However, you look at it, GIS is an unseen world, a space that represents graphs, polygon points and lines. Today, Big Data technology can presently process huge sets of data in the shortest curve, it has since become the new frontier for geospatial analysis. Big Data is represented by three Vs namely, volume, velocity and variety. Analyzing this data can be very challenging thanks to the improvement in the processing power of hardware and advancement of software developments which has increased the chances for using Big Data technology to process geospatial data.

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

Discover the booming Spatial Analysis Software market! Our in-depth analysis reveals a $5 billion market projected to reach $12.4 billion by 2033, driven by AI, cloud computing, and rising geospatial data. Learn about key trends, regional insights, and leading companies shaping this dynamic sector.

Learn how defense and intelligence users can leverage ArcGIS GeoEvent Server and ArcGIS GeoAnalytics Server to connect to real-time data feeds and run analytics on the stored data. From tracking units in the field to analyzing intelligence feeds and weather, ArcGIS GeoEvent Server enables users to stay current on what is happening. When you want to analyze massive amounts of stored track and report data, ArcGIS GeoAnalytics Server uses distributed computing to return spatiotemporal insight helping you make better planning decisions.

Geographic Information System (GIS) Market Outlook

The Geographic Information System (GIS) market is witnessing robust growth with its global market size projected to reach USD 25.7 billion by 2032, up from USD 8.7 billion in 2023, at a compound annual growth rate (CAGR) of 12.4% during the forecast period. This growth is primarily driven by the increasing integration of GIS technology across various industries to improve spatial data visualization, enhance decision-making, and optimize operations. The benefits offered by GIS in terms of accuracy, efficiency, and cost-effectiveness are convincing more sectors to adopt these systems, thereby expanding the market size significantly.

A major growth factor contributing to the GIS market expansion is the escalating demand for location-based services. As businesses across different sectors recognize the importance of spatial data analytics in driving strategic decisions, the reliance on GIS applications is becoming increasingly pronounced. The rise in IoT devices, coupled with the enhanced capabilities of AI and machine learning, has further fueled the demand for GIS solutions. These technologies enable the processing and analysis of large volumes of spatial data, thereby providing valuable insights that businesses can leverage for competitive advantage. In addition, government initiatives promoting the adoption of digital infrastructure and smart city projects are playing a crucial role in the growth of the GIS market.

The advancement in satellite imaging and remote sensing technologies is another key driver of the GIS market growth. With enhanced satellite capabilities, the precision and quality of geospatial data have significantly improved, making GIS applications more reliable and effective. The availability of high-resolution satellite imagery has opened new avenues in various sectors including agriculture, urban planning, and disaster management. Moreover, the decreasing costs of satellite data acquisition and the proliferation of drone technology are making GIS more accessible to small and medium enterprises, further expanding the market potential.

The advent of 3D Geospatial Technologies is revolutionizing the way industries utilize GIS data. By providing a three-dimensional perspective, these technologies enhance spatial analysis and visualization, offering more detailed and accurate representations of geographical areas. This advancement is particularly beneficial in urban planning, where 3D models can simulate cityscapes and infrastructure, allowing planners to visualize potential developments and assess their impact on the environment. Moreover, 3D geospatial data is proving invaluable in sectors such as construction and real estate, where it aids in site analysis and project planning. As these technologies continue to evolve, they are expected to play a pivotal role in the future of GIS, expanding its applications and driving further market growth.

Furthermore, the increasing application of GIS in environmental monitoring and management is bolstering market growth. With growing concerns over climate change and environmental degradation, GIS is being extensively used for resource management, biodiversity conservation, and natural disaster risk management. This trend is expected to continue as more organizations and governments prioritize sustainability, thereby driving the demand for advanced GIS solutions. The integration of GIS with other technologies such as big data analytics, and cloud computing is also expected to enhance its capabilities, making it an indispensable tool for environmental management.

Regionally, North America is currently leading the GIS market, driven by the widespread adoption of advanced technologies and the presence of major GIS vendors. The regionÂ’s focus on infrastructure development and smart city projects is further propelling the market growth. Europe is also witnessing significant growth owing to the increasing adoption of GIS in various industries such as agriculture and transportation. The Asia Pacific region is anticipated to exhibit the highest CAGR during the forecast period, attributed to rapid urbanization, government initiatives for digital transformation, and increasing investments in infrastructure development. In contrast, the markets in Latin America and the Middle East & Africa are growing steadily as these regions continue to explore and adopt GIS technologies.

