100+ datasets found
  1. Natural Earth Counties of the United States - larger scale

    • hub.arcgis.com
    Updated Jun 18, 2025
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    Esri SDI (2025). Natural Earth Counties of the United States - larger scale [Dataset]. https://hub.arcgis.com/datasets/1cccf99d65b641819f83e9963f14d37f
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    Dataset updated
    Jun 18, 2025
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri SDI
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    United States,
    Description

    Polygon layer representing United States counties with name attributes.About Natural EarthNatural Earth is a convenient resource for creating custom maps. Unlike other map data intended for analysis or detailed government mapping, it is designed to meet the needs of cartographers and designers to make generalized maps. Maximum flexibility is a goal.Natural Earth is a public domain collection of map datasets available at 1:10 million (larger scale/more detailed), 1:50 million (medium scale/moderate detail), and 1:110 million (small scale/coarse detail) scales. It features tightly integrated vector and raster data to create a variety of visually pleasing, well-crafted maps with cartography or GIS software. Natural Earth data is made possible by many volunteers and supported by the North American Cartographic Information Society (NACIS).Convenience – Natural Earth solves a problem: finding suitable data for making small-scale maps. In a time when the web is awash in geospatial data, cartographers are forced to waste time sifting through confusing tangles of poorly attributed data to make clean, legible maps. Because your time is valuable, Natural Earth data comes ready to use.Neatness Counts–The carefully generalized linework maintains consistent, recognizable geographic shapes at 1:10m, 1:50m, and 1:110m scales. Natural Earth was built from the ground up, so you will find that all data layers align precisely with one another. For example, where rivers and country borders are one and the same, the lines are coincident.GIS Attributes – Natural Earth, however, is more than just a collection of pretty lines. The data attributes are equally important for mapmaking. Most data contain embedded feature names, which are ranked by relative importance. Other attributes facilitate faster map production, such as width attributes assigned to river segments for creating tapers. Intelligent dataThe attributes assigned to Natural Earth vectors make for efficient mapmaking. Most lines and areas contain embedded feature names, which are ranked by relative importance. Up to eight rankings per data theme allow easy custom map “mashups” to emphasize your subject while de-emphasizing reference features. Other attributes focus on map design. For example, width attributes assigned to rivers allow you to create tapered drainages. Assigning different colors to contiguous country polygons is another task made easier thanks to data attribution.Other key featuresVector features include name attributes and bounding box extents. Know that the Rocky Mountains are larger than the Ozarks.Large polygons are split for more efficient data handling—such as bathymetric layers.Projection-friendly vectors precisely match at 180 degrees longitude. Lines contain enough data points for smooth bending in conic projections, but not so many that computer processing speed suffers.Raster data includes grayscale-shaded relief and cross-blended hypsometric tints derived from the latest NASA SRTM Plus elevation data and tailored to register with Natural Earth Vector.Optimized for use in web mapping applications, with built-in scale attributes to assist features to be shown at different zoom levels.

