Tax District Boundaries: Official tax district boundary lines adopted by the WV Legislature in 1978 as a general reference to delineate rural tax district boundaries. The boundaries were drawn from 1:24,000-scale USGS topographic maps in 1978 and coincide with county magisterial districts as of July 1, 1973. Unlike magisterial districts that are realigned every ten years following the census, the tax district boundary does not follow equal representation requirements. In 1978 the West Virginia Geologic and Economical Survey published six 1:500,000-scale maps delineating official county and tax district boundary lines for the State. In 1996 the West Virginia Department of Tax and Revenue, Property Tax Division, converted the 1978 source maps into a digital format and added descriptive attributes for each tax district. In October of 2003, the WV GIS Technical Center appended 24K DLG boundary files and lines drawn from 24K DRGs into a statewide 24K Tax District Boundary dataset. In 2017, WVGISTC has appended this file with parcel data or Census Populated Places boundaries for missing tax districts.

Digitized from USGS 1:24,000-scale Digital Raster Graphics (scanned topographic maps) by the West Virginia Department of Environmental Protection. First published January 2002, updated with Census 2000 attribute data and re-published March 2005. Scale: 1:24000. Attribute Information includes Federal Information Processing Standards (FIPS) codes and 2000 Census data.Coordinate System: NAD_1983_UTM_Zone_17N

The 2022 cartographic boundary shapefiles 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 cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2022, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

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. The cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2023, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated or updated as part of the the 2023 BAS or the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

Will vary by map. In each map, each pixel will have a value representing the index of interest. For example, the ForDen_66ha dataset is a grid map for West Virginia at 30 meter resolution. Each pixel value represents an index of forest area density for the surrounding 65.61 ha.(27x27 pixel) analysis window.

The 2020 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.

The mapped area boundary, flood inundation extents, and depth rasters were created to provide an estimated extent of flood inundation along the Greenbrier River within the community of Alderson, West Virginia. These geospatial data include the following items: 1. greenbrier_ald_bnd; shapefile containing the polygon showing the mapped area boundary for the Greenbrier River flood maps, 2. greenbrier_ald_hwm; shapefile containing high-water mark points, 3. polygon_greenbrier_ald_hwm; shapefile containing mapped extent of flood inundation, derived from the water-surface elevation surveyed at high-water marks, 4. depth_hwm; raster file for the flood depths derived from the water-surface elevation surveyed at high-water marks, 5. polygon_greenbrier_ald_dem; shapefile containing mapped extent of flood inundation, derived from the height above ground recorded at high-water marks and the digital elevation model (DEM) raster, 6. depth_dem; raster file for the flood depths derived from the height above ground recorded at high-water marks and the digital elevation model raster. The upstream and downstream mapped area extent is limited to the upstream-most and downstream-most high-water mark locations. In areas of uncertainty of flood extent, the mapped area boundary is lined up with the flood inundation polygon extent. The mapped area boundary polygon was used to extract the final flood inundation polygon and depth raster from the water-surface elevation raster file. Depth raster files were created using the "Topo to Raster" tool in ArcMap (ESRI, 2012). For this study two sets of inundation layers were generated for each reach. One raster file showing flood depths, "depth_hwm", was created by using high-water mark water-surface elevation values on the land surface and a digital elevation model. However, differences in elevation between the surveyed water-surface elevation values at HWM’s and the land-surface elevation from the digital elevation model data provided uncertainty in the inundation extent of the generated layers. Often times elevation differences of +/- 20 feet were noticed between the surveyed elevation from a HWM on the land surface and the digital elevation model land-surface elevation. Due to these elevation differences, we incorporated a second method of interpolating the water-surface layer. The recorded height above ground value from the surveyed HWM was added to the digital elevation model land-surface elevation at that point. This created a new water-surface elevation value to be used with the “Topo to Raster” interpolation method to create a second depth raster, "depth_dem". Both sets of inundation layers are provided.

