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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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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Converting Topographic Maps into Digital Form to Aid in Archeological Research in the Peten, Guatemala

The purpose of my project was to convert a topographical map into digital form so that the data can be manipulated and easily accessed in the field. With the data in this particular format, Dr. Sever and his colleagues can highlight the specific features of the landscape that they require for their research of the ancient Mayan civilization. Digital elevation models (DEMs) can also be created from the digitized contour features adding another dimension to their research.

Aldrich, Serena R.↗
NASA NTRS1991

Landsat Legacy

The Landsat resources survey system spawned a number of companies engaged in commercial applications of remote sensing, among them International Imaging Systems (I2S). With initial NASA assistance, I2S has provided remote sensing hardware and software to several foreign countries, developed meteorological analysis systems, medical diagnostic software and scanning equipment for government and commercial use. Latest product is an advanced image-based photogrammetric system employing digital technology - not optical or mechanical systems - to generate terrain elevation data and other processing functions. Called PRI2SM, it compensates automatically for topographic relief displacement, is cheaper, faster, and easier to use and maintain. Company product line includes four major areas: image processing equipment for Earth Resources Management; meteorological analysis systems; satellite ground processing systems; and digital photogrammetric mapping systems.

Source record↗
NASA NTRS1998

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

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

Bryan, J.↗
NASA NTRS2009

Topography of the Martian Impact Crater Tooting

Tooting crater is approx.29 km in diameter, is located at 23.4degN, 207.5degE, and is classified as a multi-layered ejecta crater [1]. Our mapping last year identified several challenges that can now be addressed with HiRISE and CTX images, but specifically the third dimension of units. To address the distribution of ponded sediments, lobate flows, and volatile-bearing units within the crater cavity, we have focused this year on creating digital elevation models (DEMs) for the crater and ejecta blanket from stereo CTX and HiRISE images. These DEMs have a spatial resolution of approx.50 m for CTX data, and 2 m for HiRISE data. Each DEM is referenced to all of the available individual MOLA data points within an image, which number approx.5,000 and 800 respectively for the two data types

Mouginis-Mark, P. J.↗
NASA NTRS2014

Myanmar Ecological Forecasting: Utilizing NASA Earth Observations to Monitor, Map, and Analyze Mangrove Forests in Myanmar for Enhanced Conservation

Mangroves supply many essential environmental amenities, such as preventing soil erosion, filtering water pollution, and protecting shorelines from harmful waves, floods, storms and winds. The Mangroves in Myanmar not only provide citizens with a food source, but they also offer firewood, charcoal, and construction materials. The depletion of mangroves is threatening more than the biodiversity however; Myanmar's fiscal livelihood is also in harm's way. Mangroves are valued at $100,000 to $277,000 per square kilometer and if managed in a sustainable fashion, can infuse constant income to the emerging Myanmarese economy. This study analyzed three coastline regions, the Ayeyarwady Delta, Rakhine and Tanintharyi, and mapped the spatial extent of mangrove forest during the dry season in 2000 and 2013. The classifications were derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operation Land Imager (OLI) imagery, as well as the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model information. This data was atmospherically corrected, mosaicked, masked and classified in ENVI, followed by ArcGIS to perform raster calculations and create final products. Forest degradation collected from 2000 to 2013 was later used to forecast the density and health of Mangroves in the year 2030. These results were subsequently presented to project partners Dr. Peter Leimgruber and Ellen Aiken at the Smithsonian Conservation Biology Institute in Front Royal, VA. After the presentation of the project to the partners, these organizations formally passed on to the Myanmar Ministry of Environment, Conservation and Forestry for policy makers and forest managers to utilize in order to protect the Myanmar mangrove ecosystem while sustaining a healthy economy.

