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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

Hi, I'm Kiaran Ratcliffe a GIS Consultant within the Education Team at Esri UK. Esri is a company that creates and distributes GIS software, and my focus is on helping schools and universities access and use this software effectively. That means helping educators bring GIS into the classroom in ways that are engaging, inclusive, and relevant. We want students to leave school or university not just knowing how to use GIS, but understanding how to apply it to make a difference—socially, environmentally, and across all kinds of industries.It’s a really rewarding role. We get to support both students and teachers, and help them use modern spatial tools to explore the world, solve problems, and tell powerful stories with data.

ArcGIS Pro is Esri's main desktop GIS software and it is easy to enable student to install and use it on their personal laptops. All you have to do is:set students up with an Esri Identity in ArcGIS Onlinepoint student at the video explaining how to download ArcGIS ProStudent logs into ArcGIS Pro using their identityLets go through those steps in a bit more detail.

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GIS Market Size 2025-2029

The GIS market size is forecast to increase by USD 24.07 billion, at a CAGR of 20.3% between 2024 and 2029.

The Global Geographic Information System (GIS) market is experiencing significant growth, driven by the increasing integration of Building Information Modeling (BIM) and GIS technologies. This convergence enables more effective spatial analysis and decision-making in various industries, particularly in soil and water management. However, the market faces challenges, including the lack of comprehensive planning and preparation leading to implementation failures of GIS solutions. Companies must address these challenges by investing in thorough project planning and collaboration between GIS and BIM teams to ensure successful implementation and maximize the potential benefits of these advanced technologies.
By focusing on strategic planning and effective implementation, organizations can capitalize on the opportunities presented by the growing adoption of GIS and BIM technologies, ultimately driving operational efficiency and innovation.

What will be the Size of the GIS 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.
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The global Geographic Information Systems (GIS) market continues to evolve, driven by the increasing demand for advanced spatial data analysis and management solutions. GIS technology is finding applications across various sectors, including natural resource management, urban planning, and infrastructure management. The integration of Bing Maps, terrain analysis, vector data, Lidar data, and Geographic Information Systems enables precise spatial data analysis and modeling. Hydrological modeling, spatial statistics, spatial indexing, and route optimization are essential components of GIS, providing valuable insights for sectors such as public safety, transportation planning, and precision agriculture. Location-based services and data visualization further enhance the utility of GIS, enabling real-time mapping and spatial analysis.

The ongoing development of OGC standards, spatial data infrastructure, and mapping APIs continues to expand the capabilities of GIS, making it an indispensable tool for managing and analyzing geospatial data. The continuous unfolding of market activities and evolving patterns in the market reflect the dynamic nature of this technology and its applications.

How is this GIS Industry segmented?

The GIS 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


Type

  Telematics and navigation
  Mapping
  Surveying
  Location-based services


Device

  Desktop
  Mobile


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  Middle East and Africa

    UAE


  APAC

    China
    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.

The Global Geographic Information System (GIS) market encompasses a range of applications and technologies, including raster data, urban planning, geospatial data, geocoding APIs, GIS services, routing APIs, aerial photography, satellite imagery, GIS software, geospatial analytics, public safety, field data collection, transportation planning, precision agriculture, OGC standards, location intelligence, remote sensing, asset management, network analysis, spatial analysis, infrastructure management, spatial data standards, disaster management, environmental monitoring, spatial modeling, coordinate systems, spatial overlay, real-time mapping, mapping APIs, spatial join, mapping applications, smart cities, spatial data infrastructure, map projections, spatial databases, natural resource management, Bing Maps, terrain analysis, vector data, Lidar data, and geographic information systems.

The software segment includes desktop, mobile, cloud, and server solutions. Open-source GIS software, with its industry-specific offerings, poses a challenge to the market, while the adoption of cloud-based GIS software represents an emerging trend. However, the lack of standardization and interoperability issues hinder the widespread adoption of cloud-based solutions. Applications in sectors like public safety, transportation planning, and precision agriculture are driving market growth. Additionally, advancements in technologies like remote sensing, spatial modeling, and real-time mapping are expanding the market's scope.

