Abstract copyright UK Data Service and data collection copyright owner.
Background:Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Business creations and closures from the Inter-Departmental Business Register, a low-level geographic breakdown for the UK, quarterly data. These are official statistics in development
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,
Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically
We present the results of a major crowd-sourcing campaign to create open geographic data for over 260,000 solar PV installations across the UK, covering the vast majority of the capacity in the country. We focus in particular on capturing small-scale domestic solar PV, which accounts for a significant fraction of generation but was until now very poorly documented.
The data we introduce will enable decarbonisation at national scales, through forecasting and management of generation, and also serves as a training dataset for machine vision detection of new PV.
For a complete description please see the research paper describing the dataset. Please cite this paper in any academic use of the data.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This ONS Geography Linked Data site (http://statistics.data.gov.uk) is the access point for information on statistical geographies required to support the use of official statistics. It is designed to allow users to discover, view and use geospatial data.
This dataset contains grouping of areas and 'within' relationships to support hierarchical browsing.
This site is complementary to the ONS Open Geography Portal (https://geoportal.statistics.gov.uk). It allows access directly to data within the geography products, in machine-readable form and using an Application Programming Interface.
This ONS Geography Linked Data site is the access point for information on statistical geographies required to support the use of official statistics. It is designed to allow users to discover, view and use geospatial data.
This dataset contains grouping of areas and 'within' relationships to support hierarchical browsing.
This site is complementary to the ONS Open Geography Portal. It allows access directly to data within the geography products, in machine-readable form and using an Application Programming Interface.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Location quotients for 2015 for NUTS 1 regions, NUTS 2 areas and local authorities in Great Britain. Location quotients are available by industrial sections (local authorities) and up to SIC 2 industries (NUTS 2) and up to SIC 3 industries (NUTS 1).
The dataset is the lake polygons from the UK Lakes Portal (https://eip.ceh.ac.uk/apps/lakes/), originally based on OS PANORAMA but this dataset includes data from a number of sources. It has a basic set of attributes including the water body ID (WBID) as well as the computed area and perimeter of each lake. The WBID is commonly used across research institutions and is the same ID as used on the UK Lakes Portal, where more information can be found on each lake in this dataset. This is v3.6, which follows the same versioning as the underlying database. Although the database has seen the majority of the changes since version 1, the polygons have also been changed and improved over that time, mostly fixing issues with lake outlines, but also some new sites being added.
This statistic illustrates the share of coverage of mobile data services in England in 2019, by all operators. In 2019, 81 percent of England's geographical area was covered by all mobile data service (4G) operators.
This statistic illustrates the share of data network coverage in England in 2019, by operator. In 2019, EE had the largest geographic coverage of mobile data network, covering 93 percent of the landmass of England.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Super Output Areas are a geographic hierarchy designed to improve the reporting of small-area statistics.
The Lower Super Output Areas and Data Zones list contains 42,619 areas of the following constituent geographies:
Please visit ONS Beginner's Guide to UK Geography for more info.
The boundaries are available as either extent of the realm (usually this is the Mean Low Water mark but in some cases boundaries extend beyond this to include off shore islands) or
clipped to the coastline (Mean High Water mark).
This dataset contains gridded human population with a spatial resolution of 1 km x 1 km for the UK based on Census 2021 (Census 2022 for Scotland) and Land Cover Map 2021 input data. Data on population distribution for the United Kingdom is available from statistical offices in England, Wales, Northern Ireland and Scotland and provided to the public e.g. via the Office for National Statistics (ONS). Population data is typically provided in tabular form or, based on a range of different geographical units, in file types for geographical information systems (GIS), for instance as ESRI Shapefiles. The geographical units reflect administrative boundaries at different levels of detail, from Devolved Administration to Output Areas (OA), wards or intermediate geographies. While the presentation of data on the level of these geographical units is useful for statistical purposes, accounting for spatial variability for instance of environmental determinants of public health requires a more spatially homogeneous population distribution. For this purpose, the dataset presented here combines 2021/2022 UK Census population data on Output Area level with Land Cover Map 2021 land-use classes 'urban' and 'suburban' to create a consistent and comprehensive gridded population data product at 1 km x 1 km spatial resolution. The mapping product is based on British National Grid (OSGB36 datum).
The Register of Geographic Codes (RGC) is a key product that contains the definitive list of UK statistical geographies. ONS maintains the definitive set of statistical geographies, coordinates the issue of new codes, and maintains the relationship between active and archived code ranges on behalf of the Government Statistical Service. The RGC should be used in conjunction with the Code History Database, available to download separately.
