Improving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series

Lopes, M, Frison, P, Crowson, M et al. (8 more authors) (2020) Improving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series. Methods in Ecology and Evolution, 11 (4). pp. 532-541. ISSN 2041-210X

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Copyright, Publisher and Additional Information: © 2020 British Ecological Society. All rights reserved. This is the peer reviewed version of the following article: Lopes, M, Frison, P, Crowson, M et al. (8 more authors) (2020) Improving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series. Methods in Ecology and Evolution, 11 (4). 2041-210X.13359. pp. 532-541. ISSN 2041-210X. Accepted Author Manuscript, which has been published in final form at https://doi.org/10.1111/2041-210X.13359. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
Keywords: cloud persistent areas; data combination; land cover mapping; remote sensing; satellite image time series; Sentinel‐1; Sentinel‐2
Dates:
  • Published: 2 April 2020
  • Accepted: 23 December 2019
  • Published (online): 27 January 2020
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biology (Leeds)
The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Sustainability Research Institute (SRI) (Leeds)
Funding Information:
FunderGrant number
NERC (Natural Environment Research Council)Not Known
Depositing User: Symplectic Publications
Date Deposited: 14 Feb 2020 12:29
Last Modified: 27 Jan 2021 01:39
Status: Published
Publisher: Wiley
Identification Number: https://doi.org/10.1111/2041-210x.13359

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