100+ datasets found
  1. h

    MAP-CC

    • huggingface.co
    Updated Apr 5, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Multimodal Art Projection (2024). MAP-CC [Dataset]. https://huggingface.co/datasets/m-a-p/MAP-CC
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 5, 2024
    Dataset authored and provided by
    Multimodal Art Projection
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    MAP-CC

    🌐 Homepage | 🤗 MAP-CC | 🤗 CHC-Bench | 🤗 CT-LLM | 📖 arXiv | GitHub An open-source Chinese pretraining dataset with a scale of 800 billion tokens, offering the NLP community high-quality Chinese pretraining data.

      Disclaimer
    

    This model, developed for academic purposes, employs rigorously compliance-checked training data to uphold the highest standards of integrity and compliance. Despite our efforts, the inherent complexities of data and the broad spectrum of… See the full description on the dataset page: https://huggingface.co/datasets/m-a-p/MAP-CC.

  2. USGS National Map

    • data.openlaredo.com
    • data.baltimorecity.gov
    • +13more
    html
    Updated Apr 11, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    GIS Portal (2025). USGS National Map [Dataset]. https://data.openlaredo.com/dataset/usgs-national-map
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Apr 11, 2025
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    GIS Portal
    Description

    The USGS Topo base map service from The National Map is a combination of contours, shaded relief, woodland and urban tint, along with vector layers, such as geographic names, governmental unit boundaries, hydrography, structures, and transportation, to provide a composite topographic base map. Data sources are the National Atlas for small scales, and The National Map for medium to large scales.

  3. OpenStreetMap

    • esriindia.hub.arcgis.com
    • cacgeoportal.com
    • +27more
    Updated Nov 21, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Esri India SAAS App (2024). OpenStreetMap [Dataset]. https://esriindia.hub.arcgis.com/maps/671a954016794bef88b76ac215ec5fef
    Explore at:
    Dataset updated
    Nov 21, 2024
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri India SAAS App
    License

    Attribution-ShareAlike 2.0 (CC BY-SA 2.0)https://creativecommons.org/licenses/by-sa/2.0/
    License information was derived automatically

    Description

    This web map references the live tiled map service from the OpenStreetMap (OSM) project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: https://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in ESRI products under a Creative Commons Attribution-ShareAlike license. Tip: This service is one of the basemaps used in the ArcGIS.com map viewer. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10. Tip: Here are some well known locations as they appear in this web map, accessed by launching the web map with a URL that contains location parameters: Athens, Cairo, Jakarta, Moscow, Mumbai, Nairobi, Paris, Rio De Janeiro, Shanghai

  4. Maps generator

    • zenodo.org
    text/x-python, zip
    Updated Mar 8, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Marcos Terol; Marcos Terol; Pedro Gomez-Gasquet; Pedro Gomez-Gasquet; Francisco Fraile; Francisco Fraile; Andrés Boza; Andrés Boza (2024). Maps generator [Dataset]. http://doi.org/10.5281/zenodo.10796431
    Explore at:
    text/x-python, zipAvailable download formats
    Dataset updated
    Mar 8, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Marcos Terol; Marcos Terol; Pedro Gomez-Gasquet; Pedro Gomez-Gasquet; Francisco Fraile; Francisco Fraile; Andrés Boza; Andrés Boza
    License

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

    Description

    The Python code provided generates polygonal maps resembling geographical landscapes, where certain areas may represent features like lakes or inaccessible regions. These maps are generated with specified characteristics such as regularity, gap density, and gap scale.

    Features:

    1. Polygon Generation:

      • The code utilizes the Shapely library to generate polygonal shapes within specified bounding boxes. These polygons serve as the primary representation of the map.
    2. Gap Generation:

      • Within the generated polygons, the code introduces gaps to simulate features like lakes or inaccessible areas. These gaps are represented as holes within the central polygon.
    3. Forest Generation
      • Within the generated polygons, the code introduces different forest areas. These forest are added like a new Feature inside the GEOJSON.
    4. Parameterized Generation:

      • The generation process is parameterized, allowing control over features such as regularity (shape uniformity), gap density (homogeneity of gaps), and gap scale (size of gaps relative to the polygon).

