A PDF map that shows the counties and unitary authorities in the United Kingdom as at 1 April 2020. (File Size - 472 KB)

A PDF map that shows the regions and their constituent counties and unitary authorities in the United Kingdom as at 1 April 2020. (File Size - 557 KB)

A PDF map that shows the counties and unitary authorities in the United Kingdom as at 1 April 2020. (File Size - 472 KB)

The Crop Map of England (CROME) is a polygon vector dataset mainly containing the crop types of England. The dataset contains approximately 32 million hexagonal cells classifying England into over 15 main crop types, grassland, and non-agricultural land covers, such as Woodland, Water Bodies, Fallow Land and other non-agricultural land covers. The classification was created automatically using supervised classification (Random Forest Classification) from the combination of Sentinel-1 Radar and Sentinel-2 Optical Satellite images during the period late January 2020 – September 2020. The dataset was created to aid the classification of crop types from optical imagery, which can be affected by cloud cover. The results were checked against survey data collected by field inspectors and visually validated. The data has been split into the Ordnance Survey Ceremonial Counties and each county is given a three letter code. Please refer to the CROME specification document to see which county each CODE label represents.

This file contains the digital vector boundaries for Counties, in England, 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 ArcGIS for INSPIRE View Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_(December_2020)_EN_BFE/MapServerREST URL of ArcGIS for INSPIRE Feature Download Service – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_December_2020_EN_BFE/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_December_2020_EN_BFE_2022/FeatureServer

This file contains the digital vector boundaries for Counties and Unitary Authorities, in the United Kingdom, as at December 2020.The boundaries available are: (BGC) Generalised (20m) - clipped to the coastline (Mean High Water mark).Contains both Ordnance Survey and ONS Intellectual Property Rights.REST URL of Map Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_and_Unitary_Authorities_(December_2020)_UK_BGC/MapServerREST URL of WFS Service – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_and_Unitary_Authorities_December_2020_UK_BGC/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_and_Unitary_Authorities_December_2020_UK_BGC_2022/FeatureServer

This file contains the digital vector boundaries for Counties and Unitary Authorities, in the United Kingdom, 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 ArcGIS for INSPIRE View Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_and_Unitary_Authorities_(December_2020)_UK_BFC/MapServerREST URL of ArcGIS for INSPIRE Feature Download Service – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_and_Unitary_Authorities_December_2020_UK_BFC/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_and_Unitary_Authorities_December_2020_UK_BFC_2022/FeatureServer

This file contains the digital vector boundaries for Counties, in England, as at December 2020.The boundaries available are: (BGC) Generalised (20m) - clipped to the coastline (Mean High Water mark).Contains both Ordnance Survey and ONS Intellectual Property Rights.REST URL of ArcGIS for INSPIRE View Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_(Dec_2020)_EN_BGC/MapServerREST URL of ArcGIS for INSPIRE Feature Download Service – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_December_2020_EN_BGC/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_Dec_2020_EN_BGC_2022/FeatureServer

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Two vector (.shp) files are provided. The first, (macro assemblages.shp) shows the modelled (random forest) macrofaunal assemblage type based on a clustering of abundance data from the OneBenthic database (see https://sway.office.com/HM5VkWvBoZ86atYP?ref=Link). The second file, (macro assemblages confidence.shp) shows associated confidence in the modelled output, with darker shades (high values) indicating higher confidence and lighter shades (lower values) indicating lower confidence. Both layers can be viewed in the OneBenthic Layers tool (https://rconnect.cefas.co.uk/onebenthic_layers/), together with further details of the methodology used to produce them.

