Xverum’s Point of Interest (POI) Data is a comprehensive dataset containing 230M+ verified locations across 5000 business categories. Our dataset delivers structured geographic data, business attributes, location intelligence, and mapping insights, making it an essential tool for GIS applications, market research, urban planning, and competitive analysis.

With regular updates and continuous POI discovery, Xverum ensures accurate, up-to-date information on businesses, landmarks, retail stores, and more. Delivered in bulk to S3 Bucket and cloud storage, our dataset integrates seamlessly into mapping, geographic information systems, and analytics platforms.

🔥 Key Features:

Extensive POI Coverage: ✅ 230M+ Points of Interest worldwide, covering 5000 business categories. ✅ Includes retail stores, restaurants, corporate offices, landmarks, and service providers.

Geographic & Location Intelligence Data: ✅ Latitude & longitude coordinates for mapping and navigation applications. ✅ Geographic classification, including country, state, city, and postal code. ✅ Business status tracking – Open, temporarily closed, or permanently closed.

Continuous Discovery & Regular Updates: ✅ New POIs continuously added through discovery processes. ✅ Regular updates ensure data accuracy, reflecting new openings and closures.

Rich Business Insights: ✅ Detailed business attributes, including company name, category, and subcategories. ✅ Contact details, including phone number and website (if available). ✅ Consumer review insights, including rating distribution and total number of reviews (additional feature). ✅ Operating hours where available.

Ideal for Mapping & Location Analytics: ✅ Supports geospatial analysis & GIS applications. ✅ Enhances mapping & navigation solutions with structured POI data. ✅ Provides location intelligence for site selection & business expansion strategies.

Bulk Data Delivery (NO API): ✅ Delivered in bulk via S3 Bucket or cloud storage. ✅ Available in structured format (.json) for seamless integration.

🏆Primary Use Cases:

Mapping & Geographic Analysis: 🔹 Power GIS platforms & navigation systems with precise POI data. 🔹 Enhance digital maps with accurate business locations & categories.

Retail Expansion & Market Research: 🔹 Identify key business locations & competitors for market analysis. 🔹 Assess brand presence across different industries & geographies.

Business Intelligence & Competitive Analysis: 🔹 Benchmark competitor locations & regional business density. 🔹 Analyze market trends through POI growth & closure tracking.

Smart City & Urban Planning: 🔹 Support public infrastructure projects with accurate POI data. 🔹 Improve accessibility & zoning decisions for government & businesses.

💡 Why Choose Xverum’s POI Data?

• 230M+ Verified POI Records – One of the largest & most detailed location datasets available.
• Global Coverage – POI data from 249+ countries, covering all major business sectors.
• Regular Updates – Ensuring accurate tracking of business openings & closures.
• Comprehensive Geographic & Business Data – Coordinates, addresses, categories, and more.
• Bulk Dataset Delivery – S3 Bucket & cloud storage delivery for full dataset access.
• 100% Compliant – Ethically sourced, privacy-compliant data.

Access Xverum’s 230M+ POI dataset for mapping, geographic analysis, and location intelligence. Request a free sample or contact us to customize your dataset today!

Work in progress: data might be changed

The data set contains the locations of public roadside parking spaces in the northeastern part of Hanover Linden-Nord. As a sample data set, it explicitly does not provide a complete, accurate or correct representation of the conditions! It was collected and processed as part of the 5GAPS research project on September 22nd and October 6th 2022 as a basis for further analysis and in particular as input for simulation studies.

Vehicle Detections

Based on the mapping methodology of Bock et al. (2015) and processing of Leichter et al. (2021), the utilization was determined using vehicle detections in segmented 3D point clouds. The corresponding point clouds were collected by driving over the area on two half-days using a LiDAR mobile mapping system, resulting in several hours between observations. Accordingly, these are only a few sample observations. The trips are made in such a way that combined they cover a synthetic day from about 8-20 clock.

