To achieve true data interoperability is to eliminate format and data model barriers, allowing you to seamlessly access, convert, and model any data, independent of format. The ArcGIS Data Interoperability extension is based on the powerful data transformation capabilities of the Feature Manipulation Engine (FME), giving you the data you want, when and where you want it.In this course, you will learn how to leverage the ArcGIS Data Interoperability extension within ArcCatalog and ArcMap, enabling you to directly read, translate, and transform spatial data according to your independent needs. In addition to components that allow you to work openly with a multitude of formats, the extension also provides a complex data model solution with a level of control that would otherwise require custom software.After completing this course, you will be able to:Recognize when you need to use the Data Interoperability tool to view or edit your data.Choose and apply the correct method of reading data with the Data Interoperability tool in ArcCatalog and ArcMap.Choose the correct Data Interoperability tool and be able to use it to convert your data between formats.Edit a data model, or schema, using the Spatial ETL tool.Perform any desired transformations on your data's attributes and geometry using the Spatial ETL tool.Verify your data transformations before, after, and during a translation by inspecting your data.Apply best practices when creating a workflow using the Data Interoperability extension.

These products were developed to provide scientific and correspondingly spatially explicit information regarding the distribution and abundance of conifers (namely, singleleaf pinyon (Pinus monophylla), Utah juniper (Juniperus osteosperma), and western juniper (Juniperus occidentalis)) in Nevada and portions of northeastern California. Encroachment of these trees into sagebrush ecosystems of the Great Basin can present a threat to populations of greater sage-grouse (Centrocercus urophasianus). These data provide land managers and other interested parties with a high-resolution representation of conifers across the range of sage-grouse habitat in Nevada and northeastern California that can be used for a variety of management and research applications. We mapped conifer trees at 1 x 1 meter resolution across the extent of all Nevada Department of Wildlife Sage-grouse Population Management Units plus a 10 km buffer. Using 2010 and 2013 National Agriculture Imagery Program digital orthophoto quads (DOQQs) as our reference imagery, we applied object-based image analysis with Feature Analyst software (Overwatch, 2013) to classify conifer features across our study extent. This method relies on machine learning algorithms that extract features from imagery based on their spectral and spatial signatures. Conifers in 6230 DOQQs were classified and outputs were then tested for errors of omission and commission using stratified random sampling. Results of the random sampling were used to populate a confusion matrix and calculate the overall map accuracy of 84.3 percent. We provide 5 sets of products for this mapping process across the entire mapping extent: (1) a shapefile representing accuracy results linked to our mapping subunits; (2) binary rasters representing conifer presence or absence at a 1 x 1 meter resolution; (3) a 30 x 30 meter resolution raster representing percentage of conifer canopy cover within each cell from 0 to 100; (4) 1 x 1 meter resolution canopy cover classification rasters derived from a 50 meter radius moving window analysis; and (5) a raster prioritizing pinyon-juniper management for sage-grouse habitat restoration efforts. The latter three products can be reclassified into user-specified bins to meet different management or study objectives, which include approximations for phases of encroachment. These products complement, and in some cases improve upon, existing conifer maps in the western United States, and will help facilitate sage-grouse habitat management and sagebrush ecosystem restoration. These data support the following publication: Coates, P.S., Gustafson, K.B., Roth, C.L., Chenaille, M.P., Ricca, M.A., Mauch, Kimberly, Sanchez-Chopitea, Erika, Kroger, T.J., Perry, W.M., and Casazza, M.L., 2017, Using object-based image analysis to conduct high-resolution conifer extraction at regional spatial scales: U.S. Geological Survey Open-File Report 2017-1093, 40 p., https://doi.org/10.3133/ofr20171093. References: ESRI, 2013, ArcGIS Desktop: Release 10.2: Environmental Systems Research Institute. Overwatch, 2013, Feature Analyst Version 5.1.2.0 for ArcGIS: Overwatch Systems Ltd.