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The Software segment was valued at USD 5.06 billion in 2019 and sho

Geostrat Report – The Sequence Stratigraphy and Sandstone Play Fairways of the Late Jurassic Humber Group of the UK Central Graben This non-exclusive report was purchased by the OGA from Geostrat as part of the Data Purchase tender process (TRN097012017) that was carried out during Q1 2017. The contents do not necessarily reflect the technical view of the OGA but the report is being published in the interests of making additional sources of data and interpretation available for use by the wider industry and academic communities. The Geostrat report provides stratigraphic analyses and interpretations of data from the Late Jurassic to Early Cretaceous Humber Group across the UK Central Graben and includes a series of depositional sequence maps for eight stratigraphic intervals. Stratigraphic interpretations and tops from 189 wells (up to Release 91) are also included in the report. The outputs as published here include a full PDF report, ODM/IC .dat format sequence maps, and all stratigraphic tops (lithostratigraphy, ages, sequence stratigraphy) in .csv format (for import into different interpretation platforms). In addition, the OGA has undertaken to provide the well tops, stratigraphic interpretations and sequence maps in an ESRI ArcGIS format that is intended to facilitate the integration of these data into projects and data storage systems held by individual organisations. As part of this process, the Geostrat well names have been matched as far as possible to the OGA well names from the OGA Offshore Wells shapefile (as provided on the OGA’s Open Data website) and the original polygon files have been incorporated into an ArcGIS project. All the files within the GIS folder of this delivery have been created by the OGA. OGA web feature services (WFSs) have been included in the map document in this delivery. They replace the use of a shapefile or feature class to represent block, licence and quadrant data. By using a WFS, the data is automatically updated when it becomes available via the OGA. A version of this delivery containing shapefiles for well tops, stratigraphic interpretations and sequence maps is available on the OGA’s Open Data website for use in other GIS software packages. All releases included in the Data Purchase tender process that have been made openly available are summarised in a mapping application available from the OGA website. The application includes an area of interest outline for each of the products and an overview of which wellbores have been included in the products.

Prior experience of GIS is variable, but a number of PGCE students and in-service teachers reported negative prior experiences with geospatial technology. Common complaints include a course focussed on data students found irrelevant, with learning exercises in the form of list-like instructions. The complexity of desktop GIS software is also often mentioned as off-putting.

Do you resonate with the following workflow?You've been making your maps using screengrabs from Google Maps and overlaying your annotations on PowerPoint or other third party software.You don't have control over how your map looks and what context you can show your readers.

Rail network in Glasgow showing the rail stations and rail lines. To view or use these files, a compression software and GIS software like ESRI ArcGIS or QGIS is needed. Data extracted 2013-01-10T13:48:15 Contains Ordnance Survey data (c) Crown Copyright 2013. Licence: None rail-station.zip - https://dataservices.open.glasgow.gov.uk/Download/Organisation/427258c9-6d38-4d1e-bc4e-246cdc02fd83/Dataset/b84dea58-4776-4bcd-93c5-650df256e609/File/50e8d50a-2a6d-42e1-9b1a-139ba1423d38/Version/45005081-779b-424d-a761-434577379f0f railway-line.zip - https://dataservices.open.glasgow.gov.uk/Download/Organisation/427258c9-6d38-4d1e-bc4e-246cdc02fd83/Dataset/b84dea58-4776-4bcd-93c5-650df256e609/File/b7a3e7b6-bd3e-4829-988d-f3c0ef41fb2c/Version/a8436afe-4c7e-4867-b3aa-33ccba6857f4

This volume contains the papers presented at GIS Research UK 2015 (GISRUK2015) held at the School of Geography, University of Leeds, on 15-17 April 2015.

[From The Landmap Project: Introduction, "http://www.landmap.ac.uk/background/intro.html"]

 A joint project to provide orthorectified satellite image mosaics of Landsat,
 SPOT and ERS radar data and a high resolution Digital Elevation Model for the
 whole of the UK. These data will be in a form which can easily be merged with
 other data, such as road networks, so that any user can quickly produce a
 precise map of their area of interest.

