Morton, R.D.; Marston, C.G.; O'Neil, A.W.; Rowland, C.S.
        
        Land Cover Map 2020 (25m rasterised land parcels, GB)
         https://doi.org/10.5285/6c22cf6e-b224-414e-aa85-900325baedbd
        
       
            Cite this dataset as: 
            
           
          Morton, R.D.; Marston, C.G.; O'Neil, A.W.; Rowland, C.S. (2021). Land Cover Map 2020 (25m rasterised land parcels, GB) . NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/6c22cf6e-b224-414e-aa85-900325baedbd
             
             
            
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         By accessing or using this dataset, you agree to the terms of the relevant licence agreement(s). You will ensure that this dataset is cited in any publication that describes research in which the data have been used.
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          https://catalogue.ceh.ac.uk/maps/315e9cbb-efdc-4726-bf97-bd9176af3c9d?request=getCapabilities&service=WMS&cache=false&
         
        
          This is a 25m pixel data set representing the land surface, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a three-band dataset in GeoTiff format, produced by rasterising three properties of the classified land parcels dataset. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover, the third band is a measure of parcel purity. The probability and purity bands (scaled 0 to 100) combine to give an indication of uncertainty. A full description of this and all UKCEH LCM2020 products are available from the LCM2020 product documentation. 
          
         
           Publication date: 2021-10-25
          
         View numbers valid from 01 June 2023 Download numbers valid from 11 November 2021 (information prior to this was not collected)
           
          Format
TIFF
Spatial information
          Study area
         
         
          Spatial representation type
         
         
          Raster
         
        
          Spatial reference system
         
         
          OSGB 1936 / British National Grid
         
        Temporal information
          Temporal extent
         
         2020-01-01    to    2020-12-31
          
         Provenance & quality
         UKCEH's automated land cover classification algorithms generated the 10m classified pixels, from which all remaining products were generated. Training data for classification were automatically selected from stable land covers over the interval of 2017 to 2019. A Random Forest classifier used these to classify four composite images representing per season median surface reflectance. 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 pixel classification into a land parcel framework (the LCM2020 Classified Land Parcels product). The classified land parcels were compared to known land cover producing confusion matrix to determine overall and per class accuracy. Details are available from the product documentation.
 
This dataset represents LCM2020 25m rasterised land parcels. It was produced by rasterising three properties of the LCM2020 Classified Land Parcels GB product (_mode, _conf and _purity).
       Land cover was validated by organising the pixel classification into a land parcel framework (the LCM2020 Classified Land Parcels product). The classified land parcels were compared to known land cover producing confusion matrix to determine overall and per class accuracy. Details are available from the product documentation.
This dataset represents LCM2020 25m rasterised land parcels. It was produced by rasterising three properties of the LCM2020 Classified Land Parcels GB product (_mode, _conf and _purity).
Licensing and constraints
Licence terms and conditions apply
         Cite this dataset as: 
         
       Morton, R.D.; Marston, C.G.; O'Neil, A.W.; Rowland, C.S. (2021). Land Cover Map 2020 (25m rasterised land parcels, GB) . NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/6c22cf6e-b224-414e-aa85-900325baedbd
          
          
         
        Related
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Citations
Shaw, J., Cunningham, C., Harper, S., Ragazzon-Smith, A., Lythgoe, P.R. & Walker, T.R. (2023) Biomonitoring of honey metal(loid) pollution in Northwest England by citizen scientists. Environmental Advances 13, 100406.  https://doi.org/10.1016/j.envadv.2023.100406
        
        Chapman, C., & Hall, J.W. (2022). Designing green infrastructure and sustainable drainage systems in urban development to achieve multiple ecosystem benefits. In Sustainable Cities and Society (Vol. 85, p. 104078). Elsevier BV.   https://doi.org/10.1016/j.scs.2022.104078
        
        Jones, G.C.A., Woods, D., Broom, C.M., Panter, C.T., Sutton, L.J., Drewitt, E.J.A., & Fathers, J. (2024). Fine-Scale Spatial Variation in Eurasian Kestrel Falco tinnunculus Diet in Southern England Revealed from Indirect Prey Sampling and Direct Stable Usotope Analysis. In Ardea (Vol. 112, Issue 1). Netherlands Ornithologists' Union.   https://doi.org/10.5253/arde.2023.a3
        
       Correspondence/contact details
          Morton, D.
         
         
          UK Centre for Ecology & Hydrology
         
         
          Lancaster Environment Centre, Library Avenue, Bailrigg
Lancaster
Lancashire
LA1 4AP
UNITED KINGDOM
         
  enquiries@ceh.ac.uk
        Lancaster
Lancashire
LA1 4AP
UNITED KINGDOM
Authors
Other contacts
          Rights holder
         
         
           UK Centre for Ecology & Hydrology
          
         
          Custodian
         
         
            NERC EDS Environmental Information Data Centre
           
  info@eidc.ac.uk
          
          Publisher
         
         
            NERC EDS Environmental Information Data Centre
           
  info@eidc.ac.uk
           
      
 https://orcid.org/0000-0003-3947-6463
 https://orcid.org/0000-0003-3947-6463