Land Cover Map 2021 (10m classified pixels, GB)

https://doi.org/10.5285/a22baa7c-5809-4a02-87e0-3cf87d4e223a

Download data Supporting docs Cite this dataset

PLEASE NOTE:

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.

Licence terms and conditions apply

Download the data

Add to your GIS application:

https://catalogue.ceh.ac.uk/maps/2ad19a50-b940-469e-a40d-17818b77020c?request=getCapabilities&service=WMS&cache=false&

This is a 10m pixel data set representing the land surface of Great Britain, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a two-band raster in GeoTiff format. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover. A full description of this and all UKCEH LCM2021 products are available from the LCM2021 product documentation accompanying this dataset.

Publication date: 2022-08-03

9 citations

443 downloads *

12,190 views *

More information

View numbers valid from 01 June 2023 Download numbers valid from 03 August 2022 (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

2021-01-01 to 2021-12-31

Provenance & quality

UKCEH's automated land cover algorithms classify 10 m pixels across the whole of UK. Training data were automatically selected from stable land covers over the interval of 2018 to 2020. 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 10 m pixel classification into a land parcel framework (the LCM2021 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 accompanying this dataset.

The 25 m rasterised land parcels product is created by pixelating the corresponding land parcel product.

Licensing and constraints

Licence terms and conditions apply

Cite this dataset as:

Marston, C.; Rowland, C.S.; O'Neil, A.W.; Morton, R.D. (2022). Land Cover Map 2021 (10m classified pixels, GB). NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/a22baa7c-5809-4a02-87e0-3cf87d4e223a

BibTeX RIS

Services associated with this dataset

UK gridded population at 1 km resolution for 2021 based on Census 2021/2022 and Land Cover Map 2021

Land Cover Map 2021 10m web map service

This dataset is included in the following collections

Land Cover Map 2021

Citations

Price, B., Huber, N., Nussbaumer, A., & Ginzler, C. (2023). The Habitat Map of Switzerland: A Remote Sensing, Composite Approach for a High Spatial and Thematic Resolution Product. In Remote Sensing (Vol. 15, Issue 3, p. 643) https://doi.org/10.3390/rs15030643

Marston, C.G., O'Neil, A.W., Morton, R.D., Wood, C.M., & Rowland, C.S. (2023). LCM2021 – the UK Land Cover Map 2021. In Earth System Science Data (Vol. 15, Issue 10, pp. 4631–4649). Copernicus GmbH. https://doi.org/10.5194/essd-15-4631-2023

Filippelli, S.K., Schleeweis, K., Nelson, M.D., Fekety, P.A., & Vogeler, J.C. (2024). Testing temporal transferability of remote sensing models for large area monitoring. In Science of Remote Sensing (Vol. 9, p. 100119). Elsevier BV. https://doi.org/10.1016/j.srs.2024.100119

van der Plas, T.L., Geikie, S.T., Alexander, D.G., & Simms, D.M. (2023). Multi-Stage Semantic Segmentation Quantifies Fragmentation of Small Habitats at a Landscape Scale. In Remote Sensing (Vol. 15, Issue 22, p. 5277). MDPI AG. https://doi.org/10.3390/rs15225277

Hooftman, D.A.P., Ridding, L.E., Redhead, J.W., & Willcock, S. (2023). National scale mapping of supply and demand for recreational ecosystem services. In Ecological Indicators (Vol. 154, p. 110779). Elsevier BV. https://doi.org/10.1016/j.ecolind.2023.110779

Lewis, C.H.M., Little, K., Graham, L.J., Kettridge, N., & Ivison, K. (2024). Diurnal fuel moisture content variations of live and dead Calluna vegetation in a temperate peatland. In Scientific Reports (Vol. 14, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1038/s41598-024-55322-z

Tomkins, M., McDonald, H., Huck, J.J., Tippet, J., Elliot, S., Harris, E., & Maxwell, C. (2024). Modelling the cooling effects of urban canals. Zenodo. https://doi.org/10.5281/ZENODO.10927598

Dennis, M., Huck, J. ., Holt, C. D., Bispo, P. da C., McHenry, E., Speak, A., & James, P. (2024). Land-cover gradients determine alternate drivers of mammalian species richness in fragmented landscapes. In Landscape Ecology (Vol. 39, Issue 8). Springer Science and Business Media LLC. https://doi.org/10.1007/s10980-024-01952-7

Rong, Y., Bates, P., & Neal, J. (2024). GPU‐Accelerated Urban Flood Modeling Using a Nonuniform Structured Grid and a Super Grid Scale River Channel. In Water Resources Research (Vol. 60, Issue 6). American Geophysical Union (AGU). https://doi.org/10.1029/2023wr036128