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.

This site is part of pilot effort at the US Department of Energy (DOE) - Office of NEPA Policy and Compliance to evaluate providing IT web services as a shared service, hosted on the cloud, and using only Free and Open Source Software (FOSS). The site is an integrated component of the larger NEPAnode project but is a stand alone service. The site allows users to upload static map images with no geographic data so that they can be accurately referenced/rectified on an webmap. This site allows for the revitalizing of otherwise unusable/archived maps such as historic maps, site surveys, site plans, etc. turning them into usable geographic data which is subsequently made available as a KML file for use in Google Earth/Maps and as a Web Mapping Service (WMS) for using in web-based webmapping application such as NEPAnode or in desktop GIS software.

The interactive map creation tools market is experiencing robust growth, driven by increasing demand for visually engaging data representation across diverse sectors. The market, estimated at $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $8 billion by 2033. This expansion is fueled by several key factors. The rising adoption of cloud-based solutions and the proliferation of readily available geospatial data are lowering the barrier to entry for both individual and corporate users. Furthermore, advancements in mapping technologies, such as 3D mapping capabilities and improved user interfaces, are enhancing the overall user experience and driving wider adoption. The increasing need for effective data visualization in fields like real estate, urban planning, environmental monitoring, and marketing is further bolstering market growth. Segmentation reveals a significant portion of the market is attributed to paid use licenses, reflecting the advanced features and support provided by premium tools. However, the free-use segment is also growing rapidly, driven by the availability of user-friendly open-source tools and freemium models offered by major players. Corporate users constitute a larger portion of the market compared to individual users, primarily due to their higher budget allocations for data visualization and analysis tools. Geographic distribution reveals a concentration of market share in North America and Europe, largely due to higher technological adoption and a well-established digital infrastructure. However, rapid growth is anticipated in Asia Pacific regions like China and India, driven by increasing urbanization and government initiatives promoting digital transformation. Market restraints include the high cost of advanced mapping software, the need for specialized technical skills for complex projects, and the potential for data security and privacy concerns. Nevertheless, ongoing technological innovation, coupled with the increasing accessibility of data and analytical tools, is anticipated to mitigate these challenges and continue to drive significant market expansion throughout the forecast period. Key players like Mapbox, ArcGIS StoryMaps, and Google are actively shaping the market landscape through continuous product development and strategic partnerships, fostering innovation and competitive pricing strategies.

The global GIS mapping tools market is experiencing robust growth, driven by increasing demand across diverse sectors. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching an estimated market value of approximately $45 billion by 2033. Key drivers include the rising adoption of cloud-based GIS solutions, enhanced data analytics capabilities, the proliferation of location-based services, and the growing need for precise spatial data analysis in various industries like urban planning, geological exploration, and water resource management. The market is segmented by application (Geological Exploration, Water Conservancy Projects, Urban Planning, Others) and type (Cloud-based, Web-based). Cloud-based solutions are gaining significant traction due to their scalability, accessibility, and cost-effectiveness. The increasing availability of high-resolution satellite imagery and advancements in artificial intelligence (AI) and machine learning (ML) are further fueling market expansion. While data security concerns and the high initial investment costs for some advanced solutions present restraints, the overall market outlook remains positive, with significant opportunities for both established players and emerging technology providers. Geographical expansion is another key aspect of market growth. North America and Europe currently hold a significant market share, owing to established GIS infrastructure and early adoption of advanced technologies. However, the Asia-Pacific region is expected to witness rapid growth in the coming years, driven by rising government investments in infrastructure development and increasing urbanization in countries like China and India. Competitive dynamics are shaping the market, with major players like Esri, Autodesk, Hexagon, and Mapbox competing on the basis of software features, data integration capabilities, and customer support. The emergence of open-source GIS solutions like QGIS and GRASS GIS is also challenging the dominance of proprietary software, offering cost-effective alternatives for various applications. The continued development and integration of advanced technologies like 3D mapping, real-time data visualization, and location intelligence will further enhance the capabilities of GIS mapping tools, driving market expansion and innovation across various sectors.

This pdf includes all of the articles that included in the study, "Quality and Success in Open Source Software : A Systematic Mapping".

Global UAV Mapping Software market size 2025 was XX Million. UAV Mapping Software Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.