    Components:

    1. PolygonGenerator Class:

      • Responsible for generating the outer polygon shape and introducing gaps to simulate features.
      • Offers methods to generate individual polygons with specified characteristics.
    2. Parameter Ranges and Experimentation:

      • The code includes predefined ranges for regularity, gap density, vertex number, bounding box, forest density and forest scale range in 3 different CSV.
      • It conducts experiments by generating maps with different parameter combinations, offering insights into how these parameters affect the map's appearance.

    Usage:

    1. Map Generation:

      • Users can instantiate the PolygonGenerator class to generate individual polygons representing maps with specific features.
      • Parameters such as regularity, gap density, and gap scale can be adjusted to customize the map generation process.
    2. Experimentation:

      • Users can experiment with different parameter combinations to observe the effects on map generation.
      • This allows for exploration and understanding of how different parameters influence the characteristics of generated maps.

    Potential Applications:

    • The code can be used in various applications requiring the generation of simulated landscapes, such as in gaming, geographical analysis, or educational tools.
    • It provides a flexible and customizable framework for creating maps with specific features, allowing users to tailor the generated maps to their requirements.
    • Can be applied to generate maps for drone scanning operations, facilitating optimized area division and efficient data collection.
  5. d

    Google Address Data, Google Address API, Google location API, Google Map...

    • datarade.ai
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    APISCRAPY, Google Address Data, Google Address API, Google location API, Google Map API, Business Location Data- 100 M Google Address Data Available [Dataset]. https://datarade.ai/data-products/google-address-data-google-address-api-google-location-api-apiscrapy
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset authored and provided by
    APISCRAPY
    Area covered
    Moldova (Republic of), Åland Islands, China, Luxembourg, Estonia, Monaco, United Kingdom, Liechtenstein, Andorra, Spain
    Description

    Welcome to Apiscrapy, your ultimate destination for comprehensive location-based intelligence. As an AI-driven web scraping and automation platform, Apiscrapy excels in converting raw web data into polished, ready-to-use data APIs. With a unique capability to collect Google Address Data, Google Address API, Google Location API, Google Map, and Google Location Data with 100% accuracy, we redefine possibilities in location intelligence.

    Key Features:

    Unparalleled Data Variety: Apiscrapy offers a diverse range of address-related datasets, including Google Address Data and Google Location Data. Whether you seek B2B address data or detailed insights for various industries, we cover it all.

    Integration with Google Address API: Seamlessly integrate our datasets with the powerful Google Address API. This collaboration ensures not just accessibility but a robust combination that amplifies the precision of your location-based insights.

    Business Location Precision: Experience a new level of precision in business decision-making with our address data. Apiscrapy delivers accurate and up-to-date business locations, enhancing your strategic planning and expansion efforts.

    Tailored B2B Marketing: Customize your B2B marketing strategies with precision using our detailed B2B address data. Target specific geographic areas, refine your approach, and maximize the impact of your marketing efforts.

    Use Cases:

    Location-Based Services: Companies use Google Address Data to provide location-based services such as navigation, local search, and location-aware advertisements.

    Logistics and Transportation: Logistics companies utilize Google Address Data for route optimization, fleet management, and delivery tracking.

    E-commerce: Online retailers integrate address autocomplete features powered by Google Address Data to simplify the checkout process and ensure accurate delivery addresses.

    Real Estate: Real estate agents and property websites leverage Google Address Data to provide accurate property listings, neighborhood information, and proximity to amenities.

    Urban Planning and Development: City planners and developers utilize Google Address Data to analyze population density, traffic patterns, and infrastructure needs for urban planning and development projects.

    Market Analysis: Businesses use Google Address Data for market analysis, including identifying target demographics, analyzing competitor locations, and selecting optimal locations for new stores or offices.

    Geographic Information Systems (GIS): GIS professionals use Google Address Data as a foundational layer for mapping and spatial analysis in fields such as environmental science, public health, and natural resource management.

    Government Services: Government agencies utilize Google Address Data for census enumeration, voter registration, tax assessment, and planning public infrastructure projects.

    Tourism and Hospitality: Travel agencies, hotels, and tourism websites incorporate Google Address Data to provide location-based recommendations, itinerary planning, and booking services for travelers.

    Discover the difference with Apiscrapy – where accuracy meets diversity in address-related datasets, including Google Address Data, Google Address API, Google Location API, and more. Redefine your approach to location intelligence and make data-driven decisions with confidence. Revolutionize your business strategies today!

