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Dataset and code used in a journal paper entitled Detecting Geospatial Location Descriptions in Natural Language Text, published in the International Journal of Geographical Information Science. Abstract:References to geographic locations are common in text data sources including social media and web pages. They take different forms, from simple place names to relative expressions that describe location through a spatial relationship to a reference object (e.g. the house beside the Waikato River). Often complex, multi-word phrases are employed (e.g. the road and railway cross at right angles; the road in line with the canal) where spatial relationships are communicated with various parts of speech including prepositions, verbs, adverbs and adjectives. We address the problem of automatically detecting relative geospatial location descriptions, which we define as those that include spatial relation terms referencing geographic objects, and distinguishing them from non-geographical descriptions of location (e.g. the book on the table). We experiment with several methods for automated classification of text expressions, using features for machine learning that include bag of words that detect distinctive words; word embeddings that encode meanings of words; and manually identified language patterns that characterise geospatial expressions. Using three data sets created for this study, we find that ensemble and meta-classifier approaches, that variously combine predictions from several other classifiers with data features, provide the best F-measure of 0.90 for detecting geospatial expressions.

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...

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 global GIS data collector market is experiencing robust growth, driven by increasing adoption of precision agriculture, expanding infrastructure development projects, and the rising demand for accurate geospatial data across various industries. The market, estimated at $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033, reaching approximately $4.2 billion by 2033. Key drivers include the increasing availability of affordable and high-precision GPS technology, coupled with advancements in data processing and cloud-based solutions. The integration of GIS data collectors with other technologies, such as drones and IoT sensors, is further fueling market expansion. The demand for high-precision GIS data collectors is particularly strong in sectors like surveying, mapping, and construction, where accuracy is paramount. While the market faces challenges such as high initial investment costs and the need for specialized expertise, the overall growth trajectory remains positive. The market is segmented by application (agriculture, industrial, forestry, and others) and by type (general precision and high precision). North America and Europe currently hold significant market shares, but the Asia-Pacific region is anticipated to experience rapid growth in the coming years due to substantial infrastructure development and increasing government investments in geospatial technologies. The competitive landscape is characterized by both established players like Trimble, Garmin, and Hexagon (Leica Geosystems) and emerging companies offering innovative solutions. These companies are constantly innovating, integrating advanced technologies like AI and machine learning to enhance data collection and analysis capabilities. This competition is driving down prices and improving product quality, benefiting end-users. The increasing use of mobile GIS and cloud-based data management solutions is also transforming the industry, making data collection and analysis more accessible and efficient. Future growth will be largely influenced by the advancement of 5G networks, enabling faster data transmission and real-time applications, and the increasing adoption of automation and AI in data processing workflows. Furthermore, government regulations promoting the use of accurate geospatial data for sustainable development and environmental monitoring are creating new opportunities for the market’s expansion.

The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for 19 countries of interest in the Indo-Pacific region (area of study): Bangladesh, Bhutan, Brunei, Burma, Fiji, Malaysia, Mongolia, Nauru, New Caledonia, New Zealand, Papua New Guinea, Philippines, Singapore, Solomon Islands, South Korea (Republic of Korea), Sri Lanka, Taiwan, Timor-Leste, and Vietnam. The data can be used in analyses of the extractive fuel and nonfuel mineral industries integral for the successful operation of the mineral industries within the area of study. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration sites, and mineral sites and processing facilities under development for the countries in the area of study. The geodatabase contains data feature classes from USGS, foreign governmental, and open-source sources as follows: (1) mineral production and processing facilities, (2) mineral exploration sites, (3) mineral production and processing facilities under development, (4) undiscovered mineral resource tracts for copper, (5) coal occurrence areas, (6) undiscovered, technically recoverable conventional and continuous hydrocarbon resources (by USGS geologic province), and (7) cumulative production and recoverable conventional resources (by province groups).

This dataset is about books. It has 5 rows and is filtered where the book subjects is Geospatial data-Computer processing. It features 9 columns including author, publication date, language, and book publisher.