Weber, Samuel J.↗
NASA NTRS1977

Viking 1975 Mars lander interactive computerized video stereophotogrammetry

A novel computerized interactive video stereophotogrammetry system has been developed for analysis of Viking 1975 lander imaging data. Prompt, accurate, and versatile performance is achieved. Earth-returned digital imagery data are driven from a computer to a pair of video monitors. Powerful computer support enables a photogrammetrist, stereoscopically viewing the video displays, to create diverse topographic products. Profiles, representing the intersection of any definable surface with the Martian relief, are readily generated. Vertical profiles and elevation contour maps, including stereo versions, are produced. Computer overlays of map products on stereo images aid map interpretation and permit independent quality evaluation. Slaved monitors enable parallel viewing. Maps span from the immediate foreground to the remote limits of ranging capability. Surface sampler arm specific vertical profiles enable direct reading of arm commands required for sample acquisition, rock rolling, and trenching. The ranging accuracy of plus or minus 2 cm throughout the sample area degrades to plus or minus 20 m at 100-m range.

Liebes, S., Jr.↗
NASA NTRS2003

Characterizing the Siple Coast Ice Stream System using Satellite Images, Improved Topography, and Integrated Aerogeophysical Measurements

A technique for improving elevation maps of the polar ice sheets has been developed using AVHRR images. The technique is based on 'photoclinometry' or 'shape from shading', a technique used in the past for mapping planetary surfaces where little elevation information was available. The fundamental idea behind photoclinometry is using the brightness of imaged areas to infer their surface slope in the sun-illuminated direction. Our version of the method relies on a calibration of the images based on an existing lower-resolution digital elevation model (DEM), and then using the images to improve the input DEM resolution to the scale of the image data. Most current DEMs covering the ice sheets are based on Radar altimetry data, and have an inherent resolution of 10 to 25 km at best - although the grid scale of the DEM is often finer. These DEMs are highly accurate (to less than 1 meter); but they report the mean elevation of a broad area, thus erasing smaller features of glaciological interest. AVHRR image data, when accurately geolocated and calibrated, provides surface slope measurements (based on the pixel brightness under known lighting conditions) every approximately 1.1 km. The limitations of the technique are noisiness in the image data, small variations in the albedo of the snow surface, and the integration technique used to create an elevation field from the image-derived slopes. Our study applied the technique to several ice sheet areas having some elevation data; Greenland, the Amery Ice Shelf, the Institute Ice Stream, and the Siple Coast. For the latter, the input data set was laser-altimetry data collected under NSF's SOAR Facility (Support Office for Aerogeophysical Research) over the onset area of the Siple Coast. Over the course of the grant, the technique was greatly improved and modified, significantly improving accuracy and reducing noise from the images. Several publications resulted from the work, and a follow-on proposal to NASA has been submitted to apply the same method to MODIS data using ICESat and other elevation input information. This follow-on grant will explore two applications that are facilitated by the improved surface morphology characterizations of the ice sheets: accumulation and temperature variations near small undulations in the ice.

Scambos, Ted↗
NASA NTRS2002

Russian-US Partnership to Study the 23-km-diameter El'gygtgyn Impact Crater, Northeast Russia

El'gygytgyn crater, located within Eastern Siberia, is a Pliocene-aged (3.6 Ma), well-preserved impact crater with a rim diameter of roughly 23 km. The target rocks are a coherent assemblage of crystalline rocks ranging from andesite to basalt. At the time of impact the region was forested and the Arctic Ocean was nearly ice-free. A 15-km lake fills the center of the feature and water depths are approximately 175 m. Evidence of shock metamorphism, -- including coesite, fused mineral glasses, and planar deformation features in quartz -- has been reported. This feature is one of the youngest and best preserved complex craters on Earth. Because of its remote Arctic setting, however, El gygytgyn crater remains poorly investigated. The objectives of this three-year project are to establish and maintain a research partnership between scientists from Russia and the United States interested in the El gygytgyn crater. The principal institutions in the U.S. will be the Geophysical Institute, University of Alaska Fairbanks and the University of Massachusetts Amherst. The principal institution in Russia will be the North East Interdisciplinary Scientific Research Institute (NEISRI), which is the Far-East Branch of the Russian Academy of Science. Three science tasks are identified for the exchange program: (1) Evaluate impactite samples collected during previous field excursions for evidence of and level of shock deformation. (2) Build a high-resolution digital elevation model for the crater and its surroundings using interferometric synthetic aperture radar techniques on JERS-1, ERS-1, ERS-2, and/or RadarSat range-doppler data. (3) Gather all existing surface data available from Russian and U.S. institutions (DEM, remote sensing image data, field-based lithological and sample maps, and existing geophysical data) and assemble into a Geographic Information Systems database.

