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The global location analysis market is experiencing robust growth, driven by the increasing adoption of location intelligence across diverse sectors. The market, valued at approximately $15 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching an estimated market size of $45 billion by 2033. This expansion is fueled by several key factors. The rise of big data and advanced analytics empowers businesses to leverage location data for improved decision-making, resulting in enhanced operational efficiency and competitive advantage. Furthermore, the burgeoning adoption of IoT devices generates massive location-based data streams, further fueling market growth. Key application areas driving demand include banking and financial services (risk assessment, branch optimization), medical and life sciences (epidemic monitoring, healthcare resource allocation), and retail and consumer goods (targeted advertising, supply chain optimization). Technological advancements, such as the integration of AI and machine learning into location analytics platforms, are also contributing to this market's upward trajectory. The market is segmented geographically, with North America currently holding a significant share, followed by Europe and Asia-Pacific. However, rapidly developing economies in Asia-Pacific, particularly India and China, are expected to witness substantial growth in the coming years, driven by increasing digitalization and infrastructure development. While the market faces some restraints, such as data privacy concerns and the high cost of implementation of advanced location analytics solutions, these challenges are anticipated to be mitigated by the development of robust data security protocols and more cost-effective solutions. The competitive landscape is characterized by the presence of both established technology giants like IBM, Google, and Oracle, and specialized location analytics providers like ESRI and TomTom, fostering innovation and competition within the market. This dynamic environment ensures a continued trajectory of growth and advancement in location analysis technologies and applications.
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The global market size for Location Intelligence (LI) and Location Analytics is projected to grow from $XX billion in 2023 to $XX billion by 2032, exhibiting a CAGR of XX%. This remarkable growth is driven by the increasing adoption of geospatial data in business operations and the rising demand for location-based services in various industries.
One of the primary growth factors for the Location Intelligence and Location Analytics market is the proliferation of Internet of Things (IoT) devices. These devices generate vast amounts of location-based data that can be analyzed to provide valuable insights. Companies are increasingly recognizing the importance of leveraging this data to enhance operational efficiency, improve customer experience, and drive strategic decision-making. The integration of artificial intelligence (AI) and machine learning (ML) with Location Analytics further enhances the ability to process and analyze large datasets, providing more accurate and actionable insights.
Another significant driver is the growing need for real-time location-based services. In sectors such as retail, transportation, and logistics, real-time location analytics enable businesses to track assets, monitor workforce movements, and manage facilities more effectively. This real-time data helps in optimizing routes, reducing fuel consumption, and improving overall productivity. Additionally, the COVID-19 pandemic has accelerated the adoption of location-based services for contact tracing, social distancing monitoring, and ensuring workplace safety, further propelling market growth.
Advancements in geographic information systems (GIS) and the increasing availability of high-resolution satellite imagery are also contributing to market expansion. Modern GIS platforms offer sophisticated tools for spatial analysis, mapping, and visualization, enabling organizations to derive meaningful insights from complex geospatial data. The integration of location analytics with business intelligence (BI) tools allows for comprehensive analysis and visualization of data, leading to better strategic planning and decision-making.
Regionally, North America is expected to hold the largest market share, driven by the presence of major technology companies and early adoption of advanced technologies. The Asia Pacific region is anticipated to witness the highest growth rate, fueled by rapid urbanization, increasing investments in smart city projects, and the expanding e-commerce sector. Europe, Latin America, and the Middle East & Africa are also expected to contribute significantly to the market growth, with various industries adopting location-based services to enhance operational efficiency and customer engagement.
The Location Intelligence and Location Analytics market is segmented into two main components: Software and Services. The Software segment dominates the market, driven by the increasing demand for sophisticated analytics tools that can process and visualize geospatial data. Advanced software solutions offer capabilities such as spatial analysis, mapping, and real-time data processing, enabling businesses to gain deeper insights into their operations and customer behavior. The integration of AI and ML with location analytics software further enhances its analytical capabilities, making it a crucial component for businesses seeking to leverage geospatial data.
Within the Software segment, geographic information systems (GIS) and business intelligence (BI) tools play a pivotal role. GIS platforms provide extensive functionalities for spatial data analysis, mapping, and visualization, allowing organizations to derive actionable insights from complex datasets. The integration of BI tools with location analytics enables businesses to perform comprehensive analyses and generate interactive dashboards, facilitating informed decision-making. The increasing adoption of cloud-based software solutions is also driving market growth, offering scalability, flexibility, and cost-effectiveness to businesses of all sizes.
The Services segment encompasses various professional and managed services that support the deployment and utilization of location analytics solutions. Consulting services assist organizations in identifying their specific needs and developing customized solutions, while implementation services ensure seamless integration of location analytics tools with existing systems. Managed services provide ongoing support, maintenance, and optimization of location analy
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,
Xverum’s Point of Interest (POI) Data is a comprehensive dataset containing 230M+ verified locations across 5000 business categories. Our dataset delivers structured geographic data, business attributes, location intelligence, and mapping insights, making it an essential tool for GIS applications, market research, urban planning, and competitive analysis.
With regular updates and continuous POI discovery, Xverum ensures accurate, up-to-date information on businesses, landmarks, retail stores, and more. Delivered in bulk to S3 Bucket and cloud storage, our dataset integrates seamlessly into mapping, geographic information systems, and analytics platforms.
