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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2016

A Synthesis of Star Calibration Techniques for Ground-Based Narrowband Electron-Multiplying Charge-Coupled Device Imagers Used in Auroral Photometry

A technique is presented for the periodic and systematic calibration of ground-based optical imagers. It is important to have a common system of units (Rayleighs or photon flux) for cross comparison as well as self-comparison over time. With the advancement in technology, the sensitivity of these imagers has improved so that stars can be used for more precise calibration. Background subtraction, flat fielding, star mapping, and other common techniques are combined in deriving a calibration technique appropriate for a variety of ground-based imager installations. Spectral (4278, 5577, and 8446 A ) ground-based imager data with multiple fields of view (19, 47, and 180 deg) are processed and calibrated using the techniques developed. The calibration techniques applied result in intensity measurements in agreement between different imagers using identical spectral filtering, and the intensity at each wavelength observed is within the expected range of auroral measurements. The application of these star calibration techniques, which convert raw imager counts into units of photon flux, makes it possible to do quantitative photometry. The computed photon fluxes, in units of Rayleighs, can be used for the absolute photometry between instruments or as input parameters for auroral electron transport models.

Grubbs, Guy II↗
NASA NTRS2001

Multi-Sensor Characterization of the Boreal Forest: Initial Findings

Results are presented in an initial apriori knowledge approach toward using complementary multi-sensor multi-temporal imagery in characterizing vegetated landscapes over a site in the Boreal Ecosystem-Atmosphere Study (BOREAS). Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data were segmented using multiple endmember spectral mixture analysis and binary decision tree approaches. Individual date/sensor land cover maps had overall accuracies between 55.0% - 69.8%. The best eight land cover layers from all dates and sensors correctly characterized 79.3% of the cover types. An overlay approach was used to create a final land cover map. An overall accuracy of 71.3% was achieved in this multi-sensor approach, a 1.5% improvement over our most accurate single scene technique, but 8% less than the original input. Black spruce was evaluated to be particularly undermapped in the final map possibly because it was also contained within jack pine and muskeg land coverages.

Reith, Ernest↗
NASA NTRS1993

Ultra low-noise charge coupled device

Special purpose CCD designed for ultra low-noise imaging and spectroscopy applications that require subelectron read noise floors, wherein a non-destructive output circuit operating near its 1/f noise regime is clocked in a special manner to read a single pixel multiple times. Off-chip electronics average the multiple values, reducing the random noise by the square-root of the number of samples taken. Noise floors below 0.5 electrons rms are possible in this manner. In a preferred embodiment of the invention, a three-phase CCD horizontal register is used to bring a pixel charge packet to an input gate adjacent a floating gate amplifier. The charge is then repeatedly clocked back and forth between the input gate and the floating gate. Each time the charge is injected into the potential well of the floating gate, it is sensed non-destructively. The floating gate amplifier is provided with a reference voltage of a fixed value and a pre-charge gate for resetting the amplifier between charge samples to a constant gain. After the charge is repeatedly sampled a selected number of times, it is transferred by means of output gates, back into the horizontal register, where it is clocked in a conventional manner to a diffusion MOSFET amplifier. It can then be either sampled (destructively) one more time or otherwise discarded.

Janesick, James R.↗
NASA NTRS2018

JPSS-1/NOAA-20 VIIRS Early On-Orbit Geometric Performance

The first NOAA/NASA Join Polar Satellite System (JPSS-1) satellite was successfully launched on November 18, 2017,becoming NOAA-20. Instruments on-board the NOAA-20 satellite include the Visible Infrared Imaging RadiometerSuite (VIIRS). This instrument is the second build of VIIRS, with the first flight instrument on-board NASA/NOAASuomi National Polar-orbiting Partnership (SNPP) satellite operating since October 2011. The purpose of these VIIRSinstruments is to continue the long-term measurements of biogeophysical variables for multiple applications includingweather forecasting, rapid response and climate research. The geometric performance of VIIRS is essential to retrievingaccurate biogeophysical variables. This paper describes the early on-orbit geometric performance of the JPSS-1/NOAA-20 VIIRS. It first discusses the on-orbit orbit and attitude performance, a key input needed for accurate geolocation. Itthen discusses the on-orbit geometric characterization and calibration of VIIRS and an initial assessment of thegeometric accuracy. It follows with a discussion of an improvement in the instrument geometric model that correctssmall geometrical artifacts that appear in the along-scan direction. Finally, this paper discusses on-orbit measurements ofthe focal length and the impact of this on the scan-to-scan underlap/overlap.

