Ogunbadewa, EY, Armitage, RP ORCID: https://orcid.org/0000-0002-7569-425X and Danson, FM
ORCID: https://orcid.org/0000-0002-3984-0432
2014,
'Optical medium spatial resolution satellite constellation data for monitoring woodland in the UK'
, Forests, 5 (7)
, pp. 1798-1814.
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Abstract
The aim of this study was to test the potential of a constellation of remote sensing satellites, the Disaster Monitoring Constellation (DMC), for retrieving a temporal record of forest leaf area index (LAI) in the United Kingdom (U.K.). Ground-based LAI measurements were made over a 12-month period in broadleaf woodland at Risley Moss Nature Reserve, Lancashire, U.K. The ground-based LAI varied between zero in January to a maximum of 4.5 in July. Nine DMC images, combining data from UK-DMC and NigeriaSat-1, were acquired, and all images were cross-calibrated and atmospherically corrected. The spectral reflectance of the test site was extracted, and a range of vegetation indices were then computed and correlated with the ground measurements of LAI. The soil adjusted vegetation index (SAVI) had the strongest correlation, and this was used to derive independent estimates of LAI using the “leave-one-out” method. The root mean square error of the LAI estimates was 0.47, which was close to that calculated for the ground-measured LAI. This study shows, for the first time, that data from a constellation of high temporal, medium spatial resolution optical satellite sensors may be used to map seasonal variation in woodland canopy leaf area index (LAI) in cloud-prone areas, like the U.K.
Item Type: | Article |
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Themes: | Subjects outside of the University Themes |
Schools: | Schools > School of Environment and Life Sciences > Ecosystems and Environment Research Centre |
Journal or Publication Title: | Forests |
Publisher: | Multidisciplinary Digital Publishing Institute (MDPI) |
Refereed: | Yes |
ISSN: | 1999-4907 |
Related URLs: | |
Funders: | Nigerian Government |
Depositing User: | DR Richard P Armitage |
Date Deposited: | 13 Aug 2014 11:37 |
Last Modified: | 15 Feb 2022 18:37 |
URI: | https://usir.salford.ac.uk/id/eprint/32106 |
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