This layer was created from the California Aviation System Plan list of Automated Weather Observation Systems. The upgrades and distribution of Automated Weather Observing Systems (AWOS) Automated Surface Observation Systems (ASOS), and Automated Terminal Information Services (ATIS) in California are a critical part of the State aviation system. Access to localized weather conditions benefit both commercial and General Aviation (GA) operations. Caltrans Division of Aeronautics (Division) is monitoring the expansion and updating of the system with a focus on bringing more of this technology to key airports thereby improving air safety. Also, as AWOS/ASOS technology improves, the use of the hardware for shared uses, such as monitoring remote highways concurrently with remote airports is seen as an essential safety measure for normal as well as emergency response operations. The State is currently researching a cooperative approach to improving the road and aviation automated weather reporting system to support multimodal safety statewide. The expansion of the system through Public Private Partnerships (P3) is also becoming a topic of increasing interest as data and cost sharing strategies among various users becomes more desired, available and practical.Automated Weather Observation System (AWOS)AWOS is a computer-generated voice which is used to automate the broadcast of the minute-by-minute weather observations.Automated Surface Observation System (ASOS)The ASOS is the primary surface weather observing system of the United States.Automatic Terminal Information Service (ATIS)This the continuous broadcast of recorded non-control information which converts selected meteorological data and air traffic control data into human speech.

An automated inventory of the names and locations of physical and cultural geographic features located throughout the United States. To promote geographic feature name standardization and to serve as the Federal Government's repository of information regarding feature name spellings and applications for features in U.S. The names listed in the inventory can be published on Federal maps, charts, and in other documents. The feature locative information has been used in emergency preparedness, marketing, site-selection and analysis, genealogical and historical research, and transportation routing applications.The full Kansas geospatial catalog is administered by the Kansas Data Access & Support Center (DASC) and can be found at the following URL: https://hub.kansasgis.org/

GIS Software Market Outlook

According to our latest research, the global GIS software market size reached USD 9.4 billion in 2024, demonstrating robust expansion driven by digital transformation across multiple industries. The market is anticipated to grow at a CAGR of 12.3% from 2025 to 2033, with the forecasted market size expected to reach USD 29.7 billion by 2033. This impressive growth trajectory is primarily fueled by increasing adoption of spatial analytics, the proliferation of IoT devices, and the rising need for real-time geospatial data across sectors such as government, utilities, and transportation.

One of the principal growth factors underpinning the GIS software market is the rapid digitalization of infrastructure and asset management worldwide. As organizations seek to optimize operations, reduce costs, and improve decision-making processes, GIS software has become indispensable for integrating spatial data with business intelligence. The utility sector, for instance, leverages GIS solutions to manage grid assets, monitor outages, and plan network expansions efficiently. The widespread integration of GIS with enterprise resource planning (ERP) and customer relationship management (CRM) systems further enhances operational visibility and data-driven strategies. Additionally, the growing demand for location-based services in urban planning and smart city initiatives has significantly contributed to the expansion of the GIS software market.

Another significant driver is the evolution of GIS technology itself, particularly the transition from traditional desktop software to cloud-based and mobile GIS solutions. Cloud deployment has democratized access to advanced geospatial tools, enabling small and medium enterprises (SMEs) as well as large organizations to leverage GIS capabilities without heavy upfront investments in IT infrastructure. The rise of cloud-native GIS platforms has accelerated collaboration, scalability, and real-time data sharing, which is essential for dynamic industries like transportation and logistics. Moreover, advancements in artificial intelligence and machine learning have enhanced the analytical power of GIS software, allowing for predictive modeling, automated mapping, and improved spatial data visualization.

The increasing emphasis on environmental monitoring and sustainable development is also propelling market growth. Governments and environmental agencies utilize GIS software for land use planning, disaster management, and climate change mitigation projects. The ability to analyze spatial patterns and predict environmental impacts is critical for designing resilient infrastructure and resource management strategies. The agriculture sector, in particular, has embraced GIS for precision farming, crop monitoring, and supply chain optimization, further expanding the application scope of GIS software. This convergence of technological innovation and sustainability imperatives is expected to sustain high growth rates in the GIS software market over the forecast period.

From a regional perspective, North America continues to dominate the global GIS software market, accounting for the largest revenue share in 2024, followed closely by Europe and Asia Pacific. The presence of leading GIS vendors, early adoption of advanced technologies, and strong government support for smart infrastructure projects have positioned North America at the forefront of market expansion. However, the Asia Pacific region is witnessing the fastest growth, driven by rapid urbanization, infrastructure investments, and increasing digital literacy. Countries such as China, India, and Japan are investing heavily in GIS-enabled solutions for urban planning, disaster management, and transportation, signaling a significant shift in the global market landscape.