 Predominately aimed at the UK academic and educational sectors these data and
 software are held online at the Manchester University super computer facility
 where users can either process the data remotely or download it to their local
 network.

 Please follow the links to the left for more information about the project or
 how to obtain data or access to the radar processing system at MIMAS. Please
 also refer to the MIMAS spatial-side website,
 "http://www.mimas.ac.uk/spatial/", for related remote sensing materials.

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GIS In Telecom Sector Market Size 2025-2029

The GIS in telecom sector market size is valued to increase USD 2.35 billion, at a CAGR of 15.7% from 2024 to 2029. Increased use of GIS for capacity planning will drive the GIS in telecom sector market.

Major Market Trends & Insights

APAC dominated the market and accounted for a 28% growth during the forecast period.
By Product - Software segment was valued at USD 470.60 billion in 2023
By Deployment - On-premises segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 256.91 million
Market Future Opportunities: USD 2350.30 million
CAGR from 2024 to 2029: 15.7%

Market Summary

The market is experiencing significant growth as communication companies increasingly adopt Geographic Information Systems (GIS) for network planning and optimization. Core technologies, such as satellite imagery and location-based services, are driving this trend, enabling telecom providers to improve network performance and customer experience. One major application of GIS in the telecom sector is capacity planning, which allows companies to optimize their network infrastructure based on real-time data.
However, the integration of GIS with big data and other advanced technologies presents a communication gap between developers and end-users, requiring a focus on user-friendly interfaces and training programs. Additionally, regulatory compliance and data security remain significant challenges for the market. Despite these hurdles, the opportunities for innovation and improved operational efficiency make the market an exciting and evolving space.

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

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How is the GIS In Telecom Sector Market 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.

The global telecom sector's reliance on Geographic Information Systems (GIS) continues to expand, with the market for GIS in telecoms projected to grow significantly. According to recent industry reports, the market for GIS data visualization and spatial data infrastructure in telecoms has experienced a notable increase of 18.7% in the past year. Furthermore, the demand for advanced spatial analysis tools, such as building penetration analysis, geospatial asset management, and work order management systems, has risen by 21.3%. Telecom companies utilize GIS for network performance monitoring, data integration platforms, and network planning. For instance, GIS enables network design, radio frequency interference analysis, route optimization software, mobile network optimization, signal propagation modeling, and service area mapping.

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The Software segment was valued at USD 470.60 billion in 2019 and showed a gradual increase during the forecast period.

Additionally, it plays a crucial role in infrastructure management, location-based services, emergency response planning, maintenance scheduling, and telecom network design. Moreover, the adoption of 3D GIS modeling, LIDAR data processing, and customer location mapping has gained traction, contributing to the market's expansion. The future outlook is promising, with industry experts anticipating a 25.6% increase in the use of GIS for telecom network capacity planning and telecom outage prediction. These trends underscore the continuous evolution of the market and its applications across various sectors.

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Regional Analysis

APAC is estimated to contribute 28% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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In China, the construction of smart cities in Qingdao, Hangzhou, and Xiamen, among others, is driving the demand for Geographic Information Systems (GIS) in various sectors. By 2025, China aims to build more smart cities, leading to significant growth opportunities for GIS companies. Esri Global Inc., a leading player

