This geodatabase reflects the U.S. Geological Survey’s (USGS) ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports in Africa. The geodatabase and geospatial data layers serve to create a new geographic information product in the form of a geospatial portable document format (PDF) map. The geodatabase contains data layers from USGS, foreign governmental, and open-source sources as follows: (1) mineral production and processing facilities, (2) mineral exploration and development sites, (3) mineral occurrence sites and deposits, (4) undiscovered mineral resource tracts for Gabon and Mauritania, (5) undiscovered mineral resource tracts for potash, platinum-group elements, and copper, (6) coal occurrence areas, (7) electric po ...

The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for 10 countries of interest in Southwest Asia (area of study): Afghanistan, Cambodia, Laos, India, Indonesia, Iran, Nepal, North Korea, Pakistan, and Thailand. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports for the countries in the area of study. The geodatabase contains data feat ...

Increasing popularity of social networks made them a viable data source for many data mining applications and event detection is no exception. Researchers aim not only to find events that happen in networks but more importantly to identify and locate events occurring in the real world.In this paper, we propose an enhanced version of quadtree - convolutional quadtree (ConvTree) - and demonstrate its advantage compared to the standard quadtree. We also introduce the algorithm for searching events of different scales using geospatial data obtained from social networks. The algorithm is based on statistical analysis of historical data, generation of ConvTrees representing the normal state of the city and anomalies evaluation for events detection.Experimental study conducted on the dataset of 60 million geotagged Instagram posts in the New York City area demonstrates that the proposed approach is able to find a wide range of events from very local (indie band concert or wedding party) to city (baseball game or holiday march) and even country scale (political protest or Christmas) events. This opens up a perspective of building simple and fast yet powerful system for real-time multiscale events monitoring.

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Geographic Information System Analytics Market Size 2024-2028

The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.

What will be the Size of the GIS Analytics Market during the forecast period?

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The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.

How is this Geographic Information System Analytics Industry segmented?

The geographic information system analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  Retail and Real Estate
  Government
  Utilities
  Telecom
  Manufacturing and Automotive
  Agriculture
  Construction
  Mining
  Transportation
  Healthcare
  Defense and Intelligence
  Energy
  Education and Research
  BFSI


Components

  Software
  Services


Deployment Modes

  On-Premises
  Cloud-Based


Applications

  Urban and Regional Planning
  Disaster Management
  Environmental Monitoring Asset Management
  Surveying and Mapping
  Location-Based Services
  Geospatial Business Intelligence
  Natural Resource Management


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    South Korea


  Middle East and Africa

    UAE


  South America

    Brazil


  Rest of World

By End-user Insights

The retail and real estate segment is estimated to witness significant growth during the forecast period.

