Search NASA⌕ Search

SEARCH · Search NASA

Results for “USGS Data”

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 289 records · Page 16

Clementine High Resolution Camera Mosaicking Project: CL 6018; 80 deg N to 80 deg S Latitude, 330 deg E to 360 deg E Longitude - Volume 18

This compact disk (CD) is part of the Malin Space Science Systems (MSSS) effort to mosaic Clementine I high resolution (HiRes) camera lunar images. These mosaics were developed through calibration and semi-automated registration against the recently released geometrically and photometrically controlled Ultraviolet/Visible (UV/Vis) Basemap Mosaic, which is available through the PDS, as CD-ROM volumes CL_3001-3015. The HiRes mosaics are compiled from non-uniformity corrected, 750 nanometer ("D") filter high resolution observations from the HiRes imaging system onboard the Clementine Spacecraft. These mosaics are spatially warped using the sinusoidal equal-area projection at a scale of 20 m/pixel. The geometric control is provided by the 100 m/pixel U. S. Geological Survey (USGS) Clementine Basemap Mosaic compiled from the 750 nm Ultraviolet/Visible Clementine imaging system. Calibration was achieved by removing the image nonuniformity largely caused by the HiRes system's light intensifier. Also provided are offset and scale factors, achieved by a fit of the HiRes data to the corresponding photometrically calibrated UV/Vis basemap that approximately transform the 8-bit HiRes data to photometric units. The mosaics on this CD were compiled from sub-polar data (latitudes 80 degrees South to 80 degrees North; -80 to +80) within the longitude range 0-30 deg E. The mosaics are divided into tiles that cover approximately 1.75 degrees of latitude and span the longitude range of the mosaicked frames. Images from a given orbit are map projected using the orbit's nominal central latitude. This CD contains ancillary data files that support the HiRes mosaic. These files include browse images with UV/Vis context stored in a Joint Photographic Experts Group (JPEG) format, index files ('imgindx.tab' and 'srcindx.tab') that tabulate the contents of the CD, and documentation files. For more information on the contents and organization of the CD volume set refer to the "FILES, DIRECTORIES AND DISK CONTENTS" section of this document. The image files are organized according to NASA's Planetary Data System (PDS) standards. An image file (tile) is organized as a PDS labeled file containing an "image object".

Malin, Michael↗

Clementine High Resolution Camera Mosaicking Project: CL 6017; 0 deg to 80 deg S Latitude, 330 deg E Longitude - Volume 17

This compact disk (CD) is part of the Malin Space Science Systems (MSSS) effort to mosaic Clementine I high resolution (HiRes) camera lunar images. These mosaics were developed through calibration and semi-automated registration against the recently released geometrically and photometrically controlled Ultraviolet/Visible (UV/Vis) Basemap Mosaic, which is available through the PDS, as CD-ROM volumes CL_3001-3015. The HiRes mosaics are compiled from non-uniformity corrected, 750 nanometer ("D") filter high resolution observations from the HiRes imaging system onboard the Clementine Spacecraft. These mosaics are spatially warped using the sinusoidal equal-area projection at a scale of 20 m/pixel. The geometric control is provided by the 100 m/pixel U.S. Geological Survey (USGS) Clementine Basemap Mosaic compiled from the 750 nm Ultraviolet/Visible Clementine imaging system. Calibration was achieved by removing the image nonuniformity largely caused by the HiRes system's light intensifier. Also provided are offset and scale factors, achieved by a fit of the HiRes data to the corresponding photometrically calibrated UV/Vis basemap that approximately transform the 8-bit HiRes data to photometric units. The mosaics on this CD were compiled from sub-polar data (latitudes 80 degrees South to 80 degrees North; -80 to +80) within the longitude range 0-30 deg E. The mosaics are divided into tiles that cover approximately 1.75 degrees of latitude and span the longitude range of the mosaicked frames. Images from a given orbit are map projected using the orbit's nominal central latitude. This CD contains ancillary data files that support the HiRes mosaic. These files include browse images with UV/Vis context stored in a Joint Photographic Experts Group (JPEG) format, index files ('imgindx.tab' and 'srcindx.tab') that tabulate the contents of the CD, and documentation files. For more information on the contents and organization of the CD volume set refer to the "FILES, DIRECTORIES AND DISK CONTENTS" section of this document. The image files are organized according to NASA's Planetary Data System (PDS) standards. An image file (tile) is organized as a PDS labeled file containing an "image object".

