Towns in England and Wales: towns list, cities list, classification and population data.

Village Greens and Registered Common Lands in York *Please note that the data published within this dataset is a live API link to CYC's GIS server. Any changes made to the master copy of the data will be immediately reflected in the resources of this dataset.The date shown in the "Last Updated" field of each GIS resource reflects when the data was first published.

This dataset comprises polygon data showing the extent & location of all Common Land & Village Greens within Bristol. Commons are typically unfenced land in private ownership with development / land use protected by legislation, although commoners may be granted specific rights. Village Greens are generally areas where local residents go for exercise, lawful sports & pastimes. Some Village Greens also have rights of common over them but enjoy separate statutory protection.

GVA estimates for middle layer super output areas, travel to work areas (TTWA), towns and cities, integrated care board and health board areas, parliamentary and devolved government constituencies, highlands and islands area offices, and bespoke areas. Productivity estimates are for TTWA, and towns and cities. These are official statistics in development.

This file provides a rural-urban view of 2001 Middle Layer Super Output Areas (MSOA) in England and Wales. The ZIP file contains the Rural Urban Classification in XLSX and CSV format and includes a user guide. The files were originally from the NeSS website. Click on the Download button to download the ZIP file.The classification of rural and urban areas is the outcome of a project co-sponsored by:Office for National Statistics (ONS);Department for Environment, Food and Rural Affairs (Defra);Office of the Deputy Prime Minister (now Communities and Local Government);Countryside Agency (CA); andNational Assembly for Wales (NAW).The classification was developed in 2004 by a consortium co-ordinated by Prof. John Shepherd from Birkbeck College. The technical work was lead by Peter Bibby of University of Sheffield and the project also involved the University of Glamorgan and Geowise. The rural and urban classification of Output Areas, Super Output Areas (this dataset) and Wards has been provided to enable datasets to be analysed according to the classification. This provides a powerful tool for the development and monitoring of rural and urban policies.Please Note: Super Output Areas do not have all the same codes as the OA level Dataset. For SOAs and Wards the classifications for ‘Villages, Hamlets and Isolated Dwellings’ have been combined.Similar procedures to those used to classify Output Areas apply to the classification to the 7,194 Middle Layer Super Output Areas in the dataset. However the morphological classification differs in the number of categories as very few MSOAs can be classified as predominantly dispersed settlements. MSOAs are categorised into just three domains: urban 10k, town and fringe and villages, hamlets and isolated dwellings, using the key below:2005 Rural and Urban morphology indicator1 - denotes predominantly urban >10k2 - denotes predominantly town and fringe3 - denotes other rural (including village, hamlet and isolated dwellings)2005 Rural and Urban context indicator0 - denotes less sparsely populated areas1 - denotes sparsely populated areas

This file provides a rural-urban view of 2001 Lower Layer Super Output Areas (LSOA) in England and Wales. The ZIP file contains the Rural Urban Classification in XLSX and CSV format and includes a user guide. The files were originally from the NeSS website. Click on the Download button to download the ZIP file.The classification of rural and urban areas is the outcome of a project co-sponsored by:Office for National Statistics (ONS);Department for Environment, Food and Rural Affairs (Defra);Office of the Deputy Prime Minister (now Communities and Local Government);Countryside Agency (CA); andNational Assembly for Wales (NAW).The classification was developed in 2004 by a consortium co-ordinated by Prof. John Shepherd from Birkbeck College. The technical work was lead by Peter Bibby of University of Sheffield and the project also involved the University of Glamorgan and Geowise. The rural and urban classification of Output Areas, Super Output Areas (this dataset) and Wards has been provided to enable datasets to be analysed according to the classification. This provides a powerful tool for the development and monitoring of rural and urban policies.Please Note: Super Output Areas do not have all the same codes as the OA level Dataset. For SOAs and Wards the classifications for ‘Villages, Hamlets and Isolated Dwellings’ have been combined.Similar procedures to those used to classify Output Areas apply to the classification for the 34,378 Lower Layer Super Output Areas in the dataset. However the morphological classification differs in the number of categories as very few LSOAs can be classified as predominantly dispersed settlements. LSOAs are categorised into just three domains: urban 10k, town and fringe and villages, hamlets and isolated dwellings, using the key below:2005 Rural and Urban morphology indicator1 - denotes predominantly urban >10k2 - denotes predominantly town and fringe3 - denotes other rural (including village, hamlet and isolated dwellings)2005 Rural and Urban context indicator0 - denotes less sparsely populated areas1 - denotes sparsely populated areas

This data set contains annual data and the most recent quarterly data on house building starts. From 2011/12 imputed data is included. Imputed data should not be seen as an estimate for the individual authority but is given on an authority basis to allow custom totals to be constructed.

