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.)

USSOILS is an Arc 7.0 coverage containing hydrology-relevant information for 10,498 map units covering the entire conterminous United States. The coverage was compiled from individual State coverages contained in the October 1994 State Soil Geographic (STATSGO) Data Base produced on CD-ROM. The geo-dataset USSOILS.PAT relates (on the basis of a map unit identifier) the 10,498 map units to 78,518 polygons. The scale of the geo-dataset is 1:250,000. The INFO attribute table USSOILS.MUID_ATTS contains selected variables from the STATSGO data set for 10,501 map units (an extra 3 map units are contained in the attribute table that are not in the geo-dataset - see the 'Procedures' section below), including: the map unit identifier, a 2-character state abbreviation, available water capacity of the soil, percent clay in the soil, the actual k-factor used in the water erosion component of the universal soil loss equation, the organic material in soil, soil permeability, cumulative thickness of all soil layers, hydrologic characteristics of the soil, quality of drainage, surface slope, liquid limit of the soil, share of a map unit having hydric soils, and the annual frequency of flooding. To facilitate mapping the attribute data, the narrative section below contains instructions for transferring the information contained in the attribute table USSOILS.MUID_ATTS to the polygon attribute table USSOILS.PAT. STATSGO United States Soil Water Capacity Clay Organic material Permeability Infiltration Drainage Hydric Flood frequency Slope

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 record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: STATSGO2-State For complete information, please visit https://data.gov.

This data set consists of general soil association units. It was developed by the National Cooperative Soil Survey and supersedes the State Soil Geographic (STATSGO) data set 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. The data set 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 whole map unit.

This data set 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 data set. It is distributed in state/territory and national extents. The soil map units are linked to attributes in the National Soil Information System data base which gives the proportionate extent of the component soils and their properties.

MnGeo adapted the NRCS metadata record to create this record.

This data release reformats the STATSGO soil thickness (THICK) dataset (Schwarz and Alexander, 1995) as a cloud-optimized GeoTIFF (COG). The COG format allows standard software tools to efficiently access the datasets over an internet connection. The soil thickness values have units of inches. Please refer to the documentation of the source archive (Schwarz and Alexander, 1995) for additional details on the underlying dataset. The COG dataset spans the continental US at a nominal 30 meter resolution. The spatial reference is EPSG:5069. Each COG uses a float32 precision, and the NoData value (NaN) indicates raster pixels not covered by the original STATSGO dataset. The COG also includes non-physical values of -0.1, which were used by the source dataset to mark large water bodies. The COG format uses compression internally to reduce file size. As such, reading large portions of a COG into memory can require much more RAM than the nominal file size. This COG will require ~60GB of memory to read in full. This dataset can be reproduced by running the rasterize_statsgo.py Python script included in this dataset's parent folder (https://doi.org/10.5066/P13WAPYV). Please refer to the script for documentation and usage instructions. Disclaimer: Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. References: Schwarz, G.E. and Alexander, R.B., 1995, Soils data for the Conterminous United States Derived from the NRCS State Soil Geographic (STATSGO) Data Base. [Original title: State Soil Geographic (STATSGO) Data Base for the Conterminous United States.]: U.S. Geological Survey data release, https://doi.org/10.5066/P94JAULO.

This layer shows the U.S. General Soil Map of general soil association units by the United States Department of Agriculture’s Natural Resources Conservation Service. 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. The soil units are symbolized by Esri to show the dominant condition for the 12 soil orders according to Soil Taxonomy. Dominant condition was determined by evaluating each of the components in a map unit; the percentage of the component that each soil order represented was accumulated for all the soil orders present in the map unit. The soil order with the highest accumulated percentage is then characterized as the dominant condition for that unit. If a tie was found between soil orders, a “tie-break” rule was applied. The tie-break was based on the component’s “slope_r” attribute value, which represents the Slope Gradient – Representative Value. The slope_r values were accumulated in the same fashion as the soil order attributes, i.e., by soil order, and the order with the lowest slope_r value was selected as dominant because that represented the lower slope value, and therefore we assumed the soils were more likely to be staying in that area or being deposited in that area.

