Science.gov

Sample records for airborne hyperspectral sensor

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. [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.

  7. [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

  8. 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

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. Airborne Hyperspectral Imaging of Seagrass and Coral Reef

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  14. 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.

  15. 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.

  16. 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.

  17. 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

  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. PMID:25447169

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  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. 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.

  8. 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.

  9. 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.

  10. 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

  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. 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 ...

  13. 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.

  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. 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.

  16. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

  18. Airborne Hyperspectral Remote Sensing for Identification Grassland Vegetation

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  19. Onboard Image Processing System for Hyperspectral Sensor.

    PubMed

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

    2015-09-25

    Onboard image processing systems for a hyperspectral sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS) sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS), which is a hierarchical predictive coding method with resolution scaling. To improve FELICS's performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the sensor system without adding size, weight, power consumption, and fabrication cost.

  20. Onboard Image Processing System for Hyperspectral Sensor

    PubMed Central

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

    2015-01-01

    Onboard image processing systems for a hyperspectral sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS) sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS), which is a hierarchical predictive coding method with resolution scaling. To improve FELICS’s performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the sensor system without adding size, weight, power consumption, and fabrication cost. PMID:26404281

  1. Onboard Image Processing System for Hyperspectral Sensor.

    PubMed

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

    2015-01-01

    Onboard image processing systems for a hyperspectral sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS) sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS), which is a hierarchical predictive coding method with resolution scaling. To improve FELICS's performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the sensor system without adding size, weight, power consumption, and fabrication cost. PMID:26404281

  2. 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...

  3. 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...

  4. 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.

  5. Hyperspectral image projector for advanced sensor characterization

    NASA Astrophysics Data System (ADS)

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

    2006-08-01

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

  6. 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

  7. Global Test Range: Toward Airborne Sensor Webs

    NASA Technical Reports Server (NTRS)

    Mace, Thomas H.; Freudinger, Larry; DelFrate John H.

    2008-01-01

    This viewgraph presentation reviews the planned global sensor network that will monitor the Earth's climate, and resources using airborne sensor systems. The vision is an intelligent, affordable Earth Observation System. Global Test Range is a lab developing trustworthy services for airborne instruments - a specialized Internet Service Provider. There is discussion of several current and planned missions.

  8. 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.

  9. 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.

  10. Hyperspectral monitoring of chemically sensitive plant sensors

    NASA Astrophysics Data System (ADS)

    Simmons, Danielle A.

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

  11. 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.

  12. 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

  13. [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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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...

  19. 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 ...

  20. 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.

  1. 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.

  2. Infrared hyperspectral imaging sensor for gas detection

    NASA Astrophysics Data System (ADS)

    Hinnrichs, Michele

    2000-11-01

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

  3. 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

  4. 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

  5. Airborne Sensor Thermal Management Solution

    SciTech Connect

    Ng, K. K.

    2015-06-03

    The customer wants to outfit aircraft (de Havilland Twin Otter) with optical sensors. In previous product generations the sensor line-of-sight direction was fixed – the sensor’s direction relied on the orientation of the aircraft. The next generation sensor will be packaged in a rotatable turret so that the line-of-sight is reasonably independent of the aircraft’s orientation. This turret will be mounted on a boom protruding from the side of the aircraft. The customer wants to outfit aircraft (de Havilland Twin Otter) with optical sensors. In previous product generations the sensor line-of-sight direction was fixed – the sensor’s direction relied on the orientation of the aircraft. The next generation sensor will be packaged in a rotatable turret so that the line-of-sight is reasonably independent of the aircraft’s orientation. This turret will be mounted on a boom protruding from the side of the aircraft.

  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. Hyperspectral sensor HSC3000 for nano-satellite TAIKI

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  8. 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.

  9. Cyberinfrastructure for Airborne Sensor Webs

    NASA Technical Reports Server (NTRS)

    Freudinger, Lawrence C.

    2009-01-01

    Since 2004 the NASA Airborne Science Program has been prototyping and using infrastructure that enables researchers to interact with each other and with their instruments via network communications. This infrastructure uses satellite links and an evolving suite of applications and services that leverage open-source software. The use of these tools has increased near-real-time situational awareness during field operations, resulting in productivity improvements and the collection of better data. This paper describes the high-level system architecture and major components, with example highlights from the use of the infrastructure. The paper concludes with a discussion of ongoing efforts to transition to operational status.

  10. Airborne laser sensors and integrated systems

    NASA Astrophysics Data System (ADS)

    Sabatini, Roberto; Richardson, Mark A.; Gardi, Alessandro; Ramasamy, Subramanian

    2015-11-01

    The underlying principles and technologies enabling the design and operation of airborne laser sensors are introduced and a detailed review of state-of-the-art avionic systems for civil and military applications is presented. Airborne lasers including Light Detection and Ranging (LIDAR), Laser Range Finders (LRF), and Laser Weapon Systems (LWS) are extensively used today and new promising technologies are being explored. Most laser systems are active devices that operate in a manner very similar to microwave radars but at much higher frequencies (e.g., LIDAR and LRF). Other devices (e.g., laser target designators and beam-riders) are used to precisely direct Laser Guided Weapons (LGW) against ground targets. The integration of both functions is often encountered in modern military avionics navigation-attack systems. The beneficial effects of airborne lasers including the use of smaller components and remarkable angular resolution have resulted in a host of manned and unmanned aircraft applications. On the other hand, laser sensors performance are much more sensitive to the vagaries of the atmosphere and are thus generally restricted to shorter ranges than microwave systems. Hence it is of paramount importance to analyse the performance of laser sensors and systems in various weather and environmental conditions. Additionally, it is important to define airborne laser safety criteria, since several systems currently in service operate in the near infrared with considerable risk for the naked human eye. Therefore, appropriate methods for predicting and evaluating the performance of infrared laser sensors/systems are presented, taking into account laser safety issues. For aircraft experimental activities with laser systems, it is essential to define test requirements taking into account the specific conditions for operational employment of the systems in the intended scenarios and to verify the performance in realistic environments at the test ranges. To support the

  11. 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.

  12. A global shutter CMOS image sensor for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  13. 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.

  14. Band selection for viewing underwater objects using hyperspectral sensors

    NASA Astrophysics Data System (ADS)

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

    1999-10-01

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

  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. Hyperspectral Imaging Sensors and the Marine Coastal Zone

    NASA Technical Reports Server (NTRS)

    Richardson, Laurie L.

    2000-01-01

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

  17. 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).

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. Radiometric sensitivity contrast metrics for hyperspectral remote sensors

    NASA Astrophysics Data System (ADS)

    Silny, John F.; Zellinger, Lou

    2014-09-01

    This paper discusses the calculation, interpretation, and implications of various radiometric sensitivity metrics for Earth-observing hyperspectral imaging (HSI) sensors. The most commonly used sensor performance metric is signal-to-noise ratio (SNR), from which additional noise equivalent quantities can be computed, including: noise equivalent spectral radiance (NESR), noise equivalent delta reflectance (NEΔρ), noise equivalent delta emittance (NEΔƐ), and noise equivalent delta temperature (NEΔT). For hyperspectral sensors, these metrics are typically calculated from an at-aperture radiance (typically generated by MODTRAN) that includes both target radiance and non-target (atmosphere and background) radiance. Unfortunately, these calculations treat the entire at-aperture radiance as the desired signal, even when the target radiance is only a fraction of the total (such as when sensing through a long or optically dense atmospheric path). To overcome this limitation, an augmented set of metrics based on contrast signal-to-noise ratio (CNSR) is developed, including their noise equivalent counterparts (CNESR, CNEΔρ, CNEΔƐ, and CNEΔT). These contrast metrics better quantify sensor performance in an operational environment that includes remote sensing through the atmosphere.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Methods for gas detection using stationary hyperspectral imaging sensors

    SciTech Connect

    Conger, James L.; Henderson, John R.

    2012-04-24

    According to one embodiment, a method comprises producing a first hyperspectral imaging (HSI) data cube of a location at a first time using data from a HSI sensor; producing a second HSI data cube of the same location at a second time using data from the HSI sensor; subtracting on a pixel-by-pixel basis the second HSI data cube from the first HSI data cube to produce a raw difference cube; calibrating the raw difference cube to produce a calibrated raw difference cube; selecting at least one desired spectral band based on a gas of interest; producing a detection image based on the at least one selected spectral band and the calibrated raw difference cube; examining the detection image to determine presence of the gas of interest; and outputting a result of the examination. Other methods, systems, and computer program products for detecting the presence of a gas are also described.

  9. 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.

  10. 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.

  11. 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

  12. HIL range performance of notional hyperspectral imaging sensors

    NASA Astrophysics Data System (ADS)

    Hodgkin, Van A.; Howell, Christopher L.

    2016-05-01

    In the use of conventional broadband imaging systems, whether reflective or emissive, scene image contrasts are often so low that target discrimination is difficult or uncertain, and it is contrast that drives human-in-the-loop (HIL) sensor range performance. This situation can occur even when the spectral shapes of the target and background signatures (radiances) across the sensor waveband differ significantly from each other. The fundamental components of broadband image contrast are the spectral integrals of the target and background signatures, and this spectral integration can average away the spectral differences between scene objects. In many low broadband image contrast situations, hyperspectral imaging (HSI) can preserve a greater degree of the intrinsic scene spectral contrast for the display, and more display contrast means greater range performance by a trained observer. This paper documents a study using spectral radiometric signature modeling and the U.S. Army's Night Vision Integrated Performance Model (NV-IPM) to show how waveband selection by a notional HSI sensor using spectral contrast optimization can significantly increase HIL sensor range performance over conventional broadband sensors.

  13. Innovativ Airborne Sensors for Disaster Management

    NASA Astrophysics Data System (ADS)

    Altan, M. O.; Kemper, G.

    2016-06-01

    Disaster management by analyzing changes in the DSM before and after the "event". Advantage of Lidar is that beside rain and clouds, no other weather conditions limit their use. As an active sensor, missions in the nighttime are possible. The new mid-format cameras that make use CMOS sensors (e.g. Phase One IXU1000) can capture data also under poor and difficult light conditions and might will be the first choice for remotely sensed data acquisition in aircrafts and UAVs. UAVs will surely be more and more part of the disaster management on the detailed level. Today equipped with video live cams using RGB and Thermal IR, they assist in looking inside buildings and behind. Thus, they can continue with the aerial survey where airborne anomalies have been detected.

  14. 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.

  15. 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

  16. 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. ...

  17. Surface emissivity and temperature retrieval for a hyperspectral sensor

    SciTech Connect

    Borel, C.C.

    1998-12-01

    With the growing use of hyper-spectral imagers, e.g., AVIRIS in the visible and short-wave infrared there is hope of using such instruments in the mid-wave and thermal IR (TIR) some day. The author believes that this will enable him to get around using the present temperature-emissivity separation algorithms using methods which take advantage of the many channels available in hyper-spectral imagers. A simple fact used in coming up with a novel algorithm is that a typical surface emissivity spectrum are rather smooth compared to spectral features introduced by the atmosphere. Thus, a iterative solution technique can be devised which retrieves emissivity spectra based on spectral smoothness. To make the emissivities realistic, atmospheric parameters are varied using approximations, look-up tables derived from a radiative transfer code and spectral libraries. One such iterative algorithm solves the radiative transfer equation for the radiance at the sensor for the unknown emissivity and uses the blackbody temperature computed in an atmospheric window to get a guess for the unknown surface temperature. By varying the surface temperature over a small range a series of emissivity spectra are calculated. The one with the smoothest characteristic is chosen. The algorithm was tested on synthetic data using MODTRAN and the Salisbury emissivity database.

  18. 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.

  19. 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.

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

    PubMed Central

    Miura, Tomoaki; Huete, Alfredo R.

    2009-01-01

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

  1. 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

  2. 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

  3. Real-time sensor mapping display for airborne imaging sensor test with the adaptive infrared imaging spectroradiometer (AIRIS)

    NASA Astrophysics Data System (ADS)

    Burton, Megan M.; Cruger, William E.; Gittins, Christopher; Kindle, Harry; Ricks, Timothy P.

    2005-11-01

    Captive flight testing (CFT) of sensors and seekers requires accurate data collection and display for sensor performance evaluation. The U.S. Army Redstone Technical Test Center (RTTC), in support of the U.S. Army Edgewood Chemical Biological Center (ECBC), has developed a data collection suite to facilitate airborne test of hyperspectral chemical/biological sensors. The data collection suite combines global positioning system (GPS) tracking, inertial measurement unit (IMU) data, accurate timing streams, and other test scenario information. This data collection suite also contains an advanced real-time display of aircraft and sensor field-of-view information. The latest evolution of this system has been used in support of the Adaptive InfraRed Imaging Spectroradiometer (AIRIS), currently under development by Physical Sciences Incorporated for ECBC. For this test, images from the AIRIS sensor were overlaid on a digitized background of the test area, with latencies of 1 second or less. Detects of surrogate chemicals were displayed and geo-referenced. Video overlay was accurate and reliable. This software suite offers great versatility in the display of imaging sensor data; support of future tests with the AIRIS sensor are planned as the system evolves.

  4. 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

  5. Coherent lidar airborne windshear sensor: performance evaluation.

    PubMed

    Targ, R; Kavaya, M J; Huffaker, R M; Bowles, R L

    1991-05-20

    National attention has focused on the critical problem of detecting and avoiding windshear since the crash on 2 Aug. 1985 of a Lockheed L-1011 at Dallas/Fort Worth International Airport. As part of the NASA/FAA National Integrated Windshear Program, we have defined a measurable windshear hazard index that can be remotely sensed from an aircraft, to give the pilot information about the wind conditions he will experience at some later time if he continues along the present flight path. A technology analysis and end-to-end performance simulation measuring signal-to-noise ratios and resulting wind velocity errors for competing coherent laser radar (lidar) systems have been carried out. The results show that a Ho:YAG lidar at a wavelength of 2.1 microm and a CO(2) lidar at 10.6 microm can give the pilot information about the line-of-sight component of a windshear threat from his present position to a region extending 2-4 km in front of the aircraft. This constitutes a warning time of 20-40 s, even in conditions of moderately heavy precipitation. Using these results, a Coherent Lidar Airborne Shear Sensor (CLASS) that uses a Q-switched CO(2) laser at 10.6 microm is being designed and developed for flight evaluation in the fall of 1991.

  6. Airborne imaging sensors for environmental monitoring & surveillance in support of oil spills & recovery efforts

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R.; Jones, James; Frystacky, Heather; Coppin, Gaelle; Leavaux, Florian; Neyt, Xavier

    2011-11-01

    Collection of pushbroom sensor imagery from a mobile platform requires corrections using inertial measurement units (IMU's) and DGPS in order to create useable imagery for environmental monitoring and surveillance of shorelines in freshwater systems, coastal littoral zones and harbor areas. This paper describes a suite of imaging systems used during collection of hyperspectral imagery in northern Florida panhandle and Gulf of Mexico airborne missions to detect weathered oil in coastal littoral zones. Underlying concepts of pushbroom imagery, the needed corrections for directional changes using DGPS and corrections for platform yaw, pitch, and roll using IMU data is described as well as the development and application of optimal band and spectral regions associated with weathered oil. Pushbroom sensor and frame camera data collected in response to the recent Gulf of Mexico oil spill disaster is presented as the scenario documenting environmental monitoring and surveillance techniques using mobile sensing platforms. Data was acquired during the months of February, March, April and May of 2011. The low altitude airborne systems include a temperature stabilized hyperspectral imaging system capable of up to 1024 spectral channels and 1376 spatial across track pixels flown from 3,000 to 4,500 feet altitudes. The hyperspectral imaging system is collocated with a full resolution high definition video recorder for simultaneous HD video imagery, a 12.3 megapixel digital, a mapping camera using 9 inch film types that yields scanned aerial imagery with approximately 22,200 by 22,200 pixel multispectral imagery (~255 megapixel RGB multispectral images in order to conduct for spectral-spatial sharpening of fused multispectral, hyperspectral imagery. Two high spectral (252 channels) and radiometric sensitivity solid state spectrographs are used for collecting upwelling radiance (sub-meter pixels) with downwelling irradiance fiber optic attachment. These sensors are utilized for

  7. 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.

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

    PubMed Central

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

    2008-01-01

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

  9. 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.

  10. 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.

  11. 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.

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

    USGS Publications Warehouse

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

    2011-01-01

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

  13. 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

  14. 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.

  15. Data dimensionality reduction and data fusion for fast characterization of green coffee samples using hyperspectral sensors.

    PubMed

    Calvini, Rosalba; Foca, Giorgia; Ulrici, Alessandro

    2016-10-01

    Hyperspectral sensors represent a powerful tool for chemical mapping of solid-state samples, since they provide spectral information localized in the image domain in very short times and without the need of sample pretreatment. However, due to the large data size of each hyperspectral image, data dimensionality reduction (DR) is necessary in order to develop hyperspectral sensors for real-time monitoring of large sets of samples with different characteristics. In particular, in this work, we focused on DR methods to convert the three-dimensional data array corresponding to each hyperspectral image into a one-dimensional signal (1D-DR), which retains spectral and/or spatial information. In this way, large datasets of hyperspectral images can be converted into matrices of signals, which in turn can be easily processed using suitable multivariate statistical methods. Obviously, different 1D-DR methods highlight different aspects of the hyperspectral image dataset. Therefore, in order to investigate their advantages and disadvantages, in this work, we compared three different 1D-DR methods: average spectrum (AS), single space hyperspectrogram (SSH) and common space hyperspectrogram (CSH). In particular, we have considered 370 NIR-hyperspectral images of a set of green coffee samples, and the three 1D-DR methods were tested for their effectiveness in sensor fault detection, data structure exploration and sample classification according to coffee variety and to coffee processing method. Principal component analysis and partial least squares-discriminant analysis were used to compare the three separate DR methods. Furthermore, low-level and mid-level data fusion was also employed to test the advantages of using AS, SSH and CSH altogether. Graphical Abstract Key steps in hyperspectral data dimenionality reduction.

  16. Data dimensionality reduction and data fusion for fast characterization of green coffee samples using hyperspectral sensors.

    PubMed

    Calvini, Rosalba; Foca, Giorgia; Ulrici, Alessandro

    2016-10-01

    Hyperspectral sensors represent a powerful tool for chemical mapping of solid-state samples, since they provide spectral information localized in the image domain in very short times and without the need of sample pretreatment. However, due to the large data size of each hyperspectral image, data dimensionality reduction (DR) is necessary in order to develop hyperspectral sensors for real-time monitoring of large sets of samples with different characteristics. In particular, in this work, we focused on DR methods to convert the three-dimensional data array corresponding to each hyperspectral image into a one-dimensional signal (1D-DR), which retains spectral and/or spatial information. In this way, large datasets of hyperspectral images can be converted into matrices of signals, which in turn can be easily processed using suitable multivariate statistical methods. Obviously, different 1D-DR methods highlight different aspects of the hyperspectral image dataset. Therefore, in order to investigate their advantages and disadvantages, in this work, we compared three different 1D-DR methods: average spectrum (AS), single space hyperspectrogram (SSH) and common space hyperspectrogram (CSH). In particular, we have considered 370 NIR-hyperspectral images of a set of green coffee samples, and the three 1D-DR methods were tested for their effectiveness in sensor fault detection, data structure exploration and sample classification according to coffee variety and to coffee processing method. Principal component analysis and partial least squares-discriminant analysis were used to compare the three separate DR methods. Furthermore, low-level and mid-level data fusion was also employed to test the advantages of using AS, SSH and CSH altogether. Graphical Abstract Key steps in hyperspectral data dimenionality reduction. PMID:27342797

  17. Field of view selection for optimal airborne imaging sensor performance

    NASA Astrophysics Data System (ADS)

    Goss, Tristan M.; Barnard, P. Werner; Fildis, Halidun; Erbudak, Mustafa; Senger, Tolga; Alpman, Mehmet E.

    2014-05-01

    The choice of the Field of View (FOV) of imaging sensors used in airborne targeting applications has major impact on the overall performance of the system. Conducting a market survey from published data on sensors used in stabilized airborne targeting systems shows a trend of ever narrowing FOVs housed in smaller and lighter volumes. This approach promotes the ever increasing geometric resolution provided by narrower FOVs, while it seemingly ignores the influences the FOV selection has on the sensor's sensitivity, the effects of diffraction, the influences of sight line jitter and collectively the overall system performance. This paper presents a trade-off methodology to select the optimal FOV for an imaging sensor that is limited in aperture diameter by mechanical constraints (such as space/volume available and window size) by balancing the influences FOV has on sensitivity and resolution and thereby optimizing the system's performance. The methodology may be applied to staring array based imaging sensors across all wavebands from visible/day cameras through to long wave infrared thermal imagers. Some examples of sensor analysis applying the trade-off methodology are given that highlights the performance advantages that can be gained by maximizing the aperture diameters and choosing the optimal FOV for an imaging sensor used in airborne targeting applications.

  18. Airborne Electro-Optical Sensor Simulation System. Final Report.

    ERIC Educational Resources Information Center

    Hayworth, Don

    The total system capability, including all the special purpose and general purpose hardware comprising the Airborne Electro-Optical Sensor Simulation (AEOSS) System, is described. The functional relationship between hardware portions is described together with interface to the software portion of the computer image generation. Supporting rationale…

  19. Methodology for Determining Optimal Exposure Parameters of a Hyperspectral Scanning Sensor

    NASA Astrophysics Data System (ADS)

    Walczykowski, P.; Siok, K.; Jenerowicz, A.

    2016-06-01

    The purpose of the presented research was to establish a methodology that would allow the registration of hyperspectral images with a defined spatial resolution on a horizontal plane. The results obtained within this research could then be used to establish the optimum sensor and flight parameters for collecting aerial imagery data using an UAV or other aerial system. The methodology is based on an user-selected optimal camera exposure parameters (i.e. time, gain value) and flight parameters (i.e. altitude, velocity). A push-broom hyperspectral imager- the Headwall MicroHyperspec A-series VNIR was used to conduct this research. The measurement station consisted of the following equipment: a hyperspectral camera MicroHyperspec A-series VNIR, a personal computer with HyperSpec III software, a slider system which guaranteed the stable motion of the sensor system, a white reference panel and a Siemens star, which was used to evaluate the spatial resolution. Hyperspectral images were recorded at different distances between the sensor and the target- from 5m to 100m. During the registration process of each acquired image, many exposure parameters were changed, such as: the aperture value, exposure time and speed of the camera's movement on the slider. Based on all of the registered hyperspectral images, some dependencies between chosen parameters had been developed: - the Ground Sampling Distance - GSD and the distance between the sensor and the target, - the speed of the camera and the distance between the sensor and the target, - the exposure time and the gain value, - the Density Number and the gain value. The developed methodology allowed us to determine the speed and the altitude of an unmanned aerial vehicle on which the sensor would be mounted, ensuring that the registered hyperspectral images have the required spatial resolution.

  20. 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

  1. Miniature Sensors for Airborne Particulate Matter

    EPA Science Inventory

    Our group is working to design a small,lightweight, low-cost real-time particulate matter(PM) sensor to enable better monitoring of PMconcentrations in air, with the goal of informingpolicymakers and regulators to provide betterpublic health. The sensor reads the massconcentratio...

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. [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

  8. 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.

  9. 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.

  10. Evaluation of onboard hyperspectral-image compression techniques for a parallel push-broom sensor

    SciTech Connect

    Briles, S.

    1996-04-01

    A single hyperspectral imaging sensor can produce frames with spatially-continuous rows of differing, but adjacent, spectral wavelength. If the frame sample-rate of the sensor is such that subsequent hyperspectral frames are spatially shifted by one row, then the sensor can be thought of as a parallel (in wavelength) push-broom sensor. An examination of data compression techniques for such a sensor is presented. The compression techniques are intended to be implemented onboard a space-based platform and to have implementation speeds that match the date rate of the sensor. Data partitions examined extend from individually operating on a single hyperspectral frame to operating on a data cube comprising the two spatial axes and the spectral axis. Compression algorithms investigated utilize JPEG-based image compression, wavelet-based compression and differential pulse code modulation. Algorithm performance is quantitatively presented in terms of root-mean-squared error and root-mean-squared correlation coefficient error. Implementation issues are considered in algorithm development.

  11. A digital sensor simulator of the pushbroom Offner hyperspectral imaging spectrometer.

    PubMed

    Tao, Dongxing; Jia, Guorui; Yuan, Yan; Zhao, Huijie

    2014-12-11

    Sensor simulators can be used in forecasting the imaging quality of a new hyperspectral imaging spectrometer, and generating simulated data for the development and validation of the data processing algorithms. This paper presents a novel digital sensor simulator for the pushbroom Offner hyperspectral imaging spectrometer, which is widely used in the hyperspectral remote sensing. Based on the imaging process, the sensor simulator consists of a spatial response module, a spectral response module, and a radiometric response module. In order to enhance the simulation accuracy, spatial interpolation-resampling, which is implemented before the spatial degradation, is developed to compromise the direction error and the extra aliasing effect. Instead of using the spectral response function (SRF), the dispersive imaging characteristics of the Offner convex grating optical system is accurately modeled by its configuration parameters. The non-uniformity characteristics, such as keystone and smile effects, are simulated in the corresponding modules. In this work, the spatial, spectral and radiometric calibration processes are simulated to provide the parameters of modulation transfer function (MTF), SRF and radiometric calibration parameters of the sensor simulator. Some uncertainty factors (the stability, band width of the monochromator for the spectral calibration, and the integrating sphere uncertainty for the radiometric calibration) are considered in the simulation of the calibration process. With the calibration parameters, several experiments were designed to validate the spatial, spectral and radiometric response of the sensor simulator, respectively. The experiment results indicate that the sensor simulator is valid.

