100+ datasets found
  1. Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter...

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Nov 25, 2025
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    National Park Service (2025). Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida (NPS, GRD, GRI, GUIS, GUIS_geomorphology digital map) adapted from U.S. Geological Survey Open File Report maps by Morton and Rogers (2009) and Morton and Montgomery (2010) [Dataset]. https://catalog.data.gov/dataset/digital-geomorphic-gis-map-of-gulf-islands-national-seashore-5-meter-accuracy-and-1-foot-r
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    Dataset updated
    Nov 25, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Guisguis Port Sariaya, Quezon
    Description

    The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida 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 (guis_geomorphology.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 (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.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.) A GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.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 (guis_geomorphology_metadata_faq.pdf). Please read the guis_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 (guis_geomorphology_metadata.txt or guis_geomorphology_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 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 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, 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).

  2. d

    Addresses (Open Data)

    • catalog.data.gov
    • data-academy.tempe.gov
    • +11more
    Updated Nov 22, 2025
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    City of Tempe (2025). Addresses (Open Data) [Dataset]. https://catalog.data.gov/dataset/addresses-open-data
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    Dataset updated
    Nov 22, 2025
    Dataset provided by
    City of Tempe
    Description

    This dataset is a compilation of address point data for the City of Tempe. The dataset contains a point location, the official address (as defined by The Building Safety Division of Community Development) for all occupiable units and any other official addresses in the City. There are several additional attributes that may be populated for an address, but they may not be populated for every address. Contact: Lynn Flaaen-Hanna, Development Services Specialist Contact E-mail Link: Map that Lets You Explore and Export Address Data Data Source: The initial dataset was created by combining several datasets and then reviewing the information to remove duplicates and identify errors. This published dataset is the system of record for Tempe addresses going forward, with the address information being created and maintained by The Building Safety Division of Community Development.Data Source Type: ESRI ArcGIS Enterprise GeodatabasePreparation Method: N/APublish Frequency: WeeklyPublish Method: AutomaticData Dictionary

  3. Shoreline Types - R7 - CDFW [ds3115]

    • data.ca.gov
    • data.cnra.ca.gov
    • +5more
    Updated Jan 8, 2024
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    California Department of Fish and Wildlife (2024). Shoreline Types - R7 - CDFW [ds3115] [Dataset]. https://data.ca.gov/dataset/shoreline-types-r7-cdfw-ds3115
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    csv, zip, kml, arcgis geoservices rest api, geojson, htmlAvailable download formats
    Dataset updated
    Jan 8, 2024
    Dataset authored and provided by
    California Department of Fish and Wildlifehttps://wildlife.ca.gov/
    License

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

    Description

    This feature contains vector lines representing the shoreline and coastal habitats of California. Line segments are classified according to the Environmental Sensitivity Index (ESI) classification system and are a compilation of the ESI data from the most recent ESI atlas publications. The ESI data includes information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. This California dataset contains only the ESI shoreline data layer and is a merged set of individual ESI data sets to cover the entire California coast. For many parts of the California shoreline, the NOAA-ESI database lists several shoreline types present at a given location, described from landward to seaward. A simplified singular classification [Map_Class] was created to generalize the most dominant features of the multiple shore type attributes present in the raw data. More information can be found at the source citation at ESI Guidelines | response.restoration.noaa.gov Attributes: Line: Type of geographic feature (H: Hydrography, P: Pier, S: Shoreline) Most_sensitive: If multiple shoreline types appear in ESI classification, this field represents the highest value (most sensitive type); otherwise it is the same value as the ESI field. Shore_code: The ESI shoreline type. In many cases shorelines are ranked with multiple codes, such as "6B/3A" (listed landward to seaward). Source: Original year of ESI data. Esi_description: Concatenation of shore type descriptions (listed landward to seaward) Shoretype_1: Numeric classification for the first (most landward) ESI type. Shoretype_1_name: Physical description for the first ESI type. Shoretype_2: Numeric classification for the second ESI type. Shoretype_2_name: Physical description for the second ESI type Shoretype_3: Numeric classification for the third (most seaward) ESI type. Shoretype_3_name: Physical description for the third ESI type. Map_class: Generalized ESI shoreline type for simplified sym

  4. California Vegetation - WHR13 Types

    • data.ca.gov
    • data.cnra.ca.gov
    • +5more
    Updated Jul 25, 2025
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    CAL FIRE (2025). California Vegetation - WHR13 Types [Dataset]. https://data.ca.gov/dataset/california-vegetation-whr13-types
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    html, arcgis geoservices rest api, csv, kml, geojson, zipAvailable download formats
    Dataset updated
    Jul 25, 2025
    Dataset provided by
    California Department of Forestry and Fire Protectionhttp://calfire.ca.gov/
    Authors
    CAL FIRE
    License

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

    Area covered
    California
    Description
  5. BOEM BSEE Marine Cadastre Layers National Scale - OCS Oil & Gas Pipelines

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Nov 16, 2016
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    US Bureau of Ocean Energy Management (BOEM) (2016). BOEM BSEE Marine Cadastre Layers National Scale - OCS Oil & Gas Pipelines [Dataset]. https://koordinates.com/layer/15435-boem-bsee-marine-cadastre-layers-national-scale-ocs-oil-gas-pipelines/
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    dwg, kml, mapinfo tab, geopackage / sqlite, mapinfo mif, geodatabase, shapefile, csv, pdfAvailable download formats
    Dataset updated
    Nov 16, 2016
    Dataset provided by
    Bureau of Ocean Energy Managementhttp://www.boem.gov/
    Federal government of the United Stateshttp://www.usa.gov/
    Authors
    US Bureau of Ocean Energy Management (BOEM)
    Area covered
    Description

    This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

    © MarineCadastre.gov This layer is a component of BOEMRE Layers.

