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NASA NTRS2005

Spectral Ratio Imaging with Hyperion Satellite Data for Geological Mapping

Since the advent of LANDSAT I in 1972, many different multispectral satellites have been orbited by the U.S. and other countries. These satellites have varied from 4 spectral bands in LANDSAT I to 14 spectral bands in the ASTER sensor aboard the TERRA space platform. Hyperion is a relatively new hyperspectral sensor with over 220 spectral bands. The huge increase in the number of spectral bands offers a substantial challenge to computers and analysts alike when it comes to the task of mapping features on the basis of chemical composition, especially if little or no ground truth is available beforehand from the area being mapped. One approach is the theoretical approach of the modeler, where all extraneous information (atmospheric attenuation, sensor electronic gain and offset, etc.) is subtracted off and divided out, and laboratory (or field) spectra of materials are used as training sets to map features in the scene of similar composition. This approach is very difficult to keep accurate because of variations in the atmosphere, solar illumination, and sensor electronic gain and offset that are not always perfectly recorded or accounted for. For instance, to apply laboratory or field spectra of materials as data sets from the theoretical approach, the header information of the files must reflect the correct, up-to-date sensor electronic gain and offset and the analyst must pick the exact atmospheric model that is appropriate for the day of data collection in order for classification procedures to accurately match pixels in the scene with the laboratory or field spectrum of a desired target on the basis of the hyperspectral data. The modeling process is so complex that it is difficult to tell when it is operating well or determine how to fix it when it is incorrect. Recently RSI has announced that the latest version of their ENVI software package is not performing atmospheric corrections correctly with the FLAASH atmospheric model. It took a long time to determine that it was wrong, and may take an equally long time (or longer) to fix.

Vincent, Robert K.↗
NASA NTRS2005

A Parallel Processing Algorithm for Remote Sensing Classification

A current thread in parallel computation is the use of cluster computers created by networking a few to thousands of commodity general-purpose workstation-level commuters using the Linux operating system. For example on the Medusa cluster at NASA/GSFC, this provides for super computing performance, 130 G(sub flops) (Linpack Benchmark) at moderate cost, $370K. However, to be useful for scientific computing in the area of Earth science, issues of ease of programming, access to existing scientific libraries, and portability of existing code need to be considered. In this paper, I address these issues in the context of tools for rendering earth science remote sensing data into useful products. In particular, I focus on a problem that can be decomposed into a set of independent tasks, which on a serial computer would be performed sequentially, but with a cluster computer can be performed in parallel, giving an obvious speedup. To make the ideas concrete, I consider the problem of classifying hyperspectral imagery where some ground truth is available to train the classifier. In particular I will use the Support Vector Machine (SVM) approach as applied to hyperspectral imagery. The approach will be to introduce notions about parallel computation and then to restrict the development to the SVM problem. Pseudocode (an outline of the computation) will be described and then details specific to the implementation will be given. Then timing results will be reported to show what speedups are possible using parallel computation. The paper will close with a discussion of the results.

Gualtieri, J. Anthony↗
NASA NTRS2004

Analysis Of AVIRIS Data From LEO-15 Using Tafkaa Atmospheric Correction

We previously developed an algorithm named Tafkaa for atmospheric correction of remote sensing ocean color data from aircraft and satellite platforms. The algorithm allows quick atmospheric correction of hyperspectral data using lookup tables generated with a modified version of Ahmad & Fraser s vector radiative transfer code. During the past few years we have extended the capabilities of the code. Current modifications include the ability to account for within scene variation in solar geometry (important for very long scenes) and view geometries (important for wide fields of view). Additionally, versions of Tafkaa have been made for a variety of multi-spectral sensors, including SeaWiFS and MODIS. In this proceeding we present some initial results of atmospheric correction of AVIRIS data from the 2001 July Hyperspectral Coastal Ocean Dynamics Experiment (HyCODE) at LEO-15.

Montes, Marcos J.↗
NASA NTRS2006

Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion data will be used to produce simulated MODIS and VIIRS products. Hyperion-derived MODIS data will be compared with near-coincident MODIS collects to validate both spectral and spatial synthesis, which will ascertain the accuracy of converting from MODIS to VIIRS. MODIS-derived VIIRS data is needed for global coverage and for the generation of time series for regional and global investigations. These types of simulations will have errors associated with aliasing for some scene types. This study will help quantify these errors and will identify cases where high-quality, MODIS-derived VIIRS data will be available.

