100+ datasets found
  1. d

    USGS Topo Map Vector Data Downloadable Data Collection

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Mar 11, 2025
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    U.S. Geological Survey (2025). USGS Topo Map Vector Data Downloadable Data Collection [Dataset]. https://catalog.data.gov/dataset/usgs-topo-map-vector-data-downloadable-data-collection
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    Dataset updated
    Mar 11, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.

  2. e

    GIS vector data for sample locations and plots associated with the Hillslope...

    • portal.edirepository.org
    kml, zip
    Updated 2016
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    Lawrence Band (2016). GIS vector data for sample locations and plots associated with the Hillslope Study in Macon County, NC [Dataset]. http://doi.org/10.6073/pasta/7229e742973a9da49e27fa43fd21f977
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    zip(not specified kb), kmlAvailable download formats
    Dataset updated
    2016
    Dataset provided by
    EDI
    Authors
    Lawrence Band
    Time period covered
    Nov 14, 2013 - Sep 20, 2016
    Area covered
    Macon County
    Description

    The Hillslope Study sites represent a gradient of landscapes, including forested, valley agriculture, and mountain housing developments. These locations and plots were used to collect samples of various matrices for numerous analyses at differing intervals. The data set consists of Open Office spreadsheet and other files that document all the Hillslope Study locations.

  3. g

    Iran 1:100,000 Scale Geochemical Vector Data

    • shop.geospatial.com
    Updated Dec 2, 2020
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    (2020). Iran 1:100,000 Scale Geochemical Vector Data [Dataset]. https://shop.geospatial.com/publication/XB34MFJGWC9GMFA81911S8XGP3/Iran-1-to-100000-Scale-Geochemical-Vector-Data
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    Dataset updated
    Dec 2, 2020
    Area covered
    Iran
    Description

    Spatial coverage index compiled by East View Geospatial of set "Iran 1:100,000 Scale Geochemical Vector Data". Source data from GSI (publisher). Type: Geoscientific - Geology. Scale: 1:100,000. Region: Middle East.

  4. r

    Natural Earth Vector (NE)

    • researchdata.edu.au
    • catalogue.eatlas.org.au
    • +1more
    bin
    Updated Aug 2, 2016
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    Nathaniel Vaughn KELSO (2016). Natural Earth Vector (NE) [Dataset]. https://researchdata.edu.au/natural-earth-vector-ne/675135
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    binAvailable download formats
    Dataset updated
    Aug 2, 2016
    Dataset provided by
    eAtlas
    Authors
    Nathaniel Vaughn KELSO
    Area covered
    Description

    Natural Earth is a public domain map dataset available at 1:10m, 1:50m, and 1:110 million scales. Featuring tightly integrated vector and raster data, with Natural Earth you can make a variety of visually pleasing, well-crafted maps with cartography or GIS software.

    Natural Earth was built through a collaboration of many volunteers and is supported by NACIS (North American Cartographic Information Society).

    Natural Earth Vector comes in ESRI shapefile format, the de facto standard for vector geodata. Character encoding is Windows-1252.

    Natural Earth Vector includes features corresponding to the following:

    Cultural Vector Data Thremes:

    • Countries: matched boundary lines and polygons with names attributes for countries and sovereign states. Includes dependencies (French Polynesia), map units (U.S. Pacific Island Territories) and sub-national map subunits (Corsica versus mainland Metropolitan France).
    • Disputed areas and breakaway regions - From Kashmir to the Elemi Triangle, Northern Cyprus to Western Sahara.
    • First order admin (provinces, departments, states, etc.): internal boundaries and polygons for all but a few tiny island nations. Includes names attributes and some statistical groupings of the same for smaller countries.
    • Populated places: point symbols with name attributes. Includes capitals, major cities and towns, plus significant smaller towns in sparsely inhabited regions. We favor regional significance over population census in determining rankings.
    • Urban polygons: derived from 2002-2003 MODIS satellite data.
    • Parks and protected areas: US National Park Service units.
    • Pacific nation groupings: boxes for keeping these far-flung islands tidy.
    • Water boundary indicators: partial selection of key 200-mile nautical limits, plus some disputed, treaty, and median lines.

