The digital map market, currently valued at $25.55 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 13.39% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing adoption of location-based services (LBS) across diverse sectors like automotive, logistics, and smart city initiatives is a primary catalyst. Furthermore, advancements in technologies such as AI, machine learning, and high-resolution satellite imagery are enabling the creation of more accurate, detailed, and feature-rich digital maps. The shift towards cloud-based deployment models offers scalability and cost-effectiveness, further accelerating market growth. While data privacy concerns and the high initial investment costs for sophisticated mapping technologies present some challenges, the overall market outlook remains overwhelmingly positive. The competitive landscape is dynamic, with established players like Google, TomTom, and ESRI vying for market share alongside innovative startups offering specialized solutions. The segmentation of the market by solution (software and services), deployment (on-premise and cloud), and industry reveals significant opportunities for growth in sectors like automotive navigation, autonomous vehicle development, and precision agriculture, where real-time, accurate mapping data is crucial. The Asia-Pacific region, driven by rapid urbanization and technological advancements in countries like China and India, is expected to witness particularly strong growth. The market's future hinges on continuous innovation. We anticipate a rise in the demand for 3D maps, real-time updates, and integration with other technologies like the Internet of Things (IoT) and augmented reality (AR). Companies are focusing on enhancing the accuracy and detail of their maps, incorporating real-time traffic data, and developing tailored solutions for specific industry needs. The increasing adoption of 5G technology promises to further boost the market by enabling faster data transmission and real-time updates crucial for applications like autonomous driving and drone delivery. The development of high-precision mapping solutions catering to specialized sectors like infrastructure management and disaster response will also fuel future growth. Ultimately, the digital map market is poised for continued expansion, driven by technological advancements and increased reliance on location-based services across a wide spectrum of industries. Recent developments include: December 2022 - The Linux Foundation has partnered with some of the biggest technology companies in the world to build interoperable and open map data in what is an apparent move t. The Overture Maps Foundation, as the new effort is called, is officially hosted by the Linux Foundation. The ultimate aim of the Overture Maps Foundation is to power new map products through openly available datasets that can be used and reused across applications and businesses, with each member throwing their data and resources into the mix., July 27, 2022 - Google declared the launch of its Street View experience in India in collaboration with Genesys International, an advanced mapping solutions company, and Tech Mahindra, a provider of digital transformation, consulting, and business re-engineering solutions and services. Google, Tech Mahindra, and Genesys International also plan to extend this to more than around 50 cities by the end of the year 2022.. Key drivers for this market are: Growth in Application for Advanced Navigation System in Automotive Industry, Surge in Demand for Geographic Information System (GIS); Increased Adoption of Connected Devices and Internet. Potential restraints include: Complexity in Integration of Traditional Maps with Modern GIS System. Notable trends are: Surge in Demand for GIS and GNSS to Influence the Adoption of Digital Map Technology.

Polygon layer representing United States counties with name attributes.About Natural EarthNatural Earth is a convenient resource for creating custom maps. Unlike other map data intended for analysis or detailed government mapping, it is designed to meet the needs of cartographers and designers to make generalized maps. Maximum flexibility is a goal.Natural Earth is a public domain collection of map datasets available at 1:10 million (larger scale/more detailed), 1:50 million (medium scale/moderate detail), and 1:110 million (small scale/coarse detail) scales. It features tightly integrated vector and raster data to create a variety of visually pleasing, well-crafted maps with cartography or GIS software. Natural Earth data is made possible by many volunteers and supported by the North American Cartographic Information Society (NACIS).Convenience – Natural Earth solves a problem: finding suitable data for making small-scale maps. In a time when the web is awash in geospatial data, cartographers are forced to waste time sifting through confusing tangles of poorly attributed data to make clean, legible maps. Because your time is valuable, Natural Earth data comes ready to use.Neatness Counts–The carefully generalized linework maintains consistent, recognizable geographic shapes at 1:10m, 1:50m, and 1:110m scales. Natural Earth was built from the ground up, so you will find that all data layers align precisely with one another. For example, where rivers and country borders are one and the same, the lines are coincident.GIS Attributes – Natural Earth, however, is more than just a collection of pretty lines. The data attributes are equally important for mapmaking. Most data contain embedded feature names, which are ranked by relative importance. Other attributes facilitate faster map production, such as width attributes assigned to river segments for creating tapers. Intelligent dataThe attributes assigned to Natural Earth vectors make for efficient mapmaking. Most lines and areas contain embedded feature names, which are ranked by relative importance. Up to eight rankings per data theme allow easy custom map “mashups” to emphasize your subject while de-emphasizing reference features. Other attributes focus on map design. For example, width attributes assigned to rivers allow you to create tapered drainages. Assigning different colors to contiguous country polygons is another task made easier thanks to data attribution.Other key featuresVector features include name attributes and bounding box extents. Know that the Rocky Mountains are larger than the Ozarks.Large polygons are split for more efficient data handling—such as bathymetric layers.Projection-friendly vectors precisely match at 180 degrees longitude. Lines contain enough data points for smooth bending in conic projections, but not so many that computer processing speed suffers.Raster data includes grayscale-shaded relief and cross-blended hypsometric tints derived from the latest NASA SRTM Plus elevation data and tailored to register with Natural Earth Vector.Optimized for use in web mapping applications, with built-in scale attributes to assist features to be shown at different zoom levels.