The collected point clouds were georeferenced, processed, and automatically segmented semantically (see Leichter et al., 2021). To automatically extract cars, those points with car labels were clustered by observation epoch and bounding boxes were estimated for the clusters as a representation of car instances. The boxes serve both to filter out unrealistically small and large objects, and to rudimentarily complete the vehicle footprint that may not be fully captured from all sides.

https://data.uni-hannover.de/dataset/0945cd36-6797-44ac-a6bd-b7311f0f96bc/resource/807618b6-5c38-4456-88a1-cb47500081ff/download/detection_map.png" alt="Overview map of detected vehicles" title="Overview map of detected vehicles"> Figure 1: Overview map of detected vehicles

Parking Areas

The public parking areas were digitized manually using aerial images and the detected vehicles in order to exclude irregular parking spaces as far as possible. They were also tagged as to whether they were aligned parallel to the road and assigned to a use at the time of recording, as some are used for construction sites or outdoor catering, for example. Depending on the intended use, they can be filtered individually.

https://data.uni-hannover.de/dataset/0945cd36-6797-44ac-a6bd-b7311f0f96bc/resource/16b14c61-d1d6-4eda-891d-176bdd787bf5/download/parking_area_example.png" alt="Example parking area occupation pattern" title="Visualization of example parking areas on top of an aerial image [by LGLN]"> Figure 2: Visualization of example parking areas on top of an aerial image [by LGLN]

Parking Occupancy

For modelling the parking occupancy, single slots are sampled as center points every 5 m from the parking areas. In this way, they can be integrated into a street/routing graph, for example, as prepared in Wage et al. (2023). Own representations can be generated from the parking area and vehicle detections. Those parking points were intersected with the vehicle boxes to identify occupancy at the respective epochs.

https://data.uni-hannover.de/dataset/0945cd36-6797-44ac-a6bd-b7311f0f96bc/resource/ca0b97c8-2542-479e-83d7-74adb2fc47c0/download/datenpub-bays.png" alt="Overview map of parking slots' average load" title="Overview map of parking slots' average load"> Figure 3: Overview map of average parking lot load

However, unoccupied spaces cannot be determined quite as trivially the other way around, since no detected vehicle can result just as from no measurement/observation. Therefore, a parking space is only recorded as unoccupied if a vehicle was detected at the same time in the neighborhood on the same parking lane and therefore it can be assumed that there is a measurement.

To close temporal gaps, interpolations were made by hour for each parking slot, assuming that between two consecutive observations with an occupancy the space was also occupied in between - or if both times free also free in between. If there was a change, this is indicated by a proportional value. To close spatial gaps, unobserved spaces in the area are drawn randomly from the ten closest occupation patterns around.

This results in an exemplary occupancy pattern of a synthetic day. Depending on the application, the value could be interpreted as occupancy probability or occupancy share.

https://data.uni-hannover.de/dataset/0945cd36-6797-44ac-a6bd-b7311f0f96bc/resource/184a1f75-79ab-4d0e-bb1b-8ed170678280/download/occupation_example.png" alt="Example parking area occupation pattern" title="Example parking area occupation pattern"> Figure 4: Example parking area occupation pattern

References

• F. Bock, D. Eggert and M. Sester (2015): On-street Parking Statistics Using LiDAR Mobile Mapping, 2015 IEEE 18th International Conference on Intelligent Transportation Systems, Gran Canaria, Spain, 2015, pp. 2812-2818. https://doi.org/10.1109/ITSC.2015.452
• A. Leichter, U. Feuerhake, and M. Sester (2021): Determination of Parking Space and its Concurrent Usage Over Time Using Semantically Segmented Mobile Mapping Data, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 185–192. https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-185-2021
• O. Wage, M. Heumann, and L. Bienzeisler (2023): Modeling and Calibration of Last-Mile Logistics to Study Smart-City Dynamic Space Management Scenarios. In 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility (SuMob ’23), November 13, 2023, Hamburg, Germany. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3615899.3627930

The Digital Geologic-GIS Map of Buffalo National River and Vicinity, Arkansas 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 (buff_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 (buff_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 (buff_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.) A GIS readme file (buff_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (buff_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 (buff_geology_metadata_faq.pdf). Please read the buff_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: Arkansas Geological Survey and U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (buff_geology_metadata.txt or buff_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).

