Diazo copy of Hubbard Brook Major Vegetation Units Map. UTM coordinate system shown. The vegetation unit boundaries were manually digitized. Data distributed as shapefile in Coordinate system EPSG:26919 - NAD83 / UTM zone 19N

UTM Zones within State of Iowa. This data has been modified by Iowa DOT and may not reflect actual boundary.

This dataset contains data used to test the protocol for high-resolution mapping and monitoring of recreational impacts in protected natural areas (PNAs) using unmanned aerial vehicle (UAV) surveys, Structure-from-Motion (SfM) data processing and geographic information systems (GIS) analysis to derive spatially coherent information about trail conditions (Tomczyk et al., 2023). Dataset includes the following folders:

Cocora_raster_data (~3GB) and Vinicunca_raster_data (~32GB) - a very high-resolution (cm-scale) dataset derived from UAV-generated images. Data covers selected recreational trails in Colombia (Valle de Cocora) and Peru (Vinicunca). UAV-captured images were processed using the structure-from-motion approach in Agisoft Metashape software. Data are available as GeoTIFF files in the UTM projected coordinate system (UTM 18N for Colombia, UTM 19S for Peru). Individual files are named as follows [location]_[year]_[product]_[raster cell size].tif, where:

[location] is the place of data collection (e.g., Cocora, Vinicucna)

[year] is the year of data collection (e.g., 2023)

[product] is the tape of files: DEM = digital elevation model; ortho = orthomosaic; hs = hillshade

[raster cell size] is the dimension of individual raster cell in mm (e.g., 15mm)

Cocora_vector_data. and Vinicunca_vector_data – mapping of trail tread and conditions in GIS environment (ArcPro). Data are available as shp files. Data are in the UTM projected coordinate system (UTM 18N for Colombia, UTM 19S for Peru).

Structure-from-motio n processing was performed in Agisoft Metashape (https://www.agisoft.com/, Agisoft, 2023). Mapping was performed in ArcGIS Pro (https://www.esri.com/en-us/arcgis/about-arcgis/overview, Esri, 2022). Data can be used in any GIS software, including commercial (e.g. ArcGIS) or open source (e.g. QGIS).

Tomczyk, A. M., Ewertowski, M. W., Creany, N., Monz, C. A., & Ancin-Murguzur, F. J. (2023). The application of unmanned aerial vehicle (UAV) surveys and GIS to the analysis and monitoring of recreational trail conditions. International Journal of Applied Earth Observations and Geoinformation, 103474. doi: https://doi.org/10.1016/j.jag.2023.103474

DescriptionThe Structures layer is used primarily to reference structural features for GIS-based highway project planning. It is also used for reference within various GIS applications, such as OTIS.

    Last Update
    2023


    Update FrequencyAs needed


    Data Owner
    CDOT Staff Bridge


    Data Contact
    Division of Transportation Development - GIS Support Unit


    Collection Method



    Projection
    NAD83 / UTM zone 13N


    Coverage Area
    Statewide


    Temporal



    Disclaimer/Limitations
    There are no restrictions and legal prerequisites for using the data set. The State of Colorado assumes no liability relating to the completeness, correctness, or fitness for use of this data.

Summary

This feature class documents the fire history on CMR from 1964 - present. This is 1 of 2 feature classes, a polygon and a point. This data has a variety of different origins which leads to differing quality of data. Within the polygon feature class, this contains perimeters that were mapped using a GPS, hand digitized, on-screen digitized, and buffered circles to the estimated acreage. These 2 files should be kept together. Within the point feature class, fires with only a location of latitude/longitude, UTM coordinate, TRS and no estimated acreage were mapped using a point location. GPS started being used in 1992 when the technology became available. Records from FMIS (Fire Management Information System) were reviewed and compared to refuge records. Polygon data in FMIS only occurs from 2012 to current and many acreage estimates did not match. This dataset includes ALL fires no matter the size.

