Boundaries of the 67 Pennsylvania Counties. For more information on this layer, you can use the Data Dictionary available in both web and spreadsheet format.Data layer was updated on 01/01/2024.

Delaware County Office of Data and Mapping Innovation (ODMI), using a Geographic Information System, supports departments within the County with custom mapping, interactive applications, and authoritative data to be used in their workflows and engagement with the public. The office always supports and works with local governments, private companies, and the public. The open data site provides information in the form of interactive applications as well as a data inventory to download specific datasets for mapping purposes.

For more information or questions contact - Email: data_mapping@co.delaware.pa.us

The Pennsylvania Flood Risk Tool is an interactive web map application developed by Penn State University with funding from the Federal Emergency Management Agency (FEMA). This application depicts 1% annual chance floodplain boundaries in an online map environment. https://pafloodrisk.psu.edu/home/index.html

This is an interactive webmap of the Sanborn Fire Insurance maps of Pittsburgh and Allegheny County, PA. Not all maps are in copyright and posted. This project entailed georeferencing the index or key maps, and individual sheets if no index was available. Georeferenced maps were mosaicked and polygons were created with the extent of the index maps. Links to Penn State's online holdings were added if maps were out of copyright.

Vector polygon map data of property parcels from Montgomery County, Pennsylvania containing 307,283 features.

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Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

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Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

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Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

This map shows where obesity and diabetes are happening in the US, by county. It shows each component of the map as its own layer, and also shows the patterns overlapping. Diabetes prevalence (% of adults)Obesity prevalence (% of adults)This data can be used to assess the health factors, and answer questions such as:Are certain counties more/less at risk in regards to diabetes and obesity?Are diabetes, obesity, and physical inactivity happening within the same areas of the US?According to the CDC: "These data can help the public to better use existing resources for diabetes management and prevention efforts." The data comes from the Behavioral Risk Factor Surveillance System (BRFSS) through the Centers for Disease Control and Prevention (CDC), and the data vintage is 2013. To explore other county indicators, different vintages, or the original data, click here. To view the interactive map through the CDC website, click here. To learn more about the methodology of how county-level estimates are calculated, see this PDF.

This EnviroAtlas dataset demonstrates the effect of changes in pollution concentration on local populations in 3974 block groups in Philadelphia, PA. The US EPA's Environmental Benefits Mapping and Analysis Program (BenMAP) was used to estimate the incidence of adverse health effects (i.e., mortality and morbidity) and associated monetary value that result from changes in pollution concentrations for Philadelphia City and County, PA, New Castle County, DE, Cecil County, MD, Camden County, NJ, Atlantic County, NJ, Gloucester County, NJ, Burlington County, NJ, Delaware County, PA, Bucks County, PA, Chester County, PA, and Montgomery County, PA. Incidence and value estimates for the block groups are calculated using i-Tree models (www.itreetools.org), local weather data, pollution data, and U.S. Census derived population data. This dataset was produced by the USDA Forest Service with support from The Davey Tree Expert Company 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).

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).

These contour lines were derived and delivered for Pennsylvania from the PAMAP Quality Level 3 (QL3) LIDAR data collection between 2006 and 2008. Some post-processing has been done to the original deliverables, including merging, line smoothing, and eliminating duplicate (overlapping) data between collections. This dataset renders the contour lines with the following scale-dependent visibility: 100 foot increments between 1:200,000 and 1:100,000 | 50 foot increments between 1:100,000 and 1:30,000 | 20 foot increments between 1:30,000 and 1:5,000 | 10 foot increments between 1:5,000 and 1:1,000 | and 2 foot increments between 1:1,000 and 1:10. The lines have been smoothed using the ArcGIS Pro 3.3 Smooth Line geoprocessing tool via the Polynomial Approximation with Exponential Kernal (PAEK) and setting a 10 ft smoothing tolerance distance. The extent of this data extends slightly beyond the Pennsylvania boundary into all surrounding states to ensure complete coverage of Pennsylvania. Duplicate (overlapping) contour data between collection years and north/south state plane zones has been eliminated by splitting the data from adjacent collects at county boundaries to ensure a seamless product with no duplication or overlapping data. The contour line geometries along the county boundaries that separate different years of PAMAP data collection (2006, 2007, and 2008) do not always connect properly.

