100+ datasets found
  1. m

    GeoStoryTelling

    • data.mendeley.com
    Updated Apr 21, 2023
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    Manuel Gonzalez Canche (2023). GeoStoryTelling [Dataset]. http://doi.org/10.17632/nh2c5t3vf9.1
    Explore at:
    Dataset updated
    Apr 21, 2023
    Authors
    Manuel Gonzalez Canche
    License

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

    Description

    Database created for replication of GeoStoryTelling. Our life stories evolve in specific and contextualized places. Although our homes may be our primarily shaping environment, our homes are themselves situated in neighborhoods that expose us to the immediate “real world” outside home. Indeed, the places where we are currently experiencing, and have experienced life, play a fundamental role in gaining a deeper and more nuanced understanding of our beliefs, fears, perceptions of the world, and even our prospects of social mobility. Despite the immediate impact of the places where we experience life in reaching a better understanding of our life stories, to date most qualitative and mixed methods researchers forego the analytic and elucidating power that geo-contextualizing our narratives bring to social and health research. From this view then, most research findings and conclusions may have been ignoring the spatial contexts that most likely have shaped the experiences of research participants. The main reason for the underuse of these geo-contextualized stories is the requirement of specialized training in geographical information systems and/or computer and statistical programming along with the absence of cost-free and user-friendly geo-visualization tools that may allow non-GIS experts to benefit from geo-contextualized outputs. To address this gap, we present GeoStoryTelling, an analytic framework and user-friendly, cost-free, multi-platform software that enables researchers to visualize their geo-contextualized data narratives. The use of this software (available in Mac and Windows operative systems) does not require users to learn GIS nor computer programming to obtain state-of-the-art, and visually appealing maps. In addition to providing a toy database to fully replicate the outputs presented, we detail the process that researchers need to follow to build their own databases without the need of specialized external software nor hardware. We show how the resulting HTML outputs are capable of integrating a variety of multi-media inputs (i.e., text, image, videos, sound recordings/music, and hyperlinks to other websites) to provide further context to the geo-located stories we are sharing (example https://cutt.ly/k7X9tfN). Accordingly, the goals of this paper are to describe the components of the methodology, the steps to construct the database, and to provide unrestricted access to the software tool, along with a toy dataset so that researchers may interact first-hand with GeoStoryTelling and fully replicate the outputs discussed herein. Since GeoStoryTelling relied on OpenStreetMap its applications may be used worldwide, thus strengthening its potential reach to the mixed methods and qualitative scientific communities, regardless of location around the world. Keywords: Geographical Information Systems; Interactive Visualizations; Data StoryTelling; Mixed Methods & Qualitative Research Methodologies; Spatial Data Science; Geo-Computation.

  2. H

    Big Data Visualization: A Game changer in GIS, Geo-analysis and...

    • dataverse.harvard.edu
    Updated Feb 27, 2019
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    Prince Ogbonna (2019). Big Data Visualization: A Game changer in GIS, Geo-analysis and Geo-demographics [Dataset]. http://doi.org/10.7910/DVN/Y5EUPG
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 27, 2019
    Dataset provided by
    Harvard Dataverse
    Authors
    Prince Ogbonna
    License

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

    Description

    Today, everybody around the world is living and working under the coverage of Geographic Information system (GIS) application and services such as the Google Earth, GPS and much more. Big Data visualization tools are increasingly creating a wonder in the world of GIS. GIS has diverse application, from geo-positioning services to 3D demonstrations and virtual reality. Big Data and its tools of visualization has boosted the field of GIS. This article seeks to explore how Big data visualization has expanded the field of Geo- spatial analysis with the intention to present practicable GIS-based tools required to stay ahead in this field.

  3. D

    Geospatial Analytics Software Market Report | Global Forecast From 2025 To...

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Geospatial Analytics Software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-geospatial-analytics-software-market
    Explore at:
    csv, pptx, pdfAvailable 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

    Geospatial Analytics Software Market Outlook



    The global geospatial analytics software market size is projected to grow from USD 50.1 billion in 2023 to USD 114.5 billion by 2032, reflecting a robust compound annual growth rate (CAGR) of 9.5%. This remarkable growth is largely driven by the increasing adoption of geospatial technologies across various sectors, including urban planning, agriculture, transportation, and disaster management. The surge in the utilization of geospatial data for strategic decision-making, coupled with advancements in technology such as artificial intelligence (AI) and big data analytics, plays a pivotal role in propelling market growth.



    One of the key growth factors of the geospatial analytics software market is the rapid digital transformation occurring globally. Governments and enterprises are increasingly recognizing the value of geospatial data in enhancing operational efficiency and strategic planning. The rise in smart city initiatives across the world has bolstered the demand for geospatial analytics, as cities leverage these technologies to optimize infrastructure, manage resources, and improve public services. Additionally, the integration of AI and machine learning with geospatial analytics has enhanced the accuracy and predictive capabilities of these systems, further driving their adoption.



