Science.gov

Sample records for airborne hyperspectral sensor

  1. 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.

  2. Diffused Matrix Format: a new storage and processing format for airborne hyperspectral sensor images.

    PubMed

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

    2010-01-01

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

  3. Detecting coral reef substrate types by airborne and spaceborne hyperspectral sensors

    NASA Astrophysics Data System (ADS)

    Kutser, Tiit; Dekker, Arnold G.; Skirving, William

    2002-01-01

    Traditional approaches to remote sensing of coral reefs have been highly empirical, relying on classification of remote sensing images. We have chosen a physics based approach - the collection of reflectance spectra of different substrates and the determination of the inherent optical properties of the water column. This information, together with radiative transfer models of water and atmosphere as well as technical characteristics of different remote sensing sensors, allows us to estimate what benthic communities are spectrally resolvable with respect to water column depth and the sensor characteristics. A hyperspectral library of more than 140 different coral reefs substrates (living hard and soft corals, dead corals, rubble, sand, algae and sponges) were collected from the Great Barrier Reef. Hydrolight 4.1 model was used to simulate remote sensing reflectances above the water and a MODTRAN3 type in-house atmosphere model was used to simulate radiance at airborne and space borne sensor levels. Most of the spectral variability in reflectance of coral reef benthic communities occurs in the spectral range of 550-680 nm (green to red light). The water itself is a main limiting factor in remote detection of various reef substrates, as water itself is absorbing light strongly in the same part of the spectrum where most of the variability in reflectance spectra of different coral reef benthic substrates occurs. Hyperspectral information allows us to separate different substrates from each other more easily and in deeper waters than broad band sensors.

  4. Airborne hyperspectral imaging in the visible-to-mid wave infrared spectral range by fusing three spectral sensors

    NASA Astrophysics Data System (ADS)

    Jakovels, Dainis; Filipovs, Jevgenijs; Erinš, Gatis; Taskovs, Juris

    2014-10-01

    Airborne hyperspectral imaging is widely used for remote sensing of environment. The choice of spectral region usually depends on the availability and cost of the sensor. Visible-to-near infrared (400-1100 nm) spectral range corresponds to spectral sensitivity of relatively cheap Si detectors therefore it is the most commonly used. The implementation of shortwave infrared (1100-3000 nm) requires more expensive solutions, but can provide valuable information about the composition of the substance. Mid wave infrared (3000-8000 nm) is rarely used for civilian applications, but it provides information on the thermal emission of materials. The fusion of different sensors allows spectral analysis of a wider spectral range combining and improving already existing algorithms for the analysis of chemical content and classification. Here we introduce our Airborne Surveillance and Environmental Monitoring System (ARSENAL) that was developed by fusing seven sensors. The first test results from the fusion of three hyperspectral imaging sensors in the visible-to-mid wave infrared (365-5000 nm) are demonstrated. Principal component analysis (PCA) is applied to test correlation between principal components (PCs) and common vegetation indices.

  5. [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.

  6. Airborne hyperspectral sensor radiometric self-calibration using near-infrared properties of deep water and vegetation

    NASA Astrophysics Data System (ADS)

    Barbieux, Kévin; Nouchi, Vincent; Merminod, Bertrand

    2016-10-01

    Retrieving the water-leaving reflectance from airborne hyperspectral data implies to deal with three steps. Firstly, the radiance recorded by an airborne sensor comes from several sources: the real radiance of the object, the atmospheric scattering, sky and sun glint and the dark current of the sensor. Secondly, the dispersive element inside the sensor (usually a diffraction grating or a prism) could move during the flight, thus shifting the observed spectra on the wavelengths axis. Thirdly, to compute the reflectance, it is necessary to estimate, for each band, what value of irradiance corresponds to a 100% reflectance. We present here our calibration method, relying on the absorption features of the atmosphere and the near-infrared properties of common materials. By choosing proper flight height and flight lines angle, we can ignore atmospheric and sun glint contributions. Autocorrelation plots allow to identify and reduce the noise in our signals. Then, we compute a signal that represents the high frequencies of the spectrum, to localize the atmospheric absorption peaks (mainly the dioxygen peak around 760 nm). Matching these peaks removes the shift induced by the moving dispersive element. Finally, we use the signal collected over a Lambertian, unit-reflectance surface to estimate the ratio of the system's transmittances to its near-infrared transmittance. This transmittance is computed assuming an average 50% reflectance of the vegetation and nearly 0% for water in the near-infrared. Results show great correlation between the output spectra and ground measurements from a TriOS Ramses and the water-insight WISP-3.

  7. Airborne Hyperspectral Remote Sensing

    DTIC Science & Technology

    2016-06-07

    conducted studies of the sediments, seagrass and corals . The objective is to correlate the hyperspectral imagery with the detailed in-situ measurements...seagrass and coral reefs (Mazel, 1998). In addition to the basic science there is a directed effort in remote sensing for seafloor imaging and...area includes different bottom types – coral , sand, seagrass – sometimes within the same local area, at a variety of depths. Most of the region is quite

  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. 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. PMID:27873868

  11. Advanced Airborne Hyperspectral Imaging System (AAHIS)

    NASA Astrophysics Data System (ADS)

    Topping, Miles Q.; Pfeiffer, Joel E.; Sparks, Andrew W.; Jim, Kevin T. C.; Yoon, Dugan

    2002-11-01

    The design, operation, and performance of the fourth generation of Science and Technology International's Advanced Airborne Hyperspectral Imaging Sensors (AAHIS) are described. These imaging spectrometers have a variable bandwidth ranging from 390-840 nm. A three-axis image stabilization provides spatially and spectrally coherent imagery by damping most of the airborne platform's random motion. A wide 40-degree field of view coupled with sub-pixel detection allows for a large area coverage rate. A software controlled variable aperture, spectral shaping filters, and high quantum efficiency, back-illuminated CCD's contribute to the excellent sensitivity of the sensors. AAHIS sensors have been operated on a variety of fixed and rotary wing platforms, achieving ground-sampling distances ranging from 6.5 cm to 2 m. While these sensors have been primarily designed for use over littoral zones, they are able to operate over both land and water. AAHIS has been used for detecting and locating submarines, mines, tanks, divers, camouflage and disturbed earth. Civilian applications include search and rescue on land and at sea, agricultural analysis, environmental time-series, coral reef assessment, effluent plume detection, coastal mapping, damage assessment, and seasonal whale population monitoring

  12. 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.

  13. Mapping Waterhyacinth Infestations Using Airborne Hyperspectral Imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. The enhanced MODIS airborne simulator hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Guerin, Daniel C.; Fisher, John; Graham, Edward R.

    2011-06-01

    The EMAS-HS or Enhanced MODIS Airborne Simulator is an upgrade to the solar reflected and thermal infrared channels of NASA's MODIS Airborne Simulator (MAS). In the solar reflected bands, the MAS scanner functionality will be augmented with the addition of this separate pushbroom hyperspectral instrument. As well as increasing the spectral resolution of MAS beyond 10 nm, this spectrometer is designed to maintain a stable calibration that can be transferred to the existing MAS sensor. The design emphasizes environmental control and on-board radiometric stability monitoring. The system is designed for high-altitude missions on the ER-2 and the Global Hawk platforms. System trades optimize performance in MODIS spectral bands that support land, cloud, aerosol, and atmospheric water studies. The primary science mission driving the development is high altitude cloud imaging, with secondary missions possible for ocean color. The sensor uses two Offner spectrometers to cover the 380-2400 nm spectral range. It features an all-reflective telescope with a 50° full field-of-view. A dichroic cold mirror will split the image from the telescope, with longer radiation transmitted to the SWIR spectrometer. The VNIR spectrometer uses a TE-cooled Si CCD detector that samples the spectrum at 2.5 nm intervals, while the SWIR spectrometer uses a Stirling-cooled hybrid HgCdTe detector to sample the spectrum at 10 nm per band. Both spectrometers will feature 1.05 mRad instantaneous fields-of-view registered to the MAS scanner IFOV's.

  15. 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.

  16. 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.

  17. Verification of the calibration technique of airborne hyperspectral raw data to reflectance based on sky light reference data

    NASA Astrophysics Data System (ADS)

    Suhama, T.; Rikimaru, A.; Takahashi, K.; Takemine, S.

    Airborne hyperspectral sensor is increasingly being used for the precision agriculture and for the monitoring our environment In general data obtained by airborne hyperspectral sensor are affected by atmospheric conditions and solar illumination geometry Therefore airborne hyperspectral sensor data are commonly expressed as relative radiance value For measuring and monitoring ground surface changes through time it is important to calibrate hyperspectral sensor data to amount of reflectance A number of calibration techniques have been developed ranging from empirical approaches to analytical radiative transfer approaches These methods require a priori knowledge such as field reflectance observations or atmospheric conditions Several airborne hyperspectral sensor systems which are used for commercial purpose include a fiber optic probe on the aircraft roof A fiber optic probe is able to monitor sky light reference data to ratio to hyperspectral raw data This is a simple and practical calibration technique However there is a problem that small inaccuracies in sky right reference data calibrations may lead to unacceptable errors in calculated apparent reflectance In this paper simple calibration technique based on sky light reference data was discussed The resultant reflectance estimates are compared with field reflectance observations of flat and homogeneous ground target and illustrate that proposed calibration technique is possible to derive reasonable reflectance from airborne hyperspectral raw data

  18. Regional lithology mapping using airborne hyperspectral data

    NASA Astrophysics Data System (ADS)

    Qin, Kai; Chen, Jianping; Zhao, Yingjun

    2015-04-01

    This paper proposed a new procedure for rock identifiction and mapping using airborne hyperspectral CASI/SASI data (wavelength: 380-2450 nm) for the Nanbaishiling in Liuyuan area, Gansu Province, NW China. Rocks in the study area include granite, diorite, marble, basalt and quartzite. In situ and laboratory reflectance spectra (400 to 2500 nm) show Al-OH absorption of muscovite, kaolinite, and illite in granite, granodiorite and quartz diorite, and Fe-OH, Mg-OH absorptions of biotite and chlorite .The absorption near 2.3µm caused by carbonate is most intense in marble reflectance spectra. Ferric-iron absorption is intense in most of the felsic rocks. CASI/SASI data with approximately 2-m spatial resolution were recorded in 149 narrow bands along a 1.2-km-wide swath. Correction of the data to spectral reflectance was performed by reference to in situ measurements of an extensive, alluvial plain. Five major rock types have been identified by using MNF and analysis of in situ and laboratory spectra. The lithoglogic map presented in this study were verified by field investigation, and was compared with previous lithologic map. The result show a reliable classification of lithology using Airborne Hyperspectral data.

  19. 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

  20. Airborne Hyperspectral Imaging of Supraglacial Lakes in Greenland's Ablation Zone

    NASA Astrophysics Data System (ADS)

    Adler, J.; Behar, A. E.; Jacobson, N. T.

    2010-12-01

    In 2010 an airborne instrument was assembled to image supraglacial lakes near the Jakobshavn Isbrae of the Greenland Ice Sheet. The instrument was designed to fly on a helicopter, and consists of a hyperspectral imager, a GPS/inertial measurement unit (GPS/IMU), and a data-logging computer. A series of narrow visible optical channels ~13nm wide, such as found in a hyperspectral imager, are theorized to be useful in determining the depths of supraglacial lakes using techniques based on the Beer-Lambert-Bouguer Law. During June, several supraglacial lakes were selected for study each day, based upon MODIS imagery taken during the previous week. Flying over a given lake, several track lines were flown to image both shallow and deep sections of the lake, imaging the full range of depth for future algorithm development. The telescoping instrument mount was constructed to allow the sensor package to be deployed from a helicopter in-flight, with an unobstructed downward-facing field of view. The GPS/IMU records the pointing orientation, altitude, and geographical coordinates of the imager to the data-logger, in order to allow post-flight geo-referencing of the raw hyperspectral imagery. With this geo-referenced spectrum data, a depth map for a given lake can be calculated through reference to a water absorptivity model. This risk-reduction expedition to fly a helicopter-borne hyperspectral imager over the supraglacial lakes of Greenland was a success. The instrument mount for the imager worked as designed, and no vibration issues were encountered. As a result, we have confidence in the instrument platform's performance during future surveys of Greenland's supraglacial lakes. The hyperspectral imager, data acquisition computer, and geo-referencing services are provided by Resonon, Inc. of Bozeman, MT, and the GPS/IMU is manufactured by Cloudcap Technology of Hood River, OR.

  1. 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.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

    Hegyi, Alex N.; Martini, Joerg

    2015-06-01

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

  4. Sensor fusion for airborne landmine detection

    NASA Astrophysics Data System (ADS)

    Schatten, Miranda A.; Gader, Paul D.; Bolton, Jeremy; Zare, Alina; Mendez-Vasquez, Andres

    2006-05-01

    Sensor fusion has become a vital research area for mine detection because of the countermine community's conclusion that no single sensor is capable of detecting mines at the necessary detection and false alarm rates over a wide variety of operating conditions. The U. S. Army Night Vision and Electronic Sensors Directorate (NVESD) evaluates sensors and algorithms for use in a multi-sensor multi-platform airborne detection modality. A large dataset of hyperspectral and radar imagery exists from the four major data collections performed at U. S. Army temperate and arid testing facilities in Autumn 2002, Spring 2003, Summer 2004, and Summer 2005. There are a number of algorithm developers working on single-sensor algorithms in order to optimize feature and classifier selection for that sensor type. However, a given sensor/algorithm system has an absolute limitation based on the physical phenomena that system is capable of sensing. Therefore, we perform decision-level fusion of the outputs from single-channel algorithms and we choose to combine systems whose information is complementary across operating conditions. That way, the final fused system will be robust to a variety of conditions, which is a critical property of a countermine detection system. In this paper, we present the analysis of fusion algorithms on data from a sensor suite consisting of high frequency radar imagery combined with hyperspectral long-wave infrared sensor imagery. The main type of fusion being considered is Choquet integral fusion. We evaluate performance achieved using the Choquet integral method for sensor fusion versus Boolean and soft "and," "or," mean, or majority voting.

  5. Evaluating Airborne Hyperspectral imagery for mapping waterhyacinth infestations

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  8. 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.

  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. 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.

  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. Fast compression implementation for hyperspectral sensor

    NASA Astrophysics Data System (ADS)

    Hihara, Hiroki; Yoshida, Jun; Ishida, Juro; Takada, Jun; Senda, Yuzo; Suzuki, Makoto; Seki, Taeko; Ichikawa, Satoshi; Ohgi, Nagamitsu

    2010-11-01

    Fast and small foot print lossless image compressors aiming at hyper-spectral sensor for the earth observation satellite have been developed. Since more than one hundred channels are required for hyper-spectral sensors on optical observation satellites, fast compression algorithm with small foot print implementation is essential for reducing encoder size and weight resulting in realizing light-weight and small-size sensor system. The image compression method should have low complexity in order to reduce size and weight of the sensor signal processing unit, power consumption and fabrication cost. Coding efficiency and compression speed enables enlargement of the capacity of signal compression channels, which resulted in reducing signal compression channels onboard by multiplexing sensor signal channels into reduced number of compression channels. The employed method is based on FELICS1, which is hierarchical predictive coding method with resolution scaling. To improve FELICS's performance of image decorrelation and entropy coding, we applied two-dimensional interpolation prediction and adaptive Golomb-Rice coding, which enables small footprint. It supports progressive decompression using resolution scaling, whilst still delivering superior performance as measured by speed and complexity. The small footprint circuitry is embedded into the hyper-spectral sensor data formatter. In consequence, lossless compression function has been added without additional size and weight.

  15. Buried archaeological structures detection using MIVIS hyperspectral airborne data

    NASA Astrophysics Data System (ADS)

    Merola, P.; Allegrini, A.; Guglietta, D.; Sampieri, S.

    2006-08-01

    The identification of buried archaeological structures, using remote sensing technologies (aerophotos or satellite and airborne images) is based on the analysis of surface spectral features changes that overlying underground terrain units, located on the basis of texture variations, humidity and vegetation cover. The study of these anomalies on MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) hyperspectral data is the main goal of a research project that the CNR-IIA has carried on over different archaeological test sites. The major archaeological information were gathered by data analysis in the VIS and NIR spectral region and by use of the apparent thermal inertia image and their different vegetation index.

  16. 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

  17. Interpretation of absorption bands in airborne hyperspectral radiance data.

    PubMed

    Szekielda, Karl H; Bowles, Jeffrey H; Gillis, David B; Miller, W David

    2009-01-01

    It is demonstrated that hyperspectral imagery can be used, without atmospheric correction, to determine the presence of accessory phytoplankton pigments in coastal waters using derivative techniques. However, care must be taken not to confuse other absorptions for those caused by the presence of pigments. Atmospheric correction, usually the first step to making products from hyperspectral data, may not completely remove Fraunhofer lines and atmospheric absorption bands and these absorptions may interfere with identification of phytoplankton accessory pigments. Furthermore, the ability to resolve absorption bands depends on the spectral resolution of the spectrometer, which for a fixed spectral range also determines the number of observed bands. Based on this information, a study was undertaken to determine under what circumstances a hyperspectral sensor may determine the presence of pigments. As part of the study a hyperspectral imager was used to take high spectral resolution data over two different water masses. In order to avoid the problems associated with atmospheric correction this data was analyzed as radiance data without atmospheric correction. Here, the purpose was to identify spectral regions that might be diagnostic for photosynthetic pigments. Two well proven techniques were used to aid in absorption band recognition, the continuum removal of the spectra and the fourth derivative. The findings in this study suggest that interpretation of absorption bands in remote sensing data, whether atmospherically corrected or not, have to be carefully reviewed when they are interpreted in terms of photosynthetic pigments.

  18. Interpretation of Absorption Bands in Airborne Hyperspectral Radiance Data

    PubMed Central

    Szekielda, Karl H.; Bowles, Jeffrey H.; Gillis, David B.; Miller, W. David

    2009-01-01

    It is demonstrated that hyperspectral imagery can be used, without atmospheric correction, to determine the presence of accessory phytoplankton pigments in coastal waters using derivative techniques. However, care must be taken not to confuse other absorptions for those caused by the presence of pigments. Atmospheric correction, usually the first step to making products from hyperspectral data, may not completely remove Fraunhofer lines and atmospheric absorption bands and these absorptions may interfere with identification of phytoplankton accessory pigments. Furthermore, the ability to resolve absorption bands depends on the spectral resolution of the spectrometer, which for a fixed spectral range also determines the number of observed bands. Based on this information, a study was undertaken to determine under what circumstances a hyperspectral sensor may determine the presence of pigments. As part of the study a hyperspectral imager was used to take high spectral resolution data over two different water masses. In order to avoid the problems associated with atmospheric correction this data was analyzed as radiance data without atmospheric correction. Here, the purpose was to identify spectral regions that might be diagnostic for photosynthetic pigments. Two well proven techniques were used to aid in absorption band recognition, the continuum removal of the spectra and the fourth derivative. The findings in this study suggest that interpretation of absorption bands in remote sensing data, whether atmospherically corrected or not, have to be carefully reviewed when they are interpreted in terms of photosynthetic pigments. PMID:22574053

  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. Compressive hyperspectral sensor for LWIR gas detection

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

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

  2. 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...

  3. 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...

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  6. HSI mapping of marine and coastal environments using the advanced airborne hyperspectral imaging system (AAHIS)

    NASA Astrophysics Data System (ADS)

    Holasek, Rick E.; Portigal, Frederick P.; Mooradian, Gregory C.; Voelker, Mark A.; Even, Detlev M.; Fene, Michael W.; Owensby, Pamela D.; Breitwieser, David S.

    1997-08-01

    The advanced airborne hyperspectral imaging system (AAHIS) is an operational, high signal-to-noise ratio, high resolution, integrated hyperspectral imaging spectrometer. The compact, lightweight and portable AAHIS system is normally flown in Piper Aztec aircraft. AAHIS collect 'push- broom' data with 385 spatial channels and 288 simultaneous spectral channels from 433 nm to 832 nm, recording at 12 bits up to 55 frames/second. Typical operation incorporates on-chip pixel binning of four pixels spectrally and two pixels spatially, increasing the signal-to-noise ratio and reducing data rate. When binned, the spectral resolution is 5.5 nm and the instantaneous field-of-view is 1 mrad, resulting in a ground sample distance of 0.5 m from 500 m altitude. The sensor is optimized for littoral region remote sensing for a variety of civilian and defense applications including ecosystem surveying and inventory, detection and monitoring of environmental pollution, infrastructure mapping, and surveillance. Since August 1994, AAHIS has acquired over 120 GB of hyperspectral image data of littoral, urban, desert and tropical scenes. System upgrades include real-time spectral image processing, integrated flight navigation and 3-axis image stabilization. A description of the sensor system, its performance characteristics, and several processed images demonstrating material discrimination are presented. The remote assessment, characterization, and mapping of coral reef health and species identification and floral species at Nu'upia Ponds, are shown and compared to extensive ground truthing in and around Kaneohe Bay, Oahu, Hawaii. SETS emphasizes providing georegistered, GIS-integrated, value- added data products for customers to help them solve real- world problems.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. Classification of urban features using airborne hyperspectral data

    NASA Astrophysics Data System (ADS)

    Ganesh Babu, Bharath

    Accurate mapping and modeling of urban environments are critical for their efficient and successful management. Superior understanding of complex urban environments is made possible by using modern geospatial technologies. This research focuses on thematic classification of urban land use and land cover (LULC) using 248 bands of 2.0 meter resolution hyperspectral data acquired from an airborne imaging spectrometer (AISA+) on 24th July 2006 in and near Terre Haute, Indiana. Three distinct study areas including two commercial classes, two residential classes, and two urban parks/recreational classes were selected for classification and analysis. Four commonly used classification methods -- maximum likelihood (ML), extraction and classification of homogeneous objects (ECHO), spectral angle mapper (SAM), and iterative self organizing data analysis (ISODATA) - were applied to each data set. Accuracy assessment was conducted and overall accuracies were compared between the twenty four resulting thematic maps. With the exception of SAM and ISODATA in a complex commercial area, all methods employed classified the designated urban features with more than 80% accuracy. The thematic classification from ECHO showed the best agreement with ground reference samples. The residential area with relatively homogeneous composition was classified consistently with highest accuracy by all four of the classification methods used. The average accuracy amongst the classifiers was 93.60% for this area. When individually observed, the complex recreational area (Deming Park) was classified with the highest accuracy by ECHO, with an accuracy of 96.80% and 96.10% Kappa. The average accuracy amongst all the classifiers was 92.07%. The commercial area with relatively high complexity was classified with the least accuracy by all classifiers. The lowest accuracy was achieved by SAM at 63.90% with 59.20% Kappa. This was also the lowest accuracy in the entire analysis. This study demonstrates the

  12. 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.