Ross, Kenton W.↗
NASA NTRS2006

AIRS Retrieval Validation During the EAQUATE

Atmospheric and surface thermodynamic parameters retrieved with advanced hyperspectral remote sensors of Earth observing satellites are critical for weather prediction and scientific research. The retrieval algorithms and retrieved parameters from satellite sounders must be validated to demonstrate the capability and accuracy of both observation and data processing systems. The European AQUA Thermodynamic Experiment (EAQUATE) was conducted mainly for validation of the Atmospheric InfraRed Sounder (AIRS) on the AQUA satellite, but also for assessment of validation systems of both ground-based and aircraft-based instruments which will be used for other satellite systems such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) from the NPOESS Preparatory Project and the following NPOESS series of satellites. Detailed inter-comparisons were conducted and presented using different retrieval methodologies: measurements from airborne ultraspectral Fourier transform spectrometers, aircraft in-situ instruments, dedicated dropsondes and radiosondes, and ground based Raman Lidar, as well as from the European Center for Medium range Weather Forecasting (ECMWF) modeled thermal structures. The results of this study not only illustrate the quality of the measurements and retrieval products but also demonstrate the capability of these validation systems which are put in place to validate current and future hyperspectral sounding instruments and their scientific products.

Zhou, Daniel K.↗
NASA NTRS2006

Three Years of Atmospheric Infrared Sounder Radiometric Calibration Validation using Sea Surface Temperatures

This paper evaluates the absolute accuracy and stability of the radiometric calibration of the Atmospheric Infrared Sounder (AIRS) by analyzing the difference between the brightness temperatures measured at 2616 cm(exp -1) and those calculated at the top of the atmosphere (TOA), using the Real-Time Global Sea Surface Temperature (RTGSST) for cloud-free night tropical oceans between +/- 30 degrees latitude. The TOA correction is based on radiative transfer. The analysis of the first 3 years of AIRS radiances verifies the absolute calibration at 2616 cm(exp -1) to better than 200 mK, with better than 16 mK/yr stability. The AIRS radiometric calibration uses an internal full aperture wedge blackbody with the National Institute of Standards and Technology (NIST) traceable prelaunch calibration coefficients. The calibration coefficients have been unchanged since launch. The analysis uses very tight cloud filtering, which selects about 7000 cloud-free tropical ocean spectra per day, about 0.5% of the data. The absolute accuracy and stability of the radiometry demonstrated at 2616 cm(sup -1) are direct consequences of the implementation of AIRS as a thermally controlled, cooled grating-array spectrometer and meticulous attention to details. Comparable radiometric performance is inferred from the AIRS design for all 2378 channels. AIRS performance sets the benchmark for what can be achieved with a state-of-the-art hyperspectral radiometer from polar orbit and what is expected from future hyperspectral sounders. AIRS was launched into a 705 km altitude polar orbit on NASA's Earth Observation System (EOS) Aqua spacecraft on 4 May 2002. AIRS covers the 3.7-15.4 micron region of the thermal infrared spectrum with a spectral resolution of nu/Delta nu = 1200 and has returned 3.7 million spectra of the upwelling radiance each day since the start of routine data gathering in September 2002.

climate↗
NASA NTRS2005

Evaluation of Vertically Resolved Water Winds from AIRS using Hurricane Katrina

The knowledge of wind velocity as a function of altitude is key to weather forecast improvements. The ability of hyperspectral sounders in principle to measure vertically resolved water winds, which has long been recognized, has been tested with Atmospheric Infrared Sounder (AIRS) data. AIRS retrievals of total column water above 300 mb have been correlated with the radiosonde upper-tropospheric wind velocity and moisture data. The excellent correlation is illustrated with results obtained from hurricane Katrina and from the western United States. AIRS is a hyperspectral infrared sounder in low Earth orbit. It was launched in May 2002. We illustrate the use of AIRS data for the measurement of upper tropospheric water by using the 2387/cm CO2 R-branch channel and the 1551/cm water vapor channel. The 2387/cm channel measures the temperature at 300 mb totally independent of water vapor. The weighting function of the 1551/cm channel peaks at 300 mb only under moist conditions; the peak shifts downward (higher temperature) for less water and upward (lower temperature) for more water. The difference between the brightness temperatures bt2387 and bt1551 cancels the local several degree weather related variability of the temperature and measures the component due to the water vapor at 300 mb.

