Digital elevation model for Ukraine from the Copernicus GLO-30 DEM product. Streamflow from the European Centre for Medium-range Weather Forecasting (ECMWF) made available as a map image layer from the ArcGIS Living Atlas produced by Esri.

Link to Geographic Information Services (GIS) for Lincoln County, South Dakota.

The Digital Geologic-GIS Map of Devils Tower National Monument, Wyoming 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 (deto_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 (deto_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 (deto_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 readme file (deto_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (deto_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 (deto_geology_metadata_faq.pdf). Please read the deto_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: 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 (deto_geology_metadata.txt or deto_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 1:4,800 and United States National Map Accuracy Standards features are within (horizontally) 4.1 meters or 13.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

Populated places in Ukraine from the Humanitarian OpenStreetMap Team and Humanitarian Data Exchange.

This page contains the help documentation for the GIS Open Data Portal. Refer to https://gisdata-csj.opendata.arcgis.com/pages/help.

These are the main layers that were used in mapping and analysis for the Santa Monica Mountains North Area Plan, which was adopted by the Board of Supervisors on May 4, 2021. Below are some links to important documents and to actually GIS data.Plan Website - This has links to the actual plan, maps and all project related materials. Click here for website.Online Web Mapping Application - This is the online application that shows all of the layers associated with the plan. These are the same layers that will be available for download below. Click here for the web mapping application.GIS Layers - The main GIS layers used in the application are available below.Below is a list of the GIS layers provided (shapefile format):Environmental (Zipped - 4.4 MB - click here)Habitat Connectivity - Essential Connectivity Area (ECA)Vegetation Sensitivity (includes ArcGIS .lyr file for version 10.0 and higher)Scenic Resources (Zipped - 1.3 MB - click here)State-Designated Scenic Highway 200-foot buffer (Please see 'State-Designated Scenic Highway' on our Open Data site here)Scenic RouteScenic Route 200-foot buffer

The Digital Bedrock Geologic-GIS Map of Lincoln Boyhood National Memorial and Vicinity, Indiana 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 (libo_bedrock_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 (libo_bedrock_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 (libo_bedrock_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 readme file (libo_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (libo_bedrock_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 (libo_bedrock_geology_metadata_faq.pdf). Please read the libo_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: Indiana 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 (libo_bedrock_geology_metadata.txt or libo_bedrock_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).

This service combines parcel data from various local government bodies in Alaska and describes a subset of input fields using consistent field names. This service was designed for use in statewide applications that only require specific types of land parcel information, and benefit from having this information in a single service with a consistent schema. Any changes to input parcel data will trigger this service to update. Note that many input services do not include a truly unique identifier, or sometimes any identifier at all. The 'parcel_id' field contains a record identifier carried over from the input service, or is null if there is none. The 'local_gov' value of any record can be used to reference an input parcel web service in the table below.During processing, a *mostly unique identifier is created, called 'feature_id'. Duplicate values will occur for records that have identical 'local_gov' and 'parcel_id' values and also identical geometries. These cases are extremely rare (< 0.003%), and for the vast majority of records 'feature_id' is unique. Any duplicate values will be attached to parcels in the exact same place.Please reference original parcel web services if your use case requires official, authoritative, or comprehensive land parcel information. Local Government Parcel Web Service

    Anchorage Municipality
    https://services2.arcgis.com/Ce3DhLRthdwbHlfF/ArcGIS/rest/services/PropertyInformation_Hosted/FeatureServer/0


    Denali Borough
    https://arcgis.dnr.alaska.gov/arcgis/rest/services/OpenData/Administrative_BoroughParcels/FeatureServer/1

    Bristol Bay Borough
    https://services8.arcgis.com/MqzStQjDmKoNl0E6/ArcGIS/rest/services/TaxParcels_Related/FeatureServer/0


    Dillingham Census Area
    https://services3.arcgis.com/gdLTz4xpy5IxwbSz/arcgis/rest/services/ParcelsOnline/FeatureServer/0


