100+ datasets found
  1. Digital Geologic-GIS Map of Sagamore Hill National Historic Site and...

    • catalog.data.gov
    Updated Jun 5, 2024
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    National Park Service (2024). Digital Geologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York (NPS, GRD, GRI, SAHI, SAHI digital map) adapted from U.S. Geological Survey Water-Supply Paper maps by Isbister (1966) and Lubke (1964) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-sagamore-hill-national-historic-site-and-vicinity-new-york-nps
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    New York
    Description

    The Digital Geologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (sahi_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 (sahi_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 (sahi_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.) A GIS readme file (sahi_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (sahi_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (sahi_geology_metadata_faq.pdf). Please read the sahi_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: 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 (sahi_geology_metadata.txt or sahi_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 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 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).

  2. GIS Mapping Software Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). GIS Mapping Software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/gis-mapping-software-market
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    pdf, pptx, csvAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    GIS Mapping Software Market Outlook



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



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



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



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



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



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



    Component Analysis



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



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



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

  3. a

    2019 Geospatial @ TNC Annual Report & Map Book (PDF)

    • hub.arcgis.com
    Updated Sep 30, 2024
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    The Nature Conservancy (2024). 2019 Geospatial @ TNC Annual Report & Map Book (PDF) [Dataset]. https://hub.arcgis.com/documents/a38120251e7d4802afc1fae568b1f2fe
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    Dataset updated
    Sep 30, 2024
    Dataset authored and provided by
    The Nature Conservancy
    Description

    For the first time The Nature Conservancy has defined its geospatial community and described some of the impacts on conservation. Geospatial technology, the combined disciplines of Geographic Information Systems (GIS), remote sensing and more recently artificial intelligence, has informed the Conservancy’s conservation science approaches for decades. With the launch of the Geospatial Conservation at The Nature Conservancy 2019 Annual Report and Map Book, we are at a pivotal and exciting time. At least one in every three Conservancy staff uses maps, whether to monitor preserves, negotiate land and water transactions, or develop global ecosystem services analyses. The Nature Conservancy’s Geospatial Systems Team in IT has established a global GIS Leadership Council, formed working groups in key areas such as cartography and increased our central capacity to support the vast array of geospatial activity across the organization. “Following decades of collaboration between Esri and The Nature Conservancy, I am excited to see this inaugural geospatial annual report,” says Jack Dangermond, Founder and President of the Environmental Systems Research Institute (Esri). “TNC is a global leader in applying GIS to inform conservation management plans and actions to address complex environmental challenges powered by the best available data, scientifically grounded spatial analysis and advanced visualization tools. This series of reports will inform readers about the trends and profound conservation impacts which have been realized by leveraging geospatial technology.”This report is designed to (a) provide a baseline of the Conservancy’s 2019 geospatial work, (b) present use cases that illustrate ways that technology supports conservation and (c) examine emerging opportunities where TNC can best leverage geospatial technology to protect, conserve and restore ecosystems around the globe.

  4. Digital Geologic-GIS Map of San Miguel Island, California (NPS, GRD, GRI,...

    • catalog.data.gov
    Updated Jun 4, 2024
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    National Park Service (2024). Digital Geologic-GIS Map of San Miguel Island, California (NPS, GRD, GRI, CHIS, SMIS digital map) adapted from a American Association of Petroleum Geologists Field Trip Guidebook map by Weaver and Doerner (1969) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-san-miguel-island-california-nps-grd-gri-chis-smis-digital-map
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    Dataset updated
    Jun 4, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    California, San Miguel Island
    Description

    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).

  5. a

    OpenStreetMap

    • africageoportal.com
    • data.baltimorecity.gov
    • +43more
    Updated May 19, 2020
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    Africa GeoPortal (2020). OpenStreetMap [Dataset]. https://www.africageoportal.com/maps/a5511fbe18ce46788b78adbcba13bc1e
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    Dataset updated
    May 19, 2020
    Dataset authored and provided by
    Africa GeoPortal
    Area covered
    Description

    This web map references the live tiled map service from the OpenStreetMap project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information such as free satellite imagery, and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: http://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in Esri products under a Creative Commons Attribution-ShareAlike license.Tip: This service is one of the basemaps used in the ArcGIS.com map viewer and ArcGIS Explorer Online. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10.

