100+ datasets found
  1. f

    IMCOMA-example-datasets

    • figshare.com
    xml
    Updated Feb 12, 2021
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    Nowosad (2021). IMCOMA-example-datasets [Dataset]. http://doi.org/10.6084/m9.figshare.13379228.v1
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    xmlAvailable download formats
    Dataset updated
    Feb 12, 2021
    Dataset provided by
    figshare
    Authors
    Nowosad
    License

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

    Description

    Datasets- simple_land_cover1.tif - an example land cover dataset presented in Figures 1 and 2- simple_landform1.tif - an example landform dataset presented in Figures 1 and 2- landcover_europe.tif - a land cover dataset with nine categories for Europe - landcover_europe.qml - a QGIS color style for the landcover_europe.tif dataset- landform_europe.tif - a landform dataset with 17 categories for Europe - landform_europe.qml - a QGIS color style for the landform_europe.tif dataset- map1.gpkg - a map of LTs in Europe constructed using the INCOMA-based method- map1.qml - a QGIS color style for the map1.gpkg dataset- map2.gpkg - a map of LTs in Europe constructed using the COMA method to identify and delineate pattern types in each theme separately- map2.qml - a QGIS color style for the map2.gpkg dataset- map3.gpkg - a map of LTs in Europe constructed using the map overlay method- map3.qml - a QGIS color style for the map3.gpkg dataset

  2. Tactile Maps of Canada-Maps for Education-The Thematic Tactile Atlas of...

    • open.canada.ca
    • data.amerigeoss.org
    • +1more
    cdr, gif, html, pdf
    Updated Feb 22, 2022
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    Natural Resources Canada (2022). Tactile Maps of Canada-Maps for Education-The Thematic Tactile Atlas of Canada-Forest Types [Dataset]. https://open.canada.ca/data/dataset/c962bb2e-b896-5113-9e55-23130d4e07a4
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    pdf, html, cdr, gifAvailable download formats
    Dataset updated
    Feb 22, 2022
    Dataset provided by
    Ministry of Natural Resources of Canadahttps://www.nrcan.gc.ca/
    License

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

    Area covered
    Canada
    Description

    The map title is Forest Types. Map scale. North arrow pointing to the north. Map projection is Hammer-Aitoff. Border of Canada. Great Lakes Border for each theme category within Canada. Neat line around the map. Each theme category is identified by a number that corresponds to the legend. Legend is divided into six categories: West Coast forest, Montane forest, Taiga forest, Boreal forest, Mixed forest, No forest. Tactile maps are designed with Braille, large text, and raised features for visually impaired and low vision users. The Tactile Maps of Canada collection includes: (a) Maps for Education: tactile maps showing the general geography of Canada, including the Tactile Atlas of Canada (maps of the provinces and territories showing political boundaries, lakes, rivers and major cities), and the Thematic Tactile Atlas of Canada (maps showing climatic regions, relief, forest types, physiographic regions, rock types, soil types, and vegetation). (b) Maps for Mobility: to help visually impaired persons navigate spaces and routes in major cities by providing information about streets, buildings and other features of a travel route in the downtown area of a city. (c) Maps for Transportation and Tourism: to assist visually impaired persons in planning travel to new destinations in Canada, showing how to get to a city, and streets in the downtown area.

  3. Geospatial data for the Vegetation Mapping Inventory Project of Fort Larned...

    • catalog.data.gov
    Updated Jun 5, 2024
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    National Park Service (2024). Geospatial data for the Vegetation Mapping Inventory Project of Fort Larned National Historic Site [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-fort-larned-national-histo
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Larned
    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. GIS Database 2002-2005: Project Size = 1,898 acres Fort Larned National Historic Site (including the Rut Site) = 705 acres 16 Map Classes 11 Vegetated 5 Non-vegetated Minimum Mapping Unit = ½ hectare is the program standard but this was modified at FOLS to ¼ acre. Total Size = 229 Polygons Average Polygon Size = 8.3 acres Overall Thematic Accuracy = 92% To produce the digital map, a combination of 1:8,500-scale (0.75 meter pixels) color infrared digital ortho-imagery acquired on October 26, 2005 by the Kansas Applied Remote Sensing Program and 1:12,000-scale true color ortho-rectified imagery acquired in 2005 by the U.S. Department of Agriculture - Farm Service Agency’s Aerial Photography Field Office, and all of the GPS referenced ground data were used to interpret the complex patterns of vegetation and land-use. In the end, 16 map units (11 vegetated and 5 land-use) were developed and directly cross-walked or matched to corresponding plant associations and land-use classes. All of the interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases using ArcGIS© software. Draft maps were printed, field tested, reviewed and revised. One hundred and six accuracy assessment (AA) data points were collected in 2006 by KNSHI and used to determine the map’s accuracy. After final revisions, the accuracy assessment revealed an overall thematic accuracy of 92%.

  4. D

    Soil Data Confidence map for NSW

    • data.nsw.gov.au
    • researchdata.edu.au
    html, pdf +2
    Updated Feb 26, 2024
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    NSW Department of Climate Change, Energy, the Environment and Water (2024). Soil Data Confidence map for NSW [Dataset]. https://data.nsw.gov.au/data/dataset/soil-data-confidence-map-for-nsw9859e
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    spatial viewer, pdf, html, zipAvailable download formats
    Dataset updated
    Feb 26, 2024
    Dataset provided by
    Department of Climate Change, Energy, the Environment and Water of New South Waleshttps://www.nsw.gov.au/departments-and-agencies/dcceew
    License

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

    Area covered
    New South Wales
    Description

    This map provides a guide to the data confidence of DPIE's soil related thematic map products in NSW. Examples of products this map supports includes Land and Soil Capability mapping, Inherent fertility of soils in NSW and Great Soil Group soil types in NSW.

