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.

The Gilmore Project is a pilot study designed to test holistic systems approaches to mapping mineral systems and dryland salinity in areas of complex regolith cover. The project is coordinated by the Australian Geological Survey Organisation, and involves over 50 scientists from 14 research organisations. Research partners include: Cooperative Research Centres for Advanced Mineral Exploration Technologies (CRC AMET), Landscape Evolution and Mineral Exploration (CRC LEME), the CRC for Sensor Signal and Information Processing, and the Australian Geodynamics Cooperative Research Centre (AGCRC) Land & Water Sciences Division of Bureau of Rural Sciences (BRS) NSW Department of Land & Water Conservation and the NSW Department of Mineral Resources. Various universities including the Australian National University, University of Canberra, Macquarie University, Monash University, University of Melbourne, and Curtin University of Technology, and Australian National Seismic Imaging Resource (ANSIR). The project area lies on the eastern margin of the Murray-Darling Basin in central-west NSW. The project area was chosen for its overlapping mineral exploration (Au-Cu) and salinity management issues, and the availability of high-resolution geophysical datasets and drillhole materials and datasets made available by the minerals exploration industry. The project has research agreements with the minerals exploration industry, and is collaborating with rural land-management groups, and the Grains Research and Development Corporation. The study area (100 x 150 km), straddles the Gilmore Fault Zone, a major NNW-trending crustal structure that separates the Wagga-Omeo and the Junee-Narromine Volcanic Belts in the Lachlan Fold Belt. The project area includes tributaries of the Lachlan and the Murrumbidgee Rivers, considered to be two of the systems most at risk from rising salinities. This project area was chosen to compare and contrast salt stores and delivery systems in floodplain (in the Lachlan catchment) and incised undulating hill landscapes (Murrumbidgee catchment). The study area is characteristic of other undulating hill landscapes on the basin margins, areas within the main and tributary river valleys, and the footslopes and floodplains of the Murray-Darling Basin itself. Studies of the bedrock geology in the study area reveal a complex architecture. The Gilmore Fault Zone consist of a series of subparallel, west-dipping thrust faults, that juxtapose, from west to east, Cambro-Ordovician meta-sediments and granites of the Wagga Metamorphics, and further to the east, a series of fault-bounded packages comprising volcanics and intrusions, and siliciclastic meta-sediments. Two airborne electromagnetic (AEM) surveys were flown in smaller areas within the two catchments. Large-scale hydrothermal alteration and structural overprinting, particularly in the volcanics, has added to the complexity within the bedrock architecture.

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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 and sho

In 1995, the Arizona Department of Transportation (ADOT) initiated research project SPR 371, Maintenance Cost Effectiveness Study. That project identified the maintenance surface treatment alternatives suitable for evaluation by ADOT, developed a consensus on which alternatives to test, evaluated the performance and cost effectiveness of those treatments, and identified procurement issues that inhibit effective pavement maintenance. As part of that study, during a period from 1999 to 2002, over 200 bituminous test sections were constructed at different locations in Arizona, including wearing courses (Phase I), surface treatments (Phase II), and sealer-rejuvenators (Phase III). While a significant effort was made to develop and construct the test sections associated with the various experimental Phases, there has been less success in monitoring these test sites and either drawing appropriate conclusions about performance and closing them out, or continuing treatments and monitoring the test sites, as was originally planned. In this report, available documentation and data from the Maintenance Cost Effectiveness Study were collected and reviewed. The overall experimental phases are described, each experiment and test site is summarized, and recommendations are made for either continuing the Phase or closing it out and drawing appropriate conclusions. Overall, the potential of the findings from these various experiments to contribute to more cost effective pavement preservation practices, better specifications and construction practices, and even more cost-effective agency practices, are all reasons for better documenting these experiments and concluding them according to a rational research plan.

