A Rapid Assessment Method for Flood Risk Mapping Integrating Aerial Point Clouds and Deep Learning

In recent years, floods have brought renewed attention and requirement for real-time and city-scaled flood forecasting due to climate change and urbanization. In this study, a rapid assessment method for flood risk mapping is proposed by integrating aerial point clouds and deep learning technique th...

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Veröffentlicht in:	Water resources management 2024-03, Vol.38 (5), p.1753-1772
Hauptverfasser:	Fang, Xin, Wu, Jie, Jiang, Peiqi, Liu, Kang, Wang, Xiaohua, Zhang, Sherong, Wang, Chao, Li, Heng, Lai, Yishu
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Assessments Atmospheric Sciences case studies China Civil Engineering Climate change Cloud computing Clouds Computation Data acquisition data collection Deep learning Digital Elevation Models Earth and Environmental Science Earth Sciences Embedding Environment Environmental risk Flood forecasting Flood mapping Floods Fluid mechanics Geotechnical Engineering & Applied Earth Sciences Hydrodynamics Hydrogeology Hydrology/Water Resources Image segmentation information science Mapping Photography Physiographic features rapid methods Reconstruction risk Smoothing Spatial data Three dimensional models topography Urbanization water Water transfer
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