Bolton & Menk, an engineering planning and consulting firm from the Midwestern United States has released a series of illustrated children’s books as a way of helping young people discover several different professions that typically do not get as much attention as other more traditional ones do.Topics of the award winning book series include landscape architecture, civil engineering, water resource engineering, urban planning and now Geographic Information Systems (GIS). The books are available free online in digital format, and easily accessed via a laptop, smart phone or tablet.The book Lindsey the GIS Specialist – A GIS Mapping Story Tyler Danielson, covers some the basics of what geographic information is and the type of work that a GIS Specialist does. It explains what the acronym GIS means, the different types of geospatial data, how we collect data, and what some of the maps a GIS Specialist creates would be used for.Click here to check out the GIS Specialist – A GIS Mapping Story e-book

eBook that explains GIS.

Questions, experts' profile and results of a world expert opinion elicitation conducted (2023) through an online survey on the current implementation of GIS for surveillance and disease response in the aquatic animal health domain.

Uncover historical ownership history and changes over time by performing a reverse Whois lookup for the company GIS-SPECIALIST.

This dataset is intended for read-only use. The purpose of these data is to provide display, identification, and analysis tools for determining current boundary information for Forest Service managers, GIS specialists, and others.

The Geographic Information System (GIS) industry is experiencing robust growth, projected to maintain a Compound Annual Growth Rate (CAGR) of 10.80% from 2025 to 2033. This expansion is driven by increasing adoption across diverse sectors, including agriculture, utilities, mining, construction, transportation, and oil and gas. The rising need for precise location-based data for efficient operations, optimized resource management, and informed decision-making fuels this market growth. Advancements in hardware, such as high-resolution sensors and drones, coupled with sophisticated software capabilities like advanced spatial analytics and cloud-based GIS solutions, are key contributors. Furthermore, the proliferation of location-based services (LBS) and the growing adoption of telematics and navigation systems are expanding the applications of GIS technology. While data security concerns and the need for skilled professionals present some challenges, the overall market outlook remains positive. The segmentation of the GIS market reveals a strong demand across various components (hardware and software) and functionalities (mapping, surveying, telematics and navigation, and location-based services). North America currently holds a significant market share due to early adoption and technological advancements, but regions like Asia are exhibiting rapid growth fueled by infrastructure development and increasing digitalization. Leading companies like Bentley Systems, Esri, Trimble, and Hexagon AB are at the forefront of innovation, continuously developing and implementing advanced GIS solutions to meet the evolving needs of different industries. The forecast for the next decade points to further market consolidation, with leading players investing heavily in research and development to enhance their product offerings and expand their market reach. The continued integration of GIS with other technologies such as AI and IoT will further drive market expansion and create new opportunities for growth. Comprehensive Coverage GIS Industry Report (2019-2033) This in-depth report provides a comprehensive analysis of the Geographic Information System (GIS) industry, projecting robust growth from $XXX million in 2025 to $YYY million by 2033. The study covers the historical period (2019-2024), base year (2025), and forecast period (2025-2033), offering invaluable insights for businesses, investors, and policymakers. Keywords: GIS market, GIS software, GIS hardware, GIS solutions, geospatial technology, location intelligence, mapping software, surveying equipment, spatial analysis, geospatial analytics. Recent developments include: November 2022 : The new Geodata Portal and broadband maps for the state will be accessible starting on November 18, 2022, according to a statement from the Connecticut Office of Policy and Management (OPM). This announcement was made on GIS Day 2022, which encourages people to learn about geography and the practical uses of GIS that can improve society., November 2022 : The lt. governor of the Indian state, Jammu and Kashmir, launched a GIS-based system in the region. It highlights the significance of GIS technology in addressing new challenges and exploring new opportunities and its real-world applications, accelerating growth in business, government, and society.. Key drivers for this market are: Growing role of GIS in smart cities ecosystem, Integration of location-based mapping systems with business intelligence systems. Potential restraints include: Integration issues with traditional systems, Data quality and accuracy issues. Notable trends are: The Rising Smart Cities Development and Urban Planning to Drive the Market Growth.

Data Collection

Because titles vary widely across local governments our researchers call 22,000 counties, cities, and towns every 180 days to learn who is currently in the role and what their title is. It's common for officials to be responsible for multiple roles especially in smaller local governments. Because the data is phone verified MarketEdge's contact data achieves 97% accuracy.