  13. ICARE-HS: atmospheric correction of airborne hyperspectral urban images using 3D information

    NASA Astrophysics Data System (ADS)

    Ceamanos, Xavier; Briottet, Xavier; Roussel, Guillaume; Gilardy, Hugo

    2016-10-01

    The algorithm ICARE-HS (Inversion Code for urban Areas Reflectance Extraction using HyperSpectral imagery) is presented in this paper. ICARE-HS processes airborne hyperspectral images for atmospheric compensation taking into account the strong relief of urban areas. A digital surface model is used to provide the 3D information, which is key to simulating relief-related effects such as shadow casting, multiple reflections between objects and variable illumination depending on local solid angle of view of the sky. Some of these effects are modeled using ray tracing techniques. ICARE-HS is applied to airborne hyperspectral data of the city center of Toulouse, which are also processed by a standard atmospheric correction method for comparison.

  14. 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...

  15. 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.

  16. GRIN-optics-based hyperspectral imaging micro-sensor

    NASA Astrophysics Data System (ADS)

    Zhou, Wei; Leger, James

    2007-09-01

    By utilizing diffractive, refractive and graded-index optics technology, a miniature (1 mm x 1 mm x 2 mm) Computer-Tomography Imaging Spectrometer (CTIS) sensor has been designed with 16 independent optical channels working in a snap-shot mode for hyper-spectral imaging. The designed prototype covers a 400~700 nm wavelength range. One optical channel has been fabricated and characterized. By azimuthally rotating this optical channel along the optical axis and collecting different dispersed images to simulate the full sensor read-out, the full hyperspectral detection scheme has been demonstrated.

  17. 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

  18. 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.

  19. 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

  20. US open-skies follow-on evaluation program, multispectral hyperspectral (MSHS) sensor survey

    SciTech Connect

    Ryan, R.; Del Guidice, P.; Smith, L.; Soel, M.

    1996-10-01

    The Follow-On Sensor Evaluation Program (FOSEP) has evaluated the potential benefits of hyperspectral and multispectral sensor additions to the existing sensor suite on the U.S. Open Skies aircraft and recommends a multispectral sensor for implementation in the Open Skies program. Potential enhancements to the Open Skies missions include environmental monitoring and improved treaty verification capabilities. A previous study indicated the inadequacy of the current U.S. Open Skies aircraft sensor suite, with or without modifications to existing sensors, in the performance of environmental monitoring. The most beneficial modifications identified in this previous report were multispectral modifications of the existing sensor suite. However, even with these modifications significant inadequacies for many environmental and other missions would still remain. That study concluded that enhancement of Open Skies missions could be achieved with the addition of sensors specifically designed for multispectral imagery. In this current study, we examined and compared a wide range of commercially available airborne imaging spectrometers for a host of Open Skies missions which included both environmental and military applications. A set of tables and figures were developed ensuring that the evaluated sensors matched the Open Skies parameters of interest and flight profiles. These tables provide a common basis for comparing commercially available sensor systems for their suitability to Open Skies missions. Several figures of merit were used to compare different sensors including ground sample distance (GSD), number of spectral bands, signal-to-noise ratio and exportability. This methodology was applied to potential Open Skies multispectral and hyperspectral sensors. Rankings were developed using these of figures of merit and constraints imposed by the existing and future platforms. 6 refs., 2 figs., 4 tabs.

  1. Application of airborne hyperspectral remote sensing for the retrieval of forest inventory parameters

    NASA Astrophysics Data System (ADS)

    Dmitriev, Yegor V.; Kozoderov, Vladimir V.; Sokolov, Anton A.

    2016-04-01

    Collecting and updating forest inventory data play an important part in the forest management. The data can be obtained directly by using exact enough but low efficient ground based methods as well as from the remote sensing measurements. We present applications of airborne hyperspectral remote sensing for the retrieval of such important inventory parameters as the forest species and age composition. The hyperspectral images of the test region were obtained from the airplane equipped by the produced in Russia light-weight airborne video-spectrometer of visible and near infrared spectral range and high resolution photo-camera on the same gyro-stabilized platform. The quality of the thematic processing depends on many factors such as the atmospheric conditions, characteristics of measuring instruments, corrections and preprocessing methods, etc. An important role plays the construction of the classifier together with methods of the reduction of the feature space. The performance of different spectral classification methods is analyzed for the problem of hyperspectral remote sensing of soil and vegetation. For the reduction of the feature space we used the earlier proposed stable feature selection method. The results of the classification of hyperspectral airborne images by using the Multiclass Support Vector Machine method with Gaussian kernel and the parametric Bayesian classifier based on the Gaussian mixture model and their comparative analysis are demonstrated.

  2. A regression approach to the mapping of bio-physical characteristics of surface sediment using in situ and airborne hyperspectral acquisitions

    NASA Astrophysics Data System (ADS)

    Ibrahim, Elsy; Kim, Wonkook; Crawford, Melba; Monbaliu, Jaak

    2017-02-01

    Remote sensing has been successfully utilized to distinguish and quantify sediment properties in the intertidal environment. Classification approaches of imagery are popular and powerful yet can lead to site- and case-specific results. Such specificity creates challenges for temporal studies. Thus, this paper investigates the use of regression models to quantify sediment properties instead of classifying them. Two regression approaches, namely multiple regression (MR) and support vector regression (SVR), are used in this study for the retrieval of bio-physical variables of intertidal surface sediment of the IJzermonding, a Belgian nature reserve. In the regression analysis, mud content, chlorophyll a concentration, organic matter content, and soil moisture are estimated using radiometric variables of two airborne sensors, namely airborne hyperspectral sensor (AHS) and airborne prism experiment (APEX) and and using field hyperspectral acquisitions by analytical spectral device (ASD). The performance of the two regression approaches is best for the estimation of moisture content. SVR attains the highest accuracy without feature reduction while MR achieves good results when feature reduction is carried out. Sediment property maps are successfully obtained using the models and hyperspectral imagery where SVR used with all bands achieves the best performance. The study also involves the extraction of weights identifying the contribution of each band of the images in the quantification of each sediment property when MR and principal component analysis are used.

  3. A regression approach to the mapping of bio-physical characteristics of surface sediment using in situ and airborne hyperspectral acquisitions

    NASA Astrophysics Data System (ADS)

    Ibrahim, Elsy; Kim, Wonkook; Crawford, Melba; Monbaliu, Jaak

    2017-01-01

    Remote sensing has been successfully utilized to distinguish and quantify sediment properties in the intertidal environment. Classification approaches of imagery are popular and powerful yet can lead to site- and case-specific results. Such specificity creates challenges for temporal studies. Thus, this paper investigates the use of regression models to quantify sediment properties instead of classifying them. Two regression approaches, namely multiple regression (MR) and support vector regression (SVR), are used in this study for the retrieval of bio-physical variables of intertidal surface sediment of the IJzermonding, a Belgian nature reserve. In the regression analysis, mud content, chlorophyll a concentration, organic matter content, and soil moisture are estimated using radiometric variables of two airborne sensors, namely airborne hyperspectral sensor (AHS) and airborne prism experiment (APEX) and and using field hyperspectral acquisitions by analytical spectral device (ASD). The performance of the two regression approaches is best for the estimation of moisture content. SVR attains the highest accuracy without feature reduction while MR achieves good results when feature reduction is carried out. Sediment property maps are successfully obtained using the models and hyperspectral imagery where SVR used with all bands achieves the best performance. The study also involves the extraction of weights identifying the contribution of each band of the images in the quantification of each sediment property when MR and principal component analysis are used.

  4. 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.

  5. 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

  6. 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.

  7. Underwater monitoring experiment using hyperspectral sensor, LiDAR and high resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Yang, Chan-Su; Kim, Sun-Hwa

    2014-10-01

    In general, hyper-spectral sensor, LiDAR and high spatial resolution satellite imagery for underwater monitoring are dependent on water clarity or water transparency that can be measured using a Secchi disk or satellite ocean color data. Optical properties in the sea waters of South Korea are influenced mainly by a strong tide and oceanic currents, diurnal, daily and seasonal variations of water transparency. The satellite-based Secchi depth (ZSD) analysis showed the applicability of hyper-spectral sensor, LiDAR and optical satellite, determined by the location connected with the local distribution of Case 1 and 2 waters. The southeast coastal areas of Jeju Island are selected as test sites for a combined underwater experiment, because those areas represent Case 1 water. Study area is a small port (<15m) in the southeast area of the island and linear underwater target used by sewage pipe is located in this area. Our experiments are as follows: 1. atmospheric and sun-glint correction methods to improve the underwater monitoring ability; 2. intercomparison of water depths obtained from three different sensors. Three sensors used here are the CASI-1500 (Wide-Array Airborne Hyperspectral VNIR Imager (0.38-1.05 microns), the Coastal Zone Mapping and Imaging Lidar (CZMIL) and Korean Multi-purpose Satellite-3 (KOMPSAT-3) with 2.8 meter multi-spectral resolution. The experimental results were affected by water clarity and surface condition, and the bathymetric results of three sensors show some differences caused by sensor-itself, bathymetric algorithm and tide level. It is shown that CASI-1500 was applicable for bathymetry and underwater target detection in this area, but KOMPSAT-3 should be improved for Case 1 water. Although this experiment was designed to compare underwater monitoring ability of LIDAR, CASI-1500, KOMPSAT-3 data, this paper was based on initial results and suggested only results about the bathymetry and underwater target detection.

  8. Image capture: simulation of sensor responses from hyperspectral images.

    PubMed

    Vora, P L; Farrell, J E; Tietz, J D; Brainard, D H

    2001-01-01

    This paper describes the design and performance of an image capture simulator. The general model underlying the simulator assumes that the image capture device contains multiple classes of sensors with different spectral sensitivities and that each sensor responds in a known way to irradiance over most of its operating range. The input to the simulator is a set of narrow-band images of the scene taken with a custom-designed hyperspectral camera system. The parameters for the simulator are the number of sensor classes, the sensor spectral sensitivities, the noise statistics and number of quantization levels for each sensor class, the spatial arrangement of the sensors and the exposure duration. The output of the simulator is the raw image data that would have been acquired by the simulated image capture device. To test the simulator, we acquired images of the same scene both with the hyperspectral camera and with a calibrated Kodak DCS-200 digital color camera. We used the simulator to predict the DCS-200 output from the hyperspectral data. The agreement between simulated and acquired images validated the image capture response model and our simulator implementation. We believe the simulator will provide a useful tool for understanding the effect of varying the design parameters of an image capture device.

  9. 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.

  10. Advanced Airborne Hyperspectral Imaging System (AAHIS): an imaging spectrometer for maritime applications

    NASA Astrophysics Data System (ADS)

    Voelker, Mark A.; Resmini, Ronald G.; Mooradian, Gregory C.; McCord, Thomas B.; Warren, Christopher P.; Fene, Michael W.; Coyle, Christopher C.; Anderson, Richard

    1995-06-01

    The Advanced Airborne Hyperspectral Imaging System (AAHIS) is a compact, lightweight visible and near IR pushbroom hyperspectral imaging spectrometer flown on a Piper Aztec aircraft. AAHIS is optimized for use in shallow water, littoral, and vegetation remote sensing. Data are collected at up to 55 frames/second and may be displayed and analyzed inflight or recorded for post-flight processing. Swath width is 200 meters at a flight altitude of 1 km. Each image pixel contains hyperspectral data simultaneously recorded in up to 288 contiguous spectral channels covering the 432 to 832 nm spectral region. Pixel binning typically yields pixels 1.0 meter square with a spectral channel width of 5.5 nm. Design and performance of the AAHIS is presented, including processed imagery demonstrating feature detection and materials discrimination on land and underwater at depths up to 27 meters.

  11. Forest tree species clssification based on airborne hyper-spectral imagery

    NASA Astrophysics Data System (ADS)

    Dian, Yuanyong; Li, Zengyuan; Pang, Yong

    2013-10-01

    Forest precision classification products were the basic data for surveying of forest resource, updating forest subplot information, logging and design of forest. However, due to the diversity of stand structure, complexity of the forest growth environment, it's difficult to discriminate forest tree species using multi-spectral image. The airborne hyperspectral images can achieve the high spatial and spectral resolution imagery of forest canopy, so it will good for tree species level classification. The aim of this paper was to test the effective of combining spatial and spectral features in airborne hyper-spectral image classification. The CASI hyper spectral image data were acquired from Liangshui natural reserves area. Firstly, we use the MNF (minimum noise fraction) transform method for to reduce the hyperspectral image dimensionality and highlighting variation. And secondly, we use the grey level co-occurrence matrix (GLCM) to extract the texture features of forest tree canopy from the hyper-spectral image, and thirdly we fused the texture and the spectral features of forest canopy to classify the trees species using support vector machine (SVM) with different kernel functions. The results showed that when using the SVM classifier, MNF and texture-based features combined with linear kernel function can achieve the best overall accuracy which was 85.92%. It was also confirm that combine the spatial and spectral information can improve the accuracy of tree species classification.

  12. Airborne Hyperspectral Sensing of Monitoring Harmful Algal Blooms in the Great Lakes Region: System Calibration and Validation

    NASA Technical Reports Server (NTRS)

    Lekki, John; Anderson, Robert; Avouris, Dulcinea; Becker, RIchard; Churnside, James; Cline, Michael; Demers, James; Leshkevich, George; Liou, Larry; Luvall, Jeffrey; Ortiz, Joseph; Royce, Anthony; Ruberg, Steve; Sawtell, Reid; Sayers, Michael; Schiller, Stephen; Shuchman, Robert; Simic, Anita; Stuart, Dack; Sullivan, Glenn; Tavernelli, Paul; Tokars, Roger; Vander Woude, Andrea

    2017-01-01

    Harmful algal blooms (HABs) in Lake Erie have been prominent in recent years. The bloom in 2014 reached a severe level causing the State of Ohio to declare a state of emergency. At that time NASA Glenn Research Center was requested by stakeholders to help monitor the blooms in Lake Erie. Glenn conducted flights twice a week in August and September and assembled and distributed the HAB information to the shoreline water resource managers using its hyperspectral imaging sensor (in development since 2006), the S??3 Viking aircraft, and funding resources from the NASA Headquarters Earth Science Division. Since then, the State of Ohio, National Oceanic and Atmospheric Administration (NOAA), and U.S. Environmental Protection Agency (EPA) have elevated their funding and activities for observing, monitoring, and addressing the root cause of HABs. Also, the communities and stakeholders have persistently requested NASA Glenn??s participation in HAB observation. Abundant field campaigns and sample analyses have been funded by Ohio and NOAA, which provided a great opportunity for NASA to advance science and airborne hyperspectral remote sensing economically. Capitalizing on this opportunity to advance the science of algal blooms and remote sensing, NASA Glenn conducted the Airborne Hyperspectral Observation of harmful algal blooms campaign in 2015 that was, in many respects, twice as large as the 2014 campaign. Focusing mostly on Lake Erie, but also including other small inland lakes and the Ohio River, the campaign was conducted in partnership with a large number of partners specializing in marine science and remote sensing. Airborne hyperspectral observation of HABs holds promise to distinguish potential HABs from nuisance blooms, determine their concentrations, and delineate their movement in an augmented spatial and temporal resolution and under clouds??all of which are excellent complements to satellite observations. Working with collaborators at several Ohio and Michigan

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  14. Hyperspectral Imaging Sensors and the Marine Coastal Zone

    NASA Technical Reports Server (NTRS)

    Richardson, Laurie L.

    2000-01-01

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

  15. 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).

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

    PubMed Central

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

    2014-01-01

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

  17. Biodiversity mapping in a tropical West African forest with airborne hyperspectral data.

    PubMed

    Vaglio Laurin, Gaia; Cheung-Wai Chan, Jonathan; Chen, Qi; Lindsell, Jeremy A; Coomes, David A; Guerriero, Leila; Del Frate, Fabio; 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 m(2) 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 m(2) 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-R(2) = 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.

  18. Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data.

    PubMed

    Dalponte, Michele; Coomes, David A

    2016-10-01

    Forests are a major component of the global carbon cycle, and accurate estimation of forest carbon stocks and fluxes is important in the context of anthropogenic global change. Airborne laser scanning (ALS) data sets are increasingly recognized as outstanding data sources for high-fidelity mapping of carbon stocks at regional scales.We develop a tree-centric approach to carbon mapping, based on identifying individual tree crowns (ITCs) and species from airborne remote sensing data, from which individual tree carbon stocks are calculated. We identify ITCs from the laser scanning point cloud using a region-growing algorithm and identifying species from airborne hyperspectral data by machine learning. For each detected tree, we predict stem diameter from its height and crown-width estimate. From that point on, we use well-established approaches developed for field-based inventories: above-ground biomasses of trees are estimated using published allometries and summed within plots to estimate carbon density.We show this approach is highly reliable: tests in the Italian Alps demonstrated a close relationship between field- and ALS-based estimates of carbon stocks (r(2) = 0·98). Small trees are invisible from the air, and a correction factor is required to accommodate this effect.An advantage of the tree-centric approach over existing area-based methods is that it can produce maps at any scale and is fundamentally based on field-based inventory methods, making it intuitive and transparent. Airborne laser scanning, hyperspectral sensing and computational power are all advancing rapidly, making it increasingly feasible to use ITC approaches for effective mapping of forest carbon density also inside wider carbon mapping programs like REDD++.

  19. Refining the Concept of Combining Hyperspectral and Multi-Angle Sensors for Land Surface Applications

    NASA Astrophysics Data System (ADS)

    Simic, Anita

    Assessment of leaf and canopy chlorophyll content provides information on plant physiological status; it is related to nitrogen content and hence, photosynthesis process, net primary productivity and carbon budget. In this study, a method is developed for the retrieval of total chlorophyll content (Chlorophyll a+b) per unit leaf and per unit ground area based on improved vegetation structural parameters which are derived using multispectral multi-angle remote sensing data. Structural characteristics such as clumping and gaps within a canopy affect its solar radiation absorption and distribution and impact its reflected radiance acquired by a sensor. One of the main challenges for the remote sensing community is to accurately estimate vegetation structural parameters, which inevitably influence the retrieval of leaf chlorophyll content. Multi-angle optical measurements provide a means to characterize the anisotropy of surface reflectance, which has been shown to contain information on vegetation structural characteristics. Hyperspectral optical measurements, on the other hand, provide a fine spectral resolution at the red-edge, a narrow spectral range between the red and near infra-red spectra, which is particularly useful for retrieving chlorophyll content. This study explores a new refined measurement concept of combining multi-angle and hyperspectral remote sensing that employs hyperspectral signals only in the vertical (nadir) direction and multispectral measurements in two additional (off-nadir) directions within two spectral bands, red and near infra-red (NIR). The refinement has been proposed in order to reduce the redundancy of hyperspectral data at more than one angle and to better retrieve the three-dimensional vegetation structural information by choosing the two most useful angles of measurements. To illustrate that hyperspectral data acquired at multiple angles exhibit redundancy, a radiative transfer model was used to generate off-nadir hyperspectral

  20. 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.

  1. Cloud detection using disposable airborne sensors

    NASA Astrophysics Data System (ADS)

    Nicoll, K.; Harrison, R. G.

    2012-04-01

    Measurements from airborne platforms are important for studies of clouds' impact on the radiation balance and on precipitation. A range of small, low cost, disposable sensors has been developed for cloud detection from unmanned balloon or UAS (Unmanned Aerial Systems) platforms (Nicoll and Harrison, 2010). The techniques already deployed include exploiting the associated solar radiation modification, electric charge changes, and optical fluctuations due to cloud droplets. As well as needing to be inexpensive, the sensors are required to be lightweight (mass typically ~ 100g) with low consumption (typical power ~100mW), and have been tested alongside standard meteorological radiosondes, as well as on a small UAS (SUMO - Small Unmanned Meteorological Observer (Reuder et al 2009)). Design criteria for these sensors will be discussed, as well as measurements from the test flights, through a variety of different cloud layers. The advantages of using optical and charge methods of cloud detection over the normal thermodynamic method deployed with conventional radiosondes (capacitative sensing of relative humidity combined with temperature measurements), will also be discussed. Nicoll K.A. and R.G. Harrison. Research Radiosondes, Met. Tech. Int. Nov 2010, 140 (2010). Reuder J., P. Brisset, M. Jonassen, M. Muller, S. Mayer. The Small Unmanned Meteorological Observer SUMO: A new tool for atmospheric boundary layer research Meteorologische Zeitschrift, Vol. 18, No. 2, 141-147 (2009).

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

    NASA Astrophysics Data System (ADS)

    Liu, Lanfa; Buchroithner, Manfred

    2016-04-01

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

  3. 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.

  4. 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.

  5. Methods for gas detection using stationary hyperspectral imaging sensors

    DOEpatents

    Conger, James L [San Ramon, CA; Henderson, John R [Castro Valley, CA

    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.

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  8. 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.

  9. Advances in soil mapping: Mapping quartz content of soil surface using airborne hyperspectral remote sensing in the longwave-infrared region

    NASA Astrophysics Data System (ADS)

    Weksler, Shahar; Notesco, Gila; Ben-Dor, Eyal

    2016-04-01

    Hyperspectral remote sensing in the longwave-infrared (LWIR) spectral region has proven to be a new and efficient tool for mineral mapping (Adar et al. 2013). Minerals which are featureless in the visible, near-infrared and shortwave-infrared regions, e.g., quartz, have a unique fingerprint in the LWIR region (8-12 μm). This spectral region adds to the optical region in which several important minerals can be characterized with significant features (e.g., clay). Accordingly, using airborne hyperspectral remote-sensing data in the LWIR region is an important and practical means of classifying and quantifying minerals. Day and night airborne data, acquired by the AisaOWL sensor over Nitzana National Park in Israel, were used to demonstrate how LWIR region data can be used to map quartz content on the soil surface in a pixel-by-pixel process. The LWIR radiance image is composed of the surface emissivity (and hence the surface's chemical and physical properties), the radiant temperature (according to the Plank equation) and the atmospheric attenuation (which is different during the day and at night). In this work, we show that it is possible to separate surface emissivity, temperature and atmospheric attenuation by using the radiance measured from a vicarious calibration site which was found to be distinctive for the atmospheric contribution. Applying the spectrum of this area as a gain factor to each pixel in the image reduced the atmospheric effects while emphasizing the mineralogical features. Based on this finding and using the same vicarious calibration site used by Notesco et al. (2015), we further studied the possibility of mapping quartz in an area outside the vicarious calibration site. The resulting emissivity image of Nitzana soils (100 km away from the vicarious calibration site) enabled quantifying the quartz in each pixel and mapping its abundance. The day and night images showed a similar quartz distribution, thereby validating the methodology and

  10. 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. ...

