100+ datasets found
  1. d

    Raster map of CONUS forest change frequency from 1985-2020

    • catalog.data.gov
    • data.usgs.gov
    Updated Nov 27, 2025
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    U.S. Geological Survey (2025). Raster map of CONUS forest change frequency from 1985-2020 [Dataset]. https://catalog.data.gov/dataset/raster-map-of-conus-forest-change-frequency-from-1985-2020
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    Dataset updated
    Nov 27, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    We summarized annual remote sensing land cover classifications from the U.S. Geological Survey Land Cover Monitoring, Assessment, and Projection (LCMAP) annual time series to characterize forest change across the conterminous United States (CONUS) for the years 1985-2020. The raster output includes a map where each pixel is given an integer value based on the number of years in which it was classified as forest across the annual LCMAP time series. Values of 36 indicate the pixel was classified as forest across all years while a value of 0 indicates forests (tree cover) was never detected during the time series.

  2. N

    Land Cover Raster Data (2017) – 6in Resolution

    • data.cityofnewyork.us
    • s.cnmilf.com
    • +2more
    csv, xlsx, xml
    Updated Dec 7, 2018
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    Office of Technology and Innovation (OTI) (2018). Land Cover Raster Data (2017) – 6in Resolution [Dataset]. https://data.cityofnewyork.us/Environment/Land-Cover-Raster-Data-2017-6in-Resolution/he6d-2qns
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    xml, xlsx, csvAvailable download formats
    Dataset updated
    Dec 7, 2018
    Dataset authored and provided by
    Office of Technology and Innovation (OTI)
    Description

    A 6-in resolution 8-class land cover dataset derived from the 2017 Light Detection and Ranging (LiDAR) data capture. This dataset was developed as part of an updated urban tree canopy assessment and therefore represents a ''top-down" mapping perspective in which tree canopy overhanging features is assigned to the tree canopy class. The eight land cover classes mapped were: (1) Tree Canopy, (2) Grass\Shrubs, (3) Bare Soil, (4) Water, (5) Buildings, (6) Roads, (7) Other Impervious, and (8) Railroads. The primary sources used to derive this land cover layer were 2017 LiDAR (1-ft post spacing) and 2016 4-band orthoimagery (0.5-ft resolution). Object based image analysis was used to automate land-cover features using LiDAR point clouds and derivatives, orthoimagery, and vector GIS datasets -- City Boundary (2017, NYC DoITT) Buildings (2017, NYC DoITT) Hydrography (2014, NYC DoITT) LiDAR Hydro Breaklines (2017, NYC DoITT) Transportation Structures (2014, NYC DoITT) Roadbed (2014, NYC DoITT) Road Centerlines (2014, NYC DoITT) Railroads (2014, NYC DoITT) Green Roofs (date unknown, NYC Parks) Parking Lots (2014, NYC DoITT) Parks (2016, NYC Parks) Sidewalks (2014, NYC DoITT) Synthetic Turf (2018, NYC Parks) Wetlands (2014, NYC Parks) Shoreline (2014, NYC DoITT) Plazas (2014, NYC DoITT) Utility Poles (2014, ConEdison via NYCEM) Athletic Facilities (2017, NYC Parks)

    For the purposes of classification, only vegetation > 8 ft were classed as Tree Canopy. Vegetation below 8 ft was classed as Grass/Shrub.

    To learn more about this dataset, visit the interactive "Understanding the 2017 New York City LiDAR Capture" Story Map -- https://maps.nyc.gov/lidar/2017/ Please see the following link for additional documentation on this dataset -- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_LandCover.md

  3. G

    Digital Topographic Raster Maps, 1944-2012

    • open.canada.ca
    • gimi9.com
    geopdf, geotif, kmz +2
    Updated Feb 1, 2022
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    Natural Resources Canada (2022). Digital Topographic Raster Maps, 1944-2012 [Dataset]. https://open.canada.ca/data/en/dataset/d248b5be-5887-4cfb-942f-d425d82e6ea9
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    pdf, tiff, geotif, kmz, geopdfAvailable download formats
    Dataset updated
    Feb 1, 2022
    Dataset provided by
    Natural Resources Canada
    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, 1944 - Jan 1, 2012
    Description