The resource management features of the CanVec series include power lines, communication lines, pipelines, valves, petroleum wells, wind-operated devices, transformer stations, ore extraction sites, aggregate extraction sites, peat extraction sites and oil and gas sites. The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool. Related Products: Topographic Data of Canada - CanVec Series

The global geospatial data provider market is anticipated to reach a value of XX million USD by 2033, exhibiting a CAGR of XX% during the forecast period (2023-2033). The market was valued at USD 5515 million in 2022. This growth is primarily attributed to the growing demand for geospatial data in various industry verticals, such as urban planning, natural resource management, transportation, and defense. The increasing adoption of geospatial technologies, such as Geographic Information Systems (GIS) and Remote Sensing (RS), is also contributing to the market growth. The increasing demand for real-time and accurate geospatial data for decision-making and strategic planning is driving the market growth. The advancements in data collection and processing technologies, such as Artificial Intelligence (AI) and Machine Learning (ML), are enabling the extraction and analysis of valuable insights from geospatial data. The growing adoption of cloud-based geospatial platforms and services is also contributing to the market growth. Key market players include SafeGraph, Esri, PlanetObserver, Korem, L3Harris, Intellias, EOSDA, The Data Appeal Company, Echo Analytics, and Gravy Analytics.

A wide variety of state-wide GIS layers with periodic updates from various agencies and sources: Borough Parcels • North Slope Borough Boundaries • ACMP Coastal Districts • ACMP Coastal Zone Management • ACMP Permit Notification Area • ACMP Special Area Management Plan • ADEC Contingency Planning Regions • ADFG Game Management Units • ANCSA Corporations • Administrative Large Parcels • Alaska Seaward Boundary • Borough Boundary • Conservation System Units • DNR Regions • Election District 1994 • Election District 2002 • Election District 2006 • Incorporated City Boundary • Recording Districts • Rural Education Attendance Areas • Soil and Water Conservation Districts • State Park Units through ILMA Cultural • Cities • GNIS Concise Features • GNIS Features • GNIS Historical Features • GNIS Populated Places • Populated Places • Recording District Offices • USGS Place Names DNR Land Records • Base • Airstrips 63,360 • Alaska Seaward Boundary • BLM Monument - Digitized • BLM Monument - GCDB • BLM Monument - SDMS • Borough Boundary • Conservation System Units • Fiberoptic Cables 63,360 • Highways 63,360 • Hydrography 63,360 • Incorporated City Boundary • National Geodetic Survey Monuments • Pipelines 63,360 • Power Lines 63,360 • Railroads 63,360 • Recording Districts • Secondary Roads 63,360 • Sections • State Control Monuments • Survey Boundary • Telephone Lines 63,360 • Townships • Trails 63,360 • Land Estate • Agreement, Settlement, Reconveyance • Easements • Federal Actions • Land Disposal - Available • Land Disposal - Conveyed • Land Disposal - Other • Management Agreement • Mental Health Trust Land • Municipal Entitlement • Municipal Tideland • Native Allotment • Other Activities • Other State Acquired Land - LE • Permit or Lease - LE • RS2477 Trails • Resource Sale • State Selected or Top Filed Land - LE • State Tentatively Approved or Patented - LE • Mineral Estate • Agreement, Settlement, Reconveyance • Annual Placer Mining Application • Federal Actions • Federal Mining Claims • Leasehold Location • Management Agreement • Mental Health Trust Land • Mineral Order • Native Allotment • Oil & Gas Lease Sale Tracts • Other State Acquired Land - ME • Permit or Lease - ME • State Mining Claim • State Prospecting Site • State Selected or Top Filed Land - ME • State Tentatively Approved or Patented - ME • Well Site • Ownership • ANILCA Top Filed - All • Agreement, Settlement, Reconveyance • Federal Actions • Land Disposal - Conveyed • Management Agreement • Mental Health Trust Land • Municipal Entitlement • Municipal Tideland • Native Allotment • Other State Acquired Land - All • RS2477 Trails • State Selected Land - ALL • State Tentatively Approved or Patented - All • Surface Classification • Disposable Interest • General Land • Habitat Land • Legislatively Designated Areas • Miscellaneous • Recreation Land • Reserved Use • Special Use Land • Water Estate • Instream Flow Reservation • Subsurface Temporary Water Use Permit • Subsurface Water Rights • Surface Temporary Water Use Permit • Surface Water Rights Environmental • Environmental Sensitivity Index • ESI North Slope • ESI Northwest Arctic • NOAA Shorezone • Shorezone