as RH increased from 40 to 95%; however, under identical conditions with visible light present, the UV inactivation rate of airborne cells decreased only by a factor of 2. When irradiated in the absence of visible light, cellular cyclobutane thymine dimer content of UV-irradiated airborne M. parafortuitum and Serratia marcescens increased in response to RH increases. Results suggest that, unlike in waterborne bacteria, cyclobutane thymine dimers are not the most significant form of UV-induced DNA damage incurred by airborne bacteria and that the distribution of DNA photoproducts incorporated into UV-irradiated airborne cells is a function of RH. PMID:11526027

  20. Concept of an advanced hyperspectral remote sensing system for pipeline monitoring

    NASA Astrophysics Data System (ADS)

    Keskin, Göksu; Teutsch, Caroline D.; Lenz, Andreas; Middelmann, Wolfgang

    2015-10-01

    Areas occupied by oil pipelines and storage facilities are prone to severe contamination due to leaks caused by natural forces, poor maintenance or third parties. These threats have to be detected as quickly as possible in order to prevent serious environmental damage. Periodical and emergency monitoring activities need to be carried out for successful disaster management and pollution minimization. Airborne remote sensing stands out as an appropriate choice to operate either in an emergency or periodically. Hydrocarbon Index (HI) and Hydrocarbon Detection Index (HDI) utilize the unique absorption features of hydrocarbon based materials at SWIR spectral region. These band ratio based methods require no a priori knowledge of the reference spectrum and can be calculated in real time. This work introduces a flexible airborne pipeline monitoring system based on the online quasi-operational hyperspectral remote sensing system developed at Fraunhofer IOSB, utilizing HI and HDI for oil leak detection on the data acquired by an SWIR imaging sensor. Robustness of HI and HDI compared to state of the art detection algorithms is evaluated in an experimental setup using a synthetic dataset, which was prepared in a systematic way to simulate linear mixtures of selected background and oil spectra consisting of gradually decreasing percentages of oil content. Real airborne measurements in Ettlingen, Germany are used to gather background data while the crude oil spectrum was measured with a field spectrometer. The results indicate that the system can be utilized for online and offline monitoring activities.

  1. A manifold learning approach to target detection in high-resolution hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Ziemann, Amanda K.

    Imagery collected from airborne platforms and satellites provide an important medium for remotely analyzing the content in a scene. In particular, the ability to detect a specific material within a scene is of high importance to both civilian and defense applications. This may include identifying "targets" such as vehicles, buildings, or boats. Sensors that process hyperspectral images provide the high-dimensional spectral information necessary to perform such analyses. However, for a d-dimensional hyperspectral image, it is typical for the data to inherently occupy an m-dimensional space, with m << d. In the remote sensing community, this has led to a recent increase in the use of manifold learning, which aims to characterize the embedded lower-dimensional, non-linear manifold upon which the hyperspectral data inherently lie. Classic hyperspectral data models include statistical, linear subspace, and linear mixture models, but these can place restrictive assumptions on the distribution of the data; this is particularly true when implementing traditional target detection approaches, and the limitations of these models are well-documented. With manifold learning based approaches, the only assumption is that the data reside on an underlying manifold that can be discretely modeled by a graph. The research presented here focuses on the use of graph theory and manifold learning in hyperspectral imagery. Early work explored various graph-building techniques with application to the background model of the Topological Anomaly Detection (TAD) algorithm, which is a graph theory based approach to anomaly detection. This led towards a focus on target detection, and in the development of a specific graph-based model of the data and subsequent dimensionality reduction using manifold learning. An adaptive graph is built on the data, and then used to implement an adaptive version of locally linear embedding (LLE). We artificially induce a target manifold and incorporate it into

  2. Dynamical Spectral Unmixing of Multitemporal Hyperspectral Images

    NASA Astrophysics Data System (ADS)

    Henrot, Simon; Chanussot, Jocelyn; Jutten, Christian

    2016-07-01

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

  3. Hyperspectral Thermal Emission Spectrometer: Engineering Flight Campaign

    NASA Technical Reports Server (NTRS)

    Johnson, William R.; Hook, Simon J.; Shoen, Steven S.; Eng, Bjorn T.

    2013-01-01

    The Hyperspectral Thermal Emission Spectrometer (HyTES) successfully completed its first set of engineering test flights. HyTES was developed in support of the Hyperspectral Infrared Imager (HyspIRI). HyspIRI is one of the Tier II Decadal Survey missions. HyTES currently provides both high spectral resolution (17 nm) and high spatial resolution (2-5m) data in the thermal infrared (7.5-12 micron) part of the electromagnetic spectrum. HyTES data will be used to help determine the optimum band positions for the HyspIRI Thermal Infrared (TIR) sensor and provide antecedent data for HyspIRI related studies.

  4. 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

  5. Remotely Measured Terrestrial Chlorophyll Fluorescence Using Airborne G-LiHT and APFS Sensors

    NASA Astrophysics Data System (ADS)

    Cook, W. B.; Yee, J. H.; Corp, L. A.; Cook, B. D.; Huemmrich, K. F.

    2014-12-01

    In September 2014 the Goddard Lidar, Hyperspectral and Thermal (G-LiHT) and the APL/JHU Airborne Plant Fluorescence Sensor (APFS) were flown together on a NASA Langley King Air over vegetated targets in North Carolina and Virginia. The instruments provided high spatial and spectral resolution data in the visible and near infrared, down-welling irradiance, elevation maps, and thermal imagery. Ground validation data was also collected concurrently. Here we report the results of these measurements and show the feasibility of using these types of instruments for collection the fluorescence and other information essential for ecological and carbon cycle studies.

  6. VNIR, MWIR, and LWIR source assemblies for optical quality testing and spectro-radiometric calibration of earth observation satellites

    NASA Astrophysics Data System (ADS)

    Compain, Eric; Maquet, Philippe; Leblay, Pierrick; Gavaud, Eric; Marque, Julien; Glastre, Wilfried; Cortese, Maxime; Sugranes, Pierre; Gaillac, Stephanie; Potheau, Hervé

    2015-09-01

    This document presents several original OGSEs, Optical Ground Support Equipment, specifically designed and realized for the optical testing and calibration of earth observation satellites operating in a large spectral band from 0.4μm to 14.7μm. This work has been mainly supported by recent development dedicated to MTG, Meteosat Third Generation, the ESA next generation of meteorological satellites. The improved measurement capabilities of this new satellite generation has generated new challenging requirements for the associated optical test equipments. These improvements, based on design and component innovation will be illustrated for the MOTA, the GICS and the DEA OGSEs. MOTA and GICS are dedicated to the AIT, Assembly Integration and Test, of FCI, the Flexible Combined Imager of the imaging satellite MTG-I. DEA OGSE is dedicated to the AIT of the DEA, Detection Electronics Assembly, which is part of IRS instrument, an IR sounder part of MTG-S satellite. From an architectural point of view, the presented original designs enable to run many optical tests with a single system thanks to a limited configuration effort. Main measurement capabilities are optical quality testing (MTF based mainly on KEF measurement), Line of Sight (LoS) stability measurement, straylight analyses, VNIR-MWIR-LWIR focal plane array co-registration, and broadband large dynamic spectro-radiometric calibration. Depending on the AIT phase of the satellite, these source assemblies are operated at atmospheric pressure or under secondary vacuum. In operation, they are associated with an opto-mechanical projection system that enables to conjugate the image of the source assembly with the focal plane of the satellite instruments. These conjugation systems are usually based on high resolution, broadband collimator, and are optionally mounted on hexapod to address the entire field of instruments.

  7. [Air-borne disease].