    This group of maps, which includes the CanMatrix and CanTopo collections, is now a legacy product that is no longer maintained. It may not meet current government standards. Natural Resources Canada's (NRCan) topographic raster maps provide a representation of the topographic phenomena of the Canadian landmass. Several editions of paper maps have been produced over time in order to offer improved products compared to their predecessors in terms of quality and the most up to date information possible. The georeferenced maps can be used in a Geographic Information System (GIS). In all cases, they accurately represent the topographical data available for the date indicated (validity date). The combination of CanMatrix and CanTopo data provides complete national coverage. • CanMatrix - Print Ready: Raster maps produced by scanning topographic maps at scales from 1:25 000 to 1:1 000 000. This product is not georeferenced. Validity dates: 1944 to 2005 (1980 on average). Available formats: PDF and TIFF • CanMatrix - Georeferenced: Raster maps produced by scanning topographic maps at scales of 1:50 000 and 1:250 000. These maps are georeferenced according to the 1983 North American Reference System (NAD 83). Validity dates: 1944 to 2005 (1980 on average). Available format: GeoTIFF • CanTopo: Digital raster maps produced mainly from the GeoBase initiative, NRCan digital topographic data, and other sources. Approximately 2,234 datasets (maps) at scale of 1:50 000, primarily covering northern Canada, are available. CanTopo datasets in GeoPDF and GeoTIFF format are georeferenced according to the 1983 North American Reference System (NAD 83). Validity dates: 1946 to 2012 (2007 on average). Available formats: PDF, GeoPDF, TIFF and GeoTIFF

  4. E

    Land Cover Map 2000 (25m raster, GB)

    • catalogue.ceh.ac.uk
    • hosted-metadata.bgs.ac.uk
    • +2more
    Updated Jan 1, 2002
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    R.M. Fuller; G.M. Smith; J.M. Sanderson; R.A. Hill; A.G Thomson; R. Cox; N.J. Brown; R.T Clarke; P. Rothery; F.F. Gerard (2002). Land Cover Map 2000 (25m raster, GB) [Dataset]. http://doi.org/10.5285/f802edfc-86b7-4ab9-b8fa-87e9135237c9
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    Dataset updated
    Jan 1, 2002
    Dataset provided by
    NERC EDS Environmental Information Data Centre
    Authors
    R.M. Fuller; G.M. Smith; J.M. Sanderson; R.A. Hill; A.G Thomson; R. Cox; N.J. Brown; R.T Clarke; P. Rothery; F.F. Gerard
    License

    https://eidc.ceh.ac.uk/licences/lcm-raster/plainhttps://eidc.ceh.ac.uk/licences/lcm-raster/plain

    Time period covered
    Jan 1, 2000 - Dec 31, 2000
    Area covered
    Description

    This dataset consists of a 25m resolution raster version of the Land Cover Map 2000 for Great Britain. Each 25m pixel represents a 25m area of land cover target class, broadly representing Broad Habitats (see below). The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2000. LCM2000 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990. Like the earlier 1990 products, LCM2000 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2000 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2000 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions.

  5. A

    Raster Circumpolar Arctic Vegetation Map (CAVM) from AVHRR, MODIS and...

    • apgc.awi.de
    geotiff, html, png
    Updated Nov 7, 2022
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    Mendeley Data (2022). Raster Circumpolar Arctic Vegetation Map (CAVM) from AVHRR, MODIS and elevation data [Dataset]. http://doi.org/10.17632/c4xj5rv6kv.1
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    png(273102), geotiff, htmlAvailable download formats
    Dataset updated
    Nov 7, 2022
    Dataset authored and provided by
    Mendeley Data
    License

    Attribution-NonCommercial 3.0 (CC BY-NC 3.0)https://creativecommons.org/licenses/by-nc/3.0/
    License information was derived automatically

    Area covered
    Arctic
    Description

    Land cover maps are the basic data layer required for understanding and modeling ecological patterns and processes. The Circumpolar Arctic Vegetation Map (CAVM), produced in 2003, has been widely used as a base map for studies in the arctic tundra biome. However, the relatively coarse resolution and vector format of the map were not compatible with many other data sets. We present a new version of the CAVM, building on the strengths of the original map, while providing a finer spatial resolution, raster format, and improved mapping. The Raster CAVM uses the legend, extent and projection of the original CAVM. The legend has 16 vegetation types, glacier, saline water, freshwater, and non-arctic land. The Raster CAVM divides the original rock-water-vegetation complex map unit that mapped the Canadian Shield into two map units, one with lichen-dominated vegetation and one with shrub-dominated vegetation. In contrast to the original hand-drawn CAVM, the raster map is based on unsupervised classifications of seventeen geographic/floristic sub-sections of the Arctic, using AVHRR and MODIS data (reflectance data and NDVI) and elevation data. The units resulting from the classification were modeled to the CAVM types using a wide variety of ancillary data. The map was reviewed by experts familiar with their particular region, including of the original authors of the CAVM from the U.S., Canada, Greenland (Denmark), Iceland, Norway (including Svalbard) and Russia.