  6. 3D Map System Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 3, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Dataintelo (2024). 3D Map System Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-3d-map-system-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Dec 3, 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

    3D Map System Market Outlook



    The global 3D map system market size was valued at approximately $4.2 billion in 2023 and is projected to reach around $11.3 billion by 2032, growing at a robust CAGR of 11.5% during the forecast period. The increasing demand for advanced mapping solutions across various sectors such as automotive, urban planning, and infrastructure development is a significant growth factor propelling this market. The adoption of 3D maps, driven by technological advancements and the need for precise spatial data, is transforming how industries manage and utilize geospatial information.



    One of the primary growth factors of the 3D map system market is the burgeoning demand within the automotive industry. The rise of autonomous and connected vehicles relies heavily on high-precision 3D mapping systems to ensure safety and efficiency. As vehicles become increasingly sophisticated, the need for accurate terrain and environmental data becomes paramount, driving the integration of these systems into modern automobiles. Additionally, the evolution of smart cities and infrastructure projects around the globe has necessitated the use of 3D maps for planning and management, further fueling market growth.



    The aerospace and defense sectors are also major proponents of 3D map systems, utilizing them for navigation, simulation, and mission planning. The accuracy and detailed visualization provided by these maps are indispensable in military applications, where precise terrain understanding can critically impact operations and strategy development. Furthermore, the expansion of drone technology has increased the demand for 3D mapping solutions, as these aerial vehicles increasingly rely on detailed geospatial data to perform a variety of tasks ranging from surveillance to environmental monitoring.



    In urban planning, the use of 3D mapping systems has gained significant traction due to their ability to provide a comprehensive view of urban landscapes, aiding in efficient planning and decision-making. These systems enable planners to visualize and simulate different developmental scenarios, assessing their impact on the environment and city infrastructure. Such capabilities are invaluable in developing sustainable urban areas that can accommodate growing populations while minimizing ecological footprints. Moreover, as environmental concerns and regulatory pressures increase, the use of 3D maps is becoming more prevalent in infrastructure planning and development.



    Regionally, North America dominates the 3D map system market, driven by technological innovation and high adoption rates across various industries. The presence of key market players and substantial investment in research and development further bolster the region's dominance. Meanwhile, the Asia Pacific is experiencing the fastest growth, attributed to rapid urbanization and infrastructure development, particularly in countries like China and India. The implementation of smart city initiatives and the expansion of automotive and defense sectors are significant factors contributing to the region's market expansion.



    Component Analysis



    The component segment of the 3D map system market is subdivided into software, hardware, and services, each playing a pivotal role in the overall functionality and utilization of 3D mapping technologies. Software components are at the core of the 3D map system market, offering essential functionalities for creating, editing, and managing 3D spatial data. The demand for sophisticated software solutions is rising as users seek advanced features such as real-time data processing, analytics, and augmented reality integration. These software solutions enable various applications, from navigation and simulation to geospatial data analysis, making them indispensable across multiple industries.



    Hardware components include the physical devices and infrastructure required to capture, store, and process 3D mapping data. This includes GPS devices, LiDAR systems, and high-resolution cameras, which are critical for accurate data acquisition. The hardware segment is experiencing growth due to technological advances that enhance data capture accuracy and efficiency. The integration of artificial intelligence and machine learning with hardware components further improves the capability of 3D mapping systems, enabling automated data processing and real-time applications.



    The services component encompasses the various support and maintenance services essential for the optimal functioning of 3D map systems. These services include system integration,

  7. Digital Geologic Map of Big Thicket National Preserve and Vicinity, Texas...

    • catalog.data.gov
    • data.amerigeoss.org
    Updated Jun 5, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Park Service (2024). Digital Geologic Map of Big Thicket National Preserve and Vicinity, Texas (NPS, GRD, GRI, BITH, BITH digital map) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-map-of-big-thicket-national-preserve-and-vicinity-texas-nps-grd-gri-bith-
    Explore at:
    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Texas
    Description

    The Digital Geologic Map of Big Thicket National Preserve and Vicinity, Texas is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Texas Water Development Board and Railroad Commission of Texas. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (bith_metadata.txt; available at http://nrdata.nps.gov/bith/nrdata/geology/gis/bith_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (bith_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 15N. That data is within the area of interest of Big Thicket National Preserve.