Sharpton, Virgil L.↗
NASA NTRSDate not supplied

Utilizing Earth Observations to Model Probable Coastal Wetland Extent, Sea-Level Rise Inundation Risk, and Assess Impacts on Historic Hawaiian Lands

Climate induced sea-level rise poses a risk to coastal areas on the Island of Hawai’i, and many of the island’s historic cultural lands are in danger of becoming overtaken by wetlands or inundation. In partnership with the County of Hawai’i, State of Hawai’i Department of Land and Natural Resources, and Arizona State University, NASA DEVELOP mapped wetland extent and short-term sea-level rise inundation risk. We utilized Earth observations over a 10-year span (2013 – 2022) that included the NASA MEaSUREs Gridded Sea Surface Height Anomalies and MEaSUREs Group for High Resolution Sea Surface Temperature datasets, United States Geological Survey (USGS) Hawaii Digital Elevation Models (DEM), and in situ tidal gauge data. Flood risk index values were acquired for 5 known Hawai’i flood events between 2019 – 2021 from the Global Flood Mapper tool on Google Earth Engine. We used a random forest model to predict short-term sea-level rise inundation risk along the entire coast of Hawai’i. Current wetland extents and probabilistic locations of new wetlands were modeled with the most recently available data from PlanetScope Surface Reflectance optical imagery (2022), USGS 3D Elevation Program (3DEP) 10m DEM (2020), temperature and precipitation data from the Hawai’i Climate Atlas, and soils data from the Hawai’i Soil Atlas (2014) using the Wetland Intrinsic Potential tool. Results indicated locations that had the highest probability of wetland creation. The end products aimed to help the partners prioritize efforts to meeting regulation requirements for wetlands protection, evaluate the inundation risk to historical features, and support decision-making for their Shoreline Setback and Climate Adaption plans.

Lisa Tanh↗
NASA NTRS1984

Automatic terrain elevation mapping and registration

Optimum radar illumination geometries for stereoscopic analysis of surface topography are determined. Correlation and image processing experiments on synthetic aperture radar (SAR) data for improved information extraction are conducted. Model of the geometry of the multiple SIR-B views of the Earth are developed the sensitivity of the derived terrain altitude data to the various system parameters is established. The limits of accuracy of terrain data achievable with shuttle imaging radar (SIR-B) are derived. Algorithms for matching multiple SIR-B images to generate digital terrain maps are developed. Finally, the use of such terrain maps in geometric correction and registration of SIR-B and LANDSAT Thematic Mapper data is demonstrated.