The modelled layer for macrofaunal assemblage is based on a random forest modelling of point sample data from the OneBenthic (OB, https://rconnect.cefas.co.uk/onebenthic dashboard/) dataset, largely following the methodology in Cooper et al. (2019), but with an expanded dataset covering the Greater North Sea and including data from the EurOBIS (https://www.eurobis.org/) data repository. Of the 44,407 samples within OB, we selected a subset of 31,845 for which data were considered comparable (i.e. sample acquired using a 0.1 m2 grab or core, processed using a 1 mm sieve and not taken from a known impacted site). Colonial taxa were included and given a value of one. To take account of potential differences in taxonomic resolution between surveys, macrofaunal data were aggregated to family level using the taxonomic hierarchy provided by the World Register of Marine Species (https://www.marinespecies.org/). This reduced the number of taxa from 3,659 to 750. To address spatial autocorrelation in the data, and in keeping with the previous approach, samples closer than 50 m were removed from the dataset, reducing the overall number to 18,348. A fourth-root transformation was then applied to the data to down weight the influence of highly abundant taxa. Data were then subjected to clustering using k-means. A species distribution modelling approach, based on random forest, was then used to model cluster group (i.e. macrofaunal assemblage or biotope) identity across the study area (Greater North Sea). Cross-validation via repeated sub-sampling was done to evaluate the robustness of the model estimate and predictions to data sub-setting and to extract additional information from the model outputs to produce maps of confidence in the predicted distribution, following the approach described in Mitchell et al. (2018). The cross-validation was done on 10 split sample data sets with 75% used to train and 25% to test models, randomly sampled within the levels of the response variable to maintain the class balance. The final model output was plotted as the cluster class with the majority vote of all 10 model runs. An associated confidence map was produced by multiplying map layers for 1) the frequency of the most common class and ii) the average probability of the most common class. Model outputs are used in the OneBenthic Layers Tool (https://rconnect.cefas.co.uk/onebenthic_layers/).

Cooper, K.M.; Bolam, S.G.; Downie, A.-L.; Barry, J. 2019. Biological-based habitat classification approaches promote cost-efficient monitoring: An example using seabed assemblages. J. Appl. Ecol. 56:1085–1098. https://doi.org/10.1111/1365-2664.13381

Mitchell, P.J., Downie, A.-L., Diesing, M. How good is my map? 2018. A tool for semi-automated thematic mapping and spatially explicit confidence assessment. Env. Model. Softw. 108, 111–122. https://doi.org/10.1016/j.envsoft.2018.07.014

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.

Important Note: This item is in mature support as of November 2021 and will be retired. A NEW VERSION of this item is available for your use. We recommend updating your maps and apps to use the new version.Boundary-Line is a specialist 1:10 000 scale boundaries dataset. It contains all levels of electoral and administrative boundaries, from district, wards and civil parishes (or communities) up to parliamentary, assembly and European constituencies. The currency of this data is 10/2019.

The coverage of the map service is GB. The map projection is British National Grid. The service is appropriate for viewing down to a scale of approximately 1:20,000. Updated by Esri UK: 22/01/2020To download this dataset use the link here.Ever wondered how Boundary-Line data could be used in analysis? Take a look at our police or supermarket story map.

A lookup of wards to local authority districts to county to county electoral divisions in England as at 7th May 2020. (File Size - 2 MB).Field Names – WD20CD, WD20NM, LAD20CD, LAD20NM, CTY20CD, CTY20NM, CED20CD, CED20NM, FIDField Types – Text, Text, Text, Text, Text, Text, Text, TextField Lengths – 9, 53, 9, 28, 9, 16, 9, 55FID = 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. NB: Electoral Change orders operative in May 2020 postponed until May 2021REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/WD20_LAD20_CTY20_CED20_EN_LU_64f6cc3a536e4d3a9adb011398476c1f/FeatureServer

This dataset provides digital spatial information on the location of mineral resources in England at a scale of 1:50 000. The term ‘mineral resources’ has a definition under international standards that includes both an economic and geological dimension. These data are based primarily on mapped geology with limited assessment of economics. Therefore, the term ‘mineral resources’ is used here in a broad sense. The dataset allows users to visualise the extent and distribution of mineral resources and to relate them to other forms of land-use (such as urban areas or designated environmentally sensitive areas) or to other factors (such as transport infrastructure and conservation information). The dataset is derived from a set of commissioned projects to prepare a series of mineral resource maps based on counties or amalgamations of counties. Maps for England were commissioned by the central government department with responsibility for mineral planning at the time (Department of the Environment (DoE), Department of the Environment, Transport and the Regions (DETR), Department for Transport, Local Government and the Regions (DTLR), Office of the Deputy Prime Minister (ODPM), and the Department for Communities and Local Government (DCLG) between 1994 and 2006. Each map produced (with an accompanying report describing the mineral resources depicted on the map) is available to download, as a PDF file from the BGS-hosted website: www.MineralsUK.com. During 2011-2012 revisions were made to areas of the resource linework. These changes were made as a result of new research and release of a new version of DiGMap (v5). This work was on an ad hoc basis but affects all resource layers. In 2020 minor revisions to geometry and attributes were made in in response to minor corrections that were required. The paper maps were not re-released with these data updates. The BGS Mineral Resource data does not determine mineral reserves and therefore does not denote potential areas of extraction. Only onshore, mainland mineral resources are included in the dataset. This dataset has been produced by the collation and interpretation of mineral resource data principally held by the British Geological Survey. The mineral resource data presented are based on the best available information, but are not comprehensive and their quality is variable. The dataset should only be used to show a broad distribution of those mineral resources which may be of current or potential economic interest.

