This is a link to the QGIS website where you can download open-source GIS software for viewing, analyzing and manipulating geodata like our downloadable shapefiles.

Discover the booming GIS mapping tools market! This in-depth analysis reveals a $15B market in 2025 projected to reach $39B by 2033, driven by cloud adoption, AI integration, and surging demand across sectors. Explore key trends, leading companies (Esri, ArcGIS, QGIS, etc.), and regional growth forecasts.

Discover the booming GIS Mapping Tools market! Explore key trends, growth drivers, and leading companies in this $15 billion industry projected to reach $28 billion by 2033. Learn about cloud-based solutions, regional market shares, and the future of geographic information systems.

The size of the GIS Mapping Tools market was valued at USD XXX million in 2024 and is projected to reach USD XXX million by 2033, with an expected CAGR of XX % during the forecast period.

The Minnesota DNR Toolbox and Hydro Tools provide a number of convenience geoprocessing tools used regularly by MNDNR staff. Many of these may be useful to the wider public. However, some tools may rely on data that is not available outside of the DNR. All tools require at least ArcGIS 10+.

If you create a GDRS using GDRS Manager and include this toolbox resource and MNDNR Quick Layers, the DNR toolboxes will automatically be added to the ArcToolbox window whenever Quick Layers GDRS Location is set to the GDRS location that has the toolboxes.

Toolsets included in MNDNR Tools V10:
- Analysis Tools
- Conversion Tools
- Division Tools
- General Tools
- Hydrology Tools
- LiDAR and DEM Tools
- Raster Tools
- Sampling Tools

These toolboxes are provided free of charge and are not warrantied for any specific use. We do not provide support or assistance in downloading or using these tools. We do, however, strive to produce high-quality tools and appreciate comments you have about them.

The booming GIS Mapping Tools market is projected to reach $45 billion by 2033, driven by cloud adoption and AI. Explore market trends, key players (Esri, Autodesk, Hexagon), and regional growth in this comprehensive analysis.

The Geographic Information System (GIS) software market is projected to expand significantly, with a market size of XXX million in 2025 and a CAGR of XX% during the forecast period of 2025-2033. The growing adoption of GIS technology across various industries, including urban planning, environmental management, and transportation, is driving market growth. Additionally, the increasing availability of spatial data and the advancements in cloud computing and mobile GIS are further fueling market expansion. Key trends in the GIS software market include the rise of web-based GIS platforms, the integration of artificial intelligence (AI) and machine learning (ML) capabilities, and the growing popularity of open-source GIS solutions. North America and Europe are the major markets for GIS software, while the Asia Pacific region is expected to witness significant growth in the coming years. Major players in the GIS software market include Esri, Hexagon, Pitney Bowes, SuperMap, Bentley Systems, GE, GeoStar, and Zondy Cyber Group. These companies offer a wide range of GIS software products and services to meet the varying needs of different industries and organizations.

Smart agriculture refers to tools that collect, store and analyze digital data along the agricultural value chain. Geographic Information System (GIS) system software is one of those tools used in the agricultural sector. The GIS System market in Spain had a value of over ** million dollars in 2019.

This mapping tool provides a representation of the general watershed boundaries for stream systems declared fully appropriated by the State Water Board. The boundaries were created by Division of Water Rights staff by delineating FASS critical reaches and consolidating HUC 12 sub-watersheds to form FASS Watershed boundaries. As such, the boundaries are in most cases conservative with respect to the associated stream system. However, users should check neighboring FASS Watersheds to ensure the stream system of interest is not restricted by other FASS listings. For more information regarding the Declaration of Fully Appropriated Stream Systems, visit the Division of Water Rights’ Fully Appropriated Streams webpage. How to Use the Interactive Mapping Tool: If it is your first time viewing the map, you will need to click the “OK” box on the splash screen and agree to the disclaimer before continuing. Navigate to your point of interest by either using the search bar or by zooming in on the map. You may enter a stream name, street address, or watershed ID in the search bar. Click on the map to identify the location of interest and one or more pop-up boxes may appear with information about the fully appropriated stream systems within the general watershed boundaries of the identified location. The information provided in the pop-up box may include: (a) stream name, (b) tributary, (c) season declared fully appropriated, (d) Board Decisions/Water Right Orders, and/or (e) court references/adjudications. You may toggle the FAS Streams reference layer on and off to find representative critical reaches associated with the FASS Watershed layer. Please note that this layer is for general reference purposes only and ultimately the critical reach listed in Appendix A of Water Rights Order 98-08 and Appendix A together with any associated footnotes controls. Note: A separate FAS Watershed boundary layer was created for the Bay-Delta Watershed. The Bay-Delta Watershed layer should be toggled on to check if the area of interest is fully appropriated under State Water Board Decision 1594.

