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.

A story map on how and why the boundaries were made, and a guide to their use for statistics

Towns and Cities boundaries built from Built-up Areas.

This dataset is about books. It has 1 row and is filtered where the book is Historic towns : maps and plans of towns and cities in the British Isles, with historical commentaries, from earliest times to 1800. It features 7 columns including author, publication date, language, and book publisher.

This file contains names and codes for Major Towns and Cities (TCITY) in England and Wales as at December 2015. (File size - 16KB).

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.

Field Names - TCITYCD, TCITYNM, FID

Field Types - Text, Text, Number

Field Lengths - 9, 20

FID = The FID, or Feature ID is created by the publication process when the names and codes / lookup products are published to the Open Geography portal. REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Major_Towns_and_Cities_Dec_2015_Names_and_Codes_in_England_and_Wales_2022/FeatureServer

This is a collection of Opportunity Maps for mine water heat, produced for the Department of Energy Security and Net Zero, and their contractor AECOM, covering the following 10 cities: Birmingham, Bristol, Coventry, Leeds, Manchester, Newcastle, Nottingham, Sheffield, Stoke-on-Trent, Sunderland. Also included is a report outlining the methodology criteria for the opportunity map assessment. The dataset has been developed using Coal Authority data, consisting of Underground Workings data, and Environmental Data, and a bespoke assessment methodology. It consists of 15m x 15m square grid cells, containing attribution of Good, Possible, Challenging on the basis of the opportunity method criteria and expert input. In November 2024, the Coal Authority changed its name to the Mining Remediation Authority to better reflect its mission and continued commitment to environmental sustainability, safety, and community support.

This is a collection of simple maps in PDF format that are designed to be printed off and used in the classroom. The include maps of Great Britain that show the location of major rivers, cities and mountains as well as maps of continents and the World. There is very little information on the maps to allow teachers to download them and add their own content to fit with their lesson plans. Customise one print out then photocopy them for your lesson. data not available yet, holding data set (7th August). Other. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2012-08-07 and migrated to Edinburgh DataShare on 2017-02-22.

This global accessibility map enumerates land-based travel time to the nearest densely-populated area for all areas between 85 degrees north and 60 degrees south for a nominal year 2015. Densely-populated areas are defined as contiguous areas with 1,500 or more inhabitants per square kilometre or a majority of built-up land cover types coincident with a population centre of at least 50,000 inhabitants. This map was produced through a collaboration between MAP (University of Oxford), Google, the European Union Joint Research Centre (JRC), and the University of Twente, Netherlands.The underlying datasets used to produce the map include roads (comprising the first ever global-scale use of Open Street Map and Google roads datasets), railways, rivers, lakes, oceans, topographic conditions (slope and elevation), landcover types, and national borders. These datasets were each allocated a speed or speeds of travel in terms of time to cross each pixel of that type. The datasets were then combined to produce a "friction surface"; a map where every pixel is allocated a nominal overall speed of travel based on the types occurring within that pixel. Least-cost-path algorithms (running in Google Earth Engine and, for high-latitude areas, in R) were used in conjunction with this friction surface to calculate the time of travel from all locations to the nearest (in time) city. The cities dataset used is the high-density-cover product created by the Global Human Settlement Project. Each pixel in the resultant accessibility map thus represents the modelled shortest time from that location to a city. Authors: D.J. Weiss, A. Nelson, H.S. Gibson, W. Temperley, S. Peedell, A. Lieber, M. Hancher, E. Poyart, S. Belchior, N. Fullman, B. Mappin, U. Dalrymple, J. Rozier, T.C.D. Lucas, R.E. Howes, L.S. Tusting, S.Y. Kang, E. Cameron, D. Bisanzio, K.E. Battle, S. Bhatt, and P.W. Gething. A global map of travel time to cities to assess inequalities in accessibility in 2015. (2018). Nature. doi:10.1038/nature25181

Processing notes: Data were processed from numerous sources including OpenStreetMap, Google Maps, Land Cover mapping, and others, to generate a global friction surface of average land-based travel speed. This accessibility surface was then derived from that friction surface via a least-cost-path algorithm finding at each location the closest point from global databases of population centres and densely-populated areas. Please see the associated publication for full details of the processing.

Source: https://map.ox.ac.uk/research-project/accessibility_to_cities/

Great Britain's (England, Scotland, Wales) cities (e.g. London, Birmingham, Edinburgh) named and represented as point features with an indicative bounding box. This data is often used for geocoding, service delivery and statistical analysis. OS Cities Data is available in a number of Ordnance Survey (OS) products: OS Open Names (bounding box and point geometry), OS Names API, MasterMap Topography Layer (point geometry), Vector Map Local (point geometry) and Vector Map District (point geometry). Small-scale cartographic representations are also available in OS cartographic products. All data is collected by Ordnance Survey as part of their role as the National Mapping Agency of Great Britain.