Biobands • Shorezone Combined Video and Photo Pts • Shorezone Photo Points • Shorezone Unit Information • Shorezone Video Points General Land Status • BLM Native Allotment • Borough Parcels • Federal Parcels • GLS Current Edition • State Land Activity by Case • State Land Activity by Feature • State Parcels • State, Federal, Borough Parcels Graticule • Latitude Longitude Lines 1 Degree • Latitude Longitude Lines 2 Degrees • NOAA Nautical Charts • PLSS Section Grid • PLSS Township Grid • State Plane Zone • USGS Quadrangle 250,000 • USGS Quadrangle 63,360 • UTM Zones Monuments • BLM Monument - Digitized • BLM Monument - GCDB • BLM Monument - SDMS • National Geodetic Survey Monuments • State Control Monuments Natural Resources • Aquaculture and Tidelands • Tidal Conveyances • Tidal Easements • Tidal Leases • Geothermal • Mining • Alaska Resource Data File • Coal Basin • Coal Districts • Coal Field • Coal Occurrence • Coal Unit • Federal Mining Claims • Mining Districts • Placer Districts • Significant Metalliferous Lode Deposits • State Mining Claim • State Mining Claim Closed • State Mining Lease • State Offshore Permit or Lease • State Prospecting Site • Oil and Gas • Oil And Gas Basins • Statewide Unit Tracts • Statewide PA Boundaries • Statewide PA Tracts • Statewide Sale Boundaries • Statewide Sale Tracts • Statewide Unit Boundaries • Water • Hydrologic Units • Navigable Water • Water Information Parks and Recreation Physical Features • Alaska Coast 1,000,000 • Alaska Coast 250,000 • Alaska Coast 63,360 • Alaska Coast 63,360 Excluding Small Islands • Alaska Coast Simplified • Canada Coast • Contours 1,000,000 • Elevation Points 1,000,000 • Glaciers 1,000,000 • Glaciers 2,000,000 • Hydrography 1,000,000 • Hydrography 2,000,000 • Hydrography 63,360 • Major Lakes • Major Rivers • Russia Coast • Summit Points 1,000,000 • Biotic • ANHP Biotic Areas • Anadromous Fish Line • Anadromous Fish Point • Caribou • Dall Sheep Point • Dall Sheep Polygon • Duck Habitat Areas • Eagle Point • Eagle Polygon • Moose Habitat Areas • Seabirds Point • Seabirds Polygon • Seal Point • Seal Polygon • Swan Polygon • Trumpeter Swan • Environmental • Geology • Beikman 1980 • Exploration Points • Geotech Photo Points • Hydrology Base • NHD Flowline • NHD Waterbody • Watersheds • Ice Study 2012 • Open Lead Points • Permafrost • Wetlands • Reference • Administrative • Game Management Units • Bridges • CEA Service Area • Crossings • Dam Sites • Legacy • Transmission Lines Corridor • Recreation • Trails • Transportation • Local Airstrip Points Transportation • Airstrips 63,360 • DOT Centerline Milepost • DOT Centerline Route • FAA Airports and Runways • Fiberoptic Cables 63,360 • Highways 63,360 • Iditarod Trail • Infrastructure 63,360 • Major Roads • Pipelines 63,360 • Power Lines 63,360 • RS2477 Trails • Railroads 1,000,000 • Railroads 2,000,000 • Railroads 63,360 • Roads 1,000,000 • Roads 2,000,000 • Secondary Roads 63,360 • State Park Trails through ILMA • Telephone Lines 63,360 • Trails 63,360 • Trans Alaska Pipeline System

The elevation features of the CanVec series include the elevation contours and elevation points. These entities are used to describe the relief of the Canadian Landmass. The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.

The Digital Geologic-GIS Map of the Mammoth Cave Quadrangle, Kentucky 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 (macv_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (macv_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 (macv_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (maca_abli_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (maca_abli_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 (macv_geology_metadata_faq.pdf). Please read the maca_abli_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: 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 (macv_geology_metadata.txt or macv_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 ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

This geodatabase reflects the U.S. Geological Survey’s (USGS) ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports in Africa. The geodatabase and geospatial data layers serve to create a new geographic information product in the form of a geospatial portable document format (PDF) map. The geodatabase contains data layers from USGS, foreign governmental, and open-source sources as follows: (1) mineral production and processing facilities, (2) mineral exploration and development sites, (3) mineral occurrence sites and deposits, (4) undiscovered mineral resource tracts for Gabon and Mauritania, (5) undiscovered mineral resource tracts for potash, platinum-group elements, and copper, (6) coal occurrence areas, (7) electric po ...

