This dataset consists of general soil association units. It was developed by the National Cooperative Soil Survey and supersedes the State Soil Geographic (STATSGO) dataset published in 1994. It consists of a broad based inventory of soils and non-soil areas that occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped of 1:250,000 in the continental U.S., Hawaii, Puerto, and the Virgin Islands and 1:1,000,000 in Alaska. The dataset was created by generalizing more detailed soil survey maps. Where more detailed soil survey maps were not available, data on geology, topography, vegetation, and climate were assembled, together with Land Remote Sensing Satellite (LANDSAT) images. Soils of like areas were studied, and the probable classification and extent of the soils were determined. Map unit composition was determined by transecting or sampling areas on the more detailed maps and expanding the data statistically to characterize the entire map unit. This dataset consists of georeferenced vector digital data and tabular digital data. The map data were collected in 1- by 2-degree topographic quadrangle units and merged into a seamless national dataset. The soil map units are linked to attributes in the National Soil Information system relational database, which gives the proportionate extent of the component soils and their properties. These data provide information about soil features on or near the surface of the Earth. Data were collected as part of the National Cooperative Soil Survey. These data are intended for geographic display and analysis at the state, regional, and national level. The data should be displayed and analyzed at scales appropriate for 1:250,000-scale data.

This dataset consists of general soil association units. It was developed by the National Cooperative Soil Survey and supersedes the State Soil Geographic (STATSGO) dataset published in 1994. It consists of a broad based inventory of soils and nonsoil areas that occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped of 1:250,000 in the continental U.S., Hawaii, Puerto, and the Virgin Islands and 1:1,000,000 in Alaska. The dataset was created by generalizing more detailed soil survey maps. Where more detailed soil survey maps were not available, data on geology, topography, vegetation, and climate were assembled, together with Land Remote Sensing Satellite (LANDSAT) images. Soils of like areas were studied, and the probable classification and extent of the soils were determined. Map unit composition was determined by transecting or sampling areas on the more detailed maps and expanding the data statistically to characterize the entire map unit. This dataset consists of georeferenced vector digital data and tabular digital data. The map data were collected in 1- by 2-degree topographic quadrangle units. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties. These data provide information about soil features on or near the surface of the Earth. Data were collected as part of the National Cooperative Soil Survey. These data are intended for geographic display and analysis at the state, regional, and national level. The data should be displayed and analyzed at scales appropriate for 1:250,000-scale data.

This digital data release consists of an ARC/INFO grid and associated INFO tables. The grid is called MUID and has STATSGO (U.S. Department of Agriculture, 1994) soil mapping unit identifiers gridded on a 1-kilometer resolution for the conterminous United States. The INFO tables have soil characteristics data in them. The ITEMS in the tables are weighted average values for several soil characteristics in the STATSGO data base. The weighted average values were computed by aggregating the soil layers and components in the data base. The INFO tables are called MUID.LAYER, MUID.COMP, MUID.KFACT, MUID.TFACT, and MUID.WEG. The INFO tables can be related or joined to the MUID grid or to individual State coverages (grids or polygons) of MUIDs. Joining or relating the tables to the MUID grid creates 1-kilometer resolution grids of the soil characteristics for the conterminous United States. The soil characteristics in MUID.LAYER are permeability (PERML and PERMH in the STATSGO data base), available water capacity (AWCL and AWCH), bulk density (BDL and BDH), and organic matter (OML and OMH). The soil characteristics in MUID.COMP are slope (SLOPEL and SLOPEH), depth to seasonally high water table (WTDEPL and WTDEPH), and depth to bedrock (ROCKDEPL and ROCKDEPH). The soil characteristic in MUID.KFACT is the soil erodibility factor (KFACT), the soil characteristic in MUID.TFACT is the soil loss tolerance factor (TFACT), and the soil characteristic in MUID.WEG is the wind erosion group (WEG). The MUID grid and INFO tables were created with a set of arc macro language (aml) and Fortran programs. Send electronic mail to dwolock@usgs.gov to obtain copies of the computer code. (See Procedures_Used.)

This dataset is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This dataset consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties. SSURGO depicts information about the kinds and distribution of soils on the landscape. The soil map and data used in the SSURGO product were prepared by soil scientists as part of the National Cooperative Soil Survey.

This dataset is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This dataset consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties. SSURGO depicts information about the kinds and distribution of soils on the landscape. The soil map and data used in the SSURGO product were prepared by soil scientists as part of the National Cooperative Soil Survey.