  8. a

    Main Map

    • hub.arcgis.com
    Updated Aug 8, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    City of Ashland (2018). Main Map [Dataset]. https://hub.arcgis.com/maps/ea96db24dabb442b9d68784098db796a
    Explore at:
    Dataset updated
    Aug 8, 2018
    Dataset authored and provided by
    City of Ashland
    Area covered
    Description

    This web map is for the main City Base Map application for general city use.

  9. d

    Data from: California State Waters Map Series--Offshore of Santa Cruz Web...

    • catalog.data.gov
    • data.usgs.gov
    • +2more
    Updated Jul 6, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    U.S. Geological Survey (2024). California State Waters Map Series--Offshore of Santa Cruz Web Services [Dataset]. https://catalog.data.gov/dataset/california-state-waters-map-series-offshore-of-santa-cruz-web-services
    Explore at:
    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Santa Cruz, California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Santa Cruz map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Santa Cruz map area data layers. Data layers are symbolized as shown on the associated map sheets.

  10. U

    California State Waters Map Series--Offshore of Ventura Web Services

    • data.usgs.gov
    • gimi9.com
    • +3more
    Updated Jan 1, 2015
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Samuel Johnson; Peter Dartnell; Guy Cochrane; Nadine Golden; Eleyne Phillips; Andrew Ritchie; Rikk Kvitek; H. Greene; Lisa Krigsman; Charles Endris; Gordon Seitz; Carlos Gutierrez; Ray Sliter; Mercedes Erdey; Florence Wong; Mary Yoklavich; Amy Draut; Patrick Hart; Susan Cochran (2015). California State Waters Map Series--Offshore of Ventura Web Services [Dataset]. https://data.usgs.gov/datacatalog/data/USGS:b86279e2-854a-4ea1-8b43-c32830b121ff
    Explore at:
    Dataset updated
    Jan 1, 2015
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Samuel Johnson; Peter Dartnell; Guy Cochrane; Nadine Golden; Eleyne Phillips; Andrew Ritchie; Rikk Kvitek; H. Greene; Lisa Krigsman; Charles Endris; Gordon Seitz; Carlos Gutierrez; Ray Sliter; Mercedes Erdey; Florence Wong; Mary Yoklavich; Amy Draut; Patrick Hart; Susan Cochran
    License

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

    Time period covered
    2006 - 2015
    Area covered
    California, Ventura
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, ...

  11. a

    Oregon Statewide Habitat Map

    • hub.arcgis.com
    • data.oregon.gov
    Updated Jun 16, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    State of Oregon (2023). Oregon Statewide Habitat Map [Dataset]. https://hub.arcgis.com/documents/894a627ba88b45b89d91ed37bc347365
    Explore at:
    Dataset updated
    Jun 16, 2023
    Dataset authored and provided by
    State of Oregon
    Area covered
    Oregon
    Description

    This is a dataset download, not a document. The Open button will start the download.In 2015, the Oregon Biodiversity Information Center at Portland State University worked with the Oregon Department of Fish and Wildlife (ODFW), to assist in their 2015 conservation strategy update. This work involved updating the maps of each of ODFW’s conservation strategy habitats originally created for the first strategy in 2006,and integrating these into a 2015 strategy habitat map. The updated maps took advantage of new data and spatial modeling tools. However, strategy habitats only represent only 11 of the approximately 77 Oregon habitats, and are only mapped in the ecoregions in which they are conservation priorities. As a result, there was a strong interest in using this 2015 data to create a statewide, comprehensive habitat map. In 2017, the Oregon Department of Administrative Services, Geographic Enterprise Office (DAS-GEO), through their Framework Implementation program, with additional support from ODFW, funded the completion of a statewide habitat map, which was completed at the end of 2018. The habitat map is a compilation of a number of recent regional and ecosystem focused vegetation-mapping efforts. It includes the best available data for each of the habitat types. As a result, different parts of the map rely on varied methods and data. For detailed methodology please see the enclosed PDF document.

