64 datasets found
  1. CrowdMag Visualization Web Map

    • noaa.hub.arcgis.com
    Updated May 15, 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 15, 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.
    
  2. R

    World Countries Boundaries

    • entrepot.recherche.data.gouv.fr
    Updated Apr 10, 2025
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    Kyllian James; Kyllian James (2025). World Countries Boundaries [Dataset]. http://doi.org/10.57745/ABJ8OQ
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    application/geo+json(32366068), html(400495994), html(1043808), pdf(82736), application/geo+json(32388771), application/geo+json(19764013)Available download formats
    Dataset updated
    Apr 10, 2025
    Dataset provided by
    Recherche Data Gouv
    Authors
    Kyllian James; Kyllian James
    License

    https://spdx.org/licenses/etalab-2.0.htmlhttps://spdx.org/licenses/etalab-2.0.html

    Area covered
    World
    Dataset funded by
    Agence nationale de la recherche
    Description

    1 Overview World Administrative Boundaries are available from various sources (UN, WHO, Global Administrative Areas [GADM], Natural Earth, World Bank). We would like to have the most accurate one with a reasonable size for an interactive world map in a Data Exploration Application, called CLIMINET. We provide a complete Geospatial Data that covers at least all 249 countries in the international ISO 3166-1 standard. We aim to maintain a reasonable data size, with countries' boundaries as accurate as possible, to ensure FLUIDITY in data visualization applications. The data are optimized for efficient performance and smooth interactions in interactive world maps for the best possible user experience. 2. Data Overview Number of Spatial Features: 275 countries/territories Data Sources: Compiled from multiple sources to ensure completeness and precision (WHO, Global Administrative Areas [GADM]) CRS Options: WGS84 [EPSG:4326] World Robinson (1963) [ESRI:54030] World Winkel-Tripel (Winkel III) - (1921) [ESRI:54042] Data Level: Level 0 (Countries) File Format: GeoJSON File Size: WGS84 [EPSG:4326]: 18.86 MB World Robinson (1963) [ESRI:54030]: 30.91 MB World Winkel-Tripel (Winkel III) - (1921) [ESRI:54042]: 30.90 MB 3. Data Revision Date The data were last updated on 2024-12-19. For further information on data structure and implementation, refer to the metadata files.

  3. World Countries (shapefile/raster): Natural Earth

    • kaggle.com
    Updated Nov 30, 2021
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    GeorgeAM (2021). World Countries (shapefile/raster): Natural Earth [Dataset]. https://www.kaggle.com/datasets/georgeam/world-countries-shapefile-natural-earth-data/versions/1
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 30, 2021
    Dataset provided by
    Kaggle
    Authors
    GeorgeAM
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    World
    Description

    Context

    When I started exploring how to create interactive maps (using the leaflet() package in R) I come across this free data set (shapefile format) that contains the geographical coordinates (polygons) for all the countries in the world. I thought it would be nice to share this with the Kaggle community.

    Content

    The .zip folder contains all the necessary files needed for the shapefile data to work properly on your computer. If you are new to using the shapefile format, please see the information provided below:

    https://en.wikipedia.org/wiki/Shapefile "The shapefile format stores the data as primitive geometric shapes like points, lines, and polygons. These shapes, together with data attributes that are linked to each shape, create the representation of the geographic data. The term "shapefile" is quite common, but the format consists of a collection of files with a common filename prefix, stored in the same directory. The three mandatory files have filename extensions .shp, .shx, and .dbf. The actual shapefile relates specifically to the .shp file, but alone is incomplete for distribution as the other supporting files are required. "

    Acknowledgements

    Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com.

  4. a

    GLOBE Tree Heights Web Map Service pts

    • globe-data-igestrategies.hub.arcgis.com
    • geospatial.strategies.org
    Updated Nov 6, 2020
    + more versions
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    Institute for Global Environmental Strategies (2020). GLOBE Tree Heights Web Map Service pts [Dataset]. https://globe-data-igestrategies.hub.arcgis.com/maps/a7e32e42fa874078b0580b9e27274659
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    Dataset updated
    Nov 6, 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.

  5. G

    Interactive data visualizations of COVID-19 around the world

    • ouvert.canada.ca
    • open.canada.ca
    csv, html
    Updated Sep 24, 2021
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    Public Health Agency of Canada (2021). Interactive data visualizations of COVID-19 around the world [Dataset]. https://ouvert.canada.ca/data/dataset/fc11aa70-821b-4c64-be19-020a2465b0de
    Explore at:
    html, csvAvailable download formats
    Dataset updated
    Sep 24, 2021
    Dataset provided by
    Public Health Agency of Canada
    License

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

    Area covered
    World
    Description

    Interactive data map of COVID-19 cases around the world. Shows number of total cases and deaths by country over time, starting from December 31, 2019 to present time.

  6. d

    HERE Map Data - street maps for 200 countries worldwide provided by MBI...

    • datarade.ai
    .xml, .csv
    Updated Sep 21, 2020
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    MBI Geodata (2020). HERE Map Data - street maps for 200 countries worldwide provided by MBI Geodata [Dataset]. https://datarade.ai/data-products/here-map-data
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    .xml, .csvAvailable download formats
    Dataset updated
    Sep 21, 2020
    Dataset authored and provided by
    MBI Geodata
    Area covered
    British Indian Ocean Territory, Serbia, Chile, Andorra, Heard Island and McDonald Islands, Paraguay, Isle of Man, Qatar, Guatemala, Tunisia
    Description

    MBI is one of the first distributors of HERE Technologies and provides detailed street maps from HERE for most of the countries or territories worldwide.

    HERE Maps are available as Essential or Advanced Map. Essential Map is a basic 2D canvas of the world that enables use cases such as basic map display, data visualization, search, localization tracking and tracing.

