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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, gover

The GIS Analytics market is booming, projected to reach $2979.7 million by 2025, with a 5.6% CAGR. Discover key drivers, trends, and restraints shaping this dynamic industry, including cloud adoption, location intelligence, and AI integration. Leading companies and regional market analysis are included.

Literature review dataset

This table lists the surveyed papers concerning the application of spatial analysis, GIS (Geographic Information Systems) as well as general geographic approaches and geostatistics, to the assessment of CoViD-19 dynamics. The period of survey is from January 1^st, 2020 to December 15^th, 2020. The first column lists the reference. The second lists the date of publication (preferably, the date of online publication). The third column lists the Country or the Countries and/or the subnational entities investigated. The fourth column lists the epidemiological data utilized in each paper. The fifth column lists other types of data utilized for the analysis. The sixth column lists the more traditionally statistically-based methods, if utilized. The seventh column lists the geo-statistical, GIS or geographic methods, if utilized. The eight column sums up the findings of each paper. The papers are also classified within seven thematic categories. The full references are available at the end of the table in alphabetical order.

This table was the basis for the realization of a comprehensive geographic literature review. It aims to be a useful tool to ease the "due-diligence" activity of all the researchers interested in the spatial analysis of the pandemic.

The reference to cite the related paper is the following:

Pranzo, A.M.R., Dai Prà, E. & Besana, A. Epidemiological geography at work: An exploratory review about the overall findings of spatial analysis applied to the study of CoViD-19 propagation along the first pandemic year. GeoJournal (2022). https://doi.org/10.1007/s10708-022-10601-y

To read the manuscript please follow this link: https://doi.org/10.1007/s10708-022-10601-y

Online Appendix for A GIS Analysis of Coastal Proximity with a Prehistoric Greek Case Study, in the Journal of Computer Applications in Archaeology, 7(1): 170–184. DOI: https://doi.org/10.5334/jcaa.143

Contained in this dataset is the appendix with the results of the analyses, as well as the DEM and Cost-surface files and three .csv files which contain the Geospatial data for each of the sites mentioned in-text. It is then possible for those interested to reproduce this analysis using the steps outlined in the original article. Also included are the results of the analyses in the form of .csv files for an alternative data source in addition to the PDF file.

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

Geotagged Twitter posts dataset

Dataset used for the research presented in the following paper: Takayuki Hiraoka, Takashi Kirimura, Naoya Fujiwara (2024) "Geospatial analysis of toponyms in geo-tagged social media posts".

We collected georeferenced Twitter posts tagged to coordinates inside the bounding box of Japan between 2012-2018. The present dataset represents the spatial distributions of all geotagged posts as well as posts containing in the text each of 24 domestic toponyms, 12 common nouns, and 6 foreign toponyms. The code used to analyze the data is available on GitHub.

Data description

• selected_geotagged_tweet_data/: Number of geotagged twitter posts in each grid cell. Each csv file under this directory associates each grid cell (spanning 30 seconds of latitude and 45 secoonds of longitude, which is approximately a 1km x 1km square, specified by an 8 digit code m3code) with the number of geotagged tweets tagged to the coordinates inside that cell (tweetcount). file_names.json relates each of the toponyms studied in this work to the corresponding datafile (all denotes the full data).
• population/population_center_2020.xlsx: Center of population of each municipality based on the 2020 census. Derived from data published by the Statistics Bureau of Japan on their website (Japanese)
• population/census2015mesh3_totalpop_setai.csv: Resident population in each grid cell based on the 2015 census. Derived from data published by the Statistics Bureau of Japan on e-stat (Japanese)
• population/economiccensus2016mesh3_jigyosyo_jugyosya.csv: Employed population in each grid cell based on the 2016 Economic Census. Derived from data published by the Statistics Bureau of Japan on e-stat (Japanese)
• japan_MetropolitanEmploymentArea2015map/: Shape file for the boundaries of Metropolitan Employment Areas (MEA) in Japan. See this website for details of MEA.
• ward_shapefiles/: Shape files for the boundaries of wards in large cities, published by the Statistics Bureau of Japan on e-stat

GIS project files and imagery data required to complete the Introduction to Planetary Image Analysis and Geologic Mapping in ArcGIS Pro tutorial. These data cover the area in and around Jezero crater, Mars.

Geographic Information System (GIS) Software Market Outlook

The global Geographic Information System (GIS) software market size is projected to grow from USD 9.1 billion in 2023 to USD 18.5 billion by 2032, reflecting a compound annual growth rate (CAGR) of 8.5% over the forecast period. This growth is driven by the increasing application of GIS software across various sectors such as agriculture, construction, transportation, and utilities, along with the rising demand for location-based services and advanced mapping solutions.

