The use of satellite remote sensing for exploring river meander migration

被引:3
|
作者
Nagel, Gustavo Willy [1 ]
Darby, Stephen E. [2 ]
Leyland, Julian [2 ]
机构
[1] Univ Southampton, Sch Ocean & Earth Sci, Southampton SO17 1BJ, England
[2] Univ Southampton, Dept Geog, Southampton SO17 1BJ, England
关键词
Remote sensing; River meander migration; Rivers; Fluvial dynamics; DIFFERENCE WATER INDEX; CHANNEL MIGRATION; PLANFORM GEOMETRY; FLOW STRUCTURE; CHUTE-CUTOFF; BAR PUSH; AMAZON; MORPHODYNAMICS; DYNAMICS; EXTRACTION;
D O I
10.1016/j.earscirev.2023.104607
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Meandering rivers are complex systems that support high rates of biodiversity and the livelihoods of millions of inhabitants through their ecological services. Meandering rivers are often located in remote locations and cover long distances. As a result, observational satellites are crucial for investigating and monitoring meandering river dynamics. Satellite remote sensing technology is responsible for many advances in our knowledge about the variables that affect these rivers and their interaction with their surrounding floodplains. Furthermore, new sensors and the advent of cloud computing are allowing researchers to revisit theories that have hitherto lacked observational evidence to support them. In this paper, we review articles that have applied remote sensing techniques to analyse river meander migration processes. Our findings show that the majority of articles analysed the meandering rivers of the Ganges/Brahmaputra (29.0% of all articles) and the Amazon Basin (26.1%). We propose that these two locations are popular for different reasons: to improve management in highly populated floodplains of Ganges/Brahmaputra, and to investigate the meandering mechanisms without major anthropogenic interference in the Amazon Basin. Furthermore, most of the articles used Landsat for river monitoring (80.7%) and tracked the river changes throughout time using satellite time series (82.0%). However, the incorporation of Synthetic Aperture Radar satellites in papers was minimal, and only a small fraction (13%) of studies utilized cloud computing platforms for processing satellite images. Finally, we discuss new possibilities in terms of sensors and processing that might in the future advance our knowledge of river geomorphology.
引用
收藏
页数:15
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