https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
Towns and Cities boundaries built from Built-up Areas.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
🇬🇧 영국 English How would you define the boundaries of a town or city in England and Wales in 2016? Maybe your definition would be based on its population size, geographic extent or where the industry and services are located. This was a question the ONS had to consider when creating a new statistical geography called Towns and Cities. In reality, the ability to delimit the boundaries of a city or town is difficult! Major Towns and Cities The new statistical geography, Towns and Cities has been created based on population size and the extent of the built environment. It contains 112 towns and cities in England and Wales, where the residential and/or workday population > 75,000 people at the 2011 Census. It has been constructed using the existing Built-Up Area boundary set produced by Ordnance Survey in 2011. This swipe map shows where the towns and cities and built-up areas are different. Just swipe the bar from left to right. The blue polygons are the towns and cities and the purple polygons are the built-up areas.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
INDEX VILLARIS: or, An Alphabetical Table of all the cities, market-towns, parishes, villages, and private seats in England and Wales was first published by John Adams in 1680. This dataset consists of a transcription of all 24,000 place-names listed in Index Villaris, together with the the symbols representing Adams's categorisation of each place and modern versions of the place-names and the counties and administrative hundred in which they lie or lay. It also comprises a transcription of the latitude and longitude recorded by Adams, and another set of coordinates generated by the application of a thin plate spline transformation calculated by matching some 2,000 place-names to the accurately-georeferenced CAMPOP Towns dataset.
The dataset has been corrected and refined to include linkage to other geospatial references such as GB1900 and OpenStreetMap, and this version is available as GeoJSON in the Linked Places Format.
The dataset can be viewed both on an interactive map and in reconstituted tabular form through the GitHub repository here.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Maybe your definition would be based on its population size, geographic extent or where the industry and services are located. This was a question the ONS had to consider when creating a new statistical geography called Towns and Cities. In reality, the ability to delimit the boundaries of a city or town is difficult! Major Towns and Cities The new statistical geography, Towns and Cities has been created based on population size and the extent of the built environment. It contains 112 towns and cities in England and Wales, where the residential and/or workday population > 75,000 people at the 2011 Census. It has been constructed using the existing Built-Up Area boundary set produced by Ordnance Survey in 2011. This swipe map shows where the towns and cities and built-up areas are different. Just swipe the bar from left to right. The blue polygons are the towns and cities and the purple polygons are the built-up areas.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
INDEX VILLARIS: or, An Alphabetical Table of all the cities, market-towns, parishes, villages, and private seats in England and Wales was first published by John Adams in 1680. This dataset consists of a transcription of all 24,000 place-names listed in Index Villaris, together with the the symbols representing Adams's categorisation of each place and modern versions of the place-names and the counties and administrative hundred in which they lie or lay. It also comprises a transcription of the latitude and longitude recorded by Adams, and another set of coordinates generated by the application of a thin plate spline transformation calculated by matching some 2,000 place-names to the accurately-georeferenced CAMPOP Towns dataset.
The dataset is being checked, corrected, and refined to include linkage to other geospatial references such as OpenStreetMap and Wikidata, and will in due course be made available in the Linked Places Format.
https://data.gov.tw/licensehttps://data.gov.tw/license
The China Post provides postal service-related information, primarily offering Excel files for counties and towns in Chinese and English (Hanyu Pinyin, csv format).
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
This file contains the digital vector boundaries for the Major Towns and Cities in England and Wales, as at December 2015. Version 2 includes centroid data in the attributes table.The boundaries available are: (BGG) Generalised Grid (50m) - clipped to the coastline (Mean High Water mark).Contains both Ordnance Survey and ONS Intellectual Property Rights.REST URL of ArcGIS for INSPIRE View Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Major_Towns_and_Cities_(Dec_2015)_Boundaries_V2/MapServerREST URL of ArcGIS for INSPIRE Feature DownloadService – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Major_Towns_and_Cities_Dec_2015_Boundaries_V2/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Major_Towns_and_Cities_Dec_2015_Boundaries_V2_2022/FeatureServer
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Monmouth Rebellion of 1685 prompted the government in London to undertake a survey the following year to establish the number of guest beds and quantity of stabling available across England and Wales for billeting soldiers. This dataset represents an attempt to identify and geolocate all of the place-names noted in that survey.