    Detailed information about the methods can be found in the publication to which this dataset is a supplement.

    Citation

    In order to use these data, you must cite this data set with the following citation:

    Raynolds, Martha; Walker, Donald (2019), “Raster Circumpolar Arctic Vegetation Map”, Mendeley Data, v1 https://dx.doi.org/10.17632/c4xj5rv6kv.1

  6. d

    Frank Miller Vegetation and Disturbance History Map 1938 Raster Image

    • catalog.data.gov
    Updated Nov 25, 2025
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    National Park Service (2025). Frank Miller Vegetation and Disturbance History Map 1938 Raster Image [Dataset]. https://catalog.data.gov/dataset/frank-miller-vegetation-and-disturbance-history-map-1938-raster-image
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    Dataset updated
    Nov 25, 2025
    Dataset provided by
    National Park Service
    Description

    The Frank Miller vegetation and disturbance history map, which was drawn in 1938, was scanned using a Vidar color scanner at 600 DPI. The map was originally separated into two segments. A digital image of each segment was brought into ArcMap. Each piece was Georeferenced based on the coordinates given on the map and was then Clipped based on the same coordinates to remove any white space. The Mosaic tool was then used to join the map pieces into one large image. The image was then projected using UTM17N as the basis for the projection.

  7. a

    Florida Cooperative Land Cover (Raster)

    • mapdirect-fdep.opendata.arcgis.com
    Updated Nov 1, 2022
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    Florida Fish and Wildlife Conservation Commission (2022). Florida Cooperative Land Cover (Raster) [Dataset]. https://mapdirect-fdep.opendata.arcgis.com/documents/9b791b9269f14caea04d995f8fbe6a14
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    Dataset updated
    Nov 1, 2022
    Dataset authored and provided by
    Florida Fish and Wildlife Conservation Commission
    License