The Geographic Information System (GIS) plays a crucial role in the digital transformation journey of many industries. By providing a framework for gathering, managing, and analyzing spatial and geographic data, GIS helps organizations make informed decisions. This technology is not only pivotal in urban planning and environmental conservation but also in enhancing operational efficiencies across various sectors. For instance, in the transportation industry, GIS is used for route optimization and traffic management, whi

Geographic Information System (GIS) analyses are an essential part of natural resource management and research. Calculating and summarizing data within intersecting GIS layers is common practice for analysts and researchers. However, the various tools and steps required to complete this process are slow and tedious, requiring many tools iterating over hundreds, or even thousands of datasets. USGS scientists will combine a series of ArcGIS geoprocessing capabilities with custom scripts to create tools that will calculate, summarize, and organize large amounts of data that can span many temporal and spatial scales with minimal user input. The tools work with polygons, lines, points, and rasters to calculate relevant summary data and combine them into a single output table that can be easily incorporated into statistical analyses. These tools are useful for anyone interested in using an automated script to quickly compile summary information within all areas of interest in a GIS dataset.

Toolbox Use
License
Creative Commons-PDDC
Recommended Citation
Welty JL, Jeffries MI, Arkle RS, Pilliod DS, Kemp SK. 2021. GIS Clipping and Summarization Toolbox: U.S. Geological Survey Software Release. https://doi.org/10.5066/P99X8558

Pipeline Geospatial Information System Market Outlook

According to our latest research, the global Pipeline Geospatial Information System (GIS) market size reached USD 4.2 billion in 2024, reflecting the rapid adoption of advanced geospatial technologies across critical infrastructure sectors. The market is poised for robust expansion, registering a CAGR of 10.1% from 2025 to 2033, and is forecasted to attain a value of USD 10.1 billion by 2033. This growth trajectory is primarily driven by the increasing need for real-time asset monitoring, regulatory compliance, and the integration of digital technologies in pipeline management and infrastructure development.

One of the most significant growth factors for the Pipeline Geospatial Information System market is the escalating demand for efficient asset management solutions within the oil & gas, water & wastewater, and utilities sectors. As pipeline networks become more complex and geographically dispersed, organizations are turning to GIS technologies to enhance the accuracy of asset tracking, optimize maintenance schedules, and minimize operational disruptions. The integration of GIS with Internet of Things (IoT) sensors and advanced data analytics is further enabling organizations to gain actionable insights, reduce downtime, and proactively address potential pipeline failures. These capabilities are crucial for ensuring regulatory compliance, environmental safety, and cost efficiency, all of which are paramount concerns for industry stakeholders.

Another key driver propelling market growth is the increasing focus on digital transformation and automation across pipeline operations. The adoption of cloud-based GIS platforms is enabling real-time data sharing, collaboration, and remote monitoring, thereby improving decision-making processes and operational agility. The ability to visualize pipeline assets in a geospatial context is empowering organizations to plan expansions, conduct risk assessments, and respond swiftly to incidents. Furthermore, the integration of GIS with emerging technologies such as artificial intelligence (AI), machine learning (ML), and unmanned aerial vehicles (UAVs) is revolutionizing the inspection, monitoring, and maintenance of pipeline infrastructure. These advancements are not only enhancing operational efficiency but also reducing costs and improving safety outcomes.

Stringent regulatory requirements and heightened environmental concerns are also fueling the adoption of geospatial solutions in pipeline management. Governments and regulatory bodies worldwide are mandating comprehensive asset documentation, regular inspections, and proactive risk mitigation strategies to prevent leaks, spills, and other environmental hazards. GIS technologies are playing a pivotal role in enabling organizations to comply with these regulations by providing accurate mapping, real-time monitoring, and automated reporting capabilities. The growing emphasis on sustainability and environmental stewardship is expected to further accelerate the deployment of GIS solutions in the coming years, particularly in regions with aging pipeline infrastructure and high environmental risks.

From a regional perspective, North America continues to dominate the Pipeline Geospatial Information System market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The presence of extensive pipeline networks, stringent regulatory frameworks, and a strong focus on technological innovation are key factors driving market growth in these regions. Meanwhile, emerging economies in Asia Pacific and Latin America are witnessing rapid infrastructure development and increasing investments in digital technologies, presenting lucrative opportunities for market expansion. The Middle East & Africa region is also expected to exhibit robust growth, driven by the ongoing modernization of oil & gas infrastructure and the rising adoption of GIS solutions for asset management and environmental monitoring.