This TNC Lands spatial dataset represents the lands and waters in which The Nature Conservancy (TNC) currently has, or historically had, an interest, legal or otherwise in West Virginia. The system of record for TNC Lands is the Legal Records Management (LRM) system, which is TNC’s database for all TNC land transactions.TNC properties should not be considered open to the public unless specifically designated as being so. TNC may change the access status at any time at its sole discretion. It's recommended to visit preserve-specific websites or contact the organization operating the preserve before any planned visit for the latest conditions, notices, and closures. TNC prohibits redistribution or display of the data in maps or online in any way that misleadingly implies such lands are universally open to the public.The types of current land interests represented in the TNC Lands data include: Fields and Attributes included in the public dataset:Field NameField DefinitionAttributesAttribute Definitions Public NameThe name of the tract that The Nature Conservancy (TNC) Business Unit (BU) uses for public audiences.Public name of tract if applicableN/A TNC Primary InterestThe primary interest held by The Nature Conservancy (TNC) on the tractFee OwnershipProperties where TNC currently holds fee-title or exclusive rights and control over real estate. Fee Ownership can include TNC Nature Preserves, managed areas, and properties that are held for future transfer. Conservation EasementProperties on which TNC holds a conservation easement, which is a legally binding agreement restricting the use of real property for conservation purposes (e.g., no development). The easement may additionally provide the holder (TNC) with affirmative rights, such as the rights to monitor species or to manage the land. It may run forever or for an expressed term of years. Deed RestrictionProperties where TNC holds a deed restriction, which is a provision placed in a deed restricting or limiting the use of the property in some manner (e.g., if a property goes up for sale, TNC gets the first option). TransferProperties where TNC historically had a legal interest (fee or easement), then subsequently transferred the interest to a conservation partner. AssistProperties where TNC assisted another agency/entity in protecting. Management Lease or AgreementAn agreement between two parties whereby one party allows the other to use their property for a certain period of time in exchange for a periodic fee. Grazing Lease or PermitA grazing lease or permit held by The Nature Conservancy Right of WayAn access easement or agreement held by The Nature Conservancy. OtherAnother real estate interest or legal agreement held by The Nature Conservancy Fee OwnerThe name of the organization serving as fee owner of the tract, or "Private Land Owner" if the owner is a private party. If The Nature Conservancy (TNC) primary interest is a "Transfer" or "Assist", then this is the fee owner at the time of the transaction.Fee Owner NameN/A Fee Org TypeThe type of organization(s) that hold(s) fee ownership. Chosen from a list of accepted values.Organization Types for Fee OwnershipFED:Federal, TRIB:American Indian Lands, STAT:State,DIST:Regional Agency Special District, LOC:Local Government, NGO:Non-Governmental Organization, PVT:Private, JNT:Joint, UNK:Unknown, TERR:Territorial, DESG:Designation Other Interest HolderThe name of the organization(s) that hold(s) a different interest in the tract, besides fee ownership or TNC Primary Interest. This may include TNC if the Other Interest is held or co-held by TNC. Multiple interest holders should be separated by a semicolon (;).Other Interest Holder NameN/A Other Interest Org TypeThe type of organization(s) that hold(s) a different interest in the tract, besides fee ownership. This may include TNC if the Other Interest is held or co-held by TNC. Chosen from a list of accepted values.Organization Types for interest holders:FED:Federal, TRIB:American Indian Lands, STAT:State,DIST:Regional Agency Special District, LOC:Local Government, NGO:Non-Governmental Organization, PVT:Private, JNT:Joint, UNK:Unknown, TERR:Territorial, DESG:Designation Other Interest TypeThe other interest type held on the tract. Chosen from a list of accepted values.​Access Right of Way; Conservation Easement; Co-held Conservation Easement; Deed Restriction; Co-held Deed Restriction; Fee Ownership; Co-held Fee Ownership; Grazing Lease or Permit; Life Estate; Management Lease or Agreement; Timber Lease or Agreement; OtherN/A Preserve NameThe name of The Nature Conservancy (TNC) preserve that the tract is a part of, this may be the same name as the as the "Public Name" for the tract.Preserve Name if applicableN/APublic AccessThe level of public access allowed on the tract.Open AccessAccess is encouraged on the tract, trails are maintained, signage is abundant, and parking is available. The tract may include regular hours of availability.Open with Limited AccessThere are no special requirements for public access to the tract, the tract may include regular hours of availability with limited amenities.Restricted AccessThe tract requires a special permit from the owner for access, a registration permit on public land, or has highly variable times or conditions to use.Closed AccessNo public access is allowed on the tract.UnknownAccess information for the tract is not currently available.Gap CategoryThe Gap Analysis Project (GAP) code for the tract. Gap Analysis is the science of determining how well we are protecting common plants and animals. Developing the data and tools to support that science is the mission of the Gap Analysis Project (GAP) at the US Geological Survey. See their website for more information, linked in the field name.1 - Permanent Protection for BiodiversityPermanent Protection for Biodiversity2 - Permanent Protection to Maintain a Primarily Natural StatePermanent Protection to Maintain a Primarily Natural State3 - Permanently Secured for Multiple Uses and in natural coverPermanently Secured for Multiple Uses and in natural cover39 - Permanently Secured and in agriculture or maintained grass coverPermanently Secured and in agriculture or maintained grass cover4 - UnsecuredUnsecured (temporary easements lands and/or municipal lands that are already developed (schools, golf course, soccer fields, ball fields)9 - UnknownUnknownProtected AcresThe planar area of the tract polygon in acres, calculated by the TNC Lands geographic information system (GIS).Total geodesic area of polygon in acresProjection: WGS 1984 Web Mercator Auxiliary SphereOriginal Protection DateThe original protection date for the tract, from the Land Resource Management (LRM) system record.Original protection dateN/AStateThe state within the United States of America or the Canadian province where the tract is located.Chosen from a list of state names.N/ACountryThe name of the country where the tract is located.Chosen from a list of countries.N/ADivisionThe name of the TNC North America Region Division where the tract is located. Chosen from a list of TNC North America DivisionsN/A