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990-1999 and 2000-2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990-1999 and 2000-2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000-2009 than during 1990-1999; and that inland water levels were generally lower during 2000-2009 than during 1990-1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990-1999. Mean October water levels during 2000-2009 were generally higher than during 1990-1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

GIS Data Management Market Outlook

The global GIS Data Management market size is projected to grow from USD 12.5 billion in 2023 to USD 25.6 billion by 2032, exhibiting a CAGR of 8.4% during the forecast period. This impressive growth is driven by the increasing adoption of geographic information systems (GIS) across various sectors such as urban planning, disaster management, and agriculture. The rising need for effective data management systems to handle the vast amounts of spatial data generated daily also significantly contributes to the market's expansion.

One of the primary growth factors for the GIS Data Management market is the burgeoning demand for spatial data analytics. Businesses and governments are increasingly leveraging GIS data to make informed decisions and strategize operational efficiencies. With the rapid urbanization and industrialization worldwide, there's an unprecedented need to manage and analyze geographic data to plan infrastructure, monitor environmental changes, and optimize resource allocation. Consequently, the integration of GIS with advanced technologies like artificial intelligence and machine learning is becoming more prominent, further fueling market growth.

Another significant factor propelling the market is the advancement in GIS technology itself. The development of sophisticated software and hardware solutions for GIS data management is making it easier for organizations to capture, store, analyze, and visualize geographic data. Innovations such as 3D GIS, real-time data processing, and cloud-based GIS solutions are transforming the landscape of geographic data management. These advancements are not only enhancing the capabilities of GIS systems but also making them more accessible to a broader range of users, from small enterprises to large governmental agencies.

The growing implementation of GIS in disaster management and emergency response activities is also a critical factor driving market growth. GIS systems play a crucial role in disaster preparedness, response, and recovery by providing accurate and timely geographic data. This data helps in assessing risks, coordinating response activities, and planning resource deployment. With the increasing frequency and intensity of natural disasters, the reliance on GIS data management systems is expected to grow, resulting in higher demand for GIS solutions across the globe.

Geospatial Solutions are becoming increasingly integral to the GIS Data Management landscape, offering enhanced capabilities for spatial data analysis and visualization. These solutions provide a comprehensive framework for integrating various data sources, enabling users to gain deeper insights into geographic patterns and trends. As organizations strive to optimize their operations and decision-making processes, the demand for robust geospatial solutions is on the rise. These solutions not only facilitate the efficient management of spatial data but also support advanced analytics and real-time data processing. By leveraging geospatial solutions, businesses and governments can improve their strategic planning, resource allocation, and environmental monitoring efforts, thereby driving the overall growth of the GIS Data Management market.

Regionally, North America holds a significant share of the GIS Data Management market, driven by high technology adoption rates and substantial investments in GIS technologies by government and private sectors. However, Asia Pacific is anticipated to witness the highest growth rate during the forecast period. The rapid urbanization, economic development, and increasing adoption of advanced technologies in countries like China and India are major contributors to this growth. Governments in this region are also focusing on smart city projects and infrastructure development, which further boosts the demand for GIS data management solutions.

Component Analysis

The GIS Data Management market is segmented by component into software, hardware, and services. The software segment is the largest and fastest-growing segment, driven by the continuous advancements in GIS software capabilities. GIS software applications enable users to analyze spatial data, create maps, and manage geographic information efficiently. The integration of GIS software with other enterprise systems and the development of user-friendly interfaces are key factors propelling the growth of this segment. Furthermore, the rise of mobile GIS applications, which allow field data collectio

Spatial Mapping Software Market Outlook

According to our latest research, the global spatial mapping software market size reached USD 6.2 billion in 2024, reflecting the sector’s robust expansion across industries. The market is expected to grow at a CAGR of 14.1% from 2025 to 2033, reaching an estimated USD 19.3 billion by 2033. The primary growth factor propelling this market is the increasing adoption of spatial data analytics and geospatial intelligence across urban planning, environmental monitoring, and asset management sectors, as organizations strive for enhanced decision-making and operational efficiency.