    This Map Service contains many of the primary data types created by both the Bureau of Ocean Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) within the Department of Interior (DOI) for the purpose of managing offshore federal real estate leases for oil, gas, minerals, renewable energy, sand and gravel. These data layers are being made available as REST mapping services for the purpose of web viewing and map overlay viewing in GIS systems. Due to re-projection issues which occur when converting multiple UTM zone data to a single national or regional projected space, and line type changes that occur when converting from UTM to geographic projections, these data layers should not be used for official or legal purposes. Only the original data found within BOEM/BSEE’s official internal database, federal register notices or official paper or pdf map products may be considered as the official information or mapping products used by BOEM or BSEE. A variety of data layers are represented within this REST service are described further below. These and other cadastre information the BOEM and BSEE produces are generated in accordance with 30 Code of Federal Regulations (CFR) 256.8 to support Federal land ownership and mineral resource management.

    For more information – Contact: Branch Chief, Mapping and Boundary Branch, BOEM, 381 Elden Street, Herndon, VA 20170. Telephone (703) 787-1312; Email: mapping.boundary.branch@boem.gov

    The REST services for National Level Data can be found here: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE/MMC_Layers/MapServer

    REST services for regional level data can be found by clicking on the region of interest from the following URL: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE

    Individual Regional Data or in depth metadata for download can be obtained in ESRI Shape file format by clicking on the region of interest from the following URL: http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx

    Currently the following layers are available from this REST location:

    OCS Drilling Platforms -Locations of structures at and beneath the water surface used for the purpose of exploration and resource extraction. Only platforms in federal Outer Continental Shelf (OCS) waters are included. A database of platforms and rigs is maintained by BSEE.

    OCS Oil and Natural Gas Wells -Existing wells drilled for exploration or extraction of oil and/or gas products. Additional information includes the lease number, well name, spud date, the well class, surface area/block number, and statistics on well status summary. Only wells found in federal Outer Continental Shelf (OCS) waters are included. Wells information is updated daily. Additional files are available on well completions and well tests. A database of wells is maintained by BSEE.

    OCS Oil & Gas Pipelines -This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

    Unofficial State Lateral Boundaries - The approximate location of the boundary between two states seaward of the coastline and terminating at the Submerged Lands Act Boundary. Because most State boundary locations have not been officially described beyond the coast, are disputed between states or in some cases the coastal land boundary description is not available, these lines serve as an approximation that was used to determine a starting point for creation of BOEM’s OCS Administrative Boundaries. GIS files are not available for this layer due to its unofficial status.

    BOEM OCS Administrative Boundaries - Outer Continental Shelf (OCS) Administrative Boundaries Extending from the Submerged Lands Act Boundary seaward to the Limit of the United States OCS (The U.S. 200 nautical mile Limit, or other marine boundary)For additional details please see the January 3, 2006 Federal Register Notice.

    BOEM Limit of OCSLA ‘8(g)’ zone - The Outer Continental Shelf Lands Act '8(g) Zone' lies between the Submerged Lands Act (SLA) boundary line and a line projected 3 nautical miles seaward of the SLA boundary line. Within this zone, oil and gas revenues are shared with the coastal state(s). The official version of the ‘8(g)’ Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction described below.

    Submerged Lands Act Boundary - The SLA boundary defines the seaward limit of a state's submerged lands and the landward boundary of federally managed OCS lands. The official version of the SLA Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction Diagrams described below.

    Atlantic Wildlife Survey Tracklines(2005-2012) - These data depict tracklines of wildlife surveys conducted in the Mid-Atlantic region since 2005. The tracklines are comprised of aerial and shipboard surveys. These data are intended to be used as a working compendium to inform the diverse number of groups that conduct surveys in the Mid-Atlantic region.The tracklines as depicted in this dataset have been derived from source tracklines and transects. The tracklines have been simplified (modified from their original form) due to the large size of the Mid-Atlantic region and the limited ability to map all areas simultaneously.The tracklines are to be used as a general reference and should not be considered definitive or authoritative. This data can be downloaded from http://www.boem.gov/uploadedFiles/BOEM/Renewable_Energy_Program/Mapping_and_Data/ATL_WILDLIFE_SURVEYS.zip

    BOEM OCS Protraction Diagrams & Leasing Maps - This data set contains a national scale spatial footprint of the outer boundaries of the Bureau of Ocean Energy Management’s (BOEM’s) Official Protraction Diagrams (OPDs) and Leasing Maps (LMs). It is updated as needed. OPDs and LMs are mapping products produced and used by the BOEM to delimit areas available for potential offshore mineral leases, determine the State/Federal offshore boundaries, and determine the limits of revenue sharing and other boundaries to be considered for leasing offshore waters. This dataset shows only the outline of the maps that are available from BOEM.Only the most recently published paper or pdf versions of the OPDs or LMs should be used for official or legal purposes. The pdf maps can be found by going to the following link and selecting the appropriate region of interest. http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx Both OPDs and LMs are further subdivided into individual Outer Continental Shelf(OCS) blocks which are available as a separate layer. Some OCS blocks that also contain other boundary information are known as Supplemental Official Block Diagrams (SOBDs.) Further information on the historic development of OPD's can be found in OCS Report MMS 99-0006: Boundary Development on the Outer Continental Shelf: http://www.boemre.gov/itd/pubs/1999/99-0006.PDF Also see the metadata for each of the individual GIS data layers available for download. The Official Protraction Diagrams (OPDs) and Supplemental Official Block Diagrams (SOBDs), serve as the legal definition for BOEM offshore boundary coordinates and area descriptions.