The mapped area boundary, flood inundation extents, and depth rasters were created to provide an estimated extent of flood inundation along the Meadow River and Sewell Creek within the community of Rainelle, West Virginia. These geospatial data include the following items: 1. meadow_sewell_bnd; shapefile containing the polygon showing the mapped area boundary for the Meadow River and Sewell Creek flood maps, 2. meadow_sewell_hwm; shapefile containing high-water mark points, 3. polygon_meadow_sewell_hwm; shapefile containing mapped extent of flood inundation, derived from the water-surface elevation surveyed at high-water marks, 4. depth_hwm; raster file for the flood depths derived from the water-surface elevation surveyed at high-water marks, 5. polygon_meadow_sewell_dem; shapefile containing mapped extent of flood inundation, derived from the height above ground recorded at high-water marks and the digital elevation model (DEM) raster, 6. depth_dem; raster file for the flood depths derived from the height above ground recorded at high-water marks and the digital elevation model raster. The upstream and downstream mapped area extent is limited to the upstream-most and downstream-most high-water mark locations. In areas of uncertainty of flood extent, the mapped area boundary is lined up with the flood inundation polygon extent. The mapped area boundary polygon was used to extract the final flood inundation polygon and depth raster from the water-surface elevation raster file. Depth raster files were created using the "Topo to Raster" tool in ArcMap (ESRI, 2012). For this study two sets of inundation layers were generated for each reach. One raster file showing flood depths, "depth_hwm", was created by using high-water mark water-surface elevation values on the land surface and a digital elevation model. However, differences in elevation between the surveyed water-surface elevation values at HWM’s and the land-surface elevation from the digital elevation model data provided uncertainty in the inundation extent of the generated layers. Often times elevation differences of +/- 20 feet were noticed between the surveyed elevation from a HWM on the land surface and the digital elevation model land-surface elevation. Due to these elevation differences, we incorporated a second method of interpolating the water-surface layer. The recorded height above ground value from the surveyed HWM was added to the digital elevation model land-surface elevation at that point. This created a new water-surface elevation value to be used with the “Topo to Raster” interpolation method to create a second depth raster, "depth_dem". Both sets of inundation layers are provided.

Digitized from USGS 1:24,000-scale Digital Raster Graphics (scanned topographic maps) by the West Virginia Department of Environmental Protection. WVGISTC dissolved county boundaries to create the state boundary. Published May 2002.Coordinate System: Lat/Long NAD 1983,UTM NAD 1983