    Physical Vector Data Themes:

    • Coastline: ocean coastline, including major islands. Coastline is matched to land and water polygons.
    • Land: Land polygons including major islands
    • Ocean: Ocean polygon split into contiguous pieces.
    • Minor Islands: additional small ocean islands ranked to two levels of relative importance.
    • Reefs: major coral reefs from WDB2.
    • Physical region features: polygon and point labels of major physical features.
    • Rivers and Lake Centerlines: ranked by relative importance. Includes name and line width attributes. Don’t want minor lakes? Turn on their centerlines to avoid unseemly data gaps.
    • Lakes: ranked by relative importance, coordinating with river ranking. Includes name attributes.
    • Glaciated areas: polygons derived from DCW, except for Antarctica derived from MOA. Includes name attributes for major polar glaciers.
    • Antarctic ice shelves: derived from 2003-2004 MOA. Reflects recent ice shelf collapses.
    • Bathymetry: nested polygons at 0, -200, -1,000, -2,000, -3,000, -4,000, -5,000, -6,000, -7,000, -8,000, -9,000,and -10,000 meters. Created from SRTM Plus.
    • Geographic lines: Polar circles, tropical circles, equator, and International Date Line.
    • Graticules: 1-, 5-, 10-, 15-, 20-, and 30-degree increments. Includes WGS84 bounding box.
  5. OpenStreetMap (Streets with Relief - WGS84)

    • hub.arcgis.com
    • cacgeoportal.com
    • +4more
    Updated Sep 5, 2019
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    Esri (2019). OpenStreetMap (Streets with Relief - WGS84) [Dataset]. https://hub.arcgis.com/maps/8978501dcd724175be8913ed87166b2f
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    Dataset updated
    Sep 5, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Important Note: This item is in mature support as of December 2024. See blog for more information.This web map presents a vector basemap of OpenStreetMap (OSM) data hosted by Esri. This version of the map is rendered in a style similar to the Esri Street Map (with Relief). It includes the World Hillshade layer. Created from the sunsetted Daylight map distribution, data updates supporting this layer are no longer available.OpenStreetMap is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project. Precise Tile Registration: The web map uses the improved tiling scheme “WGS84 Geographic, Version 2” to ensure proper tile positioning at higher resolutions (neighborhood level and beyond). The new tiling scheme is much more precise than tiling schemes of the legacy basemaps Esri released years ago. We recommend that you start using this new basemap for any new web maps in WGS84 that you plan to author. Due to the number of differences between the old and new tiling schemes, some web clients will not be able to overlay tile layers in the old and new tiling schemes in one web map.

  6. D

    Atolls of Pacific Ocean: geospatial vector data (MCRMP project)

    • dataverse.ird.fr
    Updated Sep 4, 2023
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    Serge Andréfouët; Serge Andréfouët (2023). Atolls of Pacific Ocean: geospatial vector data (MCRMP project) [Dataset]. http://doi.org/10.23708/OS20O0
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    application/zipped-shapefile(6005350), application/zipped-shapefile(321404), application/zipped-shapefile(36298), application/zipped-shapefile(31225), application/zipped-shapefile(1099015), application/zipped-shapefile(4068492), txt(1815), application/zipped-shapefile(172785), application/zipped-shapefile(7896860), application/zipped-shapefile(80999), application/zipped-shapefile(882730), application/zipped-shapefile(87981), application/zipped-shapefile(2871925), application/zipped-shapefile(26475), application/zipped-shapefile(942356), application/zipped-shapefile(2070283), application/zipped-shapefile(1959790), application/zipped-shapefile(436716)Available download formats
    Dataset updated
    Sep 4, 2023
    Dataset provided by
    DataSuds
    Authors
    Serge Andréfouët; Serge Andréfouët
    License

    https://dataverse.ird.fr/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.23708/OS20O0https://dataverse.ird.fr/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.23708/OS20O0

    Area covered
    Pacific Ocean, Cook Islands, Tuvalu, Fiji, Solomon Islands, Vanuatu, Pitcairn, Niue, Kiribati, Samoa
    Dataset funded by
    IRD (2003-present)
    NASA (2001-2007)
    Description