Transcription was undertaken for CAMPOP by Jacob Field, with funding provided by Leigh Shaw-Taylor and Dan Bogart. Stephen Gadd is responsible for place-name identification and geolocation, matching place-names as far as possible to the Index Villaris, 1680 dataset, GB1900 labels, and OpenStreetMap nodes.
PLEASE NOTE: THIS PRE-RELEASE DOES NOT CONTAIN ANY DATA
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
1:1,000,000 raster map of Northern Ireland with place names. A raster map is a static image displayed on screen which is suitable as background mapping. 1:1 000,000 Raster is smallest scale OSNI raster product giving an excellent overview of Northern Ireland. Published here for OpenData. By download or use of this dataset you agree to abide by the Open Government Data Licence.Please Note for Open Data NI Users: Esri Rest API is not Broken, it will not open on its own in a Web Browser but can be copied and used in Desktop and Webmaps
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
A CSV file containing the best fit lookup between 2011 Output Areas (OA) and Major Towns and Cities (TCITY) as at December 2015 in England and Wales. The TCITY statistical geography provides a precise definition of the major towns and cities in England and Wales. The geography has been developed specifically for the production and analysis of statistics, and is based on the Built-Up Areas geography that was created for the release of 2011 Census data. (File Size 6.5MB).Field Names – OA01CD, OA01CDOLD, TCITY15CD, TCITY15NM
Field Types – Text, Text, Text, Text
Field Lengths – 9, 10, 9, 25REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/OA01_TCITY15_EW_LU_a0e2581567bc425ba62da183b51ead0f/FeatureServer
For more information and an overview of best-fitting follow this link - https://geoportal.statistics.gov.uk/datasets/f0aac7ccbfd04cda9eb03e353c613faa/about
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
A best fit lookup between 2011 Output Areas (OA) and Major Towns and Cities (TCITY) as at December 2015 in England and Wales. The TCITY statistical geography provides a precise definition of the major towns and cities in England and Wales. The geography has been developed specifically for the production and analysis of statistics, and is based on the Built-Up Areas geography that was created for the release of 2011 Census data. (File Size - 4 MB). REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/OA11_TCITY15_EW_LU_65267a69bf06490d81a4ee1458747f48/FeatureServer
For more information and an overview of best-fitting follow this link - https://geoportal.statistics.gov.uk/datasets/f0aac7ccbfd04cda9eb03e353c613faa/about
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
A PDF map that shows the counties and unitary authorities in the United Kingdom as at 1 April 2023. (File Size - 583 KB)
Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
License information was derived automatically
Georeferenced map of 'Old and New Town of Edinburgh and Leith with the proposed docks' By John Ainslie (1804) as part of the Visualising Urban Geographies project- view other versions of the map at http://geo.nls.uk/urbhist/resources_maps.html. Scanned map. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2011-05-31 and migrated to Edinburgh DataShare on 2017-02-21.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The dataset and the validation are fully described in a Nature Scientific Data Descriptor https://www.nature.com/articles/s41597-019-0265-5
If you want to use this dataset in an interactive environment, then use this link https://mybinder.org/v2/gh/GeographerAtLarge/TravelTime/HEAD
The following text is a summary of the information in the above Data Descriptor.
The dataset is a suite of global travel-time accessibility indicators for the year 2015, at approximately one-kilometre spatial resolution for the entire globe. The indicators show an estimated (and validated), land-based travel time to the nearest city and nearest port for a range of city and port sizes.
The datasets are in GeoTIFF format and are suitable for use in Geographic Information Systems and statistical packages for mapping access to cities and ports and for spatial and statistical analysis of the inequalities in access by different segments of the population.
These maps represent a unique global representation of physical access to essential services offered by cities and ports.