  6. Geospatial Data Gateway

    • agdatacommons.nal.usda.gov
    bin
    Updated Nov 30, 2023
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    USDA, Natural Resources Conservation Service (NRCS); USDA, Farm Service Agency (FSA); USDA, Rural Development (RD) (2023). Geospatial Data Gateway [Dataset]. http://doi.org/10.15482/USDA.ADC/1241880
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    binAvailable download formats
    Dataset updated
    Nov 30, 2023
    Dataset provided by
    Natural Resources Conservation Servicehttp://www.nrcs.usda.gov/
    United States Department of Agriculturehttp://usda.gov/
    Authors
    USDA, Natural Resources Conservation Service (NRCS); USDA, Farm Service Agency (FSA); USDA, Rural Development (RD)
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The Geospatial Data Gateway (GDG) provides access to a map library of over 100 high resolution vector and raster layers in the Geospatial Data Warehouse. It is the one stop source for environmental and natural resource data, available anytime, from anywhere. It allows a user to choose an area of interest, browse and select data, customize the format, then download or have it shipped on media. The map layers include data on: Public Land Survey System (PLSS), Census data, demographic statistics, precipitation, temperature, disaster events, conservation easements, elevation, geographic names, geology, government units, hydrography, hydrologic units, land use and land cover, map indexes, ortho imagery, soils, topographic images, and streets and roads. This service is made available through a close partnership between the three Service Center Agencies (SCA): Natural Resources Conservation Service (NRCS), Farm Service Agency (FSA), and Rural Development (RD). Resources in this dataset:Resource Title: Geospatial Data Gateway. File Name: Web Page, url: https://gdg.sc.egov.usda.gov This is the main page for the GDG that includes several links to view, download, or order various datasets. Find additional status maps that indicate the location of data available for each map layer in the Geospatial Data Gateway at https://gdg.sc.egov.usda.gov/GDGHome_StatusMaps.aspx

  7. 3

    3D Mapping Modelling Market Report

    • promarketreports.com
    doc, pdf, ppt
    Updated Feb 1, 2025
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    Pro Market Reports (2025). 3D Mapping Modelling Market Report [Dataset]. https://www.promarketreports.com/reports/3d-mapping-modelling-market-10299
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    doc, pdf, pptAvailable download formats
    Dataset updated
    Feb 1, 2025
    Dataset authored and provided by
    Pro Market Reports
    License

