Geospatial Analytics Software Market Outlook

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

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

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

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

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

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

Component Analysis

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

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

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.

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.

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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,

In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.

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

The United States geospatial analytics market is experiencing robust growth, driven by increasing adoption across diverse sectors. The market, valued at approximately $X billion in 2025 (assuming a proportional share of the global market size based on US economic weight), is projected to exhibit a Compound Annual Growth Rate (CAGR) of 10.04% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the rising availability of high-resolution satellite imagery, drone data, and other geospatial data sources provides rich information for analysis. Secondly, advancements in artificial intelligence (AI) and machine learning (ML) are enhancing the capabilities of geospatial analytics platforms, enabling more sophisticated insights and predictions. Thirdly, the increasing need for precise location-based services across various industries, such as precision agriculture, smart city initiatives, and autonomous vehicle development, is driving demand for sophisticated geospatial analytics solutions. Finally, government initiatives promoting data sharing and open data policies further contribute to market growth. The market is segmented by type (surface analysis, network analysis, geovisualization) and end-user vertical (agriculture, utility & communication, defense & intelligence, government, mining & natural resources, automotive & transportation, healthcare, real estate & construction). North America, particularly the US, holds a significant market share due to advanced technological infrastructure and high adoption rates across various sectors. Within the US market, significant growth is expected in sectors like precision agriculture, where geospatial analytics is used for optimized crop management and resource allocation, and in the transportation sector, supporting logistics optimization, traffic management, and autonomous vehicle navigation. The defense and intelligence sectors remain major consumers of geospatial analytics, relying on these technologies for surveillance, intelligence gathering, and military planning. The increasing adoption of cloud-based geospatial analytics platforms is also a significant trend, offering scalability, accessibility, and cost-effectiveness. However, challenges such as data security concerns, high implementation costs, and the need for skilled professionals could potentially hinder market growth. Despite these challenges, the overall market outlook for geospatial analytics in the US remains exceptionally positive, projecting substantial growth over the forecast period. Recent developments include: May 2023 : CAPE Analytics, a player in AI-powered geospatial property intelligence, has extended its partnership with The Hanover Insurance Group, which provides independent agents with the best insurance coverage and prices. Integrating geospatial analytics and inspection and rating models into Hanover's underwriting procedure is the central component of the partnership expansion. The company's rating plans will benefit from this strategic move, which will improve workflows, new and renewal underwriting outcomes, and pricing segmentation., March 2023 : Carahsoft Technology Corp., The Trusted Government IT Solutions Provider, and Orbital Insight, a player in geospatial intelligence, announced a partnership. By the terms of the agreement, Carahsoft will act as Orbital Insight's Master Government Aggregator, making the leading AI-powered geospatial data analytics available to the public sector through Carahsoft's reseller partners and contracts for Information Technology Enterprise Solutions - Software 2 (ITES-SW2), NASA Solutions for Enterprise-Wide Procurement (SEWP) V, National Association of State Procurement Officials (NASPO) ValuePoint, National Cooperative Purchasing.. Key drivers for this market are: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Potential restraints include: High Costs and Operational Concerns, Concerns related to Geoprivacy and Confidential Data. Notable trends are: Network Analysis is Expected to Hold Significant Share of the Market.

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

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

According to Cognitive Market Research, the global geospatial analytics artificial intelligence market size is USD 100.5 million in 2024 and will expand at a compound annual growth rate (CAGR) of 28.60% from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD 40.20 million in 2024 and will grow at a compound annual growth rate (CAGR) of 26.8% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 30.15 million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD 23.12 million in 2024 and will grow at a compound annual growth rate (CAGR) of 30.6% from 2024 to 2031.
Latin America market of more than 5% of the global revenue with a market size of USD 5.03 million in 2024 and will grow at a compound annual growth rate (CAGR) of 28.0% from 2024 to 2031.
Middle East and Africa held the major market of around 2% of the global revenue with a market size of USD 2.01 million in 2024 and will grow at a compound annual growth rate (CAGR) of 28.3% from 2024 to 2031.
The remote sensing held the highest geospatial analytics artificial intelligence market revenue share in 2024.