One of the primary growth factors for the GIS software market is the widespread adoption of spatial data by various industries to enhance operational efficiency. In agriculture, for instance, GIS software plays a crucial role in precision farming by aiding in crop monitoring, soil analysis, and resource management, thereby optimizing yield and reducing costs. In the construction sector, GIS software is utilized for site selection, design and planning, and infrastructure management, making project execution more efficient and cost-effective.

Additionally, the integration of GIS with emerging technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) is significantly enhancing the capabilities of GIS software. AI-driven data analytics and IoT-enabled sensors provide real-time data, which, when combined with spatial data, results in more accurate and actionable insights. This integration is particularly beneficial in fields like smart city planning, disaster management, and environmental monitoring, further propelling the market growth.

Another significant factor contributing to the market expansion is the increasing government initiatives and investments aimed at improving geospatial infrastructure. Governments worldwide are recognizing the importance of GIS in policy-making, urban planning, and public safety, leading to substantial investments in GIS technologies. For example, the U.S. governmentÂ’s Geospatial Data Act emphasizes the development of a cohesive national geospatial policy, which in turn is expected to create more opportunities for GIS software providers.

Geographic Information System Analytics is becoming increasingly pivotal in transforming raw geospatial data into actionable insights. By employing sophisticated analytical tools, GIS Analytics allows organizations to visualize complex spatial relationships and patterns, enhancing decision-making processes across various sectors. For instance, in urban planning, GIS Analytics can identify optimal locations for new infrastructure projects by analyzing population density, traffic patterns, and environmental constraints. Similarly, in the utility sector, it aids in asset management by predicting maintenance needs and optimizing resource allocation. The ability to integrate GIS Analytics with other data sources, such as demographic and economic data, further amplifies its utility, making it an indispensable tool for strategic planning and operational efficiency.

Regionally, North America holds the largest share of the GIS software market, driven by technological advancements and high adoption rates across various sectors. Europe follows closely, with significant growth attributed to the increasing use of GIS in environmental monitoring and urban planning. The Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, fueled by rapid urbanization, infrastructure development, and government initiatives in countries like China and India.

Component Analysis

The GIS software market is segmented into software and services, each playing a vital role in meeting the diverse needs of end-users. The software segment encompasses various types of GIS software, including desktop GIS, web GIS, and mobile GIS. Desktop GIS remains the most widely used, offering comprehensive tools for spatial analysis, data management, and visualization. Web GIS, on the other hand, is gaining traction due to its accessibility and ease of use, allowing users to access GIS capabilities through a web browser without the need for extensive software installations.

Mobile GIS is another crucial aspect of the software segment, providing field-based solutions for data collection, asset management, and real-time decision making. With the increasing use of smartphones and tablets, mobile GIS applications are becoming indispensable for sectors such as utilities, transportation, and

This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups include: new/revised datasets (paleo-geothermal features, geochemistry, geophysics, heat flow, slip and dilation, potential structures, geothermal power plants, positive and negative test sites), machine learning model input grids, machine learning models (Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Bayesian Neural Network (BNN), Principal Component Analysis (PCA/PCAk), Non-negative Matrix Factorization (NMF/NMFk) - supervised and unsupervised), original NV Play Fairway data and models, and NV cultural/reference data.

See layer descriptions for additional metadata. Smaller GIS resource packages (by category) can be found in the related datasets section of this submission. A submission linking the full codebase for generating machine learning output models is available through the "Related Datasets" link on this page, and contains results beyond the top picks present in this compilation.

The Global GIS Mapping Tools Market is poised for significant expansion, projected to reach a substantial market size of $10 billion by 2025, with an anticipated Compound Annual Growth Rate (CAGR) of 12.5% through 2033. This robust growth trajectory is fueled by the increasing demand for advanced spatial analysis and visualization capabilities across a multitude of sectors. Key drivers include the escalating need for accurate geological exploration to identify and manage natural resources, the critical role of GIS in planning and executing complex water conservancy projects for sustainable water management, and the indispensable application of GIS in urban planning for efficient city development and infrastructure management. Furthermore, the burgeoning adoption of cloud-based and web-based GIS solutions is democratizing access to powerful mapping tools, enabling broader use by organizations of all sizes. The market is also benefiting from advancements in data processing, artificial intelligence integration, and the growing availability of open-source GIS platforms. Despite the optimistic outlook, certain restraints could temper the market's full potential. High initial investment costs for sophisticated GIS software and hardware, coupled with a shortage of skilled GIS professionals in certain regions, may pose challenges. However, the overwhelming benefits of enhanced decision-making, improved operational efficiency, and the ability to gain deep insights from spatial data are compelling organizations to overcome these hurdles. The competitive landscape is dynamic, featuring established players like Esri and Autodesk alongside innovative providers such as Mapbox and CARTO, all vying for market share by offering specialized features, user-friendly interfaces, and integrated solutions. The continuous evolution of GIS technology, driven by the integration of remote sensing data, big data analytics, and real-time information, will continue to shape the market's future. Here's a comprehensive report description on GIS Mapping Tools, incorporating your specified requirements:

