GIS Mapping Software Market Outlook

The global GIS Mapping Software market size was valued at approximately USD 8.5 billion in 2023 and is projected to reach around USD 17.5 billion by 2032, growing at a CAGR of 8.3% from 2024 to 2032. This robust growth is driven by the increasing adoption of geospatial technologies across various sectors, including urban planning, disaster management, and agriculture.

One of the primary growth factors for the GIS Mapping Software market is the rising need for spatial data analytics. Organizations are increasingly recognizing the value of geographical data in making informed decisions, driving the demand for sophisticated mapping solutions. Furthermore, advancements in satellite imaging technology and the increasing availability of high-resolution imagery are enhancing the capabilities of GIS software, making it a crucial tool for various applications.

Another significant driver is the integration of GIS with emerging technologies such as artificial intelligence (AI) and the Internet of Things (IoT). These integrations are facilitating real-time data processing and analysis, thereby improving the efficiency and accuracy of GIS applications. For instance, in urban planning and disaster management, real-time data can significantly enhance predictive modeling and response strategies. This synergy between GIS and cutting-edge technologies is expected to fuel market growth further.

The growing emphasis on sustainable development and smart city initiatives globally is also contributing to the market's expansion. Governments and private entities are investing heavily in GIS technologies to optimize resource management, enhance public services, and improve urban infrastructure. These investments are particularly evident in developing regions where urbanization rates are high, and there is a pressing need for efficient spatial planning and management.

In terms of regional outlook, North America holds a significant share of the GIS Mapping Software market, driven by robust technological infrastructure and high adoption rates across various industries. However, Asia Pacific is expected to witness the highest growth rate during the forecast period. This growth is attributed to rapid urbanization, increasing government initiatives for smart cities, and rising investments in infrastructure development.

The Geographic Information Systems Platform has become an integral part of modern spatial data management, offering a comprehensive framework for collecting, analyzing, and visualizing geographic data. This platform facilitates the integration of diverse data sources, enabling users to create detailed maps and spatial models that support decision-making across various sectors. With the increasing complexity of urban environments and the need for efficient resource management, the Geographic Information Systems Platform provides the tools necessary for real-time data processing and analysis. Its versatility and scalability make it an essential component for organizations looking to leverage geospatial data for strategic planning and operational efficiency.

Component Analysis

The GIS Mapping Software market is segmented by component into software and services. The software segment dominates the market, primarily due to the continuous advancements in GIS software capabilities. Modern GIS software offers a range of functionalities, from basic mapping to complex spatial analysis, making it indispensable for various sectors. These software solutions are increasingly user-friendly, allowing even non-experts to leverage geospatial data effectively.

Moreover, the software segment is witnessing significant innovation with the integration of AI and machine learning algorithms. These advancements are enabling more sophisticated data analysis and predictive modeling, which are crucial for applications such as disaster management and urban planning. The adoption of cloud-based GIS software is also on the rise, offering scalability and real-time data processing capabilities, which are essential for dynamic applications like transport management.

The services segment, although smaller than the software segment, is also experiencing growth. This includes consulting, implementation, and maintenance services that are critical for the successful deployment and operation of GIS systems. The increasing complexity of GIS applications nec

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

Point Cloud Mapping Software Market Outlook

The global point cloud mapping software market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 3.8 billion by 2032, growing at a CAGR of 13.5% during the forecast period. This growth is driven by the increasing adoption of 3D imaging technology across various industries, advancements in LiDAR technology, and the need for precise and accurate data for engineering and construction projects.

One of the primary growth factors for the point cloud mapping software market is the surge in demand for 3D imaging technology. Industries such as architecture, construction, and urban planning are increasingly utilizing point cloud mapping software to create detailed and accurate 3D models. This technology significantly enhances the precision of measurements and spatial analysis, thereby reducing the potential for errors in construction and design. As urbanization continues to rise globally, the need for effective mapping and planning solutions is expected to drive the market further.

Additionally, the advancements in LiDAR technology are playing a crucial role in the growth of the point cloud mapping software market. LiDAR systems have become more affordable and accessible, enabling a broader range of applications. These systems are now being used extensively in autonomous vehicles, drones, and environmental monitoring, which in turn boosts the demand for sophisticated point cloud mapping software. The integration of artificial intelligence (AI) and machine learning (ML) with LiDAR systems is further enhancing the capabilities of these software solutions, providing more accurate and efficient data processing.