These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the NOAA Lake Level Viewer. It depicts potential lake level rise and fall and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at lake level change, coastal flooding impacts, and exposed lakeshore. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The NOAA Lake Level Viewer may be accessed at: https://coast.noaa.gov/llv. This metadata record describes the Lake Erie digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Lake Level Viewer described above. This DEM includes the best available lidar and US Army Corps of Engineer dredge survey data known to exist at the time of DEM creation that met project specifications. This DEM includes data for Monroe and Wayne Counties in Michigan; Chautauqua and Erie Counties in New York; Ashtabula, Cuyahoga, Erie, Lake, Lorain, Lucas, Ottawa, Sandusky, and Wood Counties in Ohio; and Erie County in Pennsylvania. The DEM was produced from the following lidar data sets: 1. 2011 - 2012 USACE NCMP Topobathy Lidar: Lake Erie (MI, NY, OH, PA) 2. 2011 USACE NCMP Topobathy Lidar: MI/NY Great Lakes 3. 2008 FEMA Lidar: Erie County, NY 4. 2007 USACE NCMP Topobathy Lidar: Lake Erie (Erie County, PA) and Lake Michigan (Manitou Islands) (MI, PA) 5. 2007 USACE NCMP Topobathy Lidar: Lake Erie (NY Shoreline) 6. 2006 USACE NCMP Topobathy Lidar: Lake Erie (OH, PA), Lake Huron (MI) and Lake Michigan (Porter County, IN) 7. 2007 Pennsylvania Department of Conservation and Natural Resources (PA DCNR) Statewide Lidar 8. 2006 Ohio Statewide Imagery Program (OSIP) Lidar: North The DEM was produced from the following sonar data sets: 9. 2015 USACE Detroit District; Detroit River, MI; Livingstone Channel Reach 10. 2015 USACE Buffalo District, Ashtabula Harbor, OH 11. 2015 USACE Buffalo District, Erie Harbor, PA 12. 2015 USACE Buffalo District, Fairport Harbor, OH 13. 2015 USACE Buffalo District, Rocky River, OH 14. 2013 USACE Buffalo District; Buffalo Harbor, NY; Buffalo River and Ship Canal 15. 2014 USACE Detroit District, Point Mouillee, MI 16. 2014 USACE Buffalo District, Conneaut Harbor, OH 17. 2014 USACE Buffalo District, Dunkirk Harbor, NY 18. 2014 USACE Buffalo District, Niagara River, NY 19. 2014 USACE Buffalo District, Sandusky Harbor, OH The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 3 meters.

This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter strip beginning at the estimated road edge. Percent tree cover is calculated for each block between road intersections. In this community, tree cover is defined as Trees & Forest, Orchards, and Woody Wetlands. Tree cover provides valuable benefits to neighborhood residents and walkers by providing shade, improved aesthetics, and outdoor gathering spaces. This dataset was produced by 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).

This layer is a component of JuniataCounty.

This dataset contains the lithologic class and topographic position index information and quality-assurance and quality-control data not available in the online National Water Information System for 54 domestic wells sampled by the U.S. Geological Survey in Clinton County, Pennsylvania, May-September 2017. The topographic position index (TPI) for each well _location was computed on the basis of a 25-meter digital elevation model (U.S. Geological Survey, 2009) using criteria reported by Llewellyn (2014) to indicate potential classes for topographic setting. The bedrock geologic unit and primary lithology were determined for each well _location on the basis of the digital bedrock geologic map of Pennsylvania (Miles and Whitfield, 2001). The quality-assurance and quality-control data (such as blanks or replicates) were collected at a subset of sites to ensure that the data met specific data-quality objectives outlined for the study.

This dataset contains the lithologic class and topographic position index information and quality-assurance and quality-control data not available in the online National Water Information System for 47 domestic wells sampled by the U.S. Geological Survey in Potter County, Pennsylvania, April-September 2017. The topographic position index (TPI) for each well _location was computed on the basis of a 25-meter digital elevation model (U.S. Geological Survey, 2009) using criteria reported by Llewellyn (2014) to indicate potential classes for topographic setting. The bedrock geologic unit and primary lithology were determined for each well _location on the basis of the digital bedrock geologic map of Pennsylvania (Miles and Whitfield, 2001). The quality-assurance and quality-control data (such as blanks or replicates) were collected at a subset of sites to ensure that the data met specific data-quality objectives outlined for the study.