    Confidence classes are determined based on the data scale, type of mapping and information collected, accuracy of the attributes and quality assurance on the product.

    Soil data confidence is described using a 4 class system between high and very low as outlined below.:

    • Good (1) - All necessary soil and landscape data is available at a catchment scale (1:100,000 & 1:250,000) to undertake the assessment of LSC and other soil thematic maps.

    • Moderate (2) - Most soil and landscape data is available at a catchment scale (1:100,000 - 1:250,000) to undertake the assessment of LSC and other soil thematic maps.

    • Low (3) - Limited soil and landscape data is available at a reconnaissance catchment scale (1:100,000 & 1:250,000) which limits the quality of the assessment of LSC and other soil thematic maps.

    • Very low (4) - Very limited soil and landscape data is available at a broad catchment scale (1:250,000 - 1:500,000) and the LSC and other soil thematic maps should be used as a guide only.

    Online Maps: This dataset can be viewed using eSPADE (NSW’s soil spatial viewer), which contains a suite of soil and landscape information including soil profile data. Many of these datasets have hot-linked soil reports. An alternative viewer is the SEED Map; an ideal way to see what other natural resources datasets (e.g. vegetation) are available for this map area.

    Reference: Department of Planning, Industry and Environment, 2020, Soil Data Confidence map for NSW, Version 4, NSW Department of Planning, Industry and Environment, Parramatta.

  5. Map Drawing Services Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Oct 4, 2024
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    Dataintelo (2024). Map Drawing Services Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/map-drawing-services-market
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    pptx, pdf, csvAvailable download formats
    Dataset updated
    Oct 4, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Map Drawing Services Market Outlook




    The global map drawing services market size was valued at approximately $1.2 billion in 2023 and is projected to reach $2.3 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.1% during the forecast period. This growth can be attributed to the increasing demand for precise and customized mapping solutions across various industries such as urban planning, environmental management, and tourism.




    One of the primary growth factors of the map drawing services market is the rapid advancement in Geographic Information Systems (GIS) technology. The integration of advanced GIS tools allows for the creation of highly accurate and detailed maps, which are essential for urban planning and environmental management. Additionally, the growing emphasis on smart city initiatives worldwide has led to an increased need for customized mapping solutions to manage urban development and infrastructure efficiently. These technological advancements are not only improving the quality of map drawing services but are also making them more accessible to a broader range of end-users.




    Another significant growth factor is the rising awareness and adoption of map drawing services in the tourism sector. Customized maps are increasingly being used to enhance the tourist experience by providing detailed information about destinations, routes, and points of interest. This trend is particularly prominent in regions with rich cultural and historical heritage, where detailed thematic maps can offer tourists a more immersive and informative experience. Furthermore, the digitalization of the tourism industry has made it easier to integrate these maps into various applications, further driving the demand for map drawing services.




    Environmental management is another key area driving the growth of the map drawing services market. With the increasing focus on sustainable development and environmental conservation, there is a growing need for accurate maps to monitor natural resources, track changes in land use, and plan conservation efforts. Map drawing services provide essential tools for environmental scientists and policymakers to analyze and visualize data, aiding in better decision-making and management of natural resources. The rising environmental concerns globally are expected to continue driving the demand for these services.




    From a regional perspective, North America is anticipated to hold a significant share of the map drawing services market due to the high adoption rate of advanced mapping technologies and the presence of major market players in the region. Furthermore, the region's focus on smart city projects and environmental conservation initiatives is expected to fuel the demand for map drawing services. Meanwhile, the Asia Pacific region is projected to witness the highest growth rate, driven by rapid urbanization, industrialization, and the growing need for efficient infrastructure planning and management.



    Service Type Analysis




    The map drawing services market is segmented into several service types, including custom map drawing, thematic map drawing, topographic map drawing, and others. Custom map drawing services cater to specific client needs, offering tailored mapping solutions for various applications. This segment is expected to witness significant growth due to the increasing demand for personalized maps in sectors such as urban planning, tourism, and corporate services. Businesses and government agencies are increasingly relying on custom maps to support their operations, leading to the expansion of this segment.




    Thematic map drawing services focus on creating maps that highlight specific themes or topics, such as population density, climate patterns, or economic activities. These maps are particularly useful for educational purposes, research, and community planning. The growing emphasis on data-driven decision-making and the need for visual representation of complex datasets are driving the demand for thematic maps. Additionally, thematic maps play a crucial role in public health, disaster management, and policy formulation, contributing to the segment's growth.




    Topographic map drawing services offer detailed representations of physical features of a landscape, including elevation, terrain, and landforms. These maps are essential for various applications, such as environmental management, military ope

  6. Global Digital Maps Market Size By Type (Outdoor Maps, 3D and 4D Metaverse),...

    • verifiedmarketresearch.com
    Updated Sep 15, 2024
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    VERIFIED MARKET RESEARCH (2024). Global Digital Maps Market Size By Type (Outdoor Maps, 3D and 4D Metaverse), By Component (Solution, Service), By Purpose (Navigation Maps, Thematic Maps), By Application (Automotive, Telecommunications, Logistics and Transportation), By Geographic Scope And Forecast [Dataset]. https://www.verifiedmarketresearch.com/product/digital-maps-market/
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    Dataset updated
    Sep 15, 2024
    Dataset provided by
    Verified Market Researchhttps://www.verifiedmarketresearch.com/
    Authors
    VERIFIED MARKET RESEARCH
    License

    https://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/

    Description

    Digital Maps Market Size And Forecast

    Digital Maps Market size was valued at USD 25.95 Billion in 2024 and is projected to reach USD 100.9 Billion by 2031, growing at a CAGR of 18.50% from 2024 to 2031.

