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The glacial aquifer system of the United States encompasses all or parts of 25 states and is the most widely used supply of drinking water in the Nation (Maupin and Barber, 2005; Maupin and Arnold, 2010). A series of seven raster data sets were derived from a database of water-well drillers' records that was compiled in partial fulfillment of the goals of the U.S. Geological Survey’s Groundwater Availability and Use assessment program (U.S. Geological Survey, 2002). They contain hydrogeologic information for areas of the U.S. that are north of the southern limit of Pleistocene glaciation, including the total thickness of glacial deposits, thickness of coarse-grained sediment within the glacial deposits, specific-capacity...
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Accurate and consistent estimates of shrubland ecosystem components are crucial to a better understanding of ecosystems condition in arid and semiarid lands. We developed an innovative approach by integrating multiple information to quantify shrubland components as continuous field products within the National Land Cover Database (NLCD). The approach consists of five major parts: field sample collection, high-resolution mapping of shrubland components using WorldView-3 imagery and regression tree models, Landsat 8 radiometric balancing and phenological mosaicking, coarse resolution estimate of shrubland components across a large geographic extent using Landsat 8 phenological mosaics and regression tree models, and...
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Accurate and consistent estimates of shrubland ecosystem components are crucial to a better understanding of ecosystems condition in arid and semiarid lands. We developed an innovative approach by integrating multiple information to quantify shrubland components as continuous field products within the National Land Cover Database (NLCD). The approach consists of five major parts: field sample collection, high-resolution mapping of shrubland components using WorldView-3 imagery and regression tree models, Landsat 8 radiometric balancing and phenological mosaicking, coarse resolution estimate of shrubland components across a large geographic extent using Landsat 8 phenological mosaics and regression tree models, and...
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The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in dense time series of Landsat image stacks to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm makes use of predictors derived from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions. Outputs of the BAECV algorithm consist of pixel-level burn probabilities for each Landsat scene, and annual burn probability, burn classification, and burn date composites. These products were generated for the conterminous United States for 1984 through 2015. These data are also available for download at https://rmgsc.cr.usgs.gov/outgoing/baecv/BAECV_CONUS_v1.1_2017/...


map background search result map search result map Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 - 2015) USGS Small-scale Dataset - Congressional Districts of the United States - 110th Congress 200710 Shapefile USGS Small-scale Dataset - Congressional Districts of the United States - 112th Congress 201101 Shapefile Total Thickness of Glacial Deposits Shrub Percent - Provisional Remote Sensing Shrub/Grass NLCD Products for the Montona/Wyoming Study Area Bare Ground Percent  - Provisional Remote Sensing Shrub/Grass NLCD Products for the Montona/Wyoming Study Area USGS Combined Vector for Elk Point NE, Iowa 20160513 7.5 x 7.5 minute Shapefile USGS Topo Map Vector Data (Vector) 447 Alcester SE, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 56 Aberdeen West, South Dakota 20180210 for 7.5 x 7.5 minute Shapefile USGS Topo Map Vector Data (Vector) 250 Agar NW, South Dakota 20180210 for 7.5 x 7.5 minute Shapefile USGS Topo Map Vector Data (Vector) 2209 Bald Hills, South Dakota 20180209 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 6479 Butte, Nebraska 20180209 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 4771 Bond Bottom, South Dakota 20180209 for 7.5 x 7.5 minute Shapefile USGS Topo Map Vector Data (Vector) 17011 Geddes, South Dakota 20180209 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 25404 Lemmon Creek, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 25405 Lemmon Lake, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 32706 Oahe Dam, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 39935 Santee, Nebraska 20180209 for 7.5 x 7.5 minute Shapefile USGS Topo Map Vector Data (Vector) 40574 Seneca NW, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 48097 Wentworth, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Combined Vector for Elk Point NE, Iowa 20160513 7.5 x 7.5 minute Shapefile USGS Topo Map Vector Data (Vector) 447 Alcester SE, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 56 Aberdeen West, South Dakota 20180210 for 7.5 x 7.5 minute Shapefile USGS Topo Map Vector Data (Vector) 250 Agar NW, South Dakota 20180210 for 7.5 x 7.5 minute Shapefile USGS Topo Map Vector Data (Vector) 2209 Bald Hills, South Dakota 20180209 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 6479 Butte, Nebraska 20180209 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 4771 Bond Bottom, South Dakota 20180209 for 7.5 x 7.5 minute Shapefile USGS Topo Map Vector Data (Vector) 17011 Geddes, South Dakota 20180209 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 25404 Lemmon Creek, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 25405 Lemmon Lake, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 32706 Oahe Dam, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 39935 Santee, Nebraska 20180209 for 7.5 x 7.5 minute Shapefile USGS Topo Map Vector Data (Vector) 40574 Seneca NW, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 48097 Wentworth, South Dakota 20180210 for 7.5 x 7.5 minute FileGDB 10.1 Shrub Percent - Provisional Remote Sensing Shrub/Grass NLCD Products for the Montona/Wyoming Study Area Bare Ground Percent  - Provisional Remote Sensing Shrub/Grass NLCD Products for the Montona/Wyoming Study Area Total Thickness of Glacial Deposits Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 - 2015) USGS Small-scale Dataset - Congressional Districts of the United States - 110th Congress 200710 Shapefile USGS Small-scale Dataset - Congressional Districts of the United States - 112th Congress 201101 Shapefile