This feature class documents the fire history on CMR from 1964 - present. This is 1 of 2 feature classes, a polygon and a point. This data has a variety of different origins which leads to differing quality of data. Within the polygon feature class, this contains perimeters that were mapped using a GPS, hand digitized, on-screen digitized, and buffered circles to the estimated acreage. These 2 files should be kept together. Within the point feature class, fires with only a location of latitude/longitude, UTM coordinate, TRS and no estimated acreage were mapped using a point location. GPS started being used in 1992 when the technology became available. Data origins include: Data origins include: 1) GPS Polygon-data (Best), 2) GPS Lat/Long or UTM, 3)TRS QS, 4)TRS Point, 6)Hand digitized from topo map, 7) Circle buffer, 8)Screen digitized, 9) FMIS Lat/Long. Started compiling fire history of CMR in 2007. This has been a 10 year process.FMIS doesn't include fires polygons that are less than 10 acres. This dataset has been sent to FMIS for FMIS records to be updated with correct information. The spreadsheet contains 10-15 records without spatial information and weren't included in either feature class. Fire information from 1964 - 1980 came from records Larry Eichhorn, BLM, provided to CMR staff. Mike Granger, CMR Fire Management Officer, tracked fires on an 11x17 legal pad and all this information was brought into Excel and ArcGIS. Frequently, other information about the fires were missing which made it difficult to back track and fill in missing data. Time was spent verifiying locations that were occasionally recorded incorrectly (DMS vs DD) and converting TRS into Lat/Long and/or UTM. CMR is divided into 2 different UTM zones, zone 12 and zone 13. This occasionally caused errors in projecting. Naming conventions caused confusion. Fires are frequently names by location and there are several "Soda Creek", "Rock Creek", etc fires. Fire numbers were occasionally missing or incorrect. Fires on BLM were included if they were "Assists". Also, fires on satellite refuges and the district were also included. Acreages from GIS were compared to FMIS acres. Please see documentation in ServCat (URL) to see how these were handled.

UTM Market Outlook

According to our latest research, the UTM (Universal Transverse Mercator) market size reached USD 1.42 billion globally in 2024. The market is projected to grow at a robust CAGR of 11.8% from 2025 to 2033, reaching an estimated value of USD 3.87 billion by the end of the forecast period. This significant growth is driven by the increasing adoption of advanced geospatial technologies across industries, expanding applications in defense and commercial sectors, and the ongoing digital transformation in navigation and mapping solutions.

One of the primary growth factors propelling the UTM market is the escalating demand for accurate, real-time geospatial data across diverse applications such as military navigation, land surveying, and commercial mapping. As industries increasingly rely on precise location-based services for strategic decision-making, the need for robust coordinate systems like UTM becomes paramount. The proliferation of smart cities, infrastructure development, and autonomous systems further amplifies the requirement for reliable mapping and navigation tools. Additionally, the integration of UTM with emerging technologies such as Geographic Information Systems (GIS), satellite imaging, and Internet of Things (IoT) devices is enhancing the accuracy and usability of geospatial information, thereby fueling market expansion.

Another significant driver is the growing emphasis on national security and defense modernization programs globally. Military and defense organizations are leveraging UTM systems to optimize mission planning, troop movement, and asset tracking in complex terrains. The precision offered by UTM coordinates is indispensable for defense operations, particularly in regions with challenging topographies. Furthermore, government agencies are increasingly investing in advanced mapping and surveying solutions to support disaster management, resource allocation, and infrastructure planning. The synergy between commercial and governmental initiatives is fostering innovation and broadening the scope of UTM applications beyond traditional boundaries.

The rapid shift towards cloud-based deployment and service-oriented architectures is also catalyzing the growth of the UTM market. Enterprises are migrating from on-premises solutions to cloud platforms to benefit from enhanced scalability, remote accessibility, and cost-effectiveness. This transition is particularly evident among small and medium-sized enterprises (SMEs) and startups, which are leveraging cloud-based UTM solutions to streamline operations and reduce upfront investments. The growing adoption of Software-as-a-Service (SaaS) models is enabling organizations to access advanced mapping tools and analytics without the need for extensive infrastructure, thereby democratizing the use of geospatial technologies and expanding the UTM user base.