The datasets travel_time_to_cities_x.tif (where x has values from 1 to 12) The value of each pixel is the estimated travel time in minutes to the nearest urban area in 2015. There are 12 data layers based on different sets of urban areas, defined by their population in year 2015 (see PDF report).
travel_time_to_ports_x (x ranges from 1 to 5)
The value of each pixel is the estimated travel time to the nearest port in 2015. There are 5 data layers based on different port sizes.
Format Raster Dataset, GeoTIFF, LZW compressed Unit Minutes
Data type Byte (16 bit Unsigned Integer)
No data value 65535
Flags None
Spatial resolution 30 arc seconds
Spatial extent
Upper left -180, 85
Lower left -180, -60 Upper right 180, 85 Lower right 180, -60 Spatial Reference System (SRS) EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long)
Temporal resolution 2015
Temporal extent Updates may follow for future years, but these are dependent on the availability of updated inputs on travel times and city locations and populations.
Methodology Travel time to the nearest city or port was estimated using an accumulated cost function (accCost) in the gdistance R package (van Etten, 2018). This function requires two input datasets: (i) a set of locations to estimate travel time to and (ii) a transition matrix that represents the cost or time to travel across a surface.
The set of locations were based on populated urban areas in the 2016 version of the Joint Research Centre’s Global Human Settlement Layers (GHSL) datasets (Pesaresi and Freire, 2016) that represent low density (LDC) urban clusters and high density (HDC) urban areas (https://ghsl.jrc.ec.europa.eu/datasets.php). These urban areas were represented by points, spaced at 1km distance around the perimeter of each urban area.
Marine ports were extracted from the 26th edition of the World Port Index (NGA, 2017) which contains the location and physical characteristics of approximately 3,700 major ports and terminals. Ports are represented as single points
The transition matrix was based on the friction surface (https://map.ox.ac.uk/research-project/accessibility_to_cities) from the 2015 global accessibility map (Weiss et al, 2018).
Code The R code used to generate the 12 travel time maps is included in the zip file that can be downloaded with these data layers. The processing zones are also available.
Validation The underlying friction surface was validated by comparing travel times between 47,893 pairs of locations against journey times from a Google API. Our estimated journey times were generally shorter than those from the Google API. Across the tiles, the median journey time from our estimates was 88 minutes within an interquartile range of 48 to 143 minutes while the median journey time estimated by the Google API was 106 minutes within an interquartile range of 61 to 167 minutes. Across all tiles, the differences were skewed to the left and our travel time estimates were shorter than those reported by the Google API in 72% of the tiles. The median difference was −13.7 minutes within an interquartile range of −35.5 to 2.0 minutes while the absolute difference was 30 minutes or less for 60% of the tiles and 60 minutes or less for 80% of the tiles. The median percentage difference was −16.9% within an interquartile range of −30.6% to 2.7% while the absolute percentage difference was 20% or less in 43% of the tiles and 40% or less in 80% of the tiles.
This process and results are included in the validation zip file.
Usage Notes The accessibility layers can be visualised and analysed in many Geographic Information Systems or remote sensing software such as QGIS, GRASS, ENVI, ERDAS or ArcMap, and also by statistical and modelling packages such as R or MATLAB. They can also be used in cloud-based tools for geospatial analysis such as Google Earth Engine.
The nine layers represent travel times to human settlements of different population ranges. Two or more layers can be combined into one layer by recording the minimum pixel value across the layers. For example, a map of travel time to the nearest settlement of 5,000 to 50,000 people could be generated by taking the minimum of the three layers that represent the travel time to settlements with populations between 5,000 and 10,000, 10,000 and 20,000 and, 20,000 and 50,000 people.
The accessibility layers also permit user-defined hierarchies that go beyond computing the minimum pixel value across layers. A user-defined complete hierarchy can be generated when the union of all categories adds up to the global population, and the intersection of any two categories is empty. Everything else is up to the user in terms of logical consistency with the problem at hand.
