The Geospatial Fabric is a dataset of spatial modeling units for use within the National Hydrologic Model that covers the conterminous United States (CONUS), Alaska, and most major river basins that flow in from Canada. This U.S. Geological Survey (USGS) data release consists of the geospatial fabric features and other related datasets created to expand the National Hydrologic Model to Hawaii. This page contains data and information related to the GIS features of the Geospaital Fabric for National Hydrologic Model, Hawaii domain. An Open Geospatial Consortium geopackage (GF_20.gpkg) contains 4 feature layers (layer names in parentheses): points of interest (poi), a stream network (nsegment), aggregated catchments (catchment), and hydrologic repsonse units (nhru). Features were derived from NHDPlus, version 2.0, and several hydroclimatic datasets representing domain-specific processes and key drainage basins within the Hawaii. All data cover the National Hydrologic Model's (NHM) Hawaiin domain. The NHM is a modeling infrastructure consisting of three main parts: 1) an underlying geospatial fabric of modeling units (hydrologic response units and stream segments) with an associated parameter database, 2) a model input data archive, and 3) a repository of the physical model simulation code bases (Regan and others, 2014). The pois represent hydro locations and points on the network. Segments are connected by the pois and are used to route streamflow and characterize upstream watershed conditions. The HRUs represent the spatial modeling units at which most of the physical processes (such as precipitation, runoff, evapotranspiration, and infiltration) are simulated. Some HRUs are connected to a corresponding segment, and may represent left and right-bank areas of each stream segment. See Regan and others (2018) and entities and attributes for more information.

The Geopspatial Fabric provides a consistent, documented, and topologically connected set of spatial features that create an abstracted stream/basin network of features useful for hydrologic modeling.The GIS vector features contained in this Geospatial Fabric (GF) data set cover the lower 48 U.S. states, Hawaii, and Puerto Rico. Four GIS feature classes are provided for each Region: 1) the Region outline ("one"), 2) Points of Interest ("POIs"), 3) a routing network ("nsegment"), and 4) Hydrologic Response Units ("nhru"). A graphic showing the boundaries for all Regions is provided at http://dx.doi.org/doi:10.5066/F7542KMD. These Regions are identical to those used to organize the NHDPlus v.1 dataset (US EPA and US Geological Survey, 2005). Although the GF Feature data set has been derived from NHDPlus v.1, it is an entirely new data set that has been designed to generically support regional and national scale applications of hydrologic models. Definition of each type of feature c ...

The Geospatial Fabric version 1.1 (GFv1.1 or v1_1) is a dataset of spatial modeling units covering the conterminous United States (CONUS) and most major river basins that flow in from Canada. The GFv1.1 is an update to the original Geospatial Fabric (GFv1, Viger and Bock, 2014) for the National Hydrologic Modeling (NHM). Analogous to the GFv1, the GFv1.1 described here includes the following vector feature classes: points of interest (POIs_v1_1), a stream network (nsegment_v1_1), and hydrologic response units (nhru_v1_1), with several additional ancillary tables. These data are contained within the Environmental Systems Research Institute (ESRI) geodatabase format (GFv1.1.gdb).

The Spatial Analysis Software market is experiencing robust growth, driven by the increasing adoption of cloud-based solutions, the expanding use of drones and other data acquisition technologies for precise geographic data collection, and the rising demand for advanced analytics across diverse sectors. The market's expansion is fueled by the need for efficient geospatial data processing and interpretation in applications such as urban planning, infrastructure development, environmental monitoring, and precision agriculture. Key trends include the integration of Artificial Intelligence (AI) and Machine Learning (ML) for automating analysis and improving accuracy, the proliferation of readily available satellite imagery and sensor data, and the growing adoption of 3D modeling and visualization techniques. While data security concerns and the high initial investment costs for advanced software solutions pose some restraints, the overall market outlook remains positive, with a projected compound annual growth rate (CAGR) exceeding 10% (a reasonable estimate based on the rapid technological advancements and market penetration observed in related sectors). This growth is expected to be particularly strong in the North American and Asia-Pacific regions, driven by substantial government investments in infrastructure projects and burgeoning private sector adoption. The segmentation by application (architecture, engineering, and other sectors) reflects the versatility of spatial analysis software, enabling its use across various industries. Similarly, the choice between cloud-based and locally deployed solutions caters to specific organizational needs and technical capabilities. The competitive landscape is characterized by both established players and emerging technology companies, showcasing the dynamic nature of the market. Major players like Autodesk, Bentley Systems, and Trimble are leveraging their existing portfolios to integrate advanced spatial analysis capabilities, while smaller companies are focusing on niche applications and innovative analytical techniques. The ongoing advancements in both hardware and software, coupled with increasing data availability and affordability, are set to further fuel the market's growth in the coming years. The historical period (2019-2024) likely witnessed moderate growth as the market matured, laying the foundation for the accelerated expansion expected during the forecast period (2025-2033). Continued innovation and industry convergence will be key drivers shaping the future trajectory of the Spatial Analysis Software market.