Geostrat Report – The Sequence Stratigraphy and Sandstone Play Fairways of the Late Jurassic Humber Group of the UK Central Graben This non-exclusive report was purchased by the NSTA from Geostrat as part of the Data Purchase tender process (TRN097012017) that was carried out during Q1 2017. The contents do not necessarily reflect the technical view of the NSTA but the report is being published in the interests of making additional sources of data and interpretation available for use by the wider industry and academic communities. The Geostrat report provides stratigraphic analyses and interpretations of data from the Late Jurassic to Early Cretaceous Humber Group across the UK Central Graben and includes a series of depositional sequence maps for eight stratigraphic intervals. Stratigraphic interpretations and tops from 189 wells (up to Release 91) are also included in the report. The outputs as published here include a full PDF report, ODM/IC .dat format sequence maps, and all stratigraphic tops (lithostratigraphy, ages, sequence stratigraphy) in .csv format (for import into different interpretation platforms). In addition, the NSTA has undertaken to provide the well tops, stratigraphic interpretations and sequence maps in an ESRI ArcGIS format that is intended to facilitate the integration of these data into projects and data storage systems held by individual organisations. As part of this process, the Geostrat well names have been matched as far as possible to the NSTA well names from the NSTA Offshore Wells shapefile (as provided on the NSTA’s Open Data website) and the original polygon files have been incorporated into an ArcGIS project. All the files within the GIS folder of this delivery have been created by the NSTA. NSTA web feature services (WFSs) have been included in the map document in this delivery. They replace the use of a shapefile or feature class to represent block, licence and quadrant data. By using a WFS, the data is automatically updated when it becomes available via the NSTA. A version of this delivery containing shapefiles for well tops, stratigraphic interpretations and sequence maps is available on the NSTA’s Open Data website for use in other GIS software packages. All releases included in the Data Purchase tender process that have been made openly available are summarised in a mapping application available from the NSTA website. The application includes an area of interest outline for each of the products and an overview of which wellbores have been included in the products.

ESYS plc and the Department of Geomatic Engineering at University College London (UCL) have been funded by the British National Space Centre (BNSC) to develop a web GIS service to serve geographic data derived from remote sensing datasets. Funding was provided as part of the BNSC International Co-operation Programme 2 (ICP-2).

Particular aims of the project were to:

1. use Open Geospatial Consortium (OGC, recently renamed from the OpenGIS Consortium) technologies for map and data serving;

2. serve datasets for Europe and Africa, particularly Landsat TM and Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data;

3. provide a website giving access to the served data;

4. provide software scripts, etc., and a document reporting the data processing and software set-up methods developed during the project.

ICEDS was inspired in particular by the Committee on Earth Observing Satellites (CEOS) CEOS Landsat and SRTM Project (CLASP) proposal. An express intention of ICEDS (aim 4 in the list above) was therefore that the solution developed by ESYS and UCL should be redistributable, for example, to other CEOS members. This was taken to mean not only software scripts but also the methods developed by the project team to prepare the data and set up the server. In order to be compatible with aim 4, it was also felt that the use of Open Source, or at least 'free-of-cost' software for the Web GIS serving was an essential component. After an initial survey of the Web GIS packages available at the time , the ICEDS team decided to use the Deegree package, a free software initiative founded by the GIS and Remote Sensing unit of the Department of Geography, University of Bonn , and lat/lon . However the Red Spider web mapping software suite was also provided by IONIC Software - this is a commercial web mapping package but was provided pro bono by IONIC for this project and has been used in parallel to investigate the possibilities and limitations opened up by using a commercial package.

http://iceds.ge.ucl.ac.uk/

River network in Glasgow showing the river and coast lines. To view or use these files, a compression software and GIS software like ESRI ArcGIS or QGIS is needed. Data extracted 2013-10-15T14:30:45

Contains Ordnance Survey data © Crown Copyright and Database right (2018).

GIS files for the zoning system used in the National Trip End Model (NTEM).

Shapefiles for the zoning system used in the National Trip End Model (NTEM).

The files are provided in MapInfo and Shapefile format to allow viewing of the NTEM zoning system with GIS software. The smallest geographical zones of the model are based on the census Middle Super Output Area (MSOA).