The need for precise and accurate data in engineering and construction projects is another significant factor contributing to the market growth. Point cloud mapping software allows for the detailed visualization and analysis of complex structures, making it an indispensable tool in these industries. The ability to create 3D models from point cloud data helps engineers and architects to visualize projects in a more comprehensive manner, thus facilitating better decision-making. This drives the adoption of point cloud mapping software in large-scale infrastructure projects, contributing to market expansion.

From a regional perspective, the North American market is expected to dominate the point cloud mapping software market during the forecast period. This can be attributed to the presence of a large number of technology companies, high adoption rates of advanced technologies, and significant investments in infrastructure development. The Asia Pacific region is also anticipated to witness substantial growth, driven by rapid urbanization, the expansion of the automotive industry, and increasing investments in smart city projects.

Component Analysis

The point cloud mapping software market by component is segmented into software and services. The software segment is expected to hold the largest market share throughout the forecast period. This can be attributed to the growing demand for advanced software solutions that offer high precision and accuracy in 3D mapping and modeling. Companies are continuously developing innovative software solutions to meet the evolving needs of various industries, thereby driving the growth of this segment.

In the software segment, various types of point cloud mapping software are available, ranging from basic tools to highly advanced platforms with extensive features. These software solutions are used for a variety of applications, including 3D modeling, spatial analysis, and data visualization. The continuous advancements in software technology, such as the integration of AI and ML, are enhancing the capabilities of point cloud mapping software, making them more efficient and effective in processing large amounts of data.

The services segment is also expected to witness significant growth during the forecast period. This segment includes professional services such as consulting, training, support, and maintenance. As the adoption of point cloud mapping software increases, the demand for these services is also rising. Companies are seeking expert guidance and support to effectively implement and utilize point cloud mapping software, driving the growth of the services segment.

Another key factor contributing to the growth of the services segment is the increasing complexity of point cloud mapping projects. Large-scale projects often require specialized knowledge and expertise

description: This tool provides a no-cost downloadable software tool that allows users to interact with professional quality GIS maps. Users access pre-compiled projects through a free software product called ArcReader, and are able to open and explore HUD-specific project data as well as design and print custom maps. No special software/map skills beyond basic computer skills are required, meaning users can quickly get started working with maps of their communities.; abstract: This tool provides a no-cost downloadable software tool that allows users to interact with professional quality GIS maps. Users access pre-compiled projects through a free software product called ArcReader, and are able to open and explore HUD-specific project data as well as design and print custom maps. No special software/map skills beyond basic computer skills are required, meaning users can quickly get started working with maps of their communities.

3D Drone Mapping Software Market Outlook

The global 3D drone mapping software market size stood at approximately $2.1 billion in 2023, and it is projected to reach $7.4 billion by 2032, exhibiting a robust CAGR of 15.2% during the forecast period. The growth of the market is driven by the increasing adoption of drone technology across various sectors, including agriculture, construction, and environmental monitoring, combined with the advancements in mapping and imaging software capabilities.

One of the primary growth factors for the 3D drone mapping software market is the rapid increase in the utilization of drones for data collection and analysis. Drones equipped with high-resolution cameras and advanced sensors are capable of capturing precise data, which is then processed by 3D mapping software to create accurate and detailed maps. This capability is invaluable in sectors such as agriculture for crop monitoring, construction for site surveys, and environmental monitoring for tracking changes in ecosystems. The continual improvement in drone technology and software algorithms has significantly enhanced the accuracy and efficiency of these applications, thereby driving market growth.

Another key factor contributing to the market's expansion is the growing awareness and implementation of smart city projects worldwide. Urban planning authorities are increasingly leveraging 3D drone mapping software to undertake comprehensive planning, development, and management of urban areas. This software aids in the creation of detailed 3D models of cities, which can be used for infrastructure development, traffic management, and disaster preparedness. The ability to visualize and analyze data in three dimensions allows city planners to make more informed decisions, ultimately leading to more efficient and sustainable urban environments.

The surge in demand for remote and automated data collection solutions is further accelerating the market's growth. Traditional methods of surveying and mapping are often time-consuming, labor-intensive, and costly. In contrast, drones equipped with 3D mapping software can cover large areas quickly and with minimal human intervention, reducing operational costs and increasing productivity. This is particularly beneficial in industries such as mining, where accurate mapping of large and often inaccessible areas is crucial for operational planning and safety.

Regionally, North America is anticipated to hold a significant share of the 3D drone mapping software market, driven by the early adoption of advanced technologies, strong presence of key market players, and substantial investments in research and development. However, the Asia-Pacific region is expected to witness the highest growth rate over the forecast period, fueled by increasing government initiatives to promote the use of drone technology, rapid urbanization, and the burgeoning construction industry. Countries such as China, India, and Japan are leading this growth trajectory, with substantial investments in infrastructure development and smart city projects.

