Towns and Cities boundaries built from Built-up Areas.

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

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.

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.

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 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.

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

Living England is a multi-year project which delivers a broad habitat map for the whole of England, created using satellite imagery, field data records and other geospatial data in a machine learning framework. The Living England habitat map shows the extent and distribution of broad habitats across England aligned to the UKBAP classification, providing a valuable insight into our natural capital assets and helping to inform land management decisions. Living England is a project within Natural England, funded by and supports the Defra Natural Capital and Ecosystem Assessment (NCEA) Programme and Environmental Land Management (ELM) Schemes to provide an openly available national map of broad habitats across England.This dataset includes very complex geometry with a large number of features so it has a default viewing distance set to 1:80,000 (City in the map viewer).Process Description:A number of data layers are used to develop a ground dataset of habitat reference data, which are then used to inform a machine-learning model and spatial analyses to generate a map of the likely locations and distributions of habitats across England. The main source data layers underpinning the spatial framework and models are Sentinel-2 and Sentinel-1 satellite data from the ESA Copernicus programme, Lidar from the EA's national Lidar Programme and collected data through the project's national survey programme. Additional datasets informing the approach as detailed below and outlined in the accompanying technical user guide.Datasets used:OS MasterMap® Topography Layer; Geology aka BGS Bedrock Mapping 1:50k; Long Term Monitoring Network; Uplands Inventory; Coastal Dune Geomatics Mapping Ground Truthing; Crop Map of England (RPA) CROME; Lowland Heathland Survey; National Grassland Survey; National Plant Monitoring Scheme; NE field Unit Surveys; Northumberland Border Mires Survey; Sentinel-2 multispectral imagery; Sentinel-1 backscatter imagery; Sentinel-1 single look complex (SLC) imagery; National forest inventory (NFI); Cranfield NATMAP; Agri-Environment HLS Monitoring; Living England desktop validation; Priority Habitat Inventory; Space2 Eye Lens: Ainsdale NNR, State of the Bog Bowland Survey, State of the Bog Dark Peak Condition Survey, State of the Bog Manchester Metropolitan University (MMU) Mountain Hare Habitat Survey Dark Peak, State of the Bog; Moors for the Future Dark Peak Survey; West Pennines Designation NVC Survey; Wetland Annex 1 inventory; Soils-BGS Soil Parent Material; Met Office HadUK gridded climate product; Saltmarsh Extent and Zonation; EA LiDAR DSM & DTM; New Forest Mires Wetland Survey; New Forest Mires Wetland Survey; West Cumbria Mires Survey; England Peat Map Vegetation Surveys; NE protected sites monitoring; ERA5; OS Open Built-up Areas; OS Boundaries dataset; EA IHM (Integrated height model) DTM; OS VectorMap District; EA Coastal Flood Boundary: Extreme Sea Levels; AIMS Spatial Sea Defences; LIDAR Sand Dunes 2022; EA Coastal saltmarsh species surveys; Aerial Photography GB (APGB); NASA SRT (Shuttle Radar Topography Mission) M30; Provisional Agricultural Land Classification; Renewable Energy Planning Database (REPD); Open Street Map 2024.Attribute descriptions: Column Heading Full Name Format Description

SegID SegID Character (100) Unique Living England segment identifier. Format is LEZZZZ_BGZXX_YYYYYYY where Z = release year (2223 for this version), X = BGZ and Y = Unique 7-digit number

Prmry_H Primary_Habitat Date Primary Living England Habitat

Relblty Reliability
Character (12) Reliability Metric Score

Mdl_Hbs Model_Habs Interger List of likely habitats output by the Random Forest model.

Mdl_Prb Model_Probs Double (6,2) List of probabilities for habitats listed in ‘Model_Habs’, calculated by the Random Forest model.

Mixd_Sg Mixed_Segment Character (50) Indication of the likelihood a segment contains a mixture of dominant habitats. Either Unlikely or Probable.

Source Source

Description of how the habitat classification was derived. Options are: Random Forest; Vector OSMM Urban; Vector Classified OS Water; Vector EA saltmarsh; LE saltmarsh & QA; Vector RPA Crome, ALC grades 1-4; Vector LE Bare Ground Analysis; LE QA Adjusted

SorcRsn Source_Reason

Reasoning for habitat class adjustment if ‘Source’ equals ‘LE QA Adjusted’

Shap_Ar Shape_Area

Segment area (m2) Full metadata can be viewed 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)

This is a city map of London, England, shown at a 1:63,360 scale. This city map was created by the Director General of the Ordnance Survey.

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.

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Mature Support Notice: 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.To launch a web map containing this map layer, click here.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. Here's a ready-to-use web map that uses the National Geographic World Map as its basemap. 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, INCREMENT P, 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

The table Limited English Proficiency Towns is part of the dataset Connecticut EJ Communities Maps, available at https://redivis.com/datasets/ck4g-d60ynh7dt. It contains 171 rows across 3 variables.

Georeferenced map of 'Plan of the City of Edinburgh, including all the latest and intended improvements' By John Wood (1831) 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 2011-05-30 and migrated to Edinburgh DataShare on 2017-02-21.

Georeferenced map of 'A plan of the city and suburbs of Edinburgh' By Alexander Kincaid (1784) 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.

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.

In 2024, over 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 just over 3.03 million, closely followed by Greater Manchester at three million, and then West Yorkshire with a population of 2.4 million. Kent, Essex, and Hampshire were the three next-largest counties in terms of population, each with just over 1.9 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 2024, the most-populated Scottish council area was Glasgow City, with over 650,000 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.

Service that generates the cartography of the city plan that covers the territory of Barcelona's city council