Mobile GIS Data Collection Software Market Outlook

According to our latest research, the global mobile GIS data collection software market size reached USD 1.64 billion in 2024. The market is experiencing robust expansion, driven by the increasing demand for real-time geospatial data across industries. The market is projected to grow at a CAGR of 14.2% from 2025 to 2033, reaching a forecasted value of USD 4.46 billion by 2033. This growth is primarily fueled by the widespread adoption of mobile GIS solutions for field data collection, asset management, and environmental monitoring, as organizations seek efficient, accurate, and scalable geospatial data collection tools to enhance operational decision-making.

One of the primary growth factors propelling the mobile GIS data collection software market is the rapid digital transformation occurring across multiple sectors, such as utilities, government, agriculture, and transportation. Organizations are increasingly recognizing the value of real-time geospatial data in optimizing workflows, improving resource allocation, and ensuring regulatory compliance. The integration of mobile GIS solutions with Internet of Things (IoT) devices and advanced sensors enables seamless data capture, transmission, and analysis, empowering field teams to make informed decisions on the go. Furthermore, advancements in mobile hardware and connectivity, such as the proliferation of 5G networks, have significantly enhanced the usability and effectiveness of mobile GIS platforms, making them indispensable tools for field operations.

Another significant driver is the growing emphasis on environmental monitoring and sustainability initiatives worldwide. Governments and private organizations are leveraging mobile GIS data collection software to track environmental parameters, monitor land use changes, and support conservation efforts. The ability to collect, visualize, and analyze spatial data in real time is critical for managing natural resources, assessing environmental risks, and responding to emergencies such as natural disasters or hazardous material spills. As climate change concerns intensify and regulatory frameworks become more stringent, the demand for robust and scalable mobile GIS solutions is expected to rise, further boosting market growth.

The market is also benefiting from the increasing adoption of cloud-based mobile GIS solutions, which offer unparalleled scalability, flexibility, and cost-effectiveness. Cloud deployment enables organizations to centralize data storage, streamline collaboration, and ensure data integrity across geographically dispersed teams. The shift towards Software-as-a-Service (SaaS) models is reducing the upfront costs associated with traditional GIS deployments and making advanced geospatial analytics accessible to small and medium-sized enterprises (SMEs) as well as large corporations. This democratization of GIS technology is expanding the addressable market and fostering innovation in application development, user experience, and integration capabilities.

Regionally, North America remains the dominant market, accounting for the largest revenue share in 2024, driven by high technology adoption, a mature IT infrastructure, and the presence of leading GIS software providers. However, Asia Pacific is emerging as the fastest-growing region, supported by rapid urbanization, infrastructure development, and government initiatives promoting digital transformation. Europe also holds a significant market share, particularly in sectors such as utilities management and environmental monitoring. Meanwhile, Latin America and the Middle East & Africa are witnessing increasing investments in GIS technologies, reflecting the global trend toward smarter, data-driven decision-making across industries.

Component Analysis

The mobile GIS data collection software market is segmented by component into software and services, each playing a pivotal role in driving the adoption and effectiveness of GIS solutions. The software segment encompasses a wide array of applications designed for data capture, visualization, editing, and analysis on mobile devices. These software solutions are increasingly equipped with advanced features such as offline data collection, real-time synchronization, customizable workflows, and integration with third-party systems. The evolution of user-friendly interfaces and mobile-first design principles has further acceler

Cartography Software Market Outlook

According to our latest research, the global cartography software market size reached USD 2.15 billion in 2024, driven by increasing demand for advanced mapping solutions across diverse sectors. The market is expected to expand at a CAGR of 9.2% between 2025 and 2033, with the market size forecasted to reach USD 4.79 billion by 2033. This robust growth is primarily attributed to rapid urbanization, the proliferation of geospatial data, and growing integration of GIS technologies in government and commercial applications.

The primary growth factor propelling the cartography software market is the accelerating adoption of geospatial intelligence and geographic information systems (GIS) across various sectors. Governments, urban planners, and commercial enterprises are increasingly leveraging cartography software for enhanced decision-making, spatial data visualization, and resource management. The surge in smart city initiatives and infrastructure development projects worldwide is further boosting demand for sophisticated mapping tools. These tools enable stakeholders to visualize complex datasets, analyze spatial relationships, and optimize planning processes, thereby improving efficiency and reducing operational costs.

Another significant driver is the technological evolution within the cartography software landscape. The integration of artificial intelligence, machine learning, and cloud computing has transformed traditional mapping solutions into dynamic, interactive, and real-time platforms. These advancements have broadened the application scope of cartography software, making it indispensable in fields such as disaster management, environmental monitoring, and business intelligence. The ability to process large volumes of geospatial data quickly and accurately has enhanced the value proposition of cartography solutions, attracting investments from both public and private sectors.

Furthermore, the growing need for disaster risk management and environmental monitoring is catalyzing the adoption of cartography software. Governments and humanitarian organizations are increasingly utilizing these tools to map vulnerable areas, monitor climate change impacts, and plan emergency response strategies. The software’s capability to provide real-time situational awareness and predictive analytics is critical in mitigating risks and enhancing preparedness. As climate-related challenges intensify, the reliance on advanced cartographic solutions is expected to deepen, further fueling market growth.

From a regional perspective, North America currently dominates the cartography software market, supported by substantial investments in geospatial infrastructure and a high concentration of technology-driven enterprises. However, Asia Pacific is poised for the fastest growth, driven by rapid urbanization, expanding infrastructure projects, and increasing government focus on smart city development. Europe also holds a significant share, benefiting from robust regulatory frameworks and widespread adoption of GIS technologies across various sectors. The Middle East & Africa and Latin America are emerging as promising markets, with growing awareness of the benefits of digital mapping in resource management and urban planning.

