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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,

At NASA they use Geographic Information systems to provide:maps and powerful capabilities to visualise, analyse and interact with big dataFind out more about how they do this in this ArcGIS StoryMap created by NASA in 2020. This StoryMap includes a section on where you can find NASA data.

Geographic Information System (GIS) Software Market Outlook

According to our latest research, the global Geographic Information System (GIS) Software market size reached USD 11.6 billion in 2024, reflecting a robust demand for spatial data analytics and location-based services across various industries. The market is experiencing a significant growth trajectory, driven by a CAGR of 12.4% from 2025 to 2033. By the end of 2033, the GIS Software market is forecasted to attain a value of USD 33.5 billion. This remarkable expansion is primarily attributed to the integration of advanced technologies such as artificial intelligence, IoT, and cloud computing, which are enhancing the capabilities and accessibility of GIS platforms.

One of the major growth factors propelling the GIS Software market is the increasing adoption of location-based services across urban planning, transportation, and utilities management. Governments and private organizations are leveraging GIS solutions to optimize infrastructure development, streamline resource allocation, and improve emergency response times. The proliferation of smart city initiatives worldwide has further fueled the demand for GIS tools, as urban planners and municipal authorities require accurate spatial data for effective decision-making. Additionally, the evolution of 3D GIS and real-time mapping technologies is enabling more sophisticated modeling and simulation, expanding the scope of GIS applications beyond traditional mapping to include predictive analytics and scenario planning.

Another significant driver for the GIS Software market is the rapid digitization of industries such as agriculture, mining, and oil & gas. Precision agriculture, for example, relies heavily on GIS platforms to monitor crop health, manage irrigation, and enhance yield forecasting. Similarly, the mining sector uses GIS for exploration, environmental impact assessment, and asset management. The integration of remote sensing data with GIS software is providing stakeholders with actionable insights, leading to higher efficiency and reduced operational risks. Furthermore, the growing emphasis on environmental sustainability and regulatory compliance is prompting organizations to invest in advanced GIS solutions for monitoring land use, tracking deforestation, and managing natural resources.

The expanding use of cloud-based GIS solutions is also a key factor driving market growth. Cloud deployment offers scalability, cost-effectiveness, and remote accessibility, making GIS tools more accessible to small and medium enterprises as well as large organizations. The cloud model supports real-time data sharing and collaboration, which is particularly valuable for disaster management and emergency response teams. As organizations increasingly prioritize digital transformation, the demand for cloud-native GIS platforms is expected to rise, supported by advancements in data security, interoperability, and integration with other enterprise systems.

Regionally, North America remains the largest market for GIS Software, accounting for a significant share of global revenues. This leadership is underpinned by substantial investments in smart infrastructure, advanced transportation systems, and environmental monitoring programs. The Asia Pacific region, however, is witnessing the fastest growth, driven by rapid urbanization, government-led digital initiatives, and the expansion of the utility and agriculture sectors. Europe continues to demonstrate steady adoption, particularly in environmental management and urban planning, while Latin America and the Middle East & Africa are emerging as promising markets due to increasing investments in infrastructure and resource management.

Component Analysis

The GIS Software market is segmented by component into Software and Services, each playing a pivotal role in the overall value chain. The software segment includes comprehensive GIS platforms, spatial analytics tools, and specialized applications

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

Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.

This feature class (shapefile) consists of point locations of public, private, and charter schools including pre-schools, day care facilities, adult and vocational schools in New Jersey, with minimal attributes. Most of the public schools were initially located in 2003 by the New Jersey Department of Environmental Protection, and were checked in 2007-2016 by the NJ Office of Geographic Information Systems (OGIS), other organizations and volunteers. Charter schools were located in 2011 and checked through 2016 by OGIS against the 2016 NJ Department of Education table of public schools that also lists charter schools.Private schools were located initially in 2010, and updated later in 2014 only for Somerset County using the spatial data provided by Somerset County GIS team. The present data set is the result of checking and updating the previous locations by processing the tabular data that were acquired from NJDOE in August, 2016.

