93 datasets found
  1. I

    Interactive Map Creation Tools Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Mar 15, 2025
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    Market Research Forecast (2025). Interactive Map Creation Tools Report [Dataset]. https://www.marketresearchforecast.com/reports/interactive-map-creation-tools-35432
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    pdf, ppt, docAvailable download formats
    Dataset updated
    Mar 15, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

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

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Discover the booming interactive map creation tools market! This in-depth analysis reveals a $2.5 billion market in 2025, projected to reach $8 billion by 2033, driven by cloud-based solutions and growing data visualization needs. Learn about key players, market segmentation, and regional trends shaping this exciting sector.

  2. I

    Interactive Map Creation Tools Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 3, 2025
    + more versions
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    Market Report Analytics (2025). Interactive Map Creation Tools Report [Dataset]. https://www.marketreportanalytics.com/reports/interactive-map-creation-tools-55534
    Explore at:
    doc, pdf, pptAvailable download formats
    Dataset updated
    Apr 3, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

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

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Discover the booming interactive map creation tools market! Our in-depth analysis reveals a $2 billion market in 2025, projected to grow at 15% CAGR through 2033. Learn about key trends, leading companies (Mapbox, ArcGIS, Google), and regional insights to capitalize on this expanding sector.

  3. d

    Tutorial: How to use Google Data Studio and ArcGIS Online to create an...

    • search.dataone.org
    • hydroshare.org
    • +1more
    Updated Apr 15, 2022
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    Sarah Beganskas (2022). Tutorial: How to use Google Data Studio and ArcGIS Online to create an interactive data portal [Dataset]. http://doi.org/10.4211/hs.9edae0ef99224e0b85303c6d45797d56
    Explore at:
    Dataset updated
    Apr 15, 2022
    Dataset provided by
    Hydroshare
    Authors
    Sarah Beganskas
    Description

    This tutorial will teach you how to take time-series data from many field sites and create a shareable online map, where clicking on a field location brings you to a page with interactive graph(s).

    The tutorial can be completed with a sample dataset (provided via a Google Drive link within the document) or with your own time-series data from multiple field sites.

    Part 1 covers how to make interactive graphs in Google Data Studio and Part 2 covers how to link data pages to an interactive map with ArcGIS Online. The tutorial will take 1-2 hours to complete.

    An example interactive map and data portal can be found at: https://temple.maps.arcgis.com/apps/View/index.html?appid=a259e4ec88c94ddfbf3528dc8a5d77e8

  4. d

    California State Waters Map Series--Offshore of Coal Oil Point Web Services

    • catalog.data.gov
    • search.dataone.org
    • +2more
    Updated Nov 21, 2025
    + more versions
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    U.S. Geological Survey (2025). California State Waters Map Series--Offshore of Coal Oil Point Web Services [Dataset]. https://catalog.data.gov/dataset/california-state-waters-map-series-offshore-of-coal-oil-point-web-services
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    Dataset updated
    Nov 21, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Coal Oil Point, 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 Coal Oil Point 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 Coal Oil Point map area data layers. Data layers are symbolized as shown on the associated map sheets.

  5. d

    California State Waters Map Series--Point Conception to Hueneme Canyon Web...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Nov 27, 2025
    + more versions
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    U.S. Geological Survey (2025). California State Waters Map Series--Point Conception to Hueneme Canyon Web Services [Dataset]. https://catalog.data.gov/dataset/california-state-waters-map-series-point-conception-to-hueneme-canyon-web-services
    Explore at:
    Dataset updated
    Nov 27, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    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, 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 Point Conception to Hueneme Canyon 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 Point Conception to Hueneme Canyon map area data layers. Data layers are symbolized as shown on the associated map sheets.