    https://www.promarketreports.com/privacy-policyhttps://www.promarketreports.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global 3D mapping and modeling market is expected to grow significantly in the next few years as demand increases for detailed and accurate representations of physical environments in three-dimensional space. Estimated to be valued at USD 38.62 billion in the year 2025, the market was expected to grow at a CAGR of 14.5% from 2025 to 2033 and was estimated to reach an amount of USD 90.26 billion by the end of 2033. The high growth rate is because of improvement in advanced technologies with the development of high-resolution sensors and methods of photogrammetry that make possible higher-resolution realistic and immersive 3D models.Key trends in the market are the adoption of virtual and augmented reality (VR/AR) applications, 3D mapping with smart city infrastructure, and increased architecture, engineering, and construction utilization of 3D models. Other factors are driving the growing adoption of cloud-based 3D mapping and modeling solutions. The solutions promise scalability, cost-effectiveness, and easy access to 3D data, thus appealing to business and organizations of all sizes. Recent developments include: Jun 2023: Nomoko (Switzerland), a leading provider of real-world 3D data technology, announced that it has joined the Overture Maps Foundation, a non-profit organization committed to fostering collaboration and innovation in the geospatial domain. Nomoko will collaborate with Meta, Amazon Web Services (AWS), TomTom, and Microsoft, to create interoperable, accessible 3D datasets, leveraging its real-world 3D modeling capabilities., May 2023: The Sanborn Map Company (Sanborn), an authority in 3D models, announced the development of a powerful new tool, the Digital Twin Base Map. This innovative technology sets a new standard for urban analysis, implementation of Digital Cities, navigation, and planning with a fundamental transformation from a 2D map to a 3D environment. The Digital Twin Base Map is a high-resolution 3D map providing unprecedented detail and accuracy., Feb 2023: Bluesky Geospatial launched the MetroVista, a 3D aerial mapping program in the USA. The service employs a hybrid imaging-Lidar airborne sensor to capture highly detailed 3D data, including 360-degree views of buildings and street-level features, in urban areas to create digital twins, visualizations, and simulations., Feb 2023: Esri, a leading global provider of geographic information system (GIS), location intelligence, and mapping solutions, released new ArcGIS Reality Software to capture the world in 3D. ArcGIS Reality enables site, city, and country-wide 3D mapping for digital twins. These 3D models and high-resolution maps allow organizations to analyze and interact with a digital world, accurately showing their locations and situations., Jan 2023: Strava, a subscription-based fitness platform, announced the acquisition of FATMAP, a 3D mapping platform, to integrate into its app. The acquisition adds FATMAP's mountain-focused maps to Strava's platform, combining with the data already within Strava's products, including city and suburban areas for runners and other fitness enthusiasts., Jan 2023: The 3D mapping platform FATMAP is acquired by Strava. FATMAP applies the concept of 3D visualization specifically for people who like mountain sports like skiing and hiking., Jan 2022: GeoScience Limited (the UK) announced receiving funding from Deep Digital Cornwall (DDC) to develop a new digital heat flow map. The DDC project has received grant funding from the European Regional Development Fund. This study aims to model the heat flow in the region's shallower geothermal resources to promote its utilization in low-carbon heating. GeoScience Ltd wants to create a more robust 3D model of the Cornwall subsurface temperature through additional boreholes and more sophisticated modeling techniques., Aug 2022: In order to create and explore the system's possibilities, CGTrader worked with the online retailer of dietary supplements Hello100. The system has the ability to scale up the generation of more models, and it has enhanced and improved Hello100's appearance on Amazon Marketplace.. Key drivers for this market are: The demand for 3D maps and models is growing rapidly across various industries, including architecture, engineering, and construction (AEC), manufacturing, transportation, and healthcare. Advances in hardware, software, and data acquisition techniques are making it possible to create more accurate, detailed, and realistic 3D maps and models. Digital twins, which are virtual representations of real-world assets or systems, are driving the demand for 3D mapping and modeling technologies for the creation of accurate and up-to-date digital representations.

    . Potential restraints include: The acquisition and processing of 3D data can be expensive, especially for large-scale projects. There is a lack of standardization in the 3D mapping modeling industry, which can make it difficult to share and exchange data between different software and systems. There is a shortage of skilled professionals who are able to create and use 3D maps and models effectively.. Notable trends are: 3D mapping and modeling technologies are becoming essential for a wide range of applications, including urban planning, architecture, construction, environmental management, and gaming. Advancements in hardware, software, and data acquisition techniques are enabling the creation of more accurate, detailed, and realistic 3D maps and models. Digital twins, which are virtual representations of real-world assets or systems, are driving the demand for 3D mapping and modeling technologies for the creation of accurate and up-to-date digital representations..

  8. Geospatial data for the Vegetation Mapping Inventory Project of Shenandoah...

    • catalog.data.gov
    Updated Jun 4, 2024
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    National Park Service (2024). Geospatial data for the Vegetation Mapping Inventory Project of Shenandoah National Park [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-shenandoah-national-park
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    Dataset updated
    Jun 4, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We followed methods in Anderson and Merrill (1998) for combining gradient layers into an “ecological land units” map (also referred to as a “biophysical units” map). Our goal was to use this information to create sampling strata that capture the range of environments observed. The Anderson and Merrill (1998) method (implemented as a set of GIS scripts by F. Biasi (2001)) builds an ecological units map by classifying and combining individual environmental gradient maps in a GIS. Maps of aspect, moisture, slope, and slope shape are reclassified and assembled to produce maps of landform units. These landform units are then combined with reclassified elevation and geologic maps to produce a final ecological land units or “ELU” map. We used these methods as a guide to building an ecological land units map for Shenandoah National Park, adapting the procedures for local conditions. Individual steps in the process and maps resulting from intermediate and final stages are described in the report.