Geographic Information System Software plays a crucial role in the pipeline industry by providing advanced tools for spatial analysis, data integration, and visualization. These software solutions are essential for managing complex pip

The Grid Garage Toolbox is designed to help you undertake the Geographic Information System (GIS) tasks required to process GIS data (geodata) into a standard, spatially aligned format. This format …Show full descriptionThe Grid Garage Toolbox is designed to help you undertake the Geographic Information System (GIS) tasks required to process GIS data (geodata) into a standard, spatially aligned format. This format is required by most, grid or raster, spatial modelling tools such as the Multi-criteria Analysis Shell for Spatial Decision Support (MCAS-S). Grid Garage contains 36 tools designed to save you time by batch processing repetitive GIS tasks as well diagnosing problems with data and capturing a record of processing step and any errors encountered. Grid Garage provides tools that function using a list based approach to batch processing where both inputs and outputs are specified in tables to enable selective batch processing and detailed result reporting. In many cases the tools simply extend the functionality of standard ArcGIS tools, providing some or all of the inputs required by these tools via the input table to enable batch processing on a 'per item' basis. This approach differs slightly from normal batch processing in ArcGIS, instead of manually selecting single items or a folder on which to apply a tool or model you provide a table listing target datasets. In summary the Grid Garage allows you to: List, describe and manage very large volumes of geodata. Batch process repetitive GIS tasks such as managing (renaming, describing etc.) or processing (clipping, resampling, reprojecting etc.) many geodata inputs such as time-series geodata derived from satellite imagery or climate models. Record any errors when batch processing and diagnose errors by interrogating the input geodata that failed. Develop your own models in ArcGIS ModelBuilder that allow you to automate any GIS workflow utilising one or more of the Grid Garage tools that can process an unlimited number of inputs. Automate the process of generating MCAS-S TIP metadata files for any number of input raster datasets. The Grid Garage is intended for use by anyone with an understanding of GIS principles and an intermediate to advanced level of GIS skills. Using the Grid Garage tools in ArcGIS ModelBuilder requires skills in the use of the ArcGIS ModelBuilder tool. Download Instructions: Create a new folder on your computer or network and then download and unzip the zip file from the GitHub Release page for each of the following items in the 'Data and Resources' section below. There is a folder in each zip file that contains all the files. See the Grid Garage User Guide for instructions on how to install and use the Grid Garage Toolbox with the sample data provided.

GIS in the Cloud Market Outlook

The GIS in the Cloud market is poised for significant growth, with a projected market size increasing from $3.2 billion in 2023 to $7.5 billion by 2032, reflecting a robust compound annual growth rate (CAGR) of 9.8%. This growth is primarily driven by the increasing adoption of cloud-based geographic information systems (GIS) across various industries. Factors such as cost efficiency, scalability, and ease of access to geospatial data are encouraging industries to shift from traditional GIS solutions to cloud-based platforms. Additionally, the surge in demand for real-time location data analytics and the proliferation of Internet of Things (IoT) devices further underpin the market's expansion.

One of the primary growth drivers for the GIS in the Cloud market is the increasing need for spatial data in various sectors. Industries such as agriculture and utilities rely heavily on geospatial data to enhance their operational efficiency and decision-making processes. The integration of AI and machine learning with cloud-based GIS has further amplified the capabilities of these systems, enabling more precise and automated data analysis. This technological synergy is propelling the demand for cloud GIS solutions, as businesses seek to harness advanced analytics for improved insights and competitive advantage. Furthermore, the rise of smart city initiatives globally is fueling the demand for GIS solutions hosted in the cloud, as urban planning and management increasingly rely on spatial analytics for sustainable development.

The transition from on-premises GIS to cloud-based solutions offers significant cost benefits, which is a major growth factor for the market. Cloud GIS solutions eliminate the need for expensive hardware and maintenance, allowing companies to allocate resources more efficiently. This cost-effectiveness is particularly appealing to small and medium enterprises (SMEs) that may lack substantial IT budgets. Moreover, the cloud's scalability allows organizations to adjust their GIS capabilities in line with their growth, avoiding the limitations of fixed-capacity systems. The flexibility and reduced total cost of ownership associated with cloud GIS are encouraging more businesses to adopt these solutions, boosting market growth.