Snapshot img

Geographic Information System Analytics Market Size 2024-2028

The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.

What will be the Size of the GIS Analytics Market during the forecast period?

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The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.

How is this Geographic Information System Analytics Industry segmented?

The geographic information system analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  Retail and Real Estate
  Government
  Utilities
  Telecom
  Manufacturing and Automotive
  Agriculture
  Construction
  Mining
  Transportation
  Healthcare
  Defense and Intelligence
  Energy
  Education and Research
  BFSI


Components

  Software
  Services


Deployment Modes

  On-Premises
  Cloud-Based


Applications

  Urban and Regional Planning
  Disaster Management
  Environmental Monitoring Asset Management
  Surveying and Mapping
  Location-Based Services
  Geospatial Business Intelligence
  Natural Resource Management


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    South Korea


  Middle East and Africa

    UAE


  South America

    Brazil


  Rest of World

By End-user Insights

The retail and real estate segment is estimated to witness significant growth during the forecast period.

The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector,

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.
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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

Xverum’s Global GIS & Geospatial Data is a high-precision dataset featuring 230M+ verified points of interest across 249 countries. With rich metadata, structured geographic attributes, and continuous updates, our dataset empowers businesses, researchers, and governments to extract location intelligence and conduct advanced geospatial analysis.

Perfectly suited for GIS systems, mapping tools, and location intelligence platforms, this dataset covers everything from businesses and landmarks to public infrastructure, all classified into over 5000 categories. Whether you're planning urban developments, analyzing territories, or building location-based products, our data delivers unmatched coverage and accuracy.

Key Features: ✅ 230M+ Global POIs Includes commercial, governmental, industrial, and service locations - updated regularly for accurate relevance.

✅ Comprehensive Geographic Coverage Worldwide dataset covering 249 countries, with attributes including latitude, longitude, city, country code, postal code, etc.

✅ Detailed Mapping Metadata Get structured address data, place names, categories, and location, which are ideal for map visualization and geospatial modeling.

✅ Bulk Delivery for GIS Platforms Available in .json - delivered via S3 Bucket or cloud storage for easy integration into ArcGIS, QGIS, Mapbox, and similar systems.

✅ Continuous Discovery & Refresh New POIs added and existing ones refreshed on a regular refresh cycle, ensuring reliable, up-to-date insights.

✅ Compliance & Scalability 100% compliant with global data regulations and scalable for enterprise use across mapping, urban planning, and retail analytics.

Use Cases: 📍 Location Intelligence & Market Analysis Identify high-density commercial zones, assess regional activity, and understand spatial relationships between locations.

🏙️ Urban Planning & Smart City Development Design infrastructure, zoning plans, and accessibility strategies using accurate location-based data.

🗺️ Mapping & Navigation Enrich digital maps with verified business listings, categories, and address-level geographic attributes.

📊 Retail Site Selection & Expansion Analyze proximity to key POIs for smarter retail or franchise placement.

📌 Risk & Catchment Area Assessment Evaluate location clusters for insurance, logistics, or regional outreach strategies.

Why Xverum? ✅ Global Coverage: One of the largest POI geospatial databases on the market ✅ Location Intelligence Ready: Built for GIS platforms and spatial analysis use ✅ Continuously Updated: New POIs discovered and refreshed regularly ✅ Enterprise-Friendly: Scalable, compliant, and customizable ✅ Flexible Delivery: Structured format for smooth data onboarding

Request a free sample and discover how Xverum’s geospatial data can power your mapping, planning, and spatial analysis projects.

The Digital Geologic-GIS Map of the Harriet Quadrangle, Arkansas 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 (hrrt_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (hrrt_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 (hrrt_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). 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.) A GIS readme file (buff_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (buff_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 (hrrt_geology_metadata_faq.pdf). Please read the buff_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. 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: Arkansas Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (hrrt_geology_metadata.txt or hrrt_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 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).