  2. d

    Lunar Grid Reference System Rasters and Shapefiles

    • catalog.data.gov
    • data.usgs.gov
    • +2more
    Updated Nov 21, 2025
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    U.S. Geological Survey (2025). Lunar Grid Reference System Rasters and Shapefiles [Dataset]. https://catalog.data.gov/dataset/lunar-grid-reference-system-rasters-and-shapefiles
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    Dataset updated
    Nov 21, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    USGS is assessing the feasibility of map projections and grid systems for lunar surface operations. We propose developing a new Lunar Transverse Mercator (LTM), the Lunar Polar Stereographic (LPS), and the Lunar Grid Reference Systems (LGRS). We have also designed additional grids designed to NASA requirements for astronaut navigation, referred to as LGRS in Artemis Condensed Coordinates (ACC), but this is not released here. LTM, LPS, and LGRS are similar in design and use to the Universal Transverse Mercator (UTM), Universal Polar Stereographic (LPS), and Military Grid Reference System (MGRS), but adhere to NASA requirements. LGRS ACC format is similar in design and structure to historic Army Mapping Service Apollo orthotopophoto charts for navigation. The Lunar Transverse Mercator (LTM) projection system is a globalized set of lunar map projections that divides the Moon into zones to provide a uniform coordinate system for accurate spatial representation. It uses a transverse Mercator projection, which maps the Moon into 45 transverse Mercator strips, each 8°, longitude, wide. These transverse Mercator strips are subdivided at the lunar equator for a total of 90 zones. Forty-five in the northern hemisphere and forty-five in the south. LTM specifies a topocentric, rectangular, coordinate system (easting and northing coordinates) for spatial referencing. This projection is commonly used in GIS and surveying for its ability to represent large areas with high positional accuracy while maintaining consistent scale. The Lunar Polar Stereographic (LPS) projection system contains projection specifications for the Moon’s polar regions. It uses a polar stereographic projection, which maps the polar regions onto an azimuthal plane. The LPS system contains 2 zones, each zone is located at the northern and southern poles and is referred to as the LPS northern or LPS southern zone. LPS, like is equatorial counterpart LTM, specifies a topocentric, rectangular, coordinate system (easting and northing coordinates) for spatial referencing. This projection is commonly used in GIS and surveying for its ability to represent large polar areas with high positional accuracy, while maintaining consistent scale across the map region. LGRS is a globalized grid system for lunar navigation supported by the LTM and LPS projections. LGRS provides an alphanumeric grid coordinate structure for both the LTM and LPS systems. This labeling structure is utilized in a similar manner to MGRS. LGRS defines a global area grid based on latitude and longitude and a 25×25 km grid based on LTM and LPS coordinate values. Two implementations of LGRS are used as polar areas require a LPS projection and equatorial areas a transverse Mercator. We describe the difference in the techniques and methods report associated with this data release. Request McClernan et. al. (in-press) for more information. ACC is a method of simplifying LGRS coordinates and is similar in use to the Army Mapping Service Apollo orthotopophoto charts for navigation. These data will be released at a later date. Two versions of the shape files are provided in this data release, PCRS and Display only. See LTM_LPS_LGRS_Shapefiles.zip file. PCRS are limited to a single zone and are projected in either LTM or LPS with topocentric coordinates formatted in Eastings and Northings. Display only shapefiles are formatted in lunar planetocentric latitude and longitude, a Mercator or Equirectangular projection is best for these grids. A description of each grid is provided below: Equatorial (Display Only) Grids: Lunar Transverse Mercator (LTM) Grids: LTM zone borders for each LTM zone Merged LTM zone borders Lunar Polar Stereographic (LPS) Grids: North LPS zone border South LPS zone border Lunar Grid Reference System (LGRS) Grids: Global Areas for North and South LPS zones Merged Global Areas (8°×8° and 8°×10° extended area) for all LTM zones Merged 25km grid for all LTM zones PCRS Shapefiles:` Lunar Transverse Mercator (LTM) Grids: LTM zone borders for each LTM zone Lunar Polar Stereographic (LPS) Grids: North LPS zone border South LPS zone border Lunar Grid Reference System (LGRS) Grids: Global Areas for North and South LPS zones 25km Gird for North and South LPS zones Global Areas (8°×8° and 8°×10° extended area) for each LTM zone 25km grid for each LTM zone The rasters in this data release detail the linear distortions associated with the LTM and LPS system projections. For these products, we utilize the same definitions of distortion as the U.S. State Plane Coordinate System. Scale Factor, k - The scale factor is a ratio that communicates the difference in distances when measured on a map and the distance reported on the reference surface. Symbolically this is the ratio between the maps grid distance and distance on the lunar reference sphere. This value can be precisely calculated and is provided in their defining publication. See Snyder (1987) for derivation of the LPS scale factor. This scale factor is unitless and typically increases from the central scale factor k_0, a projection-defining parameter. For each LPS projection. Request McClernan et. al., (in-press) for more information. Scale Error, (k-1) - Scale-Error, is simply the scale factor differenced from 1. Is a unitless positive or negative value from 0 that is used to express the scale factor’s impact on position values on a map. Distance on the reference surface are expended when (k-1) is positive and contracted when (k-1) is negative. Height Factor, h_F - The Height Factor is used to correct for the difference in distance caused between the lunar surface curvature expressed at different elevations. It is expressed as a ratio between the radius of the lunar reference sphere and elevations measured from the center of the reference sphere. For this work, we utilized a radial distance of 1,737,400 m as recommended by the IAU working group of Rotational Elements (Archinal et. al., 2008). For this calculation, height factor values were derived from a LOLA DEM 118 m v1, Digital Elevation Model (LOLA Science Team, 2021). Combined Factor, C_F – The combined factor is utilized to “Scale-To-Ground” and is used to adjust the distance expressed on the map surface and convert to the position on the actual ground surface. This value is the product of the map scale factor and the height factor, ensuring the positioning measurements can be correctly placed on a map and on the ground. The combined factor is similar to linear distortion in that it is evaluated at the ground, but, as discussed in the next section, differs numerically. Often C_F is scrutinized for map projection optimization. Linear distortion, δ - In keeping with the design definitions of SPCS2022 (Dennis 2023), we refer to scale error when discussing the lunar reference sphere and linear distortion, δ, when discussing the topographic surface. Linear distortion is calculated using C_F simply by subtracting 1. Distances are expended on the topographic surface when δ is positive and compressed when δ is negative. The relevant files associated with the expressed LTM distortion are as follows. The scale factor for the 90 LTM projections: LUNAR_LTM_GLOBAL_PLOT_HEMISPHERES_distortion_K_grid_scale_factor.tif Height Factor for the LTM portion of the Moon: LUNAR_LTM_GLOBAL_PLOT_HEMISPHERES_distortion_EF_elevation_factor.tif Combined Factor in LTM portion of the Moon LUNAR_LTM_GLOBAL_PLOT_HEMISPHERES_distortion_CF_combined_factor.tif The relevant files associated with the expressed LPS distortion are as follows. Lunar North Pole The scale factor for the northern LPS zone: LUNAR_LGRS_NP_PLOT_LPS_K_grid_scale_factor.tif Height Factor for the north pole of the Moon: LUNAR_LGRS_NP_PLOT_LPS_EF_elevation_factor.tif Combined Factor for northern LPS zone: LUNAR_LGRS_NP_PLOT_LPS_CF_combined_factor.tif Lunar South Pole Scale factor for the northern LPS zone: LUNAR_LGRS_SP_PLOT_LPS_K_grid_scale_factor.tif Height Factor for the south pole of the Moon: LUNAR_LGRS_SP_PLOT_LPS_EF_elevation_factor.tif Combined Factor for northern LPS zone: LUNAR_LGRS_SP_PLOT_LPS_CF_combined_factor.tif For GIS utilization of grid shapefiles projected in Lunar Latitude and Longitude, referred to as “Display Only”, please utilize a registered lunar geographic coordinate system (GCS) such as IAU_2015:30100 or ESRI:104903. LTM, LPS, and LGRS PCRS shapefiles utilize either a custom transverse Mercator or polar Stereographic projection. For PCRS grids the LTM and LPS projections are recommended for all LTM, LPS, and LGRS grid sizes. See McClernan et. al. (in-press) for such projections. Raster data was calculated using planetocentric latitude and longitude. A LTM and LPS projection or a registered lunar GCS may be utilized to display this data. Note: All data, shapefiles and rasters, require a specific projection and datum. The projection is recommended as LTM and LPS or, when needed, IAU_2015:30100 or ESRI:104903. The datum utilized must be the Jet Propulsion Laboratory (JPL) Development Ephemeris (DE) 421 in the Mean Earth (ME) Principal Axis Orientation as recommended by the International Astronomy Union (IAU) (Archinal et. al., 2008).

  3. z

    L'Alpe d'Huez: a dataset to benchmark topographic map generalisation

    • zenodo.org
    • data.niaid.nih.gov
    • +1more
    bin, xls
    Updated Jan 19, 2024
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    Guillaume Touya; Guillaume Touya (2024). L'Alpe d'Huez: a dataset to benchmark topographic map generalisation [Dataset]. http://doi.org/10.5281/zenodo.5749324
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    bin, xlsAvailable download formats
    Dataset updated
    Jan 19, 2024
    Dataset provided by
    Zenodo
    Authors
    Guillaume Touya; Guillaume Touya
    License

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

    Area covered
    Huez, Alps
    Description

    This dataset derives from the one used in a past EuroSDR benchmark (http://dx.doi.org/10.1016/j.compenvurbsys.2009.06.002), and should be used as a benchmark for topographic map generalisation techniques. It contains several topographic layers as shapefiles (roads, buildings, rivers, forests, contour lines...), a style description to display the data at the 1:50k scale, and a table of the generalisation constraints that should be respected in this 1:50k scale map.

    The initial data can considered as detailed for maps at the 1:15k scale. The projection of the data is "Lambert II Etendu", EPSG:27572.

    The area is 11*11 km large.