    The Millennium Coral Reef Mapping Project provides thematic maps of coral reefs worldwide at geomorphological scale. Maps were created by photo-interpretation of Landsat 7 and Landsat 8 satellite images. Maps are provided as standard Shapefiles usable in GIS software. The geomorphological classification scheme is hierarchical and includes 5 levels. The GIS products include for each polygon a number of attributes. The 5 level geomorphological attributes are provided (numerical codes or text). The Level 1 corresponds to the differentiation between oceanic and continental reefs. Then from Levels 2 to 5, the higher the level, the more detailed the thematic classification is. Other binary attributes specify for each polygon if it belongs to terrestrial area (LAND attribute), and sedimentary or hard-bottom reef areas (REEF attribute). Examples and more details on the attributes are provided in the references cited. The products distributed here were created by IRD, in their last version. Shapefiles for 245 atolls of the Pacific Ocean as mapped by the Global coral reef mapping project at geomorphological scale using LANDSAT satellite data (L7 and L8). The data set provides one zip file per country or region of interest. Global coral reef mapping project at geomorphological scale using LANDSAT satellite data (L7 and L8). Funded by National Aeronautics and Space Administration, NASA grants NAG5-10908 (University of South Florida, PIs: Franck Muller-Karger and Serge Andréfouët) and CARBON-0000-0257 (NASA, PI: Julie Robinson) from 2001 to 2007. Funded by IRD since 2003 (in kind, PI: Serge Andréfouët).

  7. a

    LiDAR Derived Hydrologic Data Products (vector products)

    • hub.arcgis.com
    Updated Mar 2, 2016
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    Sonoma County Ag + Open Space (2016). LiDAR Derived Hydrologic Data Products (vector products) [Dataset]. https://hub.arcgis.com/datasets/c9f7503b9838497d9bd283b20aeec569
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    Dataset updated
    Mar 2, 2016
    Dataset authored and provided by
    Sonoma County Ag + Open Space
    Area covered
    Description

    The full datasheet for this product is available here.The Sonoma County hydrologic data deliverables were produced in fall 2015 and winter 2016 from the countywide 2013 LiDAR data. The hydrologic products include a set of vector deliverables and a set of raster deliverables. Vector products include stream centerlines, confluence points, hydroenforcement burn locations, and watersheds. Raster products include flow direction, flow accumulation, and a hydroenforced bare earth digital elevation model (DEM). Hydroenforcement of a DEM imparts the true elevations of culverts, pipelines, and other buried passages for water into a Digital Elevation Model, creating a DEM suitable for modeling the flow of surface water.

    The extent of all deliverables is all of Sonoma County, the Lake Sonoma watershed in Mendocino County, and the Lake Mendocino area. Appropriate Use: These hydrologic datasets are a mostly-automated first step in the eventual development of a 'localized' or 'LiDAR enhanced' National Hydrography Dataset (NHD). They are suitable for landscape level planning and hydrologic modeling. These data products do not contain a guarantee of accuracy or precision and – without site specific validation and/or refinement – should not be relied upon for engineering level or very fine scale decision making. Detailed Dataset Description:These hydrologic data products were produced by Quantum Spatial. Quantum Spatial used mainly automated methods to create the hydrologic data products. Quantum Spatial included a short data report with the hydrologic datasets titled Sonoma County Hydroenforcement Technical Data Report - access that report here: https://sonomaopenspace.egnyte.com/dl/nHT2fGg8TP

    The individual hydrologic data products are described briefly below.

      Vector Hydro Products (contained in this file gdb):    
    

    Stream Centerlines – Centerlines of streams in Sonoma County. An area of flow concentration is considered a stream if its flow accumulation (upstream catchment area) exceeds 5 acres and a clearly defined channel exists. Where possible, stream centerline names (GNIS_Name) are consistent with the NHD. Hydroenforcement Burn Locations - Line features that represent locations where hydroenforcement occurred. Confluence Points – Points that represent stream intersections (confluences).Watersheds (HUC2 through HUC16) – Watershed boundaries for nested hydrologic units from HUC 2 (region) to HUC 16 (eighth level sub-watershed). Where possible, watershed names are consistent with the NHD. Watershed mapping conventions follow those for NHD's Watershed Boundary Dataset (http://nhd.usgs.gov/wbd.html).