Overview

The Head of GIS is the custodian of geospatial data that is critical for departments like Planning and Zoning, Economic Development, Building Permits and Inspections, Public Utilities, and Resource Management for the development and maintenance of public infrastructure.

Responsibilities

To qualify as the Head of GIS the person must perform one or more of the following primary responsibilities: - Manage and maintain geographic data like maps, zones, facility locations etc. - Manage GIS project plans and data collection schedules - Developing and implement standards for GIS deployment and creating and - maintaining structures necessary for GIS data storage - May also analyze and present geographical and spatial information

Reporting Structure and Occurrence A GIS function can exist within a government as an independent department OR may be an additional responsibility of another larger department like IT, Community Development, Building and Permits, Planning and Zoning and Public Works. In some local governments this function is outsourced to a private company or another government (county/state).

Titles You Might Expect - Town / Township Assessor - County Assessor - GIS Manager / Coordinator - GIS Specialist - GIS Analyst - GIS Technician - GIS Administrator - City Planner - Surprising Titles - Planning Director - Community Development Director - City Engineer - Chief Appraiser - County Engineer - Revenue Commissioner - Director of Engineering

The Geographic Information System (GIS) market, currently valued at approximately $10.88 billion (2025), is poised for robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 5.8% from 2025 to 2033. This expansion is driven by several key factors. Increasing urbanization and infrastructure development necessitate advanced spatial data management and analysis capabilities offered by GIS. The rising adoption of cloud-based GIS solutions, providing scalability and cost-effectiveness, further fuels market growth. Furthermore, the integration of GIS with other technologies like IoT (Internet of Things) and AI (Artificial Intelligence) is unlocking new applications across diverse sectors, enhancing decision-making processes and improving operational efficiency. The oil and gas, construction, mining, and transportation industries are major contributors to market demand, leveraging GIS for asset management, resource exploration, and infrastructure planning. The market segmentation reveals a dynamic landscape. Hardware components, including GIS collectors, total stations, and LIDAR systems, constitute a significant portion of the market, alongside the rapidly expanding software segment. While North America currently holds a substantial market share, driven by early adoption and technological advancements, the Asia-Pacific region exhibits significant growth potential, fuelled by rapid infrastructure development and increasing government investments in digital technologies. Competition is intense, with established players like Hexagon, Topcon, Trimble, and Autodesk vying for market dominance alongside emerging players. While challenges exist, such as the high initial investment costs for implementing GIS solutions and the need for skilled professionals, the overall market trajectory indicates continued expansion and innovation in the coming years. The ongoing evolution of GIS technology, coupled with the expanding range of applications, ensures its continued relevance across diverse industries.

The Geographic Information Technology (GIT) Services market is experiencing robust growth, driven by increasing adoption of location intelligence across diverse sectors. The market's expansion is fueled by the rising need for precise mapping, spatial data analysis, and improved decision-making capabilities. Factors such as urbanization, infrastructure development, and the burgeoning need for efficient resource management are significantly contributing to the market's upward trajectory. Furthermore, technological advancements, including the proliferation of high-resolution satellite imagery, drone technology, and sophisticated GIS software, are enhancing the capabilities and applications of GIT services. This is leading to wider adoption across various sectors, including urban planning, environmental management, transportation, and agriculture. We estimate the 2025 market size to be approximately $150 billion, based on observed growth trends in related technology sectors and expert analysis. A projected Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033 suggests continued expansion, potentially reaching a value exceeding $275 billion by 2033. While the market presents significant opportunities, certain challenges exist. High initial investment costs for software and hardware, coupled with the need for skilled professionals to operate and interpret the complex data, can pose barriers to entry for smaller companies. Data privacy concerns and the need for robust data security measures also represent challenges that need to be addressed. Despite these restraints, the overall outlook remains positive, driven by ongoing technological innovations and the increasing recognition of the value proposition offered by GIT services across a wide range of industries and applications. The market is segmented by service type (data acquisition, data processing, software development, etc.), industry vertical (government, utilities, etc.), and geographic region. Leading players like Esri, Hexagon, and Pitney Bowes continue to consolidate their market positions, while several regional players also contribute significantly.

During a search and rescue (SAR) operation, officials don't have time to wait until a GIS specialist is on scene. They need maps immediately. Preconfigured and ready-to-use GIS tools must be available to SAR teams before an incident occurs.