These contour lines were derived and delivered for Pennsylvania from the PAMAP Quality Level 3 (QL3) LIDAR data collection between 2006 and 2008. Some post-processing has been done to the original deliverables, including merging, line smoothing, and eliminating duplicate (overlapping) data between collections. This dataset renders the contour lines with the following scale-dependent visibility: 100 foot increments between 1:200,000 and 1:100,000 | 50 foot increments between 1:100,000 and 1:30,000 | 20 foot increments between 1:30,000 and 1:5,000 | 10 foot increments between 1:5,000 and 1:1,000 | and 2 foot increments between 1:1,000 and 1:10. The lines have been smoothed using the ArcGIS Pro 3.3 Smooth Line geoprocessing tool via the Polynomial Approximation with Exponential Kernal (PAEK) and setting a 10 ft smoothing tolerance distance. The extent of this data extends slightly beyond the Pennsylvania boundary into all surrounding states to ensure complete coverage of Pennsylvania. Duplicate (overlapping) contour data between collection years and north/south state plane zones has been eliminated by splitting the data from adjacent collects at county boundaries to ensure a seamless product with no duplication or overlapping data. The contour line geometries along the county boundaries that separate different years of PAMAP data collection (2006, 2007, and 2008) do not always connect properly.

School Districts in York County. Intended for illustration and demonstration purposes only.

The Dauphin County, PA 2016 QL2 LiDAR project called for the planning, acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet; NAVD1988 (Geoid 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 711 individual 5,000-foot x 5,000-foot tiles. Tile names use the following naming schema: "YYYYXXXXPAd" where YYYY is the first 3 characters of the tile's upper left corner Y-coordinate, XXXX - the first 4 characters of the tile's upper left corner X-coordinate, PA = Pennsylvania, and d = 'N' for North or 'S' for South. Corresponding 2.5-foot gridded hydro-flattened bare earth raster tiled DEM files and intensity image files were created using the same 5,000-foot x 5,000-foot schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. Continuous 2-foot contours were produced in Esri file geodatabase format. Ground Conditions: LiDAR collection began in Spring 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 84 control points (24 calibration control points and 60 QC checkpoints). These were used to calibrate the LIDAR to known ground locations established throughout the project area.