🔥 Key Features:
Extensive POI Coverage: ✅ 230M+ Points of Interest worldwide, covering 5000 business categories. ✅ Includes retail stores, restaurants, corporate offices, landmarks, and service providers.
Geographic & Location Intelligence Data: ✅ Latitude & longitude coordinates for mapping and navigation applications. ✅ Geographic classification, including country, state, city, and postal code. ✅ Business status tracking – Open, temporarily closed, or permanently closed.
Continuous Discovery & Regular Updates: ✅ New POIs continuously added through discovery processes. ✅ Regular updates ensure data accuracy, reflecting new openings and closures.
Rich Business Insights: ✅ Detailed business attributes, including company name, category, and subcategories. ✅ Contact details, including phone number and website (if available). ✅ Consumer review insights, including rating distribution and total number of reviews (additional feature). ✅ Operating hours where available.
Ideal for Mapping & Location Analytics: ✅ Supports geospatial analysis & GIS applications. ✅ Enhances mapping & navigation solutions with structured POI data. ✅ Provides location intelligence for site selection & business expansion strategies.
Bulk Data Delivery (NO API): ✅ Delivered in bulk via S3 Bucket or cloud storage. ✅ Available in structured format (.json) for seamless integration.
🏆Primary Use Cases:
Mapping & Geographic Analysis: 🔹 Power GIS platforms & navigation systems with precise POI data. 🔹 Enhance digital maps with accurate business locations & categories.
Retail Expansion & Market Research: 🔹 Identify key business locations & competitors for market analysis. 🔹 Assess brand presence across different industries & geographies.
Business Intelligence & Competitive Analysis: 🔹 Benchmark competitor locations & regional business density. 🔹 Analyze market trends through POI growth & closure tracking.
Smart City & Urban Planning: 🔹 Support public infrastructure projects with accurate POI data. 🔹 Improve accessibility & zoning decisions for government & businesses.
💡 Why Choose Xverum’s POI Data?
Access Xverum’s 230M+ POI dataset for mapping, geographic analysis, and location intelligence. Request a free sample or contact us to customize your dataset today!
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The global location analytics market size was valued at approximately USD 18.2 billion in 2023 and is projected to reach around USD 65.4 billion by 2032, growing at a robust CAGR of 15.2% during the forecast period from 2024 to 2032. This impressive growth can be attributed to the escalating demand for spatial data and analytical solutions across various industries, aiming to enhance decision-making processes and optimize business operations.
One of the primary growth factors driving the location analytics market is the increasing use of smartphones and the proliferation of Internet of Things (IoT) devices. These advancements have led to an explosion of location-based data, offering businesses the capability to analyze real-time information and make informed decisions. Moreover, the integration of location analytics with Geographic Information System (GIS) technologies has further enhanced the scope of applications, making it indispensable for sectors such as retail, transportation, and healthcare.
Another significant growth driver is the rising need for businesses to gain a competitive edge through location-based insights. Companies are leveraging location analytics to understand customer behaviors, optimize supply chains, and enhance marketing strategies. For instance, retail businesses are increasingly using location analytics to determine ideal store locations, manage inventory efficiently, and provide personalized customer experiences. Similarly, in the transportation and logistics sector, location analytics is crucial for route optimization, fleet management, and reducing operational costs.
The emergence of advanced technologies such as artificial intelligence (AI) and machine learning (ML) is also catalyzing the growth of the location analytics market. By incorporating AI and ML algorithms, location analytics solutions can offer predictive insights and trend analyses, enabling businesses to anticipate market changes and act proactively. This technological advancement is particularly beneficial for risk management and emergency response applications, where timely and accurate data is critical.
In this context, Points-of-Interest (POI) Data Solutions have emerged as a crucial component in the location analytics ecosystem. POI data provides detailed information about specific locations, such as businesses, landmarks, and other significant places, which can be leveraged by companies to enhance their spatial analysis capabilities. By integrating POI data, businesses can gain deeper insights into consumer behavior, optimize location-based services, and improve decision-making processes. This data is particularly valuable for sectors like retail and hospitality, where understanding the proximity and accessibility of various points of interest can significantly impact customer engagement and operational efficiency. As the demand for precise and comprehensive location data continues to grow, POI Data Solutions are set to play a pivotal role in advancing the capabilities of location analytics platforms.
Regionally, North America is expected to dominate the location analytics market due to the early adoption of advanced technologies and the presence of major market players in the region. Additionally, the Asia Pacific region is anticipated to witness significant growth, driven by the rapid urbanization, increasing smartphone penetration, and government initiatives promoting smart city projects. Europe is also poised for substantial growth, supported by stringent data regulations and the growing demand for spatial data analytics in various industries.
The location analytics market can be segmented by component into software and services. The software segment includes tools and platforms that facilitate spatial data analysis, while the services segment encompasses consulting, integration, and maintenance services. The software segment is expected to hold a significant market share due to the increasing adoption of location analytics software solutions by enterprises to gain actionable insights from spatial data. These software solutions are designed to integrate seamlessly with existing business systems, providing users with real-time data analysis and visualization capabilities.