  12. A Digital Sensor Simulator of the Pushbroom Offner Hyperspectral Imaging Spectrometer

    PubMed Central

    Tao, Dongxing; Jia, Guorui; Yuan, Yan; Zhao, Huijie

    2014-01-01

    Sensor simulators can be used in forecasting the imaging quality of a new hyperspectral imaging spectrometer, and generating simulated data for the development and validation of the data processing algorithms. This paper presents a novel digital sensor simulator for the pushbroom Offner hyperspectral imaging spectrometer, which is widely used in the hyperspectral remote sensing. Based on the imaging process, the sensor simulator consists of a spatial response module, a spectral response module, and a radiometric response module. In order to enhance the simulation accuracy, spatial interpolation-resampling, which is implemented before the spatial degradation, is developed to compromise the direction error and the extra aliasing effect. Instead of using the spectral response function (SRF), the dispersive imaging characteristics of the Offner convex grating optical system is accurately modeled by its configuration parameters. The non-uniformity characteristics, such as keystone and smile effects, are simulated in the corresponding modules. In this work, the spatial, spectral and radiometric calibration processes are simulated to provide the parameters of modulation transfer function (MTF), SRF and radiometric calibration parameters of the sensor simulator. Some uncertainty factors (the stability, band width of the monochromator for the spectral calibration, and the integrating sphere uncertainty for the radiometric calibration) are considered in the simulation of the calibration process. With the calibration parameters, several experiments were designed to validate the spatial, spectral and radiometric response of the sensor simulator, respectively. The experiment results indicate that the sensor simulator is valid. PMID:25615727

  13. Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Development

    NASA Technical Reports Server (NTRS)

    Daniels, Taumi S.

    2002-01-01

    In response to recommendations from the National Aviation Weather Program Council, the National Aeronautics and Space Administration (NASA) is working with industry to develop an electronic pilot reporting capability for small aircraft. This paper describes the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) sensor development effort. NASA is working with industry to develop a sensor capable of measuring temperature, relative humidity, magnetic heading, pressure, icing, and average turbulence energy dissipation. Users of the data include National Centers for Environmental Prediction (NCEP) forecast modelers, air traffic controllers, flight service stations, airline operation centers, and pilots. Preliminary results from flight tests are presented.

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

    NASA Astrophysics Data System (ADS)

    Bodechtel, Johann

    2001-01-01

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

  15. 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

  16. 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

  17. Cross-calibration between airborne SAR sensors

    NASA Technical Reports Server (NTRS)

    Zink, Manfred; Olivier, Philippe; Freeman, Anthony

    1993-01-01

    As Synthetic Aperture Radar (SAR) system performance and experience in SAR signature evaluation increase, quantitative analysis becomes more and more important. Such analyses require an absolute radiometric calibration of the complete SAR system. To keep the expenditure on calibration of future multichannel and multisensor remote sensing systems (e.g., X-SAR/SIR-C) within a tolerable level, data from different tracks and different sensors (channels) must be cross calibrated. The 1989 joint E-SAR/DC-8 SAR calibration campaign gave a first opportunity for such an experiment, including cross sensor and cross track calibration. A basic requirement for successful cross calibration is the stability of the SAR systems. The calibration parameters derived from different tracks and the polarimetric properties of the uncalibrated data are used to describe this stability. Quality criteria for a successful cross calibration are the agreement of alpha degree values and the consistency of radar cross sections of equally sized corner reflectors. Channel imbalance and cross talk provide additional quality in case of the polarimetric DC-8 SAR.

  18. 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

  19. 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

  20. CLASS: Coherent Lidar Airborne Shear Sensor. Windshear avoidance

    NASA Technical Reports Server (NTRS)

    Targ, Russell

    1991-01-01

    The coherent lidar airborne shear sensor (CLASS) is an airborne CO2 lidar system being designed and developed by Lockheed Missiles and Space Company, Inc. (LMSC) under contract to NASA Langley Research Center. The goal of this program is to develop a system with a 2- to 4-kilometer range that will provide a warning time of 20 to 40 seconds, so that the pilot can avoid the hazards of low-altitude wind shear under all weather conditions. It is a predictive system which will warn the pilot about a hazard that the aircraft will experience at some later time. The ability of the system to provide predictive warnings of clear air turbulence will also be evaluated. A one-year flight evaluation program will measure the line-of-sight wind velocity from a wide variety of wind fields obtained by an airborne radar, an accelerometer-based reactive wind-sensing system, and a ground-based Doppler radar. The success of the airborne lidar system will be determined by its correlation with the windfield as indicated by the onboard reactive system, which indicates the winds actually experienced by the NASA Boeing 737 aircraft.

  1. 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

  2. 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

  3. Improved Airborne Gravity Results Using New Relative Gravity Sensor Technology

    NASA Astrophysics Data System (ADS)

    Brady, N.

    2013-12-01

    Airborne gravity data has contributed greatly to our knowledge of subsurface geophysics particularly in rugged and otherwise inaccessible areas such as Antarctica. Reliable high quality GPS data has renewed interest in improving the accuracy of airborne gravity systems and recent improvements in the electronic control of the sensor have increased the accuracy and ability of the classic Lacoste and Romberg zero length spring gravity meters to operate in turbulent air conditions. Lacoste and Romberg type gravity meters provide increased sensitivity over other relative gravity meters by utilizing a mass attached to a horizontal beam which is balanced by a ';zero length spring'. This type of dynamic gravity sensor is capable of measuring gravity changes on the order of 0.05 milliGals in laboratory conditions but more commonly 0.7 to 1 milliGal in survey use. The sensor may have errors induced by the electronics used to read the beam position as well as noise induced by unwanted accelerations, commonly turbulence, which moves the beam away from its ideal balance position otherwise known as the reading line. The sensor relies on a measuring screw controlled by a computer which attempts to bring the beam back to the reading line position. The beam is also heavily damped so that it does not react to most unwanted high frequency accelerations. However this heavily damped system is slow to react, particularly in turns where there are very high Eotvos effects. New sensor technology utilizes magnetic damping of the beam coupled with an active feedback system which acts to effectively keep the beam locked at the reading line position. The feedback system operates over the entire range of the system so there is now no requirement for a measuring screw. The feedback system operates at very high speed so that even large turbulent events have minimal impact on data quality and very little, if any, survey line data is lost because of large beam displacement errors. Airborne testing

  4. Collation of earth resources data collected by ERIM airborne sensors

    NASA Technical Reports Server (NTRS)

    Hasell, P. G., Jr.

    1975-01-01

    Earth resources imagery from nine years of data collection with developmental airborne sensors is cataloged for reference. The imaging sensors include single and multiband line scanners and side-looking radars. The operating wavelengths of the sensors include ultraviolet, visible and infrared band scanners, and X- and L-band radar. Imagery from all bands (radar and scanner) were collected at some sites and many sites had repeated coverage. The multiband scanner data was radiometrically calibrated. Illustrations show how the data can be used in earth resource investigations. References are made to published reports which have made use of the data in completed investigations. Data collection sponsors are identified and a procedure described for gaining access to the data.

  5. Simulating and testing autonomous behaviour in multiple airborne sensor systems

    NASA Astrophysics Data System (ADS)

    Smith, Moira I.; Hernandez, Marcel L.; Cooper, Matthew

    2007-04-01

    The Multiple Airborne Sensor Targeting and Evaluation Rig (MASTER) is a high fidelity simulation environment in which data fusion, tracking and sensor management algorithms developed within QinetiQ Ltd. can be demonstrated and evaluated. In this paper we report an observer trajectory planning tool that adds considerable functionality to MASTER. This planning tool can coordinate multiple sensor platforms in tracking highly manoeuvring targets. It does this by applying instantaneous thrusts to each platform, the magnitude of which is chosen to gain maximum observability of the target. We use an efficient search technique to determine the thrust that should be applied to each platform at each time step, and the planning horizon can either be one-step (greedy) or two-step. The measure of performance used in evaluating each potential sensor manoeuvre (thrust) is the posterior Cramer-Rao lower bound (PCRLB), which gives the best possible (lowest mean square error) tracking performance. We exploit a recent novel approach to approximating the PCRLB for manoeuvring target tracking (the "best-fitting Gaussian" (BFG) approach: Hernandez et al., 2005). A closed-form expression gives the BFG approximation at each sampling time. Hence, the PCRLB can be approximated with a very low computational overhead. As a result, the planning tool can be implemented as an aid to decision-making in real-time, even in this time-critical airborne domain. The functionality of MASTER enables one to access the performance of the planning tool in a range of sensor-target scenarios, enabling one to determine the minimal sensor requirement in order to satisfy mission requirements.

  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. 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...

  8. Persistent unmanned airborne network support for cooperative sensors

    NASA Astrophysics Data System (ADS)

    Verma, Ajay; Fernandes, Ronald

    2013-05-01

    In future we expect that UAV platoon based military / civilian missions would require persistent airborne network support for command, control and communication needs for the mission. Highly-dynamic mobile-wireless sensor networks operating in a large region present unique challenges in end-to-end communication for sensor data sharing and data fusion, particularly caused by the time varying connectivity of high-velocity nodes combined with the unreliability of the wireless communication channel. To establish an airborne communication network, a UAV must maintain a link(s) with other UAV(s) and/or base stations. A link between two UAVs is deemed to be established when the linked UAVs are in line of sight as well as within the transmission range of each other. Ideally, all the UAVs as well as the ground stations involved in command, control and communication operations must be fully connected. However, the continuous motion of UAVs poses a challenge to ensure full connectivity of the network. In this paper we explore the dynamic topological network configuration control under mission-related constraints in order to maintain connectivity among sensors enabling data sharing.

  9. 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

  10. 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.

  11. Hyperspectral sensor for gypsum detection on monumental buildings

    NASA Astrophysics Data System (ADS)

    Camaiti, M.; Vettori, S.; Benvenuti, M.; Chiarantini, L.; Costagliola, P.; Di Benedetto, F.; Moretti, S.; Paba, F.; Pecchioni, E.

    2011-09-01

    A portable hyperspectral device (ASD-FieldSpec FR Pro) has been employed for the characterization of alterations affecting the marble facade of the Santa Maria Novella church (XIII cent.) in Florence (Italy). The ASD-FieldSpec FR Pro collects the reflectance spectra of a selected target area (about 1.5 cm2). The spectra of calcite, gypsum and other mineral phases commonly occurring on outdoor surfaces exposed to the urban atmosphere were collected and presented. The spectral features of alteration minerals (depth of reflectance minima) appear to be affected by grain size, phase abundance in addition to lightness (L*) of the target area. Notwithstanding these limitations, the spectra may be used for a qualitative screening of the alteration and, under reasonable assumptions, the reflectance band depth may be used also for quantitative estimation of phase abundance. The monitoring of the conservation state of outdoor surfaces is considered of fundamental importance to plan conservative interventions on historical buildings. Our results point out that portable hyperspectral instruments may be considered as powerful tools for characterizing historical surfaces in a nondestructive and noninvasive way.

  12. Extended SWIR imaging sensors for hyperspectral imaging applications

    NASA Astrophysics Data System (ADS)

    Weber, A.; Benecke, M.; Wendler, J.; Sieck, A.; Hübner, D.; Figgemeier, H.; Breiter, R.

    2016-05-01

    AIM has developed SWIR modules including FPAs based on liquid phase epitaxy (LPE) grown MCT usable in a wide range of hyperspectral imaging applications. Silicon read-out integrated circuits (ROIC) provide various integration and readout modes including specific functions for spectral imaging applications. An important advantage of MCT based detectors is the tunable band gap. The spectral sensitivity of MCT detectors can be engineered to cover the extended SWIR spectral region up to 2.5μm without compromising in performance. AIM developed the technology to extend the spectral sensitivity of its SWIR modules also into the VIS. This has been successfully demonstrated for 384x288 and 1024x256 FPAs with 24μm pitch. Results are presented in this paper. The FPAs are integrated into compact dewar cooler configurations using different types of coolers, like rotary coolers, AIM's long life split linear cooler MCC030 or extreme long life SF100 Pulse Tube cooler. The SWIR modules include command and control electronics (CCE) which allow easy interfacing using a digital standard interface. The development status and performance results of AIM's latest MCT SWIR modules suitable for hyperspectral systems and applications will be presented.

  13. 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...

  14. Differentiating Biological Colours with Few and Many Sensors: Spectral Reconstruction with RGB and Hyperspectral Cameras

    PubMed Central

    Garcia, Jair E.; Girard, Madeline B.; Kasumovic, Michael; Petersen, Phred; Wilksch, Philip A.; Dyer, Adrian G.

    2015-01-01

    Background The ability to discriminate between two similar or progressively dissimilar colours is important for many animals as it allows for accurately interpreting visual signals produced by key target stimuli or distractor information. Spectrophotometry objectively measures the spectral characteristics of these signals, but is often limited to point samples that could underestimate spectral variability within a single sample. Algorithms for RGB images and digital imaging devices with many more than three channels, hyperspectral cameras, have been recently developed to produce image spectrophotometers to recover reflectance spectra at individual pixel locations. We compare a linearised RGB and a hyperspectral camera in terms of their individual capacities to discriminate between colour targets of varying perceptual similarity for a human observer. Main Findings (1) The colour discrimination power of the RGB device is dependent on colour similarity between the samples whilst the hyperspectral device enables the reconstruction of a unique spectrum for each sampled pixel location independently from their chromatic appearance. (2) Uncertainty associated with spectral reconstruction from RGB responses results from the joint effect of metamerism and spectral variability within a single sample. Conclusion (1) RGB devices give a valuable insight into the limitations of colour discrimination with a low number of photoreceptors, as the principles involved in the interpretation of photoreceptor signals in trichromatic animals also apply to RGB camera responses. (2) The hyperspectral camera architecture provides means to explore other important aspects of colour vision like the perception of certain types of camouflage and colour constancy where multiple, narrow-band sensors increase resolution. PMID:25965264

  15. 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.

  16. 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.

  17. 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

  18. An automated data exploitation system for airborne sensors

    NASA Astrophysics Data System (ADS)

    Chen, Hai-Wen; McGurr, Mike

    2014-06-01

    Advanced wide area persistent surveillance (WAPS) sensor systems on manned or unmanned airborne vehicles are essential for wide-area urban security monitoring in order to protect our people and our warfighter from terrorist attacks. Currently, human (imagery) analysts process huge data collections from full motion video (FMV) for data exploitation and analysis (real-time and forensic), providing slow and inaccurate results. An Automated Data Exploitation System (ADES) is urgently needed. In this paper, we present a recently developed ADES for airborne vehicles under heavy urban background clutter conditions. This system includes four processes: (1) fast image registration, stabilization, and mosaicking; (2) advanced non-linear morphological moving target detection; (3) robust multiple target (vehicles, dismounts, and human) tracking (up to 100 target tracks); and (4) moving or static target/object recognition (super-resolution). Test results with real FMV data indicate that our ADES can reliably detect, track, and recognize multiple vehicles under heavy urban background clutters. Furthermore, our example shows that ADES as a baseline platform can provide capability for vehicle abnormal behavior detection to help imagery analysts quickly trace down potential threats and crimes.

  19. Linking morphology to ecosystem structure using air-borne sensors for monitoring the Earth System

    NASA Astrophysics Data System (ADS)

    Taramelli, A.; Giardino, C.; Valentini, E.; Bresciani, M.; Gasperini, L.

    2010-12-01

    Coastal Landscape, and how they change over time, provide the template on which the emerging role of Earth system science (ESS) closely linked with the development of space-borne sensors can stand in the center of a newly emerging science of the Earth's surface, where strong couplings links human dynamics, biology, biochemistry, geochemistry, geomorphology, and fluid dynamics including climate change. Modern views on the behavior of complex systems like the coastal one, allow the interpretation of phenomenological coastal landscape as a stationary landscape-state that correspond to a dynamic equilibrium, and to a self-organized exogenic order of the edge of the chaos. Therefore is essential for a thoroughly understanding of spatiotemporal variations in coastal dynamics and habitat distribution for the source of nonlinearity and complexity in geomorphic system make gathering data appropriate for use in developing and testing models of biological and physical process interacting across a wide range of scale. In this paper a physics based approach was applied to MIVIS (Multi-spectral IR and Visible Imaging Spectrometer) and LiDAR (Light Detection and Ranging) airborne data, simultaneously acquired on 12 May 2009 in order to integrate geomorphological and ecological observations into a detailed macrophytes map of Lake Trasimeno (Italy). Shallow water vegetation, in fact, plays an essential role in determining how coastal morphology and ecosystems dynamics respond to feedbacks between biological and physical processes. An accurate field campaign was carried out during the airborne survey and a collection of different biophysical parameter has been achieved. The purposes of the field observations were twofold. First, field observations allowed identification of biophysical habitats and properties associated both to radiometric and limnological features. Secondly, field reconnaissance allowed identifying significant parameters involved in optical interpretation of the

  20. 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.

  1. 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.

  2. 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.

  3. A fluorescence LIDAR sensor for hyper-spectral time-resolved remote sensing and mapping.

    PubMed

    Palombi, Lorenzo; Alderighi, Daniele; Cecchi, Giovanna; Raimondi, Valentina; Toci, Guido; Lognoli, David

    2013-06-17

    In this work we present a LIDAR sensor devised for the acquisition of time resolved laser induced fluorescence spectra. The gating time for the acquisition of the fluorescence spectra can be sequentially delayed in order to achieve fluorescence data that are resolved both in the spectral and temporal domains. The sensor can provide sub-nanometric spectral resolution and nanosecond time resolution. The sensor has also imaging capabilities by means of a computer-controlled motorized steering mirror featuring a biaxial angular scanning with 200 μradiant angular resolution. The measurement can be repeated for each point of a geometric grid in order to collect a hyper-spectral time-resolved map of an extended target.

  4. A fluorescence LIDAR sensor for hyper-spectral time-resolved remote sensing and mapping.

    PubMed

    Palombi, Lorenzo; Alderighi, Daniele; Cecchi, Giovanna; Raimondi, Valentina; Toci, Guido; Lognoli, David

    2013-06-17

    In this work we present a LIDAR sensor devised for the acquisition of time resolved laser induced fluorescence spectra. The gating time for the acquisition of the fluorescence spectra can be sequentially delayed in order to achieve fluorescence data that are resolved both in the spectral and temporal domains. The sensor can provide sub-nanometric spectral resolution and nanosecond time resolution. The sensor has also imaging capabilities by means of a computer-controlled motorized steering mirror featuring a biaxial angular scanning with 200 μradiant angular resolution. The measurement can be repeated for each point of a geometric grid in order to collect a hyper-spectral time-resolved map of an extended target. PMID:23787661

  5. 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.

  6. 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.

  7. 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.

  8. Self-refreshing characteristics of an airborne particle sensor using a bridged paddle oscillator

    NASA Astrophysics Data System (ADS)

    Choi, Eunsuk; Lee, Seung-Beck; Park, Bonghyun; Sul, Onejae

    2016-05-01

    We report on the self-refreshing characteristics of a micromachined airborne particle sensor. The sensor consists of a bridge-type beam having an oscillating paddle-type particle collector at its center. When a positive potential is applied to the paddle, the sensor is able to attract and collect negatively charged airborne particles while oscillating close to its resonant frequency and thereby measure their density from the change in the oscillating phase at ˜10 pg resolution. When the applied potential is removed, the collected particles are detached from the sensor due to momentum transfer from the oscillating paddle, thus demonstrating a self-refreshing capability.

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. Multipurpose hyperspectral imaging system

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. 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.

  15. Advanced shortwave infrared and Raman hyperspectral sensors for homeland security and law enforcement operations

    NASA Astrophysics Data System (ADS)

    Klueva, Oksana; Nelson, Matthew P.; Gardner, Charles W.; Gomer, Nathaniel R.

    2015-05-01

    Proliferation of chemical and explosive threats as well as illicit drugs continues to be an escalating danger to civilian and military personnel. Conventional means of detecting and identifying hazardous materials often require the use of reagents and/or physical sampling, which is a time-consuming, costly and often dangerous process. Stand-off detection allows the operator to detect threat residues from a safer distance minimizing danger to people and equipment. Current fielded technologies for standoff detection of chemical and explosive threats are challenged by low area search rates, poor targeting efficiency, lack of sensitivity and specificity or use of costly and potentially unsafe equipment such as lasers. A demand exists for stand-off systems that are fast, safe, reliable and user-friendly. To address this need, ChemImage Sensor Systems™ (CISS) has developed reagent-less, non-contact, non-destructive sensors for the real-time detection of hazardous materials based on widefield shortwave infrared (SWIR) and Raman hyperspectral imaging (HSI). Hyperspectral imaging enables automated target detection displayed in the form of image making result analysis intuitive and user-friendly. Application of the CISS' SWIR-HSI and Raman sensing technologies to Homeland Security and Law Enforcement for standoff detection of homemade explosives and illicit drugs and their precursors in vehicle and personnel checkpoints is discussed. Sensing technologies include a portable, robot-mounted and standalone variants of the technology. Test data is shown that supports the use of SWIR and Raman HSI for explosive and drug screening at checkpoints as well as screening for explosives and drugs at suspected clandestine manufacturing facilities.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  17. Sensors and Sensory Processing for Airborne Vibrations in Silk Moths and Honeybees

    PubMed Central

    Ai, Hiroyuki

    2013-01-01

    Insects use airborne vibrations caused by their own movements to control their behaviors and produce airborne vibrations to communicate with conspecific mates. In this review, I use two examples to introduce how insects use airborne vibrations to accurately control behavior or for communication. The first example is vibration-sensitive sensilla along the wing margin that stabilize wingbeat frequency. There are two specialized sensors along the wing margin for detecting the airborne vibration caused by wingbeats. The response properties of these sensors suggest that each sensor plays a different role in the control of wingbeats. The second example is Johnston's organ that contributes to regulating flying speed and perceiving vector information about food sources to hive-mates. There are parallel vibration processing pathways in the central nervous system related with these behaviors, flight and communication. Both examples indicate that the frequency of airborne vibration are filtered on the sensory level and that on the central nervous system level, the extracted vibration signals are integrated with other sensory signals for executing quick adaptive motor response. PMID:23877129

  18. ANALYZING WATER QUALITY WITH IMAGES ACQUIRED FROM AIRBORNE SENSORS

    EPA Science Inventory

    Monitoring different parameters of water quality can be a time consuming and expensive activity. However, the use of airborne light-sensitive (optical) instruments may enhance the abilities of resource managers to monitor water quality in rivers in a timely and cost-effective ma...

  19. 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.

  20. 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.

  1. 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.

  2. Gulf stream ground truth project - Results of the NRL airborne sensors

    NASA Technical Reports Server (NTRS)

    Mcclain, C. R.; Chen, D. T.; Hammond, D. L.

    1980-01-01

    Results of an airborne study of the waves in the Gulf Stream are presented. These results show that the active microwave sensors (high-flight radar and wind-wave radar) provide consistent and accurate estimates of significant wave height and surface wind speed, respectively. The correlation between the wave height measurements of the high-flight radar and a laser profilometer is excellent.

  3. 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.

  4. Dynamic scene generation, multimodal sensor design, and target tracking demonstration for hyperspectral/polarimetric performance-driven sensing

    NASA Astrophysics Data System (ADS)

    Presnar, Michael D.; Raisanen, Alan D.; Pogorzala, David R.; Kerekes, John P.; Rice, Andrew C.

    2010-04-01

    Simulation of moving vehicle tracking has been demonstrated using hyperspectral and polarimetric imagery (HSI/PI). Synthetic HSI/PI image cubes of an urban scene containing moving vehicle content were generated using the Rochester Institute of Technology's Digital Imaging and Remote Sensing Image Generation (DIRSIG) Megascene #1 model. Video streams of sensor-reaching radiance frames collected from a virtual orbiting aerial platform's imaging sensor were used to test adaptive sensor designs in a target tracking application. A hybrid division-of-focal-plane imaging sensor boasting an array of 2×2 superpixels containing both micromirrors and micropolarizers was designed for co-registered HSI/PI aerial remote sensing. Pixel-sized aluminum wire-grid linear polarizers were designed and simulated to measure transmittance, extinction ratio, and diattenuation responses in the presence of an electric field. Wire-grid spacings of 500 [nm] and 80 [nm] were designed for lithographic deposition and etching processes. Both micromirror-relayed panchromatic imagery and micropolarizer-collected PI were orthorectified and then processed by Numerica Corporation's feature-aided target tracker to perform multimodal adaptive performance-driven sensing of moving vehicle targets. Hyperspectral responses of selected target pixels were measured using micromirror-commanded slits to bolster track performance. Unified end-to-end track performance case studies were completed using both panchromatic and degree of linear polarization sensor modes.

  5. 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.

  6. Multi Sensor and Platforms Setups for Various Airborne Applications

    NASA Astrophysics Data System (ADS)

    Kemper, G.; Vasel, R.

    2016-06-01

    To combine various sensors to get a system for specific use became popular within the last 10 years. Metric mid format cameras meanwhile reach the 100 MPix and entered the mapping market to compete with the big format sensors. Beside that also other sensors as SLR Cameras provide high resolution and enter the aerial surveying market for orthophoto production or monitoring applications. Flexibility, purchase-costs, size and weight are common aspects to design multi-sensor systems. Some sensors are useful for mapping while others are part of environmental monitoring systems. Beside classical surveying aircrafts also UL Airplanes, Para/Trikes or UAVs make use of multi sensor systems. Many of them are customer specific while other already are frequently used in the market. This paper aims to show some setup, their application, what are the results and what are the pros and cons of them are.

  7. Spectral characterization of tracheal and esophageal tissues using a hyperspectral camera and fiber optic sensors

    NASA Astrophysics Data System (ADS)

    Nawn, Corinne D.; Souhan, Brian E.; Carter, Robert; Kneapler, Caitlin; Fell, Nicholas; Ye, Jing Yong

    2016-03-01

    During emergency medical situations where the patient has an obstructed airway or necessitates respiratory support, endotracheal intubation (ETI) is the medical technique of placing a tube into the trachea in order to facilitate adequate ventilation of the lungs. In particular, the anatomical, visual and time-sensitive challenges presented in these scenarios, such as in trauma, require a skilled provider in order to successfully place the tube into the trachea. Complications during ETI such as repeated attempts, failed intubation or accidental intubation of the esophagus can lead to severe consequences or ultimately death. Consequently, a need exists for a feedback mechanism to aid providers in performing successful ETI. To investigate potential characteristics to exploit as a feedback mechanism, our study examined the spectral properties of the trachea tissue to determine whether a unique spectral profile exists. In this work, hyperspectral cameras and fiber optic sensors were used to capture and analyze the reflectance profiles of tracheal and esophageal tissues illuminated with UV and white light. Our results show consistent and specific spectral characteristics of the trachea, providing foundational support for using spectral properties to detect features of the trachea.

  8. Effect of atmospheric interference and sensor noise in retrieval of optically active materials in the ocean by hyperspectral remote sensing.