Regionally, North America leads the UTM market, driven by substantial investments in defense, aerospace, and geospatial technologies. The Asia Pacific region is emerging as a high-growth market, fueled by rapid urbanization, infrastructure development, and increasing adoption of digital mapping solutions. Europe also holds a significant share, supported by robust governmental initiatives and a mature industrial sector. Latin America and the Middle East & Africa are witnessing steady growth, with rising investments in land management, maritime navigation, and resource exploration. The global landscape is characterized by a dynamic interplay of technological advancements, regulatory frameworks, and cross-industry collaborations, shaping the future trajectory of the UTM market.

Component Analysis

The UTM market is segmented by component into hardware, software, and services, each playing a vital role in the overall ecosystem. Hardware components, including GPS receivers, surveying instruments, and navigation devices, form the backbone of UTM-based solutions. The demand for advanced hardware is driven by the need for high-precision data collection and real-time location tracking across various sectors. Innovations in sensor technology, miniaturization, and integration with wireless networks are enhancing the capabilities of UTM hardware, making them more versatile and reliable for field operations. The rise of unmanned systems, drones, and autonomous vehicles is further boosting the demand for robust UTM hardware to ensure seamless navigation and mapping.

These DEMs were produced from digitized contours at a cell resolution of 100 meters. Vector contours of the area were used as input to a software package that interpolates between contours to create a DEM representing the terrain surface. The vector contours had a contour interval of 25 feet. The data cover the BOREAS MSAs of the SSA and NSA and are given in a UTM map projection.

A digital raster graphic (DRG) is a scanned image of an U.S. Geological Survey (USGS) standard series topographic map, including all map collar information. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Universal Transverse Mercator projection. The horizontal positional accuracy and datum of the DRG matches the accuracy and datum of the source map. The map is scanned at a minimum resolution of 250 dots per inch.

DRG's are created by scanning published paper maps on high-resolution scanners. The raster image is georeferenced and fit to the UTM projection. Colors are standardized to remove scanner limitations and artifacts. The average data set size is about 6 megabytes in Tagged Image File Format (TIFF) with PackBits compression. DRG's can be easily combined with other digital cartographic products such as digital elevation models (DEM) and digital orthophoto quadrangles (DOQ).

DRG's are stored as rectified TIFF files in geoTIFF format. GeoTIFF is a relatively new TIFF image storage format that incorporates georeferencing information in the header. This allows software, such as ArcView, ARC/INFO, or EPPL7 to reference the image without an additional header or world file.

Within the Minnesota Department of Natural Resources Core GIS data set the DRG's have been processed to be in compliance with departmental data standards (UTM Extended Zone 15, NAD83 datum) and the map collar information has been removed to facilitate the display of the DRG's in a seamless fashion.

These DRG's were clipped and transformed to UTM Zone 15 using EPPL7 Raster GIS.

The Unpublished Digital Geologic-GIS Map of the Wickiup Canyon Quadrangle, Utah and Colorado is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (wicn_geology.gdb), a 10.1 ArcMap (.MXD) map document (wicn_geology.mxd), individual 10.1 layer (.LYR) files for each GIS data layer, an ancillary map information (.PDF) document (hove_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 (wicn_gis_readme.pdf). Please read the wicn_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O’Meara (stephanie.omeara@colostate.edu; see contact information below). Presently, a GRI Google Earth KMZ/KML product doesn't exist for this map. 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: National Park Service Geologic Resources Inventory and 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 (wicn_metadata_faq.html; available at http://nrdata.nps.gov/geology/gri_data/gis/hove/wicn_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 (127 meters or 416.7 feet for structure contour lines) 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 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. 2.3. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 12N. The data is within the area of interest of Hovenweep National Monument.