    PubMed

    Lameiro Vilariño, Carmen; del Campo Pérez, Victor M; Alonso Bürger, Susana; Felpeto Nodar, Irene; Guimarey Pérez, Rosa; Pérez Alvarellos, Alberto

    2003-11-01

    Respiratory protection is a factor which worries nursing professionals who take care of patients susceptible of transmitting microorganisms through the air more as every day passes. This type of protection covers the use of surgical or hygienic masks against the transmission of infection by airborne drops to the use of highly effective masks or respirators against the transmission of airborne diseases such as tuberculosis or SARS, a recently discovered disease. The adequate choice of this protective device and its correct use are fundamental in order to have an effective protection for exposed personnel. The authors summarize the main protective respiratory devices used by health workers, their characteristics and degree of effectiveness, as well as the circumstances under which each device is indicated for use. PMID:14705591

  8. Thermal infrared hyperspectral imaging from vehicle-carried instrumentation

    NASA Astrophysics Data System (ADS)

    Kirkland, Laurel E.; Herr, Kenneth C.; Adams, Paul M.; McAfee, John; Salisbury, John

    2002-09-01

    Stand-off identification in the field using thermal infrared spectrometers (hyperspectral) is a maturing technique for gases and aerosols. However, capabilities to identify solid-phase materials on the surface lag substantially, particularly for identification in the field without benefit of ground truth (e.g. for "denied areas"). Spectral signatures of solid phase materials vary in complex and non-intuitive ways, including non-linear variations with surface texture, particle size, and intimate mixing. Also, in contrast to airborne or satellite measurements, reflected downwelling radiance strongly affects the signature measured by field spectrometers. These complex issues can confound interpretations or cause a misidentification in the field. Problems that remain particularly obstinate are (1) low ambiguity identification when there is no accompanying ground truth (e.g. measurements of denied areas, or Mars surface by the 2003 Mars lander spectrometer); (2) real- or near real-time identification, especially when a low ambiguity answer is critical; (3) identification of intimate mixtures (e.g. two fine powders mixed together) and targets composed of very small particles (e.g. aerosol fallout dust, some tailings); and (4) identification of non-diffuse targets (e.g. smooth coatings such as paint and desert varnish), particularly when measured at a high emission angle. In most studies that focus on gas phase targets or specific manmade targets, the solid phase background signatures are called "clutter" and are thrown out. Here we discuss our field spectrometer images measured of test targets that were selected to include a range of particle sizes, diffuse, non-diffuse, high, and low reflectance materials. This study was designed to identify and improve understanding of the issues that complicate stand-off identification in the field, with a focus on developing identification capabilities to proceed without benefit of ground truth. This information allows both improved

  9. Nonnegative Matrix Factorization for Efficient Hyperspectral Image Projection

    NASA Technical Reports Server (NTRS)

    Iacchetta, Alexander S.; Fienup, James R.; Leisawitz, David T.; Bolcar, Matthew R.

    2015-01-01

    Hyperspectral imaging for remote sensing has prompted development of hyperspectral image projectors that can be used to characterize hyperspectral imaging cameras and techniques in the lab. One such emerging astronomical hyperspectral imaging technique is wide-field double-Fourier interferometry. NASA's current, state-of-the-art, Wide-field Imaging Interferometry Testbed (WIIT) uses a Calibrated Hyperspectral Image Projector (CHIP) to generate test scenes and provide a more complete understanding of wide-field double-Fourier interferometry. Given enough time, the CHIP is capable of projecting scenes with astronomically realistic spatial and spectral complexity. However, this would require a very lengthy data collection process. For accurate but time-efficient projection of complicated hyperspectral images with the CHIP, the field must be decomposed both spectrally and spatially in a way that provides a favorable trade-off between accurately projecting the hyperspectral image and the time required for data collection. We apply nonnegative matrix factorization (NMF) to decompose hyperspectral astronomical datacubes into eigenspectra and eigenimages that allow time-efficient projection with the CHIP. Included is a brief analysis of NMF parameters that affect accuracy, including the number of eigenspectra and eigenimages used to approximate the hyperspectral image to be projected. For the chosen field, the normalized mean squared synthesis error is under 0.01 with just 8 eigenspectra. NMF of hyperspectral astronomical fields better utilizes the CHIP's capabilities, providing time-efficient and accurate representations of astronomical scenes to be imaged with the WIIT.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  11. SKYWARD: the next generation airborne infrared search and track

    NASA Astrophysics Data System (ADS)

    Fortunato, L.; Colombi, G.; Ondini, A.; Quaranta, C.; Giunti, C.; Sozzi, B.; Balzarotti, G.

    2016-05-01

    Infrared Search and Track systems are an essential element of the modern and future combat aircrafts. Passive automatic search, detection and tracking functions, are key points for silent operations or jammed tactical scenarios. SKYWARD represents the latest evolution of IRST technology in which high quality electro-optical components, advanced algorithms, efficient hardware and software solutions are harmonically integrated to provide high-end affordable performances. Additionally, the reduction of critical opto-mechanical elements optimises weight and volume and increases the overall reliability. Multiple operative modes dedicated to different situations are available; many options can be selected among multiple or single target tracking, for surveillance or engagement, and imaging, for landing or navigation aid, assuring the maximum system flexibility. The high quality 2D-IR sensor is exploited by multiple parallel processing chains, based on linear and non-linear techniques, to extract the possible targets from background, in different conditions, with false alarm rate control. A widely tested track processor manages a large amount of candidate targets simultaneously and allows discriminating real targets from noise whilst operating with low target to background contrasts. The capability of providing reliable passive range estimation is an additional qualifying element of the system. Particular care has been dedicated to the detector non-uniformities, a possible limiting factor for distant targets detection, as well as to the design of the electro-optics for a harsh airborne environment. The system can be configured for LWIR or MWIR waveband according to the customer operational requirements. An embedded data recorder saves all the necessary images and data for mission debriefing, particularly useful during inflight system integration and tuning.

  12. MLS airborne antenna research

    NASA Technical Reports Server (NTRS)

    Yu, C. L.; Burnside, W. D.

    1975-01-01

    The geometrical theory of diffraction was used to analyze the elevation plane pattern of on-aircraft antennas. The radiation patterns for basic elements (infinitesimal dipole, circumferential and axial slot) mounted on fuselage of various aircrafts with or without radome included were calculated and compared well with experimental results. Error phase plots were also presented. The effects of radiation patterns and error phase plots on the polarization selection for the MLS airborne antenna are discussed.

  13. Airborne forest fire research

    NASA Technical Reports Server (NTRS)

    Mattingly, G. S.

    1974-01-01

    The research relating to airborne fire fighting systems is reviewed to provide NASA/Langley Research Center with current information on the use of aircraft in forest fire operations, and to identify research requirements for future operations. A literature survey, interview of forest fire service personnel, analysis and synthesis of data from research reports and independent conclusions, and recommendations for future NASA-LRC programs are included.

