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[HTML][HTML] Urban flood modeling using deep-learning approaches in Seoul, South Korea
Identification of flood-prone sites in urban environments is necessary, but there is insufficient
hydraulic information and time series data on surface runoff. To date, several attempts have …
hydraulic information and time series data on surface runoff. To date, several attempts have …
Deep learning enables super-resolution hydrodynamic flooding process modeling under spatiotemporally varying rainstorms
J He, L Zhang, T ** and flood vulnerability analysis of residential buildings: The case of Khando River in eastern Nepal
Study region This study considers the Khando River (a tributary of Koshi River) in eastern
Nepal. Study focus To quantify the hazard and vulnerabilities across one of the frequently …
Nepal. Study focus To quantify the hazard and vulnerabilities across one of the frequently …
Water identification from high-resolution remote sensing images based on multidimensional densely connected convolutional neural networks
G Wang, M Wu, X Wei, H Song - Remote sensing, 2020 - mdpi.com
The accurate acquisition of water information from remote sensing images has become
important in water resources monitoring and protections, and flooding disaster assessment …
important in water resources monitoring and protections, and flooding disaster assessment …
Application of entropy weighting method for urban flood hazard map**
Flooding is one of the most frequently occurring natural hazards worldwide. Map** and
assessment of possible flood hazards are critical components of the evaluation and …
assessment of possible flood hazards are critical components of the evaluation and …
Improving urban flood susceptibility map** using transfer learning
The flood inventory in urban areas is often difficult to collect and therefore inadequate for
training a machine learning (ML)-based assessment model. In this study, we investigated …
training a machine learning (ML)-based assessment model. In this study, we investigated …