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

    Area covered
    Description

    The Cooperative Land Cover Map is a project to develop an improved statewide land cover map from existing sources and expert review of aerial photography. The project is directly tied to a goal of Florida's State Wildlife Action Plan (SWAP) to represent Florida's diverse habitats in a spatially-explicit manner. The Cooperative Land Cover Map integrates 3 primary data types: 1) 6 million acres are derived from local or site-specific data sources, primarily on existing conservation lands. Most of these sources have a ground-truth or local knowledge component. We collected land cover and vegetation data from 37 existing sources. Each dataset was evaluated for consistency and quality and assigned a confidence category that determined how it was integrated into the final land cover map. 2) 1.4 million acres are derived from areas that FNAI ecologists reviewed with high resolution aerial photography. These areas were reviewed because other data indicated some potential for the presence of a focal community: scrub, scrubby flatwoods, sandhill, dry prairie, pine rockland, rockland hammock, upland pine or mesic flatwoods. 3) 3.2 million acres are represented by Florida Land Use Land Cover data from the FL Department of Environmental Protection and Water Management Districts (FLUCCS). The Cooperative Land Cover Map integrates data from the following years: NWFWMD: 2006 - 07 SRWMD: 2005 - 08 SJRWMD: 2004 SFWMD: 2004 SWFWMD: 2008 All data were crosswalked into the Florida Land Cover Classification System. This project was funded by a grant from FWC/Florida's Wildlife Legacy Initiative (Project 08009) to Florida Natural Areas Inventory. The current dataset is provided in 10m raster grid format.Changes from Version 1.1 to Version 2.3:CLC v2.3 includes updated Florida Land Use Land Cover for four water management districts as described above: NWFWMD, SJRWMD, SFWMD, SWFWMDCLC v2.3 incorporates major revisions to natural coastal land cover and natural communities potentially affected by sea level rise. These revisions were undertaken by FNAI as part of two projects: Re-evaluating Florida's Ecological Conservation Priorities in the Face of Sea Level Rise (funded by the Yale Mapping Framework for Biodiversity Conservation and Climate Adaptation) and Predicting and Mitigating the Effects of Sea-Level Rise and Land Use Changes on Imperiled Species and Natural communities in Florida (funded by an FWC State Wildlife Grant and The Kresge Foundation). FNAI also opportunistically revised natural communities as needed in the course of species habitat mapping work funded by the Florida Department of Environmental Protection. CLC v2.3 also includes several new site specific data sources: New or revised FNAI natural community maps for 13 conservation lands and 9 Florida Forever proposals; new Florida Park Service maps for 10 parks; Sarasota County Preserves Habitat Maps (with FNAI review); Sarasota County HCP Florida Scrub-Jay Habitat (with FNAI Review); Southwest Florida Scrub Working Group scrub polygons. Several corrections to the crosswalk of FLUCCS to FLCS were made, including review and reclassification of interior sand beaches that were originally crosswalked to beach dune, and reclassification of upland hardwood forest south of Lake Okeechobee to mesic hammock. Representation of state waters was expanded to include the NOAA Submerged Lands Act data for Florida.Changes from Version 2.3 to 3.0: All land classes underwent revisions to correct boundaries, mislabeled classes, and hard edges between classes. Vector data was compared against high resolution Digital Ortho Quarter Quads (DOQQ) and Google Earth imagery. Individual land cover classes were converted to .KML format for use in Google Earth. Errors identified through visual review were manually corrected. Statewide medium resolution (spatial resolution of 10 m) SPOT 5 images were available for remote sensing classification with the following spectral bands: near infrared, red, green and short wave infrared. The acquisition dates of SPOT images ranged between October, 2005 and October, 2010. Remote sensing classification was performed in Idrisi Taiga and ERDAS Imagine. Supervised and unsupervised classifications of each SPOT image were performed with the corrected polygon data as a guide. Further visual inspections of classified areas were conducted for consistency, errors, and edge matching between image footprints. CLC v3.0 now includes state wide Florida NAVTEQ transportation data. CLC v3.0 incorporates extensive revisions to scrub, scrubby flatwoods, mesic flatwoods, and upland pine classes. An additional class, scrub mangrove – 5252, was added to the crosswalk. Mangrove swamp was reviewed and reclassified to include areas of scrub mangrove. CLC v3.0 also includes additional revisions to sand beach, riverine sand bar, and beach dune previously misclassified as high intensity urban or extractive. CLC v3.0 excludes the Dry Tortugas and does not include some of the small keys between Key West and Marquesas.Changes from Version 3.0 to Version 3.1: CLC v3.1 includes several new site specific data sources: Revised FNAI natural community maps for 31 WMAs, and 6 Florida Forever areas or proposals. This data was either extracted from v2.3, or from more recent mapping efforts. Domains have been removed from the attribute table, and a class name field has been added for SITE and STATE level classes. The Dry Tortugas have been reincorporated. The geographic extent has been revised for the Coastal Upland and Dry Prairie classes. Rural Open and the Extractive classes underwent a more thorough reviewChanges from Version 3.1 to Version 3.2:CLC v3.2 includes several new site specific data sources: Revised FNAI natural community maps for 43 Florida Park Service lands, and 9 Florida Forever areas or proposals. This data is from 2014 - 2016 mapping efforts. SITE level class review: Wet Coniferous plantation (2450) from v2.3 has been included in v3.2. Non-Vegetated Wetland (2300), Urban Open Land (18211), Cropland/Pasture (18331), and High Pine and Scrub (1200) have undergone thorough review and reclassification where appropriate. Other classification errors were opportunistically corrected as found or as reported by users to landcovermap@myfwc.com. Changes from Version 3.2.5 to Version 3.3: The CLC v3.3 includes several new site specific data sources: Revised FNAI natural community maps for 14 FWC managed or co-managed lands, including 7 WMA and 7 WEA, 1 State Forest, 3 Hillsboro County managed areas, and 1 Florida Forever proposal. This data is from the 2017 – 2018 mapping efforts. Select sites and classes were included from the 2016 – 2017 NWFWMD (FLUCCS) dataset. M.C. Davis Conservation areas, 18331x agricultural classes underwent a thorough review and reclassification where appropriate. Prairie Mesic Hammock (1122) was reclassified to Prairie Hydric Hammock (22322) in the Everglades. All SITE level Tree Plantations (18333) were reclassified to Coniferous Plantations (183332). The addition of FWC Oyster Bar (5230) features. Other classification errors were opportunistically corrected as found or as reported by users to landcovermap@myfwc.com, including classification corrections to sites in T.M. Goodwin and Ocala National Forest. CLC v3.3 utilizes the updated The Florida Land Cover Classification System (2018), altering the following class names and numbers: Irrigated Row Crops (1833111), Wet Coniferous Plantations (1833321) (formerly 2450), Major Springs (4131) (formerly 3118). Mixed Hardwood-Coniferous Swamps (2240) (formerly Other Wetland Forested Mixed).Changes from Version 3.4 to Version 3.5: The CLC v3.5 includes several new site specific data sources: Revised FNAI natural community maps for 16 managed areas, and 10 Florida Forever Board of Trustees Projects (FFBOT) sites. This data is from the 2019 – 2020 mapping efforts. Other classification errors were opportunistically corrected as found or as reported by users to landcovermap@myfwc.com. This version of the CLC is also the first to include land identified as Salt Flats (5241).Changes from Version 3.5 to 3.6: The CLC v3.6 includes several new site specific data sources: Revised FNAI natural community maps for 11 managed areas, and 24 Florida Forever Board of Trustees Projects (FFBOT) sites. This data is from the 2018 – 2022 mapping efforts. Other classification errors were opportunistically corrected as found or as reported by users to landcovermap@myfwc.com. Changes from Version 3.6 to 3.7: The CLC 3.7 includes several new site specific data sources: Revised FNAI natural community maps for 5 managed areas (2022-2023). Revised Palm Beach County Natural Areas data for Pine Glades Natural Area (2023). Other classification errors were opportunistically corrected as found or as reported by users to landcovermap@myfwc.com. In this version a few SITE level classifications are reclassified for the STATE level classification system. Mesic Flatwoods and Scrubby Flatwoods are classified as Dry Flatwoods at the STATE level. Upland Glade is classified as Barren, Sinkhole, and Outcrop Communities at the STATE level. Lastly Upland Pine is classified as High Pine and Scrub at the STATE level.Changes from Version 3.7 to 4.0: CLC 4.0 represents a major update to CLC performed cooperatively by FWC and FNAI via a State Wildlife Grant to address changes on the landscape such as conversion to development and to integrate other recent high quality land cover sources. CLC v4.0 includes FWC's comprehensive delineation of solar farms, FLUCCS updates based on aerial photos from 2017-2022, ground-truthed mapping from FNAI and Florida Park Service, a statewide update of Intensive Development from Google Dynamic World land cover as of 2024, and additional FNAI review and revisions of target classes including sand beach and beach dune. A complete description of updates is available in the Cooperative Land Cover version 4.0 report, available from FNAI