Component Analysis

The cartography software market by component is bifurcated into software and services. The software segment captures the largest market share, accounting for over 65% in 2024, owing to the widespread adoption of advanced mapping solutions across government, commercial, and utility sectors. Modern cartography software platforms offer comprehensive features such as data visualization, spatial analysis, and real-time collaboration, making them indispensable tools for urban planners, environmental agencies, and businesses. The proliferation of open-source platforms and the availability of customizable mapping solutions have further accelerated the adoption of cartography software globally.
<

Streetlight GIS Inventory Platform Market Outlook

According to our latest research, the global Streetlight GIS Inventory Platform market size reached USD 1.17 billion in 2024, demonstrating robust growth driven by increasing urbanization and the adoption of smart city initiatives worldwide. The market is expected to expand at a CAGR of 12.4% from 2025 to 2033, with the total market value forecasted to reach USD 3.38 billion by 2033. This impressive growth trajectory is primarily fueled by the rising need for efficient asset management, the integration of IoT and AI technologies, and the growing demand for sustainability in urban infrastructure management. As per our comprehensive industry analysis, the market is poised for significant transformation, with stakeholders across municipalities, utilities, and commercial enterprises investing in advanced GIS inventory solutions to optimize streetlight operations and maintenance.

The growth of the Streetlight GIS Inventory Platform market is underpinned by several critical factors, chief among them being the global push towards smart city development. Governments and city planners are increasingly leveraging Geographic Information Systems (GIS) to streamline streetlight management, reduce energy consumption, and enhance public safety. The integration of GIS with streetlight infrastructure allows for real-time monitoring, predictive maintenance, and efficient resource allocation, which not only reduces operational costs but also supports environmental sustainability goals. Moreover, the proliferation of IoT-enabled sensors and cloud-based platforms has made it easier for municipalities and utilities to collect, analyze, and act upon vast amounts of data, further accelerating the adoption of GIS inventory platforms in urban settings.

Another significant driver for the Streetlight GIS Inventory Platform market is the growing emphasis on preventive and predictive maintenance strategies. Traditional approaches to streetlight management often result in delayed repairs, increased downtime, and higher maintenance costs. By implementing GIS-based inventory platforms, organizations can visualize asset locations, track maintenance histories, and predict potential failures before they occur. This proactive approach not only improves service reliability but also extends the lifespan of streetlight assets, thereby delivering substantial cost savings over time. Additionally, regulatory mandates concerning energy efficiency and public safety are compelling utilities and transportation authorities to adopt advanced GIS solutions, further propelling market growth.

Technological advancements represent another pivotal growth factor for the Streetlight GIS Inventory Platform market. The convergence of GIS with artificial intelligence, machine learning, and big data analytics is enabling more sophisticated asset management capabilities. These innovations allow for automated detection of faults, optimization of lighting schedules based on real-time traffic and weather data, and seamless integration with other urban infrastructure systems. As a result, end-users are increasingly seeking scalable and customizable GIS inventory platforms that can evolve with their operational needs. The market is also witnessing increased collaboration between public and private sectors, with commercial enterprises playing a vital role in driving innovation and offering value-added services to municipalities and utilities.

From a regional perspective, North America currently dominates the Streetlight GIS Inventory Platform market, owing to early adoption of smart city technologies, significant investments in infrastructure modernization, and stringent regulatory frameworks. Europe follows closely, driven by ambitious sustainability targets and widespread deployment of GIS solutions across urban centers. The Asia Pacific region is emerging as a high-growth market, fueled by rapid urbanization, government-led smart city projects, and increasing awareness of the benefits of GIS-based asset management. Latin America and the Middle East & Africa are also witnessing gradual adoption, supported by infrastructure development initiatives and international partnerships. Overall, the market exhibits a strong global footprint, with regional dynamics shaped by varying levels of technological maturity, regulatory support, and investment capacity.

Repository providing free access to marine geophysical data (e.g. bathymetry, seismic data, magnetics, gravity, images) and related land-based data from NSF-funded research conducted throughout the global oceans. Data Portals include GeoPRISMS, MARGINS, Ridge 2000, Antarctic and Southern Ocean Data Synthesis, the Global Multi-Resolution Topography Synthesis, and Seismic Reflection Field Data Portal. Primary data types served are multibeam bathymetric data from the ocean floor, seismic reflection data imaging below the seafloor, and multi-disciplinary ship based data from the Southern Ocean. Other holdings include deep-sea photographic transects, and ultra-high resolution bathymetry, temperature probe data, biological species compilations, MAPR and CTD data. Derived data products and sets include microseismicity catalogs, images, visualization scenes, magnetic and gravity compilations, grids of seismic layer thickness, velocity models, GIS project files, and 3D visualizations. Tools to discover, explore, and visualize data are available. They deliver catalogs, maps, and data through standard programmatic interfaces. GeoMapApp, a standalone data visualization and analysis tool, permits dynamic data exploration from a map interface and the capability to generate and download custom grids and maps and other data. Through GeoMapApp, users can access data hosted at the MGDS, at other data repositories, and import their own data sets. Global Multi-Resolution Topography (GMRT) is a continuously-updated compilation of seafloor bathymetry integrated with global land topography. It can be used to create maps and grids and it can be accessed through several standard programmatic interfaces including GeoMapApp and Google Earth. The GMRT compilation can also be explored in 3D using Virtual Ocean. The MGDS MediaBank contains high quality images, illustrations, animations and video clips that are organized into galleries. Media can be sorted by category, and keyword and map-based search options are provided. Each item in the MediaBank is accompanied by metadata that provides access to a cruise catalog and data repository.

Trade Area Mapping Platform Market Outlook

According to our latest research, the global Trade Area Mapping Platform market size is valued at USD 4.2 billion in 2024, and is expected to reach USD 11.8 billion by 2033, growing at a robust CAGR of 12.1% during the forecast period. The market is experiencing significant growth, propelled by the increasing adoption of advanced geospatial analytics and data-driven decision-making across various industries. The rapid integration of AI, machine learning, and cloud-based solutions is further transforming how businesses leverage trade area mapping platforms to optimize site selection, analyze consumer behavior, and enhance operational efficiency.

The primary growth driver for the Trade Area Mapping Platform market stems from the surging demand for sophisticated location intelligence tools across the retail, real estate, and logistics sectors. Organizations are increasingly recognizing the critical role of trade area mapping in identifying optimal locations for expansion, understanding competitive landscapes, and predicting consumer trends. Retailers, for instance, are leveraging these platforms to analyze foot traffic, demographic data, and purchasing patterns, which directly influence site selection strategies and marketing initiatives. The ability to visualize and interpret spatial data in real time is empowering businesses to make more informed, data-backed decisions, thereby fueling market growth.

