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These data represent total vegetation and surface water along approximately 12 kilometers of the Paria River upstream from the confluence of the Colorado River at Lees Ferry, Arizona. They are derived from airborne, multispectral imagery obtained in late May 2009, 2013, and 2021, collected with a push-broom sensor with 4 spectral bands depicting Blue, Green, Red and Near-Infrared wavelengths at a spatial resolution of 20 centimeters. The vegetation classification data were created using a supervised classification algorithm provided by Harris Geospatial in ENVI version 5.6.3 (Exelis Visual Information Solutions, Boulder, Colorado). The water data were created using a Green Normalized Difference Vegetation Index...
Tags: Arizona, Botany, Cloud Optimized GeoTIFF data, Colorado River, Ecology, All tags...
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The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
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This dataset of the elevation of basement and thickness of sediment above the syn- and post-rift unconformity (sediments above being generally Late Cretaceous and younger) was constructed for application to site response models in earthquake hazard analyses. Sediment thickness in meters is provided in zipped csv format on a 0.01-degree grid, and sediment thickness and basement elevation in meters relative to mean sea level are provided in GeoTIFF format on a 1-km grid.
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The Mohorovicic discontinuity or 'Moho' maps the boundary between the earth's crust and mantle and is defined by an abrupt change in seismic velocity due to changes in the density of rocks between the crust and mantle. GeoTIFF grids that map depth to Moho (crustal thickness) for the United States and Canada, and for Australia are provided in this report and were used as evidential layers in developing prospectivity models for basin-hosted Pb-Zn mineralization (Lawley and others, 2022). A composite grid of Moho depths across the United States and Canada was created using data from Shen and Ritzwoller (2016) for the conterminous United States, from Zhang and others (2019) for Alaska, and from Schetselaar and Snyder...
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Several evidential layers calculated from the national-scale gravity anomaly map of Australia (Geophysical Acquisition and Processing Section, 2020) are provided here. This directory includes GeoTIFF grids of Bouguer gravity, the horizontal gradient magnitude of the Bouguer gravity, the Bouguer gravity upward continued 30 km, and the horizontal gradient magnitude of the upward continued gravity, The directory also includes shapefiles of locations that trace the maxima of the horizontal gradient magnitude of the gravity and of the maxima of the horizontal gradient magnitude of the upward continued gravity. Otherwise known as “worms”, the points tracking the maxima mark the edges of shallow density sources (in the...
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This data release has been deprecated. Please see new data release here: https://doi.org/10.5066/P9CIK9ZF. This data release documents the digital data used to produce flood-inundation maps for a range of gage heights (stages) for the Sabinal River near Utopia, Tex. The simulated flood-inundation maps correspond to a range in stage from 7 to 24 feet (ft) at U.S. Geological Survey (USGS) streamgage 08197970 Sabinal River at Utopia, Tex. at intervals of 0.5-ft. The maps were created for a 10-mile reach of the Sabinal River from USGS streamgage 08197936 Sabinal River below Mill Creek near Vanderpool, Tex., at the upstream boundary of the study reach, to USGS streamgage 08197970 Sabinal River at Utopia, Tex. (hereinafter...
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These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin above Hoover Dam. Random forest models related environmental raster layers representing soil forming factors with field samples to render predictive maps that interpolate between sample locations. Maps represented soil pH, texture fractions (sand, silt clay, fine sand, very fine sand), rock, electrical conductivity (ec), gypsum, CaCO3, sodium adsorption ratio (sar), available water capacity (awc), bulk density (dbovendry), erodibility (kwfact), and organic matter (om) at 7 depths (0, 5, 15, 30, 60, 100, and 200 cm) as well as depth to restrictive...
Tags: Arizona, Colorado, Colorado River, Colorado River Basin, Colorado River Basin above Hoover Dam, All tags...