The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector, gover

A wide variety of state-wide GIS layers with periodic updates from various agencies and sources: Borough Parcels • North Slope Borough Boundaries • ACMP Coastal Districts • ACMP Coastal Zone Management • ACMP Permit Notification Area • ACMP Special Area Management Plan • ADEC Contingency Planning Regions • ADFG Game Management Units • ANCSA Corporations • Administrative Large Parcels • Alaska Seaward Boundary • Borough Boundary • Conservation System Units • DNR Regions • Election District 1994 • Election District 2002 • Election District 2006 • Incorporated City Boundary • Recording Districts • Rural Education Attendance Areas • Soil and Water Conservation Districts • State Park Units through ILMA Cultural • Cities • GNIS Concise Features • GNIS Features • GNIS Historical Features • GNIS Populated Places • Populated Places • Recording District Offices • USGS Place Names DNR Land Records • Base • Airstrips 63,360 • Alaska Seaward Boundary • BLM Monument - Digitized • BLM Monument - GCDB • BLM Monument - SDMS • Borough Boundary • Conservation System Units • Fiberoptic Cables 63,360 • Highways 63,360 • Hydrography 63,360 • Incorporated City Boundary • National Geodetic Survey Monuments • Pipelines 63,360 • Power Lines 63,360 • Railroads 63,360 • Recording Districts • Secondary Roads 63,360 • Sections • State Control Monuments • Survey Boundary • Telephone Lines 63,360 • Townships • Trails 63,360 • Land Estate • Agreement, Settlement, Reconveyance • Easements • Federal Actions • Land Disposal - Available • Land Disposal - Conveyed • Land Disposal - Other • Management Agreement • Mental Health Trust Land • Municipal Entitlement • Municipal Tideland • Native Allotment • Other Activities • Other State Acquired Land - LE • Permit or Lease - LE • RS2477 Trails • Resource Sale • State Selected or Top Filed Land - LE • State Tentatively Approved or Patented - LE • Mineral Estate • Agreement, Settlement, Reconveyance • Annual Placer Mining Application • Federal Actions • Federal Mining Claims • Leasehold Location • Management Agreement • Mental Health Trust Land • Mineral Order • Native Allotment • Oil & Gas Lease Sale Tracts • Other State Acquired Land - ME • Permit or Lease - ME • State Mining Claim • State Prospecting Site • State Selected or Top Filed Land - ME • State Tentatively Approved or Patented - ME • Well Site • Ownership • ANILCA Top Filed - All • Agreement, Settlement, Reconveyance • Federal Actions • Land Disposal - Conveyed • Management Agreement • Mental Health Trust Land • Municipal Entitlement • Municipal Tideland • Native Allotment • Other State Acquired Land - All • RS2477 Trails • State Selected Land - ALL • State Tentatively Approved or Patented - All • Surface Classification • Disposable Interest • General Land • Habitat Land • Legislatively Designated Areas • Miscellaneous • Recreation Land • Reserved Use • Special Use Land • Water Estate • Instream Flow Reservation • Subsurface Temporary Water Use Permit • Subsurface Water Rights • Surface Temporary Water Use Permit • Surface Water Rights Environmental • Environmental Sensitivity Index • ESI North Slope • ESI Northwest Arctic • NOAA Shorezone • Shorezone Biobands • Shorezone Combined Video and Photo Pts • Shorezone Photo Points • Shorezone Unit Information • Shorezone Video Points General Land Status • BLM Native Allotment • Borough Parcels • Federal Parcels • GLS Current Edition • State Land Activity by Case • State Land Activity by Feature • State Parcels • State, Federal, Borough Parcels Graticule • Latitude Longitude Lines 1 Degree • Latitude Longitude Lines 2 Degrees • NOAA Nautical Charts • PLSS Section Grid • PLSS Township Grid • State Plane Zone • USGS Quadrangle 250,000 • USGS Quadrangle 63,360 • UTM Zones Monuments • BLM Monument - Digitized • BLM Monument - GCDB • BLM Monument - SDMS • National Geodetic Survey Monuments • State Control Monuments Natural Resources • Aquaculture and Tidelands • Tidal Conveyances • Tidal Easements • Tidal Leases • Geothermal • Mining • Alaska Resource Data File • Coal Basin • Coal Districts • Coal Field • Coal Occurrence • Coal Unit • Federal Mining Claims • Mining Districts • Placer Districts • Significant Metalliferous Lode Deposits • State Mining Claim • State Mining Claim Closed • State Mining Lease • State Offshore Permit or Lease • State Prospecting Site • Oil and Gas • Oil And Gas Basins • Statewide Unit Tracts • Statewide PA Boundaries • Statewide PA Tracts • Statewide Sale Boundaries • Statewide Sale Tracts • Statewide Unit Boundaries • Water • Hydrologic Units • Navigable Water • Water Information Parks and Recreation Physical Features • Alaska Coast 1,000,000 • Alaska Coast 250,000 • Alaska Coast 63,360 • Alaska Coast 63,360 Excluding Small Islands • Alaska Coast Simplified • Canada Coast • Contours 1,000,000 • Elevation Points 1,000,000 • Glaciers 1,000,000 • Glaciers 2,000,000 • Hydrography 1,000,000 • Hydrography 2,000,000 • Hydrography 63,360 • Major Lakes • Major Rivers • Russia Coast • Summit Points 1,000,000 • Biotic • ANHP Biotic Areas • Anadromous Fish Line • Anadromous Fish Point • Caribou • Dall Sheep Point • Dall Sheep Polygon • Duck Habitat Areas • Eagle Point • Eagle Polygon • Moose Habitat Areas • Seabirds Point • Seabirds Polygon • Seal Point • Seal Polygon • Swan Polygon • Trumpeter Swan • Environmental • Geology • Beikman 1980 • Exploration Points • Geotech Photo Points • Hydrology Base • NHD Flowline • NHD Waterbody • Watersheds • Ice Study 2012 • Open Lead Points • Permafrost • Wetlands • Reference • Administrative • Game Management Units • Bridges • CEA Service Area • Crossings • Dam Sites • Legacy • Transmission Lines Corridor • Recreation • Trails • Transportation • Local Airstrip Points Transportation • Airstrips 63,360 • DOT Centerline Milepost • DOT Centerline Route • FAA Airports and Runways • Fiberoptic Cables 63,360 • Highways 63,360 • Iditarod Trail • Infrastructure 63,360 • Major Roads • Pipelines 63,360 • Power Lines 63,360 • RS2477 Trails • Railroads 1,000,000 • Railroads 2,000,000 • Railroads 63,360 • Roads 1,000,000 • Roads 2,000,000 • Secondary Roads 63,360 • State Park Trails through ILMA • Telephone Lines 63,360 • Trails 63,360 • Trans Alaska Pipeline System