The land features of the CanVec series contains landscape features of Canada such as islands, shoreline delineation, wooded areas, saturated soil features, landform features (esker, sand, etc.). The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.

“Automatically Extracted Buildings” is a raw digital product in vector format created by NRCan. It consists of a single topographical feature class that delineates polygonal building footprints automatically extracted from airborne Lidar data, high-resolution optical imagery or other sources.

The land features of the CanVec series contains landscape features of Canada such as islands, shoreline delineation, wooded areas, saturated soil features, landform features (esker, sand, etc.). The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool. Related Products: Topographic Data of Canada - CanVec Series

The U.S. Geological Survey (USGS) has compiled a geodatabase containing mineral-related geospatial data for 10 countries of interest in Southwest Asia (area of study): Afghanistan, Cambodia, Laos, India, Indonesia, Iran, Nepal, North Korea, Pakistan, and Thailand. The data can be used in analyses of the extractive fuel and nonfuel mineral industries and related economic and physical infrastructure integral for the successful operation of the mineral industries within the area of study as well as the movement of mineral products across domestic and global markets. This geodatabase reflects the USGS ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports for the countries in the area of study. The geodatabase contains data feat ...

The administrative features of the CanVec series includes geopolitical regions (international, territorial and provincial) and populated place names. A wide selection of attributes describe the data. The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.

The resource management features of the CanVec series include power lines, communication lines, pipelines, valves, petroleum wells, wind-operated devices, transformer stations, ore extraction sites, aggregate extraction sites, peat extraction sites and oil and gas sites. The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool. Related Products: Topographic Data of Canada - CanVec Series

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Geographic Information System Analytics Market Size 2024-2028

The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.

What will be the Size of the GIS Analytics Market during the forecast period?

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The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.

How is this Geographic Information System Analytics Industry segmented?

The geographic information system analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  Retail and Real Estate
  Government
  Utilities
  Telecom
  Manufacturing and Automotive
  Agriculture
  Construction
  Mining
  Transportation
  Healthcare
  Defense and Intelligence
  Energy
  Education and Research
  BFSI


Components

  Software
  Services


Deployment Modes

  On-Premises
  Cloud-Based


Applications

  Urban and Regional Planning
  Disaster Management
  Environmental Monitoring Asset Management
  Surveying and Mapping
  Location-Based Services
  Geospatial Business Intelligence
  Natural Resource Management


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    South Korea


  Middle East and Africa

    UAE


  South America

    Brazil


  Rest of World

By End-user Insights

The retail and real estate segment is estimated to witness significant growth during the forecast period.

The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector, gover

The administrative features of the CanVec series include geopolitical regions (international, territorial and provincial) and populated place names. A wide selection of attributes describe the data. The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool. Related Products: Topographic Data of Canada - CanVec Series

Geospatial ETL Platform Market Outlook

According to our latest research, the global Geospatial ETL Platform market size reached USD 1.68 billion in 2024, demonstrating robust momentum driven by the increasing demand for spatial data integration and advanced analytics across industries. The market is set to expand at a CAGR of 13.7% from 2025 to 2033, with the forecasted market size projected to reach USD 5.23 billion by 2033. This growth trajectory is primarily attributed to the proliferation of location-based services, advancements in geospatial data infrastructure, and the rising importance of real-time decision-making in sectors such as government, utilities, and transportation.

One of the most significant growth factors fueling the Geospatial ETL Platform market is the exponential rise in the volume and variety of geospatial data generated from multiple sources, including satellites, IoT devices, drones, and mobile applications. Organizations are increasingly seeking sophisticated tools to extract, transform, and load (ETL) this data efficiently to derive actionable insights. The need for seamless integration of spatial and non-spatial data has become critical for enterprises aiming to enhance operational efficiency, optimize resource allocation, and improve situational awareness. As businesses realize the value of spatial analytics, investments in geospatial ETL solutions are accelerating, especially for applications such as urban planning, disaster management, and infrastructure monitoring.