In this lesson, you'll create a web map to prepare data for search operations. Your map will contain static base data showing regional boundaries and key features, as well as editable layers that can be changed as an incident develops. Then, you'll use the map to create a web app that even non-GIS professionals can use. Finally, you'll use the app to track a fictional SAR mission.

In this lesson you will build skills in the these areas:

• Mapping base and incident data
• Configure widgets in a web app
• Adding Situational Awareness and Smart Editor widgets
• Plotting Initial Planning Point and adding trail blocks
• Creating search assignments
• Mapping incident data

Learn ArcGIS is a hands-on, problem-based learning website using real-world scenarios. Our mission is to encourage critical thinking, and to develop resources that support STEM education.

The global GIS mapping tools market is experiencing robust growth, driven by increasing demand across diverse sectors. The market, estimated at $15 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033, reaching approximately $28 billion by 2033. This growth is fueled by several key factors. Firstly, the burgeoning adoption of cloud-based solutions offers scalability, cost-effectiveness, and enhanced accessibility to a wider user base, including small and medium-sized enterprises (SMEs). Secondly, the escalating need for precise spatial data analysis in various applications, such as urban planning, geological exploration, and water resource management, is significantly boosting market demand. The increasing integration of GIS with other technologies like AI and IoT further amplifies its capabilities, leading to more sophisticated applications and increased market penetration. Finally, government initiatives promoting digitalization and smart city development across the globe are indirectly fueling this market expansion. However, certain restraints limit market growth. The high initial investment cost for advanced GIS software and the requirement for skilled professionals to operate these systems can be a barrier, especially for smaller organizations. Additionally, data security and privacy concerns related to the handling of sensitive geographical information pose challenges to wider adoption. Market segmentation reveals strong growth in the cloud-based GIS segment, driven by its inherent advantages, while applications in urban planning and geological exploration lead the application-based segmentation. North America and Europe currently hold significant market shares, with strong growth potential in the Asia-Pacific region due to increasing infrastructure development and government investments. Leading companies like Esri, Hexagon, and Autodesk are shaping the market landscape through continuous innovation and competitive pricing strategies, while the emergence of open-source options like QGIS and GRASS GIS provides alternative, cost-effective solutions.

An introduction to ArcView 3.x. (Note: Data associated with this presentation is available on the DLI FTP site under folder 1873-204.)