    Global Digital Maps Market Drivers

    Increasing smartphone penetration: The growing number of smartphone users and the widespread availability of internet connectivity have made digital maps easily accessible. Advancements in mapping technology: The development of more accurate and detailed digital maps, incorporating real-time traffic updates and navigation features, has increased their appeal to users. Growth of the ride-sharing and delivery services industry: These industries rely heavily on accurate and up-to-date digital maps for navigation and route optimization.

    Global Digital Maps Market Restraints

    Data privacy concerns: The collection and use of location data raise privacy concerns, which can hinder the adoption of digital maps. Map inaccuracies: Despite advancements in mapping technology, inaccuracies and errors can still occur, leading to user dissatisfaction. Competition from free mapping services: The availability of free mapping services from tech giants like Google and Apple can limit the market for premium digital mapping solutions.

  7. s

    Digital Map Market Size, Share, Growth Analysis, By Offering (Solution,...

    • skyquestt.com
    Updated Nov 15, 2024
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    SkyQuest Technology (2024). Digital Map Market Size, Share, Growth Analysis, By Offering (Solution, Services), By Mapping Type (Outdoor Mapping, Indoor Mapping), By Purpose (Navigation Maps, Thematic Maps), By Scale (Large Scale Maps, Small Scale Maps), By Region - Industry Forecast 2025-2032 [Dataset]. https://www.skyquestt.com/report/digital-map-market
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    Dataset updated
    Nov 15, 2024
    Dataset authored and provided by
    SkyQuest Technology
    License

    https://www.skyquestt.com/privacy/https://www.skyquestt.com/privacy/

    Time period covered
    2025 - 2032
    Area covered
    Global
    Description

    Digital Map Market size was valued at USD 25.9 Billion in 2023 and is poised to grow from USD 28.75 Billion in 2024 to USD 66.16 Billion by 2032, growing at a CAGR of 11% during the forecast period (2025-2032).

  8. Links to all datasets and downloads for 80 A0/A3 digital image of map...

    • data.csiro.au
    Updated Jan 18, 2016
    + more versions
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    Kristen Williams; Nat Raisbeck-Brown; Tom Harwood; Suzanne Prober (2016). Links to all datasets and downloads for 80 A0/A3 digital image of map posters accompanying AdaptNRM Guide: Helping Biodiversity Adapt: supporting climate adaptation planning using a community-level modelling approach [Dataset]. http://doi.org/10.4225/08/569C1F6F9DCC3
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    Dataset updated
    Jan 18, 2016
    Dataset provided by
    CSIROhttp://www.csiro.au/
    Authors
    Kristen Williams; Nat Raisbeck-Brown; Tom Harwood; Suzanne Prober
    License

    https://research.csiro.au/dap/licences/csiro-data-licence/https://research.csiro.au/dap/licences/csiro-data-licence/

    Time period covered
    Jan 1, 2015 - Jan 10, 2015
    Area covered
    Dataset funded by
    CSIROhttp://www.csiro.au/
    Description

    This dataset is a series of digital map-posters accompanying the AdaptNRM Guide: Helping Biodiversity Adapt: supporting climate adaptation planning using a community-level modelling approach.

    These represent supporting materials and information about the community-level biodiversity models applied to climate change. Map posters are organised by four biological groups (vascular plants, mammals, reptiles and amphibians), two climate change scenario (1990-2050 MIROC5 and CanESM2 for RCP8.5), and five measures of change in biodiversity.

    The map-posters present the nationally consistent data at locally relevant resolutions in eight parts – representing broad groupings of NRM regions based on the cluster boundaries used for climate adaptation planning (http://www.environment.gov.au/climate-change/adaptation) and also Nationally.

    Map-posters are provided in PNG image format at moderate resolution (300dpi) to suit A0 printing. The posters were designed to meet A0 print size and digital viewing resolution of map detail. An additional set in PDF image format has been created for ease of download for initial exploration and printing on A3 paper. Some text elements and map features may be fuzzy at this resolution.

    Each map-poster contains four dataset images coloured using standard legends encompassing the potential range of the measure, even if that range is not represented in the dataset itself or across the map extent.

    Most map series are provided in two parts: part 1 shows the two climate scenarios for vascular plants and mammals and part 2 shows reptiles and amphibians. Eight cluster maps for each series have a different colour theme and map extent. A national series is also provided. Annotation briefly outlines the topics presented in the Guide so that each poster stands alone for quick reference.

    An additional 77 National maps presenting the probability distributions of each of 77 vegetation types – NVIS 4.1 major vegetation subgroups (NVIS subgroups) - are currently in preparation.

    Example citations:

    Williams KJ, Raisbeck-Brown N, Prober S, Harwood T (2015) Generalised projected distribution of vegetation types – NVIS 4.1 major vegetation subgroups (1990 and 2050), A0 map-poster 8.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

    Williams KJ, Raisbeck-Brown N, Harwood T, Prober S (2015) Revegetation benefit (cleared natural areas) for vascular plants and mammals (1990-2050), A0 map-poster 9.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

    This dataset has been delivered incrementally. Please check that you are accessing the latest version of the dataset. Lineage: The map posters show case the scientific data. The data layers have been developed at approximately 250m resolution (9 second) across the Australian continent to incorporate the interaction between climate and topography, and are best viewed using a geographic information system (GIS). Each data layers is 1Gb, and inaccessible to non-GIS users. The map posters provide easy access to the scientific data, enabling the outputs to be viewed at high resolution with geographical context information provided.