Market Dynamics of Geospatial analytics artificial intelligence Market

Key Drivers for Geospatial analytics artificial intelligence Market

Advancements in AI and Machine Learning to Increase the Demand Globally

The global demand for geospatial analytics is significantly driven by advancements in AI and machine learning, technologies that are revolutionizing how spatial data is analyzed and interpreted. As AI models become more sophisticated, they enhance the capability to automate complex geospatial data processing tasks, leading to more accurate and insightful analyses. Machine learning, particularly, enables systems to improve their accuracy over time by learning from vast datasets of geospatial information, including satellite imagery and sensor data. This leads to more precise predictions and better decision-making across multiple sectors such as environmental management, urban planning, and disaster response. The integration of AI with geospatial technologies not only improves efficiency but also opens up new possibilities for innovation, making it a critical driver for increased global demand in the geospatial analytics market.

Government Initiatives and Support for Smart Cities to Propel Market Growth

Government initiatives supporting the development of smart cities are propelling the growth of the geospatial analytics market. As urban areas around the world transform into smart cities, there is a significant increase in demand for advanced technologies that can analyze and interpret geospatial data to enhance urban planning, infrastructure management, and public safety. Geospatial analytics, powered by AI, plays a crucial role in these projects by enabling real-time data processing and insights for traffic control, utility management, and emergency services coordination. These technologies ensure more efficient resource allocation and improved quality of urban life. Government funding and policy support not only validate the importance of geospatial analytics but also stimulate innovation, attract investments, and foster public-private partnerships, thus driving the market forward and enhancing the capabilities of smart city initiatives globally.

Restraint Factor for the Geospatial analytics artificial intelligence Market

Complexity of Data Integration to Limit the Sales

The complexity of data integration poses a significant barrier to the adoption and effectiveness of geospatial analytics AI systems, potentially limiting sales in this market. Geospatial data, inherently diverse and sourced from various collection methods like satellites, UAVs, and ground sensors, comes in multiple formats and resolutions. Integrating such disparate data into a cohesive, usable format for AI analysis is a challenging process that requires advanced data processing tools and expertise. This complexity not only increases the time and costs associated with project implementation but also raises the risk of errors and inefficiencies in data analysis. Furthermore, the difficulty in achieving seamless integration can deter organizations, particularly those with limited IT capabilities, from investing in geospatial analytics solutions. Overcoming these integration challenges is crucial for enabl...

This data supports the paper entitled "Mapping the landscape of geospatial data citations". The dataset covers geospatial data-intensive research papers published between 2015-2018 retrieved using Scopus. The article's citations were assessed for data citation occurances, and coded using a data citation classification. Data were enhanced and linked to subject coverage and journal policy status information using Excel & SPSS. For more information about how the data were created and coded please review the 'Methodology' section of the paper. More information is provided below, including supplemental documentation and related publications. Abstract (paper) ABSTRACT Data citations, similar to article and other research citations, are important references to research data that underlie published research results. In support of open science directives, these citations must adhere to specific conventions in terms of consistency of both placement within an article, and the actual availability or access to research data. To better understand the level to which geospatial research data are currently cited, we undertook a study to analyse the rate of data citation within a set of data-intensive geospatial research articles. After analysing 1717 scholarly articles published between 2015 and 2018, we found that very few, or 78 (5%), meaningfully cited primary or secondary geospatial data sources in the cited references section of the article. Even fewer researchers, only 25 or 1.5%, were found to have cited data using a DOI. Given the relatively low data citation rate, a focus on contributing factors including barriers to citing geospatial data is needed. And while open sharing requirements for geospatial data may change over time, driving data citation as a result, understanding benchmarks for data citation for monitoring purposes is useful.