    Another significant driver is the growing need for disaster management and climate change adaptation. As the frequency and intensity of natural disasters increase due to climate change, there is a heightened demand for geospatial analytics to predict, monitor, and mitigate the impact of such events. Geospatial software aids in mapping hazard zones, planning evacuation routes, and assessing damage post-disaster. This capability is crucial for governments and organizations involved in disaster management and mitigation, thereby boosting the market growth.



    The transportation and logistics sector is also a major contributor to the growth of the geospatial analytics software market. The advent of autonomous vehicles and the continuous evolution of logistics and supply chain management have heightened the need for precise geospatial data. Geospatial analytics enables real-time tracking, route optimization, and efficient fleet management, which are critical for the smooth operation of transportation systems. This trend is expected to continue, driving the demand for geospatial analytics solutions in transportation and logistics.



    On a regional level, North America is anticipated to dominate the geospatial analytics software market, driven by technological advancements and substantial investments in geospatial technologies. The presence of major market players and the high adoption rate of advanced technologies in sectors such as defense, agriculture, and urban planning contribute to this dominance. However, the Asia Pacific region is expected to witness the highest growth rate, fueled by rapid urbanization, government initiatives for smart cities, and increasing investments in infrastructure development.



    GIS Software plays a crucial role in the geospatial analytics software market, offering powerful tools for data visualization, spatial analysis, and geographic mapping. As organizations across various sectors increasingly rely on geospatial data for strategic decision-making, GIS Software provides the necessary infrastructure to manage, analyze, and interpret this data effectively. Its integration with other technologies such as AI and machine learning enhances its capabilities, enabling more accurate predictions and insights. This makes GIS Software an indispensable component for industries like urban planning, agriculture, and transportation, where spatial data is pivotal for optimizing operations and improving outcomes. The growing demand for GIS Software is a testament to its importance in driving the geospatial analytics market forward.



    Component Analysis



    The geospatial analytics software market is segmented into software and services when considering components. The software segment includes comprehensive solutions that integrate various geospatial data types and provide analytical tools for mapping, visualization, and data processing. This segment is expected to hold the largest market share due to the increasing adoption of these solutions in various industries for efficient data management and decision-making. The continuous advancements in software capabilities, such as the inclusion of AI and machine learning algorithms

  4. f

    VR/AR/XR Visualization of Geospatial Data from NASA GES-DISC

    • esip.figshare.com
    pdf
    Updated Jul 16, 2023
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    Zachariah Abueg; Allison Alcott; Armin Mehrabian (2023). VR/AR/XR Visualization of Geospatial Data from NASA GES-DISC [Dataset]. http://doi.org/10.6084/m9.figshare.23691930.v1
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Jul 16, 2023
    Dataset provided by
    ESIP
    Authors
    Zachariah Abueg; Allison Alcott; Armin Mehrabian
    License

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

    Description

    The Goddard Earth Sciences Data and Information Services Center (GES-DISC) at NASA is responsible for safeguarding and distributing invaluable Earth science data. Recognizing the critical role of satellite data visualization in immersive environments, we have embarked on a venture that explores the utilization of existing tools and technologies such as virtual reality (VR), augmented reality (AR), and extended reality (XR).

    The intention of this project is not merely to experiment, but to potentially redefine how we interact with our large data inventory. Our objective is to deepen our comprehension of data and create engaging, interactive experiences.

  5. f

    Data from: Bringing micro to the macro: how citizen science data enrich...

    • tandf.figshare.com
    pdf
    Updated Dec 15, 2023
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    Shamsi Soltani; Jessica A. Hinman; Isela Blanco-Velazquez; Ann W. Banchoff; Maria I. Campero; Lorene M. Nelson; Abby C. King (2023). Bringing micro to the macro: how citizen science data enrich geospatial visualizations to advance health equity [Dataset]. http://doi.org/10.6084/m9.figshare.23576602.v3
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Dec 15, 2023
    Dataset provided by
    Taylor & Francis
    Authors
    Shamsi Soltani; Jessica A. Hinman; Isela Blanco-Velazquez; Ann W. Banchoff; Maria I. Campero; Lorene M. Nelson; Abby C. King
    License

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

    Description

    Social and spatial contexts affect health, and understanding nuances of context is key to informing successful interventions for health equity. Layering mixed methods and mixed scale data sources to visualize patterns of health outcomes facilitates analysis of both broad trends and person-level experiences across time and space. We used micro-scale citizen scientist-collected data from four Bay Area communities along with aggregate epidemiologic and population-level data sets to illustrate barriers to, and facilitators of, physical activity in low-income aging adults. These data integrations highlight the synergistic value added by combining data sources, and what might be missed by relying on either a micro- or macro-level data source alone. Mixed methods and granularity data integration can generate a deeper understanding of environmental context, which in turn can inform more relevant and attainable community, advocacy, and policy improvements.

