100+ datasets found
  1. a

    Cadastral - All Features (GDB)

    • hub.arcgis.com
    Updated Oct 29, 2020
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    City of Coquitlam (2020). Cadastral - All Features (GDB) [Dataset]. https://hub.arcgis.com/documents/c39c66c4aafa4d97aacc90b886bd41bc
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    Dataset updated
    Oct 29, 2020
    Dataset authored and provided by
    City of Coquitlam
    Description

    Complete Cadastral dataset in file geodatabase format. Consume this dataset if you wish to download the entire Cadastral dataset at once.

  2. g

    GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb) | gimi9.com

    • gimi9.com
    Updated Mar 13, 2019
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    (2019). GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb) | gimi9.com [Dataset]. https://gimi9.com/dataset/au_96ebf889-f726-4967-9964-714fb57d679b/
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    Dataset updated
    Mar 13, 2019
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Abstract This dataset was derived by the Bioregional Assessment Programme from the GEODATA TOPO 250K Series 3 dataset (GUID: a0650f18-518a-4b99-a553-44f82f28bb5f). The source dataset is identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. This dataset is a copy of the original Geodata Topo 250k Series 3 data, converted from Personal (Microsoft Access) Databases, to ESRI File Geodatabases. This was done to ensure .mdb lock files would not restrict map makers from using the topographic data in their cartographic products. The data and folders are structured the same as the original dataset. ## Dataset History A new file geodatabase schema was created in the same structure as the original .mdb data (including database and feature dataset names and projections). Feature Classes were then copied from the .mdb format to the .gdb format, using ArcCatalog 10.0. ## Dataset Citation Bioregional Assessment Programme (2014) GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb). Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/96ebf889-f726-4967-9964-714fb57d679b. ## Dataset Ancestors * Derived From GEODATA TOPO 250K Series 3

  3. a

    Transportation Network (File Geodatabase .gdb)

    • data-langleycity.opendata.arcgis.com
    Updated Feb 19, 2021
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    LangleyCityGIS (2021). Transportation Network (File Geodatabase .gdb) [Dataset]. https://data-langleycity.opendata.arcgis.com/datasets/4bba119c2e9042d683cc9378fb1e836e
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    Dataset updated
    Feb 19, 2021
    Dataset authored and provided by
    LangleyCityGIS
    License

    https://langleycity.ca/open-data-licensehttps://langleycity.ca/open-data-license

    Description

    This File Geodatabase download, (last updated September 25, 2024), contains all the feature classes within the Transportation Network. The City of Langley has compiled all the Transportation Network feature classes into one file geodatabase. File Geodatabase Feature Classes:Bicycle RoutesBridgesDisaster Response RoutesMediansRailwayRoadsSidewalksStreet Names

  4. d

    Parcelization (File Geodatabase)

    • catalog.data.gov
    • data.ca.gov
    • +2more
    Updated Jul 24, 2025
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    California Energy Commission (2025). Parcelization (File Geodatabase) [Dataset]. https://catalog.data.gov/dataset/parcelization-file-geodatabase-0bf35
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    Dataset updated
    Jul 24, 2025
    Dataset provided by
    California Energy Commission
    Description

    DescriptionThis dataset is available for download from: Parcelization (File Geodatabase)Parcelization, a measure of size and density of parcels in a localized area, is a development feasibility factor that is used in evaluating substations’ ability to support new utility-scale resources in long-term energy planning. A statewide dataset of parcel boundaries are used to develop this index. The parcels are converted into a 90-meter raster, containing values of a unique identifier reflective of Parcel APN. A focal statistics tool is used to count the number of unique parcels within a 0.5 mile radius of each parcel. This output is provided here and is an intermediate output to the final parcelization map. Users who wish to use this information to produce the final map should overlay parcel boundary data and extract the mean raster value within each parcel. The map is limited to the area considered with solar technical resource potential after a minimum set of land-use screens (referred to as the Base Exclusions) has been applied. More information on the methods developing this dataset as well as the main use of this dataset in state electric system planning processes can be found in a recent CEC staff report and workshops supporting the resource-to-busbar mapping methodology for the 2024-2025 Transmission Planning Process.