MOOD standard Mapping and Analysis polygons.

Abstract:

Standard extents and polygons were defined at the start of the MOOD project. There sets of standatd geographies are provided:
a) A series of decimal degree grids (0.05, 0.1, 0.2, 0.5 ) in moodgrids.zip
b) raster extents in EPRS ( molandmasketrslaeaepsg3035.tif) and geographic projection (molatlonglandmask.tif) in moodpolygonsjanmasks21.zip; and
c) standard Administrative unit Polygons adopted from the Vectornet Project : one with relatively equal sized units designed for mapping (vectornetMAPforMOODjan21.shp) and one more suited to analysing and entering data recorded by admin unit that has consistent NITS 3 or Gaul 2 polygons (VectornetDATAforMOODjan21.shp) also in moodpolygonsjanmasks21.zip

Projection + EPSG code:
Latitude-Longitude/WGS84 (EPSG: 4326)
Spatial extent:

-73.2634658809999451,18.9632860000000392 : 69.0703202920000763,83.6274185180000700

Software used:
The software used for map production is ESRI ArcMap 10.8

License: CC-BY-SA 4.0

Processed by:
ERGO (Environmental Research Group Oxford) https://ergoonline.co.uk/ for the H2020 MOOD project

Two datasets provide geographic, land use and population data for US Counties within the contiguous US. Land area, water area, cropland area, farmland area, pastureland area and idle cropland area are given along with latitude and longitude of the county centroid and the county population. Variables in this dataset come from the US Dept. of Agriculture (USDA) Natural Resources Conservation Service (NRCS) and the US Census Bureau.

EOS-WEBSTER provides seven datasets which provide county-level data on agricultural management, crop production, livestock, soil properties, geography and population. These datasets were assembled during the mid-1990's to provide driving variables for an assessment of greenhouse gas production from US agriculture using the DNDC agro-ecosystem model [see, for example, Li et al. (1992), J. Geophys. Res., 97:9759-9776; Li et al. (1996) Global Biogeochem. Cycles, 10:297-306]. The data (except nitrogen fertilizer use) were all derived from publicly available, national databases. Each dataset has a separate DIF.

The US County data has been divided into seven datasets.

US County Data Datasets:

1) Agricultural Management 2) Crop Data (NASS Crop data) 3) Crop Summary (NASS Crop data) 4) Geography and Population 5) Land Use 6) Livestock Populations 7) Soil Properties

The PALEOMAP project produces paleogreographic maps illustrating the Earth's plate tectonic, paleogeographic, climatic, oceanographic and biogeographic development from the Precambrian to the Modern World and beyond.

A series of digital data sets has been produced consisting of plate tectonic data, climatically sensitive lithofacies, and biogeographic data. Software has been devloped to plot maps using the PALEOMAP plate tectonic model and digital geographic data sets: PGIS/Mac, Plate Tracker for Windows 95, Paleocontinental Mapper and Editor (PCME), Earth System History GIS (ESH-GIS), PaleoGIS(uses ArcView), and PALEOMAPPER.

Teaching materials for educators including atlases, slide sets, VHS animations, JPEG images and CD-ROM digital images.

Some PALEOMAP products include: Plate Tectonic Computer Animation (VHS) illustrating motions of the continents during the last 850 million years.

Paleogeographic Atlas consisting of 20 full color paleogeographic maps. (Scotese, 1997).

Paleogeographic Atlas Slide Set (35mm)

Paleogeographic Digital Images (JPEG, PC/Mac diskettes)

Paleogeographic Digital Image Archive (EPS, PC/Mac Zip disk) consists of the complete digital archive of original digital graphic files used to produce plate tectonic and paleographic maps for the Paleographic Atlas.

GIS software such as PaleoGIS and ESH-GIS.

This spatial dataset is an output of the Natural England County & City Natural Capital Atlas project (July 2020). It shows variation in ecosystem service flow for habitats across England, based on indicators identified by NE in the 2018 Natural Capital Indicators project. The dataset comprises a hexagonal grid which summarises indicator values across the country (each unit = 5km²).Natural Capital is an important aspect of current environmental policy and management. This dataset, in combination with the other project outputs, will support understanding of Natural Capital in England and serve as a valuable engagement tool to communicate concepts of the Natural Capital approach to a wide variety of stakeholders.