AI in Geospatial Analytics Market Outlook

According to our latest research, the AI in Geospatial Analytics market size reached USD 9.2 billion in 2024 globally, driven by the increasing adoption of artificial intelligence to analyze and interpret geospatial data across various industries. The market is expected to grow at a robust CAGR of 19.8% from 2025 to 2033, reaching a projected value of USD 41.7 billion by 2033. This remarkable growth is underpinned by the rising need for real-time location-based insights, advancements in AI algorithms, and the proliferation of high-resolution satellite imagery and IoT devices. As per our latest research, the integration of AI with geospatial analytics is transforming decision-making processes in sectors such as urban planning, agriculture, defense, and environmental monitoring.

One of the most significant growth factors for the AI in Geospatial Analytics market is the exponential increase in the volume and variety of geospatial data generated from satellites, drones, and IoT sensors. Organizations are leveraging AI-driven geospatial analytics to efficiently process and analyze these massive datasets, extracting actionable insights that drive operational efficiency and strategic planning. The capability of AI to automate feature extraction, pattern recognition, and predictive modeling has enabled businesses and government agencies to make faster and more informed decisions. Furthermore, the integration of machine learning and deep learning techniques with geospatial data is enabling the development of sophisticated models for land-use classification, disaster response, and urban infrastructure management.

Another key driver is the growing demand for real-time geospatial intelligence across critical applications such as disaster management, transportation, and security. AI-powered geospatial analytics platforms are enabling authorities to monitor and respond to natural disasters, optimize logistics routes, and enhance situational awareness in defense operations. The ability to analyze spatial data in real time is proving invaluable for emergency response teams, urban planners, and logistics providers, who require up-to-date information to make timely decisions. Additionally, the increasing use of AI in monitoring environmental changes, such as deforestation and climate change, is supporting sustainability initiatives and regulatory compliance.

The rapid advancements in cloud computing and edge AI are also contributing to the growth of the AI in Geospatial Analytics market. Cloud-based geospatial analytics solutions offer scalable processing power and storage, enabling organizations to handle large-scale spatial datasets without significant infrastructure investments. Edge AI, on the other hand, facilitates real-time analytics at the source of data generation, reducing latency and bandwidth requirements. The convergence of AI, cloud, and geospatial technologies is fostering new business models and service offerings, making advanced geospatial analytics accessible to a broader range of industries, including agriculture, utilities, and BFSI.

From a regional perspective, North America currently leads the AI in Geospatial Analytics market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The presence of major technology providers, strong government initiatives, and early adoption of AI-driven geospatial solutions are driving market growth in these regions. Asia Pacific is expected to witness the highest growth rate during the forecast period, fueled by rapid urbanization, infrastructure development, and increasing investments in smart city projects. Meanwhile, Latin America and the Middle East & Africa are gradually embracing AI-powered geospatial analytics, particularly in sectors such as agriculture, oil & gas, and disaster management, albeit at a slower pace due to infrastructural and regulatory challenges.

Component Analysis

The AI in Geospatial Analytics market by component is segmented into software, hardware, and services, each playing a vital role in the overall ecosystem. Software forms the backbone of geospatial analytics, encompassing platforms and tools that leverage AI algorithms for spatial data processing, visualization, and predictive modeling. The software segment is witnessing rapid innovation, with vendors introducing user-friendly interfaces, automated feature extraction capabilities, and integration with GIS and remote sensing platforms. Cloud-based software solutions are gaining

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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

This metadata record documents a set of 116 comma delimited files and a data dictionary describing the inputs for the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS) which is used to drive the National Hydrologic Model (NHM) for the Hawaiian domain. The National Hydrologic Model database contains parameters for hydrologic response units (HRUs) and stream segments needed to run the NHM. These parameters are generated using python scripts to process input datasets such as digital elevation models, soil maps, and land cover classifications. Many of the parameters were left at their default model value as they would need to be calibrated as part of the PRMS model development process. Please refer to the Supplemental Information and the Process Description elements of this metadata record for more details on the source datasets and scripts used to generate these parameters.