The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (guis_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (guis_geomorphology_metadata_faq.pdf). Please read the guis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (guis_geomorphology_metadata.txt or guis_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

Geographic Information System (GIS) Software Market Outlook

The global Geographic Information System (GIS) software market size is projected to grow from USD 9.1 billion in 2023 to USD 18.5 billion by 2032, reflecting a compound annual growth rate (CAGR) of 8.5% over the forecast period. This growth is driven by the increasing application of GIS software across various sectors such as agriculture, construction, transportation, and utilities, along with the rising demand for location-based services and advanced mapping solutions.

One of the primary growth factors for the GIS software market is the widespread adoption of spatial data by various industries to enhance operational efficiency. In agriculture, for instance, GIS software plays a crucial role in precision farming by aiding in crop monitoring, soil analysis, and resource management, thereby optimizing yield and reducing costs. In the construction sector, GIS software is utilized for site selection, design and planning, and infrastructure management, making project execution more efficient and cost-effective.

Additionally, the integration of GIS with emerging technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) is significantly enhancing the capabilities of GIS software. AI-driven data analytics and IoT-enabled sensors provide real-time data, which, when combined with spatial data, results in more accurate and actionable insights. This integration is particularly beneficial in fields like smart city planning, disaster management, and environmental monitoring, further propelling the market growth.

Another significant factor contributing to the market expansion is the increasing government initiatives and investments aimed at improving geospatial infrastructure. Governments worldwide are recognizing the importance of GIS in policy-making, urban planning, and public safety, leading to substantial investments in GIS technologies. For example, the U.S. governmentÂ’s Geospatial Data Act emphasizes the development of a cohesive national geospatial policy, which in turn is expected to create more opportunities for GIS software providers.

Geographic Information System Analytics is becoming increasingly pivotal in transforming raw geospatial data into actionable insights. By employing sophisticated analytical tools, GIS Analytics allows organizations to visualize complex spatial relationships and patterns, enhancing decision-making processes across various sectors. For instance, in urban planning, GIS Analytics can identify optimal locations for new infrastructure projects by analyzing population density, traffic patterns, and environmental constraints. Similarly, in the utility sector, it aids in asset management by predicting maintenance needs and optimizing resource allocation. The ability to integrate GIS Analytics with other data sources, such as demographic and economic data, further amplifies its utility, making it an indispensable tool for strategic planning and operational efficiency.

Regionally, North America holds the largest share of the GIS software market, driven by technological advancements and high adoption rates across various sectors. Europe follows closely, with significant growth attributed to the increasing use of GIS in environmental monitoring and urban planning. The Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, fueled by rapid urbanization, infrastructure development, and government initiatives in countries like China and India.

Component Analysis

The GIS software market is segmented into software and services, each playing a vital role in meeting the diverse needs of end-users. The software segment encompasses various types of GIS software, including desktop GIS, web GIS, and mobile GIS. Desktop GIS remains the most widely used, offering comprehensive tools for spatial analysis, data management, and visualization. Web GIS, on the other hand, is gaining traction due to its accessibility and ease of use, allowing users to access GIS capabilities through a web browser without the need for extensive software installations.

Mobile GIS is another crucial aspect of the software segment, providing field-based solutions for data collection, asset management, and real-time decision making. With the increasing use of smartphones and tablets, mobile GIS applications are becoming indispensable for sectors such as utilities, transportation, and

The global Geographic Information System (GIS) Tools market is experiencing robust growth, projected to reach $2979.7 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.5% from 2025 to 2033. This expansion is driven by several key factors. Firstly, the increasing adoption of cloud-based GIS solutions offers scalability, cost-effectiveness, and improved accessibility for businesses of all sizes, particularly SMEs seeking efficient resource management. Secondly, the rising demand for precise location-based data analysis across diverse sectors like urban planning, environmental monitoring, and precision agriculture fuels market growth. Furthermore, technological advancements, including the integration of AI and machine learning capabilities within GIS platforms, enhance analytical power and facilitate more sophisticated spatial decision-making. Finally, government initiatives promoting smart cities and digital transformation worldwide further stimulate market expansion. The market is segmented by application (SMEs, Large Enterprises) and type (Cloud-Based, On-Premises), reflecting the diverse needs of various user groups. Large enterprises, with their extensive spatial data requirements and resources, are expected to drive significant market share, while cloud-based solutions are poised for faster growth due to their flexible deployment models. The regional landscape reveals a dynamic distribution of market share. North America, particularly the United States, holds a prominent position, driven by high technological adoption rates and the presence of major GIS solution providers. Europe follows closely, fueled by increasing government investments in infrastructure development and digitalization initiatives. The Asia-Pacific region is expected to experience significant growth, propelled by rapid urbanization and the expanding adoption of GIS technologies in developing economies like China and India. While the on-premises segment currently dominates, the cloud-based segment is anticipated to exhibit higher growth in the forecast period, driven by its inherent advantages in scalability, accessibility, and cost-efficiency. Competitive dynamics are shaped by both established players like IBM TRIRIGA and emerging technology companies, leading to innovation and diversification of GIS tool offerings. The market's future hinges on continuous technological innovation, the growing adoption of location intelligence across sectors, and the expansion of robust infrastructure supporting data accessibility and management.

