This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 ½ minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The second division of the PLSS is quarter, quarter-quarter, sixteenth or government lot division of the PLSS. The second and third divisions are combined into this feature class as an intentional de-normalization of the PLSS hierarchical data. The polygons in this feature class represent the smallest division to the sixteenth that has been defined for the first division. For example In some cases sections have only been divided to the quarter. Divisions below the sixteenth are in the Special Survey or Parcel Feature Class. The second division of the PLSS is quarter, quarter-quarter, sixteenth or government lot division of the PLSS. The second and third divisions are combined into this feature class as an intentional de-normalization of the PLSS hierarchical data. The polygons in this feature class represent the smallest division to the sixteenth that has been defined for the first division. For example In some cases sections have only been divided to the quarter. Divisions below the sixteenth are in the Special Survey or Parcel Feature Class.

The Digital Geologic-GIS Map of Washita Battlefield National Historic Site and Vicinity, Oklahoma is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (waba_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 map file (.mapx) file (waba_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (waba_geology.mxd) and individual 10.1 layer (.lyr) 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 10.1 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.) this file (waba_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (waba_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 (waba_geology_metadata_faq.pdf). Please read the waba_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: 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: Geological Society of America GeoCorps. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (waba_geology_metadata.txt or waba_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 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 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, 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).

The Unpublished Digital Geologic Map of Chickasaw National Recreation Area and Vicinity, Oklahoma is composed of GIS data layers and GIS tables in a 10.0 file geodatabase (chic_geology.gdb), a 10.0 ArcMap (.MXD) map document (chic_geology.mxd), and individual 10.0 layer (.LYR) files for each GIS data layer, an ancillary map information (.PDF) document (chic_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.TXT) and FAQ (.HTML) formats, and a GIS readme file (chic_gis_readme.pdf). Please read the chic_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.0 shapefile format contact Stephanie O’Meara (stephanie_o’meara@colostate.edu; see contact information below). The data is also available as a 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. Google Earth software is available for free at: http://www.google.com/earth/index.html. 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). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological 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 (chic_metadata_faq.html; available at http://nrdata.nps.gov/geology/gri_data/gis/chic/chic_metadata_faq.html). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 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 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. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 14N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth. The data is within the area of interest of Chickasaw National Recreation Area.

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Transportation, legislative, municipal, and hydrology geospatial data for Adair County.

FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme, orthographic imagery, is packaged in a separate NFIP Metadata Profile): cadastral, geodetic control, governmental unit, transportation, general structures, hydrography (water areas & lines. These data include an encoding of the geographic extent of the features and a minimal number of attributes needed to identify and describe the features. (Source: Circular A16, p. 13)

Geospatial data about Oklahoma Cities and Towns. Export to CAD, GIS, PDF, CSV and access via API.

The U.S. Geological Survey, in cooperation with the Grand River Dam Authority, computed a 2009 capacity and area table of Grand Lake O’ the Cherokees. The capacity and area table defines the relation between the elevation of the water surface and the volume and area of water that is impounded. The capacity and area of Grand Lake O’ the Cherokees were computed from a Triangular Irregular Network (TIN) surface created in Esri ArcGIS 10.5.1, a geographic information system (GIS). The TIN surface was created from three datasets: (1) a 2009 Oklahoma Water Resources Board (OWRB) bathymetric survey of Grand Lake (OWRB, 2009, 2016), (2) a 2017 USGS bathymetric survey of the Neosho, Spring, and Elk Rivers (Hunter and others, 2017; Smith and others, 2017), and (3) a 2010 lidar-derived digital elevation model (DEM) (USGS, 2016a). Where the USGS and OWRB survey data overlapped, the more recently collected USGS data were given preference. The DEM data were used in areas with land-surface elevations above the conservation pool elevation of 743.40 ft above NAVD88. Because the OWRB (2009) bathymetric survey data were the predominant source of data used (in terms of quantity and areal coverage), the results and products of this data release and the report (Hunter and Labriola, 2019) were considered to reflect bathymetric conditions in 2009.

