Vector polygon map data of property parcels from Kanawha County, West Virginia containing 117689 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.

The WV_Parcel data is a composite dataset of individual county parcel data. Each county provides a unique dataset, with different temporal currencies, attributes and geographies.Website Link: https://www.mapwv.gov/

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.

Vector polygon map data of property parcels from Berkeley County, West Virginia containing 54,024 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.

The Digital Surficial Geologic-GIS Map of Gauley River National Recreation Area, West Virginia is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (gari_surficial_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (gari_surficial_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (gari_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (gari_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (gari_surficial_geology_metadata_faq.pdf). Please read the gari_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: West Virginia Geological and Economic Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (gari_surficial_geology_metadata.txt or gari_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:12,000 and United States National Map Accuracy Standards features are within (horizontally) 10.2 meters or 33.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

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 USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

This map shows high-resolution (1 meter) land cover in the EPA Region 3, covering the parts of West Virginia, Virginia, and Pennsylvania outside of the Chesapeake Bay Watershed. It contains the following classes: Water, Tree Canopy, Scrub\Shrub, Low Vegetation, Barren, Impervious Structures, Other Impervious, Impervious Roads, Tree Canopy Over Impervious Structures, Tree Canopy Over Other Impervious, and Tree Canopy Over Impervious Roads. Using object-based image analysis mapping techniques, it was mapped from a combination of remote-sensing imagery and GIS datasets, including LiDAR, multispectral imagery, and thematic layers (e.g., roads, building footprints). Draft output was then manually reviewed and edited to eliminate obvious errors of omission and commission. The classification scheme closely follows a similar mapping effort for the Chesapeake Bay Watershed; together, maps from the two projects cover the entirety of the EPA Region 3 states. One difference between the projects, however, is that tidal wetlands were mapped in the Chesapeake Bay effort, included as the class Emergent Wetlands, but not in the EPA Region 3 zones outside of the watershed. The map is considered current as of 2020 for West Virginia, 2021 for Virginia, and 2022 for Pennsylvania.

The Map Service (WFS Group) provides the maps of the Land Development Plan Environment (2004) and Settlement (2006) of the Saarland.:Generalised presentation of waterway connections (WV) within the framework of the LEP Environment 2004.

This data publication contains a shapefile of points created from 1930s maps of the first land grants within the Monongahela National Forest (MNF) proclamation boundary. Corner or witness trees are those trees listed in a land survey to describe the survey corner for future re-establishment of the corner or property line. Witness trees listed in the deeds were added as attributes to the digital point locations. Deed dates range from 1752 to 1899. If no trees were listed in the deed to witness the corner, the corner was created in the point file, but no species was assigned. The deeds and surveys were created under the metes and bounds method of land survey common in the colonial era. The entire area was not surveyed in any systematic method as is found in the Western United States so there are areas of the MNF with no witness trees. Also included are the scanned images of the maps used to create the database of corner points. Each map covers a portion of the Monongahela National Forest, WV and includes latitude and longitude reference lines. On each map are the individual parcels of land drawn by draftsmen in the 1930s from the original deeds or grants. With each tract is the name of the grantee, the data of the deed or grant, the size of the tract of land (in acres), and a unique identification number that references the deed/grant from which the sketch was made. This data publication also includes two location maps (north and south) showing the location and area covered by the individual map sheets. The base map is a 1936 map of the Monongahela National Forest, WV produced by the USDA Forest Service.This database was developed to help characterize the forest at the time of European settlement.Original metadata date was 10/09/2014. Scanned images of the maps used to create the database of corner points were added on 09/15/2016 along with a few minor metadata updates.

Minor metadata updates on 12/13/2016 and 09/16/2024 (which included URL updates for related articles).

The mapped area boundary, flood inundation extents, and depth rasters were created to provide an estimated extent of flood inundation along the Cherry River within the communities of Richwood and Fenwick, West Virginia. These geospatial data include the following items: 1. cherry_bnd; shapefile containing the polygon showing the mapped area boundary for the Cherry River flood maps, 2. cherry_hwm; shapefile containing high-water mark points, 3. polygon_cherry_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_cherry_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.

Map associated with WVDEP Press Release 7/31/2017 "Grant Funding Available for Economic Development of Abandoned Mine Lands"

This study mapped land cover (water, bare ground, forest, grass, marsh, algal flat, building, bridge culvert, and agriculture) around Matagorda Bay, Texas. The study area was defined by a 2-km buffer around the West Matagorda Bay shoreline and extended from the western portion of the Colorado River Delta through the eastern portion of Matagorda Island, Texas. This study incorporated WorldView-2 (WV-2; acquired on 2012-11-17, 2013-05-05, and 2013-12-16) and lidar (acquired 2018-01-04 - 2018-02-23 and 2019-01-24 – 2019-01-29) to obtain a 2-m resolution habitat map for the entire study area. A novel stacked classification approach was developed to take advantage of high-resolution satellite imagery and airborne lidar point clouds. Ultimately, a rule-based classifier was stacked on a group of machine learning classifiers for multispectral images and a filter classifier for lidar point clouds. The data were created for the Texas Office of the Comptroller project titled “Matagorda Bay Ecosystem Assessment.†Maps of vegetation, sand, and water coverage for discrete dates from 1850 to 2020 are available in related dataset HI.x833.000:0020 (https://doi.org/10.7266/zs2f74bj).

no abstract provided

This map service, Mine Working Layers (WMDRGISC - 2020), describes abandoned mine workings near Thomas, WV. The data associated with this map service was (we believe) created Western Pocahontas Properties and received from the Western Maryland Regional GIS Center.Source and date:The known information on this source is limited. The linework in this feature collection was supposedly digitized by Western Pocahontas Properties, c. 2000 from paper maps of the mines. Initial requests to WPP for information about this data have not yet been acknowledged. The data was obtained from Western Maryland Regional GIS Center (Jason Litten, Co-Director) as a set of shapefiles. Accessed in October of 2020.Purpose:This data was created in order to show the various mine workings in this area and the locations of underground mine pools which, if breached by road construction, would cause significant subsidence hazards and pollutants of surface waters, respectively.Processing:ABRA created this layer by publishing the shapefiles to ArcGIS Online as a map service..Symbolization:The following symbolizations are how they appear in the Parsons to Davis online map provided by ABRA.Coal Barrier: gray polygonCoketon Mine Pool: translucent blue polygonKempton Mine Pool: translucent light blue polygonMetikki Mine Pool: opaque light purple polygonUndefined Mine Workings: dashed gray polylineMine Perimeter: black polyline