Another significant factor contributing to the market’s upward trajectory is the proliferation of cloud-based deployment models. Cloud technology has democratized access to powerful mapping and analytics tools, enabling enterprises of all sizes to harness the benefits of trade area mapping without the need for substantial upfront investments in IT infrastructure. The scalability, flexibility, and cost-effectiveness of cloud-based platforms are particularly attractive to small and medium-sized enterprises (SMEs), which are increasingly adopting these solutions to stay competitive. Additionally, the integration of APIs and interoperability with other business intelligence tools is enhancing the overall value proposition of trade area mapping platforms.

Technological advancements, such as the incorporation of artificial intelligence, machine learning algorithms, and real-time analytics, are also reshaping the landscape of the Trade Area Mapping Platform market. These innovations are enabling more accurate predictions of consumer behavior, dynamic modeling of trade areas, and automated insights generation. The growing availability of high-quality geospatial data, coupled with improved data processing capabilities, is further driving adoption across sectors like urban planning, government, and logistics. As businesses continue to prioritize data-driven strategies for growth and efficiency, the demand for advanced trade area mapping solutions is expected to accelerate further.

From a regional perspective, North America currently dominates the Trade Area Mapping Platform market, accounting for the largest revenue share, followed by Europe and Asia Pacific. The presence of leading technology providers, high digital adoption rates, and a mature retail and real estate ecosystem are key factors underpinning North America’s leadership. However, the Asia Pacific region is witnessing the fastest growth, driven by rapid urbanization, expanding retail networks, and increasing investments in smart city initiatives. The Middle East & Africa and Latin America are also emerging as promising markets, supported by infrastructure development and growing awareness of geospatial intelligence solutions.

Component Analysis

The Component segment of the Trade Area Mapping Platform market is bifurcated into software and services, both of which play pivotal roles in the overall ecosystem. The software component encompasses a wide array of solutions designed to facilitate spatial analysis, geocoding, data visualization, and predictive modeling. These software platforms are increasingly leveraging cloud computing, artificial intelligence, and machine learning to deliver more accurate and actionable insights. The demand for intuitive, user-friendly interfaces and customizable dashboards is on the rise, as organizations seek to empower non-technical users to harness the power of geospatial analytics for business decision-making.

The Ontario government, generates and maintains thousands of datasets. Since 2012, we have shared data with Ontarians via a data catalogue. Open data is data that is shared with the public. Click here to learn more about open data and why Ontario releases it. Ontario’s Open Data Directive states that all data must be open, unless there is good reason for it to remain confidential. Ontario’s Chief Digital and Data Officer also has the authority to make certain datasets available publicly. Datasets listed in the catalogue that are not open will have one of the following labels: If you want to use data you find in the catalogue, that data must have a licence – a set of rules that describes how you can use it. A licence: Most of the data available in the catalogue is released under Ontario’s Open Government Licence. However, each dataset may be shared with the public under other kinds of licences or no licence at all. If a dataset doesn’t have a licence, you don’t have the right to use the data. If you have questions about how you can use a specific dataset, please contact us. The Ontario Data Catalogue endeavors to publish open data in a machine readable format. For machine readable datasets, you can simply retrieve the file you need using the file URL. The Ontario Data Catalogue is built on CKAN, which means the catalogue has the following features you can use when building applications. APIs (Application programming interfaces) let software applications communicate directly with each other. If you are using the catalogue in a software application, you might want to extract data from the catalogue through the catalogue API. Note: All Datastore API requests to the Ontario Data Catalogue must be made server-side. The catalogue's collection of dataset metadata (and dataset files) is searchable through the CKAN API. The Ontario Data Catalogue has more than just CKAN's documented search fields. You can also search these custom fields. You can also use the CKAN API to retrieve metadata about a particular dataset and check for updated files. Read the complete documentation for CKAN's API. Some of the open data in the Ontario Data Catalogue is available through the Datastore API. You can also search and access the machine-readable open data that is available in the catalogue. How to use the API feature: Read the complete documentation for CKAN's Datastore API. The Ontario Data Catalogue contains a record for each dataset that the Government of Ontario possesses. Some of these datasets will be available to you as open data. Others will not be available to you. This is because the Government of Ontario is unable to share data that would break the law or put someone's safety at risk. You can search for a dataset with a word that might describe a dataset or topic. Use words like “taxes” or “hospital locations” to discover what datasets the catalogue contains. You can search for a dataset from 3 spots on the catalogue: the homepage, the dataset search page, or the menu bar available across the catalogue. On the dataset search page, you can also filter your search results. You can select filters on the left hand side of the page to limit your search for datasets with your favourite file format, datasets that are updated weekly, datasets released by a particular organization, or datasets that are released under a specific licence. Go to the dataset search page to see the filters that are available to make your search easier. You can also do a quick search by selecting one of the catalogue’s categories on the homepage. These categories can help you see the types of data we have on key topic areas. When you find the dataset you are looking for, click on it to go to the dataset record. Each dataset record will tell you whether the data is available, and, if so, tell you about the data available. An open dataset might contain several data files. These files might represent different periods of time, different sub-sets of the dataset, different regions, language translations, or other breakdowns. You can select a file and either download it or preview it. Make sure to read the licence agreement to make sure you have permission to use it the way you want. Read more about previewing data. A non-open dataset may be not available for many reasons. Read more about non-open data. Read more about restricted data. Data that is non-open may still be subject to freedom of information requests. The catalogue has tools that enable all users to visualize the data in the catalogue without leaving the catalogue – no additional software needed. Have a look at our walk-through of how to make a chart in the catalogue. Get automatic notifications when datasets are updated. You can choose to get notifications for individual datasets, an organization’s datasets or the full catalogue. You don’t have to provide and personal information – just subscribe to our feeds using any feed reader you like using the corresponding notification web addresses. Copy those addresses and paste them into your reader. Your feed reader will let you know when the catalogue has been updated. The catalogue provides open data in several file formats (e.g., spreadsheets, geospatial data, etc). Learn about each format and how you can access and use the data each file contains. A file that has a list of items and values separated by commas without formatting (e.g. colours, italics, etc.) or extra visual features. This format provides just the data that you would display in a table. XLSX (Excel) files may be converted to CSV so they can be opened in a text editor. How to access the data: Open with any spreadsheet software application (e.g., Open Office Calc, Microsoft Excel) or text editor. Note: This format is considered machine-readable, it can be easily processed and used by a computer. Files that have visual formatting (e.g. bolded headers and colour-coded rows) can be hard for machines to understand, these elements make a file more human-readable and less machine-readable. A file that provides information without formatted text or extra visual features that may not follow a pattern of separated values like a CSV. How to access the data: Open with any word processor or text editor available on your device (e.g., Microsoft Word, Notepad). A spreadsheet file that may also include charts, graphs, and formatting. How to access the data: Open with a spreadsheet software application that supports this format (e.g., Open Office Calc, Microsoft Excel). Data can be converted to a CSV for a non-proprietary format of the same data without formatted text or extra visual features. A shapefile provides geographic information that can be used to create a map or perform geospatial analysis based on location, points/lines and other data about the shape and features of the area. It includes required files (.shp, .shx, .dbt) and might include corresponding files (e.g., .prj). How to access the data: Open with a geographic information system (GIS) software program (e.g., QGIS). A package of files and folders. The package can contain any number of different file types. How to access the data: Open with an unzipping software application (e.g., WinZIP, 7Zip). Note: If a ZIP file contains .shp, .shx, and .dbt file types, it is an ArcGIS ZIP: a package of shapefiles which provide information to create maps or perform geospatial analysis that can be opened with ArcGIS (a geographic information system software program). A file that provides information related to a geographic area (e.g., phone number, address, average rainfall, number of owl sightings in 2011 etc.) and its geospatial location (i.e., points/lines). How to access the data: Open using a GIS software application to create a map or do geospatial analysis. It can also be opened with a text editor to view raw information. Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A text-based format for sharing data in a machine-readable way that can store data with more unconventional structures such as complex lists. How to access the data: Open with any text editor (e.g., Notepad) or access through a browser. Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A text-based format to store and organize data in a machine-readable way that can store data with more unconventional structures (not just data organized in tables). How to access the data: Open with any text editor (e.g., Notepad). Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A file that provides information related to an area (e.g., phone number, address, average rainfall, number of owl sightings in 2011 etc.) and its geospatial location (i.e., points/lines). How to access the data: Open with a geospatial software application that supports the KML format (e.g., Google Earth). Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. This format contains files with data from tables used for statistical analysis and data visualization of Statistics Canada census data. How to access the data: Open with the Beyond 20/20 application. A database which links and combines data from different files or applications (including HTML, XML, Excel, etc.). The database file can be converted to a CSV/TXT to make the data machine-readable, but human-readable formatting will be lost. How to access the data: Open with Microsoft Office Access (a database management system used to develop application software). A file that keeps the original layout and