Malin, Michael↗

Western Rainier Seismic Zone Airborne Laser Swath Mapping

Airborne laser swath mapping (ALSM) of the Puget Lowland conducted by TerraPoint LLC for the Purget Sound Lidar Concortium (PSLC), has been successful in revealing Holocene fault scarps and lendsliders hidden beneath the dense, temperate rain forest cover and in quantifying shoreline terrace uplift. Expanding the PSLC efforts, NASA-USGS collaboration is now focusing on topographic mapping of seismogenic zones adjacent to volcanois in the western Cascades range in order to assess the presence of active faulting and tectonic deformation, better define the extend of lahars and understand their flow processes, and characterize landslide occurrence. Mapping of the western Rainier zone (WRZ) was conducted by TerraPoint in late 2002, after leaf fall and before snow accumulation. The WRZ is a NNW-trending, approx. 30 km-long zone of seismicity west of Mount Rainier National Park. The Puget Lowland ALSM methods were modified to accommodate challenges posed by the steep, high relief terrian. The laser data, acquired with a density of approx. 2 pulses /sq m, was filtered to identify returns from the ground from which a bare Earth digital elevation model (DEM) was produced with a grid size of 1.8 m. The RMS elevation accuracy of the DEM in flat, unvegetated areas is approx. 10cm based on consistency between overlapping flight swaths and comparisons to ground control points. The resulting DEM substantially improves upon Shuttle Radar Topography Mission and USGS photogrammetric mapping. For example, the DEM defines the size and spatial distribution of flood erratics left by the Electron lahar and of megaclasts within the Round Pass lahar, important for characterizing the lahar hydraulics. A previously unknown lateral levee on the Round Pass lahar is also revealed. In addition, to illustrating geomorfic feature within the WRZ, future plans for laser mapping of the Saint Helens and Darrington seismic zones will be described.

Harding, David J.↗

Relief Evolution in Tectonically Active Mountain Ranges

The overall aims of this 3-yr project, as originally proposed were to: (1) investigate quantitatively the roles of fluvial and glacial erosion in the evolution of relief in mountainous regions, and (2) test rigorously the quality and accuracy of SRTM topographic data in areas of rugged relief - both the most challenging and of greatest interest to geomorphic, neotectonic, and hazards applications. Natural laboratories in both the western US and the Southern Alps of New Zealand were identified as most promising. The project has been both successful and productive, despite the fact that no SRTM data for our primary field sites in New Zealand were released on the time frame of the work effort. Given the delayed release of SRTM data, we pursued the scientific questions of the roles of fluvial and, especially, glacial erosion in the evolution of relief in mountainous regions using available digital elevation models (DEMs) for the Southern Alps of New Zealand (available at both 25m and 50m pixel sizes), and USGS 10m and 30m DEMs within the Western US. As emphasized in the original proposal, we chose the emphasis on the role of glacial modification of topographic relief because there has been little quantitative investigation of glacial erosion processes at landscape scale. This is particularly surprising considering the dramatic sculpting of most mid- and high-latitude mountain ranges, the prodigious quantities of glacially-derived sediment in terrestrial and marine basins, and the current cross-disciplinary interest in the role of denudational processes in orogenesis and the evolution of topography in general. Moreover, the evolution of glaciated landscapes is not only a fundamental problem in geomorphology in its own right, but also is at the heart of the debate over Late Cenozoic linkages between climate and tectonics.

