This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

This file is a digital geospatial Environmental Systems Research Institute (ESRI) ArcGIS File Geodatabase Polygon Feature Class representing land use in the seven northeastern Illinois counties (Cook, DuPage, Kane, Kendall, Lake, McHenry and Will). Land use is identified to 60 categories, and was created using county parcel GIS boundaries and Assessor data, along with color orthorectificed aerial photography captured in April, 2010. Land uses were assigned to parcels using a combination of automated and manual techniques, using a variety of reference data sets for land use identification and validation. Parcels were then dissolved on common land uses (to the limits of PLS sections or assessor blocks); polygons were generated for “non-parcel” (water, right-of-way) areas and classified using automated processes, and extnesive topological cleaning was necessary to minimize gap/overlap issues.In addition to this metadata record, additional information can be found in the following documents:2010 Land Use Inventory Classification Scheme2010 Land Use Inventory Geodatabase Schema2010 Land Use Inventory MetadataLANDUSE lookup .csv table to support shapefile downloadsProcess Narrative: Creating the 2010 Land Use Inventory for Northeastern IllinoisProcess Narrative Addendum: Creating Version 2.0Comparison Guide: Differences between the 2010 and 2005 Land Use InventoriesNOTE: Land use polygons are based on county parcel boundaries; special care must be exercised when comparing these data to earlier (2005, 2001, 1990) Inventories, which relied on manual drafting of land use boundaries that would extend to road centerlines. Additionally, the classification scheme was rewritten to accommodate the parcel approach; see the "comparison guide" link above for inter-inventory analysis guidance.

This data set was designed for statewide evaluation of agrichemical leaching characteristics and associated aquifer sensitivity to contamination. It was created to classify soils and aquifer settings according to predictions of leaching potential. The classifications have not been validated by the results of water quality sampling and accordingly, the reliability of these aquifer sensitivity ratings as predictors of water quality has not been evaluated.

 This is a statewide Arc/Info data set for evaluating the potential
 for contamination of shallow aquifers by nitrate. The sources of
 this data set were published and digitized at 1:250,000; however,
 the soils map and depth to aquifer map (stack-unit map) were
 generated from source data mapped at 1:15,000 and 1:64,000,
 respectively. This aquifer sensitivity map was published at
 1:500,000. Nominal scale is 1:250,000.

 Two statewide data sets were identified as containing
 information that would be useful for producing aquifer
 sensitivity maps: a soil association map (and database)
 and a map of geologic materials to a depth of 50 feet
 (Stack-unit map). The soil association map and database
 were used in an interpretive mapping model that generated
 a map of nitrate leaching classes by examining factors that
 relate to water movement characteristics of the soil.

 The Stack-Unit map was used to create a map of depth to the
 uppermost aquifer, which was then combined with the map of
 nitrate leaching classes. This combined map was interpreted
 based on the sensitivity of aquifers (to create a map of
 aquifer sensitivity) to contamination by nitrate leaching.
 Six aquifer sensitivity classes are indicated: Excessive, High,
 Moderate, Somewhat limited, Limited, and Very limited.

 Disturbed land and surface water areas are also shown.

 These data are to be used in conjunction with ISGS Environmental
 Geology report 148. This data set is one of a suite of six
 related data sets (listed below). Full citation details are
 available in the Cross References section.

 Aquifer Sensitivity to Contamination by Nitrate Leaching in Illinois
 Nitrate Leaching Classes of Illinois Soils (this data set)
 Nitrate Leaching Class Ranges

 Aquifer Sensitivity to Contamination by Pesticide Leaching in Illinois
 Pesticide Leaching Classes of Illinois Soils
 Pesticide Leaching Class Ranges

 This coverage includes county lines. These lines are not directly
 relevant to the data, but are necessary for technical reasons.
 Without the additional county lines, some of the polygons exceed
 the maximum allowable vertex limit in ARCPLOT. This problem is
 solved by the additional county lines, which serve to divide polygons
 with too many vertices into smaller units. Accordingly, to remove
 the county lines from maps created with ARCPLOT, the DROPLINE
 command must be used on conjunction with the COUNTY_NAME
 polygon item.