Lin, Guoqing↗
NASA NTRS2006

Grayscale Optical Correlator Workbench

Grayscale Optical Correlator Workbench (GOCWB) is a computer program for use in automatic target recognition (ATR). GOCWB performs ATR with an accurate simulation of a hardware grayscale optical correlator (GOC). This simulation is performed to test filters that are created in GOCWB. Thus, GOCWB can be used as a stand-alone ATR software tool or in combination with GOC hardware for building (target training), testing, and optimization of filters. The software is divided into three main parts, denoted filter, testing, and training. The training part is used for assembling training images as input to a filter. The filter part is used for combining training images into a filter and optimizing that filter. The testing part is used for testing new filters and for general simulation of GOC output. The current version of GOCWB relies on the mathematical software tools from MATLAB binaries for performing matrix operations and fast Fourier transforms. Optimization of filters is based on an algorithm, known as OT-MACH, in which variables specified by the user are parameterized and the best filter is selected on the basis of an average result for correct identification of targets in multiple test images.

Hanan, Jay↗
NASA NTRSDate not supplied

Using Polarized PCRTM-Solar Model to Validate EMIT Surface Reflectance L2A Product

Using the vector linearized discrete ordinate radiative transfer model (VLIDORT), a multiple-scattering multi-layer scattering code, coupled with a fast principal component (PC) radiative transfer model (PCRTM), we can simulate hyperspectral radiation fields from visible to shortwave infrared (VSWIR), i.e., 250 nm to 2500 nm. Since only limited accurate line-by-line calculation using VLIDORT is needed, this coupled PCRTM-VLIDORT approach is very efficient for simulating hyperspectral VSWIR spectra. These simulations incorporate accurately defined optical properties (gas absorptions, molecular and aerosol/cloud particle scattering) and detailed surface reflectance inputs. In this study we used the current L2A products of the Earth Surface Mineral Dust Source Investigation (EMIT) imaging spectrometer as the inputs to PCRTM-VLIDORT to simulate EMIT spectra. Comparing the simulated spectra with EMIT measurements provides an efficient method to validate the current EMIT product.

Xiaozhen Xiong↗
NASA NTRS1988

A hardware implementation of a relaxation algorithm to segment images

Relaxation labelling is a mathematical technique frequently applied in image processing algorithms. In particular, it is extensively used for the purpose of segmenting images. The paper presents a hardware implementation of a segmentation algorithm, for images consisting of two regions, based on relaxation labelling. The algorithm determines, for each pixel, the probability that it should be labelled as belonging to a particular region, for all regions in the image. The label probabilities (labellings) of every pixel are iteratively updated, based on those of the pixel's neighbors, until they converge. The pixel is then assigned to the region correspondent to the maximum label probability. The system consists of a control unit and of a pipeline of segmentation stages. Each segmentation stage emulates in the hardware an iteration of the relaxation algorithm. The design of the segmentation stage is based on commercially available digital signal processing integrated circuits. Multiple iterations are accomplished by stringing stages together or by looping the output of a stage, or string of stages, to its input. The system interfaces with a generic host computer. Given the modularity of the architecture, performance can be enhanced by merely adding segmentation stages.

Loda, Antonio G.↗
NASA NTRS2005

Vision Based Localization in Urban Environments

As part of DARPA's MARS2020 program, the Jet Propulsion Laboratory developed a vision-based system for localization in urban environments that requires neither GPS nor active sensors. System hardware consists of a pair of small FireWire cameras and a standard Pentium-based computer. The inputs to the software system consist of: 1) a crude grid-based map describing the positions of buildings, 2) an initial estimate of robot location and 3) the video streams produced by each camera. At each step during the traverse the system: captures new image data, finds image features hypothesized to lie on the outside of a building, computes the range to those features, determines an estimate of the robot's motion since the previous step and combines that data with the map to update a probabilistic representation of the robot's location. This probabilistic representation allows the system to simultaneously represent multiple possible locations, For our testing, we have derived the a priori map manually using non-orthorectified overhead imagery, although this process could be automated. The software system consists of two primary components. The first is the vision system which uses binocular stereo ranging together with a set of heuristics to identify features likely to be part of building exteriors and to compute an estimate of the robot's motion since the previous step. The resulting visual features and the associated range measurements are software component, a particle-filter based localization system. This system uses the map and the then fed to the second primary most recent results from the vision system to update the estimate of the robot's location. This report summarizes the design of both the hardware and software and will include the results of applying the system to the global localization of a robot over an approximately half-kilometer traverse across JPL'S Pasadena campus.