  11. 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.

  12. 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

  13. 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.

  14. 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.

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

    PubMed

    Miura, Tomoaki; Huete, Alfredo R

    2009-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  17. Canopy foliar nitrogen retrieved from airborne hyperspectral imagery by correcting for canopy structure effects

    NASA Astrophysics Data System (ADS)

    Wang, Zhihui; Skidmore, Andrew K.; Wang, Tiejun; Darvishzadeh, Roshanak; Heiden, Uta; Heurich, Marco; Latifi, Hooman; Hearne, John

    2017-02-01

    A statistical relationship between canopy mass-based foliar nitrogen concentration (%N) and canopy bidirectional reflectance factor (BRF) has been repeatedly demonstrated. However, the interaction between leaf properties and canopy structure confounds the estimation of foliar nitrogen. The canopy scattering coefficient (the ratio of BRF and the directional area scattering factor, DASF) has recently been suggested for estimating %N as it suppresses the canopy structural effects on BRF. However, estimation of %N using the scattering coefficient has not yet been investigated for longer spectral wavelengths (>855 nm). We retrieved the canopy scattering coefficient for wavelengths between 400 and 2500 nm from airborne hyperspectral imagery, and then applied a continuous wavelet analysis (CWA) to the scattering coefficient in order to estimate %N. Predictions of %N were also made using partial least squares regression (PLSR). We found that %N can be accurately retrieved using CWA (R2 = 0.65, RMSE = 0.33) when four wavelet features are combined, with CWA yielding a more accurate estimation than PLSR (R2 = 0.47, RMSE = 0.41). We also found that the wavelet features most sensitive to %N variation in the visible region relate to chlorophyll absorption, while wavelet features in the shortwave infrared regions relate to protein and dry matter absorption. Our results confirm that %N can be retrieved using the scattering coefficient after correcting for canopy structural effect. With the aid of high-fidelity airborne or upcoming space-borne hyperspectral imagery, large-scale foliar nitrogen maps can be generated to improve the modeling of ecosystem processes as well as ecosystem-climate feedbacks.

  18. 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

  19. 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

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

    PubMed Central

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

    2008-01-01

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

  1. 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.

  2. 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.

  3. Polarimetric sensor systems for airborne ISR

    NASA Astrophysics Data System (ADS)

    Chenault, David; Foster, Joseph; Pezzaniti, Joseph; Harchanko, John; Aycock, Todd; Clark, Alex

    2014-06-01

    Over the last decade, polarimetric imaging technologies have undergone significant advancements that have led to the development of small, low-power polarimetric cameras capable of meeting current airborne ISR mission requirements. In this paper, we describe the design and development of a compact, real-time, infrared imaging polarimeter, provide preliminary results demonstrating the enhanced contrast possible with such a system, and discuss ways in which this technology can be integrated with existing manned and unmanned airborne platforms.

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

    NASA Astrophysics Data System (ADS)

    Nidamanuri, Rama Rao; Zbell, Bernd

    2011-09-01

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

  5. Design and Performance of the Hyper-Cam, an Infrared Hyperspectral Imaging Sensor

    DTIC Science & Technology

    2009-10-01

    UXO) and for the detection of camouflaged targets . Imaging spectrometers have unmatched capabilities to meet the requirements of these applications...Cam, operating in the LWIR band, is well suited for standoff chemical agent detection and can be used as a powerful hyperspectral imager for any...Design and Performance of the Hyper-Cam, an Infrared Hyperspectral Imaging Sensor Philippe Lagueux*a, Vincent Farleya, Martin Chamberlanda

  6. 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.

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

    PubMed

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

    2015-09-11

    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.

  8. 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.

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

    PubMed Central

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

    2015-01-01

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

  10. 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.

  11. Application of hydrothermal alteration mineral mapping using airborne hyperspectral remote sensing: data taken in the Baixianishan region of Gansu Province as an example

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

    Hyperspectral remote sensing, featured by integrated images and spectra, is now a frontier of the remote sensing. Using meticulous spectra, hyperspectral remote sensing technology can depict spectral features of objects in detail and are capable of identifying objects rather than simply discriminating them. This study took the Baixianishan region in Gansu Province as an example, and CASI/SASI airborne hyperspectral data were utilized to extract and map alteration minerals by MTMF mapping method. Six hydrothermal alteration minerals were mapped, which contained limonite, sericite and epidote. In addition, we analyzed the types, combinations and distribution of the alteration minerals and divided three stages of hydrothermal activity. It is considered that the favorable ore-forming elements for gold deposits are middle Hercynian porphyraceous granite, fracture and veined distribution of sericite and limonite. The application of CASI/SASI airborne hyperspectral remote sensing data in the Baixianishan area has achieved ideal results, indicative of their wide application potential in the geological research.

  12. Case studies for observation planning algorithm of a Japanese spaceborne sensor: Hyperspectral Imager Suite (HISUI)

    NASA Astrophysics Data System (ADS)

    Ogawa, Kenta; Konno, Yukiko; Yamamoto, Satoru; Matsunaga, Tsuneo; Tachikawa, Tetsushi; Komoda, Mako; Kashimura, Osamu; Rokugawa, Shuichi

    2016-10-01

    Hyperspectral Imager Suite (HISUI)[1] is a Japanese future spaceborne hyperspectral instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be delivered to ISS in 2018. In HISUI project, observation strategy is important especially for hyperspectral sensor, and relationship between the limitations of sensor operation and the planned observation scenarios have to be studied. We have developed concept of multiple algorithms approach. The concept is to use two (or more) algorithm models (Long Strip Model and Score Downfall Model) for selecting observing scenes from complex data acquisition requests with satisfactory of sensor constrains. We have tested the algorithm, and found that the performance of two models depends on remaining data acquisition requests, i.e. distribution score along with orbits. We conclude that the multiple algorithms approach will be make better collection plans for HISUI comparing with single fixed approach.

  13. 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.

  14. 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...

  15. Spectral characterization of coastal sediments using Field Spectral Libraries, Airborne Hyperspectral Images and Topographic LiDAR Data (FHyL)

    NASA Astrophysics Data System (ADS)

    Manzo, Ciro; Valentini, Emiliana; Taramelli, Andrea; Filipponi, Federico; Disperati, Leonardo

    2015-04-01

    Beach dune systems are important for coastal zone ecosystems as they provide natural sea defences that dissipate wave energy. Geomorphological models of this near-shore topography require site-specific sediment composition, grain size and moisture content as inputs. Hyperspectral, field radiometry and LiDAR remote sensing can be used as tools by providing synoptic maps of these properties. However, multi-remote sensing of near-shore beach images can only be interpreted if there are adequate bio-geophysical or empirical models for information extraction. Our aim was thus to model the effects of varying sediment properties on the reflectance in both field and laboratory conditions within the FHyL (Field Spectral Libraries, Airborne Hyperspectral Images and Topographic LiDAR) procedure, using a multisource dataset (airborne Hyperspectral - MIVIS and topographic LiDAR - Hawk-eye II and field radiometry). The methodology consisted of (i) acquisition of simultaneous multi-source datasets (airborne Hyperspectral - MIVIS and topographic LiDAR - Hawk-eye) (ii) hyperspectral measurements of sediment mixtures with varying physical characteristics (moisture, grain size and minerals) in field and laboratory conditions, (iii) determination and quantification of specific absorption features, and (iv) correlation between the absorption features and physical parameters cited above. Results showed the potential of hyperspectral signals to assess the effect of moisture, grain-size and mineral composition on sediment properties.

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

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

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

  17. A 868MHz-based wireless sensor network for ground truthing of soil moisture for a hyperspectral remote sensing campaign - design and preliminary results

    NASA Astrophysics Data System (ADS)

    Näthe, Paul; Becker, Rolf

    2014-05-01

    Soil moisture and plant available water are important environmental parameters that affect plant growth and crop yield. Hence, they are significant parameters for vegetation monitoring and precision agriculture. However, validation through ground-based soil moisture measurements is necessary for accessing soil moisture, plant canopy temperature, soil temperature and soil roughness with airborne hyperspectral imaging systems in a corresponding hyperspectral imaging campaign as a part of the INTERREG IV A-Project SMART INSPECTORS. At this point, commercially available sensors for matric potential, plant available water and volumetric water content are utilized for automated measurements with smart sensor nodes which are developed on the basis of open-source 868MHz radio modules, featuring a full-scale microcontroller unit that allows an autarkic operation of the sensor nodes on batteries in the field. The generated data from each of these sensor nodes is transferred wirelessly with an open-source protocol to a central node, the so-called "gateway". This gateway collects, interprets and buffers the sensor readings and, eventually, pushes the data-time series onto a server-based database. The entire data processing chain from the sensor reading to the final storage of data-time series on a server is realized with open-source hardware and software in such a way that the recorded data can be accessed from anywhere through the internet. It will be presented how this open-source based wireless sensor network is developed and specified for the application of ground truthing. In addition, the system's perspectives and potentials with respect to usability and applicability for vegetation monitoring and precision agriculture shall be pointed out. Regarding the corresponding hyperspectral imaging campaign, results from ground measurements will be discussed in terms of their contributing aspects to the remote sensing system. Finally, the significance of the wireless sensor

  18. The Multi-sensor Airborne Radiation Survey (MARS) Instrument

    SciTech Connect

    Fast, James E.; Aalseth, Craig E.; Asner, David M.; Bonebrake, Christopher A.; Day, Anthony R.; Dorow, Kevin E.; Fuller, Erin S.; Glasgow, Brian D.; Hossbach, Todd W.; Hyronimus, Brian J.; Jensen, Jeffrey L.; Johnson, Kenneth I.; Jordan, David V.; Morgen, Gerald P.; Morris, Scott J.; Mullen, O Dennis; Myers, Allan W.; Pitts, W. Karl; Rohrer, John S.; Runkle, Robert C.; Seifert, Allen; Shergur, Jason M.; Stave, Sean C.; Tatishvili, Gocha; Thompson, Robert C.; Todd, Lindsay C.; Warren, Glen A.; Willett, Jesse A.; Wood, Lynn S.

    2013-01-11

    The Multi-sensor Airborne Radiation Survey (MARS) project has developed a new single cryostat detector array design for high purity germanium (HPGe) gama ray spectrometers that achieves the high detection efficiency required for stand-off detection and actionable characterization of radiological threats. This approach, we found, is necessary since a high efficiency HPGe detector can only be built as an array due to limitations in growing large germanium crystals. Moreover, the system is ruggedized and shock mounted for use in a variety of field applications, including airborne and maritime operations.

  19. The Multi-sensor Airborne Radiation Survey (MARS) instrument

    NASA Astrophysics Data System (ADS)

    Fast, J. E.; Aalseth, C. E.; Asner, D. M.; Bonebrake, C. A.; Day, A. R.; Dorow, K. E.; Fuller, E. S.; Glasgow, B. D.; Hossbach, T. W.; Hyronimus, B. J.; Jensen, J. L.; Johnson, K. I.; Jordan, D. V.; Morgen, G. P.; Morris, S. J.; Mullen, O. D.; Myers, A. W.; Pitts, W. K.; Rohrer, J. S.; Runkle, R. C.; Seifert, A.; Shergur, J. M.; Stave, S. C.; Tatishvili, G.; Thompson, R. C.; Todd, L. C.; Warren, G. A.; Willett, J. A.; Wood, L. S.

    2013-01-01

    The Multi-sensor Airborne Radiation Survey (MARS) project has developed a new single cryostat detector array design for high purity germanium (HPGe) gama ray spectrometers that achieves the high detection efficiency required for stand-off detection and actionable characterization of radiological threats. This approach is necessary since a high efficiency HPGe detector can only be built as an array due to limitations in growing large germanium crystals. The system is ruggedized and shock mounted for use in a variety of field applications, including airborne and maritime operations.

  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. 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.

  2. Flight and Ground Results from Long-Wave and Mid-wave Airborne Hyperspectral Spectrographic Images

    DTIC Science & Technology

    2009-10-01

    hyperspectral imager for landmine detection ,” in Detection and Remediation Technologies for Mines and Mine-like Targets X, R.S.Harmon, J.T.Broach... hyperspectral imaging of land mines,” in Detection and Remediation Technologies for Mines and Mine-Like Targets XII, R.S.Harmon, J.T.Broach, and... hyperspectral pushbroom imagers which are ideally suited for landmine detection , but which also have numerous applications outside the defence community

  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. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2005-05-01

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

  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. Airborne FLIR sensors for runway incursion detection

    NASA Astrophysics Data System (ADS)

    Archer, Cynthia; White, Joseph; Neece, Robert

    2009-05-01

    Forward Looking Infrared (FLIR) sensors are potential components in hazard monitoring systems for general aviation aircraft. FLIR sensors can provide images of the runway area when normal visibility is reduced by meteorological conditions. We are investigating short wave infrared (SWIR) and long wave infrared (LWIR) cameras. Pre-recorded video taken from an aircraft on approach to landing provides raw data for our analysis. This video includes approaches under four conditions: clear morning, cloudy afternoon, clear evening, and clear night. We used automatic object detection techniques to quantify the ability of these sensors to alert the pilot to potential runway hazards. Our analysis is divided into three stages: locating the airport, tracking the runway, and detecting vehicle sized objects. The success or failure of locating the runway provides information on the ability of the sensors to provide situational awareness. Tracking the runway position from frame to frame provides information on the visibility of runway features, such as landing lights or runway edges, in the scene. Detecting small objects quantifies clutter and provides information on the ability of these sensors to image potential hazards. In this paper, we present results from our analysis of sample approach video.

  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. Airborne Sensor Potential for Habitat Evaluation Procedures (HEP).

    DTIC Science & Technology

    1986-02-01

    guidelines for the d, vol-Ipitnet (A airborne sensor 3ppi ic~tions to the US Fish and Wililtifc...fr.iq J.Iqjsn *uld q~jq pooCg - A0,I- P.9A -41100fi uPall- -iied qus. o .;A (W.3 P.S’-.9. .1JI1OP. ua.l.t:4 𔃻𔃾lti P.,SC)Pts r.- aaop s0ul-~r9Iw

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

    NASA Astrophysics Data System (ADS)

    Franke, Jonas; Mewes, Thorsten; Menz, Gunter

    2008-08-01

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

  11. 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.

  12. Aerospace wetland monitoring by hyperspectral imaging sensors: a case study in the coastal zone of San Rossore Natural Park.

    PubMed

    Barducci, Alessandro; Guzzi, Donatella; Marcoionni, Paolo; Pippi, Ivan

    2009-05-01

    The San Rossore Natural Park, located on the Tuscany (Italy) coast, has been utilized over the last 10 years for many remote sensing campaigns devoted to coastal zone monitoring. A wet area is located in the south-west part of the Natural Park and it is characterized by a system of ponds and dunes formed by sediment deposition occurring at the Arno River estuary. The considerable amount of collected data has permitted us to investigate the evolution of wetland spreading and land coverage as well as to retrieve relevant biogeochemical parameters, e.g. green biomass, from remote sensing images and products. This analysis has proved that the monitoring of coastal wetlands, characterized by shallow waters, moor and dunes, demands dedicated aerospace sensors with high spatial and spectral resolution. The outcomes of the processing of images gathered during several remote sensing campaigns by airborne and spaceborne hyperspectral sensors are presented and discussed. A particular effort has been devoted to sensor response calibration and data validation due to the complex heterogeneity of the observed natural surfaces.

  13. 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.

  14. 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

  15. 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.

  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. 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.

  18. 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

  19. Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS)

    NASA Astrophysics Data System (ADS)

    Rhothermel, Jeffry; Jones, W. D.; Dunkin, J. A.; McCaul, E. W., Jr.

    1993-01-01

    This effort involves development of a calibrated, pulsed coherent CO2 Doppler lidar, followed by a carefully-planned and -executed program of multi-dimensional wind velocity and aerosol backscatter measurements from the NASA DC-8 research aircraft. The lidar, designated as the Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS), will be applicable to two research areas. First, MACAWS will enable specialized measurements of atmospheric dynamical processes in the planetary boundary layer and free troposphere in geographic locations and over scales of motion not routinely or easily accessible to conventional sensors. The proposed observations will contribute fundamentally to a greater understanding of the role of the mesoscale, helping to improve predictive capabilities for mesoscale phenomena and to provide insights into improving model parameterizations of sub-grid scale processes within large-scale circulation models. As such, it has the potential to contribute uniquely to major, multi-institutional field programs planned for the mid 1990's. Second, MACAWS measurements can be used to reduce the degree of uncertainty in performance assessments and algorithm development for NASA's prospective Laser Atmospheric Wind Sounder (LAWS), which has no space-based instrument heritage. Ground-based lidar measurements alone are insufficient to address all of the key issues. To minimize costs, MACAWS is being developed cooperatively by the lidar remote sensing groups of the Jet Propulsion Laboratory, NOAA Wave Propagation Laboratory, and MSFC using existing lidar hardware and manpower resources. Several lidar components have already been exercised in previous airborne lidar programs (for example, MSFC Airborne Doppler Lidar System (ADLS) used in 1981,4 Severe Storms Wind Measurement Program; JPL Airborne Backscatter Lidar Experiment (ABLE) used in 1989,90 Global Backscatter Experiment Survey Missions). MSFC has been given responsibility for directing the overall

  20. 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

  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. Automatic extraction of optimal endmembers from airborne hyperspectral imagery using iterative error analysis (IEA) and spectral discrimination measurements.

    PubMed

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

    2015-01-23

    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.

  3. 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

  4. 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.

  5. Sensor integration and testing in an airborne environment

    NASA Astrophysics Data System (ADS)

    Ricks, Timothy P.; Streling, Julie T.; Williams, Kirk W.

    2005-11-01

    The U.S. Army Redstone Technical Test Center (RTTC) has been supporting captive flight testing of missile sensors and seekers since the 1980's. Successful integration and test of sensors in an airborne environment requires attention to a broad range of disciplines. Data collection requirements drive instrumentation and flight profile configurations, which along with cost and airframe performance factors influence the choice of test aircraft. Installation methods used for instrumentation must take into consideration environmental and airworthiness factors. In addition, integration of test equipment into the aircraft will require an airworthiness release; procedures vary between the government for military aircraft, and the Federal Aviation Administration (FAA) for the use of private, commercial, or experimental aircraft. Sensor mounting methods will depend on the type of sensor being used, both for sensor performance and crew safety concerns. Pilots will require navigation input to permit the execution of accurate and repeatable flight profiles. Some tests may require profiles that are not supported by standard navigation displays, requiring the use of custom hardware/software. Test locations must also be considered in their effect on successful data collection. Restricted airspace may also be required, depending on sensor emissions and flight profiles.

  6. 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...

  7. Sensor noise informed representation of hyperspectral data, with benefits for image storage and processing.

    PubMed

    Skauli, Torbjørn

    2011-07-04

    Many types of hyperspectral image processing can benefit from knowledge of noise levels in the data, which can be derived from sensor physics. Surprisingly, such information is rarely provided or exploited. Usually, the image data are represented as radiance values, but this representation can lead to suboptimal results, for example in spectral difference metrics. Also, radiance data do not provide an appropriate baseline for calculation of image compression ratios. This paper defines two alternative representations of hyperspectral image data, aiming to make sensor noise accessible to image processing. A "corrected raw data" representation is proportional to the photoelectron count and can be processed like radiance data, while also offering simpler estimation of noise and somewhat more compact storage. A variance-stabilized representation is obtained by square-root transformation of the photodetector signal to make the noise signal-independent and constant across all bands while also reducing data volume by almost a factor 2. Then the data size is comparable to the fundamental information capacity of the sensor, giving a more appropriate measure of uncompressed data size. It is noted that the variance-stabilized representation has parallels in other fields of imaging. The alternative data representations provide an opportunity to reformulate hyperspectral processing algorithms to take actual sensor noise into account.

  8. Flight model performances of HISUI hyperspectral sensor onboard ISS (International Space Station)

    NASA Astrophysics Data System (ADS)

    Tanii, Jun; Kashimura, Osamu; Ito, Yoshiyuki; Iwasaki, Akira

    2016-10-01

    Hyperspectral Imager Suite (HISUI) is a next-generation Japanese sensor that will be mounted on Japanese Experiment Module (JEM) of ISS (International Space Station) in 2019 as timeframe. HISUI hyperspectral sensor obtains spectral images of 185 bands with the ground sampling distance of 20x31 meter from the visible to shortwave-infrared region. The sensor system is the follow-on mission of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) in the visible to shortwave infrared region. The critical design review of the instrument was accomplished in 2014. Integration and tests of an flight model of HISUI hyperspectral sensor is being carried out. Simultaneously, the development of JEM-External Facility (EF) Payload system for the instrument started. The system includes the structure, the thermal control system, the electrical system and the pointing mechanism. The development status and the performances including some of the tests results of Instrument flight model, such as optical performance, optical distortion and radiometric performance are reported.

  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. Enhanced monitoring of sulfur dioxide sources with hyperspectral UV sensors

    NASA Astrophysics Data System (ADS)

    Krueger, Arlin; Yang, Kai; Krotkov, Nickolay

    2009-09-01

    Sulfur dioxide, a short-lived atmospheric constituent, is oxidized to sulfate aerosols, a climate agent. Main sources are volcanoes, smelters, and fossil fuel combustion. Satellite monitoring of SO2 began with TOMS data in 1978 that detected volcanic eruption clouds. Hyperspectral instruments, like OMI and GOME, have a twenty-fold improvement in sensitivity. Degassing volcanoes, smelters, and large power plants are now monitored for a database of SO2 emission to the atmosphere. SO2 is a distinctive marker for volcanic ash clouds, a hazard to aircraft.

  11. The Multi-Center Airborne Coherent Atmospheric Wind Sensor, MACAWS

    NASA Technical Reports Server (NTRS)

    Rothermel, Jeffry; Cutten, Dean R.; Hardesty, R. Michael; Menzies, Robert T.; Howell, James; Johnson, Steven C.; Tratt, David M.; Olivier, Lisa D.; Banta, Robert M.