This bucket contains multiple datasets (as Quilt packages) created by the Center for Geospatial Sciences (CGS) at the University of California-Riverside. The data in this bucket contains the following:

1. Tabular and geographic data from the US Census
2. Land Cover imagery collected from Multi-Resolution Land Characteristics Consortium
3. Road network data processed from OpenStreetMap

The Geographic Information System (GIS) Analytics market is experiencing robust growth, projected to reach $15.10 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 12.41% from 2025 to 2033. This expansion is fueled by several key drivers. Increasing adoption of cloud-based GIS solutions enhances accessibility and scalability for diverse industries. The growing need for data-driven decision-making across sectors like retail, real estate, government, and telecommunications is a significant catalyst. Furthermore, advancements in artificial intelligence (AI) and machine learning (ML) integrated with GIS analytics are revolutionizing spatial data analysis, enabling more sophisticated predictive modeling and insightful interpretations. The market's segmentation reflects this broad adoption, with retail and real estate, government and utilities, and telecommunications representing key end-user segments, each leveraging GIS analytics for distinct applications such as location optimization, infrastructure management, and network planning. Competitive pressures are shaping the market landscape, with established players like Esri, Trimble, and Autodesk innovating alongside emerging tech companies focusing on AI and specialized solutions. The North American market currently holds a significant share, driven by early adoption and technological advancements. However, Asia-Pacific is expected to witness substantial growth due to rapid urbanization and increasing investment in infrastructure projects. Market restraints primarily involve the high cost of implementation and maintenance of advanced GIS analytics solutions and the need for skilled professionals to effectively utilize these technologies. However, the overall outlook remains extremely positive, driven by continuous technological innovation and escalating demand across multiple sectors. The future trajectory of the GIS analytics market hinges on several factors. Continued investment in research and development, especially in AI and ML integration, will be crucial for unlocking new possibilities. Furthermore, the simplification of GIS analytics software and the development of user-friendly interfaces will broaden accessibility beyond specialized technical experts. Growing data volumes from various sources (IoT, remote sensing) present both opportunities and challenges; efficient data management and analytics techniques will be paramount. The market's success also depends on addressing cybersecurity concerns related to sensitive geospatial data. Strong partnerships between technology providers and end-users will be vital in optimizing solution implementation and maximizing return on investment. Government initiatives promoting the use of GIS technology for smart city development and infrastructure planning will also play a significant role in market expansion. Overall, the GIS analytics market is poised for sustained growth, driven by technological advancements, increasing data availability, and heightened demand for location-based intelligence across a wide range of industries.

Data files for the examples in the book Geographic Data Science in R: Visualizing and Analyzing Environmental Change by Michael C. Wimberly.

The Location Analysis market is experiencing robust growth, driven by the increasing adoption of location-based services across diverse sectors. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching an estimated value of $45 billion by 2033. This expansion is fueled by several key factors. The burgeoning adoption of IoT devices and the exponential growth of location data are significantly contributing to this market's expansion. Furthermore, the increasing need for real-time location intelligence in sectors like transportation and logistics, retail, and financial services is driving demand for sophisticated location analysis solutions. Advanced analytics capabilities, including predictive modeling and machine learning, are enhancing the value proposition of these solutions, enabling businesses to make more informed decisions based on precise location-based insights. The market segmentation reflects this breadth of application, with Banking and Financial Services, Medical and Life Sciences, and Telecommunications and Information Technology leading the way in adoption. The growth is also geographically diverse, with North America and Europe currently dominating the market, followed by a rapidly expanding Asia-Pacific region. However, challenges remain. Data privacy concerns and the complexity of integrating location data from various sources continue to pose obstacles for market growth. Overcoming these challenges will require robust data governance frameworks and the development of user-friendly, scalable solutions. The increasing availability of open-source location data and the development of more sophisticated analytical tools, however, are mitigating these challenges and driving further innovation. The competitive landscape is fiercely contested, with major technology companies and specialized location analytics providers vying for market share. This competition is likely to further stimulate innovation and drive down costs, ultimately benefiting end-users across various industries. The ongoing evolution of location technologies, coupled with the growing reliance on location data across sectors, promises sustained growth for the Location Analysis market in the coming years.