Location analytics software is further categorized into desktop, mobile, and web-based platforms. Desktop solutions are traditionally used for comprehensive geospati
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The Location Analytics Tools market is experiencing robust growth, projected to reach $15 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 16.93% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing adoption of location-based services across diverse sectors like transportation, retail, BFSI (Banking, Financial Services, and Insurance), media and entertainment, and telecommunications is a significant factor. Businesses are leveraging location data to optimize operations, personalize customer experiences, and gain a competitive edge. Furthermore, advancements in technologies such as GPS, GIS (Geographic Information System), and big data analytics are enabling more sophisticated location intelligence solutions. The market is segmented by end-user and type of location (outdoor and indoor), reflecting the diverse applications of these tools. North America currently holds a significant market share due to early adoption and the presence of major technology companies, but the Asia-Pacific region is expected to witness substantial growth in the coming years driven by increasing digitalization and infrastructure development. Competitive dynamics are shaped by a mix of established players like Google (Alphabet Inc.), Microsoft, and IBM, and innovative startups offering specialized solutions. These companies are employing various competitive strategies, including mergers and acquisitions, partnerships, and product innovation, to secure market share and cater to the evolving needs of businesses. The market faces certain restraints, such as data privacy concerns and the complexity involved in integrating location analytics into existing systems. However, the overall growth trajectory remains positive, indicating significant opportunities for market participants. The forecast period (2025-2033) anticipates continued expansion, driven by rising demand for real-time location intelligence and the increasing availability of high-quality location data. The transportation sector, for instance, benefits from route optimization and fleet management capabilities offered by these tools, while retailers utilize them for targeted advertising and store location analysis. The BFSI sector uses location analytics for risk management and fraud detection, highlighting the versatility of this market. The growing integration of location analytics with other emerging technologies like IoT (Internet of Things) and AI (Artificial Intelligence) further enhances its capabilities, promising even more innovative applications in the future. This convergence is expected to further accelerate market growth and drive innovation in location-based services, solidifying the long-term prospects of this dynamic market.
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The Location Intelligence Analytics market is experiencing robust growth, driven by increasing adoption of location-based services across diverse sectors. The market size in 2025 is estimated at $15 billion, projected to expand at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant growth is fueled by several key factors. The rising availability of granular location data from various sources, including GPS, mobile devices, and IoT sensors, is enabling businesses to gain deeper insights into customer behavior, optimize operations, and improve decision-making. Furthermore, advancements in analytics techniques, such as machine learning and AI, are enhancing the capabilities of location intelligence platforms, allowing for more sophisticated analysis and prediction. The growing adoption of cloud-based solutions is also contributing to market expansion, providing scalability and cost-effectiveness. Major industries like BFSI (Banking, Financial Services, and Insurance), Healthcare, and Retail are significantly contributing to this growth, leveraging location analytics for targeted marketing campaigns, risk management, and supply chain optimization. The market segmentation reveals strong growth across various sectors. BFSI utilizes location intelligence for fraud detection, branch optimization, and targeted financial services. Healthcare benefits from improved patient care, efficient resource allocation, and epidemiological analysis. The retail sector leverages location analytics for optimizing store locations, understanding customer foot traffic, and personalizing marketing strategies. Government and utility companies employ location analytics for infrastructure management, emergency response, and resource planning. The competitive landscape is characterized by a mix of established players, such as SAP, IBM, Oracle, and Microsoft, and specialized location intelligence vendors. These companies are constantly innovating to meet the evolving needs of businesses and enhance their offerings through strategic partnerships and acquisitions. The global spread of the market, with significant regional presence in North America, Europe, and Asia Pacific, indicates a widespread demand for location intelligence solutions.
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The Location Intelligence Data Solution market is experiencing robust growth, projected to reach $1013.3 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 8.8% from 2025 to 2033. This expansion is driven by several key factors. Increasing reliance on data-driven decision-making across industries like retail, logistics, and finance fuels the demand for location-based insights. Furthermore, advancements in technologies such as GPS, GIS, and big data analytics are enhancing the accuracy and scope of location intelligence, providing more granular and actionable information. The rise of mobile devices and the proliferation of location data further contribute to market growth. Competitive pressures and the need for optimized resource allocation are also pushing businesses to leverage location intelligence for improved operational efficiency and strategic planning. The market is segmented by various deployment models (cloud, on-premise), data types (geographic, demographic), and industry verticals. While data privacy concerns and the complexity of integrating location data into existing systems present challenges, the overall market outlook remains positive, indicating substantial growth opportunities for vendors specializing in location intelligence solutions. The competitive landscape is dynamic, featuring established players like Esri and Alteryx alongside emerging innovative companies like Carto and Geoblink. These companies compete based on their data coverage, analytical capabilities, ease of use, and pricing strategies. The market is witnessing a shift towards cloud-based solutions due to their scalability and cost-effectiveness. Further growth drivers include the increasing adoption of IoT devices generating location data and the rising demand for real-time location tracking. The forecast period anticipates continued growth, with new applications of location intelligence emerging in areas such as smart cities, precision agriculture, and environmental monitoring. Companies are investing heavily in research and development to enhance the accuracy, speed, and accessibility of their location intelligence platforms. This investment, combined with the growing market need, ensures sustained market expansion.
