Comprehensive dataset of 3 New England restaurants in United Kingdom as of August, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

What is it?The “Regional self-reliance model of the New England food system” explores future scenarios of regional food self-reliance. In this model, self-reliance is defined as the ratio of production to consumption and can be expressed for individual commodities, food groups, or the overall diet. The model allows a user to define assumptions about diet composition and target self-reliance for different groups of foods. The model estimates the regional self-reliance across seven food groups (grains, vegetables, fruits, dairy, protein-rich foods, fats and oils, and sweeteners) and for the overall diet. In addition, the model calculates land requirements for producing the target amounts of food from New England agriculture. These estimates are presented beside data on current land use to place the results in context.Why was it generated?The model was generated as part of the New England Feeding New England (NEFNE) project. The central question of NEFNE was, "What would it take for 30% of the food consumed in New England to be regionally produced by 2030?" The model addresses the agricultural production capacity of the region, while accounting for the contribution of capture fisheries and aquaculture to food production. The purpose of the model is to estimate the production capacity of the region’s land resources to evaluate the land requirements of increasing regional self-reliance in food.How was it generated?A team of researchers collaborated to construct the model. The model builds on prior work on regional self-reliance, the human carrying capacity of agricultural resources, and analysis of livestock feed requirements. As described below, the model estimates the land requirements of supplying a given level of self-reliance, accounting for food needs, food losses and waste, livestock feed requirements, crop yields, and land availability.Starting from the food consumption end of the food system, the model takes input data on food intake (in servings person-1 day-1) by food group (e.g., grains) and distributes consumption across primary food commodities from that food group (e.g., corn meal, wheat flour) in the Loss-Adjusted Food Supply. Intake for each primary food commodity is then converted into the equivalent quantity of agricultural commodity (in pounds year-1) needed to supply the region with a sufficient amount of that commodity to meet the target level of self-reliance, at a given projected population size. This conversion accounts for the serving size of the commodity (in grams), losses at different stages of the food system, and processing conversions. For animal products, a further step is taken to convert the quantity of food consumed into equivalent quantities of crop biomass required to feed the requisite livestock. Land requirements for each food are determined by dividing the agricultural commodity (for plant foods) or crop biomass requirements (for animal products) by regional average yields for the appropriate crop(s).Input data were collected from an array of secondary data sources, including, the Loss-Adjusted Food Supply, the Census of Agriculture, the New England Agricultural Bulletin, Major Land Uses, the Atlantic Coastal Cooperative Statistics Program Data Warehouse, and the NOAA Fisheries Landings data portal. Additional sources used to develop the model are cited in the workbook and reference information is provided in each worksheet. The unique contribution of the model is to organize the data in a form that permits exploration of alternative scenarios of diet, target self-reliance, and land availability for the New England region.

Population figures over a 25-year period, by five-year age groups and sex for regions in England. 2022-based datasets are the latest projection.

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.

The Doorstep Greens initiative provides new or renovated areas of public open space close to people's homes that could be enjoyed permanently by the local community. The initiative is a joint Natural England and New Opportunities Fund project. The initiative is aimed at targeting communities who experience disadvantage and where regeneration of the local environment and outdoor recreation provision is sorely needed. They could be small or large, and in urban or rural locations. Attribution statement: © Natural England copyright. Contains Ordnance Survey data © Crown copyright and database right [year].

Water that falls to the earth in the form of rain, snow, sleet, or hail continues its journey in one of four ways: It might land on a water body and, essentially, go with the flow; it might run off the land into a nearby water body or storm drain; it might evaporate from a water body or land surface; or it might seep into the ground. Water that seeps into the ground moves in a downward direction, passing through the pore spaces between the rock and soil particles in what is known as the zone of aeration, or unsaturated zone.

New experimental statistics presenting travel time data measuring connectivity to key transport destinations (major airports, stations, road junctions and ports) from each area of England, by road and by public transport. Source agency: Transport Designation: Experimental Official Statistics Language: English Alternative title: Transport Connectivity Statistics: England

Annual estimates of population by marital status and living arrangements by age group and sex.

The energy efficiency of new homes as measured by the SAP rating system. Source agency: Communities and Local Government Designation: Official Statistics not designated as National Statistics Language: English Alternative title: DSO 2.5

Findings from the Coronavirus (COVID-19) Infection Survey for England.

Annual publication of the number of new criminal offences created each year. Source agency: Justice Designation: Official Statistics not designated as National Statistics Language: English Alternative title: New Criminal Offences, England and Wales

There are approximately 2.6 million agricultural land parcels in England, and the Parcel Points (England) point dataset represents the approximate centres, or centroids of these parcels. The number of agricultural parcels varies over time as fields are split or joined consequently creating new fields with new centroids. Some parcels may be sold for development and are no longer available for agricultural use, occasionally land that was previously developed may return to agriculture, e.g. disused airfields. Parcel Points is a simple point dataset that uses the centres of agricultural parcels attributed only with the parcel reference ID. Parcel points are categorised according to county and are available as England-wide coverage too. Users can use the data as supplied or attach their own attributes. When viewed overlying other publicly available data, e.g. satellite imagery (Google earth), OS open data, OpenStreetMap, etc. that may feature agricultural land the points provide a useful reference point to identify the approximate centre of agricultural parcels. Parcel Points uses the Open Government Licence v3.0 as used by other publicly accessible data on the Defra Data Services Platform and will be updated every 6 months. Coverage will be for agricultural land parcels in England only. Users should be aware that client-side constraints associated WFS and OGC API, such as maximum feature limits, may affect the loading and display of parcel points. Parcel Points WMS are not affected to the same extent. Attribution statement: © Rural Payments Agency

Household projections for England, by region and local authority. Formerly referred to as live tables on household projections. The 2018-based projections are the most recent available.

Crime Survey for England and Wales (CSEW) and Home Office police recorded crime data, by quarterly time periods.

Population figures over a 25-year period, by single year of age and sex for local authorities in England. 2022-based datasets are the latest projection.