One of the most significant growth drivers for the spatial mapping software market is the rapid urbanization witnessed globally. Governments and private entities are investing heavily in smart city initiatives, which require advanced mapping tools for infrastructure planning, traffic management, and resource allocation. The integration of spatial mapping software with IoT devices and sensors is enabling real-time data collection and visualization, thus streamlining urban planning processes. Moreover, the growing need for sustainable development and efficient land use is pushing city planners to leverage spatial mapping solutions for accurate geospatial analysis, zoning, and resource optimization. This trend is expected to continue, with urban centers increasingly relying on spatial intelligence to tackle challenges related to population growth, environmental sustainability, and public safety.

Technological advancements in artificial intelligence, machine learning, and cloud computing are further accelerating the growth of the spatial mapping software market. Modern mapping platforms now offer sophisticated features such as 3D visualization, predictive analytics, and automated data processing, which significantly enhance the value proposition for end-users. These innovations are not only improving the accuracy and usability of spatial data but are also making it accessible to non-technical users through intuitive interfaces and seamless integrations with enterprise resource planning (ERP) and geographic information system (GIS) platforms. Additionally, the proliferation of mobile devices and high-speed internet connectivity has made spatial mapping tools more versatile, enabling field workers and remote teams to access, update, and share geospatial information in real time.

Another critical factor contributing to the market’s expansion is the rising importance of spatial mapping software in disaster management and environmental monitoring. Governments, NGOs, and emergency response teams are increasingly utilizing these platforms to assess risks, plan evacuations, and coordinate relief efforts in the wake of natural disasters such as floods, earthquakes, and wildfires. Spatial mapping software enables the integration of diverse datasets, including satellite imagery, sensor data, and historical records, to create comprehensive risk maps and predictive models. This capability is invaluable for proactive disaster preparedness and rapid response, helping to minimize loss of life and property. Similarly, environmental agencies are leveraging these tools to monitor deforestation, track wildlife movements, and manage natural resources, further boosting market demand.

From a regional perspective, North America currently leads the spatial mapping software market, driven by substantial investments in smart infrastructure, advanced technological adoption, and a mature ecosystem of geospatial solution providers. Europe follows closely, with strong government support for digital transformation in urban planning and environmental sustainability. The Asia Pacific region is emerging as a high-growth market, fueled by rapid urbanization, infrastructure development, and increasing adoption of smart city solutions in countries like China, India, and Japan. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth, supported by government initiatives for modernization and improved disaster management capabilities. These regional dynamics are shaping the competitive landscape and driving innovation in the global spatial mapping software market.

Component Analysis

The spatial mapping software market is segmented by component into software and services. The software segment dominates the market, accounting for the largest share due to the widespread adoption of propriet

Industrial Drone Mapping Software Market Outlook

As per our latest research, the global industrial drone mapping software market size reached USD 1.42 billion in 2024, demonstrating robust momentum driven by expanding applications across multiple sectors. The market is expected to grow at a CAGR of 17.8% from 2025 to 2033, reaching a forecasted value of USD 6.13 billion by 2033. The primary growth factor fueling this expansion is the accelerated adoption of drone technology for high-precision mapping and surveying in industries such as construction, agriculture, energy, and mining, where efficiency, accuracy, and data-driven decision-making have become paramount.

One of the major growth drivers for the industrial drone mapping software market is the increasing demand for geospatial intelligence and real-time data analytics in industrial operations. Companies across sectors are leveraging drone mapping software to streamline site inspections, manage assets, and optimize resource allocation. The softwareÂ’s ability to generate high-resolution maps, 3D models, and actionable insights allows businesses to reduce operational costs, minimize manual labor, and enhance safety. Furthermore, as industries increasingly focus on digital transformation and automation, drone mapping solutions are becoming integral to project planning, progress monitoring, and risk assessment, thereby accelerating market growth.

Another significant factor propelling the market is the rapid advancement in drone and mapping technologies. The integration of artificial intelligence, machine learning, and cloud computing with drone mapping software has revolutionized data processing capabilities, enabling faster and more accurate analysis. Modern industrial drone mapping software platforms offer automated flight planning, real-time data streaming, and seamless integration with enterprise resource planning (ERP) systems. These technological enhancements not only improve user experience but also expand the scope of applications, making drone mapping indispensable for large-scale infrastructure projects, environmental monitoring, and precision agriculture.