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).

description: In May 2014, staff at the San Bernardino National Wildlife Refuge (SBNWR) requested the production of a vegetation map to document the ongoing restoration of the refuge. Utilizing object-based image analysis (OBIA) a 9 class vegetation map was produced. This was a piloted effort to develop a simple, repeatable and low-cost land cover mapping framework that could be carried out on other refuges. Thus, iterative steps were taken and refined as part of the mapping process. This document has a Digital Object Identifier: http://dx.doi.org/10.7944/W3WC7M; abstract: In May 2014, staff at the San Bernardino National Wildlife Refuge (SBNWR) requested the production of a vegetation map to document the ongoing restoration of the refuge. Utilizing object-based image analysis (OBIA) a 9 class vegetation map was produced. This was a piloted effort to develop a simple, repeatable and low-cost land cover mapping framework that could be carried out on other refuges. Thus, iterative steps were taken and refined as part of the mapping process. This document has a Digital Object Identifier: http://dx.doi.org/10.7944/W3WC7M

The global drone photogrammetry software market is experiencing robust growth, driven by increasing adoption across diverse sectors. The market size in 2025 is estimated at $800 million, exhibiting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant expansion is fueled by several key factors. The construction industry leverages drone photogrammetry for site surveying, progress monitoring, and volume calculations, improving efficiency and reducing costs. Similarly, agriculture benefits from precise land mapping, crop health assessments, and yield optimization. Public utilities utilize this technology for infrastructure inspections and maintenance planning, minimizing disruptions and enhancing safety. The rising availability of affordable drones and user-friendly software, coupled with the decreasing costs of data storage and processing, further contributes to market growth. Moreover, advancements in Artificial Intelligence (AI) and machine learning are enhancing the accuracy and speed of data processing, making drone photogrammetry increasingly accessible and attractive to a wider range of users. Open-source software solutions are gaining traction, offering cost-effective alternatives to proprietary options, while the closed-source segment benefits from advanced features and dedicated support. Despite this positive outlook, challenges remain. Data security and privacy concerns, particularly in sensitive sectors like defense and surveillance, require careful consideration. The need for skilled professionals to operate the software and interpret the resulting data is another factor hindering broader adoption. However, ongoing advancements in user interfaces and the development of automated processing tools are mitigating these challenges. The market is segmented by software type (open source and closed source) and application (construction, agriculture, public utility, personal, and others), with construction and agriculture currently representing the largest segments. Geographic distribution shows a strong presence in North America and Europe, with Asia-Pacific emerging as a high-growth region due to increasing infrastructure development and technological advancements. The market's future trajectory suggests continued growth driven by technological innovation, increasing affordability, and the expanding applications of drone photogrammetry across various industries.

This is the dataset adopted for the paperZheying Zhang, Outi-Sievi Korte, Ulla-Tarvikki Virta, Hannu-Marri Jarvinen, Davide Taibi. An Investigation on the Availability of Contribution Information in Open-Source Projects. Euromicro/SEAA 2021.

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.

Software tool as an open source knowledge mapping software that increases the visibility of research findings for science and society. Visual interface to the world's scientific knowledge.

The market for UAV mapping software is expected to grow from approximately USD XXX million in 2023 to USD XXX million by 2033, exhibiting a CAGR of XX% during the forecast period 2023-2033. The increasing adoption of UAVs for mapping and surveying applications in various industries such as agriculture, construction, and mining is driving the market growth. Factors such as the rising demand for accurate and timely data for decision-making, the proliferation of cost-effective drones, and the growing popularity of open source mapping software are contributing to the market expansion. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) technologies into UAV mapping software is enhancing data analysis capabilities, further fueling market growth. Key players in the market include Airware, Inc., 3D Robotics, Dreamhammer Inc., Drone Volt, Dronedeploy Inc., ESRI, Pix4D, Precisionhawk Inc., Sensefly Ltd., Skyward Io, and others.

This file includes all of the classification details of "Quality and Success in Open Source Software: A Systematic Mapping" study.

The controller mapping software market, encompassing solutions like Xpadder, JoyToKey, and reWASD, is experiencing robust growth driven by the increasing popularity of gaming across PCs and consoles. The market's expansion is fueled by several factors: the rising demand for personalized gaming experiences, the proliferation of gaming peripherals beyond standard controllers (e.g., steering wheels, flight sticks), and the growing accessibility of game development tools encouraging modding and customization. This allows gamers to tailor controller inputs to their preferences, improving gameplay and accessibility for players with disabilities. The market is segmented by software type (e.g., open-source vs. commercial), operating system compatibility (Windows, macOS, Linux), and user type (casual gamers, professional esports players, accessibility users). The competitive landscape is characterized by a mix of established players and emerging niche developers, leading to continuous innovation and feature enhancements in the software. While challenges exist, such as the need for software updates to maintain compatibility with new games and operating systems, the overall market outlook remains positive. We anticipate consistent growth over the next decade, driven by technological advancements and the expanding gaming community's ongoing demand for greater customization and control. This expanding market presents opportunities for both established software developers and new entrants. The rise of cloud gaming further enhances market potential, broadening accessibility to players without high-end gaming PCs. However, challenges include ensuring compatibility across diverse hardware and software configurations, as well as navigating the complexities of licensing and intellectual property rights related to game modifications. Future growth will likely be influenced by technological advancements like haptic feedback integration, AI-driven controller mapping assistance, and the increased focus on cross-platform gaming compatibility. The market will continue to diversify, with specialized software targeting particular gaming genres or accessibility needs emerging. A strategic approach focusing on user experience, robust customer support, and ongoing development will be crucial for success in this dynamic market.