The Digital Geologic-GIS Map of the Marshall Quadrangle, Arkansas 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 (mrsh_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (mrsh_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 (mrsh_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). 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.) A GIS readme file (buff_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (buff_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 (mrsh_geology_metadata_faq.pdf). Please read the buff_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. 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: Arkansas Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (mrsh_geology_metadata.txt or mrsh_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 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).

Snapshot img

GIS Market Size 2025-2029

The GIS market size is forecast to increase by USD 24.07 billion, at a CAGR of 20.3% between 2024 and 2029.

The Global Geographic Information System (GIS) market is experiencing significant growth, driven by the increasing integration of Building Information Modeling (BIM) and GIS technologies. This convergence enables more effective spatial analysis and decision-making in various industries, particularly in soil and water management. However, the market faces challenges, including the lack of comprehensive planning and preparation leading to implementation failures of GIS solutions. Companies must address these challenges by investing in thorough project planning and collaboration between GIS and BIM teams to ensure successful implementation and maximize the potential benefits of these advanced technologies.
By focusing on strategic planning and effective implementation, organizations can capitalize on the opportunities presented by the growing adoption of GIS and BIM technologies, ultimately driving operational efficiency and innovation.

What will be the Size of the GIS 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

The global Geographic Information Systems (GIS) market continues to evolve, driven by the increasing demand for advanced spatial data analysis and management solutions. GIS technology is finding applications across various sectors, including natural resource management, urban planning, and infrastructure management. The integration of Bing Maps, terrain analysis, vector data, Lidar data, and Geographic Information Systems enables precise spatial data analysis and modeling. Hydrological modeling, spatial statistics, spatial indexing, and route optimization are essential components of GIS, providing valuable insights for sectors such as public safety, transportation planning, and precision agriculture. Location-based services and data visualization further enhance the utility of GIS, enabling real-time mapping and spatial analysis.

The ongoing development of OGC standards, spatial data infrastructure, and mapping APIs continues to expand the capabilities of GIS, making it an indispensable tool for managing and analyzing geospatial data. The continuous unfolding of market activities and evolving patterns in the market reflect the dynamic nature of this technology and its applications.

How is this GIS Industry segmented?

The GIS 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.

Product

  Software
  Data
  Services


Type

  Telematics and navigation
  Mapping
  Surveying
  Location-based services


Device

  Desktop
  Mobile


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  Middle East and Africa

    UAE


  APAC

    China
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Product Insights

The software segment is estimated to witness significant growth during the forecast period.

The Global Geographic Information System (GIS) market encompasses a range of applications and technologies, including raster data, urban planning, geospatial data, geocoding APIs, GIS services, routing APIs, aerial photography, satellite imagery, GIS software, geospatial analytics, public safety, field data collection, transportation planning, precision agriculture, OGC standards, location intelligence, remote sensing, asset management, network analysis, spatial analysis, infrastructure management, spatial data standards, disaster management, environmental monitoring, spatial modeling, coordinate systems, spatial overlay, real-time mapping, mapping APIs, spatial join, mapping applications, smart cities, spatial data infrastructure, map projections, spatial databases, natural resource management, Bing Maps, terrain analysis, vector data, Lidar data, and geographic information systems.

The software segment includes desktop, mobile, cloud, and server solutions. Open-source GIS software, with its industry-specific offerings, poses a challenge to the market, while the adoption of cloud-based GIS software represents an emerging trend. However, the lack of standardization and interoperability issues hinder the widespread adoption of cloud-based solutions. Applications in sectors like public safety, transportation planning, and precision agriculture are driving market growth. Additionally, advancements in technologies like remote sensing, spatial modeling, and real-time mapping are expanding the market's scope.

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The Software segment was valued at USD 5.06 billion in 2019

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Geographic Information System (GIS) Software Market Outlook

According to our latest research, the global Geographic Information System (GIS) Software market size reached USD 11.6 billion in 2024, reflecting a robust demand for spatial data analytics and location-based services across various industries. The market is experiencing a significant growth trajectory, driven by a CAGR of 12.4% from 2025 to 2033. By the end of 2033, the GIS Software market is forecasted to attain a value of USD 33.5 billion. This remarkable expansion is primarily attributed to the integration of advanced technologies such as artificial intelligence, IoT, and cloud computing, which are enhancing the capabilities and accessibility of GIS platforms.