Regulatory support and favorable government initiatives are also contributing to the expansion of the industrial drone mapping software market. Many countries have introduced policies that facilitate the commercial use of drones, including streamlined licensing procedures and safety guidelines. These regulations have fostered innovation and encouraged investments in drone-based solutions, particularly in regions with significant infrastructure development and agricultural modernization. Moreover, the growing emphasis on sustainability and environmental monitoring is pushing organizations to adopt drone mapping software for efficient land use management, disaster response, and ecological assessments, further bolstering market growth.

Drone Photogrammetry Software is becoming an essential tool in the realm of industrial drone mapping. This software leverages advanced photogrammetric techniques to transform aerial images into precise, high-quality maps and 3D models. By automating the process of image stitching and analysis, drone photogrammetry software significantly reduces the time and effort required for data processing. Industries such as construction, agriculture, and mining are increasingly adopting this technology to enhance their operational efficiency and accuracy. The ability to generate detailed topographical data and orthomosaic maps is particularly beneficial for large-scale projects, enabling better planning and resource management. As the demand for high-resolution geospatial data continues to rise, drone photogrammetry software is poised to play a pivotal role in the future of industrial mapping solutions.

From a regional perspective, North America currently leads the global market, driven by early technology adoption, a strong presence of key players, and substantial investments in research and development. Europe follows closely, supported by stringent environmental regulations and an increasing focus on smart infrastructure. The Asia Pacific region is witnessing the fastest growth, with countries like China, Japan, and India rapidly integrating drone mapping software into their industrial ecosystems. These regions are benefiting from large-scale construction projects, expanding agr

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990-1999 and 2000-2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990-1999 and 2000-2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000-2009 than during 1990-1999; and that inland water levels were generally lower during 2000-2009 than during 1990-1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990-1999. Mean October water levels during 2000-2009 were generally higher than during 1990-1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

COVID-19: Army Corps Uses Maps and Models to Create Surge Hospital CapacityAfter recognizing the possibility that the COVID-19 pandemic could cause hospital bed capacity to be exceeded, the US Army Corps of Engineers (USACE) was tasked with working with the states to build and inspect alternate care facilities.A team from USACE developed engineering plans for converting existing facilities with rooms (such as hotels or college dormitories) and those with large open areas (like field houses or convention centers). From there, the team developed standardized designs, then used mobile applications to quickly assess candidate sites and inspect the retrofitted facilities for readiness._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

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Geomarketing Software Market Size 2024-2028

The geomarketing software market size is forecast to increase by USD 29.25 billion at a CAGR of 25.77% between 2023 and 2028.

The market is experiencing significant growth due to several key trends. The increasing adoption of technologically advanced mobile devices has led to a growth in location-based services, enabling businesses to reach customers more effectively. Big data and location-based analytics are also driving market growth, providing valuable insights for targeted marketing campaigns. However, privacy and security concerns surrounding the use of sensitive customer data pose a challenge for market players. As the market continues to evolve, companies must prioritize data protection and transparency to build trust with consumers. Overall, the market is poised for continued expansion as businesses seek to leverage location data to enhance customer engagement and drive growth.

What will be the Size of the Geomarketing Software Market During the Forecast Period?

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The market is experiencing significant growth due to the increasing use of mobile devices and social networks. This trend is driving the adoption of location-based technology for regional, local, and micro-local geomarketing and nano marketing efforts. Digital marketing strategies are increasingly focusing on investment optimization for business success among local and internet customers, particularly among smartphone users. Additionally, the software enables campaign scheduling and personalization, enhancing the overall effectiveness of marketing efforts. Location-based technology plays a crucial role in this market condition, enabling sales increases through targeted marketing to mobile and social media users.

How is this Geomarketing Software Industry segmented and which is the largest segment?

The geomarketing software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Location

  Outdoor
  Indoor


Deployment

  Cloud-based
  On-premises


Geography

  North America

    US


  APAC

    China
    Japan


  Europe

    Germany
    UK


  Middle East and Africa



  South America

By Location Insights

The outdoor segment is estimated to witness significant growth during the forecast period.

Geomarketing software is a valuable tool for businesses seeking to understand and engage with their customers more effectively. This technology leverages mobile devices, social networks, and location-based technology to deliver targeted marketing campaigns to local, mobile, and internet customers. In the retail sector, software enables businesses to analyze customer behavior and shopping patterns through regional, local, and micro-local geomarketing. Nano marketing and investment optimization are additional benefits, allowing businesses to reach their target audience with personalized offers and relevant content. Geomarketing software also facilitates local search positioning, campaign scheduling, and data visualization, providing businesses with a competitive advantage In the digital marketing landscape.