The collection includes the audio recording of Mokila story by Bruno Ewundi, a Baka elder in south-eastern Cameroon. The story describes the belief by the indigenous Baka people that hunters called Tuma can shape-shift into other animals, specifically in this account, elephants. The elder outlines an instance of this. Oral consent was gained to share this story in a non-anonymous fashion. The broader study was a 5-year project incorporating both ethnographic work and applied socio-technical work. The objective was to develop appropriate mobile technology which can enable any community, anywhere, to collect and analyse data on a range of socio-ecological issues on their own terms. The motivation for this work is the urgent need for more data on social and environmental aspects in every context around the world in order to achieve the Sustainable Development Goals and other aspirations of social and ecological wellbeing. Specifically, the project collaborated with remote indigenous communities in Africa and South America who expressed great interest in documenting and sharing their extensive knowledge using the Sapelli digital tool developed by the team. Through this work, the project worked towards addressing issues of hegemonic research practices, epistemological hierarchies, indigenous rights, and equitable conservation.The challenge of Extreme Citizen Science is to enable any community, regardless of literacy or education, to initiate, run, and use the result of a local citizen science activity, so they can be empowered to address and solve issues that concern them. Citizen Science is understood here as the participation of members of the public in a scientific project, from shaping the question, to collecting the data, analysing it and using the knowledge that emerges from it. Over the past 3 years, under the leadership of Prof. Muki Haklay, the Extreme Citizen Science programme at UCL has demonstrated that non-literate people and those with limited technical literacy can participate in formulating research questions and collecting the data that is important to them. Extreme Citizen Science: Analysis and Visualisation (ECSAnVis) takes the next ambitious step – developing geographical analysis and visualisation tools that can be used, successfully, by people with limited literacy, in a culturally appropriate way. At the core of the proposal is the imperative to see technology as part of socially embedded practices and culture and avoid ‘technical fixes’. The development of novel, socially and culturally accessible Geographic Information System (GIS) interface and underlying algorithms, will provide communities with tools to support them to combine their local environmental knowledge with scientific analysis to improve environmental management. In an exciting collaboration with local indigenous partners on case studies in critically important, yet fragile and menaced ecosystems in the Amazon and the Congo-basin, our network of anthropologists, ecologists, computer scientists, designers and electronic engineers will develop innovative hardware, software and participatory methodologies that will enable any community to use this innovative GIS. The research will contribute to the fields of geography, geographic information science, anthropology, development, agronomy and conservation.

This dataset consists of a review of research publications about the OpenStreetMap (OSM) project published from 2016 to 2019.

The dataset was obtained as follows. First, papers published between 2016 and 2019 were extracted using Google Scholar with a query identifying all records with at least one of the keywords “OpenStreetMap” and “OSM” in the title. The extracted records were further filtered to only keep papers having a minimum length of 4 pages and published in academic journals or conference proceedings. In addition, irrelevant papers (e.g. using “OSM” as an acronym for another purpose) and non-English papers were removed from the dataset. The remaining paper were then analyzed and manually classified.

The attributes included in the dataset are the following:

id [paper ID]

Paper Citation [citation of the paper]

Authors’ disciplines — multiplicity: 1-7; allowed values: computer science, informatics, social sciences, geo-information, engineering, exact sciences, interdisciplinary

Journal’s discipline — multiplicity: 1; allowed values: computer science, informatics, social sciences, geo-information, engineering, exact sciences, interdisciplinary

Topic(s) — multiplicity: 1:10; allowed values: application, data quality, contribution behaviours, analyzing contributions, contributors, shaping contributions, OSM effects, data enrichment, development, review

Authors' Geography (countries) — multiplicity: 1:n; allowed values: [list of countries]

Authors' Geography (continents) — multiplicity: 1:n; allowed values: [list of continents]

Study Area Geography (countries) — multiplicity: 1:n; allowed values: [list of countries], [list of continents], Global, NA

Geographic Correspondence— multiplicity: 1; allowed values: no correspondence, partial affiliation/partial location, partial affiliation/full location , full correspondence, NA

Perspective on the community — multiplicity: 1; allowed values: OSM as a data source, data produced by contributors, a collaborative project based on contributors, contributors producing data, a unified community, a diverse community, a social product

Evidence of engagement — multiplicity: 1-8; allowed values: none, acknowledgement, meaningful development, occasional development, object of study - direct, object of study - indirect, contribution, participation

General comments [comments on the paper]

In recent years, formalization and reasoning of topological relations have become a hot topic as a means to generate knowledge about the relations between spatial objects at the conceptual and geometrical levels. These mechanisms have been widely used in spatial data query, spatial data mining, evaluation of equivalence and similarity in a spatial scene, as well as for consistency assessment of the topological relations of multi-resolution spatial databases. The concept of computational fuzzy topological space is applied to simple fuzzy regions to efficiently and more accurately solve fuzzy topological relations. Thus, extending the existing research and improving upon the previous work, this paper presents a new method to describe fuzzy topological relations between simple spatial regions in Geographic Information Sciences (GIS) and Artificial Intelligence (AI). Firstly, we propose a new definition for simple fuzzy line segments and simple fuzzy regions based on the computational fuzzy topology. And then, based on the new definitions, we also propose a new combinational reasoning method to compute the topological relations between simple fuzzy regions, moreover, this study has discovered that there are (1) 23 different topological relations between a simple crisp region and a simple fuzzy region; (2) 152 different topological relations between two simple fuzzy regions. In the end, we have discussed some examples to demonstrate the validity of the new method, through comparisons with existing fuzzy models, we showed that the proposed method can compute more than the existing models, as it is more expressive than the existing fuzzy models.