This webmap displays the percent of population 25 years and over whose highest education completed is associate's degree. This webmap also contains the following layers: City of Corona Limits, State Boundary, County Boundary and Tract Boundary.

This U.S. Geological Survey (USGS) data release provides a digital geospatial database for the geologic map of the Hailey 1 x 2 degree quadrangle, Idaho (Worl and others, 1991). Attribute tables and geospatial features (lines and polygons) conform to the Geologic Map Schema (USGS NCGMP, 2020) and represent the geologic map as published in Idaho Geological Survey Geologic Map 10 (Worl and others, 1991). The database represents the geology for the 4.4-million-acre map plate at a publication scale of 1:250,000. References: Worl, R.G., Kiilsgaard, T.H., Bennett, E.H., Link, P.K., Lewis, R.S., Mitchell, V.E., Johnson, K.M., and Snyder, L.D., 1991, Geologic map of the Hailey 1 x 2 degree quadrangle, Idaho: Idaho Geological Survey, Geologic Map GM-10, scale 1:250,000; https://www.idahogeology.org/Product/GM-10. U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020, GeMS (Geologic Map Schema) - A standard format for the digital publication of geologic maps: U.S. Geological Survey Techniques and Methods, book 11, chap. B10, 74 p., https://doi.org//10.3133/tm11B10.

The maps and tables presented here represent potential variability of projected climate change across the conterminous United States during three 30-year periods in this century and emphasizes the importance of evaluating multiple signals of change across large spatial domains. Maps of growing degree days, plant hardiness zones, heat zones, and cumulative drought severity depict the potential for markedly shifting conditions and highlight regions where changes may be multifaceted across these metrics. In addition to the maps, the potential change in these climate variables are summarized in tables according to the seven regions of the fourth National Climate Assessment to provide additional regional context. Viewing these data collectively further emphasizes the potential for novel climatic space under future projections of climate change and signals the wide disparity in these conditions based on relatively near-term human decisions of curtailing (or not) greenhouse gas emissions. More information available at https://www.fs.usda.gov/nrs/pubs/rmap/rmap_nrs9.pdf.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

The Protected Areas Database of the United States (PAD-US) is a geodatabase, managed by USGS GAP, that illustrates and describes public land ownership, management and other conservation lands, including voluntarily provided privately protected areas. The State, Regional and LCC geodatabases contain two feature classes. The PADUS1_3_FeeEasement feature class and the national MPA feature class. Legitimate and other protected area overlaps exist in the full inventory, with Easements loaded on top of Fee. Parcel data within a protected area are dissolved in this file that powers the PAD-US Viewer. As overlaps exist, GAP creates separate analytical layers to summarize area statistics for "GAP Status Code" and "Owner Name". Contact the PAD-US Coordinator for more information. The lands included in PAD-US are assigned conservation measures that qualify their intent to manage lands for the preservation of biological diversity and to other natural, recreational and cultural uses; managed for these purposes through legal or other effective means. The geodatabase includes: 1) Geographic boundaries of public land ownership and voluntarily provided private conservation lands (e.g., Nature Conservancy Preserves); 2) The combination land owner, land manager, management designation or type, parcel name, GIS Acres and source of geographic information of each mapped land unit 3) GAP Status Code conservation measure of each parcel based on USGS National Gap Analysis Program (GAP) protection level categories which provide a measurement of management intent for long-term biodiversity conservation 4) IUCN category for a protected area's inclusion into UNEP-World Conservation Monitoring Centre's World Database for Protected Areas. IUCN protected areas are defined as, "A clearly defined geographical space, recognized, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values" and are categorized following a classification scheme available through USGS GAP; 5) World Database of Protected Areas (WDPA) Site Codes linking the multiple parcels of a single protected area in PAD-US and connecting them to the Global Community. As legitimate and other overlaps exist in the combined inventory GAP creates separate analytical layers to obtain area statistics for "GAP Status Code" and "Owner Name". PAD-US version 1.3 Combined updates include: 1) State, local government and private protected area updates delivered September 2011 from PAD-US State Data Stewards: CO (Colorado State University), FL (Florida Natural Areas Inventory), ID (Idaho Fish and Game), MA (The Commonwealth's Office of Geographic Information Systems, MassGIS), MO (University of Missouri, MoRAP), MT (Montana Natural Heritage Program), NM (Natural Heritage New Mexico), OR (Oregon Natural Heritage Program), VA (Department of Conservation and Recreation, Virginia Natural Heritage Program). 2) Select local government (i.e. county, city) protected areas (3,632) across the country (to complement the current PAD-US inventory) aggregated by the Trust for Public Land (TPL) for their Conservation Almanac that tracks the conservation finance movement across the country. 3) A new Date of Establishment field that identifies the year an area was designated or otherwise protected, attributed for 86% of GAP Status Code 1 and 2 protected areas. Additional dates will be provided in future updates. 4) A national wilderness area update from wilderness.net 5) The Access field that describes public access to protected areas as defined by data stewards or categorical assignment by Primary Designation Type. . The new Access Source field documents local vs. categorical assignments. See the PAD-US Standard Manual for more information: gapanalysis.usgs.gov/padus 6) The transfer of conservation measures (i.e. GAP Status Codes, IUCN Categories) and documentation (i.e. GAP Code Source, GAP Code Date) from PAD-US version 1.2 or categorical assignments (see PAD-US Standard) when not provided by data stewards 7) Integration of non-sensitive National Conservation Easement Database (NCED) easements from August 2011, July 2012 with PAD-US version 1.2 easements. Duplicates were removed, unless 'Stacked' = Y and multiple easements exist. 8) Unique ID's transferred from NCED or requested for new easements. NCED and PAD-US are linked via Source UID in the PAD-US version 1.3 Easement feature class. 9) Official (member and eligible) MPAs from the NOAA MPA Inventory (March 2011, www.mpa.gov) translated into the PAD-US schema with conservation measures transferred from PAD-US version 1.2 or categorically assigned to new protected areas. Contact the PAD-US Coordinator for documentation of categorical GAP Status Code assignments for MPAs. 10) Identified MPA records that overlap existing protected areas in the PAD-US Fee feature class (i.e. PADUS Overlap field in MPA feature class). For example, many National Wildlife Refuges and National Parks are also MPAs and are represented in the PAD-US MPA and Fee feature classes.