By utilizing demographic and economic data, businesses can optimize their strategies for success, reaching smartphone users and social media users with targeted campaigns. Key features include personalized maps, heat maps, and satellite maps, enabling businesses to better understand foot traffic and catchment areas. Geomarketing software is an essential component of a comprehensive business strategy, helping to increase sales and improve customer engagement.

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The Outdoor segment was valued at USD 3.63 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 39% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The North American market is poised for steady expansion, driven by the widespread adoption of advanced technologies in sectors such as telecommunications, retail, healthcare, and media and entertainment In the US and Canada. The region's significant presence of location software providers is fueling the demand for customer management and engagement solutions, leading to increased adoption of software. In the US, marketers leverage mobile ads, display ads, and search ads to target local, internet, and mobile customers effectively. Features such as data visualization, map features, and campaign scheduling offer comp

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

ArcGIS is a system that provides an integrated collection of GIS software products that provides a standards-based platform for spatial analysis, data management, and mapping. ArcGIS mapping tools are used so that WebEOC can make and share maps during emergency response. WebEOC sends the geological characteristics of the area such as the address, latitude and longitude information for mapping development. This a llows users to have access to real-time information simultaneously without having to purchase the product.

It is a collection of selected human-focused cellular pathways implicated in cancer that are linked to visualization and analysis tools. Biologists can browse and search the Cancer Cell Map pathways and view gene expression data on any pathway. All data is freely available. Computational biologists can download all pathways in BioPAX format for global analysis. Software developers can build software on top of the Cancer Cell Map using the web service API. Download and install the cPath pathway database software to create a local mirror of the Cancer Cell Map. Cancer Cell Map pathways were selected based on the scientific interests of research labs at Memorial Sloan-Kettering Cancer Center. Effort was made not to duplicate information in other public pathway databases. Available pathways include: Alpha6Beta4Integrin, AndrogenReceptor, EGFR1, Hedgehog, ID, KitReceptor, NOTCH, TGFBR, TNF alpha/NF-kB, Wnt. Each pathway has around 100-400 interactions.

Wafer Map Analytics Software Market Outlook

According to our latest research, the Global Wafer Map Analytics Software market size was valued at $1.2 billion in 2024 and is projected to reach $3.6 billion by 2033, expanding at a CAGR of 13.2% during the forecast period of 2025–2033. The accelerating adoption of advanced analytics in semiconductor manufacturing, driven by the need for higher yield, defect reduction, and process optimization, is a primary factor fueling the robust growth of the wafer map analytics software market globally. As the semiconductor industry faces increasing complexity and miniaturization, manufacturers are turning to sophisticated software solutions to analyze wafer maps, enabling real-time defect detection, process control, and yield improvement. This trend is further amplified by the ongoing digital transformation and automation across the electronics and semiconductor sectors, positioning wafer map analytics software as a critical enabler of competitive advantage and operational excellence.

Regional Outlook

North America currently holds the largest share of the global wafer map analytics software market, commanding over 35% of the total market value in 2024. This dominance is attributed to the mature semiconductor manufacturing ecosystem, strong presence of leading foundries and integrated device manufacturers, and a high level of technology adoption across the United States and Canada. The region benefits from well-established R&D infrastructure, favorable government policies supporting semiconductor innovation, and a robust network of technology providers and end-users. Furthermore, North American companies are at the forefront of integrating artificial intelligence and machine learning into wafer analytics platforms, enhancing defect detection and process optimization capabilities. The ongoing investments in next-generation semiconductor fabs and the push for domestic chip production, particularly in response to global supply chain disruptions, are expected to sustain North America’s leadership in the wafer map analytics software market throughout the forecast period.

Asia Pacific is projected to be the fastest-growing region in the wafer map analytics software market, with a remarkable CAGR of 16.5% from 2025 to 2033. This rapid expansion is fueled by the region’s status as the global epicenter of semiconductor manufacturing, with countries like China, Taiwan, South Korea, and Japan hosting leading foundries and integrated device manufacturers. Substantial investments in manufacturing capacity, government-backed initiatives to boost domestic semiconductor industries, and the proliferation of advanced packaging and process technologies are driving the demand for sophisticated wafer map analytics solutions. Asia Pacific’s growth is also supported by the increasing adoption of automation and Industry 4.0 practices among semiconductor players, as well as a growing pool of skilled analytics and data science professionals. As regional players strive to enhance yield, reduce defects, and maintain competitiveness in the global market, the adoption of wafer map analytics software is set to surge.