    Raster Hydrologic Products (1-meter resolution - available at http://sonomavegmap.org/data-downloads)Hydroenforced Digital Elevation Model – The Hydroenforced DEM is the LiDAR derived (2013) bare earth DEM with contours, pipelines and other buried passages to water 'burned in', so that the DEM correctly models surface water flow.Flow Direction Rasters – Values in a flow direction raster represent one of eight directions (pixel values range from 1 to 8); No Data represents areas where there is no flow off of the pixel (sinks).Flow Accumulation Rasters – Flow accumulation is a measure of upstream catchment area. Pixel values in a flow accumulation raster represent the cumulative number of upstream pixels (in other words, the count of pixels that contribute flow to a given pixel).

  8. Vector datasets for workshop "Introduction to Geospatial Raster and Vector...

    • figshare.com
    Updated Oct 5, 2022
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    Ryan Avery (2022). Vector datasets for workshop "Introduction to Geospatial Raster and Vector Data with Python" [Dataset]. http://doi.org/10.6084/m9.figshare.21273837.v1
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    application/x-sqlite3Available download formats
    Dataset updated
    Oct 5, 2022
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Ryan Avery
    License

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

    Description

    Cadaster data from PDOK used to illustrate the use of geopandas and shapely, geospatial python packages for manipulating vector data. The brpgewaspercelen_definitief_2020.gpkg file has been subsetted in order to make the download manageable for workshops. Other datasets are copies of those available from PDOK.

  9. GIS dataset of candidate terrestrial ecological restoration areas for the...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Nov 12, 2020
    + more versions
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    U.S. EPA Office of Research and Development (ORD) (2020). GIS dataset of candidate terrestrial ecological restoration areas for the United States [Dataset]. https://catalog.data.gov/dataset/gis-dataset-of-candidate-terrestrial-ecological-restoration-areas-for-the-united-states
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    Dataset updated
    Nov 12, 2020
    Dataset provided by
    United States Environmental Protection Agencyhttp://www.epa.gov/
    Area covered
    United States
    Description

    A vector GIS dataset of candidate areas for terrestrial ecological restoration based on landscape context. The dataset was created using NLCD 2011 (www.mrlc.gov) and morphological spatial pattern analysis (MSPA) (http://forest.jrc.ec.europa.eu/download/software/guidos/mspa/). There are 13 attributes for the polygons in the dataset, including presence and length of roads, candidate area size, size of surround contiguous natural areas, soil productivity, presence and length of road, areas suitable for wetland restoration, and others. This dataset is associated with the following publication: Wickham, J., K. Riiters, P. Vogt, J. Costanza, and A. Neale. An inventory of continental U.S. terrestrial candidate ecological restoration areas based on landscape context. RESTORATION ECOLOGY. Blackwell Publishing, Malden, MA, USA, 25(6): 894-902, (2017).

  10. f

    coastline classification samples

    • figshare.com
    Updated Feb 15, 2024
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    Aji Gao (2024). coastline classification samples [Dataset]. http://doi.org/10.6084/m9.figshare.25212536.v1
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    application/x-sqlite3Available download formats
    Dataset updated
    Feb 15, 2024
    Dataset provided by
    figshare
    Authors
    Aji Gao
    License

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

    Description

    The dataset focuses on coastline morphology and is designed for classification purposes. It includes coastline samples in vector format, derived from both satellite remote sensing imagery and manually created based on specific characteristics. These samples have been preprocessed for topological correction, scaling, and arranged closely for efficient analysis.The dataset is distributed in a Geopackage database format, comprising 5 files. Each file contains 500 samples of a single category. The files are named according to the coastline categories, using one-hot encoding for easy identification. The categories are as follows:10000 for Elongated coastlines.01000 for Broad coastlines.00100 for Rugged coastlines.00010 for Smooth coastlines.00001 for Orthogonal coastlines.

  11. g

    Qatar 1:10,000 Scale Vector Data

    • shop.geospatial.com
    Updated Nov 23, 2020
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    (2020). Qatar 1:10,000 Scale Vector Data [Dataset]. https://shop.geospatial.com/publication/K9YJHMNDHG1K47PFCB3C8A1ER5/Qatar-1-to-10000-Scale-Vector-Data
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    Dataset updated
    Nov 23, 2020
    Area covered
    Qatar
    Description

    Spatial coverage index compiled by East View Geospatial of set "Qatar 1:10,000 Scale Vector Data". Source data from QCGIS (publisher). Type: Topographic. Scale: 1:10,000. Region: Middle East.