USDA/NRCS SSURGO: This layer shows the Soil Survey Geographic (SSURGO) by the United States Department of Agriculture’s Natural Resources Conservation Service. SSURGO digitizing duplicates the original soil survey maps. This level of mapping is designed for use by landowners, townships, and county natural resource planning and management. The user should be knowledgeable of soils data and their characteristics. The soil units are symbolized by Esri to show the dominant condition for the 12 soil orders according to Soil Taxonomy. Dominant condition was determined by evaluating each of the components in a map unit; the percentage of the component that each soil order represented was accumulated for all the soil orders present in the map unit. The soil order with the highest accumulated percentage is then characterized as the dominant condition for that unit. If a tie was found between soil orders, a “tie-break” rule was applied. The tie-break was based on the component’s “slope_r” attribute value, which represents the Slope Gradient – Representative Value. The slope_r values were accumulated in the same fashion as the soil order attributes, i.e., by soil order, and the order with the lowest slope_r value was selected as dominant because that represented the lower slope value, and therefore we assumed the soils were more likely to be staying in that area or being deposited in that area. USDA/NRCS STATSGO This layer shows the U.S. General Soil Map of general soil association units by the United States Department of Agriculture’s Natural Resources Conservation Service. 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. The soil units are symbolized by Esri to show the dominant condition for the 12 soil orders according to Soil Taxonomy. Dominant condition was determined by evaluating each of the components in a map unit; the percentage of the component that each soil order represented was accumulated for all the soil orders present in the map unit. The soil order with the highest accumulated percentage is then characterized as the dominant condition for that unit. If a tie was found between soil orders, a “tie-break” rule was applied. The tie-break was based on the component’s “slope_r” attribute value, which represents the Slope Gradient – Representative Value. The slope_r values were accumulated in the same fashion as the soil order attributes, i.e., by soil order, and the order with the lowest slope_r value was selected as dominant because that represented the lower slope value, and therefore we assumed the soils were more likely to be staying in that area or being deposited in that area. USDA/NRCS GLOBAL SOIL REGIONS This layer shows the Global Soil Regions map by the United States Department of Agriculture’s Natural Resources Conservation Service. The data and symbology are based on a reclassification of the FAO-UNESCO Soil Map of the World combined with a soil climate map. The soils data is symbolized to show the distribution of the 12 soil orders according to Soil Taxonomy. For more information on this map, including the terms of use, visit us online.Website Link: https://www.nrcs.usda.gov/wps/portal/nrcs/site/national/home/

This data release reformats data fields from the STATSGO soil characteristics dataset (Schwarz and Alexander, 1995) as cloud-optimized GeoTIFFs (COGs). The COG format allows standard software tools to efficiently access the datasets over an internet connection. Please refer to the documentation of the source archive (Schwarz and Alexander, 1995) for additional details on the underlying dataset. This data release includes COGs for the KF-factor (KFFACT) and soil thickness (THICK) data fields. KF-factors are defined as the saturated hydraulic conductivity of the fine soil (< 2mm) fraction in units of inches per hour. The soil thickness dataset has units of inches. Each COG raster spans the continental US at a nominal 30 meter resolution. The spatial reference is EPSG:5069. Each COG uses a float32 precision, and the NoData value (NaN) indicates raster pixels not covered by the original STATSGO dataset. The COGs also include non-physical values of -0.1, which were used by the source STATSGO archive to mark large water bodies. The COG format uses compression internally to reduce file size. As such, reading large portions of a COG into memory can require much more RAM than the nominal file size. The COGs in this dataset will require ~60GB of memory to read in full. This dataset can be reproduced by running the included rasterize_statsgo.py Python script. Please refer to the script for documentation and usage instructions. Disclaimer: Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. References: Schwarz, G.E. and Alexander, R.B., 1995, Soils data for the Conterminous United States Derived from the NRCS State Soil Geographic (STATSGO) Data Base. [Original title: State Soil Geographic (STATSGO) Data Base for the Conterminous United States.]: U.S. Geological Survey data release, https://doi.org/10.5066/P94JAULO.

This data set consists of general soil association units. It was developed by the National Cooperative Soil Survey and supersedes the State Soil Geographic (STATSGO) data set published in 2006. 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 data set 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 whole map unit.

This data set 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 data set. It is distributed in state/territory and national extents. The soil map units are linked to attributes in the National Soil Information System data base which gives the proportionate extent of the component soils and their properties.

This data release reformats the STATSGO KF-factor (KFFACT) dataset (Schwarz and Alexander, 1995) as a cloud-optimized GeoTIFF (COG). The COG format allows standard software tools to efficiently access the datasets over an internet connection. KF-factors are defined as the saturated hydraulic conductivity of the fine soil (< 2mm) fraction. Units are inches per hour. Please refer to the documentation of the source archive (Schwarz and Alexander, 1995) for additional details on the underlying dataset. The COG dataset spans the continental US at a nominal 30 meter resolution. The spatial reference is EPSG:5069. Each COG uses a float32 precision, and the NoData value (NaN) indicates raster pixels not covered by the original STATSGO dataset. The COG also includes non-physical values of -0.1, which were used by the source dataset to mark large water bodies. The COG format uses compression internally to reduce file size. As such, reading large portions of a COG into memory can require much more RAM than the nominal file size. This COG will require ~60GB of memory to read in full. This dataset can be reproduced by running the rasterize_statsgo.py Python script included in this dataset's parent folder (https://doi.org/10.5066/P13WAPYV). Please refer to the script for documentation and usage instructions. Disclaimer: Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. References: Schwarz, G.E. and Alexander, R.B., 1995, Soils data for the Conterminous United States Derived from the NRCS State Soil Geographic (STATSGO) Data Base. [Original title: State Soil Geographic (STATSGO) Data Base for the Conterminous United States.]: U.S. Geological Survey data release, https://doi.org/10.5066/P94JAULO.

This data set consists of general soil association units. It was develped by the National Cooperative Soil Survey and supersedes the State Soil Geographic (STATSGO) data set 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. The data set 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 whole map unit. This data set 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 data set. It is distributed in state/territory and national extents. The soil map units are linked to attributes in the National Soil Information System data base which gives the proportionate extent of the component soils and their properties.