    PubMed

    Levin, Iosif M; Levina, Elizaveta

    2007-10-01

    We present a method to construct the best linear estimate of optically active material concentration from ocean radiance spectra measured through an arbitrary atmosphere layer by a hyperspectral sensor. The algorithm accounts for sensor noise. Optical models of seawater and maritime atmosphere were used to obtain the joint distribution of spectra and concentrations required for the algorithm. The accuracy of phytoplankton retrieval is shown to be substantially lower than that of sediment and dissolved matter. In all cases, the sensor noise noticeably reduces the retrieval accuracy. Additional errors due to atmospheric interference are analyzed, and possible ways to increase the accuracy of retrieval are suggested, such as changing sensor parameters and including a priori information about observation conditions.

  9. 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.

  10. Real-time short-wave infrared hyperspectral conformal imaging sensor for the detection of threat materials

    NASA Astrophysics Data System (ADS)

    Nelson, Matthew P.; Shi, Lei; Zbur, Lucas; Priore, Ryan J.; Treado, Patrick J.

    2016-05-01

    Hyperspectral imaging (HSI) systems can provide sensitive and specific detection and identification of high value targets in the presence of complex backgrounds. However, current generation sensors are typically large and costly to field, and do not usually operate in real-time. Sensors that are capable of real-time operation have to compromise on the number of spectral bands, image definition, and/or the number of targets being detected. Additionally, these systems command a high cost and are typically designed and configured for specific mission profiles, making them unable to adapt to multiple threats within often rapidly evolving and dynamic missions. Despite these shortcomings, HSI-based sensors have proven to be valuable tools, thus resulting in increased demand for HSI technology. A cost-effective sensor system that can easily and quickly adapt to accomplish significantly different tasks in a changing environment is highly desirable. The capability to detect and identify user-defined targets in complex backgrounds under a range of varying conditions with an easily reconfigured, automated, real-time, portable HSI sensor is a critical need. ChemImage Sensor Systems (CISSTM) is developing a novel real-time, adaptable, compressive sensing short-wave infrared (SWIR) hyperspectral imaging technology called the Reconfigurable Conformal Imaging Sensor (RCIS). RCIS will address many shortcomings of current generation systems and offer improvements in operational agility and detection performance, while addressing sensor weight, form factor and cost needs. This paper discusses the development of the RCIS system, and considers its application in various use scenarios.

  11. Optical cloud detection from a disposable airborne sensor

    NASA Astrophysics Data System (ADS)

    Nicoll, Keri; Harrison, R. Giles; Brus, David

    2016-04-01

    In-situ measurement of cloud droplet microphysical properties is most commonly made from manned aircraft platforms due to the size and weight of the instrumentation, which is both costly and typically limited to sampling only a few clouds. This work describes the development of a small, lightweight (<200g), disposable, optical cloud sensor which is designed for use on routine radiosonde balloon flights and also small unmanned aerial vehicle (UAV) platforms. The sensor employs the backscatter principle, using an ultra-bright LED as the illumination source, with a photodiode detector. Scattering of the LED light by cloud droplets generates a small optical signal which is separated from background light fluctuations using a lock-in technique. The signal to noise obtained permits cloud detection using the scattered LED light, even in daytime. During recent field tests in Pallas, Finland, the retrieved optical sensor signal has been compared with the DMT Cloud and Aerosol Spectrometer (CAS) which measures cloud droplets in the size range from 0.5 to 50 microns. Both sensors were installed at the hill top observatory of Sammaltunturi during a field campaign in October and November 2015, which experienced long periods of immersion inside cloud. Preliminary analysis shows very good agreement between the CAPS and the disposable cloud sensor for cloud droplets >5micron effective diameter. Such data and calibration of the sensor will be discussed here, as will simultaneous balloon launches of the optical cloud sensor through the same cloud layers.

  12. Calibration, Sensor Model Improvements and Uncertainty Budget of the Airborne Imaging Spectrometer APEX

    NASA Astrophysics Data System (ADS)

    Hueni, A.

    2015-12-01

    ESA's Airborne Imaging Spectrometer APEX (Airborne Prism Experiment) was developed under the PRODEX (PROgramme de Développement d'EXpériences scientifiques) program by a Swiss-Belgian consortium and entered its operational phase at the end of 2010 (Schaepman et al., 2015). Work on the sensor model has been carried out extensively within the framework of European Metrology Research Program as part of the Metrology for Earth Observation and Climate (MetEOC and MetEOC2). The focus has been to improve laboratory calibration procedures in order to reduce uncertainties, to establish a laboratory uncertainty budget and to upgrade the sensor model to compensate for sensor specific biases. The updated sensor model relies largely on data collected during dedicated characterisation experiments in the APEX calibration home base but includes airborne data as well where the simulation of environmental conditions in the given laboratory setup was not feasible. The additions to the model deal with artefacts caused by environmental changes and electronic features, namely the impact of ambient air pressure changes on the radiometry in combination with dichroic coatings, influences of external air temperatures and consequently instrument baffle temperatures on the radiometry, and electronic anomalies causing radiometric errors in the four shortwave infrared detector readout blocks. Many of these resolved issues might be expected to be present in other imaging spectrometers to some degree or in some variation. Consequently, the work clearly shows the difficulties of extending a laboratory-based uncertainty to data collected under in-flight conditions. The results are hence not only of interest to the calibration scientist but also to the spectroscopy end user, in particular when commercial sensor systems are used for data collection and relevant sensor characteristic information tends to be sparse. Schaepman, et al, 2015. Advanced radiometry measurements and Earth science

  13. Michigan experimental multispectral mapping system: A description of the M7 airborne sensor and its performance

    NASA Technical Reports Server (NTRS)

    Hasell, P. G., Jr.

    1974-01-01

    The development and characteristics of a multispectral band scanner for an airborne mapping system are discussed. The sensor operates in the ultraviolet, visual, and infrared frequencies. Any twelve of the bands may be selected for simultaneous, optically registered recording on a 14-track analog tape recorder. Multispectral imagery recorded on magnetic tape in the aircraft can be laboratory reproduced on film strips for visual analysis or optionally machine processed in analog and/or digital computers before display. The airborne system performance is analyzed.

  14. Measurements of Solar Induced Chlorophyll Fluorescence at 685 nm by Airborne Plant Fluorescence Sensor (APFS)

    NASA Astrophysics Data System (ADS)

    Morgan, F.; Yee, J. H.; Boldt, J.; Cook, W. B.; Corp, L. A.

    2015-12-01

    Solar-induced chlorophyll fluorescence (ChlF) by terrestrial vegetation is linked closely to photosynthetic efficiency that can be exploited to monitor the plant health status and to assess the terrestrial carbon budget from space. The weak, broad continuum ChlF signal can be detected from the fill-in of strong O2 absorption lines or solar Fraunhofer lines in the reflected spectral radiation. The Johns Hopkins University, Applied Physics Laboratory (JHU/APL) Airborne Plant Fluorescence Sensor (APFS) is a triple etalon Fabry-Perot interferometer designed and optimized specifically for the ChlF sensing from an airborne platform using this line fill-in technique. In this paper, we will present the results of APFS ChlF measurements obtained from a NASA Langley King Air during two airborne campaigns (12/12 in 2014 and 5/20 in 2015) over various land, river, and vegetated targets in Virginia during stressed and growth seasons.

  15. Remote Sensing of Chlorophyll Fluorescence by the Airborne Plant Fluorescence Sensor (APFS)

    NASA Astrophysics Data System (ADS)

    Yee, J. H.; Boldt, J.; Cook, W. B.; Morgan, F., II; Demajistre, R.; Cook, B. D.; Corp, L. A.

    2014-12-01

    Solar-induced chlorophyll fluorescence (ChlF) by terrestrial vegetation is linked closely to photosynthetic efficiency that can be exploited to monitor the plant health status and to assess the terrestrial carbon budget from space. The weak, broad continuum ChlF signal can be detected from the amount of fill-in of strong O2 absorption lines or Fraunhofer lines in the reflected solar spectral radiation. The Johns Hopkins University, Applied Physics Laboratory (JHU/APL) Airborne Plant Fluorescence Sensor (APFS) is designed and constructed specifically for airborne and groundbased ChlF measurements using the line fill-in ChlF measurement technique. In this paper, we will present the design of this triple etalon Fabry-Perot imaging instrument and the results of its vegetation fluorescence measurements obtained from the ground in the laboratory and from a NASA Langley King Air during our 2014 airborne campaign over vegetated targets in North Carolina and Virginia.

  16. An integrated decision model for the application of airborne sensors for improved response to accidental and terrorist chemical vapor releases

    NASA Astrophysics Data System (ADS)

    Kapitan, Loginn

    This research created a new model which provides an integrated approach to planning the effective selection and employment of airborne sensor systems in response to accidental or intentional chemical vapor releases. The approach taken was to use systems engineering and decision analysis methods to construct a model architecture which produced a modular structure for integrating both new and existing components into a logical procedure to assess the application of airborne sensor systems to address chemical vapor hazards. The resulting integrated process model includes an internal aggregation model which allowed differentiation among alternative airborne sensor systems. Both models were developed and validated by experts and demonstrated using appropriate hazardous chemical release scenarios. The resultant prototype integrated process model or system fills a current gap in capability allowing improved planning, training and exercise for HAZMAT teams and first responders when considering the selection and employment of airborne sensor systems. Through the research process, insights into the current response structure and how current airborne capability may be most effectively used were generated. Furthermore, the resultant prototype system is tailorable for local, state, and federal application, and can potentially be modified to help evaluate investments in new airborne sensor technology and systems. Better planning, training and preparedness exercising holds the prospect for the effective application of airborne assets for improved response to large scale chemical release incidents. Improved response will result in fewer casualties and lives lost, reduced economic impact, and increased protection of critical infrastructure when faced with accidental and intentional terrorist release of hazardous industrial chemicals. With the prospect of more airborne sensor systems becoming available, this prototype system integrates existing and new tools into an effective

  17. 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.

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

    USGS Publications Warehouse

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

    2007-01-01

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

  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. Handheld and mobile hyperspectral imaging sensors for wide-area standoff detection of explosives and chemical warfare agents

    NASA Astrophysics Data System (ADS)

    Gomer, Nathaniel R.; Gardner, Charles W.; Nelson, Matthew P.

    2016-05-01

    Hyperspectral imaging (HSI) is a valuable tool for the investigation and analysis of targets in complex background with a high degree of autonomy. HSI is beneficial for the detection of threat materials on environmental surfaces, where the concentration of the target of interest is often very low and is typically found within complex scenery. Two HSI techniques that have proven to be valuable are Raman and shortwave infrared (SWIR) HSI. Unfortunately, current generation HSI systems have numerous size, weight, and power (SWaP) limitations that make their potential integration onto a handheld or field portable platform difficult. The systems that are field-portable do so by sacrificing system performance, typically by providing an inefficient area search rate, requiring close proximity to the target for screening, and/or eliminating the potential to conduct real-time measurements. To address these shortcomings, ChemImage Sensor Systems (CISS) is developing a variety of wide-field hyperspectral imaging systems. Raman HSI sensors are being developed to overcome two obstacles present in standard Raman detection systems: slow area search rate (due to small laser spot sizes) and lack of eye-safety. SWIR HSI sensors have been integrated into mobile, robot based platforms and handheld variants for the detection of explosives and chemical warfare agents (CWAs). In addition, the fusion of these two technologies into a single system has shown the feasibility of using both techniques concurrently to provide higher probability of detection and lower false alarm rates. This paper will provide background on Raman and SWIR HSI, discuss the applications for these techniques, and provide an overview of novel CISS HSI sensors focused on sensor design and detection results.

  1. A Micro Aerosol Sensor for the Measurement of Airborne Ultrafine Particles.

    PubMed

    Zhang, Chao; Zhu, Rong; Yang, Wenming

    2016-01-01

    Particle number concentration and particle size are the two key parameters used to characterize exposure to airborne nanoparticles or ultrafine particles that have attracted the most attention. This paper proposes a simple micro aerosol sensor for detecting the number concentration and particle size of ultrafine particles with diameters from 50 to 253 nm based on electrical diffusion charging. The sensor is composed of a micro channel and a couple of planar electrodes printed on two circuit boards assembled in parallel, which thus integrate charging, precipitating and measurement elements into one chip, the overall size of which is 98 × 38 × 25 mm³. The experiment results demonstrate that the sensor is useful for measuring monodisperse aerosol particles with number concentrations from 300 to 2.5 × 10⁴ /cm³ and particle sizes from 50 to 253 nm. The aerosol sensor has a simple structure and small size, which is favorable for use in handheld devices. PMID:26999156

  2. A Micro Aerosol Sensor for the Measurement of Airborne Ultrafine Particles

    PubMed Central

    Zhang, Chao; Zhu, Rong; Yang, Wenming

    2016-01-01

    Particle number concentration and particle size are the two key parameters used to characterize exposure to airborne nanoparticles or ultrafine particles that have attracted the most attention. This paper proposes a simple micro aerosol sensor for detecting the number concentration and particle size of ultrafine particles with diameters from 50 to 253 nm based on electrical diffusion charging. The sensor is composed of a micro channel and a couple of planar electrodes printed on two circuit boards assembled in parallel, which thus integrate charging, precipitating and measurement elements into one chip, the overall size of which is 98 × 38 × 25 mm3. The experiment results demonstrate that the sensor is useful for measuring monodisperse aerosol particles with number concentrations from 300 to 2.5 × 104 /cm3 and particle sizes from 50 to 253 nm. The aerosol sensor has a simple structure and small size, which is favorable for use in handheld devices. PMID:26999156

  3. 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.

  4. NASA DC-8 Airborne Scanning Lidar Sensor Development

    NASA Technical Reports Server (NTRS)

    Nielsen, Norman B.; Uthe, Edward E.; Kaiser, Robert D.; Tucker, Michael A.; Baloun, James E.; Gorordo, Javier G.

    1996-01-01

    The NASA DC-8 aircraft is used to support a variety of in-situ and remote sensors for conducting environmental measurements over global regions. As part of the atmospheric effects of aviation program (AEAP) the DC-8 is scheduled to conduct atmospheric aerosol and gas chemistry and radiation measurements of subsonic aircraft contrails and cirrus clouds. A scanning lidar system is being developed for installation on the DC-8 to support and extend the domain of the AEAP measurements. Design and objectives of the DC-8 scanning lidar are presented.

  5. NASA DC-8 airborne scanning LIDAR sensor development

    SciTech Connect

    Nielsen, N.B.; Uthe, E.E.; Kaiser, R.D.

    1996-11-01

    The NASA DC-8 aircraft is used to support a variety of in-situ and remote sensors for conducting environmental measurements over global regions. As part of the atmospheric effects of aviation program (AEAP) the DC-8 is scheduled to conduct atmospheric aerosol and gas chemistry and radiation measurements of subsonic aircraft contrails and cirrus clouds. A scanning lidar system is being developed for installation on the DC-8 to support and extend the domain of the AEAP measurements. Design and objectives of the DC-8 scanning lidar are presented. 4 figs.

  6. DMD diffraction measurements to support design of projectors for test and evaluation of multispectral and hyperspectral imaging sensors

    NASA Astrophysics Data System (ADS)

    Rice, Joseph P.; Neira, Jorge E.; Kehoe, Michael; Swanson, Rand

    2009-02-01

    We describe our use of Digital Micromirror Devices (DMDs) for the performance testing, characterization, calibration, and system-level data product validation of multispectral and hyperspectral imaging sensors. We have developed a visible Hyperspectral Image Projector (HIP), which is capable of projecting any combination of many different arbitrarily programmable basis spectra into each image pixel at up to video frame rates. For the full HIP, we use a scheme whereby one DMD array is used in a spectrally programmable source, to produce light having the spectra of materials in the scene (i.e. grass, ocean, target, etc), and a second DMD, optically in series with the first, reflects any combination of these programmable spectra into the pixels of a 1024 ×768 element spatial image, thereby producing temporally-integrated 2D images having spectrally-mixed pixels. The HIP goes beyond conventional Digital Light Processing (DLP) projectors in that each spatial pixel can have an arbitrary spectrum, not just an arbitrary color. As such, the resulting spectral and spatial content of the projected image can simulate realistic scenes that a sensor system must acquire during its use, and can be calibrated using NIST reference instruments. Here we discuss our current HIP developments that span the visible/infrared spectral range of 380 nm through 5400 nm, with particular emphasis on DMD diffraction efficiency measurements in the infrared part of this range.

  7. The Multi-Center Airborne Coherent Atmospheric Wind Sensor: Recent Measurements and Future Applications

    NASA Technical Reports Server (NTRS)

    Rothermel, Jeffry; Cutten, Dean R.; Hardesty, R. Michael; Howell, James N.; Darby, Lisa S.; Tratt, David M.; Menzies, Robert T.

    1999-01-01

    The coherent Doppler lidar, when operated from an airborne platform, offers a unique measurement capability for study of atmospheric dynamical and physical properties. This is especially true for scientific objectives requiring measurements in optically-clear air, where other remote sensing technologies such as Doppler radar are at a disadvantage in terms of spatial resolution and coverage. Recent experience suggests airborne coherent Doppler lidar can yield unique wind measurements of--and during operation within--extreme weather phenomena. This paper presents the first airborne coherent Doppler lidar measurements of hurricane wind fields. The lidar atmospheric remote sensing groups of National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, National Oceanic and Atmospheric Administration (NOAA) Environmental Technology Laboratory, and Jet Propulsion Laboratory jointly developed an airborne lidar system, the Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS). The centerpiece of MACAWS is the lidar transmitter from the highly successful NOAA Windvan. Other field-tested lidar components have also been used, when feasible, to reduce costs and development time. The methodology for remotely sensing atmospheric wind fields with scanning coherent Doppler lidar was demonstrated in 1981; enhancements were made and the system was reflown in 1984. MACAWS has potentially greater scientific utility, compared to the original airborne scanning lidar system, owing to a factor of approx. 60 greater energy-per-pulse from the NOAA transmitter. MACAWS development was completed and the system was first flown in 1995. Following enhancements to improve performance, the system was re-flown in 1996 and 1998. The scientific motivation for MACAWS is three-fold: obtain fundamental measurements of subgrid scale (i.e., approx. 2-200 km) processes and features which may be used to improve parameterizations in hydrological, climate, and general

  8. Principal Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Sensors. Part I; Theoretical Concept

    NASA Technical Reports Server (NTRS)

    Liu, Xu; Smith, William L.; Zhou, Daniel K.; Larar, Allen

    2005-01-01

    Modern infrared satellite sensors such as Atmospheric Infrared Sounder (AIRS), Cosmic Ray Isotope Spectrometer (CrIS), Thermal Emission Spectrometer (TES), Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and Infrared Atmospheric Sounding Interferometer (IASI) are capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, super fast radiative transfer models are needed. This paper presents a novel radiative transfer model based on principal component analysis. Instead of predicting channel radiance or transmittance spectra directly, the Principal Component-based Radiative Transfer Model (PCRTM) predicts the Principal Component (PC) scores of these quantities. This prediction ability leads to significant savings in computational time. The parameterization of the PCRTM model is derived from properties of PC scores and instrument line shape functions. The PCRTM is very accurate and flexible. Due to its high speed and compressed spectral information format, it has great potential for super fast one-dimensional physical retrievals and for Numerical Weather Prediction (NWP) large volume radiance data assimilation applications. The model has been successfully developed for the National Polar-orbiting Operational Environmental Satellite System Airborne Sounder Testbed - Interferometer (NAST-I) and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is able to include multiple scattering calculations to account for clouds and aerosols.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Development

    NASA Technical Reports Server (NTRS)

    Daniels, Taumi S.; Tsoucalas, George; Anderson, Mark; Mulally, Daniel; Moninger, William; Mamrosh, Richard

    2004-01-01

    One of the recommendations of the National Aviation Weather Program Council was to expand and institutionalize the generation, dissemination, and use of automated pilot reports (PIREPS) to the full spectrum of the aviation community, including general aviation. In response to this and other similar recommendations, NASA initiated cooperative research into the development of an electronic pilot reporting capability (Daniels 2002). The ultimate goal is to develop a small low-cost sensor, collect useful meteorological observations below 25,000 ft., downlink the data in near real time, and use the data to improve weather forecasts. Primary users of the data include pilots, who are one targeted audience for the improved weather information that will result from the TAMDAR data. The weather data will be disseminated and used to improve aviation safety by providing pilots with enhanced weather situational awareness. In addition, the data will be used to improve the accuracy and timeliness of weather forecasts. Other users include air traffic controllers, flight service stations, and airline weather centers. Additionally, the meteorological data collected by TAMDAR is expected to have a significant positive impact on forecast accuracy for ground based applications.

  17. Ultrawideband synthetic vision sensor for airborne wire detection

    NASA Astrophysics Data System (ADS)

    Fontana, Robert J.; Larrick, J. F.; Cade, Jeffrey E.; Rivers, Eugene P., Jr.

    1998-07-01

    A low cost, miniature ultra wideband (UWB) radar has demonstrated the ability to detect suspended wires and other small obstacles at distances exceeding several hundred feet using an average output power of less than 10 microwatts. Originally developed as a high precision UWB radar altimeter for the Navy's Program Executive Office for Unmanned Aerial Vehicles and Cruise Missiles, an improved sensitivity version was recently developed for the Naval Surface Warfare Center (NSWC Dahlgren Division) as part of the Marine Corps Warfighting Laboratory's Hummingbird program for rotary wing platforms. Utilizing a short pulse waveform of approximately 2.5 nanoseconds in duration, the receiver processor exploits the leading edge of the radar return pulse to achieve range resolutions of less than one foot. The resultant 400 MHz bandwidth spectrum produces both a broad frequency excitation for enhanced detection, as well as a low probability of intercept and detection (LPI/D) signature for covert applications. This paper describes the design and development of the ultra wideband sensor, as well as performance results achieved during field testing at NSWC's Dahlgren, VA facility. These results are compared with those achieved with a high resolution EHF radar and a laser-based detection system.

  18. Radiometric stability assessment of an airborne photogrammetric sensor in a test field

    NASA Astrophysics Data System (ADS)

    Markelin, Lauri; Honkavaara, Eija; Hakala, Teemu; Suomalainen, Juha; Peltoniemi, Jouni

    Radiometric stability is a desired property of digital photogrammetric large-format sensors. This article presents a methodology for determining the radiometric stability of airborne imaging sensors in operational conditions in a test field and the results of stability evaluation of a large-format photogrammetric frame sensor DMC, from Intergraph. The imagery was collected in two days using nine different exposure settings, and images collected with variable exposure time and aperture were compared. The results showed promising stability in many cases, up to a level of 2% of the radiance, but less favorable results also appeared. Possible reasons for the unfavorable results could be the limitations of the experimental set-up or the instability of the sensor. DMC showed high radiometric performance potential, but high sensitivity to the exposure settings. Based on the results, recommendations for the future test field calibration and validation procedures were given. One limitation of the analysis was the insufficient information about the sensor stability potential; proposals were given to sensor manufacturers concerning the necessary information.

  19. 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.

  20. Underground and airborne matter-wave inertial sensors: towards fundamental tests of gravitation

    NASA Astrophysics Data System (ADS)

    Bouyer, Philippe

    2012-07-01

    Matter-wave inertial sensing relies on the capability of manipulating the coherent wave nature of matter to build an interferometer and accurately measure a phase difference. Since the massive particle associated to the matter wave senses inertial effects, the interferometer represents an accurate inertial probe. Atom interferometers have benefited from the outstanding developments of laser-cooling techniques and reached accuracies comparable to those of inertial sensors based on optical interferometry. Thanks to their long term stability, they offer a breakthrough advance in accelerometry, gyroscopy and gravimetry, for applications to inertial guidance, geoid determinations, geophysics and metrology. They are also excellent candidates for laboratory-based tests of general relativity that could compete with the current tests using astronomical or macroscopic bodies. For example, they may provide new answers to the question of whether the free fall acceleration of a particle is universal, i.e. independent of its internal composition and quantum properties. We report here the first operation of an airborne quantum inertial sensor. We highlight their promising applications to inertial navigation and Earth observation. We also describe the improvement of the quantum sensor sensitivity in weightlessness, and discuss the possibility to conduct airborne or spaceborne tests of the Universality of Free Fall with quantum objects. We finally describe a matter-wave laser based interferometric gravitational antenna (MIGA). This infrastructure will allow for measuring with unprecedented resolution variations of the Earths gravity and of the strain of space-time allowing for enhancing the capabilities of existing and future gravitational wave detectors.

  1. Radiometric Normalization of Large Airborne Image Data Sets Acquired by Different Sensor Types

    NASA Astrophysics Data System (ADS)

    Gehrke, S.; Beshah, B. T.

    2016-06-01

    Generating seamless mosaics of aerial images is a particularly challenging task when the mosaic comprises a large number of im-ages, collected over longer periods of time and with different sensors under varying imaging conditions. Such large mosaics typically consist of very heterogeneous image data, both spatially (different terrain types and atmosphere) and temporally (unstable atmo-spheric properties and even changes in land coverage). We present a new radiometric normalization or, respectively, radiometric aerial triangulation approach that takes advantage of our knowledge about each sensor's properties. The current implementation supports medium and large format airborne imaging sensors of the Leica Geosystems family, namely the ADS line-scanner as well as DMC and RCD frame sensors. A hierarchical modelling - with parameters for the overall mosaic, the sensor type, different flight sessions, strips and individual images - allows for adaptation to each sensor's geometric and radiometric properties. Additional parameters at different hierarchy levels can compensate radiome-tric differences of various origins to compensate for shortcomings of the preceding radiometric sensor calibration as well as BRDF and atmospheric corrections. The final, relative normalization is based on radiometric tie points in overlapping images, absolute radiometric control points and image statistics. It is computed in a global least squares adjustment for the entire mosaic by altering each image's histogram using a location-dependent mathematical model. This model involves contrast and brightness corrections at radiometric fix points with bilinear interpolation for corrections in-between. The distribution of the radiometry fixes is adaptive to each image and generally increases with image size, hence enabling optimal local adaptation even for very long image strips as typi-cally captured by a line-scanner sensor. The normalization approach is implemented in HxMap software. It has been

  2. Extracting dynamic spatial data from airborne imaging sensors to support traffic flow estimation

    NASA Astrophysics Data System (ADS)

    Toth, C. K.; Grejner-Brzezinska, D.