The Geospatial Fabric for National Hydrologic Modeling (Viger and Bock, 2014; Bock and others, 2020) is a dataset of hydrographic features and spatial data designed for use within the National Hydrologic Model that covers the conterminous United States (CONUS), Hawaii, and most major river basins that flow in from Canada. This U.S. Geological Survey (USGS) data release consists of the geospatial fabric features and other related spatial datasets created to expand the National Hydrologic Model to Alaska. This child item contains data and information related to the GIS features of the Geospatial Fabric for National Hydrologic Model, Alaska domain. Two Open Geospatial Consortium geopackages are provided: one containing source layers that have had some pre-processing done from their native data formats (Reference_19.gpkg), and one (NHM_19.gpkg) containing 4 final feature layers for the NHM: points of interest (pois), a stream network (nsegment), aggregated catchments (catchments), an ...

The geospatial data analytics market, currently valued at $86.39 billion in 2025, is projected to experience robust growth, driven by a compound annual growth rate (CAGR) of 12.81% from 2025 to 2033. This expansion is fueled by several key factors. Increasing reliance on location intelligence across diverse sectors like agriculture (precision farming), utilities (network optimization), defense (surveillance and intelligence), and government (urban planning and resource management) is a major catalyst. Advances in technologies such as AI, machine learning, and cloud computing are enhancing the analytical capabilities of geospatial data, leading to more accurate insights and predictive modeling. Furthermore, the growing availability of high-resolution satellite imagery and sensor data is significantly expanding the data pool for analysis, contributing to market growth. The market is segmented by type (surface analysis, network analysis, geovisualization analysis) and end-user vertical, each contributing uniquely to the overall market value. Competition is fierce, with established players like ESRI, Hexagon AB, and Trimble Inc. alongside emerging technology companies vying for market share. The market's geographic distribution is expected to reflect global technological adoption rates and economic activity. North America and Europe currently hold significant market shares, but the Asia-Pacific region is projected to witness substantial growth due to increasing investments in infrastructure and technological advancements. Government initiatives promoting the use of geospatial technology in various sectors are further bolstering market expansion in developing economies. While data privacy concerns and the need for skilled professionals represent challenges, the overall market outlook remains strongly positive, underpinned by the continuous increase in data generation, sophisticated analytical tools, and the widespread acceptance of location-based services across numerous industries. The forecast period (2025-2033) anticipates a continued trajectory of expansion, with significant market penetration across a wider range of applications. Recent developments include: June 2023: Intermap Technologies leveraged its high-resolution elevation data access to perform imagery correction services for a national government organization to support the development projects in El Salvador and Honduras in Central America. In partnership with GeoSolutions, Intermap enables the creation of precision maps that are invaluable resources in supporting community safety and resiliency., March 2023: Mach9, the company building the fastest technologies for geospatial production, introduced its first product. The new product leverages computer vision and AI to produce faster 2D and 3D CAD and GIS engineering deliverables. This product launch comes amidst Mach9's pivot to a software-first business model, which is a move that is primarily driven by the rising demand for tools that accelerate geospatial data processing and analysis for infrastructure management.. Key drivers for this market are: Increase in Adoption of Smart City Development, Introduction of 5G to Boost Market Growth. Potential restraints include: Increase in Adoption of Smart City Development, Introduction of 5G to Boost Market Growth. Notable trends are: Defense and Intelligence to be the Largest End-user Industry.

3D Geospatial Technologies Market Outlook

The global market size of 3D Geospatial Technologies was valued at approximately USD 17.5 billion in 2023 and is projected to reach around USD 40.3 billion by 2032, growing at a CAGR of 9.6% from 2024 to 2032. This substantial growth is driven by the increasing adoption of advanced geospatial solutions across various industries, the rise in smart city initiatives, and the increasing need for efficient and accurate geographical data.

The growth of the 3D geospatial technologies market is significantly influenced by the rising need for advanced mapping and modeling solutions in urban planning and infrastructure development. With rapid urbanization and the expansion of smart city projects, there is a growing demand for precise and detailed geographical data to support efficient planning and management. The integration of 3D geospatial technologies enables city planners and developers to visualize, analyze, and manage urban spaces more effectively, leading to better decision-making and optimized resource utilization. Furthermore, the deployment of these technologies in monitoring and managing utilities, traffic, and environmental assets further fuels market growth.

