Introduction and Rationale: Due to our increasing understanding of the role the surrounding landscape plays in ecological processes, a detailed characterization of land cover, including both agricultural and natural habitats, is ever more important for both researchers and conservation practitioners. Unfortunately, in the United States, different types of land cover data are split across thematic datasets that emphasize agricultural or natural vegetation, but not both. To address this data gap and reduce duplicative efforts in geospatial processing, we merged two major datasets, the LANDFIRE National Vegetation Classification (NVC) and USDA-NASS Cropland Data Layer (CDL), to produce an integrated land cover map. Our workflow leveraged strengths of the NVC and the CDL to produce detailed rasters comprising both agricultural and natural land-cover classes. We generated these maps for each year from 2012-2021 for the conterminous United States, quantified agreement between input layers and accuracy of our merged product, and published the complete workflow necessary to update these data. In our validation analyses, we found that approximately 5.5% of NVC agricultural pixels conflicted with the CDL, but we resolved a majority of these conflicts based on surrounding agricultural land, leaving only 0.6% of agricultural pixels unresolved in our merged product. Contents: Spatial data Attribute table for merged rasters Technical validation data Number and proportion of mismatched pixels Number and proportion of unresolved pixels Producer's and User's accuracy values and coverage of reference data Resources in this dataset:Resource Title: Attribute table for merged rasters. File Name: CombinedRasterAttributeTable_CDLNVC.csvResource Description: Raster attribute table for merged raster product. Class names and recommended color map were taken from USDA-NASS Cropland Data Layer and LANDFIRE National Vegetation Classification. Class values are also identical to source data, except classes from the CDL are now negative values to avoid overlapping NVC values. Resource Title: Number and proportion of mismatched pixels. File Name: pixel_mismatch_byyear_bycounty.csvResource Description: Number and proportion of pixels that were mismatched between the Cropland Data Layer and National Vegetation Classification, per year from 2012-2021, per county in the conterminous United States.Resource Title: Number and proportion of unresolved pixels. File Name: unresolved_conflict_byyear_bycounty.csvResource Description: Number and proportion of unresolved pixels in the final merged rasters, per year from 2012-2021, per county in the conterminous United States. Unresolved pixels are a result of mismatched pixels that we could not resolve based on surrounding agricultural land (no agriculture with 90m radius).Resource Title: Producer's and User's accuracy values and coverage of reference data. File Name: accuracy_datacoverage_byyear_bycounty.csvResource Description: Producer's and User's accuracy values and coverage of reference data, per year from 2012-2021, per county in the conterminous United States. We defined coverage of reference data as the proportional area of land cover classes that were included in the reference data published by USDA-NASS and LANDFIRE for the Cropland Data Layer and National Vegetation Classification, respectively. CDL and NVC classes with reference data also had published accuracy statistics. Resource Title: Data Dictionary. File Name: Data_Dictionary_RasterMerge.csv

Dataset

This dataset was created by neerajbhat98

Contents

Contains:World HillshadeWorld Street Map (with Relief) - Base LayerLarge Scale International Boundaries (v11.3)World Street Map (with Relief) - LabelsDoS Country Labels DoS Country LabelsCountry (admin 0) labels that have been vetted for compliance with foreign policy and legal requirements. These labels are part of the US Federal Government Basemap, which contains the borders and place names that have been vetted for compliance with foreign policy and legal requirements.Source: DoS Country Labels - Overview (arcgis.com)Large Scale International BoundariesVersion 11.3Release Date: December 19, 2023DownloadFor more information on the LSIB click here: https://geodata.state.gov/ A direct link to the data is available here: https://data.geodata.state.gov/LSIB.zipAn ISO-compliant version of the LSIB metadata (in ISO 19139 format) is here: https://geodata.state.gov/geonetwork/srv/eng/catalog.search#/metadata/3bdb81a0-c1b9-439a-a0b1-85dac30c59b2 Direct inquiries to internationalboundaries@state.govOverviewThe Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. The current edition is version 11.3 (published 19 December 2023). The 11.3 release contains updates to boundary lines and data refinements enabling reuse of the dataset. These data and generalized derivatives are the only international boundary lines approved for U.S. Government use. The contents of this dataset reflect U.S. Government policy on international boundary alignment, political recognition, and dispute status. They do not necessarily reflect de facto limits of control.National Geospatial Data AssetThis dataset is a National Geospatial Data Asset managed by the Department of State on behalf of the Federal Geographic Data Committee's International Boundaries Theme.DetailsSources for these data include treaties, relevant maps, and data from boundary commissions and national mapping agencies. Where available and applicable, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery process involves analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground.Attribute StructureThe dataset uses thefollowing attributes:Attribute NameCC1COUNTRY1CC2COUNTRY2RANKSTATUSLABELNOTES These attributes are logically linked:Linked AttributesCC1COUNTRY1CC2COUNTRY2RANKSTATUS These attributes have external sources:Attribute NameExternal Data SourceCC1GENCCOUNTRY1DoS ListsCC2GENCCOUNTRY2DoS ListsThe eight attributes listed above describe the boundary lines contained within the LSIB dataset in both a human and machine-readable fashion. Other attributes in the release include "FID", "Shape", and "Shape_Leng" are components of the shapefile format and do not form an intrinsic part of the LSIB."CC1" and "CC2" fields are machine readable fields which contain political entity codes. These codes are derived from the Geopolitical Entities, Names, and Codes Standard (GENC) Edition 3 Update 18. The dataset uses the GENC two-character codes. The code ‘Q2’, which is not in GENC, denotes a line in the LSIB representing a boundary associated with an area not contained within the GENC standard.The "COUNTRY1" and "COUNTRY2" fields contain human-readable text corresponding to the name of the political entity. These names are names approved by the U.S. Board on Geographic Names (BGN) as incorporated in the list of Independent States in the World and the list of Dependencies and Areas of Special Sovereignty maintained by the Department of State. To ensure the greatest compatibility, names are presented without diacritics and certain names are rendered using commonly accepted cartographic abbreviations. Names for lines associated with the code ‘Q2’ are descriptive and are not necessarily BGN-approved. Names rendered in all CAPITAL LETTERS are names of independent states. Other names are those associated with dependencies, areas of special sovereignty, or are otherwise presented for the convenience of the user.The following fields are an intrinsic part of the LSIB dataset and do not rely on external sources:Attribute NameMandatoryContains NullsRANKYesNoSTATUSYesNoLABELNoYesNOTESNoYesNeither the "RANK" nor "STATUS" field contains null values; the "LABEL" and "NOTES" fields do.The "RANK" field is a numeric, machine-readable expression of the "STATUS" field. Collectively, these fields encode the views of the United States Government on the political status of the boundary line.Attribute NameValueRANK123STATUSInternational BoundaryOther Line of International Separation Special Line A value of "1" in the "RANK" field corresponds to an "International Boundary" value in the "STATUS" field. Values of "2" and "3" correspond to "Other Line of International Separation" and "Special Line", respectively.The "LABEL" field contains required text necessarily to describe the line segment. The "LABEL" field is used when the line segment is displayed on maps or other forms of cartographic visualizations. This includes most interactive products. The requirement to incorporate the contents of the "LABEL" field on these products is scale dependent. If a label is legible at the scale of a given static product a proper use of this dataset would encourage the application of that label. Using the contents of the "COUNTRY1" and "COUNTRY2" fields in the generation of a line segment label is not required. The "STATUS" field is not a line labeling field but does contain the preferred description for the three LSIB line types when lines are incorporated into a map legend. Using the "CC1", "CC2", or "RANK" fields for labeling purposes is prohibited.The "NOTES" field contains an explanation of any applicable special circumstances modifying the lines. This information can pertain to the origins of the boundary lines, any limitations regarding the purpose of the lines, or the original source of the line. Use of the "NOTES" field for labeling purposes is prohibited.External Data SourcesGeopolitical Entities, Names, and Codes Registry: https://nsgreg.nga.mil/GENC-overview.jspU.S. Department of State List of Independent States in the World: https://www.state.gov/independent-states-in-the-world/U.S. Department of State List of Dependencies and Areas of Special Sovereignty: https://www.state.gov/dependencies-and-areas-of-special-sovereignty/The source for the U.S.—Canada international boundary (NGDAID97) is the International Boundary Commission: https://www.internationalboundarycommission.org/en/maps-coordinates/coordinates.phpThe source for the “International Boundary between the United States of America and the United States of Mexico” (NGDAID82) is the International Boundary and Water Commission: https://catalog.data.gov/dataset?q=usibwcCartographic UsageCartographic usage of the LSIB requires a visual differentiation between the three categories of boundaries. Specifically, this differentiation must be between:- International Boundaries (Rank 1);- Other Lines of International Separation (Rank 2); and- Special Lines (Rank 3).Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary.Additional cartographic information can be found in Guidance Bulletins (https://hiu.state.gov/data/cartographic_guidance_bulletins/) published by the Office of the Geographer and Global Issues.ContactDirect inquiries to internationalboundaries@state.gov.CreditsThe lines in the LSIB dataset are the product of decades of collaboration between geographers at the Department of State and the National Geospatial-Intelligence Agency with contributions from the Central Intelligence Agency and the UK Defence Geographic Centre.Attribution is welcome: U.S. Department of State, Office of the Geographer and Global Issues.Changes from Prior ReleaseThe 11.3 release is the third update in the version 11 series.This version of the LSIB contains changes and accuracy refinements for the following line segments. These changes reflect improvements in spatial accuracy derived from newly available source materials, an ongoing review process, or the publication of new treaties or agreements. Notable changes to lines include:• AFGHANISTAN / IRAN• ALBANIA / GREECE• ALBANIA / KOSOVO• ALBANIA/MONTENEGRO• ALBANIA / NORTH MACEDONIA• ALGERIA / MOROCCO• ARGENTINA / BOLIVIA• ARGENTINA / CHILE• BELARUS / POLAND• BOLIVIA / PARAGUAY• BRAZIL / GUYANA• BRAZIL / VENEZUELA• BRAZIL / French Guiana (FR.)• BRAZIL / SURINAME• CAMBODIA / LAOS• CAMBODIA / VIETNAM• CAMEROON / CHAD• CAMEROON / NIGERIA• CHINA / INDIA• CHINA / NORTH KOREA• CHINA / Aksai Chin• COLOMBIA / VENEZUELA• CONGO, DEM. REP. OF THE / UGANDA• CZECHIA / GERMANY• EGYPT / LIBYA• ESTONIA / RUSSIA• French Guiana (FR.) / SURINAME• GREECE / NORTH MACEDONIA• GUYANA / VENEZUELA• INDIA / Aksai Chin• KAZAKHSTAN / RUSSIA• KOSOVO / MONTENEGRO• KOSOVO / SERBIA• LAOS / VIETNAM• LATVIA / LITHUANIA• MEXICO / UNITED STATES• MONTENEGRO / SERBIA• MOROCCO / SPAIN• POLAND / RUSSIA• ROMANIA / UKRAINEVersions 11.0 and 11.1 were updates to boundary lines. Like this version, they also contained topology fixes, land boundary terminus refinements, and tripoint adjustments. Version 11.2 corrected a few errors in the attribute data and ensured that CC1 and CC2 attributes are in alignment with an updated version of the Geopolitical Entities, Names, and Codes (GENC) Standard, specifically Edition 3 Update 17.LayersLarge_Scale_International_BoundariesTerms of