  5. Wetlands (File Geodatabase)

    • data.cnra.ca.gov
    • data.ca.gov
    • +2more
    html
    Updated Dec 20, 2024
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    California Energy Commission (2024). Wetlands (File Geodatabase) [Dataset]. https://data.cnra.ca.gov/dataset/wetlands-file-geodatabase
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    htmlAvailable download formats
    Dataset updated
    Dec 20, 2024
    Dataset authored and provided by
    California Energy Commissionhttp://www.energy.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Wetlands in California are protected by several federal and state laws, regulations, and policies. This layer was extracted from the broader vegetation raster from the CA Nature project which was recently enhanced to include a more comprehensive definition of wetland. This wetlands dataset is used as an exclusion as part of the biological planning priorities in the CEC 2023 Land-Use Screens.

    This layer is featured in the CEC 2023 Land-Use Screens for Electric System Planning data viewer.

    For more information about this layer and its use in electric system planning, please refer to the Land Use Screens Staff Report in the CEC Energy Planning Library.

  6. a

    Parcels File Geodatabase

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Oct 2, 2015
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    Story County, Iowa GIS (2015). Parcels File Geodatabase [Dataset]. https://hub.arcgis.com/datasets/172bf4ac9e8d4db4942cbbabe8a52230
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    Dataset updated
    Oct 2, 2015
    Dataset authored and provided by
    Story County, Iowa GIS
    Area covered
    Description

    Story County Parcels layer

  7. Primary model outputs (packaged datasets) - A landscape connectivity...

    • catalog.data.gov
    Updated Nov 14, 2025
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    U.S. Fish and Wildlife Service (2025). Primary model outputs (packaged datasets) - A landscape connectivity analysis for the coastal marten (Martes caurina humboldtensis) [Dataset]. https://catalog.data.gov/dataset/primary-model-outputs-packaged-datasets-a-landscape-connectivity-analysis-for-the-coastal-
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    Dataset updated
    Nov 14, 2025
    Dataset provided by
    U.S. Fish and Wildlife Servicehttp://www.fws.gov/
    Description

    This packaged data collection contains all of the outputs from our primary model, including the following data layers: Habitat Cores (vector polygons) Least-cost Paths (vector lines) Least-cost Corridors (raster) Least-cost Corridors (vector polygon interpretation) Modeling Extent (vector polygon) Please refer to the embedded spatial metadata and the information in our full report for details on the development of these data layers. Packaged data are available in two formats: Geodatabase (.gdb): A related set of file geodatabase rasters and feature classes, packaged in an ESRI file geodatabase. ArcGIS Pro Map Package (.mpkx): The same data included in the geodatabase, presented as fully-symbolized layers in a map. Note that you must have ArcGIS Pro version 2.0 or greater to view. See Cross-References for links to individual datasets, which can be downloaded in shapefile (.shp) or raster GeoTIFF (.tif) formats.

  8. g

    Building Footprints (File Geodatabase Format)

    • gimi9.com
    • data.sfgov.org
    • +3more
    Updated May 2, 2017
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    (2017). Building Footprints (File Geodatabase Format) [Dataset]. https://gimi9.com/dataset/data-gov_building-footprints-file-geodatabase-format/
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    Dataset updated
    May 2, 2017
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    Note: please go to https://data.sfgov.org/d/ynuv-fyni to access the same data in additional open formats. These footprint extents are collapsed from an earlier 3D building model provided by Pictometry of 2010, and have been refined from a version of building masses publicly available on the open data portal for over two years. The building masses were manually split with reference to parcel lines, but using vertices from the building mass wherever possible. These split footprints correspond closely to individual structures even where there are common walls; the goal of the splitting process was to divide the building mass wherever there was likely to be a firewall.An arbitrary identifier was assigned based on a descending sort of building area for 177,023 footprints. The centroid of each footprint was used to join a property identifier from a draft of the San Francisco Enterprise GIS Program's cartographic base, which provides continuous coverage with distinct right-of-way areas as well as selected nearby parcels from adjacent counties. See accompanying document SF_BldgFoot_2017-05_description.pdf for more on methodology and motivation https://data.sfgov.org/d/ynuv-fyni/ about

  9. B

    Residential Schools Locations Dataset (Geodatabase)