One of the major growth factors propelling the GIS Software market is the increasing adoption of location-based services across urban planning, transportation, and utilities management. Governments and private organizations are leveraging GIS solutions to optimize infrastructure development, streamline resource allocation, and improve emergency response times. The proliferation of smart city initiatives worldwide has further fueled the demand for GIS tools, as urban planners and municipal authorities require accurate spatial data for effective decision-making. Additionally, the evolution of 3D GIS and real-time mapping technologies is enabling more sophisticated modeling and simulation, expanding the scope of GIS applications beyond traditional mapping to include predictive analytics and scenario planning.

Another significant driver for the GIS Software market is the rapid digitization of industries such as agriculture, mining, and oil & gas. Precision agriculture, for example, relies heavily on GIS platforms to monitor crop health, manage irrigation, and enhance yield forecasting. Similarly, the mining sector uses GIS for exploration, environmental impact assessment, and asset management. The integration of remote sensing data with GIS software is providing stakeholders with actionable insights, leading to higher efficiency and reduced operational risks. Furthermore, the growing emphasis on environmental sustainability and regulatory compliance is prompting organizations to invest in advanced GIS solutions for monitoring land use, tracking deforestation, and managing natural resources.

The expanding use of cloud-based GIS solutions is also a key factor driving market growth. Cloud deployment offers scalability, cost-effectiveness, and remote accessibility, making GIS tools more accessible to small and medium enterprises as well as large organizations. The cloud model supports real-time data sharing and collaboration, which is particularly valuable for disaster management and emergency response teams. As organizations increasingly prioritize digital transformation, the demand for cloud-native GIS platforms is expected to rise, supported by advancements in data security, interoperability, and integration with other enterprise systems.

Regionally, North America remains the largest market for GIS Software, accounting for a significant share of global revenues. This leadership is underpinned by substantial investments in smart infrastructure, advanced transportation systems, and environmental monitoring programs. The Asia Pacific region, however, is witnessing the fastest growth, driven by rapid urbanization, government-led digital initiatives, and the expansion of the utility and agriculture sectors. Europe continues to demonstrate steady adoption, particularly in environmental management and urban planning, while Latin America and the Middle East & Africa are emerging as promising markets due to increasing investments in infrastructure and resource management.

Component Analysis

The GIS Software market is segmented by component into Software and Services, each playing a pivotal role in the overall value chain. The software segment includes comprehensive GIS platforms, spatial analytics tools, and specialized applications

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3D Mapping And Modeling Market Size 2025-2029

The 3d mapping and modeling market size is forecast to increase by USD 35.78 billion, at a CAGR of 21.5% between 2024 and 2029.

The market is experiencing significant growth, driven primarily by the increasing adoption in smart cities and urban planning projects. This trend is attributed to the ability of 3D mapping and modeling technologies to provide accurate and detailed visualizations of complex urban environments, enabling more efficient planning and management. Another key driver is the emergence of digital twin technology, which allows for real-time monitoring and simulation of physical assets in a digital environment. However, the market also faces challenges, most notably privacy and security concerns. With the increasing use of 3D mapping and modeling in various applications, there is a growing risk of data breaches and unauthorized access to sensitive information. As such, companies must prioritize robust security measures to protect customer data and maintain trust. Additionally, the high cost of implementing and maintaining these technologies remains a barrier to entry for some organizations. Despite these challenges, the market's potential for innovation and growth is substantial, with opportunities for companies to capitalize on emerging trends and navigate challenges effectively.

What will be the Size of the 3D Mapping And Modeling Market during the forecast period?