The mapped area boundary, flood inundation extents, and depth rasters were created to provide an estimated extent of flood inundation along the Elk River within communities in Kanawha and Clay Counties, West Virginia. These geospatial data include the following items: 1. elk_bnd; shapefile containing the polygon showing the mapped area boundary for the Elk River flood maps, 2. elk_hwm; shapefile containing high-water mark points, 3. polygon_elk_hwm; shapefile containing mapped extent of flood inundation, derived from the water-surface elevation surveyed at high-water marks, 4. depth_hwm; raster file for the flood depths derived from the water-surface elevation surveyed at high-water marks, 5. polygon_elk_dem; shapefile containing mapped extent of flood inundation, derived from the height above ground recorded at high-water marks and the digital elevation model (DEM) raster, 6. depth_dem; raster file for the flood depths derived from the height above ground recorded at high-water marks and the digital elevation model raster. The upstream and downstream mapped area extent is limited to the upstream-most and downstream-most high-water mark locations. In areas of uncertainty of flood extent, the mapped area boundary is lined up with the flood inundation polygon extent. The mapped area boundary polygon was used to extract the final flood inundation polygon and depth raster from the water-surface elevation raster file. Depth raster files were created using the "Topo to Raster" tool in ArcMap (ESRI, 2012). For this study two sets of inundation layers were generated for each reach. One raster file showing flood depths, "depth_hwm", was created by using high-water mark water-surface elevation values on the land surface and a digital elevation model. However, differences in elevation between the surveyed water-surface elevation values at HWM’s and the land-surface elevation from the digital elevation model data provided uncertainty in the inundation extent of the generated layers. Often times elevation differences of +/- 20 feet were noticed between the surveyed elevation from a HWM on the land surface and the digital elevation model land-surface elevation. Due to these elevation differences, we incorporated a second method of interpolating the water-surface layer. The recorded height above ground value from the surveyed HWM was added to the digital elevation model land-surface elevation at that point. This created a new water-surface elevation value to be used with the “Topo to Raster” interpolation method to create a second depth raster, "depth_dem". Both sets of inundation layers are provided.

The mapped area boundary, flood inundation extents, and depth rasters were created to provide an estimated extent of flood inundation along the Gauley River within the community of Camden-on-Gauley, West Virginia. These geospatial data include the following items: 1. gauley_bnd; shapefile containing the polygon showing the mapped area boundary for the Gauley River flood maps, 2. gauley_hwm; shapefile containing high-water mark points, 3. polygon_gauley_hwm; shapefile containing mapped extent of flood inundation, derived from the water-surface elevation surveyed at high-water marks, 4. depth_hwm; raster file for the flood depths derived from the water-surface elevation surveyed at high-water marks, 5. polygon_gauley_dem; shapefile containing mapped extent of flood inundation, derived from the height above ground recorded at high-water marks and the digital elevation model (DEM) raster, 6. depth_dem; raster file for the flood depths derived from the height above ground recorded at high-water marks and the digital elevation model raster. The upstream and downstream mapped area extent is limited to the upstream-most and downstream-most high-water mark locations. In areas of uncertainty of flood extent, the mapped area boundary is lined up with the flood inundation polygon extent. The mapped area boundary polygon was used to extract the final flood inundation polygon and depth raster from the water-surface elevation raster file. Depth raster files were created using the "Topo to Raster" tool in ArcMap (ESRI, 2012). For this study two sets of inundation layers were generated for each reach. One raster file showing flood depths, "depth_hwm", was created by using high-water mark water-surface elevation values on the land surface and a digital elevation model. However, differences in elevation between the surveyed water-surface elevation values at HWM’s and the land-surface elevation from the digital elevation model data provided uncertainty in the inundation extent of the generated layers. Often times elevation differences of +/- 20 feet were noticed between the surveyed elevation from a HWM on the land surface and the digital elevation model land-surface elevation. Due to these elevation differences, we incorporated a second method of interpolating the water-surface layer. The recorded height above ground value from the surveyed HWM was added to the digital elevation model land-surface elevation at that point. This created a new water-surface elevation value to be used with the “Topo to Raster” interpolation method to create a second depth raster, "depth_dem". Both sets of inundation layers are provided.

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. State Legislative Districts (SLDs) are the areas from which members are elected to state legislatures. The SLDs embody the upper (senate) and lower (house) chambers of the state legislature. Nebraska has a unicameral legislature and the District of Columbia has a single council, both of which the Census Bureau treats as upper-chamber legislative areas for the purpose of data presentation; there are no data by SLDL for either Nebraska or the District of Columbia. A unique three-character census code, identified by state participants, is assigned to each SLD within a state. In Connecticut, Illinois, Louisiana, New Hampshire, Wisconsin, and Puerto Rico, the Redistricting Data Program (RDP) participant did not define the SLDs to cover all of the state or state equivalent area. In these areas with no SLDs defined, the code "ZZZ" has been assigned, which is treated as a single SLD for purposes of data presentation. The generarlized boundaries in this file are based on the most recent state legislative district boundaries collected by the Census Bureau for the 2022 election year and provided by state-level participants through the RDP.