    Fairbanks North Star Borough
    https://services.arcgis.com/f4rR7WnIfGBdVYFd/ArcGIS/rest/services/Tax_Parcels/FeatureServer/0


    Haines Borough
    https://services3.arcgis.com/pMlUMMROURtJLUZt/ArcGIS/rest/services/ParcelsOnline/FeatureServer/0


    Juneau City & Borough
    https://services.arcgis.com/kpMKjjLr8H1rZ4XO/arcgis/rest/services/Juneau_Parcel_Viewer/FeatureServer/0


    Kenai Peninsula Borough
    https://services.arcgis.com/ba4DH9pIcqkXJVfl/ArcGIS/rest/services/Redacted_Parcels_view/FeatureServer/0


    Ketchikan Borough
    https://services2.arcgis.com/65jtiGuzdaRB5FxF/ArcGIS/rest/services/KetchikanAKFeatures/FeatureServer/0


    Kodiak Island Borough
    https://services1.arcgis.com/R5BNizttyFKxRSMm/arcgis/rest/services/KIB_Parcels/FeatureServer/0


    Matanuska-Susitna Borough
    https://maps.matsugov.us/map/rest/services/OpenData/Cadastral_Parcels/FeatureServer/0


    Nome Census Area
    https://services9.arcgis.com/Oi9vFzXc8ZcONgM6/arcgis/rest/services/Parcels_Joined_with_Taxroll_Symbolized_by_Exempt/FeatureServer/0


    North Slope Borough
    https://gis-public.north-slope.org/server/rest/services/Lama/Parcels_sql/FeatureServer/9


    Petersburg Borough
    https://services7.arcgis.com/RqATEQTpM1W1xU9c/ArcGIS/rest/services/Lots/FeatureServer/0


    Sitka City & Borough
    https://services7.arcgis.com/EozEvrS4g3SEhtG3/ArcGIS/rest/services/Sitka_Parcels_2022/FeatureServer/0


    Wrangell City & Borough
    https://services7.arcgis.com/7cBSaoaaRaH5ojZy/arcgis/rest/services/Parcels/FeatureServer/0


    Yakutat City & Borough
    https://services2.arcgis.com/gRKiTtxkoTx0gERB/ArcGIS/rest/services/ParcelsOnline/FeatureServer/0

Snapshot img

GIS In Telecom Sector Market Size 2025-2029

The GIS in telecom sector market size is forecast to increase by USD 2.35 billion at a CAGR of 15.7% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing adoption of Geographic Information Systems (GIS) for capacity planning in the telecommunications industry. GIS technology enables telecom companies to optimize network infrastructure, manage resources efficiently, and improve service delivery. Telecommunication assets and network management systems require GIS integration for efficient asset management and network slicing. However, challenges persist in this market. A communication gap between developers and end-users poses a significant obstacle.
Companies seeking to capitalize on opportunities in the market must focus on addressing these challenges, while also staying abreast of technological advancements and market trends. Effective collaboration between developers and end-users, coupled with strategic investments, will be essential for success in this dynamic market. Telecom companies must bridge this divide to ensure the development of user-friendly and effective GIS solutions. Network densification and virtualization platforms are key trends, allowing for efficient spectrum management and data monetization. Additionally, the implementation of GIS in the telecom sector requires substantial investment in technology and infrastructure, which may deter smaller players from entering the market.

What will be the Size of the GIS In Telecom Sector Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

In the dynamic telecom sector, GIS technology plays a pivotal role in customer analysis, network planning, and infrastructure development. Customer experiences are enhanced through location-based services and real-time data analysis, enabling telecom companies to tailor offerings and improve service quality. Network simulation and capacity planning are crucial for network evolution, with machine learning and AI integration facilitating network optimization and compliance with industry standards.
IOT connectivity and network analytics platforms offer valuable insights for smart city infrastructure development, with 3D data analysis and network outage analysis ensuring network resilience. Telecom industry partnerships foster innovation and collaboration, driving the continuous evolution of the sector. Consulting firms offer expertise in network compliance and network management, ensuring regulatory adherence and optimal network performance.

How is this GIS In Telecom Sector Industry segmented?

