Drone-based Structure-from-Motion provides accurate forest canopy data to assess shading effects in river temperature models

Dugdale, Stephen J.; Malcolm, Iain A.; Hannah, David M.

Abstract

Climatic warming will increase river temperature globally, with consequences for cold water-adapted organisms. In regions with low forest cover, elevated river temperature is often associated with a lack of bankside shading. Consequently, river managers have advocated riparian tree planting as a strategy to reduce temperature extremes. However, the effect of riparian shading on river temperature varies substantially between locations. Process-based models can elucidate the relative importance of woodland and other factors driving river temperature and thus improve understanding of spatial variability of the effect of shading, but characterising the spatial distribution and height of riparian tree cover necessary to parameterise these models remains a significant challenge. Here, we document a novel approach that combines Structure-from-Motion (SfM) photogrammetry acquired from a drone to characterise the riparian canopy with a process based temperature model (Heat Source) to simulate the effects of tree shading on river temperature. Our approach was applied in the Girnock Burn, a tributary of the Aberdeenshire Dee, Scotland. Results show that SfM approximates true canopy elevation with a good degree of accuracy (R2 = 0.96) and reveals notable spatial heterogeneity in shading. When these data were incorporated into a process-based temperature model, it was possible to simulate river temperatures with a similarly-high level of accuracy (RMSE

Citation

Dugdale, S. J., Malcolm, I. A., & Hannah, D. M. (2019). Drone-based Structure-from-Motion provides accurate forest canopy data to assess shading effects in river temperature models. Science of the Total Environment, 678, 326-340. https://doi.org/10.1016/j.scitotenv.2019.04.229

• Journal Article Type: Article
• Acceptance Date: Apr 15, 2019
• Online Publication Date: May 8, 2019
• Publication Date: Aug 15, 2019
• Deposit Date: May 9, 2019
• Publicly Available Date: May 9, 2020
• Journal: Science of The Total Environment
• Print ISSN: 0048-9697
• Electronic ISSN: 1879-1026
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 678
• Pages: 326-340
• DOI: https://doi.org/10.1016/j.scitotenv.2019.04.229
• Keywords: River temperature; Structure from motion; Process-based model; Drones; Unoccupied aerial systems; Climate change
• Public URL: https://nottingham-repository.worktribe.com/output/2034002
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0048969719317589?via%3Dihub
• Additional Information: This article is maintained by: Elsevier; Article Title: Drone-based Structure-from-Motion provides accurate forest canopy data to assess shading effects in river temperature models; Journal Title: Science of The Total Environment; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.scitotenv.2019.04.229; Content Type: article; Copyright: Crown Copyright © 2019 Published by Elsevier B.V. All rights reserved.
• Contract Date: May 9, 2019