Whipple, Kelin X.↗

Landsat 9: Status and Plans

The Landsat 9 mission, currently under development and proceeding towards a targeted launch in late 2020, will be very similar to the Landsat 8 mission, launched in 2013. Like Landsat 8, Landsat 9 is a joint effort between NASA and USGS with two sensors, the Operational Land Imager 2 (OLI-2), essentially a copy of the OLI on Landsat 8 and the Thermal Infrared Sensor 2 (TIRS-2), very similar to the TIRS on Landsat 8. The OLI-2, like OLI, provides 14-bit image data, though for Landsat 9, all 14 bits will be retained and transmitted to the ground. The focal plane modules to be used for OLI-2 were flight spares for OLI and are currently being retested by Ball Aerospace. Results indicate radiometric performance comparable to OLI. The TIRS was a class C instrument, with a 3-year design lifetime, and therefore had limited redundancy. TIRS-2 will be a class B instrument, with a 5-year design lifetime, like OLI (and OLI-2), necessitating design changes to increase redundancy. The stray light and Scene Select Mechanism (SSM) encoder problems observed on orbit with TIRS have also instigated a few design changes to TIRS-2. Stray light analysis and testing have indicated that additional baffles in the TIRS-2 optical system will suppress the out-of-field response. The SSM encoder problems have not been definitively traced to a route cause, though conductive anodic filament growth in the circuit boards is suspected. Improved designs for the encoder are being considered for TIRS-2. The spare Focal Plane Array (FPA) from TIRS is planned for use in TIRS-2; FPA spectral and radiometric performance testing is scheduled for September of this year at NASA's Goddard Space Flight Center.

Landsat↗

Candidate-Landing Sites and Backups for the Mars Surveyor Program in the Schiaparelli. Crater Region

Our Survey area comprises the Sinus Sabeus NW quadrangle that includes most of the Schiaparelli crater and part of the Arabia SW region (3 N to 15 S Lat.) and (0 to 337.5 W long.) and covers all regions that show a potential hydrogeological link with the Schiaparelli impact structure. This area is hereafter defined as the Schiaparelli Crater Region. The Schiaparelli crater region is one of the most documented MOC targets. Up to now, MGS MOC camera took two dozen images at an average of 5m/pxl resolution that not only provide an exceptional insight on the local geology and morphology, but give also key-elements to assess landing safety criteria. In addition, the MOLA topographic profile No. 23 passes through part of the crater basin allowing the adjustment of the elevation as previously known from the Viking mission (USGS I-2125, 1991). Beyond the Mars Polar Lander mission that will land next December, the future missions (2001 APEX, 2003, and 2005) are led by a series of science objectives and engineering constraints that must be considered in order to select landing sites that will fulfill the Surveyor Program's objectives. The search for a sound and safe candidate-site (without ending up with the usual "safe but boring" or "fascinating but too risky" site) is usually limited by the data available to the investigator, by the data accuracy (e.g. poor image resolution, poor altimetry), and the lack of crucial information for science and safety that can be derived from them. The Schiaparelli region provides an exception to this recurrent pattern. We listed the preliminary constraints for landing site selection identified for the Surveyor '01 mission, in terms of safety requirements and data needed and compared them against the existing information and/or data already available for the Schiaparelli region. The engineering constraints of '03 and '05 are not designated yet but, since they are also related to atmospheric density and Lander designs, we will assume that these points will be comparable to '01. The main difference will reside in the rover design, the Rocky-7 class rover being bigger than Marie Curie ('01) will be able to overcome bigger obstacles. We listed then the main objectives of the Surveyor Program and compared them with the potential offered by the Schiaparelli Crater Region to document them. Within the survey area, the Schiaparelli impact crater is 2.5 S/343.3 W (USGS 1-1376, MC-20 NW, 1981) and occupies a significant surface area. The crater has been proposed as a potential candidate-site in the past years. The purpose of this study is to show that, not only the Schiaparelli Crater would be a high-priority target, but that the region where it is located offer several very-high potential back-up sites, all within science and engineering constraints, that make this region probably the most promising candidate area so far.