  6. Data from: NDS: an interactive, web-based system to visualize urban...

    • tandf.figshare.com
    mp4
    Updated May 31, 2023
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    Yu Lan; Elizabeth Delmelle; Eric Delmelle (2023). NDS: an interactive, web-based system to visualize urban neighborhood dynamics in United States [Dataset]. http://doi.org/10.6084/m9.figshare.14484512.v1
    Explore at:
    mp4Available download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Taylor & Francishttps://taylorandfrancis.com/
    Authors
    Yu Lan; Elizabeth Delmelle; Eric Delmelle
    License

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

    Area covered
    United States
    Description

    NDS is an interactive, web-based system, for the visualization of multidimensional neighborhood dynamics across the 50 largest US Metropolitan Statistical Areas (MSAs) from 1980 to 2010 (http://neighborhooddynamics.dreamhosters.com). Four different visualization tools are developed: (1) an interactive time slider to show neighborhood classification changes for different years; (2) multiple interactive bar charts for each variables of each neighborhood; (3) an animated neighborhood’s trajectory and sequence cluster on a self-organizing map (SOM) output space; and (4) a synchronized visualization tool showing maps for four time stamps at once. The development of this interactive online platform for visualizing dynamics overcomes many of the challenges associated with communicating changes for multiple variables, across multiple time stamps, and for a large geographic area when relying upon static maps. The system enables users to select and dive into details on particular neighborhoods and explore their changes over time.

  7. s

    GLOBE Tree Heights Web Map Service pts

    • geospatial.strategies.org
    Updated Nov 7, 2020
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    Institute for Global Environmental Strategies (2020). GLOBE Tree Heights Web Map Service pts [Dataset]. https://geospatial.strategies.org/maps/a7e32e42fa874078b0580b9e27274659
    Explore at:
    Dataset updated
    Nov 7, 2020
    Dataset authored and provided by
    Institute for Global Environmental Strategies
    Area covered
    Earth
    Description

    GLOBE provides the ability to view and interact with data measured across the world. Select the visualization tool to map, graph, filter and export data that have been measured across GLOBE protocols since 1995. Currently the GLOBE Data Visualization Tool supports a subset of protocols. Additional Features and capabilities are continually being added.

  8. B

    Development of Interactive Data Visualization Tool for the Predictive...

    • borealisdata.ca
    • search.dataone.org
    Updated Apr 19, 2022
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    Wai Chung Wilson Chan (2022). Development of Interactive Data Visualization Tool for the Predictive Ecosystem Mapping Project [Dataset]. http://doi.org/10.5683/SP3/7RVB70
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 19, 2022
    Dataset provided by
    Borealis
    Authors
    Wai Chung Wilson Chan
    License

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

    Area covered
    Canada, Babine Mountains Provincial Park, British Columbia
    Description

    Biogeoclimatic Ecosystem Classification (BEC) system is the ecosystem classification adopted in the forest management within British Columbia based on vegetation, soil, and climate characteristics whereas Site Series is the smallest unit of the system. The Ministry of Forests, Lands, Natural Resource Operations and Rural Development held under the Government of British Columbia (“the Ministry”) developed a web-based tool known as BEC Map for maintaining and sharing the information of the BEC system, but the Site Series information was not included in the tool due to its quantity and complexity. In order to allow users to explore and interact with the information, this project aimed to develop a web-based tool with high data quality and flexibility to users for the Site Series classes using the “Shiny” and “Leaflet” packages in R. The project started with data classification and pre-processing of the raster images and attribute tables through identification of client requirements, spatial database design and data cleaning. After data transformation was conducted, spatial relationships among these data were developed for code development. The code development included the setting-up of web map and interactive tools for facilitating user friendliness and flexibility. The codes were further tested and enhanced to meet the requirements of the Ministry. The web-based tool provided an efficient and effective platform to present the complicated Site Series features with the use of Web Mapping System (WMS) in map rendering. Four interactive tools were developed to allow users to examine and interact with the information. The study also found that the mode filter performed well in data preservation and noise minimization but suffered from long processing time and creation of tiny sliver polygons.

