Since 1987, the University of Delaware has prepared GIS-based Water Resource Protection Area (WRPA) mapping for New Castle County that serves to protect the quality and quantity of ground and surface water supplies as part of the Unified Development Code (UDC). The WRPA program is enabled under Section 10 (Environmental Standards) of the UDC for New Castle County. The intent of the ordinances is to protect the quality and quantity of surface water and groundwater supplies through the protection of environmentally sensitive areas important to the state’s water supply. Under the UDC, all development within recharge, wellhead, Cockeysville formation, and reservoir water resource protection areas are required to meet maximum impervious cover thresholds (20–50%) and may require groundwater recharge facilities, water monitoring, and water management facilities. Presently, over 20 percent of New Castle County’s land area is protected by the WRPA provisions of the UDC. UDWRC's 2022 GIS based mapping updates represent the sixth revision to the maps. These maps depict several data layers that represent the four main WRPA categories in New Castle County, Delaware–Cockeysville Formation, Wellhead WRPA, Surface Water WRPA, and Recharge WRPA. The maps serve as a guide for development and assist decision-making in New Castle County, Delaware. The WRPA data will soon be available for download at Delaware FirstMap and PDF versions of the maps are available on the UDWRC website.

The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA).

The 2019 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the ""urban footprint."" There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are as of January 1, 2010.

This Map Service provides both the Downtown Development District boundaries along with point information for the Grants awarded for Projects through the Downtown Development program. It also provides point locations for Building Permits and Development Applications gathered from each county and municipality by the Office of State Planning Coordination.

These maps, a product provided by the Delaware Department of Natural Resources and Environmental Control (DNREC), show the approximate boundaries and classifications of Delaware wetlands as interpreted from leaf-off color infrared aerial photography (1992, 2007, 2017). Statewide wetland maps are used for local and regional site-specific planning and management purposes, and allow for status and trends assessments provide information on the type, amount, location and causes of wetland changes. Wetlands mapping utilizes a standardized wetlands classification scheme which was adapted from the U.S. Fish and Wildlife Service’s National Wetlands Inventory (Cowardin, et al. 1979, and 2016 revision for 2017 data). The 1992 data was created by DNREC under contract with Photoscience, Inc. and Environmental Resource, Inc., and in partnership with the National Wetlands Inventory (NWI). The 2007 and 2017 map data we created by DNREC and completed under contract with Virginia Polytechnic Institute and University, Conservation Management Institute, and in coordination with NWI. Methods used meet or exceed NWI procedures and the guidelines of the Federal Geographic Data Committee's Wetland Mapping Standard (document FGDC-STD-015-2009). The 2017 wetlands are identified at a minimum mapping unit of .25 acres with smaller, highly recognizable polygons (e.g., ponds) mapped down to approximately 0.10 acres. Photo interpreters (PIs) identified the wetland targets at a scale of approximately to 1:10,000 with delineations completed at 1:5,000 and, occasionally, larger as necessary. The 2017 mapping used the NWI 2.0 guidelines which incorporate hydrography spatial data (National Hydrography Dataset – NHD) along with wetlands data.2007 Head of Tide wetlands are those salt and freshwater wetlands that have water influenced by the tides and is derived/extracted from the overall 2007 wetland data.2017 High Marsh and Low marsh are wetland polygons identified as either High or Low marsh for the purposes of beginning to track these two estuarine wetland types in response to climate change.2017 High Water Mark is an attempt to depict the high water line along coastal areas.

The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the Delaware (FIPS 0700) State Plane projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000. Coastal study data as defined in FEMA Gudelines and Specifications, Appendix D: Guidance for Coastal Flooding Analyses and Mapping, submitted as a result of a coastal study. Appendix D notes that a variety of analytical methodologies may be used to establish Base (1-percent-annual-chance) Flood Elevations (BFEs) and floodplains throughout coastal areas of the United States. Appendix D itemizes references for the methodologies currently in use by FEMA for specific coastal flood hazards, provides general guidance for documentation of a coastal flood hazard analysis, specifies flood hazard analysis procedures for the Great Lakes coasts, and outlines intermediate data submissions for coastal flood hazard analyses with new storm surge modeling and revised stillwater flood level (SWFL). (Source: FEMA Guidelines and Specs, Appendix D Guidance for Coastal Flooding Analyses and Mapping, Section D.1)