© Most of the public school records were derived from 2003 data sets created by the New Jersey Department of Environmental Protection. Special acknowledgements are to people of the following organizations who made a significant contribution to school location verification process: Seth Hackman (NJDEP), Salem county GIS; Morris County GIS; Atlantic County GIS; Cape May County GIS; DVRPC; Hunterdon County GIS; Somerset County GIS; Warren County Prosecutor's Office; Westfield Engineering; WFS (for Mercer, Middlesex, Burlington and Camden Co.) ; Monmouth GIS; voluneers and state employees who made site visits on their own time: Charles Colvard, Dominic Juliano, Matt Lawson, Richard Rabinowitz, Amy J. Ferdinand, Rebecca French-Mesch.

This layer is a component of Sites and Facilities.

DC public schools. This dataset contains points representing public schools. It was created for the D.C. public schools and later added to the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO). This dataset includes all identifiable DCPS public elementary, middle, education campus's, senior high, and special education schools as well as learning centers. Does not include private or charter schools. School locations were identified from a database from the DC Public Schools, Office of Facilities Management. Current for the 2015-2016 school year.

DC public schools. This dataset contains points representing public schools. It was created for the D.C. public schools and later added to the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO). This dataset includes all identifiable DCPS public elementary, middle, education campus's, senior high, and special education schools as well as learning centers. Does not include private or charter schools. School locations were identified from a database from the DC Public Schools, Office of Facilities Management. Current for the 2017-18 school year.

In 1989, the U.S. Geological Survey (USGS) began a major geologic and oceanographic investigation of the Gulf of the Farallones continental shelf system, designed to evaluate and monitor human impacts on the marine environment (Karl and others, 2002). The study region is located off the central California coast, adjacent to San Francisco Bay and encompasses the Gulf of the Farallones National Marine Sanctuary. Geologic mapping of this area included the use of various remote sensing and sampling techniques such as sub-bottom profiling, sidescan-sonar and bathymetric mapping, gravity core and grab sampling, and photography. These data were used to define the surficial sediment distribution, underlying structure and sea floor morphology of the study area. The primary focus of this report is to present a georeferenced, digital sidescan-sonar mosaic of the study region. The sidescan-sonar data were acquired with the AMS-120 (120kHz) sidescan-sonar system during USGS cruise F9-89-NC. The dataset covers approximately 1000 km squared of the continental shelf between Point Reyes, California and Half Moon Bay, California, extending west to the continental shelf break near the Farallon Islands. The sidescan-sonar mosaic displays a heterogenous sea-floor environment, containing outcropping rock, ripples, dunes, lineations and depressions, as well as flat, featureless sea floor (Karl and others, 2002). These data, along with sub-bottom interpretation and ground truth data define the geologic framework of the region. The sidescan-sonar mosaic can be used with supplemental remote sensing and sampling data as a base for future research, helping to define the local current regime and predominant sediment transport directions and forcing conditions within the Gulf of Farallones.

In 1989, the U.S. Geological Survey (USGS) began a major geologic and oceanographic investigation of the Gulf of the Farallones continental shelf system, designed to evaluate and monitor human impacts on the marine environment (Karl and others, 2002). The study region is located off the central California coast, adjacent to San Francisco Bay and encompasses the Gulf of the Farallones National Marine Sanctuary. Geologic mapping of this area included the use of various remote sensing and sampling techniques such as sub-bottom profiling, sidescan-sonar and bathymetric mapping, gravity core and grab sampling, and photography. These data were used to define the surficial sediment distribution, underlying structure and sea floor morphology of the study area. The primary focus of this report is to present a georeferenced, digital sidescan-sonar mosaic of the study region. The sidescan-sonar data were acquired with the AMS-120 (120kHz) sidescan-sonar system during USGS cruise F9-89-NC. The dataset covers approximately 1000 km squared of the continental shelf between Point Reyes, California and Half Moon Bay, California, extending west to the continental shelf break near the Farallon Islands. The sidescan-sonar mosaic displays a heterogenous sea-floor environment, containing outcropping rock, ripples, dunes, lineations and depressions, as well as flat, featureless sea floor (Karl and others, 2002). These data, along with sub-bottom interpretation and ground truth data define the geologic framework of the region. The sidescan-sonar mosaic can be used with supplemental remote sensing and sampling data as a base for future research, helping to define the local current regime and predominant sediment transport directions and forcing conditions within the Gulf of Farallones.