Important Note: This item is in mature support as of July 2021. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This map is designed to be used as a general reference map for informational and educational purposes as well as a basemap by GIS professionals and other users for creating web maps and web mapping applications.The map was developed by National Geographic and Esri and reflects the distinctive National Geographic cartographic style in a multi-scale reference map of the world. The map was authored using data from a variety of leading data providers, including Garmin, HERE, UNEP-WCMC, NASA, ESA, USGS, and others.This reference map includes administrative boundaries, cities, protected areas, highways, roads, railways, water features, buildings and landmarks, overlaid on shaded relief and land cover imagery for added context. The map includes global coverage down to ~1:144k scale and more detailed coverage for North America down to ~1:9k scale.Map Note: Although small-scale boundaries, place names and map notes were provided and edited by National Geographic, boundaries and names shown do not necessarily reflect the map policy of the National Geographic Society, particularly at larger scales where content has not been thoroughly reviewed or edited by National Geographic.Data Notes: The credits below include a list of data providers used to develop the map. Below are a few additional notes:Reference Data: National Geographic, Esri, Garmin, HERE, iPC, NRCAN, METILand Cover Imagery: NASA Blue Marble, ESA GlobCover 2009 (Copyright notice: © ESA 2010 and UCLouvain)Protected Areas: IUCN and UNEP-WCMC (2011), The World Database on Protected Areas (WDPA) Annual Release. Cambridge, UK: UNEP-WCMC. Available at:www.protectedplanet.net.Ocean Data: GEBCO, NOAA
We provide measures of artificial intelligence technologies for the UK at the Travel-to-Work Area (TTWA) level. The data is derived from Lightcast Technologies (formerly known as Burning Glass) vacancy. A keyword-based algorithm is applied to the text of the vacancy data to characterise vacancies as being related to either cloud computing or machine leaning technologies (collectively grouped as AI).
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
We have assessed the 114 global SDG indicators reported on our National Reporting Platform and have presented the levels of geographic coverage for these data - at a headline indicator and disaggregation level.
Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:
Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.
The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.
The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.
End User Licence versions of MCS studies:
The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.
Sub-sample studies:
Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).
Release of Sweeps 1 to 4 to Long Format (Summer 2020)
To support longitudinal research and make it easier to compare data from different time points, all data from across all sweeps is now in a consistent format. The update affects the data from sweeps 1 to 4 (from 9 months to 7 years), which are updated from the old/wide to a new/long format to match the format of data of sweeps 5 and 6 (age 11 and 14 sweeps). The old/wide formatted datasets contained one row per family with multiple variables for different respondents. The new/long formatted datasets contain one row per respondent (per parent or per cohort member) for each MCS family. Additional updates have been made to all sweeps to harmonise variable labels and enhance anonymisation.
How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.
Secure Access datasets:
Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).
Secure Access versions of the MCS include:
The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application.
Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page).
The UK Lakes database contains data for over 40,000 lakes and ponds in the UK. It includes information on lake size, volume, depth, water chemistry, typology, geology, habitats, land cover and hydrological catchments, amongst many others areas. The database was initially compiled in 2004 and has been accumulating data since, becoming the main resource for lake data in the UK. The database is accompanied by spatial data of lake outlines (originally from OS PANORAMA) and catchments for all lakes over 1 hectare (delineated from a 50m flow grid). Data has been compiled from a number of different sources, from individuals to universities and research institutions.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Supporting dataset using data from Census, Pay As You Earn (PAYE) and National Benefits Database. Tables contain data on earnings progression and geographic mobility from tax year ending 2012 to tax year ending 2016, broken down by characteristics such as age, sex, ethnicity, qualification level and local authority. The dataset also includes regression model output tables.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Towns in England and Wales: towns list, classification, population and employment data.
A global self-hosted Market Research dataset containing all administrative divisions, cities, addresses, and zip codes for 247 countries. All geospatial data is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.
Use cases for the Global Zip Code Database (Market Research data)
Address capture and validation
Map and visualization
Reporting and Business Intelligence (BI)
Master Data Mangement
Logistics and Supply Chain Management
Sales and Marketing
Data export methodology
Our map data packages are offered in variable formats, including .csv. All geographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Product Features
Fully and accurately geocoded
Administrative areas with a level range of 0-4
Multi-language support including address names in local and foreign languages
Comprehensive city definitions across countries
For additional insights, you can combine the map data with:
UNLOCODE and IATA codes
Time zones and Daylight Saving Times
Why do companies choose our Market Research databases
Enterprise-grade service
Reduce integration time and cost by 30%
Weekly updates for the highest quality
Note: Custom geographic data packages are available. Please submit a request via the above contact button for more details.
Abstract copyright UK Data Service and data collection copyright owner.
Background: