[HTML][HTML] Hazard Susceptibility Mapping with Machine and Deep Learning: A Literature Review
AJ Pugliese Viloria, A Folini, D Carrion, MA Brovelli - Remote Sensing, 2024 - mdpi.com
With the increase in climate-change-related hazardous events alongside population
concentration in urban centres, it is important to provide resilient cities with tools for …
concentration in urban centres, it is important to provide resilient cities with tools for …
A systematic literature review on classification machine learning for urban flood hazard mapping
M El baida, M Hosni, F Boushaba… - Water Resources …, 2024 - Springer
The computational expensiveness of the hydrodynamic models and the complexity of the
rainfall-runoff transformation process presents a pressing need to shift to machine learning …
rainfall-runoff transformation process presents a pressing need to shift to machine learning …
Flood hazard assessment in Yemen using a novel hybrid approach of Grey Wolf and Levenberg Marquardt optimizers
This study aims to map flood susceptibility in the Qaa'Jahran watersheds located in Dhamar,
Yemen, using geoprocessing and computational techniques. Historical flood data and SAR …
Yemen, using geoprocessing and computational techniques. Historical flood data and SAR …
Ensemble learning-based applied research on heavy metals prediction in a soil-rice system
H Hao, P Li, W Jiao, D Ge, C Hu, J Li, Y Lv… - Science of the Total …, 2023 - Elsevier
Accurate prediction of heavy metal accumulation in soil ecosystems is crucial for maintaining
healthy soil environments and ensuring high-quality agricultural products, as well as a …
healthy soil environments and ensuring high-quality agricultural products, as well as a …
Water level identification with laser sensors, inertial units, and machine learning
Flood risk management usually hinges on accurate water level identification in urban
streams such as rivers or creeks. Although research has emphasised the applicability of …
streams such as rivers or creeks. Although research has emphasised the applicability of …
Rapid prediction of urban flooding at street-scale using physics-informed machine learning-based surrogate modeling
Extreme weather has devastating impacts on communities, ecosystems, and infrastructure.
Reliable and timely predictions of flood hazards are central to better manage risk and …
Reliable and timely predictions of flood hazards are central to better manage risk and …
Optimal fuzzy wavelet neural network based road damage detection
Floods are one of the most severe and most frequent natural calamities. It causes enormous
economic damage and even leads to higher mortality rates. Studies on damage detection of …
economic damage and even leads to higher mortality rates. Studies on damage detection of …
A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping
This study addresses the challenges of flash flood susceptibility mapping in Yemen's
Qaa'Jahran Basin, characterized by complex terrain and limited hydro-meteorological data …
Qaa'Jahran Basin, characterized by complex terrain and limited hydro-meteorological data …
[HTML][HTML] Estimating elements susceptible to urban flooding using multisource data and machine learning
The accuracy of flood susceptibility prediction (FSP) could be affected by inadequate
representation of flood conditioning factors (FCFs) and the approaches used to identify the …
representation of flood conditioning factors (FCFs) and the approaches used to identify the …
Data-driven urban waterlogging risk management approach considering efficiency-equity trade-offs and risk mitigation capability evaluation
D Wang, L Zhang, Q Wu, H Guo - Journal of Hydrology, 2024 - Elsevier
Because disaster reduction resources are always constrained, risk mitigation measures and
policies need to be weighted toward efficiency or equity. Greater efficiency focuses on high …
policies need to be weighted toward efficiency or equity. Greater efficiency focuses on high …