Dataset for the textbook Computational Methods and GIS Applications in Social Science (3rd Edition), 2023 Fahui Wang, Lingbo Liu Main Book Citation: Wang, F., & Liu, L. (2023). Computational Methods and GIS Applications in Social Science (3rd ed.). CRC Press. https://doi.org/10.1201/9781003292302 KNIME Lab Manual Citation: Liu, L., & Wang, F. (2023). Computational Methods and GIS Applications in Social Science - Lab Manual. CRC Press. https://doi.org/10.1201/9781003304357 KNIME Hub Dataset and Workflow for Computational Methods and GIS Applications in Social Science-Lab Manual Update Log If Python package not found in Package Management, use ArcGIS Pro's Python Command Prompt to install them, e.g., conda install -c conda-forge python-igraph leidenalg NetworkCommDetPro in CMGIS-V3-Tools was updated on July 10,2024 Add spatial adjacency table into Florida on June 29,2024 The dataset and tool for ABM Crime Simulation were updated on August 3, 2023, The toolkits in CMGIS-V3-Tools was updated on August 3rd,2023. Report Issues on GitHub https://github.com/UrbanGISer/Computational-Methods-and-GIS-Applications-in-Social-Science Following the website of Fahui Wang : http://faculty.lsu.edu/fahui Contents Chapter 1. Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools Case Study 1: Mapping and Analyzing Population Density Pattern in Baton Rouge, Louisiana Chapter 2. Measuring Distance and Travel Time and Analyzing Distance Decay Behavior Case Study 2A: Estimating Drive Time and Transit Time in Baton Rouge, Louisiana Case Study 2B: Analyzing Distance Decay Behavior for Hospitalization in Florida Chapter 3. Spatial Smoothing and Spatial Interpolation Case Study 3A: Mapping Place Names in Guangxi, China Case Study 3B: Area-Based Interpolations of Population in Baton Rouge, Louisiana Case Study 3C: Detecting Spatiotemporal Crime Hotspots in Baton Rouge, Louisiana Chapter 4. Delineating Functional Regions and Applications in Health Geography Case Study 4A: Defining Service Areas of Acute Hospitals in Baton Rouge, Louisiana Case Study 4B: Automated Delineation of Hospital Service Areas in Florida Chapter 5. GIS-Based Measures of Spatial Accessibility and Application in Examining Healthcare Disparity Case Study 5: Measuring Accessibility of Primary Care Physicians in Baton Rouge Chapter 6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns Case Study 6: Analyzing Population Density Patterns in Chicago Urban Area >Chapter 7. Principal Components, Factor and Cluster Analyses and Application in Social Area Analysis Case Study 7: Social Area Analysis in Beijing Chapter 8. Spatial Statistics and Applications in Cultural and Crime Geography Case Study 8A: Spatial Distribution and Clusters of Place Names in Yunnan, China Case Study 8B: Detecting Colocation Between Crime Incidents and Facilities Case Study 8C: Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago Chapter 9. Regionalization Methods and Application in Analysis of Cancer Data Case Study 9: Constructing Geographical Areas for Mapping Cancer Rates in Louisiana Chapter 10. System of Linear Equations and Application of Garin-Lowry in Simulating Urban Population and Employment Patterns Case Study 10: Simulating Population and Service Employment Distributions in a Hypothetical City Chapter 11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers Case Study 11A: Measuring Wasteful Commuting in Columbus, Ohio Case Study 11B: Location-Allocation Analysis of Hospitals in Rural China Chapter 12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations Case Study 12A. Examining Zonal Effect on Urban Population Density Functions in Chicago by Monte Carlo Simulation Case Study 12B: Monte Carlo-Based Traffic Simulation in Baton Rouge, Louisiana Chapter 13. Agent-Based Model and Application in Crime Simulation Case Study 13: Agent-Based Crime Simulation in Baton Rouge, Louisiana Chapter 14. Spatiotemporal Big Data Analytics and Application in Urban Studies Case Study 14A: Exploring Taxi Trajectory in ArcGIS Case Study 14B: Identifying High Traffic Corridors and Destinations in Shanghai Dataset File Structure 1 BatonRouge Census.gdb BR.gdb 2A BatonRouge BR_Road.gdb Hosp_Address.csv TransitNetworkTemplate.xml BR_GTFS Google API Pro.tbx 2B Florida FL_HSA.gdb R_ArcGIS_Tools.tbx (RegressionR) 3A China_GX GX.gdb 3B BatonRouge BR.gdb 3C BatonRouge BRcrime R_ArcGIS_Tools.tbx (STKDE) 4A BatonRouge BRRoad.gdb 4B Florida FL_HSA.gdb HSA Delineation Pro.tbx Huff Model Pro.tbx FLplgnAdjAppend.csv 5 BRMSA BRMSA.gdb Accessibility Pro.tbx 6 Chicago ChiUrArea.gdb R_ArcGIS_Tools.tbx (RegressionR) 7 Beijing BJSA.gdb bjattr.csv R_ArcGIS_Tools.tbx (PCAandFA, BasicClustering) 8A Yunnan YN.gdb R_ArcGIS_Tools.tbx (SaTScanR) 8B Jiangsu JS.gdb 8C Chicago ChiCity.gdb cityattr.csv ...
