Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Synthetic Basin”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Terrestrial Water Mass Load Changes from Gravity Recovery and Climate Experiment (GRACE)

Recent studies show that data from the Gravity Recovery and Climate Experiment (GRACE) is promising for basin- to global-scale water cycle research. This study provides varied assessments of errors associated with GRACE water storage estimates. Thirteen monthly GRACE gravity solutions from August 2002 to December 2004 are examined, along with synthesized GRACE gravity fields for the same period that incorporate simulated errors. The synthetic GRACE fields are calculated using numerical climate models and GRACE internal error estimates. We consider the influence of measurement noise, spatial leakage error, and atmospheric and ocean dealiasing (AOD) model error as the major contributors to the error budget. Leakage error arises from the limited range of GRACE spherical harmonics not corrupted by noise. AOD model error is due to imperfect correction for atmosphere and ocean mass redistribution applied during GRACE processing. Four methods of forming water storage estimates from GRACE spherical harmonics (four different basin filters) are applied to both GRACE and synthetic data. Two basin filters use Gaussian smoothing, and the other two are dynamic basin filters which use knowledge of geographical locations where water storage variations are expected. Global maps of measurement noise, leakage error, and AOD model errors are estimated for each basin filter. Dynamic basin filters yield the smallest errors and highest signal-to-noise ratio. Within 12 selected basins, GRACE and synthetic data show similar amplitudes of water storage change. Using 53 river basins, covering most of Earth's land surface excluding Antarctica and Greenland, we document how error changes with basin size, latitude, and shape. Leakage error is most affected by basin size and latitude, and AOD model error is most dependent on basin latitude.

Seo, K.-W.↗
NASA NTRS2010

Proceedings of the Astrobiology Science Conference 2010. Evolution and Life: Surviving Catastrophes and Extremes on Earth and Beyond

