Literature DB >> 32349959

Using remote sensing to characterize riparian vegetation: A review of available tools and perspectives for managers.

Leo Huylenbroeck1, Marianne Laslier2, Simon Dufour3, Blandine Georges4, Philippe Lejeune4, Adrien Michez4.   

Abstract

Riparian vegetation is a central component of the hydrosystem. As such, it is often subject to management practices that aim to influence its ecological, hydraulic or hydrological functions. Remote sensing has the potential to improve knowledge and management of riparian vegetation by providing cost-effective and spatially continuous data over wide extents. The objectives of this review were twofold: to provide an overview of the use of remote sensing in riparian vegetation studies and to discuss the transferability of remote sensing tools from scientists to managers. We systematically reviewed the scientific literature (428 articles) to identify the objectives and remote sensing data used to characterize riparian vegetation. Overall, results highlight a strong relationship between the tools used, the features of riparian vegetation extracted and the mapping extent. Very high-resolution data are rarely used for rivers longer than 100 km, especially when mapping species composition. Multi-temporality is central in remote sensing riparian studies, but authors use only aerial photographs and relatively coarse resolution satellite images for diachronic analyses. Some remote sensing approaches have reached an operational level and are now used for management purposes. Overall, new opportunities will arise with the increased availability of very high-resolution data in understudied or data-scarce regions, for large extents and as time series. To transfer remote sensing approaches to riparian managers, we suggest mutualizing achievements by producting open-access and robust tools. These tools will then have to be adapted to each specific project, in collaboration with managers.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Keywords:  Alluvial forest; Floodplain vegetation; LiDAR; Riparian forest; Satellite; UAV

Year:  2020        PMID: 32349959     DOI: 10.1016/j.jenvman.2020.110652

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  1 in total

1.  Composition and distribution of vegetation in the water level fluctuating zone of the Lantsang cascade reservoir system using UAV multispectral imagery.

Authors:  Weiwei Jiang; Lun Liu; Henglin Xiao; Song Zhu; Wentao Li; Ying Liu
Journal:  PLoS One       Date:  2021-03-29       Impact factor: 3.240

  1 in total

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