Request Free SampleThe market continues to evolve, driven by advancements in spatial data acquisition, project management, and navigation systems. BIM software, artificial intelligence (AI), and 3D visualization services are increasingly integrated into infrastructure management, real estate development, and cultural heritage preservation. Image recognition and 3D scanning are revolutionizing asset management and virtual reality (VR) applications. In precision agriculture, AI development and machine learning enable object detection and scene understanding, while data analysis and processing facilitate more efficient crop management. Autonomous vehicles and remote sensing rely on 3D modeling software and point cloud processing for accurate environmental monitoring. Additive manufacturing and 3D printing services are transforming industries, from construction to healthcare, with advancements in 3D modeling software, materials, and processing techniques. Urban planning benefits from AI-driven data analytics and 3D model optimization for smarter city design. Deep learning and computer vision are enhancing object tracking and data visualization services, while software development and spatial analysis are improving facility management and location-based services. The ongoing integration of these technologies is shaping a dynamic and innovative market landscape.

How is this 3D Mapping And Modeling Industry segmented?

The 3d mapping and modeling 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. Product Type3D modeling3D mappingComponentSoftwareServicesGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth KoreaRest of World (ROW)

By Product Type Insights

The 3d modeling segment is estimated to witness significant growth during the forecast period.The 3D modeling market encompasses the creation of three-dimensional digital representations of objects, environments, and surfaces, finding extensive applications in industries such as architecture, gaming, film production, product design, and medical imaging. This technology's integration has revolutionized these sectors, fostering more precise and efficient design, planning, and analysis. Key technologies driving this market include computer-aided design (CAD) software, 3D scanning and rendering, simulation and animation tools, and geospatial data. CAD is a cornerstone technology in architecture, engineering, and manufacturing, enabling professionals to create intricate and accurate designs. 3D scanning and rendering technologies convert physical objects into digital models, crucial for industries where exact replicas are required. Artificial intelligence (AI) and machine learning algorithms are increasingly integrated into 3D modeling, enhancing object detection, computer vision, and data analysis capabilities. Virtual reality (VR) and augmented reality (AR) technologies are transforming 3D modeling by providing immersive experiences for design visualization, enabling better scene understanding and spatial analysis. Precision agriculture employs 3D modeling for terrain modeling and crop monitoring, while infrastructure management uses it for asset management and urban planning. 3D modeling is also instrumental in heritage preservation, environmental monitoring, and ad

Use the Reporter template to allow users to submit issues and observations about a specific area using a smart form. Reports are then added onto the map used in the app and can be viewed by other users. You can also enable commenting and voting to allow app users to provide feedback about existing reports. Reporter also includes a basic set of map exploration tools to help navigate the map and submitted reports. Examples: View and gain nonemergency requests, such as damaged infrastructure, graffiti, and clogged drains, from the public. Community members can like or dislike existing non-emergency reports if they encounter the same issue. Collect feedback on road construction projects by enabling comments. Collect health and safety reports from emergency management resources. Gather real estate locations for future development. Data requirements The Reporter template requires a web map with at least one editable feature layer. Key app capabilities Edit tools - Add and update features in editable layers. Bookmarks - Allow users to zoom and pan to a collection of preset extents that are saved in the map. Enable commenting - Track feedback on existing reports. Enable voting - Track votes on reports using likes and dislikes. Language switcher - Provide translations for custom text and create a multilingual app. Home, Zoom controls, Legend, Layer List, Search Supportability This web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

SMART (a Simple Modular Architecture Research Tool) allows the identification and annotation of genetically mobile domains and the analysis of domain architectures. SMART is based at EMBL, Heidelberg, Germany.