Village Greens, named sites and registration details collated by then Office for the Deputy Prime Minister (2004/5) now The Department for Levelling Up, Housing and Communities. Please note, this data can only be viewed between map scales of 1:26,000 and 1:500,000. Registered town or village greens recorded in registers held by commons registration authorities in England and captured during a survey c.1994. Natural England are not the data custodian/owner of the latest boundaries and do not maintain a managed dataset. Town and Village Greens boundaries are the responsibility of the local authorities across England. Please search for the local authority definitive boundaries on data.gov.uk Data available only on request from mailto:data.services@naturalengland.org.uk Attribution statement: Natural England are able to share the Town and Village Greens data displayed on MAGIC on request on a case by case basis under a Non Commercial Government Licence, but with the caveat that the boundaries are indicative and extremely out of date (captured circa 1994). The boundaries were collated into a single national dataset as part of a Defra project. Natural England are not the data custodian/owner of the latest boundaries and do not maintain a managed dataset. Town and Village Greens boundaries are the responsibility of the local authorities across England. Please search for the local authority definitive boundaries on data.gov.uk

A PDF map that shows the counties and unitary authorities in the United Kingdom as at 1 April 2023. (File Size - 583 KB)

(:unav)...........................................

Georeferenced from old maps - this gives an approximation of the land lost since Roman times. This is not a totally accurate depiction of the land lost since Roman times, so it may not match up precisely with base layer maps.http://www.eastriding.gov.uk/coastalexplorer/documents.htmland The Lost Towns of the Yorkshire Coast, at : https://www.archive.org/stream/losttownsofyorks00sheprich#page/10/mode/2up

Map of the Register of Town or Village Greens. As a Commons Registration Authority, Southampton City Council is responsible for maintaining the Registers of Common Land and Village Greens. This register is a statutory document (Commons Registration Act, 1965) and shows all such registered land in our area.

The public rights of way (PROW) in Northumberland, polylines illustrating approximate positions of rights of way recorded on the Definitive Map of Public Rights of Way for Northumberland. There are over 3200 miles of public rights of way in Northumberland. They are a great resource to help you exercise, relax or enjoy the outstanding quality of the Northumberland countryside and towns and villages. This data will help you to make the most of the public rights of way. It contains information on every recorded public right of way in the County. It shows routes which can be used by walkers (public footpaths, bridleways and byways) and horse riders and cyclists too (public bridleways and byways). You can use the data to plan your countryside visit, discover information about public rights of way in your locality and report problems with the rights of way network to the Council. If you are going to use the map for conveyance or other legal purposes please contact the Council first. The Public Rights of Way data shown here are only accurate in to a scale of 1:10,000, This is not a substitute for the Definitive Map of Public Rights of Way.

This project systematically processed high-resolution and manuscript historical maps to unlock a dormant body of information about the historical development of cities and regions during periods of structural economic transformation.

The work was organised across six interlinked work packages, combining empirical and theoretical analysis in the UK, France, and Canada. Outputs included peer-reviewed publications and robust algorithms for extracting spatial data from historical sources, contributing valuable tools and insights to the fields of urban economics and economic history.

This data package contains three segmentation codes designed to extract features and segment historical maps.

Little is known about the patterns of city development during the structural transformation of economies. This project will systematically process high-resolution and manuscript historical maps to make a dormant body of information about our cities' and regions' past accessible.

The proposed research will advance our understanding of long-run urban growth through the development of three innovative methodologies, which will overcome practical limitations of historical data sources: 1) A technique to extract land use patterns from historical colour maps applied to France (1750-1950); 2) A recognition algorithm to detect, tag and geo-locate points of interest in historical high-quality maps of the 70 largest urban centre in England and Wales; 3) An algorithm to geo-locate address information from Micro-censuses and trade registers.

We have identified four main research questions that will be developed in the following separate research projects. In Project 1, the main question is: what are the long-term empirical patterns of urban development, most notably the persistence of the spatial organisation of economic activity and the role of building infrastructure in shaping such persistence? In Project 2, the main question is: How do environmental disamenities and their unequal distribution within cities affect the spatial organisation of consumption amenities and production? In Project 3, the main question is: Do cities grow towards their bad parts, their neighbourhoods with the lowest environmental amenities? In Project 4, the main question is: How does vertical growth and advances in building technologies affect the spatial organisation of cities?