Cabrol, Nathalie A.↗

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

Assessment of Required Accuracy of Digital Elevation Data for Hydrologic Modeling

The effect of vertical accuracy of Digital Elevation Models (DEMs) on hydrologic models is evaluated by comparing three DEMs and resulting hydrologic model predictions applied to a 7.2 sq km USDA - ARS watershed at Mahantango Creek, PA. The high resolution (5 m) DEM was resempled to a 30 m resolution using method that constrained the spatial structure of the elevations to be comparable with the USGS and SIR-C DEMs. This resulting 30 m DEM was used as the reference product for subsequent comparisons. Spatial fields of directly derived quantities, such as elevation differences, slope, and contributing area, were compared to the reference product, as were hydrologic model output fields derived using each of the three DEMs at the common 30 m spatial resolution.

HYDROLOGIC MODELS↗

Improving Building Footprint Extraction Using NAIP and 3DEP Lidar Derived Features with Deep Learning

Accurate building footprint extraction is critical for applications ranging from population estimation to disaster management. Although optical imagery provides detailed spectral information, it often struggles with shadows, occlusions, and background clutter in dense urban environments. Lidar data, by contrast, offer precise elevation and structural attributes but face challenges such as variable point density and noise. This study integrates multispectral imagery from the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) with lidar-derived feature height and intensity from the U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) to improve footprint extraction using a U-Net–based deep learning model. A six-band input stack (RGB, near-infrared, height, intensity) was developed, normalized, and tiled for training and evaluation against Microsoft Global Building Footprints (GBF). Results from the Houston, TX test site show that the six-band model achieved a precision of 0.86, recall of 0.88, F1 score of 0.87, and Intersection-over-Union (IoU) of 0.76, consistently outperforming four-band baselines by reducing false positives while maintaining sensitivity. Predictions on withheld Houston tiles confirmed strong within-region generalization, yielded a precision of 0.78, recall of 0.81, F1 score of 0.79, and IoU of 0.66. Qualitative analysis further revealed limitations stemming from both training label quality and vegetation–building confusion. These findings demonstrate the complementary value of integrating spectral and structural information for robust building footprint extraction and how domain adaptation strategies can be used to enhance cross-regional transferability.

Liu, Jung Kuan [United States Geological Survey (U↗

Processed Soil Respiration at the TRACE experimental Warming project, Aug 2015 - Sep 2017, Sabana, Luquillo, Puerto Rico

This data package contains processed measurements of soil carbon dioxide (CO₂) efflux collected using LI-COR LI-8100 soil respiration chambers at the Tropical Responses to Altered Climate Experiment (TRACE) located at the Sabana Field Research Station near Luquillo, Puerto Rico. The TRACE site is a mature, closed-canopy tropical wet forest within the Luquillo Experimental Forest. These data quantify soil surface CO₂ fluxes from both ambient (control) and experimentally warmed plots to evaluate how long-term soil warming affects belowground carbon cycling in tropical ecosystems. The data files include time-series tables of CO₂ flux (µmol CO₂ m⁻² s⁻¹), soil temperature (°C), and ancillary environmental variables, stored in comma-separated values (CSV) format and viewable with any text editor, spreadsheet, or statistical software (e.g., R, Python, Excel). Associated metadata describe plot identifiers, measurement intervals, and processing steps. These data were generated to address the research question: How does sustained soil warming influence soil respiration and carbon flux dynamics in tropical wet forests?

54 ENVIRONMENTAL SCIENCES↗

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to time-series data from Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus), OLI (Operational Land Imager), and MODIS (Moderate Resolution Imaging Spectroradiometer). Our effort has been focused on development of indicators of drought impacts in the March-August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March-September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Valleys↗