Silencio’s Noise Pollution Index Maps provide on-demand, high-resolution visualizations of urban and regional noise patterns worldwide. Built from 35 billion+ real noise measurements and AI-enhanced interpolation, these maps are designed for seamless integration into GIS platforms, smart city dashboards, and real estate location intelligence tools. Only available on request - data in sample is the measurement basis on which the maps are created.

Maps are generated on-demand for: • Cities, regions, or custom-defined areas globally • Real estate platforms for environmental and livability scoring • Government portals and dashboards for noise regulation, urban planning, and public health monitoring • Smart city applications to visualize urban soundscapes and improve planning and infrastructure design

Key Features: • Global coverage with consistent high-density data across continents • Generated specifically based on client-selected regions or cities • Fully GIS-ready in high-resolution image formats • Derived from real measurements combined with AI-powered interpolation for accuracy

Flexible delivery via image exports and available for custom licensing.

Electronic Navigational Charts (ENC) are vector data sets that support all types of marine navigation. Originally designed for large commercial vessels using a sophisticated navigational computer called an Electronic Chart Display and Information System (ECDIS), ENCs are now also being used on simpler electronic chart systems and “chart plotters” on many types of ships and by recreational boaters. NOAA ENCs help provide real-time ship positioning, as well as collision and grounding avoidance.The NOAA Chart Display Service renders NOAA Electronic Navigational Chart (ENC) data with "traditional paper chart" symbols, labels, and color schemes familiar to those who have used NOAA paper nautical charts or the NOAA Custom Chart application.NOAA ENCs comply with the International Hydrographic Organization ENC Product Specification. ENCs are produced around the world by many different countries’ national hydrographic or charting agencies. NOAA maintains more than 1,000 NOAA ENC® datasets over U.S. coastal waters and the Great Lakes.Free updates for NOAA ENCs are available weekly, which provide critical changes as well as the routine addition of newly compiled data, such as hydrographic or shoreline surveys. The NOAA Weekly Chart Updates page shows the areas that have changed on each ENC since its last new edition was published.ENCs also provide vector base maps for use in geographic information systems (GIS) that are used for coastal management and other purposes. The NOAA ENC Direct to GIS service supports extracting ENC data into GIS supported formats.Note: This layer is a feature service, which means it can be used for visualization and analysis throughout the ArcGIS Platform. This layer is not editable.