  12. Outline Map

    • data-gnrc.opendata.arcgis.com
    • data.baltimorecity.gov
    • +7more
    Updated Jan 30, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Esri (2021). Outline Map [Dataset]. https://data-gnrc.opendata.arcgis.com/maps/0f26b79821374a59b306326e7d76c6b5
    Explore at:
    Dataset updated
    Jan 30, 2021
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This vector web map features outline maps of the World. The maps can be used for coloring and other fun activities by budding cartographers. These outline maps are great for teaching children about our World. Have them color and label countries, regions and bodies of water. Limited labels appear on the map at large scales. After coloring the city maps, children can do further research to learn more about these places. These maps are also available in a printable PDF format. See this blog with more details on how to work with the vector maps in ArcGIS Pro.For other creatively designed Esri vector basemaps, see the ArcGIS Living Atlas of the World gallery.

  13. U

    California State Waters Map Series--Offshore of Point Conception Web...

    • data.usgs.gov
    • s.cnmilf.com
    • +1more
    Updated Jan 1, 2015
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Samuel Johnson; Peter Dartnell; Guy Cochrane; Stephen Hartnell; Nadine Golden; Rikk Kvitek; Clifton Davenport (2015). California State Waters Map Series--Offshore of Point Conception Web Services [Dataset]. http://doi.org/10.5066/F7QN64XQ
    Explore at:
    Dataset updated
    Jan 1, 2015
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Samuel Johnson; Peter Dartnell; Guy Cochrane; Stephen Hartnell; Nadine Golden; Rikk Kvitek; Clifton Davenport
    License

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

    Time period covered
    2006 - 2015
    Area covered
    Point Conception, California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, ...

  14. h

    emoji-map

    • huggingface.co
    Updated Sep 12, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Omar Kamali (2024). emoji-map [Dataset]. https://huggingface.co/datasets/omarkamali/emoji-map
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 12, 2024
    Authors
    Omar Kamali
    Description

    📊 Dataset Overview

    The emoji-map dataset, created by omarkamali, contains text data in parquet format. It consists of 10K-100K entries, specifically 5.03k rows. The dataset is available in the train split.

      📁 Data Structure
    

    The dataset includes two main columns: emoji and unicode_description. The emoji column contains various emoji characters, while the unicode_description column provides a textual description of each emoji.

      🔍 Sample Data
    

    Examples from the… See the full description on the dataset page: https://huggingface.co/datasets/omarkamali/emoji-map.

  15. d

    California State Waters Map Series--Offshore of Fort Ross Web Services

    • datasets.ai
    • data.usgs.gov
    • +3more
    55
    Updated Sep 23, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department of the Interior (2024). California State Waters Map Series--Offshore of Fort Ross Web Services [Dataset]. https://datasets.ai/datasets/california-state-waters-map-series-offshore-of-fort-ross-web-services
    Explore at:
    55Available download formats
    Dataset updated
    Sep 23, 2024
    Dataset authored and provided by
    Department of the Interior
    Area covered
    California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore Fort Ross map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore Fort Ross map area data layers. Data layers are symbolized as shown on the associated map sheets.

  16. Dixie Fire Structure Status Map

    • gis.data.cnra.ca.gov
    • data.ca.gov
    • +7more
    Updated Jul 26, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    California Department of Forestry and Fire Protection (2021). Dixie Fire Structure Status Map [Dataset]. https://gis.data.cnra.ca.gov/maps/CALFIRE-Forestry::dixie-fire-structure-status-map
    Explore at:
    Dataset updated
    Jul 26, 2021
    Dataset authored and provided by
    California Department of Forestry and Fire Protectionhttp://calfire.ca.gov/
    Area covered
    Description

    This map feeds into a web app that allows a user to examine the known status of structures damaged by the wildfire. If a structure point does not appear on the map it may still have been impacted by the fire. Specific addresses can be searched for in the search bar. Use the imagery and topographic basemaps and photos to positively identify a structure. Photos may only be available for damaged and destroyed structures.For more information about the wildfire response efforts, visit the CAL FIRE incident page.