    1997-01-01

    In 1992 the atmospheric lidar remote sensing groups of the NASA Marshall Space Flight Center, NOAA Environmental Technology Laboratory, and Jet Propulsion Laboratory began a joint collaboration to develop an airborne high-energy Doppler laser radar (lidar) system for atmospheric research and satellite validation and simulation studies. The result is the Multi-center Airborne Coherent Atmospheric Wind Sensor, MACAWS, which has the capability to remotely sense the distribution of wind and absolute aerosol backscatter in the troposphere and lower stratosphere. A factor critical to the programmatic feasibility and technical success of this collaboration has been the utilization of existing components and expertise which were developed for previous atmospheric research by the respective institutions. The motivation for the MACAWS program Is three-fold: to obtain fundamental measurements of sub-synoptic scale processes and features which may be used as a basis to improve sub-grid scale parameterizations in large-scale models; to obtain similar datasets in order to improve the understanding and predictive capabilities on the mesoscale; and to validate (simulate) the performance of existing (planned) satellite-borne sensors. Examples of the latter include participation in the validation of the NASA Scatterometer and the assessment of prospective satellite Doppler lidar for global tropospheric wind measurement. Initial flight tests were made in September 1995; subsequent flights were made in June 1996 following improvements. This paper describes the MACAWS instrument, principles of operation, examples of measurements over the eastern Pacific Ocean and western United States, and future applications.

  12. Multi-center airborne coherent atmospheric wind sensor (MACAWS)

    SciTech Connect

    Rothermel, J.; Menzies, R.T.; Tratt, D.M.

    1996-11-01

    The Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) is an airborne scanning coherent Doppler lidar designed to acquire remote multi-dimensional measurements of winds and absolute aerosol backscatter in the troposphere and lower stratosphere. These measurements enable study of atmospheric dynamic processes and features at scales of motion that may be undersampled by, or may be beyond the capability of, existing or planned sensors. MACAWS capabilities enable more realistic assessments of concepts in global tropospheric wind measurement with satellite Doppler lidar, as well as a unique capability to validate the NASA Scatterometer currently scheduled for launch in late 1996. MACAWS consists of a Joule-class CO{sub 2} coherent Doppler lidar on a ruggedized optical table, a programmable scanner to direct the lidar beam in the desired direction, and a dedicated inertial navigation system to account for variable aircraft attitude and speed. MACAWS was flown for the first time in September 1995, over the eastern Pacific Ocean and western US. 33 refs., 2 figs.

  13. SENSOR: a tool for the simulation of hyperspectral remote sensing systems

    NASA Astrophysics Data System (ADS)

    Börner, Anko; Wiest, Lorenz; Keller, Peter; Reulke, Ralf; Richter, Rolf; Schaepman, Michael; Schläpfer, Daniel

    The consistent end-to-end simulation of airborne and spaceborne earth remote sensing systems is an important task, and sometimes the only way for the adaptation and optimisation of a sensor and its observation conditions, the choice and test of algorithms for data processing, error estimation and the evaluation of the capabilities of the whole sensor system. The presented software simulator SENSOR (Software Environment for the Simulation of Optical Remote sensing systems) includes a full model of the sensor hardware, the observed scene, and the atmosphere in between. The simulator consists of three parts. The first part describes the geometrical relations between scene, sun, and the remote sensing system using a ray-tracing algorithm. The second part of the simulation environment considers the radiometry. It calculates the at-sensor radiance using a pre-calculated multidimensional lookup-table taking the atmospheric influence on the radiation into account. The third part consists of an optical and an electronic sensor model for the generation of digital images. Using SENSOR for an optimisation requires the additional application of task-specific data processing algorithms. The principle of the end-to-end-simulation approach is explained, all relevant concepts of SENSOR are discussed, and first examples of its use are given. The verification of SENSOR is demonstrated. This work is closely related to the Airborne PRISM Experiment (APEX), an airborne imaging spectrometer funded by the European Space Agency.

  14. 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.

  15. 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. Spatially explicit modelling of forest structure and function using airborne lidar and hyperspectral remote sensing data combined with micrometeorological measurements

    NASA Astrophysics Data System (ADS)

    Thomas, Valerie Anne

    This research models canopy-scale photosynthesis at the Groundhog River Flux Site through the integration of high-resolution airborne remote sensing data and micrometeorological measurements collected from a flux tower. Light detection and ranging (lidar) data are analysed to derive models of tree structure, including: canopy height, basal area, crown closure, and average aboveground biomass. Lidar and hyperspectral remote sensing data are used to model canopy chlorophyll (Chl) and carotenoid concentrations (known to be good indicators of photosynthesis). The integration of lidar and hyperspectral data is applied to derive spatially explicit models of the fraction of photosynthetically active radiation (fPAR) absorbed by the canopy as well as a species classification for the site. These products are integrated with flux tower meteorological measurements (i.e., air temperature and global solar radiation) collected on a continuous basis over 2004 to apply the C-Fix model of carbon exchange to the site. Results demonstrate that high resolution lidar and lidar-hyperspectral integration techniques perform well in the boreal mixedwood environment. Lidar models are well correlated with forest structure, despite the complexities introduced in the mixedwood case (e.g., r2=0.84, 0.89, 0.60, and 0.91, for mean dominant height, basal area, crown closure, and average aboveground biomass). Strong relationships are also shown for canopy scale chlorophyll/carotenoid concentration analysis using integrated lidar-hyperspectral techniques (e.g., r2=0.84, 0.84, and 0.82 for Chl(a), Chl(a+b), and Chl(b)). Examination of the spatially explicit models of fPAR reveal distinct spatial patterns which become increasingly apparent throughout the season due to the variation in species groupings (and canopy chlorophyll concentration) within the 1 km radius surrounding the flux tower. Comparison of results from the modified local-scale version of the C-Fix model to tower gross ecosystem

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  19. Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation

    NASA Astrophysics Data System (ADS)

    Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

    2014-02-01

    A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

  20. (DCT-FY08) Target Detection Using Multiple Modality Airborne and Ground Based Sensors

    DTIC Science & Technology

    2013-03-01

    AFRL-OSR-VA-TR-2013-0005 (DCT-FY08) Target Detection Using Multiple Modality Airborne and Ground Based Sensors Avideh Zakhor...Include area code) 17-08-2012 FINAL 4-1-2008 to 11-30-2011 (DCT-FY08) Target Detection Using Multiple Modality Airborne and Ground Based Sensors ...automatic, photo-realistic 3D models of building interiors. We have developed an ambulatory human operated backpack system made of a suite of sensors

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  2. 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.

  3. 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

  4. The Multi-center Airborne Coherent Atmospheric Wind Sensor.

    NASA Astrophysics Data System (ADS)

    Rothermel, Jeffry; Cutten, Dean R.; Hardesty, R. Michael; Menzies, Robert T.; Howell, James N.; Johnson, Steven C.; Tratt, David M.; Olivier, Lisa D.; Banta, Robert M.

    1998-04-01

    In 1992 the atmospheric lidar remote sensing groups of the National Aeronautics and Space Administration Marshall Space Flight Center, the National Oceanic and Atmospheric Administration/Environmental Technology Laboratory (NOAA/ETL), and the Jet Propulsion Laboratory began a joint collaboration to develop an airborne high-energy Doppler laser radar (lidar) system for atmospheric research and satellite validation and simulation studies. The result is the Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS), which has the capability to remotely sense the distribution of wind and absolute aerosol backscatter in three-dimensional volumes in the troposphere and lower stratosphere.A factor critical to the programmatic feasibility and technical success of this collaboration has been the utilization of existing components and expertise that were developed for previous atmospheric research by the respective institutions. For example, the laser transmitter is that of the mobile ground-based Doppler lidar system developed and used in atmospheric research for more than a decade at NOAA/ETL.The motivation for MACAWS is threefold: 1) to obtain fundamental measurements of subsynoptic-scale processes and features to improve subgrid-scale parameterizations in large-scale models, 2) to obtain datasets in order to improve the understanding of and predictive capabilities for meteorological systems on subsynoptic scales, and 3) to validate (simulate) the performance of existing (planned) satellite-borne sensors.Initial flight tests were made in September 1995; subsequent flights were made in June 1996 following system improvements. This paper describes the MACAWS instrument, principles of operation, examples of measurements over the eastern Pacific Ocean and western United States, and future applications.

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

    NASA Astrophysics Data System (ADS)

    Kruse, Fred A.

    2015-05-01

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

  6. 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.

  7. 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.

  8. 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.

  9. Use of Airborne Hyperspectral Data in the Simulation of Satellite Images

    NASA Astrophysics Data System (ADS)

    de Miguel, Eduardo; Jimenez, Marcos; Ruiz, Elena; Salido, Elena; Gutierrez de la Camara, Oscar

    2016-08-01

    The simulation of future images is part of the development phase of most Earth Observation missions. This simulation uses frequently as starting point images acquired from airborne instruments. These instruments provide the required flexibility in acquisition parameters (time, date, illumination and observation geometry...) and high spectral and spatial resolution, well above the target values (as required by simulation tools). However, there are a number of important problems hampering the use of airborne imagery. One of these problems is that observation zenith angles (OZA), are far from those that the misisons to be simulated would use.We examine this problem by evaluating the difference in ground reflectance estimated from airborne images for different observation/illumination geometries. Next, we analyze a solution for simulation purposes, in which a Bi- directional Reflectance Distribution Function (BRDF) model is attached to an image of the isotropic surface reflectance. The results obtained confirm the need for reflectance anisotropy correction when using airborne images for creating a reflectance map for simulation purposes. But this correction should not be used without providing the corresponding estimation of BRDF, in the form of model parameters, to the simulation teams.

  10. Comparison of four methods of aerodynamic roughness length parameterization in semi-arid shrublands with airborne LiDAR, hyperspectral, and meteorological data

    NASA Astrophysics Data System (ADS)

    Li, A.; Mitchell, J. J.; Glenn, N. F.; Zhao, W.; Germino, M. J.; Allen, R.; Sankey, J. B.

    2013-12-01

    The aerodynamic roughness length (z0) plays an important role in the flux exchange between the land surface and atmosphere. Especially in semiarid shrublands, z0 is a key parameter for physical models of aeolian transport. z0 is influenced by the height, geometry, density and pattern of roughness elements. Light detection and ranging (LiDAR) is well suited to measure the vegetation height and has been used to estimate z0 across large areas. In this study, we combined airborne LiDAR, hyperspectral imagery and meteorological measurements to estimate z0, and assessed the ability of airborne LiDAR to estimate z0 over semi-arid shrublands. Airborne LiDAR data was used to derive the height of Wyoming big sagebrush (Artemisia tridentate subsp. wyomingensis) over a study area in the Great Basin, Idaho. Roughness density was related with percent vegetation cover which was estimated by integrating LiDAR and hyperspectral data, both collected in August 2011. Four methods of parameterization of z0 were applied and compared with the vegetation height from LiDAR; roughness from LiDAR and hyperspectral; NDVI and LAI from HyMap; and a geometric approach using meteorological data (e.g. wind speed). Micrometeorological measurements at two eddy covariance sites in the study area were used for validation of parameterized z0. The spatial variability of z0 was analyzed and the relationship with vegetation density was explored. The results demonstrated the potential of using airborne LiDAR data to estimate z0 at a regional scale in semi-arid shrublands. Furthermore, z0 showed a tight relationship with local variance of vegetation height and vegetation density.

  11. 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.

  12. 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.

  13. Hyperspectral image sensor for weed-selective spraying

    NASA Astrophysics Data System (ADS)

    Feyaerts, Filip; Pollet, P.; Van Gool, Luc J.; Wambacq, Patrick

    1999-11-01

    Recognizing, online, cops and weeds enables to reduce the use of chemicals in agriculture. First, a sensor and classifier is proposed to measure and classify, online, the plant reflectance. However, as plant reflectance varies with unknown field dependent plant stress factors, the classifier must be trained on each field separately in order to recognize crop and weeds accurately on that field. Collecting the samples manually requires user-knowledge and time and is therefore economically not feasible. The posed tree-based cluster algorithm enables to automatically collect and label the necessary set of training samples for crops that are planted in rows, thus eliminating every user- interaction and user-knowledge. The classifier, trained with the automatically collected and labeled training samples, is able to recognize crop and weeds with an accuracy of almost 94 percent. This result in acceptable weed hit rates and significant herbicide reductions. Spot-spraying on the weeds only becomes economically feasible.

  14. 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

  15. 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

  16. Mapping the Riparian Vegetation Using Multiple Hyperspectral and Thermal Infrared Airborne Imagery over the Republican River, Nebraska

    NASA Astrophysics Data System (ADS)

    Akasheh, O. Z.; Irmak, A.; Martin, D.; Irmak, S.; Awada, T.; Zhou, X.; Huddle, J.

    2009-12-01

    As the dependency on rivers for fresh water increases, rivers ecosystem analysis becomes essential for proper water management and riparian vegetation protection. Changes in river water flow pattern have affected the riparian vegetation distribution and encouraged invasive species to replace the native ones. Mapping riparian vegetation helps quantify changes in species composition. Land managers will be able to use our map to monitor and control invasive species and estimate riparian vegetation water use. Based on water use estimates decision makers can decide on how much water could be diverted from the river and how to distribute it while preserving the river ecosystem. In this study we will show the use of high spectral and spatial resolution imagery to map the riparian vegetation in the Republican River. Eight flights were conducted during the summer of 2009 using AisaEagle Airborne Hyperspectral Imaging System and FLIR SC640 thermal digital camera. The AisaEagle acquires visible and near infrared images in the waver band over 400 - 970 nm of the electromagnetic spectrum, while the thermal infrared captures images in the range of 800-1200 nm. Early and mid-season images were primarily acquired to classify the overstory cottonwood (Populus deltoides) vegetation and late-season images were primarily acquired to classify the understory vegetation and the invasive eastern redcedar (Juniperus virginiana) after the senescence of cottonwood leaves. The land use map was developed using a supervised classification technique. The high resolution imagery delineated the riparian vegetation accurately with an overall classification accuracy of 85 %. Overall, our results indicate that high resolution imagery is very useful in mapping both heterogonous forest systems and woody invasive species along the Republican River.

  17. 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.

  18. 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.

  19. Multicenter airborne coherent atmospheric wind sensor (MACAWS) instrument: recent upgrades and results

    NASA Astrophysics Data System (ADS)

    Howell, James N.; Rothermel, Jeffrey; Tratt, David M.; Cutten, Dean; Darby, Lisa S.; Hardesty, R. Michael

    1999-10-01

    The Multicenter Airborne Coherent Atmospheric Wind Sensor instrument is an airborne coherent Doppler laser radar (Lidar) capable of measuring atmospheric wind fields and aerosol structure. Since the first demonstration flights onboard the NASA DC-8 research aircraft in September 1995, two additional science flights have been completed. Several system upgrades have also bee implemented. In this paper we discuss the system upgrades and present several case studies which demonstrate the various capabilities of the system.

  20. 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.

  1. 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.

  2. Aspects of detection and tracking of ground targets from an airborne EO/IR sensor

    NASA Astrophysics Data System (ADS)

    Balaji, Bhashyam; Sithiravel, Rajiv; Daya, Zahir; Kirubarajan, Thiagalingam

    2015-05-01

    An airborne EO/IR (electro-optical/infrared) camera system comprises of a suite of sensors, such as a narrow and wide field of view (FOV) EO and mid-wave IR sensors. EO/IR camera systems are regularly employed on military and search and rescue aircrafts. The EO/IR system can be used to detect and identify objects rapidly in daylight and at night, often with superior performance in challenging conditions such as fog. There exist several algorithms for detecting potential targets in the bearing elevation grid. The nonlinear filtering problem is one of estimation of the kinematic parameters from bearing and elevation measurements from a moving platform. In this paper, we developed a complete model for the state of a target as detected by an airborne EO/IR system and simulated a typical scenario with single target with 1 or 2 airborne sensors. We have demonstrated the ability to track the target with `high precision' and noted the improvement from using two sensors on a single platform or on separate platforms. The performance of the Extended Kalman filter (EKF) is investigated on simulated data. Image/video data collected from an IR sensor on an airborne platform are processed using an image tracking by detection algorithm.

  3. Sensors and sensory processing for airborne vibrations in silk moths and honeybees.

    PubMed

    Ai, Hiroyuki

    2013-07-19

    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.

  4. 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.

  5. 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.

  6. 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.

  7. Adaptive Noise Reduction Techniques for Airborne Acoustic Sensors

    DTIC Science & Technology

    2012-01-01

    25 4.3 Super Kraft Monocoupe 90A RC airplane. . . . . . . . . . . . . . . . . . . . . . . 27 4.4 Access panel for fuselage of...begin clipping. This is an important consideration for airborne acoustic sensing, as the sound level aboard a UAV must not cause saturation of the...specifications of the Monocoupe used for this experiment are in Table 4.3. 26 Figure 4.3: Super Kraft Monocoupe 90A RC airplane. Figure 4.4: Access panel for

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  10. 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.

  11. 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.

  12. Airborne sensor systems under development at the NASA/NSTL/Earth Resources Laboratory

    NASA Technical Reports Server (NTRS)

    Anderson, James E.; Meeks, Gerald R.

    1988-01-01

    The operational characteristics of the Airborne Bathymetric System (ABS) MSS and the Airborne Multispectral Pushbroom Scanner (AMPS), which are currently being developed at NASA's Earth Resources Laboratory (ERL), are described. The ABS MSS system scans through a swath width of + or - 40 deg from nadir and the sensor incorporates onboard calibration references for the visible and short-wavelength IR channels. The AMPS uses five separate f/1.8 refractive telecentric lens systems, each incorporating nine optical elements, and a replaceable fixed bandwidth filter.

  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. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. New Thermal Infrared Hyperspectral Imagers

    DTIC Science & Technology

    2009-10-01

    SET-151 Thermal Hyperspectral Imagery (Imagerie hyperspectrale thermique). Meeting Proceedings of Sensors and Electronics Panel (SET) Specialists...in hyperspectral instruments, where the optical power from the target is spread spectrally over tens of pixels, but the instrument radiation is not...because it also depends on temperature, emissivity and spectral features of the target . The well describing figure of merit for a hyperspectral

  1. 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.

  2. 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.

  3. An Improved High-Sensitivity Airborne Transient Electromagnetic Sensor for Deep Penetration

    PubMed Central

    Chen, Shudong; Guo, Shuxu; Wang, Haofeng; He, Miao; Liu, Xiaoyan; Qiu, Yu; Zhang, Shuang; Yuan, Zhiwen; Zhang, Haiyang; Fang, Dong; Zhu, Jun

    2017-01-01

    The investigation depth of transient electromagnetic sensors can be effectively increased by reducing the system noise, which is mainly composed of sensor internal noise, electromagnetic interference (EMI), and environmental noise, etc. A high-sensitivity airborne transient electromagnetic (AEM) sensor with low sensor internal noise and good shielding effectiveness is of great importance for deep penetration. In this article, the design and optimization of such an AEM sensor is described in detail. To reduce sensor internal noise, a noise model with both a damping resistor and a preamplifier is established and analyzed. The results indicate that a sensor with a large diameter, low resonant frequency, and low sampling rate will have lower sensor internal noise. To improve the electromagnetic compatibility of the sensor, an electromagnetic shielding model for a central-tapped coil is established and discussed in detail. Previous studies have shown that unclosed shields with multiple layers and center grounding can effectively suppress EMI and eddy currents. According to these studies, an improved differential AEM sensor is constructed with a diameter, resultant effective area, resonant frequency, and normalized equivalent input noise of 1.1 m, 114 m2, 35.6 kHz, and 13.3 nV/m2, respectively. The accuracy of the noise model and the shielding effectiveness of the sensor have been verified experimentally. The results show a good agreement between calculated and measured results for the sensor internal noise. Additionally, over 20 dB shielding effectiveness is achieved in a complex electromagnetic environment. All of these results show a great improvement in sensor internal noise and shielding effectiveness. PMID:28106718

  4. An Improved High-Sensitivity Airborne Transient Electromagnetic Sensor for Deep Penetration.

    PubMed

    Chen, Shudong; Guo, Shuxu; Wang, Haofeng; He, Miao; Liu, Xiaoyan; Qiu, Yu; Zhang, Shuang; Yuan, Zhiwen; Zhang, Haiyang; Fang, Dong; Zhu, Jun

    2017-01-17

    The investigation depth of transient electromagnetic sensors can be effectively increased by reducing the system noise, which is mainly composed of sensor internal noise, electromagnetic interference (EMI), and environmental noise, etc. A high-sensitivity airborne transient electromagnetic (AEM) sensor with low sensor internal noise and good shielding effectiveness is of great importance for deep penetration. In this article, the design and optimization of such an AEM sensor is described in detail. To reduce sensor internal noise, a noise model with both a damping resistor and a preamplifier is established and analyzed. The results indicate that a sensor with a large diameter, low resonant frequency, and low sampling rate will have lower sensor internal noise. To improve the electromagnetic compatibility of the sensor, an electromagnetic shielding model for a central-tapped coil is established and discussed in detail. Previous studies have shown that unclosed shields with multiple layers and center grounding can effectively suppress EMI and eddy currents. According to these studies, an improved differential AEM sensor is constructed with a diameter, resultant effective area, resonant frequency, and normalized equivalent input noise of 1.1 m, 114 m², 35.6 kHz, and 13.3 nV/m², respectively. The accuracy of the noise model and the shielding effectiveness of the sensor have been verified experimentally. The results show a good agreement between calculated and measured results for the sensor internal noise. Additionally, over 20 dB shielding effectiveness is achieved in a complex electromagnetic environment. All of these results show a great improvement in sensor internal noise and shielding effectiveness.

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Using Hyperspectral Frame Images from Unmanned Airborne Vehicle for Detailed Measurement of Boreal Forest 3D Structure

    NASA Astrophysics Data System (ADS)

    de Oliveira, Raquel A.; Tommaselli, Antonio M. G.; Honkavaara, Eija

    2016-10-01

    Objective of this work was to investigate the feasibility of using multi-image matching and information extracted from image classification to improve strategies in generation of point clouds of 3D forest scene. Image data sets were collected by a Fabry-Pérot interferometer (FPI) based hyperspectral frame camera on-board a UAV in a boreal forest area. The results of the new method are analysed and compared with commercial software and LiDAR data. Experiments showed that the point clouds generated with the proposed algorithm fitted better with the LiDAR data at the ground level, which is favourable for digital terrain model (DTM) extraction.

  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. Hyperspectral Image Classification using a Self-Organizing Map

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  14. 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.

  15. 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.

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

    PubMed

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

    2008-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-11-01

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

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

    PubMed Central

    Oppelt, Natascha; Mauser, Wolfram

    2007-01-01

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

  19. 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

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

    PubMed Central

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

    2008-01-01

    Airborne multispectral and hyperspectral remote sensing is a powerful tool for environmental monitoring applications. In this paper we describe a new system (ASPIS) composed by a 4-CCD spectral sensor, a thermal IR camera and a laser altimeter that is mounted on a flexible Sky-Arrow airplane. A test application of the multispectral sensor to estimate durum wheat quality is also presented. PMID:27879875

  1. Overview of the first Multicenter Airborne Coherent Atmospheric Wind Sensor (MACAWS) experiment: conversion of a ground-based lidar for airborne applications

    NASA Astrophysics Data System (ADS)

    Howell, James N.; Hardesty, R. Michael; Rothermel, Jeffrey; Menzies, Robert T.