    • borealisdata.ca
    • search.dataone.org
    Updated May 31, 2019
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    Rosa Orlandini (2019). Residential Schools Locations Dataset (Geodatabase) [Dataset]. http://doi.org/10.5683/SP2/JFQ1SZ
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 31, 2019
    Dataset provided by
    Borealis
    Authors
    Rosa Orlandini
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1863 - Jun 30, 1998
    Area covered
    Canada
    Description

    The Residential Schools Locations Dataset in Geodatabase format (IRS_Locations.gbd) contains a feature layer "IRS_Locations" that contains the locations (latitude and longitude) of Residential Schools and student hostels operated by the federal government in Canada. All the residential schools and hostels that are listed in the Residential Schools Settlement Agreement are included in this dataset, as well as several Industrial schools and residential schools that were not part of the IRRSA. This version of the dataset doesn’t include the five schools under the Newfoundland and Labrador Residential Schools Settlement Agreement. The original school location data was created by the Truth and Reconciliation Commission, and was provided to the researcher (Rosa Orlandini) by the National Centre for Truth and Reconciliation in April 2017. The dataset was created by Rosa Orlandini, and builds upon and enhances the previous work of the Truth and Reconcilation Commission, Morgan Hite (creator of the Atlas of Indian Residential Schools in Canada that was produced for the Tk'emlups First Nation and Justice for Day Scholar's Initiative, and Stephanie Pyne (project lead for the Residential Schools Interactive Map). Each individual school location in this dataset is attributed either to RSIM, Morgan Hite, NCTR or Rosa Orlandini. Many schools/hostels had several locations throughout the history of the institution. If the school/hostel moved from its’ original location to another property, then the school is considered to have two unique locations in this dataset,the original location and the new location. For example, Lejac Indian Residential School had two locations while it was operating, Stuart Lake and Fraser Lake. If a new school building was constructed on the same property as the original school building, it isn't considered to be a new location, as is the case of Girouard Indian Residential School.When the precise location is known, the coordinates of the main building are provided, and when the precise location of the building isn’t known, an approximate location is provided. For each residential school institution location, the following information is provided: official names, alternative name, dates of operation, religious affiliation, latitude and longitude coordinates, community location, Indigenous community name, contributor (of the location coordinates), school/institution photo (when available), location point precision, type of school (hostel or residential school) and list of references used to determine the location of the main buildings or sites. Access Instructions: there are 47 files in this data package. Please download the entire data package by selecting all the 47 files and click on download. Two files will be downloaded, IRS_Locations.gbd.zip and IRS_LocFields.csv. Uncompress the IRS_Locations.gbd.zip. Use QGIS, ArcGIS Pro, and ArcMap to open the feature layer IRS_Locations that is contained within the IRS_Locations.gbd data package. The feature layer is in WGS 1984 coordinate system. There is also detailed file level metadata included in this feature layer file. The IRS_locations.csv provides the full description of the fields and codes used in this dataset.

  10. a

    Water Utility - All Features (GDB)

    • hub.arcgis.com
    Updated Aug 14, 2020
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    City of Coquitlam (2020). Water Utility - All Features (GDB) [Dataset]. https://hub.arcgis.com/documents/e6d025f534e34ab19743fc7f609b20be
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    Dataset updated
    Aug 14, 2020
    Dataset authored and provided by
    City of Coquitlam
    Description

    Complete Water Utility Network in file geodatabase format. Consume this dataset if you wish to download the entire Water Utility network dataset at once.

  11. l

    Contour Lines File Geodatabase (2007)

    • maps.leegov.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Mar 7, 2025
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    Lee County Florida GIS (2025). Contour Lines File Geodatabase (2007) [Dataset]. https://maps.leegov.com/datasets/b6e9937f903b4a9cab82c5d6955905c9
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    Dataset updated
    Mar 7, 2025
    Dataset authored and provided by
    Lee County Florida GIS
    Area covered
    Description

