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).

This is a link to the QGIS website where you can download open-source GIS software for viewing, analyzing and manipulating geodata like our downloadable shapefiles.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Coal Oil Point map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore Coal Oil Point map area data layers. Data layers are symbolized as shown on the associated map sheets.

The global network mapping software market size was valued at USD 2,325.4 million in 2025 and is projected to grow at a CAGR of 12.3% during the forecast period (2025-2033). The rapid growth of cloud-based, on-premises, and hybrid IT environments, coupled with the increasing adoption of network management best practices, are some of the key factors driving market growth. Furthermore, the need to enhance network visibility and control, improve performance, and simplify network troubleshooting is also contributing to the growing demand for network mapping software. Cloud-based and on-premises solutions held a significant market share in 2025. However, the cloud-based segment is expected to witness faster growth during the forecast period. The growing adoption of cloud-based services, the need for remote network management, and the cost-effectiveness of cloud-based solutions are driving the growth of this segment. In terms of application, the small and medium enterprises (SMEs) segment dominated the market in 2025, and it is expected to maintain its dominance throughout the forecast period. The increasing number of SMEs, the need for cost-effective network management solutions, and the growing awareness of network security are driving the growth of this segment. Network mapping software is a tool that helps businesses visualize and manage their networks. It can be used to create diagrams of the network, identify potential problems, and track down performance issues. The software can also be used to automate tasks such as device discovery and configuration.

NM Environment Department Surface Water Quality Bureau GIS Web Mapping Tool

Discover the booming interactive map creation tools market! Our in-depth analysis reveals a $2 billion market in 2025, projected to grow at 15% CAGR through 2033. Learn about key trends, leading companies (Mapbox, ArcGIS, Google), and regional insights to capitalize on this expanding sector.

Business location data for Maptitude mapping software are from Caliper Corporation and contain point locations for businesses.

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 Digital Geomorphic-GIS Map of the Pea Island (1:24,000 scale 2007 mapping), North Carolina 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 (peai_geomorphology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (peai_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 (peai_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). 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 (caha_fora_wrbr_geomorphology.pdf), 2.) the GRI ancillary map information document (.pdf) file (caha_fora_wrbr_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 (peai_geomorphology_metadata_faq.pdf). Please read the caha_fora_wrbr_geomorphology.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. 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: North Carolina 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 (peai_geomorphology_metadata.txt or peai_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 1:24,000 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 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).

ZIP Code business counts data for Maptitude mapping software are from Caliper Corporation and contain aggregated ZIP Code Business Patterns (ZBP) data and Rural-Urban Commuting Area (RUCA) data.

The Network Mapping Tool market is experiencing robust growth, driven by the increasing complexity of IT infrastructures and the rising demand for enhanced network visibility and security. The market, estimated at $5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This growth is fueled by several key factors, including the widespread adoption of cloud computing, the rise of hybrid and multi-cloud environments, and the increasing prevalence of cyber threats. Businesses are increasingly relying on network mapping tools to optimize network performance, proactively identify and resolve issues, and ensure compliance with regulatory requirements. The need for real-time network monitoring and automated incident response further contributes to market expansion. The competitive landscape is characterized by a mix of established players like SolarWinds, Cisco, and Tufin, along with emerging innovative companies like 10-Strike and ManageEngine. These vendors offer a diverse range of solutions catering to different enterprise needs and budget considerations. Future growth will be influenced by the ongoing development of AI-powered analytics within network mapping tools, enabling predictive maintenance and automated remediation. Furthermore, the integration of network mapping with other security and IT management platforms will play a crucial role in shaping market evolution. The market's segmentation based on deployment type (cloud, on-premise), organization size, and industry vertical offers substantial opportunities for specialized vendors to cater to specific niche requirements. Geographic expansion, particularly in developing economies, will also contribute to overall market growth throughout the forecast period.

The global application dependency mapping tool market size was valued at over USD 878.4 million in 2025 and is expected to expand at a CAGR of around 21.4%, surpassing USD 6.11 billion revenue by 2035, attributed to the rising requirement for dependency visibility for security posture in the application dependency mapping tool market.