House building data are collected at local authority district level, but it is important to treat figures at this level with care. House building is unevenly distributed both geographically and over time and patterns of housing development can produce clusters of new homes which make the figures at a low geographic level volatile and difficult to interpret.

For detailed definitions of all tenures, see definitions of housing terms on Housing Statistics

The district level and county figures are as reported by local authorities and the NHBC. Where a local authority has not submitted a quarterly return to DCLG, no figure has been presented for this local authority (and when relevant its county) for any 12-month period that includes the missing quarter.

England total figures include estimates for missing data returns from independent Approved Inspectors and Local Authorities, so the sum of district values may be slightly less than the England totals.

House building starts - A dwelling is counted as started on the date work begins on the laying of the foundation, including 'slabbing' for houses that require it, but not including site preparation. Thus when foundation work commences on a pair of semi-detached houses two houses are counted as started, and when work begins on a block of flats all the dwellings in that block are counted as started. The starts of houses in building schemes are usually phased over a period of weeks or even, in very large schemes, months.

Tenure – For the purposes of these statistics, the term tenure refers to the nature of the organisation responsible for the development of a new housing start or completion. It does not necessarily describe the terms of occupancy for the dwelling on completion. For example, some housing associations develop homes for sale on the open market. Such homes would be reported in the Housing Association tenure of these statistics, but would ultimately most likely be owned and occupied in the private sector.

Housing association - “Housing associations (HAs)” is used as the generic name for all social landlords not covered by local authorities (see below). In previous editions HAs were referred to as Registered Social Landlords (RSL), and the technical term (private) Registered Provider (pRP) of social housing is also sometimes used. The more all-encompassing description of ‘housing associations’ is now seen as more helpful to users of these statistics.

These data were derived from live table 253a (quarterly figures).

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

A Town or Village Green is land over which a significant number of inhabitants of any locality have indulged as of right in lawful sports and pastimes on the land for a period of at least 20 years. Commons are areas of land, usually in private ownership, which are subject to rights held by other individuals, for example the right for others to graze animals, collect firewood etc., over that land. These “rights of common” usually originate from local custom. To view and download this data, please visit our Open Data Hub. https://wiltshire-council-open-data-hub-wiltscouncil.hub.arcgis.com/

The neighbourhood profiles are 22 data profiles that, collectively, cover the whole borough of Camden. The profiles contain comprehensive, verifiable and up-to-date statistics from a variety of sources about the community characteristics, assets and strengths, challenges and needs in each neighbourhood. They are designed to help the Council, other statutory partners and the VCS understand what is being delivered in small areas and the resources that already exist in each area, and identify any gaps. The neighbourhoods are composites of lower super output areas (LSOAs), which are smaller than wards. The neighbourhoods do not conform to administrative boundaries or electoral wards. Their borders are instead based on the actual way that residents identify with particular areas and how they really move about within certain localities.

Settlement or development boundaries seek to set clear limits to towns and villages. They are designed to define the existing settlement and to identify those areas of land where development may be acceptable in principle, subject to other policies and material planning considerations. To view and download this data, please visit our Open Data Hub. https://wiltshire-council-open-data-hub-wiltscouncil.hub.arcgis.com/

Woodlands In and Around Towns (WIAT) The Woods In and Around Towns (WIAT) Programme provides the focus for Scottish Forestry’s work on improving quality of life in towns and cities. The purpose of WIAT is to: Bring neglected woodland into active management. Work with people to help them use their local woodland. There are four key characteristics of woodland that determine whether it improves quality of life: Where it is The woodland must be close to where people live and/or work. We will undertake WIAT related activities within 1km of settlements of over 2000 people (Fig 1). Within the WIAT area, deprived areas are a priority. How it is managed Management for people will be the top priority in most WIAT woodlands. Woods should be safe and welcoming to all. WIAT woodland is also important for other aspects of forestry such as biodiversity. Woodland involved in WIAT should be managed in accordance with the UK Forestry Standard. How it is connected to other woodland and greenspace WIAT will promote the creation and management of woodland that is close to other woodland and greenspace so that it contributes to green networks. Paths should link the networks. How it is connected to people Most of the activity in this programme is directed at the physical elements of WIAT: where it is, how it is managed, and how it is connected into green networks. However, reaching out to people should be part of every WIAT project to help people use woodland.