  9. d

    Rose Swanson Mountain Data Collation and Citizen Science

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
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    Sun, Xiaoqing (Sunny) (2023). Rose Swanson Mountain Data Collation and Citizen Science [Dataset]. http://doi.org/10.5683/SP3/FSTOUQ
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Sun, Xiaoqing (Sunny)
    Description

    This study focuses on the use of citizen science and GIS tools for collecting and analyzing data on Rose Swanson Mountain in British Columbia, Canada. While several organizations collect data on wildlife habitats, trail mapping, and fire documentation on the mountain, there are few studies conducted on the area and citizen science is not being addressed. The study aims to aggregate various data sources and involve citizens in the data collection process using ArcGIS Dashboard and ArcGIS Survey 123. These GIS tools allow for the integration and analysis of different kinds of data, as well as the creation of interactive maps and surveys that can facilitate citizen engagement and data collection. The data used in the dashboard was sourced from BC Data Catalogue, Explore the Map, and iNaturalist. Results show effective citizen participation, with 1073 wildlife observations and 3043 plant observations. The dashboard provides a user-friendly interface for citizens to tailor their map extent and layers, access surveys, and obtain information on each attribute included in the pop-up by clicking. Analysis on classification of fuel types, ecological communities, endangered wildlife species presence and critical habitat, and scope of human activities can be conducted based on the distribution of data. The dashboard can provide direction for researchers to develop research or contribute to other projects in progress, as well as advocate for natural resource managers to use citizen science data. The study demonstrates the potential for GIS and citizen science to contribute to meaningful discoveries and advancements in areas.

  10. d

    Data from: California State Waters Map Series--Offshore of Tomales Point Web...

    • datasets.ai
    • data.usgs.gov
    • +4more
    55
    Updated Jun 1, 2023
    + more versions
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    Department of the Interior (2023). California State Waters Map Series--Offshore of Tomales Point Web Services [Dataset]. https://datasets.ai/datasets/california-state-waters-map-series-offshore-of-tomales-point-web-services
    Explore at:
    55Available download formats
    Dataset updated
    Jun 1, 2023
    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 of Tomales Point 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 Tomales Point map area data layers. Data layers are symbolized as shown on the associated map sheets.

  11. z

    Classification of web-based Digital Humanities projects leveraging...

    • zenodo.org
    • data-staging.niaid.nih.gov
    csv, tsv
    Updated Nov 10, 2025
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    Tommaso Battisti; Tommaso Battisti (2025). Classification of web-based Digital Humanities projects leveraging information visualisation techniques [Dataset]. http://doi.org/10.5281/zenodo.14192758
    Explore at:
    tsv, csvAvailable download formats
    Dataset updated
    Nov 10, 2025
    Dataset provided by
    Zenodo
    Authors
    Tommaso Battisti; Tommaso Battisti
    License

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

    Description

    Description

    This dataset contains a list of 186 Digital Humanities projects leveraging information visualisation techniques. Each project has been classified according to visualisation and interaction methods, narrativity and narrative solutions, domain, methods for the representation of uncertainty and interpretation, and the employment of critical and custom approaches to visually represent humanities data.

    Classification schema: categories and columns

    The project_id column contains unique internal identifiers assigned to each project. Meanwhile, the last_access column records the most recent date (in DD/MM/YYYY format) on which each project was reviewed based on the web address specified in the url column.
    The remaining columns can be grouped into descriptive categories aimed at characterising projects according to different aspects:

    Narrativity. It reports the presence of information visualisation techniques employed within narrative structures. Here, the term narrative encompasses both author-driven linear data stories and more user-directed experiences where the narrative sequence is determined by user exploration [1]. We define 2 columns to identify projects using visualisation techniques in narrative, or non-narrative sections. Both conditions can be true for projects employing visualisations in both contexts. Columns:

    • non_narrative (boolean)

    • narrative (boolean)

    Domain. The humanities domain to which the project is related. We rely on [2] and the chapters of the first part of [3] to abstract a set of general domains. Column:

    • domain (categorical):

      • History and archaeology

      • Art and art history

      • Language and literature

      • Music and musicology

      • Multimedia and performing arts

      • Philosophy and religion

      • Other: both extra-list domains and cases of collections without a unique or specific thematic focus.