The remote sensing software market is experiencing robust growth, driven by increasing demand for geospatial data across various sectors. The market's expansion is fueled by advancements in sensor technology, satellite imagery availability, and the rising adoption of cloud-based solutions for data processing and analysis. Factors like the need for precise land management, environmental monitoring, urban planning, and defense applications are significant contributors to this growth. While precise figures for market size and CAGR are unavailable in the provided information, based on industry reports and trends, a reasonable estimation would place the 2025 market size at approximately $5 billion, experiencing a compound annual growth rate (CAGR) of around 8% during the forecast period (2025-2033). This growth trajectory is expected to continue, driven by the increasing integration of AI and machine learning algorithms within remote sensing software for improved data analysis and automation. The competitive landscape is marked by a mix of established players like PCI Geomatics, Hexagon, and Esri, and emerging technology providers. These companies are constantly innovating to offer advanced functionalities such as 3D modeling, image processing, and data visualization capabilities. However, high initial investment costs for software licenses and specialized hardware can present a barrier to entry for some organizations. Further, data security concerns and the need for specialized expertise in data interpretation can pose some challenges to market growth. Despite these constraints, the long-term prospects of the remote sensing software market remain highly positive, fueled by government initiatives promoting geospatial data accessibility and the ongoing development of more sophisticated and user-friendly software solutions. The increasing availability of affordable high-resolution imagery and the integration of remote sensing data with other data sources promise to further boost market expansion in the coming years.

The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for the People's Republic of China. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports for the countries in the area of study. The geodatabase contains data feature classes from USGS, foreign governmental, and open-source sources as follows: (1) mineral production and processing facilities, (2) mineral exploration and development sites, (3) mineral occurrence sites and deposits, (4) undiscovered mineral resource tracts for antimony, copper, phosphate, and potash, (5) coal occurrence areas, (6) electric power generating facilities, (7) electric power transmission lines, (8) liquefied natural gas terminals, (9) undiscovered, technically recoverable conventional and continuous hydrocarbon resources (by USGS geologic province), (10) cumulative production and recoverable conventional resources (by province groups), and (11) major mineral exporting maritime ports.

This paper provides an abstract analysis of parallel processing strategies for spatial and spatio-temporal data. It isolates aspects such as data locality and computational locality as well as redundancy and locally sequential access as central elements of parallel algorithm design for spatial data. Furthermore, the paper gives some examples from simple and advanced GIS and spatial data analysis highlighting both that big data systems have been around long before the current hype of big data and that they follow some design principles which are inevitable for spatial data including distributed data structures and messaging, which are, however, incompatible with the popular MapReduce paradigm. Throughout this discussion, the need for a replacement or extension of the MapReduce paradigm for spatial data is derived. This paradigm should be able to deal with the imperfect data locality inherent to spatial data hindering full independence of non-trivial computational tasks. We conclude that more research is needed and that spatial big data systems should pick up more concepts like graphs, shortest paths, raster data, events, and streams at the same time instead of solving exactly the set of spatially separable problems such as line simplifications or range queries in manydifferent ways.

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

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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,

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.

The global geospatial data provider market is anticipated to reach a value of XX million USD by 2033, exhibiting a CAGR of XX% during the forecast period (2023-2033). The market was valued at USD 5515 million in 2022. This growth is primarily attributed to the growing demand for geospatial data in various industry verticals, such as urban planning, natural resource management, transportation, and defense. The increasing adoption of geospatial technologies, such as Geographic Information Systems (GIS) and Remote Sensing (RS), is also contributing to the market growth. The increasing demand for real-time and accurate geospatial data for decision-making and strategic planning is driving the market growth. The advancements in data collection and processing technologies, such as Artificial Intelligence (AI) and Machine Learning (ML), are enabling the extraction and analysis of valuable insights from geospatial data. The growing adoption of cloud-based geospatial platforms and services is also contributing to the market growth. Key market players include SafeGraph, Esri, PlanetObserver, Korem, L3Harris, Intellias, EOSDA, The Data Appeal Company, Echo Analytics, and Gravy Analytics.

The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for 10 countries of interest in Southwest Asia (area of study): Afghanistan, Cambodia, Laos, India, Indonesia, Iran, Nepal, North Korea, Pakistan, and Thailand. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports for the countries in the area of study. The geodatabase contains data feature classes from USGS, foreign governmental, and open-source sources as follows: (1) mineral production and processing facilities, (2) mineral exploration and development sites, (3) mineral occurrence sites and deposits, (4) undiscovered mineral resource tracts for copper, phosphate, and potash, (5) coal occurrence areas, (6) electric power generating facilities, (7) electric power transmission lines, (8) liquefied natural gas terminals, (9) undiscovered, technically recoverable conventional and continuous hydrocarbon resources (by USGS geologic province), (10) cumulative production and recoverable conventional resources (by oil- and gas-producing nation), and (11) major mineral exporting maritime ports.

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.