IntroductionThis is a spatial dataset that describes the location and extent of Wood Pasture and Parkland habitat across England. Wood Pasture and Parkland is a Priority Habitat as listed in the UK Biodiversity Action Plan (UKBAP) 2008.Wood pastures and parkland are the products of historic land management systems and designed landscapes and represent a vegetation structure rather than a particular plant community. Typically, this structure consists of large, open-grown or high forest trees (often pollards) at various densities, in a matrix of grazed grassland, heathland and/or woodland floras.Why is it important that Natural England publishes this dataWood Pasture and Parkland (England) is a priority habitat as identified in the UK Biodiversity Action Plan (UKBAP) and listed as being of principal importance for the purposes of conserving or enhancing biodiversity under Section 41 of the Natural Environment and Rural Communities (NERC) act. Wood-pasture and parkland are mosaic habitats valued for their trees, especially veteran and ancient trees and the plants and animals that they support. Specialised and varied habitats within woodpasture and parkland provide a home for a wide range of species, many of which occur only in these habitats, particularly insects, lichens and fungi which depend on dead and decaying wood.LineageThe Wood Pasture and Parkland Inventory (WPPI) was initially created in 2011 under contract by Exegesis as a provisional inventory. The inventory was established by collating exsisting datasets, drawing on specialist knowledge, refering old maps and aerial photography. This inventory included data from: OS county series maps (Epoch 1 1843 - 1893, Epoch 2 1891 - 1912, Epoch 3 1904 - 1939, Epoch 4 1919 - 1943) and first and second edition UK perspective Aerial Photographs dated 1999 to 2009. Modern OS maps were used to created polygon boundaries and these boundaries were mapped to the OS Master Map framework.This first inventory did not cover all England, subsequent inventories added missing counties e.g. Greater London by using the same techniques.Data was added to the inventory in subsequent years based on expert feedback and survey work.The inventory was updated in 2020 by collating data from the existing dataset, local record centers, local councils and other sources all verified by OS county series Epoch 1 - 4 maps and aerial photography. Parkland was defined as areas with a minimum of 3 trees, excluding boundary trees, which had less than 250 m between trees. Park extent was mapped to boundary features where park trees were less than 100 m from the boundary or the boundary included a large tree which was less than 250 m from a park tree.Some areas of woodland were included where possible park trees were present. Some open areas and wooded areas were not removed as the precise extent of parkland habitat was difficult to determine from aerial photography.Cemeteries and churchyards were excluded unless they were entirely within the park boundary.The minimum mappable unit for the inventory was 0.25ha. Metalled roads and rivers were excluded according to Natural England mapping rules, therefore some areas <0.25ha may be present if separated by a road.In 2025 the inventory was updated further by remapped all polygons to a new version of OSMM and by aligning the attributes to the Priority Habitats Inventory (PHI), which had also been updated since 2020. A series of datasets remapping Cumbria was added to the inventory to replace and update all the polygons Cumbria. Further data was added via submission to the PHI mailbox (habitatinventories@naturalengland.org.uk) on consultation with NE habitat specialists.AttributionColumn HeadingFull NameFormatDescriptionObjectIDObjectIDgeometryGeodatabase identifierShapeShapegeometrySpatial format identifierMainHabsMain HabitatsTextName of Habitat presentHabCodesHabitat CodesTextCode representing main habitats present in the polygonFeatDescFeature DescriptionTextAdditional information about the nature of the habitat or features presentFeatCodesFeature CodesTextCode corresponding to the habitat feature descriptionsOtherClassOther habitat classificationsTextAdditional Habitat classification information relating to main habitatsAddHabsAdditional habitats presentTextList of codes for additional habitats present within the polygonPrimSourcePrimary data sourcesTextList of primary sources for main habitat present in polygon. With corresponding HabCode in bracketsAreaHaArea in hectaresNumericPolygon area in hectaresVersionPublication versionTextDate of publication for current updateUIDUnique IDTextUnique ID for the polygon based on XY location coordinatesShape_LengthShape_LengthNumericPolygon perimeterShape_AreaShape_AreaNumericPolygon area Full metadata can be viewed on data.gov.uk.

A lookup between postcodes and postcode sectors, postcode districts and postcode areas as at March 2021 in England and Wales (File size 5MB).