The Monitoring and Mapping Software market is experiencing robust growth, driven by the increasing adoption of drones, advanced sensors, and the rising need for precise geospatial data across diverse sectors. The market's expansion is fueled by applications in construction, agriculture, mining, and urban planning, where real-time data and accurate 3D models are crucial for efficient operations and informed decision-making. The integration of AI and machine learning capabilities within these software solutions is further enhancing their analytical power, enabling automated feature extraction, object recognition, and predictive modeling. This leads to improved efficiency, reduced operational costs, and enhanced safety measures. Key players like Hexagon, Trimble, and Autodesk are driving innovation through continuous product development and strategic acquisitions, while the emergence of open-source solutions like Regard3D and Alicevision fosters community development and wider accessibility. The market is segmented by software type (image/video-based, 3D scanning-based) and deployment (cloud, on-premise), with cloud-based solutions gaining significant traction due to their scalability and accessibility. Looking ahead, the market is expected to witness continued expansion, propelled by ongoing technological advancements, including the development of higher-resolution sensors, improved processing power, and the integration of Internet of Things (IoT) devices. The growing demand for precise mapping and monitoring in infrastructure projects, environmental monitoring, and disaster management will also contribute significantly to market growth. However, factors such as the high initial investment costs associated with sophisticated software and hardware, and the need for specialized expertise to operate and interpret the data, could pose challenges to market penetration. Nevertheless, the overall outlook remains positive, with a substantial increase in market size projected over the forecast period. The market's competitiveness is expected to intensify as more players enter the market and existing companies strive to enhance their product offerings to meet evolving customer demands.

Abstract: In this work we introduce an object-based method, applied to urban land cover mapping. The method is implemented with two open-source tools: SIPINA, a data mining software package; and InterIMAGE, an object-based image analysis system. Initially, segmentation, feature extraction and sample selection procedures are performed with InterIMAGE. In order to reduce the time and subjectivity involved to develop the decision rules in InterIMAGE, a data mining step is then carried out with SIPINA. In sequence, the decision trees delivered by SIPINA are analysed and encoded into InterIMAGE decision rules for the final classification step. Experiments were conducted using a subset of a GeoEye image, acquired in January 01, 2013, covering the urban portion of the municipality of Goianésia, Brazil. Five decision tree induction algorithms, available in SIPINA, were tested: ID3, C45, GID3, Assistant86 and CHAID. The TAU and Kappa coefficients were used to evaluate the results. The TAU values obtained were in the range of 0.66 and 0.70, while those for Kappa varied from 0.65 to 0.69.

OpenStreetMap - The Map API

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Browsing our map is easy. Have a look around and see what you think of our coverage and detail. Over the years we've progressed quite spectacularly, achieving many mapping milestones. Individuals, governments and commercial companies have already begun putting this data to use, and in many countries, for many uses, OpenStreetMap is a viable alternative to other map providers. However the map isn't finished yet. The world is a big place. How does your neighbourhood look on OSM? There's lots of other ways to start using OpenStreetMap too.

Development

Extensive software development work is taking this project in many different directions. As mentioned above, we have created various map editing tools. In fact OpenStreetMap is powered by open-source software from its slippy map interface to the underlying data access API (a web service interface for reading and writing map data). There is opportunity for subprojects that work with or use our data, but we also need help fixing bugs and adding features to our core components.

Developers and translators are always welcome!

The OpenStreetMap Foundation

The OpenStreetMap Foundation is an organization that performs fund-raising. One major expense is acquiring and maintaining the servers that host the OpenStreetMap project. While the foundation supports the project, it does not control the project or "own" the OSM data. The foundation is dedicated to encouraging the growth, development and distribution of free geospatial data and to providing geospatial data for anyone to use and share.

Inspiration

I LOVE IT!

The Digital Geomorphic-GIS Map of the Ocracoke Village to The Plains Area (1:10,000 scale 2006 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 (ocis_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 (ocis_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 (ocis_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 (ocis_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: East Carolina University. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (ocis_geomorphology_metadata.txt or ocis_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 1:10,000 and United States National Map Accuracy Standards features are within (horizontally) 8.5 meters or 27.8 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).

The Antarctic Digital Magnetic Anomaly Project (ADMAP) is an Expert Group of the Scientific Committee on Antarctic Research (SCAR). ADMAP compiles and publishes compilations of near surface magnetic anomaly data south of 60°S. Its two most recent compilations are referred to as ADMAP2B and ADMAP2S. ADMAP2B shows near-surface data only, with large gaps. ADMAP2S fills the gaps with satellite-derived data. Both products are freely available, but until now only for proprietary and/or custom software and with a custom map projection that is not widely used outside of the group. This contribution offers both ADMAP2B and ADMAP2S gridded data products in the widely used geotiff, netcdf, and kmz grid formats, and projected into the well known geodetic longitude-latitude and SCAR's recommended WGS-84 Antarctic Polar Stereographic system. These grids are suitable for use in a wide range of applications, including the widely-used free and open source products QGIS, Generic Mapping Tools, and Google Earth.