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These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This coverage contains estimates of herbicide use for the eighty-first through the ninety-sixth most-used herbicides in the conterminous United States as reported in Gianessi and Puffer (1991). Herbicide-use estimates in this coverage are reported for each county polygon as acres treated, pounds of active ingredient used, and pounds used per square mile. The herbicide-use estimates provided by Gianessi and Puffer (1991) list acres...
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This data set represents the estimated percentage of the 1-km grid cell that is covered by or subject to the agricultural conservation practice (CP330), Contour Farming (CF) on agricultural land by county. Contour Farming is described as "tillage, planting, and other farming operations performed on or near the contour of the field slope." (U.S. Department of Agriculture, 1995) This data set was created with geographic information...
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. A point coverage was created from the 1980 Master Area Reference File (MARF) of the U.S. Census Bureay. Each point represents the center of a census tract, though some tracts were split. A 1980 population is associated with each point. Populations for 1970, 1982, 1984, and 1985 were inferred from county population data.
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This data set represents soil surface slope, in percent times 1000, in the conterminous United States. The data set was used as an input data layer for a national model to predict nitrate concentration in shallow ground water. Nolan and Hitt (2006) developed two national models to predict contamination of ground water by nonpoint sources of nitrate. The nonlinear approach to national-scale Ground-WAter Vulnerability Assessment (GWAVA)...
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This data set represents the average monthly maximum temperature in Celsius multiplied by 100 for 2002 compiled for every catchment of NHDPlus for the conterminous United States. The source data were the Near-Real-Time High-Resolution Monthly Average Maximum/Minimum Temperature for the Conterminous United States for 2002 raster dataset produced by the Spatial Climate Analysis Service at Oregon State University. The NHDPlus Version...
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This tabular data set represents the area of each level 3 nutrient ecoregion in square meters compiled for every MRB_E2RF1 catchment of the Major River Basins (MRBs, Crawford and others, 2006). The source data are from the 2002 version of the U.S. Environmental Protection Agency's (USEPA) Aggregations of Level III Ecoregions for National Nutrient Assessment & Management Strategy (USEPA, 2002). The MRB_E2RF1 catchments are based on...
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This tabular data set represents the estimated area of level 3 ecological landscape regions (ecoregions), as defined by Omernik (1987), compiled for every MRB_E2RF1 catchment of the Major River Basins (MRBs, Crawford and others, 2006). The source data set is Level III Ecoregions of the Continental United States (U.S. Environmental Protection Agency, 2003). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental...
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This is a line coverage of average annual runoff in the conterminous United States, 1951-1980. Surface runoff Average runoff Surface waters United States
A raster dataset representing multi-year mean (1998-2018) capacity factors (CF) for a solar photovoltaic system based on current technology, for the Conterminous United States. These data are calculated using ½ hourly irradiance values from the National Solar Radiation Database (NSRDB) Sengupta et al. (2018), and the Systems Advisor Model (Blair et al. 2014). Cell values represent the estimated capacity factor (a ratio of net generation to the maximum generation) for photovoltaic energy production for a 1-axis tracking system (technology details found in Maclaurin et al. 2019). The continuous raster were put into 8 quantile bins for interpretation and reporting. For more information and further data, please visit...
A raster dataset representing the soil organic carbon content of surface soil horizons (top 15 cm or ~6 inches) in the conterminous United States. Soil organic carbon is a readily component of soil organic matter, which plays an important role the functioning of soils, including formation of soil structure, soil nutrient content, soil moisture retention, and carbon sequestration. Soil carbon content here is measured as percent by mass. This dataset was created using the soil percent organic carbon 100 m spatial resolution predictive rasters for 0, 5, and 15 cm depths developed by Ramcharan et al. (2018). The average soil organic carbon over the top 15 cm was calculated using the trapezoidal rule, and then put into...