  4. G

    Topographic maps on a scale of 1/100,000

    • open.canada.ca
    • catalogue.arctic-sdi.org
    • +1more
    csv, e00, fgdb/gdb +7
    Updated Nov 19, 2025
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    Government and Municipalities of Québec (2025). Topographic maps on a scale of 1/100,000 [Dataset]. https://open.canada.ca/data/en/dataset/d3812df2-6988-409d-a626-ccbc58a59431
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    html, pdf, wmts, xls, geotif, csv, wms, shp, fgdb/gdb, e00Available download formats
    Dataset updated
    Nov 19, 2025
    Dataset provided by
    Government and Municipalities of Québec
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Time period covered
    Jan 1, 1950 - Jan 1, 2006
    Description

    **Note that topographic maps at a scale of 1/100,000 are no longer updated. For the latest update date, see the metadata. The reference map data is now constituted using a continuous information layer approach: ** * AQNetwork+ * Quebec Hydrographic Network Geobase (GRHQ) * Administrative divisions on a scale of 1/20,000 (SDA) * Regional Coherent Hydro Digital Terrain Models (RTM) _ Topographic maps at a scale of 1/100,000 offer an overview of the occupation of Quebec territory at a scale of 1/100,000. A series in the south (266 sheets) and a series in the north (151 sheets) of the 53rd parallel cover the majority of Quebec. The data is less than 10 meters accurate and each file covers an area of approximately 4,000 km2, equivalent to 16 sheets at a scale of 1/20,000. Main components: * Hydrography (lakes of more than three hectares, permanent watercourses, swamps, etc.). * Vegetation (wooded areas and peatlands of more than 13 hectares). * The constructions of man: * transport infrastructures (passable roads, bridges, airports, etc.); * buildings larger than 12,500 m2; * equipment and designated areas. * The relief (level curves at an equidistance of 20 meters and elevation points). ##### Special features of the series south of the 53rd parallel * The data is obtained by generalizing map data at a scale of 1/20,000. Between the 51st and 53rd parallel, they are extracted from SPOT satellite imagery at 10 meters of resolution. * The data formats available for this series are: * ArcInfo cover (vector); * GeoTIFF, CCL projection (matrix); * GeoTIFF, MTM projection (matrix); * PDF (matrix). ##### Special features of the series north of the 53rd parallel * The data is obtained by generalizing cartographic data from Natural Resources Canada (CanVec product) at a scale of 1:50,000. Multi-source data, namely data from Adresses Québec, data on airports and hydrobases from the Ministère des Transports du Québec, and data on reservoirs from Hydro-Québec, increase the quality of this cartographic product on a scale of 1/100,000. * The data format available for this series is: * FGDB (vector).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

  5. Geospatial data for the Vegetation Mapping Inventory Project of King...

    • catalog.data.gov
    Updated Nov 25, 2025
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    National Park Service (2025). Geospatial data for the Vegetation Mapping Inventory Project of King Mountain National Military Park [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-king-mountain-national-mil
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    Dataset updated
    Nov 25, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Large scale final map products were created within ArcMap and designed to show both the orthophoto coverage and the vegetation maps. For the vegetation maps, colors were assigned and the polygons labeled with the dominant vegetation and modifier and, where present, the second vegetation and modifier. For the orthophoto maps, the photos were simply plotted at the same scale and area coverage as the vegetation maps. Additional planimetric map data included roads, trails, hydrology, boundaries and a UTM coordinate grid. Legends are designed to provide full definitions of the vegetation and buffer classes and modifiers, as well as information about the park, map projection, data sources and authorship (Figure 19). All maps are projected to the Universal Transverse Mercator Coordinate System, North American Datum of 1984, in the local zone for the specific park. Photo Date: 10/24/2000 Area (ac): 3945 Area (ha): 1597 Completion Date: Oct, 2008 Veg Class: 20 Polygons: 382 Avg Polygon Size: 4.18 Map Scale: 1:9,000

  6. w

    Paper map sheets distribution of OKXE at 1:5000 scale and projection EGSA 87...

    • data.wu.ac.at
    kml
    Updated Oct 10, 2013
    + more versions
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    Greece (2013). Paper map sheets distribution of OKXE at 1:5000 scale and projection EGSA 87 KML [Dataset]. https://data.wu.ac.at/schema/datahub_io/YTQyOGVjOTYtOGMzMi00Yjg0LTliYzktMjg0NmQyYzI5MjNl
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    kml(1610027.0)Available download formats
    Dataset updated
    Oct 10, 2013
    Dataset provided by
    Greece
    License

    http://www.opendefinition.org/licenses/cc-by-sahttp://www.opendefinition.org/licenses/cc-by-sa

    Description

    Paper map sheets distribution of OKXE at 1:5000 scale and projection EGSA 87

  7. g

    Topography - State Refence Map layers - PED | gimi9.com

    • gimi9.com
    Updated May 19, 2016
    + more versions
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    (2016). Topography - State Refence Map layers - PED | gimi9.com [Dataset]. https://gimi9.com/dataset/au_431f9e07-7436-4820-9bfd-c90a0a6cc293/
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    Dataset updated
    May 19, 2016
    License

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

    Description

    Abstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. Dataset contains framework layers compiled for representation on state reference map, scale 1:1.5 million. Line and polygon features only. Road, rail, waterbody and watercourse themes included. State coastline not included. ## Purpose Can be used as a framework layer for whole of state mapping or for a generalised framework for regional mapping. Not suitable for analysis. ## Dataset History Information was compiled and digitised in generalised form from 1:250 000 scale hard copy maps. The individual CAD files were combined into seamless form and converted to Lambert Conformal Conic projection, standard parallels 29 degrees and 35 degrees S, central meridian 135 degrees E. Subsequently the information was converted to GIS format and re-projected to the state standard LCC projection. ## Dataset Citation SA Department of Environment, Water and Natural Resources (2015) Topography - State Refence Map layers - PED. Bioregional Assessment Source Dataset. Viewed 12 October 2016, http://data.bioregionalassessments.gov.au/dataset/431f9e07-7436-4820-9bfd-c90a0a6cc293.

  8. u

    Data from: Data products for visualizing of past, current, and alternate...

