The U.S. Department of Agriculture's (USDA) Natural Resources Conservation Service (NRCS), established the STATSGO data base to be designed primarily for regional, multistate, river basin, state, and multicounty resource planning, management, and monitoring. Soil maps for STATSGO are compiled by generalizing more detailed (SSURGO) 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. Using the United States Geological Survey's (USGS) 1:250,000 scale, 1- by 2-degree quadrangle series as a map base, the soil data are digitized by line segment (vector) method to comply with national guidelines and standards. Data for the STATSGO data base are collected in 1- by 2-degree topographic quadrangle units and merged and distributed as statewide coverages. Features are edge matched between states. The map unit composition and the proportionate extent of the map unit components also match between states. STATSGO data provides national coverage at a scale of 1:250,000, except for Alaska, which is at a scale of 1:2,000,000.
The U.S. Department of Agriculture's (USDA) Natural Resources Conservation Service (NRCS), established the STATSGO data base to be designed primarily for regional, multistate, river basin, State, and multicounty resource planning, management, and monitoring. STATSGO data provides national coverage at a scale of 1:250,000, except for Alaska, which is at a scale of 1:2,000,000. This data layer is part of the GeoStac Database, which has been created to simplify risk assesment by providing a common data set upon which to perform analysis for all stakeholders.
This data set does not contain all the attribute data tables in the original source STATSGO tabular data base issued by the NRCS. Rather, it is a portion thereof, consisting only of those tables most useful for performing pesticide risk assesments. To obtain the entire original source STATSGO attribute or spatail data sets, visit the following web site: http://www.essc.psu.edu/soil_info/index.cgi?soil_data&statsgo. The Earth System Science Center in the College of Earth and Mineral Sciences at The Pennsylvania State University has compiled and updated the USDA NRCS STATSGO spatial and tabular data.
A soil map in a soil survey is a representation of soil patterns in a landscape. The scale of the map and the complexity of the soil patterns determine what can be shown on the soil map. In designing soil surveys, the projected uses of the survey and the complexity of the soil patterns largely determine the scale of the soil map. A soil map at 1:250,000 scale should not be used to locate soils for intensive land uses, such as determining suitability for house lots. It is useful for understanding the soil resources and for planning broad use in a State or region. A soil map at 1:20,000 scale is useful in understanding and planning the soil resources of fields, farms, and communities, but it is not useful for planning small (less than 1 acre) research plots. In many places the pattern of soils is very complex, and in some places soils grade imperceptibly to others. Because of this, soil delineations, even on large-scale maps, are not homogeneous or pure; thus, onsite investigations are needed to determine, for example, the suitability of a plot for a septic tank installation when using a soil map at scale of 1:20,000.
897-B Harrison Street, S.E.
The U.S. Department of Agriculture's (USDA) Natural Resources Conservation Service (NRCS).
Downloaded, in Export Exchange (.E00) file format, the three original source STATSGO attribute tabular data sets of interest, 1) Component, 2) Layer, 3) Map Unit, for each of the 48 states in the lower United States, from the following web site: http://www.essc.psu.edu/soil_info/index.cgi?soil_data&statsgo.
Converted the original source tabular data sets from native file to ArcINFO table file type using the ArcMap Tool, Import from Export Exchange.
Imported each of the ArcINFO data tables into an Arc Geodatabase and appended all state files into one comp table, one layer table, and one mapunit table.
Created metadata.
Loaded comp, layer, and mapunit tables into tabular database and created field description table for attributes.
The STATSGO tables available in this data set consist of the following: 1) layer (soil layer): stores characteristics of soil layers for soil components, 2) comp ( soil component): stores soil component information, 3) mapunit (map units): stores information that applies to all components of a soil map unit. The above three tables exist for each states of the lower 48 United States. This metadata document does not define the field types or possible attribute variables that for each of three STATSGO tables in this data set. The STATSGO Data Use Information Publication (cited below) provides this detailed information. This document has been included as an attachment (PDF format) to this database and should be referenced for a full description of field and attribute variables. Note that MUID values NE165 and VT029 are present in the tabular data but missing in spatial representation. Problems in tables discovered during data analysis at PSU/Earth System Science Center (ESSC) are described by state in the known_problems directory. To obtain the STATSGO Data Use Information Publication on the World Wide Web, visit: http://dbwww.essc.psu.edu/dbtop/doc/statsgo/statsgo_info.html.
United States Department of Agriculture, Natural Resources Conservation Service. Soil Geographic (STATSG0) Data Base, Data Use Information Publication, Miscellaneous Publication Number 1492. December 1994.
1500 Research Parkway, Suite B223
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Data can be downloaded from www.geostac.org with a registered user ID and password provided by the Spatial Sciences Laboratory.
Not Applicable
897-B Harrison Street, S.E.