This product is part of the Landscape Change Monitoring System (LCMS) data suite. It shows LCMS change attribution classes for each year. See additional information about change in the Entity_and_Attribute_Information or Fields section below.LCMS is a remote sensing-based system for mapping and monitoring landscape change across the United States. Its objective is to develop a consistent approach using the latest technology and advancements in change detection to produce a "best available" map of landscape change. Because no algorithm performs best in all situations, LCMS uses an ensemble of models as predictors, which improves map accuracy across a range of ecosystems and change processes (Healey et al., 2018). The resulting suite of LCMS change, land cover, and land use maps offer a holistic depiction of landscape change across the United States over the past four decades.Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). To produce annual composites, the cFmask (Zhu and Woodcock, 2012), cloudScore, and TDOM (Chastain et al., 2019) cloud and cloud shadow masking methods are applied to Landsat Tier 1 and Sentinel 2a and 2b Level-1C top of atmosphere reflectance data. The annual medoid is then computed to summarize each year into a single composite. The composite time series is temporally segmented using LandTrendr (Kennedy et al., 2010; Kennedy et al., 2018; Cohen et al., 2018). All cloud and cloud shadow free values are also temporally segmented using the CCDC algorithm (Zhu and Woodcock, 2014). LandTrendr, CCDC and terrain predictors can be used as independent predictor variables in a Random Forest (Breiman, 2001) model. LandTrendr predictor variables include fitted values, pair-wise differences, segment duration, change magnitude, and slope. CCDC predictor variables include CCDC sine and cosine coefficients (first 3 harmonics), fitted values, and pairwise differences from the Julian Day of each pixel used in the annual composites and LandTrendr. Terrain predictor variables include elevation, slope, sine of aspect, cosine of aspect, and topographic position indices (Weiss, 2001) from the USGS 3D Elevation Program (3DEP) (U.S. Geological Survey, 2019). Reference data are collected using TimeSync, a web-based tool that helps analysts visualize and interpret the Landsat data record from 1984-present (Cohen et al., 2010).Outputs fall into three categories: change, land cover, and land use. Change relates specifically to vegetation cover and includes slow loss (not included for PRUSVI), fast loss (which also includes hydrologic changes such as inundation or desiccation), and gain. These values are predicted for each year of the time series and serve as the foundational products for LCMS. References: Breiman, L. (2001). Random Forests. In Machine Learning (Vol. 45, pp. 5-32). https://doi.org/10.1023/A:1010933404324Chastain, R., Housman, I., Goldstein, J., Finco, M., and Tenneson, K. (2019). Empirical cross sensor comparison of Sentinel-2A and 2B MSI, Landsat-8 OLI, and Landsat-7 ETM top of atmosphere spectral characteristics over the conterminous United States. In Remote Sensing of Environment (Vol. 221, pp. 274-285). https://doi.org/10.1016/j.rse.2018.11.012Cohen, W. B., Yang, Z., and Kennedy, R. (2010). Detecting trends in forest disturbance and recovery using yearly Landsat time series: 2. TimeSync - Tools for calibration and validation. In Remote Sensing of Environment (Vol. 114, Issue 12, pp. 2911-2924). https://doi.org/10.1016/j.rse.2010.07.010Cohen, W. B., Yang, Z., Healey, S. P., Kennedy, R. E., and Gorelick, N. (2018). A LandTrendr multispectral ensemble for forest disturbance detection. In Remote Sensing of Environment (Vol. 205, pp. 131-140). https://doi.org/10.1016/j.rse.2017.11.015Foga, S., Scaramuzza, P.L., Guo, S., Zhu, Z., Dilley, R.D., Beckmann, T., Schmidt, G.L., Dwyer, J.L., Hughes, M.J., Laue, B. (2017). Cloud detection algorithm comparison and validation for operational Landsat data products. Remote Sensing of Environment, 194, 379-390. http://doi.org/10.1016/j.rse.2017.03.026Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. In Remote Sensing of Environment (Vol. 202, pp. 18-27). https://doi.org/10.1016/j.rse.2017.06.031Healey, S. P., Cohen, W. B., Yang, Z., Kenneth Brewer, C., Brooks, E. B., Gorelick, N., Hernandez, A. J., Huang, C., Joseph Hughes, M., Kennedy, R. E., Loveland, T. R., Moisen, G. G., Schroeder, T. A., Stehman, S. V., Vogelmann, J. E., Woodcock, C. E., Yang, L., and Zhu, Z. (2018). Mapping forest change using stacked generalization: An ensemble approach. In Remote Sensing of Environment (Vol. 204, pp. 717-728). https://doi.org/10.1016/j.rse.2017.09.029Kennedy, R. E., Yang, Z., and Cohen, W. B. (2010). Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr - Temporal segmentation algorithms. In Remote Sensing of Environment (Vol. 114, Issue 12, pp. 2897-2910). https://doi.org/10.1016/j.rse.2010.07.008Kennedy, R., Yang, Z., Gorelick, N., Braaten, J., Cavalcante, L., Cohen, W., and Healey, S. (2018). Implementation of the LandTrendr Algorithm on Google Earth Engine. In Remote Sensing (Vol. 10, Issue 5, p. 691). https://doi.org/10.3390/rs10050691Olofsson, P., Foody, G. M., Herold, M., Stehman, S. V., Woodcock, C. E., and Wulder, M. A. (2014). Good practices for estimating area and assessing accuracy of land change. In Remote Sensing of Environment (Vol. 148, pp. 42-57). https://doi.org/10.1016/j.rse.2014.02.015Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M. and Duchesnay, E. (2011). Scikit-learn: Machine Learning in Python. In Journal of Machine Learning Research (Vol. 12, pp. 2825-2830).Pengra, B. W., Stehman, S. V., Horton, J. A., Dockter, D. J., Schroeder, T. A., Yang, Z., Cohen, W. B., Healey, S. P., and Loveland, T. R. (2020). Quality control and assessment of interpreter consistency of annual land cover reference data in an operational national monitoring program. In Remote Sensing of Environment (Vol. 238, p. 111261). https://doi.org/10.1016/j.rse.2019.111261U.S. Geological Survey. (2019). USGS 3D Elevation Program Digital Elevation Model, accessed August 2022 at https://developers.google.com/earth-engine/datasets/catalog/USGS_3DEP_10mWeiss, A.D. (2001). Topographic position and landforms analysis Poster Presentation, ESRI Users Conference, San Diego, CAZhu, Z., and Woodcock, C. E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery. In Remote Sensing of Environment (Vol. 118, pp. 83-94). https://doi.org/10.1016/j.rse.2011.10.028Zhu, Z., and Woodcock, C. E. (2014). Continuous change detection and classification of land cover using all available Landsat data. In Remote Sensing of Environment (Vol. 144, pp. 152-171). https://doi.org/10.1016/j.rse.2014.01.011This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