    One-foot and two-foot contours derived from LiDAR terrain model. The DTM was developed to support the Florida Division of Emergency Management (FDEM) development and maintenance of Regional Evacuation Studies (Study), which include vulnerability assessments and assist disaster response personnel in understanding threats to Florida's citizens and visitors. Breaklines improve the digital elevation model in areas where the point density is insufficient.This data set is one component of a digital terrain model (DTM) for the Florida Division of Emergency Management's (FDEM) Project Management and Technical Services for Mapping within Coastal Florida (Contract 07-HS-34-14-00-22-469), encompassing the entire coastline of Florida. The dataset is comprised of mass points, 2-D and 3-D breakline features, 1-foot and 2-foot contours, ground control, vertical test points, and a footprint of the data set, in the ESRI ArcGIS File Geodatabase format. In accordance with the Baseline Specifications 1.2, the following breakline features are contained within the database: closed water bodies (lakes, reservoirs, etc) as 2-D or 3-D polygons; linear hydrographic features (streams, shorelines, canals, swales, embankments, etc) as 3-D breaklines; coastal shorelines as 2-D or 3-D linear features; edge of pavement road features as 3-D breaklines; soft features (ridges, valleys, etc.) as 3-D breaklines; low confidence areas as 2-D polygons; island features as 2-D or 3-D polygons; overpasses and bridges as 3-D breaklines. Contours were generated from a gridded DEM: 2-foot contours meet National Map Accuracy Standards, with 1-foot contours for visualization purposes. The LiDAR masspoints are delivered in the LAS file format based on the FDEM's 5,000' by 5,000' grid. Breakline features were captured to develop a hydrologically correct DTM. Bare earth LiDAR masspoint data display a vertical accuracy of at least 0.3-feet root mean square error (RMSE) in open unobscured areas.

  12. d

    Previous mineral-resource assessment data compilation - geodatabases with...

    • catalog.data.gov
    • data.usgs.gov
    • +2more
    Updated Oct 2, 2025
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    U.S. Geological Survey (2025). Previous mineral-resource assessment data compilation - geodatabases with raster mosaic datasets [Dataset]. https://catalog.data.gov/dataset/previous-mineral-resource-assessment-data-compilation-geodatabases-with-raster-mosaic-data
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    Dataset updated
    Oct 2, 2025
    Dataset provided by
    U.S. Geological Survey
    Description

    This zip file contains geodatabases with raster mosaic datasets. The raster mosaic datasets consist of georeferenced tiff images of mineral potential maps, their associated metadata, and descriptive information about the images. These images are duplicates of the images found in the georeferenced tiff images zip file. There are four geodatabases containing the raster mosaic datasets, one for each of the four SaMiRA report areas: North-Central Montana; North-Central Idaho; Southwestern and South-Central Wyoming and Bear River Watershed; and Nevada Borderlands. The georeferenced images were clipped to the extent of the map and all explanatory text, gathered from map explanations or report text was imported into the raster mosaic dataset database as ‘Footprint’ layer attributes. The data compiled into the 'Footprint' layer tables contains the figure caption from the original map, online linkage to the source report when available, and information on the assessed commodities according to the legal definition of mineral resources—metallic, non-metallic, leasable non-fuel, leasable fuel, geothermal, paleontological, and saleable. To use the raster mosaic datasets in ArcMap, click on “add data”, double click on the [filename].gdb, and add the item titled [filename]_raster_mosaic. This will add all of the images within the geodatabase as part of the raster mosaic dataset. Once added to ArcMap, the raster mosaic dataset appears as a group of three layers under the mosaic dataset. The first item in the group is the ‘Boundary’, which contains a single polygon representing the extent of all images in the dataset. The second item is the ‘Footprint’, which contains polygons representing the extent of each individual image in the dataset. The ‘Footprint’ layer also contains the attribute table data associated with each of the images. The third item is the ‘Image’ layer and contains the images in the dataset. The images are overlapping and must be selected and locked, or queried in order to be viewed one at a time. Images can be selected from the attribute table, or can be selected using the direct select tool. When using the direct select tool, you will need to deselect the ‘overviews’ after clicking on an image or group of images. To do this, right click on the ‘Footprint’ layer and hover over ‘Selection’, then click ‘Reselect Only Primary Rasters’. To lock a selected image after selecting it, right-click on the ‘Footprint’ layer in the table of contents window and hover over ‘Selection’, then click ‘Lock To Selected Rasters’. Another way to view a single image is to run a definition query on the image. This is done by right clicking on the raster mosaic in the table of contents and opening the layer properties box. Then click on the ‘Definition Query’ tab and create a query for the desired image.