This in-depth report provides a panoramic view of the global GIS Mapping Tools market, meticulously analyzing its landscape from the Historical Period (2019-2024) through to the Forecast Period (2025-2033), with 2025 serving as both the Base Year and the Estimated Year. The study period encompasses 2019-2033, offering a robust historical context and forward-looking projections. The market is valued in the millions of US dollars, with detailed segment-specific valuations and growth trajectories. The report is structured to deliver actionable intelligence to stakeholders, covering market concentration, key trends, regional dominance, product insights, and critical industry dynamics. It delves into the intricate interplay of companies such as Esri, Hexagon, Autodesk, CARTO, and Mapbox, alongside emerging players like Geoway and Shenzhen Edraw Software, across diverse applications including Geological Exploration, Water Conservancy Projects, and Urban Planning. The analysis also differentiates between Cloud Based and Web Based GIS solutions, providing a granular understanding of market segmentation.

This dataset provides a complete and highly structured view of retail precincts across multiple regions, designed to support market analysis, location intelligence, retail expansion, and AI/ML modelling. It delivers information in multiple formats to accommodate a wide range of analytical, GIS, and business use cases, making it an essential resource for retail analysts, urban planners, investment teams, and data-driven decision-makers.

Included Data Files & Formats

1. Point File
2. All Precincts by Centroid (GeoJSON/Shapefile).
3. Each precinct is represented as a single point located at its geometric centroid.
4. Includes key attributes: id, precinct name. Ideal for quick visualisation, clustering, and spatial reference when boundary shapes are not required.

5. Supports applications such as proximity analysis, mapping, and location-based AI/ML models.

6. Polygon File – All Precincts by Polygon (GeoJSON/Shapefile)

7. Provides full precinct boundaries in polygon geometry for precise spatial representation.

8. Includes key attributes: id, precinct name.

9. Enables detailed GIS analysis, including area calculations, spatial overlays, and integration with mobility or demographic datasets.

10. Suitable for urban planning, retail network optimisation, trade area analysis, and catchment studies.

PDF – Precinct Reports (see attached sample) - Reports include comprehensive retail precinct insights across malls and high streets, showing retailer mix by category (F&B, Apparel, Fitness, Grocery, Health/Fitness, and more), catchment size, shopper origins, population, consuming class population and precinct ranking—designed to provide insights on store expansion opportunities. - Supports qualitative assessments, market research, and executive reporting.

1. Excel – Tabular Overview
2. Comprehensive spreadsheet with all precincts, including the following fields: ID, Precinct Name, Ranking, State, Country
3. Enables straightforward filtering, sorting, and integration with other datasets.
4. Useful for high-level analysis, reporting, and as a reference table for GIS mapping or AI models.

Parcel boundary lines in this dataset are published once a year, after the boundary adjustments have been approved by Planning and Zoning and certified through the Assessor's Office. Attribute data is published at different times throughout the year, as detailed below.

*Attribute data excludes ownership and address data in this dataset. If you wish to have these data, please fill out the Public Information request form found in the Download Datasets page of the GIS Portal and email to lfrederick@co.valley.id.us.

ATTRIBUTE DATA - MONTHLY UPDATES

These fields are updated in the dataset monthly. After the public table updates are run by the Assessor's Office, Valley County GIS analyst exports the tables to append/update the new data values.

ATTRIBUTE DATA - ANNUAL UPDATES

These fields are updated annually after certification of parcel boundaries and valuation have been completed.

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!

This research study considers one such urban technology, namely utilising digital twins in cities. Digital twin city (DTC) technology is investigated to identify the gap in soft infrastructure data inclusion in DTC development. Soft infrastructure data considers the social and economic systems of a city, which leads to the identification of socio-economic security (SES) as the metric of investigation. The study also investigated how GIS mapping of the SES system in the specific context of Hatfield informs a soft infrastructure understanding that contributes to DTC readiness. This research study collected desk-researched secondary data and field-researched primary data in GIS using ArcGIS PRO and the Esri Online Platform using ArcGIS software. To form conclusions, grounded theory qualitative analysis and descriptive statistics analysis of the spatial GIS data schema data sets were performed.