This dataset was developed by Chris Stermer (CDFG - RAP Program). No original metadata were located, but the following is an abstract from a document describing the product: We conducted field surveys for Willow Flycatchers (Empidonax traillii brewsterii) in 1997 and 1998, from June 15 through July 31, within the McCloud Flats region of Siskiyou County, California. A Geographic Information System (GIS) was used to predict potentially suitable habitat to survey prior to field visits. We used a GIS to model willow flycatcher habitat within our study area from remotely sensed data and digitally mapped data layers. Spatially explicit data used in our predictions included a vegetation map (a vegetation classification derived from Landsat 5 Thematic Mapper imagery), a Digital Elevation Model (DEM), a slope gradient model, and a stream layer. Seventy-seven Willow Flycatcher territories were found during our surveys. Nine of the territories were located within a large montane meadow complex (Bigelow Meadows) known to have Willow Flycatchers, the remaining territories (68) were predicted using a GIS pattern analysis. We characterized vegetation within .07 ha circular plots centered on sixty-six territories located in 1997. Riparian thickets > 2 m in height was the most abundant vegetation type, making up 53% of the vegetation within the plots. Twenty-one percent of the vegetation was a composite of live green grasses and forbs. A pattern based habitat predictability model was developed using the 66 territories located in the 1997 field season as image training sites. The model integrated two environmental variables found to have predictive capability: (1) composition of vegetation classes, and; (2) slope gradient. An accuracy assessment indicated the model was 94% correct when predicting suitable habitat greater than 6 ac. We concluded that Landsat Thematic Mapper imagery, when applied in conjunction with other landscape data, was an effective technique to identify suitable Willow Flycatcher habitat for our study area. Currently, this technique is being used by the California Department of Fish and Game to identify habitat throughout Northern California. This dataset was modified on May 17, 2005 by Eric Haney of CDFG - Information Services branch. Modifications included addition of a Site_ID Field, and fields representing UTM Northing and Easting coordinates (using NAD83 Datum). These fields were added to assist in an effort to field validate the dataset. Note that not all UTM coordinates are located within habitat polygons. Depending on the irregular shape of the polygons, some of the utm coordinates are located outside the boundaries. These coordinates are only to be used for coarse navigational purposes. While there is no publication date planned, Region 1 staff are working to validate the model results.

DescriptionPolyline (linear) geographic features representing public roads under local jurisdiction that are functionally classified as arterials or collectors. Last Update2024Update FrequencyAs neededData OwnerDivision of Transportation DevelopmentData ContactGIS Support UnitCollection Method ProjectionNAD83 / UTM zone 13NCoverage AreaStatewideTemporal Disclaimer/LimitationsThere are no restrictions and legal prerequisites for using the data set. The State of Colorado assumes no liability relating to the completeness, correctness, or fitness for use of this data.

The Digital Geomorphic Map of Assateague Island National Seashore, Maryland and Virginia is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) 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 sections(s) of this metadata record (asis_metadata.txt; available at http://nrdata.nps.gov/asis/nrdata/geology/gis/asis_metadata.xml). 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 is available as a 9.3 personal geodatabase (asis_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 18N. That data is within the area of interest of Assateague Island National Seashore.

The Unpublished Digital Geologic-GIS Map of the Long Lake Quadrangle, Mississippi and Louisiana is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (lola_geology.gdb), a 10.1 ArcMap (.MXD) map document (lola_geology.mxd), individual 10.1 layer (.LYR) files for each GIS data layer, an ancillary map information (.PDF) document (vick_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 (lola_gis_readme.pdf). Please read the lola_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O’Meara (stephanie.omeara@colostate.edu; see contact information below). Presently, a GRI Google Earth KMZ/KML product doesn't exist for this map. 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: Mississippi Department of Environmental Quality, Office of Geology. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (lola_metadata_faq.html; available at http://nrdata.nps.gov/geology/gri_data/gis/vick/lola_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 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. 2.3. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 15N. The data is within the area of interest of Vicksburg National Military Park.