The Program of the 2010 Astrobiology Science Conference: Evolution and Life: Surviving Catastrophes and Extremes on Earth and Beyond, included sessions on: 50 Years of Exobiology and Astrobiology: Greatest Hits; Extraterrestrial Molecular Evolution and Pre-Biological Chemistry: From the Interstellar Medium to the Solar System I; Human Exploration, Astronaut Health; Diversity in Astrobiology Research and Education; Titan: Past, Present, and Future; Energy Flow in Microbial Ecosystems; Extraterrestrial Molecular Evolution and Prebiological Chemistry: From the Interstellar Medium to the Solar System II; Astrobiology in Orbit; Astrobiology and Interdisciplinary Communication; Science from Rio Tinto: An Acidic Environment; Can We Rule Out Spontaneous Generation of RNA as the Key Step in the Origin of Life?; How Hellish Was the Hadean Earth?; Results from ASTEP and Other Astrobiology Field Campaigns I; Prebiotic Evolution: From Chemistry to Life I; Adaptation of Life in Hostile Space Environments; Extrasolar Terrestrial Planets I: Formation and Composition; Collaborative Tools and Technology for Astrobiology; Results from ASTEP and Other Astrobiology Field Campaigns II; Prebiotic Evolution: From Chemistry to Life II; Survival, Growth, and Evolution of Microrganisms in Model Extraterrestrial Environments; Extrasolar Terrestrial Planets II: Habitability and Life; Planetary Science Decadal Survey Update; Astrobiology Research Funding; Bioessential Elements Through Space and Time I; State of the Art in Life Detection; Terrestrial Evolution: Implications for the Past, Present, and Future of Life on Earth; Psychrophiles and Polar Environments; Life in Volcanic Environments: On Earth and Beyond; Geochronology and Astrobiology On and Off the Earth; Bioessential Elements Through Space and Time II; Origins and Evolution of Genetic Systems; Evolution of Advanced Life; Water-rich Asteroids and Moons: Composition and Astrobiological Potential; Impact Events and Evolution; A Warm, Wet Mars?; Titan Versus Europa - Potential for Astrobiology; Habitability Potential of Mars; Biosignatures: Tools and Development I; Origins of Molecular Asymmetry, Homochirality, and Life Detection; Deserts and Evaporite Basins and Associated Microbialite Systems; Ancient Life and Synthetic Biology: Crossroad of the Past and Future; Biosignatures: Tools and Development II; Free Oxygen: Proxies, Causes, and Consequences; Life in Modern Microbialite Systems - Function and Adaptation; Hydrothermal Systems and Organosynthesis Processes: Origin and Evolution of Life; Where Should We Go on Mars to Seek Signs of Life?; Search for Intelligent Life I. Innovative SETI Observing Programs and Future Directions; Integrating Astrobiology Research Across and Beyond the Community; Education in Astrobiology in K-12; Search for Intelligent Life II. Global Engagement and Interstellar Message Construction; Poster sessions included: Extraterrestrial Molecular Evolution and Pre-Biological Chemistry; Prebiotic Evolution: From Chemistry to Life; RNA World; Terrestrial Evolution: Implications for the Past, Present, and Future of Life on Earth; Hydrothermal Systems and Organosynthesis Processes: Origin and Evolution of Life; Virology and Astrobiology; Horizontal Genetic Transfer and Properties of Ancestral Organisms; Life in Volcanic Environments: On Earth and Beyond; Impact Events and Evolution; Evolution of Advanced Life; Evolution of Intelligent Life; Education in Astrobiology in K-12; Origins of Molecular Asymmetry, Homochirality, and Life Detection; Astrobiology and Interdisciplinary Communication; Diversity in Astrobiology Research and Education; Integrating Astrobiology Research Across and Beyond the Community; Policy and Societal Issues: Dealing with Potential Bumps in the Astrobiology Road Ahead; Results from ASTEP and Other Astrobiology Field Campaigns; Energy Flow in Microbial Ecosystems; Psychrophiles and Polar Environments; Deserts and Evaporite Basins and Associated Microbialite stems; Life in Modern Microbialite Systems - Function and Adaptation; Free Oxygen: Proxies, Causes, and Consequences; Bioessential Elements Through Space and Time; Water-rich Asteroids and Moons: Composition and Astrobiological Potential; Biosignatures: Tools and Developments; Robotics and Instrumentation for Astrobiology; State of the Art in Life Detection; Astrobiology in Orbit; Survival, Growth, and Evolution of Microrganisms in Model Extraterrestrial Evolution; Search for Intelligent Life; Habitability Potential of Mars; How and Where Should We Seek Signs of Life on Mars?; Titan: Past, Present, and Future; Extrasolar Terrestrial Planets: Formation, Composition, Diversity, Habitability and Life; Human Exploration, Astronaut Health; Science from Rio Tinto: An Acidic Environment and Adaptation of Life in Hostile Space Environments;

Source record↗
NASA NTRS1985

Multisensor Data Integration Techniques

The availability of data from sensors operating in several different wavelength regions had led to the development of new techniques and strategies for both data management and image analysis. Work is ongoing to develop computer techniques for analysis of integrated data sets. These techniques include coregistration of multisensor images, rectification of radar images in areas of topographic relief to ensure pixel to pixel registration with planimetric data sets, calibration of data so that signatures can be applied to remote areas, normalization of data acquired with disparate sensors and determination of extended spectral signatures of surface units. In addition, software is being developed to analyze coregistrated digital terrain and image data so that automated stratigraphic and structural analyses can be performed. These software procedures include: strike and dip determination, terrain profile generation, stratigraphic column generation, stratigraphic thickness measurements, structural cross-section generation, and creation of 3-D block diagrams. These techniques were applied to coregistered LANDSAT 4 Thematic Mapper (TM), Thermal Infrared Multispectral Scanner (TIMS), and multipolarization synthetic aperture radar (SAR) data of the Wind River Basin in Wyoming.

Evans, D. L.↗
NASA NTRS1997

Interpretation of ERS-SAR images over urban surfaces

The results of a preliminary analysis of ERS synthetic aperture radar (SAR) images collected over the Los Angeles basin (CA) are reported. The observations were performed in order to explore the applicability of microwave remote sensing to the study of the energy balance at the urban surface. Large variations of backscatter intensities were observed in the SAR images. The imaging anisotropies observed mask the variations of backscatter due to other processes, illustrating the difficulties of extracting quantitative information from SAR images of urban surfaces.