  8. e

    State map 1:5 000 new form raster data - Beroun 1-0

    • data.europa.eu
    Updated Dec 16, 2012
    + more versions
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    (2012). State map 1:5 000 new form raster data - Beroun 1-0 [Dataset]. https://data.europa.eu/data/datasets/cz-cuzk-sm5-rb-bero10?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 in raster 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. The cartographic visualisation is solved automatically without manual works of a cartographer. 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).

  9. E

    Land Cover Map 2007 (25m raster, GB) v1.2

    • catalogue.ceh.ac.uk
    • data-search.nerc.ac.uk
    • +1more
    Updated Jul 23, 2014
    + more versions
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    R.D. Morton; C.S. Rowland; C.M. Wood; L. Meek; C.G. Marston; G.M. Smith (2014). Land Cover Map 2007 (25m raster, GB) v1.2 [Dataset]. http://doi.org/10.5285/a1f88807-4826-44bc-994d-a902da5119c2
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    Dataset updated
    Jul 23, 2014
    Dataset provided by
    NERC EDS Environmental Information Data Centre
    Authors
    R.D. Morton; C.S. Rowland; C.M. Wood; L. Meek; C.G. Marston; G.M. Smith
    License

    https://eidc.ceh.ac.uk/licences/lcm-raster/plainhttps://eidc.ceh.ac.uk/licences/lcm-raster/plain

    Time period covered
    Sep 2, 2005 - Jul 18, 2008
    Area covered
    Description

    This dataset consists of a 25m resolution raster version of the Land Cover Map 2007 for Great Britain. Each 25m pixel represents a 25m area of land cover target class, broadly representing Broad Habitats (see below). The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2007. LCM2007 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990 and LCM2000. Like the earlier 1990 and 2000 products, LCM2007 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2007 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2007 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions.

  10. d

    Raster map of interpolated areas of bathymetric maps of Morris Lake (Newton...

    • catalog.data.gov
    Updated Nov 26, 2025
    + more versions
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    U.S. Geological Survey (2025). Raster map of interpolated areas of bathymetric maps of Morris Lake (Newton Reservoir), New Jersey, 2018 [Dataset]. https://catalog.data.gov/dataset/raster-map-of-interpolated-areas-of-bathymetric-maps-of-morris-lake-newton-reservoir-new-j
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    Dataset updated
    Nov 26, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    New Jersey
    Description

    This dataset contains a raster map of the areas of the bathymetric map of Morris Lake that were interpolated.

  11. e

    State map 1:5 000 new form raster data - Hořice 8-6

    • data.europa.eu
    Updated Dec 16, 2012
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    (2012). State map 1:5 000 new form raster data - Hořice 8-6 [Dataset]. https://data.europa.eu/data/datasets/cz-cuzk-sm5-rb-hori86?locale=en
    Explore at:
    Dataset updated
    Dec 16, 2012
    Description

    The product represents a new design of the State Map at a scale of 1:5,000 in raster 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. The cartographic visualisation is solved automatically without manual works of a cartographer. 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).