    1996-11-01

    The first Multi center Airborne Coherent Atmospheric Wind Sensor (MACAWS) field experiment demonstrated an airborne high energy TEA CO2 Doppler lidar system for measurement of atmospheric wind fields and aerosol structure. The system was deployed on the NASA DC-8 during September 1995 in a series of checkout flights to observe several important atmospheric phenomena, including upper level winds in a Pacific hurricane, marine boundary layer winds, cirrus cloud properties, and land-sea breeze structure. The instrument, with its capability to measure 3D winds and backscatter fields, promises to be a valuable tool for climate and global change, severe weather, and air quality research. In this paper, we describe the airborne instrument, assess its performance, discuss future improvements, and show some preliminary results from the September experiments.

  2. Overview of the first Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) experiment: Conversion of a ground-based lidar for airborne applications

    SciTech Connect

    Howell, J.N.; Hardesty, R.M.; Rothermel, J.; Menzies, R.T.

    1996-12-31

    The first Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) field experiment demonstrated an airborne high energy TEA CO{sub 2} Doppler lidar system for measurement of atmospheric wind fields and aerosol structure. The system was deployed on the NASA DC-8 during September 1995 in a series of checkout flights to observe several important atmospheric phenomena, including upper level winds in a Pacific hurricane, marine boundary layer winds, cirrus cloud properties, and land-sea breeze structure. The instrument, with its capability to measure three-dimensional winds and backscatter fields, promises to be a valuable tool for climate and global change, severe weather, and air quality research. In this paper, the authors describe the airborne instrument, assess its performance, discuss future improvements, and show some preliminary results from September experiments.

  3. 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.

  4. NASA/LMSC coherent LIDAR airborne shear sensor: System capabilities and flight test plans

    NASA Technical Reports Server (NTRS)

    Robinson, Paul

    1992-01-01

    The primary objective of the NASA/LMSC Coherent Lidar Airborne Shear Sensor (CLASS) system flight tests is to evaluate the capability of an airborne coherent lidar system to detect, measure, and predict hazardous wind shear ahead of the aircraft with a view to warning flight crew of any impending dangers. On NASA's Boeing 737 Transport Systems Research Vehicle, the CLASS system will be used to measure wind velocity fields and, by incorporating such measurements with real-time aircraft state parameters, identify regions of wind shear that may be detrimental to the aircraft's performance. Assessment is to be made through actual wind shear encounters in flight. Wind shear measurements made by the class system will be compared to those made by the aircraft's in situ wind shear detection system as well as by ground-based Terminal Doppler Weather Radar (TDWR) and airborne Doppler radar. By examining the aircraft performance loss (or gain) due to wind shear that the lidar predicts with that actually experienced by the aircraft, the performance of the CLASS system as a predictive wind shear detector will be assessed.

  5. The prediction of the optical contrast of air-borne targets against the night-sky background for Photopic and NVG sensors

    NASA Astrophysics Data System (ADS)

    Havemann, Stephan; Wong, Gerald

    2016-10-01

    The Havemann-Taylor Fast Radiative Transfer Code (HT-FRTC) represents transmittances, radiances and fluxes by principal components that cover the spectra at very high resolution, allowing fast highly-resolved pseudo line-by-line, hyperspectral and broadband simulations across the electromagnetic spectrum form the microwave to the ultraviolet for satellite-based, airborne and ground-based sensors. HT-FRTC models clear atmospheres and those containing clouds and aerosols, as well as any surface (land/sea/man-made). The HT-FRTC has been used operationally in the NEON Tactical Decision Aid (TDA) since 2008. The TDA combines the HT-FRTC with a thermal contrast model and an NWP model forecast data feed to predict the apparent thermal contrast between different surfaces and ground-based targets in the thermal and short-wave IR. The new objective here is to predict the optical contrast of air-borne targets under realistic night-time scenarios in the Photopic and NVG parts of the spectrum. This requires the inclusion of all the relevant radiation sources, which include twilight, moonlight, starlight, airglow and cultural light. A completely new exact scattering code has been developed which allows the straight-forward addition of any number of direct and diffuse sources anywhere in the atmosphere. The new code solves the radiative transfer equation iteratively and is faster than the previous solution. Simulations of scenarios with different light levels, from situations during a full moon to a moonless night with very low light levels and a situation with cultural light from a town are presented. The impact of surface reflectance and target reflectance is investigated.

  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. 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.

  8. 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.

  9. Spectral/spatial data fusion and neural networks for vegetation understory information extraction from hyperspectral airborne images

    NASA Astrophysics Data System (ADS)

    Binaghi, Elisabetta; Gallo, Ignazio; Boschetti, Mirco; Brivio, Pietro A.

    2004-02-01

    In this paper, we propose a method able to fuse spectral information with spatial contextual information in order to solve "operationally" classification problem. The salient aspect of the method is the integration of heterogeneous data within a Multi-Layer Perceptron model. Spatial and spectral relationships are not explicitly formalized in an attempt to limit design and computational complexity; raw data are instead presented directly as input to the neural network classifier. The method in particular addresses new open problems in processing hyperspectral and high resolution data finding solution for multisource analysis. Experimental results in real domain show this fusing approach is able to produce accurate classification. The method in fact is able to handle the problem of a volumetric mixture typical of natural forest ecosystems identifying the different surfaces present under the tree canopy. The understory map, produced by the neural classification method, was used as input to the inversion of radiative transfer models that show a significant increase in the retrieval of important biophysical vegetation parameter.

  10. 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

  11. 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

  12. 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

  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. Physics-based, reduced-order gas cloud with radiative transport model for rapid simulation of hyperspectral infrared sensors

    NASA Astrophysics Data System (ADS)

    Kottke, Peter A.; Fedorov, Andrei G.

    2012-05-01

    We have developed a reduced-order, physics-based model of gas cloud transport and combined it with an approximate formulation of the equation of radiative transport to enable efficient prediction of spectral irradiation for simulation of hyperspectral infrared sensors. The resulting combined model is easily implemented, providing a rapid and flexible in silico experimentation capability. The gas cloud model is based on the entrainment hypothesis and predicts cloud trajectories in three-dimensions, with elevation changes occurring primarily due to buoyancy effects and with spreading and accompanying dilution and cooling occurring due to a turbulence dominated growth mechanism. The radiation transport model is simplified through an approximate treatment of scattering that transforms the governing equation from an integro-differential equation to an ordinary differential equation. The conjugate model has been combined with a simple sensor model and has been validated through comparison to results from large-scale field tests. The utility of the simulations has also been demonstrated through inclusion in a larger algorithm development and analysis program, the chem/bio algorithm development kit.

  15. 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

  16. 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.

  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. 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.

  19. Determination of target detection limits in hyperspectral data using band selection and dimensionality reduction

    NASA Astrophysics Data System (ADS)

    Gross, W.; Boehler, J.; Twizer, K.; Kedem, B.; Lenz, A.; Kneubuehler, M.; Wellig, P.; Oechslin, R.; Schilling, H.; Rotman, S.; Middelmann, W.

    2016-10-01

    Hyperspectral remote sensing data can be used for civil and military applications to robustly detect and classify target objects. High spectral resolution of hyperspectral data can compensate for the comparatively low spatial resolution, which allows for detection and classification of small targets, even below image resolution. Hyperspectral data sets are prone to considerable spectral redundancy, affecting and limiting data processing and algorithm performance. As a consequence, data reduction strategies become increasingly important, especially in view of near-real-time data analysis. The goal of this paper is to analyze different strategies for hyperspectral band selection algorithms and their effect on subpixel classification for different target and background materials. Airborne hyperspectral data is used in combination with linear target simulation procedures to create a representative amount of target-to-background ratios for evaluation of detection limits. Data from two different airborne hyperspectral sensors, AISA Eagle and Hawk, are used to evaluate transferability of band selection when using different sensors. The same target objects were recorded to compare the calculated detection limits. To determine subpixel classification results, pure pixels from the target materials are extracted and used to simulate mixed pixels with selected background materials. Target signatures are linearly combined with different background materials in varying ratios. The commonly used classification algorithms Adaptive Coherence Estimator (ACE) is used to compare the detection limit for the original data with several band selection and data reduction strategies. The evaluation of the classification results is done by assuming a fixed false alarm ratio and calculating the mean target-to-background ratio of correctly detected pixels. The results allow drawing conclusions about specific band combinations for certain target and background combinations. Additionally

  20. 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.

  1. Detecting subtle environmental change: a multi-temporal airborne imaging spectroscopy approach

    NASA Astrophysics Data System (ADS)

    Yule, Ian J.; Pullanagari, Reddy R.; Kereszturi, G.

    2016-10-01

    Airborne and satellite hyperspectral remote sensing is a key technology to observe finite change in ecosystems and environments. The role of such sensors will improve our ability to monitor and mitigate natural and agricultural environments on a much larger spatial scale than can be achieved using field measurements such as soil coring or proximal sensors to estimate the chemistry of vegetation. Hyperspectral sensors for commentarial and scientific activities are increasingly available and cost effective, providing a great opportunity to measure and detect changes in the environment and ecosystem. This can be used to extract critical information to develop more advanced management practices. In this research, we provide an overview of the data acquisition, processing and analysis of airborne, full-spectrum hyperspectral imagery from a small-scale aerial mapping project in hill-country farms in New Zealand, using an AISA Fenix sensor (Specim, Finland). The imagery has been radiometrically and atmospherically corrected, georectified and mosaicked. The hyperspectral data cube was then spectrally and spatially smoothed using Savitzky-Golay and median filter, respectively. The mosaicked imagery used to calculate bio-chemical properties of surface vegetation, such as pasture. Ground samples (n = 200) were collected a few days after the over-flight are used to develop a calibration model using partial least squares regression method. In-leaf nitrogen, potassium and phosphorous concentration were calculated using the reflectance values from the airborne hyperspectral imagery. In total, three surveys of an example property have been acquired that show changes in the pattern of availability of a major element in vegetation canopy, in this case nitrogen.

  2. Monitoring of Carbon Dioxide and Methane Plumes from Combined Ground-Airborne Sensors

    NASA Astrophysics Data System (ADS)

    Jacob, Jamey; Mitchell, Taylor; Honeycutt, Wes; Materer, Nicholas; Ley, Tyler; Clark, Peter

    2016-11-01

    A hybrid ground-airborne sensing network for real-time plume monitoring of CO2 and CH4 for carbon sequestration is investigated. Conventional soil gas monitoring has difficulty in distinguishing gas flux signals from leakage with those associated with meteorologically driven changes. A low-cost, lightweight sensor system has been developed and implemented onboard a small unmanned aircraft and is combined with a large-scale ground network that measures gas concentration. These are combined with other atmospheric diagnostics, including thermodynamic data and velocity from ultrasonic anemometers and multi-hole probes. To characterize the system behavior and verify its effectiveness, field tests have been conducted with simulated discharges of CO2 and CH4 from compressed gas tanks to mimic leaks and generate gaseous plumes, as well as field tests over the Farnsworth CO2-EOR site in the Anadarko Basin. Since the sensor response time is a function of vehicle airspeed, dynamic calibration models are required to determine accurate location of gas concentration in space and time. Comparisons are made between the two tests and results compared with historical models combining both flight and atmospheric dynamics. Supported by Department of Energy Award DE-FE0012173.

  3. 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

  4. Quantifying the variability of surface reflectance and estimating canopy chlorophyll content and green leaf biomass using hyperspectral close-range data and airborne imagery

    NASA Astrophysics Data System (ADS)

    Razzaghi, Tarlan

    Advances in agricultural studies have benefited from the use of remote sensing in generating and analyzing datasets, efficiently. Remotely sensed images facilitate a diverse array of non-intrusive agricultural investigations including new approaches such as high-throughput phenotyping. This research examines the variability of surface reflectance and estimates two biophysical parameters associated with crops. The first goal of the project was to provide an estimation of reflectance variability within low-resolution satellite imagery. The quantified variability of intra-pixel spectral reflectance can then be used to determine the level of uncertainty in estimating biophysical characteristics of plants. The study revealed how the variability in a composite spectral signal emanating from a large pixel was influenced by crop type, phenological stage, and irrigation method. A second goal of this study was to examine algorithms developed using multi-temporal airborne hyperspectal imagery for estimation and mapping of canopy Chl content in irrigated and rainfed maize and soybean fields. The optimal spectral range for two conceptual models, Chlorophyll Index and Normalized Difference, were determined and calibrated for the spectral bands of AISA, Sentinel-2 MSI and Sentinel-3 OLCI sensors. The results showed that CI red edge model derived solely from airborne imagery was capable of accurately estimating canopy Chl in fields with different crop management practices, field history and climatic conditions. The spatial and temporal dynamics of canopy Chl content were elucidated for maize and soybean fields at different phenological stages and rainfall regimes. The final goal of this study was to evaluate the performance of several vegetation indices for estimating green leaf biomass (GLB) in maize and soybean fields using canopy reflectance collected at close-range and airborne imagery. It was determined that models containing red edge and near-infrared bands were capable of

  5. Expanding the dimensions of hyperspectral imagery to improve target detection

    NASA Astrophysics Data System (ADS)

    Salvador, Mark Z.

    2016-10-01

    On-going research to improve hyperspectral target detection generally focuses on statistical detector performance, reduction of background or environmental contributions to at-sensor radiance, dimension reduction and many other mathematical or physical techniques. These efforts are all aimed at improving target identification in a single scene or data cube. This focus on single scene performance is driven directly by the airborne collection concept of operations (CONOPS) of a single pass per target location. Today's pushbroom and whiskbroom sensors easily achieve single passes and single collects over a target location. If multiple passes are flown for multiple collects on the same location, the time scale for revisit is several minutes. Emerging gimbaled hyperspectral imagers have the capability to collect multiple scans over the same target location in a time scale of seconds. The ability to scan the same location from slightly different collection geometries below the time scale of significant solar and atmospheric change forces us to reexamine the methods for target detection via the fundamental radiance equation. By expanding the radiance equation in the spatial and temporal dimensions, data from multiple hyperspectral images is used simultaneously for determining at-sensor radiance and surface leaving radiance with the ultimate goal of improving target detection. This research reexamines the fundamental radiance equation for multiple scan collection geometries expanding both the spatial and temporal domains. In addition, our assumptions for determining at-sensor radiance are revisited in light of the increased dimensionality. The expanded radiance equation is then applied to data collected by a gimbaled long wave infrared hyperspectral imager. Initial results and future work are discussed.

  6. 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.

  7. The NASA Airborne Earth Science Microwave Imaging Radiometer (AESMIR): A New Sensor for Earth Remote Sensing

    NASA Technical Reports Server (NTRS)

    Kim, Edward

    2003-01-01

    The Airborne Earth Science Microwave Imaging Radiometer (AESMIR) is a versatile new airborne imaging radiometer recently developed by NASA. The AESMIR design is unique in that it performs dual-polarized imaging at all standard passive microwave frequency bands (6-89 GHz) using only one sensor headscanner package, providing an efficient solution for Earth remote sensing applications (snow, soil moisture/land parameters, precipitation, ocean winds, sea surface temperature, water vapor, sea ice, etc.). The microwave radiometers themselves will incorporate state-of-the-art receivers, with particular attention given to instrument calibration for the best possible accuracy and sensitivity. The single-package design of AESMIR makes it compatible with high-altitude aircraft platforms such as the NASA ER-2s. The arbitrary 2-axis gimbal can perform conical and cross-track scanning, as well as fixed-beam staring. This compatibility with high-altitude platforms coupled with the flexible scanning configuration, opens up previously unavailable science opportunities for convection/precip/cloud science and co-flying with complementary instruments, as well as providing wider swath coverage for all science applications. By designing AESMIR to be compatible with these high-altitude platforms, we are also compatible with the NASA P-3, the NASA DC-8, C-130s and ground-based deployments. Thus AESMIR can provide low-, mid-, and high- altitude microwave imaging. Parallel filter banks allow AESMIR to simultaneously simulate the exact passbands of multiple satellite radiometers: SSM/I, TMI, AMSR, Windsat, SSMI/S, and the upcoming GPM/GMI and NPOESS/CMIS instruments --a unique capability among aircraft radiometers. An L-band option is also under development, again using the same scanner. With this option, simultaneous imaging from 1.4 to 89 GHz will be feasible. And, all receivers except the sounding channels will be configured for 4-Stokes polarimetric operation using high-speed digital

  8. A comparison of real and simulated airborne multisensor imagery

    NASA Astrophysics Data System (ADS)

    Bloechl, Kevin; De Angelis, Chris; Gartley, Michael; Kerekes, John; Nance, C. Eric

    2014-06-01

    This paper presents a methodology and results for the comparison of simulated imagery to real imagery acquired with multiple sensors hosted on an airborne platform. The dataset includes aerial multi- and hyperspectral imagery with spatial resolutions of one meter or less. The multispectral imagery includes data from an airborne sensor with three-band visible color and calibrated radiance imagery in the long-, mid-, and short-wave infrared. The airborne hyperspectral imagery includes 360 bands of calibrated radiance and reflectance data spanning 400 to 2450 nm in wavelength. Collected in September 2012, the imagery is of a park in Avon, NY, and includes a dirt track and areas of grass, gravel, forest, and agricultural fields. A number of artificial targets were deployed in the scene prior to collection for purposes of target detection, subpixel detection, spectral unmixing, and 3D object recognition. A synthetic reconstruction of the collection site was created in DIRSIG, an image generation and modeling tool developed by the Rochester Institute of Technology, based on ground-measured reflectance data, ground photography, and previous airborne imagery. Simulated airborne images were generated using the scene model, time of observation, estimates of the atmospheric conditions, and approximations of the sensor characteristics. The paper provides a comparison between the empirical and simulated images, including a comparison of achieved performance for classification, detection and unmixing applications. It was found that several differences exist due to the way the image is generated, including finite sampling and incomplete knowledge of the scene, atmospheric conditions and sensor characteristics. The lessons learned from this effort can be used in constructing future simulated scenes and further comparisons between real and simulated imagery.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. Naval hyperspectral remote sensing research for the oceans, atmosphere, and space

    NASA Astrophysics Data System (ADS)

    McCoy, Robert P.; Cleveland, Joan S.; Ferek, Ronald J.

    2004-10-01

    To meet Naval needs for sensing of the global environment, the Office of Naval Research (ONR) and the Naval Research Laboratory (NRL) sponsor or carry out a variety of research programs using hyperspectral sensing. For ocean sensing, airborne and space-borne hyperspectral sensors are used to characterize the littoral environment with the aim of providing specification of ocean optical parameters including water clarity, diver visibility, bathymetry, bottom type and beach characterization. For the atmosphere, the Navy has interest in hyperspectral remote sensing from geosynchronous orbit. ONR interests include improved modeling of radiation transport in the atmosphere to infer high resolution profiles of wind, temperature and minor species and cloud characteristics. With sponsorship from Director Defense Research and Engineering (DDR&E), ONR is managing a Multidisciplinary University Research Initiative (MURI) to provide new models for use with geosynchronous data. In partnership with NASA, NOAA and the Air Force, ONR is promoting the flight of the Geosynchronous Imaging Fourier Transform Spectrometer-Indian Ocean METOC Imager (GIFTS-IOMI) program to obtain hyperspectral atmospheric imagery with high spatial, spectral and temporal resolution. For the space environment, NRL has flown a suite of experimental ultraviolet hyperspectral sensors to determine altitude profiles of the ionospheric electron density and upper atmospheric neutral density. The High Resolution Airglow/Aurora Spectroscopy (HIRAAS) experiment on the ARGOS satellite provided a proof of concept for a future series of hyperspectral ultraviolet space weather sensors the first of which has recently been launch on a DMSP weather satellite. ONR is sponsoring the development of a multispectral ultraviolet imager to take this capability to geosynchronous orbit.

  17. 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.

  18. 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...

  19. 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.

  20. 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.

  1. Hyperspectral image classification using functional data analysis.

    PubMed

    Li, Hong; Xiao, Guangrun; Xia, Tian; Tang, Y Y; Li, Luoqing

    2014-09-01

    The large number of spectral bands acquired by hyperspectral imaging sensors allows us to better distinguish many subtle objects and materials. Unlike other classical hyperspectral image classification methods in the multivariate analysis framework, in this paper, a novel method using functional data analysis (FDA) for accurate classification of hyperspectral images has been proposed. The central idea of FDA is to treat multivariate data as continuous functions. From this perspective, the spectral curve of each pixel in the hyperspectral images is naturally viewed as a function. This can be beneficial for making full use of the abundant spectral information. The relevance between adjacent pixel elements in the hyperspectral images can also be utilized reasonably. Functional principal component analysis is applied to solve the classification problem of these functions. Experimental results on three hyperspectral images show that the proposed method can achieve higher classification accuracies in comparison to some state-of-the-art hyperspectral image classification methods.

  2. Concept for an airborne real-time ISR system with multi-sensor 3D data acquisition

    NASA Astrophysics Data System (ADS)

    Haraké, Laura; Schilling, Hendrik; Blohm, Christian; Hillemann, Markus; Lenz, Andreas; Becker, Merlin; Keskin, Göksu; Middelmann, Wolfgang

    2016-10-01

    In modern aerial Intelligence, Surveillance and Reconnaissance operations, precise 3D information becomes inevitable for increased situation awareness. In particular, object geometries represented by texturized digital surface models constitute an alternative to a pure evaluation of radiometric measurements. Besides the 3D data's level of detail aspect, its availability is time-relevant in order to make quick decisions. Expanding the concept of our preceding remote sensing platform developed together with OHB System AG and Geosystems GmbH, in this paper we present an airborne multi-sensor system based on a motor glider equipped with two wing pods; one carries the sensors, whereas the second pod downlinks sensor data to a connected ground control station by using the Aerial Reconnaissance Data System of OHB. An uplink is created to receive remote commands from the manned mobile ground control station, which on its part processes and evaluates incoming sensor data. The system allows the integration of efficient image processing and machine learning algorithms. In this work, we introduce a near real-time approach for the acquisition of a texturized 3D data model with the help of an airborne laser scanner and four high-resolution multi-spectral (RGB, near-infrared) cameras. Image sequences from nadir and off-nadir cameras permit to generate dense point clouds and to texturize also facades of buildings. The ground control station distributes processed 3D data over a linked geoinformation system with web capabilities to off-site decision-makers. As the accurate acquisition of sensor data requires boresight calibrated sensors, we additionally examine the first steps of a camera calibration workflow.

  3. 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.