    • research.usc.edu.au
    • researchdata.edu.au
    zip
    Updated Sep 14, 2021
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    Sanjeev K Srivastava; Gary Scott; Jo Rosier (2021). Data products for visualizing of past, current, and alternate scenarios for an ecologically sensitive coastal spit at a local scale [Dataset]. https://research.usc.edu.au/esploro/outputs/dataset/Data-products-for-visualizing-of-past/99450756102621
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    zip(1175901733 bytes), zip(92133340 bytes)Available download formats
    Dataset updated
    Sep 14, 2021
    Dataset provided by
    University of the Sunshine Coast
    Authors
    Sanjeev K Srivastava; Gary Scott; Jo Rosier
    License

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

    Time period covered
    2018
    Description

    This study presents data products to visualize past, current and alternate scenarios for an ecologically sensitive and development prone area in a sub-tropical coastal spit. Data products are created using a diverse range of geodesign tools that include existing and archived high resolution active and passive remote sensing datasets, existing, derived, and digitized spatial layers together with procedural modelling. The final products include 3d and interactive Cityengine Webscene files and fly-throughs in a generic movie format. While the fly-through movies can be played on standard digital devices, the Cityengine Webscenes once uploaded on ArcGIS website requires an Internet ready device for visualization and interaction.

  9. d

    Data from: Lunar Grid Reference System (LGRS) Terrestrial Navigational...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Oct 30, 2025
    + more versions
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    U.S. Geological Survey (2025). Lunar Grid Reference System (LGRS) Terrestrial Navigational Training Grids in Artemis Condensed Coordinate (ACC) Format [Dataset]. https://catalog.data.gov/dataset/lunar-grid-reference-system-lgrs-terrestrial-navigational-training-grids-in-artemis-conden
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    Dataset updated
    Oct 30, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    USGS is assessing the feasibility of map projections and grid systems for lunar surface operations. We propose developing a new Lunar Transverse Mercator (LTM), the Lunar Polar Stereographic (LPS), and the Lunar Grid Reference Systems (LGRS). We have also designed additional grids to meet NASA requirements for astronaut navigation, referred to as LGRS in Artemis Condensed Coordinates (ACC). This data release includes LGRS grids finer than 25km (1km, 100m, and 10m) in ACC format for a small number of terrestrial analog sites of interest. The grids contained in this data release are projected in the terrestrial Universal Transverse Mercator (UTM) Projected Coordinate Reference System (PCRS) using the World Geodetic System of 1984 (WGS84) as its reference datum. A small number of geotiffs used to related the linear distortion the UTM and WGS84 systems imposes on the analog sites include: 1) a clipped USGS Nation Elevation Dataset (NED) Digital Elevation Model (DEM); 2) the grid scale factor of the UTM zone the data is projected in, 3) the height factor based on the USGS NED DEM, 4) the combined factor, and 5) linear distortion calculated in parts-per-million (PPM). Geotiffs are projected from WGS84 in a UTM PCRS zone. Distortion calculations are based on the methods State Plane Coordinate System of 2022. See Dennis (2021; https://www.fig.net/resources/proceedings/fig_proceedings/fig2023/papers/cinema03/CINEMA03_dennis_12044.pdf) for more information. Coarser grids, (>=25km) such as the lunar LTM, LPS, and LGRS grids are not released here but may be acceded from https://doi.org/10.5066/P13YPWQD and displayed using a lunar datum. LTM, LPS, and LGRS are similar in design and use to the Universal Transverse Mercator (UTM), Universal Polar Stereographic (LPS), and Military Grid Reference System (MGRS), but adhere to NASA requirements. LGRS ACC format is similar in design and structure to historic Army Mapping Service Apollo orthotopophoto charts for navigation. Terrestrial Locations and associated LGRS ACC Grids and Files: Projection Location Files UTM 11N Yucca Flat 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile USGS 1/3" DEM Geotiff UTM Projection Scale Factor Geotiff Map Height Factor Geotiff Map Combined Factor Geotiff Map Linear Distortion Geotiff UTM 12N Buffalo Park 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile USGS 1/3" DEM Geotiff UTM Projection Scale Factor Geotiff Map Height Factor Geotiff Map Combined Factor Geotiff Map Linear Distortion Geotiff Cinder Lake 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile USGS 1/3" DEM Geotiff UTM Projection Scale Factor Geotiff Map Height Factor Geotiff Map Combined Factor Geotiff Map Linear Distortion Geotiff JETT3 Arizona 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile USGS 1/3" DEM Geotiff UTM Projection Scale Factor Geotiff Map Height Factor Geotiff Map Combined Factor Geotiff Map Linear Distortion Geotiff JETT5 Arizona 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile USGS 1/3" DEM Geotiff UTM Projection Scale Factor Geotiff Map Height Factor Geotiff Map Combined Factor Geotiff Map Linear Distortion Geotiff Meteor Crater 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile USGS 1/3" DEM Geotiff UTM Projection Scale Factor Geotiff Map Height Factor Geotiff Map Combined Factor Geotiff Map Linear Distortion Geotiff UTM 13N HAATS 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile 1km Grid Shapefile Derby LZ Clip 100m Grid Shapefile Derby LZ Clip 10m Grid Shapefile Derby LZ Clip 1km Grid Shapefile Eagle County Regional Airport KEGE Clip 100m Grid Shapefile Eagle County Regional Airport KEGE Clip 10m Grid Shapefile Eagle County Regional Airport KEGE Clip 1km Grid Shapefile Windy Point LZ Clip 100m Grid Shapefile Windy Point LZ Clip 10m Grid Shapefile Windy Point LZ Clip USGS 1/3" DEM Geotiff UTM Projection Scale Factor Geotiff Map Height Factor Geotiff Map Combined Factor Geotiff Map Linear Distortion Geotiff UTM 15N Johnson Space Center 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile USGS 1/3" DEM Geotiff UTM Projection Scale Factor Geotiff Map Height Factor Geotiff Map Combined Factor Geotiff Map Linear Distortion Geotiff UTM 28N JETT2 Icelandic Highlands 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile USGS 1/3" DEM Geotiff UTM Projection Scale Factor Geotiff Map Height Factor Geotiff Map Combined Factor Geotiff Map Linear Distortion Geotiff The shapefiles and rasters utilize UTM projections. For GIS utilization of grid shapefiles projected in Lunar Latitude and Longitude should utilize a registered PCRS. To select the correct UTM EPSG code, determine the zone based on longitude (zones are 6° wide, numbered 1–60 from 180°W) and hemisphere (Northern Hemisphere uses EPSG:326XX; Southern Hemisphere uses EPSG:327XX), where XX is the zone number. For display in display in latitude and longitude, select a correct WGS84 EPSG code, such as EPSG:4326. Note: The Lunar Transverse Mercator (LTM) projection system is a globalized set of lunar map projections that divides the Moon into zones to provide a uniform coordinate system for accurate spatial representation. It uses a Transverse Mercator projection, which maps the Moon into 45 transverse Mercator strips, each 8°, longitude, wide. These Transverse Mercator strips are subdivided at the lunar equator for a total of 90 zones. Forty-five in the northern hemisphere and forty-five in the south. LTM specifies a topocentric, rectangular, coordinate system (easting and northing coordinates) for spatial referencing. This projection is commonly used in GIS and surveying for its ability to represent large areas with high positional accuracy while maintaining consistent scale. The Lunar Polar Stereographic (LPS) projection system contains projection specifications for the Moon’s polar regions. It uses a polar stereographic projection, which maps the polar regions onto an azimuthal plane. The LPS system contains 2 zones, each zone is located at the northern and southern poles and is referred to as the LPS northern or LPS southern zone. LPS, like its equatorial counterpart LTM, specifies a topocentric, rectangular, coordinate system (easting and northing coordinates) for spatial referencing. This projection is commonly used in GIS and surveying for its ability to represent large polar areas with high positional accuracy while maintaining consistent scale across the map region. LGRS is a globalized grid system for lunar navigation supported by the LTM and LPS projections. LGRS provides an alphanumeric grid coordinate structure for both the LTM and LPS systems. This labeling structure is utilized similarly to MGRS. LGRS defines a global area grid based on latitude and longitude and a 25×25 km grid based on LTM and LPS coordinate values. Two implementations of LGRS are used as polar areas require an LPS projection and equatorial areas a Transverse Mercator. We describe the differences in the techniques and methods reported in this data release. Request McClernan et. al. (in-press) for more information. ACC is a method of simplifying LGRS coordinates and is similar in use to the Army Mapping Service Apollo orthotopophoto charts for navigation. These grids are designed to condense a full LGRS coordinate to a relative coordinate of 6 characters in length. LGRS in ACC format is completed by imposing a 1km grid within the LGRS 25km grid, then truncating the grid precision to 10m. To me the character limit, a coordinate is reported as a relative value to the lower-left corner of the 25km LGRS zone without the zone information; However, zone information can be reported. As implemented, and 25km^2 area on the lunar surface will have a set of a unique set of ACC coordinates to report locations The shape files provided in this data release are projected in the LTM or LPS PCRSs and must utilize these projections to be dimensioned correctly.