Address point data for use with GIS mapping software, databases, and web applications are from Caliper Corporation and contain a point layer of over 48 million addresses in 22 states and the District of Columbia.

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).

Mind Mapping Software Market Outlook

According to our latest research, the global mind mapping software market size reached USD 2.13 billion in 2024 and is anticipated to grow at a CAGR of 13.5% from 2025 to 2033. By the end of 2033, the market is forecasted to achieve a value of USD 6.61 billion. The primary growth driver for this market is the increasing adoption of digital collaboration tools and visual thinking platforms in both corporate and academic environments, as organizations and institutions seek more efficient ways to foster creativity, streamline project management, and enhance productivity.

One of the most significant growth factors propelling the mind mapping software market is the rising emphasis on collaborative and remote work environments. As businesses continue to embrace flexible work models, there is a growing demand for digital tools that facilitate seamless communication, brainstorming, and project tracking among geographically dispersed teams. Mind mapping software addresses these needs by providing intuitive interfaces for visualizing ideas, managing tasks, and sharing information in real-time. The shift towards digital transformation across industries has further amplified the necessity for such platforms, as organizations seek to replace traditional whiteboards and paper-based methods with interactive, cloud-based solutions that can be accessed anytime, anywhere.

Another key driver is the increasing integration of artificial intelligence and machine learning capabilities into mind mapping software. Modern solutions now offer advanced features such as automated idea generation, sentiment analysis, and intelligent suggestions, which significantly enhance the user experience and productivity. These innovations are particularly valuable in sectors like education, where instructors and students benefit from dynamic visualization tools that adapt to individual learning styles. Additionally, the growing popularity of mind mapping in personal productivity and self-management applications has broadened the market’s appeal, attracting individual users who seek to organize their thoughts, set goals, and track progress in a visually engaging manner.

The proliferation of mobile devices and web-based platforms has also contributed to the expanding adoption of mind mapping software. With the increasing penetration of smartphones and tablets, users now expect seamless cross-platform compatibility and synchronization of their mind maps across devices. Vendors are responding by developing applications that support multiple operating systems, including Windows, macOS, Android, iOS, and web browsers. This trend not only enhances user convenience but also enables organizations to standardize their workflows and ensure consistency in project management and knowledge sharing. The integration of mind mapping tools with other business applications, such as project management suites, CRM systems, and cloud storage services, further augments their utility and drives market growth.

From a regional perspective, North America currently dominates the mind mapping software market, accounting for the largest revenue share in 2024, followed closely by Europe and Asia Pacific. The strong presence of leading technology companies, coupled with high digital literacy rates and early adoption of innovative software solutions, has fueled market growth in these regions. Meanwhile, the Asia Pacific region is witnessing the fastest growth, driven by increasing investments in digital infrastructure, expanding educational initiatives, and the rapid proliferation of SMEs. As organizations worldwide continue to prioritize digital collaboration, the mind mapping software market is poised for robust expansion across all major regions.

Component Analysis

The mind mapping software market is segmented by component into software and services, each playing a pivotal role in shaping the industry landscape. The software segment, which includes standalone applications and integrated platforms, dominates the market due to its direct role in enabling users

This map displays drought, climate and public health-related data for the United States. The map was created by the National Integrated Drought Information System (NIDIS) and is a component of the NIDIS Public Health Sector web mapping application, a tool for exploring the relationship between drought, climate and agriculture in the United States.Data Sources for each layer are identified in the Layer section below as well as in the Layer and Legend sections of the web map. Additional information about the impact of drought on public health can be found on the NIDIS Public Health Sector page.

Healthcare Data for use with GIS mapping software, databases, and web applications are from Caliper Corporation and contain point geographic files of healthcare organizations, providers, and hospitals and an boundary file of Primary Care Service Areas.

This software contains the v1.0.0 release of Nilas: the south ocean mapping platform (https://nilas.org). This mapping tool (beta) has been developed by the Australian Antarctic Division for the Antarctic sea-ice zone to support their research and operational activities. Nilas displays multiple layers of physical and biogeochemical variables. These variables are primarily derived from remotely sensed products and updated as source data become available. The source code is well documented with both readme files and inline comments. This application is written primarily in javascript and was developed using Node.js, vite and a small amount of vue. The Nilas platform was based on the Leaflet open source library. It can be configured to display other Antarctic related geospatial products including raster and vector data.