ABSTRACT Objective: To identify geographically the beneficiaries categorized as prone to Type 2 Diabetes Mellitus, using the recognition of patterns in a database of a health plan operator, through data mining. Method: The following steps were developed: the initial step, the information survey. Development, construction of the process of extraction, transformation, and loading of the database. Deployment, presentation of the geographical information through a georeferencing tool. Results: As a result, the mapping of Paraná according to its health care network and the concentration of Type 2 Diabetes Mellitus is presented, enabling the identification of cause-and-effect relationships. Conclusion: It is concluded that the analysis of georeferenced information, linked to health information obtained through the data mining technique, can be an excellent tool for the health management of a health plan operator, contributing to the decision-making process in Health.

The United States Geospatial Analytics Market is Segmented by Type (Surface Analysis, Network Analysis, Geovisualization), by End User Vertical ( Agriculture, Utility and Communication, Defense and Intelligence, Government, Mining and Natural Resources, Automotive and Transportation, Healthcare, Real Estate and Construction). The Market Sizes and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

Spatial association rule mining (SARM) is an important data mining task for understanding implicit and sophisticated interactions in spatial data. The usefulness of SARM results, represented as sets of rules, depends on their reliability: the abundance of rules, control over the risk of spurious rules, and accuracy of rule interestingness measure (RIM) values. This study presents crisp-fuzzy SARM, a novel SARM method that can enhance the reliability of resultant rules. The method firstly prunes dubious rules using statistically sound tests and crisp supports for the patterns involved, and then evaluates RIMs of accepted rules using fuzzy supports. For the RIM evaluation stage, the study also proposes a Gaussian-curve-based fuzzy data discretization model for SARM with improved design for spatial semantics. The proposed techniques were evaluated by both synthetic and real-world data. The synthetic data was generated with predesigned rules and RIM values, thus the reliability of SARM results could be confidently and quantitatively evaluated. The proposed techniques showed high efficacy in enhancing the reliability of SARM results in all three aspects. The abundance of resultant rules was improved by 50% or more compared with using conventional fuzzy SARM. Minimal risk of spurious rules was guaranteed by statistically sound tests. The probability that the entire result contained any spurious rules was below 1%. The RIM values also avoided large positive errors committed by crisp SARM, which typically exceeded 50% for representative RIMs. The real-world case study on New York City points of interest reconfirms the improved reliability of crisp-fuzzy SARM results, and demonstrates that such improvement is critical for practical spatial data analytics and decision support.