Prior research has shown that sediment budgets, and therefore stability, of microtidal marsh complexes scale with areal unvegetated to vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. This effort has developed the UVVR metric using readily available satellite imagery for the coastal areas of the contiguous United States (CONUS). These datasets provide annual averages of 1) developed, 2) vegetated, 3) unvegetated ratios and 4) an unvegetated to vegetated ratio (UVVR) at 30-meter resolution over the coastal areas of the contiguous United States for the years 2014-2018. Additionally, multi-year average values of vegetated ratio, its standard...
Prior research has shown that sediment budgets, and therefore stability, of microtidal marsh complexes scale with areal unvegetated to vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. This effort has developed the UVVR metric using readily available satellite imagery for the coastal areas of the contiguous United States (CONUS). These datasets provide annual averages of 1) developed, 2) vegetated, 3) unvegetated ratios and 4) an unvegetated to vegetated ratio (UVVR) at 30-meter resolution over the coastal areas of the contiguous United States for the years 2014-2018. Additionally, multi-year average values of vegetated ratio, its standard...
These data were used to quantify land area change in a wetlands possible zone of coastal wetlands during a 1985-2020 observation period. The datasets presented in this data release represent annual median estimates of the fractional amount of land, floating aquatic vegetation, submerged aquatic vegetation, and water per Landsat pixel. These data are intended for coarse-scale analysis of wetland change area. The datasets are summarized by 10-digit Hydrologic Unit Code (HUC10), and land area change through time is fit using a penalized regression smooth spline. The trends are therefore generalized in time and are intended to present coarse scale observations of trends in wetland area change.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Conterminous United States,
Florida,
Gulf of Mexico Coast,
Louisiana,
These data were used to quantify land area change in a wetlands possible zone of coastal wetlands during a 1985-2020 observation period. The datasets presented in this data release represent annual median estimates of the fractional amount of land, floating aquatic vegetation, submerged aquatic vegetation, and water per Landsat pixel. These data are intended for coarse-scale analysis of wetland change area. The datasets are summarized by 10-digit Hydrologic Unit Code (HUC10), and land area change through time is fit using a penalized regression smooth spline. The trends are therefore generalized in time and are intended to present coarse scale observations of trends in wetland area change.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Conterminous United States,
Florida,
Gulf of Mexico Coast,
Louisiana,
These data were used to quantify land area change in a wetlands possible zone of coastal wetlands during a 1985-2020 observation period. The datasets presented in this data release represent annual median estimates of the fractional amount of land, floating aquatic vegetation, submerged aquatic vegetation, and water per Landsat pixel. These data are intended for coarse-scale analysis of wetland change area. The datasets are summarized by 10-digit Hydrologic Unit Code (HUC10), and land area change through time is fit using a penalized regression smooth spline. The trends are therefore generalized in time and are intended to present coarse scale observations of trends in wetland area change.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Conterminous United States,
Florida,
Gulf of Mexico Coast,
Louisiana,
This child item describes Python code used to estimate average yearly and monthly tourism per 1000 residents within public-supply water service areas. Increases in population due to tourism may impact amounts of water used by public-supply water systems. This data release contains model input datasets, Python code used to develop the tourism information, and output estimates of tourism. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Output from this code was used as an input feature in the public supply delivery and water use machine learning models. This page includes the following files: tourism_input_data.zip...
This child item describes a public supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. This dataset is part of a larger data release using machine learning to predict public-supply water use for 12-digit hydrologic units from 2000-2020. This page includes the following...
This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input...
Maintaining the native prairie lands of the Northern Great Plains (NGP), which provide an important habitat for declining grassland species, requires anticipating the effects of increasing atmospheric carbon dioxide (CO2) concentrations and climate change on the region’s vegetation. Specifically, climate change threatens NGP grasslands by increasing the potential encroachment of native woody species into areas where they were previously only present in minor numbers. This project used a dynamic vegetation model to simulate vegetation type (grassland, shrubland, woodland, and forest) for the NGP for a range of projected future climates and relevant management scenarios. Comparing results of these simulations illustrates...
Categories: Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2012,
Biology,
CASC,
Climate change,
Completed,
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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