Dousset, Benedicte↗
NASA NTRSDate not supplied

Harmonized Sentinel-1 SAR Global River Geometry and Inundation Database

Satellite-based observations on river geometries are sporadic in time, space, or both. Most satellite-based surface water maps, river widths, water surface elevations (WSE), slopes, and bathymetry are asynchronized in time and space. The current configuration of satellites such as Sentinel-6 measured the WSE but is missing the river width, slopes, and depths. To advance hydrological sciences research, there is a need to produce a harmonized time series of river geometry data of non-SWOT satellites in partnership with the upcoming SWOT mission. The SWOT satellite will measure river width, height, and slope but missing river depth measurements in space and time. Further, none of these current satellites measure the WSE, river width, and slopes synchronously. In this work, we use the Sentinel-1 SAR satellite data archive from 2015 to the present to create a global river width and surface water database at the reach scale. A modified version of the Sentinel SAR surface water classification algorithm from ASF is used to quantify the surface water extent on the stream approximately every six days (at the equator) at 10m spatial resolution globally. This 10m water mask is fed into a workflow to quantify the river widths, surface water inundations, slopes, and synthetic bathymetry in SWORD (SWOT River Database) stream networks. A Satellite HAND is used to address the cloud obscured surface water observations using a trained machine learning algorithm. We use WSE derived from the Global Water Monitor from NASA GSFC, Hydroweb from LEGOS, and ICESat-2 to harmonize the WSE observation. And Landsat-8/9 and Sentinel-2 water observations to fill the gaps in the Sentinel-1 SAR database. We use Congo River Basin as a test case where we have more than 500 radar altimetry-based WSE, continuous series of Sentinel-1, ICESat-2, Landsat-8/9, and Sentinel-2 observations. A Congo River hydrologic model is used to generate the streamflow discharge. The satellite observed river reaches are assimilated with the stream flows computed by the routing models. And the downstream reaches in the river network without satellite observations get optimized for discharge/river geometry at each observation cycle. Our final product is a harmonized river geometry dataset (reach's water extent, WSE, slope, synthetic bathymetry) for Congo Basin's SWORD reaches.

Chandana Gangodagamage↗
NASA NTRS2008

Validation of a Remote Sensing Based Index of Forest Disturbance Using Streamwater Nitrogen Data

Vegetation disturbances are known to alter the functioning of forested ecosystems by contributing to export ('leakage') of dissolved nitrogen (N), typically nitrate-N, from watersheds that can contribute to acidification of acid-sensitive streams, leaching of base cations, and eutrophication of downstream receiving waters. Yet, at a landscape scale, direct evaluation of how disturbance is linked to spatial variability in N leakage is complicated by the fact that disturbances operate at different spatial scales, over different timescales, and at different intensities. In this paper we explore whether data from synoptic streamwater surveys conducted in an Appalachian oak-dominated forested river basin in western MD (USA) can be used to test and validate a scalable, synthetic, and integrative forest disturbance index (FDI) derived from Landsat imagery. In particular, we found support for the hypothesis that the interannual variation in spring baseflow total dissolved nitrogen (TDN) and nitrate-N concentrations measured at 35 randomly selected stream stations varied as a linear function of the change in FDI computed for the corresponding set of subwatersheds. Our results demonstrate that the combined effects of forest disturbances can be detected using synoptic water quality data. It appears that careful timing of the synoptic baseflow sampling under comparable phenological and hydrometeorological conditions increased our ability to identify a forest disturbance signal.

Eshleman, Keith N.↗
NASA NTRS1976

Selection of remote sensing techniques - Surface roughness information from 3 cm wavelength SLAR images

The value of SLAR (Side-Looking Airborne Radar) image data for detecting and measuring small-scale surface roughness is examined, using as an example the Cottonball Basin in Death Valley National Monument, California. The SLAR image was obtained by an X-band (3 cm wavelength) synthetic aperture radar system operated at an altitude of 10,732 m above sea level. The polarization of the transmitted and received signals was horizontal. Film density values were used to produce color hypsometric maps of small-scale surface irregularities. It is shown that semi-quantitative surface roughness information, from uniquely flat surfaces such as the Cottonball Basin, can be obtained by analysis of 3 cm wavelength SLAR images calibrated by limited field measurements. Quantitative roughness data could be obtained with proper consideration of modifying surface and radar system parameters.