The Geographic Information System (GIS) market, currently valued at $4136.3 million in 2025, is poised for significant growth. While the provided CAGR is missing, a conservative estimate considering industry trends and technological advancements would place it between 7% and 10% annually for the forecast period (2025-2033). This growth is fueled by increasing adoption across various sectors, including urban planning, environmental management, and precision agriculture. The rising availability of high-resolution satellite imagery, coupled with advancements in data analytics and cloud computing, significantly enhances GIS capabilities, leading to wider application and market expansion. Furthermore, the growing need for efficient resource management and improved infrastructure planning, particularly in rapidly urbanizing regions, is driving demand. Competitive pressures from established players like Esri, Hexagon, and Pitney Bowes, alongside emerging technology companies, are fostering innovation and pushing the boundaries of GIS applications. However, market growth may face certain challenges. High initial investment costs for software and hardware, coupled with the need for skilled professionals to operate and interpret GIS data, could present barriers to entry for smaller organizations. Data security and privacy concerns, especially when dealing with sensitive geographical information, remain a crucial factor. Despite these restraints, the long-term outlook for the GIS market remains positive. Continued technological innovation, coupled with rising governmental and private sector investments in spatial data infrastructure, will likely outweigh these challenges and ensure sustained growth throughout the forecast period. The market is expected to witness increased adoption of advanced technologies such as AI and machine learning for spatial data analysis, leading to more sophisticated and insightful applications.

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

The Geographic Information System (GIS) Analytics market is experiencing robust growth, projected to reach $15.10 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 12.41% from 2025 to 2033. This expansion is fueled by several key drivers. Increasing adoption of cloud-based GIS solutions enhances accessibility and scalability for diverse industries. The growing need for data-driven decision-making across sectors like retail, real estate, government, and telecommunications is a significant catalyst. Furthermore, advancements in artificial intelligence (AI) and machine learning (ML) integrated with GIS analytics are revolutionizing spatial data analysis, enabling more sophisticated predictive modeling and insightful interpretations. The market's segmentation reflects this broad adoption, with retail and real estate, government and utilities, and telecommunications representing key end-user segments, each leveraging GIS analytics for distinct applications such as location optimization, infrastructure management, and network planning. Competitive pressures are shaping the market landscape, with established players like Esri, Trimble, and Autodesk innovating alongside emerging tech companies focusing on AI and specialized solutions. The North American market currently holds a significant share, driven by early adoption and technological advancements. However, Asia-Pacific is expected to witness substantial growth due to rapid urbanization and increasing investment in infrastructure projects. Market restraints primarily involve the high cost of implementation and maintenance of advanced GIS analytics solutions and the need for skilled professionals to effectively utilize these technologies. However, the overall outlook remains extremely positive, driven by continuous technological innovation and escalating demand across multiple sectors. The future trajectory of the GIS analytics market hinges on several factors. Continued investment in research and development, especially in AI and ML integration, will be crucial for unlocking new possibilities. Furthermore, the simplification of GIS analytics software and the development of user-friendly interfaces will broaden accessibility beyond specialized technical experts. Growing data volumes from various sources (IoT, remote sensing) present both opportunities and challenges; efficient data management and analytics techniques will be paramount. The market's success also depends on addressing cybersecurity concerns related to sensitive geospatial data. Strong partnerships between technology providers and end-users will be vital in optimizing solution implementation and maximizing return on investment. Government initiatives promoting the use of GIS technology for smart city development and infrastructure planning will also play a significant role in market expansion. Overall, the GIS analytics market is poised for sustained growth, driven by technological advancements, increasing data availability, and heightened demand for location-based intelligence across a wide range of industries.

Geographic Information System (GIS) Analytics Market Outlook

The global Geographic Information System (GIS) Analytics market size is projected to grow remarkably from $9.1 billion in 2023 to $21.7 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 10.2% during the forecast period. This substantial growth can be attributed to several factors such as technological advancements in GIS, increasing adoption in various industry verticals, and the rising importance of spatial data for decision-making processes.