    Building on Essential Map, Advanced Map is the most complete and detailed map available. It includes detailed features for modeling road networks, such as navigable attributes, speed limits, sign text and the full set of Places (Point of Interest), and enables use cases such as point-to-point routing, turn-by-turn navigation, advanced navigation for cars and trucks, business intelligence, planning and optimization, and much more.

    The HERE Map product line can be further enriched with additional curated and specialized location content products that enable you to build differentiating location-enabled services and applications. Over 50 premium location content products seamlessly integrate with the HERE Map Data product line, such as Places, Point Addressing, Trucks, Road Infrastructure, and many more. Available in the following formats: GDF, RDF, NavStreets, FGDB,

  7. 10 powerful tools and maps with which to teach about population and...

    • library.ncge.org
    Updated Jul 27, 2021
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    NCGE (2021). 10 powerful tools and maps with which to teach about population and demographics [Dataset]. https://library.ncge.org/documents/bae1d5f1cba243ea88d09b043b8444ee
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    Dataset updated
    Jul 27, 2021
    Dataset provided by
    National Council for Geographic Educationhttp://www.ncge.org/
    Authors
    NCGE
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    Author: Joseph Kerski, post_secondary_educator, Esri and University of DenverGrade/Audience: high school, ap human geography, post secondary, professional developmentResource type: lessonSubject topic(s): population, maps, citiesRegion: africa, asia, australia oceania, europe, north america, south america, united states, worldStandards: All APHG population tenets. Geography for Life cultural and population geography standards. Objectives: 1. Understand how population change and demographic characteristics are evident at a variety of scales in a variety of places around the world. 2. Understand the whys of where through analysis of change over space and time. 3. Develop skills using spatial data and interactive maps. 4. Understand how population data is communicated using 2D and 3D maps, visualizations, and symbology. Summary: Teaching and learning about demographics and population change in an effective, engaging manner is enriched and enlivened through the use of web mapping tools and spatial data. These tools, enabled by the advent of cloud-based geographic information systems (GIS) technology, bring problem solving, critical thinking, and spatial analysis to every classroom instructor and student (Kerski 2003; Jo, Hong, and Verma 2016).

  8. Z

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

    • data.niaid.nih.gov
    Updated Jul 22, 2024
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    Havemann, Jo (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
    Akligoh, Harry
    Obanda, Johanssen
    Havemann, Jo
    Restrepo, Martin
    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

  9. World Traffic Web Map

    • walmart-event-collaboration-portal-walmarttech.hub.arcgis.com
    Updated Jun 18, 2021
    + more versions
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    Walmart Emergency Management (2021). World Traffic Web Map [Dataset]. https://walmart-event-collaboration-portal-walmarttech.hub.arcgis.com/maps/world-traffic-web-map
    Explore at:
    Dataset updated
    Jun 18, 2021
    Dataset provided by
    Walmarthttp://walmart.com/
    Authors
    Walmart Emergency Management
    Area covered
    Description

    This is a dynamic traffic map service with capabilities for visualizing traffic speeds relative to free-flow speeds as well as traffic incidents which can be visualized and identified. The traffic data is updated every five minutes. Traffic speeds are displayed as a percentage of free-flow speeds, which is frequently the speed limit or how fast cars tend to travel when unencumbered by other vehicles. The streets are color coded as follows:Green (fast): 85 - 100% of free flow speedsYellow (moderate): 65 - 85%Orange (slow); 45 - 65%Red (stop and go): 0 - 45%Esri's historical, live, and predictive traffic feeds come directly from HERE (www.HERE.com). HERE collects billions of GPS and cell phone probe records per month and, where available, uses sensor and toll-tag data to augment the probe data collected. An advanced algorithm compiles the data and computes accurate speeds. Historical traffic is based on the average of observed speeds over the past three years. The live and predictive traffic data is updated every five minutes through traffic feeds. The color coded traffic map layer can be used to represent relative traffic speeds; this is a common type of a map for online services and is used to provide context for routing, navigation and field operations. The traffic map layer contains two sublayers: Traffic and Live Traffic. The Traffic sublayer (shown by default) leverages historical, live and predictive traffic data; while the Live Traffic sublayer is calculated from just the live and predictive traffic data only. A color coded traffic map image can be requested for the current time and any time in the future. A map image for a future request might be used for planning purposes. The map layer also includes dynamic traffic incidents showing the location of accidents, construction, closures and other issues that could potentially impact the flow of traffic. Traffic incidents are commonly used to provide context for routing, navigation and field operations. Incidents are not features; they cannot be exported and stored for later use or additional analysis. The service works globally and can be used to visualize traffic speeds and incidents in many countries. Check the service coverage web map to determine availability in your area of interest. In the coverage map, the countries color coded in dark green support visualizing live traffic. The support for traffic incidents can be determined by identifying a country. For detailed information on this service, including a data coverage map, visit the directions and routing documentation and ArcGIS Help.

  10. Web Mapping Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Web Mapping Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/web-mapping-market
    Explore at:
    pdf, csv, pptxAvailable download formats
    Dataset updated
    Jan 7, 2025
    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

    Web Mapping Market Outlook



    The global web mapping market size was valued at approximately USD 3.5 billion in 2023 and is projected to reach USD 8.2 billion by 2032, growing at a compound annual growth rate (CAGR) of 9.8% during the forecast period. The robust growth of this market can be attributed to the increasing demand for geographic information system (GIS) technologies and the expanding applications of web mapping across various industries.



    One of the primary growth factors driving the web mapping market is the proliferation of location-based services. With the rise of smartphones and IoT devices, the demand for real-time location data has skyrocketed, fueling the need for advanced web mapping solutions. Businesses are leveraging location-based services to enhance customer engagement, optimize logistics, and improve decision-making processes. Moreover, the integration of web mapping with emerging technologies such as AI and machine learning is further bolstering market growth, allowing for more sophisticated and predictive mapping capabilities.



