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.

Open-Source GIS plays a pivotal role in advancing GIS education, fostering research collaboration, and supporting global sustainability by enabling the sharing of data, models, and knowledge. However, the integration of big data, deep learning methods, and artificial intelligence deep learning in geospatial research presents significant challenges for GIS education. These include increasing software learning costs, higher computational power demand, and the management of fragmented information in the Web 2.0 context. Addressing these challenges while integrating emerging GIS innovations and restructuring GIS knowledge systems is crucial for the evolution of GIS Education 3.0. This study introduces a Visual Programming-based Geospatial Cyberinfrastructure (V-GCI) framework, integrated with the replicable and reproducible (R&R) framework, to enhance GIS function compatibility, learning scalability, and web GIS application interoperability. Through a case study on spatial accessibility using the generalized two-step floating catchment area method (G2SFCA), this paper demonstrates how V-GCI can reshape the GIS knowledge tree and its potential to enhance replicability and reproducibility within open-source GIS Education 3.0.

In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.

The global GIS in the Cloud market is projected to reach $1528 million by 2033, exhibiting a CAGR of 17.2% during 2025-2033. The market has witnessed steady growth due to factors such as the increasing adoption of cloud computing, advancements in GIS technology, and the need for real-time data analysis. The market is segmented based on application (government, enterprises) and type (SaaS, PaaS, IaaS). Key drivers of the GIS in the Cloud market include the growing need for geospatial data, the increasing adoption of mobile GIS applications, and the rising demand for real-time data analysis. Major trends in the market include the integration of GIS with other technologies such as IoT and AI, the development of new cloud-based GIS platforms, and the increasing use of open source GIS software. The market is also expected to benefit from the increasing adoption of cloud computing in emerging economies, as well as the growing demand for GIS services in sectors such as natural resource management, urban planning, and disaster response.

The global satellite remote sensing software market is experiencing robust growth, driven by increasing demand across diverse sectors. While precise figures for market size and CAGR aren't provided, considering the technological advancements and applications in agriculture (precision farming, crop monitoring), water conservancy (flood management, irrigation optimization), forest management (deforestation monitoring, resource assessment), and the public sector (urban planning, disaster response), a conservative estimate places the 2025 market size at approximately $2 billion. This figure reflects the substantial investments in satellite imagery acquisition and analysis capabilities worldwide. The market is further fueled by the rising adoption of cloud-based solutions, enhancing accessibility and scalability of software platforms. Trends such as the integration of AI and machine learning for automated image processing, the proliferation of high-resolution satellite imagery, and the increasing availability of open-source software are accelerating market expansion. However, factors such as the high cost of specialized software licenses and the need for skilled professionals to operate the sophisticated systems act as restraints. The market is segmented by application (agriculture, water conservancy, forest management, public sector, others) and software type (open-source, non-open-source). The North American and European markets currently hold significant shares, but the Asia-Pacific region is witnessing rapid growth due to increasing infrastructure development and government initiatives promoting geospatial technologies. This dynamic market landscape presents lucrative opportunities for both established players and emerging companies in the years to come. The forecast period (2025-2033) anticipates continued growth, with a projected CAGR of approximately 12%, driven by the aforementioned technological advancements and broadening applications across various industry verticals. The competitive landscape is comprised of both major players like ESRI, Trimble, and PCI Geomatica, offering comprehensive suites of software, and smaller, specialized companies focusing on niche applications or open-source solutions. The market is characterized by both proprietary and open-source software options. Open-source solutions like QGIS and GRASS GIS offer cost-effective alternatives, particularly for research and smaller organizations, while commercial solutions provide advanced functionalities and support. The increasing availability of cloud-based solutions is blurring the lines between these segments, with hybrid models emerging that combine the benefits of both. Future growth will be significantly influenced by collaborations between software providers and satellite imagery providers, fostering a more integrated ecosystem and streamlining the data acquisition and processing workflow. The market will continue to benefit from advancements in satellite technology, producing higher-resolution, more frequent, and more affordable imagery.

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.

This Excel dataset comprises surveyed information on the use of GIS and remote sensing platforms in climate justice initiatives, providing valuable insights from professionals and stakeholders in the field. This dataset forms the basis for the research paper, offering a comprehensive overview of current platforms / applications in addressing climate justice concerns.