    Maps were generated using layout and drawing tools in ArcGIS 10.2.2

    A check list of map posters and datasets is provided with the collection.

    Map Series: 7.(1-77) National probability distribution of vegetation type – NVIS 4.1 major vegetation subgroup pre-1750 #0x

    8.1 Generalised projected distribution of vegetation types (NVIS subgroups) (1990 and 2050)

    9.1 Revegetation benefit (cleared natural areas) for plants and mammals (1990-2050)

    9.2 Revegetation benefit (cleared natural areas) for reptiles and amphibians (1990-2050)

    10.1 Need for assisted dispersal for vascular plants and mammals (1990-2050)

    10.2 Need for assisted dispersal for reptiles and amphibians (1990-2050)

    11.1 Refugial potential for vascular plants and mammals (1990-2050)

    11.1 Refugial potential for reptiles and amphibians (1990-2050)

    12.1 Climate-driven future revegetation benefit for vascular plants and mammals (1990-2050)

    12.2 Climate-driven future revegetation benefit for vascular reptiles and amphibians (1990-2050)

  9. e

    Data on the nationwide biotope and usage type mapping Mecklenburg-Western...

    • data.europa.eu
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    Data on the nationwide biotope and usage type mapping Mecklenburg-Western Pomerania [Dataset]. https://data.europa.eu/data/datasets/a5e7d68d-a171-11d3-a00c-00105ab0cf38?locale=en
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    Description

    In 1990/91, nationwide aerial photography flights were carried out using a color infrared (CIR) film that is particularly suitable for analysis purposes on a scale of 1:10.000. As a result of the visual image processing process, thematic maps were created on the basis of the intersection of the topographic map 1:10.000, in which the encoded information is attached to each area- and line-like biotope type according to the alpha-numeric key of the biotope types and usage types. The biotope and usage type key consists of letter and number coding. It has a three-stage hierarchical structure within the biotope groups. Based on 6 landscape element types (biotope groups), these were broken down into a total of 23 structural types (subunits), which in turn comprise several biotope types (subunits). Each biotope type can have features from two further columns (vegetational characteristic; Location and usage characteristics) which are to be assigned freely as letter encodings.

  10. World Land Cover

    • hub.arcgis.com
    Updated Mar 28, 2015
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    Esri (2015). World Land Cover [Dataset]. https://hub.arcgis.com/maps/esri::world-land-cover/about
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    Dataset updated
    Mar 28, 2015
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Important Note: This item is in mature support as of May 2025 and will retire in December 2025.This map features land cover data represent a descriptive thematic surface for characteristics of the land's surface such as densities or types of developed areas, agricultural lands, and natural vegetation regimes. Land cover data are the result of a model, so a good way to think of the values in each cell are as the predominating value rather than the only characteristic in that cell.Land use and land cover data are critical and fundamental for environmental monitoring, planning, and assessment.This web map uses Terrain with Labels vector layers as its basemap.Dataset SummaryBaseVue 2013 is a commercial global, land use / land cover (LULC) product developed by MDA. BaseVue covers the Earth’s entire land area, excluding Antarctica. BaseVue is independently derived from roughly 9,200 Landsat 8 images and is the highest spatial resolution (30m), most current LULC product available. The capture dates for the Landsat 8 imagery range from April 11, 2013 to June 29, 2014. The following 16 classes of land use / land cover are listed by their cell value in this layer: Deciduous Forest: Trees > 3 meters in height, canopy closure >35% (<25% inter-mixture with evergreen species) that seasonally lose their leaves, except Larch.Evergreen Forest: Trees >3 meters in height, canopy closure >35% (<25% inter-mixture with deciduous species), of species that do not lose leaves. (will include coniferous Larch regardless of deciduous nature).Shrub/Scrub: Woody vegetation <3 meters in height, > 10% ground cover. Only collect >30% ground cover.Grassland: Herbaceous grasses, > 10% cover, including pasture lands. Only collect >30% cover.Barren or Minimal Vegetation: Land with minimal vegetation (<10%) including rock, sand, clay, beaches, quarries, strip mines, and gravel pits. Salt flats, playas, and non-tidal mud flats are also included when not inundated with water.Not Used (in other MDA products 6 represents urban areas or built up areas, which have been split here in into values 20 and 21).Agriculture, General: Cultivated crop landsAgriculture, Paddy: Crop lands characterized by inundation for a substantial portion of the growing seasonWetland: Areas where the water table is at or near the surface for a substantial portion of the growing season, including herbaceous and woody species (except mangrove species)Mangrove: Coastal (tropical wetlands) dominated by Mangrove speciesWater: All water bodies greater than 0.08 hectares (1 LS pixel) including oceans, lakes, ponds, rivers, and streamsIce / Snow: Land areas covered permanently or nearly permanent with ice or snowClouds: Areas where no land cover interpretation is possible due to obstruction from clouds, cloud shadows, smoke, haze, or satellite malfunctionWoody Wetlands: Areas where forest or shrubland vegetation accounts for greater than 20% of vegetative cover and the soil or substrate periodically is saturated with, or covered by water. Only used within the continental U.S.Mixed Forest: Areas dominated by trees generally greater than 5 meters tall, and greater than 20% of total vegetation cover. Neither deciduous nor evergreen species are greater than 75% of total tree cover. Only used within the continental U.S.Not UsedNot UsedNot UsedNot UsedHigh Density Urban: Areas with over 70% of constructed materials that are a minimum of 60 meters wide (asphalt, concrete, buildings, etc.). Includes residential areas with a mixture of constructed materials and vegetation where constructed materials account for >60%. Commercial, industrial, and transportation i.e., Train stations, airports, etc.Medium-Low Density Urban: Areas with 30%-70% of constructed materials that are a minimum of 60 meters wide (asphalt, concrete, buildings, etc.). Includes residential areas with a mixture of constructed materials and vegetation, where constructed materials account for greater than 40%. Commercial, industrial, and transportation i.e., Train stations, airports, etc.What can you do with this layer?This layer has query, identify, and export image services available. The layer is restricted to an 16,000 x 16,000 pixel limit, which represents an area of nearly 300 miles on a side. This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.\For more information, see the Landscape Layers group on ArcGIS Online.