  13. a

    Post Offices (Places of Interest) (File Geodatabase)

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Apr 4, 2023
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    Montgomery Maps (2023). Post Offices (Places of Interest) (File Geodatabase) [Dataset]. https://hub.arcgis.com/datasets/54511e1898a149f3a5f519effee8f34d
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    Dataset updated
    Apr 4, 2023
    Dataset authored and provided by
    Montgomery Maps
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    This dataset includes post offices located within Montgomery County. It was developed and is maintained by TEBS-GIS. This dataset satisfies County basemap accuracy requirements (1:2400) and is included in the Places of Interest Guide. This data is used both by Government and the public. The Places of Interest Guide can be used to find a Place of Interest within Montgomery County, Maryland by address, by title, by place name or city, or by category. Once you've located the place of interest, then you can generate travel directions, time estimates, maps and distances.

  14. d

    Geodatabase of Toolbox Geospatial Output Files for Difficult Run, VA

    • datasets.ai
    • data.usgs.gov
    • +1more
    55
    Updated Jun 1, 2023
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    Department of the Interior (2023). Geodatabase of Toolbox Geospatial Output Files for Difficult Run, VA [Dataset]. https://datasets.ai/datasets/geodatabase-of-toolbox-geospatial-output-files-for-difficult-run-va
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    55Available download formats
    Dataset updated
    Jun 1, 2023
    Dataset authored and provided by
    Department of the Interior
    Area covered
    Virginia, Difficult Run River
    Description

    Geodatabase of outputs generated from the hydrologically conidtioned DEM and the USGS Stream Channel and Floodplain Metric Toolbox.

  15. u

    Arc/INFO Interchange File

    • gstore.unm.edu
    zip
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    Earth Data Analysis Center, Arc/INFO Interchange File [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/75c8b148-4f10-450a-aa2c-40cef9e948d9/metadata/FGDC-STD-001-1998.html
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    zip(28)Available download formats
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Jan 28, 2008
    Area covered
    New Mexico, West Bounding Coordinate -110.67 East Bounding Coordinate -108.346 North Bounding Coordinate 36.207 South Bounding Coordinate 35.167
    Description

    This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

  16. d

    Data from: Bull Trout (Salvelinus confluentus) Telemetry and Associated...

    • search.dataone.org
    • data.usgs.gov
    • +3more
    Updated Apr 13, 2017
    + more versions
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    Dorene E. MacCoy; Zach Shephard; Joseph Benjamin; Dmitri Vidergar; Anthony Prisciandaro (2017). Bull Trout (Salvelinus confluentus) Telemetry and Associated Habitat Data Collected in a Geodatabase from the Upper Boise River, Southwestern Idaho [Dataset]. https://search.dataone.org/view/88cf653c-9173-4e7d-abe9-2d1a8acc4b34
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    Dataset updated
    Apr 13, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Dorene E. MacCoy; Zach Shephard; Joseph Benjamin; Dmitri Vidergar; Anthony Prisciandaro
    Time period covered
    Oct 1, 1997 - Oct 1, 2014
    Area covered
    Description

    Bull trout (Salvelinus confluentus), listed as threatened under the Endangered Species Act, are among the more thermally sensitive of coldwater species in North America. The Boise River upstream of Arrowrock Dam in southwestern Idaho (including Arrowrock Reservoir) provides habitat for one of the southernmost populations of bull trout. The presence of the species in Arrowrock Reservoir poses implications for dam and reservoir operations. From 2011 to 2014, the Bureau of Reclamation and the U.S. Geological Survey collected fish telemetry data to improve understanding of bull trout distribution and movement in Arrowrock Reservoir and in the upper Boise River tributaries. The U.S. Geological Survey compiled the telemetry (fish location) data, along with reservoir elevation, river discharge, precipitation, and water-quality data in a geodatabase. The geodatabase includes metadata compliant with Federal Geographic Data Committee content standards. Reclamation plans to incorporate the data in a decision-support tool for reservoir management.