  9. A

    Geospatial data for the Vegetation Mapping Inventory Project of American...

    • data.amerigeoss.org
    • catalog.data.gov
    api, zip
    Updated Jan 1, 2008
    + more versions
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    United States (2008). Geospatial data for the Vegetation Mapping Inventory Project of American Memorial Park [Dataset]. https://data.amerigeoss.org/sq/dataset/showcases/geospatial-data-for-the-vegetation-mapping-inventory-project-of-american-memorial-park
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    api, zipAvailable download formats
    Dataset updated
    Jan 1, 2008
    Dataset provided by
    United States
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for American Memorial Park. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles.

    To produce the spatial database and map layer, 0.6-meter, 4-band Quickbird satellite imagery from 2006 was provided by PACN. By comparing the signatures on the imagery to field and ground data 27 map classes (16 vegetated, three barren, and eight land-use / land-cover) were developed and directly crosswalked or matched to their corresponding NVC plant associations. The interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases and maps were printed, field tested, reviewed, and revised. The final map layer was accessed for thematic accuracy by overlaying 48 independent accuracy assessment points.

  10. w

    Kentucky Geological Survey: Geospatial Data Library

    • data.wu.ac.at
    html
    Updated Mar 23, 2015
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    (2015). Kentucky Geological Survey: Geospatial Data Library [Dataset]. https://data.wu.ac.at/odso/edx_netl_doe_gov/YjU5ODExODEtODljYi00YmY3LWE4NTUtOGQ5MzEwYzJiMzA2
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    htmlAvailable download formats
    Dataset updated
    Mar 23, 2015
    Area covered
    e6b005132ff975e458d3ea0a449441e7311b0d76
    Description

    Maps and GIS data provided by The Kentucky Geological Survey; includes maps, elevation, geology data, hydrology data, and transportation information.

  11. A

    Geospatial data for the Vegetation Mapping Inventory Project of Great Basin...

    • data.amerigeoss.org
    api
    Updated Jul 27, 2019
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    United States[old] (2019). Geospatial data for the Vegetation Mapping Inventory Project of Great Basin National Park [Dataset]. https://data.amerigeoss.org/tr/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-great-basin-national-park
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    apiAvailable download formats
    Dataset updated
    Jul 27, 2019
    Dataset provided by
    United States[old]
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles.

    GRBA’s spatial database and map layer was produced from high-resolution 2007 Digital Map, Inc. imagery provided to CTI by the NPS. By comparing the signatures on the imagery to field and ground data, 64 map units (48 vegetated, four barren geology and snow, and 12 land-use / land-cover) were developed and the vegetation map units were directly cross-walked or matched to their corresponding rUSNVC plant associations. The interpreted and remotely sensed data were converted to Geographic Information System (GIS) spatial geodatabases and maps were printed, field tested, reviewed, and revised.

  12. a

    US Dept of Transportation - Geospatial Maps & Apps

    • regional-planning-northcentral.hub.arcgis.com
    • hub.arcgis.com
    Updated Nov 9, 2016
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    North Central Pa Regional Planning & Development (2016). US Dept of Transportation - Geospatial Maps & Apps [Dataset]. https://regional-planning-northcentral.hub.arcgis.com/datasets/us-dept-of-transportation-geospatial-maps-apps
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    Dataset updated
    Nov 9, 2016
    Dataset authored and provided by
    North Central Pa Regional Planning & Development
    Area covered
    United States
    Description

    United State Department of Transportation, Office of the Assistant Secretary for Research and Technology Bureau of Transportation Statistics - Geospatial Maps and Apps.

  13. O

    FireStation_data

    • data.cityofgainesville.org
    Updated Dec 3, 2020
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    City of Gainesville (2020). FireStation_data [Dataset]. https://data.cityofgainesville.org/w/7ang-kwek/default?cur=0U9I1RgeMM8
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    xml, kmz, application/geo+json, application/rdfxml, csv, application/rssxml, kmlAvailable download formats
    Dataset updated
    Dec 3, 2020
    Dataset authored and provided by
    City of Gainesville
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    GFR and ACFR fire stations. This map is provided by the City of Gainesville ArcGIS

  14. a

    Interactive GIS Mapping Tool – Fully Appropriated Stream Systems (FASS) in...