AI Generated Summary: The Ontario Data Catalogue is a data portal providing access to open datasets generated and maintained by the Ontario government. It allows users to search, access, visualize, and download data in various machine-readable formats, often through APIs, while also indicating licensing terms and data update frequencies. The catalogue also provides tools for data visualization and notifications for dataset updates. About: The Ontario government generates and maintains thousands of datasets. Since 2012, we have shared data with Ontarians via a data catalogue. Open data is data that is shared with the public. Click here to learn more about open data and why Ontario releases it. Ontario’s Digital and Data Directive states that all data must be open, unless there is good reason for it to remain confidential. Ontario’s Chief Digital and Data Officer also has the authority to make certain datasets available publicly. Datasets listed in the catalogue that are not open will have one of the following labels: If you want to use data you find in the catalogue, that data must have a licence – a set of rules that describes how you can use it. A licence: Most of the data available in the catalogue is released under Ontario’s Open Government Licence. However, each dataset may be shared with the public under other kinds of licences or no licence at all. If a dataset doesn’t have a licence, you don’t have the right to use the data. If you have questions about how you can use a specific dataset, please contact us. The Ontario Data Catalogue endeavors to publish open data in a machine readable format. For machine readable datasets, you can simply retrieve the file you need using the file URL. The Ontario Data Catalogue is built on CKAN, which means the catalogue has the following features you can use when building applications. APIs (Application programming interfaces) let software applications communicate directly with each other. If you are using the catalogue in a software application, you might want to extract data from the catalogue through the catalogue API. Note: All Datastore API requests to the Ontario Data Catalogue must be made server-side. The catalogue's collection of dataset metadata (and dataset files) is searchable through the CKAN API. The Ontario Data Catalogue has more than just CKAN's documented search fields. You can also search these custom fields. You can also use the CKAN API to retrieve metadata about a particular dataset and check for updated files. Read the complete documentation for CKAN's API. Some of the open data in the Ontario Data Catalogue is available through the Datastore API. You can also search and access the machine-readable open data that is available in the catalogue. How to use the API feature: Read the complete documentation for CKAN's Datastore API. The Ontario Data Catalogue contains a record for each dataset that the Government of Ontario possesses. Some of these datasets will be available to you as open data. Others will not be available to you. This is because the Government of Ontario is unable to share data that would break the law or put someone's safety at risk. You can search for a dataset with a word that might describe a dataset or topic. Use words like “taxes” or “hospital locations” to discover what datasets the catalogue contains. You can search for a dataset from 3 spots on the catalogue: the homepage, the dataset search page, or the menu bar available across the catalogue. On the dataset search page, you can also filter your search results. You can select filters on the left hand side of the page to limit your search for datasets with your favourite file format, datasets that are updated weekly, datasets released by a particular ministry, or datasets that are released under a specific licence. Go to the dataset search page to see the filters that are available to make your search easier. You can also do a quick search by selecting one of the catalogue’s categories on the homepage. These categories can help you see the types of data we have on key topic areas. When you find the dataset you are looking for, click on it to go to the dataset record. Each dataset record will tell you whether the data is available, and, if so, tell you about the data available. An open dataset might contain several data files. These files might represent different periods of time, different sub-sets of the dataset, different regions, language translations, or other breakdowns. You can select a file and either download it or preview it. Make sure to read the licence agreement to make sure you have permission to use it the way you want. A non-open dataset may be not available for many reasons. Read more about non-open data. Read more about restricted data. Data that is non-open may still be subject to freedom of information requests. The catalogue has tools that enable all users to visualize the data in the catalogue without leaving the catalogue – no additional software needed. Get automatic notifications when datasets are updated. You can choose to get notifications for individual datasets, an organization’s datasets or the full catalogue. You don’t have to provide and personal information – just subscribe to our feeds using any feed reader you like using the corresponding notification web addresses. Copy those addresses and paste them into your reader. Your feed reader will let you know when the catalogue has been updated. The catalogue provides open data in several file formats (e.g., spreadsheets, geospatial data, etc). Learn about each format and how you can access and use the data each file contains. A file that has a list of items and values separated by commas without formatting (e.g. colours, italics, etc.) or extra visual features. This format provides just the data that you would display in a table. XLSX (Excel) files may be converted to CSV so they can be opened in a text editor. How to access the data: Open with any spreadsheet software application (e.g., Open Office Calc, Microsoft Excel) or text editor. Note: This format is considered machine-readable, it can be easily processed and used by a computer. Files that have visual formatting (e.g. bolded headers and colour-coded rows) can be hard for machines to understand, these elements make a file more human-readable and less machine-readable. A file that provides information without formatted text or extra visual features that may not follow a pattern of separated values like a CSV. How to access the data: Open with any word processor or text editor available on your device (e.g., Microsoft Word, Notepad). A spreadsheet file that may also include charts, graphs, and formatting. How to access the data: Open with a spreadsheet software application that supports this format (e.g., Open Office Calc, Microsoft Excel). Data can be converted to a CSV for a non-proprietary format of the same data without formatted text or extra visual features. A shapefile provides geographic information that can be used to create a map or perform geospatial analysis based on location, points/lines and other data about the shape and features of the area. It includes required files (.shp, .shx, .dbt) and might include corresponding files (e.g., .prj). How to access the data: Open with a geographic information system (GIS) software program (e.g., QGIS). A package of files and folders. The package can contain any number of different file types. How to access the data: Open with an unzipping software application (e.g., WinZIP, 7Zip). Note: If a ZIP file contains .shp, .shx, and .dbt file types, it is an ArcGIS ZIP: a package of shapefiles which provide information to create maps or perform geospatial analysis that can be opened with ArcGIS (a geographic information system software program). A file that provides information related to a geographic area (e.g., phone number, address, average rainfall, number of owl sightings in 2011 etc.) and its geospatial location (i.e., points/lines). How to access the data: Open using a GIS software application to create a map or do geospatial analysis. It can also be opened with a text editor to view raw information. Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A text-based format for sharing data in a machine-readable way that can store data with more unconventional structures such as complex lists. How to access the data: Open with any text editor (e.g., Notepad) or access through a browser. Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A text-based format to store and organize data in a machine-readable way that can store data with more unconventional structures (not just data organized in tables). How to access the data: Open with any text editor (e.g., Notepad). Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A file that provides information related to an area (e.g., phone number, address, average rainfall, number of owl sightings in 2011 etc.) and its geospatial location (i.e., points/lines). How to access the data: Open with a geospatial software application that supports the KML format (e.g., Google Earth). Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. This format contains files with data from tables used for statistical analysis and data visualization of Statistics Canada census data. How to access the data: Open with the Beyond 20/20 application. A database which links and combines data from different files or

This project developed a comprehensive data management system designed to support collaborative groundwater research across institutions by establishing a centralized, structured database for hydrologic time series data. Built on the Observations Data Model (ODM), the system stores time series data and metadata in a relational SQLite database. Key project components included database construction, automation of data formatting and importation, development of analytical and visualization tools, and integration with ArcGIS for geospatial representation. The data import workflow standardizes and validates diverse .csv datasets by aligning them with ODM formatting. A Python-based module was created to facilitate data retrieval, analysis, visualization, and export, while an interactive map feature enables users to explore site-specific data availability. Additionally, a custom ArcGIS script was implemented to generate maps that incorporate stream networks, site locations, and watershed boundaries using DEMs from USGS sources. The system was tested using real-world datasets from groundwater wells and surface water gages across Utah, demonstrating its flexibility in handling diverse formats and parameters. The relational structure enabled efficient querying and visualization, and the developed tools promoted accessibility and alignment with FAIR principles.