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 expand at a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033, reaching approximately $28 billion by 2033. This growth is fueled by several key factors. Firstly, the burgeoning adoption of cloud-based solutions offers scalability, cost-effectiveness, and enhanced accessibility to a wider user base, including small and medium-sized enterprises (SMEs). Secondly, the escalating need for precise spatial data analysis in various applications, such as urban planning, geological exploration, and water resource management, is significantly boosting market demand. The increasing integration of GIS with other technologies like AI and IoT further amplifies its capabilities, leading to more sophisticated applications and increased market penetration. Finally, government initiatives promoting digitalization and smart city development across the globe are indirectly fueling this market expansion. However, certain restraints limit market growth. The high initial investment cost for advanced GIS software and the requirement for skilled professionals to operate these systems can be a barrier, especially for smaller organizations. Additionally, data security and privacy concerns related to the handling of sensitive geographical information pose challenges to wider adoption. Market segmentation reveals strong growth in the cloud-based GIS segment, driven by its inherent advantages, while applications in urban planning and geological exploration lead the application-based segmentation. North America and Europe currently hold significant market shares, with strong growth potential in the Asia-Pacific region due to increasing infrastructure development and government investments. Leading companies like Esri, Hexagon, and Autodesk are shaping the market landscape through continuous innovation and competitive pricing strategies, while the emergence of open-source options like QGIS and GRASS GIS provides alternative, cost-effective solutions.

The global satellite remote sensing software market is experiencing robust growth, driven by increasing demand across diverse sectors. While precise market size figures for 2025 aren't provided, considering a plausible CAGR of 10% (a conservative estimate given the technological advancements and expanding applications) and an assumed 2024 market size of $2 billion, we can project a 2025 market valuation of approximately $2.2 billion. This expansion is fueled by several key factors. Firstly, the agricultural sector is leveraging satellite imagery for precision farming, crop monitoring, and yield prediction, significantly enhancing efficiency and productivity. Secondly, advancements in water resource management are heavily reliant on remote sensing data for efficient irrigation and flood control. Furthermore, forest management and conservation efforts utilize this technology for deforestation monitoring and biodiversity assessment. The public sector, including government agencies and research institutions, is also a major consumer, relying on these tools for environmental monitoring, disaster response, and urban planning. The market is segmented by software type (open-source and non-open-source) and application, with non-open-source solutions currently commanding a larger share due to their advanced features and robust support. Growth is further propelled by continuous technological innovation leading to more sophisticated analytics capabilities and easier data accessibility. However, certain restraints hinder market expansion. High initial investment costs for software licenses and hardware can pose a significant barrier, particularly for smaller organizations. Furthermore, the need for specialized expertise to interpret and analyze the complex satellite data can limit widespread adoption. Data security and privacy concerns related to sensitive geographic information are also emerging challenges. Despite these limitations, the long-term outlook for the satellite remote sensing software market remains positive, fueled by ongoing technological advancements, increased government investments in space-based technologies, and the growing recognition of its importance in various sectors. The market is expected to continue its growth trajectory, creating opportunities for established players and new entrants alike. The diverse range of applications and continued integration with other technologies like AI and machine learning will significantly shape the future landscape of this market.

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 global Geographic Information System (GIS) Tools market, valued at $2979.7 million in 2025, is projected to experience robust growth, driven by increasing adoption across various sectors. The Compound Annual Growth Rate (CAGR) of 5.5% from 2025 to 2033 indicates a substantial market expansion. Key drivers include the rising need for spatial data analysis in urban planning, environmental management, and infrastructure development. The increasing availability of cloud-based GIS solutions, offering enhanced scalability and accessibility, further fuels market growth. Furthermore, advancements in data visualization and analytics capabilities within GIS tools are attracting a wider range of users. Segmentation reveals a significant market share held by large enterprises, reflecting the considerable resources and data management needs of these organizations. Cloud-based solutions dominate the market, reflecting the shift towards flexible and cost-effective technology deployments. While the market faces some restraints like the high initial investment costs associated with implementing GIS systems and the requirement for skilled personnel, the overall market outlook remains positive due to the expanding applications and technological advancements in the field. North America currently holds a significant market share, driven by high technological adoption rates and the presence of major GIS solution providers. However, the Asia-Pacific region is expected to witness substantial growth in the coming years due to increasing urbanization and infrastructure development initiatives in rapidly growing economies like China and India. The market's growth trajectory is also influenced by the evolving needs of various industry verticals. The application of GIS tools in precision agriculture, disaster management, and supply chain optimization is creating new opportunities for market expansion. The integration of GIS with other technologies, such as IoT and AI, is leading to the development of more sophisticated and insightful applications. This convergence is enabling real-time data analysis and predictive modeling, offering businesses and governments valuable insights for informed decision-making. The competitive landscape is characterized by a mix of established players and emerging startups, driving innovation and fostering competition, ultimately benefiting end-users with a diverse range of solutions and pricing models. The ongoing development of open-source GIS software is also creating a more accessible and collaborative environment within the ecosystem.