Atmospheric Infrared Sounder (AIRS)↗
NASA NTRS2009

Transmittance Measurement of a Heliostat Facility used in the Preflight Radiometric Calibration of Earth-Observing Sensors

Ball Aerospace and Technologies Corporation in Boulder, Colorado, has developed a heliostat facility that will be used to determine the preflight radiometric calibration of Earth-observing sensors that operate in the solar-reflective regime. While automatically tracking the Sun, the heliostat directs the solar beam inside a thermal vacuum chamber, where the sensor under test resides. The main advantage to using the Sun as the illumination source for preflight radiometric calibration is because it will also be the source of illumination when the sensor is in flight. This minimizes errors in the pre- and post-launch calibration due to spectral mismatches. It also allows the instrument under test to operate at irradiance values similar to those on orbit. The Remote Sensing Group at the University of Arizona measured the transmittance of the heliostat facility using three methods, the first of which is a relative measurement made using a hyperspectral portable spectroradiometer and well-calibrated reference panel. The second method is also a relative measurement, and uses a 12-channel automated solar radiometer. The final method is an absolute measurement using a hyperspectral spectroradiometer and reference panel combination, where the spectroradiometer is calibrated on site using a solar-radiation-based calibration.

Czapla-Myers, J.↗
NASA NTRS2010

A History of NASA Remote Sensing Contributions to Archaeology

During its long history of developing and deploying remote sensing instruments, NASA has provided a scientific data that have benefitted a variety of scientific applications among them archaeology. Multispectral and hyperspectral instrument mounted on orbiting and suborbital platforms have provided new and important information for the discovery, delineation and analysis of archaeological sites worldwide. Since the early 1970s, several of the ten NASA centers have collaborated with archaeologists to refine and validate the use of active and passive remote sensing for archeological use. The Stennis Space Center (SSC), located in Mississippi USA has been the NASA leader in archeological research. Together with colleagues from Goddard Space Flight Center (GSFC), Marshall Space Flight Center (MSFC), and the Jet Propulsion Laboratory (JPL), SSC scientists have provided the archaeological community with useful images and sophisticated processing that have pushed the technological frontiers of archaeological research and applications. Successful projects include identifying prehistoric roads in Chaco canyon, identifying sites from the Lewis and Clark Corps of Discovery exploration and assessing prehistoric settlement patterns in southeast Louisiana. The Scientific Data Purchase (SDP) stimulated commercial companies to collect archaeological data. At present, NASA formally solicits "space archaeology" proposals through its Earth Science Directorate and continues to assist archaeologists and cultural resource managers in doing their work more efficiently and effectively. This paper focuses on passive remote sensing and does not consider the significant contributions made by NASA active sensors. Hyperspectral data offers new opportunities for future archeological discoveries.

Giardino, Marco J.↗
NASA NTRS2008

Requirements for an Advanced Low Earth Orbit (LEO) Sounder (ALS) for Improved Regional Weather Prediction and Monitoring of Greenhouse Gases

Hyperspectral infrared atmospheric sounders (e.g., the Atmospheric Infrared Sounder (AIRS) on Aqua and the Infrared Atmospheric Sounding Interferometer (IASI) on Met Op) provide highly accurate temperature and water vapor profiles in the lower to upper troposphere. These systems are vital operational components of our National Weather Prediction system and the AIRS has demonstrated over 6 hrs of forecast improvement on the 5 day operational forecast. Despite the success in the mid troposphere to lower stratosphere, a reduction in sensitivity and accuracy has been seen in these systems in the boundary layer over land. In this paper we demonstrate the potential improvement associated with higher spatial resolution (1 km vs currently 13.5 km) on the accuracy of boundary layer products with an added consequence of higher yield of cloud free scenes. This latter feature is related to the number of samples that can be assimilated and has also shown to have a significant impact on improving forecast accuracy. We also present a set of frequencies and resolutions that will improve vertical resolution of temperature and water vapor and trace gas species throughout the atmosphere. Development of an Advanced Low Earth Orbit (LEO) Sounder (ALS) with these improvements will improve weather forecast at the regional scale and of tropical storms and hurricanes. Improvements are also expected in the accuracy of the water vapor and cloud properties products, enhancing process studies and providing a better match to the resolution of future climate models. The improvements of technology required for the ALS are consistent with the current state of technology as demonstrated in NASA Instrument Incubator Program and NOAA's Hyperspectral Environmental Suite (HES) formulation phase development programs.