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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.

This data set contains small-scale base GIS data layers compiled by the National Park Service Servicewide Inventory and Monitoring Program and Water Resources Division for use in a Baseline Water Quality Data Inventory and Analysis Report that was prepared for the park. The report presents the results of surface water quality data retrievals for the park from six of the United States Environmental Protection Agency's (EPA) national databases: (1) Storage and Retrieval (STORET) water quality database management system; (2) River Reach File (RF3) Hydrography; (3) Industrial Facilities Discharges; (4) Drinking Water Supplies; (5) Water Gages; and (6) Water Impoundments. The small-scale GIS data layers were used to prepare the maps included in the report that depict the locations of water quality monitoring stations, industrial discharges, drinking intakes, water gages, and water impoundments. The data layers included in the maps (and this dataset) vary depending on availability, but generally include roads, hydrography, political boundaries, USGS 7.5' minute quadrangle outlines, hydrologic units, trails, and others as appropriate. The scales of each layer vary depending on data source but are generally 1:100,000.

The global spatiotemporal big data platform market is booming, projected to reach $48.56 billion by 2033 with a 9.2% CAGR. Driven by smart city initiatives and environmental monitoring needs, this market offers immense opportunities for businesses. Learn about key players, market trends, and growth projections.

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 ...

The Geographic Information System (GIS) Services market is experiencing robust growth, driven by increasing adoption across various sectors. While the provided data lacks specific market size figures, based on industry reports and observed trends in related technology sectors, we can estimate a 2025 market size of approximately $15 billion USD. This reflects the significant investments being made in spatial data infrastructure and the growing demand for location-based analytics. Assuming a Compound Annual Growth Rate (CAGR) of 8%, the market is projected to reach roughly $25 billion by 2033. Key drivers include the rising need for precise mapping and location intelligence in environmental management, urban planning, and resource optimization. Furthermore, advancements in cloud-based GIS platforms, the increasing availability of big data, and the development of sophisticated geospatial analytics tools are fueling market expansion. The market is segmented by service type (Analyze, Visualize, Manage, Others) and application (primarily Environmental Agencies, but also extending to various sectors such as utilities, transportation, and healthcare). North America currently holds a significant market share due to early adoption and advanced technological infrastructure. However, regions like Asia-Pacific are demonstrating rapid growth, driven by increasing urbanization and infrastructure development. While the lack of readily available detailed market figures presents a challenge for complete precision in projection, the overall trend points to a considerable expansion of the GIS services sector over the forecast period. The competitive landscape is characterized by a mix of large multinational corporations like Infosys and Intellias and smaller, specialized firms like EnviroScience and R&K Solutions, reflecting the diverse needs of the market. These companies compete based on their technological capabilities, industry expertise, and geographical reach. The ongoing integration of GIS with other technologies, such as artificial intelligence (AI) and machine learning (ML), will further shape the market landscape, creating opportunities for innovation and differentiation. Challenges include the high initial investment costs associated with implementing GIS solutions and the need for skilled professionals to effectively utilize these technologies. However, the long-term benefits of improved decision-making and operational efficiency are driving wider adoption despite these hurdles. The future growth of the GIS services market hinges on the continued development of innovative technologies and the increasing awareness of the value that location-based insights provide across various industries.

Discover the booming Location Intelligence Data Solution market, projected to reach $1013.3 million in 2025 with an 8.8% CAGR. This analysis explores key drivers, trends, and competitive landscapes, highlighting opportunities for businesses leveraging location-based insights. Learn more about this rapidly expanding market.