Dataset

This dataset was created by K Scott Mader

Contents

Recommendations for the suitable contents of the geospatial datasets presenting the distribution of languages including the benefits of each, and our solutions (selected in the case study) concerning the Uralic languages.

This map data product delivers high-precision, real-time, and historical GPS event records across North America. It is designed for organizations that require granular spatial data for applications such as mapping, movement tracking, retail analytics, and infrastructure planning.

Data Contents: Latitude & longitude coordinates Timestamp (epoch & human-readable date) Device ID (MAID: IDFA/GAID) Country code (ISO3) Horizontal accuracy (85% fill rate) Optional metadata: IP address, mobile carrier, device model

Access & Delivery: Available via API with custom polygon queries (up to 10,000 tiles) for targeted location insights. Data can be delivered hourly or daily in JSON, CSV, or Parquet formats, through AWS S3, Google Cloud Storage, or direct API access. Historical coverage extends back to September 2024, with 95% of events delivered within 3 days for near-real-time analysis.

Compliance & Flexibility: GDPR and CCPA compliant Credit-based query pricing for scalability Custom schema mapping and folder structure available

Applications: Map creation and enhancement POI visitation analytics Urban mobility and transit modeling Retail site selection and catchment area mapping Real estate and zoning analysis Geospatial risk and environmental planning

This dataset contains key characteristics about the data described in the Data Descriptor ERA5-based global meteorological wildfire danger maps. Contents:

    1. human readable metadata summary table in CSV format


    2. machine readable metadata file in JSON format

This vector tile layer is designed to support exporting small volumes of basemap tiles for offline use. The content of this layer is equivalent to World Street Map (with Relief). This layer includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, building footprints, and administrative boundaries, designed for use with shaded relief for added context. See World Street Map (with Relief) for more details.Use this MapThis vector tile service supporting this layer will enable you to export a small number of tiles in a single request. This layer is not intended to be used to display live map tiles for use in a web map or web mapping application. To display map tiles, please use World Street Map (with Relief).Service Information for DevelopersTo export tiles for World Street Map (with Relief- for Export), you must use the instance of the World_Basemap_Export_v2 service hosted on basemaps.arcgis.com referenced by this layer (see URL in Contents below), which has the Export Tiles operation enabled. This layer is optimized to minimize the size of the download for offline use. Due to this optimization, there are small differences between this layer and the display optimized World_Basemap_v2 service. This layer is intended to support export of basemap tiles for offline use in ArcGIS applications and other applications built with an ArcGIS Runtime SDK.

The Map of the Czech Republic 1:1,000,000 (MČR 1M) relates with the contents of the map of the Czech Republic 1:500,000 and is conceived as a general geographic map. It shows the entire territory of the Czech Republic on a single map sheet. The MČR 1M contains planimetry, altimetry, geographic coordinate grid, map lettering and the map legend. Planimetry consists of settlements, transportation (highways, roads, railways), hydrography (significant water courses and reservoirs), state and regional boundaries, vegetation and land surface (forests). Subject of the altimetry are elevation points. Map lettering and marginal notes consist of standard geographic names, map name and its scale with imprint data and the graphic scale, textual part of the legend geographic coordinates on the frame edges. The subjects of the map contents are coherently displayed also on the adjacent areas of neighbour states.

ArcGIS Map Packages and GIS Data for Gillreath-Brown, Nagaoka, and Wolverton (2019)

**When using the GIS data included in these map packages, please cite all of the following:

Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, 2019. PLoSONE 14(8):e0220457. http://doi.org/10.1371/journal.pone.0220457

Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. ArcGIS Map Packages for: A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, Gillreath-Brown et al., 2019. Version 1. Zenodo. https://doi.org/10.5281/zenodo.2572018

OVERVIEW OF CONTENTS

This repository contains map packages for Gillreath-Brown, Nagaoka, and Wolverton (2019), as well as the raw digital elevation model (DEM) and soils data, of which the analyses was based on. The map packages contain all GIS data associated with the analyses described and presented in the publication. The map packages were created in ArcGIS 10.2.2; however, the packages will work in recent versions of ArcGIS. (Note: I was able to open the packages in ArcGIS 10.6.1, when tested on February 17, 2019). The primary files contained in this repository are:

Raw DEM and Soils data

Digital Elevation Model Data (Map services and data available from U.S. Geological Survey, National Geospatial Program, and can be downloaded from the National Elevation Dataset)

DEM_Individual_Tiles: Individual DEM tiles prior to being merged (1/3 arc second) from USGS National Elevation Dataset.