Schaber, G. G.↗
NASA NTRS2020

Central Valley Water Resources: Improving California Groundwater Assessments using GRACE and InSAR Datasets for Water Resource Management

California’s Central Valley is one of the most productive agricultural areas in the world, producing approximately $20 billion in crops annually. The recent California droughts of 2007-2010 and 2011-2017 resulted in increased groundwater pumping in the Central Valley to adequately irrigate farmland. Overdrafting of the Central Valley aquifer results in groundwater depletion, land subsidence, and permanent loss of groundwater storage. In 2014, depletion of groundwater led the state of California to enact the Sustainable Groundwater Management Act (SGMA), requiring critically overdrafted, high, and medium priority sub-basins to reach sustainable levels of groundwater pumping and recharge by 2042. SGMA allows local Groundwater Sustainability Agencies the authority to create Groundwater Sustainability Plans at the sub-basin level. To assist California’s Department of Water Resources, this project quantified groundwater change and land subsidence in Central Valley sub-basins with sparse or unreliable well and GPS data. This was done using NASA’s Gravity Recovery and Climate Experiment (GRACE), GRACE Follow-On (GRACE-FO), and interferograms derived from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2). Time series of the GRACE and InSAR data were compared with well and GPS data in data-dense sub-basins to determine the feasibility of these datasets for groundwater storage and subsidence monitoring. We found thatGRACE and InSAR data are effective tools for determining groundwater change and land subsidence and can be used on their own to monitor sub-basins in the absence of well and GPS data.

Water Resources↗
NASA NTRS2021

Data Assimilation of Terrestrial Water Storage Observations to Estimate Precipitation Fluxes: A Synthetic Experiment

The Gravity Recovery and Climate Experiment (GRACE) mission and its Follow-On (GRACE-FO) mission provide unprecedented observations of terrestrial water storage (TWS) dynamics at basin to continental scales. Established GRACE data assimilation techniques directly adjust the simulated water storage components to improve the estimation of groundwater, streamflow, and snow water equivalent. Such techniques artificially add/subtract water to/from prognostic variables, thus upsetting the simulated water balance. To overcome this limitation, we propose and test an alternative assimilation scheme in which precipitation fluxes are adjusted to achieve the desired changes in simulated TWS. Using a synthetic data assimilation experiment, we show that the scheme improves performance skill in precipitation estimates in general, but that it is more robust for snowfall than for rainfall, and it fails in certain regions with strong horizontal gradients in precipitation. The results demonstrate that assimilation of TWS observations can help correct (adjust) the model’s precipitation forcing and, in turn, enhance model estimates of TWS, snow mass, soil moisture, runoff, and evaporation. A key limitation of the approach is the assumption that all errors in TWS originate from errors in precipitation. Nevertheless, the proposed approach produces more consistent improvements in simulated runoff than the established GRACE data assimilation techniques.

Data Assimilation↗
NASA NTRS2020

Central Valley Water Resources: Improving California Groundwater Assessments using GRACE and InSAR Datasets for Water Resource Management

California’s Central Valley is one of the most productive agricultural areas in the world, producing approximately $20 billion in crops annually. The recent California droughts of 2007-2010 and 2012-2019 resulted in increased groundwater pumping in the Central Valley to adequately irrigate farmland. Overdrafting of the Central Valley aquifer results in groundwater depletion, land subsidence, and permanent loss of groundwater storage. In 2014, depletion of groundwater led the state of California to enact the Sustainable Groundwater Management Act (SGMA),requiring critically overdrafted, high, and medium priority sub-basins to reach sustainable levels of groundwater pumping and recharge by 2042. SGMA allows local Groundwater Sustainability Agencies (GSAs) the authority to create Groundwater Sustainability Plans (GSPs) at the sub-basin level. To assist California’s Department of Water Resources (DWR), this project quantified groundwater change and land subsidence in Central Valley sub-basins with sparse or unreliable well and Geographic Positioning Systems (GPS) data. This was done using NASA’s Gravity Recovery and Climate Experiment (GRACE), GRACE FollowOn (GRACE-FO), and interferograms derived from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and Advanced Land Observing Satellite 2 (ALOS-2)Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2). Time series of the GRACE and InSAR data were compared with well and GPS data in data-dense sub-basins to determine the feasibility of these datasets for groundwater storage and subsidence monitoring. We found that GRACE and InSAR data are effective tools for determining groundwater change and land subsidence and can be used on their own to monitor sub-basins in the absence of well and GPS data