  14. Spectral Similarity Assessment Based on a Spectrum Reflectance-Absorption Index and Simplified Curve Patterns for Hyperspectral Remote Sensing

    PubMed Central

    Ma, Dan; Liu, Jun; Huang, Junyi; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing

    2016-01-01

    Hyperspectral images possess properties such as rich spectral information, narrow bandwidth, and large numbers of bands. Finding effective methods to retrieve land features from an image by using similarity assessment indices with specific spectral characteristics is an important research question. This paper reports a novel hyperspectral image similarity assessment index based on spectral curve patterns and a reflection-absorption index. First, some spectral reflection-absorption features are extracted to restrict the subsequent curve simplification. Then, the improved Douglas-Peucker algorithm is employed to simplify all spectral curves without setting the thresholds. Finally, the simplified curves with the feature points are matched, and the similarities among the spectral curves are calculated using the matched points. The Airborne Visible Infrared Imaging Spectrometer (AVIRIS) and Reflective Optics System Imaging Spectrometer (ROSIS) hyperspectral image datasets are then selected to test the effect of the proposed index. The practical experiments indicate that the proposed index can achieve higher precision and fewer points than the traditional spectral information divergence and spectral angle match. PMID:26821030

  15. Hyperspectral Mineral Mapping in Support of Geothermal Exploration: Examples from Long Valley Caldera, CA and Dixie Valley, NV, USA

    SciTech Connect

    Martini, B; Silver, E; Pickles, W; Cocks, P

    2004-03-25

    Growing interest and exploration dollars within the geothermal sector have paved the way for increasingly sophisticated suites of geophysical and geochemical tools and methodologies. The efforts to characterize and assess known geothermal fields and find new, previously unknown resources has been aided by the advent of higher spatial resolution airborne geophysics (e.g. aeromagnetics), development of new seismic processing techniques, and the genesis of modern multi-dimensional fluid flow and structural modeling algorithms, just to name a few. One of the newest techniques on the scene, is hyperspectral imaging. Really an optical analytical geochemical tool, hyperspectral imagers (or imaging spectrometers as they are also called), are generally flown at medium to high altitudes aboard mid-sized aircraft and much in the same way more familiar geophysics are flown. The hyperspectral data records a continuous spatial record of the earth's surface, as well as measuring a continuous spectral record of reflected sunlight or emitted thermal radiation. This high fidelity, uninterrupted spatial and spectral record allows for accurate material distribution mapping and quantitative identification at the pixel to sub-pixel level. In volcanic/geothermal regions, this capability translates to synoptic, high spatial resolution, large-area mineral maps generated at time scales conducive to both the faster pace of the exploration and drilling managers, as well as to the slower pace of geologists and other researchers trying to understand the geothermal system over the long run.

  16. Hyperspectral Mineral Mapping in Support of Geothermal Exploration: Examples from Long Valley Caldera, CA and Dixie Valley, NV, USA

    SciTech Connect

    Pickles, W L; Martini, B A; Silver, E A; Cocks, P A

    2004-03-03

    Growing interest and exploration dollars within the geothermal sector have paved the way for increasingly sophisticated suites of geophysical and geochemical tools and methodologies. The efforts to characterize and assess known geothermal fields and find new, previously unknown resources has been aided by the advent of higher spatial resolution airborne geophysics (e.g. aeromagnetics), development of new seismic processing techniques, and the genesis of modern multi-dimensional fluid flow and structural modeling algorithms, just to name a few. One of the newest techniques on the scene, is hyperspectral imaging. Really an optical analytical geochemical tool, hyperspectral imagers (or imaging spectrometers as they are also called), are generally flown at medium to high altitudes aboard mid-sized aircraft and much in the same way more familiar geophysics are flown. The hyperspectral data records a continuous spatial record of the earth's surface, as well as measuring a continuous spectral record of reflected sunlight or emitted thermal radiation. This high fidelity, uninterrupted spatial and spectral record allows for accurate material distribution mapping and quantitative identification at the pixel to sub-pixel level. In volcanic/geothermal regions, this capability translates to synoptic, high spatial resolution, large-area mineral maps generated at time scales conducive to both the faster pace of the exploration and drilling managers, as well as to the slower pace of geologists and other researchers trying to understand the geothermal system over the long run.

  17. Comparative analysis of different implementations of a parallel algorithm for automatic target detection and classification of hyperspectral images

    NASA Astrophysics Data System (ADS)

    Paz, Abel; Plaza, Antonio; Plaza, Javier

    2009-08-01

    Automatic target detection in hyperspectral images is a task that has attracted a lot of attention recently. In the last few years, several algoritms have been developed for this purpose, including the well-known RX algorithm for anomaly detection, or the automatic target detection and classification algorithm (ATDCA), which uses an orthogonal subspace projection (OSP) approach to extract a set of spectrally distinct targets automatically from the input hyperspectral data. Depending on the complexity and dimensionality of the analyzed image scene, the target/anomaly detection process may be computationally very expensive, a fact that limits the possibility of utilizing this process in time-critical applications. In this paper, we develop computationally efficient parallel versions of both the RX and ATDCA algorithms for near real-time exploitation of these algorithms. In the case of ATGP, we use several distance metrics in addition to the OSP approach. The parallel versions are quantitatively compared in terms of target detection accuracy, using hyperspectral data collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the World Trade Center in New York, five days after the terrorist attack of September 11th, 2001, and also in terms of parallel performance, using a massively Beowulf cluster available at NASA's Goddard Space Flight Center in Maryland.

  18. Spectral Similarity Assessment Based on a Spectrum Reflectance-Absorption Index and Simplified Curve Patterns for Hyperspectral Remote Sensing.

    PubMed

    Ma, Dan; Liu, Jun; Huang, Junyi; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing

    2016-01-01

    Hyperspectral images possess properties such as rich spectral information, narrow bandwidth, and large numbers of bands. Finding effective methods to retrieve land features from an image by using similarity assessment indices with specific spectral characteristics is an important research question. This paper reports a novel hyperspectral image similarity assessment index based on spectral curve patterns and a reflection-absorption index. First, some spectral reflection-absorption features are extracted to restrict the subsequent curve simplification. Then, the improved Douglas-Peucker algorithm is employed to simplify all spectral curves without setting the thresholds. Finally, the simplified curves with the feature points are matched, and the similarities among the spectral curves are calculated using the matched points. The Airborne Visible Infrared Imaging Spectrometer (AVIRIS) and Reflective Optics System Imaging Spectrometer (ROSIS) hyperspectral image datasets are then selected to test the effect of the proposed index. The practical experiments indicate that the proposed index can achieve higher precision and fewer points than the traditional spectral information divergence and spectral angle match. PMID:26821030

  19. Spectral Similarity Assessment Based on a Spectrum Reflectance-Absorption Index and Simplified Curve Patterns for Hyperspectral Remote Sensing.

    PubMed

    Ma, Dan; Liu, Jun; Huang, Junyi; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing

    2016-01-01

    Hyperspectral images possess properties such as rich spectral information, narrow bandwidth, and large numbers of bands. Finding effective methods to retrieve land features from an image by using similarity assessment indices with specific spectral characteristics is an important research question. This paper reports a novel hyperspectral image similarity assessment index based on spectral curve patterns and a reflection-absorption index. First, some spectral reflection-absorption features are extracted to restrict the subsequent curve simplification. Then, the improved Douglas-Peucker algorithm is employed to simplify all spectral curves without setting the thresholds. Finally, the simplified curves with the feature points are matched, and the similarities among the spectral curves are calculated using the matched points. The Airborne Visible Infrared Imaging Spectrometer (AVIRIS) and Reflective Optics System Imaging Spectrometer (ROSIS) hyperspectral image datasets are then selected to test the effect of the proposed index. The practical experiments indicate that the proposed index can achieve higher precision and fewer points than the traditional spectral information divergence and spectral angle match.

  20. Hyperspectral exploitation with plant sentinels

    NASA Astrophysics Data System (ADS)

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

    2007-04-01

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

  1. Mutagenicity of airborne particles.

    PubMed

    Chrisp, C E; Fisher, G L

    1980-09-01

    The physical and chemical properties of airborne particles are important for the interpretation of their potential biologic significance as genotoxic hazards. For polydisperse particle size distributions, the smallest, most respirable particles are generally the most mutagenic. Particulate collection for testing purposes should be designed to reduce artifact formation and allow condensation of mutagenic compounds. Other critical factors such as UV irradiation, wind direction, chemical reactivity, humidity, sample storage, and temperature of combustion are important. Application of chemical extraction methods and subsequent class fractionation techniques influence the observed mutagenic activity. Particles from urban air, coal fly ash, automobile and diesel exhaust, agricultural burning and welding fumes contain primarily direct-acting mutagens. Cigarette smoke condensate, smoke from charred meat and protein pyrolysates, kerosene soot and cigarette smoke condensates contain primarily mutagens which require metabolic activation. Fractionation coupled with mutagenicity testing indicates that the most potent mutagens are found in the acidic fractions of urban air, coal fly ash, and automobile diesel exhaust, whereas mutagens in rice straw smoke and cigarette smoke condensate are found primarily in the basic fractions. The interaction of the many chemical compounds in complex mixtures from airborne particles is likely to be important in determining mutagenic or comutagenic potentials. Because the mode of exposure is generally frequent and prolonged, the presence of tumor-promoting agents in complex mixtures may be a major factor in evaluation of the carcinogenic potential of airborne particles.