A fifteen degree grid in latitude and longitude covering the entire world

This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

The data release for the geologic and structure maps of the Wallace 1 x 2 degrees quadrangle, Montana and Idaho, is a Geologic Map Schema (GeMS)-compliant version that updates the GIS files for the geologic map published in U.S. Geological Survey (USGS) Miscellaneous Investigations Series Map I-1509-A (Harrison and others, 2000). The updated digital data present the attribute tables and geospatial features (points, lines and polygons) in the format that meets GeMS requirements. This data release presents the geologic map as shown on the plates and captured in geospatial data for the published map. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected in this version. The database represents the geology for the 16,754 square kilometer, geologically complex Wallace quadrangle in northern Idaho and western Montana, at a publication scale of 1:250,000. The map covers primarily Lake, Mineral, Sanders and Shoshone Counties, but also includes minor parts of Flathead, Lincoln, and Missoula Counties. These GIS data supersede those in the interpretive report: Harrison, J.E., Griggs, A.B., Wells, J.D., Kelley, W.N., Derkey, P.D., and EROS Data Center, 2000, Geologic and structure maps of the Wallace 1- x 2- degree quadrangle, Montana and Idaho: a digital database: U.S. Geological Survey Miscellaneous Investigations Series Map I-1509-A, https://pubs.usgs.gov/imap/i1509a/.

The data release for the geologic map of the Butte 1 degree x 2 degrees quadrangle, Montana, is a Geologic Map Schema (GeMS)-compliant version that updates the GIS files for the geologic map published in Montana Bureau of Mines and Geology Open File Report MBMG 363 (Lewis, 1998). The updated digital data present the attribute tables and geospatial features (points, lines and polygons) in the format that meets GeMS requirements. This data release presents the geologic map as shown on the plates and captured in geospatial data for the published map. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected in this version. The database represents the geology for the 4.4 million acre, geologically complex Butte 1 x 2 degrees quadrangle, at a publication scale of 1:250,000. The map covers parts of Deer Lodge, Granite, Jefferson, Lewis and Clark, Missoula, Powell, Ravalli, and Silver Bow Counties. These GIS data supersede those in the interpretive report: Lewis, R.S., 1998, Geologic map of the Butte 1 x 2 quadrangle, southwestern Montana: Montana Bureau of Mines and Geology Open-File Report 363, 16 p., 1 sheet, scale 1:250,000, http://www.mbmg.mtech.edu/mbmgcat/public/ListCitation.asp?pub_id=11212&.

Raw 1/10th Degree Wind Force Probability data for all wind speeds.

Create your own initiative by combining existing applications with a custom site. Use this initiative to form teams around a problem and invite your community to participate.

A six degree grid in latitude and longitude covering the entire world

The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updatesTitle: Degree Programs Complete by NM County, 2016Item Type: CSVSummary: Degree programs and leveled completed by program type and NM County, 2016Notes: Prepared by: Uploaded by EMcRae_NMCDCSource: New Mexico Dept of Workforce SolutionsFeature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=707bf05d8b454bcdb6efeef39de63427UID: 21Data Requested: Current and projected employment stats for workforce categories across the supply chainMethod of Acquisition: Data is publicly available for download by the NM Dept of Workforce SolutionsDate Acquired: March 2022Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 3Tags: PENDING

The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updatesTitle: Degree Programs Complete by NM County, 2019Item Type: CSVSummary: Degree programs and leveled completed by program type and NM County, 2019Notes: Prepared by: Uploaded by EMcRae_NMCDCSource: New Mexico Dept of Workforce SolutionsFeature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=258185b9b483447495e1071d6a2ec249UID: 21Data Requested: Current and projected employment stats for workforce categories across the supply chainMethod of Acquisition: Data is publicly available for download by the NM Dept of Workforce SolutionsDate Acquired: March 2022Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 3Tags: PENDING

This dataset attempts to represent the point locations of every educational program in the state of Minnesota that is currently operational and reporting to the Minnesota Department of Education. It can be used to identify schools, various individual school programs, school districts (by office location), colleges, and libraries, among other programs. Please note that not all school programs are statutorily required to report, and many types of programs can be reported at any time of the year, so this dataset is by nature an incomplete snapshot in time.