  12. OS Open Raster Tile Layer

    • hub.arcgis.com
    Updated May 18, 2015
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    Esri UK (2015). OS Open Raster Tile Layer [Dataset]. https://hub.arcgis.com/maps/esriukcontent::os-open-raster-tile-layer/about
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    Dataset updated
    May 18, 2015
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri UK
    Area covered
    Description

    OS Open Raster stack of GB for use as base mapping from national scale through to street level data. The currency of the data is: GB Overview Maps - 12/2014 MiniScale - 01/2024 OS 250K Raster - 06/2024Vector Map District Raster - 05/2024Open Map Local Raster - 10/2024 The coverage of the map service is GB. The map projection is British National Grid. The service is appropriate for viewing down to a scale of approximately 1:2,500. For more information on OS Open Services see: https://osdatahub.os.uk/downloads/open Updated: 29/10/2024

  13. U

    Data from: Digital Raster Graphic (DRG) image of U.S. Geological Survey...

    • data.usgs.gov
    • datasets.ai
    • +1more
    Updated Sep 1, 2021
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    U.S. Geological Survey (2021). Digital Raster Graphic (DRG) image of U.S. Geological Survey standard series topographic map of Rincon, Puerto Rico (rincon_drg.tif) [Dataset]. https://data.usgs.gov/datacatalog/data/USGS:8a8dbbf8-8fbc-44ed-8f03-098e5fbaf067
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    Dataset updated
    Sep 1, 2021
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    License

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

    Time period covered
    Jul 1, 1966
    Area covered
    Rincón, Puerto Rico, United States
    Description

    The Digital Raster Graphic (DRG) is a raster image of a scanned USGS topographic map including the collar information, georeferenced to the UTM grid. This version of the Digital Raster Graphic (DRG) has been clipped to remove the collar (white border of the map) and has been reprojected to geographic coordinates.

  14. w

    Gridded Soil Survey Geographic (gSSURGO-30) Database for the Conterminous...

    • data.wu.ac.at
    • catalog.data.gov
    html
    Updated Oct 2, 2014
    + more versions
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    Department of Agriculture (2014). Gridded Soil Survey Geographic (gSSURGO-30) Database for the Conterminous United States - 30 meter [Dataset]. https://data.wu.ac.at/schema/data_gov/MzIxNTIwZDgtNDFkYS00MWMzLWEzYTktNTFmYWQ2NGVlNjRk
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    htmlAvailable download formats
    Dataset updated
    Oct 2, 2014
    Dataset provided by
    Department of Agriculture
    License

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

    Description

    This dataset is called the Gridded SSURGO (gSSURGO) Database and is derived from the Soil Survey Geographic (SSURGO) Database. SSURGO is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey (NCSS) in accordance with NCSS mapping standards. The tabular data represent the soil attributes, and are derived from properties and characteristics stored in the National Soil Information System (NASIS). The gSSURGO data were prepared by merging traditional SSURGO digital vector map and tabular data into a Conterminous US-wide extent, and adding a Conterminous US-wide gridded map layer derived from the vector, plus a new value added look up (valu) table containing "ready to map" attributes. The gridded map layer is offered in an ArcGIS file geodatabase raster format.

    The raster and vector map data have a Conterminous US-wide extent. The raster map data have a 30 meter cell size. Each cell (and polygon) is linked to a map unit identifier called the map unit key. A unique map unit key is used to link to raster cells and polygons to attribute tables, including the new value added look up (valu) table that contains additional derived data.

    The value added look up (valu) table contains attribute data summarized to the map unit level using best practice generalization methods intended to meet the needs of most users. The generalization methods include map unit component weighted averages and percent of the map unit meeting a given criteria.

    The Gridded SSURGO dataset was created for use in national, regional, and state-wide resource planning and analysis of soils data. The raster map layer data can be readily combined with other national, regional, and local raster layers, e.g., National Land Cover Database (NLCD), the National Agricultural Statistics Service (NASS) Crop Data Layer, or the National Elevation Dataset (NED).