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In this seminar, you will learn about the spatial analysis tools built directly into the ArcGIS.com map viewer. You will learn of the spatial analysis capabilities in ArcGIS Online for Organizations, whether for analyzing your own data, data that's publicly available on ArcGIS Online, or a combination of both. You will learn the overall features and benefits of ArcGIS Online Analysis, how to get started, and how to choose the right approach in order to solve a specific spatial problem.
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The global Spatial Intelligence Software market is experiencing robust growth, driven by the increasing adoption of location analytics across various industries. This market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching an impressive $45 billion by 2033. This significant expansion is fueled by several key factors. Firstly, the rising availability of geospatial data and advanced analytical tools empowers businesses to derive actionable insights from location data, optimizing operations, improving decision-making, and gaining a competitive edge. Secondly, the increasing adoption of cloud-based solutions offers scalable and cost-effective access to spatial intelligence capabilities for organizations of all sizes, from large enterprises to SMEs. Furthermore, emerging trends such as the Internet of Things (IoT), the increasing sophistication of mapping and visualization technologies, and the growing demand for real-time location analytics are further accelerating market growth. However, certain restraints also influence market expansion. High implementation costs, particularly for complex solutions and the need for specialized expertise to effectively utilize spatial intelligence software, can hinder adoption, especially among smaller businesses. Data security concerns and the complexity of integrating geospatial data with existing business systems also pose challenges. Nevertheless, the overall market outlook remains positive, with the continuous advancements in technology and the rising recognition of the value proposition of spatial intelligence expected to outweigh these challenges. The market is segmented by application (Large Enterprises, SMEs) and type (Cloud-Based, Web-Based), with cloud-based solutions gaining significant traction due to their flexibility and accessibility. Key players in this dynamic market include Alteryx, Caliper Corporation, CartoDB, and many others, constantly innovating to meet the evolving needs of businesses across diverse sectors.
The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (guis_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (guis_geomorphology_metadata_faq.pdf). Please read the guis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (guis_geomorphology_metadata.txt or guis_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).
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The global location analysis market size was valued at approximately USD 15.8 billion in 2023 and is projected to reach around USD 43.2 billion by 2032, growing at a CAGR of 12.1% during the forecast period. The market is being propelled by increasing demand for real-time data analytics, advancements in geospatial data technologies, and the rising adoption of IoT devices that require precise location data for various applications.
One of the primary growth factors driving the location analysis market is the burgeoning need for real-time location data to enhance business operations and customer experiences. Companies are increasingly relying on location-based services to optimize supply chain management, improve customer engagement, and gain competitive advantage by leveraging geospatial intelligence. Furthermore, the proliferation of smartphones and connected devices has significantly increased the volume of location-based data available, providing businesses with valuable insights into consumer behavior and movement patterns.
Advancements in technology, such as the integration of artificial intelligence (AI) and machine learning (ML) with geospatial data, are further fueling the market's growth. These technologies enable more accurate predictions and sophisticated analytics, thereby improving decision-making processes across various industries. For instance, AI-driven location analysis can help in predicting foot traffic patterns in retail spaces, optimizing delivery routes in logistics, and even tracking the spread of diseases in healthcare settings. This technological integration is expected to continue evolving, offering new opportunities for market expansion.
Another significant factor contributing to the market's growth is the increasing adoption of IoT devices. As the number of connected devices continues to rise, there is a growing need for precise location data to ensure seamless operation and connectivity. Location analysis tools are essential for managing and optimizing IoT ecosystems, as they provide critical insights into device locations, movement patterns, and environmental conditions. This trend is particularly evident in sectors such as transportation and logistics, where IoT devices are used to track vehicle fleets, manage inventory, and monitor supply chains.
From a regional perspective, North America and Europe are currently leading the market, owing to their advanced technological infrastructure and high adoption rates of location-based services. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by rapid urbanization, increasing smartphone penetration, and significant investments in smart city initiatives. Latin America and the Middle East & Africa are also anticipated to experience substantial growth, albeit at a slower pace, due to ongoing infrastructural developments and increasing awareness of location-based analytics benefits.
The location analysis market is segmented by components into software and services. The software segment encompasses a wide range of solutions such as geographic information systems (GIS), mapping and navigation software, and location-based data analytics platforms. These software solutions are pivotal for businesses to visualize and interpret spatial data, enabling them to make informed decisions. The increasing complexity and volume of location-based data are driving the demand for sophisticated software solutions that can handle large datasets and provide real-time analytics.
In the services segment, offerings include consulting, system integration, and support and maintenance services. Consulting services are crucial for businesses to understand the potential applications and benefits of location analysis within their specific contexts. System integration services ensure that location data and analytics tools are seamlessly integrated with existing IT infrastructure, enabling smooth operation and data flow. Support and maintenance services are essential for ensuring the continuous and efficient functioning of location analysis systems, addressing any issues or updates as needed.