Layers in this dataset represent Public Land Survey System subdivisions for Canadian County. Included are Townships, Sections, Quarter Sections and Government Lots. This data was created from 2019 to 2021 as part of a project to update county parcel data in partnership with ProWest & Associates (https://www.prowestgis.com/) and CEC Corporation (https://www.connectcec.com/). Corners were located to the quarter section level and additional corners were determined for the South Canadian River meanders based on the original government surveys. Quarter section corners were located using Certified Corner Records ( filed by Oklahoma licensed professional surveyors with the Oklahoma Department of Libraries where those records included coordinates. When a corner record could not be found or did not include coordinates, other interpolation methods were employed. These included connecting known corner record locations to unknown corners using data from filed subdivisions or from highway plans on record with the Oklahoma Department of Transportation. Where no corner records with coordinates were available and no interpolation methods could be used, aerial inspection was used to locate corners as the last option.Corner location accuracy varies as the method of locating the corner varies. For corners located using Certified Corner Records, accuracy is high depending on the age of the corner record and can possibly be less than 1 U.S. Foot. For corners located using interpolation methods, accuracy depends on the additional material used to interpolate the corner. In general, newer subdivisions and highway plans yield higher accuracy. For meander corners located using original government surveys, accuracy will be low due to the age of those surveys which date to the 1870's at the earliest. Additionally, corners that were located with aerials as the last available option cannot be assumed to be accurate.The data was built at the quarter section level first by connecting located corners and larger subdivisions were created from the quarter sections. For townships that extend into Grady County, township lines were only roughly located outside sections not in Canadian County.

Data about parks in the state of Oklahoma.

Mobile Map Packages (MMPK’s) can be used in the ESRI Field Maps app (no login required), either by direct download in the Field Maps app or by sideloading from your PC. They can also be used in desktop applications that support MMPK’s such as ArcGIS Pro, and ArcGIS Navigator. MMPK’s will expire quarterly and have a warning for the user at that time but will still function afterwards. They are updated quarterly to ensure you have the most up to date data possible. These mobile map packages include the following national datasets along with others: Surface Management Agency, Public Land Survey System (PLSS), BLM Recreation Sites, National Conservation Lands, ESRI’s Navigation Basemap and Vector Tile Package. Last updated 20250321. Contact jlzimmer@blm.gov with any questions.

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. The TIGER/Line shapefiles 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 boundaries of most incorporated places in this shapefile are as of January 1, 2022, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census, but some CDPs were added or updated through the 2022 BAS as well.

Layer-rich searchable mapping application displaying available well data curated by the Oklahoma Corporation Commission. Multiple outside data sources are included for geologic and hydrogeologic reference (sources cited in item descriptions). Cultural data and political districts also included for convenience.

Geospatial data about Oklahoma Township/Range. Export to CAD, GIS, PDF, CSV and access via API.

The Missouri Resource Assessment Partnership (MoRAP) of the University of Missouri, in conjunction with the Oklahoma Biological Survey of the University of Oklahoma, produced a vegetation and landcover GIS data layer for the eastern portions of Oklahoma. This effort was accomplished with direction and funding from the Oklahoma Department of Wildlife Conservation and state and federal partners (particularly the Gulf Coast Prairie and Great Plains Landscape Conservation Cooperatives of the U. S. Fish and Wildlife Service). The legend for the layer is based on NatureServe’s Ecological System Classification, with finer thematic units derived from land cover and abiotic modifiers of the System unit. Data for development of a supervised classification of landcover was collected in the field by Oklahoma Biological Survey staff and through photo interpretation of aerial imagery by MoRAP staff. This data was used with decision tree classifier on 3 dates of LandSat imagery, abiotic data, and additional available data to perform a supervised classification to a simplified set of landcover classes. Improved thematic resolution was achieved using image objects at 10 m resolution based on NAIP imagery. The landcover classes, along with EPA Level IV Ecoregion, SSURGO soils, DEM-based, and hydrology variables, were applied to the image objects and were used to interpret ecological context and assign appropriate vegetation type or landcover to the objects. Vector data was then transformed to a 10 m raster product to simplify presentation and use. Project and partner ecologists have produced detailed descriptions of most Ecological Systems that were mapped in this effort. Project ecologists have also developed an Interpretive Booklet that includes a general description of each mapped type, a general range map for each type, and a photograph representing the type (when available). The interpretive booklet also includes detailed product methodology.

Councils of Government (COG) boundaries for the state of Oklahoma.

A GIS database of geologic units and structural features in Oklahoma, with lithology, age, data structure, and format written and arranged just like the other states.

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

Find health care facilities in the state of Oklahoma.

Geospatial data for Oklahoma from State of Oklahoma. Export to CAD, GIS, PDF, KML and CSV, and access via API.