  2. Mammalian airborne allergens.

    PubMed

    Aalberse, Rob C

    2014-01-01

    Historically, horse dandruff was a favorite allergen source material. Today, however, allergic symptoms due to airborne mammalian allergens are mostly a result of indoor exposure, be it at home, at work or even at school. The relevance of mammalian allergens in relation to the allergenic activity of house dust extract is briefly discussed in the historical context of two other proposed sources of house dust allergenic activity: mites and Maillard-type lysine-sugar conjugates. Mammalian proteins involved in allergic reactions to airborne dust are largely found in only 2 protein families: lipocalins and secretoglobins (Fel d 1-like proteins), with a relatively minor contribution of serum albumins, cystatins and latherins. Both the lipocalin and the secretoglobin family are very complex. In some instances this results in a blurred separation between important and less important allergenic family members. The past 50 years have provided us with much detailed information on the genomic organization and protein structure of many of these allergens. However, the complex family relations, combined with the wide range of post-translational enzymatic and non-enzymatic modifications, make a proper qualitative and quantitative description of the important mammalian indoor airborne allergens still a significant proteomic challenge. PMID:24925404

  3. Performance of 12- μm- to 15- μm-Pitch MWIR and LWIR HgCdTe FPAs at Elevated Temperatures

    NASA Astrophysics Data System (ADS)

    Strong, Roger L.; Kinch, Michael A.; Armstrong, John M.

    2013-11-01

    Infrared (IR) focal-plane arrays (FPAs) with higher operating temperatures and smaller pitches enable reduced size, weight, and power in infrared systems. We have characterized a large number of medium- and long-wavelength IR (MWIR and LWIR) FPAs as a function of temperature and cutoff wavelength to determine the impact of these parameters on their performance. The 77-K cutoff wavelength range for the MWIR arrays was 5.0 μm to 5.6 μm, and 8.6 μm to 11.3 μm for the LWIR. The dark currents in DRS's high-density vertically integrated photodiode (HDVIP)® FPAs (based on a front-side- illuminated, via-interconnected, cylindrical-geometry N+/N/P architecture) are dominated by Auger-7 recombination from 120 K to 200 K for the MWIR and 70 K to 100 K for the LWIR. In these temperature ranges the FPA operability is generally limited not by dark current defects but by noise defects. Pixels with high 1/ f noise should produce a tail in the root-mean-square (rms) noise distribution. We have found that the skewness of the rms noise distribution is the simplest measure of an array's 1/ f noise, and that the rms noise skewness typically shows little variation over these temperature ranges. The temperature dependence of the defect counts in normal arrays (wet etched prior to CdTe interdiffusion) increases as n i, while nonstandard arrays (ion milled or plasma etched prior to CdTe interdiffusion) can have high 1/ f noise and defect counts that vary as n {i/2}. Our models indicate that, if the dominant dark current is due to diffusion, then the 1/ f noise varies as n {i/2}, whereas if depletion current dominates, then the 1/ f noise varies as n i. Systemic 1/ f noise is not an issue for DRS's standard MWIR FPAs at 110 K to 160 K, or for standard LWIR FPAs at 77 K to 100 K.

  4. Airborne wireless communication systems, airborne communication methods, and communication methods

    DOEpatents

    Deaton, Juan D.; Schmitt, Michael J.; Jones, Warren F.

    2011-12-13

    An airborne wireless communication system includes circuitry configured to access information describing a configuration of a terrestrial wireless communication base station that has become disabled. The terrestrial base station is configured to implement wireless communication between wireless devices located within a geographical area and a network when the terrestrial base station is not disabled. The circuitry is further configured, based on the information, to configure the airborne station to have the configuration of the terrestrial base station. An airborne communication method includes answering a 911 call from a terrestrial cellular wireless phone using an airborne wireless communication system.

  5. Quality evaluation of fruit by hyperspectral imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. Hyperspectral signature analysis of skin parameters

    NASA Astrophysics Data System (ADS)

    Vyas, Saurabh; Banerjee, Amit; Garza, Luis; Kang, Sewon; Burlina, Philippe

    2013-02-01

    The temporal analysis of changes in biological skin parameters, including melanosome concentration, collagen concentration and blood oxygenation, may serve as a valuable tool in diagnosing the progression of malignant skin cancers and in understanding the pathophysiology of cancerous tumors. Quantitative knowledge of these parameters can also be useful in applications such as wound assessment, and point-of-care diagnostics, amongst others. We propose an approach to estimate in vivo skin parameters using a forward computational model based on Kubelka-Munk theory and the Fresnel Equations. We use this model to map the skin parameters to their corresponding hyperspectral signature. We then use machine learning based regression to develop an inverse map from hyperspectral signatures to skin parameters. In particular, we employ support vector machine based regression to estimate the in vivo skin parameters given their corresponding hyperspectral signature. We build on our work from SPIE 2012, and validate our methodology on an in vivo dataset. This dataset consists of 241 signatures collected from in vivo hyperspectral imaging of patients of both genders and Caucasian, Asian and African American ethnicities. In addition, we also extend our methodology past the visible region and through the short-wave infrared region of the electromagnetic spectrum. We find promising results when comparing the estimated skin parameters to the ground truth, demonstrating good agreement with well-established physiological precepts. This methodology can have potential use in non-invasive skin anomaly detection and for developing minimally invasive pre-screening tools.

  7. Biometric study using hyperspectral imaging during stress

    NASA Astrophysics Data System (ADS)

    Nagaraj, Sheela; Quoraishee, Shafik; Chan, Gabriel; Short, Kenneth R.

    2010-04-01

    To the casual observer, transient stress results in a variety of physiological changes that can be seen in the face. Although the conditions can be seen visibly, the conditions affect the emissivity and absorption properties of the skin, which imaging spectrometers, commonly referred to as Hyperspectral (HS) cameras, can quantify at every image pixel. The study reported on in this paper, using Hyperspectral cameras, provides a basis for continued study of HS imaging to eventually quantify biometric stress. This study was limited to the visible to near infrared (VNIR) spectral range. Signal processing tools and algorithms have been developed and are described for using HS face data from human subjects. The subjects were placed in psychologically stressful situations and the camera data were analyzed to detect stress through changes in dermal reflectance and emissivity. Results indicate that hyperspectral imaging may potentially serve as a non-invasive tool to measure changes in skin emissivity indicative of a stressful incident. Particular narrow spectral bands in the near-infrared region of the electromagnetic spectrum seem especially important. Further studies need to be performed to determine the optimal spectral bands and to generalize the conclusions. The enormous information available in hyperspectral imaging needs further analysis and more spectral regions need to be exploited. Non-invasive stress detection is a prominent area of research with countless applications for both military and commercial use including border patrol, stand-off interrogation, access control, surveillance, and non-invasive and un-attended patient monitoring.