Emerging economies in Latin America and the Middle East & Africa are gradually entering the wafer map analytics software market, albeit from a lower base. These regions face unique challenges, including limited local semiconductor manufacturing infrastructure, skill gaps, and restricted access to advanced analytics technologies. However, localized demand is rising due to increased investments in electronics manufacturing, government-led technology parks, and incentives for foreign direct investment. Policy reforms aimed at fostering digital transformation and industrial automation are slowly creating a conducive environment for the adoption of wafer map analytics software. While growth rates may lag behind more mature markets, the gradual build-up of semiconductor capabilities and the integration of analytics-driven process control are expected to open new opportunities for software vendors and service providers in these regions over the coming decade.

Report Scope

Mapping incident locations from a CSV file in a web map (YouTube video).View this short demonstration video to learn how to geocode incident locations from a spreadsheet in ArcGIS Online. In this demonstration, the presenter drags a simple .csv file into a browser-based Web Map and maps the appropriate address fields to display incident points allowing different types of spatial overlays and analysis. _Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

Underground Cable Mapping Software Market Outlook

According to our latest research, the global Underground Cable Mapping Software market size reached USD 1.12 billion in 2024, and is projected to grow at a CAGR of 12.7% from 2025 to 2033, reaching an estimated USD 3.33 billion by 2033. The market’s robust expansion is primarily attributed to the increasing need for accurate subsurface utility mapping, driven by rapid urbanization, infrastructure modernization, and the growing complexity of underground utility networks worldwide. As per our comprehensive analysis, the adoption of advanced mapping technologies and the integration of AI and geospatial analytics are further accelerating the demand for sophisticated underground cable mapping solutions across various industries.

One of the most significant growth factors for the Underground Cable Mapping Software market is the global surge in construction and infrastructure development projects. Urban areas are expanding at an unprecedented rate, placing immense pressure on existing utility networks and demanding more precise and reliable mapping solutions. Governments and private developers are increasingly mandating the use of advanced mapping software to minimize risks associated with accidental utility strikes, which can lead to costly delays, safety hazards, and service interruptions. Furthermore, the push towards smart cities and digitally enabled infrastructure is fueling investments in mapping software that can seamlessly integrate with other digital platforms, enabling real-time data sharing and enhanced project coordination. These dynamics are propelling the market forward, as stakeholders recognize the value of minimizing operational risks and maximizing efficiency through accurate underground asset visualization.

Technological advancements play a pivotal role in shaping the future of the Underground Cable Mapping Software market. The integration of artificial intelligence, machine learning, and advanced geospatial analytics has revolutionized the ability to detect, map, and manage underground utilities with unparalleled accuracy. Modern mapping software now offers features such as 3D visualization, real-time data integration, and predictive maintenance capabilities, empowering utilities and construction firms to make data-driven decisions. Additionally, the growing adoption of cloud-based deployment models is enhancing collaboration among project teams, enabling remote access to mapping data, and reducing IT infrastructure costs. These innovations are not only improving the safety and reliability of underground utility management but are also opening new avenues for market growth, particularly as industries seek to leverage digital transformation for competitive advantage.

Another key growth driver is the increasing regulatory emphasis on safety and compliance in utility management. Regulatory bodies across the globe are implementing stringent guidelines to ensure the accurate documentation and mapping of underground assets. Non-compliance can result in severe penalties, legal liabilities, and reputational damage, prompting organizations to invest in robust mapping software that ensures regulatory adherence. Moreover, the rising incidence of utility strikes and the associated economic losses are compelling stakeholders to prioritize preventive measures, further boosting the adoption of advanced mapping solutions. The integration of mapping software with asset management and maintenance systems is enabling organizations to streamline operations, reduce downtime, and enhance service reliability, thereby supporting long-term market growth.

From a regional perspective, North America currently dominates the Underground Cable Mapping Software market, owing to its mature utility infrastructure, high adoption of digital technologies, and stringent regulatory frameworks. Europe follows closely, driven by extensive infrastructure modernization initiatives and increasing investments in smart city projects. The Asia Pacific region is emerging as a high-growth market, propelled by rapid urbanization, large-scale infrastructure projects, and rising awareness of the benefits of underground cable mapping. Latin America and the Middle East & Africa are also witnessing steady growth, supported by government-led infrastructure development and the gradual digitalization of utility networks. Each region presents unique opportunities and challenges, with local regulations, technological maturity, and market dynamics influencing the pace a

At Forestreet we want to democratise market and innovation discovery. Built and guided by industry experts over the last five years, our AI-powered market intelligence and vendor discovery software uses advanced analytics, NLP and machine learning to map, categorise and analyse any market in fine detail. The current expensive, time-consuming and biased research model has remained static for decades. We think things need shaking up.