TheFlorida Department of Revenue’s Property Tax Oversight(PTO) program collects parcel level Geographic Information System (GIS) data files every April from all of Florida’s 67 county property appraisers’ offices. This GIS data was exported from these file submissions between March 15 to April 1, 2023. The GIS parcel polygon features have been joined with thereal property roll (Name – Address – Legal, or NAL)file. No line work was adjusted between county boundaries.The polygon data set represents the information property appraisers gathered from the legal description on deeds, lot layout of recorded plats, declaration of condominium documents, recorded and unrecorded surveys.Individual parcel data is updated continually by each county property appraiser as needed. The GIS linework and related attributions for the statewide parcel map are updated annually by the Department every August. The dataset extends countywide and is attribute by Federal Information Processing Standards (FIPS) code.DOR reference with FIPS county codes and attribution definitions - https://fgio.maps.arcgis.com/home/item.html?id=ff7b985e139c4c7ba844500053e8e185If you discover the inadvertent release of a confidential record exempt from disclosure pursuant to Chapter 119, Florida Statutes, public records laws, immediately notify the Department of Revenue at 850-717-6570 and your local Florida Property Appraisers’ Office.Please contact the county property appraiser with any parcel specific questions: Florida Property Appraisers’ Offices:Alachua County Property Appraiser – https://www.acpafl.org/Baker County Property Appraiser – https://www.bakerpa.com/Bay County Property Appraiser – https://baypa.net/Bradford County Property Appraiser – https://www.bradfordappraiser.com/Brevard County Property Appraiser – https://www.bcpao.us/Broward County Property Appraiser – https://bcpa.net/Calhoun County Property Appraiser – https://calhounpa.net/Charlotte County Property Appraiser – https://www.ccappraiser.com/Citrus County Property Appraiser – https://www.citruspa.org/Clay County Property Appraiser – https://ccpao.com/Collier County Property Appraiser – https://www.collierappraiser.com/Columbia County Property Appraiser – https://columbia.floridapa.com/DeSoto County Property Appraiser – https://www.desotopa.com/Dixie County Property Appraiser – https://www.qpublic.net/fl/dixie/Duval County Property Appraiser – https://www.coj.net/departments/property-appraiser.aspxEscambia County Property Appraiser – https://www.escpa.org/Flagler County Property Appraiser – https://flaglerpa.com/Franklin County Property Appraiser – https://franklincountypa.net/Gadsden County Property Appraiser – https://gadsdenpa.com/Gilchrist County Property Appraiser – https://www.qpublic.net/fl/gilchrist/Glades County Property Appraiser – https://qpublic.net/fl/glades/Gulf County Property Appraiser – https://gulfpa.com/Hamilton County Property Appraiser – https://hamiltonpa.com/Hardee County Property Appraiser – https://hardeepa.com/Hendry County Property Appraiser – https://hendryprop.com/Hernando County Property Appraiser – https://www.hernandopa-fl.us/PAWEBSITE/Default.aspxHighlands County Property Appraiser – https://www.hcpao.org/Hillsborough County Property Appraiser – https://www.hcpafl.org/Holmes County Property Appraiser – https://www.qpublic.net/fl/holmes/Indian River County Property Appraiser – https://www.ircpa.org/Jackson County Property Appraiser – https://www.qpublic.net/fl/jackson/Jefferson County Property Appraiser – https://jeffersonpa.net/Lafayette County Property Appraiser – https://www.lafayettepa.com/Lake County Property Appraiser – https://www.lakecopropappr.com/Lee County Property Appraiser – https://www.leepa.org/Leon County Property Appraiser – https://www.leonpa.gov/Levy County Property Appraiser – https://www.qpublic.net/fl/levy/Liberty County Property Appraiser – https://libertypa.org/Madison County Property Appraiser – https://madisonpa.com/Manatee County Property Appraiser – https://www.manateepao.gov/Marion County Property Appraiser – https://www.pa.marion.fl.us/Martin County Property Appraiser – https://www.pa.martin.fl.us/Miami-Dade County Property Appraiser – https://www.miamidade.gov/pa/Monroe County Property Appraiser – https://mcpafl.org/Nassau County Property Appraiser – https://www.nassauflpa.com/Okaloosa County Property Appraiser – https://okaloosapa.com/Okeechobee County Property Appraiser – https://www.okeechobeepa.com/Orange County Property Appraiser – https://ocpaweb.ocpafl.org/Osceola County Property Appraiser – https://www.property-appraiser.org/Palm Beach County Property Appraiser – https://www.pbcgov.org/papa/index.htmPasco County Property Appraiser – https://pascopa.com/Pinellas County Property Appraiser – https://www.pcpao.org/Polk County Property Appraiser – https://www.polkpa.org/Putnam County Property Appraiser – https://pa.putnam-fl.com/Santa Rosa County Property Appraiser – https://srcpa.gov/Sarasota County Property Appraiser – https://www.sc-pa.com/Seminole County Property Appraiser – https://www.scpafl.org/St. Johns County Property Appraiser – https://www.sjcpa.gov/St. Lucie County Property Appraiser – https://www.paslc.gov/Sumter County Property Appraiser – https://www.sumterpa.com/Suwannee County Property Appraiser – https://suwannee.floridapa.com/Taylor County Property Appraiser – https://qpublic.net/fl/taylor/Union County Property Appraiser – https://union.floridapa.com/Volusia County Property Appraiser – https://vcpa.vcgov.org/Wakulla County Property Appraiser – https://mywakullapa.com/Walton County Property Appraiser – https://waltonpa.com/Washington County Property Appraiser – https://www.qpublic.net/fl/washington/Florida Department of Revenue Property Tax Oversight https://floridarevenue.com/property/Pages/Home.aspx

The National Pipeline Mapping System (NPMS) Public Viewer enables the user to view NPMS pipeline, liquefied natural gas (LNG) plant and breakout tank data one county at a time, including attributes and pipeline operator contact information. The user can also view gas transmission and hazardous liquid pipeline accidents and incidents going back to 2002 for the entire US. NPMS pipeline data consists of gas transmission pipelines and hazardous liquid pipelines jurisdictional to the Pipeline and Hazardous Materials Safety Administration (PHMSA). It does not contain gas gathering or distribution pipelines, such as lines which deliver gas to a customer 's home. Therefore, not all pipelines in an area will be visible in the Public Viewer. As well, the breakout tank data is not complete as submission of that data is not a requirement. All NPMS data is for reference purposes only. It should never be used as a substitute for contacting a one-call center prior to excavation activities. Please call 811 before any digging occurs.