unmanned-ground vehicles↗
NASA NTRS2011

Science of Opportunity: Heliophysics on the FASTSAT Mission and STP-S26

The FASTSAT spacecraft, which was launched on November 19, 2010 on the DoD STP-S26 mission, carries three instruments developed in joint collaboration by NASA GSFC and the US Naval Academy: PISA, TTl, and MINI_ME.I,1 As part of a rapid-development, low-cost instrument design and fabrication program, these instruments were a perfect match for FASTSAT, which was designed and built in less than one year. These instruments, while independently developed, provide a collaborative view of important processes in the upper atmosphere relating to solar and energetic particle input, atmospheric response, and ion outflow. PISA measures in-situ irregularities in electron number density, TIl provides limb measurements of the atomic oxygen temperature profile with altitude, and MINI-ME provides a unique look at ion populations by a remote sen sing technique involving neutral atom imaging. Together with other instruments and payloads on STP-S26 such as the NSF RAX mission, FalconSat-5, and NanoSail-D (launched as a tertiary payload from FASTSAT), these instruments provide a valuable "constellation of opportunity" for following the now of energy and charged and neutral particles through the upper atmosphere. Together, and for a small fraction of the price of a major mission, these spacecraft will measure the energetic electrons impacting the upper atmosphere, the ions leaving it, and the large-scale plasma and neutral response to these energy inputs. The result will be a new model for maximizing scientific return from multiple small, distributed payloads as secondary payloads on a larger launch vehicle.

Rowland, Douglas E.↗
NASA NTRS2010

FASTSAT-HSV01 Synergistic Observations of the Magnetospheric Response During Active Periods: MINI-ME, PISA and TTI

Understanding the complex processes within the inner magnetosphere of Earth particularly during storm periods requires coordinated observations of the particle and field environment using both in-situ and remote sensing techniques. In fact in order to gain a better understanding of our Heliophysics and potentially improve our space weather forecasting capabilities, new observation mission approaches and new instrument technologies which can provide both cost effective and robust regular observations of magnetospheric activity and other space weather related phenomenon are necessary. As part of the effort to demonstrate new instrument techniques and achieve necessary coordinated observation missions, NASA's Fast Affordable Science and Technology Satellite Huntsville 01 mission (FASTSAT-HSVOI) scheduled for launch in 2010 will afford a highly synergistic solution which satisfies payload mission opportunities and launch requirements as well as contributing iri the near term to our improved understanding of Heliophysics. NASA's FASTSAT-HSV01 spacecraft on the DoD Space Test Program-S26 (STP-S26) Mission is a multi-payload mission executed by the DoD Space Test Program (STP) at the Space Development and Test Wing (SDTW), Kirtland AFB, NM. and is an example of a responsive and economical breakthrough in providing new possibilities for small space technology-driven and research missions. FASTSAT-HSV is a unique spacecraft platform that can carry multiple small instruments or experiments to low-Earth orbit on a wide range of expendable launch vehicles for a fraction of the cost traditionally required for such missions. The FASTSAT-HSV01 mission allows NASA to mature and transition a technical capability to industry while increasing low-cost access to space for small science and technology (ST) payloads. The FASTSAT-HSV01 payload includes three NASA Goddard Space Flight Center (GSFC) new technology built instruments that will study the terrestrial space environment and potentially contribute to space weather research in a synergistic manner. MINI-ME, a neutral atom imager, will observe the neutral atom inputs to ionospheric heating which can be important during high levels of magnetospheric activity. PISA, a plasma impedance spectrometer, will measure simultaneously the local electron densities and temperatures as well as measure small scale density structure (500 m spatial scale) during these active periods. TTI, a thermospheric imager, will remotely determine the thermospheric temperature response to this magnetospheric activity. Together, these observations will contribute significantly to a comprehensive understanding of the flow of energy through and the response of the storm-time terrestrial magnetosphere.