Component Analysis

The 3D drone mapping software market is segmented by component into software and services. The software segment dominates the market, driven by the increasing need for advanced mapping and imaging solutions that offer high precision and efficiency. These software solutions provide a range of functionalities, from basic mapping to advanced analytics and visualization, catering to diverse industry needs. Companies are continually upgrading their software offerings to incorporate new features such as real-time data processing, AI-driven analytics, and enhanced user interfaces, thereby attracting a larger customer base.

The services segment, though smaller, is also experiencing steady growth. This segment includes various services such as installation, training, maintenance, and support, which are essential for the optimal functioning of 3D mapping software. As the adoption of drone technology expands, the demand for these ancillary services is expected to rise, creating new revenue streams for service providers. Moreover, companies offering end-to-end solutions, including both software and services, are likely to gain a competitive edge in the market.

The integration of cloud computing with 3D drone mapping software is another significant trend impacting the software segment. Cloud-based solutions offer several advantages, including scalability, remote access, and reduced IT infrastructure costs. These benefits are particularly appealing to small and medium ente

The Story Map Basic application is a simple map viewer with a minimalist user interface. Apart from the title bar, an optional legend, and a configurable search box the map fills the screen. Use this app to let your map speak for itself. Your users can click features on the map to get more information in pop-ups. The Story Map Basic application puts all the emphasis on your map, so it works best when your map has great cartography and tells a clear story.You can create a Basic story map by sharing a web map as an application from the map viewer. You can also click the 'Create a Web App' button on this page to create a story map with this application. Optionally, the application source code can be downloaded for further customization and hosted on your own web server.For more information about the Story Map Basic application, a step-by-step tutorial, and a gallery of examples, please see this page on the Esri Story Maps website.

TDEC is continuously striving to create better business practices through GIS and one way that we have found to provide information and answer some question is utilizing an interactive map. An interactive map is a display of geospatial data that allows you to manipulate and query the contents to get the information needed using a set of provided tools. Interactive maps are created using GIS software, and then distributed to users, usually over a computer network. The TDEC Land and Water interactive map will allow you to do simple tasks such as pan, zoom, measure and find a lat/long, while also giving you the capability of running simple queries to locate land and waters by name, entity, and number. With the ability to turn off and on back ground images such as aerial imagery (both black and white as well as color), we hope that you can find much utility in the tools provided.

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

The main objective of the mapping tools is to provide a simple and useable platform for Member States and other reporting countries to map their country-specific standard terminology to that used by EFSA and to enable the production of an XML file for the submission of antimicrobial resistance data via the Data Collection Framework (DCF).

The tools can be used to report antimicrobial resistance data within the framework of Directive 2003/99/EC and Decision 2020/1729/EU.

The catalogues and the specific hierarchy of each data model (AMR and ESBL) are already inserted into each of the specific mapping tool. Specific Excel mapping tools corresponding to each of the two data models are available.

Dynamic or manual version of the tool can be chosen for each data models.

Generic Mapping Tool (GMT)

GMT is an open source collection of about 80 command-line tools for manipulating geographic and Cartesian data sets (including filtering, trend fitting, gridding, projecting, etc.) and producing PostScript illustrations ranging from simple x–y plots via contour maps to artificially illuminated surfaces and 3D perspective views; the GMT supplements add another 40 more specialized and discipline-specific tools. GMT supports over 30 map projections and transformations and requires support data such as GSHHG coastlines, rivers, and political boundaries and optionally DCW country polygons. GMT is developed and maintained by Paul Wessel, Walter H. F. Smith, Remko Scharroo, Joaquim Luis and Florian Wobbe, with help from a global set of volunteers, and is supported by the National Science Foundation. It is released under the GNU Lesser General Public License version 3 or any later version.

The Digital Geomorphologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (sahi_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (sahi_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (sahi_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (sahi_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (sahi_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (sahi_geomorphology_metadata_faq.pdf). Please read the sahi_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Rutgers University, Institute of Marine and Coastal Sciences. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (sahi_geomorphology_metadata.txt or sahi_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:6,000 and United States National Map Accuracy Standards features are within (horizontally) 5.1 meters or 16.7 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

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Geographic Information System Software Market Outlook

The global Geographic Information System (GIS) Software market size was valued at approximately USD 7.8 billion in 2023 and is projected to reach USD 15.6 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.3% during the forecast period. This impressive growth can be attributed to the increasing demand for efficient data management tools across various industries, which rely on spatial data for decision-making and strategic planning. The rapid advancements in technology, such as the integration of AI and IoT with GIS software, have further propelled the market, enabling organizations to harness the full potential of geographic data in innovative ways.