The gis in telecom sector industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Software
  Data
  Services


Deployment

  On-premises
  Cloud


Application

  Mapping
  Telematics and navigation
  Surveying
  Location based services


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Product Insights

The software segment is estimated to witness significant growth during the forecast period. In the telecom sector, the deployment of 5G networks is driving the need for advanced Geographic Information Systems (GIS) to optimize network performance and efficiency. GIS technology enables spatial analysis, network automation, capacity analysis, and bandwidth management, all crucial elements in the rollout of 5G networks. Large enterprises and telecom consulting firms are integrating GIS data into their operations for network planning, optimization, and troubleshooting. Machine learning and artificial intelligence are transforming GIS applications, offering predictive analytics and real-time network performance monitoring. Network virtualization and software-defined networking are also gaining traction, enhancing network capacity and improving network reliability and maintenance.

GIS software companies provide solutions for desktops, mobiles, cloud, and servers, catering to various industry needs. Smart city initiatives and location-based services are expanding the use cases for GIS in telecom, offering new opportunities for growth. Infrastructure deployment and population density analysis are critical factors in network rollout and capacity enhancement. Network security and performance monitoring are essential components of GIS applications, ensuring network resilience and customer experience management. Edge computing and network latency reduction are also signi

GIS database Odessa Agglomeration was collected within the PlanCoast Project and now is available on the site of UkrSCES (http://ims2.sea.gov.ua:8083/website/Agglomeration/viewer.htm). GIS database was created as a basis for spatial planning of the coastal zone and sea area of the Odessa agglomeration.

This data set contains small-scale base GIS data layers compiled by the National Park Service Servicewide Inventory and Monitoring Program and Water Resources Division for use in a Baseline Water Quality Data Inventory and Analysis Report that was prepared for the park. The report presents the results of surface water quality data retrievals for the park from six of the United States Environmental Protection Agency's (EPA) national databases: (1) Storage and Retrieval (STORET) water quality database management system; (2) River Reach File (RF3) Hydrography; (3) Industrial Facilities Discharges; (4) Drinking Water Supplies; (5) Water Gages; and (6) Water Impoundments. The small-scale GIS data layers were used to prepare the maps included in the report that depict the locations of water quality monitoring stations, industrial discharges, drinking intakes, water gages, and water impoundments. The data layers included in the maps (and this dataset) vary depending on availability, but generally include roads, hydrography, political boundaries, USGS 7.5' minute quadrangle outlines, hydrologic units, trails, and others as appropriate. The scales of each layer vary depending on data source but are generally 1:100,000.

The Unpublished Digital Geologic-GIS Map of Navajo National Monument and Vicinity, Arizona is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (nava_geology.gdb), a 10.1 ArcMap (.mxd) map document (nava_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (nava_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.txt) and FAQ (.pdf) formats, and a GIS readme file (nava_geology_gis_readme.pdf). Please read the nava_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@colostate.edu; see contact information below). The data is also available as a 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. Google Earth software is available for free at: http://www.google.com/earth/index.html. 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). 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 (nava_geology_metadata.txt or nava_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 1:125,000 and United States National Map Accuracy Standards features are within (horizontally) 63.5 meters or 208.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm). The GIS data projection is NAD83, UTM Zone 12N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth. The data is within the area of interest of Navajo National Monument.

Commonage GIS Dataset. Published by Department of Housing, Local Government and Heritage. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Commonage Framework Planning was a joint initiative between the National Parks and Wildlife Service and the Department of Agriculture and Food. Teams combining agricultural and ecological skills to assess the sustainable use of these areas have surveyed all known commonage areas in Ireland.

To date in excess of 4,400 plans have been prepared, covering more than 440,000 hectares. Where necessary, destocking (removal of some of the stock kept on commonage) was prescribed to ensure recovery of the vegetation. These plans have been implemented through REPS, AEOS and the NPWS Farm Plan Scheme, as relevant, from 1999 - 2012.