  8. Novel hyperspectral prediction method and apparatus

    NASA Astrophysics Data System (ADS)

    Kemeny, Gabor J.; Crothers, Natalie A.; Groth, Gard A.; Speck, Kathy A.; Marbach, Ralf

    2009-05-01

    Both the power and the challenge of hyperspectral technologies is the very large amount of data produced by spectral cameras. While off-line methodologies allow the collection of gigabytes of data, extended data analysis sessions are required to convert the data into useful information. In contrast, real-time monitoring, such as on-line process control, requires that compression of spectral data and analysis occur at a sustained full camera data rate. Efficient, high-speed practical methods for calibration and prediction are therefore sought to optimize the value of hyperspectral imaging. A novel method of matched filtering known as science based multivariate calibration (SBC) was developed for hyperspectral calibration. Classical (MLR) and inverse (PLS, PCR) methods are combined by spectroscopically measuring the spectral "signal" and by statistically estimating the spectral "noise." The accuracy of the inverse model is thus combined with the easy interpretability of the classical model. The SBC method is optimized for hyperspectral data in the Hyper-CalTM software used for the present work. The prediction algorithms can then be downloaded into a dedicated FPGA based High-Speed Prediction EngineTM module. Spectral pretreatments and calibration coefficients are stored on interchangeable SD memory cards, and predicted compositions are produced on a USB interface at real-time camera output rates. Applications include minerals, pharmaceuticals, food processing and remote sensing.

  9. Convex geometry analysis method of hyperspectral data

    NASA Astrophysics Data System (ADS)

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

    2003-06-01

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

  10. Mapping Soil Organic Matter with Hyperspectral Imaging

    NASA Astrophysics Data System (ADS)

    Moni, Christophe; Burud, Ingunn; Flø, Andreas; Rasse, Daniel

    2014-05-01

    Soil organic matter (SOM) plays a central role for both food security and the global environment. Soil organic matter is the 'glue' that binds soil particles together, leading to positive effects on soil water and nutrient availability for plant growth and helping to counteract the effects of erosion, runoff, compaction and crusting. Hyperspectral measurements of samples of soil profiles have been conducted with the aim of mapping soil organic matter on a macroscopic scale (millimeters and centimeters). Two soil profiles have been selected from the same experimental site, one from a plot amended with biochar and another one from a control plot, with the specific objective to quantify and map the distribution of biochar in the amended profile. The soil profiles were of size (30 x 10 x 10) cm3 and were scanned with two pushbroomtype hyperspectral cameras, one which is sensitive in the visible wavelength region (400 - 1000 nm) and one in the near infrared region (1000 - 2500 nm). The images from the two detectors were merged together into one full dataset covering the whole wavelength region. Layers of 15 mm were removed from the 10 cm high sample such that a total of 7 hyperspectral images were obtained from the samples. Each layer was analyzed with multivariate statistical techniques in order to map the different components in the soil profile. Moreover, a 3-dimensional visalization of the components through the depth of the sample was also obtained by combining the hyperspectral images from all the layers. Mid-infrared spectroscopy of selected samples of the measured soil profiles was conducted in order to correlate the chemical constituents with the hyperspectral results. The results show that hyperspectral imaging is a fast, non-destructive technique, well suited to characterize soil profiles on a macroscopic scale and hence to map elements and different organic matter quality present in a complete pedon. As such, we were able to map and quantify biochar in our

  11. ICER-3D Hyperspectral Image Compression Software

    NASA Technical Reports Server (NTRS)

    Xie, Hua; Kiely, Aaron; Klimesh, matthew; Aranki, Nazeeh

    2010-01-01

    Software has been developed to implement the ICER-3D algorithm. ICER-3D effects progressive, three-dimensional (3D), wavelet-based compression of hyperspectral images. If a compressed data stream is truncated, the progressive nature of the algorithm enables reconstruction of hyperspectral data at fidelity commensurate with the given data volume. The ICER-3D software is capable of providing either lossless or lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The compression algorithm, which was derived from the ICER image compression algorithm, includes wavelet-transform, context-modeling, and entropy coding subalgorithms. The 3D wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of sets of hyperspectral image data, while facilitating elimination of spectral ringing artifacts, using a technique summarized in "Improving 3D Wavelet-Based Compression of Spectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. Correlation is further exploited by a context-modeling subalgorithm, which exploits spectral dependencies in the wavelet-transformed hyperspectral data, using an algorithm that is summarized in "Context Modeler for Wavelet Compression of Hyperspectral Images" (NPO-43239), which follows this article. An important feature of ICER-3D is a scheme for limiting the adverse effects of loss of data during transmission. In this scheme, as in the similar scheme used by ICER, the spatial-frequency domain is partitioned into rectangular error-containment regions. In ICER-3D, the partitions extend through all the wavelength bands. The data in each partition are compressed independently of those in the other partitions, so that loss or corruption of data from any partition does not affect the other partitions. Furthermore, because compression is progressive within each partition, when data are lost, any data from that partition received

  12. Compression of hyperspectral data for automated analysis

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

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

  13. Hyperspectral Data Classification Using Factor Graphs

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  14. VEGETATION COVER ANALYSIS OF HAZARDOUS WASTE SITES IN UTAH AND ARIZONA USING HYPERSPECTRAL REMOTE SENSING

    SciTech Connect

    Serrato, M.; Jungho, I.; Jensen, J.; Jensen, R.; Gladden, J.; Waugh, J.

    2012-01-17

    Remote sensing technology can provide a cost-effective tool for monitoring hazardous waste sites. This study investigated the usability of HyMap airborne hyperspectral remote sensing data (126 bands at 2.3 x 2.3 m spatial resolution) to characterize the vegetation at U.S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. The specific objectives of this study were to: (1) estimate leaf-area-index (LAI) of the vegetation using three different methods (i.e., vegetation indices, red-edge positioning (REP), and machine learning regression trees), and (2) map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF)-derived metrics and vegetation indices. Regression trees resulted in the best calibration performance of LAI estimation (R{sup 2} > 0.80). The use of REPs failed to accurately predict LAI (R{sup 2} < 0.2). The use of the MTMF-derived metrics (matched filter scores and infeasibility) and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI) and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of 1 higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches (< 1m) found on the sites.

  15. Hyperspectral Mapping of Iron-bearing Minerals Associated with Dry and Ephemeral Lakes

    NASA Astrophysics Data System (ADS)

    Farrand, W. H.; Bowen, B. B.

    2014-12-01

    This research project is utilizing data from the Hyperspectral Imager for the Coastal Ocean (HICO) on the International Space Station (ISS) to examine a set of playas and ephemeral lakes in Australia and in the southwestern United States. HICO collects hyperspectral data from 0.35 to 1.08 μm thus excluding the SWIR vibrational overtone region of clays and carbonates. We are assessing the utility of HICO for detecting iron-bearing minerals and materials associated with playas and mapping their fractional abundance outside of the playa boundaries. Sites being investigated include the clastics-dominated Railroad Valley and Lunar Lake playas of Nevada, the evaporite-dominated Bonneville Salt Flats, and the acid-saline Lake Tyrrell of northwest Victoria, Australia. HICO, and supporting airborne hyperspectral datasets (AVIRIS and HyMap), are being converted from at-sensor radiance to surface reflectance using the FLAASH radiance transfer-based atmospheric correction software. Fe-bearing minerals and materials are determined through a standardized endmember detection approach using the commercial ENVI software and mapped using a variety of approaches including linear spectral mixture analysis, constrained energy minimization, and spectral feature fitting. Interpretations of remote data are guided by field-based observations and mapping. We are using the remote sensing data to assess the surface state of the playa (wet vs. dry, soft vs. hard). These factors have bearing in that dusts stripped from playa surfaces can affect nearby human communities and agricultural fields. Playas are also used for recreation and sometimes as transportation corridors and their physical state has important bearing for those functions. Assessing the types of minerals present has relevance for their impact as wind-entrained particulates that could have adverse effects on the health of humans, crops, or livestock.

  16. Airborne Submillimeter Spectroscopy

    NASA Technical Reports Server (NTRS)

    Zmuidzinas, J.