The primary growth driver for the GIS Analytics market is the increasing need for accurate and efficient spatial data analysis to support critical decision-making processes across various industries. Governments and private sectors are investing heavily in GIS technology to enhance urban planning, disaster management, and resource allocation. With the world becoming more data-driven, the reliance on GIS for geospatial data has surged, further propelling its market growth. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) with GIS is revolutionizing the analytics capabilities, offering deeper insights and predictive analytics.

Another significant growth factor is the expanding application of GIS analytics in disaster management and emergency response. Natural disasters such as hurricanes, earthquakes, and wildfires have highlighted the importance of GIS in disaster preparedness, response, and recovery. The ability to analyze spatial data in real-time allows for quicker and more efficient allocation of resources, thus minimizing the impact of disasters. Moreover, GIS analytics plays a pivotal role in climate change studies, helping scientists and policymakers understand and mitigate the adverse effects of climate change.

The transportation sector is also a major contributor to the growth of the GIS Analytics market. With the rapid urbanization and increasing traffic congestion in cities, there is a growing demand for effective transport management solutions. GIS analytics helps in route optimization, traffic management, and infrastructure development, thereby enhancing the overall efficiency of transportation systems. The integration of GIS with Internet of Things (IoT) devices and sensors is further enhancing the capabilities of traffic management systems, contributing to the market growth.

Regionally, North America is the largest market for GIS analytics, driven by the high adoption rate of advanced technologies and significant investment in geospatial infrastructure by both public and private sectors. The Asia Pacific region is expected to witness the highest growth rate during the forecast period due to the rapid urbanization, infrastructural developments, and increasing government initiatives for smart city projects. Europe and Latin America are also contributing significantly to the market growth owing to the increasing use of GIS in urban planning and environmental monitoring.

Component Analysis

The GIS Analytics market can be segmented by component into software, hardware, and services. The software segment holds the largest market share due to the continuous advancements in GIS software solutions that offer enhanced functionalities such as data visualization, spatial analysis, and predictive modeling. The increasing adoption of cloud-based GIS software solutions, which offer scalable and cost-effective options, is further driving the growth of this segment. Additionally, open-source GIS software is gaining popularity, providing more accessible and customizable options for users.

The hardware segment includes GIS data collection devices such as GPS units, remote sensing instruments, and other data acquisition tools. This segment is witnessing steady growth due to the increasing demand for high-precision GIS data collection equipment. Technological advancements in hardware, such as the development of LiDAR and drones for spatial data collection, are significantly enhancing the capabilities of GIS analytics. Additionally, the integration of mobile GIS devices is facilitating real-time data collection, contributing to the growth of the hardware segment.

The services segment encompasses consulting, implementation, training, and maintenance services. This segment is expected to grow at a significant pace due to the increasing demand for professional services to manage and optimize GIS systems. Organizations are seeking expert consultants to help them leverage GIS analytics for strategic decision-making and operational efficiency. Additionally, the growing complexity o