Casas, Joseph C.↗
NASA NTRS2023

A Synthetic Roman Space Telescope High-Latitude Time-Domain Survey: Supernovae in the Deep Field

NASA will launch the Nancy Grace Roman Space Telescope (hereafter Roman ) in the second half of this decade, which will allow for a generation-defining measurement of dark energy through multiple probes, including Type Ia supernovae (SNe Ia). To impro v e decisions on surv e y strate gy, we hav e created the first simulations of realistic Roman images that include artificial SNe Ia injected as point sources in the images. Our analysis combines work done on Roman simulations for weak gravitational lensing studies as well as catalogue-level simulations of SN Ia samples. We have created a time series of images o v er 2 yr containing ∼1050 SNe Ia, co v ering a 1 deg 2 subarea of a planned 5 deg 2 deep survey. We have released these images publicly for community use along with input catalogues of all injected sources. We create secondary products from these images by generating coadded images and demonstrating reco v ery of transient sources using image subtraction. We perform first-use analyses on these images in order to measure galaxy detection efficiency, point source detection efficiency, and host-galaxy association biases. The simulated images can be found here at https:// roman.ipac.caltech.edu/sims/ SN Survey Image sim.html .

supernovae↗
NASA NTRS1993

Estimation of crown closure from AVIRIS data using regression analysis

Crown closure is one of the input parameters used for forest growth and yield modelling. Preliminary work by Staenz et al. indicates that imaging spectrometer data acquired with sensors such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) have some potential for estimating crown closure on a stand level. The objectives of this paper are: (1) to establish a relationship between AVIRIS data and the crown closure derived from aerial photography of a forested test site within the Interior Douglas Fir biogeoclimatic zone in British Columbia, Canada; (2) to investigate the impact of atmospheric effects and the forest background on the correlation between AVIRIS data and crown closure estimates; and (3) to improve this relationship using multiple regression analysis.

Staenz, K.↗
NASA NTRS2008

Orchestrator Telemetry Processing Pipeline

Orchestrator is a software application infrastructure for telemetry monitoring, logging, processing, and distribution. The architecture has been applied to support operations of a variety of planetary rovers. Built in Java with the Eclipse Rich Client Platform, Orchestrator can run on most commonly used operating systems. The pipeline supports configurable parallel processing that can significantly reduce the time needed to process a large volume of data products. Processors in the pipeline implement a simple Java interface and declare their required input from upstream processors. Orchestrator is programmatically constructed by specifying a list of Java processor classes that are initiated at runtime to form the pipeline. Input dependencies are checked at runtime. Fault tolerance can be configured to attempt continuation of processing in the event of an error or failed input dependency if possible, or to abort further processing when an error is detected. This innovation also provides support for Java Message Service broadcasts of telemetry objects to clients and provides a file system and relational database logging of telemetry. Orchestrator supports remote monitoring and control of the pipeline using browser-based JMX controls and provides several integration paths for pre-compiled legacy data processors. At the time of this reporting, the Orchestrator architecture has been used by four NASA customers to build telemetry pipelines to support field operations. Example applications include high-volume stereo image capture and processing, simultaneous data monitoring and logging from multiple vehicles. Example telemetry processors used in field test operations support include vehicle position, attitude, articulation, GPS location, power, and stereo images.

Powell, Mark↗
NASA NTRS2013

On-Orbit Lunar Modulation Transfer Function Measurements for the Moderate Resolution Imaging Spectroradiometer

Spatial quality of an imaging sensor can be estimated by evaluating its modulation transfer function (MTF) from many different sources such as a sharp edge, a pulse target, or bar patterns with different spatial frequencies. These well-defined targets are frequently used for prelaunch laboratory tests, providing very reliable and accurate MTF measurements. A laboratory-quality edge input source was included in the spatial-mode operation of the Spectroradiometric Calibration Assembly (SRCA), which is one of the onboard calibrators of the Moderate Resolution Imaging Spectroradiometer (MODIS). Since not all imaging satellites have such an instrument, SRCA MTF estimations can be used as a reference for an on-orbit lunar MTF algorithm and results. In this paper, the prelaunch spatial quality characterization process from the Integrated Alignment Collimator and SRCA is briefly discussed. Based on prelaunch MTF calibration using the SRCA, a lunar MTF algorithm is developed and applied to the lifetime on-orbit Terra and Aqua MODIS lunar collections. In each lunar collection, multiple scan-directionMoon-to-background transition profiles are aligned by the subpixel edge locations from a parametric Fermi function fit. Corresponding accumulated edge profiles are filtered and interpolated to obtain the edge spread function (ESF). The MTF is calculated by applying a Fourier transformation on the line spread function through a simple differentiation of the ESF. The lifetime lunar MTF results are analyzed and filtered by a relationship with the Sun-Earth-MODIS angle. Finally, the filtered lunarMTF values are compared to the SRCA MTF results. This comparison provides the level of accuracy for on-orbit MTF estimations validated through prelaunch SRCA measurements. The lunar MTF values had larger uncertainty than the SRCA MTF results; however, the ratio mean of lunarMTF fit and SRCA MTF values is within 2% in the 250- and 500-m bands. Based on the MTF measurement uncertainty range, the suggested lunar MTF algorithm can be applied to any on-orbit imaging sensor with lunar calibration capability.