temperature↗
NASA NTRS2005

Simultaneous Conoscopic Holography and Raman Spectroscopy

A new instrument was developed for chemical characterization of surfaces that combines the analytical power of Raman spectroscopy with the three-dimensional topographic information provided by conoscopic holography. The figure schematically depicts the proposed hybrid instrument. The output of the conoscopic holographic portion of the instrument is a topographical map of the surface; the output of the Raman portion of the instrument is hyperspectral Raman data, from which the chemical and/or biological composition of the surface would be deduced. By virtue of the basic principles of design and operation of the instrument, the hyperspectral image data would be inherently spatially registered with the topographical data. In conoscopic holography, the object and reference beams of classical holography are replaced by the ordinary and extraordinary components generated by a single beam traveling through a birefringent, uniaxial crystal. In the basic conoscopic configuration, a laser light is projected onto a specimen and the resulting illuminated spot becomes a point source of diffuse light that propagates in every direction. The laser beam is rasterscanned in two dimensions (x and y) perpendicular to the beam axis (z), and at each x,y location, the pattern of interference between the ordinary and extraordinary rays is recorded. The recorded interferogram constitutes the conoscopic hologram. Of particular significance for the proposed instrument is that the conoscopic hologram contains information on the z coordinate (height) of the illuminated surface spot. Hence, a topographical map of the specimen is constructed point-by-point by rastering the laser beam in the x and y directions and correlating the x and y coordinates with the z information obtained from the interferograms. Conoscopic imaging is an established method, and conoscopic laboratory instruments for surface metrology are commercially available. In Raman spectroscopy of a surface, one measures the spectrum of laser light scattered inelastically from a laser-illuminated spot on the surface. The wavelengths of the inelastically scattered light differ from that of the incident laser beam by amounts that correspond to the energies of molecular vibrations. The resulting vibrational spectrum can be used to identify the molecules. Raman spectroscopy is a standard laboratory technique for identifying mineralogical, biological, and other specific chemical compositions.

Schramm, Harry F.↗
NASA NTRS2010

Spectral Indices to Monitor Nitrogen-Driven Carbon Uptake in Field Corn

Climate change is heavily impacted by changing vegetation cover and productivity with large scale monitoring of vegetation only possible with remote sensing techniques. The goal of this effort was to evaluate existing reflectance (R) spectroscopic methods for determining vegetation parameters related to photosynthetic function and carbon (C) dynamics in plants. Since nitrogen (N) is a key constituent of photosynthetic pigments and C fixing enzymes, biological C sequestration is regulated in part by N availability. Spectral R information was obtained from field corn grown at four N application rates (0, 70, 140, 280 kg N/ha). A hierarchy of spectral observations were obtained: leaf and canopy with a spectral radiometer; aircraft with the AISA sensor; and satellite with EO-1 Hyperion. A number of spectral R indices were calculated from these hyperspectral observations and compared to geo-located biophysical measures of plant growth and physiological condition. Top performing indices included the R derivative index D730/D705 and the normalized difference of R750 vs. R705 (ND705), both of which differentiated three of the four N fertilization rates at multiple observation levels and yielded high correlations to these carbon parameters: light use efficiency (LUE); C:N ratio; and crop grain yield. These results advocate the use of hyperspectral sensors for remotely monitoring carbon cycle dynamics in managed terrestrial ecosystems.

Corp, Lawrence A.↗
NASA NTRS2004

Coastal Research Imaging Spectrometer

The Coastal Research Imaging Spectrometer (CRIS) is an airborne remote sensing system designed specifically for research on the physical, chemical, and biological characteristics of coastal waters. The CRIS includes a visible-light hyperspectral imaging subsystem for measuring the color of water, which contains information on the biota, sediment, and nutrient contents of the water. The CRIS also includes an infrared imaging subsystem, which provides information on the temperature of the water. The combination of measurements enables investigation of biological effects of both natural and artificial flows of water from land into the ocean, including diffuse and point-source flows that may contain biological and/or chemical pollutants. Temperature is an important element of such measurements because temperature contrasts can often be used to distinguish among flows from different sources: for example, a sewage outflow could manifest itself in spectral images as a local high-temperature anomaly. Both the visible and infrared subsystems scan in pushbroom mode: that is, an aircraft carrying the system moves along a ground track, the system is aimed downward, and image data are acquired in across-track linear arrays of pixels. Both subsystems operate at a frame rate of 30 Hz. The infrared and visible-light optics are adjusted so that both subsystems are aimed at the same moving swath, which has across-track angular width of 15 . Data from the infrared and visible imaging subsystems are stored in the same file along with aircraft- position data acquired by a Global Positioning System receiver. The combination of the three sets of data is used to construct infrared and hyperspectral maps of scanned areas (see figure). The visible subsystem is based on a grating spectrograph and a rapid-readout charge-coupled-device camera. Images of the swatch are acquired in 256 spectral bands at wavelengths from 400 to 800 nm. The infrared subsystem, which is sensitive in a single wavelength band of 8 to 10 m, is based on a focal-plane array of HgCdTe photodetectors that are cooled to an operating temperature of 77 K by use of a closed-Stirling-cycle mechanical cooler. The nonuniformities of the HgCdTe photodetector array are small enough that the raw pixel data from the infrared subsystem can be used to recognize temperature differences on the order of 1 C. By use of a built-in blackbody calibration source that can be switched into the field of view, one can obtain bias and gain offset terms for individual pixels, making it possible to offset the effects of nonuniformities sufficiently to enable the measurement of temperature differences as small as 0.1 C.