These geospatial files are the essential components for the Geologic Map of the Stibnite Mining Area in Valley County, Idaho, which was published by the Idaho Geological Survey in 2022. Three main file types are in this dataset: geographic, geologic, and mining. Geographic files are map extent, lidar base, topographic contours, labels for contours, waterways, and roads. Geologic files are geologic map units, faults, structural lines meaning axial traces, structural points like bedding strike and dip locations, cross section lines, and drill core sample locations. Lastly, mining files are disturbed ground features including open pit polygons or outlines, and general mining features such as the location of an adit. File formats are shape, layer, or raster. Of the 14 shapefiles, 7 have layer files that provide pre-set symbolization for use in ESRI ArcMap that match up with the Geologic Map of the Stibnite Mining Area in Valley County, Idaho. The lidar data have two similar, but distinct, raster format types (ESRI GRID and TIFF) intended to increase end user accessibility. This dataset is a compilation of both legacy data (from Smitherman’s 1985 masters thesis published in 1988, Midas Gold Corporation employees, the Geologic Map of the Stibnite Quadrangle (Stewart and others, 2016) and Reed S. Lewis of the Idaho Geological Survey) and new data from 2013, 2015, and 2016 field work by Niki E. Wintzer.

Three semi-automated detection approaches using Sentinel-1 Synthetic Aperture Radar (SAR) have been performed to identify artisanal and small-scale mining (ASM) riverine dredges on the Madeira River in Brazil. The methods are: i) Search for Unidentified Maritime Objects (SUMO), an established method for large ocean ship detection; and two techniques specifically developed for riverine environments: ii) a local detection method; and iii) a global threshold method. The results from each method are contained on this landing page along with the visual interpretation dataset of SAR data used as the validation dataset. The pre-processed SAR data used to produce these results are found also found on this page.

Discover the booming Drone GIS Mapping market! This comprehensive analysis reveals market size, CAGR, key trends, and regional insights (North America, Europe, Asia-Pacific), highlighting growth drivers and challenges from 2019-2033. Explore applications in agriculture, construction, and energy.

The Nigeria Geospatial Analytics Market is booming, projected to reach $132.83 million by 2033 with a 5.94% CAGR. Discover key drivers, trends, and leading companies shaping this dynamic sector. Learn about the opportunities in agriculture, government, and more. Recent developments include: April 2023: Abuduganiyu Adebomehin, the Surveyor General of the Federation (SGoF), has praised Sambus Geospatial Nigeria Limited, a provider of solutions, for its dedication to the promotion of a producing high-quality, accurate, and real-time geographic data for Nigeria. The Office of the Surveyor General of the Federation (OSGoF) donated five copies of mapping software (ESRI Arc GIS Pro Advance with ten extensions), which the SGoF accepted in exchange for the praise.. Key drivers for this market are: Commercialization of spatial data, Increased smart city & infrastructure projects. Potential restraints include: Commercialization of spatial data, Increased smart city & infrastructure projects. Notable trends are: Commercialization of spatial data would drive the market in Nigeria.

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

The global Geographic Information System (GIS) market is booming, projected to reach $17.5 billion by 2033 with a 5.8% CAGR. Discover key trends, drivers, and regional insights in this comprehensive market analysis, covering major players and applications.

This dataset is a collection of scraped public twitter updates used in coordination with an academic project to study the geolocation data related to twittering. We provide both training set and test set in the paper You Are Where You Tweet: A Content-Based Approach to Geo-locating Twitter Users in CIKM 2010. The training set contains 115,886 Twitter users and 3,844,612 updates from the users. All the locations of the users are self-labeled in United States in city-level granularity. The test set contains 5,136 Twitter users and 5,156,047 tweets from the users. All the locations of users are uploaded from their smart phones with the form of "UT: Latitude,Longitude".