ArcGIS Map Packages and GIS Data for Gillreath-Brown, Nagaoka, and Wolverton (2019)

**When using the GIS data included in these map packages, please cite all of the following:

Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, 2019. PLoSONE 14(8):e0220457. http://doi.org/10.1371/journal.pone.0220457

Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. ArcGIS Map Packages for: A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, Gillreath-Brown et al., 2019. Version 1. Zenodo. https://doi.org/10.5281/zenodo.2572018

OVERVIEW OF CONTENTS

This repository contains map packages for Gillreath-Brown, Nagaoka, and Wolverton (2019), as well as the raw digital elevation model (DEM) and soils data, of which the analyses was based on. The map packages contain all GIS data associated with the analyses described and presented in the publication. The map packages were created in ArcGIS 10.2.2; however, the packages will work in recent versions of ArcGIS. (Note: I was able to open the packages in ArcGIS 10.6.1, when tested on February 17, 2019). The primary files contained in this repository are:

• Raw DEM and Soils data
  • Digital Elevation Model Data (Map services and data available from U.S. Geological Survey, National Geospatial Program, and can be downloaded from the National Elevation Dataset)
    • DEM_Individual_Tiles: Individual DEM tiles prior to being merged (1/3 arc second) from USGS National Elevation Dataset.
    • DEMs_Merged: DEMs were combined into one layer. Individual watersheds (i.e., Goodman, Coffey, and Crow Canyon) were clipped from this combined DEM.
  • Soils Data (Map services and data available from Natural Resources Conservation Service Web Soil Survey, U.S. Department of Agriculture)
    • Animas-Dolores_Area_Soils: Small portion of the soil mapunits cover the northeastern corner of the Coffey Watershed (CW).
    • Cortez_Area_Soils: Soils for Montezuma County, encompasses all of Goodman (GW) and Crow Canyon (CCW) watersheds, and a large portion of the Coffey watershed (CW).
• ArcGIS Map Packages
  • Goodman_Watershed_Full_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the full Goodman Watershed (GW).
  • Goodman_Watershed_Mesa-Only_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the mesa-only Goodman Watershed.
  • Crow_Canyon_Watershed_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the Crow Canyon Watershed (CCW).
  • Coffey_Watershed_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the Coffey Watershed (CW).

For additional information on contents of the map packages, please see see "Map Packages Descriptions" or open a map package in ArcGIS and go to "properties" or "map document properties."

LICENSES

Code: MIT year: 2019
Copyright holders: Andrew Gillreath-Brown, Lisa Nagaoka, and Steve Wolverton

CONTACT

Andrew Gillreath-Brown, PhD Candidate, RPA
Department of Anthropology, Washington State University
andrew.brown1234@gmail.com – Email
andrewgillreathbrown.wordpress.com – Web

Spatial analysis and statistical summaries of the Protected Areas Database of the United States (PAD-US) provide land managers and decision makers with a general assessment of management intent for biodiversity protection, natural resource management, and outdoor recreation access across the nation. This data release presents results from statistical summaries of the PAD-US 3.0 protection status (by GAP Status Code) and public access status for various land unit boundaries (Protected Areas Database of the United States 3.0 Vector Analysis and Summary Statistics). Summary statistics are also available to explore and download (Comma-separated Table [CSV], Microsoft Excel Workbook (.xlsx), Portable Document Format [.pdf] Report) from the PAD-US Lands and Inland Water Statistics Dashboard ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-statistics ). The vector GIS analysis file, source data used to summarize statistics for areas of interest to stakeholders (National, State, Department of the Interior Region, Congressional District, County, EcoRegions I-IV, Urban Areas, Landscape Conservation Cooperative), and complete Summary Statistics Tabular Data (CSV) are included in this data release. Raster GIS analysis files are also available for combination with other raster data (Protected Areas Database of the United States (PAD-US) 3.0 Raster Analysis). The PAD-US 3.0 Combined Fee, Designation, Easement feature class in the full inventory, with Military Lands and Tribal Areas from the Proclamation and Other Planning Boundaries feature class (Protected Areas Database of the United States (PAD-US) 3.0, https://doi.org/10.5066/P9Q9LQ4B), was modified to prioritize and remove overlapping management designations, limiting overestimation in protection status or public access statistics and to support user needs for vector and raster analysis data. Analysis files in this data release were clipped to the Census State boundary file to define the extent and fill in areas (largely private land) outside the PAD-US, providing a common denominator for statistical summaries.

Attribute reclassification for fixed amplitude and varying Cmin.