Choi, Taeyong↗
NASA NTRS2014

Exploring NASA OMI Level 2 Data With Visualization

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms, etc.).Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as images, with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data-map sources.

Level 2↗
NASA NTRS2014

Exploring NASA OMI Level 2 Data With Visualization

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms,... etc.). Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as "images", with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data/map sources.

Aura↗
NASA NTRS1980

Studies of auroral X-ray imaging from high altitude spacecraft

Results of a study of techniques for imaging the aurora from a high altitude satellite at X-ray wavelengths are summarized. The X-ray observations allow the straightforward derivation of the primary auroral X-ray spectrum and can be made at all local times, day and night. Five candidate imaging systems are identified: X-ray telescope, multiple pinhole camera, coded aperture, rastered collimator, and imaging collimator. Examples of each are specified, subject to common weight and size limits which allow them to be intercompared. The imaging ability of each system is tested using a wide variety of sample spectra which are based on previous satellite observations. The study shows that the pinhole camera and coded aperture are both good auroral imaging systems. The two collimated detectors are significantly less sensitive. The X-ray telescope provides better image quality than the other systems in almost all cases, but a limitation to energies below about 4 keV prevents this system from providing the spectra data essential to deriving electron spectra, energy input to the atmosphere, and atmospheric densities and conductivities. The orbit selection requires a tradeoff between spatial resolution and duty cycle.