    BOEM OCS Lease Blocks - Outer Continental Shelf (OCS) lease blocks serve as the legal definition for BOEM offshore boundary coordinates used to define small geographic areas within an Official Protraction Diagram (OPD) for leasing and administrative purposes. OCS blocks relate back to individual Official Protraction Diagrams and are not uniquely numbered. Only the most recently published paper or pdf

  6. U

    GIS Data for Geologic Map of the Lake Owen Quadrangle, Albany County,...

    • data.usgs.gov
    • catalog.data.gov
    Updated Nov 15, 2025
    + more versions
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    Stuart Giles; John Horton (2025). GIS Data for Geologic Map of the Lake Owen Quadrangle, Albany County, Wyoming [Dataset]. http://doi.org/10.5066/P950UJG5
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    Dataset updated
    Nov 15, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Stuart Giles; John Horton
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    Sep 29, 2022
    Area covered
    Albany County, Lake Owen, Wyoming
    Description

    This U.S. Geological Survey (USGS) data release presents a digital database of geospatially enabled vector layers and tabular data transcribed from the geologic map of the Lake Owen quadrangle, Albany County, Wyoming, which was originally published as U.S. Geological Survey Geologic Quadrangle Map GQ-1304 (Houston and Orback, 1976). The 7.5-minute Lake Owen quadrangle is located in southeastern Wyoming approximately 25 miles (40 kilometers) southwest of Laramie in the west-central interior of southern Albany County, and covers most of the southern extent of Sheep Mountain, the southeastern extent of Centennial Valley, and a portion of the eastern Medicine Bow Mountains. This relational geodatabase, with georeferenced data layers digitized at the publication scale of 1:24,000, organizes and describes the geologic and structural data covering the quadrangle's approximately 35,954 acres and enables the data for use in spatial analyses and computer cartography. The data types present ...

  7. ESI GIS Data and PDF Maps: Environmental Sensitivity Index including GIS...

    • fisheries.noaa.gov
    • catalog.data.gov
    • +1more
    Updated Jan 1, 1984
    + more versions
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    Office of Response and Restoration (1984). ESI GIS Data and PDF Maps: Environmental Sensitivity Index including GIS Data and Maps (for the U.S. Shorelines, including Alaska, Hawaii, and Puerto Rico) [Dataset]. https://www.fisheries.noaa.gov/inport/item/40691
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    shapefile, pdf - adobe portable document formatAvailable download formats
    Dataset updated
    Jan 1, 1984
    Dataset provided by
    Office of Response and Restoration
    Time period covered
    1984 - 2007
    Area covered
    United States, American Samoa, Puerto Rican shoreline, Golfo de Fonseca (Honduras and Nicaragua),
    Description

    Environmental Sensitivity Index (ESI) maps are an integral component in oil-spill contingency planning and assessment. They serve as a source of information in the event of an oil spill incident. ESI maps are a product of the Hazardous Materials Response Division of the Office of Response and Restoration (OR&R).ESI maps contain three types of information: shoreline habitats (classified accordin...

  8. a

    Water Bodies

    • hub.arcgis.com
    Updated Apr 15, 2020
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    City of Cambridge (2020). Water Bodies [Dataset]. https://hub.arcgis.com/datasets/CambridgeGIS::water-bodies/about
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    Dataset updated
    Apr 15, 2020
    Dataset authored and provided by
    City of Cambridge
    License

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

    Area covered
    Description

    City of Cambridge, MA, GIS basemap development project encompasses the land area of City of Cambridge with a 200-foot fringe surrounding the area and Charles River shoreline towards Boston. The basemap data was developed at 1" = 40' mapping scale using digital photogrammetric techniques. Planimetric features; both man-made and natural features like vegetation, rivers have been depicted. These features are important to all GIS/mapping applications and publication. A set of data layers such as Buildings, Roads, Rivers, Utility structures, 1 ft interval contours are developed and represented in the geodatabase. The features are labeled and coded in order to represent specific feature class for thematic representation and topology between the features is maintained for an accurate representation at the 1:40 mapping scale for both publication and analysis. The basemap data has been developed using procedures designed to produce data to the National Standard for Spatial Data Accuracy (NSSDA) and is intended for use at 1" = 40 ' mapping scale. Where applicable, the vertical datum is NAVD1988.Explore all our data on the Cambridge GIS Data Dictionary.Attributes NameType DetailsDescription TYPE type: Stringwidth: 50precision: 0 Type of water body (pond, stream, wetland)

    NAME type: Stringwidth: 50precision: 0 Name of water body (unpopulated)