  6. India GIS Data

    • kaggle.com
    Updated Sep 11, 2020
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    Neha Prabhavalkar (2020). India GIS Data [Dataset]. https://www.kaggle.com/nehaprabhavalkar/india-gis-data/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 11, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Neha Prabhavalkar
    License

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

    Area covered
    India
    Description

    Content

    This dataset contains various geospatial file formats of India such as shape files, project files, etc that are useful for geospatial analysis.

    Acknowledgements

    The files were collected from Igismap - https://www.igismap.com/

  7. d

    GIS Data | Global Geospatial data | Postal/Administrative boundaries |...

    • datarade.ai
    .json, .xml
    Updated Oct 18, 2024
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    GeoPostcodes (2024). GIS Data | Global Geospatial data | Postal/Administrative boundaries | Countries, Regions, Cities, Suburbs, and more [Dataset]. https://datarade.ai/data-products/geopostcodes-gis-data-gesopatial-data-postal-administrati-geopostcodes
    Explore at:
    .json, .xmlAvailable download formats
    Dataset updated
    Oct 18, 2024
    Dataset authored and provided by
    GeoPostcodes
    Area covered
    United States
    Description

    Overview

    Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.

    Our self-hosted GIS data cover administrative and postal divisions with up to 6 precision levels: a zip code layer and up to 5 administrative levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.

    The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.

    Use cases for the Global Boundaries Database (GIS data, Geospatial data)

    • In-depth spatial analysis

    • Clustering

    • Geofencing

    • Reverse Geocoding

    • Reporting and Business Intelligence (BI)

    Product Features

    • Coherence and precision at every level

    • Edge-matched polygons

    • High-precision shapes for spatial analysis

    • Fast-loading polygons for reporting and BI

    • Multi-language support

    For additional insights, you can combine the GIS data with:

    • Population data: Historical and future trends

    • UNLOCODE and IATA codes

    • Time zones and Daylight Saving Time (DST)

    Data export methodology

    Our geospatial data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson

    All GIS data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

    Why companies choose our map data

    • Precision at every level

    • Coverage of difficult geographies

    • No gaps, nor overlaps

    Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

  8. G

    Geospatial Analytics Market Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Jan 10, 2025
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    Market Research Forecast (2025). Geospatial Analytics Market Report [Dataset]. https://www.marketresearchforecast.com/reports/geospatial-analytics-market-1650
    Explore at:
    doc, ppt, pdfAvailable download formats
    Dataset updated
    Jan 10, 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

    The Geospatial Analytics Market size was valued at USD 79.06 USD billion in 2023 and is projected to reach USD 202.74 USD billion by 2032, exhibiting a CAGR of 14.4 % during the forecast period. The growing adoption of location-based technologies and the increasing need for data-driven decision-making in various industries are key factors driving market growth. Geospatial analytics captures, produces and displays GIS (geographic information system)-maps and pictures that may be weather maps, GPS or satellite photos. The geospatial analysis as a tool works with state of art technology in every formats namely; the GPS, sensors that locates, social media, mobile devices, multi of the satellite imagery to produce data visualizations that are facilitating trend-finding in complex relations between people and places as well are the situations' understanding. Visualizations are depicted through the use of maps, graphs, figures, and cartograms that illustrate the entire historical picture as well as a current changing trend. This is why the forecast becomes more confident and the situation is anticipated better. Recent developments include: February 2024: Placer.ai and Esri, a Geographic Information System (GIS) technology provider, partnered to empower customers with enhanced analytics capabilities, integrating consumer behavior analysis. Additionally, the agreement will foster collaborations to unlock further features by synergizing our respective product offerings., December 2023: CKS and Esri India Technologies Pvt Ltd teamed up to introduce the 'MMGEIS' program, focusing on students from 8th grade to undergraduates, to position India as a global leader in geospatial technology through skill development and innovation., December 2023: In collaboration with Bayanat, the UAE Space Agency revealed the initiation of the operational phase of the Geospatial Analytics Platform during its participation in organizing the Space at COP28 initiatives., November 2023: USAID unveiled its inaugural Geospatial Strategy, designed to harness geospatial data and technology for more targeted international program delivery. The strategy foresees a future where geographic methods enhance the effectiveness of USAID's efforts by pinpointing development needs, monitoring program implementation, and evaluating outcomes based on location., May 2023: TomTom International BV, a geolocation technology specialist, expanded its partnership with Alteryx, Inc. Through this partnership, Alteryx will use TomTom’s Maps APIs and location data to integrate spatial data into Alteryx’s products and location insights packages, such as Alteryx Designer., May 2023: Oracle Corporation announced the launch of Oracle Spatial Studio 23.1, available in the Oracle Cloud Infrastructure (OCI) marketplace and for on-premises deployment. Users can browse, explore, and analyze geographic data stored in and managed by Oracle using a no-code mapping tool., May 2023: CAPE Analytics, a property intelligence company, announced an enhanced insurance offering by leveraging Google geospatial data. Google’s geospatial data can help CAPE create appropriate solutions for insurance carriers., February 2023: HERE Global B.V. announced a collaboration with Cognizant, an information technology, services, and consulting company, to offer digital customer experience using location data. In this partnership, Cognizant will utilize the HERE location platform’s real-time traffic data, weather, and road attribute data to develop spatial intelligent solutions for its customers., July 2022: Athenium Analytics, a climate risk analytics company, launched a comprehensive tornado data set on the Esri ArcGIS Marketplace. This offering, which included the last 25 years of tornado insights from Athenium Analytics, would extend its Bronze partner relationship with Esri. . Key drivers for this market are: Advancements in Technologies to Fuel Market Growth. Potential restraints include: Lack of Standardization Coupled with Shortage of Skilled Workforce to Limit Market Growth. Notable trends are: Rise of Web-based GIS Platforms Will Transform Market.