The accessibility layers are relative measures of the ease of access from a given location to the nearest target. While the validation demonstrates that they do correspond to typical journey times, they cannot be taken to represent actual travel times. Errors in the friction surface will be accumulated as part of the accumulative cost function and it is likely that locations that are further away from targets will have greater a divergence from a plausible travel time than those that are closer to the targets. Care should be taken when referring to travel time to the larger cities when the locations of interest are extremely remote, although they will still be plausible representations of relative accessibility. Furthermore, a key assumption of the model is that all journeys will use the fastest mode of transport and take the shortest path.
In 2023, almost nine million people lived in Greater London, making it the most populated ceremonial county in England. The West Midlands Metropolitan County, which contains the large city of Birmingham, was the second-largest county at 2.98 million inhabitants, followed by Greater Manchester and then West Yorkshire with populations of 2.95 million and 2.4 million, respectively. Kent, Essex, and Hampshire were the three next-largest counties in terms of population, each with around 1.89 million people. A patchwork of regions England is just one of the four countries that compose the United Kingdom of Great Britain and Northern Ireland, with England, Scotland and Wales making up Great Britain. England is therefore not to be confused with Great Britain or the United Kingdom as a whole. Within England, the next subdivisions are the nine regions of England, containing various smaller units such as unitary authorities, metropolitan counties and non-metropolitan districts. The counties in this statistic, however, are based on the ceremonial counties of England as defined by the Lieutenancies Act of 1997. Regions of Scotland, Wales, and Northern Ireland Like England, the other countries of the United Kingdom have their own regional subdivisions, although with some different terminology. Scotland’s subdivisions are council areas, while Wales has unitary authorities, and Northern Ireland has local government districts. As of 2022, the most-populated Scottish council area was Glasgow City, with over 622,000 inhabitants. In Wales, Cardiff had the largest population among its unitary authorities, and in Northern Ireland, Belfast was the local government area with the most people living there.
https://www.nconemap.gov/pages/termshttps://www.nconemap.gov/pages/terms
The 2020 TIGER/Line Shapefiles contain current geographic extent and boundaries of both legal and statistical entities (which have no governmental standing) for the United States, the District of Columbia, Puerto Rico, and the Island areas. This vintage includes boundaries of governmental units that match the data from the surveys that use 2020 geography (e.g., 2020 Population Estimates and the 2020 American Community Survey). In addition to geographic boundaries, the 2020 TIGER/Line Shapefiles also include geographic feature shapefiles and relationship files. Feature shapefiles represent the point, line and polygon features in the MTDB (e.g., roads and rivers). Relationship files contain additional attribute information users can join to the shapefiles. Both the feature shapefiles and relationship files reflect updates made in the database through September 2020. To see how the geographic entities, relate to one another, please see our geographic hierarchy diagrams here.Census Urbanized Areashttps://www2.census.gov/geo/tiger/TIGER2020/UACCensus Urban/Rural Census Block Shapefileshttps://www.census.gov/cgi-bin/geo/shapefiles/index.php2020 TIGER/Line and Redistricting shapefiles:https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2020.htmlTechnical documentation:https://www2.census.gov/geo/pdfs/maps-data/data/tiger/tgrshp2020/TGRSHP2020_TechDoc.pdfTIGERweb REST Services:https://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_restmapservice.htmlTIGERweb WMS Services:https://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_wms.htmlThe legal entities included in these shapefiles are:American Indian Off-Reservation Trust LandsAmerican Indian Reservations – FederalAmerican Indian Reservations – StateAmerican Indian Tribal Subdivisions (within legal American Indian areas)Alaska Native Regional CorporationsCongressional Districts – 116th CongressConsolidated CitiesCounties and Equivalent Entities (except census areas in Alaska)Estates (US Virgin Islands only)Hawaiian Home LandsIncorporated PlacesMinor Civil DivisionsSchool Districts – ElementarySchool Districts – SecondarySchool Districts – UnifiedStates and Equivalent EntitiesState Legislative Districts – UpperState Legislative Districts – LowerSubminor Civil Divisions (Subbarrios in Puerto Rico)The statistical