The US Geospatial Imagery Analytics market is experiencing robust growth, fueled by increasing adoption across various sectors. The market's expansion is driven by several key factors. Firstly, the rising availability of high-resolution satellite imagery and advancements in artificial intelligence (AI) and machine learning (ML) algorithms are enabling more sophisticated and accurate analysis. This translates to improved decision-making capabilities across diverse applications, from precision agriculture optimizing crop yields and resource management to urban planning enhancing infrastructure development and risk mitigation. Secondly, government initiatives promoting the use of geospatial data for national security, environmental monitoring, and infrastructure development are significantly boosting market demand. The integration of geospatial imagery analytics into existing workflows is becoming increasingly seamless, further accelerating market penetration. While on-premise solutions still hold a significant share, cloud-based deployments are gaining traction due to their scalability and cost-effectiveness. Large enterprises are currently the major consumers, but the market is seeing substantial growth from SMEs seeking cost-effective solutions for business intelligence. Finally, the increasing focus on environmental sustainability and climate change monitoring contributes to heightened demand for geospatial analytics in the environmental monitoring and agricultural sectors. Looking ahead, the US Geospatial Imagery Analytics market is poised for continued expansion, driven by technological innovations and increasing data accessibility. The forecast period (2025-2033) anticipates consistent growth, propelled by further AI/ML integration, the emergence of new applications (like autonomous vehicles and smart cities), and a greater emphasis on data security and privacy within the geospatial domain. While potential restraints include the high initial investment cost for some solutions and the need for specialized expertise to interpret the data, these challenges are being addressed by the development of user-friendly software and the expanding availability of skilled professionals. The market segmentation by deployment mode (on-premise vs. cloud), organization size (SMEs vs. large enterprises), and vertical (e.g., insurance, agriculture) reflects the diverse application and user base of this dynamic market. The North American market, particularly the US, is expected to remain a dominant player, given its advanced technological infrastructure and high adoption rates. This in-depth report provides a comprehensive analysis of the US Geospatial Imagery Analytics market, offering valuable insights for businesses, investors, and researchers. With a study period spanning from 2019 to 2033, a base year of 2025, and a forecast period from 2025 to 2033, this report meticulously examines market dynamics, growth drivers, and future projections. The report is built using data from the historical period (2019-2024) and delivers actionable intelligence to navigate this rapidly evolving landscape. Recent developments include: May 2023: CAPE Analytics, a player in AI-powered geospatial property intelligence, has extended its partnership with The Hanover Insurance Group, which provides independent agents with the best insurance coverage and prices. Integrating geospatial analytics and inspection and rating models into Hanover's underwriting procedure is the central component of the partnership expansion. The company's rating plans will benefit from this strategic move, improving workflows, new and renewal underwriting outcomes, and pricing segmentation., March 2023 : Carahsoft Technology Corp., The Trusted Government IT Solutions Provider, and Orbital Insight, a player in geospatial intelligence, announced a partnership. By the terms of the agreement, Carahsoft will act as Orbital Insight's Master Government Aggregator, making the leading AI-powered geospatial data analytics available to the public sector through Carahsoft's reseller partners and contracts for Information Technology Enterprise Solutions - Software 2 (ITES-SW2), NASA Solutions for Enterprise-Wide Procurement (SEWP) V, National Association of State Procurement Officials (NASPO) ValuePoint, National Cooperative Purchasing.. Key drivers for this market are: Increasing demand for Location based services, Technological innovations in geospatial imagery services. Potential restraints include: Lack of Awareness about benefits of Geospatial Imagery Services. Notable trends are: Small Satellities will Boost Market Growth.