The data are derived from interpretation of seismic reflection profiles within the offshore Corinth Rift, Greece (the Gulf of Corinth) integrated with IODP scientific ocean drilling borehole data from IODP Expedition 381 (McNeill et al., 2019a, 2019b). The data include rift fault coordinate (location, geometry) information and slip rate and extension rate information for the major faults. Seismic reflection data were published in Taylor et al. (2011) and in Nixon et al. (2016). Preliminary fault interpretations and rate data, prior to IODP drilling, were published in Nixon et al. (2016). Details of datasets: The data can be viewed in GIS software (ArcGIS, QGIS) or the Excel and .dbf files can be used for viewing of rate data and import of fault coordinates into other software. The 4 folders are for different time periods with shape files for the N-Dipping and S-Dipping Faults in the offshore Corinth Rift and respective slip and extension (horizontal) rates. The shapefiles are digitised fault traces for the basement offsetting faults, picked from the Multichannel Seismic Data collected by the R/V Maurice Ewing. Fault traces are segmented and each segment has an average throw (vertical) rate (Tavg) in mm/yr. The rates for the segments are averages based on measurements at the ends of each segment. The major fault trace segments also have slip-rates (slip_rate) and extension-rates (ext_rate or extension_) in mm/yr. All rates as well as the names for major faults can be located in the attribute table of the shape files along with X- and Y-coordinates. The coordinate system is WGS84 UTM Zone 34N. The shape files can be loaded into a GIS (ArcGIS, QGIS etc.) allowing mapping and visualization of the fault traces and their activity rates. In addition, the attribute tables are .dbf files found within each folder. These have also been provided as .xlsx (Excel) files which include the fault coordinate information, and slip rates and extension rates along the major faults. References McNeill, L.C., Shillington, D.J., Carter, G.D.O., and the Expedition 381 Participants, 2019a. Corinth Active Rift Development. Proceedings of the International Ocean Discovery Program, 381: College Station, TX (International Ocean Discovery Program). McNeill, L.C., Shillington, D.J., et al., 2019b, High-resolution record reveals climate-driven environmental and sedimentary changes in an active rift, Scientific Reports, 9, 3116. Nixon, C.W., McNeill, L.C., Bull, J.M., Bell, R.E., Gawthorpe, R.L., Henstock, T.J., Christodoulou, D., Ford, M., Taylor, B., Sakellariou, S. et al., 2016. Rapid spatiotemporal variations in rift structure during development of the Corinth Rift, central Greece. Tectonics, 35, 1225–1248. Taylor, B., J. R. Weiss, A. M. Goodliffe, M. Sachpazi, M. Laigle, and A. Hirn (2011), The structures, stratigraphy and evolution of the Gulf of Corinth Rift, Greece, Geophys. J. Int., 185(3), 1189–1219.

The 1885 UK parliamentary constituencies for Ireland were re-created in 2017 as part of a conference paper delivered at the Southern Irish Loyalism in Context conference at Maynooth University. The intial map only included the territory of the Irish Free State and was created by Martin Charlton and Jack Kavanagh. The remaining six counties of Ulster were completed by Eoin McLaughlin in 2018-19, the combined result is a GIS map of all the parliamentary constituecies across the island of Ireland for the period 1885-1918. The map is available in both ESRI Shapefile format and as a GeoPackage (GPKG). The methodology for creating the constituencies is outlined in detail below.

Methodology

A map showing the outlines of the 1855 – 1918 Constituency boundaries can be found on page 401 of Parliamentary Elections in Ireland, 1801-1922 (Dublin, 1978) by Brian Walker. This forms the basis for the creation of a set of digital boundaries which can then be used in a GIS. The general workflow involves allocating an 1885 Constituency identifier to each of the 309 Electoral Divisions present in the boundaries made available for the 2011 Census of Population data release by CSO. The ED boundaries are available in ‘shapefile’ format (a de facto standard for spatial data transfer). Once a Constituency identifier has been given to each ED, the GIS operation known as ‘dissolve’ is used to remove the boundaries between EDs in the same Constituency. To begin with Walker’s map was scanned at 1200 dots per inch in JPEG form. A scanned map cannot be linked to other spatial data without undergoing a process known as georeferencing. The CSO boundaries are available with spatial coordinates in the Irish National Grid system. The goal of georeferencing is to produce a rectified version of the map together with a world file. Rectification refers to the process of recomputing the pixel positions in the scanned map so that they are oriented with the ING coordinate system; the world file contains the extent in both the east-west and north-south directions of each pixel (in metres) and the coordinates of the most north-westerly pixel in the rectified image.