    Visualisation of uncertainty and interpretation. Buiding upon the frameworks proposed by [4] and [5], a set of categories was identified, highlighting a distinction between precise and impressional communication of uncertainty. Precise methods explicitly represent quantifiable uncertainty such as missing, unknown, or uncertain data, precisely locating and categorising it using visual variables and positioning. Two sub-categories are interactive distinction, when uncertain data is not visually distinguishable from the rest of the data but can be dynamically isolated or included/excluded categorically through interaction techniques (usually filters); and visual distinction, when uncertainty visually “emerges” from the representation by means of dedicated glyphs and spatial or visual cues and variables. On the other hand, impressional methods communicate the constructed and situated nature of data [6], exposing the interpretative layer of the visualisation and indicating more abstract and unquantifiable uncertainty using graphical aids or interpretative metrics. Two sub-categories are: ambiguation, when the use of graphical expedients—like permeable glyph boundaries or broken lines—visually convey the ambiguity of a phenomenon; and interpretative metrics, when expressive, non-scientific, or non-punctual metrics are used to build a visualisation. Column:

    • uncertainty_interpretation (categorical):

      • Interactive distinction

      • Visual distinction

      • Ambiguation

      • Interpretative metrics

    Critical adaptation. We identify projects in which, with regards to at least a visualisation, the following criteria are fulfilled: 1) avoid repurposing of prepackaged, generic-use, or ready-made solutions; 2) being tailored and unique to reflect the peculiarities of the phenomena at hand; 3) avoid simplifications to embrace and depict complexity, promoting time-consuming visualisation-based inquiry. Column:

    • critical_adaptation (boolean)

    Non-temporal visualisation techniques. We adopt and partially adapt the terminology and definitions from [7]. A column is defined for each type of visualisation and accounts for its presence within a project, also including stacked layouts and more complex variations. Columns and inclusion criteria:

    • plot (boolean): visual representations that map data points onto a two-dimensional coordinate system.

    • cluster_or_set (boolean): sets or cluster-based visualisations used to unveil possible inter-object similarities.

    • map (boolean): geographical maps used to show spatial insights. While we do not specify the variants of maps (e.g., pin maps, dot density maps, flow maps, etc.), we make an exception for maps where each data point is represented by another visualisation (e.g., a map where each data point is a pie chart) by accounting for the presence of both in their respective columns.

    • network (boolean): visual representations highlighting relational aspects through nodes connected by links or edges.

    • hierarchical_diagram (boolean): tree-like structures such as tree diagrams, radial trees, but also dendrograms. They differ from networks for their strictly hierarchical structure and absence of closed connection loops.

    • treemap (boolean): still hierarchical, but highlighting quantities expressed by means of area size. It also includes circle packing variants.

    • word_cloud (boolean): clouds of words, where each instance’s size is proportional to its frequency in a related context

    • bars (boolean): includes bar charts, histograms, and variants. It coincides with “bar charts” in [7] but with a more generic term to refer to all bar-based visualisations.

    • line_chart (boolean): the display of information as sequential data points connected by straight-line segments.

    • area_chart (boolean): similar to a line chart but with a filled area below the segments. It also includes density plots.

    • pie_chart (boolean): circular graphs divided into slices which can also use multi-level solutions.

    • plot_3d (boolean): plots that use a third dimension to encode an additional variable.

    • proportional_area (boolean): representations used to compare values through area size. Typically, using circle- or square-like shapes.

    • other (boolean): it includes all other types of non-temporal visualisations that do not fall into the aforementioned categories.

    Temporal visualisations and encodings. In addition to non-temporal visualisations, a group of techniques to encode temporality is considered in order to enable comparisons with [7]. Columns:

    • timeline (boolean): the display of a list of data points or spans in chronological order. They include timelines working either with a scale or simply displaying events in sequence. As in [7], we also include structured solutions resembling Gantt chart layouts.

    • temporal_dimension (boolean): to report when time is mapped to any dimension of a visualisation, with the exclusion of timelines. We use the term “dimension” and not “axis” as in [7] as more appropriate for radial layouts or more complex representational choices.