Water Resources↗
NASA NTRS2022

Using Sentinel-1 and GRACE Satellite Data to Monitor the Hydrological Variations Within the Tulare Basin, California

Subsidence induced by groundwater depletion is a grave problem in many regions around the world, leading to a permanent loss of groundwater storage within an aquifer and even producing structural damage at the Earth’s surface. California’s Tulare Basin is no exception, experiencing about a meter of subsidence between 2015 and 2020. However, understanding the relationship between changes in groundwater volumes and ground deformation has proven difficult. We employ surface displacement measurements from Interferometric Synthetic Aperture Radar (InSAR) and gravimetric estimates of terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE) satellite pair to characterize the hydrological dynamics within the Tulare basin. The removal of the long-term aquifer compaction from the InSAR time series reveals coherent short-term variations that correlate with hydrological features. For example, in the winter of 2018–2019 uplift is observed at the confluence of several rivers and streams that drain into the southeastern edge of the basin. These observations, combined with estimates of mass changes obtained from the orbiting GRACE satellites, form the basis for imaging the monthly spatial variations in water volumes. This approach facilitates the quick and effective synthesis of InSAR and gravimetric datasets and will aid efforts to improve our understanding and management of groundwater resources around the world.

Donald W. Vasco↗
NASA NTRS2020

Great Lakes Water Resources II: A Google Earth Engine Tool to Automate Wetland Mapping Using Optical and Radar Satellite Sensors in the Great Lakes Basin for Wetland Management and Monitoring

The Great Lakes Basin is one of the world’s largest freshwater ecosystems. The Basin harbors over 200,000 acres of wetlands. These wetlands provide a variety of environmental, ecological, and recreational functions to over 30 million people in the region. Some of these functions include improving water quality, mitigating flood impacts, providing wildlife habitat, and housing recreational activities. However, due to anthropogenic activities, habitat conversion and degradation threaten to disrupt or destroy remaining wetland ecosystems. Maps of wetland distribution based on ground surveys are costly and labor-intensive, prohibiting timely evaluations of wetland loss and gain. The Great Lakes Water Resources II team at the NASA Jet Propulsion Laboratory developed the Wetlands Extent Tool 2.0 (WET 2.0) in Google Earth Engine to automate mapping of wetland distribution in the Great Lakes Basin. The team partnered with the US Fish and Wildlife Service (USFWS), Environmental Protection Agency (EPA), Minnesota Department of Natural Resources (MDNR), the National Oceanic and Atmospheric Administration (NOAA), and Ducks Unlimited (DU). WET 2.0 incorporates Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) satellite data. WET 2.0 is trained to classify anywhere in the Great Lakes Basin. Utilizing a Random Forest classifier, WET 2.0 is capable of automatically mapping wetland extent in the entire Great Lakes Basin, achieving a mean overall accuracy of 80.12% when tested in Michigan. Findings and maps produced in WET 2.0 will enable our partners to identify areas of ecosystem degradation and wetland destruction in order to enact environmental practices and policy initiatives to maintain environmental and economic health in the area.

Water Resources↗
NASA NTRS1992

Hydrologic applications of SAR derived soil moisture

The MACHYDRO-90 was a multi-sensor aircraft campaign conducted to study drainage basin hydrology and the role of soil moisture in defining hydrologic characteristics and patterns. The results from the synthetic aperture radar (SAR) are presented. Data were collected over a period in which the soil conditions changed from dry to wet and then through a drying period which was close to ideal. Radar backscatter data are compared to detailed soil moisture samples taken to define soil moisture gradients within a watershed. The analysis also includes 40-MHz bandwidth SAR data, which provide very high spatial resolution. It is shown these data can be interpreted for hydrology and their application to hydrologic modeling is discussed.