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The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
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The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
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The Chesapeake Bay Land Use and Land Cover Database (LULC) facilitates characterization of the landscape and land change for and between discrete time periods. The database was developed by the University of Vermont’s Spatial Analysis Laboratory in cooperation with Chesapeake Conservancy (CC) and U.S. Geological Survey (USGS) as part of a 6-year Cooperative Agreement between Chesapeake Conservancy and the U.S. Environmental Protection Agency (EPA) and a separate Interagency Agreement between the USGS and EPA to provide geospatial support to the Chesapeake Bay Program Office. The database contains one-meter 13-class Land Cover (LC) and 54-class Land Use/Land Cover (LULC) for all counties within or adjacent to the...
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This data release has been deprecated. Please see new data release here: https://doi.org/10.5066/P9CIK9ZF. This data release documents the digital data used to produce flood-inundation maps for a range of gage heights (stages) for the Sabinal River near Utopia, Tex. The simulated flood-inundation maps correspond to a range in stage from 7 to 24 feet (ft) at U.S. Geological Survey (USGS) streamgage 08197970 Sabinal River at Utopia, Tex. at intervals of 0.5-ft. The maps were created for a 10-mile reach of the Sabinal River extending from USGS streamgage 08197936 Sabinal River below Mill Creek near Vanderpool, Tex. to USGS streamgage 08197970 Sabinal River at Utopia, Tex. (hereinafter referred to as the “Utopia gage”)...
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The St. Louis area has experienced minor earthquake damage at least 12 times in the past 205 years. The St. Louis metropolitan area, with a population of about 2.8 million, faces earthquake hazard from large earthquakes in the New Madrid and Wabash Valley seismic zones, as well as a closer region of diffuse historical and prehistoric seismicity to its south and east. Also, low attenuation of seismic energy in the region and a substantial number of historic older unreinforced brick and stone buildings make the St. Louis area vulnerable to moderate earthquakes at relatively large distances compared to the western United States. This geotechnical database was compiled by James Palmer and others at the Missouri Department...
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These raster datasets are 3-meter lidar-derived images of Monroe County, West Virginia, and were created using geographic information systems (GIS) software. Lidar-derived elevation data acquired in late December of 2016 were used to create a 3-meter resolution working digital elevation model (DEM), from which a hillshade was applied and a topographic position index (TPI) raster was calculated. These two rasters were uploaded into GlobalMapper, where the TPI raster was made partially transparent and overlaid the hillshade DEM. The resulting image was exported to create a 3-meter resolution lidar-derived image. The data is projected in North America Datum (NAD) 1983 UTM Zone 17.
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This directory includes GeoTIFF grids and shapefiles of magnetic data that cover the countries of the US and Canada. GeoTIFF grids of national-scale magnetic anomaly data for the conterminous United States (Ravat and others, 2009), Alaska (Division of Geological and Geophysical Surveys, 2016) and Canada (Miles and Oneschuk, 2016) were merged to create a composite residual magnetic anomaly grid of the United States and Canada. Several derivative products were calculated from the residual magnetic anomaly grid and are provided in this directory. Derivative grids include a reduced-to-pole (RTP) magnetic anomaly grid, the 1st vertical derivative of the RTP, the horizontal gradient magnitude pseudo-gravity calculated...
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The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
The U.S. Geological Survey (USGS) National Extent Hydrogeologic Framework for National Water Census (NEHF) project is a multi-year effort (2022 through 2025) that will compile existing assets (approaches, data, software, etc.), develop a strategic plan, and implement an operational framework that is dynamic and multi-scale. Within the USGS, numerical groundwater-flow and solute- and heat-transport models have been created for a variety of purposes that include water-resource assessments, contaminant-transport evaluations, and water-management planning. These models are often supported by hydrogeologic-framework studies that describe the surface and subsurface distribution of geologic materials and their hydrologic...
The Chesapeake Bay Land Use and Land Cover Database (LULC) facilitates characterization of the landscape and land change for and between discrete time periods. The database was developed by the University of Vermont’s Spatial Analysis Laboratory in cooperation with Chesapeake Conservancy (CC) and U.S. Geological Survey (USGS) as part of a 6-year Cooperative Agreement between Chesapeake Conservancy and the U.S. Environmental Protection Agency (EPA) and a separate Interagency Agreement between the USGS and EPA to provide geospatial support to the Chesapeake Bay Program Office. The database contains one-meter 13-class Land Cover (LC) and 54-class Land Use/Land Cover (LULC) for all counties within or adjacent to the...