Our market discovery and analytics platform is the only tool on the market that can make sense of noise and deliver data-led insights to support your business. Leveraging the latest in AI and automation, Forestreet can provide structured, real-time information to support your process.

Comprehensive market mapping in minutes

From a seed company or key words, users can fully map out highly complex markets in a matter of minutes. No more biased presentations, outdated listings or incomplete datasets. Gone are the days of waiting months for a generic analyst report. With all companies identified live through our internet scraping mechanics, our agile software is as dynamic as the industries you monitor and perfectly catered to your needs. So you can make confident decisions, knowing you’re acting on the most up to date research.

With our SaaS software, you can find companies you didn't know you were competing with and understand their services right down to a features level. Avoid that moment in meetings when a client says, "but what about company X?" Our Forestreet dashboard can have you responding in seconds with fact-based details showing how your product’s features compare to any competitor’s offerings.

Dive deep with our in-depth analysis tools

Beyond its extensive mapping and categorisation capabilities, the Forestreet platform has detailed enrichment options allowing you to deep dive into an individual company’s characteristics and performance. This includes data about size, funding and location, as well as public perceptions and interaction. Our company Momentum scores also combine a range of signals to give an insight into a company’s potential for growth and current market interest.

Other available tools include the Feature Architecture, which shows all the features offered by the whole market, and our Phrase Explorer, which allows you to search companies based on the specific language they use to describe themselves.

Stay at the forefront with up to date news and sentiment analysis

Make sure you know what’s been talked about in your market right now with our news and insights feature. Our AI crawls popular and hard-to-find news sites, providing you with unique comments and feedback about what's going on anywhere in the world. These news sources go well beyond what can be found on Google News, or even paid services like Factiva, so you’ll never get out of touch with the latest trends and developments.

And no need to worry about old data or your key findings getting out of date. In today’s world, we know that markets are constantly shifting and are changing faster and more unpredictably than ever before. But with the ability to refresh and update data on demand, you can embrace smart decision making at pace.

Our platform enables you to understand your market segment with the granularity required for highly informed sourcing, competitor analysis, investment and procurement decisions or de-risk regulation. Insightful data generated by you for any market or geography. All at your fingertips.

Kuwait's arid desert landscape, geological formations, and extreme climate conditions make it a potential site for establishing a terrestrial Mars analog, as this research presents a new GIS-based methodology. The Analog Conjunctive Method (ACM) was specifically developed to identify a suitable location in Kuwait to hold a terrestrial Mars analog using a geographic information system (GIS) and remote sensing techniques. Analogs play a crucial role in simulating different Martian conditions, supporting astronaut training, testing various exploration technologies, and doing different types of scientific research on these environments. The ACM method integrates GIS and remote sensing techniques to evaluate the study area, resulting in potential sites for analog. The analysis employs two stages to finalize the best location. In stage one, the newly developed ACM is applied; it systematically eliminates unstable areas while allowing minimal flexibility for real-world environmental adjustment, particularly in regions with natural wind barriers. ACM is used to process the buffers created for the seven criteria (urban areas and farms, coastal areas, streets, airports, oil fields, natural reserves, and country borders) in QGIS to exclude unsuitable areas. Stage two screens the stage one map locations using different data (STRM, Copernicus sentinel-2, and field visits) to polish the selection based on other criteria (water bodies, dust rate, vegetation cover, and topography). The result shows nine locations in Jal Al-Zor as potential analog sites where a random location is selected for a 3D model creation to visualize the analog. Java Mission-planning and Analysis for Remote Sensing (JMARS) software was used to identify similarities between specific areas, such as the Jal Al-Zor escarpment and Huwaimllyah sand dunes in the Kuwait desert, and comparable terrains on Mars. The research concluded that Jal Al-Zor holds substantial potential as a terrestrial Mars analog site due to its geological and topographical similarities to Martian landscapes. This makes it an ideal location for crew training, Mars equipment testing, and further research in Mars analog studies, providing valuable insights for future planetary exploration.

These data were created for planimetric display and tax area analysis.Procedures_Used:The principal method of data entry used coordinate geometry software.Digitizing from paper maps and use of digital planimetric data were supplemental. Conversions, filling of gaps, georeferencing, reconciliations, and reformatting were often necessary to create a coherent database. Boundary updates are occasionally accepted from local GIS departments when the USTC has not received all relevant boundary change information through required channels. Updates have been made in this manner to Sandy, some Cache, Washington, Utah, Wasatch, and Carbon County cities.Revisions: Municipal boundaries are revised as documents are filed with the Lt. Governor's Office.Reviews_Applied_to_Data:Digital sources were visually compared with planimetric data. Digitized data were overlaid with source material and visually compared. Technical errors were also identified and corrected with ArcGIS Software.Notes: This metadata document contains a composite of information for alltiles in the library.Current thru April 29, 2015

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990-1999 and 2000-2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990-1999 and 2000-2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000-2009 than during 1990-1999; and that inland water levels were generally lower during 2000-2009 than during 1990-1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990-1999. Mean October water levels during 2000-2009 were generally higher than during 1990-1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

This preliminary version is based on all available satellite data until August 2025 (*_2025_08). The map will be updated when more data are available.