2018 NISAR Applications Workshop: Wetlands; Workshop Report

Wetland ecosystems are a critical part of our natural environment, providing socioeconomic benefits to human communities and habitats to a rich diversity of plant and animal life. Socioeconomic benefits include improved water quality, flood control, foods, shoreline stabilization, groundwater recharge, and recreational opportunities. Wetlands also have a major role as carbon sinks and sources through processes that are influenced by the duration and timing of soil saturation and inundation. Thus, carbon and water cycle models must take into account wetland extent and seasonal patterns of wetland inundation. The joint NASA, US Geological Survey (USGS) and Fish and Wildlife Service (FWS) workshop focused on advancing wetland applications of the spaceborne NASA-ISRO Synthetic Aperture Radar (SAR) mission (NISAR), a jointly developed satellite between NASA and the Indian Space Research Organisation (ISRO) expected for launch early 2022. Participants from 15 national and international organizations --including US Federal Agencies, nonprofits, academics, and the private sector-- had been identified as key-players in facilitating integration of Earth Observations into decision support workflows. Discussions were held over two and a half days to convey the knowledge and measurement needs of the wetlands community and discuss the delivery of relevant geospatial products that could be derived from NISAR data. While the community typically characterizes wetlands by their hydrological process, vegetation and soil types, a central defining characteristic is that a wetland is a land area inundated or saturated in the rootzone for at least 2 weeks of the average vegetation growing season.

FWS↗

A review of application studies on Indian lands using NASA aerospace imagery

Three remote sensing projects are being conducted on three different Indian reservations in eastern Arizona. On the Fort Apache Reservation, a multiband thermal and false color sensing of an Englemann spruce beetle infestation is being investigated on Mount Baldy, adjacent to a U.S. Forest Service proposed wilderness area. On the San Carlos Reservation, there is a joint USGS, EROS, and San Carlos tribe project to examine intensively a circular topographic feature noted on the Apollo 9 imagery. On the Papago Reservation, an EROS-funded contract will provide the Papago tribe with a report showing potential mineral areas, by comparing and correlating space imagery with high resolution imagery and aeromagnetic data.

Woll, A. M.↗

Lunar and Planetary Science XXXV: Lunar Remote Sensing: Fire, Ice, and Regolith

The session "Lunar Remote Sensing: Fire, Ice, and Regolith" included the following:Compositional and Structural Study of the Aristarchus Plateau from Integrated UV-VIS-NIR Spectral Data; Clementine 2.7-?m Data: Mapping the Mare and Searching for Water; On the Search for Water at the Lunar Poles: Results of Forward Modeling of Permanently Shaded Areas and Lunar Prospector Measurements; Searching the Moon for Aluminous Mare Basalts Using Compositional Remote-Sensing Constraints I: Finding the Regions of Interest; Semi-automated Extraction of Contours from Lunar Topographic Maps; Basalts in Mare Humorum and S.E. Procellarum; The Hansteen and Helmet Volcanic Dome Regions on the Moon: Stratigraphy and Ages; Derivation of Elemental Abundance Maps at 15-km Spatial Resolution from the Merging of Clementine Optical and Lunar Prospector Geochemical Data; Remote Sensing and Geologic Studies of the Balmer Region of the Moon; Lava Flows in Mare Nubium and Mare Cognitum: A Geological History Based on Analysis of Multispectral Data; Development of Ground-based Lunar VIS/NEAR IR Spectral Imager; A BRDF Measurement Apparatus for Lab-based Samples; A New Source of High Resolution Lunar Images: Amateur Astronomers! ; Leakage of Gamma Rays and Neutrons from Thick Targets Bombarded by Energetic Protons; Progress on Reviving Lunar Orbiter: Scanning, Archiving, and Cartographic Processing at USGS; Modeling Lateral and Vertical Mixing by Impact Cratering with Applications for the Moon; Optical Maturity Study of Stuart#s Crater Candidate Impact; Evidence for Three Basins Beneath Oceanus Procellarum; and Ellipses of the South Pole-Aitken Basin: Implications for Basin Formation.