  17. o

    Data from: Scarps

    • geohub.oregon.gov
    • data.oregon.gov
    • +3more
    Updated Apr 12, 2024
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    State of Oregon (2024). Scarps [Dataset]. https://geohub.oregon.gov/datasets/oregon-geo::scarps
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    Dataset updated
    Apr 12, 2024
    Dataset authored and provided by
    State of Oregon
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    SLIDO-4.5 is an Esri ArcGIS version 10.7 file geodatabase which can be downloaded here: https://www.oregon.gov/dogami/slido/Pages/data.aspx The geodatabase contains two feature datasets (a group of datasets within the geodatabase) containing six feature classes total, as well as two raster data sets, one individual table, and two individual feature classes. The original studies vary widely in scale, scope and focus which is reflected in the wide range of accuracy, detail, and completeness with which landslides are mapped. In the future, we propose a continuous update of SLIDO. These updates should take place: 1) each time DOGAMI publishes a new GIS dataset that contains landslide inventory or susceptibility data or 2) at the end of each winter season, a common time for landslide occurrences in Oregon, which will include recent historic landslide point data. In order to keep track of the updates, we will use a primary release number such as Release 4.0 along with a decimal number identifying the update such as 4.5.

  18. v

    National Hydrography Dataset v2.2.1 GDB (USGS) - Arizona

    • anrgeodata.vermont.gov
    • geodata-asu.hub.arcgis.com
    Updated Jun 16, 2020
    + more versions
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    Arizona State University (2020). National Hydrography Dataset v2.2.1 GDB (USGS) - Arizona [Dataset]. https://anrgeodata.vermont.gov/maps/c0e3706d6170483f87e1ab6a511d8bea
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    Dataset updated
    Jun 16, 2020
    Dataset authored and provided by
    Arizona State University
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.Download the National Hydrography Dataset file geodatabase v2.2.1.

  19. u

    ArcGIS Geodatabase files for Chinle Area, Parts of Apache and Navajo...

    • gstore.unm.edu
    zip
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    Earth Data Analysis Center, ArcGIS Geodatabase files for Chinle Area, Parts of Apache and Navajo Counties, Arizona and San Juan County, New Mexico [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/579e81d4-f213-428c-8d9a-efd8aea17b20/metadata/FGDC-STD-001-1998.html
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    zip(16)Available download formats
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Sep 16, 2011
    Area covered
    Arizona, West Bounding Coordinate -110.617 East Bounding Coordinate -108.988 North Bounding Coordinate 36.693 South Bounding Coordinate 35.802, New Mexico
    Description

    This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The partial data set includes a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

  20. Digital Bedrock Geologic-GIS Map of the Saint-Gaudens National Historical...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Nov 25, 2025
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    National Park Service (2025). Digital Bedrock Geologic-GIS Map of the Saint-Gaudens National Historical Park and Vicinity, New Hampshire (NPS, GRD, GRI, SAGA, SAGA_bedrock digital map) adapted from U.S. Geological Survey Scientific Investigations Maps by Walsh, Valley, Thompson, Ratcliffe, Proctor and Sicard (2020), and Walsh (2016) [Dataset]. https://catalog.data.gov/dataset/digital-bedrock-geologic-gis-map-of-the-saint-gaudens-national-historical-park-and-vicinit
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    Dataset updated
    Nov 25, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Description

    The Digital Bedrock Geologic-GIS Map of the Saint-Gaudens National Historical Park and Vicinity, New Hampshire 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 (saga_bedrock_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 (saga_bedrock_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 (saga_bedrock_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 (saga_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (saga_bedrock_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 (saga_bedrock_geology_metadata_faq.pdf). Please read the saga_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: 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 (saga_bedrock_geology_metadata.txt or saga_bedrock_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).

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City of Coquitlam (2020). Cadastral - All Features (GDB) [Dataset]. https://hub.arcgis.com/documents/c39c66c4aafa4d97aacc90b886bd41bc

Cadastral - All Features (GDB)

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Dataset updated
Oct 29, 2020
Dataset authored and provided by
City of Coquitlam
Description

Complete Cadastral dataset in file geodatabase format. Consume this dataset if you wish to download the entire Cadastral dataset at once.

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