    Another critical factor contributing to the market's expansion is the growing adoption of web mapping solutions in government and public sector initiatives. Governments across the globe are increasingly utilizing web mapping technologies for urban planning, disaster management, and community services. These technologies provide invaluable insights and real-time data that aid in making informed decisions and improving public services. The push for smart city developments and the need for efficient infrastructure management are also significant drivers for the adoption of web mapping solutions in the public sector.



    Furthermore, the transportation and logistics industry is witnessing a substantial uptake of web mapping technologies. With the rise of e-commerce and the need for efficient supply chain management, companies are relying on web mapping to optimize routes, monitor shipments, and ensure timely deliveries. The integration of GPS technology and real-time tracking systems with web mapping solutions is enhancing operational efficiencies and reducing costs. This trend is likely to continue as the demand for seamless logistics and transportation services grows.



    The concept of an Electronic Map has become increasingly significant in the web mapping market. Electronic maps are digital representations of geographic areas and are pivotal in providing real-time data and location-based insights. They are extensively used in various applications, from navigation systems to urban planning and environmental monitoring. The integration of electronic maps with web mapping technologies allows for enhanced visualization and analysis of spatial data, offering users detailed and interactive geographic information. As the demand for digital mapping solutions continues to grow, electronic maps are playing a crucial role in transforming how geographic information is accessed and utilized across different sectors.



    On the regional front, North America remains a dominant player in the web mapping market, primarily due to the early adoption of advanced technologies and the presence of major market players in the region. The Asia Pacific region is expected to exhibit the highest growth rate during the forecast period, driven by rapid urbanization, technological advancements, and increasing investments in smart city projects. Europe and Latin America are also anticipated to witness significant growth, supported by favorable government initiatives and the expanding use of web mapping across various industries.



    Component Analysis



    The web mapping market can be segmented by component into software and services. The software segment encompasses a wide range of GIS and mapping software that enable users to create, visualize, and analyze geographic data. This segment is witnessing significant growth due to the increasing need for sophisticated mapping tools that offer real-time data and advanced analytical capabilities. Companies are continuously enhancing their software offerings with features like AI integration, cloud compatibility, and user-friendly interfaces, driving the adoption of web mapping software across various industries.



    On the other hand, the services segment includes a variety of professional services such as consulting, implementation, and maintenance. As organizations seek to leverage web mapping technologies, they often require expert guidance and support to ensu

  11. g

    Global Midwifery Regulation Map - 2021 SoWMy Data

    • globalmidwiveshub.org
    Updated Aug 7, 2023
    + more versions
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    Direct Relief (2023). Global Midwifery Regulation Map - 2021 SoWMy Data [Dataset]. https://www.globalmidwiveshub.org/datasets/global-midwifery-regulation-map-2021-sowmy-data
    Explore at:
    Dataset updated
    Aug 7, 2023
    Dataset authored and provided by
    Direct Relief
    Description

    Data focused on the regulation of midwives globally was collected for the 2021 State of the World's Midwifery Report by the International Confederation of Midwives, with support by Direct Relief, and can be accessed and downloaded in the Open Data Portal of the Global Midwives' Hub. This map supports the Regulation of Midwives Story map: https://directrelief.maps.arcgis.com/home/item.html?id=31e0b498ecc145e2b320481119a82d6eData collected on the state of midwifery regulation throughout the world for the 2021 State of the World's Midwifery Report. The data was collected via a survey that was sent to midwives' associations, who filled it out for their country and shared it with their Ministry of Health for validation. Data was collected by the International Confederation of Midwives with the support of UNFPA, WHO, and Direct Relief. This data visualization is just one of the many data products 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.

  12. Power BI Global Superstore Data 2

    • kaggle.com
    Updated May 6, 2024
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    Sanjana Murthy (2024). Power BI Global Superstore Data 2 [Dataset]. https://www.kaggle.com/datasets/sanjanamurthy392/power-bi-global-superstore-data-2
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 6, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Sanjana Murthy
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    This data contains Scroller, Matrix, Map, Back button, Text box, table

  13. Interactive Map Creation Tools Market Report | Global Forecast From 2025 To...

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Interactive Map Creation Tools Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-interactive-map-creation-tools-market
    Explore at:
    pdf, pptx, csvAvailable download formats
    Dataset updated
    Jan 7, 2025
    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

    Interactive Map Creation Tools Market Outlook




    The global market size for Interactive Map Creation Tools was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 3.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 13.5% during the forecast period. The primary growth factors for this market include the increasing need for advanced geospatial data visualization, the rise of smart city initiatives, and the growing demand for real-time location-based services.




    One of the key growth drivers is the increasing demand for geospatial analytics across various sectors such as urban planning, transportation, and environmental monitoring. As urbanization accelerates, city planners and government authorities are turning to interactive mapping tools to visualize complex data sets that help in making informed decisions. These tools assist in laying out city infrastructures, optimizing traffic routes, and planning emergency response strategies. The trend towards smart cities further amplifies the need for such sophisticated tools, which can handle dynamic and interactive data layers in real-time.




    The transportation sector also finds significant utility in interactive map creation tools. With the surge in smart transportation projects globally, there is a mounting need to integrate real-time data into interactive maps for efficient route planning, traffic management, and logistics operations. Such tools not only aid in reducing congestion and travel times but also contribute to making transportation systems more sustainable. Additionally, interactive maps are becoming vital for managing fleets in logistics, enhancing the efficiency of delivery networks and reducing operational costs.




    Environmental monitoring is another critical application area driving market growth. With increasing concerns about climate change and natural disasters, there is a heightened need for tools that can provide real-time environmental data. Interactive maps enable organizations to monitor various environmental parameters such as air quality, water levels, and wildlife movements effectively. These tools are instrumental in disaster management, helping authorities to visualize affected areas and coordinate relief operations efficiently.