This layer describes USFS vs. non-USFS land (surface) ownership in the Monongahela and George Washington-Jefferson National Forests of West Virginia and Virginia.Purpose:This layer aids in the planning and management of lands and resources administered by the U.S. Forest Service in West Virginia and Virginia.Source:Referenced from US Forest Service Enterprise Map Services Program.Processing:N/ASymbolization: Forest Service-owned lands: green polygonsPrivately-owned lands: tan polygons

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme ( https://communities.geoplatform.gov/ngda-cadastre/ ). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all open space public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, permanent and long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of U.S. public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas using thirty-six attributes and five separate feature classes representing the U.S. protected areas network: Fee (ownership parcels), Designation, Easement, Marine, Proclamation and Other Planning Boundaries. An additional Combined feature class includes the full PAD-US inventory to support data management, queries, web mapping services, and analyses. The Feature Class (FeatClass) field in the Combined layer allows users to extract data types as needed. A Federal Data Reference file geodatabase lookup table (PADUS3_0Combined_Federal_Data_References) facilitates the extraction of authoritative federal data provided or recommended by managing agencies from the Combined PAD-US inventory. This PAD-US Version 3.0 dataset includes a variety of updates from the previous Version 2.1 dataset (USGS, 2020, https://doi.org/10.5066/P92QM3NT ), achieving goals to: 1) Annually update and improve spatial data representing the federal estate for PAD-US applications; 2) Update state and local lands data as state data-steward and PAD-US Team resources allow; and 3) Automate data translation efforts to increase PAD-US update efficiency. The following list summarizes the integration of "best available" spatial data to ensure public lands and other protected areas from all jurisdictions are represented in the PAD-US (other data were transferred from PAD-US 2.1). Federal updates - The USGS remains committed to updating federal fee owned lands data and major designation changes in annual PAD-US updates, where authoritative data provided directly by managing agencies are available or alternative data sources are recommended. The following is a list of updates or revisions associated with the federal estate: 1) Major update of the Federal estate (fee ownership parcels, easement interest, and management designations where available), including authoritative data from 8 agencies: Bureau of Land Management (BLM), U.S. Census Bureau (Census Bureau), Department of Defense (DOD), U.S. Fish and Wildlife Service (FWS), National Park Service (NPS), Natural Resources Conservation Service (NRCS), U.S. Forest Service (USFS), and National Oceanic and Atmospheric Administration (NOAA). The federal theme in PAD-US is developed in close collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/ ). 2) Improved the representation (boundaries and attributes) of the National Park Service, U.S. Forest Service, Bureau of Land Management, and U.S. Fish and Wildlife Service lands, in collaboration with agency data-stewards, in response to feedback from the PAD-US Team and stakeholders. 3) Added a Federal Data Reference file geodatabase lookup table (PADUS3_0Combined_Federal_Data_References) to the PAD-US 3.0 geodatabase to facilitate the extraction (by Data Provider, Dataset Name, and/or Aggregator Source) of authoritative data provided directly (or recommended) by federal managing agencies from the full PAD-US inventory. A summary of the number of records (Frequency) and calculated GIS Acres (vs Documented Acres) associated with features provided by each Aggregator Source is included; however, the number of records may vary from source data as the "State Name" standard is applied to national files. The Feature Class (FeatClass) field in the table and geodatabase describe the data type to highlight overlapping features in the full inventory (e.g. Designation features often overlap Fee features) and to assist users in building queries for applications as needed. 4) Scripted the translation of the Department of Defense, Census Bureau, and Natural Resource Conservation Service source data into the PAD-US format to increase update efficiency. 5) Revised conservation measures (GAP Status Code, IUCN Category) to more accurately represent protected and conserved areas. For example, Fish and Wildlife Service (FWS) Waterfowl Production Area Wetland Easements changed from GAP Status Code 2 to 4 as spatial data currently represents the complete parcel (about 10.54 million acres primarily in North Dakota and South Dakota). Only aliquot parts of these parcels are documented under wetland easement (1.64 million acres). These acreages are provided by the U.S. Fish and Wildlife Service and are referenced in the PAD-US geodatabase Easement feature class 'Comments' field. State updates - The USGS is committed to building capacity in the state data-steward network and the PAD-US Team to increase the frequency of state land updates, as resources allow. The USGS supported efforts to significantly increase state inventory completeness with the integration of local parks data in the PAD-US 2.1, and developed a state-to-PAD-US data translation script during PAD-US 3.0 development to pilot in future updates. Additional efforts are in progress to support the technical and organizational strategies needed to increase the frequency of state updates. The PAD-US 3.0 included major updates to the following three states: 1) California - added or updated state, regional, local, and nonprofit lands data from the California Protected Areas Database (CPAD), managed by GreenInfo Network, and integrated conservation and recreation measure changes following review coordinated by the data-steward with state managing agencies. Developed a data translation Python script (see Process Step 2 Source Data Documentation) in collaboration with the data-steward to increase the accuracy and efficiency of future PAD-US updates from CPAD. 2) Virginia - added or updated state, local, and nonprofit protected areas data (and removed legacy data) from the Virginia Conservation Lands Database, provided by the Virginia Department of Conservation and Recreation's Natural Heritage Program, and integrated conservation and recreation measure changes following review by the data-steward. 3) West Virginia - added or updated state, local, and nonprofit protected areas data provided by the West Virginia University, GIS Technical Center. For more information regarding the PAD-US dataset please visit, https://www.usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual . A version history of PAD-US updates is summarized below (See https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-history for more information): 1) First posted - April 2009 (Version 1.0 - available from the PAD-US: Team pad-us@usgs.gov). 2) Revised - May 2010 (Version 1.1 - available from the PAD-US: Team pad-us@usgs.gov). 3) Revised - April 2011 (Version 1.2 - available from the PAD-US: Team pad-us@usgs.gov). 4) Revised - November 2012 (Version 1.3) https://doi.org/10.5066/F79Z92XD 5) Revised - May 2016 (Version 1.4) https://doi.org/10.5066/F7G73BSZ 6) Revised - September 2018 (Version 2.0) https://doi.org/10.5066/P955KPLE 7) Revised - September 2020 (Version 2.1) https://doi.org/10.5066/P92QM3NT 8) Revised - January 2022 (Version 3.0) https://doi.org/10.5066/P9Q9LQ4B Comparing protected area trends between PAD-US versions is not recommended without consultation with USGS as many changes reflect improvements to agency and organization GIS systems, or conservation and recreation measure classification, rather than actual changes in protected area acquisition on the ground.