Maintenance of these locations is a result of an ongoing project to identify current school program locations where Food and Nutrition Services Office (FNS) programs are utilized. The FNS Office is in the Minnesota Department of Education (MDE). GIS staff at MDE maintain the dataset using school program and physical addresses provided by local education authorities (LEAs) for an MDE database called "MDE ORG". MDE GIS staff track weekly changes to program locations, along with comprehensive reviews each summer. All records have been reviewed for accuracy or edited at least once since January 1, 2020.

Note that there may remain errors due to the number of program locations and inconsistency in reporting from LEAs and other organizations. Some organization types (such as colleges and treatment programs) are not subject to annual reporting requirements, so various records included in this file may in fact be inactive or inaccurately located.

Note that multiple programs may occur at the same location and are represented as separate records. For example, an elementary and secondary school may be in the same building, but each has a separate record in the data layer. Users may leverage the "CLASS" and "ORGTYPE" attributes to filter and sort records according to their needs. In general, records at the same physical address will be located at the same coordinates.

This data is also available in CSV format. For that format only, OBJECTID and Shape columns are removed, and the Shape column is replaced by Latitude and Longitude columns.

This data is used for a broadband mapping initiative conducted by the Washington State Broadband Office. The source dataset has been modified from the existing Digital Divide Index published by Purdue University using Ookla Speedtest® open data for 2020 and the 5-year American Community Survey (ACS) dataset.

This is a map service displaying a graticule (latitude/longitude lines) in the Arctic. It can be used as an overlay alongside other layers for general reference.Map projection: WGS84 Arctic Polar Stereographic; standard parallel of 71 degrees; EPSG:3995; outer edge at 50 degrees north.Note: this will not display in the correct projection if you click on the thumbnail or choose "Add to Map". For a combined ArcGIS Online map displaying this service in Arctic projection along with other useful reference layers, please see: https://noaa.maps.arcgis.com/home/item.html?id=94f14eb0995e4bfc9d2439fc868345da

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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 data release for the geologic and structure map of the Choteau 1 x 2 degree quadrangle, western Montana, is a Geologic Map Schema (GeMS)-compliant version that updates the GIS files for the geologic map published in U.S. Geological Survey (USGS) Miscellaneous Investigations Series Map I-1300 (Mudge and others, 2001). The updated digital data present the attribute tables and geospatial features (lines and polygons) in the format that meets GeMS requirements. This data release presents geospatial data for the geologic map that is published as two plates. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected in this version. The database represents the geology for the 4.2 million acre, geologically complex Choteau 1 x 2 degree quadrangle, at a publication scale of 1:250,000. The map covers primarily Lewis and Clark, Teton, Powell, Missoula, Lake, and Flathead Counties, but also includes minor parts of Cascade County. These GIS data supersede those in the report: Mudge, M.R., Earhart, R.L., Whipple, J.W., Harrison, J.E., Munts, S.R., and Silkwood, J.T., 2001, Geologic and structure map of the Choteau 1 x 2 degree quadrangle, western Montana: a digital database: U.S. Geological Survey Miscellaneous Investigations Series Map I-1300, version 1.0, 38 p., scale 1:250,000, https://pubs.er.usgs.gov/publication/i1300.

Esri Health & Human Services grant program provides assistance for international Ministries of Health.While the relationship between health and place has long been recognized, modern tools make it possible to leverage geographic information to make faster and better decisions. GIS will help you to understand population needs, identify gaps and allocate your precious resources most effectively._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

The data release for the geologic terranes of the Hailey 1 x 2 degrees quadrangle and the western part of the Idaho Falls 1 x 2 degrees quadrangle, south-central Idaho is a Geologic Map Schema (GeMS)-compliant version that updates the GIS files for the geologic map published in U.S. Geological Survey (USGS) Bulletin 2064-A (Worl and Johnson, 1995). The updated digital data present the attribute tables and geospatial features (lines and polygons) in the format that meets GeMS requirements. This data release presents the geologic map as shown on the plate and captured in geospatial data for the published map. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected in this version. The database represents the geology for the 6.1 million-acre, geologically complex Hailey quadrangle and the western part of the Idaho Falls quadrangle, at a publication scale of 1:250,000. The map covers primarily Blaine, Camas, Custer and Elmore Counties, but also includes minor parts of Ada, Butte, Gooding, Lincoln, and Minidoka Counties. These GIS data supersede those in the interpretive report: Worl, R.G. and Johnson, K.M., 1995, Geology and mineral deposits of the Hailey 1 degree x 2 degrees quadrangle and the western part of the Idaho Falls 1 degree x 2 degrees quadrangle, south-central Idaho - an overview: U.S. Geological Survey, Bulletin 2064-A, scale 1:250,000, https://pubs.usgs.gov/bul/b2064-a/.