The dataset contains a map of the main classes of agricultural land use (dominant crop types and other land use types) in Germany for the year 2025. It complements a series of maps that are produced annually at the Thünen Institute beginning with the year 2017 on the basis of satellite data. The maps cover the entire open landscape, i.e., the agriculturally used area (UAA) and e.g., uncultivated areas.

Data and methods used to create map versions v301/2 differ from those used in previous versions. The v301/2 maps were derived from a time series of Sentinel-2 and Landsat 8/9 images. Map production is based on the methods described in Pham et al. (2024).

All optical satellite data were managed, pre-processed and structured in an analysis-ready data (ARD) cube using the open-source software FORCE - Framework for Operational Radiometric Correction for Environmental monitoring (Frantz, D., 2019), in which SAR and environmental data were integrated.

The map extent covers all areas in Germany that are defined as agricultural land, grassland, small woody features, heathland, peatland or unvegetated areas according to ATKIS Basis-DLM (Geobasisdaten: © GeoBasis-DE / BKG, 2020).

Version v301:
Post-processing of the maps included a sieve filter as well as a ruleset for the reduction of non-plausible areas using the Basis-DLM and the digital terrain model of Germany (Geobasisdaten: © GeoBasis-DE / BKG, 2015).

Version v302:
Additional post-processing was performed to detect and mask additional non-plausible areas that were not adequately covered by the first post-processing (e.g., areas with sparse vegetation, montane forests) based on the „Ökosystematlas Deutschland“ (© Statistisches Bundesamt, Deutschland, 2024). As a consequence, the current version includes a new class “Small woody features on other land”. Furthermore, the class "permanent grassland" was refinded. Each pixel that was classified as "cultivated grassland" in at least five years (between 2017 and 2022) was translated to "permanent grassland" in the annual maps.

Validation:
The final maps were validated using all pixels of the publicly available IACS parcels from the federal states of Brandenburg, Lower Saxony, and North Rhine-Westphalia that were not used for model training. Classes that are underrepresented in these federal states could therefore not be adequately evaluated (e.g., hops and grapevines). We provide this dataset "as is" without any warranty regarding the accuracy or completeness and exclude all liability.

The maps are available as cloud optimized GeoTiffs, which makes downloading the full dataset optional. All data can directly be accessed in QGIS, R, Python or any supported software of your choice using the URL that will be provided on request. By doing so the entire map area or only the regions of interest can be accessed. QGIS legend files for data visualization can be downloaded separately.

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References:

Pham, V.-D., Tetteh, G., Thiel, F., Erasmi, S., Schwieder, M., Frantz, D., & van der Linden, S. (2024). Temporally transferable crop mapping with temporal encoding and deep learning augmentations. International Journal of Applied Earth Observation and Geoinformation, 129, 103867.

BKG, Bundesamt für Kartographie und Geodäsie (2015). Digitales Geländemodell Gitterweite 10 m. DGM10. https://sg.geodatenzentrum.de/web_public/gdz/dokumentation/deu/dgm10.pdf (last accessed: 28. April 2022).

BKG, Bundesamt für Kartographie und Geodäsie (2020). Digitales Basis-Landschaftsmodell.
https://sg.geodatenzentrum.de/web_public/gdz/dokumentation/deu/basis-dlm.pdf (last accessed: 28. April 2022).

Frantz, D. (2019). FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sensing, 11, 1124.

Statistisches Bundesamt, Deutschland (2024). Ökosystematlas Deutschland
https://oekosystematlas-ugr.destatis.de/ (last accessed: 08.02.2024).

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National-scale crop type maps for Germany from combined time series of Sentinel-2 and Landsat data (2025) © 2025 by Tetteh, Gideon Okpoti; Schwieder, Marcel; Blickensdörfer, Lukas; Gocht, Alexander; Erasmi, Stefan; licensed under CC BY 4.0.

Funding was provided by the German Federal Ministry of Food and Agriculture as part of the joint project “Monitoring der biologischen Vielfalt in Agrarlandschaften” (MonViA, Monitoring of biodiversity in agricultural landscapes).