This layer describes USFS land (surface) ownership in the Monongahela and George Washington-Jefferson National Forests of West Virginia and Virginia. Privately-held land within the forests' Proclamation Boundaries are not shown.

This layer provides information on municipal, county, and state boundary monuments located throughout the Commonwealth of Pennsylvania. For more information on this layer, you can use the Data Dictionary available in Spreadsheet format. This layer is for use in PennDOT's Open Data Portal. PennDOT is actively updating and maintaining this spatial data. The following sources were used to digitize geometry and populate attributes: USGS Historical Topographic Maps – provided by USGS and ESRI was used as a primary source in geolocating boundary monument points throughout the Commonwealth. Municipal, County, and State boundary monuments are symbolized distinctly within historical USGS Topographic maps. https://www.waymarking.com – provided secondary source information for locating boundary monument point locations, photos, and information. The site is utilized primarily by volunteers and hobbyists who geolocate and catalog physical constructs such as boundary monuments.Google Maps and Google Earth were used to locate boundary monuments and for image acquisition with street view.And with the help of additional DOT departments and agencies such as:Franklin County GIS, Potter County, Tioga County, RETTEW, Professional Survey Societies of NY and PA, Wetmore Surveying, JMT, West Virginia Surveyors Historical Society, National Geodetic SurveyQuestions, comments, or corrections – please contact: Mark Leitzell - mleitzell@pa.govWilliam Havrilchak - wihavrilch@pa.gov

The U.S. housing market has slowed, after 13 consecutive years of rising home prices. In 2021, house prices surged by an unprecedented 18 percent, marking the highest increase on record. However, the market has since cooled, with the Freddie Mac House Price Index showing more modest growth between 2022 and 2024. In 2024, home prices increased by 4.2 percent. That was lower than the long-term average of 4.4 percent since 1990. Impact of mortgage rates on homebuying The recent cooling in the housing market can be partly attributed to rising mortgage rates. After reaching a record low of 2.96 percent in 2021, the average annual rate on a 30-year fixed-rate mortgage more than doubled in 2023. This significant increase has made homeownership less affordable for many potential buyers, contributing to a substantial decline in home sales. Despite these challenges, forecasts suggest a potential recovery in the coming years. How much does it cost to buy a house in the U.S.? In 2023, the median sales price of an existing single-family home reached a record high of over 389,000 U.S. dollars. Newly built homes were even pricier, despite a slight decline in the median sales price in 2023. Naturally, home prices continue to vary significantly across the country, with West Virginia being the most affordable state for homebuyers.