  9. Medical Service Study Area Data Dictionary

    • gis.data.chhs.ca.gov
    • data.ca.gov
    • +4more
    Updated Sep 6, 2024
    + more versions
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    CA Department of Health Care Access and Information (2024). Medical Service Study Area Data Dictionary [Dataset]. https://gis.data.chhs.ca.gov/datasets/hcai::medical-service-study-area-data-dictionary
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    Dataset updated
    Sep 6, 2024
    Dataset provided by
    Department of Health Care Access and Information
    Authors
    CA Department of Health Care Access and Information
    Description

    Field Name Data Type Description

    Statefp Number US Census Bureau unique identifier of the state

    Countyfp Number US Census Bureau unique identifier of the county

    Countynm Text County name

    Tractce Number US Census Bureau unique identifier of the census tract

    Geoid Number US Census Bureau unique identifier of the state + county + census tract

    Aland Number US Census Bureau defined land area of the census tract

    Awater Number US Census Bureau defined water area of the census tract

    Asqmi Number Area calculated in square miles from the Aland

    MSSAid Text ID of the Medical Service Study Area (MSSA) the census tract belongs to

    MSSAnm Text Name of the Medical Service Study Area (MSSA) the census tract belongs to

    Definition Text Type of MSSA, possible values are urban, rural and frontier.

    TotalPovPop Number US Census Bureau total population for whom poverty status is determined of the census tract, taken from the 2020 ACS 5 YR S1701

  10. d

    GIS Data | USA & Canada | Over 40k Demographics Variables To Inform Business...

    • datarade.ai
    .json, .csv
    Updated Aug 13, 2024
    + more versions
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    GapMaps (2024). GIS Data | USA & Canada | Over 40k Demographics Variables To Inform Business Decisions | Consumer Spending Data| Demographic Data [Dataset]. https://datarade.ai/data-products/gapmaps-premium-demographic-data-by-ags-usa-canada-gis-gapmaps
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    .json, .csvAvailable download formats
    Dataset updated
    Aug 13, 2024
    Dataset authored and provided by
    GapMaps
    Area covered
    Canada, United States
    Description

    GapMaps GIS data for USA and Canada sourced from Applied Geographic Solutions (AGS) includes an extensive range of the highest quality demographic and lifestyle segmentation products. All databases are derived from superior source data and the most sophisticated, refined, and proven methodologies.

    GIS Data attributes include:

    1. Latest Estimates and Projections The estimates and projections database includes a wide range of core demographic data variables for the current year and 5- year projections, covering five broad topic areas: population, households, income, labor force, and dwellings.

    2. Crime Risk Crime Risk is the result of an extensive analysis of a rolling seven years of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, Crime Risk provides an accurate view of the relative risk of specific crime types (personal, property and total) at the block and block group level.

    3. Panorama Segmentation AGS has created a segmentation system for the United States called Panorama. Panorama has been coded with the MRI Survey data to bring you Consumer Behavior profiles associated with this segmentation system.

    4. Business Counts Business Counts is a geographic summary database of business establishments, employment, occupation and retail sales.

    5. Non-Resident Population The AGS non-resident population estimates utilize a wide range of data sources to model the factors which drive tourists to particular locations, and to match that demand with the supply of available accommodations.

    6. Consumer Expenditures AGS provides current year and 5-year projected expenditures for over 390 individual categories that collectively cover almost 95% of household spending.

    7. Retail Potential This tabulation utilizes the Census of Retail Trade tables which cross-tabulate store type by merchandise line.

    8. Environmental Risk The environmental suite of data consists of several separate database components including: -Weather Risks -Seismological Risks -Wildfire Risk -Climate -Air Quality -Elevation and terrain

    Primary Use Cases for GapMaps GIS Data:

    1. Retail (eg. Fast Food/ QSR, Cafe, Fitness, Supermarket/Grocery)
    2. Customer Profiling: get a detailed understanding of the demographic & segmentation profile of your customers, where they work and their spending potential
    3. Analyse your trade areas at a granular census block level using all the key metrics
    4. Site Selection: Identify optimal locations for future expansion and benchmark performance across existing locations.
    5. Target Marketing: Develop effective marketing strategies to acquire more customers.
    6. Integrate AGS demographic data with your existing GIS or BI platform to generate powerful visualizations.

    7. Finance / Insurance (eg. Hedge Funds, Investment Advisors, Investment Research, REITs, Private Equity, VC)

    8. Network Planning

    9. Customer (Risk) Profiling for insurance/loan approvals

    10. Target Marketing

    11. Competitive Analysis

    12. Market Optimization

    13. Commercial Real-Estate (Brokers, Developers, Investors, Single & Multi-tenant O/O)

    14. Tenant Recruitment

    15. Target Marketing

    16. Market Potential / Gap Analysis

    17. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)

    18. Customer Profiling

    19. Target Marketing

    20. Market Share Analysis

  11. m

    D5 2030 Hatch

    • gis.data.mass.gov
    • geodot.mass.gov
    • +1more
    Updated Dec 7, 2023
    + more versions
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    Massachusetts geoDOT (2023). D5 2030 Hatch [Dataset]. https://gis.data.mass.gov/datasets/MassDOT::d5-2030-hatch
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    Dataset updated
    Dec 7, 2023
    Dataset authored and provided by
    Massachusetts geoDOT
    Area covered
    Description