One of the primary growth drivers of the GIS Software market is the burgeoning need for urban planning and smart city initiatives worldwide. As urbanization trends escalate, cities are increasingly relying on GIS technology to manage resources more effectively, optimize transportation networks, and enhance public safety. The ability of GIS software to provide real-time data and spatial analysis is vital for city planners and administrators faced with the challenges of modern urban environments. Furthermore, the trend towards digital transformation in governmental organizations is boosting the adoption of GIS solutions, as they seek to improve operational efficiency and service delivery.

The agricultural sector is also experiencing significant transformations due to the integration of GIS software, which is another pivotal growth factor for the market. Precision agriculture, which involves the use of GIS technologies to monitor and manage farming practices, is enabling farmers to increase crop yields while reducing resource consumption. By leveraging spatial data, farmers can make informed decisions about planting, irrigation, and harvesting, ultimately leading to more sustainable agricultural practices. This trend is particularly prominent in regions where agriculture forms a substantial portion of the economy, encouraging the adoption of advanced GIS tools to maintain competitive advantage.

Another influential factor contributing to the growth of the GIS Software market is the increasing importance of environmental management and disaster response. GIS technology plays a crucial role in assessing environmental changes, managing natural resources, and planning responses to natural disasters. The ability to overlay various data sets onto geographic maps allows for better analysis and understanding of environmental phenomena, making GIS indispensable in tackling issues such as climate change and resource depletion. Moreover, governments and organizations are investing heavily in GIS tools that aid in disaster preparedness and response, ensuring timely and effective action during emergencies.

The evolution of GIS Mapping Software has been instrumental in transforming how spatial data is utilized across various sectors. These software solutions offer robust tools for visualizing, analyzing, and interpreting geographic data, enabling users to make informed decisions based on spatial insights. With the ability to integrate multiple data sources, GIS Mapping Software provides a comprehensive platform for conducting spatial analysis, which is crucial for applications ranging from urban planning to environmental management. As technology continues to advance, the capabilities of GIS Mapping Software are expanding, offering more sophisticated features such as 3D visualization and real-time data processing. These advancements are not only enhancing the utility of GIS tools but also making them more accessible to a wider range of users, thereby driving their adoption across different industries.

Regionally, North America and Europe have traditionally dominated the GIS Software market, thanks to their robust technological infrastructure and higher adoption rates of advanced technologies. However, Asia Pacific is expected to witness the highest growth rate during the forecast period, driven by rapid urbanization, increased government spending on infrastructure development, and the expanding telecommunications sector. The growing awareness and adoption of GIS solutions in countries like China and India are significant contributors to this regional growth. Furthermore, Latin America and the Middle East & Africa regions are slowly catching up, with ongoing investments in smart city projects and infrastructure development driving the demand for GIS software.

Component Analysis</h2&

The Digital Geologic-GIS Map of San Miguel Island, California is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (smis_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (smis_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (smis_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) this file (chis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (chis_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (smis_geology_metadata_faq.pdf). Please read the chis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: American Association of Petroleum Geologists. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (smis_geology_metadata.txt or smis_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

The main objective of the mapping tool is to provide a simple and useable platform for MSs to map their country-specific standard terminology to that used by EFSA and to enable the production of an XML file for the submission of sample or aggregated-based zoonoses monitoring data via the DCF.

The catalogues and the specific hierarchy of each data model (AMR, ESBL, PRV, FBO, POP and DST) are already inserted into each of the specific mapping tool. Specific Excel mapping tools correspond to each of the six data models are available.

You can choose between the dynamic or the manual version of the tool.

The main objective of the mapping tools is to provide a simple and useable platform for Member states and other reporting countries to map their country-specific standard terminology to that used by EFSA and to enable the production of an XML file for the submission of sample or aggregated-based zoonoses monitoring data via the Data Collection Framework (DCF).

The catalogues and the specific hierarchy of each data model (PRV, FBO, AP, DS and SSD2 for Echinococcus multilocularis) are already inserted into each of the specific mapping tool. Specific Excel mapping tools corresponding to each of the five data models are available.

Dynamic or manual version of the tool can be chosen for the first four data models.

The Emulti_SSD2_tool can be used to report sample-based results of Echinococcus multilocularis under the Commission Delegated Regulation (EU) 2018/772.