entities included in these shapefiles are:Alaska Native Village Statistical AreasAmerican Indian/Alaska Native Statistical AreasAmerican Indian Tribal Subdivisions (within Oklahoma Tribal Statistical Areas)Block Groups3-5Census AreasCensus BlocksCensus County Divisions (Census Subareas in Alaska)Unorganized Territories (statistical county subdivisions)Census Designated Places (CDPs)Census TractsCombined New England City and Town AreasCombined Statistical AreasMetropolitan and Micropolitan Statistical Areas and related statistical areasMetropolitan DivisionsNew England City and Town AreasNew England City and Town Area DivisionsOklahoma Tribal Statistical AreasPublic Use Microdata Areas (PUMAs)State Designated Tribal Statistical AreasTribal Designated Statistical AreasUrban AreasZIP Code Tabulation Areas (ZCTAs)Shapefiles - Features:Address Range-FeatureAll Lines (called Edges)All RoadsArea HydrographyArea LandmarkCoastlineLinear HydrographyMilitary InstallationPoint LandmarkPrimary RoadsPrimary and Secondary RoadsTopological Faces (polygons with all geocodes)Relationship Files:Address Range-Feature NameAddress RangesFeature NamesTopological Faces – Area LandmarkTopological Faces – Area HydrographyTopological Faces – Military Installations
The population of the United Kingdom in 2023 was estimated to be approximately 68.3 million in 2023, with almost 9.48 million people living in South East England. London had the next highest population, at over 8.9 million people, followed by the North West England at 7.6 million. With the UK's population generally concentrated in England, most English regions have larger populations than the constituent countries of Scotland, Wales, and Northern Ireland, which had populations of 5.5 million, 3.16 million, and 1.92 million respectively. English counties and cities The United Kingdom is a patchwork of various regional units, within England the largest of these are the regions shown here, which show how London, along with the rest of South East England had around 18 million people living there in this year. The next significant regional units in England are the 47 metropolitan and ceremonial counties. After London, the metropolitan counties of the West Midlands, Greater Manchester, and West Yorkshire were the biggest of these counties, due to covering the large urban areas of Birmingham, Manchester, and Leeds respectively. Regional divisions in Scotland, Wales and Northern Ireland The smaller countries that comprise the United Kingdom each have different local subdivisions. Within Scotland these are called council areas whereas in Wales the main regional units are called unitary authorities. Scotland's largest Council Area by population is that of Glasgow City at over 622,000, while in Wales, it was the Cardiff Unitary Authority at around 372,000. Northern Ireland, on the other hand, has eleven local government districts, the largest of which is Belfast with a population of around 348,000.
This is a restricted dataset and this download is available to NIMA users only.
OSNI 250k contains a tabulated list of 330 main cities, towns and villages of Northern Ireland appearing on the 1:250,000 map. Irish grid references are incorporated in the table to allow the spatial location of the settlements to be plotted. The data has been captured by extracting all textual levels for the main cities, towns and villages of Northern Ireland appearing on the 1:250,000 map. OSNI 50k Gazetteer contains a list of all main text appearing on OSNI 1:50 000 scale Discoverer Map Series. Includes names of cities, towns, villages, water features, mountains, hills and forests of Northern Ireland. Irish Grid references are incorporated.
Users outside of the Spatial NI Portal please use Resource Locator 2.
http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence
The Town ward dataset includes the ward map; demographic profile; Public Health England local health report; Index of Multiple Deprivation (IMD) factsheet; Public health data; a ward hex map; and primary and secondary school census data.
Town ward covers a mixed and contrasting area. It includes the retail, commercial and business centre of Halifax, Dean Clough Business Park and the neighbourhood of Boothtown to the north, the mainly residential area of Siddal to the south, the steep escarpment of Beacon Hill to the east and the smaller hilltop communities of Southowram and Bank Top. It also includes Halifax's sporting and historic attractions, including The Shay and the Piece Hall, as well as the town's bus and railway stations.
For schools data at ward level, see Schools data by ward.
Keywords: Cities, Towns, Rivers, Buildings The most detailed street-level open data vector mapping product available, OS Open Map â Local is a great backdrop over which to display and analyse your data.
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
Towns and Cities boundaries built from Built-up Areas.