    Regionally, North America has been the dominant market for interactive map creation tools, driven by the high adoption of advanced technologies and significant investments in smart city projects. Europe follows closely, with countries like Germany and the UK leading the charge in urban planning and environmental monitoring initiatives. The Asia Pacific region is expected to witness the fastest growth, fueled by rapid urbanization and increasing investments in infrastructure development. Emerging economies in Latin America and the Middle East & Africa are also exploring these tools to address urbanization challenges and improve municipal services.



    In addition to the regional growth dynamics, the emergence of Custom Digital Map Service is revolutionizing the way organizations approach geospatial data. These services offer tailor-made mapping solutions that cater to the unique needs of businesses and government agencies. By providing highly customizable maps, these services enable users to integrate specific data layers, adjust visual styles, and incorporate branding elements, thereby enhancing the utility and appeal of the maps. As the demand for personalized mapping solutions grows, Custom Digital Map Service is becoming a vital component in sectors such as urban planning, logistics, and tourism, where tailored insights can drive strategic decisions and improve operational efficiency.



    Component Analysis




    In the Interactive Map Creation Tools market, the component segment is divided into Software and Services. The Software segment comprises products such as GIS software, mapping platforms, and data visualization tools. This segment holds a significant share of the market, fueled by the rising need for sophisticated software solutions that can handle vast amounts of geospatial data. Advanced mapping software offers features like real-time data integration, multi-layer visualization, and high customization capabilities, making it an indispensable tool for various industries.




    The increasing complexity

  14. Terrain - Aspect Map

    • data.catchmentbasedapproach.org
    • cacgeoportal.com
    • +5more
    Updated Dec 30, 2013
    + more versions
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    Esri (2013). Terrain - Aspect Map [Dataset]. https://data.catchmentbasedapproach.org/datasets/63fe6ad86c3d4536a3c44a0fbad0045e
    Explore at:
    Dataset updated
    Dec 30, 2013
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map provides a colorized representation of aspect, generated dynamically using the server-side aspect function on the Terrain layer. The orientation of the downward sloping terrain (0° – 360°) is indicated by different colors, rotating from green (North) to blue (East), to magenta (South) to orange (West). Flat areas having no down slope direction are given a value of 361° and rendered as gray. This service can be used for visualization or analysis. Note: If you require access to numeric (float) aspect values, use the Terrain - Aspect layer, which returns orientation values from 0 to 360 degrees. Units: DegreesUpdate Frequency: QuarterlyCoverage: World/GlobalData Sources: This layer is compiled from a variety of best available sources from several data providers. To see the coverage and extents of various datasets comprising this service in an interactive map, see World Elevation Coverage Map.What can you do with this layer?Use for Visualization: Yes. This colorized aspect map is appropriate for visualizing the downslope direction of the terrain. This layer can be added to applications or maps to enhance contextual understanding.Use for Analysis: Yes. 8 bit color values returned by this service represent integer aspect values. For float values, use the Terrain - Aspect layer.For more details such as Data Sources, Mosaic method used in this layer, please see the Terrain layer. This layer allows query, identify, and export image requests. The layer is restricted to a 5,000 x 5,000 pixel limit in a single export image request.

    This layer is part of a larger collection of elevation layers that you can use to perform a variety of mapping analysis tasks.

  15. a

    Catholic Carbon Footprint Story Map Map

    • hub.arcgis.com
    • catholic-geo-hub-cgisc.hub.arcgis.com
    Updated Oct 7, 2019
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    burhansm2 (2019). Catholic Carbon Footprint Story Map Map [Dataset]. https://hub.arcgis.com/maps/8c3112552bdd4bd3962ab8b94bcf6ee5
    Explore at:
    Dataset updated
    Oct 7, 2019
    Dataset authored and provided by
    burhansm2
    License

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

    Area covered
    Description

    Catholic Carbon Footprint Story Map Map:DataBurhans, Molly A., Cheney, David M., Gerlt, R.. . “PerCapita_CO2_Footprint_InDioceses_FULL”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.Map Development: Molly BurhansMethodologyThis is the first global Carbon footprint of the Catholic population. We will continue to improve and develop these data with our research partners over the coming years. While it is helpful, it should also be viewed and used as a "beta" prototype that we and our research partners will build from and improve. The years of carbon data are (2010) and (2015 - SHOWN). The year of Catholic data is 2018. The year of population data is 2016. Care should be taken during future developments to harmonize the years used for catholic, population, and CO2 data.1. Zonal Statistics: Esri Population Data and Dioceses --> Population per dioceses, non Vatican based numbers2. Zonal Statistics: FFDAS and Dioceses and Population dataset --> Mean CO2 per Diocese3. Field Calculation: Population per Diocese and Mean CO2 per diocese --> CO2 per Capita4. Field Calculation: CO2 per Capita * Catholic Population --> Catholic Carbon FootprintAssumption: PerCapita CO2Deriving per-capita CO2 from mean CO2 in a geography assumes that people's footprint accounts for their personal lifestyle and involvement in local business and industries that are contribute CO2. Catholic CO2Assumes that Catholics and non-Catholic have similar CO2 footprints from their lifestyles.Derived from:A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of resultshttp://ffdas.rc.nau.edu/About.htmlRayner et al., JGR, 2010 - The is the first FFDAS paper describing the version 1.0 methods and results published in the Journal of Geophysical Research.Asefi et al., 2014 - This is the paper describing the methods and results of the FFDAS version 2.0 published in the Journal of Geophysical Research.Readme version 2.2 - A simple readme file to assist in using the 10 km x 10 km, hourly gridded Vulcan version 2.2 results.Liu et al., 2017 - A paper exploring the carbon cycle response to the 2015-2016 El Nino through the use of carbon cycle data assimilation with FFDAS as the boundary condition for FFCO2."S. Asefi‐Najafabady P. J. Rayner K. R. Gurney A. McRobert Y. Song K. Coltin J. Huang C. Elvidge K. BaughFirst published: 10 September 2014 https://doi.org/10.1002/2013JD021296 Cited by: 30Link to FFDAS data retrieval and visualization: http://hpcg.purdue.edu/FFDAS/index.phpAbstractHigh‐resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high‐resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long‐term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long‐term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter‐term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set."Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/Esri Gridded Population Data 2016DescriptionThis layer is a global estimate of human population for 2016. Esri created this estimate by modeling a footprint of where people live as a dasymetric settlement likelihood surface, and then assigned 2016 population estimates stored on polygons of the finest level of geography available onto the settlement surface. Where people live means where their homes are, as in where people sleep most of the time, and this is opposed to where they work. Another way to think of this estimate is a night-time estimate, as opposed to a day-time estimate.Knowledge of population distribution helps us understand how humans affect the natural world and how natural events such as storms and earthquakes, and other phenomena affect humans. This layer represents the footprint of where people live, and how many people live there.Dataset SummaryEach cell in this layer has an integer value with the estimated number of people likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Population Density Estimate 2016: this layer is represented as population density in units of persons per square kilometer.World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.Frye, C. et al., (2018). Using Classified and Unclassified Land Cover Data to Estimate the Footprint of Human Settlement. Data Science Journal. 17, p.20. DOI: http://doi.org/10.5334/dsj-2018-020.What can you do with this layer?This layer is unsuitable for mapping or cartographic use, and thus it does not include a convenient legend. Instead, this layer is useful for analysis, particularly for estimating counts of people living within watersheds, coastal areas, and other areas that do not have standard boundaries. Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the count of population within those zones. https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/data-management/2016-world-population-estimate-services-are-now-available/