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Block Groups (BGs) are clusters of blocks within the same census tract. Each census tract contains at least one BG, and BGs are uniquely numbered within census tracts. BGs have a valid code range of 0 through 9. BGs have the same first digit of their 4-digit census block number from the same decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within BG 3 within that census tract. BGs coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas. Block groups generally contain between 600 and 3,000 people. A BG usually covers a contiguous area but never crosses county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. The BG boundaries in this release are those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the Delaware (FIPS 0700) State Plane projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000. Coastal study data as defined in FEMA Gudelines and Specifications, Appendix D: Guidance for Coastal Flooding Analyses and Mapping, submitted as a result of a coastal study. Appendix D notes that a variety of analytical methodologies may be used to establish Base (1-percent-annual-chance) Flood Elevations (BFEs) and floodplains throughout coastal areas of the United States. Appendix D itemizes references for the methodologies currently in use by FEMA for specific coastal flood hazards, provides general guidance for documentation of a coastal flood hazard analysis, specifies flood hazard analysis procedures for the Great Lakes coasts, and outlines intermediate data submissions for coastal flood hazard analyses with new storm surge modeling and revised stillwater flood level (SWFL). (Source: FEMA Guidelines and Specs, Appendix D Guidance for Coastal Flooding Analyses and Mapping, Section D.1)

The 2023 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Block Groups (BGs) are clusters of blocks within the same census tract. Each census tract contains at least one BG, and BGs are uniquely numbered within census tracts. BGs have a valid code range of 0 through 9. BGs have the same first digit of their 4-digit census block number from the same decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within BG 3 within that census tract. BGs coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas. Block groups generally contain between 600 and 3,000 people. A BG usually covers a contiguous area but never crosses county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. The generalized BG boundaries in this release are based on those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

description: The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the Delaware (FIPS 0700) State Plane projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000. Coastal study data as defined in FEMA Gudelines and Specifications, Appendix D: Guidance for Coastal Flooding Analyses and Mapping, submitted as a result of a coastal study. Appendix D notes that a variety of analytical methodologies may be used to establish Base (1-percent-annual-chance) Flood Elevations (BFEs) and floodplains throughout coastal areas of the United States. Appendix D itemizes references for the methodologies currently in use by FEMA for specific coastal flood hazards, provides general guidance for documentation of a coastal flood hazard analysis, specifies flood hazard analysis procedures for the Great Lakes coasts, and outlines intermediate data submissions for coastal flood hazard analyses with new storm surge modeling and revised stillwater flood level (SWFL). (Source: FEMA Guidelines and Specs, Appendix D Guidance for Coastal Flooding Analyses and Mapping, Section D.1); abstract: The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the Delaware (FIPS 0700) State Plane projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000. Coastal study data as defined in FEMA Gudelines and Specifications, Appendix D: Guidance for Coastal Flooding Analyses and Mapping, submitted as a result of a coastal study. Appendix D notes that a variety of analytical methodologies may be used to establish Base (1-percent-annual-chance) Flood Elevations (BFEs) and floodplains throughout coastal areas of the United States. Appendix D itemizes references for the methodologies currently in use by FEMA for specific coastal flood hazards, provides general guidance for documentation of a coastal flood hazard analysis, specifies flood hazard analysis procedures for the Great Lakes coasts, and outlines intermediate data submissions for coastal flood hazard analyses with new storm surge modeling and revised stillwater flood level (SWFL). (Source: FEMA Guidelines and Specs, Appendix D Guidance for Coastal Flooding Analyses and Mapping, Section D.1)

description: These data are a set of ARC/INFO coverages composed of polygonal and linear features. Coverages are based on official New York State Freshwater Wetlands Maps as described in Article 24-0301 of the Environmental Conservation Law. Coverages are not, however, a legal substitute for the official maps. Coverages are available on a county basis for all areas of New York State outside the Adirondack Park.; abstract: These data are a set of ARC/INFO coverages composed of polygonal and linear features. Coverages are based on official New York State Freshwater Wetlands Maps as described in Article 24-0301 of the Environmental Conservation Law. Coverages are not, however, a legal substitute for the official maps. Coverages are available on a county basis for all areas of New York State outside the Adirondack Park.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The purpose of this file is to provide the geography for the 2010 Census Blocks along with their 2010 housing unit count and population. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.

Locations of Delaware Public Schools. Maintained by the Delaware Department of Education.The school district boundaries are intended to reflect current legal boundaries for Public School and VoTech Districts in Delaware