    1998-01-01

    This is the final technical report for NASA-Ames grant NAG2-1068 to Caltech, entitled "Airborne Submillimeter Spectroscopy", which extended over the period May 1, 1996 through January 31, 1998. The grant was funded by the NASA airborne astronomy program, during a period of time after the Kuiper Airborne Observatory was no longer operational. Instead. this funding program was intended to help develop instrument concepts and technology for the upcoming SOFIA (Stratospheric Observatory for Infrared Astronomy) project. SOFIA, which is funded by NASA and is now being carried out by a consortium lead by USRA (Universities Space Research Association), will be a 747 aircraft carrying a 2.5 meter diameter telescope. The purpose of our grant was to fund the ongoing development of sensitive heterodyne receivers for the submillimeter band (500-1200 GHz), using sensitive superconducting (SIS) detectors. In 1997 July we submitted a proposal to USRA to construct a heterodyne instrument for SOFIA. Our proposal was successful [1], and we are now continuing our airborne astronomy effort with funding from USRA. A secondary purpose of the NAG2-1068 grant was to continue the anaIN'sis of astronomical data collected with an earlier instrument which was flown on the NASA Kuiper Airborne Observatory (KAO). The KAO instrument and the astronomical studies which were carried out with it were supported primarily under another grant, NAG2-744, which extended over October 1, 1991 through Januarv 31, 1997. For a complete description of the astronomical data and its anailysis, we refer the reader to the final technical report for NAG2-744, which was submitted to NASA on December 1. 1997. Here we report on the SIS detector development effort for SOFIA carried out under NAG2-1068. The main result of this effort has been the demonstration of SIS mixers using a new superconducting material niobium titanium nitride (NbTiN), which promises to deliver dramatic improvements in sensitivity in the 700

  17. Co-aligning aerial hyperspectral push-broom strips for change detection

    NASA Astrophysics Data System (ADS)

    Ringaby, Erik; Ahlberg, Jörgen; Wadströmer, Niclas; Forssén, Per-Erik

    2010-10-01

    We have performed a field trial with an airborne push-broom hyperspectral sensor, making several flights over the same area and with known changes (e.g., moved vehicles) between the flights. Each flight results in a sequence of scan lines forming an image strip, and in order to detect changes between two flights, the two resulting image strips must be geometrically aligned and radiometrically corrected. The focus of this paper is the geometrical alignment, and we propose an image- and gyro-based method for geometric co-alignment (registration) of two image strips. The method is particularly useful when the sensor is not stabilized, thus reducing the need for expensive mechanical stabilization. The method works in several steps, including gyro-based rectification, global alignment using SIFT matching, and a local alignment using KLT tracking. Experimental results are shown but not quantified, as ground truth is, by the nature of the trial, lacking.

  18. A linear mixture analysis-based compression for hyperspectral image analysis

    SciTech Connect

    C. I. Chang; I. W. Ginsberg

    2000-06-30

    In this paper, the authors present a fully constrained least squares linear spectral mixture analysis-based compression technique for hyperspectral image analysis, particularly, target detection and classification. Unlike most compression techniques that directly deal with image gray levels, the proposed compression approach generates the abundance fractional images of potential targets present in an image scene and then encodes these fractional images so as to achieve data compression. Since the vital information used for image analysis is generally preserved and retained in the abundance fractional images, the loss of information may have very little impact on image analysis. In some occasions, it even improves analysis performance. Airborne visible infrared imaging spectrometer (AVIRIS) data experiments demonstrate that it can effectively detect and classify targets while achieving very high compression ratios.

  19. Detection of Tephra Layers in Antarctic Sediment Cores with Hyperspectral Imaging

    PubMed Central

    Aymerich, Ismael F.; Oliva, Marc; Giralt, Santiago; Martín-Herrero, Julio

    2016-01-01

    Tephrochronology uses recognizable volcanic ash layers (from airborne pyroclastic deposits, or tephras) in geological strata to set unique time references for paleoenvironmental events across wide geographic areas. This involves the detection of tephra layers which sometimes are not evident to the naked eye, including the so-called cryptotephras. Tests that are expensive, time-consuming, and/or destructive are often required. Destructive testing for tephra layers of cores from difficult regions, such as Antarctica, which are useful sources of other kinds of information beyond tephras, is always undesirable. Here we propose hyperspectral imaging of cores, Self-Organizing Map (SOM) clustering of the preprocessed spectral signatures, and spatial analysis of the classified images as a convenient, fast, non-destructive method for tephra detection. We test the method in five sediment cores from three Antarctic lakes, and show its potential for detection of tephras and cryptotephras. PMID:26815202

  20. Detection of Tephra Layers in Antarctic Sediment Cores with Hyperspectral Imaging.

    PubMed

    Aymerich, Ismael F; Oliva, Marc; Giralt, Santiago; Martín-Herrero, Julio

    2016-01-01

    Tephrochronology uses recognizable volcanic ash layers (from airborne pyroclastic deposits, or tephras) in geological strata to set unique time references for paleoenvironmental events across wide geographic areas. This involves the detection of tephra layers which sometimes are not evident to the naked eye, including the so-called cryptotephras. Tests that are expensive, time-consuming, and/or destructive are often required. Destructive testing for tephra layers of cores from difficult regions, such as Antarctica, which are useful sources of other kinds of information beyond tephras, is always undesirable. Here we propose hyperspectral imaging of cores, Self-Organizing Map (SOM) clustering of the preprocessed spectral signatures, and spatial analysis of the classified images as a convenient, fast, non-destructive method for tephra detection. We test the method in five sediment cores from three Antarctic lakes, and show its potential for detection of tephras and cryptotephras.

  1. Detection of Tephra Layers in Antarctic Sediment Cores with Hyperspectral Imaging.

    PubMed

    Aymerich, Ismael F; Oliva, Marc; Giralt, Santiago; Martín-Herrero, Julio

    2016-01-01

    Tephrochronology uses recognizable volcanic ash layers (from airborne pyroclastic deposits, or tephras) in geological strata to set unique time references for paleoenvironmental events across wide geographic areas. This involves the detection of tephra layers which sometimes are not evident to the naked eye, including the so-called cryptotephras. Tests that are expensive, time-consuming, and/or destructive are often required. Destructive testing for tephra layers of cores from difficult regions, such as Antarctica, which are useful sources of other kinds of information beyond tephras, is always undesirable. Here we propose hyperspectral imaging of cores, Self-Organizing Map (SOM) clustering of the preprocessed spectral signatures, and spatial analysis of the classified images as a convenient, fast, non-destructive method for tephra detection. We test the method in five sediment cores from three Antarctic lakes, and show its potential for detection of tephras and cryptotephras. PMID:26815202

  2. Shrimp pond effluent dominates foliar nitrogen in disturbed mangroves as mapped using hyperspectral imagery.

    PubMed

    Fauzi, Anas; Skidmore, Andrew K; van Gils, Hein; Schlerf, Martin; Heitkönig, Ignas M A

    2013-11-15

    Conversion of mangroves to shrimp ponds creates fragmentation and eutrophication. Detection of the spatial variation of foliar nitrogen is essential for understanding the effect of eutrophication on mangroves. We aim (i) to estimate nitrogen variability across mangrove landscapes of the Mahakam delta using airborne hyperspectral remote sensing (HyMap) and (ii) to investigate links between the variation of foliar nitrogen mapped and local environmental variables. In this study, multivariate prediction models achieved a higher level of accuracy than narrow-band vegetation indices, making multivariate modeling the best choice for mapping. The variation of foliar nitrogen concentration in mangroves was significantly influenced by the local environment: (1) position of mangroves (seaward/landward), (2) distance to the shrimp ponds, and (3) predominant mangrove species. The findings suggest that anthropogenic disturbances, in this case shrimp ponds, influence nitrogen variation in mangroves. Mangroves closer to the shrimp ponds had higher foliar nitrogen concentrations.