Another critical factor driving the market's growth is the growing demand for real-time geospatial analytics. Modern businesses require instantaneous access to data to make timely and informed decisions. Cloud-based GIS platforms facilitate real-time data processing and sharing, providing organizations with up-to-the-minute insights into their operations and environments. This capability is particularly vital in sectors such as transportation and emergency services, where rapid response and decision-making are essential. The ability to leverage real-time data, combined with the global accessibility of cloud platforms, is significantly enhancing the value proposition of cloud GIS solutions.

Regionally, North America is expected to maintain its dominance in the GIS in the Cloud market, driven by the early adoption of advanced technologies and the presence of key market players. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period. Rapid urbanization, coupled with growing investments in smart city projects and infrastructure development, is fueling the demand for cloud GIS solutions in this region. Additionally, government initiatives aimed at enhancing digital infrastructure are further propelling the market. Both Europe and Latin America are also experiencing increased adoption of cloud GIS, driven by technological advancements and the need for efficient resource management in various industries.

Component Analysis

The component segment of the GIS in the Cloud market can be broadly categorized into software and services. The software component is a critical part of the market, which includes GIS platforms and applications that facilitate data visualization, spatial analysis, and mapping. The increasing demand for user-friendly and feature-rich GIS software is driving the growth of this segment. Advances in software functionalities, such as enhanced 3D visualization, real-time data processing, and AI-driven analytics, are making cloud-based GIS software more attractive to users. These advancements are helping organizations to derive more value from their spatial data, leading to higher adoption rates of GIS software solutions in the cloud environment.

On the services front, the market is witnessing a growing demand for professional

The Tamalpais Lands Collaborative (One Tam; https://www.onetam.org/), the network of organizations that manage lands on Mount Tamalpais in Marin County, initiated the countywide mapping project with their interest in creating a seamless, comprehensive map depicting vegetation communities across the landscape. With support from their non-profit partner the Golden Gate National Parks Conservancy (https://www.parksconservancy.org/) One Tam was able to build a consortium to fund and implement the countywide fine scale vegetation map.Development of the Marin fine-scale vegetation map was managed by the Golden Gate National Parks Conservancy and staffed by personnel from Tukman Geospatial (https://tukmangeospatial.com/) Aerial Information Systems (AIS; http://www.aisgis.com/), and Kass Green and Associates. The fine-scale vegetation map effort included field surveys by a team of trained botanists. Data from these surveys, combined with older surveys from previous efforts, were analyzed by the California Native Plant Society (CNPS) Vegetation Program (https://www.cnps.org/vegetation) with support from the California Department of Fish and Wildlife Vegetation Classification and Mapping Program (VegCAMP; https://wildlife.ca.gov/Data/VegCAMP) to develop a Marin County-specific vegetation classification.High density lidar data was obtained countywide in the early winter of 2019 to support the project. The lidar point cloud, and many of its derivatives, were used extensively during the process of developing the fine-scale vegetation and habitat map. The lidar data was used in conjunction with optical data. Optical data used throughout the project included 6-inch resolution airborne 4-band imagery collected in the summer of 2018, as well as 6-inch imagery from 2014 and various dates of National Agriculture Imagery Program (NAIP) imagery.In 2019, a 26-class lifeform map was produced which serves as the foundation for the much more floristically detailed fine-scale vegetation and habitat map. The lifeform map was developed using expert systems rulesets in Trimble Ecognition®, followed by manual editing.In 2019, Tukman Geospatial staff and partners conducted countywide reconnaissance fieldwork to support fine-scale mapping. Field-collected data were used to train automated machine learning algorithms, which produced a fully automated countywide fine-scale vegetation and habitat map. Throughout 2020, AIS manually edited the fine-scale maps, and Tukman Geospatial and AIS went to the field for validation trips to inform and improve the manual editing process. In the spring of 2021, draft maps were distributed and reviewed by Marin County's community of land managers and by the funders of the project. Input from these groups was used to further refine the map. The countywide fine-scale vegetation map and related data products were made public in June 2021. In total, 107 vegetation classes were mapped with a minimum mapping size of one fifth to one acre, varying by class.Accuracy assessment plot data were collected in 2019, 2020, and 2021. Accuracy assessment results were compiled and analyzed in the summer of 2021. Overall accuracy of the lifeformmap is 95%. Overall accuracy of the fine-scale vegetation map is 77%, with an overall 'fuzzy' accuracy of 81%.The Marin County fine-scale vegetation map was designed for a broad audience for use at many floristic and spatial scales. At its most floristically resolute scale, the fine-scale vegetation map depicts the landscape at the National Vegetation Classification alliance level - which characterizes stands of vegetation generally by the dominant species present. This product is useful to managers interested in specific information about vegetation composition. For those interested in general land use and land cover, the lifeform map may be more appropriate. Tomake the information contained in the map accessible to the most users, the vegetation map is published as a suite of GIS deliverables available in a number of formats. Map products are being made available wherever possible by the project stakeholders, including the regional data portal Pacific Veg Map (http://pacificvegmap.org/data-downloads).

