07 Jan 2022
07 Jan 2022
Status: this preprint is currently under review for the journal ESurf.

Exploring the 4D scales of eco-geomorphic interactions along a river corridor using repeat UAV Laser Scanning (UAV-LS), multispectral imagery, and a functional traits framework

Christopher Tomsett and Julian Leyland Christopher Tomsett and Julian Leyland
  • School of Geography and Environmental Science, University of Southampton, Highfield, Southampton, SO17 1BJ, UK

Abstract. Vegetation plays a critical role in the modulation of fluvial process and morphological evolution. However, adequately capturing the spatial variability and complexity of vegetation characteristics remains a challenge. Currently, most of the research seeking to address these issues takes place at either the individual plant scale or via larger scale bulk classifications, with the former seeking to characterise vegetation-flow interactions and the latter identifying spatial variation in vegetation types. Herein, we devise a method which extracts functional vegetation traits using UAV laser scanning and multispectral imagery, and upscale these to reach scale guild classifications. Simultaneous monitoring of morphological change is undertaken to identify eco-geomorphic links between different guilds and the geomorphic response of the system in the context of long-term decadal changes. Identification of four guilds from quantitative structural modelling based on analysis of terrestrial and UAV based laser scanning and two further guilds from image analysis was achieved. These were upscaled to reach-scale guild classifications with an overall accuracy of 80 % and links to magnitudes of geomorphic activity explored. We show that different vegetation guilds have a role in influencing morphological change through the stabilisation of banks, but that limits on this influence are evident in the prior long-term analysis. This research reveals that remote sensing offers a solution to the difficulty of scaling traits-based approaches for eco-geomorphic research, and that these methods may be applied to larger areas using airborne laser scanning and satellite imagery datasets.

Christopher Tomsett and Julian Leyland

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on esurf-2021-102', Anonymous Referee #1, 10 Feb 2022
  • RC2: 'Comment on esurf-2021-102', Anonymous Referee #2, 13 Apr 2022

Christopher Tomsett and Julian Leyland

Christopher Tomsett and Julian Leyland


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Short summary
Vegetation influences how rivers change through time, yet the way in which we analyse vegetation is limited. Current methods collect detailed data at the individual plant level or determine dominant vegetation types across larger areas. Herein, we use UAVs to collect detailed vegetation datasets for a 1 km length of river and link vegetation properties to channel evolution occurring within the study site, providing a new method for investigating the influence of vegetation on river systems.