0ac15fd6-6f3a-4f28-8ed7-34461ca62a6e English ISO/IEC 8859-1 (also known as Latin 1) dataset dataset NERC EDS Environmental Information Data Centre Lancaster Environment Centre, Library Avenue, Bailrigg Lancaster LA1 4AP UK info@eidc.ac.uk https://eidc.ac.uk/ EIDC website The Environmental Information Data Centre (EIDC) is the UK's national data centre for terrestrial and freshwater sciences. information pointOfContact 2026-01-09T10:18:08 UK GEMINI 2.3 OSGB 1936 / British National Grid TM75 / Irish Grid Land Cover Map 2024 (1km summary rasters, GB and N. Ireland) 2025-07-22 publication https://catalogue.ceh.ac.uk/id/0ac15fd6-6f3a-4f28-8ed7-34461ca62a6e 10.5285/0ac15fd6-6f3a-4f28-8ed7-34461ca62a6e doi: Rowland, C.S., Marston, C.G., O'Neil, A.W. (2025). Land Cover Map 2024 (1km summary rasters, GB and N. Ireland). NERC EDS Environmental Information Data Centre 10.5285/0ac15fd6-6f3a-4f28-8ed7-34461ca62a6e This 1 km summary pixel data set represents the land surface of Great Britain and Northern Ireland, classified using two classification schemas, target and aggregate classes. The target class schema comprise 21 UKCEH land cover classes based upon Biodiversity Action Plan broad habitats. The aggregate class schema comprises 10 aggregate classes that are groupings of the 21 target classes. The aggregate classes group some of the more specialised target classes into more general classes. For example, the five coastal classes in the target class are grouped into a single aggregate class. The 1km percentage product provides the percentage cover for each of the 21 land cover classes for 1km x 1km pixels. This product contains one band per habitat class, producing 21 and 10 band images for the target and aggregate class products respectively. The 1km dominant coverage product is based on the 1km percentage product, and reports the land cover class with the highest percentage cover for each 1km pixel. A full description of this and all UKCEH LCM2024 products are available from the LCM2024 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/0ac15fd6-6f3a-4f28-8ed7-34461ca62a6e Marston, C.G. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk https://orcid.org/0000-0002-2070-2187 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information pointOfContact Rowland, C.S. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk https://orcid.org/0000-0002-0459-506X ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Marston, C.G. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk https://orcid.org/0000-0002-2070-2187 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author O'Neil, A.W. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk https://orcid.org/0000-0003-3591-1034 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk owner NERC EDS Environmental Information Data Centre info@eidc.ac.uk custodian NERC EDS Environmental Information Data Centre info@eidc.ac.uk publisher Land Cover theme GEMET - INSPIRE themes, version 1.0 2008-06-01 publication land cover habitat map GEMET - Concepts, version 4.1.3 2019-01-28 creation Land cover Mapping Northern Ireland Great Britain Biodiversity Action Plan otherRestrictions Registration is required to access this data otherRestrictions Licence terms and conditions apply otherRestrictions If you reuse this data, you should cite: Rowland, C.S., Marston, C.G., O'Neil, A.W. (2025). Land Cover Map 2024 (1km summary rasters, GB and N. Ireland). NERC EDS Environmental Information Data Centre https://doi.org/10.5285/0ac15fd6-6f3a-4f28-8ed7-34461ca62a6e grid 1000 English utf8 environment imageryBaseMapsEarthCover 2024-01-01 2024-12-31 -8.648 1.768 49.864 60.861 TIFF NERC EDS Environmental Information Data Centre info@eidc.ac.uk distributor https://data-package.ceh.ac.uk/data/0ac15fd6-6f3a-4f28-8ed7-34461ca62a6e Download the data Download a copy of this data download https://data-package.ceh.ac.uk/sd/0ac15fd6-6f3a-4f28-8ed7-34461ca62a6e.zip Supporting information Supporting information available to assist in re-use of this dataset information https://catalogue.ceh.ac.uk/maps/e499059a-3ca1-4204-a0ba-e1006a823b6c?request=getCapabilities&service=WMS&cache=false& WMS A web map service for this dataset is available dataset dataset Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 UKCEH’s automated land cover algorithms classify 10 m pixels across the whole of UK. A Random Forest classifier is used to classify four composite satellite images representing per season median surface reflectance, based on training data comprising locations of known land cover for 21 land cover classes. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra. Land cover was validated by organising the 10 m pixel classification into a land parcel framework (the LCM2024 classified land parcels product). The classified land parcels were compared to known land cover producing a confusion matrix to determine overall and per class accuracy. Details are available from the product documentation. The 25 m rasterised land parcels product is created by rasterising the corresponding land parcel product.