Abstract Relief classification methodologies seek to define the parameters that determine those parts of the terrestrial surface that present homogeneous forms and elements. The rapid development of geotechnology has increasingly provided tools and methodologies that assist in studies related to relief. The present work proposes a methodology to classify the relief in three taxonomic levels, using automated processing in a GIS environment. This procedure was applied in a case study of the Santa Maria River basin, in the west of Rio Grande do Sul State, Brazil. The digital data processing employed was the Geographic Information System ArcGIS® and the data from the SRTM 3 arc-second radar (90 meters) was the basis for the Digital Elevation Model. The processing for the first taxon used the amplitude and slope data to define four forms of relief: flat areas, slightly undulating hills, undulating hills, and hills with buttes and larger hills. In the second taxonomic level, ten relief elements were identified: flat, peak, ridge, shoulder, spur, slope, hollow, footslope, valley, and pit. In the third taxonomic level, the slope forms were characterized into eight units using the slope, profile, and curvature plane parameters. It was possible to detect the three proposed levels, the relief forms, relief elements, and slope forms. GIS processing offers a fast and precise definition of the relief forms and elements, and the slope forms, as well as the relationship between the three taxonomic levels.

Utility GIS-ADMS Integration Services Market Outlook

According to our latest research, the global Utility GIS-ADMS Integration Services market size reached USD 1.87 billion in 2024, reflecting robust adoption and technological innovation across utilities worldwide. The market is set to expand at a compound annual growth rate (CAGR) of 13.4% from 2025 to 2033, with the market forecasted to reach USD 5.72 billion by 2033. This remarkable growth is driven by the increasing need for enhanced grid reliability, the modernization of aging utility infrastructure, and the rising integration of distributed energy resources (DERs), all of which are fueling the demand for seamless Geographic Information System (GIS) and Advanced Distribution Management System (ADMS) integration.

The primary growth driver for the Utility GIS-ADMS Integration Services market is the escalating complexity of utility networks, particularly as utilities transition toward smart grid operations. As utilities face mounting pressure to improve operational efficiency, reduce outage durations, and optimize asset management, the integration of GIS and ADMS platforms has become indispensable. GIS provides a spatially accurate, real-time view of utility assets and networks, while ADMS offers advanced analytics and control capabilities. The synergy between these systems enables utilities to visualize, analyze, and manage their distribution networks more effectively, resulting in improved decision-making, faster outage response, and enhanced customer satisfaction. The proliferation of smart meters and IoT devices within utility grids further amplifies the relevance of integrated GIS-ADMS solutions, as these technologies generate vast volumes of spatial and operational data that must be efficiently managed and analyzed.

Another significant growth factor is the regulatory push for grid modernization and resilience, particularly in regions prone to natural disasters or with aging infrastructure. Governments and regulatory bodies are mandating utilities to invest in advanced technologies that can bolster grid reliability, facilitate the integration of renewable energy, and ensure regulatory compliance. As a result, utility companies are increasingly turning to GIS-ADMS integration services to meet these requirements. These integrated solutions support advanced functionalities such as real-time outage management, predictive maintenance, and automated restoration, all of which are critical for meeting stringent reliability and performance standards. Furthermore, the growing emphasis on sustainability and the global transition toward decarbonization are compelling utilities to adopt advanced distribution management solutions that can effectively manage distributed renewable generation and electric vehicle charging infrastructure.

The digital transformation of the utility sector is also propelling the growth of the Utility GIS-ADMS Integration Services market. Utilities are investing heavily in digital technologies to streamline operations, reduce costs, and enhance customer engagement. The convergence of GIS and ADMS platforms is a cornerstone of this digital transformation, enabling utilities to break down information silos, automate workflows, and leverage advanced analytics for proactive decision-making. Cloud-based deployment models are gaining traction, offering utilities greater scalability, flexibility, and cost-efficiency compared to traditional on-premises solutions. The adoption of cloud-based GIS-ADMS integration services is particularly pronounced among small and medium-sized utilities, which often lack the resources to maintain complex IT infrastructure in-house. As digitalization accelerates, the demand for skilled integration service providers capable of delivering customized, scalable, and secure solutions is set to rise sharply.

