Application of LiDAR UAV for High-Resolution Flood Modelling

Bingyao Li, Jingming Hou (), Donglai Li, Dong Yang, Hao Han, Xu Bi, Xinghua Wang, Reinhard Hinkelmann and Junqiang Xia
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Bingyao Li: Xi’an University of Technology
Jingming Hou: Xi’an University of Technology
Donglai Li: Xi’an University of Technology
Dong Yang: Xi’an University of Technology
Hao Han: Xi’an University of Technology
Xu Bi: Xi’an Meteorological Bureau
Xinghua Wang: Xi’an University of Technology
Reinhard Hinkelmann: Technische Universität Berlin
Junqiang Xia: Wuhan University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2021, vol. 35, issue 5, No 3, 1433-1447

Abstract: Abstract To overcome the difficulty of collecting fine-grained terrain data that is important for flood modelling, this work presents a method for the application of UAV-based LiDAR techniques to drive high-resolution flood propagation and inundation modelling. This paper comprehensively introduces the UAV platform, LiDAR sensor and data processing techniques required and proposes the approach for obtaining refined DEM for flood management using which the DEM accuracy can reach ±3 cm. Accordingly, two kinds of terrains, a small mountain area and a large urban area, have been measured and the time requirements for the method are 5 h and 2 days respectively. Based on the collected data, a full hydrodynamic numerical flood model is applied to simulate a flash flood in the mountain catchment and an urban flood at high-resolution. The results show that the water depth and velocity affected by key micro terrain features, such as tiny channels and roads, can be captured and considered, indicating that LiDAR UAV techniques are an efficient and reliable method for surveying terrain making them highly important for creating high accurate flood simulation.

Keywords: LiDAR; UAV; Filtering algorithm; High-resolution modelling; Flood simulation (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11269-021-02783-w

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