    The recent transition from analog to totally digital data acquisition and processing techniques in airborne surveying represents a major milestone in the evolution of spatial information science and practice. On one hand, the improved quality of the primary sensor data can provide the foundation for better automation of the information extraction processes. This phenomenon is also strongly supported by continuously expanding computer technology, which offers almost unlimited processing power. On the other hand, the variety of the data, including rich information content and better temporal characteristics, acquired by the new digital sensors and coupled with rapidly advancing processing techniques, is broadening the applications of airborne surveying. One of these new application areas is traffic flow extraction aimed at supporting better traffic monitoring and management. Transportation mapping has always represented a significant segment of civilian mapping and is mainly concerned with road corridor mapping for design and engineering purposes, infrastructure mapping and facility management, and more recently, environmental mapping. In all these cases, the objective of the mapping is to extract the static features of the object space, such as man-made and natural objects, typically along the road network. In contrast, the traffic moving in the transportation network represents a very dynamic environment, which complicates the spatial data extraction processes as the signals of moving vehicles should be identified and removed. Rather than removing and discarding the signals, however, they can be turned into traffic flow information. This paper reviews initial research efforts to extract traffic flow information from laserscanner and digital camera sensors installed in airborne platforms.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  4. Parameterization of gaseous constituencies concentration profiles in the planetary boundary layer as required in support of airborne and satellite borne sensors

    NASA Technical Reports Server (NTRS)

    Kindle, E. C.; Condon, E.; Casas, J.

    1976-01-01

    The research to develop the capabilities for sensing air pollution constituencies using satellite or airborne remote sensors is reported. Sensor evaluation and calibration are analyzed including data reduction. The proposed follow-on research is presented.

  5. 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.

  6. New Airborne Sensors and Platforms for Solving Specific Tasks in Remote Sensing

    NASA Astrophysics Data System (ADS)

    Kemper, G.

    2012-07-01

    A huge number of small and medium sized sensors entered the market. Today's mid format sensors reach 80 MPix and allow to run projects of medium size, comparable with the first big format digital cameras about 6 years ago. New high quality lenses and new developments in the integration prepared the market for photogrammetric work. Companies as Phase One or Hasselblad and producers or integrators as Trimble, Optec, and others utilized these cameras for professional image production. In combination with small camera stabilizers they can be used also in small aircraft and make the equipment small and easy transportable e.g. for rapid assessment purposes. The combination of different camera sensors enables multi or hyper-spectral installations e.g. useful for agricultural or environmental projects. Arrays of oblique viewing cameras are in the market as well, in many cases these are small and medium format sensors combined as rotating or shifting devices or just as a fixed setup. Beside the proper camera installation and integration, also the software that controls the hardware and guides the pilot has to solve much more tasks than a normal FMS did in the past. Small and relatively cheap Laser Scanners (e.g. Riegl) are in the market and a proper combination with MS Cameras and an integrated planning and navigation is a challenge that has been solved by different softwares. Turnkey solutions are available e.g. for monitoring power line corridors where taking images is just a part of the job. Integration of thermal camera systems with laser scanner and video capturing must be combined with specific information of the objects stored in a database and linked when approaching the navigation point.

  7. 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

  8. 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

  9. Efficient method for the determination of image correspondence in airborne applications using inertial sensors.

    PubMed

    Woods, Matthew; Katsaggelos, Aggelos

    2013-01-01

    This paper presents a computationally efficient method for the measurement of a dense image correspondence vector field using supplementary data from an inertial navigation sensor (INS). The application is suited to airborne imaging systems, such as an unmanned air vehicle, where size, weight, and power restrictions limit the amount of onboard processing available. The limited processing will typically exclude the use of traditional, but computationally expensive, optical flow and block matching algorithms, such as Lucas-Kanade, Horn-Schunck, or the adaptive rood pattern search. Alternatively, the measurements obtained from an INS, on board the platform, lead to a closed-form solution to the correspondence field. Airborne platforms are well suited to this application because they already possess INSs and global positioning systems as part of their existing avionics package. We derive the closed-form solution for the image correspondence vector field based on the INS data. We then show, through both simulations and real flight data, that the closed-form inertial sensor solution outperforms traditional optical flow and block matching methods.

  10. Continued development of a portable widefield hyperspectral imaging (HSI) sensor for standoff detection of explosive, chemical, and narcotic residues

    NASA Astrophysics Data System (ADS)

    Nelson, Matthew P.; Gardner, Charles W.; Klueva, Oksana; Tomas, David

    2014-05-01

    Passive, standoff detection of chemical, explosive and narcotic threats employing widefield, shortwave infrared (SWIR) hyperspectral imaging (HSI) continues to gain acceptance in defense and security fields. A robust and user-friendly portable platform with such capabilities increases the effectiveness of locating and identifying threats while reducing risks to personnel. In 2013 ChemImage Sensor Systems (CISS) introduced Aperio, a handheld sensor, using real-time SWIR HSI for wide area surveillance and standoff detection of explosives, chemical threats, and narcotics. That SWIR HSI system employed a liquid-crystal tunable filter for real-time automated detection and display of threats. In these proceedings, we report on a next generation device called VeroVision™, which incorporates an improved optical design that enhances detection performance at greater standoff distances with increased sensitivity and detection speed. A tripod mounted sensor head unit (SHU) with an optional motorized pan-tilt unit (PTU) is available for precision pointing and sensor stabilization. This option supports longer standoff range applications which are often seen at checkpoint vehicle inspection where speed and precision is necessary. Basic software has been extended to include advanced algorithms providing multi-target display functionality, automatic threshold determination, and an automated detection recipe capability for expanding the library as new threats emerge. In these proceedings, we report on the improvements associated with the next generation portable widefield SWIR HSI sensor, VeroVision™. Test data collected during development are presented in this report which supports the targeted applications for use of VeroVision™ for screening residue and bulk levels of explosive and drugs on vehicles and personnel at checkpoints as well as various applications for other secure areas. Additionally, we highlight a forensic application of the technology for assisting forensic

  11. Chemometric analysis of multi-sensor hyperspectral images of coarse mode aerosol particles for the image-based investigation on aerosol particles

    NASA Astrophysics Data System (ADS)

    Ofner, Johannes; Kamilli, Katharina A.; Eitenberger, Elisabeth; Friedbacher, Gernot; Lendl, Bernhard; Held, Andreas; Lohninger, Hans

    2015-04-01

    Multi-sensor hyperspectral imaging is a novel technique, which allows the determination of composition, chemical structure and pure components of laterally resolved samples by chemometric analysis of different hyperspectral datasets. These hyperspectral datasets are obtained by different imaging methods, analysing the same sample spot and superimposing the hyperspectral data to create a single multi-sensor dataset. Within this study, scanning electron microscopy (SEM), Raman and energy-dispersive X-ray spectroscopy (EDX) images were obtained from size-segregated aerosol particles, sampled above Western Australian salt lakes. The particles were collected on aluminum foils inside a 2350 L Teflon chamber using a Sioutas impactor, sampling aerosol particles of sizes between 250 nm and 10 µm. The complex composition of the coarse-mode particles can be linked to primary emissions of inorganic species as well as to oxidized volatile organic carbon (VOC) emissions. The oxidation products of VOC emissions are supposed to form an ultra-fine nucleation mode, which was observed during several field campaigns between 2006 and 2013. The aluminum foils were analysed using chemical imaging and electron microscopy. A Horiba LabRam 800HR Raman microscope was used for vibrational mapping of an area of about 100 µm x 100 µm of the foils at a resolution of about 1 µm. The same area was analysed using a Quanta FEI 200 electron microscope (about 250 nm resolution). In addition to the high-resolution image, the elemental composition could be investigated using energy-dispersive X-ray spectroscopy. The obtained hyperspectral images were combined into a multi-sensor dataset using the software package Imagelab (Epina Software Labs, www.imagelab.at). After pre-processing of the images, the multi-sensor hyperspectral dataset was analysed using several chemometric methods such as principal component analysis (PCA), hierarchical cluster analysis (HCA) and other multivariate methods. Vertex

  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. 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.

  14. 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.

  15. 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.

  16. The Laser Vegetation Imaging Sensor (LVIS): An Airborne Laser Altimeter for Mapping Vegetation and Topography

    NASA Technical Reports Server (NTRS)

    Bryan, J.; Rabine, David L.

    1998-01-01

    The Laser Vegetation Imaging Sensor (LVIS) is an airborne laser altimeter designed to quickly and extensively map surface topography as well as the relative heights of other reflecting surfaces within the laser footprint. Since 1997, this instrument has primarily been used as the airborne simulator for the Vegetation Canopy Lidar (VCL) mission, a spaceborne mission designed to measure tree height, vertical structure and ground topography (including sub-canopy topography). LVIS is capable of operating from 500 m to 10 km above ground level with footprint sizes from 1 to 60 m. Laser footprints can be randomly spaced within the 7 degree telescope field-of-view, constrained only by the operating frequency of the ND:YAG Q-switched laser (500 Hz). A significant innovation of the LVIS altimeter is that all ranging, waveform recording, and range gating are performed using a single digitizer, clock base, and detector. A portion of the outgoing laser pulse is fiber-optically fed into the detector used to collect the return signal and this entire time history of the outgoing and return pulses is digitized at 500 Msamp/sec. The ground return is then located using software digital signal processing, even in the presence of visibly opaque clouds. The surface height distribution of all reflecting surfaces within the laser footprint can be determined, for example, tree height and ground elevation. To date, the LVIS system has been used to monitor topographic change at Long Valley caldera, CA, as part of NASA's Topography and Surface Change program, and to map tree structure and sub-canopy topography at the La Selva Biological Research Station in Costa Rica, as part of the pre-launch calibration activities for the VCL mission. We present results that show the laser altimeter consistently and accurately maps surface topography, including sub-canopy topography, and vegetation height and structure. These results confirm the measurement concept of VCL and highlight the benefits of

  17. 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

  18. A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales

    NASA Astrophysics Data System (ADS)

    Ghosh, Aniruddha; Fassnacht, Fabian Ewald; Joshi, P. K.; Koch, Barbara

    2014-02-01

    Knowledge of tree species distribution is important worldwide for sustainable forest management and resource evaluation. The accuracy and information content of species maps produced using remote sensing images vary with scale, sensor (optical, microwave, LiDAR), classification algorithm, verification design and natural conditions like tree age, forest structure and density. Imaging spectroscopy reduces the inaccuracies making use of the detailed spectral response. However, the scale effect still has a strong influence and cannot be neglected. This study aims to bridge the knowledge gap in understanding the scale effect in imaging spectroscopy when moving from 4 to 30 m pixel size for tree species mapping, keeping in mind that most current and future hyperspectral satellite based sensors work with spatial resolution around 30 m or more. Two airborne (HyMAP) and one spaceborne (Hyperion) imaging spectroscopy dataset with pixel sizes of 4, 8 and 30 m, respectively were available to examine the effect of scale over a central European forest. The forest under examination is a typical managed forest with relatively homogenous stands featuring mostly two canopy layers. Normalized digital surface model (nDSM) derived from LiDAR data was used additionally to examine the effect of height information in tree species mapping. Six different sets of predictor variables (reflectance value of all bands, selected components of a Minimum Noise Fraction (MNF), Vegetation Indices (VI) and each of these sets combined with LiDAR derived height) were explored at each scale. Supervised kernel based (Support Vector Machines) and ensemble based (Random Forest) machine learning algorithms were applied on the dataset to investigate the effect of the classifier. Iterative bootstrap-validation with 100 iterations was performed for classification model building and testing for all the trials. For scale, analysis of overall classification accuracy and kappa values indicated that 8 m spatial

  19. Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

    PubMed Central

    Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier

    2009-01-01

    The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989

  20. Airborne Digital Sensor System and GPS-aided inertial technology for direct geopositioning in rough terrain

    USGS Publications Warehouse

    Sanchez, Richard D.

    2004-01-01

    High-resolution airborne digital cameras with onboard data collection based on the Global Positioning System (GPS) and inertial navigation systems (INS) technology may offer a real-time means to gather accurate topographic map information by reducing ground control and eliminating aerial triangulation. Past evaluations of this integrated system over relatively flat terrain have proven successful. The author uses Emerge Digital Sensor System (DSS) combined with Applanix Corporation?s Position and Orientation Solutions for Direct Georeferencing to examine the positional mapping accuracy in rough terrain. The positional accuracy documented in this study did not meet large-scale mapping requirements owing to an apparent system mechanical failure. Nonetheless, the findings yield important information on a new approach for mapping in Antarctica and other remote or inaccessible areas of the world.

  1. 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.

  2. Iterative retrieval of surface emissivity and temperature for a hyperspectral sensor

    SciTech Connect

    Borel, C.C.

    1997-11-01

    The central problem of temperature-emissivity separation is that we obtain N spectral measurements of radiance and need to find N + 1 unknowns (N emissivities and one temperature). To solve this problem in the presence of the atmosphere we need to find even more unknowns: N spectral transmissions {tau}{sub atmo}({lambda}) up-welling path radiances L{sub path}{up_arrow}({lambda}) and N down-welling path radiances L{sub path}{down_arrow}({lambda}). Fortunately there are radiative transfer codes such as MODTRAN 3 and FASCODE available to get good estimates of {tau}{sub atmo}({lambda}), L{sub path}{up_arrow}({lambda}) and L{sub path}{down_arrow}({lambda}) in the order of a few percent. With the growing use of hyperspectral imagers, e.g. AVIRIS in the visible and short-wave infrared there is hope of using such instruments in the mid-wave and thermal IR (TIR) some day. We believe that this will enable us to get around using the present temperature - emissivity separation (TES) algorithms using methods which take advantage of the many channels available in hyperspectral imagers. The first idea we had is to take advantage of the simple fact that a typical surface emissivity spectrum is rather smooth compared to spectral features introduced by the atmosphere. Thus iterative solution techniques can be devised which retrieve emissivity spectra {epsilon} based on spectral smoothness. To make the emissivities realistic, atmospheric parameters are varied using approximations, look-up tables derived from a radiative transfer code and spectral libraries. By varying the surface temperature over a small range a series of emissivity spectra are calculated. The one with the smoothest characteristic is chosen. The algorithm was tested on synthetic data using MODTRAN and the Salisbury emissivity database.

  3. Correction of systematic spatial noise in push-broom hyperspectral sensors: application to CHRIS/PROBA images.

    PubMed

    Gómez-Chova, Luis; Alonso, Luis; Guanter, Luis; Camps-Valls, Gustavo; Calpe, Javier; Moreno, José

    2008-10-01

    Hyperspectral remote sensing images are affected by different types of noise. In addition to typical random noise, nonperiodic partially deterministic disturbance patterns generally appear in the data. These patterns, which are intrinsic to the image formation process, are characterized by a high degree of spatial and spectral coherence. We present a new technique that faces the problem of removing the spatially coherent noise known as vertical striping, usually found in images acquired by push-broom sensors. The developed methodology is tested on data acquired by the Compact High Resolution Imaging Spectrometer (CHRIS) onboard the Project for On-board Autonomy (PROBA) orbital platform, which is a typical example of a push-broom instrument exhibiting a relatively high noise component. The proposed correction method is based on the hypothesis that the vertical disturbance presents higher spatial frequencies than the surface radiance. A technique to exclude the contribution of the spatial high frequencies of the surface from the destriping process is introduced. First, the performance of the proposed algorithm is tested on a set of realistic synthetic images with added modeled noise in order to quantify the noise reduction and the noise estimation accuracy. Then, algorithm robustness is tested on more than 350 real CHRIS images from different sites, several acquisition modes (different spatial and spectral resolutions), and covering the full range of possible sensor temperatures. The proposed algorithm is benchmarked against the CHRIS reference algorithm. Results show excellent rejection of the noise pattern with respect to the original CHRIS images, especially improving the removal in those scenes with a natural high contrast. However, some low-frequency components still remain. In addition, the developed correction model captures and corrects the dependency of the noise patterns on sensor temperature, which confirms the robustness of the presented approach. PMID

  4. Correction of systematic spatial noise in push-broom hyperspectral sensors: application to CHRIS/PROBA images.

    PubMed

    Gómez-Chova, Luis; Alonso, Luis; Guanter, Luis; Camps-Valls, Gustavo; Calpe, Javier; Moreno, José

    2008-10-01

    Hyperspectral remote sensing images are affected by different types of noise. In addition to typical random noise, nonperiodic partially deterministic disturbance patterns generally appear in the data. These patterns, which are intrinsic to the image formation process, are characterized by a high degree of spatial and spectral coherence. We present a new technique that faces the problem of removing the spatially coherent noise known as vertical striping, usually found in images acquired by push-broom sensors. The developed methodology is tested on data acquired by the Compact High Resolution Imaging Spectrometer (CHRIS) onboard the Project for On-board Autonomy (PROBA) orbital platform, which is a typical example of a push-broom instrument exhibiting a relatively high noise component. The proposed correction method is based on the hypothesis that the vertical disturbance presents higher spatial frequencies than the surface radiance. A technique to exclude the contribution of the spatial high frequencies of the surface from the destriping process is introduced. First, the performance of the proposed algorithm is tested on a set of realistic synthetic images with added modeled noise in order to quantify the noise reduction and the noise estimation accuracy. Then, algorithm robustness is tested on more than 350 real CHRIS images from different sites, several acquisition modes (different spatial and spectral resolutions), and covering the full range of possible sensor temperatures. The proposed algorithm is benchmarked against the CHRIS reference algorithm. Results show excellent rejection of the noise pattern with respect to the original CHRIS images, especially improving the removal in those scenes with a natural high contrast. However, some low-frequency components still remain. In addition, the developed correction model captures and corrects the dependency of the noise patterns on sensor temperature, which confirms the robustness of the presented approach.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  7. The New Hyperspectral Sensor Desis on the Multi-Payload Platform Muses Installed on the Iss

    NASA Astrophysics Data System (ADS)

    Müller, R.; Avbelj, J.; Carmona, E.; Eckardt, A.; Gerasch, B.; Graham, L.; Günther, B.; Heiden, U.; Ickes, J.; Kerr, G.; Knodt, U.; Krutz, D.; Krawczyk, H.; Makarau, A.; Miller, R.; Perkins, R.; Walter, I.

    2016-06-01

    The new hyperspectral instrument DLR Earth Sensing Imaging Spectrometer (DESIS) will be developed and integrated in the Multi-User-System for Earth Sensing (MUSES) platform installed on the International Space Station (ISS). The DESIS instrument will be launched to the ISS mid of 2017 and robotically installed in one of the four slots of the MUSES platform. After a four month commissioning phase the operational phase will last at least until 2020. The MUSES / DESIS system will be commanded and operated by the publically traded company TBE (Teledyne Brown Engineering), which initiated the whole program. TBE provides the MUSES platform and the German Aerospace Center (DLR) develops the instrument DESIS and establishes a Ground Segment for processing, archiving, delivering and calibration of the image data mainly used for scientific and humanitarian applications. Well calibrated and harmonized products will be generated together with the Ground Segment established at Teledyne. The article describes the Space Segment consisting of the MUSES platform and the instrument DESIS as well as the activities at the two (synchronized) Ground Segments consisting of the processing methods, product generation, data calibration and product validation. Finally comments to the data policy are given.

  8. 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.

  9. Non-Invasive Survey of Old Paintings Using Vnir Hyperspectral Sensor

    NASA Astrophysics Data System (ADS)

    Matouskova, E.; Pavelka, K.; Svadlenkova, Z.

    2013-07-01

    Hyperspectral imaging is relatively new method developed primarily for army applications with respect to detection of possible chemical weapon existence and as an efficient assistant for a geological survey. The method is based on recording spectral profile for many hundreds of narrow spectral band. The technique gives full spectral curve of explored pixel which is an unparalleled signature of pixels material. Spectral signatures can then be compared with pre-defined spectral libraries or they can be created with respect to application. A new project named "New Modern Methods of Non-invasive Survey of Historical Site Objects" started at CTU in Prague with the New Year. The project is designed for 4 years and is funded by the Ministry of Culture in the Czech Republic. It is focused on material and chemical composition, damage diagnostics, condition description of paintings, images, construction components and whole structure object analysis in cultural heritage domain. This paper shows first results of the project on painting documentation field as well as used instrument. Hyperspec VNIR by Headwall Photonics was used for this analysis. It operates in the spectral range between 400 and 1000 nm. Comparison with infrared photography is discussed. The goal of this contribution is a non-destructive deep exploration of specific paintings. Two original 17th century paintings by Flemish authors Thomas van Apshoven ("On the Road") and David Teniers the Younger ("The Interior of a Mill") were chosen for the first analysis with a kind permission of academic painter Mr. M. Martan. Both paintings oil painted on wooden panel. This combination was chosen because of the possibility of underdrawing visualization which is supposed to be the most uncomplicated painting combination for this type of analysis.

  10. Design and performance of the Civil Air Patrol ARCHER hyperspectral processing system

    NASA Astrophysics Data System (ADS)

    Stevenson, Brian; O'Connor, Rory; Kendall, William; Stocker, Alan; Schaff, William; Alexa, Drew; Salvador, John; Eismann, Michael; Barnard, Kenneth; Kershenstein, John

    2005-06-01

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

  11. 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.

  12. 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

  13. Remote Sensing of Selected Water-Quality Indicators with the Hyperspectral Imager for the Coastal Ocean (HICO) Sensor

    EPA Science Inventory

    The Hyperspectral Imager for the Coastal Ocean (HICO) offers the coastal environmental monitoring community an unprecedented opportunity to observe changes in coastal and estuarine water quality across a range of spatial scales not feasible with traditional field-based monitoring...

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. Vineyard zonal management for grape quality assessment by combining airborne remote sensed imagery and soil sensors

    NASA Astrophysics Data System (ADS)

    Bonilla, I.; Martínez De Toda, F.; Martínez-Casasnovas, J. A.

    2014-10-01

    Vineyard variability within the fields is well known by grape growers, producing different plant responses and fruit characteristics. Many technologies have been developed in last recent decades in order to assess this spatial variability, including remote sensing and soil sensors. In this paper we study the possibility of creating a stable classification system that better provides useful information for the grower, especially in terms of grape batch quality sorting. The work was carried out during 4 years in a rain-fed Tempranillo vineyard located in Rioja (Spain). NDVI was extracted from airborne imagery, and soil conductivity (EC) data was acquired by an EM38 sensor. Fifty-four vines were sampled at véraison for vegetative parameters and before harvest for yield and grape analysis. An Isocluster unsupervised classification in two classes was performed in 5 different ways, combining NDVI maps individually, collectively and combined with EC. The target vines were assigned in different zones depending on the clustering combination. Analysis of variance was performed in order to verify the ability of the combinations to provide the most accurate information. All combinations showed a similar behaviour concerning vegetative parameters. Yield parameters classify better by the EC-based clustering, whilst maturity grape parameters seemed to give more accuracy by combining all NDVIs and EC. Quality grape parameters (anthocyanins and phenolics), presented similar results for all combinations except for the NDVI map of the individual year, where the results were poorer. This results reveal that stable parameters (EC or/and NDVI all-together) clustering outcomes in better information for a vineyard zonal management strategy.

  19. Development of a multi-sensor airborne investigation platform based on an ultra-light aircraft

    NASA Astrophysics Data System (ADS)

    Herd, Rainer; Holst, Jonathan; Lay, Michael

    2013-04-01

    In the year 2012 the chair Raw Material and Natural Resource Management of Brandenburg University of Technology Cottbus, Germany started to develop, construct and assemble a multi-sensor airborne investigation system based on an ultra-light aircraft. The conceptual ideas were born several years before and triggered by the increasing demand of spatial underground information, increasing restrictions to access private property and the lack of affordable commercially operated systems for projects with small budgets. The concept of the presented system comprehends a full composite ultra-light aircraft, the Pipistrel VIRUS which combines a low minimum (65 km/h, a high crusing speed (250 km/h, a long range (1700 km) and a low noise potential. The investigation equipment which can be modified according to the investigation target comprises actually a CsI-y-spectrometer in the fuselage, 2 K-magnetometer at the wing tips and a VLF-EM-receiver underneath the tail. This configuration enables the system to operate for mineral exploration, geological mapping, detection of freshwater resources and brines and different environmental monitoring missions. The development and actual stage of the project will be presented. The first operating flight is scheduled for spring 2013.

  20. 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.

  1. 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.

  2. Optimization of the concentration optics of the Martian airborne dust sensor for MetNet space mission

    NASA Astrophysics Data System (ADS)

    Cortés, F.; González, A.; de Castro, A. J.; López, F.

    2012-06-01

    Martian atmosphere contains a significant and rapidly changing load of suspended dust that never drops to zero. The main component of Martian aerosol is micron-sized dust thought to be a product of soil weathering. Although airborne dust plays a key role in Martian climate, the basic physical properties of these aerosols are still poorly known. The scope of Mars MetNet Mission is to deploy several tens of mini atmospheric stations on the Martian surface. MEIGA-MetNet payload is the Spanish contribution in MetNet. Infrared Laboratory of University Carlos III (LIR-UC3M) is in charge of the design and development of a micro-sensor for the characterization of airborne dust. This design must accomplish with a strict budget of mass and power, 45 g and 1 W respectively. The sensor design criteria have been obtained from a physical model specifically developed for optimizing IR local scattering. The model calculates the spectral power density scattered and detected between 1 and 5 μm by a certain particle distribution and sensor configuration. From model calculations a modification based on the insertion of a compound ellipsoidal concentrator (CEC) has appeared as necessary. Its implementation has multiplied up to 100 the scattered optical power detected, significantly enhancing the detection limits of the sensor.

  3. 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.

  4. Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Icing Sensor Performance During the 2003 Alliance Icing Research Study (AIRS II)

    NASA Technical Reports Server (NTRS)

    Murray, John J.; Schaffner, Philip R.; Minnis, Patrick; Nguyen, Louis; Delnore, Victor E.; Daniels, Taumi S.; Grainger, C. A.; Delene, D.; Wolff, C. A.

    2004-01-01

    The Tropospheric Airborne Meteorological Data Reporting (TAMDAR) sensor was deployed onboard the University of North Dakota Citation II aircraft in the Alliance Icing Research Study (AIRS II) from Nov 19 through December 14, 2003. TAMDAR is designed to measure and report winds, temperature, humidity, turbulence and icing from regional commercial aircraft (Daniels et. al., 2004). TAMDAR icing sensor performance is compared to a) in situ validation data from the Citation II sensor suite, b) Current Icing Potential products developed by the National Center for Atmospheric Research (NCAR) and available operationally on the NOAA Aviation Weather Center s Aviation Digital Data Server (ADDS) and c) NASA Advanced Satellite Aviation-weather Products (ASAP) cloud microphysical products.