From a regional perspective, North America currently leads the Utility GIS-ADMS Integration Services market, accounting for the largest share in 2024, driven by extensive grid modernization initiatives, high technology adoption rates, and supportive regulatory frameworks. Europe follows closely, propelled by aggressive renewable energy targets and investments in smart grid infrastructure. The Asia Pacific region is emerging as the fastest-growing market, with a projected CAGR of 15.2% during the forecast period, fueled by rapid urbanization, expanding utility networks, and increasing government focus on grid reliability and sustainability. Latin America and the Mi

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning.

NG911 GIS Data Management Platforms Market Outlook

According to our latest research, the NG911 GIS Data Management Platforms market size reached USD 1.32 billion in 2024 globally, with a robust compound annual growth rate (CAGR) of 14.8% projected from 2025 to 2033. By 2033, the market is forecasted to reach USD 4.27 billion, driven by increasing government mandates for advanced emergency communication systems, rising public safety concerns, and the rapid adoption of geographic information system (GIS) technologies to enhance emergency response precision. The market demonstrates significant momentum as public and private sectors invest in next-generation 911 (NG911) infrastructure, ensuring improved situational awareness and more efficient incident management.

One of the primary growth factors propelling the NG911 GIS Data Management Platforms market is the global transition from legacy E911 systems to advanced NG911 frameworks. Governments and regulatory bodies are mandating the adoption of NG911 standards to enable more accurate, data-rich, and timely emergency responses. The integration of GIS data management platforms has become vital for supporting real-time location tracking, dynamic call routing, and interoperability among emergency services. This shift is further supported by growing urbanization, which increases the complexity of emergency management and necessitates more sophisticated solutions for mapping, visualization, and data sharing across agencies. As a result, investments in NG911 GIS platforms are surging, especially in regions with high population densities and advanced digital infrastructure.

Another key driver for market growth is the proliferation of mobile devices and the increasing use of multimedia in emergency communications. With the rise of smartphones, citizens are now able to send texts, images, and videos to emergency services, demanding platforms that can process and manage large volumes of geospatial and multimedia data efficiently. NG911 GIS Data Management Platforms are uniquely positioned to address these requirements, offering robust capabilities for data integration, analysis, and visualization. This technological evolution is fostering collaboration between public safety agencies and private technology providers, accelerating the deployment of scalable, cloud-based solutions that can adapt to evolving communication needs while ensuring data security and privacy.

The market is also benefiting from significant advancements in cloud computing, artificial intelligence, and machine learning, which are enhancing the capabilities of NG911 GIS platforms. These technologies enable predictive analytics, automated location validation, and real-time mapping, empowering emergency responders with actionable insights and situational awareness. The adoption of cloud-based deployment models is particularly notable, as it allows organizations to scale their operations, improve disaster recovery, and reduce capital expenditures. Furthermore, ongoing research and development efforts are focused on integrating next-generation features such as indoor mapping, IoT device connectivity, and augmented reality, which are expected to unlock new opportunities and expand the market’s addressable scope in the coming years.

Regionally, North America continues to dominate the NG911 GIS Data Management Platforms market, accounting for over 44% of the global market share in 2024. This leadership is attributed to the early adoption of NG911 standards, substantial government funding, and a highly developed public safety infrastructure. Europe follows as the second-largest market, driven by regulatory harmonization and cross-border emergency communication initiatives. Meanwhile, the Asia Pacific region is witnessing the fastest growth, fueled by rapid urbanization, increasing investments in smart city projects, and rising awareness about the benefits of advanced GIS platforms for emergency management. As countries across Latin America and the Middle East & Africa begin to modernize their emergency response systems, the global market is expected to experience sustained growth throughout the forecast period.