  4. Simulation of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

  5. Hyperspectral Systems Increase Imaging Capabilities

    NASA Technical Reports Server (NTRS)

    2010-01-01

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

  6. 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...

  7. 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.

  8. Hyperspectral Imagery Classification Using a Backpropagation Neural Network

    DTIC Science & Technology

    1993-12-01

    A backpropagation neural network was developed and implemented for classifying AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) hyperspectral...imagery. It is a fully interconnected linkage of three layers of neural network . Fifty input layer neurons take in signals from Bands 41 to 90 of the...moderate AVIRIS pixel resolution of 20 meters by 20 meters. Backpropagation neural network , Hyperspectral imagery

  9. 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

  10. Oil Slick Detection and Characterization by Satellite and Airborne Sensors: Experimental Results with SAR, Hyperspectral and Lidar Data

    DTIC Science & Technology

    2005-07-25

    www.actimar.fr †AS Laser Diagnostic Instruments 113A Kadaka Str. 2915 Tallin - Estonia sergeyb@ldi.ee ‡GET/ENST Bretagne , dpt ITI, TAMCIC, team TIME, CNRS UMR...specialized in operational oceanography and high resolution remote sensing, in collaboration with GET/ENST- Bretagne and is funded by the RITMER program

  11. 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

  12. 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.

  13. 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.

  14. Clusters versus GPUs for Parallel Target and Anomaly Detection in Hyperspectral Images

    NASA Astrophysics Data System (ADS)

    Paz, Abel; Plaza, Antonio

    2010-12-01

    Remotely sensed hyperspectral sensors provide image data containing rich information in both the spatial and the spectral domain, and this information can be used to address detection tasks in many applications. In many surveillance applications, the size of the objects (targets) searched for constitutes a very small fraction of the total search area and the spectral signatures associated to the targets are generally different from those of the background, hence the targets can be seen as anomalies. In hyperspectral imaging, many algorithms have been proposed for automatic target and anomaly detection. Given the dimensionality of hyperspectral scenes, these techniques can be time-consuming and difficult to apply in applications requiring real-time performance. In this paper, we develop several new parallel implementations of automatic target and anomaly detection algorithms. The proposed parallel algorithms are quantitatively evaluated using hyperspectral data collected by the NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) system over theWorld Trade Center (WTC) in New York, five days after the terrorist attacks that collapsed the two main towers in theWTC complex.

  15. [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.

  16. Hyperspectral fundus imager

    NASA Astrophysics Data System (ADS)

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

    2000-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

    The growth of the small satellite market and launch opportunities for these satellites is creating a new niche for earth observations that contrasts with the long mission durations, high costs, and long development times associated with traditional space-based earth observations. Low-cost, short-lived missions made possible by this new approach provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off-the-shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCoR), to demonstrate ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power-efficient thermal hyperspectral imager with electronics contained in a pressure vessel to enable use of COTS electronics and will be compatible with small satellite platforms. The sensor, called Thermal Hyperspectral Imager (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230 meter pixels with 20 wavenumber spectral resolution from a 400 km orbit. We are currently in the laboratory and airborne testing stage in order to demonstrate the spectro-radiometric quality of data that the instrument provides.

  18. 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.

  19. 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...

  20. 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.

  1. Soil Moisture Estimation Using Hyperspectral SWIR Imagery

    NASA Astrophysics Data System (ADS)

    Lewis, D.

    2007-12-01

    The U.S. Geological Survey (USGS) is engaged with the U.S. Department of Agriculture's (USDA) Agricultural Research Service (ARS) and the University of Georgia's National Environmentally Sound Production Agriculture Laboratory (NESPAL) both in Tifton, Georgia, USA, to develop transformations for medium and high resolution remotely sensed images to generate moisture indicators for soil. The Institute for Technology Development (ITD) is located at the Stennis Space Center in southern Mississippi and has developed hyperspectral sensor systems that, when mounted in aircraft, collect electromagnetic reflectance data of the terrain. The sensor suite consists of sensors for three different sections of the electromagnetic spectrum; the Ultra-Violet (UV), Visible/Near InfraRed (VNIR) and Short Wave InfraRed (SWIR). The USDA/ ARS' Southeast Watershed Research Laboratory has probes that measure and record soil moisture. Data taken from the ITD SWIR sensor and the USDA/ARS soil moisture meters were analyzed to study the informatics relationships between SWIR data and measured soil moisture. The geographic locations of 29 soil moisture meters provided by the USDA/ARS are in the vicinity of Tifton, Georgia. Using USGS Digital Ortho Quads (DOQ), flightlines were drawn over the 29 soil moisture meters. The SWIR sensor was installed into an aircraft. The coordinates for the flightlines were also loaded into the navigational system of the aircraft. This airborne platform was used to collect the data over these flightlines. In order to prepare the data set for analysis, standard preprocessing was performed. These standard processes included sensor calibration, spectral subsetting, and atmospheric calibration. All 60 bands of the SWIR data were collected for each line in the image data, 15 bands of which were stripped from the data set leaving 45 bands of information in the wavelength range of 906 to 1705 nanometers. All the image files were calibrated using the regression equations

  2. Uncooled long-wave infrared hyperspectral imaging

    NASA Technical Reports Server (NTRS)

    Lucey, Paul G. (Inventor)

    2006-01-01

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

  3. 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.

  4. TRACE-P OH and HO2 Measurements with the Airborne Tropospheric Hydrogen Oxides Sensor (ATHOS) on the DC-8

    NASA Technical Reports Server (NTRS)

    Brune, William H.; Martinez-Harder, Monica; Harder, Hartwig

    2004-01-01

    The Airborne Tropospheric Hydrogen Oxides Sensor (ATHOS) measures OH and HO2 from the NASA DC-8. This instrument detects OH by laser induced fluorescence (LIF) in detection chambers at low pressure and detects HO2 by chemical conversion with NO followed by LIF detection. The demonstrated detection limit (S/N=2, 5 min.) for OH is about 0.005 pptv (1x10(exp 6)/cu cm at 2 km altitude) and for HO2 is 0.05 pptv (1x10(exp 6)/cu cm at 2 km altitude). We will use ATHOS to measure OH, HO2, and HO2/OH during TRACE- P, analyze these results by comparing them against fundamental relationships and computer models, and publish the analyses. TRACE-P HO(x), measurements will help develop a clearer picture of the atmospheric oxidation and 0 3 production that occur as Asian pollution spreads across the Pacific Ocean.

  5. 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.

  6. Vine variety discrimination with airborne imaging spectroscopy

    NASA Astrophysics Data System (ADS)

    Ferreiro-Armán, M.; Alba-Castro, J. L.; Homayouni, S.; da Costa, J. P.; Martín-Herrero, J.

    2007-09-01

    We aim at the discrimination of varieties within a single plant species (Vitis vinifera) by means of airborne hyperspectral imagery collected using a CASI-2 sensor and supervised classification, both under constant and varying within-scene illumination conditions. Varying illumination due to atmospheric conditions (such as clouds) and shadows cause different pixels belonging to the same class to present different spectral vectors, increasing the within class variability and hindering classification. This is specially serious in precision applications such as variety discrimination in precision agriculture, which depends on subtle spectral differences. In this study, we use machine learning techniques for supervised classification, and we also analyze the variability within and among plots and within and among sites, in order to address the generalizability of the results.

  7. Wireless Source Localization and Signal Collection from an Airborne Symmetric Line Array Sensor Network

    DTIC Science & Technology

    2014-09-01

    predictions, covert sensors could be deployed along known supply lines to monitor enemy troop movements, or RFID sensors could be 8 deployed throughout a...ICACT, Phoenix Park, Korea, Feb. 2009. [28] W. ying and W. Kaixi, “The building of logistics management system using RFID and WSN technology

  8. Application of Hyperspectral Methods in Hydrothermal Mineral System Studies

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  10. 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.

  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. 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

  14. 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

  15. The technique flows of target detection using thermal infrared hyperspectral remote sensing

    NASA Astrophysics Data System (ADS)

    Wu, Wen Huan; Yu, Hong; Huang, Shu Tao

    2016-10-01

    In this work, the workflow of airborne thermal infrared hyperspectral technology in the actual application process is reviewed. Using the Thermal Airborne Spectrographic Imager (TASI-600), a hyperspectral thermal infrared imager manufactured by ITRES Research Limited as a case study, the work process including instrument calibration, collecting the region information of interest, data processing and analysis is elaborated. The value and effect using thermal infrared data obtained through TASI-600 is demonstrated. This work provides ideas and references for further study and investigation on the application of airborne thermal infrared hyperspectral remote sensing.

  16. New optical sensor systems for high-resolution satellite, airborne and terrestrial imaging systems

    NASA Astrophysics Data System (ADS)

    Eckardt, Andreas; Börner, Anko; Lehmann, Frank

    2007-10-01

    The department of Optical Information Systems (OS) at the Institute of Robotics and Mechatronics of the German Aerospace Center (DLR) has more than 25 years experience with high-resolution imaging technology. The technology changes in the development of detectors, as well as the significant change of the manufacturing accuracy in combination with the engineering research define the next generation of spaceborne sensor systems focusing on Earth observation and remote sensing. The combination of large TDI lines, intelligent synchronization control, fast-readable sensors and new focal-plane concepts open the door to new remote-sensing instruments. This class of instruments is feasible for high-resolution sensor systems regarding geometry and radiometry and their data products like 3D virtual reality. Systemic approaches are essential for such designs of complex sensor systems for dedicated tasks. The system theory of the instrument inside a simulated environment is the beginning of the optimization process for the optical, mechanical and electrical designs. Single modules and the entire system have to be calibrated and verified. Suitable procedures must be defined on component, module and system level for the assembly test and verification process. This kind of development strategy allows the hardware-in-the-loop design. The paper gives an overview about the current activities at DLR in the field of innovative sensor systems for photogrammetric and remote sensing purposes.

  17. Estimating woody aboveground biomass in an area of agroforestry using airborne light detection and ranging and compact airborne spectrographic imager hyperspectral data: individual tree analysis incorporating tree species information

    NASA Astrophysics Data System (ADS)

    Wang, Zhihui; Liu, Liangyun; Peng, Dailiang; Liu, Xinjie; Zhang, Su; Wang, Yingjie

    2016-07-01

    Until now, there have been only a few studies that have made estimates of the woody aboveground biomass (AGB) in an area of agroforestry using remote sensing technology. The woody AGB density was estimated using individual tree analysis (ITA) that incorporated tree species information using a combination of airborne light detection and ranging (LiDAR) and compact airborne spectrographic imagery acquired over a typical agroforestry in northwestern China. First, a series of improved LiDAR processing algorithms was applied to achieve individual tree segmentation, and accurate plot-level canopy heights and crown diameters were obtained. The individual tree species were then successfully classified using both spectral and shape characteristics with an overall accuracy of 0.97 and a kappa coefficient of 0.85. Finally, the tree-level AGB (kg) was estimated based on the ITA; the AGB density (Mg/ha) was then upscaled based on the tree-level AGB values. It is concluded that, compared with the commonly used area-based method combining LiDAR and spectral metrics [root mean square error (RMSE)=19.58 Mg/ha], the ITA method performs better at estimating AGB density (RMSE=10.56 Mg/ha). The tree species information also improved the accuracy of the AGB estimation even though the species are not well diversified in this study area.

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  20. New generation handheld hyperspectral imager

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  1. 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.

  2. 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.

  3. 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.

  4. Hyperspectral imaging—An advanced instrument concept for the EnMAP mission (Environmental Mapping and Analysis Programme)

    NASA Astrophysics Data System (ADS)

    Stuffler, Timo; Förster, Klaus; Hofer, Stefan; Leipold, Manfred; Sang, Bernhard; Kaufmann, Hermann; Penné, Boris; Mueller, Andreas; Chlebek, Christian

    2009-10-01

    In the upcoming generation of satellite sensors, hyperspectral instruments will play a significant role. This payload type is considered world-wide within different future planning. Our team has now successfully finalized the Phase B study for the advanced hyperspectral mission EnMAP (Environmental Mapping and Analysis Programme), Germans next optical satellite being scheduled for launch in 2012. GFZ in Potsdam has the scientific lead on EnMAP, Kayser-Threde in Munich is the industrial prime. The EnMAP instrument provides over 240 continuous spectral bands in the wavelength range between 420 and 2450 nm with a ground resolution of 30 m×30 m. Thus, the broad science and application community can draw from an extensive and highly resolved pool of information supporting the modeling and optimization process on their results. The performance of the hyperspectral instrument allows for a detailed monitoring, characterization 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 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.

  5. Hyperspectral data discrimination methods

    NASA Astrophysics Data System (ADS)

    Casasent, David P.; Chen, Xuewen

    2000-12-01

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

  6. 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).

  7. Airborne cable detection with a W-band FMCW imaging sensor

    NASA Astrophysics Data System (ADS)

    Goshi, D. S.; Liu, Y.; Mai, K.; Bui, L.; Shih, Y.

    2010-04-01

    Numerous accidents occur each year due to wire strikes for both military and commercial helicopters leading to a significant number of fatalities. The millimeter-wave sensor presents itself as an ideal candidate for a solution because it can see the very small attributes of the typical power line/cable wire as well as operate when visual conditions worsen due to environmental issues such as fog, smoke or dust. This paper presents recent results on the development of a W-band FMCW imaging sensor with potential application to cable detection and imaging. The sensor front end is integrated with a radar signal generator, processor, and data acquisition unit for the purpose of closing the loop between prototype demonstration and system development. Real-time imaging is achieved at a 10 Hz frame rate with a field of view of 30°. A complete flight demonstration of this system was performed on a Honeywell-operated AStar helicopter to validate the flight-worthiness of the sensor under close to actual operational conditions. The development of such technology that can detect and avoid obstacles such as cables and wires especially for rotorcraft platforms will save lives, assets, and enable the execution of more complex and dangerous tactical missions.

  8. 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

  9. 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

  10. 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.

  11. Thick sections of layered ultramafic cumulates in the Oman ophiolite revealed by an airborne hyperspectral survey: Petrogenesis and relationship to mantle diapirism

    NASA Astrophysics Data System (ADS)

    Clénet, Harold; Ceuleneer, Georges; Pinet, Patrick; Abily, Bénédicte; Daydou, Yves; Harris, Esther; Amri, Isma; Dantas, Céline

    2010-02-01

    Using the HyMap instrument, we have acquired visible and near infrared hyperspectral data over the Maqsad area of the Oman ophiolite (~ 15 × 60 km). This survey allowed us to identify and map the distribution of clinopyroxene-rich cumulates (inter-layered clinopyroxenites and wehrlites) whose occurrence was previously undocumented in this area. The cumulates reach several hundred meters in thickness and crop out at distances exceeding 15 km on both sides of the Maqsad former spreading centre. They occur either in mantle harzburgites, as km-sized layered intrusions surrounded by fields of pegmatitic dykes consisting of orthopyroxene-rich pyroxenite and gabbronorites, or at the base of the crustal section where they are conformably overlain by cumulate gabbros. These ultramafic cumulates crystallized from silica- and Mg-rich melts derived from a refractory mantle source (e.g. high Cr#, low [Al 2O 3], low [TiO 2]). These melts are close to high-Ca boninites, although, strictly speaking, not perfect equivalents of present-day, supra-subduction zone, boninites. Chemical stratigraphy reveals cycles of replenishment, mixing and fractional crystallization from primitive (high Mg#) melts, typical of open magma chambers and migration of inter-cumulus melts. The TiO 2 content of clinopyroxene is always low (≤ 0.2 wt.%) but quite variable compared to the associated pegmatites that are all derived from a source ultra-depleted in high field strength elements (HFSE). This variability is not caused by fractional crystallization alone, and is best explained by hybridization between the ultra-depleted melts (parent melts of the pegmatites) and the less depleted mid-ocean ridge basalts (MORB) parent of the dunitic-troctolitic-gabbroic cumulates making up the crustal section above the Maqsad diapir. We propose that, following a period of magma-starved spreading, the Maqsad mantle diapir, impregnated with tholeiitic melts of MORB affinity, reached shallow depths beneath the ocean

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

    DOE PAGES

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

    2016-03-31

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

  13. 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.

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

    SciTech Connect

    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 interest 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.

  15. 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.

  16. Low-cost lightweight airborne laser-based sensors for pipeline leak detection and reporting

    NASA Astrophysics Data System (ADS)

    Frish, Michael B.; Wainner, Richard T.; Laderer, Matthew C.; Allen, Mark G.; Rutherford, James; Wehnert, Paul; Dey, Sean; Gilchrist, John; Corbi, Ron; Picciaia, Daniele; Andreussi, Paolo; Furry, David

    2013-05-01

    Laser sensing enables aerial detection of natural gas pipeline leaks without need to fly through a hazardous gas plume. This paper describes adaptations of commercial laser-based methane sensing technology that provide relatively low-cost lightweight and battery-powered aerial leak sensors. The underlying technology is near-infrared Standoff Tunable Diode Laser Absorption Spectroscopy (sTDLAS). In one configuration, currently in commercial operation for pipeline surveillance, sTDLAS is combined with automated data reduction, alerting, navigation, and video imagery, integrated into a single-engine single-pilot light fixed-wing aircraft or helicopter platform. In a novel configuration for mapping landfill methane emissions, a miniaturized ultra-lightweight sTDLAS sensor flies aboard a small quad-rotor unmanned aerial vehicle (UAV).

  17. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS): Recent improvements to the sensor

    NASA Technical Reports Server (NTRS)

    Chrien, Thomas G.; Green, Robert O.; Sarture, Charles M.; Chovit, Christopher; Eastwood, Michael L.; Eng, Bjorn T.

    1993-01-01

    AVIRIS is a NASA-sponsored Earth-looking imaging spectrometer designed, built and operated by the Jet Propulsion Laboratory. Spectral, radiometric and geometric characteristics of the data acquired by AVIRIS are given in Table 1. AVIRIS has been operational since 1989, however in each year since 1989 major improvements have been completed in most of the subsystems of the sensor. As a consequence of these efforts, the capabilities of AVIRIS to acquire and deliver calibrated imaging spectrometer data of high quality have improved significantly over those in 1989. Improvements to AVIRIS prior to 1992 have been described previously (Porter et al., 1990, Chrien et al., 1991, & Chrien et al., 1992). In the following sections of this paper we describe recent and planned improvements to AVIRIS in the sensor task.

  18. 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.

  19. 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.

  20. Data assimilation of an airborne multiple-remote-sensor system and of satellite images for the North Sea and Baltic Sea

    NASA Astrophysics Data System (ADS)

    Trieschmann, Olaf; Hunsaenger, Thomas; Tufte, Lars; Barjenbruch, Ulrich

    2004-02-01

    Marine pollution in the sensible North and Baltic Sea forces an international aerial surveillance. Within this framework the German aerial surveillance operates an advanced instrumentation on board of two 'Dornier 228" aircrafts. The instrumentation consists of a set of state-of-the-art imaging remote sensors, like side looking airborne radar (SLAR), IR/UV line scanner and particularly a microwave radiometer (MWR) and a laser-fluoro-sensor (LFS). The most important aim is to detect oil discharges on the water surface, emitted accidentally or illegally. In case of discharge, the pollution has to be classified and quantified with a high accuracy. Another aim is to monitor biological and hydrological parameters, as there are the concentration of chlorophyll and dissolved organic matter (DOM) or the growth of phytoplancton. This paper describes the set of instruments and their potential to fulfill these demands. The SLAR operates to locate oil discharges and phytoplancton, whereas the IR/UV scanner allows to distinct the detected area. The IR/UV and especially the MWR sensor allow to quantify the thickness of the oil film. Finally, the LFS classifies the oil species as well as organic material. Emphasis is placed on the results of the sensor measurements and their synergy effects. The combination of the sensor data yields value added information for the operational users. An use of satellite data to improve the operational surveillance will be discussed. The potential and limitations of satellite and airborne data for the surveillance tasks will be compared.

  1. Perceptual Based Image Fusion with Applications to Hyperspectral Image Data.

    DTIC Science & Technology

    1994-12-01

    spectral bands from the AVIRIS hyperspectral sensor will be evaluated. 1.4 Approach/ Thesis Organization Chapter one described data processing problems...Based Image Fusion with Applications to Hyperspectral Image Data THESIS A o .:or \\Terry Allen Wilson NTS _ Captain, USAF DTIC Tf-, LI Unannou!c<ej LI...Applications to Hyperspectral Image Data THESIS Presented to the Faculty of the Graduate School of Engineering of the Air Force Institute of

  2. Recent development of hyperspectral LiDAR using supercontinuum laser

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Li, Chuanrong; Zhou, Mei; Zhang, Huijing; He, Wenjing; Li, Wei; Qiu, Yuanyuan

    2016-10-01

    Hyperspectral Light Detection And Ranging (Hyperspectral LiDAR), a recently developed technique, combines the advantages of the LiDAR and hyperspectral imaging and has been attractive for many applications. Supercontinuum laser (SC laser), a rapidly developing technique offers hyperspectral LiDAR a suitable broadband laser source and makes hyperspectral Lidar become an installation from a theory. In this paper, the recent research and progressing of the hyperspectral LiDAR are reviewed. The hyperspectral LiDAR has been researched in theory, prototype system, instrument, and application experiment. However, the pulse energy of the SC laser is low so that the range of the hyperspectral LiDAR is limited. Moreover, considering the characteristics of sensors and A/D converter, in order to obtain the full waveform of the echo, the repetition rate and the pulse width of the SC laser needs to be limited. Recently, improving the detection ability of hyperspectral LiDAR, especially improving the detection range, is a main research area. A higher energy pulse SC laser, a more sensitive sensor, or some algorithms are applied in hyperspectral LiDAR to improve the detection distance from 12 m to 1.5 km. At present, a lot of research has been focused on this novel technology which would be applied in more applications.

  3. 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.

  4. A new hyperspectral image compression paradigm based on fusion

    NASA Astrophysics Data System (ADS)

    Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

    2016-10-01

    The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

  5. 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

  6. 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...

  7. 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...

  8. 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.

  9. 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

  10. 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.

  11. Isograde mapping and mineral identification on the island of Naxos, Greece, using DAIS 7915 hyperspectral data

    NASA Astrophysics Data System (ADS)

    Echtler, Helmut; Segl, Karl; Dickerhof, Corinna; Chabrillat, Sabine; Kaufmann, Hermann J.