    Flood Hatch ShapefilesIn addition to the three sets of rasters (Maximum Wave Heights, Water Surface Elevations, and DFEs) provided, separate shapefiles were also created to overlap and highlight special areas within the raster datasets produced for calculating DFEs. A flood hatch shapefile is not provided for every ACFEP level or for every region, but when it is provided, it encompasses the special areas for that level and region. The same hatch shapefile is applicable for all datatypes for the particular level and region. Flood hatch shapefiles encompass all areas of special values within the data rasters (including areas of 9999, 9998, and 9997 values). All regions have a 0.1% ACFEP level flood hatch shapefile because all 0.1% ACFEP rasters contain 9999 values.The flood hatch shapefiles contain individual polygons that describe the type of special area underlying that polygon’s spatial extent. For 9999 and 9998 values in the value rasters (water surface elevations, waves, and DFEs), the special hatched polygons will have the same extent of those values within those rasters. For 9997 values in the value rasters, the hatch polygon will always encompass the 9997 values, but may be larger in extent than just the location of those value cells. For these areas, water surface elevation, wave heights, and DFEs values may be provided, but they still represent a special zone.The Hatch polygons have 5 fields (Column headers) that describe each polygon within the shapefile. These fields include FID, Shape, Hatch_Type, Zones_txt, Hatch, and Hatch_Txt. The FID field contains an ID number for each polygon within that shapefile, while the Shape fieldlists the type of shapefile contained (polygon in all cases). The Hatch_Type field contains the numerical value that can be found within the value rasters (wave height, water surface, and DFE) underlying that polygon. Zones_txt and Hatch_txt are string type fields that contain descriptors of the polygon type, while the Hatch Field contains a numerical value for the type of hatching (1 for 0.1% Edge Zone, 2 for Wave Overtopping Zones, 3 for Dynamic Zone). The following table is an example of what a flood hatch file’s attribute table might look like.FIDShapeHatch_TypeZones_TxtHatchHatch_Txt0Polygon9999Shallow water flooding during extreme storms10.1% Edge Zone1Polygon9997Influenced by wave overtopping (incl. 9997 areas)2Wave Overtopping Zone2Polygon9998Dynamic Landform Areas3Dynamic ZoneSpecifically, the various hatch shapefiles can be defined as follows:• FID 0 Hatch Type – These represent areas of shallow water flooding during extreme storms. These are locations where flooding can only be expected during the most extreme events (> 1000-year return period) or where there are only minor flood depths (shallow flooding) during 1000-year return period AEP. These values only appear in 0.1% ACFEP level since they only occur at the very upper extent of extreme flooding. Water surface elevation values in these regions can be set to 0.1 foot above the site-specific land elevation to provide an estimate of the water surface elevation. Site-specific survey information may be needed to determine the land elevation. These hatch areas directly match areas with 9999 values within the rasters.• FID 1 Hatch Type – These represent wave overtopping zones. These hatch layers encompass the 9997 areas, but also include areas that have known values. Hatched areas of this type covering 9997 values would be expected to experience flooding caused by intermittent wave spray and overtopping only. Hatched areas of this type covering locations with values indicate that the flooding is caused by both direct sheet flow and wave overtopping. These hatched zones are provided for informational purposes by identifying zones that may require special design considerations for wave overtopping. Site-specific coastal processes analysis may also be required in these areas.• FID 2 Hatch Type – These represent areas where geomorphology is extremely dynamic and as such expected flooding may vary drastically. These values can appear in any ACFEP level. There are minimal locations of this type. These hatch areas directly match areas with 9998 values within the rasters.

  12. a

    Bottom Type

    • hub.arcgis.com
    • opendata.hawaii.gov
    • +3more
    Updated Feb 7, 2014
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    Hawaii Statewide GIS Program (2014). Bottom Type [Dataset]. https://hub.arcgis.com/maps/HiStateGIS::bottom-type
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    Dataset updated
    Feb 7, 2014
    Dataset authored and provided by
    Hawaii Statewide GIS Program
    Area covered
    Description

    [Metadata] This dataset contains those marine bottom type/seabed classifications within the vicinity of the main Hawaiian Islands and recorded on the nautical charts.Source: NOAA Raster Nautical Charts, 2002June 2024: Hawaii Statewide GIS Program staff removed extraneous fields that had been added as part of a 2016 GIS database conversion and were no longer needed.For additional information, please refer to complete metadata at https://files.hawaii.gov/dbedt/op/gis/data/bottom_type.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

  13. w

    Global Geospatial Data Provider Market Research Report: By Data Type...

    • wiseguyreports.com
    Updated Sep 15, 2025
    + more versions
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    (2025). Global Geospatial Data Provider Market Research Report: By Data Type (Satellite Imagery, Topographic Data, Street Maps, Aerial Photography), By Technology (GIS, Remote Sensing, GPS), By End Use Industry (Agriculture, Urban Planning, Transportation, Environmental Monitoring), By Service Model (Subscription-Based, Pay-As-You-Go, Enterprise Solutions) and By Regional (North America, Europe, South America, Asia Pacific, Middle East and Africa) - Forecast to 2035 [Dataset]. https://www.wiseguyreports.com/reports/geospatial-data-provider-market
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    Dataset updated
    Sep 15, 2025
    License

    https://www.wiseguyreports.com/pages/privacy-policyhttps://www.wiseguyreports.com/pages/privacy-policy

