This file contains the digital vector boundaries for Counties and Unitary Authorities in the United Kingdom, as at December 2019. The boundaries available are: (BUC) Ultra Generalised (500m) - clipped to the coastline (Mean High Water mark). Contains both Ordnance Survey and ONS Intellectual Property Rights. Download File SizesUltra Generalised (500m) - clipped to the coastline (200 KB)Units for the following fields:St_length = metresSt_area = metres2REST URL of ArcGIS for INSPIRE View Service https://ons-inspire.esriuk.com/arcgis/rest/services/Administrative_Boundaries/Counties_and_Unitary_Authorities_December_2019_Boundaries_UK_BUC2/MapServer/exts/InspireView REST URL of ArcGIS for INSPIRE Feature Download Service https://ons-inspire.esriuk.com/arcgis/rest/services/Administrative_Boundaries/Counties_and_Unitary_Authorities_December_2019_Boundaries_UK_BUC2/MapServer/exts/InspireFeatureDownload REST URL of Feature Access Service https://ons-inspire.esriuk.com/arcgis/rest/services/Administrative_Boundaries/Counties_and_Unitary_Authorities_December_2019_Boundaries_UK_BUC2/FeatureServer

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 20 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 2019 – September 2019. 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.

A PDF map that shows the local authority districts, counties and unitary authorities in the United Kingdom as at April 2019. The map has been created to show the United Kingdom from country level down to local authority district level. (File Size - 2, 837 KB) https://www.ons.gov.uk/methodology/geography/licences

This file contains the digital vector boundaries for Counties, in England, as at December 2019.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_2019)_FCB_EN/MapServerREST URL of ArcGIS for INSPIRE Feature Download Service – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_December_2019_Full_Clipped_Boundaries_EN/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_December_2019_FCB_EN_2022/FeatureServer

This file contains the digital vector boundaries for Counties, in England, as at December 2019.The boundaries available are: (BFE) Full resolution - extent of the realm (usually this is the Mean Low Water mark but in some cases boundaries extend beyond this to include off shore islands). Contains both Ordnance Survey and ONS Intellectual Property Rights. Units for the following fields:St_length = metresSt_area = metres2REST URL of ArcGIS for INSPIRE View Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_(Dec_2019)_Boundaries_EN_BFE/MapServerREST URL of ArcGIS for INSPIRE Feature Download Service – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_Dec_2019_Boundaries_EN_BFE/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_Dec_2019_Boundaries_EN_BFE_2022/FeatureServer

This file contains the digital vector boundaries for Counties and Unitary Authorities, in the United Kingdom, as at December 2019.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_2019)_FCB_UK/MapServerREST URL of ArcGIS for INSPIRE Feature Download Service – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_and_Unitary_Authorities_December_2019_Full_Clipped_Boundaries_UK/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_and_Unitary_Authorities_December_2019_FCB_UK_2022/FeatureServer

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.

This file contains the digital vector boundaries for Counties and Unitary Authorities in the United Kingdom, as at April 2019. The BGC boundaries are 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_and_Unitary_Authorities_(April_2019)_Generalised_Boundaries_UK/MapServerREST URL of ArcGIS for INSPIRE Feature DownloadService – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_and_Unitary_Authorities_April_2019_Generalised_Boundaries_UK/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_and_Unitary_Authorities_April_2019_Generalised_Boundaries_UK_2022/FeatureServer

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

This file contains the digital vector boundaries for Counties and Unitary Authorities in England and Wales, as at April 2019. The BFE boundaries are full resolution - extent of the realm (usually this is the Mean Low Water mark but in some cases boundaries extend beyond this to include off shore islands). 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_(April_2019)_FEB_EW/MapServerREST URL of ArcGIS for INSPIRE Feature DownloadService – https://dservices1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/services/Counties_and_Unitary_Authorities_April_2019_Full_Extent_Boundaries_EW/WFSServer?service=wfs&request=getcapabilitiesREST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/Counties_and_Unitary_Authorities_April_2019_FEB_EW_2022/FeatureServer

This is a best fit lookup between 2011 Output Areas (OA) and counties/unitary authorities as at 31 December 2019 in England. (File Size - 19 MB)Field Names - OA11CD, CTYUA19CD, CTYUA19NM, FIDField Types - Text, Text, TextField Lengths - 9, 9, 35FID = 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/OA11_CTYUA19_EN_LU_a11317b2d23f430a92b9a191a995d1c5/FeatureServer

For more information and an overview of best-fitting follow this link - https://geoportal.statistics.gov.uk/datasets/f0aac7ccbfd04cda9eb03e353c613faa/about

This file contains names and codes for Counties in England as at 1st April 2019. (File Size - 16 KB)Field Names - CTY19CD, CTY19NM, FIDField Types - Text, Text, NumberField Lengths - 9, 16FID = 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/Counties_April_2019_Names_and_Codes_in_England_2022/FeatureServer