Georeferencing involves the identification of Ground Control Points – these are locations on the scanned map for which the spatial coordinates in ING are known. The Georeferencing option in ArcGIS 10.4 makes this a reasonably pain free task. For this map 36 GCPs were required for a local spline transformation. The Redistribution of Seats Act 1885 provides the legal basis for the constituencies to be used for future elections in England, Wales, Scotland and Ireland. Part III of the Seventh Schedule of the Act defines the Constituencies in terms of Baronies, Parishes (and part Parishes) and Townlands for Ireland. Part III of the Sixth Schedule provides definitions for the Boroughs of Belfast and Dublin.

The CSO boundary collection also includes a shapefile of Barony boundaries. This makes it possible code a barony in two ways: (i) allocated completely to a Division or (ii) split between two Divisions. For the first type, the code is just the division name, and for the second the code includes both (or more) division names. Allocation of these names to the data in the ED shapefile is accomplished by a spatial join operation. Recoding the areas in the split Baronies is done interactively using the GIS software’s editing option. EDs or groups of EDs can be selected on the screen, and the correct Division code updated in the attribute table. There are a handful of cases where an ED is split between divisions, so a simple ‘majority’ rule was used for the allocation. As the maps are to be used at mainly for displaying data at the national level, a misallocation is unlikely to be noticed. The final set of boundaries was created using the dissolve operation mentioned earlier. There were a dozen ED that had initially escaped being allocated a code, but these were quickly updated. Similarly, a few of the EDs in the split divisions had been overlooked; again updating was painless. This meant that the dissolve had to be run a few more times before all the errors have been corrected.

For the Northern Ireland districts, a slightly different methodology was deployed which involved linking parishes and townlands along side baronies, using open data sources from the OSM Townlands.ie project and OpenData NI.

This data is experimental, see the ‘Access Constraints or User Limitations’ section for more details. This dataset has been generalised to 10 metre resolution where it is still but the space needed for downloads will be improved.A set of UK wide estimated travel area geometries (isochrones), from Output Area (across England, Scotland, and Wales) and Small Area (across Northern Ireland) population-weighted centroids. The modes used in the isochrone calculations are limited to public transport and walking. Generated using Open Trip Planner routing software in combination with Open Street Maps and open public transport schedule data (UK and Ireland).The geometries provide an estimate of reachable areas by public transport and on foot between 7:15am and 9:15am for a range of maximum travel durations (15, 30, 45 and 60 minutes). For England, Scotland and Wales, these estimates were generated using public transport schedule data for Tuesday 15th November 2022. For Northern Ireland, the date used is Tuesday 6th December 2022.The data is made available as a set of ESRI shape files, in .zip format. This corresponds to a total of 18 files; one for Northern Ireland, one for Wales, twelve for England (one per English region, where London, South East and North West have been split into two files each) and four for Scotland (one per NUTS2 region, where the ‘North-East’ and ‘Highlands and Islands’ have been combined into one shape file, and South West Scotland has been split into two files).The shape files contain the following attributes. For further details, see the ‘Access Constraints or User Limitations’ section:AttributeDescriptionOA21CD or SA2011 or OA11CDEngland and Wales: The 2021 Output Area code.Northern Ireland: The 2011 Small Area code.Scotland: The 2011 Output Area code.centre_latThe population-weighted centroid latitude.centre_lonThe population-weighted centroid longitude.node_latThe latitude of the nearest Open Street Map “highway” node to the population-weighted centroid.node_lonThe longitude of the nearest Open Street Map “highway” node to the population-weighted centroid.node_distThe distance, in meters, between the population-weighted centroid and the nearest Open Street Map “highway” node.stop_latThe latitude of the nearest public transport stop to the population-weighted centroid.stop_lonThe longitude of the nearest public transport stop to the population-weighted centroid.stop_distThe distance, in metres, between the population-weighted centroid and the nearest public transport stop.centre_inBinary value (0 or 1), where 1 signifies the population-weighted centroid lies within the Output Area/Small Area boundary. 0 indicates the population-weighted centroid lies outside the boundary.node_inBinary value (0 or 1), where 1 signifies the nearest Open Street Map “highway” node lies within the Output Area/Small Area boundary. 0 indicates the nearest Open Street Map node lies outside the boundary.stop_inBinary value (0 or 1), where 1 signifies the nearest public transport stop lies within the Output Area/Small Area boundary. 0 indicates the nearest transport stop lies outside the boundary.iso_cutoffThe maximum travel time, in seconds, to construct the reachable area/isochrone. Values are either 900, 1800, 2700, or 3600 which correspond to 15, 30, 45, and 60 minute limits respectively.iso_dateThe date for which the isochrones were estimated, in YYYY-MM-DD format.iso_typeThe start point from which the estimated isochrone was calculated. Valid values are:from_centroid: calculated using population weighted centroid.from_node: calculated using the nearest Open Street Map “highway” node.from_stop: calculated using the nearest public transport stop.no_trip_found: no isochrone was calculated.geometryThe isochrone geometry.iso_hectarThe area of the isochrone, in hectares.Access constraints or user limitations.These data are experimental and will potentially have a wider degree of uncertainty. They remain subject to testing of quality, volatility, and ability to meet user needs. The methodologies used to generate them are still subject to modification and further evaluation.These experimental data have been published with specific caveats outlined in this section. The data are shared with the analytical community with the purpose of benefitting from the community's scrutiny and in improving the quality and demand of potential future releases. There may be potential modification following user feedback on both its quality and suitability.For England and Wales, where possible, the latest census 2021 Output Area population weighted centroids were used as the starting point from which isochrones were calculated.For Northern Ireland, 2011 Small Area population weighted centroids were used as the starting point from which isochrones were calculated. Small Areas and Output Areas contain a similar number of households within their boundaries. 2011 data was used because this was the most up-to-date data available at the time of generating this dataset. Population weighted centroids for Northern Ireland were calculated internally but may be subject to change - in the future we aim to update these data to be consistent with Census 2021 across the UK.For Scotland, 2011 Output Area population-weighted centroids were used as the starting point from which isochrones were calculated. 2011 data was used because this was the most up-to-date data available at the time of work.The data for England, Scotland and Wales are released with the projection EPSG:27700 (British National Grid).The data for Northern Ireland are released with the projection EPSG:29902 (Irish Grid).The modes used in the isochrone calculations are limited to public transport and walking. Other modes were not considered when generating this data.A maximum value of 1.5 kilometres walking distance was used when generating isochrones. This approximately represents typical walking distances during a commute (based on Department for Transport/Labour Force Survey data and Travel Survey for Northern Ireland technical reports).When generating Northern Ireland data, public transport schedule data for both Northern Ireland and Republic of Ireland were used.Isochrone geometries and calculated areas are subject to public transport schedule data accuracy, Open Trip Planner routing methods and Open Street Map accuracy. The location of the population-weighted centroid can also influence the validity of the isochrones, when this falls on land which is not possible or is difficult to traverse (e.g., private land and very remote locations).The Northern Ireland public transport data were collated from several files, and as such required additional pre-processing. Location data are missing for two bus stops. Some services run by local public transport providers may also be missing. However, the missing data should have limited impact on the isochrone output. Due to the availability of Northern Ireland public transport data, the isochrones for Northern Ireland were calculated on a comparable but slight later date of 6th December 2022. Any potential future releases are likely to contained aligned dates between all four regions of the UK.In cases where isochrones are not calculable from the population-weighted centroid, or when the calculated isochrones are unrealistically small, the nearest Open Street Map ‘highway’ node is used as an alternative starting point. If this then fails to yield a result, the nearest public transport stop is used as the isochrone origin. If this also fails to yield a result, the geometry will be ‘None’ and the ‘iso_hectar’ will be set to zero. The following information shows a further breakdown of the isochrone types for the UK as a whole:from_centroid: 99.8844%from_node: 0.0332%from_stop: 0.0734%no_trip_found: 0.0090%The term ‘unrealistically small’ in the point above refers to outlier isochrones with a significantly smaller area when compared with both their neighbouring Output/Small Areas and the entire regional distribution. These reflect a very small fraction of circumstances whereby the isochrone extent was impacted by the centroid location and/or how Open Trip Planner handled them (e.g. remote location, private roads and/or no means of traversing the land). Analysis showed these outliers were consistently below 100 hectares for 60-minute isochrones. Therefore, In these cases, the isochrone point of origin was adjusted to the nearest node or stop, as outlined above.During the quality assurance checks, the extent of the isochrones was observed to be in good agreement with other routing software and within the limitations stated within this section. Additionally, the use of nearest node, nearest stop, and correction of ‘unrealistically small areas’ was implemented in a small fraction of cases only. This culminates in no data being available for 8 out of 239,768 Output/Small Areas.Data is only available in ESRI shape file format (.zip) at this release.https://www.openstreetmap.org/copyright

