Estimating Elements Susceptible to Urban Flooding Using Multisource Data and Machine Learning

Author:

Asfaw Wegayehu,Rientjes Tom H. M.,Bekele Tilaye Worku,Haile Alemseged Tamiru

Publisher

Elsevier BV

Reference73 articles.

1. Assessing urban areas vulnerability to pluvial flooding using GIS applications and Bayesian Belief Network model;Y Abebe;J. Clean. Prod,2018

2. A machine learning approach to evaluate the spatial variability of New York City's 311 street flooding complaints;C Agonafir;Comput. Environ. Urban Syst,2022

3. Flash flood hazard mapping using remote sensing and GIS techniques in southwestern Saudi Arabia;S S Alarifi;Sustain,2022

4. Leveraging machine learning for predicting flash flood damage in the Southeast US;A Alipour;Environ. Res. Lett,2020

5. Flash flood susceptibility modelling using functional tree and hybrid ensemble techniques;A Arabameri;J. Hydrol,2020

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