  5. 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.

  6. Principal component-based radiative transfer model for hyperspectral sensors: theoretical concept.

    PubMed

    Liu, Xu; Smith, William L; Zhou, Daniel K; Larar, Allen

    2006-01-01

    Modern infrared satellite sensors such as the Atmospheric Infrared Sounder (AIRS), the Cross-Track Infrared Sounder (CrIS), the Tropospheric Emission Spectrometer (TES), the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS), and the Infrared Atmospheric Sounding Interferometer (IASI) are capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, superfast radiative transfer models are needed. We present a novel radiative transfer model based on principal component analysis. Instead of predicting channel radiance or transmittance spectra directly, the principal component-based radiative transfer model (PCRTM) predicts the principal component (PC) scores of these quantities. This prediction ability leads to significant savings in computational time. The parameterization of the PCRTM model is derived from the properties of PC scores and instrument line-shape functions. The PCRTM is accurate and flexible. Because of its high speed and compressed spectral information format, it has great potential for superfast one-dimensional physical retrieval and for numerical weather prediction large volume radiance data assimilation applications. The model has been successfully developed for the NAST-I and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is able to include multiple scattering calculations to account for clouds and aerosols.

  7. Sensor System Performance Evaluation and Benefits from the NPOESS Airborne Sounder Testbed-Interferometer (NAST-I)

    NASA Technical Reports Server (NTRS)

    Larar, A.; Zhou, D.; Smith, W.

    2009-01-01

    Advanced satellite sensors are tasked with improving global-scale measurements of the Earth's atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring, and environmental change detection. Validation of the entire measurement system is crucial to achieving this goal and thus maximizing research and operational utility of resultant data. Field campaigns employing satellite under-flights with well-calibrated FTS sensors aboard high-altitude aircraft are an essential part of this validation task. The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed-Interferometer (NAST-I) has been a fundamental contributor in this area by providing coincident high spectral/spatial resolution observations of infrared spectral radiances along with independently-retrieved geophysical products for comparison with like products from satellite sensors being validated. This paper focuses on some of the challenges associated with validating advanced atmospheric sounders and the benefits obtained from employing airborne interferometers such as the NAST-I. Select results from underflights of the Aqua Atmospheric InfraRed Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI) obtained during recent field campaigns will be presented.

  8. 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.

  9. 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...

  10. 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.

  11. Integrated Active Fire Retrievals and Biomass Burning Emissions Using Complementary Near-Coincident Ground, Airborne and Spaceborne Sensor Data

    NASA Technical Reports Server (NTRS)

    Schroeder, Wilfrid; Ellicott, Evan; Ichoku, Charles; Ellison, Luke; Dickinson, Matthew B.; Ottmar, Roger D.; Clements, Craig; Hall, Dianne; Ambrosia, Vincent; Kremens, Robert

    2013-01-01

    Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

  12. 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.

  13. 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.

  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. 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.

  16. 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

  17. 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.

  18. [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.

  19. 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

  20. 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.

  1. The Multi-Center Airborne Coherent Atmospheric Wind Sensor: Recent Measurements and Future Applications

    NASA Technical Reports Server (NTRS)

    Rothermel, Jeffry; Cutten, Dean R.; Howell, Burgess F.; Hardesty, Robert M.; Tratt, David M.; Darby, Lisa S.

    1999-01-01

    The atmospheric lidar remote sensing groups of NOAA Environmental Technology Laboratory, Jet Propulsion Laboratory and NASA Marshall Space Flight Center jointly developed an airborne scanning coherent Doppler Lidar. We describe the system, present recent measurement (including the first wind fields measured within a hurricane using Doppler lidar), and describe prospective instrument improvements and research applications.

  2. 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.

  3. 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.

  4. 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.

  5. Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013

    EPA Science Inventory

    The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA F...

  6. Toward hyperspectral face recognition

    NASA Astrophysics Data System (ADS)

    Robila, Stefan A.

    2008-02-01

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

  7. Airborne remote sensors applied to engineering geology and civil works design investigations

    NASA Technical Reports Server (NTRS)

    Gelnett, R. H.

    1975-01-01

    The usefulness of various airborne remote sensing systems in the detection and identification of regional and specific geologic structural features that may affect the design and location of engineering structures on major civil works projects is evaluated. The Butler Valley Dam and Blue Lake Project in northern California was selected as a demonstration site. Findings derived from the interpretation of various kinds of imagery used are given.

  8. The development of a power spectral density processor for C and L band airborne radar scatterometer sensor systems

    NASA Technical Reports Server (NTRS)

    Harrison, D. A., III; Chladek, J. T.

    1983-01-01

    A real-time signal processor was developed for the NASA/JSC L-and C-band airborne radar scatterometer sensor systems. The purpose of the effort was to reduce ground data processing costs. Conversion of two quadrature channels of data (like and cross polarized) was made to obtain Power Spectral Density (PSD) values. A chirp-z transform (CZT) approach was used to filter the Doppler return signal and improved high frequency and angular resolution was realized. The processors have been tested with record signals and excellent results were obtained. CZT filtering can be readily applied to scatterometers operating at other wavelengths by altering the sample frequency. The design of the hardware and software and the results of the performance tests are described in detail.

  9. Interpretation of Observations of Trans-Spectral Phenomena Acquired Using Hyperspectral Sensors Aboard a Remotely Operated Vehicle in Exuma Sound

    NASA Technical Reports Server (NTRS)

    Costello, D.; Carder, Kendall L.; Ivey, J.; English, D.

    2001-01-01

    Hyper-spectral (512-channel) optical data acquired during a relatively deep (102m) dive of our ROSEBUD Remotely Operated Vehicle (ROV) in the clear waters of Exuma Sound, Bahamas provided the opportunity to investigate the trans-spectral shift of photonic energy (inelastic scattering) as a function of water depth. Results show a convolution of several spectral processes (e.g. absorption, scattering) involving water molecules, dissolved material and particulates as well as trans-spectral (inelastic) processes involving fluorescence by water molecules (Raman), dissolved material and chlorophyll. The spectral signatures of these convolved causes and effects allow deconvolution with a hyperspectral approach. Intrinsic to the convolution was the ability to position the vehicle at depths where Raman fluorescence dominated at red wavelengths. Results show that the calculated Raman absorption coefficients are generally consistent with historical values (i.e. 0.9 x 10(sup)-4 at 525 nm excitation) and that an angstrom exponent of 5 is more appropriate than the often cited value of 4.

  10. 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

  11. Nano-based chemical sensor array systems for uninhabited ground and airborne vehicles

    NASA Astrophysics Data System (ADS)

    Brantley, Christina; Ruffin, Paul B.; Edwards, Eugene

    2009-03-01

    In a time when homemade explosive devices are being used against soldiers and in the homeland security environment, it is becoming increasingly evident that there is an urgent need for high-tech chemical sensor packages to be mounted aboard ground and air vehicles to aid soldiers in determining the location of explosive devices and the origin of bio-chemical warfare agents associated with terrorist activities from a safe distance. Current technologies utilize relatively large handheld detection systems that are housed on sizeable robotic vehicles. Research and development efforts are underway at the Army Aviation & Missile Research, Development, and Engineering Center (AMRDEC) to develop novel and less expensive nano-based chemical sensors for detecting explosives and chemical agents used against the soldier. More specifically, an array of chemical sensors integrated with an electronics control module on a flexible substrate that can conform to and be surface-mounted to manned or unmanned vehicles to detect harmful species from bio-chemical warfare and other explosive devices is being developed. The sensor system under development is a voltammetry-based sensor system capable of aiding in the detection of any chemical agent and in the optimization of sensor microarray geometry to provide nonlinear Fourier algorithms to characterize target area background (e.g., footprint areas). The status of the research project is reviewed in this paper. Critical technical challenges associated with achieving system cost, size, and performance requirements are discussed. The results obtained from field tests using an unmanned remote controlled vehicle that houses a CO2/chemical sensor, which detects harmful chemical agents and wirelessly transmits warning signals back to the warfighter, are presented. Finally, the technical barriers associated with employing the sensor array system aboard small air vehicles will be discussed.

  12. Towards Automatic Single-Sensor Mapping by Multispectral Airborne Laser Scanning

    NASA Astrophysics Data System (ADS)

    Ahokas, E.; Hyyppä, J.; Yu, X.; Liang, X.; Matikainen, L.; Karila, K.; Litkey, P.; Kukko, A.; Jaakkola, A.; Kaartinen, H.; Holopainen, M.; Vastaranta, M.

    2016-06-01

    This paper describes the possibilities of the Optech Titan multispectral airborne laser scanner in the fields of mapping and forestry. Investigation was targeted to six land cover classes. Multispectral laser scanner data can be used to distinguish land cover classes of the ground surface, including the roads and separate road surface classes. For forest inventory using point cloud metrics and intensity features combined, total accuracy of 93.5% was achieved for classification of three main boreal tree species (pine, spruce and birch).When using intensity features - without point height metrics - a classification accuracy of 91% was achieved for these three tree species. It was also shown that deciduous trees can be further classified into more species. We propose that intensity-related features and waveform-type features are combined with point height metrics for forest attribute derivation in area-based prediction, which is an operatively applied forest inventory process in Scandinavia. It is expected that multispectral airborne laser scanning can provide highly valuable data for city and forest mapping and is a highly relevant data asset for national and local mapping agencies in the near future.

  13. Benefits of Sharing Information from Commercial Airborne Forward-Looking Sensors in the Next Generation Air Transportation System

    NASA Technical Reports Server (NTRS)

    Schaffner, Philip R.; Harrah, Steven; Neece, Robert T.

    2012-01-01

    The air transportation system of the future will need to support much greater traffic densities than are currently possible, while preserving or improving upon current levels of safety. Concepts are under development to support a Next Generation Air Transportation System (NextGen) that by some estimates will need to support up to three times current capacity by the year 2025. Weather and other atmospheric phenomena, such as wake vortices and volcanic ash, constitute major constraints on airspace system capacity and can present hazards to aircraft if encountered. To support safe operations in the NextGen environment advanced systems for collection and dissemination of aviation weather and environmental information will be required. The envisioned NextGen Network Enabled Weather (NNEW) infrastructure will be a critical component of the aviation weather support services, providing access to a common weather picture for all system users. By taking advantage of Network Enabled Operations (NEO) capabilities, a virtual 4-D Weather Data Cube with aviation weather information from many sources will be developed. One new source of weather observations may be airborne forward-looking sensors, such as the X-band weather radar. Future sensor systems that are the subject of current research include advanced multi-frequency and polarimetric radar, a variety of Lidar technologies, and infrared imaging spectrometers.

  14. 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

  15. 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).

  16. 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

  17. 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).

  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. Evaluation of Nimbus 7 SMMR sensor with airborne radiometers and surface observations in the Norwegian Sea

    NASA Technical Reports Server (NTRS)

    Gloersen, P.; Cavalieri, D.; Crawford, J.; Campbell, W. J.; Farrelly, B.; Johannessen, J.; Johannessen, O. M.; Svendsen, E.; Kloster, K.

    1981-01-01

    Measurements made by the Nimbus 7 SMMR are compared with near simultaneous observations using the airborne SMMR simulator and with surface observations. The area of the test is in the Norwegian Sea between Bear Island and Northern Norway. It is noted that during the observation period two low-pressure systems were located in the test area, giving a spatial wind variation from 3-20 m/s. It is shown that the use of the currently available brightness temperatures and algorithms for SMMR does not give universally satisfactory results for SST and wind speed under extreme weather conditions. In addition, the SMMR simulator results are seen as indicating the need for more work on calibration.

  20. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS): Sensor improvements for 1994 and 1995

    NASA Technical Reports Server (NTRS)

    Sarture, C. M.; Chrien, T. G.; Green, R. O.; Eastwood, M. L.; Raney, J. J.; Hernandez, M. A.

    1995-01-01

    AVIRIS is a NASA-sponsored Earth-remote-sensing imaging spectrometer designed, built and operated by the Jet Propulsion Laboratory (JPL). While AVIRIS has been operational since 1989, major improvements have been completed in most of the sensor subsystems during the winter maintenance cycles. As a consequence of these efforts, the capabilities of AVIRIS to reliably acquire and deliver consistently high quality, calibrated imaging spectrometer data continue to improve annually, significantly over those in 1989. Improvements to AVIRIS prior to 1994 have been described previously. This paper details recent and planned improvements to AVIRIS in the sensor task.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. Validating MODIS above-cloud aerosol optical depth retrieved from "color ratio" algorithm using direct measurements made by NASA's airborne AATS and 4STAR sensors

    NASA Astrophysics Data System (ADS)

    Jethva, Hiren; Torres, Omar; Remer, Lorraine; Redemann, Jens; Livingston, John; Dunagan, Stephen; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal Rosenheimer, Michal; Spurr, Rob

    2016-10-01

    We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the "color ratio" method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASA's airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne matchups revealed a good agreement (root-mean-square difference < 0.1), with most matchups falling within the estimated uncertainties associated the MODIS retrievals (about -10 to +50 %). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50 % for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite-based retrievals.

  6. MAPSAR Image Simulation Based on L-band Polarimetric Data from the SAR-R99B Airborne Sensor (SIVAM System)

    PubMed Central

    Mura, José Claudio; Paradella, Waldir Renato; Dutra, Luciano Vieira; dos Santos, João Roberto; Rudorff, Bernardo Friedrich Theodor; de Miranda, Fernando Pellon; da Silva, Mario Marcos Quintino; da Silva, Wagner Fernando

    2009-01-01

    This paper describes the methodology applied to generate simulated multipolarized L-band SAR images of the MAPSAR (Multi-Application Purpose SAR) satellite from the airborne SAR R99B sensor (SIVAM System). MAPSAR is a feasibility study conducted by INPE (National Institute for Space Research) and DLR (German Aerospace Center) targeting a satellite L-band SAR innovative mission for assessment, management and monitoring of natural resources. Examples of simulated products and their applications are briefly discussed. PMID:22389590

  7. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). A description of the sensor, ground data processing facility, laboratory calibration, and first results

    NASA Technical Reports Server (NTRS)

    Vane, Gregg (Editor)

    1987-01-01

    The papers in this document were presented at the Imaging Spectroscopy 2 Conference of the 31st International Symposium on Optical and Optoelectronic Applied Science and Engineering, in San Diego, California, on 20 and 21 August 1987. They describe the design and performance of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor and its subsystems, the ground data processing facility, laboratory calibration, and first results.

  8. 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.

  9. Hyperspectral imaging utility for transportation systems

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  10. 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.

  11. Calibrating airborne measurements of airspeed, pressure and temperature using a Doppler laser air-motion sensor

    NASA Astrophysics Data System (ADS)

    Cooper, W. A.; Spuler, S. M.; Spowart, M.; Lenschow, D. H.; Friesen, R. B.

    2014-09-01

    A new laser air-motion sensor measures the true airspeed with a standard uncertainty of less than 0.1 m s-1 and so reduces uncertainty in the measured component of the relative wind along the longitudinal axis of the aircraft to about the same level. The calculated pressure expected from that airspeed at the inlet of a pitot tube then provides a basis for calibrating the measurements of dynamic and static pressure, reducing standard uncertainty in those measurements to less than 0.3 hPa and the precision applicable to steady flight conditions to about 0.1 hPa. These improved measurements of pressure, combined with high-resolution measurements of geometric altitude from the global positioning system, then indicate (via integrations of the hydrostatic equation during climbs and descents) that the offset and uncertainty in temperature measurement for one research aircraft are +0.3 ± 0.3 °C. For airspeed, pressure and temperature, these are significant reductions in uncertainty vs. those obtained from calibrations using standard techniques. Finally, it is shown that although the initial calibration of the measured static and dynamic pressures requires a measured temperature, once calibrated these measured pressures and the measurement of airspeed from the new laser air-motion sensor provide a measurement of temperature that does not depend on any other temperature sensor.

  12. Calibrating airborne measurements of airspeed, pressure and temperature using a Doppler laser air-motion sensor

    NASA Astrophysics Data System (ADS)

    Cooper, W. A.; Spuler, S. M.; Spowart, M.; Lenschow, D. H.; Friesen, R. B.

    2014-03-01

    A new laser air-motion sensor measures the true airspeed with an uncertainty of less than 0.1 m s-1 (standard error) and so reduces uncertainty in the measured component of the relative wind along the longitudinal axis of the aircraft to about the same level. The calculated pressure expected from that airspeed at the inlet of a pitot tube then provides a basis for calibrating the measurements of dynamic and static pressure, reducing standard-error uncertainty in those measurements to less than 0.3 hPa and the precision applicable to steady flight conditions to about 0.1 hPa. These improved measurements of pressure, combined with high-resolution measurements of geometric altitude from the Global Positioning System, then indicate (via integrations of the hydrostatic equation during climbs and descents) that the offset and uncertainty in temperature measurement for one research aircraft are +0.3 ± 0.3 °C. For airspeed, pressure and temperature these are significant reductions in uncertainty vs. those obtained from calibrations using standard techniques. Finally, it is shown that the new laser air-motion sensor, combined with parametrized fits to correction factors for the measured dynamic and ambient pressure, provides a measurement of temperature that is independent of any other temperature sensor.

  13. 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

  14. Development of a handheld widefield hyperspectral imaging (HSI) sensor for standoff detection of explosive, chemical, and narcotic residues

    NASA Astrophysics Data System (ADS)

    Nelson, Matthew P.; Basta, Andrew; Patil, Raju; Klueva, Oksana; Treado, Patrick J.

    2013-05-01

    The utility of Hyper Spectral Imaging (HSI) passive chemical detection employing wide field, standoff imaging continues to be advanced in detection applications. With a drive for reduced SWaP (Size, Weight, and Power), increased speed of detection and sensitivity, developing a handheld platform that is robust and user-friendly increases the detection capabilities of the end user. In addition, easy to use handheld detectors could improve the effectiveness of locating and identifying threats while reducing risks to the individual. ChemImage Sensor Systems (CISS) has developed the HSI Aperio™ sensor for real time, wide area surveillance and standoff detection of explosives, chemical threats, and narcotics for use in both government and commercial contexts. Employing liquid crystal tunable filter technology, the HSI system has an intuitive user interface that produces automated detections and real-time display of threats with an end user created library of threat signatures that is easily updated allowing for new hazardous materials. Unlike existing detection technologies that often require close proximity for sensing and so endanger operators and costly equipment, the handheld sensor allows the individual operator to detect threats from a safe distance. Uses of the sensor include locating production facilities of illegal drugs or IEDs by identification of materials on surfaces such as walls, floors, doors, deposits on production tools and residue on individuals. In addition, the sensor can be used for longer-range standoff applications such as hasty checkpoint or vehicle inspection of residue materials on surfaces or bulk material identification. The CISS Aperio™ sensor has faster data collection, faster image processing, and increased detection capability compared to previous sensors.

  15. 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-sensor

  16. 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.

  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. 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

  19. 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...

  20. 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...

  1. Estimation of algal and suspended sediment loads (singly and combined) using hyperspectral sensors and integrated mesocosm experiments

    SciTech Connect

    Schalles, J.F.; Schiebe, F.R.; Starks, P.J.

    1997-06-01

    Most remote sensing algorithms for materials in water are based on studies on natural waters with complex and variable optical properties, or of small indoor microcosm containers. We used sunlit, cylindrical, black mesocosm tanks (80m{sup 3}, 3 m depth) and a hyperspectral radiometer to examine reflectances of algal blooms and suspended kaolin white clay. In three integrated experiments, algae and clay levels were carefully manipulated: (1) Algal bloom water in one tank was pumped to a second which began with clear water, and clear make-up water was pumped to the first to obtain a well graded series (Chl. a = 0 - 62 {mu}g/L). (2) White, kaolin clay was added stepwise to clear water, resulting in an organic seston range of 0 - 40 mg/L. (3) Algal bloom water from a single source was divided between two tanks to establish Chi. a loads of 31 and 57 {mu}g/L. Then, identical additions of clay were made to both tanks to achieve a range of 0 - 72 mg/L inorganic matter while conserving the algal loads. The first experiment revealed a strong interplay between algal scattering and absorption. Pigment absorbance dominated below 510 nm, while increasing cell scattering in regions of low pigment activity caused green and NIR peaks to form near 560 and 700 nm. In spite of strong chlorophyll absorbance near 675 nm, this region had small reflectance increases with increased algae. In the second experiment, white clay had high albedo. At seston levels above 40 mg/L, green reflectance exceeded 50% and NIR reflectance at 800 nm exceeded 9%. In the third experiment, algal pigments strongly attenuated clay reflectance in a dose dependent manner, even at green wavelengths. Clay particles greatly amplified but also preserved algal reflectance patterns. Our findings affirm the importance of high spectral resolution at diagnostic wavelengths in turbid Case 2 coastal and inland waters.

  2. 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.

  3. Distributed adaptive framework for multispectral/hyperspectral imagery and three-dimensional point cloud fusion

    NASA Astrophysics Data System (ADS)

    Rand, Robert S.; Khuon, Timothy; Truslow, Eric

    2016-07-01

    A proposed framework using spectral and spatial information is introduced for neural net multisensor data fusion. This consists of a set of independent-sensor neural nets, one for each sensor (type of data), coupled to a fusion net. The neural net of each sensor is trained from a representative data set of the particular sensor to map to a hypothesis space output. The decision outputs from the sensor nets are used to train the fusion net to an overall decision. During the initial processing, three-dimensional (3-D) point cloud data (PCD) are segmented using a multidimensional mean-shift algorithm into clustered objects. Concurrently, multiband spectral imagery data (multispectral or hyperspectral) are spectrally segmented by the stochastic expectation-maximization into a cluster map containing (spectral-based) pixel classes. For the proposed sensor fusion, spatial detections and spectral detections complement each other. They are fused into final detections by a cascaded neural network, which consists of two levels of neural nets. The success of the approach in utilizing sensor synergism for an enhanced classification is demonstrated for the specific case of classifying hyperspectral imagery and PCD extracted from LIDAR, obtained from an airborne data collection over the campus of University of Southern Mississippi, Gulfport, Mississippi.

  4. Estimation of optical flow in airborne electro-optical sensors by stochastic approximation

    NASA Technical Reports Server (NTRS)

    Merhav, S. J.

    1991-01-01

    The essence of motion or range estimation by passive electrooptical means is the ability to determine the correspondence of picture elements in pairs of image frames and to estimate their coordinates and their disparity (relative shifts) in the image plane of an electrooptical imaging sensor. The disparity can be in successive frames due to self-motion or in simultaneous frames of a stereo pair. A key issue is to provide these estimates on-line. This paper describes the theoretical background of such an interframe shift estimator. It is based on a stochastic gradient algorithm, specifically implementing a form of stochastic approximation, which can achieve rapid convergence of the shift estimate. Analytical and numerical simulation examples for random texture and isolated features validate the feasibility and the effectiveness of the estimator.

  5. 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.

  6. The Relationship Between Fossil and Dairy Greenhouse Gas Emissions and Complex Urban Land-Use Patterns by In Situ and Remote Sensing Data from Surface Mobile, Airborne, and Satellite Instruments

    NASA Astrophysics Data System (ADS)

    Leifer, I.; Melton, C.; Tratt, D. M.; Kuze, A.; Buckland, K. N.; Butz, A.; Deguchi, A.; Eastwood, M. L.; Fischer, M. L.; Frash, J.; Fladeland, M. M.; Gore, W.; Iraci, L. T.; Johnson, P. D.; Kataoka, F.; Kolyer, R.; Leen, J. B.; Quattrochi, D. A.; Shiomi, K.; Suto, H.; Tanaka, T.; Thompson, D. R.; Yates, E. L.; Van Damme, M.; Yokota, T.

    2015-12-01

    The GOSAT-COMEX-IASI Experiment (Greenhouse gases Observing SATellite-CO2and Methane EXperiment) demonstrated a novel approach to airborne-surface mobile in situ data fusion for interpretation and validation of satellite and airborne remote sensing data of greenhouse gases and direct calculation of flux. Key data were collected for the Chino Dairy in the Los Angeles Basin, California and for the Kern River Oil Fields adjacent to Bakersfield, California. In situ surface and remote sensing greenhouse gas and ammonia observations were compared with IASI and GOSAT retreivals, while hyperspectral imaging data from the AVIRIS, AVIRIS NG, and Mako airborne sensors were analyzed to relate emissions and land use. Figure - platforms participating in the experiment. TANSO-FTS aboard the Ibuki satellite (GOSAT) provided targeted pixels to measure column greenhouse gases. AMOG is the AutoMObile Gas Surveyor which supports a suite of meteorology and in situ trace gas sensors for mobile high speed measurement. AVIRIS, the Airborne Visual InfraRed Imaging Spectrometer aboard the NASA ER-2 airplane collected hyperspectral imaging data at 20 m resolution from 60,000 ft. Mako is a thermal infrared imaging spectrometer that was flown on the Twin Otter International. AJAX is a fighter jet outfitted for science sporting meteorology and greenhouse gas sensors. RAMVan is an upward looking FTIR for measuring column methane and ammonia and other trace gases.

  7. 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

  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. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. [Radiance Simulation of BUV Hyperspectral Sensor on Multi Angle Observation, and Improvement to Initial Total Ozone Estimating Model of TOMS V8 Total Ozone Algorithm].