  16. Digital Map Market Analysis, Size, and Forecast 2025-2029: North America (US...

    • technavio.com
    Updated Jun 18, 2025
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    Technavio (2025). Digital Map Market Analysis, Size, and Forecast 2025-2029: North America (US and Canada), Europe (France, Germany, and UK), APAC (China, India, Indonesia, Japan, and South Korea), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/digital-map-market-industry-analysis
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    Dataset updated
    Jun 18, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    United States, Global
    Description

    Snapshot img

    Digital Map Market Size 2025-2029

    The digital map market size is forecast to increase by USD 31.95 billion at a CAGR of 31.3% between 2024 and 2029.

    The market is driven by the increasing adoption of intelligent Personal Digital Assistants (PDAs) and the availability of location-based services. PDAs, such as smartphones and smartwatches, are becoming increasingly integrated with digital map technologies, enabling users to navigate and access real-time information on-the-go. The integration of Internet of Things (IoT) enables remote monitoring of cars and theft recovery. Location-based services, including mapping and navigation apps, are a crucial component of this trend, offering users personalized and convenient solutions for travel and exploration. However, the market also faces significant challenges.
    Ensuring the protection of sensitive user information is essential for companies operating in this market, as trust and data security are key factors in driving user adoption and retention. Additionally, the competition in the market is intense, with numerous players vying for market share. Companies must differentiate themselves through innovative features, user experience, and strong branding to stand out in this competitive landscape. Security and privacy concerns continue to be a major obstacle, as the collection and use of location data raises valid concerns among consumers.
    

    What will be the Size of the Digital Map Market during the forecast period?

    Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
    Request Free Sample

    In the market, cartographic generalization and thematic mapping techniques are utilized to convey complex spatial information, transforming raw data into insightful visualizations. Choropleth maps and dot density maps illustrate distribution patterns of environmental data, economic data, and demographic data, while spatial interpolation and predictive modeling enable the estimation of hydrographic data and terrain data in areas with limited information. Urban planning and land use planning benefit from these tools, facilitating network modeling and location intelligence for public safety and emergency management.

    Spatial regression and spatial autocorrelation analyses provide valuable insights into urban development trends and patterns. Network analysis and shortest path algorithms optimize transportation planning and logistics management, enhancing marketing analytics and sales territory optimization. Decision support systems and fleet management incorporate 3D building models and real-time data from street view imagery, enabling effective resource management and disaster response. The market in the US is experiencing robust growth, driven by the integration of Geographic Information Systems (GIS), Global Positioning Systems (GPS), and advanced computer technology into various industries.

    How is this Digital Map Industry segmented?

    The digital map industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

    Application
    
      Navigation
      Geocoders
      Others
    
    
    Type
    
      Outdoor
      Indoor
    
    
    Solution
    
      Software
      Services
    
    
    Deployment
    
      On-premises
      Cloud
    
    
    Geography
    
      North America
    
        US
        Canada
    
    
      Europe
    
        France
        Germany
        UK
    
    
      APAC
    
        China
        India
        Indonesia
        Japan
        South Korea
    
    
      Rest of World (ROW)
    

    By Application Insights

    The navigation segment is estimated to witness significant growth during the forecast period. Digital maps play a pivotal role in various industries, particularly in automotive applications for driver assistance systems. These maps encompass raster data, aerial photography, government data, and commercial data, among others. Open-source data and proprietary data are integrated to ensure map accuracy and up-to-date information. Map production involves the use of GPS technology, map projections, and GIS software, while map maintenance and quality control ensure map accuracy. Location-based services (LBS) and route optimization are integral parts of digital maps, enabling real-time navigation and traffic data.

    Data validation and map tiles ensure data security. Cloud computing facilitates map distribution and map customization, allowing users to access maps on various devices, including mobile mapping and indoor mapping. Map design, map printing, and reverse geocoding further enhance the user experience. Spatial analysis and data modeling are essential for data warehousing and real-time navigation. The automotive industry's increasing adoption of connected cars and long-term evolution (LTE) technologies have fueled the demand for digital maps. These maps enable driver assistance app

  17. High Accuracy Map Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 23, 2024
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    Dataintelo (2024). High Accuracy Map Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-high-accuracy-map-market
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    csv, pdf, pptxAvailable download formats
    Dataset updated
    Sep 23, 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

    High Accuracy Map Market Outlook




    The global high accuracy map market size was valued at approximately USD 2.4 billion in 2023 and is projected to reach around USD 12.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 20.5% from 2024 to 2032. This impressive growth is primarily driven by advancements in autonomous vehicle technology and increasing demand for precise geospatial data across various sectors. The rapid urbanization and increased investment in smart city projects worldwide are also significant factors contributing to market growth.




    One of the primary growth factors fueling the high accuracy map market is the burgeoning development of autonomous vehicles. As the automotive industry continues to innovate, the need for high precision maps that provide detailed and real-time data on road conditions, traffic, and obstacles becomes more crucial. High accuracy maps enable autonomous vehicles to navigate safely and efficiently, reducing the likelihood of accidents and improving overall transportation systems. This demand is anticipated to surge further as governments and corporations strive to deploy autonomous vehicle fleets for both personal and commercial use.




    Another significant driver of market growth is the increasing implementation of high accuracy maps in infrastructure development and urban planning. As cities expand and develop, the need for accurate and detailed geographic information systems (GIS) becomes essential for efficient planning and management. High accuracy maps provide critical data for designing and maintaining roads, bridges, utilities, and other infrastructure projects. The integration of high precision mapping technology in smart city initiatives further accelerates the adoption of these systems, enabling better resource management and enhanced quality of life for urban populations.




    The agricultural sector is also contributing to the expanding high accuracy map market. Precision agriculture relies heavily on accurate geospatial data to optimize farming practices, enhance crop yields, and ensure sustainable resource use. High accuracy maps enable farmers to monitor field conditions, assess soil health, and implement targeted interventions, leading to increased productivity and reduced environmental impact. As the global demand for food continues to rise, the adoption of advanced mapping technologies in agriculture is expected to grow, driving further market expansion.




    Regionally, North America holds a significant share of the high accuracy map market, driven by technological advancements and substantial investments in autonomous vehicle research and development. The presence of leading technology companies and a robust infrastructure network further facilitate market growth in this region. However, Asia Pacific is anticipated to witness the highest growth rate during the forecast period, fueled by rapid urbanization, increasing smart city projects, and rising adoption of advanced mapping technologies across various industries. Europe also remains a key player in the market, supported by strong governmental initiatives and a focus on sustainable development.



    Component Analysis




    The high accuracy map market can be segmented by component into software, hardware, and services. The software segment, encompassing map creation, data processing, and visualization tools, plays a critical role in the market. The demand for sophisticated mapping software is driven by the need for real-time data processing and the integration of multiple data sources to create comprehensive and precise maps. Companies are continually developing advanced software solutions that leverage artificial intelligence and machine learning to enhance the accuracy and functionality of high precision maps.




    The hardware segment includes various devices and sensors used in capturing geospatial data, such as GPS units, LiDAR sensors, and high-resolution cameras. As the demand for high accuracy maps grows, the need for advanced hardware capable of capturing detailed and precise data also increases. Innovations in sensor technology and the development of more compact and cost-effective devices are contributing to the growth of this segment. The hardware segment is crucial for the initial data collection phase, which lays the foundation for accurate map creation.




    Services encompass a wide range of offerings, including consulting, system integrati

  18. g

    Global Midwives in Leadership Map - 2021 SoWMy Data

    • globalmidwiveshub.org
    Updated Aug 8, 2023
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    Direct Relief (2023). Global Midwives in Leadership Map - 2021 SoWMy Data [Dataset]. https://www.globalmidwiveshub.org/datasets/global-midwives-in-leadership-map-2021-sowmy-data
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    Dataset updated
    Aug 8, 2023
    Dataset authored and provided by
    Direct Relief
    Description

    Instant app visualizing midwives in leadership data. Data focused on the midwives in leadership globally was collected for the 2021 State of the World's Midwifery Report by the International Confederation of Midwives, with support by Direct Relief, and can be accessed and downloaded in the Open Data Portal of the Global Midwives' Hub. Data collected on the state of midwifery leadership throughout the world for the 2021 State of the World's Midwifery Report. The data was collected via a survey that was sent to midwives' associations, who filled it out for their country and shared it with their Ministry of Health for validation. Data was collected by the International Confederation of Midwives with the support of UNFPA, WHO, and Direct Relief. This data visualization is just one of the many data products 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.

  19. Large Scale International Boundaries

    • catalog.data.gov
    • geodata.state.gov
    Updated Jun 13, 2025
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    U.S. Department of State (Point of Contact) (2025). Large Scale International Boundaries [Dataset]. https://catalog.data.gov/dataset/large-scale-international-boundaries
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    Dataset updated
    Jun 13, 2025
    Dataset provided by
    United States Department of Statehttp://state.gov/
    Description