This data was collected by Google and Dublin City Council as part of Project Air View Dublin. Google's first electric Street View car equipped with Aclima’s mobile air sensing platform drove through the roads of Dublin City measuring street by street air quality. Driving predominantly took place Monday–Friday between 9:00 am and 5:00 pm from May 2021 through August 2022, so the dataset primarily represents typical daytime, weekday air quality. The car measured pollution on each street and highway at 1-second intervals, driving with the flow of traffic at normal speeds. The pollutants determined are: Carbon Monoxide(CO), Carbon Dioxide(CO2), Nitrogen Dioxide (NO2), NO (nitric oxide), Ozone (O3), and Particulate Matter PM2.5 (including size resolved particle counts from 0.3 - 2.5 μm). Airview_DublinCity_Measurements is the 1-second intervals data captured during the period. AirView_Dublin_City_RoadData is the 1-second data points aggregated in approximately 50m road segments. For more information about the project, methodology and maps, visit Google EIE Labs. Citing this data: Feel free to include the data in other analysis, materials, reports, and communications with the following data attribution: Aclima & Google 2022 via Dublinked

The CGIAR-CSI GeoPortal is able to provide SRTM 90m Digital Elevation Data for the entire world. The SRTM digital elevation data, produced by NASA originally, is a major breakthrough in digital mapping of the world, and provides a major advance in the accessibility of high quality elevation data for large portions of the tropics and other areas of the developing world. The SRTM digital elevation data provided on this site has been processed to fill data voids, and to facilitate it's ease of use by a wide group of potential users. This data is provided in an effort to promote the use of geospatial science and applications for sustainable development and resource conservation in the developing world. Digital elevation models (DEM) for the entire globe, covering all of the countries of the world, are available for download on this site. The SRTM 90m DEM's have a resolution of 90m at the equator, and are provided in mosaiced 5 deg x 5 deg tiles for easy download and use. All are produced from a seamless dataset to allow easy mosaicing. These are available in both ArcInfo ASCII and GeoTiff format to facilitate their ease of use in a variety of image processing and GIS applications. Data can be downloaded using a browser or accessed directly from the ftp site.

Dasymetric mapping is a technique used to improve the accuracy of population mapping. In the United States, census data is widely used to analyze the spatial distribution of socio-economic factors. For instance, the American Community Survey (ACS, available at https://www.census.gov/programs-surveys/acs) compiles crucial socio-economic data at the census tract level. While census boundaries cover entire states, the population is not evenly distributed but tends to concentrate in residential areas. Dasymetric mapping, in combination with other datasets like land use and land cover, enhances the precision of mapping results.This notebook applies two python packages including:Tobler, a geostatistic pytho package based on PySAL: https://github.com/pysal/tobler.The EnviroAtlas Intelligent Dasymetric Toolbox by the EPA: https://github.com/USEPA/Dasymetric-Toolbox-OpenSource/tree/masterFor more information about dasymetric mapping, see this publication by Baynes, Neale, and Hultgren (2022).Data used:Open Street Map's residential zonesU.S. 2020 Decennial Census at the census block levelNational Land Cover Dataset (NLCD) from 2019 (indexed in the Virginia Data Cube).Data was called and processed in the Virginia Data Cube: https://datacube.vmasc.org/Funding: This work was made possible by the NASA AIST-21-0031 program, grant number 80NSSC22K1407.Data Description for each layer:Open Street Map (OSM) Residential is a free layer provided by the Open Street Map community that are polygons. AIST_regionCensus are census block polygons from the 2020 deciennial US census clipped to the study region. AIST Census - Clipped to OSM are census block polygons that are clipped to the OSM residential area polygons. Tobler_MAI_totPop are hexagons representing total population through the MAI Tobler function. Tobler_MAI_medFrag are hexagons representing total number of medically fragile population through the MAI Tobler function. Tobler_AI_totPop are hexagons representing total population through the AI Tobler function. Tobler_AI_medFrag are hexagons representing total number of medically fragile population through the AI Tobler function. EPA_totPop are hexagons representing total population through the EPA's IDM open source tool without using an uninhabited mask. EPA_medFrag are hexagons representing total medically fragile population through the EPA's IDM open source tool without using an uninhabited mask. Please note the above data with EPA as a prefix does not represent EPA approved products. The EPA's EnviroAtlas has their own dasymetric output. You may find Jupyter Notebooks that show how to gather this data, powered by the Virginia Datacube, here: https://github.com/ODU-GeoSEA/va-datacube