Original Data: These files contain topographic lidar elevations generated from data collected using a Teledyne ALTM Galaxy PRIME sensor. Native lidar data is not generally in a format accessible to most Geographic Information Systems (GIS). Specialized in-house and commercial software packages are used to process the native lidar data into 3-dimensional positions that can be imported into GIS software for visualization and further analysis. Horizontal positions, provided in decimal degrees of latitude and longitude, are referenced to the North American Datum of 1983 National Adjustment of 2011 (NAD83 (2011)). Vertical positions are referenced to the NAD83 (2011) ellipsoid and provided in meters. The 3-D position data are sub-divided into a series of LAS files, which are tiled into 1-km by 1-km boxes defined by the Military Grid Reference System. The data were provided to the NOAA Office for Coastal Management (OCM) by the USACE Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) to make the data publicly available for bulk and custom downloads from the NOAA Digital Data Access Viewer (DAV).

Common Operating Picture Dashboards Market Outlook

According to our latest research, the global Common Operating Picture Dashboards market size reached USD 2.54 billion in 2024, with a robust compound annual growth rate (CAGR) of 11.2% projected from 2025 to 2033. This sustained growth trajectory is expected to drive the market to an estimated value of USD 6.65 billion by 2033. The principal growth factor fueling this market is the increasing need for real-time situational awareness and data integration across diverse sectors, particularly in public safety, critical infrastructure, and defense. As per our latest research, the expansion of digital transformation initiatives and the rising complexity of operational environments are key contributors to the market’s impressive momentum.

The growth of the Common Operating Picture Dashboards market is being significantly propelled by the rising emphasis on integrated data visualization and decision support tools across both public and private sectors. Organizations are increasingly recognizing the value of a unified dashboard that can consolidate disparate data sources into a single, actionable interface. This capability is crucial for stakeholders ranging from emergency management agencies to transportation authorities, enabling them to make swift, informed decisions during critical incidents. The proliferation of IoT devices and advanced sensor networks further amplifies the demand for dashboards capable of aggregating and interpreting large volumes of real-time data, thus enhancing operational efficiency and response times.

Another major growth factor is the escalating frequency and complexity of emergencies and security threats, which necessitate advanced situational awareness solutions. Governments and enterprises alike are investing heavily in Common Operating Picture Dashboards to enable seamless collaboration and information sharing during crises. The COVID-19 pandemic, for instance, underscored the importance of having robust, real-time monitoring systems to track infection rates, resource allocation, and emergency responses. This trend is mirrored in military and defense applications, where rapid access to up-to-date intelligence can be the difference between mission success and failure. As a result, the adoption of these dashboards is accelerating across multiple sectors, driving market expansion.

Furthermore, technological advancements in artificial intelligence, machine learning, and cloud computing are transforming the capabilities of Common Operating Picture Dashboards. Modern dashboards are now equipped with predictive analytics, automated alerts, and customizable visualization tools, making them indispensable for proactive decision-making. The integration of geospatial information systems (GIS) and advanced mapping functionalities is particularly valuable for applications in transportation, critical infrastructure, and emergency management. These innovations not only enhance the accuracy and relevance of the information displayed but also facilitate cross-departmental collaboration and interoperability, further fueling market growth.

From a regional perspective, North America currently leads the global Common Operating Picture Dashboards market due to its early adoption of advanced IT infrastructure and strong presence of major technology vendors. However, Asia Pacific is emerging as a rapidly growing market, driven by increasing investments in smart city initiatives, public safety, and critical infrastructure modernization. Europe also demonstrates significant potential, with ongoing efforts to enhance emergency preparedness and cross-border security cooperation. The Middle East & Africa and Latin America are gradually catching up, as governments in these regions recognize the strategic value of integrated situational awareness platforms for national security and disaster management.

Component Analysis

The Component segment of the Common Operating Picture Dashboards market is

This App includes 3,141 summary records by U.S. County for all Federal disaster declarations between 1964 and 2013. The initial map display shows the All Incidents later, but there are 12 Additional layers users can display showing the county declaration summary data by Incident Type (Fire, Flood, Tornado, etc...]. Click on an disaster declaration highlighted on the map and a custom pop-up attribute display will show you the disaster declaration information and census population estimates for reference. This App also includes a number of map tools to help visualize and analyze the data. NSGIC Data Citation:This project uses existing FEMA data resources that are the authoritative sources of information on this topic, including geospatial data files and open data APIs that were used to access available FEMA Federally-declared Natural Disaster data in the United States available from 1964 to 2014 (through 2013).To support our mapping needs, NSGIC downloaded a snapshot of FEMA data and published our own data Service Definitions and Feature Layers on NSGIC’s ArcGIS Online Mapping Platform to create the unfiltered Feature Layer Services we needed to support our mapping needs of the FEMA Federally Declared Disaster data.Note: These original data sources reflect a variety of inconsistencies and completeness is data collection, as well as changing definitions and priorities in FEMA’s disaster declaration information collection since record-keeping began in 1964. The original data was not modified.To publish the new Feature Layers on ArcGIS Online, NSGIC joined the FEMA Natural Disaster data with an Esri US County polygon shapefile with county population and demographic attributes from the U.S. Census Bureau’s American Community Survey. NSGIC added the 2010 and 2015 population estimates from the Census Bureau’s American Community Survey to relate the impacts of every declared natural disaster to current time frame.A significant portion of the available attribute data is not displayed in the NSGIC interactive maps, but is accessible through the site by experienced users.More recent data may be available from the original sourcesFEMA Data Citation:Data for this project was downloaded from FEMA in April 2016 and reflects the data available at that time using the available APIs.This product uses the Federal Emergency Management Agency’s API, but is not endorsed by FEMA.FEMA cannot verify the quality and/or timeliness of any data or any analysis derived therefrom after the data has been retrieved from FEMA.gov.