    2003-03-01

    The ESF-LSF 1997 flight campaign conducted by the German Aerospace Center (DLR) recorded several transects across the island of Naxos using the airborne hyperspectral scanner DAIS. The geological targets cover all major litho-tectonic units of a metamorphic dome with the transition of metamorphic zonations from the outer meta-sedimentary greenschist envelope to the gneissic amphibolite facies and migmatitic core. Mineral identification of alternating marble-dolomite sequences and interlayered schists bearing muscovite and biotite has been accomplished using the airborne hyperspectral DAIS 7915 sensor. Data have been noise filtered based on maximum noise fraction (MNF) and fast Fourier transform (FFT) and converted from radiance to reflectance. For mineral identification, constrained linear spectral unmixing and spectral angle mapper (SAM) algorithms were tested. Due to their unsatisfying results a new approach was developed which consists of a linear mixture modeling and spectral feature fitting. This approach provides more detailed and accurate information. Results are discussed in comparison with detailed geological mapping and additional information. Calcites are clearly separated from dolomites as well as the mica-schist sequences by a good resolution of the mineral muscovite. Thereon an outstanding result represents the very good resolution of the chlorite/mica (muscovite, biotite)-transition defining a metamorphic isograde.

  12. 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.

  13. Airborne Coherent Lidar for Advanced In-Flight Measurements (ACLAIM) Flight Testing of the Lidar Sensor

    NASA Technical Reports Server (NTRS)

    Soreide, David C.; Bogue, Rodney K.; Ehernberger, L. J.; Hannon, Stephen M.; Bowdle, David A.

    2000-01-01

    The purpose of the ACLAIM program is ultimately to establish the viability of light detection and ranging (lidar) as a forward-looking sensor for turbulence. The goals of this flight test are to: 1) demonstrate that the ACLAIM lidar system operates reliably in a flight test environment, 2) measure the performance of the lidar as a function of the aerosol backscatter coefficient (beta), 3) use the lidar system to measure atmospheric turbulence and compare these measurements to onboard gust measurements, and 4) make measurements of the aerosol backscatter coefficient, its probability distribution and spatial distribution. The scope of this paper is to briefly describe the ACLAIM system and present examples of ACLAIM operation in flight, including comparisons with independent measurements of wind gusts, gust-induced normal acceleration, and the derived eddy dissipation rate.

  14. 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

  15. 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.

  16. Airborne Navigation Sensors Using The Global Positioning System (GPS) / Precise Positioning Service (PPS) for Area Navigation (RNAV) in Required Navigation Performance (RNP) Airspace; RNP-20 RNAV Through RNP-0.3 RNAV

    DTIC Science & Technology

    2010-02-11

    GLOBAL POSITIONING SYSTEM ( GPS ) I PRECISE POSITIONING SERVICE (PPS) FOR AREA NAVIGATION (RNA...Navigation Sensors Using The Global Positioning System ( GPS ) / Precise Positioning Service (PPS) For Area Navigation (RNAV) In Required Navigation...Rev. 8-98) Prescribed by ANSI Std Z39-18 Subject: MSO-C145, AIRBORNE NAVIGATION SENSORS USING THE GLOBAL POSITIONING SYSTEM ( GPS

  17. Hyperspectral imaging simulation of object under sea-sky background

    NASA Astrophysics Data System (ADS)

    Wang, Biao; Lin, Jia-xuan; Gao, Wei; Yue, Hui

    2016-10-01

    Remote sensing image simulation plays an important role in spaceborne/airborne load demonstration and algorithm development. Hyperspectral imaging is valuable in marine monitoring, search and rescue. On the demand of spectral imaging of objects under the complex sea scene, physics based simulation method of spectral image of object under sea scene is proposed. On the development of an imaging simulation model considering object, background, atmosphere conditions, sensor, it is able to examine the influence of wind speed, atmosphere conditions and other environment factors change on spectral image quality under complex sea scene. Firstly, the sea scattering model is established based on the Philips sea spectral model, the rough surface scattering theory and the water volume scattering characteristics. The measured bi directional reflectance distribution function (BRDF) data of objects is fit to the statistical model. MODTRAN software is used to obtain solar illumination on the sea, sky brightness, the atmosphere transmittance from sea to sensor and atmosphere backscattered radiance, and Monte Carlo ray tracing method is used to calculate the sea surface object composite scattering and spectral image. Finally, the object spectrum is acquired by the space transformation, radiation degradation and adding the noise. The model connects the spectrum image with the environmental parameters, the object parameters, and the sensor parameters, which provide a tool for the load demonstration and algorithm development.

  18. 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.

  19. Airborne observations of bioaerosol over the Southeast United States using a Wideband Integrated Bioaerosol Sensor

    NASA Astrophysics Data System (ADS)

    Ziemba, Luke D.; Beyersdorf, Andreas J.; Chen, Gao; Corr, Chelsea A.; Crumeyrolle, Suzanne N.; Diskin, Glenn; Hudgins, Charlie; Martin, Robert; Mikoviny, Tomas; Moore, Richard; Shook, Michael; Thornhill, K. Lee; Winstead, Edward L.; Wisthaler, Armin; Anderson, Bruce E.

    2016-07-01

    Biological aerosols represent a diverse subset of particulate matter that is emitted directly to the atmosphere in the form of (but not limited to) bacteria, fungal spores, pollens, viruses, and plant debris. These particles can have local air quality implications, but potentially play a larger climate role by acting as efficient ice nucleating particles (INPs) and cloud condensation nuclei. We have deployed a Wideband Integrated Bioaerosol Sensor on the NASA DC-8 aircraft to (1) quantify boundary layer (BL) variability of fluorescent biological aerosol particle (FBAP) concentrations in the Southeast United States (SEUS), (2) link this variability explicitly to land cover heterogeneity in the region, and (3) examine the vertical profile of bioaerosols in the context of convective vertical redistribution. Flight-averaged FBAP concentrations ranged between 0.1 and 0.43 scm-3 (cm-3 at standard temperature and pressure) with relatively homogeneous concentrations throughout the region; croplands showed the highest concentrations in the BL (0.37 scm-3), and lowest concentrations were associated with evergreen forests (0.24 scm-3). Observed FBAP concentrations are in generally good agreement with model parameterized emission rates for bacteria, and discrepancies are likely the result of fungal spore contributions. Shallow convection in the region is shown to be a relatively efficient lofting mechanism as the vertical transport efficiency of FBAP is at least equal to black carbon aerosol, suggesting that ground-level FBAP survives transport into the free troposphere to be available for INP activation. Comparison of the fraction of coarse-mode particles that were biological (fFBAP) suggested that the SEUS (fFBAP = 8.5%) was a much stronger source of bioaerosols than long-range transport during a Saharan Air Layer (SAL) dust event (fFBAP = 0.17%) or summertime marine emissions in the Gulf of Mexico (fFBAP = 0.73%).

  20. Hyperspectral Imaging of River Systems

    DTIC Science & Technology

    2010-09-30

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

  1. Toward Improved Hyperspectral Analysis in Semiarid Systems

    NASA Astrophysics Data System (ADS)

    Glenn, N. F.; Mitchell, J.

    2012-12-01

    Idaho State University's Boise Center Aerospace Laboratory (BCAL) has processed and applied hyperspectral data for a variety of biophysical sciences in semiarid systems over the past 10 years. HyMap hyperspectral data have been used in most of these studies, along with AVIRIS, CASI, and PIKA-II data. Our studies began with the detection of individual weed species, such as leafy spurge, corroborated with extensive field analysis, including spectrometer data. Early contributions to the field of hyperspectral analysis included the use of: time-series datasets and classification threshold methods for target detection, and subpixel analysis for characterizing weed invasions and post-fire vegetation and soil conditions. Subsequent studies optimized subpixel unmixing performance using spectral subsetting and vegetation abundance investigations. More recent studies have extended the application of hyperspectral data from individual plant species detection to identification of biochemical constituents. We demonstrated field and airborne hyperspectral Nitrogen absorption in sagebrush using combinations of data reduction and spectral transformation techniques (i.e., continuum removal, derivative analysis, partial least squares regression). In spite of these and many other successful demonstrations, gaps still exist in effective species level discrimination due to the high complexity of soil and nonlinear mixing in semiarid shrubland. BCAL studies are currently focusing on complimenting narrowband vegetation indices with LiDAR (light detection and ranging, both airborne and ground-based) derivatives to improve vegetation cover predictions. Future combinations of LiDAR and hyperspectral data will involve exploring the full range spectral information and serve as an integral step in scaling shrub biomass estimates from plot to landscape and regional scales.

  2. Fractal Characterization of Hyperspectral Imagery

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. An algorithm of remotely sensed hyperspectral image fusion based on spectral unmixing and feature reconstruction

    NASA Astrophysics Data System (ADS)

    Sun, Xuejian; Zhang, Lifu; Cen, Yi; Zhang, Mingyue

    2016-05-01

    In order to get high spatial resolution hyperspectral data, many studies have examined methods to combine spectral information contained in hyperspectral image with spatial information contained in multispectral/panchromatic image. This paper developed a new hyperspectral image fusion method base on the non-negative matrix factorization (NMF) theory. Data sets obtained by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) was used to evaluate the performance of the method. Experimental results show that the proposed algorithm can provide a good way to solve the problem of high spatial resolution hyperspectral data shortage.

  10. 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.

  11. 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.

  12. 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.

  13. Exploitation of Intra-Spectral Band Correlation for Rapid Feature Selection, and Target Identification in Hyperspectral Imagery

    DTIC Science & Technology

    2009-03-01

    entitled “Improved Feature Extraction, Feature Selection, and Identification Techniques that Create a Fast Unsupervised Hyperspectral Target Detection...thesis proposal “Improved Feature Extraction, Feature Selection, and Identification Techniques that Create a Fast Unsupervised Hyperspectral Target...target or non-target classifications . Integration of this type of autonomous target detection algorithm along with hyperspectral imaging sensors

  14. 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

  15. Hyperspectral image processing methods

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. Developing a portable GPU library for hyperspectral image processing

    NASA Astrophysics Data System (ADS)

    Pérez-Irizarry, Gabriel J.; De La Cruz-Sanchez, Francisco; Landrón-Rivera, Brian A.; Santiago, Nayda G.; Velez-Reyes, Miguel

    2012-06-01

    The increasing volume of data produced by hyperspectral image sensors have forced researches and developers to seek out new and more ecient ways of analyzing the data as quick as possible. Medical, scientic, and military applications present performance requirements for tools that perform operations on hyperspectral sensor data. By providing a hyperspectral image analysis library, we aim to accelerate hyperspectral image application development. Development of a cross-platform library, Libdect, with GPU support for hyperspectral image analysis is presented. Coupling library development with ecient hyperspectral algorithms escalates into a signicant time invest- ment in many projects or prototypes. Provided a solution to these issues, developers can implement hyperspectral image analysis applications in less time. Developers will not be focused on implementing target detection code and potential issues related to platform or GPU architecture dierences. Libdect's development team counts with previously implemented detection algorithms. By utilizing proven tools, such as CMake and CTest, to develop Libdect's infrastructure, we were able to develop and test a prototype library that provides target detection code with GPU support on Linux platforms. As a whole, Libdect is an early prototype of an open and documented example of Software Engineering practices and tools. They are put together in an eort to increase developer productivity and encourage new developers into the eld of hyperspectral image application development.

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

    PubMed

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

    2013-04-01

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

  18. The Ring-Barking Experiment: Analysis of Forest Vitality Using Multi-Temporal Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Reichmuth, Anne; Bachmann, Martin; Heiden, Uta; Pinnel, Nicole; Holzwarth, Stefanie; Muller, Andreas; Henning, Lea; Einzmann, Kathrin; Immitzer, Markus; Seitz, Rudolf

    2016-08-01

    Through new operational optical spaceborne sensors (En- MAP and Sentinel-2) the impact analysis of climate change on forest ecosystems will be fostered. This analysis examines the potential of high spectral, spatial and temporal resolution data for detecting forest vegetation parameters, in particular Chlorophyll and Canopy Water content. The study site is a temperate spruce forest in Germany where in 2013 several trees were Ring-barked for a controlled die-off. During this experiment Ring- barked and Control trees were observed. Twelve airborne hyperspectral HySpex VNIR (Visible/Near Infrared) and SWIR (Shortwave Infrared) data with 1m spatial and 416 bands spectral resolution were acquired during the vegetation periods of 2013 and 2014. Additional laboratory spectral measurements of collected needle samples from Ring-barked and Control trees are available for needle level analysis. Index analysis of the laboratory measurements and image data are presented in this study.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  1. 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

  2. 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

  3. Hyperspectral Thermal Emission Spectrometer: Engineering Flight Campaign

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  4. 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.

  5. 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.

  6. 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.

  7. Airborne Remote Sensing

    NASA Technical Reports Server (NTRS)

    1992-01-01

    NASA imaging technology has provided the basis for a commercial agricultural reconnaissance service. AG-RECON furnishes information from airborne sensors, aerial photographs and satellite and ground databases to farmers, foresters, geologists, etc. This service produces color "maps" of Earth conditions, which enable clients to detect crop color changes or temperature changes that may indicate fire damage or pest stress problems.

  8. Simulation of APEX data: the SENSOR approach

    NASA Astrophysics Data System (ADS)

    Boerner, Anko; Schaepman, Michael E.; Schlaepfer, Daniel; Wiest, Lorenz; Reulke, Ralf

    1999-10-01

    The consistent simulation of airborne and spaceborne hyperspectral data is an important task and sometimes the only way for the adaptation and optimization of a sensor and its observing conditions, the choice and test of algorithms for data processing, error estimations and the evaluation of the capabilities of the whole sensor system. The integration of three approaches is suggested for the data simulation of APEX (Airborne Prism Experiment): (1) a spectrally consistent approach (e.g. using AVIRIS data), (2) a geometrically consistent approach (e.g. using CASI data), and (3) an end-to- end simulation of the sensor system. In this paper, the last approach is discussed in detail. Such a technique should be used if there is no simple deterministic relation between input and output parameters. The simulation environment SENSOR (Software Environment for the Simulation of Optical Remote Sensing Systems) presented here includes a full model of the sensor system, the observed object and the atmosphere. The simulator consists of three parts. The first part describes the geometrical relations between object, sun, and sensor using a ray tracing algorithm. The second part of the simulation environment considers the radiometry. It calculates the at-sensor-radiance using a pre-calculated multidimensional lookup-table for the atmospheric boundary conditions and bi- directional reflectances. Part three consists of an optical and an electronic sensor model for the generation of digital images. Application-specific algorithms for data processing must be considered additionally. The benefit of using an end- to-end simulation approach is demonstrated, an example of a simulated APEX data cube is given, and preliminary steps of evaluation of SENSOR are carried out.

  9. 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

  10. Classification of High Spatial Resolution, Hyperspectral ...

    EPA Pesticide Factsheets

    EPA announced the availability of the final report,Hyperspectral Remote Sensing Imagery of the Little Miami River Watershed in Southwest Ohio, USA . This report and associated land use/land cover (LULC) coverage is the result of a collaborative effort among an interdisciplinary team of scientists with the U.S. Environmental Protection Agency's (U.S. EPA's) Office of Research and Development in Cincinnati, Ohio. A primary goal of this project is to enhance the use of geography and spatial analytic tools in risk assessment, and to improve the scientific basis for risk management decisions affecting drinking water and water quality. The land use/land cover classification is derived from 82 flight lines of Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery acquired from July 24 through August 9, 2002 via fixed-wing aircraft.

  11. 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

  12. 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...

  13. Parallel hyperspectral image reconstruction using random projections

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

    Spaceborne sensors systems are characterized by scarce onboard computing and storage resources and by communication links with reduced bandwidth. Random projections techniques have been demonstrated as an effective and very light way to reduce the number of measurements in hyperspectral data, thus, the data to be transmitted to the Earth station is reduced. However, the reconstruction of the original data from the random projections may be computationally expensive. SpeCA is a blind hyperspectral reconstruction technique that exploits the fact that hyperspectral vectors often belong to a low dimensional subspace. SpeCA has shown promising results in the task of recovering hyperspectral data from a reduced number of random measurements. In this manuscript we focus on the implementation of the SpeCA algorithm for graphics processing units (GPU) using the compute unified device architecture (CUDA). Experimental results conducted using synthetic and real hyperspectral datasets on the GPU architecture by NVIDIA: GeForce GTX 980, reveal that the use of GPUs can provide real-time reconstruction. The achieved speedup is up to 22 times when compared with the processing time of SpeCA running on one core of the Intel i7-4790K CPU (3.4GHz), with 32 Gbyte memory.

  14. 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

  15. Retrieval of Water Quality Parameters in a Highly Turbid Estuary from Hyperspectral Remote Sensing Imagery

    NASA Astrophysics Data System (ADS)

    Hestir, E. L.; Greenberg, J. A.; Ustin, S. L.

    2007-12-01

    The Sacramento-San Joaquin River Delta is a highly turbid inland estuary that drains into the Pacific Ocean via the San Francisco Bay. The Delta has become a major ecological concern over the past decade, and the decline of the endangered fish, Delta smelt, has been attributed in part to decreasing turbidity in the Delta. Measuring and monitoring turbidity and Secchi disk depth are important to ecosystem health management and water quality monitoring of inland case-2 waters. The spectral determination of water quality parameters is dependent on (i) the inherent optical properties of water, such as the load of total suspended solids, suspended sediments, humic acids and dissolved organic matter, and planktonic content and composition, and (ii) the apparent optical properties of water which depend on both the medium and the geometric structure of light (surface reflectance, vertical diffuse attenuation). Water quality parameters such as turbidity and Secchi disk depth can be retrieved from hyperspectral remote sensing imagery, remote sensing data collected with many narrow spectral bands, using semi-empirical methods that require regression analysis, or from radiative transfer calculations that model apparent optical properties. We compared the accuracy of both semi-empirical and radiative transfer methods to retrieve turbidity and Secchi disk depths from airborne hyperspectral remote sensing imagery (the HyMap sensor, 450-2500 nm, 10-15nm bandwidth) of the Delta collected in June 2007. Results were validated using extensive field data collected concurrent with image acquisition. Additionally, we examined the effect of resampling the hyperspectral data to multispectral resolutions more commonly found on spaceborne instruments on the accuracy of water constituent retrieval from inland, case-2 waters.

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. Use of multispectral satellite imagery and hyperspectral endmember libraries for urban land cover mapping at the metropolitan scale

    NASA Astrophysics Data System (ADS)

    Priem, Frederik; Okujeni, Akpona; van der Linden, Sebastian; Canters, Frank

    2016-10-01

    The value of characteristic reflectance features for mapping urban materials has been demonstrated in many experiments with airborne imaging spectrometry. Analysis of larger areas requires satellite-based multispectral imagery, which typically lacks the spatial and spectral detail of airborne data. Consequently the need arises to develop mapping methods that exploit the complementary strengths of both data sources. In this paper a workflow for sub-pixel quantification of Vegetation-Impervious-Soil urban land cover is presented, using medium resolution multispectral satellite imagery, hyperspectral endmember libraries and Support Vector Regression. A Landsat 8 Operational Land Imager surface reflectance image covering the greater metropolitan area of Brussels is selected for mapping. Two spectral libraries developed for the cities of Brussels and Berlin based on airborne hyperspectral APEX and HyMap data are used. First the combined endmember library is resampled to match the spectral response of the Landsat sensor. The library is then optimized to avoid spectral redundancy and confusion. Subsequently the spectra of the endmember library are synthetically mixed to produce training data for unmixing. Mapping is carried out using Support Vector Regression models trained with spectra selected through stratified sampling of the mixed library. Validation on building block level (mean size = 46.8 Landsat pixels) yields an overall good fit between reference data and estimation with Mean Absolute Errors of 0.06, 0.06 and 0.08 for vegetation, impervious and soil respectively. Findings of this work may contribute to the use of universal spectral libraries for regional scale land cover fraction mapping using regression approaches.

  1. First observations using SPICE hyperspectral dataset

    NASA Astrophysics Data System (ADS)

    Rosario, Dalton; Romano, Joao; Borel, Christoph

    2014-06-01

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

  2. 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

  3. 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.

  4. Hyperspectral mineral mapping technology applied to geology based on HyMap data

    NASA Astrophysics Data System (ADS)

    Zhang, Hongliang; Yang, Kai; Yang, Zi'an; Zhang, Pubin; Lu, Yan; Yan, Peisheng

    2016-10-01

    Hyperspectral remote sensing technology has been in front of remote sensing science and technology. It brought a technical revolution for remote sensing. Hyperspectral remote sensing let the spatial and spectral dimensions of traditional image information fusion to an organic whole. It make the multispectral remote sensing image features in wide band to be detected and differentiated in hyperspectral remote sensing detection. Hyperspectral mineral mapping is the most successful technology which can exert its advantages of application field in geology. Using the airborne visible-light and near infrared and short-wave infrared imaging spectral HyMap data, we research the rock ore information recognition of Hami district in Xinjiang. Hyperspectral mineral mapping has made the good application effect in the exploration and resource prediction evaluation in ore-prospecting work.

  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

    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.

  6. 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.

  7. 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

  8. Studying groundwater and surface water interactions using airborne remote sensing in Heihe River basin, northwest China

    NASA Astrophysics Data System (ADS)

    Liu, C.; Liu, J.; Hu, Y.; Zheng, C.

    2015-05-01

    Managing surface water and groundwater as a unified system is important for water resource exploitation and aquatic ecosystem conservation. The unified approach to water management needs accurate characterization of surface water and groundwater interactions. Temperature is a natural tracer for identifying surface water and groundwater interactions, and the use of remote sensing techniques facilitates basin-scale temperature measurement. This study focuses on the Heihe River basin, the second largest inland river basin in the arid and semi-arid northwest of China where surface water and groundwater undergoes dynamic exchanges. The spatially continuous river-surface temperature of the midstream section of the Heihe River was obtained by using an airborne pushbroom hyperspectral thermal sensor system. By using the hot spot analysis toolkit in the ArcGIS software, abnormally cold water zones were identified as indicators of the spatial pattern of groundwater discharge to the river.

  9. Research on hyperspectral dynamic scene and image sequence simulation

    NASA Astrophysics Data System (ADS)

    Sun, Dandan; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei

    2016-10-01

    This paper presents a simulation method of hyper-spectral dynamic scene and image sequence for hyper-spectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyper-spectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyper-spectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyper-spectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyper-spectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyper-spectral images are consistent with the theoretical analysis results.

  10. Research on hyperspectral dynamic scene and image sequence simulation

    NASA Astrophysics Data System (ADS)

    Sun, Dandan; Liu, Fang; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei

    2016-10-01

    This paper presents a simulation method of hyperspectral dynamic scene and image sequence for hyperspectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyperspectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyperspectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyperspectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyperspectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyperspectral images are consistent with the theoretical analysis results.

  11. 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.

  12. 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.

  13. 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.