Bolton & Menk, an engineering planning and consulting firm from the Midwestern United States has released a series of illustrated children’s books as a way of helping young people discover several different professions that typically do not get as much attention as other more traditional ones do.Topics of the award winning book series include landscape architecture, civil engineering, water resource engineering, urban planning and now Geographic Information Systems (GIS). The books are available free online in digital format, and easily accessed via a laptop, smart phone or tablet.The book Lindsey the GIS Specialist – A GIS Mapping Story Tyler Danielson, covers some the basics of what geographic information is and the type of work that a GIS Specialist does. It explains what the acronym GIS means, the different types of geospatial data, how we collect data, and what some of the maps a GIS Specialist creates would be used for.Click here to check out the GIS Specialist – A GIS Mapping Story e-book

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Car GPS Navigation System Market Size 2024-2028

The car GPS navigation system market size is forecast to increase by USD 9.75 billion at a CAGR of 10.03% between 2023 and 2028.

The market is experiencing significant growth due to the advancements In the automotive industry. With the increasing demand for connected and autonomous vehicles, the integration of GPS navigation systems is becoming essential. Furthermore, the investment in satellite deployment is driving market growth, enabling real-time traffic updates and accurate location tracking.
However, design complexity and technological challenges pose significant hurdles to market growth. Manufacturers must balance the need for advanced features with affordability and user-friendliness to meet consumer demands. Incorporating voice recognition and augmented reality technologies can enhance the user experience and differentiate offerings in a competitive market. Overall, the market is expected to witness steady growth In the coming years, driven by technological advancements and evolving consumer preferences.

What will be the Car GPS Navigation System Market Size During the Forecast Period?

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The market is experiencing significant growth due to the increasing demand for advanced in-vehicle technology. These electronic devices, which integrate GPS receivers, computer mapping tools, voice recognition, and real-time traffic updates, have become essential navigation tools for drivers. The integration of voice instructions and satellite link enables hands-free use, enhancing safety while reducing driver distraction. Moreover, the addition of automobile safety features such as emergency assistance and accurate location tracking further bolsters the market's appeal. The integration of banks, gas stations, hospitals, restaurants, and other points of interest into the system enhances convenience for users.
Moreover, ride-hailing services and environmental concerns, including vehicle emissions, are also driving the market's growth. Navigation system gadgets are increasingly being integrated into dashboards, with driver alarms and vehicle tracking capabilities becoming standard features. The market is expected to continue growing as technology advances and consumer demand for real-time traffic information and improved driving experiences increases.

How is this Car GPS Navigation System Industry segmented and which is the largest segment?

The car GPS navigation system industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Component

  Software and services
  Hardware


Geography

  Europe

    Germany
    France


  North America

    US


  APAC

    China
    Japan


  Middle East and Africa



  South America

By Component Insights

The software and services segment is estimated to witness significant growth during the forecast period.

Car GPS navigation systems utilize GPS satellites and cellular networks to pinpoint the location and direction of vehicles or assets. TomTom's cloud-native automotive solution offers fast routing, search, and maps, even without an internet connection. Voice assistance technology is increasingly integrated into navigation systems, enhancing user experience and minimizing distractions. Up-to-date maps, lane assistance, traffic congestion alerts, and speed limit warnings are essential safety features. IoT and cloud services ensure map accuracy and real-time traffic updates. User-friendly interfaces and smart connected cars offer integrated navigation solutions, while safety features like warning signals, sirens, and lights provide additional security. GPS data and natural language processing enable efficient and convenient navigation.

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The software and services segment was valued at USD 7.66 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

APAC is estimated to contribute 32% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The European automotive industry, home to major manufacturers like Volkswagen, BMW, AUDI AG (Audi), and Ford Motor Co., is witnessing significant investment In the production of commercial, electric, and hybrid vehicles. In line with this trend, Ford announced a USD180 million expansion to boost EV power unit production by 70% at its northern England engine facility. Similarly, BMW unveiled plans to invest approximately USD300 milli

Iowa Department of Transportation's Intelligent Transportation System (ITS) CCTV Cameras. Includes location of cameras, static image URL, and motion video URL where available. This data gets updated once a day.