Another key driver is the rapid adoption of cloud-based geospatial ETL platforms, which offer scalability, flexibility, and cost-effectiveness compared to traditional on-premises solutions. Cloud deployment enables organizations to process large datasets in real time, collaborate across geographies, and leverage advanced analytics powered by artificial intelligence and machine learning. This shift to the cloud not only reduces infrastructure costs but also empowers organizations to respond quickly to changing business needs. Furthermore, the integration of geospatial ETL platforms with emerging technologies such as 5G, edge computing, and real-time data streaming is unlocking new opportunities for innovation in sectors like smart cities, autonomous vehicles, and precision agriculture.

The increasing focus on regulatory compliance and data governance is also propelling the adoption of geospatial ETL platforms. Governments and regulatory bodies are mandating stringent data management practices, especially for critical infrastructure and public safety applications. Geospatial ETL solutions play a pivotal role in ensuring data quality, lineage, and security, thereby supporting organizations in meeting compliance requirements. Additionally, the growing awareness of the strategic value of location intelligence is encouraging enterprises to invest in advanced ETL solutions that can handle complex spatial data transformations and deliver high-quality, actionable insights for decision-making.

From a regional perspective, North America continues to dominate the Geospatial ETL Platform market, accounting for the largest revenue share in 2024, followed closely by Europe and the Asia Pacific. The presence of leading technology providers, strong government initiatives for smart infrastructure, and the high adoption rate of digital transformation strategies are contributing to the region's leadership. Asia Pacific, on the other hand, is witnessing the fastest growth, driven by rapid urbanization, expanding digital infrastructure, and increasing investments in geospatial technologies by governments and private enterprises. Latin America and the Middle East & Africa are also emerging as promising markets, supported by initiatives to modernize infrastructure and enhance public services through spatial data integration.

Component Analysis

The Geospatial ETL Platform market by component is segmented into software and services, each playing a distinct yet complementary role in enabling organizations to harness the power of spatial data. The software segment encompasses a wide array of ETL solutions designed to automate the extraction, transformation, and loading of geospatial data from diverse sources into target systems. These solutions are equipped with advanced features such as data cleansing, schema mapping, spatial data enrichment, and workflow automation, making them indispensable for enterprises seeking to streamline data integration pro

These data are part of a larger USGS project to develop an updated geospatial database of mines, mineral deposits and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, are currently being digitized on a state-by-state basis from the 7.5-minute (1:24,000-scale) and the 15-minute (1:48,000 and 1:62,500-scale) archive of the USGS Historical Topographic Maps Collection, or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. To date, the compilation of 500,000-plus point and polygon mine symbols from approximately 67,000 maps of 22 western states has been completed: Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Idaho (ID), Iowa (IA), Kansas (KS), Louisiana (LA), Minnesota (MN), Missouri (MO), Montana (MT), North Dakota (ND), Nebraska (NE), New Mexico (NM), Nevada (NV), Oklahoma (OK), Oregon (OR), South Dakota (SD), Texas (TX), Utah (UT), Washington (WA), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the western U.S., but an approximate time line of when these activities occurred. The data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. The data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done.

The Canadian Digital Elevation Model (CDEM) is part of Natural Resources Canada's altimetry system designed to better meet the users' needs for elevation data and products.

The CDEM stems from the existing Canadian Digital Elevation Data (CDED). In these data, elevations can be either ground or reflective surface elevations.

A CDEM mosaic can be obtained for a pre-defined or user-defined extent. The coverage and resolution of a mosaic varies according to latitude and to the extent of the requested area.

Derived products such as slope, shaded relief and colour shaded relief maps can also be generated on demand by using the Geospatial-Data Extraction tool. Data can then be saved in many formats.

The pre-packaged GeoTif datasets are based on the National Topographic System of Canada (NTS) at the 1:250 000 scale; the NTS index file is available in the Resources section in many formats.

The toponymic features of the CanVec series is a collection of proper nouns designating places and representations of the territory. This data come from provincial, territorial and Canadian toponymic databases. They are used in the CanVec Series for cartographic reference purposes and vary according to the scale of display. The toponymic features of the CanVec series can differ from the Canada's official geographical names. The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool. Users can obtain information about Canada's official toponyms at: https://www.nrcan.gc.ca/earth-sciences/geography/place-names/