This dataset is called the Gridded SSURGO (gSSURGO) Database and is derived from the Soil Survey Geographic (SSURGO) Database. SSURGO is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey (NCSS) in accordance with NCSS mapping standards. The tabular data represent the soil attributes, and are derived from properties and characteristics stored in the National Soil Information System (NASIS). The gSSURGO data were prepared by merging traditional SSURGO digital vector map and tabular data into a Conterminous US-wide extent, and adding a Conterminous US-wide gridded map layer derived from the vector, plus a new value added look up (valu) table containing "ready to map" attributes. The gridded map layer is offered in an ArcGIS file geodatabase raster format. The raster and vector map data have a Conterminous US-wide extent. The raster map data have a 30 meter cell size. Each cell (and polygon) is linked to a map unit identifier called the map unit key. A unique map unit key is used to link to raster cells and polygons to attribute tables, including the new value added look up (valu) table that contains additional derived data. The value added look up (valu) table contains attribute data summarized to the map unit level using best practice generalization methods intended to meet the needs of most users. The generalization methods include map unit component weighted averages and percent of the map unit meeting a given criteria. The Gridded SSURGO dataset was created for use in national, regional, and state-wide resource planning and analysis of soils data. The raster map layer data can be readily combined with other national, regional, and local raster layers, e.g., National Land Cover Database (NLCD), the National Agricultural Statistics Service (NASS) Crop Data Layer, or the National Elevation Dataset (NED).

This dataset is called the Gridded SSURGO (gSSURGO) Database and is derived from the Soil Survey Geographic (SSURGO) Database. SSURGO is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey (NCSS) in accordance with NCSS mapping standards. The tabular data represent the soil attributes, and are derived from properties and characteristics stored in the National Soil Information System (NASIS). The gSSURGO data were prepared by merging traditional SSURGO digital vector map and tabular data into a Conterminous US-wide extent, and adding a Conterminous US-wide gridded map layer derived from the vector, plus a new value added look up (valu) table containing "ready to map" attributes. The gridded map layer is offered in an ArcGIS file geodatabase raster format. The raster and vector map data have a Conterminous US-wide extent. The raster map data have a 30 meter cell size. Each cell (and polygon) is linked to a map unit identifier called the map unit key. A unique map unit key is used to link to raster cells and polygons to attribute tables, including the new value added look up (valu) table that contains additional derived data. The value added look up (valu) table contains attribute data summarized to the map unit level using best practice generalization methods intended to meet the needs of most users. The generalization methods include map unit component weighted averages and percent of the map unit meeting a given criteria. The Gridded SSURGO dataset was created for use in national, regional, and state-wide resource planning and analysis of soils data. The raster map layer data can be readily combined with other national, regional, and local raster layers, e.g., National Land Cover Database (NLCD), the National Agricultural Statistics Service (NASS) Crop Data Layer, or the National Elevation Dataset (NED).

Data available online through the Arkansas Spatial Data Infrastructure (http://gis.arkansas.gov). This data set is a digital general soil association map developed by the National Cooperative Soil Survey. It consists of a broad based inventory of soils and nonsoil areas that occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. The soil maps for STATSGO are compiled by generalizing more detailed soil survey maps. Where more detailed soil survey maps are not available, data on geology, topography, vegetation, and climate are assembled, together with Land Remote Sensing Satellite (LANDSAT) images. Soils of like areas are studied, and the probable classification and extent of the soils are determined. Map unit composition for a STATSGO map is determined by transecting or sampling areas on the more detailed maps and expanding the data statistically to characterize the whole map unit. This data set consists of georeferenced digital map data and computerized attribute data. The map data are collected in 1- by 2-degree topographic quadrangle units and merged and distributed as statewide coverages. The soil map units are linked to attributes in the Map Unit Interpretations Record relational data base which gives the proportionate extent of the component soils and their properties.

The National Soil Information System (NASIS) data system consists of multiple interrelated soil applications and databases. This data system aids in the collection, storage, manipulation and dissemination of soil information.

The dataset consists of three raster GeoTIFF files describing the following soil properties in the US: available water capacity, field capacity, and soil porosity. The input data were obtained from the gridded National Soil Survey Geographic (gNATSGO) Database and the Gridded Soil Survey Geographic (gSSURGO) Database with Soil Data Development tools provided by the Natural Resources Conservation Service. The soil characteristics derived from the databases were Available Water Capacity (AWC), Water Content (one-third bar) (WC), and Bulk Density (one-third bar) (BD) aggregated as weighted average values in the upper 1 m of soil. AWC and WC layers were converted to mm/m to express respectively available water capacity and field capacity in 1 m of soil, and BD layer was used to produce soil porosity raster assuming that the average particle density of soils is equal to 2.65 g/cm3. For each soil property, soil maps with CONUS, Alaska, and Hawaii geographic coverages were derived from separate databases and combined into one file. To replace no data values within a raster, we used data values statistically derived from neighboring cell values. The final product is provided in a GeoTIFF format and therefore can be easily integrated into raster-based models requiring estimates of soil characteristics in the US.