  11. T

    1:100,000 desert (sand) distribution dataset in China

    • data.tpdc.ac.cn
    • tpdc.ac.cn
    zip
    Updated Apr 19, 2021
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    Jianhua WANG; Yimou WANG; Changzhen YAN; Yuan QI (2021). 1:100,000 desert (sand) distribution dataset in China [Dataset]. http://doi.org/10.3972/westdc.006.2013.db
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    zipAvailable download formats
    Dataset updated
    Apr 19, 2021
    Dataset provided by
    TPDC
    Authors
    Jianhua WANG; Yimou WANG; Changzhen YAN; Yuan QI
    Area covered
    Description

    This dataset is the first 1: 100,000 desert spatial database in China based on the graphic data of desert thematic maps. It mainly reflects the geographical distribution, area size, and mobility of sand dunes in China. According to the system design requirements and relevant standards, the input data is standardized and uniformly converted into a standard format for various types of data input. Build a library to run the delivery system. This project uses the TM image in 2000 as the information source, and interprets, extracts, and edits the coverage of the national land use map and TM digital image information in 2000. It uses remote sensing and geographic information system technology to 1: 100,000 Thematic mapping requirements for scale bar maps were made on the desert, sandy land and gravel Gobi in China. The 1: 100,000 desert map across the country can save users a lot of data entry and editing work when they are engaged in research on resources and the environment. Digital maps can be easily converted into layout maps The dataset properties are as follows: Divided into two folders e00 and shp: Desert map name and province comparison table in each folder 01 Ahsm Anhui 02 Bjsm Beijing 03 Fjsm Fujian 04 Gdsm Guangdong 05 Gssm Gansu 06 Gxsm Guangxi Zhuang Autonomous Region 07 Gzsm Guizhou 08 Hebsm Hebei 09 Hensm Henan 10 Hljsm Heilongjiang 11 Hndsm Hainan 12 Hubsm Hubei 13 Jlsm Jilin Province 14 Jssm Jiangsu 15 Jxsm Jiangxi 16 Lnsm Liaoning 17 Nmsm Inner Mongolia Gu Autonomous Region 18 Nxsm Ningxia Hui Autonomous Region 19 Qhsm Qinghai 20 Scsm Sichuan 21 Sdsm Shandong 22 Sxsm Shaanxi Province 23 Tjsm Tianjin 24 Twsm Taiwan Province 25 Xjsm Xinjiang Uygur Autonomous Region 26 Xzsm Tibet Autonomous Region 27 Zjsm Zhejiang 28 Shxsm Shanxi 1. Data projection: Projection: Albers False_Easting: 0.000000 False_Northing: 0.000000 Central_Meridian: 105.000000 Standard_Parallel_1: 25.000000 Standard_Parallel_2: 47.000000 Latitude_Of_Origin: 0.000000 Linear Unit: Meter (1.000000) 2. Data attribute table: area (area) perimeter ashm_ (sequence code) class (desert encoding) ashm_id (desert encoding) 3. Desert coding: mobile sandy land 2341010 Semi-mobile sandy land Semi-fixed sandy land 2341030 Gobi 2342000 Saline land 2343000 4: File format: National, sub-provincial and county-level desert map data types are vector shapefiles and E00 5: File naming: Data organization based on the National Basic Resources and Environmental Remote Sensing Dynamic Information Service System is performed on the file management layer of Windows NT. The file and directory names are compound names of English characters and numbers. Pinyin + SM composition, such as the desert map of Gansu Province is GSSM. The flag and county desert map is the pinyin + xxxx of the province name, and xxxx is the last four digits of the flag and county code. The division of provinces, districts, flags and counties is based on the administrative division data files in the national basic resources and environmental remote sensing dynamic information service operation system.

  12. e

    Le terroir de Tsarahonenana. A set of 8 map sheets. Scale of 1:4 000 to 1:2...

    • data.europa.eu
    Updated Dec 17, 2021
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    (2021). Le terroir de Tsarahonenana. A set of 8 map sheets. Scale of 1:4 000 to 1:2 000. Date of publication: 1967. [Dataset]. https://data.europa.eu/data/datasets/d8200c42-b8ed-43e6-88cd-0c999372e43d
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    Dataset updated
    Dec 17, 2021
    Description

    A set of 8 map sheets: 1. Carte 1 : la répartition des principaux types de sol. Scale of 1:4 000. Date of publication: 1967. 2. Carte 2 : la couverture végétale. Scale of 1:4 000. Date of publication: 1967. 3. Carte 3 : le paysage rural. Scale of 1:2 000. Date of publication: 1967. 4. Carte 4 : la distribution foncière des terres cultivées du terroir. Scale of 1:4 000. Date of publication: 1967. 5. Carte 5 : les régimes et le droit foncier. Scale of 1:2 000. Date of publication: 1967. 6. Carte 6 : structures foncières et liens de parenté : carte simplifiée. Scale of 1:4 000. Date of publication: 1967. 7. Carte 7 : les contrastes fonciers. Scale of 1:4 000. Date of publication: 1967. 8. Carte 8 : secteurs et types de cultures. Scale of 1:2 000. Date of publication: 1967.