The Unpublished Digital Geologic-GIS Map of the Jamestown Quadrangle, Alabama and Georgia is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (jmst_geology.gdb), a 10.1 ArcMap (.mxd) map document (jmst_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (liri_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 (.pdf) formats, and a GIS readme file (liri_geology_gis_readme.pdf). Please read the liri_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@colostate.edu; see contact information below). Presently, a GRI Google Earth KMZ/KML product doesn't exist for this map. 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: Geological Survey of Alabama and Auburn University, Department of Geosciences. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (jmst_geology_metadata.txt or jmst_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 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. 2.3. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 16N. The data is within the area of interest of Little River Canyon National Preserve.

The Unpublished Digital Geologic-GIS Map of the North Unit of Theodore Roosevelt National Park, North Dakota is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (thrn_geology.gdb), a 10.1 ArcMap (.mxd) map document (thrn_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (thro_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 (.pdf) formats, and a GIS readme file (thro_geology_gis_readme.pdf). Please read the thro_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@colostate.edu; see contact information below). Presently, a GRI Google Earth KMZ/KML product doesn't exist for this map. 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: North Dakota 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 (thrn_geology_metadata.txt or thrn_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 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. 2.3. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 13N. The data is within the area of interest of Theodore Roosevelt National Park.

The Unpublished Digital Geologic-GIS Map of Moores Creek National Battlefield, North Carolina is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (mocr_geology.gdb), a 10.1 ArcMap (.mxd) map document (mocr_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (mocr_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 (.pdf) formats, and a GIS readme file (mocr_geology_gis_readme.pdf). Please read the mocr_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@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 (mocr_geology_metadata.txt or mocr_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 1:250,000 and United States National Map Accuracy Standards features are within (horizontally) 127 meters or 416.7 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. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm). The GIS data projection is NAD83, UTM Zone 17N, 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 Moores Creek National Battlefield.

The Unpublished Digital Geologic-GIS Map of Great Sand Dunes National Park, Colorado is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (grsa_geology.gdb), a 10.1 ArcMap (.mxd) map document (grsa_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (grsa_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 (.pdf) formats, and a GIS readme file (grsa_geology_gis_readme.pdf). Please read the grsa_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@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 (grsa_geology_metadata.txt or grsa_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 1:35,000 and United States National Map Accuracy Standards features are within (horizontally) 17.8 meters or 58.3 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 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: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 13N, 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 Great Sand Dunes National Park and Preserve.

The Unpublished Digital Geomorphic Map of the Shackleford Banks, North Carolina is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (shkb_geology.gdb), a 10.1 ArcMap (.MXD) map document (shkb_geology.mxd), individual 10.1 layer (.LYR) files for each GIS data layer, an ancillary map information (.PDF) document (shkb_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 (calo_gis_readme.pdf). Please read the calo_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 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: East Carolina University. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (shkb_metadata_faq.html; available at http://nrdata.nps.gov/geology/gri_data/gis/calo/shkb_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 1:10,000 and United States National Map Accuracy Standards features are within (horizontally) 5.1 meters or 16.7 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. 2.2. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 18N, 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 Cape Lookout National Seashore.

The Unpublished Digital Geologic-GIS Map of Mount Desert Island and Vicinity, Acadia National Park, Maine is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (acad_geology.gdb), a 10.1 ArcMap (.mxd) map document (acad_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (acad_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 (.pdf) formats, and a GIS readme file (acad_geology_gis_readme.pdf). Please read the acad_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@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: Maine 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 (acad_geology_metadata.txt or acad_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 1:50,000 and United States National Map Accuracy Standards features are within (horizontally) 25.4 meters or 83.3 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 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 GIS data projection is NAD83, UTM Zone 19N, 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 Acadia National Park.

The Unpublished Digital Geologic-GIS Map of Navajo National Monument and Vicinity, Arizona is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (nava_geology.gdb), a 10.1 ArcMap (.mxd) map document (nava_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (nava_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 (.pdf) formats, and a GIS readme file (nava_geology_gis_readme.pdf). Please read the nava_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@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 (nava_geology_metadata.txt or nava_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 1:125,000 and United States National Map Accuracy Standards features are within (horizontally) 63.5 meters or 208.3 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 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 GIS data projection is NAD83, UTM Zone 12N, 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 Navajo National Monument.