Discover the booming GIS Mapping Tools market! This in-depth analysis reveals key trends, growth drivers, and leading companies shaping the future of spatial data. Explore market size, CAGR, regional insights, and application segments (Geological Exploration, Urban Planning, etc.). Learn how cloud-based solutions are revolutionizing GIS.

Discover the booming GIS software market! Explore its $15 billion valuation, 12% CAGR growth, key drivers, trends, and leading players like Esri & Google. This in-depth analysis reveals regional market share and future projections through 2033.

The GIS Software market is booming, projected to reach $45 billion by 2033 with a CAGR of 12%! Discover key trends, drivers, and restraints shaping this dynamic sector, including the impact of cloud computing, AI, and IoT. Leading companies and regional insights are analyzed in this comprehensive market report.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We converted the photointerpreted data into a format usable in a geographic information system (GIS) by employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM), Zone 16, using the North American Datum of 1983 (NAD83). Orthorectify: We orthorectified the interpreted overlays by using OrthoMapper, a softcopy photogrammetric software for GIS. One function of OrthoMapper is to create orthorectified imagery from scanned and unrectified imagery (Image Processing Software, Inc., 2002). The software features a method of visual orientation involving a point-and-click operation that uses existing orthorectified horizontal and vertical base maps. Of primary importance to us, OrthoMapper also has the capability to orthorectify the photointerpreted overlays of each photograph based on the reference information provided. Digitize: To produce a polygon vector layer for use in ArcGIS (Environmental Systems Research Institute [ESRI], Redlands, California), we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format by using ArcGIS. In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map-attribute codes (both map-class codes and physiognomic modifier codes) to the polygons and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer. Geodatabase: At this stage, the map layer has only map-attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map-class names, physiognomic definitions, links to NVCS types), we produced a feature-class table, along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature-class layers produced from this project, including vegetation sample plots, accuracy assessment (AA) sites, aerial photo locations, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.

eXtension Foundation, the University of New Hampshire, and Virginia Tech have developed a mapping and data exploration tool to assist Cooperative Extension staff and administrators in making strategic planning and programming decisions. The tool, called the National Extension Web-mapping Tool (or NEWT), is the key in efforts to make spatial data available within cooperative extension system. NEWT requires no GIS experience to use. NEWT provides access for CES staff and administrators to relevant spatial data at a variety of scales (national, state, county) in useful formats (maps, tables, graphs), all without the need for any experience or technical skills in Geographic Information System (GIS) software. By providing consistent access to relevant spatial data throughout the country in a format useful to CES staff and administrators, NEWT represents a significant advancement for the use of spatial technology in CES. Users of the site will be able to discover the data layers which are of most interest to them by making simple, guided choices about topics related to their work. Once the relevant data layers have been chosen, a mapping interface will allow the exploration of spatial relationships and the creation and export of maps. Extension areas to filter searches include 4-H Youth & Family, Agriculture, Business, Community, Food & Health, and Natural Resources. Users will also be able to explore data by viewing data tables and graphs. This Beta release is open for public use and feedback. Resources in this dataset:Resource Title: Website Pointer to NEWT National Extension Web-mapping Tool Beta. File Name: Web Page, url: https://www.mapasyst.org/newt/ The site leads the user through the process of selecting the data in which they would be most interested, then provides a variety of ways for the user to explore the data (maps, graphs, tables).

Market Research Intellect's GIS Mapping Software Market Report highlights a valuation of USD 3.2 billion in 2024 and anticipates growth to USD 6.5 billion by 2033, with a CAGR of 8.5% from 2026-2033.Explore insights on demand dynamics, innovation pipelines, and competitive landscapes.

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 ...

Discover the booming interactive map creation tools market! This in-depth analysis reveals a $2.5 billion market in 2025, projected to reach $8 billion by 2033, driven by cloud-based solutions and growing data visualization needs. Learn about key players, market segmentation, and regional trends shaping this exciting sector.