    Time period covered
    Sep 25, 2025
    Area covered
    Europe, North America, Global
    Description
    BASE YEAR2024
    HISTORICAL DATA2019 - 2023
    REGIONS COVEREDNorth America, Europe, APAC, South America, MEA
    REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
    MARKET SIZE 20245.64(USD Billion)
    MARKET SIZE 20256.04(USD Billion)
    MARKET SIZE 203512.0(USD Billion)
    SEGMENTS COVEREDData Type, Technology, End Use Industry, Service Model, Regional
    COUNTRIES COVEREDUS, Canada, Germany, UK, France, Russia, Italy, Spain, Rest of Europe, China, India, Japan, South Korea, Malaysia, Thailand, Indonesia, Rest of APAC, Brazil, Mexico, Argentina, Rest of South America, GCC, South Africa, Rest of MEA
    KEY MARKET DYNAMICSGrowing demand for location intelligence, Increasing adoption of AI technologies, Expansion of smart city initiatives, Rising awareness of environmental monitoring, Advancements in satellite imaging technology
    MARKET FORECAST UNITSUSD Billion
    KEY COMPANIES PROFILEDDigitalGlobe, Quantum Spatial, Hexagon, Environmental Systems Research Institute, Trelleborg, HERE Technologies, Trimble, Esri, Leaflet, GeoIQ, Spatial Networks, Garmin, Mapbox, TomTom, OpenStreetMap
    MARKET FORECAST PERIOD2025 - 2035
    KEY MARKET OPPORTUNITIESIncreased demand for AI integration, Expansion in smart city projects, Growth in remote sensing technology, Rising importance of location-based services, Enhanced data analytics capabilities
    COMPOUND ANNUAL GROWTH RATE (CAGR) 7.1% (2025 - 2035)
  14. w

    Wetlands - Forests Practices Regulation

    • geo.wa.gov
    • data-wadnr.opendata.arcgis.com
    • +1more
    Updated Jan 31, 2017
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    Washington State Department of Natural Resources (2017). Wetlands - Forests Practices Regulation [Dataset]. https://geo.wa.gov/datasets/02b250843e44485ea7d736b34fa80998
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    Dataset updated
    Jan 31, 2017
    Dataset authored and provided by
    Washington State Department of Natural Resources
    Area covered
    Description

    Click to downloadClick for metadataService URL: https://gis.dnr.wa.gov/site2/rest/services/Public_Forest_Practices/WADNR_PUBLIC_FP_Water_Type/MapServer/4For large areas, like Washington State, download as a file geodatabase. Large data sets like this one, for the State of Washington, may exceed the limits for downloading as shape files, excel files, or KML files. For areas less than a county, you may use the map to zoom to your area and download as shape file, excel or KML, if that format is desired.The DNR Forest Practices Wetlands Geographic Information System (GIS) Layer is based on the National Wetlands Inventory (NWI). In cooperation with the Washington State Department of Ecology, DNR Forest Practices developed a systematic reclassification of the original USFWS wetlands codes into WAC 222-16-035 types. The reclassification was done in 1995 according to the Forest Practice Rules in place at the time. The WAC's for defining wetlands are 222-16-035 and 222-16-050.The DNR Forest Practices Wetlands Geographic Information System (GIS) Layer is based on the National Wetlands Inventory (NWI). In cooperation with the Washington State Department of Ecology, DNR Forest Practices developed a systematic reclassification of the original USFWS wetlands codes into WAC 222-16-035 types. The reclassification was done in 1995 according to the Forest Practice Rules in place at the time. The WAC's for defining wetlands are 222-16-035 and 222-16-050.It is intended that these data be only a first step in determining whether or not wetland issues have been or need to be addressed in an area. The DNR Forest Practices Division and the Department of Ecology strongly supports the additional use of hydric soils (from the GIS soils layer) to add weight to the call of 'wetland'. Reports from the Department of Ecology indicate that these data may substantially underestimate the extent of forested wetlands. Various studies show the NWI data is 25-80% accurate in forested areas. Most of these data were collected from stereopaired aerial photos at a scale of 1:58,000. The stated accuracy is that of a 1:24,000 map, or plus or minus 40 feet. In addition, some parts of the state have data that are 30 years old and only a small percentage have been field checked. Thus, for regulatory purposes, the user should not rely solely on these data. On-the-ground checking must accompany any regulatory call based on these data.The reclassification is based on the USFWS FWS_CODE. The FWS_CODE is a concatenation of three subcomponents: Wetland system, class, and water regime. Forest Practices further divided the components into system, subsystem, class, subclass, water regime, special modifiers, xclass, subxclass, and xsystem. The last three items (xsomething) are for wetland areas which do not easily lend themselves to one class alone. The resulting classification system uses two fields: WLND_CLASS and WLND_TYPE. WLND_CLASS indicates whether the polygon is a forested wetland (F), open water (O), or a vegetated wetland (W). WLND_TYPE, indicates whether the wetland is a type A (1), type B (2), or a generic wetland (3) that doesn't fit the categories for A or B type wetlands. WLND_TYPE = 0 (zero) is used where WLND_CLASS = O (letter "O").