Another critical factor driving the market is the increasing utilization of 3D geospatial technologies in disaster management and emergency response. Natural disasters such as floods, earthquakes, and hurricanes have highlighted the importance of having accurate and real-time geographical information for effective disaster mitigation and response strategies. 3D geospatial technologies provide detailed topographical data and real-time visualization capabilities, enabling authorities to better predict, prepare for, and respond to natural calamities. The ability to model and simulate disaster scenarios helps in developing robust contingency plans and minimizing the impact on affected populations and infrastructure.

The transportation sector is also significantly benefiting from advancements in 3D geospatial technologies. These technologies are being extensively utilized in the design, construction, and maintenance of transportation infrastructure, including roads, bridges, railways, and airports. The application of 3D geospatial solutions in transportation helps in accurate route planning, traffic management, and infrastructure monitoring, leading to enhanced safety, reduced operational costs, and improved travel experiences. Additionally, autonomous vehicles and drones rely heavily on 3D geospatial data for navigation and obstacle detection, further driving the demand for these technologies in the transportation industry.

3D Mapping and Modeling in Mapping have become indispensable tools in the realm of urban planning and infrastructure development. These technologies allow for the creation of highly detailed and interactive models of urban environments, which are crucial for visualizing potential developments and assessing their impacts on existing structures and communities. By employing 3D mapping and modeling, city planners can simulate various scenarios, optimize land use, and ensure sustainable development practices. This approach not only aids in efficient resource allocation but also enhances public engagement by providing stakeholders with a clear and comprehensive view of proposed projects. As cities continue to grow and evolve, the role of 3D mapping and modeling in mapping becomes increasingly vital in shaping the urban landscapes of the future.

On a regional scale, North America currently holds the largest share of the 3D geospatial technologies market, driven by the presence of major technology companies, extensive research and development activities, and significant government funding for geospatial projects. Asia Pacific is expected to witness the highest growth rate during the forecast period, fueled by rapid urbanization, increasing infrastructure investments, and growing adoption of advanced technologies in countries such as China, India, and Japan. The European market is also experiencing substantial growth due to the rising demand for geospatial solutions in environmental monitoring, urban planning, and transportation sectors.

Component Analysis

Hardware Analysis

The hardware segment of the 3D geospatial technologies market includes various devices and equipment required for data collection, processing, and visualization. This segment encompasses a wide range of pro

Geospatial Analytics Market is Segmented by Component (Software, Services, and Hardware), Analysis Type (Surface Analysis, Network Analysis, and More), Deployment Model (On-Premises and Cloud), End-User Vertical (Government, Defense and Intelligence and More), and by Geography. The Market Forecasts are Provided in Terms of Value (USD).

The statistic displays the level of adoption of various revenue models offered within the geospatial industry, from 2012 to 2020. By 2016, the popularity of the distributor revenue model had fallen, with ** percent of companies offering this within their product portfolio, while the as-a-Service model was increasing in popularity with ** percent of geospatial technology firms making use of this revenue model.

The geospatial data fusion market is experiencing robust growth, driven by increasing demand for location-based intelligence across diverse sectors. The convergence of various data sources, including satellite imagery, sensor data, and geographic information systems (GIS), is fueling the adoption of advanced geospatial analytics. This market is segmented by delivery model (SaaS, PaaS) and application (earth observation, computer vision, military & security, and others). The SaaS model currently holds a significant market share due to its scalability and accessibility, while the demand for earth observation and computer vision applications is rapidly expanding, propelled by advancements in AI and machine learning. Government initiatives focused on national security and infrastructure development are further boosting market growth. North America and Europe currently dominate the market, but the Asia-Pacific region is projected to witness the fastest growth in the coming years due to rising investments in infrastructure and technological advancements. Competitive dynamics are characterized by a mix of established GIS vendors and specialized geospatial data fusion companies. Future growth will be influenced by factors such as increased data volumes, technological advancements in data processing and analytics, and ongoing investments in research and development. While precise figures are not provided, assuming a moderate CAGR (let's estimate at 15% for illustrative purposes), and a 2025 market size of $5 billion (a reasonable estimate considering the mentioned companies and applications), the market is poised for significant expansion. The restraints on market growth are likely associated with high initial investment costs for implementation, the need for skilled professionals to interpret the fused data, and concerns regarding data security and privacy. However, these challenges are gradually being addressed through the development of user-friendly software and robust data security protocols. The market's trajectory suggests a continuous upward trend, with growth significantly influenced by the adoption of innovative geospatial technologies and increased government and private sector investment.