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Data presented here include a shapefile that combines fault data for the United States and Canada (Chorlton, 2007; Reed and others, 2005; Styron and Pagani, 2020) and a shapefile of faults for Australia (Chorlton, 2007; Raymond and others, 2012; Styron and Pagani, 2020). These two shapefiles were used as an evidential layer to evaluate the mineral prospectivity for sediment-hosted Pb-Zn deposits (Lawley and others, 2022). References Chorlton, L.B., 2007, Generalized geology of the world: Bedrock domains and major faults in GIS format: a small-scale world geology map with an extended geological attribute database: Geological Survey of Canada Open File 5529, https://doi.org/10.4095/223767. Lawley, C.J.M., McCafferty,...
The Chesapeake Bay Land Use and Land Cover Database (LULC) facilitates characterization of the landscape and land change for and between discrete time periods. The database was developed by the University of Vermont’s Spatial Analysis Laboratory in cooperation with Chesapeake Conservancy (CC) and U.S. Geological Survey (USGS) as part of a 6-year Cooperative Agreement between Chesapeake Conservancy and the U.S. Environmental Protection Agency (EPA) and a separate Interagency Agreement between the USGS and EPA to provide geospatial support to the Chesapeake Bay Program Office. The database contains one-meter 13-class Land Cover (LC) and 54-class Land Use/Land Cover (LULC) for all counties within or adjacent to the...
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The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...


map background search result map search result map Predictive soil property map: Very fine sand content Lidar-derived imagery and digital elevation model of Monroe County, West Virginia at 3-meter resolution [Geophysical Data] Magnetic and related derivative GeoTIFF grids and data for the United States and Canada [Geophysical Data] Gravity and related derivative GeoTIFF grids and data for Australia [Geophysical Data] Depth to Moho GeoTIFF grids for the United States, Canada, and Australia [Geological Data] Shapefiles of faults for the United States, Canada, and Australia Flood-inundation depth grid files for selected reaches of the Sabinal River and the West Sabinal River near Utopia, Texas, 2021 Two-dimensional unsteady state HEC–RAS model to create flood-inundation maps for selected reaches of the Sabinal River and the West Sabinal River near Utopia, Texas, 2021 Chesapeake Bay Land Use and Land Cover (LULC) Database 2022 Edition St. Louis Geotechnical Database, v2003 Atlantic and Gulf Coastal Plains Sediment Thickness (v220517) Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 11 UMRR LTRM 2020 LCU Mapping - Mississippi River Pool 11 UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 07 UMRR LTRM 2020 LCU Mapping - Mississippi River Pool 01 UMRR LTRM 2020 LCU Mapping - St. Croix Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA Flood-inundation depth grid files for selected reaches of the Sabinal River and the West Sabinal River near Utopia, Texas, 2021 Two-dimensional unsteady state HEC–RAS model to create flood-inundation maps for selected reaches of the Sabinal River and the West Sabinal River near Utopia, Texas, 2021 UMRR LTRM 2020 LCU Mapping - Mississippi River Pool 01 UMRR LTRM 2020 LCU Mapping - St. Croix UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 07 UMRR LTRM 2020 LCU Mapping - Mississippi River Pool 11 UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 11 Lidar-derived imagery and digital elevation model of Monroe County, West Virginia at 3-meter resolution St. Louis Geotechnical Database, v2003 Chesapeake Bay Land Use and Land Cover (LULC) Database 2022 Edition Predictive soil property map: Very fine sand content Atlantic and Gulf Coastal Plains Sediment Thickness (v220517) [Geophysical Data] Gravity and related derivative GeoTIFF grids and data for Australia [Geophysical Data] Magnetic and related derivative GeoTIFF grids and data for the United States and Canada [Geophysical Data] Depth to Moho GeoTIFF grids for the United States, Canada, and Australia [Geological Data] Shapefiles of faults for the United States, Canada, and Australia