Source record↗

VISUALIZING INTERANNUAL TO DECADAL COASTAL VARIABILITY NEAR VULNERABLE NASA INFRASTRUCTURE UTILIZING VIDEOS PRODUCED FROM REMOTELY SENSED DATA AT CAPE CANAVERAL, FL AND WALLOPS ISLAND, VA

Coastlines represent an interesting convolution of intense anthropogenic development superimposed onto morphologies that are among the most dynamic on the planet. Two of NASA’s critical facilities are particularly vulnerable to coastal change, Kennedy Space Center, Cape Canaveral, FL and Wallops Flight Facility, Wallops Island, VA. With continuing global sea level rise and increasing storminess coastal vulnerabilities at these facilities will only be exacerbated. These launch centers a subject to multiple coastal hazards including, flooding, episodic coastal erosion, saltwater intrusion, and coastal morphological changes. Although rapid change is readily observed during large storms or hurricanes, long term annual to decadal coastal change is much harder to visualize and conceptualize. The authors use videos developed from remotely sensed data to enhance conceptualization of coastal processes for planning and management stakeholders at these NASA facilities. Near or better than decadal coastal imagery has been available through high altitude photogrammetry efforts since the 1930’s. A significant amount of additional imagery was acquired through other federal, state, and local government agencies such as the USGS, NOAA, State DOT, and local Assessors Offices providing annual and inter annual images at spatial resolutions of 10cm – 1m. With the advent of GIS systems these images could be rectified and then layered to better understand change through time using a multitude of visual base shoreline proxies. With the increased awareness and use of video editing software the rectified images can be used to create videos. These videos can then be used to conceptualize a multitude of coastal processes including: performance of coastal restoration efforts, rapid change in sedimentation rates due to storms or other geomorphic processes, loss of protective barrier islands as sea level rises and lower sedimentation rates occur. The videos are also useful as a tool for verification and comparison to coastal models and provide an easy to understand educational resource for stakeholder engagement at these NASA centers, and other vulnerable coastal populations.

Richard A. MacKenzie III↗

Package Data for CERF-Data Centers

This dataset contains sample input 100m resolution raster files for running the CERF-DC python package (see https://github.com/IMMM-SFA/cerf_data_centers) at the state level across the CONUS. Due to data availability constraints, some of the items included in this dataset are proxies or assumptions for siting factors used in the model. These are individually noted in the item descriptions and can be exchanged with more detailed information upon availability. Data Descriptions The following raster files are included in the data download: state_siting_region.tif — State areas identified by state FIPS code composite_siting_suitability.tif — Value of 1 indicates suitable siting location, 0 otherwise. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands land_value_dollar_per_sqft.tif — USD per square foot (sqft) derived from USDA $/acre land cost personal_property_tax_rate.tif — Personal property tax rate by state. Uses an assumed 0.0125 personal property tax rate for states with personal property tax, 0 for states without personal property tax. real_property_tax_rate.tif — Real property tax rate. Based on county level residential real estate property tax rates. sales_tax_rate.tif — Sales tax rate by state. mechanical_cooling_fraction.tif — Fraction of year (values between 0 and 1, inclusive) that the data center would be cooled through mechanical processes based on local water stress and humidity levels. water_cooling_fraction.tif — Fraction of year (values between 0 and 1, inclusive) that the data center would be cooled through evaporative (water cooled) processes based on local water stress and humidity levels. distance_to_substation.tif — Distance to nearest substation in hundreds of meters (i.e., value of 1 equals a distance of 100m). Offshore areas have a value of 0. industrial_electricity_rates_dollar_per_kwh.tif — USD/kWh industrial electricity rates. Represents the average industrial rate across all utilities that operate within a given county. Values are derived from the US Utility Rate Database. commercial_electricity_rates_dollar_per_kwh.tif — USD/kWh commercial electricity rates. Represents the average commercial rate across all utilities that operate within a given county. Values are derived from the US Utility Rate Database. data_center_market_locations.tif — Grid cells with positive values represent the centroid of existing data center market clusters. The value of non-zero grid cells represents the number of data centers in the market cluster. All other grid cells have a value of 0. Geospatial Metadata CRS: Albers Equal Area Conic (ESRI:102003) Extent: -2415585.0000000023283064,-1441981.2605773280374706 : 2384414.9999999976716936,1708018.7394226719625294 Dimensions: X: 48000 Y: 31500 Bands: 1 Origin: -2415585.0000000023283064,1708018.7394226719625294 Pixel Size: 100,-100 Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall↗