Abstract Aims: This paper sought to evaluate the infrastructure of public swimming pools in a countryside municipality of the state of São Paulo and to present the Geographic Information System (GIS) as a tool capable of assisting in the management of sports facilities and programs. Methods: This is a descriptive study since it intends to expose the characteristics of a certain context. First, documentary research was performed to map the facilities and their respective projects. After that, a field survey was conducted seeking to evaluate the infrastructure of public pools and their surroundings through observation. Lastly, using georeferencing software, the population, and socioeconomic data around these pools were obtained and analyzed. Results: It was identified ten public swimming pools, and in seven the offer of swimming projects was foreseen. The infrastructure of the pools is mainly unsatisfactory, making necessary the improvement of the installation itself and in its surroundings. According to the results of the GIS, each pool has its specific public target concerning the characteristics of the profile of the residents surrounding these facilities. Conclusion: Information regarding the public profile around sports facilities generated from a tool such as GIS showed it is possible to determine which sports projects should be prioritized in each facility, leading to improvement in the management of sports-related public policies.

This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. No Abstract Available Resources in this dataset:Resource Title: Website Pointer to html file. File Name: Web Page, url: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sgs&identifier=808 Webpage with information and links to data files for download

Abstract

The Master List of Schools is a record of all schools in South Africa. The data forms part of the national Education Management Information Systems (EMIS) database used to inform education policymakers and managers in the Department of Basic Education (DBE) and the Provincial education departments, as well as to provide valuable information to external stakeholders. The list is maintained by provincial departments and regularly sent to DBE for updating. A key function of the master list is to uniquely identify each school in the country through a school identifier called the EMIS number. Additionally, the list contains data on school quintiles - categories (quintiles) based on the socioeconomic status of the community in which the school is situated. Analyses comparing schools' performance often use school quintiles as control measures for socioeconomic status, to take into account the effect of, for example, poor infrastructure, shortage of materials and deprived home backgrounds on school performance. There are also other basic data fields in the school master list that could provide the means to answer some of the most frequently asked questions about learner enrolment, teachers and learner-teacher ratio of schools. It is a useful dataset for education planners and researchers and is even widely used in the private sector by those who regularly deal with schools.

Geographic coverage

The data has national coverage

Analysis unit

Individuals and institutions

Universe

The survey covers all schools (ordinary and special needs) in South Africa, both public and independent.

Kind of data

Administrative records and survey data

Mode of data collection

Other

Research instrument

Data from the SNAP survey and ANA that are used to compile the Master List of Schools is collected with a survey questionnaire and educator forms. The principle completes the survey questionnaire and each educator (both state paid and other) in each school completes an educator form. Schools record their EMIS number provided by the DBE on the questionnaire and form for identification.

Data appraisal

The 2023 series only includes data for quarter 2 and quarter 3. The GIS coordinates for schools in the Eastern Cape are incorrectly entered in the original data from the DBE. The data entered in the GIS_long variable is incorrectly entered into the GIS_lat variable. This issue only occurs for schools in the Eastern Cape (EC), all other GIS coordinates for all the other provinces is correct. Therefore, for geospatial analysis, users can swap the GIS coordiate data only for the Eastern Cape.