  12. i

    geospatial vector data used in HiVQ

    • ieee-dataport.org
    Updated Nov 4, 2024
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    Zebang Liu (2024). geospatial vector data used in HiVQ [Dataset]. https://ieee-dataport.org/documents/geospatial-vector-data-used-hivq
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    Dataset updated
    Nov 4, 2024
    Authors
    Zebang Liu
    License

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

    Description

    the dataset includes geospatial vector point and linestring data

  13. W

    Whitney Point Adelie Penguin Colonies, Vector GIS Layer

    • cloud.csiss.gmu.edu
    • data.aad.gov.au
    • +4more
    cfm, htm, shp
    Updated Dec 13, 2019
    + more versions
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    Australia (2019). Whitney Point Adelie Penguin Colonies, Vector GIS Layer [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/aad-asac-1219-aat-wp-adpe-colonies
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    cfm, htm, shpAvailable download formats
    Dataset updated
    Dec 13, 2019
    Dataset provided by
    Australia
    License

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

    Description

    An ArcGIS shapefile layer showing the extent of all extant and relic Adelie penguin (Pygoscelis adeliae) colonies at Whitney Point, Windmill Islands, February 2006. The field 'Status' describes each polygon as extant, relic or maximum. Extant refers to the area used by breeding birds in the summer 2005/06. Maximum refers to the historic maximal extent of the colony. Relic refers to any colony which was not occupied by any breeding pairs during 2005/06.

    Positional accuracy is approx. 1-2 m, after accounting for dGPS errors and errors in identification of the boundaries of colonies. Mapping was conducted after the end of the breeding season, so boundaries were identified as the extent of nest pebbles/fresh faeces, and it was considered that they could be reliably identified to within 0.5m.

    Data were acquired using a Trimble Pro XH differential GPS. This work was completed as part of ASAC project 1219 (ASAC_1219).

    Also for this project, three aerial photographs of Whitney point showing the adelie penguin colonies and taken on 17 December 1990 were georeferenced.

    These aerial photographs are film ANTC1219 run 54 frames 21 to 23.

    Work on this project also utilised a Digital Elevation Model (DEM) created for Shirley Island. See the metadata record, 'A digital elevation model (DEM) and orthophoto of the Whitney Point area of the Windmill Islands, Antarctica' for more information (linked below).

    Since the 2005/06 summer was a low-ice year the opportunity was also taken to survey with differential GPS a section of coastline about 230 metres long east of Whitney Point on Clark Peninsula. This section of coastline was ice free and accessible. The data was collected with differential GPS on 10 February 2006.

  14. a

    vector.GIS.AirQuality ReadingSampleData

    • hub.arcgis.com
    Updated May 15, 2019
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    Douglas County (2019). vector.GIS.AirQuality ReadingSampleData [Dataset]. https://hub.arcgis.com/datasets/dogis::vector-gis-airquality-readingsampledata/about
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    Dataset updated
    May 15, 2019
    Dataset authored and provided by
    Douglas County
    Area covered
    Description

    Query-only feature service for DCHD Air Quality Sites

  15. e

    State map 1:5000 new form vector data - Napajedla 6-0

    • data.europa.eu
    Updated Dec 16, 2012
    + more versions
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    (2012). State map 1:5000 new form vector data - Napajedla 6-0 [Dataset]. https://data.europa.eu/data/datasets/cz-cuzk-sm5-v-napa60?locale=en
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    Dataset updated
    Dec 16, 2012
    Description

    The product represents a new design of the State Map at a scale of 1:5,000 (SM 5) in vector form, whose advantages are recency and colour processing. The map contains planimetry based on cadastral map, altimetry adopted from the altimetry part of ZABAGED and map lettering based on database of geographic names Geonames and abbreviations of feature type signification coming up from attributes of selected ZABAGED features. This new design of the SM 5 is repeatedly generated once a year on the part of the Czech territory where the vector form of cadastral map is available. Therefore, part of export units (map sheets of SM 5) has not a full coverage (price of such export unit is then proportionally reduced).