  9. G

    Geospatial Imagery Analytics Market Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Dec 24, 2024
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    Market Research Forecast (2024). Geospatial Imagery Analytics Market Report [Dataset]. https://www.marketresearchforecast.com/reports/geospatial-imagery-analytics-market-1816
    Explore at:
    doc, ppt, pdfAvailable download formats
    Dataset updated
    Dec 24, 2024
    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

    The Geospatial Imagery Analytics Marketsize was valued at USD 11.88 USD Billion in 2023 and is projected to reach USD 83.39 USD Billion by 2032, exhibiting a CAGR of 32.1 % during the forecast period.Geospatial analytics gathers, manipulates, and displays geographic information system (GIS) data and imagery including GPS and satellite photographs. Geospatial data analytics rely on geographic coordinates and specific identifiers such as street address and zip code. geospatial visualization enables businesses to better understand complex information and make informed decisions. They can quickly see patterns and trends and assess the impact of different variables by visualizing data in a spatial context. The field encompasses several techniques and algorithms, such as spatial interpolation, spatial regression, spatial clustering, and spatial autocorrelation analysis, which help extract insights from various geospatial data sources. The growing adoption of location-based services in various industries, including agriculture, defense, and urban planning, is driving the demand for geospatial imagery analytics. Recent developments include: August 2023: onX, a digital navigation company, partnered with Planet Labs PBC, a satellite imagery provider, to introduce a new feature called ‘Recent Imagery’. This feature offers onX app users updated satellite imagery maps every two weeks, enhancing the user experience across onX Hunt, onX Offroad, and onX Backcountry apps. This frequent data update helps outdoor enthusiasts access real-time information for safer and more informed outdoor activities., August 2023: Quant Data & Analytics, a provider of data products and enterprise solutions for real estate and retail, partnered with Satellogic Inc. to utilize Satellogic’s high-resolution satellite imagery to enhance property technology in Saudi Arabia and the Gulf region., April 2023: Astraea, a spatiotemporal data and analytics platform, introduced a new ordering service that grants customers scalable access to top-tier commercial satellite imagery from providers such as Planet Labs PBC and others., May 2022: Satellogic Inc. established a partnership with UP42. This geospatial developer platform enables direct access to Satellogic’s satellite tasking capabilities, including high-resolution multispectral and wide-area hyperspectral imagery, through the UP42 API-based platform., April 2022: TomTom International BV, a geolocation tech company, broadened its partnership with Maxar Technologies, a space solution provider. This expansion involves integrating high-resolution global satellite imagery from Maxar’s Vivid imagery base maps into TomTom’s product lineup, enhancing their visualization solutions for customers.. Key drivers for this market are: Growing Demand for Location-based Insights across Diverse Industries to Fuel Market Growth. Potential restraints include: Complexity and Cost Associated with Data Acquisition and Processing May Hamper Market Growth. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

  10. Geospatial Analytics Market Size, Insights, Trends & Share Report, 2035

    • rootsanalysis.com
    Updated Sep 10, 2024
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    Roots Analysis (2024). Geospatial Analytics Market Size, Insights, Trends & Share Report, 2035 [Dataset]. https://www.rootsanalysis.com/geospatial-analytics-market
    Explore at:
    Dataset updated
    Sep 10, 2024
    Dataset provided by
    Authors
    Roots Analysis
    License

    https://www.rootsanalysis.com/privacy.htmlhttps://www.rootsanalysis.com/privacy.html

    Time period covered
    2021 - 2031
    Area covered
    Global
    Description

    The geospatial analytics market size is predicted to rise from $93.49 billion in 2024 to $362.45 billion by 2035, growing at a CAGR of 13.1% from 2024 to 2035.

  11. d

    GABBs MultiSpec Online

    • search.dataone.org
    Updated Dec 5, 2021
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    Larry Biehl; Abdur Rahman Maud; Wei-Kang Hsu; Tsung Tai Yeh (2021). GABBs MultiSpec Online [Dataset]. https://search.dataone.org/view/sha256%3Aeb134c6805f2363426e7039cd684bfa3b3aa1575041f70e0aebae4b3f5014553
    Explore at:
    Dataset updated
    Dec 5, 2021
    Dataset provided by
    Hydroshare
    Authors
    Larry Biehl; Abdur Rahman Maud; Wei-Kang Hsu; Tsung Tai Yeh
    Description

    This web app launches the MultiSpec Online tool on MyGeoHub (https://mygeohub.org) for geospatial data exploration, analysis and visualization.

  12. f

    Dataset for the Examples on the GWF-VIS Visualization Gallery

    • figshare.com
    Updated Apr 29, 2024
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    Debajyoti Mondal (2024). Dataset for the Examples on the GWF-VIS Visualization Gallery [Dataset]. http://doi.org/10.6084/m9.figshare.25717893.v1
    Explore at:
    application/x-sqlite3Available download formats
    Dataset updated
    Apr 29, 2024
    Dataset provided by
    figshare
    Authors
    Debajyoti Mondal
    License

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

    Description

    The dataset contains example gwfvisdb files required to run the examples displayed on the GWF-VIS visualization gallery (https://gwf-vis.usask.ca/#gallery). The code associated with each visualization example contains a 'data_source' variable. This variable can be examined to see where the data is currently hosted. Users may also upload the data file on other static file servers and update the 'data_source' to replicate the visualizations.

  13. d

    Geospatial Data | Global Map data | Administrative boundaries | Global...

    • datarade.ai
    .json, .xml
    Updated Jul 4, 2024
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    GeoPostcodes (2024). Geospatial Data | Global Map data | Administrative boundaries | Global coverage | 245k Polygons [Dataset]. https://datarade.ai/data-products/geopostcodes-geospatial-data-global-map-data-administrati-geopostcodes-a4bf
    Explore at:
    .json, .xmlAvailable download formats
    Dataset updated
    Jul 4, 2024
    Dataset authored and provided by
    GeoPostcodes
    Area covered
    United States
    Description

    Overview

    Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.

    Our self-hosted geospatial data cover administrative and postal divisions with up to 5 precision levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.

    The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.

    Use cases for the Global Administrative Boundaries Database (Geospatial data, Map data)

    • In-depth spatial analysis

    • Clustering

    • Geofencing

    • Reverse Geocoding

    • Reporting and Business Intelligence (BI)

    Product Features

    • Coherence and precision at every level

    • Edge-matched polygons

    • High-precision shapes for spatial analysis

    • Fast-loading polygons for reporting and BI

    • Multi-language support

    For additional insights, you can combine the map data with:

    • Population data: Historical and future trends

    • UNLOCODE and IATA codes

    • Time zones and Daylight Saving Time (DST)

    Data export methodology

    Our location data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson

    All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

    Why companies choose our map data

    • Precision at every level

    • Coverage of difficult geographies

    • No gaps, nor overlaps

    Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

  14. Geospatial Analytics Market Analysis, Size, and Forecast 2025-2029: North...

    • technavio.com
    Updated Apr 15, 2025
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    Technavio (2025). Geospatial Analytics Market Analysis, Size, and Forecast 2025-2029: North America (US and Canada), Europe (France, Germany, Italy, and UK), APAC (China, India, and Japan), South America (Brazil), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/geospatial-analytics-market-industry-analysis
    Explore at:
    Dataset updated
    Apr 15, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Germany, Canada, United Kingdom, United States, Global
    Description

    Snapshot img

    Geospatial Analytics Market Size 2025-2029

    The geospatial analytics market size is forecast to increase by USD 178.6 billion, at a CAGR of 21.4% between 2024 and 2029.

    The market is experiencing significant growth, driven by the increasing adoption of geospatial analytics in sectors such as healthcare and insurance. This trend is fueled by the ability of geospatial analytics to provide valuable insights from location-based data, leading to improved operational efficiency and decision-making. Additionally, emerging methods in data collection and generation, including the use of drones and satellite imagery, are expanding the scope and potential of geospatial analytics. However, the market faces challenges, including data privacy and security concerns. With the vast amounts of sensitive location data being collected and analyzed, ensuring its protection is crucial for companies to maintain trust with their customers and avoid regulatory penalties. Navigating these challenges and capitalizing on the opportunities presented by the growing adoption of geospatial analytics requires a strategic approach from industry players. Companies must prioritize data security, invest in advanced analytics technologies, and collaborate with stakeholders to build trust and transparency. By addressing these challenges and leveraging the power of geospatial analytics, businesses can gain a competitive edge and unlock new opportunities in various industries.

    What will be the Size of the Geospatial Analytics 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 SampleThe market continues to evolve, driven by the increasing demand for location-specific insights across various sectors. Urban planning relies on geospatial optimization and data enrichment to enhance city designs and improve infrastructure. Cloud-based geospatial solutions facilitate real-time data access, enabling location intelligence for public safety and resource management. Spatial data standards ensure interoperability among different systems, while geospatial software and data visualization tools provide valuable insights from satellite imagery and aerial photography. Geospatial services offer data integration, spatial data accuracy, and advanced analytics capabilities, including 3D visualization, route optimization, and data cleansing. Precision agriculture and environmental monitoring leverage geospatial data to optimize resource usage and monitor ecosystem health. Infrastructure management and real estate industries rely on geospatial data for asset tracking and market analysis. Spatial statistics and disaster management applications help mitigate risks and respond effectively to crises. Geospatial data management and quality remain critical as the volume and complexity of data grow. Geospatial modeling and interoperability enable seamless data sharing and collaboration. Sensor networks and geospatial data acquisition technologies expand the reach of geospatial analytics, while AI-powered geospatial analytics offer new opportunities for predictive analysis and automation. The ongoing development of geospatial technologies and applications underscores the market's continuous dynamism, providing valuable insights and solutions for businesses and organizations worldwide.

    How is this Geospatial Analytics Industry segmented?

    The geospatial analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. TechnologyGPSGISRemote sensingOthersEnd-userDefence and securityGovernmentEnvironmental monitoringMining and manufacturingOthersApplicationSurveyingMedicine and public safetyMilitary intelligenceDisaster risk reduction and managementOthersTypeSurface and field analyticsGeovisualizationNetwork and location analyticsOthersGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth AmericaBrazilRest of World (ROW)

    By Technology Insights

    The gps segment is estimated to witness significant growth during the forecast period.The market encompasses various applications and technologies, including geospatial optimization, data enrichment, location-based services (LBS), spatial data standards, public safety, geospatial software, resource management, location intelligence, geospatial data visualization, geospatial services, data integration, 3D visualization, satellite imagery, remote sensing, GIS platforms, spatial data infrastructure, aerial photography, route optimization, data cleansing, precision agriculture, spatial interpolation, geospatial databases, transportation planning, spatial data accuracy, spatial analysis, map projections, interactive maps, marketing analytics, d

  15. Digital Geologic-GIS Map of San Miguel Island, California (NPS, GRD, GRI,...

    • catalog.data.gov
    Updated Jun 4, 2024
    + more versions
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    National Park Service (2024). Digital Geologic-GIS Map of San Miguel Island, California (NPS, GRD, GRI, CHIS, SMIS digital map) adapted from a American Association of Petroleum Geologists Field Trip Guidebook map by Weaver and Doerner (1969) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-san-miguel-island-california-nps-grd-gri-chis-smis-digital-map
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    Dataset updated
    Jun 4, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    California, San Miguel Island
    Description

    The Digital Geologic-GIS Map of San Miguel Island, California is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (smis_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (smis_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (smis_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) this file (chis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (chis_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (smis_geology_metadata_faq.pdf). Please read the chis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: American Association of Petroleum Geologists. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (smis_geology_metadata.txt or smis_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  16. I

    Interactive Map Creation Tools Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Jun 28, 2025
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    Data Insights Market (2025). Interactive Map Creation Tools Report [Dataset]. https://www.datainsightsmarket.com/reports/interactive-map-creation-tools-1418201
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Jun 28, 2025
    Dataset authored and provided by
    Data Insights Market
    License