  13. e

    AIB10 Map of the Levels of the Winter Pyrological Risk of Forest Types

    • data.europa.eu
    Updated Jun 25, 2012
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    (2012). AIB10 Map of the Levels of the Winter Pyrological Risk of Forest Types [Dataset]. https://data.europa.eu/data/datasets/r_abruzz-00118-20120625-104413
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    Dataset updated
    Jun 25, 2012
    Description

    Map of the levels of winter pyrological risk of forest types carried out as part of the implementation of the Regional Plan for the programming of activities to forecast, prevent and actively combat forest fires, Article 3 of Law No 353/2000 — Years 2011-2012. Regional thematic map derived from the classification of elements of the 2006 Regional Thematic Map of Forestry Types (Summer classification by Tammaro F.)

  14. C

    MOLISEDB.GIS.MO_geomorphological_poi_4

    • ckan.mobidatalab.eu
    Updated May 3, 2023
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    GeoDatiGovIt RNDT (2023). MOLISEDB.GIS.MO_geomorphological_poi_4 [Dataset]. https://ckan.mobidatalab.eu/dataset/molisedb-gis-mo_geomorphologic_poi_4
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    Dataset updated
    May 3, 2023
    Dataset provided by
    GeoDatiGovIt RNDT
    Area covered
    Missouri
    Description

    The MO_geomorphological_poi_4 feature class represents the point-type geomorphological elements - acquired from the geophological map at a scale of 1:25 000. The PTPAAV maps (Piano Territoriale Landscape Ambientale di Vasta Area) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by various groups of technicians, a coordination group which established through circulars the standards to be used for the drafting of the plans which ranged from the thickness of the tip of the graph to the type of screen and the shades to be used, and 8 groups one for each area, who created the maps trying to standardize the territorial information as much as possible. The hard copy of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic maps relating to some areas, the missing ones and in the case of scans that were not suitable for georeferencing, they were scanned. The cartographic basis used by the working groups for the creation of the PTPAAV maps was the IGM in 1:25,000 scale.

  15. m

    Qld 100k mapsheets - Warwick

    • demo.dev.magda.io
    • researchdata.edu.au
    • +1more
    zip
    Updated Apr 13, 2022
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    Bioregional Assessment Program (2022). Qld 100k mapsheets - Warwick [Dataset]. https://demo.dev.magda.io/dataset/ds-dga-2e4acaf5-a291-4fa1-9811-580b41de0bc4
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    zipAvailable download formats
    Dataset updated
    Apr 13, 2022
    Dataset provided by
    Bioregional Assessment Program
    License

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

    Area covered
    Queensland
    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. The polygons in this dataset are a digital representation of the distribution or extent of geological units within the area. Polygons have a range of attributes including unit name, age, lithological description and an abbreviated symbol for use in labelling the polygons. These have been extracted from the Rock Units Table held …Show full descriptionAbstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. The polygons in this dataset are a digital representation of the distribution or extent of geological units within the area. Polygons have a range of attributes including unit name, age, lithological description and an abbreviated symbol for use in labelling the polygons. These have been extracted from the Rock Units Table held in the Department of Natural Resources, Mines and Energy Merlin Database. Purpose To display the geology polygons which define the extent of rock units. Dataset History Supplemental_Information: Data captured at 1:40 000 scale. The data set is sourced from the Department's Geoscience and Resources Database (GRDB), a component of the Mineral and Energy Resources Location and Information Network (MERLIN) corporate database.(GRDB), a component of the Mineral and Energy Resources Location and Information Network (MERLIN) corporate database. NOTE: GEOLDATA was in most cases compiled based on Datum AGD66. The map tile coverages so compiled have now been projected to geographics based on Datum GDA94. Consequently the boundaries for these map tiles will not conform to the Latitude and Longitude graticule based on Datum GDA94. Entity_and_Attribute_Information: Detailed_Description: Entity_Type: Entity_Type_Label: 9341_r Entity_Type_Definition: Polygons have a range of attributes including unit name, age, lithological description and an abbreviated symbol for use in labelling the polygons. Entity_Type_Definition_Source: The Rock Units Table held in the Department of Natural Resources, Mines and Energy Merlin Database. Attribute: Attribute_Label: FID Attribute_Definition: Internal feature number. Attribute_Definition_Source: ESRI Attribute_Domain_Values: Unrepresentable_Domain: Sequential unique whole numbers that are automatically generated. Beginning_Date_of_Attribute_Values: March 2004 Attribute: Attribute_Label: Shape Attribute_Definition: Feature geometry. Attribute_Definition_Source: ESRI Attribute_Domain_Values: Unrepresentable_Domain: Coordinates defining the features. Attribute: Attribute_Label: KEY Attribute_Definition: Unique polygon identifier and relate item for poygon attributes Attribute: Attribute_Label: ROCK_U_NAM Attribute_Definition: The Map Unit Name of the polygon. In the case of named units it comprises of the standard binomial name. Unnamed subdivisions of named units include the binomial name with a letter symbol as a suffix. Unnamed units are represented by a letter symbol, usually in combination with a map sheet number. Attribute: Attribute_Label: AGE Attribute_Definition: Geological age of unit Attribute: Attribute_Label: LITH_SUMMA Attribute_Definition: Provides a brief description of the map units as they have been described in the course of the project work, or as has appeared on relevant hard copy map legends. Attribute: Attribute_Label: ROCK_U_TYP Attribute_Definition: Provides a means of separating map units, eg for constructing a map reference. This item will contain one of the following: STRAT- Stratigraphic unit, including sedimentary, volcanic and metamorphic rock units. INTRU- Intrusive rock units; COMPST- Compound unit where the polygon includes two or more rock units, either stratigraphic, intrusive or both; COMPST- Compound unit, as above where the dominant or topmost unit is of the STRAT type; COMPIN- Compound unit, as above, where the dominant unit is of the INTRU type; WATER- Water bodies- Large dams, lakes, waterholes. Attribute: Attribute_Label: SEQUENCE_N Attribute_Definition: A numeric field to allow sorting of the rock units in approximate stratigraphic order as they would appear on a map legend. Attribute: Attribute_Label: DOMINANT_R Attribute_Definition: A simplified lithological description to allow generation of thematic maps based on broad rock types. Attribute: Attribute_Label: MAP_SYMBOL Attribute_Definition: Provides an abbreviated label for polygons. Mostly based on the letter symbols as they appear on published maps or the original hard copy compilation sheets. These are not unique across the State, but should be unique within a single map tile, and usually adjacent tiles. Attribute: Attribute_Label: NAME_100K Attribute_Definition: Name of 1:100 000 map sheet coincident with the data extent. Overview_Description: Entity_and_Attribute_Overview: Polygon Attribute information includes Polygon Key, Rock Unit Name, Age, Lithology, Rock Unit Type, Map Symbol and 1:100 000 sheet name. Dataset Citation "Queensland Department of Natural Resources, Mines and Energy" (2014) Qld 100k mapsheets - Warwick. Bioregional Assessment Source Dataset. Viewed 28 September 2017, http://data.bioregionalassessments.gov.au/dataset/3e2fa307-1f06-4873-96d3-5c3e5638894a.