This U.S. Geological Survey data release consists multiple datasets used to simulate the extents of flood inundation along the Muddy River, near Moapa, Nevada. Flood-inundation extents equal the maximum area of flood inundation and were estimated using a coupled one-dimensional (1D) and two-dimensional (2D) hydraulic model. The modeled extents represent six annual exceedance probabilities simulated for the current (2019) levee location adjacent to the Muddy River and a new levee location associated with a proposed restoration of a selected reach along the Muddy River. The data release includes: 1) a polygon dataset of the flood-inundation extents (MuddyRiver_Flood_Inundation_p.shp); 2) a zip file containing all relevant files to document and run the PeakFQ flood-frequency analysis used as input into the hydraulic model (0941600_Flood_Frequency_Archive.zip); 3) a zip file containing all relevant files to document and run the coupled 1D and 2D Hydrological Engineering Center-River Analysis System (HEC-RAS) hydraulic model used to generate a polygon dataset of flood-inundation extents (SWmodel_Archive.zip); 4) a polygon dataset of the current and proposed levee locations (MuddyRiver_Levee_p.shp); 5) a point dataset of survey points (RTK-TS_survey_x.shp) collected from April 1 to August 9, 2019, using real-time kinematic global navigation satellite system (GNSS) and total station (TS); and 6) a point dataset of seven static reference locations (Static_GNSS_x.shp) collected from March 29 to August 9, 2019, using a single-baseline online positioning user service – static (OPUS-S) GNSS survey.

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,

Geospatial Dataset

## Overview

Geospatial Dataset is a dataset for instance segmentation tasks - it contains Geospatial annotations for 1,048 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles.

For four of the map units – 3-SDF, 4-SDAF, 27-POHV, and 31-LBY – modeling using GIS principles was also employed. Modeling involves using environmental conditions of a map unit, such as elevation, slope, and aspect, which were determined by the field-collected ecological data. Data satisfying these conditions were obtained from ancillary data sources, such as USGS DEM data. These data were fed into a model that will result in locations (pixels) where all the desired conditions exist. For example, if a certain map unit was a shrubland that predominantly occurs above 8000 feet, on slopes of 3-10%, and on west-facing aspects, the correctly-constructed model will output only locations where this combination of conditions will be found. The resulting areas were then examined manually with the traditional photo interpretation process to confirm that they indeed could be accepted as that map unit. If photo interpretation determines that the areas were not acceptable, then they were changed to a more appropriate map unit.

AI in Geospatial Market is estimated to reach USD 1,165.3 Million by 2033, Riding on a Strong 31 CAGR throughout the forecast period.

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 size of the Geospatial Data Analytics market was valued at USD XXX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 12.81% during the forecast period.Geospatial data analytics is all about collecting data, analyzing and interpreting data tied to a geographical location. Its sources include information from GPS-enabled devices, satellites, remote sensing and social media sources. The analysis made possible by it helps businesses gain valuable insights from patterns, trends, and connections that would have otherwise been indistinguishable. Using the information to decide on everything from urban planning and resource management to marketing and logistics will be very possible. There are various reasons why the market for geospatial data analytics is highly driven by increased availability of data, technological advances, and increased business needs for data-driven decision-making. Recent developments include: June 2023: Intermap Technologies leveraged its high-resolution elevation data access to perform imagery correction services for a national government organization to support the development projects in El Salvador and Honduras in Central America. In partnership with GeoSolutions, Intermap enables the creation of precision maps that are invaluable resources in supporting community safety and resiliency., March 2023: Mach9, the company building the fastest technologies for geospatial production, introduced its first product. The new product leverages computer vision and AI to produce faster 2D and 3D CAD and GIS engineering deliverables. This product launch comes amidst Mach9's pivot to a software-first business model, which is a move that is primarily driven by the rising demand for tools that accelerate geospatial data processing and analysis for infrastructure management.. Key drivers for this market are: Increase in Adoption of Smart City Development, Introduction of 5G to Boost Market Growth. Potential restraints include: Strict government regulations, High-resolution Images Offered by Other Imaging Technologies. Notable trends are: Defense and Intelligence to be the Largest End-user Industry.