  15. a

    OSNI Open Data - 1:1Million Raster - Town and City Locations

    • osni-spatialni.opendata.arcgis.com
    • ckan.publishing.service.gov.uk
    • +2more
    Updated Nov 21, 2018
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    SpatialNI (2018). OSNI Open Data - 1:1Million Raster - Town and City Locations [Dataset]. https://osni-spatialni.opendata.arcgis.com/datasets/30df351ab633474cb73aa4fa61b32b87
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    Dataset updated
    Nov 21, 2018
    Dataset authored and provided by
    SpatialNI
    Area covered
    Description

    1:1,000,000 raster map of Northern Ireland with place names. A raster map is a static image displayed on screen which is suitable as background mapping. 1:1 000,000 Raster is smallest scale OSNI raster product giving an excellent overview of Northern Ireland. Published here for OpenData. By download or use of this dataset you agree to abide by the Open Government Data Licence.Please Note for Open Data NI Users: Esri Rest API is not Broken, it will not open on its own in a Web Browser but can be copied and used in Desktop and Webmaps

  16. E

    Land Cover Map 2015 (25m raster, N. Ireland)

    • catalogue.ceh.ac.uk
    • gimi9.com
    • +2more
    Updated Apr 11, 2017
    + more versions
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    C.S. Rowland; R.D. Morton; L. Carrasco; G. McShane; A.W. O'Neil; C.M. Wood (2017). Land Cover Map 2015 (25m raster, N. Ireland) [Dataset]. http://doi.org/10.5285/47f053a0-e34f-4534-a843-76f0a0998a2f
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    Dataset updated
    Apr 11, 2017
    Dataset provided by
    NERC EDS Environmental Information Data Centre
    Authors
    C.S. Rowland; R.D. Morton; L. Carrasco; G. McShane; A.W. O'Neil; C.M. Wood
    License

    https://eidc.ceh.ac.uk/licences/lcm-raster/plainhttps://eidc.ceh.ac.uk/licences/lcm-raster/plain

    Time period covered
    Jan 1, 2014 - Dec 31, 2015
    Area covered
    Description

    This dataset consists of the 25m raster version of the Land Cover Map 2015 (LCM2015) for Northern Ireland. This is the most detailed of the LCM2015 raster products both thematically and spatially, and it is used to derive the 1km products. The 25m raster product consists of two bands: Band 1 - raster representation of the majority (dominant) class per polygon for 21 target habitat classes; Band 2 - mean per polygon probability as reported by the Random Forest classifier (see supporting information). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019.

  17. d

    2023 USDA Plant Hardiness Zone Map Mean Annual Extreme Low Temperature...

    • catalog.data.gov
    • agdatacommons.nal.usda.gov
    • +1more
    Updated Dec 2, 2025
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    Agricultural Research Service (2025). 2023 USDA Plant Hardiness Zone Map Mean Annual Extreme Low Temperature Rasters [Dataset]. https://catalog.data.gov/dataset/2023-usda-plant-hardiness-zone-map-mean-annual-extreme-low-temperature-rasters
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    Dataset updated
    Dec 2, 2025
    Dataset provided by
    Agricultural Research Service
    Description

    These rasters provide the local mean annual extreme low temperature from 1991 to 2020 in an 800m x 800m grid covering the USA (including Puerto Rico) based on interpolation of data from more than a thousand weather stations. Each location's Plant Hardiness Zone is calculated based on classifying that temperature into 5 degree bands.The classified rasters are then used to create print and interactive maps.Temperature station data for the 2023 edition of the USDA Plant Hardiness Zone Map (PHZM) came from many different sources. In the eastern and central United States, Puerto Rico, and Hawaii, data came primarily from weather stations of the National Weather Service and several state networks. In the western United States and Alaska, data from stations maintained by USDA Natural Resources Conservation Service, USDA Forest Service, U.S. Department of the Interior (DOI) Bureau of Reclamation, and DOI Bureau of Land Management also helped to better define hardiness zones in mountainous areas. Environment Canada provided data from Canadian stations, and data from Mexican stations came from the Mexico National Weather Service and the Global Historical Climate Network. The USDA PHZM was produced with PRISM, a highly sophisticated climate mapping technology developed at Oregon State University. The map was produced from a digital computer grid, with each cell measuring about a half mile on a side. PRISM estimated the mean annual extreme minimum temperature for each grid cell (or pixel on the map) by examining data from nearby stations; determining how the temperature changed with elevation; and accounting for possible coastal effects, temperature inversions, and the type of topography (ridge top, hill slope, or valley bottom). Information on PRISM can be obtained from the PRISM Climate Group website https://prism.oregonstate.edu. Once a draft of the map was completed, it was reviewed by a team of climatologists, agricultural meteorologists, and horticultural experts. If the zone for an area appeared anomalous to these expert reviewers, experts doublechecked the draft maps for errors or biases. A detailed explanation of the mapmaking process and a discussion of the horticultural applications of the 2012 PHZM (similar to 2023) are available from the articles listed below. Daly, C., M.P. Widrlechner, M.D. Halbleib, J.I. Smith, and W.P. Gibson. 2012. Development of a new USDA Plant Hardiness Zone Map for the United States. Journal of Applied Meteorology and Climatology, 51: 242-264.Widrlechner, M.P., C. Daly, M. Keller, and K. Kaplan. 2012. Horticultural Applications of a Newly Revised USDA Plant Hardiness Zone Map. HortTechnology, 22: 6-19.