  16. C

    AIB09 Map of Summer Pyrological Risk Levels of Forest Types

    • ckan.mobidatalab.eu
    Updated May 3, 2023
    + more versions
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    GeoDatiGovIt RNDT (2023). AIB09 Map of Summer Pyrological Risk Levels of Forest Types [Dataset]. https://ckan.mobidatalab.eu/dataset/aib09-map-of-levels-of-summer-pyrological-risk-of-forest-typologies
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    Dataset updated
    May 3, 2023
    Dataset provided by
    GeoDatiGovIt RNDT
    Description

    Map of summer pyrological risk levels of forest typologies carried out as part of the implementation of the Regional Plan for the planning of forecasting, prevention and active fight against forest fires, art 3 Law n. 353/2000 - Years 2011-2012. Regional thematic map derived from the rating classification of elements of the regional thematic map of Forest Types 2006 (summer classification by Tammaro F.)

  17. C

    Hydrogeological overview map 1:250,000 of Germany (HÜK250)

    • ckan.mobidatalab.eu
    shp, view
    Updated Apr 23, 2021
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    Bundesanstalt für Geowissenschaften und Rohstoffe (2021). Hydrogeological overview map 1:250,000 of Germany (HÜK250) [Dataset]. https://ckan.mobidatalab.eu/dataset/hydrogeological-overview-map-1-250-000-of-germany-huk250
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    view, shpAvailable download formats
    Dataset updated
    Apr 23, 2021
    Dataset provided by
    Bundesanstalt für Geowissenschaften und Rohstoffe
    License

    http://dcat-ap.de/def/licenses/geonutz/20130319http://dcat-ap.de/def/licenses/geonutz/20130319

    Area covered
    Germany
    Description

    The hydrogeological overview map of Germany (HÜK250) describes the hydrogeological properties of the upper, extensively connected aquifers in Germany on a scale of 1:250,000. In addition to lithology, stratigraphy and ladder character, five hydrogeological attributes are recorded, which are shown in the thematic maps of consolidation, rock type, type of cavity, permeability and geochemical rock type. The respective systems and classifications are based, among other things, on the hydrogeological mapping instructions of the State Geological Services (SGD) from 1997. The HÜK250 is a digital map series. The HÜK250 is a joint project of the SGD under the leadership of the BGR, which was launched in 2000 as the HÜK200 on the occasion of the implementation of the EU Water Framework Directive (EU-WFD). The information from the geological overview map 1:200,000 (GÜK 200) on lithology, stratigraphy and genesis as well as regional maps and specialist knowledge of the SGD formed the basis. In the course of the project, cross-state coordinated hydrogeological information was compiled nationwide and finally made available digitally with a uniform general legend. In 2019, the scale migration took place from 1:200,000 to 1:250,000.