The Unpublished Digital Surficial Geologic-GIS Map of Gateway National Recreation Area and Vicinity, New Jersey and New York is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (gwsf_geology.gdb), a 10.1 ArcMap (.MXD) map document (gwsf_geology.mxd), individual 10.1 layer (.LYR) files for each GIS data layer, an ancillary map information (.PDF) document (gate_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 (.HTML) formats, and a GIS readme file (gwsf_gis_readme.pdf). Please read the gwsf_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: New Jersey Geological Survey and New York State Museum. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (gwsf_metadata_faq.html; available at http://nrdata.nps.gov/geology/gri_data/gis/gate/gwsf_metadata_faq.html). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:100,000 and United States National Map Accuracy Standards features are within (horizontally) 127 meters or 416.7 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: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 18N, 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 Gateway National Recreation Area.

WARNINGThis data is provided here for specialist users only. The same information is available in a much more user-friendly format in the Services near me page on the main council website, and anyone interested in enrolling a child in school should see the page on Enrolment in Primary and Secondary Schools in DundeePurposeThese files are intended to be downloaded and used within systems such as SEEMIS that have access to a separate source of address information such as the Council's Corporate Address Gazetteer (CAG), One Scotland Gazetteer (OSG) or Ordnance Survey AddressBase.DescriptionThis collection includes the following files:Dundee_UPRN_SEED_lookup_all.csvDundee_UPRN_SEED_lookup_all_primary.csv - required for use in SEEMISDundee_UPRN_SEED_lookup_all_secondary.csv - required for use in SEEMISDundee_UPRN_SEED_lookup_denom_primary.csvDundee_UPRN_SEED_lookup_denom_secondary.csvDundee_UPRN_SEED_lookup_non_denom_primary.csvDundee_UPRN_SEED_lookup_non_denom_secondary.csvSchema.ini - explicitly sets UPRN datatype to text (with preceding zeroes) for use in excelOnly files 2 & 3 are required for use in SEEMIS. The other files are produced by the same process and are provided here in case they are useful. The combined files (1-3) will contain multiple records for each address. The remaining files (4-7) contain just one record for each address. Each file contains just two columnsUPRN - the Unique Property Reference Number of each address in DundeeSEED - the seedcode of the school catchment that the address is within Both columns are qualified with double quotes and separated with a comma. UPRNs are Unique Property Reference Numbers, as used in the Council's Corporate Address Gazetteer (CAG), the One Scotland Gazetteer (OSG) Or the Ordnance Survey AddressBase products.. For more information please see www.osg.scotSeedcodes are unique identifiers for Scottish Schools. A full list can be found at https://www.gov.scot/publications/school-contact-details/This collection is updated each night with the latest UPRNs from the Council's Corporate Address Gazetteer (CAG). SEED codes are taken from the Council's current catchment boundaries layer ("SchoolsAndCatchments - Current") which is updated as required. This typically happens around October or November before enrolment starts for the next school year each year. The data may therefore reflect the catchments that are due to take effect at the start of the next school year. For more details on the catchment data please see the the Council's current catchment boundaries layer ("SchoolsAndCatchments - Current") This data can be combined with Ordnance Survey OpenUPRN data to visualise it on a map in GIS software such as ArcGIS or QGIS. Or alternatively see the separate "UPRNs with school catchments" layer.