DEMs_Merged: DEMs were combined into one layer. Individual watersheds (i.e., Goodman, Coffey, and Crow Canyon) were clipped from this combined DEM.

Soils Data (Map services and data available from Natural Resources Conservation Service Web Soil Survey, U.S. Department of Agriculture)

Animas-Dolores_Area_Soils: Small portion of the soil mapunits cover the northeastern corner of the Coffey Watershed (CW).

Cortez_Area_Soils: Soils for Montezuma County, encompasses all of Goodman (GW) and Crow Canyon (CCW) watersheds, and a large portion of the Coffey watershed (CW).

ArcGIS Map Packages

Goodman_Watershed_Full_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the full Goodman Watershed (GW).

Goodman_Watershed_Mesa-Only_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the mesa-only Goodman Watershed.

Crow_Canyon_Watershed_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the Crow Canyon Watershed (CCW).

Coffey_Watershed_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the Coffey Watershed (CW).

For additional information on contents of the map packages, please see see "Map Packages Descriptions" or open a map package in ArcGIS and go to "properties" or "map document properties."

LICENSES

Code: MIT year: 2019 Copyright holders: Andrew Gillreath-Brown, Lisa Nagaoka, and Steve Wolverton

CONTACT

Andrew Gillreath-Brown, PhD Candidate, RPA Department of Anthropology, Washington State University andrew.brown1234@gmail.com – Email andrewgillreathbrown.wordpress.com – Web

This dataset contains key characteristics about the data described in the Data Descriptor Depth-to-bedrock map of China at a spatial resolution of 100 meters. Contents:

    1. human readable metadata summary table in CSV format


    2. machine readable metadata file in JSON format 
     Versioning Note:Version 2 was generated when the metadata format was updated from JSON to JSON-LD. This was an automatic process that changed only the format, not the contents, of the metadata.

Orbis City Map (OCM) offers municipalities a platform to present their facilities, sights, businesses, etc. on a digital map via the community homepage. In addition, a textual description of the map contents can be retrieved. Recreational routes (hiking paths, cycle paths, MTB routes, cross-country trails, ...) are also available. In addition, the course of the route can be tracked via an interactive elevation profile. OCM has a modular structure and various other contents can also be displayed. Examples include dedication, free building plots, development concept, historically interesting places, etc. Background maps are available: Open Street Map, Open Topo Map, Base Map, Base Map Orthophoto and optional: Local map (arge-cartography), development concept, French cadastral register and much more. The municipality has an admin tool to manage the content.

The map of the Czech Republic 1:1 000 000 (MCR 1M) is a content link to the Map of the Czech Republic 1:500 000. It displays the entire territory of the Czech Republic on one map sheet, i.e. an area of 78 886 km². The dimensions of the paper are 55 x 37 cm, the dimensions of the map field are 49,5 x 31 cm. The map is derived from the map of the Czech Republic 1:500 000. It contains location, altimeter, geographical network, description and explanatory notes to the map. The subject of the location is settlements, roads (motorways, roads, railways), water (significant watercourses and reservoirs), borders (state and regional), vegetation and soil surface (forests). The height points are the subject of the altimeter. The description includes standardised geographical nomenclature (names of settlements, waters and orographic units), the name and scale of the map with printed data and the graphical scale, the text part of the explanatory notes and the frame data (geographical coordinates). The objects of the map’s contents are also continuously depicted on adjacent parts of neighbouring states.

Dataset

This dataset was created by Dương Thịnh

Contents

Dataset

This dataset was created by David Drees

Contents

This resource contains statewide networks of roadways, railroads, bridges, and low-water crossings, for Texas only.