  14. Development of the AIRIS-WAD Multispectral Sensor for Airborne Standoff Chemical Agent and Toxic Industrial Chemical Detection

    DTIC Science & Technology

    2005-02-01

    through the closely-coupled Fabry-Perot tunable filter, which is operated at ambient temperature. An integral Stirling -Cycle cryocooler maintains the...which about 70 watts is from the detector cryocooler and the remainder from the electronics. The sensor unit is air-cooled and uses a series of heat

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. Close-range environmental remote sensing with 3D hyperspectral technologies

    NASA Astrophysics Data System (ADS)

    Nevalainen, O.; Honkavaara, E.; Hakala, T.; Kaasalainen, Sanna; Viljanen, N.; Rosnell, T.; Khoramshahi, E.; Näsi, R.

    2016-10-01

    Estimation of the essential climate variables (ECVs), such as photosynthetically active radiation (FAPAR) and the leaf area index (LAI), is largely based on satellite-based remote sensing and the subsequent inversion of radiative transfer (RT) models. In order to build models that accurately describe the radiative transfer within and below the canopy, detailed 3D structural (geometrical) and spectral (radiometrical) information of the canopy is needed. Close-range remote sensing, such as terrestrial remote sensing and UAV-based 3D spectral measurements, offers significant opportunity to improve the RT modelling and ECV estimation of forests. Finnish Geospatial Research Institute (FGI) has been developing active and passive high resolution 3D hyperspectral measurement technologies that provide reflectance, anisotropy and 3D structure information of forests (i.e. hyperspectral point clouds). Technologies include hyperspectral imaging from unmanned airborne vehicle (UAV), terrestrial hyperspectral lidar (HSL) and terrestrial hyperspectral stereoscopic imaging. A measurement campaign to demonstrate these technologies in ECV estimation with uncertainty propagation was carried out in the Wytham Woods, Oxford, UK, in June 2015. Our objective is to develop traceable processing procedures for generating hyperspectral point clouds with geometric and radiometric uncertainty propagation using hyperspectral aerial and terrestrial imaging and hyperspectral terrestrial laser scanning. The article and presentation will present the methodology, instrumentation and first results of our study.

  20. 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.

  1. 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

  2. A model of the 1.6 GHz scatterometer. [performance of airborne scatterometer used as microwave remote sensor of soil moisture

    NASA Technical Reports Server (NTRS)

    Wang, J. R.

    1977-01-01

    The performance was studied of the 1.6 GHz airborne scatterometer system which is used as one of several Johnson Space Center (JSC) microwave remote sensors to detect moisture content of soil. The system is analyzed with respect to its antenna pattern and coupling, the signal flow in the receiver data channels, and the errors in the signal outputs. The operational principle and the sensitivity of the system, as well as data handling are also described. The finite cross-polarized gains of all four 1.6 GHz scatterometer antennae are found to have profound influence on the cross-polarized backscattered signal returns. If these signals are not analyzed properly, large errors could result in the estimate of the cross-polarized coefficient. It is also found necessary to make corrections to the variations of the aircraft parameters during data reduction in order to minimize the error in the coefficient estimate. Finally, a few recommendations are made to improve the overall performance of the scatterometer system.

  3. The danger signal, extracellular ATP, is a sensor for an airborne allergen and triggers IL-33 release and innate Th2-type responses.

    PubMed

    Kouzaki, Hideaki; Iijima, Koji; Kobayashi, Takao; O'Grady, Scott M; Kita, Hirohito

    2011-04-01

    The molecular mechanisms underlying the initiation of innate and adaptive proallergic Th2-type responses in the airways are not well understood. IL-33 is a new member of the IL-1 family of molecules that is implicated in Th2-type responses. Airway exposure of naive mice to a common environmental aeroallergen, the fungus Alternaria alternata, induces rapid release of IL-33 into the airway lumen, followed by innate Th2-type responses. Biologically active IL-33 is constitutively stored in the nuclei of human airway epithelial cells. Exposing these epithelial cells to A. alternata releases IL-33 extracellularly in vitro. Allergen exposure also induces acute extracellular accumulation of a danger signal, ATP; autocrine ATP sustains increases in intracellular Ca(2+) concentration and releases IL-33 through activation of P2 purinergic receptors. Pharmacological inhibitors of purinergic receptors or deficiency in the P2Y2 gene abrogate IL-33 release and Th2-type responses in the Alternaria-induced airway inflammation model in naive mice, emphasizing the essential roles for ATP and the P2Y(2) receptor. Thus, ATP and purinergic signaling in the respiratory epithelium are critical sensors for airway exposure to airborne allergens, and they may provide novel opportunities to dampen the hypersensitivity response in Th2-type airway diseases such as asthma.

  4. Hyperspectral monitoring of chemically sensitive plant sentinels

    NASA Astrophysics Data System (ADS)

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

    2009-08-01

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

  5. Sparse Modeling for Hyperspectral Imagery with Lidar Data Fusion for Subpixel Mapping

    DTIC Science & Technology

    2012-07-15

    improved small target detection. It has also been applied for obtaining higher discrimination between savanna tree species by the use of hand crafted...Cho, L. Naidoo, R. Mathieu, and G.P. Asner, “Mapping savanna tree species using carnegie airborne observatory hyperspectral data re- sampled to...G.P. Asner, “Spectral classifica- tion of savanna tree species, in the greater kruger national park region using carnegie airborne observatory (cao

  6. Ore minerals textural characterization by hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Bonifazi, Giuseppe; Picone, Nicoletta; Serranti, Silvia

    2013-02-01

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

  7. Miniaturization of a SWIR hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Warren, Christopher P.; Pfister, William; Even, Detlev; Velasco, Arleen; Yee, Selwyn; Breitwieser, David; Naungayan, Joseph

    2011-05-01

    A new approach for the design and fabrication of a miniaturized SWIR Hyperspectral imager is described. Previously, good results were obtained with a VNIR Hyperspectral imager, by use of light propagation within bonded solid blocks of fused silica. These designs use the Offner design form, providing excellent, low distortion imaging. The same idea is applied to the SWIR Hyperspectral imager here, resulting in a microHSITM SWIR Hyperspectral sensor, capable of operating in the 850-1700 nm wavelength range. The microHSI spectrometer weighs 910 g from slit input to camera output. This spectrometer can accommodate custom foreoptics to adapt to a wide range of fields-of-view (FOV). The current application calls for a 15 degree FOV, and utilizes an InGaAs image sensor with a spatial format of 640 x 25 micron pixels. This results in a slit length of 16 mm, and a foreoptics focal length of 61 mm, operating at F# = 2.8. The resulting IFOV is 417 μrad for this application, and a spectral dispersion of 4.17 nm/pixel. A prototype SWIR microHSI was fabricated, and the blazed diffraction grating was embedded within the optical blocks, resulting in a 72% diffraction efficiency at the wavelength of 1020 nm. This spectrometer design is capable of accommodating slit lengths of up to 25.6 mm, which opens up a wide variety of applications. The microHSI concepts can be extended to other wavelength regions, and a miniaturized LWIR microHSI sensor is in the conceptual design stage.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. 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...

  20. 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

  1. 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.

  2. Hyperview-fast, economical access to large data sets: a system for the archiving and distribution of hyperspectral data sets and derived products

    NASA Astrophysics Data System (ADS)

    Lurie, Joan B.

    1996-12-01

    TRW, under a Small Satellite Technology Initiative (SSTI) contract, is building the Lewis satellite. The principal sensor on Lewis is a hyperspectral imaging spectrometer. Part of the SSTI mission is to establish the commercial and educational utility of this data and the hyperspectral data already being acquired on airborne platforms. Essential requirements are rapid availability (after data acquisition) and easy accessibility to a catalog of images and imagery products. Each image is approximately 256 by 512 pixels with 384 bands of data acquired at each pixel. For some applications, some users will want the entire data sets; in other cases partial data sets (e.g. three band images) will be all that a user can handle or need for a given application. In order to make the most effective use of this new imagery and justify the cost of collecting it, we must find ways to make the information it contains more readily accessible to an ever broadening community of potential users. Tools are needed to store, access, and communicate the data more efficiently, to place it in context, and to derive both qualitative and quantitative information from it. A variety of information products which address the specific needs of particular user communities will be derived from the imagery. The data is unique in its ability to provide high spatial and spectral resolution simultaneously, and shows great promise in both military and civilian applications. A data management and analysis system has been built at TRW. This development has been prompted by the business opportunities, by the series of instruments built here and by the availability of data from other instruments. The products of the processing system have been shown to prospective customers in the U.S. and abroad. The system has been used to process data produced by TRW sensors and other instruments. This paper provides an overview of the TRW hyperspectral collection, data handling and exploitation capability.

  3. 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.

  4. Hyperspectral Imaging and Obstacle Detection for Robotics Navigation

    DTIC Science & Technology

    2005-09-01

    such as anomaly or target detection , based on imaging sensor data can enhance UGVs’ capability to safely maneuver unknown terrain with increased speed...process; otherwise the deconvoluted images become very noisy , significantly affecting detection performance. • For SECOTS the image drift should be...Hyperspectral Imaging and Obstacle Detection for Robotics Navigation by Heesung Kwon, Dalton Rosario, Neelam Gupta, Matthew Thielke

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. Using Hyperspectral Imagery to Identify Turfgrass Stresses

    NASA Technical Reports Server (NTRS)

    Hutto, Kendall; Shaw, David

    2008-01-01

    The use of a form of remote sensing to aid in the management of large turfgrass fields (e.g. golf courses) has been proposed. A turfgrass field of interest would be surveyed in sunlight by use of an airborne hyperspectral imaging system, then the raw observational data would be preprocessed into hyperspectral reflectance image data. These data would be further processed to identify turfgrass stresses, to determine the spatial distributions of those stresses, and to generate maps showing the spatial distributions. Until now, chemicals and water have often been applied, variously, (1) indiscriminately to an entire turfgrass field without regard to localization of specific stresses or (2) to visible and possibly localized signs of stress for example, browning, damage from traffic, or conspicuous growth of weeds. Indiscriminate application is uneconomical and environmentally unsound; the amounts of water and chemicals consumed could be insufficient in some areas and excessive in most areas, and excess chemicals can leak into the environment. In cases in which developing stresses do not show visible signs at first, it could be more economical and effective to take corrective action before visible signs appear. By enabling early identification of specific stresses and their locations, the proposed method would provide guidance for planning more effective, more economical, and more environmentally sound turfgrass-management practices, including application of chemicals and water, aeration, and mowing. The underlying concept of using hyperspectral imagery to generate stress maps as guides to efficient management of vegetation in large fields is not new; it has been applied in the growth of crops to be harvested. What is new here is the effort to develop an algorithm that processes hyperspectral reflectance data into spectral indices specific to stresses in turfgrass. The development effort has included a study in which small turfgrass plots that were, variously, healthy or

  10. 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.

  11. Content-based hyperspectral image retrieval using spectral unmixing

    NASA Astrophysics Data System (ADS)

    Plaza, Antonio J.

    2011-11-01

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

  12. Hyperspectral Cubesat Constellation for Rapid Natural Hazard Response

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  13. The State of the Industry and Research in Airborne Geophysics

    NASA Astrophysics Data System (ADS)

    Hodges, G.

    2007-12-01

    rotation and translation, and measurement of acceleration. Generally, solutions must be a trade-off between sensitivity and spatial resolution, restricting their application to the large structures of oil exploration. Airborne gravity gradiometry (AGG) achieves higher resolution and sensitivity with meters based on the system of accelerometers on spinning disks, implemented as horizontal gradiometers and as full tensor gradiometers. Putting the sensor on a helicopter improved the data S/N. An airship implementation promises to be a near-ideal platform, restricted by the payload limits. Many projects are on-going to develop new gravity gradiometers toward a goal of 1Eotvös sensitivity at 100m wavelength. Hyperspectral imaging measures the reflected light from the surface across a broad spectrum, originally from near-infrared through visible, but now often including thermal infrared. The research challenges for systems have been to stabilize the system sensitivities, correct for varying ambient light levels reflectance, and improve resolution without degrading signal strength. Data processing requires the determination of the mineral reflectance spectra that best fit the spectrum of each pixel, when each pixel will probably contain many minerals, or be partly covered by vegetation.

  14. Airborne remote sensing of forest biomes

    NASA Technical Reports Server (NTRS)

    Sader, Steven A.

    1987-01-01

    Airborne sensor data of forest biomes obtained using an SAR, a laser profiler, an IR MSS, and a TM simulator are presented and examined. The SAR was utilized to investigate forest canopy structures in Mississippi and Costa Rica; the IR MSS measured forest canopy temperatures in Oregon and Puerto Rico; the TM simulator was employed in a tropical forest in Puerto Rico; and the laser profiler studied forest canopy characteristics in Costa Rica. The advantages and disadvantages of airborne systems are discussed. It is noted that the airborne sensors provide measurements applicable to forest monitoring programs.

  15. Airborne LIDAR as a tool for estimating inherent optical properties

    NASA Astrophysics Data System (ADS)

    Trees, Charles; Arnone, Robert

    2012-06-01

    LIght Detection and Ranging (LIDAR) systems have been used most extensively to generate elevation maps of land, ice and coastal bathymetry. There has been space-, airborne- and land-based LIDAR systems. They have also been used in underwater communication. What have not been investigated are the capabilities of LIDARs to measure ocean temperature and optical properties vertically in the water column, individually or simultaneously. The practical use of bathymetric LIDAR as a tool for the estimation of inherent optical properties remains one of the most challenging problems in the field of optical oceanography. LIDARs can retrieve data as deep as 3-4 optical depths (e.g. optical properties can be measured through the thermocline for ~70% of the world's oceans). Similar to AUVs (gliders), UAV-based LIDAR systems will increase temporal and spatial measurements by several orders of magnitude. The LIDAR Observations of Optical and Physical Properties (LOOPP) Conference was held at NURC (2011) to review past, current and future LIDAR research efforts in retrieving water column optical/physical properties. This new observational platform/sensor system is ideally suited for ground truthing hyperspectral/geostationary satellite data in coastal regions and for model data assimilation.

  16. Acquisition, calibration, and performance of airborne high-resolution ADS40 SH52 sensor data for monitoring the Colorado River below Glen Canyon Dam

    NASA Astrophysics Data System (ADS)

    Davis, P. A.; Cagney, L. E.; Kohl, K. A.; Gushue, T. M.; Fritzinger, C.; Bennett, G. E.; Hamill, J. F.; Melis, T. S.

    2010-12-01

    Periodically, the Grand Canyon Monitoring and Research Center of the U.S. Geological Survey collects and interprets high-resolution (20-cm), airborne multispectral imagery and digital surface models (DSMs) to monitor the effects of Glen Canyon Dam operations on natural and cultural resources of the Colorado River in Grand Canyon. We previously employed the first generation of the ADS40 in 2000 and the Zeiss-Imaging Digital Mapping Camera (DMC) in 2005. Data from both sensors displayed band-image misregistration owing to multiple sensor optics and image smearing along abrupt scarps due to errors in image rectification software, both of which increased post-processing time, cost, and errors from image classification. Also, the near-infrared gain on the early, 8-bit ADS40 was not properly set and its signal was saturated for the more chlorophyll-rich vegetation, which limited our vegetation mapping. Both sensors had stereo panchromatic capability for generating a DSM. The ADS40 performed to specifications; the DMC failed. In 2009, we employed the new ADS40 SH52 to acquire 11-bit multispectral data with a single lens (20-cm positional accuracy), as well as stereo panchromatic data that provided a 1-m cell DSM (40-cm root-mean-square vertical error at one sigma). Analyses of the multispectral data showed near-perfect registration of its four band images at our 20-cm resolution, a linear response to ground reflectance, and a large dynamic range and good sensitivity (except for the blue band). Data were acquired over a 10-day period for the 450-km-long river corridor in which acquisition time and atmospheric conditions varied considerably during inclement weather. We received 266 orthorectified flightlines for the corridor, choosing to calibrate and mosaic the data ourselves to ensure a flawless mosaic with consistent, realistic spectral information. A linear least-squares cross-calibration of overlapping flightlines for the corridor showed that the dominate factors in

  17. 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

  18. 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.

  19. Real time orthorectification of high resolution airborne pushbroom imagery

    NASA Astrophysics Data System (ADS)

    Reguera-Salgado, Javier; Martin-Herrero, Julio

    2011-11-01

    Advanced architectures have been proposed for efficient orthorectification of digital airborne camera images, including a system based on GPU processing and distributed computing able to geocorrect three digital still aerial photographs per second. Here, we address the computationally harder problem of geocorrecting image data from airborne pushbroom sensors, where each individual image line has associated its own camera attitude and position parameters. Using OpenGL and CUDA interoperability and projective texture techniques, originally developed for fast shadow rendering, image data is projected onto a Digital Terrain Model (DTM) as if by a slide projector placed and rotated in accordance with GPS position and inertial navigation (IMU) data. Each line is sequentially projected onto the DTM to generate an intermediate frame, consisting of a unique projected line shaped by the DTM relief. The frames are then merged into a geometrically corrected georeferenced orthoimage. To target hyperband systems, avoiding the high dimensional overhead, we deal with an orthoimage of pixel placeholders pointing to the raw image data, which are then combined as needed for visualization or processing tasks. We achieved faster than real-time performance in a hyperspectral pushbroom system working at a line rate of 30 Hz with 200 bands and 1280 pixel wide swath over a 1 m grid DTM, reaching a minimum processing speed of 356 lines per second (up to 511 lps), over eleven (up to seventeen) times the acquisition rate. Our method also allows the correction of systematic GPS and/or IMU biases by means of 3D user interactive navigation.

  20. Absolute airborne gravimetry

    NASA Astrophysics Data System (ADS)

    Baumann, Henri

    This work consists of a feasibility study of a first stage prototype airborne absolute gravimeter system. In contrast to relative systems, which are using spring gravimeters, the measurements acquired by absolute systems are uncorrelated and the instrument is not suffering from problems like instrumental drift, frequency response of the spring and possible variation of the calibration factor. The major problem we had to resolve were to reduce the influence of the non-gravitational accelerations included in the measurements. We studied two different approaches to resolve it: direct mechanical filtering, and post-processing digital compensation. The first part of the work describes in detail the different mechanical passive filters of vibrations, which were studied and tested in the laboratory and later in a small truck in movement. For these tests as well as for the airborne measurements an absolute gravimeter FG5-L from Micro-G Ltd was used together with an Inertial navigation system Litton-200, a vertical accelerometer EpiSensor, and GPS receivers for positioning. These tests showed that only the use of an optical table gives acceptable results. However, it is unable to compensate for the effects of the accelerations of the drag free chamber. The second part describes the strategy of the data processing. It is based on modeling the perturbing accelerations by means of GPS, EpiSensor and INS data. In the third part the airborne experiment is described in detail, from the mounting in the aircraft and data processing to the different problems encountered during the evaluation of the quality and accuracy of the results. In the part of data processing the different steps conducted from the raw apparent gravity data and the trajectories to the estimation of the true gravity are explained. A comparison between the estimated airborne data and those obtained by ground upward continuation at flight altitude allows to state that airborne absolute gravimetry is feasible and

  1. FPGA-based architecture for hyperspectral endmember extraction

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  2. 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.

  3. 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.

  4. Ship classification in terrestrial hyperspectral data

    NASA Astrophysics Data System (ADS)

    Keskin, Göksu; Schilling, Hendrik; Lenz, Andreas; Groß, Wolfgang; Middelmann, Wolfgang

    2016-10-01

    This work analyzes the applicability of using hyperspectral data for ship classification in coastal or harbor environment. An approach for hyperspectral feature selection based on bag-of-words method was developed. Nearest neighbor and random forest classifiers were used for evaluating hyperspectral bag-of-words features. The evaluation dataset was self-acquired at the Kiel Harbor in Germany, using Aisa Eagle in VNIR and Aisa Hawk in SWIR sensors. The dataset included 547 samples of 72 objects ranging from passenger ferries to sailing boats in different illumination conditions. An object library was created from the dataset and bag-of-words features were extracted. Two different separation strategies for separating training and test sets were selected: Random subsets and chronologically separated subsets. Chronological separation was more challenging than the random separation for both classifiers. In order to allow a future sliding window operation for object detection, the training and the classification were performed additionally on rectangular windows including background pixels. The performance of nearest neighbor classifier dropped whereas the performance of random forest classifier slightly improved. Overall performance of random forest classifier is better than nearest neighbor classifier; however it requires a more comprehensive dataset for training. The evaluations indicated that the bag-of-words feature selection is feasible for the given application.

  5. 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.

  6. 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.

  7. Ameliorating the spatial resolution of Hyperion hyperspectral data

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

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

  8. Combining hyperspectral imaging and Raman spectroscopy for remote chemical sensing

    NASA Astrophysics Data System (ADS)

    Ingram, John M.; Lo, Edsanter

    2008-04-01

    The Photonics Research Center at the United States Military Academy is conducting research to demonstrate the feasibility of combining hyperspectral imaging and Raman spectroscopy for remote chemical detection over a broad area of interest. One limitation of future trace detection systems is their ability to analyze large areas of view. Hyperspectral imaging provides a balance between fast spectral analysis and scanning area. Integration of a hyperspectral system capable of remote chemical detection will greatly enhance our soldiers' ability to see the battlefield to make threat related decisions. It can also queue the trace detection systems onto the correct interrogation area saving time and reconnaissance/surveillance resources. This research develops both the sensor design and the detection/discrimination algorithms. The one meter remote detection without background radiation is a simple proof of concept.

  9. 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.

  10. 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.

  11. 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.

  12. Combined hyperspatial and hyperspectral imaging spectrometer concept

    NASA Technical Reports Server (NTRS)

    Burke, Ian; Zwick, Harold

    1995-01-01

    There is a user need for increasing spatial and spectral resolution in Earth Observation (EO) optical instrumentation. Higher spectral resolution will be achieved by the introduction of spaceborne imaging spectrometers. Higher spatial resolutions of 1 - 3m will be achieved also, but at the expense of sensor redesign, higher communications bandwidth, high data processing volumes, and therefore, at the risk of time delays due to large volume data-handling bottlenecks. This paper discusses a design concept whereby the hyperspectral properties of a spaceborne imaging spectrometer can be used to increase the image spatial resolution, without such adverse cost impact.

  13. 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/).

  14. Airborne Particles.

    ERIC Educational Resources Information Center

    Ojala, Carl F.; Ojala, Eric J.

    1987-01-01

    Describes an activity in which students collect airborne particles using a common vacuum cleaner. Suggests ways for the students to convert their data into information related to air pollution and human health. Urges consideration of weather patterns when analyzing the results of the investigation. (TW)

  15. 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.

  16. Multiple Spectral-Spatial Classi