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • gis.data.ca.gov
    • +2more
    Updated Apr 4, 2021
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    California Water Boards (2021). Interactive GIS Mapping Tool – Fully Appropriated Stream Systems (FASS) in California [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/6e9e2a7727ab46f8b76244cff111a4ee
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    Dataset updated
    Apr 4, 2021
    Dataset authored and provided by
    California Water Boards
    Description

    This mapping tool provides a representation of the general watershed boundaries for stream systems declared fully appropriated by the State Water Board. The boundaries were created by Division of Water Rights staff by delineating FASS critical reaches and consolidating HUC 12 sub-watersheds to form FASS Watershed boundaries. As such, the boundaries are in most cases conservative with respect to the associated stream system. However, users should check neighboring FASS Watersheds to ensure the stream system of interest is not restricted by other FASS listings. For more information regarding the Declaration of Fully Appropriated Stream Systems, visit the Division of Water Rights’ Fully Appropriated Streams webpage. How to Use the Interactive Mapping Tool: If it is your first time viewing the map, you will need to click the “OK” box on the splash screen and agree to the disclaimer before continuing. Navigate to your point of interest by either using the search bar or by zooming in on the map. You may enter a stream name, street address, or watershed ID in the search bar. Click on the map to identify the location of interest and one or more pop-up boxes may appear with information about the fully appropriated stream systems within the general watershed boundaries of the identified location. The information provided in the pop-up box may include: (a) stream name, (b) tributary, (c) season declared fully appropriated, (d) Board Decisions/Water Right Orders, and/or (e) court references/adjudications. You may toggle the FAS Streams reference layer on and off to find representative critical reaches associated with the FASS Watershed layer. Please note that this layer is for general reference purposes only and ultimately the critical reach listed in Appendix A of Water Rights Order 98-08 and Appendix A together with any associated footnotes controls. Note: A separate FAS Watershed boundary layer was created for the Bay-Delta Watershed. The Bay-Delta Watershed layer should be toggled on to check if the area of interest is fully appropriated under State Water Board Decision 1594.

  15. A

    Geospatial data for the Vegetation Mapping Inventory Project of Grand Teton...

    • data.amerigeoss.org
    • catalog.data.gov
    zip
    Updated Jul 26, 2019
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    United States[old] (2019). Geospatial data for the Vegetation Mapping Inventory Project of Grand Teton National Park [Dataset]. https://data.amerigeoss.org/es/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-grand-teton-national-park
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    zipAvailable download formats
    Dataset updated
    Jul 26, 2019
    Dataset provided by
    United States[old]
    Area covered
    Grand Teton, Teton Range
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles.

    To produce the digital map, a combination of 1:12,000-scale true color aerial photography, 1:12,000-scale true color ortho-rectified imagery, and 3 years of ground-truthing were used to interpret the complex patterns of vegetation and land-use. In the end, 52 map units were developed and directly cross-walked or matched to corresponding plant associations and land-use classes. All of the interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases using ArcGIS© software. Draft maps were printed, field tested, reviewed and revised. 1,122 accuracy assessment data points were collected and used to determine the map’s accuracy. After final revisions, the accuracy assessment revealed an overall thematic accuracy of 82%.

  16. u

    1:24,000-scale topographic maps

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Nov 5, 2019
    + more versions
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    Earth Data Analysis Center (2019). 1:24,000-scale topographic maps [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/6f952cb0-7157-4bbe-b7b7-c919701f9625/metadata/FGDC-STD-001-1998.html
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    gml(5), csv(5), xls(5), shp(5), kml(5), zip(1), geojson(5), json(5)Available download formats
    Dataset updated
    Nov 5, 2019
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    1974
    Area covered
    New Mexico, West Bounding Coordinate -109.0412036 East Bounding Coordinate -103.0513351 North Bounding Coordinate 36.9986171 South Bounding Coordinate 31.3339961
    Description

    The Geographic Names Information System (GNIS) actively seeks data from and partnerships with Government agencies at all levels and other interested organizations. The GNIS is the Federal standard for geographic nomenclature. The U.S. Geological Survey developed the GNIS for the U.S. Board on Geographic Names, a Federal inter-agency body chartered by public law to maintain uniform feature name usage throughout the Government and to promulgate standard names to the public. The GNIS is the official repository of domestic geographic names data; the official vehicle for geographic names use by all departments of the Federal Government; and the source for applying geographic names to Federal electronic and printed products of all types. See http://geonames.usgs.gov for additional information.