  10. e

    WMS TopPlusOpen - TopPlusOpen Light Grey

    • data.europa.eu
    • gimi9.com
    wms
    Updated Apr 16, 2025
    + more versions
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    Dienstleistungszentrum des Bundes für Geoinformation und Geodäsie (2025). WMS TopPlusOpen - TopPlusOpen Light Grey [Dataset]. https://data.europa.eu/88u/dataset/c5da0f3b-484e-9121-685b-a77d025958b5
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    wmsAvailable download formats
    Dataset updated
    Apr 16, 2025
    Dataset authored and provided by
    Dienstleistungszentrum des Bundes für Geoinformation und Geodäsie
    Description

    Presentation service (WMS) for a freely usable worldwide uniform web map based on free and official data sources.In the product, among other things, free official geodata of the federal government and the open data countries Berlin, Brandenburg, Hamburg, North Rhine-Westphalia, Saxony and Thuringia are presented. In addition, Mecklenburg-Western Pomerania and Rhineland-Palatinate provide their official spatial data for the TopPlusOpen within the framework of a cooperation agreement, so that these countries are also represented exclusively by official data.In the other federal states and abroad, OSM data is mainly used in the corresponding zoom levels, which from the point of view of the BKG meet all quality requirements and can be combined almost seamlessly with the official data.The web services of the TopPlusOpen are offered via the standardized interfaces WMS and WMTS and are high-performance.There are 4 different variants offered: - TopPlusOpen: Very detailed map display in solid colors - TopPlusOpen grayscale: Content identical to the full-tone version; Automatically generated grayscale - TopPlusOpen Light: Content reduced compared to the full-tone version; Subtle colour scheme - TopPlusOpen Light Grey: Content identical to the TopPlusOpen Light; Presentation in shades of grey and individual discreet colors (waters, borders)The TopPlusOpen web map is produced in two projections: - Pseudo-Mercator projection (EPSG:3857) - UTM32 (EPSG:25832)Pseudo-Mercator projection: The web map has 19 scale levels in this projection and is divided into three different display areas: - Worldwide representation for small scales - Europe-wide representation for medium scales - Detailed representation for Germany and the adjacent foreign countriesProjection UTM32: The web map has 14 scale levels in this projection and is divided into two display areas: - Europe-wide representation for medium scales - Detailed representation for Germany and neighbouring countries: The Layer TopPlusOpen-Light-Grey is well suited for use as a background map and has a reduced content compared to the solid version of the TopPlusOpen. The illustration is done in gray tones and individual pale colors (borders, waters).

  11. d

    Waterloo 1:250 000, R502 historical topographic map

    • data.gov.au
    jpeg
    Updated Aug 4, 2019
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    Division of National Mapping (2019). Waterloo 1:250 000, R502 historical topographic map [Dataset]. https://data.gov.au/dataset/ds-ga-e716d312-c9fc-63fa-e044-00144fdd4fa6/details?q=
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    jpegAvailable download formats
    Dataset updated
    Aug 4, 2019
    Dataset provided by
    Division of National Mapping
    License

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

    Description

    The R502 series of maps has been replaced by the National Topographic Map Series (NTMS). The R502 series consists of 542 map sheets and covers Australia at a scale of 1:250,000. It was compiled from aerial photography, but only about one quarter of the series was contoured. The standard sheet size is 1 degree of latitude by 1.5 degrees of longitude. Transverse Mercator map projection and Clark 1858 datum were used. Coverage of the country was completed in 1968. The R502 series of maps has been replaced by the National Topographic Map Series (NTMS). The R502 series consists of 542 map sheets and covers Australia at a scale of 1:250,000. It was compiled from aerial photography, but only about one quarter of the series was contoured. The standard sheet size is 1 degree of latitude by 1.5 degrees of longitude. Transverse Mercator map projection and Clark 1858 datum were used. Coverage of the country was completed in 1968.