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

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

    The interactive map creation tools market is experiencing robust growth, driven by increasing demand for visually engaging data representation across diverse sectors. The market, estimated at $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $7.8 billion by 2033. This expansion is fueled by several key factors. The rising adoption of location-based services (LBS) and geographic information systems (GIS) across industries like real estate, tourism, logistics, and urban planning is a major catalyst. Businesses are increasingly leveraging interactive maps to enhance customer engagement, improve operational efficiency, and gain valuable insights from geospatial data. Furthermore, advancements in mapping technologies, including the integration of AI and machine learning for improved data analysis and visualization, are contributing to market growth. The accessibility of user-friendly tools, coupled with the decreasing cost of cloud-based solutions, is also making interactive map creation more accessible to a wider range of users, from individuals to large corporations. However, the market also faces certain challenges. Data security and privacy concerns surrounding the use of location data are paramount. The need for specialized skills and expertise to effectively utilize advanced mapping technologies may also hinder broader adoption, particularly among smaller businesses. Competition among established players like Mapbox, ArcGIS StoryMaps, and Google, alongside emerging innovative solutions, necessitates constant innovation and differentiation. Nevertheless, the overall market outlook remains positive, with continued technological advancements and rising demand for data visualization expected to propel growth in the coming years. Specific market segmentation data, while unavailable, can be reasonably inferred from existing market trends, suggesting a strong dominance of enterprise-grade solutions, but with substantial growth expected from simpler, more user-friendly tools designed for individuals and small businesses.

  17. D

    Data Visualization and Analysis Platform Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Apr 22, 2025
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    Data Insights Market (2025). Data Visualization and Analysis Platform Report [Dataset]. https://www.datainsightsmarket.com/reports/data-visualization-and-analysis-platform-535494
    Explore at:
    doc, pdf, pptAvailable download formats
    Dataset updated
    Apr 22, 2025
    Dataset authored and provided by
    Data Insights Market
    License

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

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

    The global Data Visualization and Analysis Platform market is experiencing robust growth, projected to reach $6.58 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 8.5% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing volume and complexity of data generated across various sectors – notably enterprise and government – necessitate sophisticated tools for data interpretation and actionable insight extraction. Furthermore, the rising adoption of cloud-based solutions offers scalability, accessibility, and cost-effectiveness, accelerating market penetration. The trend towards advanced visualization techniques, such as geospatial and conceptual visualization, beyond basic charts and graphs, caters to the need for nuanced data understanding and improved decision-making. While data security and integration complexities pose some restraints, the overall market outlook remains positive, driven by continuous technological advancements and growing demand for data-driven strategies across industries. The market is segmented by application (Enterprise, Government) and by type of visualization (Area & Size, Color, Graphical, Geospatial, Conceptual). Major players like Baidu AI Cloud, Alibaba Cloud, Tencent Cloud, and Tableau are actively shaping the market landscape through innovation and competitive pricing strategies. Geographic growth is expected across all regions, with North America and Asia Pacific likely leading the charge, given their advanced technological infrastructure and high concentration of data-intensive businesses. The diverse range of visualization types caters to a wide spectrum of user needs, from simple data summaries to complex simulations. The strong presence of both established players and innovative startups ensures a competitive landscape fostering continuous improvement and product diversification. The increasing integration of Artificial Intelligence (AI) and Machine Learning (ML) capabilities within these platforms further enhances their analytical power, enabling predictive modeling and automated insights. This convergence of visualization and advanced analytics positions the market for significant future growth, particularly as businesses across all sizes prioritize data-driven decision making to gain a competitive edge. The continued focus on user experience and intuitive interface design is expected to expand the user base further, driving broader adoption across sectors.

  18. d

    Geospatial Data | Global | Real-Time & Historical Mobility Patterns

    • datarade.ai
    Updated Aug 23, 2023
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    Irys (2023). Geospatial Data | Global | Real-Time & Historical Mobility Patterns [Dataset]. https://datarade.ai/data-products/geospatial-data-global-real-time-historical-mobility-pa-irys
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    .json, .csv, .xls, .sqlAvailable download formats
    Dataset updated
    Aug 23, 2023
    Dataset authored and provided by
    Irys
    Area covered
    Bahrain, Colombia, Azerbaijan, Montenegro, Ascension and Tristan da Cunha, Micronesia (Federated States of), Guinea, Argentina, Sint Maarten (Dutch part), Sao Tome and Principe
    Description

    This mobility data product provides global real-time and historical origin–destination movement patterns derived from anonymized mobile devices. The dataset captures continuous location signals to generate accurate mobility insights across countries, cities, and neighborhoods. Irys processes billions of daily mobile location data points to model population flows, commuter trends, and activity hubs.

    Use this mobility data to analyze how people move between commercial zones, residential areas, and public facilities. Our geospatial data architecture enables seamless integration with map data, making it easy to overlay real-world movement on custom GIS visualizations. The dataset supports time-stamped location data, with user movement sequences, dwell time, and visit frequency.

    Whether you are building transportation models, analyzing foot traffic data, or identifying high-value POIs, this mobile location data product is ideal for planners, analysts, and data teams looking to enrich their map data pipelines.