Exploiting the Free Landsat Archive for Operational Monitoring of Ecosystem Condition and Change Across the Chesapeake Bay Watershed

For the first time, all imagery acquired by the Landsat series of satellites is being made available by the USGS to users at no cost. This represents a key opportunity to use Landsat in a truly operational monitoring framework: large regions of the U.S. such as the Chesapeake Bay Watershed can now be analyzed using "wall-to-wall" imagery at timescales from approximately 1 month to several years. With the future launch of the Landsat Data Continuity Mission (LDCM) and Decadal Survey missions such as the hyperspectral HyspIRI, it is imperative to develop robust processing systems to perform annual ecosystem assessments over large regions such as the Chesapeake Bay. We have been working at NASA's Goddard Space Flight Center (GSFC) to develop an integrative framework for inserting 30m, annual, Landsat based data and derived products into the existing decision support system for the Bay, with a particular focus on ecosystem condition and changes over the entire watershed. The basic goal is to use a 'stack' of Landsat imagery with 40% or less cloud cover to produce multi-date (2005-2009 period), cloud/shadow/gap-free composited surface reflectance products that will support the creation of watershed scale land cover/ use products and the monitoring of ecosystem change across the Bay. Our scientific focus extends beyond the conventional definition of land cover (i.e. a classification of vegetation type) as we propose to monitor both changes in surface type (e.g. forest to urban), vegetation structure (e.g. forest disturbance due to logging or insect damage), as well as winter crop cover. These processes represent a continuum from large, interannual changes in land cover type, to subtler, intra-annual changes associated with short-term disturbance. The free Landsat data are being processed to surface reflectance and composited using the existing Landsat Ecosystem Disturbance Adaptive Processing System here at NASA/ GSFC, and land cover products (type, tree cover, impervious cover, winter cover) are being produced using well-established decision tree and regression tree algorithms. The goal of this session is to present the data products that we have been developing to the Bay science community and to discuss potential avenues for improvements and usage of the products for decision support.

BrowndeColstoun, Eric↗

Importance and Incorporation of User Feedback in Data Stewardship

Since August 1994, The National Aeronautics and Space Administration's (NASA's) Earth Observation System Data and Information System (EOSDIS) has been serving a global community of over 3 million users with Earth science data in a variety of disciplines. During the entire life of EOSDIS, various mechanisms for user feedback have been extremely important and valuable to its evolution and proven performance. Some inputs from user groups have resulted in fundamental changes in the architecture, design and operations of EOSDIS, while others have provided ideas for incremental changes. The purpose of this paper is to share this experience and the benefits that have resulted from the user feedback.In early to mid-1990s, the EOSDIS Advisory Panel (a.k.a. Data Panel) provided significant inputs for the architecture and design of EOSDIS resulting in NASA's establishment of a set of Distributed Active Archive Centers (DAACs) and development of a "working prototype with operating elements" called Version 0 EOSDIS, which went into operation in August 1994. The Data Panel also participated in many of the requirement and design reviews and influenced the design of EOSDIS through their comments.In 1995, the U.S. National Research Council's Committee on Global Change Research conducted a review of the U.S. Global Change Research Program and NASA's Mission to Planet Earth/EOS, including the plans for EOSDIS. One of this committee's recommendations was that the "Responsibility for product generation and publication and for user services should be transferred to a federation of partners selected through a competitive process open to all". In response, NASA initiated an experiment with a "self-governing" federation called the Working Prototype ESIP (WP-ESIP) Federation. This federation, with support from NASA, NOAA and USGS, has now grown into the Earth Science Information Partners (ESIP) with over 140 member organizations.The EOSDIS DAACs' User Working Groups (UWGs) represent broad user communities served by the respective DAACs. As regular users of the DAACs and experts in their scientific disciplines, the UWG members provide valuable inputs for planning and prioritizing the services as well as addition of new datasets for the benefit of the community.

Research Integrity↗