Classifying grass-dominated habitats from remotely sensed data: The influence of spectral resolution, acquisition time and the vegetation classification system on accuracy and thematic resolution

Bradter, U, O'Connell, J, Kunin, WE orcid.org/0000-0002-9812-2326 et al. (3 more authors) (2020) Classifying grass-dominated habitats from remotely sensed data: The influence of spectral resolution, acquisition time and the vegetation classification system on accuracy and thematic resolution. Science of the Total Environment, 711. 134584. ISSN 0048-9697

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2019 The Author(s). Published by Elsevier B.V. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)
Keywords: Hyperspectral; Mapping; Multispectral; National Vegetation Classification (NVC); Random forest; Vegetation community
Dates:
  • Published: 1 April 2020
  • Accepted: 19 September 2019
  • Published (online): 3 November 2019
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biology (Leeds)
Funding Information:
FunderGrant number
BBSRC (Biotechnology & Biological Sciences Research Council)BB/J005851/1
Depositing User: Symplectic Publications
Date Deposited: 23 Sep 2019 14:34
Last Modified: 09 Mar 2020 16:49
Status: Published
Publisher: Elsevier
Identification Number: https://doi.org/10.1016/j.scitotenv.2019.134584

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