The global geospatial data market is poised for significant expansion, projected to reach $3,788 million and grow at a Compound Annual Growth Rate (CAGR) of 6.1% during the forecast period of 2025-2033. This robust growth is propelled by an increasing demand for location-based intelligence across diverse industries. Key drivers include the proliferation of IoT devices generating vast amounts of location data, advancements in satellite imagery and remote sensing technologies, and the growing adoption of AI and machine learning for analyzing complex geospatial datasets. The enterprise sector is emerging as a dominant application segment, leveraging geospatial data for enhanced decision-making in areas such as logistics, urban planning, real estate, and natural resource management. Furthermore, government agencies are increasingly utilizing this data for public safety, infrastructure development, and environmental monitoring. The market is characterized by a bifurcated segmentation between vector data, representing discrete geographic features, and raster data, depicting continuous phenomena like elevation or temperature. Both segments are experiencing healthy growth, driven by specialized applications and analytical needs. Emerging trends include the rise of real-time geospatial data streams, the increasing importance of high-resolution imagery, and the integration of AI-powered analytics to extract deeper insights. However, challenges such as data privacy concerns, high infrastructure costs for data acquisition and processing, and the need for skilled professionals to interpret and utilize the data effectively may pose some restraints. Despite these hurdles, the overwhelming benefits of actionable location intelligence are expected to drive sustained market expansion, with North America and Europe currently leading in adoption, followed closely by the rapidly growing Asia Pacific region. This in-depth report delves into the dynamic and rapidly evolving Geospatial Data Provider market, offering a comprehensive analysis from the historical period of 2019-2024 through to a robust forecast extending to 2033. With the Base Year and Estimated Year set at 2025, the report provides an up-to-the-minute snapshot and a forward-looking perspective on this critical industry. The market size, valued in the millions, is meticulously dissected across various segments, companies, and industry developments.

The Spatiotemporal Big Data Platform market is booming, reaching $23.83B in 2025 with a 9.2% CAGR. Discover key trends, drivers, and leading companies shaping this explosive growth in real-time location intelligence. Explore market analysis, forecasts, and regional breakdowns.

Discover the booming Location-Based Analytics market! This in-depth analysis reveals key trends, growth drivers, and leading companies shaping this $25B+ industry, projecting a massive expansion to $80B+ by 2033. Learn about regional market share and the impact of data privacy on future growth.

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.

This data set contains small-scale base GIS data layers compiled by the National Park Service Servicewide Inventory and Monitoring Program and Water Resources Division for use in a Baseline Water Quality Data Inventory and Analysis Report that was prepared for the park. The report presents the results of surface water quality data retrievals for the park from six of the United States Environmental Protection Agency's (EPA) national databases: (1) Storage and Retrieval (STORET) water quality database management system; (2) River Reach File (RF3) Hydrography; (3) Industrial Facilities Discharges; (4) Drinking Water Supplies; (5) Water Gages; and (6) Water Impoundments. The small-scale GIS data layers were used to prepare the maps included in the report that depict the locations of water quality monitoring stations, industrial discharges, drinking intakes, water gages, and water impoundments. The data layers included in the maps (and this dataset) vary depending on availability, but generally include roads, hydrography, political boundaries, USGS 7.5' minute quadrangle outlines, hydrologic units, trails, and others as appropriate. The scales of each layer vary depending on data source but are generally 1:100,000.

This data set contains small-scale base GIS data layers compiled by the National Park Service Servicewide Inventory and Monitoring Program and Water Resources Division for use in a Baseline Water Quality Data Inventory and Analysis Report that was prepared for the park. The report presents the results of surface water quality data retrievals for the park from six of the United States Environmental Protection Agency's (EPA) national databases: (1) Storage and Retrieval (STORET) water quality database management system; (2) River Reach File (RF3) Hydrography; (3) Industrial Facilities Discharges; (4) Drinking Water Supplies; (5) Water Gages; and (6) Water Impoundments. The small-scale GIS data layers were used to prepare the maps included in the report that depict the locations of water quality monitoring stations, industrial discharges, drinking intakes, water gages, and water impoundments. The data layers included in the maps (and this dataset) vary depending on availability, but generally include roads, hydrography, political boundaries, USGS 7.5' minute quadrangle outlines, hydrologic units, trails, and others as appropriate. The scales of each layer vary depending on data source but are generally 1:100,000.

The Location Intelligence Tools market is booming, projected to hit $14.15 billion by 2025 with a strong CAGR of 11.7%. Discover key market trends, leading companies (Esri, Google, Pitney Bowes), and growth opportunities in this insightful analysis covering retail, logistics, and finance applications.

Discover the booming location analysis market! Learn about its $15 billion valuation in 2025, 12% CAGR, key drivers, leading companies (IBM, Google, ESRI), and regional insights. Explore the potential of location intelligence in banking, healthcare, and retail. Get the data-driven forecast for 2025-2033.

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.