Marston, C.; Rowland, C.S.; O’Neil, A.W.; Morton, R.D.
Land Cover Map 2021 (land parcels, N. Ireland)
Cite this dataset as:
Marston, C.; Rowland, C.S.; O’Neil, A.W.; Morton, R.D. (2022). Land Cover Map 2021 (land parcels, N. Ireland). NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/abe1f414-6168-4e04-9dc9-4a658a3136ca
Bespoke licensing conditions apply to these data. If you choose to download the data, the UKCEH Data Licensing team will contact you to negotiate a licence.
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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.
Bespoke licensing conditions apply to these data. If you choose to download the data, the UKCEH Data Licensing team will contact you to negotiate a licence.
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https://doi.org/10.5285/abe1f414-6168-4e04-9dc9-4a658a3136ca
This is a vector data set representing the land surface of Northern Ireland, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. This vector Land Parcel dataset is the result of intersecting the 10m raster classified pixel datasets with the UKCEH Land Parcel Spatial Framework to generate summary land parcel attributes for each land cover parcel. A full description of this and all UKCEH LCM2021 products are available from the LCM2021 product documentation accompanying this dataset.
Publication date: 2022-08-02
View numbers valid from 01 June 2023 Download numbers valid from 02 August 2022 (information prior to this was not collected)
Format
SQLite
Spatial information
Study area
Spatial representation type
Vector
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 data.
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 data.
Licensing and constraints
Bespoke licensing conditions apply to these data. If you choose to download the data, the UKCEH Data Licensing team will contact you to negotiate a licence.
Cite this dataset as:
Marston, C.; Rowland, C.S.; O’Neil, A.W.; Morton, R.D. (2022). Land Cover Map 2021 (land parcels, N. Ireland). NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/abe1f414-6168-4e04-9dc9-4a658a3136ca
Related
This dataset is included in the following collections
Correspondence/contact details
Dr. Chris Marston
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
Additional metadata
Funding
Natural Environment Research Council Award: NE/R016429/1
Last updated
27 February 2024 16:13