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)
https://koordinates.com/license/open-government-license-3/https://koordinates.com/license/open-government-license-3/
Counties were formerly administrative units across the whole UK. Due to various administrative restructurings however, the only administrative areas still referred to as counties are the nonmetropolitan (shire) counties of England. The English metropolitan counties, although no longer administrative units, are also used for statistical purposes.
https://www.ordnancesurvey.co.uk/products/boundary-line#technical
Source:
https://osdatahub.os.uk/downloads/open/BoundaryLine
Licence:
Contains public sector information licensed under the Open Government Licence v3.0.
https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
https://koordinates.com/license/open-government-license-3/https://koordinates.com/license/open-government-license-3/
The current counties of England are defined by the ceremonial counties, a collective name for the county areas to which are appointed a Lord Lieutenant. The office of Lord Lieutenant was created in the reign of Henry VIII. The Lord Lieutenant is the chief officer of the county and representative of the Crown. Whenever the Queen visits an area she will be accompanied by the Lord Lieutenant of that area. Legally the ceremonial counties are defined by the Lieutenancies Act 1997 as ‘Counties and areas for the purposes of the lieutenancies in Great Britain’ with reference to the areas used for local government.
https://www.ordnancesurvey.co.uk/products/boundary-line#technical
Source:
https://osdatahub.os.uk/downloads/open/BoundaryLine
Licence:
Contains public sector information licensed under the Open Government Licence v3.0.
https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
PLEASE NOTE: This data product is not available in Shapefile format or KML at https://naturalengland-defra.opendata.arcgis.com/datasets/Defra::living-england-habitat-map-phase-4/about, as the data exceeds the limits of these formats. Please select an alternative download format.This data product is also available for download in multiple formats via the Defra Data Services Platform at https://environment.data.gov.uk/explore/4aa716ce-f6af-454c-8ba2-833ebc1bde96?download=true.The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable. Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes. Datasets used:Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate DataFull metadata can be viewed on data.gov.uk.
This file contains the digital vector boundaries for Counties and Unitary Authorities, in the United Kingdom, as at December 2023.
This file contains the digital vector boundaries for Counties, in England, as at December 2024.
To begin with, Bartholomew printed their half-inch maps in Scotland as stand-alone sheets known as 'District Sheets' and by 1886 the whole of Scotland was covered. They then revised the maps into an ordered set of 29 sheets covering Scotland in a regular format. This was first pubilshed under the title Bartholomew’s Reduced Ordnance Survey of Scotland. The half-inch maps formed the principal content for Bartholomew's Survey Atlas of Scotland published in 1895. Bartholomew then moved south of the Border to the more lucrative but competitive market in England and Wales, whilst continuing to revise the Scottish sheets. The first complete coverage of Great Britain at the half-inch scale was achieved by 1903 with 67 individual half-inch sheets. Generally at this time, the English sheets sold three times more quickly, at three times the volume of the Scottish sheets. As for Scotland, Bartholomew used their half-inch sheets of England and Wales in the Survey Atlas of England and Wales published in 1903. From 1901, following a copyright complaint from Ordnance Survey, Bartholomew was forced to drop 'Ordnance' from their map titles. The series was initially renamed 'Bartholomew's Reduced Survey', and by 1903 'Bartholomew's half inch to the mile map'.Bartholomew revised the most popular half-inch sheets every couple of years, ensuring that their maps were more up to date than their main rival, Ordnance Survey. Popular sheets had print runs of several tens of thousands per edition, involving nearly 20 different layer colour plates for hillier areas with more colour.More information: http://geo.nls.uk/maps/bartholomew/great_britain/further_info.html
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
A PDF map that shows the local authority districts, counties and unitary authorities in the United Kingdom as at April 2023. The map has been created to show the United Kingdom from country level down to local authority district level. (File Size - 1,909 KB)
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.
The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable.
Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes.
Datasets used: Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate Data
Geolocet's Administrative Boundaries Spatial Data serves as the gateway to visualizing geographic distributions and patterns with precision. The comprehensive dataset covers all European countries, encompassing the boundaries of each country, as well as its political and statistical divisions. Tailoring data purchases to exact needs is possible, allowing for the selection of individual levels of geography or bundling all levels for a country with a discount. The seamless integration of administrative boundaries onto digital maps transforms raw data into actionable insights.
🌐 Coverage Across European Countries
Geolocet's Administrative Boundaries Data offers coverage across all European countries, ensuring access to the most up-to-date and accurate geographic information. From national borders to the finest-grained administrative units, this data enables informed choices based on verified and official sources.
🔍 Geographic Context for Strategic Decisions
Understanding the geographical context is crucial for strategic decision-making. Geolocet's Administrative Boundaries Spatial Data empowers exploration of geo patterns, planning expansions, analysis of regional demographics, and optimization of operations with precision. Whether it is for establishing new business locations, efficient resource allocation, or policy impact analysis, this data provides the essential geographic context for success.
🌍 Integration with Geolocet’s Demographic Data
The integration of Geolocet's Administrative Boundaries Spatial Data with Geolocet's Demographic Data creates a synergy that enriches insights. The combination of administrative boundaries and demographic information offers a comprehensive understanding of regions and their unique characteristics. This integration enables tailoring of strategies, marketing campaigns, and resource allocation to specific areas with confidence.
🌍 Integration with Geolocet’s POI Data
Combining Geolocet's Administrative Boundaries Spatial Data with our POI (Points of Interest) Data unveils not only the administrative divisions but also insights into the local characteristics of these areas. Overlaying POI data on administrative boundaries reveals details about the number and types of businesses, services, and amenities within specific regions. Whether conducting market research, identifying prime locations for retail outlets, or analyzing the accessibility of essential services, this combined data empowers a holistic view of target areas.