Lucey, Paul G.↗
NASA NTRS2011

HyTES: Thermal Imaging Spectrometer Development

The Jet Propulsion Laboratory has developed the Hyperspectral Thermal Emission Spectrometer (HyTES). It is an airborne pushbroom imaging spectrometer based on the Dyson optical configuration. First low altitude test flights are scheduled for later this year. HyTES uses a compact 7.5-12 micrometer m hyperspectral grating spectrometer in combination with a Quantum Well Infrared Photodetector (QWIP) and grating based spectrometer. The Dyson design allows for a very compact and optically fast system (F/1.6). Cooling requirements are minimized due to the single monolithic prism-like grating design. The configuration has the potential to be the optimal science-grade imaging spectroscopy solution for high altitude, lighter-than-air (HAA, LTA) vehicles and unmanned aerial vehicles (UAV) due to its small form factor and relatively low power requirements. The QWIP sensor allows for optimum spatial and spectral uniformity and provides adequate responsivity which allows for near 100mK noise equivalent temperature difference (NEDT) operation across the LWIR passband. The QWIP's repeatability and uniformity will be helpful for data integrity since currently an onboard calibrator is not planned. A calibration will be done before and after eight hour flights to gage any inconsistencies. This has been demonstrated with lab testing. Further test results show adequate NEDT, linearity as well as applicable earth science emissivity target results (Silicates, water) measured in direct sunlight.

remote sensing↗
NASA NTRS2012

NASA Tech Briefs, June 2012

Topics covered include: iGlobe Interactive Visualization and Analysis of Spatial Data; Broad-Bandwidth FPGA-Based Digital Polyphase Spectrometer; Small Aircraft Data Distribution System; Earth Science Datacasting v2.0; Algorithm for Compressing Time-Series Data; Onboard Science and Applications Algorithm for Hyperspectral Data Reduction; Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data; Security Data Warehouse Application; Integrated Laser Characterization, Data Acquisition, and Command and Control Test System; Radiation-Hard SpaceWire/Gigabit Ethernet-Compatible Transponder; Hardware Implementation of Lossless Adaptive Compression of Data From a Hyperspectral Imager; High-Voltage, Low-Power BNC Feedthrough Terminator; SpaceCube Mini; Dichroic Filter for Separating W-Band and Ka-Band; Active Mirror Predictive and Requirement Verification Software (AMP-ReVS); Navigation/Prop Software Suite; Personal Computer Transport Analysis Program; Pressure Ratio to Thermal Environments; Probabilistic Fatigue Damage Program (FATIG); ASCENT Program; JPL Genesis and Rapid Intensification Processes (GRIP) Portal; Data::Downloader; Fault Tolerance Middleware for a Multi-Core System; DspaceOgreTerrain 3D Terrain Visualization Tool; Trick Simulation Environment 07; Geometric Reasoning for Automated Planning; Water Detection Based on Color Variation; Single-Layer, All-Metal Patch Antenna Element with Wide Bandwidth; Scanning Laser Infrared Molecular Spectrometer (SLIMS); Next-Generation Microshutter Arrays for Large-Format Imaging and Spectroscopy; Detection of Carbon Monoxide Using Polymer-Composite Films with a Porphyrin-Functionalized Polypyrrole; Enhanced-Adhesion Multiwalled Carbon Nanotubes on Titanium Substrates for Stray Light Control; Three-Dimensional Porous Particles Composed of Curved, Two-Dimensional, Nano-Sized Layers for Li-Ion Batteries 23 Ultra-Lightweight; and Ultra-Lightweight Nanocomposite Foams and Sandwich Structures for Space Structure Applications.