    PubMed

    Lü, Chun-guang; Wang, Wei-he; Yang, Wen-bo; Tian, Qing-iju; Lu, Shan; Chen, Yun

    2015-11-01

    New hyperspectral sensor to detect total ozone is considered to be carried on geostationary orbit platform in the future, because local troposphere ozone pollution and diurnal variation of ozone receive more and more attention. Sensors carried on geostationary satellites frequently obtain images on the condition of larger observation angles so that it has higher requirements of total ozone retrieval on these observation geometries. TOMS V8 algorithm is developing and widely used in low orbit ozone detecting sensors, but it still lack of accuracy on big observation geometry, therefore, how to improve the accuracy of total ozone retrieval is still an urgent problem that demands immediate solution. Using moderate resolution atmospheric transmission, MODT-RAN, synthetic UV backscatter radiance in the spectra region from 305 to 360 nm is simulated, which refers to clear sky, multi angles (12 solar zenith angles and view zenith angles) and 26 standard profiles, moreover, the correlation and trends between atmospheric total ozone and backward scattering of the earth UV radiation are analyzed based on the result data. According to these result data, a new modified initial total ozone estimation model in TOMS V8 algorithm is considered to be constructed in order to improve the initial total ozone estimating accuracy on big observation geometries. The analysis results about total ozone and simulated UV backscatter radiance shows: Radiance in 317.5 nm (R₃₁₇.₅) decreased as the total ozone rise. Under the small solar zenith Angle (SZA) and the same total ozone, R₃₁₇.₅ decreased with the increase of view zenith Angle (VZA) but increased on the large SZA. Comparison of two fit models shows: without the condition that both SZA and VZA are large (> 80°), exponential fitting model and logarithm fitting model all show high fitting precision (R² > 0.90), and precision of the two decreased as the SZA and VZA rise. In most cases, the precision of logarithm fitting

  17. 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.

  18. Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Validation and Verification on National Oceanographic and Atmospheric Administration (NOAA) Lockheed WP-3D Aircraft

    NASA Technical Reports Server (NTRS)

    Tsoucalas, George; Daniels, Taumi S.; Zysko, Jan; Anderson, Mark V.; Mulally, Daniel J.

    2010-01-01

    As part of the National Aeronautics and Space Administration's Aviation Safety and Security Program, the Tropospheric Airborne Meteorological Data Reporting project (TAMDAR) developed a low-cost sensor for aircraft flying in the lower troposphere. This activity was a joint effort with support from Federal Aviation Administration, National Oceanic and Atmospheric Administration, and industry. This paper reports the TAMDAR sensor performance validation and verification, as flown on board NOAA Lockheed WP-3D aircraft. These flight tests were conducted to assess the performance of the TAMDAR sensor for measurements of temperature, relative humidity, and wind parameters. The ultimate goal was to develop a small low-cost sensor, collect useful meteorological data, downlink the data in near real time, and use the data to improve weather forecasts. The envisioned system will initially be used on regional and package carrier aircraft. The ultimate users of the data are National Centers for Environmental Prediction forecast modelers. Other users include air traffic controllers, flight service stations, and airline weather centers. NASA worked with an industry partner to develop the sensor. Prototype sensors were subjected to numerous tests in ground and flight facilities. As a result of these earlier tests, many design improvements were made to the sensor. The results of tests on a final version of the sensor are the subject of this report. The sensor is capable of measuring temperature, relative humidity, pressure, and icing. It can compute pressure altitude, indicated air speed, true air speed, ice presence, wind speed and direction, and eddy dissipation rate. Summary results from the flight test are presented along with corroborative data from aircraft instruments.

  19. Retrieval of Vegetation Structure and Carbon Balance Parameters Using Ground-Based Lidar and Scaling to Airborne and Spaceborne Lidar Sensors

    NASA Astrophysics Data System (ADS)

    Strahler, A. H.; Ni-Meister, W.; Woodcock, C. E.; Li, X.; Jupp, D. L.; Culvenor, D.

    2006-12-01

    This research uses a ground-based, upward hemispherical scanning lidar to retrieve forest canopy structural information, including tree height, mean tree diameter, basal area, stem count density, crown diameter, woody biomass, and green biomass. These parameters are then linked to airborne and spaceborne lidars to provide large-area mapping of structural and biomass parameters. The terrestrial lidar instrument, Echidna(TM), developed by CSIRO Australia, allows rapid acquisition of vegetation structure data that can be readily integrated with downward-looking airborne lidar, such as LVIS (Laser Vegetation Imaging Sensor), and spaceborne lidar, such as GLAS (Geoscience Laser Altimeter System) on ICESat. Lidar waveforms and vegetation structure are linked for these three sensors through the hybrid geometric-optical radiative-transfer (GORT) model, which uses basic vegetation structure parameters and principles of geometric optics, coupled with radiative transfer theory, to model scattering and absorption of light by collections of individual plant crowns. Use of a common model for lidar waveforms at ground, airborne, and spaceborne levels facilitates integration and scaling of the data to provide large-area maps and inventories of vegetation structure and carbon stocks. Our research plan includes acquisition of Echidna(TM) under-canopy hemispherical lidar scans at North American test sites where LVIS and GLAS data have been or are being acquired; analysis and modeling of spatially coincident lidar waveforms acquired by the three sensor systems; linking of the three data sources using the GORT model; and mapping of vegetation structure and carbon-balance parameters at LVIS and GLAS resolutions based on Echidna(TM) measurements.

  20. 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...

  1. 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...

  2. 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.

  3. 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.

  4. 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

  5. Use of the Airborne Visible/Infrared Imaging Spectrometer to calibrate the optical sensor on board the Japanese Earth Resources Satellite-1

    NASA Technical Reports Server (NTRS)

    Green, Robert O.; Conel, James E.; Vandenbosch, Jeannette; Shimada, Masanobu

    1993-01-01

    We describe an experiment to calibrate the optical sensor (OPS) on board the Japanese Earth Resources Satellite-1 with data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). On 27 Aug. 1992 both the OPS and AVIRIS acquired data concurrently over a calibration target on the surface of Rogers Dry Lake, California. The high spectral resolution measurements of AVIRIS have been convolved to the spectral response curves of the OPS. These data in conjunction with the corresponding OPS digitized numbers have been used to generate the radiometric calibration coefficients for the eight OPS bands. This experiment establishes the suitability of AVIRIS for the calibration of spaceborne sensors in the 400 to 2500 nm spectral region.

  6. 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

  7. Analysis of remote sensing data collected for detection and mapping of oil spills: Reduction and analysis of multi-sensor airborne data of the NASA Wallops oil spill exercise of November 1978

    NASA Technical Reports Server (NTRS)

    1982-01-01

    Airborne, remotely sensed data of the NASA Wallops controlled oil spill were corrected, reduced and analysed. Sensor performance comparisons were made by registering data sets from different sensors, which were near-coincident in time and location. Multispectral scanner images were, in turn, overlayed with profiles of correlation between airborne and laboratory-acquired fluorosensor spectra of oil; oil-thickness contours derived (by NASA) from a scanning fluorosensor and also from a two-channel scanning microwave radiometer; and synthetic aperture radar X-HH images. Microwave scatterometer data were correlated with dual-channel (UV and TIR) line scanner images of the oil slick.

  8. 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.

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

    NASA Astrophysics Data System (ADS)

    Guelman, M.; Ortenberg, F.

    2009-06-01

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

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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.

  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. 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.

  17. 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.

  18. Validation of satellite overland retrievals of AOD at northern high latitudes with coincident measurements from airborne sunphotometer, lidar, and in situ sensors during ARCTAS

    NASA Astrophysics Data System (ADS)

    Livingston, J. M.; Shinozuka, Y.; Redemann, J.; Russell, P. B.; Ramachandran, S.; Johnson, R. R.; Clarke, A. D.; Howell, S. G.; McNaughton, C.; Freitag, S.; Kapustin, V. N.; Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.; Torres, O.; Veefkind, P.; Remer, L. A.; Mattoo, S.; Levy, R. C.; Chu, A. D.; Kahn, R. A.; Davis, M. R.

    2009-12-01

    The 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign presented a unique opportunity for validation of satellite retrievals of aerosol optical depth (AOD) over a variety of surfaces at northern high latitudes. In particular, the 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) was operated together with a variety of in-situ and other remote sensors aboard the NASA P-3B research aircraft during both the spring and summer phases of ARCTAS. Among the in-situ sensors were a nephelometer and particle soot absorption photometer (PSAP) operated by University of Hawaii Group for Environmental Aerosol Research (HIGEAR). P-3B science missions included several coincident underflights of the Terra and A-Train satellites during a variety of aerosol loading conditions, including Arctic haze and smoke plumes from boreal forest fires. In this presentation, we will compare AATS-14 AOD spectra, adjusted for the contribution from the layer below the aircraft using the HiGEAR scattering and absorption measurements, with full column AOD retrievals from coincident measurements by satellite sensors such as MISR, MODIS, OMI, and POLDER. We also intend to show comparisons of aerosol extinction derived from AATS-14 measurements during P-3B vertical profiles with coincident measurements from CALIOP aboard the CALIPSO satellite and from the high spectral resolution lidar (HSRL) flown aboard the NASA B-200 aircraft.

  19. The Laser Vegetation Imaging Sensor (LVIS): A Medium-Altitude, Digitization-Only, Airborne Laser Altimeter for Mapping Vegetation and Topography

    NASA Technical Reports Server (NTRS)

    Blair, J. Bryan; Rabine, David L.; Hofton, Michelle A.

    1999-01-01

    The Laser Vegetation Imaging Sensor (LVIS) is an airborne, scanning laser altimeter designed and developed at NASA's Goddard Space Flight Center. LVIS operates at altitudes up to 10 km above ground, and is capable of producing a data swath up to 1000 m wide nominally with 25 m wide footprints. The entire time history of the outgoing and return pulses is digitized, allowing unambiguous determination of range and return pulse structure. Combined with aircraft position and attitude knowledge, this instrument produces topographic maps with decimeter accuracy and vertical height and structure measurements of vegetation. The laser transmitter is a diode-pumped Nd:YAG oscillator producing 1064 nm, 10 nsec, 5 mJ pulses at repetition rates up to 500 Hz. LVIS has recently demonstrated its ability to determine topography (including sub-canopy) and vegetation height and structure on flight missions to various forested regions in the U.S. and Central America. The LVIS system is the airborne simulator for the Vegetation Canopy Lidar (VCL) mission (a NASA Earth remote sensing satellite due for launch in 2000), providing simulated data sets and a platform for instrument proof-of-concept studies. The topography maps and return waveforms produced by LVIS provide Earth scientists with a unique data set allowing studies of topography, hydrology, and vegetation with unmatched accuracy and coverage.

  20. 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

  1. Imager-to-Radiometer In-flight Cross Calibration: RSP Radiometric Comparison with Airborne and Satellite Sensors

    NASA Technical Reports Server (NTRS)

    McCorkel, Joel; Cairns, Brian; Wasilewski, Andrzej

    2016-01-01

    This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP), which takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI). First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.

  2. 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

  3. Overview Of Haze And Smoke Measurements in Northern High Latitudes And California During ARCTAS Using The NASA Ames Airborne Sunphotometer And Associated In Situ And Remote Sensors

    NASA Astrophysics Data System (ADS)

    Russell, P. B.; Redemann, J.; Livingston, J.; Shinozuka, Y.; Ramachandran, S.; Johnson, R. R.; Clarke, A. D.; Howell, S. G.; McNaughton, C.; Holben, B.; O'Neill, N.; McArthur, B.; Reid, E.; Ferrare, R. A.; Hostetler, C. A.

    2009-12-01

    The 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) operated in a suite of remote and in-situ sensors aboard the NASA P-3 aircraft during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. Included were 8 Spring flights in the Arctic and 13 Summer flights (3 in California and 10 in Canada), each coordinated with one or more satellite overpasses, other aircraft (e.g., NASA B-200 and DC-8, NOAA P-3), and/or ground-based Aerosol Robotic Network (AERONET) measurements. This presentation gives an overview of AATS-14 aerosol optical depth (AOD) spectra and related parameters such as Angstrom exponent and fine mode fraction. We quantify the mutual consistency of AODs calculated from measurements by AATS-14, by the HiGEAR (University of Hawaii Group for Environmental Aerosol Research) suite of P-3 in-situ optical instruments, and by AERONET . The vertical integral of the HiGEAR in-situ scattering and absorption coefficients recorded during spiral profiles typically falls within 10% ± 0.02 of the AATS-14 AOD values interpolated to 450, 550 and 700 nm. Corresponding Angstrom exponents typically differ by ~0.1. AATS-14 AODs adjusted for the contribution of the layer below the aircraft (estimated with HiGEAR data) generally agree with the full column AERONET values to within the combined uncertainties. Example results from multi-platform comparisons are also shown. These results provide context for the more detailed AATS-14 results in other presentations, e.g., by Redemann et al. (focusing on the multi-platform, multi-sensor smoke case of 30 Jun 2008), Livingston et al. (comparisons to MODIS, MISR, OMI, POLDER, CALIPSO, and airborne lidar), and Shinozuka et al. (relationship to cloud condensation nuclei and other measurements).

  4. 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

  5. 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

  6. Microfabricated Air-Microfluidic Sensor for Personal Monitoring of Airborne Particulate Matter: Design, Fabrication, and Experimental Results

    EPA Science Inventory

    We present the design and fabrication of a micro electro mechanical systems (MEMS) air-microfluidic particulate matter (PM) sensor, and show experimental results obtained from exposing the sensor to concentrations of tobacco smoke and diesel exhaust, two commonly occurring P...

  7. 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.

  8. 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.

  9. Remote sensing of shorelines using data fusion of hyperspectral and multispectral imagery acquired from mobile and fixed platforms

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R.; Frystacky, Heather

    2012-06-01

    An optimized data fusion methodology is presented and makes use of airborne and vessel mounted hyperspectral and multispectral imagery acquired at littoral zones in Florida and the northern Gulf of Mexico. The results demonstrate the use of hyperspectral-multispectral data fusion anomaly detection along shorelines and in surface and subsurface waters. Hyperspectral imagery utilized in the data fusion analysis was collected using a 64-1024 channel, 1376 pixel swath width; temperature stabilized sensing system; an integrated inertial motion unit; and differential GPS. The imaging system is calibrated using dual 18 inch calibration spheres, spectral line sources, and custom line targets. Simultaneously collected multispectral three band imagery used in the data fusion analysis was derived either a 12 inch focal length large format camera using 9 inch high speed AGFA color negative film, a 12.3 megapixel digital camera or dual high speed full definition video cameras. Pushbroom sensor imagery is corrected using Kalman filtering and smoothing in order to correct images for airborne platform motions or motions of a small vessel. Custom software developed for the hyperspectral system and the optimized data fusion process allows for post processing using atmospherically corrected and georeferenced reflectance imagery. The optimized data fusion approach allows for detecting spectral anomalies in the resolution enhanced data cubes. Spectral-spatial anomaly detection is demonstrated using simulated embedded targets in actual imagery. The approach allows one to utilize spectral signature anomalies to identify features and targets that would otherwise not be possible. The optimized data fusion techniques and software has been developed in order to perform sensitivity analysis of the synthetic images in order to optimize the singular value decomposition model building process and the 2-D Butterworth cutoff frequency selection process, using the concept of user defined "feature

  10. Spectral Band Selection for Urban Material Classification Using Hyperspectral Libraries

    NASA Astrophysics Data System (ADS)

    Le Bris, A.; Chehata, N.; Briottet, X.; Paparoditis, N.

    2016-06-01

    In urban areas, information concerning very high resolution land cover and especially material maps are necessary for several city modelling or monitoring applications. That is to say, knowledge concerning the roofing materials or the different kinds of ground areas is required. Airborne remote sensing techniques appear to be convenient for providing such information at a large scale. However, results obtained using most traditional processing methods based on usual red-green-blue-near infrared multispectral images remain limited for such applications. A possible way to improve classification results is to enhance the imagery spectral resolution using superspectral or hyperspectral sensors. In this study, it is intended to design a superspectral sensor dedicated to urban materials classification and this work particularly focused on the selection of the optimal spectral band subsets for such sensor. First, reflectance spectral signatures of urban materials were collected from 7 spectral libraires. Then, spectral optimization was performed using this data set. The band selection workflow included two steps, optimising first the number of spectral bands using an incremental method and then examining several possible optimised band subsets using a stochastic algorithm. The same wrapper relevance criterion relying on a confidence measure of Random Forests classifier was used at both steps. To cope with the limited number of available spectra for several classes, additional synthetic spectra were generated from the collection of reference spectra: intra-class variability was simulated by multiplying reference spectra by a random coefficient. At the end, selected band subsets were evaluated considering the classification quality reached using a rbf svm classifier. It was confirmed that a limited band subset was sufficient to classify common urban materials. The important contribution of bands from the Short Wave Infra-Red (SWIR) spectral domain (1000-2400 nm) to material

  11. 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.

  12. Efficiency calibration and minimum detectable activity concentration of a real-time UAV airborne sensor system with two gamma spectrometers.

    PubMed

    Tang, Xiao-Bin; Meng, Jia; Wang, Peng; Cao, Ye; Huang, Xi; Wen, Liang-Sheng; Chen, Da

    2016-04-01

    A small-sized UAV (NH-UAV) airborne system with two gamma spectrometers (LaBr3 detector and HPGe detector) was developed to monitor activity concentration in serious nuclear accidents, such as the Fukushima nuclear accident. The efficiency calibration and determination of minimum detectable activity concentration (MDAC) of the specific system were studied by MC simulations at different flight altitudes, different horizontal distances from the detection position to the source term center and different source term sizes. Both air and ground radiation were considered in the models. The results obtained may provide instructive suggestions for in-situ radioactivity measurements of NH-UAV.

  13. Efficiency calibration and minimum detectable activity concentration of a real-time UAV airborne sensor system with two gamma spectrometers.

    PubMed

    Tang, Xiao-Bin; Meng, Jia; Wang, Peng; Cao, Ye; Huang, Xi; Wen, Liang-Sheng; Chen, Da

    2016-04-01

    A small-sized UAV (NH-UAV) airborne system with two gamma spectrometers (LaBr3 detector and HPGe detector) was developed to monitor activity concentration in serious nuclear accidents, such as the Fukushima nuclear accident. The efficiency calibration and determination of minimum detectable activity concentration (MDAC) of the specific system were studied by MC simulations at different flight altitudes, different horizontal distances from the detection position to the source term center and different source term sizes. Both air and ground radiation were considered in the models. The results obtained may provide instructive suggestions for in-situ radioactivity measurements of NH-UAV. PMID:26773821

  14. Development of a low-cost airborne ultrasound sensor for the detection of brick joints behind a wall painting.

    PubMed

    García-Diego, Fernando-Juan; Bravo, José María; Pérez-Miralles, Juan; Estrada, Héctor; Fernández-Navajas, Angel

    2012-01-01

    Non-destructive methods are of great interest for the analysis of cultural heritage. Among the different possible techniques, this paper presents a low cost prototype based on the emission and reception of airborne ultrasound without direct contact with the test specimen. We successfully performed a method test for the detection of brick joints under a XV th century Renaissance fresco of the Metropolitan Cathedral of the city of Valencia (Spain). Both laboratory and in situ results are in agreement. Using this prototype system, an early moisture detection system has been installed in the dome that supports the fresco. The result is encouraging and opens interesting prospects for future research.

  15. Development of a Low-Cost Airborne Ultrasound Sensor for the Detection of Brick Joints behind a Wall Painting

    PubMed Central

    García-Diego, Fernando-Juan; Bravo, José María; Pérez-Miralles, Juan; Estrada, Héctor; Fernández-Navajas, Angel

    2012-01-01

    Non-destructive methods are of great interest for the analysis of cultural heritage. Among the different possible techniques, this paper presents a low cost prototype based on the emission and reception of airborne ultrasound without direct contact with the test specimen. We successfully performed a method test for the detection of brick joints under a XVth century Renaissance fresco of the Metropolitan Cathedral of the city of Valencia (Spain). Both laboratory and in situ results are in agreement. Using this prototype system, an early moisture detection system has been installed in the dome that supports the fresco. The result is encouraging and opens interesting prospects for future research. PMID:22438711

  16. Can the normalized soil moisture index improve the prediction of soil organic carbon based on hyperspectral remote sensing data?

    NASA Astrophysics Data System (ADS)

    van Wesemael, Bas; Nocita, Marco

    2016-04-01

    One of the problems for mapping of soil organic carbon (SOC) at large-scale based on visible - near and short wave infrared (VIS-NIR-SWIR) remote sensing techniques is the spatial variation of topsoil moisture when the images are collected. Soil moisture is certainly an aspect causing biased SOC estimations, due to the problems in discriminating reflectance differences due to either variations in organic matter or soil moisture, or their combination. In addition, the difficult validation procedures make the accurate estimation of soil moisture from optical airborne a major challenge. After all, the first millimeters of the soil surface reflect the signal to the airborne sensor and show a large spatial, vertical and temporal variation in soil moisture. Hence, the difficulty of assessing the soil moisture of this thin layer at the same moment of the flight. The creation of a soil moisture proxy, directly retrievable from the hyperspectral data is a priority to improve the large-scale prediction of SOC. This paper aims to verify if the application of the normalized soil moisture index (NSMI) to Airborne Prima Experiment (APEX) hyperspectral images could improve the prediction of SOC. The study area was located in the loam region of Wallonia, Belgium. About 40 samples were collected from bare fields covered by the flight lines, and analyzed in the laboratory. Soil spectra, corresponding to the sample locations, were extracted from the images. Once the NSMI was calculated for the bare fields' pixels, spatial patterns, presumably related to within field soil moisture variations, were revealed. SOC prediction models, built using raw and pre-treated spectra, were generated from either the full dataset (general model), or pixels belonging to one of the two classes of NSMI values (NSMI models). The best result, with a RMSE after validation of 1.24 g C kg-1, was achieved with a NSMI model, compared to the best general model, characterized by a RMSE of 2.11 g C kg-1. These

  17. Airborne agent concentration analysis

    DOEpatents

    Gelbard, Fred

    2004-02-03

    A method and system for inferring airborne contaminant concentrations in rooms without contaminant sensors, based on data collected by contaminant sensors in other rooms of a building, using known airflow interconnectivity data. The method solves a least squares problem that minimizes the difference between measured and predicted contaminant sensor concentrations with respect to an unknown contaminant release time. Solutions are constrained to providing non-negative initial contaminant concentrations in all rooms. The method can be used to identify a near-optimal distribution of sensors within the building, when then number of available sensors is less than the total number of rooms. This is achieved by having a system-sensor matrix that is non-singular, and by selecting that distribution which yields the lowest condition number of all the distributions considered. The method can predict one or more contaminant initial release points from the collected data.

  18. 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

  19. Adaptation of Industrial Hyperspectral Line Scanner for Archaeological Applications

    NASA Astrophysics Data System (ADS)

    Miljković, V.; Gajski, D.

    2016-06-01

    The spectral characteristic of the visible light reflected from any of archaeological artefact is the result of the interaction of its surface illuminated by incident light. Every particular surface depends on what material it is made of and/or which layers put on it has its spectral signature. Recent archaeometry recognises this information as very valuable data to extend present documentation of artefacts and as a new source for scientific exploration. However, the problem is having an appropriate hyperspectral imaging system available and adopted for applications in archaeology. In this paper, we present the new construction of the hyperspectral imaging system, made of industrial hyperspectral line scanner ImSpector V9 and CCD-sensor PixelView. The hyperspectral line scanner is calibrated geometrically, and hyperspectral data are geocoded and converted to the hyperspectral cube. The system abilities are evaluated for various archaeological artefacts made of different materials. Our experience in applications, visualisations, and interpretations of collected hyperspectral data are explored and presented.

  20. 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

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

    NASA Astrophysics Data System (ADS)

    Proctor, C.; He, Y.

    2015-08-01

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

  2. 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

  3. Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: retrieval algorithm and measurements during DISCOVER-AQ Texas 2013

    NASA Astrophysics Data System (ADS)

    Nowlan, C. R.; Liu, X.; Leitch, J. W.; Chance, K.; González Abad, G.; Liu, C.; Zoogman, P.; Cole, J.; Delker, T.; Good, W.; Murcray, F.; Ruppert, L.; Soo, D.; Follette-Cook, M. B.; Janz, S. J.; Kowalewski, M. G.; Loughner, C. P.; Pickering, K. E.; Herman, J. R.; Beaver, M. R.; Long, R. W.; Szykman, J. J.; Judd, L. M.; Kelley, P.; Luke, W. T.; Ren, X.; Al-Saadi, J. A.

    2015-12-01

    The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a testbed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas in September 2013. Measurements of backscattered solar radiation between 420-465 nm collected on four days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 molecules cm-2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.91 for the most polluted day). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.84, slope = 0.94). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

  4. Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013

    NASA Astrophysics Data System (ADS)

    Nowlan, Caroline R.; Liu, Xiong; Leitch, James W.; Chance, Kelly; González Abad, Gonzalo; Liu, Cheng; Zoogman, Peter; Cole, Joshua; Delker, Thomas; Good, William; Murcray, Frank; Ruppert, Lyle; Soo, Daniel; Follette-Cook, Melanie B.; Janz, Scott J.; Kowalewski, Matthew G.; Loughner, Christopher P.; Pickering, Kenneth E.; Herman, Jay R.; Beaver, Melinda R.; Long, Russell W.; Szykman, James J.; Judd, Laura M.; Kelley, Paul; Luke, Winston T.; Ren, Xinrong; Al-Saadi, Jassim A.

    2016-06-01

    The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 moleculescm-2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

  5. Multi- and hyperspectral remote sensing of tropical marine benthic habitats

    NASA Astrophysics Data System (ADS)

    Mishra, Deepak R.

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

  6. Hyperspectral and Polarimetric Signatures of Vegetation from AirMSPI and AVIRIS Measurements

    NASA Astrophysics Data System (ADS)

    Yang, B.; Knyazikhin, Y.; Seidel, F. C.; Chen, C.; Yan, K.; Park, T.; CHOI, S.; Mottus, M.; Rautiainen, M.; Stenberg, P.; Myneni, R. B.; Yan, L.

    2015-12-01

    Leaf scattering spectrum is the only optical variable that conveys information about leaf biochemistry. It cannot be directly measured from space because the radiation measured by the sensor is affected by the canopy structure and the atmosphere. Multiangle remote sensing data provide information critical to account for such effects, including structural contributions to measurements of leaf optics. Some radiation is scattered at the surface of leaves, which contains no information on the leaf interior. This represents an additional confounding factor, unless it can be accounted for. Polarization measurements are useful to quantify leaf surface characteristics because radiation scattered at the surface of leaves is partly polarized whereas that from the leaf interior is not. This poster presents analyses of surface reflectance data from Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Our results indicate that 1) sensitivity of spectral reflectance corrected for canopy structure effects to foliar nitrogen (N) content is negatively related to the leaf degree of linear polarization (DOLP); 2) polarized canopy BRF (pBRF) in oblique directions can account up to 52% of reflected radiation; 3) pBRF varies with species, suggesting that leaf surface properties cannot be neglected when interpreting BRF; 4) canopy reflects radiation specularly in all directions. In general our results suggest that hyperspectral, multiangle and polarimetric data are required to monitor leaf biochemistry from space.