    • animation (boolean): temporality is perceived through an animation changing the visualisation according to time flow.

    • visual_variable (boolean): another visual encoding strategy is used to represent any temporality-related variable (e.g., colour).

    Interactions. A set of categories to assess affordable interactions based on the concept of user intent [8] and user-allowed perceptualisation data actions [9]. The following categories roughly match the manipulative subset of methods of the “how” an interaction is performed in the conception of [10]. Only interactions that affect the aspect of the visualisation or the visual representation of its data points, symbols, and glyphs are taken into consideration. Columns:

    • basic_selection (boolean): the demarcation of an element either for the duration of the interaction or more permanently until the occurrence of another selection.

    • advanced_selection (boolean): the demarcation involves both the selected element and connected elements within the visualisation or leads to brush and link effects across views. Basic selection is tacitly implied.

    • navigation (boolean): interactions that allow moving, zooming, panning, rotating, and scrolling the view but only when applied to the visualisation and not to the web page. It also includes “drill” interactions (to navigate through different levels or portions of data detail, often generating a new view that replaces or accompanies the original) and “expand” interactions generating new perspectives on data by expanding and collapsing nodes.

    • arrangement (boolean): the organisation of visualisation elements (symbols, glyphs, etc.) or multi-visualisation layouts spatially through drag and drop or

  12. d

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

    • datasets.ai
    • data.usgs.gov
    • +2more
    55
    Updated May 31, 2023
    + more versions
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    Department of the Interior (2023). California State Waters Map Series--Offshore of Santa Cruz Web Services [Dataset]. https://datasets.ai/datasets/california-state-waters-map-series-offshore-of-santa-cruz-web-services
    Explore at:
    55Available download formats
    Dataset updated
    May 31, 2023
    Dataset authored and provided by
    Department of the Interior
    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.

  13. Data from: Mental Maps in Process Mining: Does Stabilizing DFGs Improve...

    • figshare.com
    mp4
    Updated May 26, 2025
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    Marie-Christin Häge; Jana-Rebecca Rehse (2025). Mental Maps in Process Mining: Does Stabilizing DFGs Improve Process Analysis Performance? [Dataset]. http://doi.org/10.6084/m9.figshare.28351877.v1
    Explore at:
    mp4Available download formats
    Dataset updated
    May 26, 2025
    Dataset provided by
    Figsharehttp://figshare.com/
    figshare
    Authors
    Marie-Christin Häge; Jana-Rebecca Rehse
    License

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

    Description

    This folder includes additional material to our paper "Mental Maps in Process Mining: Does Stabilizing DFGs Improve Process Analysis Performance?" by Häge and Rehse accepted at the BPM 2025. It includes screenshots and screencasts of the conducted online experiment and the used website to test if the mental map increased process analysis performance. It also includes example images of the two different representations, without and with mental map.In detail:1) Slide deck including the whole experiment design with all questions and the different representations: Screenshots_Online_Experiment_All_Questions.pdf2) Screencasts of both representations with changes of the slider settings and use of the zoom function:Screencast_Zoom_no_Mental_Map.mp4Screencast_Zoom_with_Mental_Map.mp43) Screencasts of both representations with only changes of the slider settings:Screencast_no_Mental_Map.mp4Screencast_with_Mental_Map.mp4

  14. CrowdMag Visualization Web Map

    • noaa.hub.arcgis.com
    Updated May 16, 2023
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    NOAA GeoPlatform (2023). CrowdMag Visualization Web Map [Dataset]. https://noaa.hub.arcgis.com/maps/f8e24dd400c94d4e8275417f2e8a2070
    Explore at:
    Dataset updated
    May 16, 2023
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA GeoPlatform
    Area covered
    Description

    This web map is a component of the CrowdMag Visualization App.NOAA's CrowdMag is a crowdsourced data collection project that uses a mobile app to collect geomagnetic data from the magnetometers that modern smartphones use as part of their navigation systems. NCEI collects these data from citizen scientists around the world and provides quality control services before making them available through a series of aggregated maps and charts. These data have the potential to provide a high resolution alternative to geomagnetic satellite data, as well as near real-time information about changes in the magnetic field.This map shows data collected from phones around the world! Displayed are the Crowdsourced magnetic data within a tolerance level of prediction by World Magnetic Model. We have added some uncertainty to each data point shown to ensure the privacy of our contributors. The data points are grouped together (or "aggregated") into small areas , and we display the median data value across all the readings for each point.