To address these research questions, we will organise our workflow in six inter-connected work packages (WP):

WP1--Classification of land use in France (1750-2015): The objective of WP1 will be to recover land use information at a fine scale from digitised maps using state-of-the-art machine learning techniques;

WP2--Digitisation of micro-features embedded in Ordnance Survey (OS) city maps of England and Wales (1870-1960);

WP3--Geo-localization of residents and production units in England and Wales (1851-1911);

WP4--Dynamic model of city growth with persistent building stock: WP4 builds a general equilibrium model of spatial economic activity that embeds the durability of housing and infrastructure and exploits the three hundred years of population settlement data produced in WP1;

WP5--Pollution and the long-run development of cities: WP5 builds on WP2,3 and proposes to study the joint dynamics of residential sorting and the location of production within cities to understand how a major environmental disamenity-industrial pollution-affects the spatial organisation of cities in the longer-run;

WP6--Horizontal and vertical urban growth in Montreal and Toronto: WP6 will bridge between the previous working packages WP1, WP2, WP4 and WP5, and study--empirically and theoretically--horizontal and vertical urban growth.

The project will be jointly led by three teams. The French team will be composed of Gobillon (PI), Combes (CoI) and Duranton (TM) who have contributed to the development of major theoretical approaches in urban economics. The Canadian team will be led by Heblich (PI), who is a lead researcher in urban economics/economic history, and Fortin (Co-I), a lead in GIS analysis. The UK team will be led by Zylberberg (PI), who is an economist specialist in data extraction form historical sources and remote sensing. Shaw-Taylor and Schürer, advisory board, will help design the analysis of the population micro-censuses between 1851 and 1911 (WP3). The collaboration partner, Redding (TM), involved in the design of WP3 and the implementation of WP6, is one of the World lead researchers in urban economics.

Outputs will include articles in top economic journals, and detailed algorithms to extract relevant spatial information from manuscript maps.

The population of the United Kingdom in 2024 was estimated to be approximately 69.3 million, with over 9.6 million people living in South East England. London had the next highest population, at almost 9.1 million people, followed by the North West England at 7.7 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, 3.2 million, and 1.9 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 650,000, while in Wales, it was the Cardiff Unitary Authority at around 384,000. Northern Ireland, on the other hand, has eleven local government districts, the largest of which is Belfast with a population of approxiamtely 352,000.

Overview

Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.

Our self-hosted GIS data cover administrative and postal divisions with up to 6 precision levels: a zip code layer and up to 5 administrative levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.

The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.

Use cases for the Global Boundaries Database (GIS data, Geospatial data)

• In-depth spatial analysis

• Clustering

• Geofencing

• Reverse Geocoding

• Reporting and Business Intelligence (BI)

Product Features

• Coherence and precision at every level

• Edge-matched polygons

• High-precision shapes for spatial analysis

• Fast-loading polygons for reporting and BI

• Multi-language support

For additional insights, you can combine the GIS data with:

• Population data: Historical and future trends

• UNLOCODE and IATA codes

• Time zones and Daylight Saving Time (DST)

Data export methodology

Our geospatial data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson

All GIS data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why companies choose our map data

• Precision at every level

• Coverage of difficult geographies

• No gaps, nor overlaps

Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

Survey name: Mogerhanger A1(M) Improvements (Map 4) Post 1988 Agricultural Land Classification (ALC) site survey data – scanned original paper maps and survey reports for individual sites surveyed in detail between 1989 and 1999 by the Ministry of Agriculture Fisheries and Food. Where Grade 3 is mapped this includes the subdivision of Grade 3 into subgrades 3a and 3b. Surveys use the current grading methodology as described in "Agricultural Land Classification of England and Wales," a link for which is provided with the data. Individual sites have been mapped at varying scales and level of detail from 1:5,000 to 1:50,000 (typically 1:10,000). Unedited sample point soils data and soil pit descriptions are also available for some surveys. Attribution statement: © Natural England copyright. Contains Ordnance Survey data © Crown copyright and database right [year]. Attribution statement: Attribution statement: © Natural England copyright. Contains Ordnance Survey data © Crown copyright and database right [year].

Routes including canals, river corridors and old railway lines, linking different areas within a town or city as part of a designated and managed network and used for walking, cycling or horse riding, or linking towns and cities to their surrounding countryside or country parks. These may link green spaces together.A council development plan may designate a green belt around a city or town to support the spatial strategy by:directing development to the most appropriate locations and supporting regeneration;protecting and enhancing the character, landscape setting and identity of the settlement; andprotecting and providing access to open space.