  12. r

    Map

    • opendata.rcmrd.org
    Updated Oct 21, 2022
    + more versions
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    dermotobrien (2022). Map [Dataset]. https://opendata.rcmrd.org/maps/5f21a411283f4f3f9faa89d1d04f3b21
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    Dataset updated
    Oct 21, 2022
    Dataset authored and provided by
    dermotobrien
    License

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

    Area covered
    Description

    This map contains two layers, more information on the layers can be found here:NZ ImageryNZ Hybrid ReferenceProjectionNew Zealand Transverse Mercator 2000 (NZTM2000).Scale/zoom levels:Available scale levelsLevel 0 - 23 (1:591,657,527 - 1:70)About NZ ImageryThe New Zealand Imagery map is created by Eagle Technology and uses the best available publicly owned high resolution imagery.The map combines high resolution imagery (0.075m - 1.25m) that covers around 95% of New Zealand with the New Zealand 10m Aerial Imagery. The 10m imagery is used for the smaller scales for a more consistent map and for areas where no high resolution imagery is available. This map is updated regularly with the latest high resolution imagery.A layer with the imagery footprints and metadata is available here.About NZ Hybrid ReferenceThis vector tile layer provides a detailed reference layer for New Zealand in the NZ Transverse Mercator projection. The style is based on the Esri World Hybrid Imagery style. This vector tile layer provides unique capabilities for customization and high-resolution display. This map includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, and administrative boundaries for added context.This layer is offered by Eagle Technology (Official Esri Distributor). Eagle Technology offers services that can be used in the ArcGIS platform. The Content team at Eagle Technology updates the layers on a regular basis and regularly adds new content to the Living Atlas. By using this content and combining it with other data you can create new information products quickly and easily.If you have any questions or remarks about the content, please let us know at livingatlas@eagle.co.nz

  13. BGS Geophysical maps - Dataset - data.gov.uk

    • ckan.publishing.service.gov.uk
    Updated Jun 15, 2024
    + more versions
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    ckan.publishing.service.gov.uk (2024). BGS Geophysical maps - Dataset - data.gov.uk [Dataset]. https://ckan.publishing.service.gov.uk/dataset/bgs-geophysical-maps
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    Dataset updated
    Jun 15, 2024
    Dataset provided by
    CKANhttps://ckan.org/
    Description

    A collection of 1:250 000 scale geophysical maps in the Universal Transverse Mercator (UTM) projection, covering the United Kingdom and continental shelf areas between 1975 – 1990. Mapping is divided into squares which cover 1 degree by 1 degree of latitude / longitude. A geophysical map is a graphical representation of data collected through various geophysical methods to investigate the subsurface characteristics of the Earth. Geophysics is the study of the physical properties and processes of the Earth using measurements of physical quantities such as gravity, magnetic fields, seismic waves, electrical resistivity, and others. The collection includes aeromagnetic anomaly maps (1975 – 1990), Bouguer gravity anomaly maps (1975 – 1989) and a small number of free air anomaly maps (1981 – 1989). These maps are hard-copy paper records stored in the National Geoscience Data Centre (NGDC) and are delivered as digital scans through the BGS website.

  14. A

    Geospatial data for the Vegetation Mapping Inventory Project of Mammoth Cave...

    • data.amerigeoss.org
    • catalog.data.gov
    api, zip
    Updated Jul 30, 2019
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    United States[old] (2019). Geospatial data for the Vegetation Mapping Inventory Project of Mammoth Cave National Park [Dataset]. https://data.amerigeoss.org/fi/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-mammoth-cave-national-park
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    api, zipAvailable download formats
    Dataset updated
    Jul 30, 2019
    Dataset provided by
    United States[old]
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles.

    Large scale final map products were created within ArcMap and designed to show both the orthophoto coverage and the vegetation maps. For the vegetation maps, colors were assigned and the polygons labeled with the dominant vegetation and modifier and, where present, the second vegetation and modifier. For the orthophoto maps, the photos were simply plotted at the same scale and area coverage as the vegetation maps. Additional planimetric map data included roads, trails, hydrology, boundaries and a UTM coordinate grid. Legends are designed to provide full definitions of the vegetation and buffer classes and modifiers, as well as information about the park, map projection, data sources and authorship. All maps are projected to the Universal Transverse Mercator Coordinate System, North American Datum of 1984, in the local zone for the specific park

    Map information- Veg Classes: 35 Polygons: 7,907 Avg Polygon size(ha) 2.58 Map Scale: 1:26,000

  15. Geospatial Data Pack for Visualization

    • kaggle.com
    zip
    Updated Oct 21, 2025
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    Vega Datasets (2025). Geospatial Data Pack for Visualization [Dataset]. https://www.kaggle.com/datasets/vega-datasets/geospatial-data-pack
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    zip(1422109 bytes)Available download formats
    Dataset updated
    Oct 21, 2025
    Dataset authored and provided by
    Vega Datasets
    Description

    Geospatial Data Pack for Visualization 🗺️

    Learn Geographic Mapping with Altair, Vega-Lite and Vega using Curated Datasets

    Complete geographic and geophysical data collection for mapping and visualization. This consolidation includes 18 complementary datasets used by 31+ Vega, Vega-Lite, and Altair examples 📊. Perfect for learning geographic visualization techniques including projections, choropleths, point maps, vector fields, and interactive displays.

    Source data lives on GitHub and can also be accessed via CDN. The vega-datasets project serves as a common repository for example datasets used across these visualization libraries and related projects.

    Why Use This Dataset? 🤔

    • Comprehensive Geospatial Types: Explore a variety of core geospatial data models:
      • Vector Data: Includes points (like airports.csv), lines (like londonTubeLines.json), and polygons (like us-10m.json).
      • Raster-like Data: Work with gridded datasets (like windvectors.csv, annual-precip.json).
    • Diverse Formats: Gain experience with standard and efficient geospatial formats like GeoJSON (see Table 1, 2, 4), compressed TopoJSON (see Table 1), and plain CSV/TSV (see Table 2, 3, 4) for point data and attribute tables ready for joining.
    • Multi-Scale Coverage: Practice visualization across different geographic scales, from global and national (Table 1, 4) down to the city level (Table 1).
    • Rich Thematic Mapping: Includes multiple datasets (Table 3) specifically designed for joining attributes to geographic boundaries (like states or counties from Table 1) to create insightful choropleth maps.
    • Ready-to-Use & Example-Driven: Cleaned datasets tightly integrated with 31+ official examples (see Appendix) from Altair, Vega-Lite, and Vega, allowing you to immediately practice techniques like projections, point maps, network maps, and interactive displays.
    • Python Friendly: Works seamlessly with essential Python libraries like Altair (which can directly read TopoJSON/GeoJSON), Pandas, and GeoPandas, fitting perfectly into the Kaggle notebook environment.