The software segment is anticipated to hold the largest market share during the forecast period, driven by the growing adoption of advanced analytics tools and the need for real-time data processing. However, the services segment is also expected to witness significant growth, as businesses increasingly seek expert guidance and support to implement and optimize locati
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The Regional Crime Analysis GIS (RCAGIS) is an Environmental Systems Research Institute (ESRI) MapObjects-based system that was developed by the United States Department of Justice Criminal Division Geographic Information Systems (GIS) Staff, in conjunction with the Baltimore County Police Department and the Regional Crime Analysis System (RCAS) group, to facilitate the analysis of crime on a regional basis. The RCAGIS system was designed specifically to assist in the analysis of crime incident data across jurisdictional boundaries. Features of the system include: (1) three modes, each designed for a specific level of analysis (simple queries, crime analysis, or reports), (2) wizard-driven (guided) incident database queries, (3) graphical tools for the creation, saving, and printing of map layout files, (4) an interface with CrimeStat spatial statistics software developed by Ned Levine and Associates for advanced analysis tools such as hot spot surfaces and ellipses, (5) tools for graphically viewing and analyzing historical crime trends in specific areas, and (6) linkage tools for drawing connections between vehicle theft and recovery locations, incident locations and suspects' homes, and between attributes in any two loaded shapefiles. RCAGIS also supports digital imagery, such as orthophotos and other raster data sources, and geographic source data in multiple projections. RCAGIS can be configured to support multiple incident database backends and varying database schemas using a field mapping utility.
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The global location intelligence analytics market size is projected to grow from USD 14.2 billion in 2023 to USD 31.7 billion by 2032, exhibiting a CAGR of approximately 9.4% during the forecast period. This robust growth is primarily driven by the increasing demand for spatial data and analytical tools across various industries to enhance decision-making processes and optimize business operations. As organizations increasingly recognize the value of location-based insights, they are investing in sophisticated analytics solutions that leverage geographic data to drive business outcomes and gain competitive advantages.
One of the primary growth factors for the location intelligence analytics market is the proliferation of IoT devices and the consequent surge in location-based data generation. With billions of connected devices expected to be operational in the coming years, the volume of location-specific data is set to explode. Businesses across industries are eager to harness this data to gain insights into consumer behavior, improve operational efficiency, and develop targeted marketing strategies. Moreover, advancements in AI and machine learning are enabling more sophisticated analysis of location data, providing deeper insights and predictive capabilities that are invaluable to enterprises.
Another significant driver for market growth is the growing adoption of smart city initiatives across the globe. Governments and municipalities are increasingly implementing location intelligence solutions to enhance urban planning, traffic management, and public safety. By leveraging location-based analytics, cities can optimize resource allocation, improve citizen services, and drive sustainable development. Furthermore, the integration of real-time data from various sources, such as sensors and social media, with geographic information systems (GIS) is facilitating more dynamic and responsive urban management systems, thus propelling the demand for location intelligence analytics.
The increasing emphasis on business intelligence and data-driven decision-making is also fueling the demand for location intelligence analytics. In today's competitive landscape, organizations are seeking to leverage every bit of data to gain actionable insights and stay ahead. Location intelligence provides a unique perspective by overlaying geographic data on traditional business data, offering a holistic view of trends and patterns. This capability is particularly valuable in sectors such as retail, transportation, and logistics, where location-based insights can directly impact revenue generation, cost savings, and customer satisfaction.
Regionally, North America is expected to hold the largest share of the location intelligence analytics market, driven by the presence of major technology companies and the rapid adoption of advanced analytics solutions across industries. The region's commitment to innovation and technological advancement is further supported by substantial investments in R&D activities. Additionally, Europe is anticipated to witness significant growth, influenced by stringent regulatory frameworks and a heightened focus on data privacy and security. In contrast, the Asia Pacific region is projected to demonstrate the highest growth rate, attributed to the rapid digital transformation and increasing investments in smart city projects across emerging economies like India and China.
The location intelligence analytics market is broadly segmented into software and services. Software solutions are a critical component of this market, offering the necessary tools and platforms for collecting, analyzing, and visualizing geographic data. These software solutions are designed to process large volumes of spatial data, integrate various data sources, and provide users with intuitive and interactive interfaces for data exploration. The advancements in cloud computing and the increasing adoption of Software as a Service (SaaS) models are further driving the demand for location intelligence software, as they offer greater scalability, flexibility, and cost-effectiveness to organizations of all sizes.
Within the software segment, Geographic Information System (GIS) solutions are particularly prominent. GIS technology enables the mapping and analysis of spatial data, allowing users to visualize relationships, patterns, and trends in complex datasets. The ability to integrate GIS with other enterprise systems, such as Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP), enhances its ut
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The Location Analytics market is experiencing robust growth, projected to reach a significant size by 2033. A Compound Annual Growth Rate (CAGR) of 19.70% from 2019 to 2024 suggests a substantial increase in market value. This expansion is driven by several key factors. The increasing availability and affordability of location data from various sources, including GPS, mobile devices, and IoT sensors, fuels the market's growth. Businesses across diverse sectors are leveraging location analytics to gain actionable insights for improved operational efficiency, targeted marketing campaigns, and better customer experiences. Furthermore, advancements in data analytics technologies, such as AI and machine learning, are enabling more sophisticated location-based analysis, further driving market adoption. The emergence of cloud-based location analytics platforms enhances accessibility and scalability for businesses of all sizes. However, the market also faces certain challenges. Data privacy concerns and regulations, such as GDPR, pose significant restraints. The complexity of integrating various data sources and the need for skilled professionals to interpret and utilize the insights can also hinder wider market penetration. Despite these challenges, the long-term outlook for the location analytics market remains optimistic. The continued proliferation of connected devices and the rising demand for data-driven decision-making across industries will propel further growth. Market segmentation reveals strong performance across various sectors including retail, transportation and logistics, and government, with North America and Europe currently holding the largest market shares. The increasing adoption of location analytics in emerging economies like those within the Asia-Pacific region promises substantial future growth potential. The competitive landscape is characterized by a mix of established players, including Microsoft, Salesforce (through Tableau), and SAS, and emerging pure-play vendors like Google and TomTom, indicating a dynamic and innovative market. Recent developments include: November 2021 - Noogata announced the launch of its location analytics library. Building on the success of its existing e-commerce library, the location analytics library applies the power of Noogata's no code AI data analytics platform to physical locations for consumer packaged goods (CPG) brands., December 2020 - Microsoft unveiled a 'unified data governance service' as part of its Azure cloud platform, Azure Purview, that can discover and catalog all of an organization's data across all environments and locations.. Key drivers for this market are: Increasing Use of Spatial Data and Analytics in Various Industries, Growing Propensity of Consumers Toward Applications that Use Location Data. Potential restraints include: Increasing Use of Spatial Data and Analytics in Various Industries, Growing Propensity of Consumers Toward Applications that Use Location Data. Notable trends are: FMCG and E-Commerce Sector is Expected to Hold Significant Market Share.