    This map is updated every day. Layers are available for Median Intensity, Median Horizontal Component (Y), and Median Vertical Component (Z).
    
    
    Use the time slider to select the date range. Select the different layers under the "Crowdmag Observations" menu. View a color scale using the legend tool. Zoom to your location using the "Find my Location" tool. Click or tap on a data point to view a popup containing more information.
    
  15. Data from: HazMatMapper: an online and interactive geographic visualization...

    • tandf.figshare.com
    • datasetcatalog.nlm.nih.gov
    tiff
    Updated Jun 1, 2023
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    Eric Nost; Heather Rosenfeld; Kristen Vincent; Sarah A. Moore; Robert E. Roth (2023). HazMatMapper: an online and interactive geographic visualization tool for exploring transnational flows of hazardous waste and environmental justice [Dataset]. http://doi.org/10.6084/m9.figshare.4629793
    Explore at:
    tiffAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Taylor & Francishttps://taylorandfrancis.com/
    Authors
    Eric Nost; Heather Rosenfeld; Kristen Vincent; Sarah A. Moore; Robert E. Roth
    License

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

    Description

    HazMatMapper is an online and interactive geographic visualization tool designed to facilitate exploration of transnational flows of hazardous waste in North America (http://geography.wisc.edu/hazardouswaste/map/). While conventional narratives suggest that wealthier countries such as Canada and the United States (US) export waste to poorer countries like Mexico, little is known about how waste trading may affect specific sites within any of the three countries. To move beyond anecdotal discussions and national aggregates, we assembled a novel geographic dataset describing transnational hazardous waste shipments from 2007 to 2012 through two Freedom of Information Act requests for documents held by the US Environmental Protection Agency. While not yet detailing all of the transnational hazardous waste trade in North America, HazMatMapper supports multiscale and site-specific visual exploration of US imports of hazardous waste from Canada and Mexico. It thus enables academic researchers, waste regulators, and the general public to generate hypotheses on regional clustering, transnational corporate structuring, and environmental justice concerns, as well as to understand the limitations of existing regulatory data collection itself. Here, we discuss the dataset and design process behind HazMatMapper and demonstrate its utility for understanding the transnational hazardous waste trade.

  16. National Weather Service Precipitation Forecast

    • data-napsg.opendata.arcgis.com
    • prep-response-portal.napsgfoundation.org
    • +13more
    Updated Aug 16, 2022
    + more versions
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    Esri (2022). National Weather Service Precipitation Forecast [Dataset]. https://data-napsg.opendata.arcgis.com/maps/f9e9283b9c9741d09aad633f68758bf6
    Explore at:
    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map displays the Quantitative Precipitation Forecast (QPF) for the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative precipitation data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the "Amount by Time" (incremental) layer or the "Accumulation by Time" (cumulative) layer to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces forecast data of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.qpf.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

  17. d

    California State Waters Map Series--Point Sur to Point Arguello Web Services...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Nov 21, 2025
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    U.S. Geological Survey (2025). California State Waters Map Series--Point Sur to Point Arguello Web Services [Dataset]. https://catalog.data.gov/dataset/california-state-waters-map-series-point-sur-to-point-arguello-web-services
    Explore at:
    Dataset updated
    Nov 21, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Point Arguello, 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 Point Sur to Point Arguello 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 Point Sur to Point Arguello map area data layers. Data layers are symbolized as shown on the associated map sheets.