  17. w

    California State Waters Map Series--Offshore of Scott Creek Web Services

    • data.wu.ac.at
    • search.dataone.org
    arcgis server rest +3
    Updated Jun 8, 2018
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department of the Interior (2018). California State Waters Map Series--Offshore of Scott Creek Web Services [Dataset]. https://data.wu.ac.at/schema/data_gov/ZWIzM2Y0YjEtMTlkMi00ZGE0LTg2ODktZjNjZjY0ZjljOTBk
    Explore at:
    esri rest, web mapping service (wms), wms, arcgis server restAvailable download formats
    Dataset updated
    Jun 8, 2018
    Dataset provided by
    Department of the Interior
    Area covered
    158f22826bccd563112ebc0aec8092e3a01d6c6b
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within Californiaâ s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map Californiaâ s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of â landsâ from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of Californiaâ s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bayâ s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Serviceâ Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Scott Creek map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these â ground-truthâ surveying data are available from the CSMP Video and Photograph Portal at http://dx.doi.org/10.5066/F7J1015K. The â seafloor characterâ data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The â potential habitatsâ polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Scott Creek map area data layers. Data layers are symbolized as shown on the associated map sheets.

  18. a

    Contours Offshore of Point Reyes Map Map Area, California

    • data.amerigeoss.org
    Updated Jul 25, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    United States[old] (2019). Contours Offshore of Point Reyes Map Map Area, California [Dataset]. https://data.amerigeoss.org/fr/dataset/0760af97-d27c-4fa9-8ce1-ade95023f9d5
    Explore at:
    Dataset updated
    Jul 25, 2019
    Dataset provided by
    United States[old]
    Description

    This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Point Reyes map area, California. The vector data file is included in "Contours_PointReyes.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_PointReyes.html.

    10-m interval contours of the Offshore of Point Reyes map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a bathymetric surface model. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

  19. g

    High Resolution Population Density Data - Map View

    • globalmidwiveshub.org
    Updated Aug 11, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Direct Relief (2021). High Resolution Population Density Data - Map View [Dataset]. https://www.globalmidwiveshub.org/datasets/high-resolution-population-density-data-map-view
    Explore at:
    Dataset updated
    Aug 11, 2021
    Dataset authored and provided by
    Direct Relief
    Description

    This map is just one of the many data visualizations on the Global Midwives Hub, a digital resource with open data, maps, and mapping applications (among other things), to support advocacy for improved maternal and newborn services, supported by the International Confederation of Midwives (ICM), UNFPA, WHO, and Direct Relief.

  20. Enhanced Contrast Map

    • esriaustraliahub.com.au
    • share-open-data-njtpa.hub.arcgis.com
    • +4more
    Updated Jun 21, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Esri (2022). Enhanced Contrast Map [Dataset]. https://www.esriaustraliahub.com.au/maps/084291b0ecad4588b8c8853898d72445
    Explore at:
    Dataset updated
    Jun 21, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The Enhanced Contrast Map (World Edition) web map provides a detailed vector basemap for the world symbolized using enhanced contrast and a color-vision-deficient-safe palette. It is designed for use as part of a presentation that aims to meet the WCAG (Web Content Accessibility Guidelines) AA standard, and US Government Section 508 compliance. The base layer includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, and building footprints. The reference layer includes all labels and administrative boundary lines. Label size has been increased where possible, but not to the point where it conceals the map detail. The 'Ubuntu' font is used throughout, to be clear and legible while maintaining some character.This basemap, included in the ArcGIS Living Atlas of the World, uses the Enhanced Contrast Reference and Enhanced Contrast Base vector tile layers.The vector tile layers in this web map are built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Learn more about this basemap from the cartographic designer in Working with Enhanced Contrast basemaps to improve accessibility.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layer item referenced in this map.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Multimodal Art Projection (2024). MAP-CC [Dataset]. https://huggingface.co/datasets/m-a-p/MAP-CC

MAP-CC

m-a-p/MAP-CC

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Apr 5, 2024
Dataset authored and provided by
Multimodal Art Projection
License

Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
License information was derived automatically

Description

MAP-CC

🌐 Homepage | 🤗 MAP-CC | 🤗 CHC-Bench | 🤗 CT-LLM | 📖 arXiv | GitHub An open-source Chinese pretraining dataset with a scale of 800 billion tokens, offering the NLP community high-quality Chinese pretraining data.

  Disclaimer

This model, developed for academic purposes, employs rigorously compliance-checked training data to uphold the highest standards of integrity and compliance. Despite our efforts, the inherent complexities of data and the broad spectrum of… See the full description on the dataset page: https://huggingface.co/datasets/m-a-p/MAP-CC.

Search
Clear search
Close search
Google apps
Main menu