  16. g

    Malawi 1:50,000 Scale GIS Vector Data

    • shop.geospatial.com
    Updated May 9, 2019
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    (2019). Malawi 1:50,000 Scale GIS Vector Data [Dataset]. https://shop.geospatial.com/publication/DB6YNNREZ79S4KAK8Y08SX4RX3/Malawi-1-to-50000-Scale-GIS-Vector-Data
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    Dataset updated
    May 9, 2019
    Area covered
    Malawi
    Description

    Spatial coverage index compiled by East View Geospatial of set "Malawi 1:50,000 Scale GIS Vector Data". Source data from MW-DOS (publisher). Type: Topographic. Scale: 1:50,000. Region: Africa.

  17. Data from: MAGELLAN SURFACE CHARACTERISTICS VECTOR DATA RECORD

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Apr 11, 2025
    + more versions
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    National Aeronautics and Space Administration (2025). MAGELLAN SURFACE CHARACTERISTICS VECTOR DATA RECORD [Dataset]. https://catalog.data.gov/dataset/magellan-surface-characteristics-vector-data-record-19468
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    Dataset updated
    Apr 11, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    This data set contains the Magellan Surface Characteristics Vector Data Record (SCVDR) which is an orbit-by-orbit reduction of Magellan scattering and emission measurements carried out at Stanford University. The SCVDR includes near-nadir scattering functions obtained by numerical inversion from altimetry (ALT) echoes, results (e.g., rms surface slopes and Fresnel reflectivity) from fitting analytic functions to those inversions, scattering function segments at oblique incidence angles derived from synthetic aperture radar (SAR) echoes, and estimates of surface emissivity derived from thermal microwave radiometry (RAD) measurements. The SCVDR is one of several inputs to the Global Vector Data Record (GVDR), a gridded summary of scattering results, also produced at Stanford.

  18. High resolution vector polylines of the Antarctic coastline

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Nov 17, 2022
    + more versions
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    British Antarctic Survey (2022). High resolution vector polylines of the Antarctic coastline [Dataset]. https://koordinates.com/layer/111081-high-resolution-vector-polylines-of-the-antarctic-coastline/
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    csv, geopackage / sqlite, geodatabase, pdf, mapinfo mif, mapinfo tab, dwg, shapefile, kmlAvailable download formats
    Dataset updated
    Nov 17, 2022
    Dataset authored and provided by
    British Antarctic Surveyhttps://www.bas.ac.uk/
    Area covered
    Antarctica,
    Description

    Coastline for Antarctica created from various mapping and remote sensing sources, consisting of the following coast types: ice coastline, rock coastline, grounding line, ice shelf and front, ice rumple, and rock against ice shelf. Covering all land and ice shelves south of 60°S. Suitable for topographic mapping and analysis. High resolution versions of ADD data are suitable for scales larger than 1:1,000,000. The largest suitable scale is changeable and dependent on the region.

    Major changes in v7.5 include updates to ice shelf fronts in the following regions: Seal Nunataks and Scar Inlet region, the Ronne-Filchner Ice Shelf, between the Brunt Ice Shelf and Riiser-Larsen Peninsula, the Shackleton and Conger ice shelves, and Crosson, Thwaites and Pine Island. Small areas of grounding line and ice coastlines were also updated in some of these regions as needed.

    Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research.

    Further information and useful links

    Map projection: WGS84 Antarctic Polar Stereographic, EPSG 3031. Note: by default, opening this layer in the Map Viewer will display the data in Web Mercator. To display this layer in its native projection use an Antarctic basemap.

    The currency of this dataset is May 2022 and will be reviewed every 6 months. This feature layer will always reflect the most recent version.

    For more information on, and access to other Antarctic Digital Database (ADD) datasets, refer to the SCAR ADD data catalogue.

    A related medium resolution dataset is also published via Living Atlas, as well medium and high resolution polygon datasets.

    For background information on the ADD project, please see the British Antarctic Survey ADD project page.