  17. Geospatial data for the Vegetation Mapping Inventory Project of Gettysburg...

    • catalog.data.gov
    • data.amerigeoss.org
    Updated Jun 5, 2024
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    National Park Service (2024). Geospatial data for the Vegetation Mapping Inventory Project of Gettysburg National Military Park and Eisenhower National Historic Site [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-gettysburg-national-milita
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Gettysburg
    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Following the vegetation data analysis, the formation-level vegetation map was further edited and refined to develop an association-level vegetation map. Using ArcView 3.2, polygon boundaries were revised onscreen based on the plot data and additional field observations. Each polygon was attributed with the name of a vegetation association based on plot data, field observations, classification analyses, aerial photography signatures, and topographic maps. Several polygons were labeled as mosaics of two associations because both types were present in the polygons and clear boundaries between the two associations could not be delineated. The category of Cleared Land was added as an Anderson level II category (modified) for polygons that had recently undergone woodlot removal as part of the battlefield rehabilitation. After the vegetation association map was completed, the thematic accuracy of this map was assessed.

  18. f

    IMCOMA-example-datasets

    • figshare.com
    xml
    Updated Feb 12, 2021
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    Nowosad (2021). IMCOMA-example-datasets [Dataset]. http://doi.org/10.6084/m9.figshare.13379228.v1
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    xmlAvailable download formats
    Dataset updated
    Feb 12, 2021
    Dataset provided by
    figshare
    Authors
    Nowosad
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Datasets- simple_land_cover1.tif - an example land cover dataset presented in Figures 1 and 2- simple_landform1.tif - an example landform dataset presented in Figures 1 and 2- landcover_europe.tif - a land cover dataset with nine categories for Europe - landcover_europe.qml - a QGIS color style for the landcover_europe.tif dataset- landform_europe.tif - a landform dataset with 17 categories for Europe - landform_europe.qml - a QGIS color style for the landform_europe.tif dataset- map1.gpkg - a map of LTs in Europe constructed using the INCOMA-based method- map1.qml - a QGIS color style for the map1.gpkg dataset- map2.gpkg - a map of LTs in Europe constructed using the COMA method to identify and delineate pattern types in each theme separately- map2.qml - a QGIS color style for the map2.gpkg dataset- map3.gpkg - a map of LTs in Europe constructed using the map overlay method- map3.qml - a QGIS color style for the map3.gpkg dataset

  19. Cadastral Mapping Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Oct 3, 2024
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    Dataintelo (2024). Cadastral Mapping Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/cadastral-mapping-market
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    pdf, pptx, csvAvailable download formats
    Dataset updated
    Oct 3, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Cadastral Mapping Market Outlook



    The global cadastral mapping market size was valued at approximately USD 4.2 billion in 2023 and is projected to reach around USD 7.9 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.2% during the forecast period. This market growth can be attributed to increasing urbanization, rapid advancements in geospatial technologies, and the growing need for efficient land management systems across various regions.



    The expansion of urban areas and the corresponding increase in the need for effective land management infrastructure are significant growth factors driving the cadastral mapping market. As urbanization accelerates globally, local governments and planning agencies require sophisticated tools to manage and record land ownership, boundaries, and property information. Enhanced geospatial technologies, including Geographic Information Systems (GIS) and remote sensing, are pivotal in facilitating accurate and efficient cadastral mapping, thus contributing to market growth.