This data, indicating the supply class for Mohawk River Watershed tax parcels, 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.These data represent tax parcel boundaries. Data are meant for watershed planning purposes only. Mohawk River Watershed Coalition of Conservation Districts does not take responsibility for the overall content and/or spatial accuracy of the tax parcel data available for download on this page.You should always verify actual map data and information. The limitations and accuracy level of the data should be accounted for before using them in any analyses and their validity cannot be guaranteed.Parcel boundary data was acquired by county offices. Individual County and Town files were compiled to create a seamless coverage of Tax Parcels. Areas of overlap were eliminated by clipping to adjacent county boundaries. Attribute information of interest, property class code, residential development from 1945 to present (year built), sewer service code, and water service codes were obtained from the New York Office of Real Property Services (ORPS, accessed in November 2011). Parcel boundaries and attribute information from ORPS were joined based on the municipality code and print key.Source Information:Albany: Albany County Real Property Tax Services. 2010 Albany County, NY parcel boundaries derived from AutoCAD MAP 3D tax maps; Delaware: Delaware County Planning Department. The license agreement between Delaware County and the Mohawk River Watershed prohibit the viewing of this data through a web mapping application; Fulton: Fulton County. The license agreement between Fulton County and the Mohawk River Watershed prohibit the viewing of this data through a web mapping application;Greene: Greene County; Hamilton: Hamilton County Real Property Tax Services; Herkimer: Herkimer Oneida Counties Comprehensive Planning Program, 2011; Public water and sewer were manually assigned to all City of Utica parcels. Public water and sewer were assigned to parcels within 500 feet of water and sewer lines for the City of Rome parcels.Lewis: Lewis County; The license agreement between Lewis County and the Mohawk River Watershed prohibit the viewing of this data through a web mapping application;Madison: Madison County;Montgomery: Montgomery County;Oneida: Herkimer Oneida Counties Comprehensive Planning Program, 2011;Otsego: Otsego County;Saratoga: Saratoga County, 2011;Schenectady: Schenectady County; Schoharie: Schoharie CountyView Dataset on the Gateway

This map shows Congressional District boundaries for the United States. The map is set to middle Georgia.

Congressional districts are the 435 areas from which members are elected to the U.S. House of Representatives. After the apportionment of congressional seats among the states, which is based on decennial census population counts, each state with multiple seats is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. The boundaries and numbers shown for the congressional districts are those specified in the state laws or court orders establishing the districts within each state.

Congressional districts for the 108th through 112th sessions were established by the states based on the result of the 2000 Census. Congressional districts for the 113th through 115th sessions were established by the states based on the result of the 2010 Census. Boundaries are effective until January of odd number years (for example, January 2015, January 2017, etc.), unless a state initiative or court ordered redistricting requires a change. All states established new congressional districts in 2011-2012, with the exception of the seven single member states (Alaska, Delaware, Montana, North Dakota, South Dakota, Vermont, and Wyoming).

For the states that have more than one representative, the Census Bureau requested a copy of the state laws or applicable court order(s) for each state from each secretary of state and each 2010 Redistricting Data Program state liaison requesting a copy of the state laws and/or applicable court order(s) for each state. Additionally, the states were asked to furnish their newly established congressional district boundaries and numbers by means of geographic equivalency files. States submitted equivalency files since most redistricting was based on whole census blocks. Kentucky was the only state where congressional district boundaries split some of the 2010 Census tabulation blocks. For further information on these blocks, please see the user-note at the bottom of the tables for this state.

The Census Bureau entered this information into its geographic database and produced tabulation block equivalency files that depicted the newly defined congressional district boundaries. Each state liaison was furnished with their file and requested to review, submit corrections, and certify the accuracy of the boundaries.

The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=2309

U.S. Census Bureau QuickFacts statistics for Pike Creek CDP, Delaware. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

The ScoutMuncie Property Survey was a volunteer-based community survey conducted between 2015-2017 by the Muncie Historic Preservation & Rehabilitation Commission in supported through generous funding by The Ball Brothers Foundation and in partnership with Delaware County Historical Society, Delaware County GIS Department, Ball State University, BSU Building Better Neighborhoods, BSU Department of Urban Planning (302 Neighborhood Studio), BSU Department of Landscape Architecture, BSU Graduate Program in Historic Preservation, Place Economics and the CO:LAB. More information on the survey can be found at https://scoutmuncie.wordpress.com Results of the Survey can be viewed in a summary booklet

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

The Philadelphia, PA Meter-Scale Urban Land Cover (MULC) dataset comprises 7184 km2 around the city of Philadelphia and surrounding land in parts of fourteen counties within four states (PA, DE, NJ, MD): New Castle County in Delaware and Cecil County Maryland; Bucks, Chester, Lancaster, Montgomery, Philadelphia, and Delaware Counties in Pennsylvania; and Burlington, Mercer, Camden, Gloucester, Salmen and Atlantic Counties in New Jersey. These MULC data and maps were derived from several sources from multiple years: leaf-off LiDAR; 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); 1-ft pixel orthoimagery; additional leaf-on and leaf-off imagery as well as ancillary vector data (e.g., roads, building footprints.). Ten land cover classes were mapped: Water, Impervious Surfaces, Soil/Barren, Tree/Forested, Shrub, Grass/Herbaceous NonWoody Vegetation, Agriculture, Orchard, 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 251 stratified random photo-interpreted land cover reference points yielded a simple overall user's accuracy (MAX) of 78% and an overall fuzzy user's accuracy (RIGHT) of 86% (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 the 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).