A commitment has been made to monitor the condition of commonages to demonstrate, in particular, that initiatives are delivering recovery in overgrazed areas and that undergrazing is not becoming a problem. Ireland also has obligations to monitor the state of SACs containing uplands and peatlands in non-commonage areas. This involves a reassessment of habitats in commonage areas, some of which were assessed as early as 1999, and also non-commonage areas.

Planning teams comprising both agriculturalists and environmentalists have been trained and re-surveys have been completed in commonage blocks in Counties Mayo, Galway, Cork, Kerry, Donegal, Sligo, Leitrim, Tipperary, Limerick and Louth between 2004 and 2010. Monitoring reports have been forwarded to the EU Commission highlighting the findings and trends. Additional survey work in 2007 focussed on Counties Mayo, Donegal and Kerry. In 2008, all commonage that had a destocking of greater than 50% were re-assessed.

In this context GIS files were set up to describe: - Destocking rates assigned to Agricultural Units - Habitat types and damage categories assigned to Agricultural Sub-Units and - Locations of Base-Stations and habitat types / damage categories recorded at these stations

A review of all the Commonage Framework Plans, setting sustainable stocking rates, will conclude in 2012 and will be communicated to all shareholders by the Department of Agriculture, Food and the Marine. This information is not contained here....

The Digital Geologic-GIS Map of Santa Cruz 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 (scis_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 (scis_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 (scis_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 (scis_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 (scis_geology_metadata.txt or scis_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).

The Digital Surficial Geologic-GIS Map of Delaware Water Gap National Recreation Area and Vicinity, New Jersey, Pennsylvania and 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 (dewa_surficial_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 (dewa_surficial_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 (dewa_surficial_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 (dewa_surficial_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (dewa_surficial_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 (dewa_surficial_geology_metadata_faq.pdf). Please read the dewa_surficial_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: New Jersey Geological Survey, Pennsylvania Geological Survey, New York State Museum and 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 (dewa_surficial_geology_metadata.txt or dewa_surficial_geology_metadata_faq.pdf). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

The web map is in kilograms(kg). The darker green represents higher pesticide usage, the lighter green represents lower pesticide usage.

The Irrigated Lands data comes from USSS-AB and is being used for research at Kansas State University. The dataset is for the 5 major crops in Ukraine which are maize, wheat, barley, sunflowers, and soybeans. For each major crop, there are 3 categories. Those categories are Harvested Area (thsd.ha), Volume of Production (thsd.centner), and Yield (centner per ha of the harvested area). Here is the Metadata for this Data:Oblast = OblastMaize_Har = Maize Harvested Area, (thsd.ha)Maize_Vol = Maize Volume of Production, (thsd.centners)Maize_Yie = Maize Yield, (centner per ha of the harvested area)Wheat_Har = Wheat Harvested Area, (thsd.ha)Wheat_Vol = Wheat Volume of Production, (thsd.centners)Wheat_Yie = Wheat Yield, (centner per ha of the harvested area)\Barley_Ha = Barley Harvested Area, (thsd.ha)Barley_Vo = Barley Volume of Production, (thsd.centners)Barley_Yi = Barley Yield, (centner per ha of the harvested area)Sunflower_ = Sunflower Harvested Area, (thsd.ha)Sunflower1 = Sunflower Volume of Production, (thsd.centners)Sunflower_1 = Sunflower Yield, (centner per ha of the harvested area)Soybean_H = Soybean Harvested Area, (thsd.ha)Soybean_V = Soybean Volume of Production, (thsd.centners)Soybean_Y = Soybean Yield, (centner per ha of the harvested area)

The dataset represents pesticide data by oblast for 2021.

A lookup file between unitary authorities and Department for Children Education Lifelong Learning and Skills areas in Wales as at 31st December 2023. (File Size - 16 KB)Field Names - UA23CD, UA23NM, DCELL23CD, DCELL23NMField Types - Text, Text, Text, TextField Lengths - 9, 17, 9, 20

Sunflower production in Ukraine by oblast for 2015-2023 as reported by the State Statistics Service of Ukraine (Derzhstat). Data from 2023 is mapped while other years are accessible through the attribute table or the specially configured pop-up window.