Flash Flood Susceptibility Modeling Using New Approaches of Hybrid and Ensemble Tree-Based Machine Learning Algorithms

Flash flooding is considered one of the most dynamic natural disasters for which measures need to be taken to minimize economic damages, adverse effects, and consequences by mapping flood susceptibility. Identifying areas prone to flash flooding is a crucial step in flash flood hazard management. In...

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Veröffentlicht in:	Remote sensing (Basel, Switzerland) Jg. 12; H. 21; S. 3568
Hauptverfasser:	Band, Shahab S., Janizadeh, Saeid, Chandra Pal, Subodh, Saha, Asish, Chakrabortty, Rabin, Melesse, Assefa M., Mosavi, Amirhosein
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 31.10.2020
Schlagworte:	adverse effects Algorithms altitude area artificial intelligence big data Climate change Construction Coverage Data science decision support systems Decision trees disasters extremely randomized trees (ERT) Flash floods flash-flood susceptibility flood control Flood damage Flood hazards Flood management Flood mapping Flooding Floods Generalized linear models Geographic information systems hybrids Hydrology Iran Learning algorithms Machine learning Mapping Mathematical models Modelling Natural disasters parallel random forest Parameters planning Precipitation rain Rainfall Regression analysis Regularization methods regularized random forest Remote sensing rivers Runoff Software Susceptibility Watersheds Iran
ISSN:	2072-4292, 2072-4292
Online-Zugang:	Volltext
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