    Lineage

    Dataset compiled from a variety of Antarctic map and satellite image sources. The dataset was created using ArcGIS and QGIS GIS software programmes and has been checked for basic topography and geometry checks, but does not contain strict topology. Quality varies across the dataset and certain areas where high resolution source data were available are suitable for large scale maps whereas other areas are only suitable for smaller scales. Each line has attributes detailing the source which can give the user further indications of its suitability for specific uses. Attributes also give information including 'surface' (e.g. grounding line, ice coastline, ice shelf front) and revision date. Compiled from sources ranging in time from 1990s-2022 - individual lines contain exact source dates.

  19. D

    Atolls of Asia: geospatial vector data (MCRMP project)

    • dataverse.ird.fr
    Updated Sep 4, 2023
    + more versions
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    Serge Andréfouët; Serge Andréfouët (2023). Atolls of Asia: geospatial vector data (MCRMP project) [Dataset]. http://doi.org/10.23708/ANJCRV
    Explore at:
    application/zipped-shapefile(9485), application/zipped-shapefile(765515), application/zipped-shapefile(4489969), application/zipped-shapefile(462135), txt(1700), application/zipped-shapefile(729565), application/zipped-shapefile(2660226)Available download formats
    Dataset updated
    Sep 4, 2023
    Dataset provided by
    DataSuds
    Authors
    Serge Andréfouët; Serge Andréfouët
    License

    https://dataverse.ird.fr/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.23708/ANJCRVhttps://dataverse.ird.fr/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.23708/ANJCRV

    Area covered
    Asia, Indonesia, Japan, Philippines
    Dataset funded by
    IRD (2003-present)
    NASA (2001-2007)
    Description

    The Millennium Coral Reef Mapping Project provides thematic maps of coral reefs worldwide at geomorphological scale. Maps were created by photo-interpretation of Landsat 7 and Landsat 8 satellite images. Maps are provided as standard Shapefiles usable in GIS software. The geomorphological classification scheme is hierarchical and includes 5 levels. The GIS products include for each polygon a number of attributes. The 5 level geomorphological attributes are provided (numerical codes or text). The Level 1 corresponds to the differentiation between oceanic and continental reefs. Then from Levels 2 to 5, the higher the level, the more detailed the thematic classification is. Other binary attributes specify for each polygon if it belongs to terrestrial area (LAND attribute), and sedimentary or hard-bottom reef areas (REEF attribute). Examples and more details on the attributes are provided in the references cited. The products distributed here were created by IRD, in their last version. Shapefiles for 159 atolls of South-East Asia as mapped by the Global coral reef mapping project at geomorphological scale using LANDSAT satellite data (L7 and L8). The data set provides one zip file per country or region of interest. Funded by National Aeronautics and Space Administration, NASA grants NAG5-10908 (University of South Florida, PIs: Franck Muller-Karger and Serge Andréfouët) and CARBON-0000-0257 (NASA, PI: Julie Robinson) from 2001 to 2007. Funded by IRD since 2003 (in kind, PI: Serge Andréfouët).

  20. e

    State map 1:5000 new form vector data - Nový Jičín 9-9

    • data.europa.eu
    Updated Dec 16, 2012
    + more versions
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    (2012). State map 1:5000 new form vector data - Nový Jičín 9-9 [Dataset]. https://data.europa.eu/data/datasets/cz-cuzk-sm5-v-njic99?locale=en
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    Dataset updated
    Dec 16, 2012
    Description

    The product represents a new design of the State Map at a scale of 1:5,000 (SM 5) in vector form, whose advantages are recency and colour processing. The map contains planimetry based on cadastral map, altimetry adopted from the altimetry part of ZABAGED and map lettering based on database of geographic names Geonames and abbreviations of feature type signification coming up from attributes of selected ZABAGED features. This new design of the SM 5 is repeatedly generated once a year on the part of the Czech territory where the vector form of cadastral map is available. Therefore, part of export units (map sheets of SM 5) has not a full coverage (price of such export unit is then proportionally reduced).

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U.S. Geological Survey (2025). USGS Topo Map Vector Data Downloadable Data Collection [Dataset]. https://catalog.data.gov/dataset/usgs-topo-map-vector-data-downloadable-data-collection

USGS Topo Map Vector Data Downloadable Data Collection

Explore at:
Dataset updated
Mar 11, 2025
Dataset provided by
United States Geological Surveyhttp://www.usgs.gov/
Description

Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.

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