  18. Mapping the COVID-19 global response: from grassroots to governments

    • data.niaid.nih.gov
    Updated Jul 22, 2024
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    Akligoh, Harry; Havemann, Jo; Restrepo, Martin; Obanda, Johanssen (2024). Mapping the COVID-19 global response: from grassroots to governments [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_3732376
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    Dataset updated
    Jul 22, 2024
    Dataset provided by
    Access 2 Perspectives
    Pint of Science & AfricArXiv, Kenya
    Open Bioeconomy Lab, Hive Biolab (Kumasi Hive), Ghana
    Hyper Island, Appiario Lab, Brazil
    Authors
    Akligoh, Harry; Havemann, Jo; Restrepo, Martin; Obanda, Johanssen
    Description

    Visual map at kumu.io/access2perspectives/covid19-resources

    Data set doi: 10.5281/zenodo.3732377 // available in different formats (pdf, xls, ods, csv,)

    Correspondence: (JH) info@access2perspectives.com

    Objectives

    Provide citizens with crucial and reliable information

    Encourage and facilitate South South collaboration

    Bridging language barriers

    Provide local governments and cities with lessons learned about COVID-19 crisis response

    Facilitate global cooperation and immediate response on all societal levels

    Enable LMICs to collaborate and innovate across distances and leverage locally available and context-relevant resources

    Methodology

    The data feeding the map at kumu.io was compiled from online resources and information shared in various community communication channels.

    Kumu.io is a visualization platform for mapping complex systems and to provide a deeper understanding of their intrinsic relationships. It provides blended systems thinking, stakeholder mapping, and social network analysis.

    Explore the map // https://kumu.io/access2perspectives/covid19-resources#global

    Click on individual nodes and view the information by country

    info hotlines

    governmental informational websites, Twitter feeds & Facebook pages

    fact checking online resources

    language indicator

    DIY resources

    clinical staff capacity building

    etc.

    With the navigation buttons to the right, you can zoom in and out, select and focus on specific elements.

    If you have comments, questions or suggestions for improvements on this map email us at info@access2perspectives.com

    Contribute

    Please add data to the spreadsheet at https://tinyurl.com/COVID19-global-response

    you can add additional information on country, city or neighbourhood level (see e.g. the Cape Town entry)

    Related documents

    Google Doc: tinyurl.com/COVID19-Africa-Response

  19. U

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

    • data.usgs.gov
    • search.dataone.org
    • +2more
    Updated Jan 1, 2015
    + more versions
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    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
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    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
    Ventura, 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, ...

  20. a

    TRIP Interactive Map

    • trip-thrive-geohub.hub.arcgis.com
    Updated Feb 2, 2024
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    ThriveRegionalPartnership (2024). TRIP Interactive Map [Dataset]. https://trip-thrive-geohub.hub.arcgis.com/datasets/e42e74a145a84ba7b7328bad2c576d22
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    Dataset updated
    Feb 2, 2024
    Dataset authored and provided by
    ThriveRegionalPartnership
    Description

    A web mapping application for regional freight data sharing, visualization, and analysis for the greater Chattanooga area. For information on data used in this application, please visit the Thrive Regional Infrastructure PortalThe interactive mapping application tools are listed below. Standard Tools: Zoom, Pan, Identify, Turn Layers On and Off, View Legend, Adjust TransparencyQueriesFiltersChartsInfo SummaryMeasureDrawPrintChange BasemapsDaily Traffic SummaryDirectionsShare MapAdd DataFor more information, please contact Shannon Millsaps smillsaps@thriveregion.org or TonyG@gatech.edu

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Market Research Forecast (2025). Interactive Map Creation Tools Report [Dataset]. https://www.marketresearchforecast.com/reports/interactive-map-creation-tools-35432

Interactive Map Creation Tools Report

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pdf, ppt, docAvailable download formats
Dataset updated
Mar 15, 2025
Dataset authored and provided by
Market Research Forecast
License

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

Time period covered
2025 - 2033
Area covered
Global
Variables measured
Market Size
Description

Discover the booming interactive map creation tools market! This in-depth analysis reveals a $2.5 billion market in 2025, projected to reach $8 billion by 2033, driven by cloud-based solutions and growing data visualization needs. Learn about key players, market segmentation, and regional trends shaping this exciting sector.

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