  3. Hyperspectral imager development at Army Research Laboratory

    NASA Astrophysics Data System (ADS)

    Gupta, Neelam

    2008-04-01

    Development of robust compact optical imagers that can acquire both spectral and spatial features from a scene of interest is of utmost importance for standoff detection of chemical and biological agents as well as targets and backgrounds. Spectral features arise due to the material properties of objects as a result of the emission, reflection, and absorption of light. Using hyperspectral imaging one can acquire images with narrow spectral bands and take advantage of the characteristic spectral signatures of different materials making up the scene in detection of objects. Traditional hyperspectral imaging systems use gratings and prisms that acquire one-dimensional spectral images and require relative motion of sensor and scene in addition to data processing to form a two-dimensional image cube. There is much interest in developing hyperspectral imagers using tunable filters that acquire a two-dimensional spectral image and build up an image cube as a function of time. At the Army Research Laboratory (ARL), we are developing hyperspectral imagers using a number of novel tunable filter technologies. These include acousto-optic tunable filters (AOTFs) that can provide adaptive no-moving-parts imagers from the UV to the long wave infrared, diffractive optics technology that can provide image cubes either in a single spectral region or simultaneously in different spectral regions using a single moving lens or by using a lenslet array, and micro-electromechanical systems (MEMS)-based Fabry-Perot (FP) tunable etalons to develop miniature sensors that take advantage of the advances in microfabrication and packaging technologies. New materials are being developed to design AOTFs and a full Stokes polarization imager has been developed, diffractive optics lenslet arrays are being explored, and novel FP tunable filters are under fabrication for the development of novel miniature hyperspectral imagers. Here we will brief on all the technologies being developed and present

  4. Detection and Spatial Mapping of Anthropogenic Methane Plumes with the Hyperspectral Thermal Emission Spectrometer (HyTES)

    NASA Astrophysics Data System (ADS)

    Hulley, Glynn; Duren, Riley; Hook, Simon; Hopkins, Francesca

    2016-04-01

    Detection and Spatial Mapping of Anthropogenic Methane Plumes with the Hyperspectral Thermal Emission Spectrometer (HyTES) Glynn Hulley, Simon Hook, Riley Duren, Francesca Hopkins Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA Currently large uncertainties exist associated with attribution and quantification of fugitive emissions of greenhouse gases such as methane across many regions and key economic sectors. A number of observational efforts are currently underway to better quantify and reduce uncertainties associated with these emissions, including agriculture and oil and gas production operations. One such effort led by JPL is the development of the Hyperspectral Thermal Emission Spectrometer (HyTES) - a wide swath Thermal Infrared (TIR) airborne imager with high spectral (256 bands from 7.5 - 12 micron) and spatial resolution (~1.5 m at 1-km AGL altitude) that presents a major advance in airborne TIR remote sensing measurements. Using HyTES we have developed robust and reliable techniques for the detection and high resolution mapping of small scale plumes of anthropogenic (oil and gas fields, landfills, dairies) and non-anthropogenic (natural seeps) sources of methane in the state of California and Colorado. A background on the HyTES sensor, science objectives, gas detection methods, and examples of mapping fugitive methane plumes in California and Colorado will be discussed. These kind of observational efforts and studies will help address critical science questions related to methane budgets and management of future emissions in California and other regions.

  5. HySpex ODIN-1024: a new high-resolution airborne HSI system

    NASA Astrophysics Data System (ADS)

    Blaaberg, Søren; Løke, Trond; Baarstad, Ivar; Fridman, Andrei; Koirala, Pesal

    2014-06-01

    HySpex ODIN-1024 is a next generation state-of the-art airborne hyperspectral imaging system developed by Norsk Elektro Optikk AS. Near perfect coregistration between VNIR and SWIR is achieved by employing a novel common fore-optics design and a thermally stabilized housing. Its unique design and the use of state-of-the-art MCT and sCMOS sensors provide the combination of high sensitivity and low noise, low spatial and spectral misregistration (smile and keystone) and a very high resolution (1024 pixels in the merged data products). In addition to its supreme data quality, HySpex ODIN-1024 includes real-time data processing functionalities such as real-time georeferencing of acquired images. It also features a built-in onboard calibration system to monitor the stability of the instrument. The paper presents data and results from laboratory tests and characterizations, as well as results from airborne measurements.

  6. Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring.

    PubMed

    Allison, Robert S; Johnston, Joshua M; Craig, Gregory; Jennings, Sion

    2016-08-18

    For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites). Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems like hyperspectral cameras, image intensifiers and thermal cameras that have previously been limited in use due to cost or technology considerations are now becoming widely available and affordable. Similarly, new airborne sensor platforms, particularly small, unmanned aircraft or drones, are enabling new applications for airborne fire sensing. In this review we outline the state of the art in direct, semi-automated and automated fire detection from both manned and unmanned aerial platforms. We discuss the operational constraints and opportunities provided by these sensor systems including a discussion of the objective evaluation of these systems in a realistic context.

  7. Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring

    PubMed Central

    Allison, Robert S.; Johnston, Joshua M.; Craig, Gregory; Jennings, Sion

    2016-01-01

    For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites). Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems like hyperspectral cameras, image intensifiers and thermal cameras that have previously been limited in use due to cost or technology considerations are now becoming widely available and affordable. Similarly, new airborne sensor platforms, particularly small, unmanned aircraft or drones, are enabling new applications for airborne fire sensing. In this review we outline the state of the art in direct, semi-automated and automated fire detection from both manned and unmanned aerial platforms. We discuss the operational constraints and opportunities provided by these sensor systems including a discussion of the objective evaluation of these systems in a realistic context. PMID:27548174

  8. Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring.

    PubMed

    Allison, Robert S; Johnston, Joshua M; Craig, Gregory; Jennings, Sion

    2016-01-01

    For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites). Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems like hyperspectral cameras, image intensifiers and thermal cameras that have previously been limited in use due to cost or technology considerations are now becoming widely available and affordable. Similarly, new airborne sensor platforms, particularly small, unmanned aircraft or drones, are enabling new applications for airborne fire sensing. In this review we outline the state of the art in direct, semi-automated and automated fire detection from both manned and unmanned aerial platforms. We discuss the operational constraints and opportunities provided by these sensor systems including a discussion of the objective evaluation of these systems in a realistic context. PMID:27548174

  9. Detecting and discriminating petroleum and petroleum products from water on terrestrial backgrounds with hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    Allen, C. Scott

    Petroleum and petroleum product spills are frequent and as both Hurricane Katrina and the Deepwater Horizon accident demonstrated, they can be catastrophic. A prominent portion of the response is mapping the extent to which oil has reached both shoreline and inland areas. Yet, petroleum and water--when present on common substrates such as sand, concrete, and vegetation--are often difficult to distinguish in panchromatic and multispectral imagery. This research demonstrates how hyperspectral remote sensing, also known as imaging spectroscopy, provides petroleum detection and discrimination from water on terrestrial backgrounds. Utilizing spectral libraries, it also performs material identification and successfully discriminates some petroleum products from one another as a means of further classification and mapping spill extent. To achieve these goals, this effort collected spectral signatures of four crude oils and five refined petroleum products on ten common terrestrial substrates and compared them to water on the same backgrounds over a period of 1-90 days, depending on liquid volatility. The result is the first publicly available spectral library for petroleum and petroleum products on terrestrial substrates in the reflective portion of the electromagnetic spectrum (400-2500 nm) for use in petroleum spill detection and response. It also establishes a baseline for the use of imaging spectroscopy as a technique for confident, accurate petroleum detection in the terrestrial environment. Using common material identification algorithms, the spectra were successfully applied to airborne hyperspectral data from the Hurricane Katrina disaster in 2005 as a proof-of-concept for discriminating petroleum from water.

  10. Target detection assessment of the SHARE 2010/2012 hyperspectral data collection campaign

    NASA Astrophysics Data System (ADS)

    Ientilucci, Emmett J.