See the related record, "AAS_4506_NILAS_DATA" for data from this project.

According to Cognitive Market Research, the global Mind Mapping Tool market size was USD 5124.5 million in 2024. It will expand at a compound annual growth rate (CAGR) of 8.80% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 2049.80 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.0% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 1537.35 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 1178.64 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.8% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 256.23 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.2% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 102.49 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.5% from 2024 to 2031.
The Cloud-based category is the fastest growing segment of the Mind Mapping Tool industry

Market Dynamics of Mind Mapping Tool Market

Key Drivers for Mind Mapping Tool Market

Increasing Adoption of Digital Tools for Enhanced Productivity and Organization to Boost Market Growth

The increasing adoption of digital tools for enhanced productivity and organization has been a major driver in many industries, especially in the context of digital transformation. Digital tools enable businesses and individuals to automate repetitive tasks, streamline workflows, and manage time more effectively, significantly enhancing overall productivity. Although many digital tools offer long-term savings, the initial investment in licenses, training, and setup can be a barrier, especially for small businesses or individuals with limited resources. While the adoption of digital tools offers significant benefits, such as enhanced productivity, cost savings, and improved collaboration, businesses must carefully manage the associated challenges, including high costs, security concerns, and integration complexities. Addressing these restraints while leveraging the key drivers will be essential for organizations looking to integrate digital tools into their operations successfully.

Rising demand for visual representation to improve brainstorming and creativity

The rising demand for visual representation to improve brainstorming and creativity is driven by several key factors. Visual tools enhance information retention and idea generation, making complex concepts easier to understand. The growing adoption of digital collaboration platforms fuels this demand as remote teams seek efficient ways to share ideas. Additionally, the increased focus on innovation and creative problem-solving in businesses accelerates the use of visual aids like mind maps, flowcharts, and interactive diagrams. This trend is further supported by advancements in software tools that allow real-time visualization, fostering greater collaboration, faster decision-making, and enhanced creativity.

Restraint Factor for the Mind Mapping Tool Market

Expensive software integration limits widespread adoption in businesses

The high cost of software integration is a major restraint limiting widespread adoption among businesses. The initial expenses, including licensing, implementation, and ongoing maintenance, can be prohibitive, especially for small to medium-sized enterprises (SMEs). Additionally, the need for specialized personnel and training further adds to the financial burden. Businesses may delay or avoid adoption to allocate resources elsewhere, affecting their ability to remain competitive. The complexity and time required to integrate new software into existing systems can also deter companies, as it may disrupt operations and incur additional costs, limiting scalability and overall ROI.

Impact of Covid-19 on the Mind Mapping Tool Market

The COVID-19 pandemic significantly accelerated the adoption of mind-mapping tools. Remote work and online learning necessitated efficient tools for brainstorming, note-taking, and project management. Mind mapping tools offer a visual and intuitive way to organize information, collaborate remotely, and enhance productivity. This surge in demand drove market ...