Ramapriyan, H. K.↗
NASA NTRS2004

High Resolution Digital Elevation Models of Pristine Explosion Craters

In order to effectively capture a realistic terrain applicable to studies of cratering processes and landing hazards on Mars, we have obtained high resolution digital elevation models of several pristine explosion craters at the Nevada Test Site. We used the Airborne Terrain Mapper (ATM), operated by NASA's Wallops Flight Facility to obtain DEMs with 1 m spacing and 10 cm vertical errors of 4 main craters and many other craters and collapse pits. The main craters that were mapped are Sedan, Scooter, Schooner, and Danny Boy. The 370 m diameter Sedan crater, located on Yucca Flat, is the largest and freshest explosion crater on Earth that was formed under conditions similar to hypervelocity impact cratering. As such, it is effectively pristine, having been formed in 1962 as a result of a controlled detonation of a 100 kiloton thermonuclear device, buried at the appropriate equivalent depth of burst required to make a simple crater. Sedan was formed in alluvium of mixed lithology and subsequently studied using a variety of field-based methods. Nearby secondary craters were also formed at the time and were also mapped by ATM. Adjacent to Sedan and also in alluvium is Scooter, about 90 m in diameter and formed by a high-explosive event. Schooner (240 m) and Danny Boy (80 m) craters were also important targets for ATM as they were excavated in hard basalt and therefore have much rougher ejecta. This will allow study of ejecta patterns in hard rock as well as engineering tests of crater and rock avoidance and rover trafficability. In addition to the high resolution DEMs, crater geometric characteristics, RMS roughness maps, and other higher-order derived data products will be generated using these data. These will provide constraints for models of landing hazards on Mars and for rover trafficability. Other planned studies will include ejecta size-frequency distribution at the resolution of the DEM and at finer resolution through air photography and field measurements, correlation of ejecta size and composition with radar and visible-thermal IR remote sensing signatures, and comparison of these results with similar measurements of Mars. The final DEMs, ancillary data sets, and derived data products will be made available to the community.

T G Farr↗
NASA NTRS2022

Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing

Hazard detection is critical for enabling autonomous landing on planetary surfaces. Current state-of-the-art methods leverage traditional computer vision approaches to automate the identification of safe terrain from input digital elevation models (DEMs). However, performance for these methods can degrade for input DEMs with increased sensor noise. In the last decade, deep learning techniques have been developed for various applications. Nevertheless, their applicability to safety-critical space missions has often been limited due to concerns regarding their outputs’ reliability. In response to these limitations, this paper proposes an application of the Bayesian deep learning segmentation method for hazard detection. The developed approach enables reliable, safe landing site detection by i) generating simultaneously a safety prediction map and its uncertainty map via Bayesian deep learning and semantic segmentation, and ii) using the uncertainty map to filter out the uncertain pixels in the prediction map so that the safe site identification is performed only based on the certain pixels (i.e., pixels for which the model is certain about its safety prediction). Experiments are presented with simulated data based on a Mars HiRISE digital terrain model by varying uncertainty threshold and noise levels to demonstrate the performance of the proposed approach.

Kento Tomita↗
DOE OSTI2024

Vulnerability of Wetlands Due to Projected Sea-Level Rise in the Coastal Plains of the South and Southeast United States

Coastal wetlands are vulnerable to accelerated sea-level rise, yet knowledge about their extent and distribution is often limited. We developed a land cover classification of wetlands in the coastal plains of the southern United States along the Gulf of Mexico (Texas, Louisiana, Mississippi, Alabama, and Florida) using 6161 very-high (2 m per pixel) resolution WorldView-2 and WorldView-3 satellite images from 2012 to 2015. Area extent estimations were obtained for the following vegetated classes: marsh, scrub, grass, forested upland, and forested wetland, located in elevation brackets between 0 and 10 m above sea level at 0.1 m intervals. Sea-level trends were estimated for each coastal state using tide gauge data collected over the period 1983–2021 and projected for 2100 using the trend estimated over that period. These trends were considered conservative, as sea level rise in the region accelerated between 2010 and 2021. Estimated losses in vegetation area due to sea level rise by 2100 are projected to be at least 12,587 km 2 , of which 3224 km 2 would be coastal wetlands. Louisiana is expected to suffer the largest losses in vegetation (80%) and coastal wetlands (75%) by 2100. Such high-resolution coastal mapping products help to guide adaptation plans in the region, including planning for wetland conservation and coastal development.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

International Conference on Remote Sensing Applications for Archaeological Research and World Heritage Conservation