    The wetland polygon is classified as F, forested wetland; O, open water; or W, vegetated wetland depending on the following FWS_CODE categories: F O W --------------------------------------------------- Forested Open Vegetated Wetland Water Wetland --------------------------------------------PFO* POW PUB5 E2FO PRB* PML2 PUB1-4 PEM* PAB* L2US5 PUS1-4 L2EM2 PFL* PSS* L1RB* PML1 L1UB*
    L1AB* L1OW L2RB* L2UB* L2AB* L2RS* L2US1-4 L2OW

    • indicates inclusion of the subcategory (ie. PEM* includes PEM1F, PEM1FB, etc.).

    DNR FOREST PRACTICES WETLANDS DATASET ON FPARS Internet Mapping Website: The FPARS Resource Map and Water Type Map display Forested, Type A, Type B, and "other" wetlands. Open water polygons are not displayed on the FPARS Resource Map and Water Type Map in an attempt to minimize clutter. The following code combinations are found in the DNR Forest Practices wetlands dataset:

    WLND_CLASS WLND_TYPE wetland polygon classification F 3 Forested wetland as defined in WAC 222-16-035 O 0 *NWI open water (not displayed on FPARS Resource or Water Type Maps) W 1 Type A Wetland as defined in WAC 222-16-035 W 2 Type B Wetland as defined in WAC 222-16-035 W 3 other wetland

    • NWI open water polygons are indicated by WLND_CLASS = O and WLND_TYPE = 0. Open water is used in the USFWS and WAC 222-16-035 classification system. These open water polygons are not included in the FPARS Resource Map and Water Type Map views of this dataset in an attempt to minimize clutter on the FPARS maps.
  15. H

    Data from: Land Use Land Cover (LULC)

    • opendata.hawaii.gov
    • geoportal.hawaii.gov
    • +3more
    Updated Jun 1, 2024
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    Office of Planning (2024). Land Use Land Cover (LULC) [Dataset]. https://opendata.hawaii.gov/dataset/land-use-land-cover-lulc
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    pdf, arcgis geoservices rest api, geojson, kml, html, zip, csv, ogc wms, ogc wfsAvailable download formats
    Dataset updated
    Jun 1, 2024
    Dataset provided by
    Hawaii Statewide GIS Program
    Authors
    Office of Planning
    Description

    [Metadata] Description: Land Use Land Cover of main Hawaiian Islands as of 1976

    Source: 1:100,000 1976 Digital GIRAS (Geographic Information Retrieval and Analysis) files.

    Land Use and Land Cover (LULC) data consists of historical land use and land cover classification data that was based primarily on the manual interpretation of 1970's and 1980's aerial photography. Secondary sources included land use maps and surveys. There are 21 possible categories of cover type. The spatial resolution for all LULC files will depend on the format and feature type. Files in GIRAS format will have a minimum polygon area of 10 acres (4 hectares) with a minimum width of 660 feet (200 meters) for manmade features. Non-urban or natural features have a minimum polygon area of 40 acres (16 hectares) with a minimum width of 1320 feet (400 meters). Files in CTG format will have a resolution of 30 meters.

    May 2024: Hawaii Statewide GIS Program staff removed extraneous fields that had been added as part of the 2016 GIS database conversion and were no longer needed.

    For additional information, please refer to https://files.hawaii.gov/dbedt/op/gis/data/lulc.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, HI 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

  16. d

    Digital Geologic-GIS Map of Santa Rosa Island, California (NPS, GRD, GRI,...

    • datasets.ai
    • s.cnmilf.com
    • +1more
    33, 57
    Updated May 31, 2023
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    Department of the Interior (2023). Digital Geologic-GIS Map of Santa Rosa Island, California (NPS, GRD, GRI, CHIS, SRIS digital map) adapted from a American Association of Petroleum Geologists Field Trip Guidebook map by Sonneman, as modified and extend by Weaver, Doerner, Avila and others (1969) [Dataset]. https://datasets.ai/datasets/digital-geologic-gis-map-of-santa-rosa-island-california-nps-grd-gri-chis-sris-digital-map
    Explore at:
    57, 33Available download formats
    Dataset updated
    May 31, 2023
    Dataset authored and provided by
    Department of the Interior
    Area covered
    Santa Rosa Island, California
    Description

    The Digital Geologic-GIS Map of Santa Rosa 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 (sris_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 (sris_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 (sris_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 (sris_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 (sris_geology_metadata.txt or sris_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).

  17. m

    Fences

    • gis.data.mass.gov
    Updated Apr 15, 2020
    + more versions
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    City of Cambridge (2020). Fences [Dataset]. https://gis.data.mass.gov/datasets/CambridgeGIS::fences
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    Dataset updated
    Apr 15, 2020
    Dataset authored and provided by
    City of Cambridge
    License

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

    Area covered
    Description

    City of Cambridge, MA, GIS basemap development project encompasses the land area of City of Cambridge with a 200-foot fringe surrounding the area and Charles River shoreline towards Boston. The basemap data was developed at 1" = 40' mapping scale using digital photogrammetric techniques. Planimetric features; both man-made and natural features like vegetation, rivers have been depicted. These features are important to all GIS/mapping applications and publication. A set of data layers such as Buildings, Roads, Rivers, Utility structures, 1 ft interval contours are developed and represented in the geodatabase. The features are labeled and coded in order to represent specific feature class for thematic representation and topology between the features is maintained for an accurate representation at the 1:40 mapping scale for both publication and analysis. The basemap data has been developed using procedures designed to produce data to the National Standard for Spatial Data Accuracy (NSSDA) and is intended for use at 1" = 40 ' mapping scale. Where applicable, the vertical datum is NAVD1988.Explore all our data on the Cambridge GIS Data Dictionary.Attributes NameType DetailsDescription TYPE type: Stringwidth: 50precision: 0 Type of fence (fence, guardrail, or hedge)

  18. D

    Household Types and Populations - Seattle Neighborhoods

    • data.seattle.gov
    • hub.arcgis.com
    • +1more
    csv, xlsx, xml
    Updated Oct 22, 2024
    + more versions
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    (2024). Household Types and Populations - Seattle Neighborhoods [Dataset]. https://data.seattle.gov/dataset/Household-Types-and-Populations-Seattle-Neighborho/8nez-wmwv
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    csv, xlsx, xmlAvailable download formats
    Dataset updated
    Oct 22, 2024
    Area covered
    Seattle
    Description

    Table from the American Community Survey (ACS) 5-year series on household types and population related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B11003 Family Type by Presence and Age of Own Children under 18 Years, B11005 Households by Presence of People Under 18 Years by Household Type, B11007 Households by Presence of People 65 Years and Over by Household Type, B11001 Household Type (Including Living Alone), B11002 Household Type by Relatives and Nonrelatives for Population in Households, B25003 Tenure, B25008 Total Population in Occupied Housing Units by Tenure, B09019 Household Type (Including Living Alone) by Relationship. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.


    Table created for and used in the Neighborhood Profiles application.

    Vintages: 2023


    The United States Census Bureau's American Community Survey (ACS):
    This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.

    Data Note from the Census:
    Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.

    Data Processing Notes:
    • Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb(year)a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k <a href='https://www.census.gov/geographies/mapping-files/time-series/geo/cartographic-boundary.html' style='color:rgb(0, 121, 193); text-decoration-line:none; font-family:inherit; margin:0px;

  19. a

    Jurassic Structure (GIS data, polygon features)

    • catalogue.arctic-sdi.org
    • datasets.ai
    • +2more
    Updated Apr 22, 2025
    + more versions
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    (2025). Jurassic Structure (GIS data, polygon features) [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/resources/datasets/f1042a9b-e79f-41f2-b74c-eab380774b48
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    Dataset updated
    Apr 22, 2025
    Description

    The Geological Atlas of the Western Canada Sedimentary Basin was designed primarily as a reference volume documenting the subsurface geology of the Western Canada Sedimentary Basin. This GIS dataset is one of a collection of shapefiles representing part of Chapter 18 of the Atlas, Jurassic and Lowermost Cretaceous Strata of the Western Canada Sedimentary Basin, Figure 17, Jurassic Structure. Shapefiles were produced from archived digital files created by the Alberta Geological Survey in the mid-1990s, and edited in 2005-06 to correct, attribute and consolidate the data into single files by feature type and by figure.

  20. U

    Vegetation classification crosswalk database for use in GIS to synchronize...

    • data.usgs.gov
    • catalog.data.gov
    Updated Oct 9, 2015
    + more versions
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    Kevin Hop; Shannon Menard; Ulf Gafvert (2015). Vegetation classification crosswalk database for use in GIS to synchronize vegetation map layers of the NPS Great Lakes Network to the U.S. National Vegetation Classification [Dataset]. http://doi.org/10.5066/F72N50B5
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    Dataset updated
    Oct 9, 2015
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Kevin Hop; Shannon Menard; Ulf Gafvert
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    The Great Lakes, United States
    Description

    The geodatabase contains 13 relate tables that together provide updated and synchronized classifications to an existing vegetation map layer for each of the nine park units in the Great Lakes Network (GLKN) of the National Park Service (NPS) Natural Resource Inventory and Monitoring Program. The classifications include 1) vegetation types at every hierarchical level in the 2015 version of the U.S. National Vegetation Classification (USNVC) and 2) map classes that represent vegetation and land cover in the vegetation map layers. Furthermore, the tables provide a crosswalk between the two classifications (vegetation and map). Each park unit in GLKN has received, at different times over several years, vegetation data products from the NPS Vegetation Mapping Inventory (VMI) Program. However, the vegetation and map classifications were at different stages of development over these years. With this geodatabase product, having a series of already linked relate tables, the original vegeta ...

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National Park Service (2025). Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida (NPS, GRD, GRI, GUIS, GUIS_geomorphology digital map) adapted from U.S. Geological Survey Open File Report maps by Morton and Rogers (2009) and Morton and Montgomery (2010) [Dataset]. https://catalog.data.gov/dataset/digital-geomorphic-gis-map-of-gulf-islands-national-seashore-5-meter-accuracy-and-1-foot-r
Organization logo

Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida (NPS, GRD, GRI, GUIS, GUIS_geomorphology digital map) adapted from U.S. Geological Survey Open File Report maps by Morton and Rogers (2009) and Morton and Montgomery (2010)

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Dataset updated
Nov 25, 2025
Dataset provided by
National Park Servicehttp://www.nps.gov/
Area covered
Guisguis Port Sariaya, Quezon
Description

The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida 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 (guis_geomorphology.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 (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.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.) A GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.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 (guis_geomorphology_metadata_faq.pdf). Please read the guis_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 (guis_geomorphology_metadata.txt or guis_geomorphology_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 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 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, 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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