I’d love to begin by saying that I have not “arrived” as I believe I am still on a journey of self-discovery. I have heard people say that they find my journey quite interesting and I hope my story inspires someone out there.I had my first encounter with Geographic Information System (GIS) in the third year of my undergraduate study in Geography at the University of Ibadan, Oyo State Nigeria. I was opportune to be introduced to the essentials of GIS by one of the prominent Environmental and Urban Geographers in person of Dr O.J Taiwo. Even though the whole syllabus and teaching sounded abstract to me due to the little exposure to a practical hands-on approach to GIS software, I developed a keen interest in the theoretical learning and I ended up scoring 70% in my final course exam.

Count of students in each grade (PK-12) enrolled in each Alaska public school. These data are taken from the official October 1 student count. This data set features historical data from the 2012-2013 school year to the present. Source: Alaska Department of Education & Early Development

This data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: Alaska Department of Education & Early Development Data Center.

This geodatabase serves two purposes: 1) to provide State of Illinois agencies with a fast resource for the preparation of maps and figures that require the use of shape or line files from federal agencies, the State of Illinois, or the City of Chicago, and 2) as a start for social scientists interested in exploring how geographic information systems (whether this is data visualization or geographically weighted regression) can bring new meaning to the interpretation of their data. All layer files included are relevant to the State of Illinois. Sources for this geodatabase include the U.S. Census Bureau, U.S. Geological Survey, City of Chicago, Chicago Public Schools, Chicago Transit Authority, Regional Transportation Authority, and Bureau of Transportation Statistics.

This dataset consists of a table containing information regarding all the degree programmes offered at Siauliai State University of Applied Science in the academic year 2023/2024. Each degree programme’s row contains basic information on the programme. This dataset provides detailed information about the Educational Programmes offered by the Siauliai State University of Applied Science, including data about the respective faculties, course of study, national classification, study type, EQF level, ISCED level, gender of enrolled students per course of study, geographical information.

Finding Schools is now easier than ever with the College Map, the first geographic search tool published by IPEDS (Integrated Postsecondary Education Data System) providing access to over 7,000 certificate, undergraduate and graduate-level schools. This all-in-one tool enables students, parents and counselors to filter potential programs for location, major, tuition and more. Including both certificate-level programs and advanced degrees, this public application makes the often overwhelming process of school searching simple, and it’s available on mobile devices.Once the results are narrowed down, users can share their lists on social media or download in excel format. Additionally, the College Map integrates with the College Navigator, a research based search tool providing data from the complete list of IPEDS Survey indicators.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

According to many previous studies, application of remote sensing for the complex and heterogeneous urban environments in Sub-Saharan African countries is challenging due to the spectral confusion among features caused by diversity of construction materials. Resorting to classification based on spectral indices that are expected to better highlight features of interest and to be prone to unsupervised classification, this study aims (1) to evaluate the effectiveness of index-based classification for Land Use Land Cover (LULC) using an unsupervised machine learning algorithm Product Quantized K-means (PQk-means); and (2) to monitor the urban expansion of Luanda, the capital city of Angola in a Logistic Regression Model (LRM). Comparison with state-of-the-art algorithms shows that unsupervised classification by means of spectral indices is effective for the study area and can be used for further studies. The built-up area of Luanda has increased from 94.5 km2 in 2000 to 198.3 km2 in 2008 and to 468.4 km2 in 2018, mainly driven by the proximity to the already established residential areas and to the main roads as confirmed by the logistic regression analysis. The generated probability maps show high probability of urban growth in the areas where government had defined housing programs.

Location of public elementary schools in Los Angeles CountyThis dataset is maintained through the County of Los Angeles Location Management System. The Location Management System is used by the County of Los Angeles GIS Program to maintain a single, comprehensive geographic database of locations countywide. For more information on the Location Management System, visit http://egis3.lacounty.gov/lms/.