The Watershed Health Assessment Framework (WHAF) mapping application was developed to support natural resource management through an approach that emphasizes ecosystem health.

The WHAF application delivers a suite of watershed health index scores, each index represents a unique facet of the ecosystem. The index scores are organized within the five components of ecosystem Health: Hydrology, Geomorphology, Biology, Connectivity, and Water Quality. This 5-Component model provides a consistent structure for delivering a balanced and repeatable exploration of watershed conditions.

In addition to health scores, the application provides access to:
- Watershed boundaries with tools to visualize patterns of water movement.
- 100+ GIS data layers that provide insights to support natural resource management decisions and planning efforts.
- The ability to chart land cover at each watershed scale.
- The ability to save and share interactive map layouts through custom links and bookmarks.

The WHAF application is accessible from any modern web browser, although we recommend using a recent version of Google Chrome or Mozilla Firefox.

The WHAF health scores are also available for use in desktop GIS software, the data can be downloaded from Watershed Health Assessment Scores.

Data delivered through the application varies in origin and date of publication. Every effort is made to use the most current data available, and keep resources in sync with updates made to the source data. For detailed information regarding the data used to derive health scores, consult the health score analysis documentation. For detailed information regarding the source and publication data of additional GIS layers, consult the GIS Data Sources list.

The glioblastoma spatial transcriptomics dataset was generated from 4 FFPE fixed adult glioblastoma samples, using the 10x Genomics Visium platform, producing raw FASTQ files, spatial feature matrices (.h5, .mtx, .tsv), and paired histology images (.tif). Spot-level transcript counts were aligned to tissue architecture and processed in Seurat, with results stored as .rds objects. Data visualization was performed using SpatialFeaturePlot, and quantitative analyses were supported by custom Matlab scripts. The dataset provides both raw and processed files, offering reproducible spatially resolved transcriptomic profiles of glioblastoma tissue sections

Geospatial Cloud Market Outlook

According to our latest research, the global Geospatial Cloud market size reached USD 24.6 billion in 2024, propelled by the rapid digitalization of location-based services and the growing integration of geospatial data across diverse industries. The market is projected to expand at a robust CAGR of 13.2% from 2025 to 2033, reaching an estimated USD 68.8 billion by 2033. This impressive growth is primarily driven by advancements in cloud computing technologies, increased adoption of geospatial analytics for business intelligence, and the rising demand for real-time data visualization and decision-making solutions.

A significant growth factor for the geospatial cloud market is the exponential increase in the availability and accessibility of geospatial data, fueled by the proliferation of Internet of Things (IoT) devices, satellites, and remote sensing technologies. Modern organizations are leveraging these vast datasets to gain actionable insights, optimize operations, and enhance customer experiences. Cloud platforms have democratized access to powerful geospatial tools, enabling even small and medium enterprises to harness advanced mapping, spatial analytics, and location intelligence without the need for substantial upfront infrastructure investments. As industries such as agriculture, transportation, and utilities increasingly rely on precision data for resource management, route optimization, and disaster response, the demand for scalable and flexible geospatial cloud solutions continues to accelerate.

Another crucial driver is the evolution of cloud computing infrastructure itself, which has significantly improved the scalability, security, and interoperability of geospatial applications. Public, private, and hybrid cloud deployment models now offer tailored solutions that address diverse organizational requirements, from stringent data privacy regulations to seamless integration with existing enterprise systems. The shift from on-premises GIS systems to cloud-based platforms not only reduces operational costs but also enhances collaboration and data sharing across geographically dispersed teams. This trend is particularly pronounced in the public sector, where governments and defense agencies are increasingly adopting cloud-based geospatial solutions for urban planning, resource allocation, and national security.

Furthermore, the integration of artificial intelligence (AI), machine learning, and big data analytics with geospatial cloud platforms is unlocking new possibilities for predictive modeling, automated mapping, and spatial pattern recognition. These technological advancements are enabling organizations to process and analyze massive volumes of geospatial data in real time, supporting faster and more informed decision-making. The growing ecosystem of APIs and developer tools is also fostering innovation, allowing third-party providers to build specialized applications for industries such as natural resource management, disaster response, and smart city development. As a result, the geospatial cloud market is witnessing a surge in demand for both off-the-shelf and customized solutions tailored to specific business needs.

Regionally, North America remains the dominant market for geospatial cloud solutions, accounting for the largest share of global revenues in 2024. This leadership is attributed to the presence of major cloud service providers, high adoption rates of advanced technologies, and substantial investments in smart infrastructure projects. However, the Asia Pacific region is emerging as the fastest-growing market, driven by rapid urbanization, government-led digital transformation initiatives, and increasing investments in smart city and infrastructure development. Europe also presents significant growth opportunities, particularly in sectors such as transportation, environmental monitoring, and agriculture. The Middle East & Africa and Latin America are gradually catching up, supported by rising awareness of the benefits of geospatial analytics and expanding cloud infrastructure.

Managed GeoServer Services are becoming increasingly pivotal in the geospatial cloud market, offering tailored solutions that enhance the deployment and management of geospatial data. These services provide organizations with the expertise needed to efficiently manage th

Public Engagement Portals for Transmission Market Outlook

According to our latest research, the global Public Engagement Portals for Transmission market size reached USD 1.43 billion in 2024, reflecting robust digital transformation across transmission sectors. The market is expected to grow at a CAGR of 14.2% from 2025 to 2033, with projections indicating a value of USD 4.23 billion by 2033. This growth is primarily driven by the increasing emphasis on transparency, stakeholder inclusion, and regulatory compliance in infrastructure and energy transmission projects worldwide.