This dataset contains the transcripts of interviews and discussion groups from ten villages in the Gurue district, Zambezia province, Mozambique. The ten villages were selected from a land scarcity gradient running from villages with abundant land to those with intense land constraints, mainly driven by expanding agricultural activities and population density. The villages had similar infrastructure, soils, rainfall, and vegetation types. The dataset contains information on participatory mapping of the village characteristics, seasonality, how agricultural activity has changed over time (trend analysis), wealth ranking within the villages and differences between wealth statuses, and profiles/characteristics of each village. Interviews were conducted with groups in each village or the leader of the village, between July and December 2015. Data were collected as part of a project funded under the Ecosystem Services for Poverty Alleviation (ESPA) programme. Full details about this dataset can be found at https://doi.org/10.5285/f82f7ad8-0e98-41cb-951e-be64ffd36078

This dataset contains the transcripts of interviews and discussion groups from seven villages in the Mabalane district, Gaza province, Mozambique. The seven villages were selected from a forest degradation gradient running from villages with abundant undisturbed forest areas to those with degraded forests, mainly driven by charcoal production. The villages had similar infrastructure, soils, rainfall, and vegetation types. The dataset contains information on seasonality, how availability and use of products from the forest has changed over time (trend analysis), wealth ranking within the villages and differences between wealth statuses, and profiles/characteristics of each village. Interviews were conducted with groups in each village or the leader of the village, between May and September 2014. Data were collected as part of a project funded under the Ecosystem Services for Poverty Alleviation (ESPA) programme. Full details about this dataset can be found at https://doi.org/10.5285/49a70237-c579-4669-b126-3f23d494aba6

This is the Government data catalogue page for NPTG. Use this link to visit the actual website for NPTG: https://beta-naptan.dft.gov.uk/ NPTG a database of localities (cities, towns, villages and other settlements) in Great Britain. It provides a common frame of reference for the National Public Access Nodes (NaPTAN) schema. The appropriate naming and geospatial location of towns and places is vital for providing effective place and stop finding in on-line journey planners and other passenger information systems. Names are those that would be used by the people that reside or work in that place; the geospatial location is selected to optimise journey planning and other passenger information usage. The NPTG XML schema is used to distribute topographic data from the NPTG database to the local Administrative Areas who administer NaPTAN data, as well as other downstream Public Transport Information systems such as journey planners.

The dataset includes lists of local tree names, tree species identification and local uses of trees in seventeen different villages across three Districts in Mozambique, Africa. We collated species lists from seven villages in Mabalane District, Gaza Province, ten villages in Marrupa District, Niassa Province, and ten villages in Gurue District Zambezia Province. Data were collected in Mabalane between May-Sep 2014, Marrupa between May-Aug 2015, and Gurue between Sep-Dec 2015. Lists of local tree names were collated from several forest plots and agricultural field surveys occurring within the sampled villages, and their species identified in the field by the authors and/or from dried and pressed samples by botanists at the Universidade Eduardo Mondlane in Maputo. Tree species uses by local populations were recorded through a mixture of key informant interviews, focus group discussions, village surveys and ad-hoc observations. This dataset was collected as part of the Ecosystem Services for Poverty Alleviation (ESPA) funded ACES project , which aims to understand how changing land use impacts on ecosystem services and human wellbeing of the rural poor in Mozambique. Full details about this dataset can be found at https://doi.org/10.5285/52371ef0-855f-40c8-8567-f8965f9cbf03

This dataset contains quantitative measurements of woodland structure and composition sampled in twenty-seven different villages across three Districts in Mozambique, Africa. Data were collected from 431 plots where tree stem structure and composition, litter and grass biomass, coarse woody debris, and canopy cover data were recorded. Woodlands within seven villages in Mabalane District, Gaza Province, ten villages in Marrupa District, Niassa Province, and ten villages in Gurue District Zambezia Province were sampled. Data were collected in Mabalane between May-Sep 2014, Marrupa between May-Aug 2015, and Gurue between Sep-Dec 2015. This dataset was collected as part of the Ecosystem Services for Poverty Alleviation (ESPA) funded ACES project , which aims to understand how changing land use impacts on ecosystem services and human wellbeing of the rural poor in Mozambique. Full details about this dataset can be found at https://doi.org/10.5285/70b5cdda-72df-4007-b10e-d75b4046e603