Contents include the following: Monitoring the Ancient Countryside: Remote Sensing and GIS at the Chora of Chersonesos (Crimea, Ukraine). Integration of Remote Sensing and GIS for Management Decision Support in the Pendjari Biosphere Reserve (Republic of Benin). Monitoring of deforestation invasion in natural reserves of northern Madagascar based on space imagery. Cartography of Kahuzi-Biega National Park. Cartography and Land Use Change of World Heritage Areas and the Benefits of Remote Sensing and GIS for Conservation. Assessing and Monitoring Vegetation in Nabq Protected Area, South Sinai, Egypt, using combine approach of Satellite Imagery and Land Surveys. Evaluation of forage resources in semi-arid savannah environments with satellite imagery: contribution to the management of a protected area (Nakuru National Park) in Kenya. SOGHA, the Surveillance of Gorilla Habitat in World Heritage sites using Space Technologies. Application of Remote Sensing to monitor the Mont-Saint-Michel Bay (France). Application of Remote Sensing & GIS for the Conservation of Natural and Cultural Heritage Sites of the Southern Province of Sri Lanka. Social and Environmental monitoring of a UNESCO Biosphere Reserve: Case Study over the Vosges du Nord and Pfalzerwald Parks using Corona and Spot Imagery. Satellite Remote Sensing as tool to Monitor Indian Reservation in the Brazilian Amazonia. Remote Sensing and GIS Technology for Monitoring UNESCO World Heritage Sites - A Pilot Project. Urban Green Spaces: Modern Heritage. Monitoring of the technical condition of the St. Sophia Cathedral and related monastic buildings in Kiev with Space Applications, geo-positioning systems and GIS tools. The Murghab delta palaeochannel Reconstruction on the Basis of Remote Sensing from Space. Acquisition, Registration and Application of IKONOS Space Imagery for the cultural World Heritage site at Mew, Turkmenistan. Remote Sensing and VR applications for the reconstruction of archaeological landscapes. Archaeology through Space: Experience in Indian Subcontinent. The creation of a GIS Archaeological Site Location Catalogue in Yucatan: A Tool to preserve its Cultural Heritage. Mapping the Ancient Anasazi Roads of Southeast Utah. Remote Sensing and GIS Technology for Identification of Conservation and Heritage sites in Urban Planning. Mapping Angkor: For a new appraisal of the Angkor region. Angkor and radar imaging: seeing a vast pre-industrial low-density, dispersed urban complex. Technical and methodological aspects of archaeological CRM integrating high resolution satellite imagery. The contribution of satellite imagery to archaeological survey: an example from western Syria. The use of satellite images, digital elevation models and ground truth for the monitoring of land degradation in the "Cinque Terre" National park. Remote Sensing and GIS Applications for Protection and Conservation of World Heritage Site on the coast - Case Study of Tamil Nadu Coast, India. Multispectral high resolution satellite imagery in combination with "traditional" remote sensing and ground survey methods to the study of archaeological landscapes. The case study of Tuscany. Use of Remotely-Sensed Imagery in Cultural Landscape. Characterisation at Fort Hood, Texas. Heritage Learning and Data Collection: Biodiversity & Heritage Conservation through Collaborative Monitoring & Research. A collaborative project by UNESCO's WHC (World Heritage Center) & The GLOBE Program (Global Learning and Observations to Benefit the Environment). Practical Remote Sensing Activities in an Interdisciplinary Master-Level Space Course.