  7. A next generation VNIR-SWIR hyperspectral camera system: HySpex ODIN-1024

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    The HySpex ODIN-1024 is an airborne VNIR-SWIR hyperspectral imaging system which advances the state of the art with respect to both performance and system functionality. HySpex ODIN-1024 is designed as a single instrument for both VNIR (0.4 to 1 μm wavelength) and SWIR (1 to 2.5 μm) rather than being a combination of two separate instruments. With the common fore-optics of the single instrument, a more accurate and stable co-registration is achieved across the full spectral range compared to having two individual instruments. For SWIR the across-the-track resolution is 1024 pixels, while for VNIR the user of the instrument can choose a resolution of either 1024 or 2048 pixels. In addition to high spatial resolution, the optical design enables low smile- and keystone distortion and high sensitivity obtained through low F-numbers of F1.64 for VNIR and F2.0 for SWIR. The camera utilizes state of the art scientific CMOS (VNIR) and MCT (SWIR) sensors with low readout noise, high speed and spatial resolution. The system has an onboard-calibration subsystem to monitor the stability of the instrument during variations in environmental conditions. It features an integrated real-time processing functionality, enabling real-time detection, classification, and georeferencing. We present an overview of the performance of the instrument and results from airborne data acquisitions.

  8. FAPEC-based lossless and lossy hyperspectral data compression

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  10. Designing an in-flight airborne calibration site using experience from vicarious radiometric satellite calibration

    NASA Astrophysics Data System (ADS)

    Livens, Stefan; Debruyn, Walter; Sterckx, Sindy; Reusen, Ils

    2011-11-01

    Laboratory calibration of electro-optical sensors is preferably complemented by regular in-flight verification. This checks whether the lab calibration parameters remain valid or recalibration is necessary. In-flight verification can be achieved by vicarious calibration using in-flight measurements of calibration targets. We intend to identify and design a set of suitable radiometric calibration targets. For this, we borrow from expertise gained with the PROBA-V satellite calibration system, which uses multiple vicarious methods relying on diverse natural on-ground targets. Besides reflectance based calibration using ground measurements, the PROBA-V calibration methods are unproven for use in airborne calibration. The selected targets should be suitable for the calibration of both multispectral and hyperspectral imagers. We start from general requirements for radiometric targets and investigate their applicability to airborne calibration. From this we identify two possible sets of natural calibration sites in Belgium. One set, located in the Campine region, contains small water bodies and sandy lakesides. Another set is located in the Westhoek region near the Belgian coast. It offers better suitable water bodies, as well as sandy areas, grass fields and dark targets. Airborne calibration lends itself to the use of smaller artifical targets. We propose to complement the natural targets with a portable target consisting of agricultural nets with different densities. The definition of sets of calibration targets, both natural and artificial can facilitate the investigation of the usability of vicarious targets and method for inflight radiometric verification.

  11. Hyperspectral monitoring of chemically sensitive plant sentinels

    NASA Astrophysics Data System (ADS)

    Simmons, Danielle A.; Kerekes, John P.; Raqueno, Nina G.

    2009-08-01

    Automated detection of chemical threats is essential for an early warning of a potential attack. Harnessing plants as bio-sensors allows for distributed sensing without a power supply. Monitoring the bio-sensors requires a specifically tailored hyperspectral system. Tobacco plants have been genetically engineered to de-green when a material of interest (e.g. zinc, TNT) is introduced to their immediate vicinity. The reflectance spectra of the bio-sensors must be accurately characterized during the de-greening process for them to play a role in an effective warning system. Hyperspectral data have been collected under laboratory conditions to determine the key regions in the reflectance spectra associated with the degreening phenomenon. Bio-sensor plants and control (nongenetically engineered) plants were exposed to TNT over the course of two days and their spectra were measured every six hours. Rochester Institute of Technologys Digital Imaging and Remote Sensing Image Generation Model (DIRSIG) was used to simulate detection of de-greened plants in the field. The simulated scene contains a brick school building, sidewalks, trees and the bio-sensors placed at the entrances to the buildings. Trade studies of the bio-sensor monitoring system were also conducted using DIRSIG simulations. System performance was studied as a function of field of view, pixel size, illumination conditions, radiometric noise, spectral waveband dependence and spectral resolution. Preliminary results show that the most significant change in reflectance during the degreening period occurs in the near infrared region.

  12. 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.

  13. Classification of Hyperspectral or Trichromatic Measurements of Ocean Color Data into Spectral Classes

    PubMed Central

    Prasad, Dilip K.; Agarwal, Krishna

    2016-01-01

    We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the known spectral classes of the reflectances from the ocean. The method compensates for the unknown downwelling irradiance by white balancing the radiometric data at the ocean pixels using the radiometric data of bright pixels (typically from clouds). The white-balanced data is compared with the entries in a pre-calibrated lookup table in which each entry represents the spectral properties of one class. The proposed approach is tested on two datasets of in situ measurements and 26 different daylight illumination spectra for medium resolution imaging spectrometer (MERIS), moderate-resolution imaging spectroradiometer (MODIS), sea-viewing wide field-of-view sensor (SeaWiFS), coastal zone color scanner (CZCS), ocean and land colour instrument (OLCI), and visible infrared imaging radiometer suite (VIIRS) sensors. Results are also shown for CIMEL’s SeaPRISM sun photometer sensor used on-board field trips. Accuracy of more than 92% is observed on the validation dataset and more than 86% is observed on the other dataset for all satellite sensors. The potential of applying the algorithms to non-satellite and non-multi-spectral sensors mountable on airborne systems is demonstrated by showing classification results for two consumer cameras. Classification on actual MERIS data is also shown. Additional results comparing the spectra of remote sensing reflectance with level 2 MERIS data and chlorophyll concentration estimates of the data are included. PMID:27011185

  14. Classification of Hyperspectral or Trichromatic Measurements of Ocean Color Data into Spectral Classes.

    PubMed

    Prasad, Dilip K; Agarwal, Krishna

    2016-01-01

    We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the known spectral classes of the reflectances from the ocean. The method compensates for the unknown downwelling irradiance by white balancing the radiometric data at the ocean pixels using the radiometric data of bright pixels (typically from clouds). The white-balanced data is compared with the entries in a pre-calibrated lookup table in which each entry represents the spectral properties of one class. The proposed approach is tested on two datasets of in situ measurements and 26 different daylight illumination spectra for medium resolution imaging spectrometer (MERIS), moderate-resolution imaging spectroradiometer (MODIS), sea-viewing wide field-of-view sensor (SeaWiFS), coastal zone color scanner (CZCS), ocean and land colour instrument (OLCI), and visible infrared imaging radiometer suite (VIIRS) sensors. Results are also shown for CIMEL's SeaPRISM sun photometer sensor used on-board field trips. Accuracy of more than 92% is observed on the validation dataset and more than 86% is observed on the other dataset for all satellite sensors. The potential of applying the algorithms to non-satellite and non-multi-spectral sensors mountable on airborne systems is demonstrated by showing classification results for two consumer cameras. Classification on actual MERIS data is also shown. Additional results comparing the spectra of remote sensing reflectance with level 2 MERIS data and chlorophyll concentration estimates of the data are included. PMID:27011185

  15. Classification of Hyperspectral or Trichromatic Measurements of Ocean Color Data into Spectral Classes.

    PubMed

    Prasad, Dilip K; Agarwal, Krishna

    2016-03-22

    We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the known spectral classes of the reflectances from the ocean. The method compensates for the unknown downwelling irradiance by white balancing the radiometric data at the ocean pixels using the radiometric data of bright pixels (typically from clouds). The white-balanced data is compared with the entries in a pre-calibrated lookup table in which each entry represents the spectral properties of one class. The proposed approach is tested on two datasets of in situ measurements and 26 different daylight illumination spectra for medium resolution imaging spectrometer (MERIS), moderate-resolution imaging spectroradiometer (MODIS), sea-viewing wide field-of-view sensor (SeaWiFS), coastal zone color scanner (CZCS), ocean and land colour instrument (OLCI), and visible infrared imaging radiometer suite (VIIRS) sensors. Results are also shown for CIMEL's SeaPRISM sun photometer sensor used on-board field trips. Accuracy of more than 92% is observed on the validation dataset and more than 86% is observed on the other dataset for all satellite sensors. The potential of applying the algorithms to non-satellite and non-multi-spectral sensors mountable on airborne systems is demonstrated by showing classification results for two consumer cameras. Classification on actual MERIS data is also shown. Additional results comparing the spectra of remote sensing reflectance with level 2 MERIS data and chlorophyll concentration estimates of the data are included.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  17. Self-adaptive road tracking in hyperspectral data for C-IED

    NASA Astrophysics Data System (ADS)

    Schilling, Hendrik; Gross, Wolfgang; Middelmann, Wolfgang

    2012-09-01

    For Counter Improvised Explosive Devices purposes, main routes including their vicinity are surveyed. In future military operations, small hyperspectral sensors will be used for ground covering reconnaissance, complementing images from infrared and high resolution sensors. They will be mounted on unmanned airborne vehicles and are used for on-line monitoring of convoy routes. Depending of the proximity to the road, different regions can be defined for threat assessment. Automatic road tracking can help choosing the correct areas of interest. Often, the exact discrimination between road and surroundings fails in conventional methods due to low contrast in pan-chromatic images at the road boundaries or occlusions. In this contribution, a novel real-time lock-on road tracking algorithm is introduced. It uses hyperspectral data and is specifically designed to address the afore- mentioned deficiencies of conventional methods. Local features are calculated from the high-resolution spectral signatures. They describe the similarity to the actual road cover and to either roadside. Classification is per- formed to discriminate the signatures. To improve robustness against variations in road cover, the classification results are used to progressively adapt the road and roadside classes. Occlusions are treated by predicting the course of the road and comparing the signatures in the target area to previously determined road cover signa- tures. The algorithm can be easily extended to show regions of varying threat, depending on the distance to the road. Thus, complex anomaly detectors and classification algorithms can be applied to a reduced data set. First experiments were performed for AISA Eagle II (400nm - 970nm) and AISA Hawk (970nm - 2450nm) data

  18. Multi-angular hyperspectral observations of Mediterranean forest with PROBA-CHRIS

    NASA Astrophysics Data System (ADS)

    Menenti, Massimo; Maselli, Fabio; Chiesi, Marta; Benedetti, Riccardo; Cristofori, Simone; Guzzi, Donatella; Magnani, Federico; Raddi, Sabrina; Maffei, Carmine

    2004-10-01

    Measurements of spectro-directional radiances done with the imaging spectrometer CHRIS on-board the agile platform PROBA are being used to determine key properties of terrestrial vegetation at the appropriate spatial resolution. These data on vegetation properties can then be used to improve the accuracy and the parameterizations of models describing biosphere processes, i.e. photosynthesis and water use by irrigated crops and trees. The vegetation properties considered are: albedo, Leaf Area Index (LAI), fractional cover, fraction of absorbed photosynthetically active radiation (fAPAR) and canopy chlorophyll content. The Natural Park of San Rossore (Pisa, Central Italy) is a primary test site for several national and international research projects dealing with forest ecosystem monitoring. In particular, since 1999 measurements of transpiration and ecosystem gas-exchange have been regularly taken in the park pine forest to characterize its main water and carbon fluxes. In the same period, several aerial flights have been carried out with onboard hyper-spectral sensors (MIVIS, VIRS, AISA), while a series of satellite images have been acquired using both conventional (NOAAAVHRR, Landsat-TM/ETM+) and advanced sensors (CHRIS-PROBA). The final objective of these activities is to calibrate and validate methodologies which integrate remotely sensed and ancillary data for monitoring forest ecosystem. More specifically, a major research effort has been focused on evaluating the additional information content provided by advanced hyper-spectral multi-angular sensors about the main parameters needed for forest characterization (species, LAI, pigment content, etc.). These activities are part of projects which are financed by the Italian and European Space Agencies (ASI and ESA, respectively) within the framework of the CHRIS-PROBA and SPECTRA missions. During 2002 and 2003 nine complete multi-angular acquisitions were successfully performed over the San Rossore site. This

  19. Airborne test results for smart pushbroom imaging system with optoelectronic image correction

    NASA Astrophysics Data System (ADS)

    Tchernykh, Valerij; Dyblenko, Serguei; Janschek, Klaus; Seifart, Klaus; Harnisch, Bernd

    2004-02-01

    Smart pushbroom imaging system (SMARTSCAN) solves the problem of image correction for satellite pushbroom cameras which are disturbed by satellite attitude instability effects. Satellite cameras with linear sensors are particularly sensitive to attitude errors, which cause considerable image distortions. A novel solution of distortions correction is presented, which is based on the real-time recording of the image motion in the focal plane of the satellite camera. This allows using such smart pushbroom cameras (multi-/hyperspectral) even on moderately stabilised satellites, e.g. small sat's, LEO comsat's. The SMARTSCAN concept uses in-situ measurements of the image motion with additional CCD-sensors in the focal plane and real-time image processing of these measurements by an onboard Joint Transform Optical Correlator. SMARTSCAN has been successfully demonstrated with breadboard models for the Optical Correlator and a Smart Pushbroom Camera at laboratory level (satellite motion simulator on base of a 5 DOF industrial robot) and by an airborne flight demonstration in July 2002. The paper describes briefly the principle of operation of the system and gives a description of the hardware model are provided. Detailed results of the airborne tests and performance analysis are given as well as detailed tests description.

  20. SWIR hyperspectral imaging detector for surface residues

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  1. On the effects of spatial and spectral resolution on spatial-spectral target detection in SHARE 2012 and Bobcat 2013 hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Kaufman, Jason R.; Eismann, Michael T.; Ratliff, Bradley M.; Celenk, Mehmet

    2015-05-01

    Previous work with the Bobcat 2013 data set1 showed that spatial-spectral feature extraction on visible to near infrared (VNIR) hyperspectral imagery (HSI) led to better target detection and discrimination than spectral-only techniques; however, the aforementioned study could not consider the possible benefits of the shortwaveinfrared (SWIR) portion of the spectrum due to data limitations. In addition, the spatial resolution of the Bobcat 2013 imagery was fixed at 8cm without exploring lower spatial resolutions. In this work, we evaluate the tradeoffs in spatial and spectral resolution and spectral coverage between for a common set of targets in terms of their effects on spatial-spectral target detection performance. We show that for our spatial-spectral target detection scheme and data sets, the adaptive cosine estimator (ACE) applied to S-DAISY and pseudo Zernike moment (PZM) spatial-spectral features can distinguish between targets better than ACE applied only to the spectral imagery. In particular, S-DAISY operating on bands uniformly selected from the SWIR portion of ProSpecTIR-VS sensor imagery in conjunction with bands closely corresponding to the Airborne Real-time Cueing Hyperspectral Reconnaissance (ARCHER) sensor's VNIR bands (80 total) led to the best overall average performance in both target detection and discrimination.

  2. D Hyperspectral Frame Imager Camera Data in Photogrammetric Mosaicking

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  3. PET and PVC Separation with Hyperspectral Imagery

    PubMed Central

    Moroni, Monica; Mei, Alessandro; Leonardi, Alessandra; Lupo, Emanuela; La Marca, Floriana

    2015-01-01

    Traditional plants for plastic separation in homogeneous products employ material physical properties (for instance density). Due to the small intervals of variability of different polymer properties, the output quality may not be adequate. Sensing technologies based on hyperspectral imaging have been introduced in order to classify materials and to increase the quality of recycled products, which have to comply with specific standards determined by industrial applications. This paper presents the results of the characterization of two different plastic polymers—polyethylene terephthalate (PET) and polyvinyl chloride (PVC)—in different phases of their life cycle (primary raw materials, urban and urban-assimilated waste and secondary raw materials) to show the contribution of hyperspectral sensors in the field of material recycling. This is accomplished via near-infrared (900–1700 nm) reflectance spectra extracted from hyperspectral images acquired with a two-linear-spectrometer apparatus. Results have shown that a rapid and reliable identification of PET and PVC can be achieved by using a simple two near-infrared wavelength operator coupled to an analysis of reflectance spectra. This resulted in 100% classification accuracy. A sensor based on this identification method appears suitable and inexpensive to build and provides the necessary speed and performance required by the recycling industry. PMID:25609050

  4. PET and PVC separation with hyperspectral imagery.

    PubMed

    Moroni, Monica; Mei, Alessandro; Leonardi, Alessandra; Lupo, Emanuela; Marca, Floriana La

    2015-01-20

    Traditional plants for plastic separation in homogeneous products employ material physical properties (for instance density). Due to the small intervals of variability of different polymer properties, the output quality may not be adequate. Sensing technologies based on hyperspectral imaging have been introduced in order to classify materials and to increase the quality of recycled products, which have to comply with specific standards determined by industrial applications. This paper presents the results of the characterization of two different plastic polymers--polyethylene terephthalate (PET) and polyvinyl chloride (PVC)--in different phases of their life cycle (primary raw materials, urban and urban-assimilated waste and secondary raw materials) to show the contribution of hyperspectral sensors in the field of material recycling. This is accomplished via near-infrared (900-1700 nm) reflectance spectra extracted from hyperspectral images acquired with a two-linear-spectrometer apparatus. Results have shown that a rapid and reliable identification of PET and PVC can be achieved by using a simple two near-infrared wavelength operator coupled to an analysis of reflectance spectra. This resulted in 100% classification accuracy. A sensor based on this identification method appears suitable and inexpensive to build and provides the necessary speed and performance required by the recycling industry.

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

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Yu; Yamada, Yoshiro; Ishii, Juntaro

    2013-10-01

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

  6. Hyperspectral target detection using sequential approach

    NASA Astrophysics Data System (ADS)

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

    1999-08-01

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

  7. Analysis of soil moisture retrieval from airborne passive/active L-band sensor measurements in SMAPVEX 2012

    NASA Astrophysics Data System (ADS)

    Chen, Liang; Song, Hongting; Tan, Lei; Li, Yinan; Li, Hao

    2014-11-01

    Soil moisture is a key component in the hydrologic cycle and climate system. It is an important input parameter for many hydrologic and meteorological models. NASA'S upcoming Soil Moisture Active Passive (SMAP) mission, to be launched in October 2014, will address this need by utilizing passive and active microwave measurements at L-band, which will penetrate moderately dense canopies. In preparation for the SMAP mission, the Soil Moisture Validation Experiment 2012 (SMAPVEX12) was conducted from 6 June to 17 July 2012 in the Carment-Elm Creek area in Manitoba, Canada. Over a period of six weeks diverse land cover types ranging from agriculture over pasture and grassland to forested sites were re-visited several times a week. The Passive/Active L-band Sensor (PALS) provides radiometer products, vertically and horizontally polarized brightness temperatures, and radar products. Over the past two decades, successful estimation of soil moisture has been accomplished using passive and active L-band data. However, remaining uncertainties related to surface roughness and the absorption, scattering, and emission by vegetation must be resolved before soil moisture retrieval algorithms can be applied with known and acceptable accuracy using satellite observations. This work focuses on analyzing the Passive/Active L-band Sensor observations of sites covered during SMAPVEX12, investigating the observed data, parameterizing vegetation covered surface model, modeling inversion algorithm and analyzing observed soil moisture changes over the time period of six weeks. The data and analysis results from this study are aimed at increasing the accuracy and range of validity of SMAP soil moisture retrievals via enhancing the accuracy for soil moisture retrieval.

  8. Improvement of Short-Wave InfraRed Hyperspectral Imaging by Direct Polarization Measurements

    NASA Astrophysics Data System (ADS)

    Leblanc, G. E.; Allux, S.

    2010-12-01

    Hyperspectral imaging is susceptible to a myriad of atmospheric effects that cause undesirable effects when applying advanced processing techniques. Principally, scattering of incoming solar energy and the resulting “haze” produced has a considerable influence on the resulting quality of the data acquired in the ShortWave InfraRed (SWIR) region (850nm to 2500nm) of the electromagnetic spectrum. To alleviate this condition we have devised a polarization system for the Flight Research Laboratory’s (FRL) airborne SWIR hyperspectral imaging system and have collected data from various sources via ground-based and airborne environments. The Polarized SWIR (PSWIR) system we have devised incorporates a linear 90° polarization filter, within a framework that has been attached to FRL’s SWIR system. The polarizer lens is aligned to the 0° axis of the optical slit and can be rotated a full 360°. For the ground-based data collection, the PSWIR was mounted on a z-axis 360° rotation mount which allowed for scanning within the vertical plane as the imager is a push-broom imager that requires motion of the system in order to obtain spatial information. Data was acquired at various polarization orientations in steps of 45° from 0° through to 180°. The data was then analysed using Principle Component Analysis (PCA) and results show that substantial improvement signal-to-noise in higher-order PC’s are obtained in the PSWIR system compared to the SWIR system without polarization. Further, the higher order PC’s derived from the PSWIR system once compared to the SWIR system alone, lead us to conclude that many “artefacts” often ascribed to sensor problems can, in fact, be attributed to unresolved scatter issues in the data. The entire system was then installed aboard FRL’s Twin Otter aircraft and flown over various target materials of interest (man-made, vegetation, soils...) several times over the course of 3-weeks in July/August 2010. As a result of analysing

  9. Super-resolution of hyperspectral images using sparse representation and Gabor prior

    NASA Astrophysics Data System (ADS)

    Patel, Rakesh C.; Joshi, Manjunath V.

    2016-04-01

    Super-resolution (SR) as a postprocessing technique is quite useful in enhancing the spatial resolution of hyperspectral (HS) images without affecting its spectral resolution. We present an approach to increase the spatial resolution of HS images by making use of sparse representation and Gabor prior. The low-resolution HS observations consisting of large number of bands are represented as a linear combination of a small number of basis images using principal component analysis (PCA), and the significant components are used in our work. We first obtain initial estimates of SR on this reduced dimension by using compressive sensing-based method. Since SR is an ill-posed problem, the final solution is obtained by using a regularization framework. The novelty of our approach lies in: (1) estimation of optimal point spread function in the form of decimation matrix, and (2) using a new prior called "Gabor prior" to super-resolve the significant PCA components. Experiments are conducted on two different HS datasets namely, 31-band natural HS image set collected under controlled laboratory environment and a set of 224-band real HS images collected by airborne visible/infrared imaging spectrometer remote sensing sensor. Visual inspections and quantitative comparison confirm that our method enhances spatial information without introducing significant spectral distortion. Our conclusions include: (1) incorporate the sensor characteristics in the form of estimated decimation matrix for SR, and (2) preserve various frequencies in super-resolved image by making use of Gabor prior.

  10. 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.

  11. 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...

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  13. 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)

  14. Applying emerging digital video interface standards to airborne avionics sensor and digital map integrations: benefits outweigh the initial costs

    NASA Astrophysics Data System (ADS)

    Kuehl, C. Stephen

    1996-06-01

    Video signal system performance can be compromised in a military aircraft cockpit management system (CMS) with the tailoring of vintage Electronics Industries Association (EIA) RS170 and RS343A video interface standards. Video analog interfaces degrade when induced system noise is present. Further signal degradation has been traditionally associated with signal data conversions between avionics sensor outputs and the cockpit display system. If the CMS engineering process is not carefully applied during the avionics video and computing architecture development, extensive and costly redesign will occur when visual sensor technology upgrades are incorporated. Close monitoring and technical involvement in video standards groups provides the knowledge-base necessary for avionic systems engineering organizations to architect adaptable and extendible cockpit management systems. With the Federal Communications Commission (FCC) in the process of adopting the Digital HDTV Grand Alliance System standard proposed by the Advanced Television Systems Committee (ATSC), the entertainment and telecommunications industries are adopting and supporting the emergence of new serial/parallel digital video interfaces and data compression standards that will drastically alter present NTSC-M video processing architectures. The re-engineering of the U.S. Broadcasting system must initially preserve the electronic equipment wiring networks within broadcast facilities to make the transition to HDTV affordable. International committee activities in technical forums like ITU-R (former CCIR), ANSI/SMPTE, IEEE, and ISO/IEC are establishing global consensus on video signal parameterizations that support a smooth transition from existing analog based broadcasting facilities to fully digital computerized systems. An opportunity exists for implementing these new video interface standards over existing video coax/triax cabling in military aircraft cockpit management systems. Reductions in signal

  15. Evaluation of Various Spectral Inputs for Estimation of Forest Biochemical and Structural Properties from Airborne Imaging Spectroscopy Data

    NASA Astrophysics Data System (ADS)

    Homolová, L.; Janoutová, R.; Malenovský, Z.

    2016-06-01

    In this study we evaluated various spectral inputs for retrieval of forest chlorophyll content (Cab) and leaf area index (LAI) from high spectral and spatial resolution airborne imaging spectroscopy data collected for two forest study sites in the Czech Republic (beech forest at Štítná nad Vláří and spruce forest at Bílý Kříž). The retrieval algorithm was based on a machine learning method - support vector regression (SVR). Performance of the four spectral inputs used to train SVR was evaluated: a) all available hyperspectral bands, b) continuum removal (CR) 645 - 710 nm, c) CR 705 - 780 nm, and d) CR 680 - 800 nm. Spectral inputs and corresponding SVR models were first assessed at the level of spectral databases simulated by combined leaf-canopy radiative transfer models PROSPECT and DART. At this stage, SVR models using all spectral inputs provided good performance (RMSE for Cab < 10 μg cm-2 and for LAI < 1.5), with consistently better performance for beech over spruce site. Since application of trained SVRs on airborne hyperspectral images of the spruce site produced unacceptably overestimated values, only the beech site results were analysed. The best performance for the Cab estimation was found for CR bands in range of 645 - 710 nm, whereas CR bands in range of 680 - 800 nm were the most suitable for LAI retrieval. The CR transformation reduced the across-track bidirectional reflectance effect present in airborne images due to large sensor field of view.

  16. 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.

  17. Airborne Oceanographic Lidar (AOL) (Global Carbon Cycle)

    NASA Technical Reports Server (NTRS)

    2003-01-01

    This bimonthly contractor progress report covers the operation, maintenance and data management of the Airborne Oceanographic Lidar and the Airborne Topographic Mapper. Monthly activities included: mission planning, sensor operation and calibration, data processing, data analysis, network development and maintenance and instrument maintenance engineering and fabrication.