Engman, Edwin T.↗
NASA NTRS2020

Great Lakes Water Resources II: A Google Earth Engine Tool to Automate Wetland Extent Mapping Using Optical and Radar Satellite Sensors in the Great Lakes Basin for Wetland Management and Monitoring

The Great Lakes Basin is one of the world’s largest freshwater ecosystems. The Basin harbors over 200,000 acres of wetlands that provide a variety of environmental, ecological, and recreational functions to over 30 million people in the region. Some of these functions include improving water quality, mitigating flood impacts, providing wildlife habitat, and housing recreational activities. However, due to anthropogenic activities, habitat conversion and degradation threaten to disrupt or destroy remaining wetland ecosystems. Maps of wetland distribution based on ground surveys are costly and labor-intensive, prohibiting timely evaluations of wetland loss and gain. The Great Lakes Water Resources II team at the NASA Jet Propulsion Laboratory developed the Wetlands Extent Tool 2.0 (WET 2.0) in Google Earth Engine to automate mapping of wetland distribution in the Great Lakes Basin. The team partnered with the US Fish and Wildlife Service, Environmental Protection Agency, Minnesota Department of Natural Resources, the National Oceanic and Atmospheric Administration, and Ducks Unlimited. WET 2.0 incorporates Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) data. Utilizing a Random Forest classifier, WET 2.0 is capable of automatically mapping wetland extent in the entire Great Lakes Basin, achieving a mean overall accuracy of 80.12% when tested in Michigan.Findings and maps produced by WET 2.0 will enable our partners to identify areas of ecosystem degradation and wetland destruction in order to enact environmental practices and policy initiatives to maintain environmental and economic health in the area.

Water Resources↗
NASA NTRS2012

Calibration of Two-dimensional Floodplain Modeling in the Atchafalaya River Basin Using SAR Interferometry

Two-dimensional (2D) satellite imagery has been increasingly employed to improve prediction of floodplain inundation models. However, most focus has been on validation of inundation extent, with little attention on the 2D spatial variations of water elevation and slope. The availability of high resolution Interferometric Synthetic Aperture Radar (InSAR) imagery offers unprecedented opportunity for quantitative validation of surface water heights and slopes derived from 2D hydrodynamic models. In this study, the LISFLOOD-ACC hydrodynamic model is applied to the central Atchafalaya River Basin, Louisiana, during high flows typical of spring floods in the Mississippi Delta region, for the purpose of demonstrating the utility of InSAR in coupled 1D/2D model calibration. Two calibration schemes focusing on Manning s roughness are compared. First, the model is calibrated in terms of water elevations at a single in situ gage during a 62 day simulation period from 1 April 2008 to 1 June 2008. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR interferometry during 46 days of the image acquisition interval from 16 April 2008 to 1 June 2009. The best-fit models show that the mean absolute errors are 3.8 cm for a single in situ gage calibration and 5.7 cm/46 days for InSAR water level calibration. The optimum values of Manning's roughness coefficients are 0.024/0.10 for the channel/floodplain, respectively, using a single in situ gage, and 0.028/0.10 for channel/floodplain the using SAR. Based on the calibrated water elevation changes, daily storage changes within the size of approx 230 sq km of the model area are also calculated to be of the order of 107 cubic m/day during high water of the modeled period. This study demonstrates the feasibility of SAR interferometry to support 2D hydrodynamic model calibration and as a tool for improved understanding of complex floodplain hydrodynamics

Hahn Chul Jung↗
NASA NTRS1990

Processing Of Multispectral Data For Identification Of Rocks

Linear discriminant analysis and supervised classification evaluated. Report discusses processing of multispectral remote-sensing imagery to identify kinds of sedimentary rocks by spectral signatures in geological and geographical contexts. Raw image data are spectra of picture elements in images of seven sedimentary rock units exposed on margin of Wind River Basin in Wyoming. Data acquired by Landsat Thematic Mapper (TM), Thermal Infrared Multispectral Scanner (TIMS), and NASA/JPL airborne synthetic-aperture radar (SAR).

Evans, Diane L.↗