    Table of Contents

    Dataset Inventory 🗂️

    This pack includes 18 datasets covering base maps, reference points, statistical data for choropleths, and geophysical data.

    1. BASE MAP BOUNDARIES (Topological Data)

    DatasetFileSizeFormatLicenseDescriptionKey Fields / Join Info
    US Map (1:10m)us-10m.json627 KBTopoJSONCC-BY-4.0US state and county boundaries. Contains states and counties objects. Ideal for choropleths.id (FIPS code) property on geometries
    World Map (1:110m)world-110m.json117 KBTopoJSONCC-BY-4.0World country boundaries. Contains countries object. Suitable for world-scale viz.id property on geometries
    London BoroughslondonBoroughs.json14 KBTopoJSONCC-BY-4.0London borough boundaries.properties.BOROUGHN (name)
    London CentroidslondonCentroids.json2 KBGeoJSONCC-BY-4.0Center points for London boroughs.properties.id, properties.name
    London Tube LineslondonTubeLines.json78 KBGeoJSONCC-BY-4.0London Underground network lines.properties.name, properties.color

    2. GEOGRAPHIC REFERENCE POINTS (Point Data) 📍

    DatasetFileSizeFormatLicenseDescriptionKey Fields / Join Info
    US Airportsairports.csv205 KBCSVPublic DomainUS airports with codes and coordinates.iata, state, `l...
  16. n

    Fisher Massif Satellite Image Map 1:100 000

    • access.earthdata.nasa.gov
    • researchdata.edu.au
    • +1more
    cfm
    Updated May 17, 2018
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    (2018). Fisher Massif Satellite Image Map 1:100 000 [Dataset]. https://access.earthdata.nasa.gov/collections/C1214308554-AU_AADC
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    cfmAvailable download formats
    Dataset updated
    May 17, 2018
    Time period covered
    Jul 1, 1992 - Jul 31, 1992
    Area covered
    Description

    Satellite image map of Fisher Massif, Mac. Robertson Land, Antarctica. This map was produced for the Australian Antarctic Division by AUSLIG (now Geoscience Australia) Commercial, in Australia, in 1992. The map is at a scale of 1:100000, and was produced from Landsat TM scenes (WRS 128-111, 129-110). It is projected on a Transverse Mercator projection, and shows glaciers/ice shelves and gives some historical text information. The map has both geographical and UTM co-ordinates.

  17. n

    Permafrost Map of Alaska, USA, Version 1

    • cmr.earthdata.nasa.gov
    • dataone.org
    • +4more
    not provided
    Updated Oct 7, 2025
    + more versions
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    (2025). Permafrost Map of Alaska, USA, Version 1 [Dataset]. http://doi.org/10.7265/x4fx-9m44
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    not providedAvailable download formats
    Dataset updated
    Oct 7, 2025
    Time period covered
    Jan 1, 1970 - Present
    Area covered
    Description

    This data set consists of a geo-referenced digital map and attribute data derived from the publication 'Permafrost map of Alaska'. The map is presented at a scale of 1 to 2,500,000 and shows the correlation of physiographic province to presence of permafrost across the state of Alaska. The digital data were prepared under the U.S. Geological Survey Global Change Program, Land Data Systems - Arctic Land Processes Studies for display and analysis of terrain. The line work was captured by hand digitizing the source map, Ferrians, O.J., 1965, Permafrost map of Alaska - U.S. Geological Survey Miscellaneous Geologic Investigations Map I-445. Scale 1 to 2,500,000. The digital map was assembled and edited in ARC/INFO. The source map projection is polyconic. It is based on the Clarke 1866 ellipsoid with a central meridian of 150 W longitude. The data were geo-referenced from digitizer coordinates to the polyconic projection and then projected into an Albers Equal Area projection. The coastline was taken from the U.S Geological Survey, 1 to 2,000,000 scale Digital Line Graph data (U.S. Geological Survey, 1987). Attributes for the permafrost map were assigned. Metadata documentation was completed in 1996. The map units are closed polygons that are generalized in shape and size. They are defined in terms of their physiographic characteristics and association with permafrost. Each unit differs with respect to all other units and is uniquely identified as follows. 11 Mountainous Area underlain by continuous permafrost 12 Mountainous Area underlain by discontinuous permafrost 13 Mountainous Area underlain by isolated masses of permafrost 21 Lowland and Upland Area underlain by thick permafrost 22 Lowland and Upland Area underlain by moderately thick to thin permafrost 23 Lowland and Upland Area underlain by discontinuous permafrost 24 Lowland and Upland Area underlain by numerous isolated masses of permafrost 25 Lowland and Upland Area underlain by isolated masses of permafrost 26 Lowland and Upland Area generally free of permafrost

    Use constraints - The U.S. Geological Survey should be acknowledged as the data source in products derived from these data. The data are general in nature and should not be used at a scale larger than 1 to 2,500,000, that of the original map. Users must assume responsibility to determine the usability of this data for their purposes. The use of these data is not restricted and may be interpreted by organizations, agencies, units of government or others; however, they are responsible for its appropriate application. Digital data files are periodically updated. Files are dated and users are responsible for obtaining the latest revisions of the data. Although these data have been processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made by the agency regarding the utility of the data on any other system, nor shall the act of distribution constitute any such warranty. A copy of this map is presented on the CAPS Version 1.0 CD-ROM, June 1998.

  18. u

    Topographic maps on a scale of 1/100,000 - Catalogue - Canadian Urban Data...

    • data.urbandatacentre.ca
    Updated Oct 19, 2025
    + more versions
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    (2025). Topographic maps on a scale of 1/100,000 - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/gov-canada-d3812df2-6988-409d-a626-ccbc58a59431
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    Dataset updated
    Oct 19, 2025
    Area covered
    Canada
    Description