Download In State Plane Projection Here ** In addition to the Tax Parcel polygons feature class, the hyperlink download above also contains a parcel point data layer ** Parcel boundaries are developed from deeds, plats of subdivision and other legal documents going back to the mid 1800's, following generally accepted practices used in Public Land Survey System states, and following guidelines established by the Illinois Department of Revenue and the International Association of Assessment Officials. Lake County's parcel coverage is based on resolving the accumulated evidence of all of the legal documents surrounding a particular parcel or subdivision, and not the result of a countywide resurvey. These parcel boundaries are intended to be a visual inventory of property for tax and other administrative purposes; they are not intended to be used in place of an on-site survey or for the precise determination of property corners or PLSS features based on GIS coordinates. In Illinois, only a registered professional land surveyor is authorized to determine boundary locations. Included are the tax parcel boundaries, represented as polygons and centroids, for all changes resulting from legal records submitted to the Recorder of Deeds up to December 31st of the preceding year, as well as any court orders, municipal annexations and other transactions which impact the tax parcel boundaries. NOTE: The ONLY attribute included is the Property Index Number, or PARCEL_NUM. Additional assessment attribute data can be downloaded here This parcel layer is used for tax assessment purposes and for a variety of other local government functions. It changes often, both spatially and in its attribution, based on divisions or consolidations, the sale of property and other transactions. Example: PIN 08-17-304-014 can be interpreted as follows: Township 08, Section 17, Block 304, Parcel 014. Note that the first digit of block, "3" in this example, signifies that the parcel lies in quarter section 3. The quarter sections are labeled from 1 through 4, representing the northwest, northeast, southwest and southeast quarter sections, respectively. Update Frequency: This dataset is updated on a weekly basis.

The EnviroAtlas St. Louis, Missouri Meter-Scale Urban Land Cover (MULC) dataset comprises 4188 km2 around the city of St. Louis and surrounding land in parts of eleven counties within Illinois and Missouri. These MULC data and maps were derived from several sources from multiple years: LiDAR (2008-2012); 1-m pixel, four-band (red, green, blue, and near-infrared) leaf-on aerial photography acquired from the United States Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP, 2012, 2014-2016); leaf-off 6-inch pixel four-band imagery (2015) as well as ancillary vector data (e.g., roads, building footprints.). Eight land cover classes were mapped: Water, Impervious Surfaces, Soil/Barren, Tree/Forested, Grass/Herbaceous Non Woody Vegetation, Agriculture, and Wetlands (Woody and Emergent). Wetlands were delineated using the best available existing wetlands data, which was a National Wetlands Inventory (NWI) layer. An analysis of 745 completely random and 226 stratified random photo-interpreted land cover reference points yielded a simple overall user's accuracy (MAX) of 81% and an overall fuzzy user's accuracy (RIGHT) of 90% (see confusion matrices below). This dataset was produced in three phases by the University of Missouri and the East-West Gateway Council of Governments for the Missouri Resource Assessment Partnership (MoRAP) and the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://res1wwwd-o-tepad-o-tgov.vcapture.xyz/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://res1edgd-o-tepad-o-tgov.vcapture.xyz/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://res1wwwd-o-tepad-o-tgov.vcapture.xyz/enviroatlas/enviroatlas-fact-sheets ).

The Chicago, IL EnviroAtlas Meter-scale Urban Land Cover (MULC) dataset comprises 14,687 km2 around the city of Chicago and surrounding counties in Illinois and Indiana. The study area spans 10 counties (7 in Illinois, 3 in Indiana). These MULC data and maps were derived from LiDAR and 1-m pixel, four-band (red, green, blue, and near-infrared) leaf-on aerial photography acquired from the United States Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) as well as ancillary vector data (e.g., roads, building footprints). Seven land cover classes were mapped: Water, Impervious Surfaces, Soil/Barren, Trees/Forest, Grass/Herbaceous Non-Woody Vegetation, Agriculture, and Wetlands (Woody and Emergent). Wetlands were delineated using the best available existing wetlands data, which was a National Wetlands Inventory (NWI) layer. An analysis of 600 completely random and 97 stratified random photo-interpreted land cover reference points yielded a simple overall user's accuracy (MAX) of 81% and an overall fuzzy user's accuracy (RIGHT) of 87% (see confusion matrices below). This dataset was produced by the University of Vermont Spatial Analysis Laboratory, the United States Forest Service Urban Tree Canopy (UTC) assessment program, and the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).