    Overview The Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. The current edition is version 11.4 (published 24 February 2025). The 11.4 release contains updated boundary lines and data refinements designed to extend the functionality of the dataset. These data and generalized derivatives are the only international boundary lines approved for U.S. Government use. The contents of this dataset reflect U.S. Government policy on international boundary alignment, political recognition, and dispute status. They do not necessarily reflect de facto limits of control. National Geospatial Data Asset This dataset is a National Geospatial Data Asset (NGDAID 194) managed by the Department of State. It is a part of the International Boundaries Theme created by the Federal Geographic Data Committee. Dataset Source Details Sources for these data include treaties, relevant maps, and data from boundary commissions, as well as national mapping agencies. Where available and applicable, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery process includes analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground. Cartographic Visualization The LSIB is a geospatial dataset that, when used for cartographic purposes, requires additional styling. The LSIB download package contains example style files for commonly used software applications. The attribute table also contains embedded information to guide the cartographic representation. Additional discussion of these considerations can be found in the Use of Core Attributes in Cartographic Visualization section below. Additional cartographic information pertaining to the depiction and description of international boundaries or areas of special sovereignty can be found in Guidance Bulletins published by the Office of the Geographer and Global Issues: https://data.geodata.state.gov/guidance/index.html Contact Direct inquiries to internationalboundaries@state.gov. Direct download: https://data.geodata.state.gov/LSIB.zip Attribute Structure The dataset uses the following attributes divided into two categories: ATTRIBUTE NAME | ATTRIBUTE STATUS CC1 | Core CC1_GENC3 | Extension CC1_WPID | Extension COUNTRY1 | Core CC2 | Core CC2_GENC3 | Extension CC2_WPID | Extension COUNTRY2 | Core RANK | Core LABEL | Core STATUS | Core NOTES | Core LSIB_ID | Extension ANTECIDS | Extension PREVIDS | Extension PARENTID | Extension PARENTSEG | Extension These attributes have external data sources that update separately from the LSIB: ATTRIBUTE NAME | ATTRIBUTE STATUS CC1 | GENC CC1_GENC3 | GENC CC1_WPID | World Polygons COUNTRY1 | DoS Lists CC2 | GENC CC2_GENC3 | GENC CC2_WPID | World Polygons COUNTRY2 | DoS Lists LSIB_ID | BASE ANTECIDS | BASE PREVIDS | BASE PARENTID | BASE PARENTSEG | BASE The core attributes listed above describe the boundary lines contained within the LSIB dataset. Removal of core attributes from the dataset will change the meaning of the lines. An attribute status of “Extension” represents a field containing data interoperability information. Other attributes not listed above include “FID”, “Shape_length” and “Shape.” These are components of the shapefile format and do not form an intrinsic part of the LSIB. Core Attributes The eight core attributes listed above contain unique information which, when combined with the line geometry, comprise the LSIB dataset. These Core Attributes are further divided into Country Code and Name Fields and Descriptive Fields. County Code and Country Name Fields “CC1” and “CC2” fields are machine readable fields that contain political entity codes. These are two-character codes derived from the Geopolitical Entities, Names, and Codes Standard (GENC), Edition 3 Update 18. “CC1_GENC3” and “CC2_GENC3” fields contain the corresponding three-character GENC codes and are extension attributes discussed below. The codes “Q2” or “QX2” denote a line in the LSIB representing a boundary associated with areas not contained within the GENC standard. The “COUNTRY1” and “COUNTRY2” fields contain the names of corresponding political entities. These fields contain names approved by the U.S. Board on Geographic Names (BGN) as incorporated in the ‘"Independent States in the World" and "Dependencies and Areas of Special Sovereignty" lists maintained by the Department of State. To ensure maximum compatibility, names are presented without diacritics and certain names are rendered using common cartographic abbreviations. Names for lines associated with the code "Q2" are descriptive and not necessarily BGN-approved. Names rendered in all CAPITAL LETTERS denote independent states. Names rendered in normal text represent dependencies, areas of special sovereignty, or are otherwise presented for the convenience of the user. Descriptive Fields The following text fields are a part of the core attributes of the LSIB dataset and do not update from external sources. They provide additional information about each of the lines and are as follows: ATTRIBUTE NAME | CONTAINS NULLS RANK | No STATUS | No LABEL | Yes NOTES | Yes Neither the "RANK" nor "STATUS" fields contain null values; the "LABEL" and "NOTES" fields do. The "RANK" field is a numeric expression of the "STATUS" field. Combined with the line geometry, these fields encode the views of the United States Government on the political status of the boundary line. ATTRIBUTE NAME | | VALUE | RANK | 1 | 2 | 3 STATUS | International Boundary | Other Line of International Separation | Special Line A value of “1” in the “RANK” field corresponds to an "International Boundary" value in the “STATUS” field. Values of ”2” and “3” correspond to “Other Line of International Separation” and “Special Line,” respectively. The “LABEL” field contains required text to describe the line segment on all finished cartographic products, including but not limited to print and interactive maps. The “NOTES” field contains an explanation of special circumstances modifying the lines. This information can pertain to the origins of the boundary lines, limitations regarding the purpose of the lines, or the original source of the line. Use of Core Attributes in Cartographic Visualization Several of the Core Attributes provide information required for the proper cartographic representation of the LSIB dataset. The cartographic usage of the LSIB requires a visual differentiation between the three categories of boundary lines. Specifically, this differentiation must be between: International Boundaries (Rank 1); Other Lines of International Separation (Rank 2); and Special Lines (Rank 3). Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary. Please consult the style files in the download package for examples of this depiction. The requirement to incorporate the contents of the "LABEL" field on cartographic products is scale dependent. If a label is legible at the scale of a given static product, a proper use of this dataset would encourage the application of that label. Using the contents of the "COUNTRY1" and "COUNTRY2" fields in the generation of a line segment label is not required. The "STATUS" field contains the preferred description for the three LSIB line types when they are incorporated into a map legend but is otherwise not to be used for labeling. Use of the “CC1,” “CC1_GENC3,” “CC2,” “CC2_GENC3,” “RANK,” or “NOTES” fields for cartographic labeling purposes is prohibited. Extension Attributes Certain elements of the attributes within the LSIB dataset extend data functionality to make the data more interoperable or to provide clearer linkages to other datasets. The fields “CC1_GENC3” and “CC2_GENC” contain the corresponding three-character GENC code to the “CC1” and “CC2” attributes. The code “QX2” is the three-character counterpart of the code “Q2,” which denotes a line in the LSIB representing a boundary associated with a geographic area not contained within the GENC standard. To allow for linkage between individual lines in the LSIB and World Polygons dataset, the “CC1_WPID” and “CC2_WPID” fields contain a Universally Unique Identifier (UUID), version 4, which provides a stable description of each geographic entity in a boundary pair relationship. Each UUID corresponds to a geographic entity listed in the World Polygons dataset. These fields allow for linkage between individual lines in the LSIB and the overall World Polygons dataset. Five additional fields in the LSIB expand on the UUID concept and either describe features that have changed across space and time or indicate relationships between previous versions of the feature. The “LSIB_ID” attribute is a UUID value that defines a specific instance of a feature. Any change to the feature in a lineset requires a new “LSIB_ID.” The “ANTECIDS,” or antecedent ID, is a UUID that references line geometries from which a given line is descended in time. It is used when there is a feature that is entirely new, not when there is a new version of a previous feature. This is generally used to reference countries that have dissolved. The “PREVIDS,” or Previous ID, is a UUID field that contains old versions of a line. This is an additive field, that houses all Previous IDs. A new version of a feature is defined by any change to the