  18. n

    Land Cover Map 2015 (25m raster, GB)

    • data-search.nerc.ac.uk
    • hosted-metadata.bgs.ac.uk
    • +3more
    zip
    Updated Apr 11, 2017
    + more versions
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    NERC EDS Environmental Information Data Centre (2017). Land Cover Map 2015 (25m raster, GB) [Dataset]. https://data-search.nerc.ac.uk/geonetwork/srv/api/records/bb15e200-9349-403c-bda9-b430093807c7
    Explore at:
    zipAvailable download formats
    Dataset updated
    Apr 11, 2017
    Dataset provided by
    NERC EDS Environmental Information Data Centre
    License

    https://eidc.ceh.ac.uk/licences/lcm-raster/plainhttps://eidc.ceh.ac.uk/licences/lcm-raster/plain

    Time period covered
    Jan 1, 2014 - Dec 1, 2015
    Area covered
    Description

    This dataset consists of the 25m raster version of the Land Cover Map 2015 (LCM2015) for Great Britain. The 25m raster product consists of two bands: Band 1 - raster representation of the majority (dominant) class per polygon for 21 target habitat classes; Band 2 - mean per polygon probability as reported by the Random Forest classifier (see supporting information). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. The 25m raster is the most detailed of the LCM2015 raster products both thematically and spatially, and it is used to derive the 1km products. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019. Full details about this dataset can be found at https://doi.org/10.5285/bb15e200-9349-403c-bda9-b430093807c7

  19. M

    1:100k Digital Raster Graphic - Collars Removed

    • gisdata.mn.gov
    html, jpeg
    Updated Apr 18, 2023
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    Natural Resources Department (2023). 1:100k Digital Raster Graphic - Collars Removed [Dataset]. https://gisdata.mn.gov/dataset/base-usgs-scanned-topo-100k-drg
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    html, jpegAvailable download formats
    Dataset updated
    Apr 18, 2023
    Dataset provided by
    Natural Resources Department
    Description

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

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

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

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

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

  20. n

    NYS 24K Quad Map Index

    • data.gis.ny.gov
    Updated Mar 27, 2023
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    ShareGIS NY (2023). NYS 24K Quad Map Index [Dataset]. https://data.gis.ny.gov/datasets/nys-24k-quad-map-index/about
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    Dataset updated
    Mar 27, 2023
    Dataset authored and provided by
    ShareGIS NY
    Area covered
    Description

    This index provides information and download links for the 968 digital raster quadrangle maps produced by NYS Department of Transportation. An outline for each 7.5-minute quadrangles is provided. The referenced digital maps were produced for use at 1:24,000 scale. Attributes are: REFCODE - NYS reference code associated with 7.5 minute quad; QUADNAME - Quad Name; DOTDATE - Date of NYS/DOT raster quad; CONDATE - Date of contours on NYS raster quad; CON_INTER - NYS raster quad contour interval; CON_UNITS - NYS raster quad contour units; SCANTYPE - Type of NYS raster quad product; ADDLAYERS - Additional NYS raster layers available; USGSCODE - USGS 7.5x7.5 minute quad code; ZONES - List of State Plane zones in quad; COUNTIES - Counties covered in part by quad The maps are in Zone 18 of the UTM grid/projection system. The information in the index represents the status as of 2004 when updates to the maps ended.Please contact NYS ITS Geospatial Services at nysgis@its.ny.gov if you have any questions.

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U.S. Geological Survey (2025). Raster map of CONUS forest change frequency from 1985-2020 [Dataset]. https://catalog.data.gov/dataset/raster-map-of-conus-forest-change-frequency-from-1985-2020

Raster map of CONUS forest change frequency from 1985-2020

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Dataset updated
Nov 27, 2025
Dataset provided by
United States Geological Surveyhttp://www.usgs.gov/
Description

We summarized annual remote sensing land cover classifications from the U.S. Geological Survey Land Cover Monitoring, Assessment, and Projection (LCMAP) annual time series to characterize forest change across the conterminous United States (CONUS) for the years 1985-2020. The raster output includes a map where each pixel is given an integer value based on the number of years in which it was classified as forest across the annual LCMAP time series. Values of 36 indicate the pixel was classified as forest across all years while a value of 0 indicates forests (tree cover) was never detected during the time series.

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