The Geospatial Analytics Market size was valued at USD 98.93 billion in 2023 and is projected to reach USD 227.04 billion by 2032, exhibiting a CAGR of 12.6 % during the forecasts period. The Geospatial Analytics Market describes an application of technologies and approaches processing geographic and spatial data for intelligence and decision-making purposes. This market comprises of mapping tools and software, spatial data and geographic information systems (GIS) used in various fields including urban planning, environmental, transport and defence. Use varies from inventory tracking and control to route optimization and assessment of changes in environment. Other trends are the growth of big data and machine learning to improve the predictive methods, the improved real-time data processing the use of geographic data in combination with other technologies, for example, IoT and cloud. Some of the factors that are fuelling the need to find a marketplace for GIS solutions include; Increasing importance of place-specific information Increasing possibilities for data collection The need to properly manage spatial information in a high stand environment. Recent developments include: In May 2023, Google launched Google Geospatial Creator, a powerful tool that allows users to create immersive AR experiences that are both accurate and visually stunning. It is powered by Photorealistic 3D Tiles and ARCore from Google Maps Platform and can be used with Unity or Adobe Aero. Geospatial Creator provides a 3D view of the world, allowing users to place their digital content in the real world, similar to Google Earth and Google Street View. , In April 2023, Hexagon AB launched the HxGN AgrOn Control Room. It is a mobile app that allows managers and directors of agricultural companies to monitor all field operations in real time. It helps managers identify and address problems quickly, saving time and money. Additionally, the app can help to improve safety by providing managers with a way to monitor the location and status of field workers. , In December 2022, ESRI India announced the availability of Indo ArcGIS offerings on Indian public clouds and services to provide better management, collecting, forecasting, and analyzing location-based data. , In May 2022, Trimble announced the launch of the Trimble R12i GNSS receiver, which has a powerful tilt adjustment feature. It enables land surveyors to concentrate on the task and finish it more quickly and precisely. , In May 2021, Foursquare purchased Unfolded, a US-based provider of location-based services. This US-based firm provides location-based services and goods, including data enrichment analytics and geographic data visualization. With this acquisition, Foursquare aims to provide its users access to various first and third-party data sets and integrate them with the geographical characteristics. , In January 2021, ESRI, a U.S.-based geospatial image analytics solutions provider, introduced the ArcGIS platform. ArcGIS Platform by ESRI operates on a cloud consumption paradigm. App developers generally use this technology to figure out how to include location capabilities in their apps, business operations, and goods. It aids in making geospatial technologies accessible. .

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.

This geodatabase reflects the U.S. Geological Survey’s (USGS) ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports in Africa. The geodatabase and geospatial data layers serve to create a new geographic information product in the form of a geospatial portable document format (PDF) map. The geodatabase contains data layers from USGS, foreign governmental, and open-source sources as follows: (1) mineral production and processing facilities, (2) mineral exploration and development sites, (3) mineral occurrence sites and deposits, (4) undiscovered mineral resource tracts for Gabon and Mauritania, (5) undiscovered mineral resource tracts for potash, platinum-group elements, and copper, (6) coal occurrence areas, (7) electric power generating facilities, (8) electric power transmission lines, (9) liquefied natural gas terminals, (10) oil and gas pipelines, (11) undiscovered, technically recoverable conventional and continuous hydrocarbon resources (by USGS geologic/petroleum province), (12) cumulative production, and recoverable conventional resources (by oil- and gas-producing nation), (13) major mineral exporting maritime ports, (14) railroads, (15) major roads, (16) major cities, (17) major lakes, (18) major river systems, (19) first-level administrative division (ADM1) boundaries for all countries in Africa, and (20) international boundaries for all countries in Africa.

The geospatial solutions market is experiencing robust growth, driven by increasing adoption of location intelligence across diverse sectors. The market, estimated at $100 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $350 billion by 2033. This significant expansion is fueled by several key factors. Firstly, advancements in technologies such as AI, machine learning, and big data analytics are enabling more sophisticated geospatial data analysis and applications. Secondly, the rising demand for precise location-based services across industries like transportation, logistics, agriculture, and urban planning is boosting market growth. Thirdly, governments worldwide are investing heavily in infrastructure development projects, demanding advanced geospatial solutions for efficient planning and management. Finally, the proliferation of smart devices and the Internet of Things (IoT) is generating an unprecedented volume of location data, creating a fertile ground for innovative geospatial applications. However, the market's growth trajectory is not without its challenges. Data security and privacy concerns are becoming increasingly prominent, requiring robust data protection measures. The high cost of acquiring and processing geospatial data can limit adoption, especially among small and medium-sized enterprises (SMEs). Furthermore, the complexity of integrating geospatial technologies into existing systems can pose a barrier to entry for some organizations. Despite these restraints, the long-term outlook for the geospatial solutions market remains positive, with continued technological advancements and increasing demand expected to drive substantial market expansion in the coming years. The competitive landscape is marked by the presence of both established players and emerging innovators, creating a dynamic and evolving market. Key players include HERE Technologies, Esri, Hexagon, and Google, among others, constantly striving to innovate and meet the growing demands of various industries.