  18. d

    Soil Data Confidence map for NSW

    • data.gov.au
    basic, html, pdf, zip
    Updated Jul 9, 2021
    + more versions
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    Department of Planning, Industry and Environment (2021). Soil Data Confidence map for NSW [Dataset]. https://data.gov.au/dataset/ds-nsw-80de4817-f954-4d9b-ae53-348fb7c9c831
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    basic, html, zip, pdfAvailable download formats
    Dataset updated
    Jul 9, 2021
    Dataset provided by
    Department of Planning, Industry and Environment
    License

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

    Area covered
    New South Wales
    Description

    This map provides a guide to the data confidence of DPIE's soil related thematic map products in NSW. Examples of products this map supports includes Land and Soil Capability mapping, Inherent …Show full descriptionThis map provides a guide to the data confidence of DPIE's soil related thematic map products in NSW. Examples of products this map supports includes Land and Soil Capability mapping, Inherent fertility of soils in NSW and Great Soil Group soil types in NSW. Confidence classes are determined based on the data scale, type of mapping and information collected, accuracy of the attributes and quality assurance on the product. Soil data confidence is described using a 4 class system between high and very low as outlined below.: Good (1) - All necessary soil and landscape data is available at a catchment scale (1:100,000 & 1:250,000) to undertake the assessment of LSC and other soil thematic maps. Moderate (2) - Most soil and landscape data is available at a catchment scale (1:100,000 - 1:250,000) to undertake the assessment of LSC and other soil thematic maps. Low (3) - Limited soil and landscape data is available at a reconnaissance catchment scale (1:100,000 & 1:250,000) which limits the quality of the assessment of LSC and other soil thematic maps. Very low (4) - Very limited soil and landscape data is available at a broad catchment scale (1:250,000 - 1:500,000) and the LSC and other soil thematic maps should be used as a guide only. Online Maps: This dataset can be viewed using eSPADE (NSW’s soil spatial viewer), which contains a suite of soil and landscape information including soil profile data. Many of these datasets have hot-linked soil reports. An alternative viewer is the SEED Map; an ideal way to see what other natural resources datasets (e.g. vegetation) are available for this map area. Reference: Department of Planning, Industry and Environment, 2020, Soil Data Confidence map for NSW, Version 4, NSW Department of Planning, Industry and Environment, Parramatta.

  19. u

    Tactile Maps of Canada-Maps for Education-The Thematic Tactile Atlas of...

    • data.urbandatacentre.ca
    Updated Oct 1, 2024
    + more versions
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    (2024). Tactile Maps of Canada-Maps for Education-The Thematic Tactile Atlas of Canada-Rock Types - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/gov-canada-ea93b288-1579-58e8-b7eb-b72e16370cea
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    Dataset updated
    Oct 1, 2024
    License

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

    Area covered
    Canada
    Description

    The map title is Rock Types. Map scale. North arrow pointing to the north. Map projection is Hammer-Aitoff. Border of Canada. Great Lakes Border for each theme category within Canada. Neat line around the map. Each theme category is identified by a number that corresponds to the legend. Legend is divided into three categories: Metamorphic rocks, Deformed Sedimentary and Igneous rocks, Flat Lying Sedimentary rocks. Tactile maps are designed with Braille, large text, and raised features for visually impaired and low vision users. The Tactile Maps of Canada collection includes: (a) Maps for Education: tactile maps showing the general geography of Canada, including the Tactile Atlas of Canada (maps of the provinces and territories showing political boundaries, lakes, rivers and major cities), and the Thematic Tactile Atlas of Canada (maps showing climatic regions, relief, forest types, physiographic regions, rock types, soil types, and vegetation). (b) Maps for Mobility: to help visually impaired persons navigate spaces and routes in major cities by providing information about streets, buildings and other features of a travel route in the downtown area of a city. (c) Maps for Transportation and Tourism: to assist visually impaired persons in planning travel to new destinations in Canada, showing how to get to a city, and streets in the downtown area.

  20. m

    Global Digital Maps Market Share, Size & Industry Analysis 2033

    • marketresearchintellect.com
    Updated May 15, 2025
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    Market Research Intellect (2025). Global Digital Maps Market Share, Size & Industry Analysis 2033 [Dataset]. https://www.marketresearchintellect.com/product/digital-maps-market/
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    Dataset updated
    May 15, 2025
    Dataset authored and provided by
    Market Research Intellect
    License

    https://www.marketresearchintellect.com/privacy-policyhttps://www.marketresearchintellect.com/privacy-policy

    Area covered
    Global
    Description

    The size and share of this market is categorized based on Type (Road Maps, Topographic Maps, Satellite Maps, Street Maps, Thematic Maps) and Application (Navigation, Geographic Information Systems (GIS), Location-Based Services, Smart City Development, Tourism and Travel) and Technology (Web-Based Mapping, Mobile Mapping, Augmented Reality Maps, 3D Mapping, IoT-Integrated Maps) and geographical regions (North America, Europe, Asia-Pacific, South America, Middle-East and Africa).

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Nowosad (2021). IMCOMA-example-datasets [Dataset]. http://doi.org/10.6084/m9.figshare.13379228.v1

IMCOMA-example-datasets

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xmlAvailable download formats
Dataset updated
Feb 12, 2021
Dataset provided by
figshare
Authors
Nowosad
License

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

Description

Datasets- simple_land_cover1.tif - an example land cover dataset presented in Figures 1 and 2- simple_landform1.tif - an example landform dataset presented in Figures 1 and 2- landcover_europe.tif - a land cover dataset with nine categories for Europe - landcover_europe.qml - a QGIS color style for the landcover_europe.tif dataset- landform_europe.tif - a landform dataset with 17 categories for Europe - landform_europe.qml - a QGIS color style for the landform_europe.tif dataset- map1.gpkg - a map of LTs in Europe constructed using the INCOMA-based method- map1.qml - a QGIS color style for the map1.gpkg dataset- map2.gpkg - a map of LTs in Europe constructed using the COMA method to identify and delineate pattern types in each theme separately- map2.qml - a QGIS color style for the map2.gpkg dataset- map3.gpkg - a map of LTs in Europe constructed using the map overlay method- map3.qml - a QGIS color style for the map3.gpkg dataset

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