Xverum’s Global GIS & Geospatial Data is a high-precision dataset featuring 230M+ verified points of interest across 249 countries. With rich metadata, structured geographic attributes, and continuous updates, our dataset empowers businesses, researchers, and governments to extract location intelligence and conduct advanced geospatial analysis.
Perfectly suited for GIS systems, mapping tools, and location intelligence platforms, this dataset covers everything from businesses and landmarks to public infrastructure, all classified into over 5000 categories. Whether you're planning urban developments, analyzing territories, or building location-based products, our data delivers unmatched coverage and accuracy.
Key Features: ✅ 230M+ Global POIs Includes commercial, governmental, industrial, and service locations - updated regularly for accurate relevance.
✅ Comprehensive Geographic Coverage Worldwide dataset covering 249 countries, with attributes including latitude, longitude, city, country code, postal code, etc.
✅ Detailed Mapping Metadata Get structured address data, place names, categories, and location, which are ideal for map visualization and geospatial modeling.
✅ Bulk Delivery for GIS Platforms Available in .json - delivered via S3 Bucket or cloud storage for easy integration into ArcGIS, QGIS, Mapbox, and similar systems.
✅ Continuous Discovery & Refresh New POIs added and existing ones refreshed on a regular refresh cycle, ensuring reliable, up-to-date insights.
✅ Compliance & Scalability 100% compliant with global data regulations and scalable for enterprise use across mapping, urban planning, and retail analytics.
Use Cases: 📍 Location Intelligence & Market Analysis Identify high-density commercial zones, assess regional activity, and understand spatial relationships between locations.
🏙️ Urban Planning & Smart City Development Design infrastructure, zoning plans, and accessibility strategies using accurate location-based data.
🗺️ Mapping & Navigation Enrich digital maps with verified business listings, categories, and address-level geographic attributes.
📊 Retail Site Selection & Expansion Analyze proximity to key POIs for smarter retail or franchise placement.
📌 Risk & Catchment Area Assessment Evaluate location clusters for insurance, logistics, or regional outreach strategies.
Why Xverum? ✅ Global Coverage: One of the largest POI geospatial databases on the market ✅ Location Intelligence Ready: Built for GIS platforms and spatial analysis use ✅ Continuously Updated: New POIs discovered and refreshed regularly ✅ Enterprise-Friendly: Scalable, compliant, and customizable ✅ Flexible Delivery: Structured format for smooth data onboarding
Request a free sample and discover how Xverum’s geospatial data can power your mapping, planning, and spatial analysis projects.
GIS Market Size 2025-2029
The GIS market size is forecast to increase by USD 24.07 billion, at a CAGR of 20.3% between 2024 and 2029.
The Global Geographic Information System (GIS) market is experiencing significant growth, driven by the increasing integration of Building Information Modeling (BIM) and GIS technologies. This convergence enables more effective spatial analysis and decision-making in various industries, particularly in soil and water management. However, the market faces challenges, including the lack of comprehensive planning and preparation leading to implementation failures of GIS solutions. Companies must address these challenges by investing in thorough project planning and collaboration between GIS and BIM teams to ensure successful implementation and maximize the potential benefits of these advanced technologies.
By focusing on strategic planning and effective implementation, organizations can capitalize on the opportunities presented by the growing adoption of GIS and BIM technologies, ultimately driving operational efficiency and innovation.
What will be the Size of the GIS Market during the forecast period?
Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The global Geographic Information Systems (GIS) market continues to evolve, driven by the increasing demand for advanced spatial data analysis and management solutions. GIS technology is finding applications across various sectors, including natural resource management, urban planning, and infrastructure management. The integration of Bing Maps, terrain analysis, vector data, Lidar data, and Geographic Information Systems enables precise spatial data analysis and modeling. Hydrological modeling, spatial statistics, spatial indexing, and route optimization are essential components of GIS, providing valuable insights for sectors such as public safety, transportation planning, and precision agriculture. Location-based services and data visualization further enhance the utility of GIS, enabling real-time mapping and spatial analysis.