ABSTRACT Watershed delineation, drainage network generation and determination of river hydraulic characteristics are important issues in hydrological sciences. In general, this information can be obtained from Digital Elevation Models (DEM) processing within GIS commercial softwares, such as ArcGIS and IDRISI. On the other hand, the use of open source GIS tools has increased significantly, and their advantages include free distribution, continuous development by user communities and full customization for specific requirements. Herein, we present the IPH-Hydro Tools, an open source tool coupled to MapWindow GIS software designed for watershed topology acquisition, including preprocessing steps in hydrological models such as MGB-IPH. In addition, several tests were carried out assessing the performance and applicability of the developed tool, given by a comparison with available GIS packages (ArcGIS, IDRISI, WhiteBox) for similar purposes. The IPH-Hydro Tools provided satisfactory results on tested applications, allowing for better drainage network and less processing time for catchment delineation. Regarding its limitations, the developed tool was incompatible with huge terrain data and showed some difficulties to represent drainage networks in extensive flat areas, which can occur in reservoirs and large rivers.

All of the ERS mapping applications, such as the Food Environment Atlas and the Food Access Research Atlas, use map services developed and hosted by ERS as the source for their map content. These map services are open and freely available for use outside of the ERS map applications. Developers can include ERS maps in applications through the use of the map service REST API, and desktop GIS users can use the maps by connecting to the map server directly.

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.

Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from a workshop that was conducted on October 19-23, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.

Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.

Geostrat Report – The Sequence Stratigraphy and Sandstone Play Fairways of the Late Jurassic Humber Group of the UK Central Graben

This non-exclusive report was purchased by the NSTA from Geostrat as part of the Data Purchase tender process (TRN097012017) that was carried out during Q1 2017. The contents do not necessarily reflect the technical view of the NSTA but the report is being published in the interests of making additional sources of data and interpretation available for use by the wider industry and academic communities.

The Geostrat report provides stratigraphic analyses and interpretations of data from the Late Jurassic to Early Cretaceous Humber Group across the UK Central Graben and includes a series of depositional sequence maps for eight stratigraphic intervals. Stratigraphic interpretations and tops from 189 wells (up to Release 91) are also included in the report.

The outputs as published here include a full PDF report, ODM/IC .dat format sequence maps, and all stratigraphic tops (lithostratigraphy, ages, sequence stratigraphy) in .csv format for import into different interpretation platforms.

In addition, the NSTA has undertaken to provide the well tops, stratigraphic interpretations and sequence maps in shapefile format that is intended to facilitate the integration of these data into projects and data storage systems held by individual organisations who are using non-ESRI ArcGIS GIS software. As part of this process, the Geostrat well names have been matched as far as possible to the NSTA well names from the NSTA Offshore Wells shapefile (as provided on the NSTA’s Open Data website) and the original polygon files have been incorporated into an ArcGIS project. All the files within the GIS folder of this delivery have been created by the NSTA.

An ESRI ArcGIS version of this delivery, including geodatabases, layer files and map documents for well tops, stratigraphic interpretations and sequence maps is available on the NSTA’s Open Data website and is recommended for use with ArcGIS. All releases included in the Data Purchase tender process that have been made openly available are summarised in a mapping application available from the NSTA website. The application includes an area of interest outline for each of the products and an overview of which wellbores have been included in the products.