This Innovative Technology Experiences for Students and Teachers (ITEST) project has developed, implemented, and evaluated a series of innovative Socio-Environmental Science Investigations (SESI) using a geospatial curriculum approach. It is targeted for economically disadvantaged 9th grade high school students in Allentown, PA, and involves hands-on geospatial technology to help develop STEM-related skills. SESI focuses on societal issues related to environmental science. These issues are multi-disciplinary, involve decision-making that is based on the analysis of merged scientific and sociological data, and have direct implications for the social agency and equity milieu faced by these and other school students. This project employed a design partnership between Lehigh University natural science, social science, and education professors, high school science and social studies teachers, and STEM professionals in the local community to develop geospatial investigations with Web-based Geographic Information Systems (GIS). These were designed to provide students with geospatial skills, career awareness, and motivation to pursue appropriate education pathways for STEM-related occupations, in addition to building a more geographically and scientifically literate citizenry. The learning activities provide opportunities for students to collaborate, seek evidence, problem-solve, master technology, develop geospatial thinking and reasoning skills, and practice communication skills that are essential for the STEM workplace and beyond. Despite the accelerating growth in geospatial industries and congruence across STEM, few school-based programs integrate geospatial technology within their curricula, and even fewer are designed to promote interest and aspiration in the STEM-related occupations that will maintain American prominence in science and technology. The SESI project is based on a transformative curriculum approach for geospatial learning using Web GIS to develop STEM-related skills and promote STEM-related career interest in students who are traditionally underrepresented in STEM-related fields. This project attends to a significant challenge in STEM education: the recognized deficiency in quality locally-based and relevant high school curriculum for under-represented students that focuses on local social issues related to the environment. Environmental issues have great societal relevance, and because many environmental problems have a disproportionate impact on underrepresented and disadvantaged groups, they provide a compelling subject of study for students from these groups in developing STEM-related skills. Once piloted in the relatively challenging environment of an urban school with many unengaged learners, the results will be readily transferable to any school district to enhance geospatial reasoning skills nationally.

SONG, Carol X., Rosen Center for Advanced Computing, Purdue University, 155 South Grant Street, Young Hall, West Lafayette, IN 47907

Science gateways are becoming an integral component of modern collaborative research. They find widespread adoption by research groups to share data, code and tools both within a project and with the broader community. Sustainability beyond initial funding is a significant challenge for a science gateway to continue to operate, update and support the communities it serves. MyGeoHub.org is a geospatial science gateway powered by HUBzero. MyGeoHub employs a business model of hosting multiple research projects on a single HUBzero instance to manage the gateway operations more efficiently and sustainably while lowering the cost to individual projects. This model allows projects to share the gateway’s common capabilities and the underlying hardware and other connected computing resources, and continued maintenance of their sites even after the original funding has run out allowing time for acquiring new funding. MyGeoHub has hosted a number of projects, ranging from hydrologic modeling and data sharing, plant phenotyping, global and local sustainable development, climate variability impact on crops, and most recently, modeling of industry processes to improve reuse and recycling of materials. The shared need to manage, visualize and process geospatial data across the projects has motivated the Geospatial Data Building Blocks (GABBs) development funded by NSF DIBBs. GABBs provides a “File Explorer” type user interface for managing geospatial data (no coding is needed), a builder for visualizing and exploring geo-referenced data without coding, a Python map library and other toolkits for building geospatial analysis and computational tools without requiring GIS programming expertise. GABBs can be added to an existing or new HUBzero site, as is the case on MyGeoHub. Teams use MyGeoHub to coordinate project activities, share files and information, publish tools and datasets (with DOI) to provide not only easy access but also improved reuse and reproducibility of data and code as the interactive online tools and workflows can be used without downloading or installing software. Tools on MyGeoHub have also been used in courses, training workshops and summer camps. MyGeoHub is supporting more than 8000 users annually.

Geospatial Solutions Market size was valued at USD 282.75 Billion in 2024 and is projected to reach USD 650.14 Billion by 2032, growing at a CAGR of 12.10% during the forecast period 2026-2032.

Geospatial Solutions Market: Definition/ Overview

Geospatial solutions are applications and technologies that use spatial data to address geography, location, and Earth's surface problems. They use tools like GIS, remote sensing, GPS, satellite imagery analysis, and spatial modelling. These solutions enable informed decision-making, resource allocation optimization, asset management, environmental monitoring, infrastructure planning, and addressing challenges in sectors like urban planning, agriculture, transportation, disaster management, and natural resource management. They empower users to harness spatial information for better understanding and decision-making in various contexts.

Geospatial solutions are technologies and methodologies used to analyze and visualize spatial data, ranging from urban planning to agriculture. They use GIS, remote sensing, and GNSS to gather, process, and interpret data. These solutions help users make informed decisions, solve complex problems, optimize resource allocation, and enhance situational awareness. They are crucial in addressing challenges and unlocking opportunities in today's interconnected world, such as mapping land use patterns, monitoring ecosystem changes, and real-time asset tracking.