The Automated Geospatial Watershed Assessment (AGWA) tool is a GIS-based hydrologic modeling tool that uses commonly available GIS data layers to fully parameterize, execute, and spatially visualize results for the RHEM, KINEROS2, KINEROS-OPUS, SWAT2000, and SWAT2005 watershed runoff and erosion models. Accommodating novice to expert GIS users, it is designed to be used by watershed, water resource, land use, and resource managers and scientists investigating the hydrologic impacts of land-cover/land-use change in small watershed to basin-scale studies. AGWA is currently available as AGWA 1.5 for ArcView 3.x, AGWA 2.x for ArcGIS 9.x, and AGWA 3.X for ArcGIS 10.x. Planning and assessment in land and water resource management are evolving from simple, local-scale problems toward complex, spatially explicit regional ones. Such problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extensive data requirements and the difficult task of building input parameter files, however, have long represented an obstacle to the timely and cost-effective use of such complex models by resource managers. The USDA- ARS Southwest Watershed Research Center, in cooperation with the U.S. EPA Office of Research and Development Landscape Ecology Branch, the University of Arizona, and the University of Wyoming, has developed a GIS tool to facilitate this process. A geographic information system (GIS) provides the framework within which spatially-distributed data are collected and used to prepare model input files and evaluate model results. AGWA uses widely available standardized spatial datasets that can be obtained via the internet. The data are used to develop input parameter files for two watershed runoff and erosion models: KINEROS2 and SWAT.

Features used in the toothrow-morph training set.

Utility GIS Data Quality Services Market Outlook

According to our latest research, the global Utility GIS Data Quality Services market size reached USD 1.29 billion in 2024, with a robust growth trajectory marked by a CAGR of 10.7% from 2025 to 2033. By the end of the forecast period, the market is projected to attain a value of USD 3.13 billion by 2033. This growth is primarily driven by the increasing need for accurate spatial data, the expansion of smart grid initiatives, and the rising complexity of utility network infrastructures worldwide.

The primary growth factor propelling the Utility GIS Data Quality Services market is the surging adoption of Geographic Information Systems (GIS) for utility asset management and network optimization. Utilities are increasingly relying on GIS platforms to ensure seamless operations, improved decision-making, and regulatory compliance. However, the effectiveness of these platforms is directly linked to the quality and integrity of the underlying data. With the proliferation of IoT devices and the integration of real-time data sources, the risk of data inconsistencies and inaccuracies has risen, making robust data quality services indispensable. Utilities are investing heavily in data cleansing, validation, and enrichment to mitigate operational risks, reduce outages, and enhance customer satisfaction. This trend is expected to continue, as utilities recognize the strategic importance of data-driven operations in an increasingly digital landscape.

Another significant driver is the global movement towards smart grids and digital transformation across the utility sector. As utilities modernize their infrastructure, they are deploying advanced metering infrastructure (AMI) and integrating distributed energy resources (DERs), which generate vast volumes of spatial and non-spatial data. Ensuring the accuracy, consistency, and completeness of this data is crucial for optimizing grid performance, minimizing losses, and enabling predictive maintenance. The need for real-time analytics and advanced network management further amplifies the demand for high-quality GIS data. Additionally, regulatory mandates for accurate reporting and asset traceability are compelling utilities to prioritize data quality initiatives. These factors collectively create a fertile environment for the growth of Utility GIS Data Quality Services, as utilities strive to achieve operational excellence and regulatory compliance.

Technological advancements and the rise of cloud-based GIS solutions are also fueling market expansion. Cloud deployment offers utilities the flexibility to scale data quality services, access advanced analytics, and collaborate across geographies. This has democratized access to sophisticated GIS data quality tools, particularly for mid-sized and smaller utilities that previously faced budgetary constraints. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) in data quality solutions is enabling automated data cleansing, anomaly detection, and predictive analytics. These innovations are not only reducing manual intervention but also enhancing the accuracy and reliability of utility GIS data. As utilities continue to embrace digital transformation, the demand for cutting-edge data quality services is expected to surge, driving sustained market growth throughout the forecast period.

Utility GIS plays a pivotal role in supporting the digital transformation of the utility sector. By leveraging Geographic Information Systems, utilities can achieve a comprehensive understanding of their network infrastructures, enabling more efficient asset management and network optimization. The integration of Utility GIS with advanced data quality services ensures that utilities can maintain high standards of data accuracy and integrity, which are essential for effective decision-making and regulatory compliance. As utilities continue to modernize their operations and embrace digital technologies, the role of Utility GIS in facilitating seamless data integration and real-time analytics becomes increasingly critical. This not only enhances operational efficiency but also supports the strategic goals of sustainability and resilience in utility management.