Source record↗
NASA NTRS2012

Recent Developments on Airborne Forward Looking Interferometer for the Detection of Wake Vortices

A goal of these studies was development of the measurement methods and algorithms necessary to detect wake vortex hazards in real time from either an aircraft or ground-based hyperspectral Fourier Transform Spectrometer (FTS). This paper provides an update on research to model FTS detection of wake vortices. The Terminal Area Simulation System (TASS) was used to generate wake vortex fields of 3-D winds, temperature, and absolute humidity. These fields were input to the Line by Line Radiative Transfer Model (LBLRTM), a hyperspectral radiance model in the infrared, employed for the FTS numerical modeling. An initial set of cases has been analyzed to identify a wake vortex IR signature and signature sensitivities to various state variables. Results from the numerical modeling case studies will be presented. Preliminary results indicated that an imaging IR instrument sensitive to six narrow bands within the 670 to 3150 per centimeter spectral region would be sufficient for wake vortex detection. Noise floor estimates for a recommended instrument are a current research topic.

Daniels, Taumi S.↗
NASA NTRS2012

The Photochemical Reflectance Index from Directional Cornfield Reflectances: Observations and Simulations

The two-layer Markov chain Analytical Canopy Reflectance Model (ACRM) was linked with in situ hyperspectral leaf optical properties to simulate the Photochemical Reflectance Index (PRI) for a corn crop canopy at three different growth stages. This is an extended study after a successful demonstration of PRI simulations for a cornfield previously conducted at an early vegetative growth stage. Consistent with previous in situ studies, sunlit leaves exhibited lower PRI values than shaded leaves. Since sunlit (shaded) foliage dominates the canopy in the reflectance hotspot (coldspot), the canopy PRI derived from field hyperspectral observations displayed sensitivity to both view zenith angle and relative azimuth angle at all growth stages. Consequently, sunlit and shaded canopy sectors were most differentiated when viewed along the azimuth matching the solar principal plane. These directional PRI responses associated with sunlit/shaded foliage were successfully reproduced by the ACRM. As before, the simulated PRI values from the current study were closer to in situ values when both sunlit and shaded leaves were utilized as model input data in a two-layer mode, instead of a one-layer mode with sunlit leaves only. Model performance as judged by correlation between in situ and simulated values was strongest for the mature corn crop (r = 0.87, RMSE = 0.0048), followed by the early vegetative stage (r = 0.78; RMSE = 0.0051) and the early senescent stage (r = 0.65; RMSE = 0.0104). Since the benefit of including shaded leaves in the scheme varied across different growth stages, a further analysis was conducted to investigate how variable fractions of sunlit/shaded leaves affect the canopy PRI values expected for a cornfield, with implications for 20 remote sensing monitoring options. Simulations of the sunlit to shaded canopy ratio near 50/50 +/- 10 (e.g., 60/40) matching field observations at all growth stages were examined. Our results suggest in the importance of the sunlit/shaded fraction and canopy structure in understanding and interpreting PRI.

Cheng, Yen-Ben↗
NASA NTRS2013

Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals

Mapping localized spectral features in large images demands sensitive and robust detection algorithms. Two aspects of large images that can harm matched-filter detection performance are addressed simultaneously. First, multimodal backgrounds may thwart the typical Gaussian model. Second, outlier features can trigger false detections from large projections onto the target vector. Two state-of-the-art approaches are combined that independently address outlier false positives and multimodal backgrounds. The background clustering models multimodal backgrounds, and the mixture tuned matched filter (MT-MF) addresses outliers. Combining the two methods captures significant additional performance benefits. The resulting mixture tuned clutter matched filter (MT-CMF) shows effective performance on simulated and airborne datasets. The classical MNF transform was applied, followed by k-means clustering. Then, each cluster s mean, covariance, and the corresponding eigenvalues were estimated. This yields a cluster-specific matched filter estimate as well as a cluster- specific feasibility score to flag outlier false positives. The technology described is a proof of concept that may be employed in future target detection and mapping applications for remote imaging spectrometers. It is of most direct relevance to JPL proposals for airborne and orbital hyperspectral instruments. Applications include subpixel target detection in hyperspectral scenes for military surveillance. Earth science applications include mineralogical mapping, species discrimination for ecosystem health monitoring, and land use classification.

Thompson, David R.↗