GIS Controller Market Outlook

The GIS Controller market size was valued at $8.3 billion in 2023 and is projected to reach $15.6 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.2% during the forecast period. This significant growth factor can be attributed primarily to increasing urbanization, the rising need for efficient spatial data management, and technological advancements in geospatial analytics.

One of the prime growth factors driving the GIS Controller market is the escalating demand for smart city solutions. As urbanization continues to rise globally, governments and municipalities are increasingly investing in smart city initiatives to improve urban planning, public safety, and resource management. GIS controllers play a crucial role in these initiatives by providing accurate spatial data, which is essential for efficient infrastructure development, traffic management, and environmental monitoring. Furthermore, the integration of GIS with other technologies such as IoT and AI is opening new avenues for real-time data analysis and decision-making, further propelling market growth.

The agriculture sector is another significant contributor to the growth of the GIS Controller market. Precision farming techniques that leverage GIS technology are gaining traction for their ability to enhance crop yield and optimize resource usage. By providing detailed insights into soil conditions, weather patterns, and crop health, GIS controllers enable farmers to make data-driven decisions, thereby improving operational efficiency and reducing costs. Additionally, government initiatives aimed at promoting sustainable farming practices are further fueling the adoption of GIS technology in the agricultural sector.

Disaster management is another critical application area where GIS controllers are making a substantial impact. The increasing frequency of natural disasters such as hurricanes, floods, and earthquakes necessitates advanced planning and real-time response capabilities. GIS controllers help in mapping disaster-prone areas, predicting the impact of natural calamities, and coordinating emergency response efforts. This capability is invaluable for minimizing damage and saving lives. The growing focus on disaster preparedness and management is expected to drive the demand for GIS controllers in the coming years.

Regionally, North America holds a significant share of the GIS Controller market, driven by the high adoption rate of advanced technologies and substantial investments in smart city projects. The Asia Pacific region is expected to witness the highest growth rate, fueled by rapid urbanization, infrastructural development, and increasing government initiatives for digital transformation. Europe also presents substantial growth opportunities due to the rising focus on environmental sustainability and smart transportation systems.

Component Analysis

The GIS Controller market is segmented into three primary components: Hardware, Software, and Services. The hardware segment includes devices and equipment necessary for capturing and processing geospatial data, such as GPS units, sensors, and data collection devices. This segment is witnessing steady growth due to the increasing need for advanced and accurate data collection tools. The integration of AI and IoT with GIS hardware is further enhancing the capabilities of these devices, making them indispensable for various applications such as urban planning, agriculture, and disaster management.

In terms of software, GIS Controllers are equipped with specialized software for data analysis, mapping, and modeling. This segment is experiencing rapid growth due to the increasing demand for sophisticated analytical tools that can handle large datasets and provide real-time insights. Advanced GIS software solutions are being developed to offer more user-friendly interfaces and better integration with other enterprise systems, thereby enhancing their usability and effectiveness across different sectors. The rise of cloud-based GIS software is also contributing to the growth of this segment by offering scalable and cost-effective solutions.

The services segment comprises consultancy, implementation, and maintenance services essential for the effective deployment and utilization of GIS Controllers. As organizations increasingly adopt GIS technology, the demand for specialized services that can ensure smooth integration and optimal performance is rising. Professional services providers are offering customized solutions to meet the specific needs of different industries

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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, data storytelling, geospati

The Travel Time Tool was created by the MN DNR to use GIS analysis for calculation of hydraulic travel time from gridded surfaces and develop a downstream travel time raster for each cell in a watershed. This hydraulic travel time process, known as Time of Concentration, is a concept from the science of hydrology that measures watershed response to a precipitation event. The analysis uses watershed characteristics such as land-use, geology, channel shape, surface roughness, and topography to measure time of travel for water. Described as Travel Time, it calculates the elapsed time for a simulated drop of water to migrate from its source along a hydraulic path across different surfaces of the replicated watershed landscape, ultimately reaching the watershed outlet. The Travel Time Tool creates a raster whereas each cell is a measure of the length of time (in seconds) that it takes water to flow across it, and then accumulates the time (in hours) from the cell to the outlet of the watershed.

The Travel Time Tool creates an impedance raster from Manning's Equation that determines the velocity of water flowing across the cell as a measure of time (in feet per second). The Flow Length Tool uses the travel time Grid for the impedance factor and determines the downstream flow time from each cell to the outlet of the watershed.

The toolbox works with ArcMap 10.6.1 and newer and ArcGIS Pro. Latest version of the toc2.py script is Version 2.0.1 published 2025/11/07.

For step-by-step instructions on how to use the tool, please view MN DNR Travel Time Guidance.pdf