TIGERweb allows the viewing of TIGER spatial data online and for TIGER data to be streamed to your mapping application. The web-based application allows the users to visualize our TIGER(Topologically Integrated Geographic Encoding and Referencing database) data. The application allows users to select features and view their attributes, to search for features by name or geocode, and to identify features by selecting them from a map. The TIGERweb application is a simple way to view our TIGER data without having to download the data. The web Mapping serivices provide a simple HTTP interface for requesting geo-registered map images from our geospatial database. It allows users to produce maps containg TIGERweb layers with layers from other servers.It consists of the following two applications and six services: Applications: TIGERweb TIGERweb2010 Services: Current Geography ACS 2012 ACS 2011 Census 2010 (for the TIGERweb application) Physical Features Census 2010 for the TIGERweb2010 application)

http://www.openstreetmap.org/images/osm_logo.png" alt=""/> OpenStreetMap (openstreetmap.org) is a global collaborative mapping project, which offers maps and map data released with an open license, encouraging free re-use and re-distribution. The data is created by a large community of volunteers who use a variety of simple on-the-ground surveying techniques, and wiki-syle editing tools to collaborate as they create the maps, in a process which is open to everyone. The project originated in London, and an active community of mappers and developers are based here. Mapping work in London is ongoing (and you can help!) but the coverage is already good enough for many uses.

Browse the map of London on OpenStreetMap.org

Downloads:

The whole of England updated daily:

• england.osm.bz2 ~185M - .osm formatted raw XML data (compressed)
• england.shp.zip ~156M - ESRI shapefiles

For more details of downloads available from OpenStreetMap, including downloading the whole planet, see 'planet.osm' on the wiki.

Data access APIs:

Download small areas of the map by bounding-box. For example this URL requests the data around Trafalgar Square:
http://api.openstreetmap.org/api/0.6/map?bbox=-0.13062,51.5065,-0.12557,51.50969

Data filtered by "tag". For example this URL returns all elements in London tagged shop=supermarket:
http://www.informationfreeway.org/api/0.6/*[shop=supermarket][bbox=-0.48,51.30,0.21,51.70]

The .osm format

The format of the data is a raw XML represention of all the elements making up the map. OpenStreetMap is composed of interconnected "nodes" and "ways" (and sometimes "relations") each with a set of name=value pairs called "tags". These classify and describe properties of the elements, and ultimately influence how they get drawn on the map. To understand more about tags, and different ways of working with this data format refer to the following pages on the OpenStreetMap wiki.

• .osm - About the raw XML data format of OpenStreetMap
• Downloading data - More details of the API and extract download options
• Xapi - The extended api for filtering by tag
• Map Features - A list of tags, and what map features they represent
• Converting map data between formats - catalogue of tools for converting from .osm to other formats

Simple embedded maps

Rather than working with raw map data, you may prefer to embed maps from OpenStreetMap on your website with a simple bit of javascript. You can also present overlays of other data, in a manner very similar to working with google maps. In fact you can even use the google maps API to do this. See OSM on your own website for details and links to various javascript map libraries.

Help build the map!

The OpenStreetMap project aims to attract large numbers of contributors who all chip in a little bit to help build the map. Although the map editing tools take a little while to learn, they are designed to be as simple as possible, so that everyone can get involved. This project offers an exciting means of allowing local London communities to take ownership of their part of the map.

Read about how to Get Involved and see the London page for details of OpenStreetMap community events.

The main objective of the mapping tool is to provide a simple and useable platform for MSs to map their country-specific standard terminology to that used by EFSA and to enable the production of an XML file for the submission of sample or aggregated-based zoonoses monitoring data via the DCF.

The catalogues and the specific hierarchy of each data model (AMR, ESBL, PRV, FBO, POP and DST) are already inserted into each of the specific mapping tool. Specific Excel mapping tools correspond to each of the six data models are available.

You can choose between the dynamic or the manual version of the tool.

The main objective of the mapping tools is to provide a simple and useable platform for Member states and other reporting countries to map their country-specific standard terminology to that used by EFSA and to enable the production of an XML file for the submission of sample or aggregated-based zoonoses monitoring data via the Data Collection Framework (DCF).

The catalogues and the specific hierarchy of each data model (AMR, ESBL, PRV, FBO, AP, DS and SSD2 for Echinococcus multilocularis) are already inserted into each of the specific mapping tool. Specific Excel mapping tools corresponding to each of the seven data models are available.

Dynamic or manual version of the tool can be chosen for the first six data models.

The Emulti_SSD2_tool can be used to report sample-based results of Echinococcus multilocularis under the Commission Delegated Regulation (EU) 2018/772.