RTB Maps is a cloud-based electronic Atlas. We used ArGIS 10 for Desktop with Spatial Analysis Extension, ArcGIS 10 for Server on-premise, ArcGIS API for Javascript, IIS web services based on .NET, and ArcGIS Online combining data on the cloud with data and applications on our local server to develop an Atlas that brings together many of the map themes related to development of roots, tubers and banana crops. The Atlas is structured to allow our participating scientists to understand the distribution of the crops and observe the spatial distribution of many of the obstacles to production of these crops. The Atlas also includes an application to allow our partners to evaluate the importance of different factors when setting priorities for research and development. The application uses weighted overlay analysis within a multi-criteria decision analysis framework to rate the importance of factors when establishing geographic priorities for research and development.Datasets of crop distribution maps, agroecology maps, biotic and abiotic constraints to crop production, poverty maps and other demographic indicators are used as a key inputs to multi-objective criteria analysis.Further metadata/references can be found here: http://gisweb.ciat.cgiar.org/RTBmaps/DataAvailability_RTBMaps.htmlDISCLAIMER, ACKNOWLEDGMENTS AND PERMISSIONS:This service is provided by Roots, Tubers and Bananas CGIAR Research Program as a public service. Use of this service to retrieve information constitutes your awareness and agreement to the following conditions of use.This online resource displays GIS data and query tools subject to continuous updates and adjustments. The GIS data has been taken from various, mostly public, sources and is supplied in good faith.RTBMaps GIS Data Disclaimer• The data used to show the Base Maps is supplied by ESRI.• The data used to show the photos over the map is supplied by Flickr.• The data used to show the videos over the map is supplied by Youtube.• The population map is supplied to us by CIESIN, Columbia University and CIAT.• The Accessibility map is provided by Global Environment Monitoring Unit - Joint Research Centre of the European Commission. Accessibility maps are made for a specific purpose and they cannot be used as a generic dataset to represent "the accessibility" for a given study area.• Harvested area and yield for banana, cassava, potato, sweet potato and yam for the year 200, is provided by EarthSat (University of Minnesota’s Institute on the Environment-Global Landscapes initiative and McGill University’s Land Use and the Global Environment lab). Dataset from Monfreda C., Ramankutty N., and Foley J.A. 2008.• Agroecology dataset: global edapho-climatic zones for cassava based on mean growing season, temperature, number of dry season months, daily temperature range and seasonality. Dataset from CIAT (Carter et al. 1992)• Demography indicators: Total and Rural Population from Center for International Earth Science Information Network (CIESIN) and CIAT 2004.• The FGGD prevalence of stunting map is a global raster datalayer with a resolution of 5 arc-minutes. The percentage of stunted children under five years old is reported according to the lowest available sub-national administrative units: all pixels within the unit boundaries will have the same value. Data have been compiled by FAO from different sources: Demographic and Health Surveys (DHS), UNICEF MICS, WHO Global Database on Child Growth and Malnutrition, and national surveys. Data provided by FAO – GIS Unit 2007.• Poverty dataset: Global poverty headcount and absolute number of poor. Number of people living on less than $1.25 or $2.00 per day. Dataset from IFPRI and CIATTHE RTBMAPS GROUP MAKES NO WARRANTIES OR GUARANTEES, EITHER EXPRESSED OR IMPLIED AS TO THE COMPLETENESS, ACCURACY, OR CORRECTNESS OF THE DATA PORTRAYED IN THIS PRODUCT NOR ACCEPTS ANY LIABILITY, ARISING FROM ANY INCORRECT, INCOMPLETE OR MISLEADING INFORMATION CONTAINED THEREIN. ALL INFORMATION, DATA AND DATABASES ARE PROVIDED "AS IS" WITH NO WARRANTY, EXPRESSED OR IMPLIED, INCLUDING BUT NOT LIMITED TO, FITNESS FOR A PARTICULAR PURPOSE. By accessing this website and/or data contained within the databases, you hereby release the RTB group and CGCenters, its employees, agents, contractors, sponsors and suppliers from any and all responsibility and liability associated with its use. In no event shall the RTB Group or its officers or employees be liable for any damages arising in any way out of the use of the website, or use of the information contained in the databases herein including, but not limited to the RTBMaps online Atlas product.APPLICATION DEVELOPMENT:• Desktop and web development - Ernesto Giron E. (GeoSpatial Consultant) e.giron.e@gmail.com• GIS Analyst - Elizabeth Barona. (Independent Consultant) barona.elizabeth@gmail.comCollaborators:Glenn Hyman, Bernardo Creamer, Jesus David Hoyos, Diana Carolina Giraldo Soroush Parsa, Jagath Shanthalal, Herlin Rodolfo Espinosa, Carlos Navarro, Jorge Cardona and Beatriz Vanessa Herrera at CIAT, Tunrayo Alabi and Joseph Rusike from IITA, Guy Hareau, Reinhard Simon, Henry Juarez, Ulrich Kleinwechter, Greg Forbes, Adam Sparks from CIP, and David Brown and Charles Staver from Bioversity International.Please note these services may be unavailable at times due to maintenance work.Please feel free to contact us with any questions or problems you may be having with RTBMaps.