Roadways detail: The Transportation Planning and Programming (TPP) Division of the Texas Department of Transportation (TxDOT) maintains a spatial dataset of roadway polylines for planning and asset inventory purposes, as well as for visualization and general mapping. M values are stored in the lines as DFOs (Distance From Origin), and provide the framework for managing roadway assets using linear referencing. This dataset covers the state of Texas and includes on-systems routes (those that TxDOT maintains), such as interstate highways, U.S. highways, state highways, and farm and ranch roads, as well as off-system routes, such as county roads and local streets. Date valid as of: 12/31/2014. Publish Date: 05/01/2015. Update Frequency: Quarterly.

Bridges detail: As with the roadways, both on-system and off-system bridges are maintained in separate datasets (54,844 total bridges, 36,007 on-system and 18,837 off-system). Bridges have numerous useful attributes, see coding guide [1] for documentation. One such attribute identifies structures that cross water: the second digit of Item 42 “Type of Service”. If the second digit is between 5 and 9 (inclusive) then the structure is over water. The bridges datasets are valid as of December 2016.

The roadways and bridges datasets contained here were obtained directly from TxDOT through personal correspondence. An additional transportation data resource is the Texas Natural Resources Information System (TNRIS) [3]. The railroads and low-water crossings were obtained through TNRIS.

November 2023 updates: in the years since this data archive was first published, TxDOT has developed an open data portal for downloading their roadway inventory and other datasets. Also, in 2023 TNRIS was renamed as the Texas Geographic Information Office (TxGIO). Their datahub [3] is continually evolving, but still has the tnris.org domain for now. We are not updating any of the basemap data in the contents list below, which was current at the time of Hurricane Harvey.

References [1] TxDOT Bridges Coding Guide (download below) [2] TxDOT Open Data Portal [https://gis-txdot.opendata.arcgis.com/] [3] TNRIS/TxGIO data downloads [https://data.tnris.org/]

The cadastral maps in vector format are represented in a viewer. The contents can thus be superimposed on those of the Lombardy Geoportal for a comparison with other geographical contents. The service allows you to carry out navigation and search operations by municipality, sheet and map.

The download service (OAF) maps of the mean element contents in the soil Brandenburg provides data for some selected environmentally relevant elements the maps of the mean contents (median values / P50) in the a) topsoil (OB) and in the b) subsoil (UG). The analytical data are based on approximately 2000 soil profiles recorded in accordance with soil mapping instructions (KA 5) and distributed irregularly over the country territory - royal water soluble contents in dry matter fine soil (less than 2 mm) for arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), zinc (Zn); Total levels of mercury (Hg). The map is based on the legend units of the soil overview map, which were assigned to the grade classes corresponding to the medians for the dominant of the surface soil forms involved. The salary classes, which are uniform for OB and UG respectively, depend on the range of all values for the respective element. The legend units have been designed in such a way that the contents increase from green to yellow to brown. As there are only a few and highly scattering values for anthropogenic soils, settlement areas were assigned ‘no data’ (grey). The map representations are supplemented by a tabular overview of the average grades used and their color design. (see https://geo.brandenburg.de/karten/htdocs/2020_Elementgehalte.pdf) For more information, see the metadata of the data underlying the service. OGC API features is a web API that simplifies the use of data in appropriate web development environments. The API includes the following collection: Mean element content maps

This map contains rock type data and faults for Tennessee. The data was downloaded from the USGS Mineral Resource Database. Click on a layer for details on the rock type and the geologic age. Use the tools at the top of the window to change the base map and measure on the map. Use the Contents section on the left to turn on/off layers, change transparency, and change how the map is symbolized.

The Digital Geologic-GIS Map of San Miguel Island, California 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 (smis_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 (smis_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 (smis_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 (chis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (chis_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 (smis_geology_metadata_faq.pdf). Please read the chis_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: American Association of Petroleum Geologists. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (smis_geology_metadata.txt or smis_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).