The global Geographic Information System (GIS) in the Cloud market is experiencing robust growth, projected to reach $1312.6 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 16.5% from 2025 to 2033. This expansion is fueled by several key drivers. Increasing adoption of cloud-based solutions across various sectors, including government and enterprise, offers scalability, cost-effectiveness, and enhanced accessibility to powerful geospatial analytics. The rising demand for location-based services (LBS) across industries like transportation, logistics, and utilities further boosts market growth. Furthermore, advancements in cloud computing technologies, such as improved data storage and processing capabilities, and the emergence of innovative GIS applications are contributing significantly to this upward trajectory. The market segmentation reveals strong growth across SaaS, PaaS, and IaaS models, with significant opportunities within the government and enterprise application segments. While data security and privacy concerns remain a restraint, the ongoing development of robust security protocols and increasing awareness of the benefits of cloud GIS are mitigating these challenges. Competition is fierce, with established players like ESRI, Google, and Microsoft alongside emerging innovative companies constantly vying for market share, driving innovation and competitive pricing. The geographical distribution of this market shows a significant presence across North America and Europe, with Asia-Pacific emerging as a region with substantial growth potential due to increasing digitalization and infrastructure development. The competitive landscape within the GIS in the Cloud market is dynamic, marked by both established technology giants and agile specialized companies. Major players are focusing on expanding their service offerings and enhancing their platforms to cater to the evolving needs of users. This includes integrating advanced analytics capabilities, supporting diverse data formats, and enhancing interoperability with other systems. Strategic partnerships and mergers and acquisitions are frequently employed to broaden market reach and strengthen technology portfolios. Furthermore, the market is witnessing a surge in the adoption of open-source GIS solutions, offering an alternative to proprietary platforms and fostering innovation. The future of the GIS in the Cloud market points towards increased integration with other technologies such as Artificial Intelligence (AI) and Machine Learning (ML) for advanced geospatial analysis and predictive modeling, further enhancing market growth and driving new applications. Overall, the market presents a compelling investment opportunity driven by technological advancements, increasing demand, and diverse applications.

The global satellite remote sensing software market is experiencing robust growth, driven by increasing demand across diverse sectors. While precise figures for market size and CAGR aren't provided, a reasonable estimate based on industry reports and the stated study period (2019-2033) suggests a current market valuation (2025) in the range of $3-5 billion USD. This significant market size is fueled by several key factors. The agricultural sector relies heavily on remote sensing for precision farming, crop monitoring, and yield prediction, significantly contributing to market expansion. Similarly, the water conservancy and forest management sectors utilize satellite imagery and software for resource monitoring, disaster management, and sustainable practices. Government agencies and the public sector increasingly adopt these technologies for urban planning, environmental monitoring, and national security applications. The market's growth is further enhanced by advancements in open-source software, offering cost-effective alternatives and promoting wider adoption. Trends such as cloud-based solutions, improved data processing capabilities, and the integration of artificial intelligence are further accelerating market growth. However, the market faces certain constraints. High initial investment costs for software licenses and specialized hardware can act as a barrier for entry, particularly for smaller businesses and organizations in developing regions. Data security concerns and the need for skilled professionals to interpret the complex data generated also pose challenges. Despite these obstacles, the ongoing development of user-friendly interfaces, coupled with decreasing hardware costs and increasing availability of cloud-based services, is predicted to mitigate these restraints and sustain a healthy compound annual growth rate (CAGR) in the range of 8-12% throughout the forecast period (2025-2033). Segmentation by application (Agriculture, Water Conservancy, Forest Management, Public Sector, Others) and software type (Open Source, Non-Open Source) reveals distinct market dynamics, with the non-open source segment currently holding a larger share due to its advanced capabilities. This trend is expected to continue, though the open-source segment will show considerable growth driven by its affordability and accessibility.

These data represent the land boundaries affiliated with JCOS. They are intended for public use for viewing in web applications and is available for download for various GIS uses. These features represent the boundaries of land that JCOS owns or manages. In some cases, JCOS parks are comprised of several parcels that have different ownership/management, but are considered part of a larger park. For example, South Table Mountain Park (STM) contains parcels owned by JCOS, the state, and has agreements with other entities. This is important to know if attempting to calculate acreage for a park. One must use ALL parcels of a respective park to calculate total acreage.Land Preservation Type: These are internal distinctions that help JCOS quickly determine ownership status. However, these distinctions are consolidated from a broader list in order to more easily display them on maps. For any questions regarding more specificity of ownership or management of a particular parcel, contact JCOS.Owner/Manager: A "|" in the Owner/Manager fields indicate joint ownership/management.Data Type: PolygonSensitive: NoSource: JCOSCreation Means: JCOS uses a variety of sources to create these data. These sources include, but are not limited to, survey data, coordinate geometry (COGO), legal descriptions, and subdivision plats.Original Projection: NAD_1983_StatePlane_Colorado_Central_FIPS_0502_Feet (WKID: 2232)ATTRIBUTION RELATES TO INDIVIDUAL FEATURES, not the overall associated property.

[Metadata] Description: Land Use Land Cover of main Hawaiian Islands as of 1976