  18. Hyper-spectral scanner design and analysis

    SciTech Connect

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

    1996-06-01

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

  19. Seagrass biomass and productivity in the Florida Keys, USA: ground-level and airborne measurements

    NASA Astrophysics Data System (ADS)

    Yarbro, L.; Carlson, P. R., Jr.; McHan, C.; Carlson, D. F.; Hu, C.; Danielson, T.; Durnan, B.; English, D. C.; Muller-Karger, F. E.; Yates, K. K.; Herwitz, S.; Merrill, J.; Mewes, T.

    2013-12-01

    Seagrass communities serve as essential habitat for fish and shellfish, and recent research indicates that they can play a significant role in reducing ocean acidification. As part of a collaborative project funded by the NASA ROSES program and administered by the NASA UAV Collaborative, we collected hyperspectral imagery of seagrass beds and measured productivity of Thalassia testudinum at Sugarloaf Key, Florida, in May 2012, October 2012, and May 2013. Our primary goal was to evaluate the utility of hyperspectral sensors, in general, and UAV platforms, in specific, to measure seagrass health and productivity. Airborne measurements using the AISA Eagle hyperspectral imaging system were carried out simultaneously with ground measurements of Thalassia fluorescence, oxygen metabolism, growth, and biomass, as well as remote sensing reflectance and several in situ optical properties. Water depths at the study site ranged from less than 1 m to 5 m. Phytoplankton chlorophyll-a concentrations (0.09-0.72 ug l-1), ag(440) (0-0.02 m-1), and turbidity (0.12-4.1 ntu) were relatively low for all three deployments, facilitating the collection of excellent imagery and application of water-column radiative-transfer corrections. Aboveground Thalassia and macroalgal biomass, at 18 sites in the study area, ranged from 210 to 690 and 11 to 590 gDW m-2, respectively. One-sided green leaf area index of Thalassia ranged from 0.7 to 3.0. Preliminary findings show that the sensitivity of relationships between seagrass productivity and biomass parameters and remotely-sensed habitat spectra is reduced with increasing water depth and, even in shallow water, is complicated by epiphytic algae and sediment coverage of leaf surfaces.

  20. 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.

  1. 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

  2. Estimating the relationship between urban 3D morphology and land surface temperature using airborne LiDAR and Landsat-8 Thermal Infrared Sensor data

    NASA Astrophysics Data System (ADS)

    Lee, J. H.

    2015-12-01

    Urban forests are known for mitigating the urban heat island effect and heat-related health issues by reducing air and surface temperature. Beyond the amount of the canopy area, however, little is known what kind of spatial patterns and structures of urban forests best contributes to reducing temperatures and mitigating the urban heat effects. Previous studies attempted to find the relationship between the land surface temperature and various indicators of vegetation abundance using remote sensed data but the majority of those studies relied on two dimensional area based metrics, such as tree canopy cover, impervious surface area, and Normalized Differential Vegetation Index, etc. This study investigates the relationship between the three-dimensional spatial structure of urban forests and urban surface temperature focusing on vertical variance. We use a Landsat-8 Thermal Infrared Sensor image (acquired on July 24, 2014) to estimate the land surface temperature of the City of Sacramento, CA. We extract the height and volume of urban features (both vegetation and non-vegetation) using airborne LiDAR (Light Detection and Ranging) and high spatial resolution aerial imagery. Using regression analysis, we apply empirical approach to find the relationship between the land surface temperature and different sets of variables, which describe spatial patterns and structures of various urban features including trees. Our analysis demonstrates that incorporating vertical variance parameters improve the accuracy of the model. The results of the study suggest urban tree planting is an effective and viable solution to mitigate urban heat by increasing the variance of urban surface as well as evaporative cooling effect.

  3. 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.

  4. 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

  5. Advances in Unmixing of Hyperspectral Remote Sensing Imagery

    NASA Astrophysics Data System (ADS)

    Burazerovic, Dzevdet

    Remote sensing technology has advanced tremendously in recent decades. An important driver for this development has been the offering of wide spatial and temporal coverage by space- and airborne platforms, as well as the ever-improving capability of their sensors to record images with high spatial and spectral resolution. A modality that produces a bulk of data for remote sensing is hyperspectral imaging. This modality records the reflected solar radiation in contiguous and often numerous spectral bands, thereby extending the standard photography by enabling to treat each pixel individually as a spectrum discernible for each class of materials. One limitation of such imaging, where the spatial and spectral resolutions are inherently traded against each other, is the occurrence of mixed pixels and spectral mixing. The unraveling of spectral mixtures has been widely studied as spectral unmixing, where two main aspects are of interest: the estimation of the constituent spectra, and of their fractions or abundances, in the mixture. The work described in the thesis regards spectral unmixing from two objectives: advancement of methodology and introduction of unmixing in new applications. The first part, specifically, is concerned with the development of data-driven methods for spectral unmixing that can mitigate the dependency on physical parameters and models, and reduce high computational complexity due to the typical use of optimization techniques. A concrete realization consists of several algorithms that reformulate the known geometrical framework of spectral unmixing by introducing linear and nonlinear distance-based and analytical formulations. The second part introduces or elaborates spectral unmixing for detection of the atmospheric adjacency-effect and the estimation of quality of inland and coastal waters. The presented unmixing-based approaches in this context have been validated through theoretical and empirical comparison using available datasets and

  6. 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

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

    NASA Astrophysics Data System (ADS)

    Hook, S. J.; Hulley, G. C.; Duren, R. M.; Guillevic, P.; Aubrey, A. D.; Johnson, W. R.

    2014-12-01

    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.

  8. Built-in hyperspectral camera for smartphone in visible, near-infrared and middle-infrared lights region (second report): sensitivity improvement of Fourier-spectroscopic imaging to detect diffuse reflection lights from internal human tissues for healthcare sensors

    NASA Astrophysics Data System (ADS)

    Kawashima, Natsumi; Hosono, Satsuki; Ishimaru, Ichiro

    2016-05-01

    We proposed the snapshot-type Fourier spectroscopic imaging for smartphone that was mentioned in 1st. report in this conference. For spectroscopic components analysis, such as non-invasive blood glucose sensors, the diffuse reflection lights from internal human skins are very weak for conventional hyperspectral cameras, such as AOTF (Acousto-Optic Tunable Filter) type. Furthermore, it is well known that the spectral absorption of mid-infrared lights or Raman spectroscopy especially in long wavelength region is effective to distinguish specific biomedical components quantitatively, such as glucose concentration. But the main issue was that photon energies of middle infrared lights and light intensities of Raman scattering are extremely weak. For improving sensitivity of our spectroscopic imager, the wide-field-stop & beam-expansion method was proposed. Our line spectroscopic imager introduced a single slit for field stop on the conjugate objective plane. Obviously to increase detected light intensities, the wider slit width of the field stop makes light intensities higher, regardless of deterioration of spatial resolutions. Because our method is based on wavefront-division interferometry, it becomes problems that the wider width of single slit makes the diffraction angle narrower. This means that the narrower diameter of collimated objective beams deteriorates visibilities of interferograms. By installing the relative inclined phaseshifter onto optical Fourier transform plane of infinity corrected optical systems, the collimated half flux of objective beams derived from single-bright points on objective surface penetrate through the wedge prism and the cuboid glass respectively. These two beams interfere each other and form the infererogram as spatial fringe patterns. Thus, we installed concave-cylindrical lens between the wider slit and objective lens as a beam expander. We successfully obtained the spectroscopic characters of hemoglobin from reflected lights from

  9. 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.

  10. Hyperspectral Anomaly Detection in Urban Scenarios

    NASA Astrophysics Data System (ADS)

    Rejas Ayuga, J. G.; Martínez Marín, R.; Marchamalo Sacristán, M.; Bonatti, J.; Ojeda, J. C.

    2016-06-01

    We have studied the spectral features of reflectance and emissivity in the pattern recognition of urban materials in several single hyperspectral scenes through a comparative analysis of anomaly detection methods and their relationship with city surfaces with the aim to improve information extraction processes. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of AHS sensor and HyMAP and MASTER of two cities, Alcalá de Henares (Spain) and San José (Costa Rica) respectively, have been used. In this research it is assumed no prior knowledge of the targets, thus, the pixels are automatically separated according to their spectral information, significantly differentiated with respect to a background, either globally for the full scene, or locally by image segmentation. Several experiments on urban scenarios and semi-urban have been designed, analyzing the behaviour of the standard RX anomaly detector and different methods based on subspace, image projection and segmentation-based anomaly detection methods. A new technique for anomaly detection in hyperspectral data called DATB (Detector of Anomalies from Thermal Background) based on dimensionality reduction by projecting targets with unknown spectral signatures to a background calculated from thermal spectrum wavelengths is presented. First results and their consequences in non-supervised classification and extraction information processes are discussed.

  11. Benthic habitat mapping using hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

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

    2006-09-01

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

  12. 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.

  13. 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.

  14. Support technologies involved in the development and implementation of radiometric systems for sensor calibration, characterization, and HWIL testing at AEDC

    NASA Astrophysics Data System (ADS)

    Lowry, H. S.; Breeden, M. F.; Crider, D. H.; Steely, S. L.; Nicholson, R. A.; Labello, J. M.

    2009-05-01

    The characterization, calibration, and mission simulation testing of space-based, interceptor, and air-borne sensors require a continual involvement in the development and evaluation of radiometric projection technologies. Activities at Arnold Engineering Development Center (AEDC) include Hardware in the Loop (HWIL) testing with high-fidelity complex scene-projection technologies as well as improvements in the radiometric source-calibration systems. These technologies are integrated into a low cryo-vacuum (~20 K) environment. The latest scene simulation and HWIL projection technologies are being investigated that can produce desired target temperatures and target-to-sensor ranges such that sensor mission performance can be evaluated. These technologies include multiple-band source subsystems and special spectral-tailoring methods, as well as comprehensive analysis and optical properties measurements of the components involved. Emphasis areas include the development of methodologies to test wide field of view (WFOV), polarimetric, and multi/hyperspectral radiometric imaging systems.

  15. 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.

  16. Hyperspectral Image Turbulence Measurements of the Atmosphere

    NASA Technical Reports Server (NTRS)

    Lane, Sarah E.; West, Leanne L.; Gimmestad, Gary G.; Kireev, Stanislav; Smith, William L., Sr.; Burdette, Edward M.; Daniels, Taumi; Cornman, Larry

    2012-01-01

    A Forward Looking Interferometer (FLI) sensor has the potential to be used as a means of detecting aviation hazards in flight. One of these hazards is mountain wave turbulence. The results from a data acquisition activity at the University of Colorado s Mountain Research Station will be presented here. Hyperspectral datacubes from a Telops Hyper-Cam are being studied to determine if evidence of a turbulent event can be identified in the data. These data are then being compared with D&P TurboFT data, which are collected at a much higher time resolution and broader spectrum.

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

    NASA Technical Reports Server (NTRS)

    Tarabalka, Yuliya; Tilton, James C.

    2011-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  19. 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.

  20. Sensitivity in forward modeled hyperspectral reflectance due to phytoplankton groups

    NASA Astrophysics Data System (ADS)

    Manzo, Ciro; Bassani, Cristiana; Pinardi, Monica; Giardino, Claudia; Bresciani, Mariano

    2016-04-01

    based on the decomposition of the output reflectance variance in partial variances of the output due to each functional group. This approach considers the sensitivity analysis of the model to each variable on its own and the corresponding interaction with the other variables, allowing identifying the single variability as well as the spectral interaction index. The analysis recognized three spectral ranges with specific level of interactions between the inputs. The first part of the spectrum up to 500 nm had average level of 10% of interaction; the second up to 600nm showed values of 5% with a peak around 580nm; the third showed an increasing interaction level until 15% near 715nm. The results presented in this study provide information relating the sensitivity of hyperspectral water reflectance as observable with band setting of the latest generation space- and air-borne sensors depending on different phytoplankton groups. In particular PRISMA was the best in the spectral sensitivity definition in the first part of the spectrum, while APEX in the second and third domain. The Sentinel 3 showed lower performances although in the third domain it was able to identify some spectral features. Results showed the Chlorophyta had high main effect at 440 nm and 480nm; sensitivity indices of phycoerythrin showed peaks at 550-580nm the range and near 680nm; phycocyanin showed high influence at 620-640nm. The research activity is part of the EU FP7 INFORM (Grant No. 606865, http://www.copernicus-inform.eu/).

  1. 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.

  2. 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.

  3. 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

  4. Comparison of Water Vapor Measurements by Airborne Sun Photometer and Near-Coincident in Situ and Satellite Sensors during INTEX/ITCT 2004

    NASA Technical Reports Server (NTRS)

    Livingston, J.; Schmid, B.; Redemann, J.; Russell, P. B.; Ramirez, S. A.; Eilers, J.; Gore, W.; Howard, S.; Pommier, J.; Fetzer, E. J.; Seeman, S. W.; Borbas, E.; Wolfe, D. E.; Thompson, A. M.

    2007-01-01

    We have retrieved columnar water vapor (CWV) from measurements acquired by the 14-channel NASA Ames Airborne Tracking Sun photometer (AATS-14) during 19 Jetstream 31 (J31) flights over the Gulf of Maine in summer 2004 in support of the Intercontinental Chemical Transport Experiment (INTEX)/Intercontinental Transport and Chemical Transformation (ITCT) experiments. In this paper we compare AATS-14 water vapor retrievals during aircraft vertical profiles with measurements by an onboard Vaisala HMP243 humidity sensor and by ship radiosondes and with water vapor profiles retrieved from AIRS measurements during eight Aqua overpasses. We also compare AATS CWV and MODIS infrared CWV retrievals during five Aqua and five Terra overpasses. For 35 J31 vertical profiles, mean (bias) and RMS AATS-minus-Vaisala layer-integrated water vapor (LWV) differences are -7.1 percent and 8.8 percent, respectively. For 22 aircraft profiles within 1 hour and 130 km of radiosonde soundings, AATS-minus-sonde bias and RMS LWV differences are -5.4 percent and 10.7 percent, respectively, and corresponding J31 Vaisala-minus-sonde differences are 2.3 percent and 8.4 percent, respectively. AIRS LWV retrievals within 80 lan of J31 profiles yield lower bias and RMS differences compared to AATS or Vaisala retrievals than do AIRS retrievals within 150 km of the J31. In particular, for AIRS-minus-AATS LWV differences, the bias decreases from 8.8 percent to 5.8 percent, and the RMS difference decreases from 2 1.5 percent to 16.4 percent. Comparison of vertically resolved AIRS water vapor retrievals (LWVA) to AATS values in fixed pressure layers yields biases of -2 percent to +6 percent and RMS differences of -20 percent below 700 hPa. Variability and magnitude of these differences increase significantly above 700 hPa. MODIS IR retrievals of CWV in 205 grid cells (5 x 5 km at nadir) are biased wet by 10.4 percent compared to AATS over-ocean near-surface retrievals. The MODIS-Aqua subset (79 grid cells

  5. Comparison of Water Vapor Measurements by Airborne Sun photometer and Near-Coincident In Situ and Satellite Sensors during INTEX-ITCT 2004

    SciTech Connect

    Livingston, J.; Schmid, Beat; Redemann, Jens; Russell, P. B.; Ramirez, Samuel; Eilers, J.; Gore, W.; Howard, Samuel; Pommier, J.; Fetzer, E. J.; Seemann, S. W.; Borbas, E.; Wolfe, Daniel; Thompson, Anne M.

    2007-06-06

    We have retrieved columnar water vapor (CWV) from measurements acquired by the 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) during 19 Jetstream 31 (J31) flights over the Gulf of Maine in summer 2004. In this paper we compare AATS-14 water vapor retrievals during aircraft vertical profiles with measurements by an onboard Vaisala HMP243 humidity sensor and by ship radiosondes, and with water vapor profiles retrieved from AIRS measurements during 8 Aqua overpasses. We also compare AATS CWV and MODIS infrared CWV retrievals during 5 Aqua and 5 Terra overpasses. For 35 J31 vertical profiles mean (bias) and rms AATS-minus-Vaisala layer-integrated water vapor (LWV) differences are -7.1% and 8.8%, respectively. For 22 aircraft profiles within 1 h and 130 km of radiosonde soundings, AATS-minus-sonde bias and rms LWV differences are -5.4% and 8.8%, respectively, and corresponding J31 Vaisala-minus-sonde differences are 2.3% and 8.4%, respectively. AIRS LWV retrievals within 80 km of J31 profiles yield lower bias and rms differences compared to AATS or Vaisala retrievals than do AIRS retrievals within 150 km of the J31. In particular, for AIRS-minus-AATS LWV differences, the bias decreases from 8.8% to 5.8%, and the rms difference decreases from 21.5% to 16.4%. Comparison of vertically resolved AIRS water vapor retrievals (LWVA) to AATS values in fixed pressure layers yields biases of -2% to +6% and rms differences of ~20% below 700 hPa. Variability and magnitude of these differences increase significantly above 700 hPa. MODIS IR retrievals of CWV in 205 grid cells (5 x 5-km at nadir) are biased wet by 10.4% compared to AATS over-ocean near surface retrievals. The MODIS Aqua subset (79 grid cells) exhibits a wet bias of 5.1%, and the MODIS-Terra subset (126 grid cells) yields a wet bias of 13.2%.

  6. 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

  7. 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.

  8. Analysis of Unmanned Aerial Vehicle (UAV) hyperspectral remote sensing monitoring key technology in coastal wetland

    NASA Astrophysics Data System (ADS)

    Ma, Yi; Zhang, Jie; Zhang, Jingyu

    2016-01-01

    The coastal wetland, a transitional zone between terrestrial ecosystems and marine ecosystems, is the type of great value to ecosystem services. For the recent 3 decades, area of the coastal wetland is decreasing and the ecological function is gradually degraded with the rapid development of economy, which restricts the sustainable development of economy and society in the coastal areas of China in turn. It is a major demand of the national reality to carry out the monitoring of coastal wetlands, to master the distribution and dynamic change. UAV, namely unmanned aerial vehicle, is a new platform for remote sensing. Compared with the traditional satellite and manned aerial remote sensing, it has the advantage of flexible implementation, no cloud cover, strong initiative and low cost. Image-spectrum merging is one character of high spectral remote sensing. At the same time of imaging, the spectral curve of each pixel is obtained, which is suitable for quantitative remote sensing, fine classification and target detection. Aimed at the frontier and hotspot of remote sensing monitoring technology, and faced the demand of the coastal wetland monitoring, this paper used UAV and the new remote sensor of high spectral imaging instrument to carry out the analysis of the key technologies of monitoring coastal wetlands by UAV on the basis of the current situation in overseas and domestic and the analysis of developing trend. According to the characteristic of airborne hyperspectral data on UAV, that is "three high and one many", the key technology research that should develop are promoted as follows: 1) the atmosphere correction of the UAV hyperspectral in coastal wetlands under the circumstance of complex underlying surface and variable geometry, 2) the best observation scale and scale transformation method of the UAV platform while monitoring the coastal wetland features, 3) the classification and detection method of typical features with high precision from multi scale

  9. ACTIVE-EYES: an adaptive pixel-by-pixel image-segmentation sensor architecture for high-dynamic-range hyperspectral imaging.

    PubMed

    Christensen, Marc P; Euliss, Gary W; McFadden, Michael J; Coyle, Kevin M; Milojkovic, Predrag; Haney, Michael W; van der Gracht, Joeseph; Athale, Ravindra A

    2002-10-10

    The ACTIVE-EYES (adaptive control for thermal imagers via electro-optic elements to yield an enhanced sensor) architecture, an adaptive image-segmentation and processing architecture, based on digital micromirror (DMD) array technology, is described. The concept provides efficient front-end processing of multispectral image data by adaptively segmenting and routing portions of the scene data concurrently to an imager and a spectrometer. The goal is to provide a large reduction in the amount of data required to be sensed in a multispectral imager by means of preprocessing the data to extract the most useful spatial and spectral information during detection. The DMD array provides the flexibility to perform a wide range of spatial and spectral analyses on the scene data. The spatial and spectral processing for different portions of the input scene can be tailored in real time to achieve a variety of preprocessing functions. Since the detected intensity of individual pixels may be controlled, the spatial image can be analyzed with gain varied on a pixel-by-pixel basis to enhance dynamic range. Coarse or fine spectral resolution can be achieved in the spectrometer by use of dynamically controllable or addressable dispersion elements. An experimental prototype, which demonstrated the segmentation between an imager and a grating spectrometer, was demonstrated and shown to achieve programmable pixelated intensity control. An information theoretic analysis of the dynamic-range control aspect was conducted to predict the performance enhancements that might be achieved with this architecture. The results indicate that, with a properly configured algorithm, the concept achieves the greatest relative information recovery from a detected image when the scene is made up of a relatively large area of moderate-dynamic-range pixels and a relatively smaller area of strong pixels that would tend to saturate a conventional sensor. PMID:12389978

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. 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

  16. Use of waveform lidar and hyperspectral sensors to assess selected spatial and structural patterns associated with recent and repeat disturbance and the abundance of sugar maple (Acer saccharum Marsh.) in a temperate mixed hardwood and conifer forest

    USGS Publications Warehouse

    Anderson, J.E.; Ducey, M.J.; Fast, A.; Martin, M.E.; Lepine, L.; Smith, M.-L.; Lee, T.D.; Dubayah, R.O.; Hofton, M.A.; Hyde, P.; Peterson, B.E.; Blair, J.B.

    2011-01-01

    Waveform lidar imagery was acquired on September 26, 1999 over the Bartlett Experimental Forest (BEF) in New Hampshire (USA) using NASA's Laser Vegetation Imaging Sensor (LVIS). This flight occurred 20 months after an ice storm damaged millions of hectares of forestland in northeastern North America. Lidar measurements of the amplitude and intensity of ground energy returns appeared to readily detect areas of moderate to severe ice storm damage associated with the worst damage. Southern through eastern aspects on side slopes were particularly susceptible to higher levels of damage, in large part overlapping tracts of forest that had suffered the highest levels of wind damage from the 1938 hurricane and containing the highest levels of sugar maple basal area and biomass. The levels of sugar maple abundance were determined through analysis of the 1997 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) high resolution spectral imagery and inventory of USFS Northern Research Station field plots. We found a relationship between field measurements of stem volume losses and the LVIS metric of mean canopy height (r2 = 0.66; root mean square errors = 5.7 m3/ha, p < 0.0001) in areas that had been subjected to moderate-to-severe ice storm damage, accurately documenting the short-term outcome of a single disturbance event. ?? 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).

  17. Use of waveform lidar and hyperspectral sensors to assess selected spatial and structural patterns associated with recent and repeat disturbance and the abundance of sugar maple (Acer saccharum Marsh.) in a temperate mixed hardwood and conifer forest

    NASA Astrophysics Data System (ADS)

    Anderson, Jeanne E.; Ducey, Mark J.; Fast, Andrew; Martin, Mary E.; Lepine, Lucie; Smith, Marie-Louise; Lee, Thomas D.; Dubayah, Ralph O.; Hofton, Michelle A.; Hyde, Peter; Peterson, Birgit E.; Blair, J. Bryan

    2011-01-01

    Waveform lidar imagery was acquired on September 26, 1999 over the Bartlett Experimental Forest (BEF) in New Hampshire (USA) using NASA's Laser Vegetation Imaging Sensor (LVIS). This flight occurred 20 months after an ice storm damaged millions of hectares of forestland in northeastern North America. Lidar measurements of the amplitude and intensity of ground energy returns appeared to readily detect areas of moderate to severe ice storm damage associated with the worst damage. Southern through eastern aspects on side slopes were particularly susceptible to higher levels of damage, in large part overlapping tracts of forest that had suffered the highest levels of wind damage from the 1938 hurricane and containing the highest levels of sugar maple basal area and biomass. The levels of sugar maple abundance were determined through analysis of the 1997 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) high resolution spectral imagery and inventory of USFS Northern Research Station field plots. We found a relationship between field measurements of stem volume losses and the LVIS metric of mean canopy height (r2 = 0.66; root mean square errors = 5.7 m3/ha, p < 0.0001) in areas that had been subjected to moderate-to-severe ice storm damage, accurately documenting the short-term outcome of a single disturbance event.

  18. Atmospheric Correction Algorithm for Hyperspectral Imagery

    SciTech Connect

    R. J. Pollina

    1999-09-01

    In December 1997, the US Department of Energy (DOE) established a Center of Excellence (Hyperspectral-Multispectral Algorithm Research Center, HyMARC) for promoting the research and development of algorithms to exploit spectral imagery. This center is located at the DOE Remote Sensing Laboratory in Las Vegas, Nevada, and is operated for the DOE by Bechtel Nevada. This paper presents the results to date of a research project begun at the center during 1998 to investigate the correction of hyperspectral data for atmospheric aerosols. Results of a project conducted by the Rochester Institute of Technology to define, implement, and test procedures for absolute calibration and correction of hyperspectral data to absolute units of high spectral resolution imagery will be presented. Hybrid techniques for atmospheric correction using image or spectral scene data coupled through radiative propagation models will be specifically addressed. Results of this effort to analyze HYDICE sensor data will be included. Preliminary results based on studying the performance of standard routines, such as Atmospheric Pre-corrected Differential Absorption and Nonlinear Least Squares Spectral Fit, in retrieving reflectance spectra show overall reflectance retrieval errors of approximately one to two reflectance units in the 0.4- to 2.5-micron-wavelength region (outside of the absorption features). These results are based on HYDICE sensor data collected from the Southern Great Plains Atmospheric Radiation Measurement site during overflights conducted in July of 1997. Results of an upgrade made in the model-based atmospheric correction techniques, which take advantage of updates made to the moderate resolution atmospheric transmittance model (MODTRAN 4.0) software, will also be presented. Data will be shown to demonstrate how the reflectance retrieval in the shorter wavelengths of the blue-green region will be improved because of enhanced modeling of multiple scattering effects.

  19. 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.

  20. Estimating Biochemical Parameters of Tea (camellia Sinensis (L.)) Using Hyperspectral Techniques

    NASA Astrophysics Data System (ADS)

    Bian, M.; Skidmore, A. K.; Schlerf, M.; Liu, Y.; Wang, T.

    2012-07-01

    Tea (Camellia Sinensis (L.)) is an important economic crop and the market price of tea depends largely on its quality. This research aims to explore the potential of hyperspectral remote sensing on predicting the concentration of biochemical components, namely total tea