🔍 Customized Data Solutions with DaaS
Geolocet's Data as a Service (DaaS) model offers flexibility tailored to specific needs. The transparent pricing model ensures cost-efficiency, allowing payment solely for the required data. Whether nationwide administrative boundary data or specific regional details are needed, Geolocet provides a solution to match individual objectives. Contact us today to explore how Geolocet's Administrative Boundaries Spatial Data can elevate decision-making processes and provide the essential geographic data for success.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Data, code and materials from a discrete experiment to test the validity of an Bayesian areal wombling algorithm for predicting social boundaries. The experiment was conducted as a part of project ‘Life at the Frontier: Researching the Impact of Social Frontiers on the Social Mobility and Integration of Migrants’ (2020-2023; NordForsk/ESRC, project no 95193), and experiment data was collected in Rotherham (UK).About the experimentEach border on a map is assigned a boundary value based on how dissimilar the adjacent neighbourhoods are (higher = more dissimilar = more likely to be a social boundary).The experiment was carried out as follows:- We created three maps of the same area with different boundaries using the Bayesian areal wombling approach.- Map A contained the boundaries with the highest boundary values, whilst map C had the lowest boundary values. Map B contained boundaries that were in between.- During an interview, participants were then shown pairs of maps and asked which map in each pair best corresponds to local community boundaries.- The sequence and order of the maps shown were randomised.- Assuming that residents and experts can recognise (but not necessarily recall) social boundaries, we conjecture that participants would choose the map containing borders with higher boundary values.Hypothesis: We hypothesise that participants will agree with the predictions of the areal wombling algorithm and choose boundaries with higher boundary values.Null hypothesis: Participants are not more or less likely to choose boundaries with higher boundary values.Aside from testing a hypothesis, another motivation behind the study is to explore the feasibility of the method for future replications and follow-up research.More informationThis study was approved by the University of Sheffield ethics committee (application number 042378).Please read the README file for a more detailed description of the content of this repository.
This file contains the digital vector boundaries for the historical admin counties without associated county boroughs in England and Wales as at Census Day 1921.
The boundaries available are: (BGC) Generalised resolution - clipped to the coastline (Mean High Water mark).
Contains both Ordnance Survey and ONS Intellectual Property Rights.
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
This file contains the digital vector boundaries for National Parks in Great Britain as at December 2020. The boundaries available are: (BFC) Full resolution - clipped to the coastline (Mean High Water mark). Contains both Ordnance Survey and ONS Intellectual Property Rights.
REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/National_Parks_December_2021_Boundaries_GB_BFC/FeatureServerREST URL of WFS Server – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/National_Parks_December_2020_Boundaries_GB_BFC/WFSServer?service=wfs&request=getcapabilitiesREST URL of MapServer – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/National_Parks_(December_2020)_Boundaries_GB_BFC/MapServer
https://eidc.ceh.ac.uk/licences/lcm-raster/plainhttps://eidc.ceh.ac.uk/licences/lcm-raster/plain
This dataset consists of the 25m raster version of the Land Cover Map 2015 (LCM2015) for Great Britain. The 25m raster product consists of two bands: Band 1 - raster representation of the majority (dominant) class per polygon for 21 target habitat classes; Band 2 - mean per polygon probability as reported by the Random Forest classifier (see supporting information). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. The 25m raster is the most detailed of the LCM2015 raster products both thematically and spatially, and it is used to derive the 1km products. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019.
PLEASE NOTE: This data product is not available in Shapefile format or KML at https://naturalengland-defra.opendata.arcgis.com/datasets/Defra::living-england-habitat-map-phase-4/about, as the data exceeds the limits of these formats. Please select an alternative download format.This data product is also available for download in multiple formats via the Defra Data Services Platform at https://environment.data.gov.uk/explore/4aa716ce-f6af-454c-8ba2-833ebc1bde96?download=true.The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable. Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes. Datasets used:Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate DataFull metadata can be viewed on data.gov.uk.
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.
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 showing the County boundaries of Northern Ireland. 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
PLEASE NOTE: This data product is not available in Shapefile format or KML at https://naturalengland-defra.opendata.arcgis.com/datasets/Defra::living-england-habitat-map-phase-4/about, as the data exceeds the limits of these formats. Please select an alternative download format.This data product is also available for download in multiple formats via the Defra Data Services Platform at https://environment.data.gov.uk/explore/4aa716ce-f6af-454c-8ba2-833ebc1bde96?download=true.The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable. Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes. Datasets used:Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate DataFull metadata can be viewed on data.gov.uk.
PLEASE NOTE: This data product is not available in Shapefile format or KML at https://naturalengland-defra.opendata.arcgis.com/datasets/Defra::living-england-habitat-map-phase-4/about, as the data exceeds the limits of these formats. Please select an alternative download format.This data product is also available for download in multiple formats via the Defra Data Services Platform at https://environment.data.gov.uk/explore/4aa716ce-f6af-454c-8ba2-833ebc1bde96?download=true.The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable. Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes. Datasets used:Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate DataFull metadata can be viewed on data.gov.uk.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
An exercise was conducted by the Department for Infrastructure (DfI) in Northern Ireland (NI) in collaboration with the Department of Transport, Tourism and Sport (DTTaS) in the Republic of Ireland (RoI), to map the border crossings on the public road network between the two jurisdictions.
The file contains two datasets:
NI Border Crossing Points
NI Border Crossing Lines
Note: This exercise was confined to public roads only, therefore private roads to public road border crossings are not included in this dataset.
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)