The ongoing development of OGC standards, spatial data infrastructure, and mapping APIs continues to expand the capabilities of GIS, making it an indispensable tool for managing and analyzing geospatial data. The continuous unfolding of market activities and evolving patterns in the market reflect the dynamic nature of this technology and its applications.
How is this GIS Industry segmented?
The GIS industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.
Product
Software
Data
Services
Type
Telematics and navigation
Mapping
Surveying
Location-based services
Device
Desktop
Mobile
Geography
North America
US
Canada
Europe
France
Germany
UK
Middle East and Africa
UAE
APAC
China
Japan
South Korea
South America
Brazil
Rest of World (ROW)
By Product Insights
The software segment is estimated to witness significant growth during the forecast period.
The Global Geographic Information System (GIS) market encompasses a range of applications and technologies, including raster data, urban planning, geospatial data, geocoding APIs, GIS services, routing APIs, aerial photography, satellite imagery, GIS software, geospatial analytics, public safety, field data collection, transportation planning, precision agriculture, OGC standards, location intelligence, remote sensing, asset management, network analysis, spatial analysis, infrastructure management, spatial data standards, disaster management, environmental monitoring, spatial modeling, coordinate systems, spatial overlay, real-time mapping, mapping APIs, spatial join, mapping applications, smart cities, spatial data infrastructure, map projections, spatial databases, natural resource management, Bing Maps, terrain analysis, vector data, Lidar data, and geographic information systems.
The software segment includes desktop, mobile, cloud, and server solutions. Open-source GIS software, with its industry-specific offerings, poses a challenge to the market, while the adoption of cloud-based GIS software represents an emerging trend. However, the lack of standardization and interoperability issues hinder the widespread adoption of cloud-based solutions. Applications in sectors like public safety, transportation planning, and precision agriculture are driving market growth. Additionally, advancements in technologies like remote sensing, spatial modeling, and real-time mapping are expanding the market's scope.
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The Software segment was valued at USD 5.06 billion in 2019
The Digital Geomorphologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (sahi_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (sahi_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (sahi_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (sahi_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (sahi_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (sahi_geomorphology_metadata_faq.pdf). Please read the sahi_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Rutgers University, Institute of Marine and Coastal Sciences. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (sahi_geomorphology_metadata.txt or sahi_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:6,000 and United States National Map Accuracy Standards features are within (horizontally) 5.1 meters or 16.7 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).
GapMaps Live is an easy-to-use location intelligence platform available across 25 countries globally that allows you to visualise your own store data, combined with the latest demographic, economic and population movement intel right down to the micro level so you can make faster, smarter and surer decisions when planning your network growth strategy.
With one single login, you can access the latest estimates on resident and worker populations, census metrics (eg. age, income, ethnicity), consuming class, retail spend insights and point-of-interest data across a range of categories including fast food, cafe, fitness, supermarket/grocery and more.
Some of the world's biggest brands including McDonalds, Subway, Burger King, Anytime Fitness and Dominos use GapMaps Live as a vital strategic tool where business success relies on up-to-date, easy to understand, location intel that can power business case validation and drive rapid decision making.
Primary Use Cases for GapMaps Live includes:
Some of features our clients love about GapMaps Live include: - View business locations, competitor locations, demographic, economic and social data around your business or selected location - Understand consumer visitation patterns (“where from” and “where to”), frequency of visits, dwell time of visits, profiles of consumers and much more. - Save searched locations and drop pins - Turn on/off all location listings by category - View and filter data by metadata tags, for example hours of operation, contact details, services provided - Combine public data in GapMaps with views of private data Layers - View data in layers to understand impact of different data Sources - Share maps with teams - Generate demographic reports and comparative analyses on different locations based on drive time, walk time or radius. - Access multiple countries and brands with a single logon - Access multiple brands under a parent login - Capture field data such as photos, notes and documents using GapMaps Connect and integrate with GapMaps Live to get detailed insights on existing and proposed store locations.
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The global location analysis market is experiencing robust growth, driven by the increasing adoption of location intelligence across diverse sectors. The market, valued at approximately $15 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching an estimated market size of $45 billion by 2033. This expansion is fueled by several key factors. The rise of big data and advanced analytics empowers businesses to leverage location data for improved decision-making, resulting in enhanced operational efficiency and competitive advantage. Furthermore, the burgeoning adoption of IoT devices generates massive location-based data streams, further fueling market growth. Key application areas driving demand include banking and financial services (risk assessment, branch optimization), medical and life sciences (epidemic monitoring, healthcare resource allocation), and retail and consumer goods (targeted advertising, supply chain optimization). Technological advancements, such as the integration of AI and machine learning into location analytics platforms, are also contributing to this market's upward trajectory. The market is segmented geographically, with North America currently holding a significant share, followed by Europe and Asia-Pacific. However, rapidly developing economies in Asia-Pacific, particularly India and China, are expected to witness substantial growth in the coming years, driven by increasing digitalization and infrastructure development. While the market faces some restraints, such as data privacy concerns and the high cost of implementation of advanced location analytics solutions, these challenges are anticipated to be mitigated by the development of robust data security protocols and more cost-effective solutions. The competitive landscape is characterized by the presence of both established technology giants like IBM, Google, and Oracle, and specialized location analytics providers like ESRI and TomTom, fostering innovation and competition within the market. This dynamic environment ensures a continued trajectory of growth and advancement in location analysis technologies and applications.