  20. 3

    3D Mapping Modelling Market Report

    • promarketreports.com
    doc, pdf, ppt
    Updated Feb 1, 2025
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    Pro Market Reports (2025). 3D Mapping Modelling Market Report [Dataset]. https://www.promarketreports.com/reports/3d-mapping-modelling-market-10299
    Explore at:
    doc, pdf, pptAvailable download formats
    Dataset updated
    Feb 1, 2025
    Dataset authored and provided by
    Pro Market Reports
    License

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

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

    The global 3D mapping and modeling market is expected to grow significantly in the next few years as demand increases for detailed and accurate representations of physical environments in three-dimensional space. Estimated to be valued at USD 38.62 billion in the year 2025, the market was expected to grow at a CAGR of 14.5% from 2025 to 2033 and was estimated to reach an amount of USD 90.26 billion by the end of 2033. The high growth rate is because of improvement in advanced technologies with the development of high-resolution sensors and methods of photogrammetry that make possible higher-resolution realistic and immersive 3D models.Key trends in the market are the adoption of virtual and augmented reality (VR/AR) applications, 3D mapping with smart city infrastructure, and increased architecture, engineering, and construction utilization of 3D models. Other factors are driving the growing adoption of cloud-based 3D mapping and modeling solutions. The solutions promise scalability, cost-effectiveness, and easy access to 3D data, thus appealing to business and organizations of all sizes. Recent developments include: Jun 2023: Nomoko (Switzerland), a leading provider of real-world 3D data technology, announced that it has joined the Overture Maps Foundation, a non-profit organization committed to fostering collaboration and innovation in the geospatial domain. Nomoko will collaborate with Meta, Amazon Web Services (AWS), TomTom, and Microsoft, to create interoperable, accessible 3D datasets, leveraging its real-world 3D modeling capabilities., May 2023: The Sanborn Map Company (Sanborn), an authority in 3D models, announced the development of a powerful new tool, the Digital Twin Base Map. This innovative technology sets a new standard for urban analysis, implementation of Digital Cities, navigation, and planning with a fundamental transformation from a 2D map to a 3D environment. The Digital Twin Base Map is a high-resolution 3D map providing unprecedented detail and accuracy., Feb 2023: Bluesky Geospatial launched the MetroVista, a 3D aerial mapping program in the USA. The service employs a hybrid imaging-Lidar airborne sensor to capture highly detailed 3D data, including 360-degree views of buildings and street-level features, in urban areas to create digital twins, visualizations, and simulations., Feb 2023: Esri, a leading global provider of geographic information system (GIS), location intelligence, and mapping solutions, released new ArcGIS Reality Software to capture the world in 3D. ArcGIS Reality enables site, city, and country-wide 3D mapping for digital twins. These 3D models and high-resolution maps allow organizations to analyze and interact with a digital world, accurately showing their locations and situations., Jan 2023: Strava, a subscription-based fitness platform, announced the acquisition of FATMAP, a 3D mapping platform, to integrate into its app. The acquisition adds FATMAP's mountain-focused maps to Strava's platform, combining with the data already within Strava's products, including city and suburban areas for runners and other fitness enthusiasts., Jan 2023: The 3D mapping platform FATMAP is acquired by Strava. FATMAP applies the concept of 3D visualization specifically for people who like mountain sports like skiing and hiking., Jan 2022: GeoScience Limited (the UK) announced receiving funding from Deep Digital Cornwall (DDC) to develop a new digital heat flow map. The DDC project has received grant funding from the European Regional Development Fund. This study aims to model the heat flow in the region's shallower geothermal resources to promote its utilization in low-carbon heating. GeoScience Ltd wants to create a more robust 3D model of the Cornwall subsurface temperature through additional boreholes and more sophisticated modeling techniques., Aug 2022: In order to create and explore the system's possibilities, CGTrader worked with the online retailer of dietary supplements Hello100. The system has the ability to scale up the generation of more models, and it has enhanced and improved Hello100's appearance on Amazon Marketplace.. Key drivers for this market are: The demand for 3D maps and models is growing rapidly across various industries, including architecture, engineering, and construction (AEC), manufacturing, transportation, and healthcare. Advances in hardware, software, and data acquisition techniques are making it possible to create more accurate, detailed, and realistic 3D maps and models. Digital twins, which are virtual representations of real-world assets or systems, are driving the demand for 3D mapping and modeling technologies for the creation of accurate and up-to-date digital representations.

    . Potential restraints include: The acquisition and processing of 3D data can be expensive, especially for large-scale projects. There is a lack of standardization in the 3D mapping modeling industry, which can make it difficult to share and exchange data between different software and systems. There is a shortage of skilled professionals who are able to create and use 3D maps and models effectively.. Notable trends are: 3D mapping and modeling technologies are becoming essential for a wide range of applications, including urban planning, architecture, construction, environmental management, and gaming. Advancements in hardware, software, and data acquisition techniques are enabling the creation of more accurate, detailed, and realistic 3D maps and models. Digital twins, which are virtual representations of real-world assets or systems, are driving the demand for 3D mapping and modeling technologies for the creation of accurate and up-to-date digital representations..

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NOAA GeoPlatform (2023). CrowdMag Visualization Web Map [Dataset]. https://noaa.hub.arcgis.com/maps/f8e24dd400c94d4e8275417f2e8a2070
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CrowdMag Visualization Web Map

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Dataset updated
May 15, 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.
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