A key growth factor for the Public Engagement Portals for Transmission market is the rising demand for transparent and accessible communication channels between transmission project developers and the public. As infrastructure and energy projects expand, the need for effective stakeholder engagement has intensified. Regulatory bodies in many countries now mandate public participation as a prerequisite for project approvals, leading to a surge in adoption of digital engagement platforms. These portals streamline the process of gathering feedback, disseminating information, and documenting interactions, thus ensuring compliance while fostering trust among stakeholders. The growing complexity of transmission projects, particularly in urban and environmentally sensitive areas, further underscores the necessity for sophisticated public engagement tools.

Another significant driver is the rapid advancement in digital technologies, particularly cloud computing and data analytics, which have revolutionized the capabilities of public engagement portals. Modern solutions offer real-time data visualization, multilingual support, and integration with GIS and mapping tools, enabling project developers to present complex technical information in a user-friendly format. These features not only enhance user experience but also broaden the reach of engagement efforts, ensuring that diverse community groups can participate meaningfully. The integration of artificial intelligence and machine learning is further optimizing feedback analysis and sentiment tracking, allowing organizations to respond proactively to public concerns and mitigate potential project risks.

The market is also benefiting from the global push towards sustainable development and the decarbonization of energy systems. Transmission projects, especially those related to renewable energy integration, often face public scrutiny regarding environmental and social impacts. Public engagement portals play a pivotal role in addressing these concerns by providing transparent project updates, facilitating two-way communication, and enabling collaborative decision-making. This not only accelerates project timelines by reducing opposition but also helps organizations build long-term social license to operate. As governments and private sector entities prioritize ESG (Environmental, Social, and Governance) criteria, the adoption of advanced engagement platforms is expected to rise steadily.

Regionally, North America currently dominates the Public Engagement Portals for Transmission market, accounting for over 38% of global revenue in 2024. This leadership is attributed to stringent regulatory frameworks, high digital literacy, and a proactive approach to stakeholder engagement in the United States and Canada. Europe follows closely, driven by ambitious energy transition targets and robust public consultation requirements. The Asia Pacific region is emerging as a high-growth market, fueled by rapid infrastructure development and increasing awareness of participatory governance. Latin America and the Middle East & Africa are also witnessing gradual adoption, supported by international development initiatives and rising investment in digital infrastructure.

Component Analysis

The Public Engagement Portals for Transmission market is segmented by component into Software and Services. The software segment encompasses a wide range of digital solutions designed to facilitate public consultation, feedback management, and information dissemination. These platforms are increasingly leveraging cloud-based architectures and AI-driven analytics to deliver scalable, secure, and customizable engagement experiences. The demand for robust, user-friendly software is particularly strong among large-scale infrastructure developers and government agencies, who require advan

Map-Enhanced Risk Scoring Platform Market Outlook

According to our latest research, the global Map-Enhanced Risk Scoring Platform market size reached USD 3.42 billion in 2024, exhibiting robust expansion driven by increasing demand for spatial intelligence in risk assessment. The market is projected to grow at a CAGR of 16.8% during the forecast period, reaching a forecasted value of USD 15.08 billion by 2033. This significant growth is primarily attributed to the rising integration of geospatial data analytics with risk management frameworks across diverse industries, which is enhancing the accuracy and efficiency of risk scoring methodologies.

The primary growth factor for the Map-Enhanced Risk Scoring Platform market is the growing necessity for advanced risk mitigation tools amid rapidly evolving threat landscapes. Organizations across sectors such as financial services, insurance, healthcare, and logistics are increasingly leveraging geospatial data to gain real-time insights into risk variables. The combination of mapping technologies with AI-driven analytics enables businesses to visualize, predict, and respond to risks more proactively. Furthermore, the proliferation of IoT devices and the exponential growth of data sources have made it imperative for enterprises to adopt platforms capable of integrating and analyzing spatial data for comprehensive risk assessment.

Another major driver is the regulatory push for enhanced risk management and compliance, especially in highly regulated sectors like BFSI and healthcare. Regulatory bodies are mandating the use of advanced risk assessment tools to ensure transparency, accountability, and resilience against emerging threats. The implementation of map-enhanced risk scoring platforms allows organizations to not only comply with these regulations but also to streamline internal processes, reduce fraud, and optimize operational efficiency. Additionally, the increasing frequency of natural disasters, cyber threats, and supply chain disruptions has underscored the importance of spatial intelligence in risk management strategies.

Technological advancements in cloud computing, artificial intelligence, and big data analytics are further accelerating the adoption of map-enhanced risk scoring platforms. The availability of scalable cloud-based solutions has democratized access to sophisticated spatial analytics, making it feasible for small and medium enterprises to implement these platforms without significant upfront investments. Furthermore, the integration of real-time mapping, predictive analytics, and automated reporting is transforming traditional risk scoring models into dynamic, adaptive systems that can respond to evolving risks instantaneously. This technological evolution is expected to sustain market growth over the coming years.

Regionally, North America remains the dominant market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The strong presence of leading technology providers, combined with high regulatory standards and early adoption of digital risk management solutions, has positioned North America at the forefront of the global market. However, Asia Pacific is anticipated to witness the fastest growth during the forecast period, driven by rapid digitalization, expanding financial and healthcare sectors, and increasing investments in smart city initiatives. As businesses worldwide recognize the strategic value of spatial risk intelligence, the market is poised for substantial expansion across all major regions.

Component Analysis

The Component segment of the Map-Enhanced Risk Scoring Platform market is bifurcated into Software and Services. The software sub-segment constitutes the core of these platforms, offering robust functionalities such as geospatial analytics, visualization, AI-driven risk scoring, and real-time data integration. Modern software solutions are designed to be highly customizable, enabling organizations to tailor risk models to specific industry requirements. The proliferation of SaaS-based offerings has further accelerated software adoption, allowing for seamless updates, scalability, and integration with existing enterprise systems. As organizations increasingly seek to automate and streamline risk assessment processes, the demand for advanced software solutions is expected to remain strong.