South Korea Geospatial Analytics Market size was valued at USD 970 Million in 2024 and is projected to reach USD 1953 Million by 2032, growing at a CAGR of 9.1% from 2026 to 2032. Key Market Drivers:Rising Government Investments in Smart City Development: The South Korea geospatial analytics market is experiencing strong growth due to increasing government funding for smart city infrastructure and digital transformation. According to the Ministry of Land, Infrastructure and Transport (2023), South Korea allocated 1.2 Trillion (USD 900 Million) for smart city projects leveraging geospatial data. Key players like SK Telecom and LG CNS have developed AI-powered geospatial platforms for urban planning. In 2024, Naver Labs launched a 3D digital twin solution for Seoul, enhancing real-time spatial analytics. Recent news highlights Samsung SDS’s partnership with local governments to integrate geospatial AI into traffic and disaster management systems.Growing Demand for Location-Based Services in Retail & Logistics: The rapid expansion of e-commerce and last-mile delivery services is driving adoption of geospatial analytics for route optimization and customer targeting. A 2023 Korea Statistics Bureau report revealed that over 65% of logistics firms now use geospatial data for fleet management. Companies like Coupang and Baemin are implementing real-time tracking systems powered by Google Maps Platform and Kakao Mobility. In early 2024, KT (Korea Telecom) introduced an AI-driven logistics analytics tool to reduce delivery times. Recent developments include Lotte Data Communication’s geofencing solutions for personalized retail marketing.Increasing Use of Geospatial Tech in Autonomous Vehicles & Drones: The push toward autonomous mobility and drone delivery is accelerating demand for high-precision geospatial mapping and analytics. The Korean Ministry of Science and ICT (2024) reported that autonomous vehicle testing zones expanded by 30% in 2023, requiring advanced spatial data. Hyundai’s Motional and Kia are collaborating with TomTom and HERE Technologies for HD mapping. In 2024, Kakao Mobility launched a drone delivery pilot in Seoul using real-time geospatial analytics. Recent news highlights Hanwha Systems’ AI-based geospatial platform for military and civilian drone operations.

Explore the expanding Geographic Information System (GIS) market, projected at USD 10,880 million in 2025 with a 5.8% CAGR. Discover key drivers, industry applications, hardware & software trends, and regional growth opportunities.

This paper uses text data mining to identify long-term developments in tourism academic research from the perspectives of thematic focus, geography, and gender of tourism authorship. Abstracts of papers published in the period of 1970–2017 in high-ranking tourist journals were extracted from the Scopus database and served as data source for the analysis. Fourteen subject areas were identified using the Latent Dirichlet Allocation (LDA) text mining approach. LDA integrated with GIS information allowed to obtain geography distribution and trends of scholarly output, while probabilistic methods of gender identification based on social network data mining were used to track gender dynamics with sufficient confidence. The findings indicate that, while all 14 topics have been prominent from the inception of tourism studies to the present day, the geography of scholarship has notably expanded and the share of female authorship has increased through time and currently almost equals that of male authorship.

From the site: "Coverages containing industrial mineral mining data by quadrangle for the state of Pennsylvania. Digitized from the Harrisburg Bureau of Mining and Reclamation mylar map system each quadrangle contains multiple coverages identifying seams in that quad. Also includes coverages ('noncoal') indicating industrial minerals and coal mining refuse disposal sites, permitted sites, point coverages of deep mine entry and other surface features of deep mines and Small Operators Assistance Program (SOAP) areas."

From the site: "Location of mined areas, including surface and deep coal and non-coal mining. Data incomplete, areas not mapped when screened at small scales during low level radioactive waste siting analysis."