    2015-05-01

    It has been over four years since the first SpecTIR Hyperspectral Airborne Rochester Experiment (SHARE) was conducted in 2010. As such, a second SHARE experiment was performed in 2012 using the same deployed target panels and HSI sensor (i.e., specifically related to the target detection experiment"). A suite of sensors were own over the target areas including multi- and hyperspectral imagers, as well as a LADAR sensor. Experiments were conducted to examine topics such as pixel unmixing, subpixel detection, forest health, and in-water target detection, to name a few. This paper's focus is on target detection of different colored panels deployed on different backgrounds viewed under different illumination conditions collected two years apart. Additionally, the calibration and reflectance retrieval of the data is also examined. Detection is on the standard reflectance product provided by the acquisition company. Results are illustrated in the form of ROC curves. Analysis was performed on (many) red and blue panels on backgrounds such as grass, gravel, and roof tar paper. The targets were in the open (i.e., fully illuminated), as well as heavy and light shadow, which were harder to discover than their open counterparts. Calibration of the 2012 data is good with some issues related to the 2010 data. Adjustments and corrections are discussed. Finally, discussion of where to obtain the free HSI and co-registered LADAR data set is discussed.

  11. Geobotanical characterization of a geothermal system using hyperspectral imagery: Long Valley Caldera, CA

    SciTech Connect

    Carter, M R; Cochran, S A; Martini, B A; Pickles, W L; Potts, D C; Priest, R E; Silver, E A; Wayne, B A; White, W T

    1998-12-01

    We have analyzed hyperspectral Airborne Visible-Infrared Imaging System (AVIRIS) imagery taken in September of 1992 in Long Valley Caldera, CA, a geothermally active region expressed surficially by hot springs and fumaroles. Geological and vegetation mapping are attempted through spectral classification of imagery. Particular hot spring areas in the caldera are targeted for analysis. The data is analyzed for unique geobotanical patterns in the vicinity of hot springs as well as gross identification of dominant plant and mineral species. Spectra used for the classifications come from a vegetation spectral library created for plant species found to be associated with geothermal processes. This library takes into account the seasonality of vegetation by including spectra for species on a monthly basis. Geological spectra are taken from JPL and USGS mineral libraries. Preliminary classifications of hot spring areas indicate some success in mineral identification and less successful vegetation species identification. The small spatial extent of individual plants demands either sub-pixel analysis or increased spatial resolution of imagery. Future work will also include preliminary analysis of a hyperspectral thermal imagery dataset and a multitemporal air photo dataset. The combination of these remotely sensed datasets for Long Valley will yield a valuable product for geothermal exploration efforts in other regions.

  12. a Class-Outlier Approach for Environnemental Monitoring Using Uav Hyperspectral Images

    NASA Astrophysics Data System (ADS)

    Hemissi, S.; Riadh Farah, I.

    2015-04-01

    In several remote sensing applications, detecting exceptional/irregular regions (i.e, pixels) with respect to the whole dataset homogeneity is regarded as a very interested issue. Currently, this is limited to the pre-processing step aiming to eliminate the cloud or noisy pixels. In this paper, we propose to extend the coverage area and to tackle this issue by regarding the irregular/exceptional pixels as outliers. The main purpose is the adaptation of the class outlier mining concept in order to find abnormal and irregular pixels in hyperspectral images. This should be done taking into account the class labels and the relative uncertainty of collected data. To reach this goal, the Class Outliers: DistanceBased (CODB) algorithm is enhanced to take into account the multivariate high-dimensional data and the concomitant partially available knowledge of our data. This is mainly done by using belief theory and a learnable task-specific similarity measure. To validate our approach, we apply it for vegetation inspection and normality monitoring. For experimental purposes, the Airborne Prism Experiment (APEX) data, set acquired during an APEX flight campaign in June 2011, was used. Moreover, a collection of simulated hyperspectral images and spectral indices, providing a quantitative indicator of vegetation health, were generated for this purpose. The encouraging obtained results can be used to monitor areas where vegetation may be stressed, as a proxy to detect potential drought.

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

    NASA Astrophysics Data System (ADS)

    Wasson, Steven; Walker, William

    2015-05-01

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

  14. Geological Mapping by Combining Spectral Unmixing and Cluster Analysis for Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Ishidoshiro, N.; Yamaguchi, Y.; Noda, S.; Asano, Y.; Kondo, T.; Kawakami, Y.; Mitsuishi, M.; Nakamura, H.

    2016-06-01

    Spectral unmixing of hyperspectral data often fails to select some minerals and rocks having flat spectra but no diagnostic absorption features as endmembers, even if they are actually important endmembers. To avoid this problem, we propose a novel approach that combined two methods: spectral unmixing and full-pixel classification. First, all pixels were divided into two categories, hydrothermally altered areas and unaltered rocks based on the absorption depth of 2.0 to 2.5 μm. For the hydrothermally altered areas, endmembers were extracted by the Improved Causal Random Pixel Purity Index (ICRPPI) method, which was improved from the existing Pixel Purity Index (PPI) and Causal Random Pixel Purity Index (CRPPI) methods. Endmember abundance in each pixel was calculated by linear spectral unmixing. In a separate operation, k-means clustering was applied to the unaltered rock areas. Finally, the results of these two methods were combined to generate a single distribution map of rocks and minerals. This approach was applied to the airborne hyperspectral HyMap data of Cuprite, Nevada, U.S.A. We confirmed that our mapping result was consistent with the existing geological map as well as our field survey result.

  15. Functions of multiple instances for sub-pixel target characterization in hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Zare, Alina; Jiao, Changzhe

    2015-05-01

    In this paper, the Multi-target Extended Function of Multiple Instances (Multi-target eFUMI) method is developed and described. The method is capable of learning multiple target spectral signatures from weakly- and inaccurately-labeled hyperspectral imagery. Multi-target eFUMI is a generalization of the Function of Multiple Instances approach (FUMI). The FUMI approach differs significantly from standard Multiple Instance Learning (MIL) approach in that it assumes each data is a function of target and non-target "concepts." In this paper, data points which are convex combinations of multiple target and several non-target "concepts" are considered. Moreover, it allows both "proportion-level" and "bag-level" uncertainties in training data. Training data needs only binary labels indicating whether some spatial area contains or does not contain some proportion of target; the specific target proportions for the training data are not needed. Multi-target eFUMI learns the target and non-target concepts, the number of non-target concepts, and the proportions of all the concepts for each data point. After learning the target concepts using the binary "bag-level" labeled training data, target detection can be performed on test data. Results for sub-pixel target detection on simulated and real airborne hyperspectral data are shown.

  16. Feature-enhanced spectral similarity measure for the analysis of hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Li, Qingbo; Niu, Chunyang

    2015-01-01

    In hyperspectral remote sensing, the surface compositional material can be identified by means of spectral matching algorithms. In many cases, the importance of each spectral band to measure spectral similarity is different, whereas the traditional spectral matching algorithms implicitly assume all wavelength-dependent absorption features are equal. This may yield an unsatisfactory performance for spectral matching. To remedy this deficiency, we propose methods called feature-enhanced spectral similarity measures. They are hybrids of the spectral matching algorithms combined with a feature-enhanced space projection, termed feature-enhanced spectral angle measure, feature-enhanced Euclidean distance measure, feature-enhanced spectral correlation measure, and feature-enhanced spectral information divergence. The proposed methods creatively project the original spectra into spectral feature-enhanced space, in which important features for measuring the spectral similarity will be increased to a high degree, whereas features of low importance will be suppressed. In order to demonstrate the effectiveness of the proposed approaches, performances are compared on real hyperspectral image data from Airborne Visible Infrared Imaging Spectrometer. The proposed methods are found to possess significant improvements over the original four spectral matching algorithms.