Mckenzie, D. L.↗
NASA NTRS2007

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

This report details one of three experiments performed during FY 2007 for the NASA RPC (Rapid Prototyping Capability) at Stennis Space Center. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria dispar). The intent of the RPC experiment was to assess the degree to which VIIRS data can provide forest disturbance monitoring information as an input to a forest threat EWS (Early Warning System) as compared to the level of information that can be obtained from MODIS data. The USDA Forest Service (USFS) plans to use MODIS products for generating broad-scaled, regional monitoring products as input to an EWS for forest health threat assessment. NASA SSC is helping the USFS to evaluate and integrate currently available satellite remote sensing technologies and data products for the EWS, including the use of MODIS products for regional monitoring of forest disturbance. Gypsy moth defoliation of the mid-Appalachian highland region was selected as a case study. Gypsy moth is one of eight major forest insect threats listed in the Healthy Forest Restoration Act (HFRA) of 2003; the gypsy moth threatens eastern U.S. hardwood forests, which are also a concern highlighted in the HFRA of 2003. This region was selected for the project because extensive gypsy moth defoliation occurred there over multiple years during the MODIS operational period. This RPC experiment is relevant to several nationally important mapping applications, including agricultural efficiency, coastal management, ecological forecasting, disaster management, and carbon management. In this experiment, MODIS data and VIIRS data simulated from MODIS were assessed for their ability to contribute broad, regional geospatial information on gypsy moth defoliation. Landsat and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data were used to assess the quality of gypsy moth defoliation mapping products derived from MODIS data and from simulated VIIRS data. The project focused on use of data from MODIS Terra as opposed to MODIS Aqua mainly because only MODIS Terra data was collected during 2000 and 2001-years with comparatively high amounts of gypsy moth defoliation within the study area. The project assessed the quality of VIIRS data simulation products. Hyperion data was employed to assess the quality of MODIS-based VIIRS simulation datasets using image correlation analysis techniques. The ART (Application Research Toolbox) software was used for data simulation. Correlation analysis between MODIS-simulated VIIRS data and Hyperion-simulated VIIRS data for red, NIR (near-infrared), and NDVI (Normalized Difference Vegetation Index) image data products collectively indicate that useful, effective VIIRS simulations can be produced using Hyperion and MODIS data sources. The r(exp 2) for red, NIR, and NDVI products were 0.56, 0.63, and 0.62, respectively, indicating a moderately high correlation between the 2 data sources. Temporal decorrelation from different data acquisition times and image misregistration may have lowered correlation results. The RPC experiment also generated MODIS-based time series data products using the TSPT (Time Series Product Tool) software. Time series of simulated VIIRS NDVI products were produced at approximately 400-meter resolution GSD (Ground Sampling Distance) at nadir for comparison to MODIS NDVI products at either 250- or 500-meter GSD. The project also computed MODIS (MOD02) NDMI (Normalized Difference Moisture Index) products at 500-meter GSD for comparison to NDVI-based products. For each year during 2000-2006, MODIS and VIIRS (simulated from MOD02) time series were computed during the peak gypsy moth defoliation time frame in the study area (approximately June 10 through July 27). Gypsy moth defoliation mapping products from simated VIIRS and MOD02 time series were produced using multiple methods, including image classification and change detection via image differencing. The latter enabled an automated defoliation detection product computed using percent change in maximum NDVI for a peak defoliation period during 2001 compared to maximum NDVI across the entire 2000-2006 time frame. Final gypsy moth defoliation mapping products were assessed for accuracy using randomly sampled locations found on available geospatial reference data (Landsat and ASTER data in conjunction with defoliation map data from the USFS). Extensive gypsy moth defoliation patches were evident on screen displays of multitemporal color composites derived from MODIS data and from simulated VIIRS vegetation index data. Such defoliation was particularly evident for 2001, although widespread denuded forests were also seen for 2000 and 2003. These visualizations were validated using aforementioned reference data. Defoliation patches were visible on displays of MODIS-based NDVI and NDMI data. The viewing of apparent defoliation patches on all of these products necessitated adoption of a specialized temporal data processing method (e.g., maximum NDVI during the peak defoliation time frame). The frequency of cloud cover necessitated this approach. Multitemporal simulated VIIRS and MODIS Terra data both produced effective general classifications of defoliated forest versus other land cover. For 2001, the MOD02-simulated VIIRS 400-meter NDVI classification produced a similar yet slightly lower overall accuracy (87.28 percent with 0.72 Kappa) than the MOD02 250-meter NDVI classification (88.44 percent with 0.75 Kappa). The MOD13 250-meter NDVI classification had a lower overall accuracy (79.13 percent) and a much lower Kappa (0.46). The report discusses accuracy assessment results in much more detail, comparing overall classification and individual class accuracy statistics for simulated VIIRS 400-meter NDVI, MOD02 250-meter NDVI, MOD02-500 meter NDVI, MOD13 250-meter NDVI, and MOD02 500-meter NDMI classifications. Automated defoliation detection products from simulated VIIRS and MOD02 data for 2001 also yielded similar, relatively high overall classification accuracy (85.55 percent for the VIIRS 400-meter NDVI versus 87.28 percent for the MOD02 250-meter NDVI). In contrast, the USFS aerial sketch map of gypsy moth defoliation showed a lower overall classification accuracy at 73.64 percent. The overall classification Kappa values were also similar for the VIIRS (approximately 0.67 Kappa) versus the MOD02 (approximately 0.72 Kappa) automated defoliation detection product, which were much higher than the values exhibited by the USFS sketch map product (overall Kappa of approximately 0.47). The report provides additional details on the accuracy of automated gypsy moth defoliation detection products compared with USFS sketch maps. The results suggest that VIIRS data can be effectively simulated from MODIS data and that VIIRS data will produce gypsy moth defoliation mapping products that are similar to MODIS-based products. The results of the RPC experiment indicate that VIIRS and MODIS data products have good potential for integration into the forest threat EWS. The accuracy assessment was performed only for 2001 because of time constraints and a relative scarcity of cloud-free Landsat and ASTER data for the peak defoliation period of the other years in the 2000-2006 time series. Additional work should be performed to assess the accuracy of gypsy moth defoliation detection products for additional years.The study area (mid-Appalachian highlands) and application (gypsy moth forest defoliation) are not necessarily representative of all forested regions and of all forest threat disturbance agents. Additional work should be performed on other inland and coastal regions as well as for other major forest threats.

Spruce, Joseph P.↗