Soil data from the NRCS lower resolution State Soil Geographic (STATSGO) Database.

The SSURGO data are generally not available in uninhabited landscapes with dense vegetation, such as National Forest lands. SSURGO data are available everywhere in the Lower Nooksack Subbasin. Where SSURGO data are not available in WRIA 1, STATSGO soils datasets were merged to parameterize Topnet-WM (see Tarboton, 2007, this same data layer will be used in this Lower Nooksack Water Budget project. The soils data generally pertains to the upper 80 inches of surficial material, with data in WRIA 1 ranging from 0.03 inches to 2 feet. Soils parameterization in the 2012 work is derived using information from the soils database using data extraction and depth averaging of publicly available soils data accessible through the USDA-NRCS Soils Data Mart1 . A search for soils data for Canada was completed during earlier work (Tarboton, 2007), but adequate data available in electronic form was not found at that time

This resource is a subset of the LNWB Ch06 Soil Processes and Inputs Collection Resource.

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.

This data set consists of general soil association units. It wasdevelped by the National Cooperative Soil Survey and supersedes the State Soil Geographic (STATSGO) data set 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. The data set 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 areason the more detailed maps and expanding the data statistically to characterize the whole map unit. This data set consists of georeferenced vector digital data and tabular digital data. The map data were collected in 1-by 2-degreetopographic quadrangle units and merged into a seamless national data set. It is distributed in stateterritory and national extents. The soil map units are linked to attributes in the National Soil Information System data base which gives the proportionate extent ofthe component soils and their properties.

This data set represents estimated soil variables compiled for every catchment of NHDPlus for the conterminous United States. The variables included are cation exchange capacity, percent calcium carbonate, slope, water-table depth, soil thickness, hydrologic soil group, soil erodibility (k-factor), permeability, average water capacity, bulk density, percent organic material, percent clay, percent sand, and percent silt. The source data set is the State Soil ( STATSGO ) Geographic Database (Wolock, 1997). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

This data set consists of general soil association units. It was develped by the National Cooperative Soil Survey and supersedes the State Soil Geographic (STATSGO) data set 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. The data set 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 whole map unit. This data set 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 data set. It is distributed in state/territory and national extents. The soil map units are linked to attributes in the National Soil Information System data base which gives the proportionate extent of the component soils and their properties.

This dataset represents the soil characteristics within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the STATSGO landscape rasters. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. This data set is derived from the STATSGO landscape rasters for the conterminous USA. Individual rasters (Landscape Layers) of depth to bedrock (rckdep), organic material (om), percent clay (clay), percent sand (sand), permeability (perm), soil erodibility (KFFACT/KFACT), and water table depth (wtdep) were used to calculate soil characteristics for each NHDPlusV2 catchment. The soil characteristics were summarized to produce local catchment-level and watershed-level metrics as a continuous data type. The STATSGO data are distributed in two sets, STATSGO_Set1 and STATSGO_Set2, based on common NoData locations in each set of soil GIS layers.

This data set contains vector line map information. The vector data contain selected base categories of geographic features, and characteristics of these features, in digital form. The information was collected by clipping the existing STATSGO soils map to the State of Louisiana boundary. The data set used the existing STATSGO soil maps as a data development resource. The classified data was derived from actual field identification and sampling performed by the United States Department of Agriculture and the Soil Conservation Service. Review the metadata file for more information. Coverage is of the entire State of Louisiana. The original STATSGO map is a digital general soil association map developed by the National Cooperative 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. 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. The 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 give the proportionate extent of the component soils and their properties.

This dataset represents the soil characteristic within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the STATSGO landscape rasters. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. This data set is derived from the STATSGO landscape rasters for the conterminous USA. Individual rasters (Landscape Layers) of depth to bedrock (rckdep), organic material (om), percent clay (clay), percent sand (sand), permeability (perm), soil erodibility (KFFACT/KFACT), and water table depth (wtdep) were used to calculate soil characteristics for each NHDPlusV2 catchment. The soil characteristics were summarized to produce local catchment-level and watershed-level metrics as a continuous data type. The STATSGO data are distributed in two sets, STATSGO_Set1 and STATSGO_Set2, based on common NoData locations in each set of soil GIS layers.

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 mapunit. 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. For use with the GeoStac Database, STATSGO spatial and tabular data files were imported from the source file format to geodatabase feature class format, and converted to a common GeoStac map projection. No changes were made to the geometric or tabular data. Mohawk River Watershed Processing: The original dataset was clipped for use in the Mohawk River Watershed Management Plan. The data was re-projected from Albers to UTM 18N, NAD 83. Attributes of interest were extracted and summarized. STATSGO depicts information about soil features on or near the surface of the Earth. These data are collected as part of the National Cooperative Soil Survey. For use with the GeoStac database, this data set was compiled in order to simplify presticide risk assessment and to provide a common data set upon which to perform analysis for all stakeholders. This data was collected by Stone Environmental, Inc. for the New York State Department of State with funds provided under Title 11 of the Environmental Protection Fund.View Dataset on the Gateway