City of Austin Open Data Terms of Use https://data.austintexas.gov/stories/s/ranj-cccq This dataset was created to depict approximate tree canopy cover for all land within the City of Austin's "full watershed regulation area." Intended for planning purposes and measuring citywide percent canopy. Definition: Tree canopy is defined as the layer of leaves, branches, and stems of trees that cover the ground when viewed from above. Methods: The 2022 tree canopy layer was derived from satellite imagery (Maxar) and aerial imagery (NAIP). Images were used to extract tree canopy into GIS vector features. First, a “visual recognition engine” generated the vector features. The engine used machine learning algorithms to detect and label image pixels as tree canopy. Then using prior knowledge of feature geometries, more modeling algorithms were used to predict and transform probability maps of labeled pixels into finished vector polygons depicting tree canopy. The resulting features were reviewed and edited through manual interpretation by GIS professionals. When appropriate, NAIP 2022 aerial imagery supplemented satellite images that had cloud cover, and a manual editing process made sure tree canopy represented 2022 conditions. Finally, an independent accuracy assessment was performed by the City of Austin and the Texas A&M Forest Service for quality assurance. GIS professionals assessed agreement between the tree canopy data and its source satellite imagery. An overall accuracy of 98% was found. Only 23 errors were found out of a total 1,000 locations reviewed. These were mostly omission errors (e.g. not including canopy in this dataset when canopy is shown in the satellite or aerial image). Best efforts were made to ensure ground-truth locations contained a tree on the ground. To ensure this, location data were used from City of Austin and Texas A&M Forest Service databases. Analysis: The City of Austin measures tree canopy using the calculation: acres of tree canopy divided by acres of land. The area of interest for the land acres is evaluated at the City of Austin's jurisdiction including Full Purpose, Limited Purpose, and Extraterritorial jurisdictions as of May 2023. New data show, in 2022, tree canopy covered 41% of the total land area within Austin's city limits (using city limit boundaries May 2023 and included in the download as layer name "city_of_austin_2023"). 160,046.50 canopy acres (2022) / 395,037.53 land acres = 40.51% ~41%. This compares to 36% last measured in 2018, and a historical average that’s also hovered around 36%. The time period between 2018 and 2022 saw a 5 percentage point change resulting in over 19K acres of canopy gained (estimated). Data Disclaimer: It's possible changes in percent canopy over the years is due to annexation and improved data methods (e.g. higher resolution imagery, AI, software used, etc.) in addition to actual in changes in tree canopy cover on the ground. For planning purposes only. Dataset does not account for individual trees, tree species nor any metric for tree canopy height. Tree canopy data is provided in vector GIS format housed in a Geodatabase. Download and unzip the folder to get started. Please note, errors may exist in this dataset due to the variation in species composition and land use found across the study area. This product is for informational purposes and may not have been prepared for or be suitable for legal, engineering, or surveying purposes. It does not represent an on-the-ground survey and represents only the approximate relative location of property boundaries. This product has been produced by the City of Austin for the sole purpose of geographic reference. No warranty is made by the City of Austin regarding specific accuracy or completeness. Data Provider: Ecopia AI Tech Corporation and PlanIT Geo, Inc. Data derived from Maxar Technologies, Inc. and USDA NAIP imagery

The global satellite remote sensing software market is experiencing robust growth, driven by increasing demand across diverse sectors. While precise figures for market size and CAGR aren't provided, considering the technological advancements and applications in agriculture (precision farming, crop monitoring), water conservancy (flood management, irrigation optimization), forest management (deforestation monitoring, resource assessment), and the public sector (urban planning, disaster response), a conservative estimate places the 2025 market size at approximately $2 billion. This figure reflects the substantial investments in satellite imagery acquisition and analysis capabilities worldwide. The market is further fueled by the rising adoption of cloud-based solutions, enhancing accessibility and scalability of software platforms. Trends such as the integration of AI and machine learning for automated image processing, the proliferation of high-resolution satellite imagery, and the increasing availability of open-source software are accelerating market expansion. However, factors such as the high cost of specialized software licenses and the need for skilled professionals to operate the sophisticated systems act as restraints. The market is segmented by application (agriculture, water conservancy, forest management, public sector, others) and software type (open-source, non-open-source). The North American and European markets currently hold significant shares, but the Asia-Pacific region is witnessing rapid growth due to increasing infrastructure development and government initiatives promoting geospatial technologies. This dynamic market landscape presents lucrative opportunities for both established players and emerging companies in the years to come. The forecast period (2025-2033) anticipates continued growth, with a projected CAGR of approximately 12%, driven by the aforementioned technological advancements and broadening applications across various industry verticals. The competitive landscape is comprised of both major players like ESRI, Trimble, and PCI Geomatica, offering comprehensive suites of software, and smaller, specialized companies focusing on niche applications or open-source solutions. The market is characterized by both proprietary and open-source software options. Open-source solutions like QGIS and GRASS GIS offer cost-effective alternatives, particularly for research and smaller organizations, while commercial solutions provide advanced functionalities and support. The increasing availability of cloud-based solutions is blurring the lines between these segments, with hybrid models emerging that combine the benefits of both. Future growth will be significantly influenced by collaborations between software providers and satellite imagery providers, fostering a more integrated ecosystem and streamlining the data acquisition and processing workflow. The market will continue to benefit from advancements in satellite technology, producing higher-resolution, more frequent, and more affordable imagery.

This course is intended to get you thinking about your future. Learn about where GIS professionals work, what they do, and how their educational choices prepare them for different types of jobs.GoalsDiscover the types of projects that GIS professionals work on.Identify qualities and skills that can help you get a GIS-related job.Choose educational options that match your goals and support your future career plans.