    Each data point is: Sourced from high-quality, opt-in mobile signals Time- and geo-stamped to the nearest 5 minutes GDPR and CCPA compliant

    This dataset is particularly useful for applications in: Smart city planning Retail site selection Public safety and infrastructure development Advertising and audience targeting Real-time congestion analysis

    Our platform ensures that this mobility data is continuously updated, cleaned, and validated to maximize accuracy and location data integrity. Available via flat file or API.

  19. a

    QGIS Training Tutorials: Using Spatial Data in Geographic Information...

    • catalogue.arctic-sdi.org
    • datasets.ai
    • +2more
    Updated Oct 28, 2019
    + more versions
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    (2019). QGIS Training Tutorials: Using Spatial Data in Geographic Information Systems [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/search?format=MOV
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    Dataset updated
    Oct 28, 2019
    Description

    Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.

  20. n

    LANDISVIEW 2.0 : Free Spatial Data Analysis

    • cmr.earthdata.nasa.gov
    Updated Mar 5, 2021
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    (2021). LANDISVIEW 2.0 : Free Spatial Data Analysis [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1214586381-SCIOPS
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    Dataset updated
    Mar 5, 2021
    Time period covered
    Jan 1, 1970 - Present
    Description

    LANDISVIEW is a tool, developed at the Knowledge Engineering Laboratory at Texas A&M University, to visualize and animate 8-bit/16-bit ERDAS GIS format (e.g., LANDIS and LANDIS-II output maps). It can also convert 8-bit/16-bit ERDAS GIS format into ASCII and batch files. LANDISVIEW provides two major functions: 1) File Viewer: Files can be viewed sequentially and an output can be generated as a movie file or as an image file. 2) File converter: It will convert the loaded files for compatibility with 3rd party software, such as Fragstats, a widely used spatial analysis tool. Some available features of LANDISVIEW include: 1) Display cell coordinates and values. 2) Apply user-defined color palette to visualize files. 3) Save maps as pictures and animations as video files (*.avi). 4) Convert ERDAS files into ASCII grids for compatibility with Fragstats. (Source: http://kelab.tamu.edu/)

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Manuel Gonzalez Canche (2023). GeoStoryTelling [Dataset]. http://doi.org/10.17632/nh2c5t3vf9.1

GeoStoryTelling

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61 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Apr 21, 2023
Authors
Manuel Gonzalez Canche
License

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

Description

Database created for replication of GeoStoryTelling. Our life stories evolve in specific and contextualized places. Although our homes may be our primarily shaping environment, our homes are themselves situated in neighborhoods that expose us to the immediate “real world” outside home. Indeed, the places where we are currently experiencing, and have experienced life, play a fundamental role in gaining a deeper and more nuanced understanding of our beliefs, fears, perceptions of the world, and even our prospects of social mobility. Despite the immediate impact of the places where we experience life in reaching a better understanding of our life stories, to date most qualitative and mixed methods researchers forego the analytic and elucidating power that geo-contextualizing our narratives bring to social and health research. From this view then, most research findings and conclusions may have been ignoring the spatial contexts that most likely have shaped the experiences of research participants. The main reason for the underuse of these geo-contextualized stories is the requirement of specialized training in geographical information systems and/or computer and statistical programming along with the absence of cost-free and user-friendly geo-visualization tools that may allow non-GIS experts to benefit from geo-contextualized outputs. To address this gap, we present GeoStoryTelling, an analytic framework and user-friendly, cost-free, multi-platform software that enables researchers to visualize their geo-contextualized data narratives. The use of this software (available in Mac and Windows operative systems) does not require users to learn GIS nor computer programming to obtain state-of-the-art, and visually appealing maps. In addition to providing a toy database to fully replicate the outputs presented, we detail the process that researchers need to follow to build their own databases without the need of specialized external software nor hardware. We show how the resulting HTML outputs are capable of integrating a variety of multi-media inputs (i.e., text, image, videos, sound recordings/music, and hyperlinks to other websites) to provide further context to the geo-located stories we are sharing (example https://cutt.ly/k7X9tfN). Accordingly, the goals of this paper are to describe the components of the methodology, the steps to construct the database, and to provide unrestricted access to the software tool, along with a toy dataset so that researchers may interact first-hand with GeoStoryTelling and fully replicate the outputs discussed herein. Since GeoStoryTelling relied on OpenStreetMap its applications may be used worldwide, thus strengthening its potential reach to the mixed methods and qualitative scientific communities, regardless of location around the world. Keywords: Geographical Information Systems; Interactive Visualizations; Data StoryTelling; Mixed Methods & Qualitative Research Methodologies; Spatial Data Science; Geo-Computation.

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