Regionally, North America leads the Utility GIS Data Quality Services market, accounting for the largest share in 2024, followed closely by

Over 40,000 road crossings in Maine are maintained by Maine Department of Transportation (MaineDOT) managers, emergency managers, natural resource planners, and municipalities. Resource managers need a way to quickly and comprehensively assess, during the planning stages of potential transportation-related projects, how ecological, hydrologic, and structural characteristics of bridges and culverts and their watersheds could adversely affect project schedules and budgets. Factors that are critical to evaluate and incorporate into overall assessments of project risk include basin, land-use, and climatic characteristics; vulnerability to specific events, such as floods; and complicating factors in the watershed, such as endangered species, evacuation routes, and historical sites. A Python script tool has been built for ArcGIS Pro as an automated screening tool that draws on existing geographic information system (GIS) data layers to identify potential risk factors and quantify risk scores for bridges and culverts. This tool can help resource managers quickly evaluate projects, during early planning, in terms of variables that may adversely affect schedules or budgets.

Overlap of features in the five training sets.

CDFW BIOS GIS Dataset, Contact: Matt Merrifield, Description: Aerial Information Systems, Inc. (AIS) was contracted by The Nature Conservancy to create a vegetation map covering approximately 42500 acres (~66 square miles) within the majority of the San Benito River Valley. The goal of the project is to create a baseline vegetation map depicting existing conditions within the study area. The goal of the project is to create a baseline vegetation map depicting existing conditions within the study area.

Mobile GIS Data Collection Software Market Outlook

According to our latest research, the global Mobile GIS Data Collection Software market size reached USD 2.14 billion in 2024, and is anticipated to grow at a robust CAGR of 13.7% during the forecast period, reaching approximately USD 6.42 billion by 2033. This strong growth trajectory is primarily driven by the increasing demand for real-time geospatial data across multiple industries, the proliferation of mobile devices, and the integration of advanced technologies such as IoT and AI into GIS solutions. As organizations globally seek to enhance operational efficiency and decision-making capabilities, the adoption of mobile GIS data collection software continues to accelerate, reshaping the landscape of field data management and spatial analytics.

One of the pivotal growth factors for the Mobile GIS Data Collection Software market is the rapid digital transformation across industries such as utilities, transportation, agriculture, and government. Organizations are increasingly leveraging geospatial data to streamline field operations, optimize resource allocation, and improve asset management. The shift towards digitized workflows has created a surge in demand for mobile GIS solutions that enable real-time data capture, analysis, and sharing from remote locations. Furthermore, the growing emphasis on smart infrastructure and sustainable urban planning has amplified the need for accurate, up-to-date geographic information, positioning mobile GIS software as a critical tool in supporting these initiatives. The convergence of cloud computing, 5G connectivity, and mobile technologies is further enhancing the capabilities and accessibility of GIS platforms, making them indispensable for modern enterprises.

Another significant driver is the increasing adoption of IoT and sensor technologies, which are generating vast volumes of spatial data that require efficient collection, processing, and analysis. Mobile GIS data collection software enables seamless integration with IoT devices, allowing for automated data acquisition and real-time monitoring of assets, environmental conditions, and infrastructure. This capability is particularly valuable in sectors like environmental monitoring, utilities management, and agriculture, where timely and accurate geospatial data is essential for informed decision-making. Additionally, advancements in artificial intelligence and machine learning are empowering GIS software to deliver predictive analytics, anomaly detection, and advanced visualization, further expanding the application scope and value proposition of mobile GIS solutions.

The market is also benefiting from the increasing focus on regulatory compliance and safety standards, particularly in industries such as oil and gas, construction, and transportation. Mobile GIS data collection software facilitates compliance by providing accurate and auditable records of field activities, asset inspections, and environmental assessments. Moreover, the growing need for disaster management, emergency response, and public health surveillance is driving government agencies to invest in robust GIS platforms that support rapid data collection and situational awareness. As a result, vendors are continuously innovating to offer user-friendly, scalable, and secure solutions that cater to the evolving needs of diverse end-users, further fueling market expansion.

The integration of Mobile Mapping System technology into mobile GIS solutions is revolutionizing the way geospatial data is collected and analyzed. By utilizing vehicles equipped with advanced sensors and cameras, Mobile Mapping Systems enable the rapid and accurate capture of geospatial data across large areas. This technology is particularly beneficial for urban planning, infrastructure management, and environmental monitoring, where timely and precise data is crucial. As industries strive to enhance their operational capabilities, the adoption of Mobile Mapping Systems is becoming increasingly prevalent, providing a competitive edge through improved data accuracy and efficiency.

Regionally, North America currently dominates the Mobile GIS Data Collection Software market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The presence of leading technology providers, high adoption rates of digital soluti