    Another key growth factor is the rising demand for infrastructure development. As nations invest in large-scale infrastructure projects such as roads, railways, and smart cities, there is an increased need for precise land data to ensure the proper allocation of resources and to avoid legal disputes. Cadastral mapping provides the critical data needed for these projects, hence its demand is surging. Additionally, governments worldwide are increasingly adopting digital platforms to streamline land administration processes, further propelling the market.



    Furthermore, the agricultural sector is also significantly contributing to the growth of the cadastral mapping market. Modern agriculture relies heavily on accurate land parcel information for planning and optimizing crop production. By integrating cadastral maps with other geospatial data, farmers can improve land use efficiency, monitor crop health, and enhance yield predictions. This integration is particularly valuable in precision farming, which is becoming more prevalent as the world's population grows and the demand for food increases.



    Regionally, Asia Pacific is expected to witness the highest growth in the cadastral mapping market. Factors such as rapid urbanization, extensive infrastructure development projects, and the need for improved land management are driving the demand in this region. Moreover, governments in countries like India and China are investing heavily in creating digital land records and implementing smart city initiatives, which further boosts the market. The North American and European markets are also substantial, driven by the advanced technological infrastructure and well-established land administration systems.



    Component Analysis



    The cadastral mapping market can be segmented by component into software, hardware, and services. The software segment holds a significant share in this market, driven by the increasing adoption of advanced GIS and mapping software solutions. These software solutions enable accurate land parcel mapping, data analysis, and integration with other geospatial data systems, making them indispensable tools for cadastral mapping. Companies are continuously innovating to provide more intuitive and comprehensive software solutions, which is expected to fuel growth in this segment.



    Hardware components, including GPS devices, drones, and other surveying equipment, are also critical to the cadastral mapping market. The hardware segment is expected to grow steadily as technological advancements improve the accuracy and efficiency of these devices. Innovations such as high-resolution aerial imaging and LIDAR technology are enhancing the capabilities of cadastral mapping hardware, allowing for more detailed and precise data collection. This segment is particularly essential for field surveying and data acquisition, forming the backbone of cadastral mapping projects.



    The services segment encompasses a wide range of offerings, including consulting, implementation, and maintenance services. Professional services are vital for the successful deployment and operation of cadastral mapping systems. Governments and private sector organizations often rely on specialized service providers to implement these systems, train personnel, and ensure ongoing support. As the complexity of cadastral mapping projects increases, the demand for expert services is also expected to rise, contributing to the growth of this segment.



    Integration services are another critical component within the

  20. Data from: Digital Terrain Model (DTM) from 2005 LiDAR for the Green Lakes...

    • search.dataone.org
    • portal.edirepository.org
    Updated Apr 4, 2019
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    Robert Anderson (2019). Digital Terrain Model (DTM) from 2005 LiDAR for the Green Lakes Valley, Colorado [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-nwt%2F733%2F2
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    Dataset updated
    Apr 4, 2019
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Robert Anderson
    Time period covered
    Sep 29, 2005
    Area covered
    Description

    This 1m Digital Terrain Model (DTM) is derived from bare-ground Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. This dataset is better suited for derived layers such as slope angle, aspect, and contours. The DTM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DTM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DTM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. A shaded relief model was also generated. A similar layer, the Digital Surface Model (DSM), is a first-stop elevation layer. A processing report and readme file are included with this data release. The DTM is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.

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National Park Service (2024). Digital Geologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York (NPS, GRD, GRI, SAHI, SAHI digital map) adapted from U.S. Geological Survey Water-Supply Paper maps by Isbister (1966) and Lubke (1964) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-sagamore-hill-national-historic-site-and-vicinity-new-york-nps
Organization logo

Digital Geologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York (NPS, GRD, GRI, SAHI, SAHI digital map) adapted from U.S. Geological Survey Water-Supply Paper maps by Isbister (1966) and Lubke (1964)

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Dataset updated
Jun 5, 2024
Dataset provided by
National Park Servicehttp://www.nps.gov/
Area covered
New York
Description

The Digital Geologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (sahi_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 (sahi_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 (sahi_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.) A GIS readme file (sahi_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (sahi_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (sahi_geology_metadata_faq.pdf). Please read the sahi_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: 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 (sahi_geology_metadata.txt or sahi_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 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

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