Source record↗
DOE OSTI2026

Vegetation classification map and covariates associated with NEON AOP survey, East River, CO 2018

This package includes geospatial data layers developed to investigate how environmental gradients—specifically topography and near-surface soil properties—drive the spatial arrangement of dominant plant communities in mountainous watersheds. The geospatial products, which support the analysis of these ecological relationships, are derived from airborne hyperspectral and LiDAR datasets acquired by the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP), in conjunction with an extensive ground field campaign conducted in summer 2018. This work is part of the DOE Watershed Function Science Focus Area (SFA) and features geospatial datasets developed based on observations and ground data collected at East River, Colorado, in collaboration with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey in June 2018. Classification Map: - Classification Map (PNG, GeoTIFF): Derived from hyperspectral and LiDAR airborne data using a machine learning approach. - Class Code Mapper (CSV): Associates pixel values with corresponding vegetation/non-vegetation classes. - Classification Reference Data (CSV): Reference data used in the machine learning procedure. LiDAR-Derived Products: - Topographical Metrics (GeoTIFFs): Elevation, slope, curvature, TWI, TPI, solar insolation, and canopy height model (CHM), smoothed with a 5x5 pixel window. Vegetation Indices: - GeoTIFFs of NDVI, NDNI, NDWI: Vegetation indices derived from hyperspectral data. Urban Masks: - Urban Mask (GeoTIFF): Applied to the mapping to convert bare soil classes to urban classes. Software Compatibility: GeoTIFFs: Can be visualized with GIS software or libraries that support GeoTIFF images. CSV Files: Can be opened with any software that handles comma-separated values. The FLMD file provides details and links to the source datasets used to derive the products. The manuscript (in the Method session) provides details on how each product was derived. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Update on 2026-03-25: Since the original dataset publication date of 02/28/2020, this package has a new classification map derived by an improved methodology. This update also includes additional ground data that improved the representation of some of the communities. See the methods for further details on what has changed between versions.

2018 NEON and 2025 CHESS Campaigns↗
NASA NTRS2015

High-Resolution Forest Canopy Height Estimation in an African Blue Carbon Ecosystem

Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereophotogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.

HRSI↗
NASA NTRS1999

Generation of Level 3 SMMR and SSM/I Brightness Temperatures for the Period 1978-1999

The NOAA/NASA Pathfinder Program was initially designed to assure that certain key remote sensing data sets of particular significance to global change research were scientifically validated, consistently processed and made readily available to the research community at minimal cost. Through this Program the National Snow and Ice Data Center (NSIDC), University of Colorado has successfully processed, archived and distributed the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) Level 3 (EASE-Grid format) Pathfinder data sets for the period 1978 to 1999. These data are routinely distributed to approximately 150 researchers through various media including CD-ROM, 8 mm tape, ftp and the EOS Information Management System (IMS). At NSIDC these data are currently being applied in the development and validation of algorithms to derive snow water equivalent (NASA NAG5-6636), the mapping of frozen ground and the detection of the onset of melt over ice sheets, sea ice and snow cover. The EASE-Grid format, developed at NSIDC in conjunction with the SMMR-SSM/I Pathfinder project has also been applied to Advanced Very High Resolution Radiometer (AVHRR) and TOVS Pathfinder data, as well as ancillary data such as digital elevation, land cover classification and several in situ data sets. EASE-Grid will also be used for all land products derived from the NASA EOS AMSR-E instrument.

Partington, Kim↗
NASA NTRS2008

Characterization of Lunar Polar Illumination from a Power System Perspective

This paper presents the results of illumination analyses for the lunar south and north pole regions obtained using an independently developed analytical tool and two types of digital elevation models (DEM). One DEM was based on radar height data from Earth observations of the lunar surface and the other was a combination of the radar data with a separate dataset generated using Clementine spacecraft stereo imagery. The analysis tool enables the assessment of illumination at most locations in the lunar polar regions for any time and any year. Maps are presented for both lunar poles for the worst case winter period (the critical power system design and planning bottleneck) and for the more favorable best case summer period. Average illumination maps are presented to help understand general topographic trends over the regions. Energy storage duration maps are presented to assist in power system design. Average illumination fraction, energy storage duration, solar/horizon terrain elevation profiles and illumination fraction profiles are presented for favorable lunar north and south pole sites which have the potential for manned or unmanned spacecraft operations. The format of the data is oriented for use by power system designers to develop mass optimized solar and energy storage systems.

Fincannon, James↗