    Note that topographic maps at a scale of 1/100,000 are no longer updated. For the latest update date, see the metadata. The reference cartographic data is now constituted according to a continuous information layer approach: * AQRéseau+ * Geobase of the Quebec Hydrographic Network (GRHQ) * Administrative divisions at the scale of 1/20,000 (SDA)] (https://www.donneesquebec.ca/recherche/fr/dataset/decoupages-administratifs) * Geobase of the hydrographic terrain network of Quebec (GRHQ) * Administrative divisions at the scale of 1/20,000 (SDA) _ Topographic maps at a scale of 1/100,000 offer an overview of the occupation of Quebec territory at a scale of 1/100,000. A series in the south (266 sheets) and a series in the north (151 sheets) of the 53rd parallel cover the majority of Quebec. The data is less than 10 meters accurate and each file covers an area of approximately 4,000 km2, equivalent to 16 sheets at a scale of 1/20,000. Main components: * Hydrography (lakes of more than three hectares, permanent watercourses, swamps, etc.). * Vegetation (wooded areas and peatlands of more than 13 hectares). * Human constructions: * transport infrastructures (motorable roads, bridges, airports, etc.); * buildings larger than 12,500 m2; * buildings larger than 12,500 m2; * equipment and designated areas. * The relief (level curves at an equidistance). of 20 meters and elevation points). ##### Special features of the series south of the 53rd parallel * The data are obtained by a generalization of map data on a scale of 1/20,000. Between the 51st and the 53rd parallel, they are extracted from SPOT satellite imagery at 10 meters of resolution. * The data formats available for this series are: * Cover ArcInfo (vector); * GeoTIFF, CCL projection (matrix); * GeoTIFF, MTM projection (matrix); * GeoTIFF, MTM projection (matrix); * PDF (matrix); * PDF (matrix). ##### Special features of the series north of the 53rd parallel * The data is obtained by a generalization of map data from Natural Resources Canada (CanVec product) at a scale of 1:50,000. Multi-source data, namely data from Adresses Québec, data on airports and hydrobases from the Ministère des Transports du Québec, and data on reservoirs from Hydro-Québec, increase the quality of this cartographic product on a scale of 1/100,000. * The data format available for this series is: * FGDB (vector).This third party metadata element was translated using an automated translation tool (Amazon Translate).

  19. Geospatial data for the Vegetation Mapping Inventory Project of Russell Cave...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Nov 14, 2025
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    National Park Service (2025). Geospatial data for the Vegetation Mapping Inventory Project of Russell Cave National Monument [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-russell-cave-national-monu
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    Dataset updated
    Nov 14, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Large scale final map products were created within ArcMap and designed to show both the orthophoto coverage and the vegetation maps. For the vegetation maps, colors were assigned and the polygons labeled with the dominant vegetation and modifier and, where present, the second vegetation and modifier. For the orthophoto maps, the photos were simply plotted at the same scale and area coverage as the vegetation maps. Additional planimetric map data included roads, trails, hydrology, boundaries and a UTM coordinate grid. Legends are designed to provide full definitions of the vegetation and buffer classes and modifiers, as well as information about the park, map projection, data sources and authorship (Figure 19). All maps are projected to the Universal Transverse Mercator Coordinate System, North American Datum of 1984, in the local zone for the specific park.

  20. e

    Topographic maps — WMS and WMTS services

    • data.europa.eu
    unknown
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    Administration du cadastre et de la topographie, Topographic maps — WMS and WMTS services [Dataset]. https://data.europa.eu/data/datasets/cartes-topographiques-services-wms-et-wmts
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    unknownAvailable download formats
    Dataset authored and provided by
    Administration du cadastre et de la topographie
    Description

    These are topographic maps produced and managed by the cadastre and topography administration, particularly for scales 1:5000, 1:20000, 1:50000, 1:100000 and 1:250000. The maps are originally made in the national datum LUREF (projection TM)

    These maps are derived from cartographic databases at different scales, based on an overflight followed by a field check.

    The rate of update varies from 6 to 7 years for large scales to 10 years for small scales.

    The current editions are:

    — 1:5000 -> 2015 (2013 overview) — 1:20.000 -> 2015 (2013 overview) — 1:50.000 -> 2007 — 1:100.000 -> 2011 — 1:250,000 -> 2010

    They are available as WMS and WMTS web services.

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Esri SDI (2025). Natural Earth Counties of the United States - larger scale [Dataset]. https://hub.arcgis.com/datasets/1cccf99d65b641819f83e9963f14d37f
Organization logo

Natural Earth Counties of the United States - larger scale

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Dataset updated
Jun 18, 2025
Dataset provided by
Esrihttp://esri.com/
Authors
Esri SDI
License

CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically

Area covered
United States,
Description

Polygon layer representing United States counties with name attributes.About Natural EarthNatural Earth is a convenient resource for creating custom maps. Unlike other map data intended for analysis or detailed government mapping, it is designed to meet the needs of cartographers and designers to make generalized maps. Maximum flexibility is a goal.Natural Earth is a public domain collection of map datasets available at 1:10 million (larger scale/more detailed), 1:50 million (medium scale/moderate detail), and 1:110 million (small scale/coarse detail) scales. It features tightly integrated vector and raster data to create a variety of visually pleasing, well-crafted maps with cartography or GIS software. Natural Earth data is made possible by many volunteers and supported by the North American Cartographic Information Society (NACIS).Convenience – Natural Earth solves a problem: finding suitable data for making small-scale maps. In a time when the web is awash in geospatial data, cartographers are forced to waste time sifting through confusing tangles of poorly attributed data to make clean, legible maps. Because your time is valuable, Natural Earth data comes ready to use.Neatness Counts–The carefully generalized linework maintains consistent, recognizable geographic shapes at 1:10m, 1:50m, and 1:110m scales. Natural Earth was built from the ground up, so you will find that all data layers align precisely with one another. For example, where rivers and country borders are one and the same, the lines are coincident.GIS Attributes – Natural Earth, however, is more than just a collection of pretty lines. The data attributes are equally important for mapmaking. Most data contain embedded feature names, which are ranked by relative importance. Other attributes facilitate faster map production, such as width attributes assigned to river segments for creating tapers. Intelligent dataThe attributes assigned to Natural Earth vectors make for efficient mapmaking. Most lines and areas contain embedded feature names, which are ranked by relative importance. Up to eight rankings per data theme allow easy custom map “mashups” to emphasize your subject while de-emphasizing reference features. Other attributes focus on map design. For example, width attributes assigned to rivers allow you to create tapered drainages. Assigning different colors to contiguous country polygons is another task made easier thanks to data attribution.Other key featuresVector features include name attributes and bounding box extents. Know that the Rocky Mountains are larger than the Ozarks.Large polygons are split for more efficient data handling—such as bathymetric layers.Projection-friendly vectors precisely match at 180 degrees longitude. Lines contain enough data points for smooth bending in conic projections, but not so many that computer processing speed suffers.Raster data includes grayscale-shaded relief and cross-blended hypsometric tints derived from the latest NASA SRTM Plus elevation data and tailored to register with Natural Earth Vector.Optimized for use in web mapping applications, with built-in scale attributes to assist features to be shown at different zoom levels.

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