LiDAR based Digital Terrain Model (DTM) data for South West England
Cite this dataset as:
Ferraccioli, F.; Gerard, F.; Robinson, C.; Jordan, T.; Biszczuk, M.; Ireland, L.; Beasley, M.; Vidamour, A.; Barker, A.; Arnold, R.; Dinn, M.; Fox, A.; Howard, A. (2014). LiDAR based Digital Terrain Model (DTM) data for South West England. NERC Environmental Information Data Centre. https://doi.org/10.5285/e2a742df-3772-481a-97d6-0de5133f4812
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This dataset is made available under the terms of the Open Government Licence 
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https://doi.org/10.5285/e2a742df-3772-481a-97d6-0de5133f4812
This is a high resolution spatial dataset of Digital Terrain Model (DTM) data in South West England. The DTM along with a Digital Surface Model (DSM) cover an area of 9424 km2 that includes all the land west of Exmouth (i.e. west of circa 3 degrees 21 minutes West). The DTM represents the topographic model (height) of the bare earth. The dataset is a part of outcomes from the Centre for Ecology & Hydrology South West (SW) Project. There is also a Digital Surface Model (DSM) dataset covering the same areas available from the SW project.
Publication date: 2014-04-29
View numbers valid from 01 June 2023 Download numbers valid from 20 June 2024 (information prior to this was not collected)
Format
ASCII grid
Spatial information
Study area
Spatial representation type
Raster
Spatial reference system
OSGB 1936 / British National Grid
Temporal information
Temporal extent
2013-07-01 to 2013-08-31
Provenance & quality
The British Antarctic Survey (BAS) acquired a new high resolution (circa 1 point/meter) and high accuracy (25 cm vertical) LiDAR dataset over Cornwall and Devon during the month of July and August 2013 for the Tellus South West project. The conversion of the raw LiDAR data into the digital terrain and surface model was carried out by the Environment Agency (contract). The spatial dataset consists of 2 cm height layers representing the terrain and surface height respectively at a spatial resolution of 1 m (grid cell) and an average height accuracy of 25 cm. The data is available as individual files representing sections of Ordnance Survey tiles in ESRI grid format (e.g. SX37ne; SX37nw; SX37se; SX37sw).
Licensing and constraints
This dataset is made available under the terms of the Open Government Licence
Cite this dataset as:
Ferraccioli, F.; Gerard, F.; Robinson, C.; Jordan, T.; Biszczuk, M.; Ireland, L.; Beasley, M.; Vidamour, A.; Barker, A.; Arnold, R.; Dinn, M.; Fox, A.; Howard, A. (2014). LiDAR based Digital Terrain Model (DTM) data for South West England. NERC Environmental Information Data Centre. https://doi.org/10.5285/e2a742df-3772-481a-97d6-0de5133f4812
Related
Citations
Orr, R. J., Murray, P. J., Eyles, C. J., Blackwell, M. S. A., Cardenas, L. M., Collins, A. L., … Lee, M. R. F. (2016). The North Wyke Farm Platform: effect of temperate grassland farming systems on soil moisture contents, runoff and associated water quality dynamics. European Journal of Soil Science, 67(4), 374-385 https://doi.org/10.1111/ejss.12350
Collins, A. L., Burak, E., Harris, P., Pulley, S., Cardenas, L., & Tang, Q. (2019). Field scale temporal and spatial variability of δ13C, δ15N, TC and TN soil properties: Implications for sediment source tracing. Geoderma, 333, 108-122 https://doi.org/10.1016/j.geoderma.2018.07.019
Mlambo, R., Woodhouse, I., Gerard, F., & Anderson, K. (2017). Structure from Motion (SfM) Photogrammetry with Drone Data: A Low Cost Method for Monitoring Greenhouse Gas Emissions from Forests in Developing Countries. Forests, 8(3), 68. https://doi.org/10.3390/f8030068
Langford, H.E., Griffiths, H., Horne, D.J., Keen, D.H., & Penkman, K.E.H. (2020). Age-estimate evidence for a complex Middle to Late Pleistocene fluvial terrace aggradation spanning more than a 100-kyr interglacial–glacial cycle at Sutton Cross, eastern England. In Proceedings of the Geologists’ Association (Vol. 131, Issue 6, pp. 758–777). Elsevier BV. https://doi.org/10.1016/j.pgeola.2020.09.001
Yeomans, C.M., Middleton, M., Shail, R.K., Grebby, S., & Lusty, P.A.J. (2019). Integrated Object-Based Image Analysis for semi-automated geological lineament detection in southwest England. In Computers & Geosciences (Vol. 123, pp. 137–148). Elsevier BV. https://doi.org/10.1016/j.cageo.2018.11.005
Wiltshire, C., Glendell, M., Waine, T.W., Grabowski, R.C., & Meersmans, J. (2022). Assessing the source and delivery processes of organic carbon within a mixed land use catchment using a combined n-alkane and carbon loss modelling approach. In Journal of Soils and Sediments (Vol. 22, Issue 5, pp. 1629–1642). Springer Science and Business Media LLC. https://doi.org/10.1007/s11368-022-03197-w
Supplemental information
Correspondence/contact details
Gerard, F.
UK Centre for Ecology & Hydrology
Maclean Building, Benson Lane, Crowmarsh Gifford
Wallingford
Oxfordshire
OX10 8BB
UNITED KINGDOM
enquiries@ceh.ac.uk
Wallingford
Oxfordshire
OX10 8BB
UNITED KINGDOM
Authors
Ferraccioli, F.
Natural Environment Research Council
https://orcid.org/0000-0001-5916-5174
Robinson, C.
Centre for Ecology & Hydrology
Jordan, T.
Centre for Ecology & Hydrology
Biszczuk, M.
Natural Environment Research Council
Ireland, L.
Natural Environment Research Council
Beasley, M.
Natural Environment Research Council
Vidamour, A.
Natural Environment Research Council
Barker, A.
Natural Environment Research Council
Arnold, R.
Natural Environment Research Council
Dinn, M.
Natural Environment Research Council
Fox, A.
Natural Environment Research Council
Howard, A.
Natural Environment Research Council
Other contacts
Custodian
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
info@eidc.ac.uk
Resource provider