Application of stacking hybrid machine learning algorithms in delineating multi-type flooding in Bangladesh

M Rahman, N Chen, A Elbeltagi, MM Islam… - Journal of …, 2021 - Elsevier
Floods are among the most devastating natural hazards in Bangladesh. The country
experiences multi-type floods (ie, fluvial, flash, pluvial, and surge floods) every year …

Flood susceptibility mapping of Northeast coastal districts of Tamil Nadu India using Multi-source Geospatial data and Machine Learning techniques

S Saravanan, D Abijith - Geocarto International, 2022 - Taylor & Francis
Flooding is one of the most challenging and important natural disasters to predict, it is
becoming more frequent and more intense. The study area is badly damaged by devastating …

Potential flood-prone area identification and mapping using GIS-based multi-criteria decision-making and analytical hierarchy process in Dega Damot district …

A Negese, D Worku, A Shitaye, H Getnet - Applied Water Science, 2022 - Springer
Flood is one of the natural hazards that causes widespread destruction such as huge
infrastructural damages, considerable economic losses, and social disturbances across the …

Evaluation of flood susceptibility prediction based on a resampling method using machine learning

S Aldiansyah, F Wardani - Journal of Water and Climate Change, 2023 - iwaponline.com
The largest recorded flood loss occurred in the study area in 2013. This study aims to
examine resampling methods (ie cross-validation (CV), bootstrap, and random …

[HTML][HTML] Flood risk mapping of the flood-prone Rangpur division of Bangladesh using remote sensing and multi-criteria analysis

SMS Rana, SMA Habib, MNH Sharifee… - Natural Hazards …, 2024 - Elsevier
Identification of potential flood risk areas is crucial to reduce flood damage for the frequently
flooded and low-lying South Asian developing countries. The present study has prepared …

Spatial congruency or discrepancy? Exploring the spatiotemporal dynamics of built-up expansion patterns and flood risk

M Mabrouk, H Han, KI Abdrabo, MGN Mahran… - Science of The Total …, 2024 - Elsevier
Most coastal cities have been experiencing unprecedented urbanization-induced flood risk,
climatic events, and haphazard anthropogenic activities, jeopardizing residents' lives and …

[HTML][HTML] Assessing multi-climate-hazard threat in the coastal region of Bangladesh by combining influential environmental and anthropogenic factors

S Murshed, AL Griffin, MA Islam, XH Wang… - Progress in Disaster …, 2022 - Elsevier
This study developed a geo-spatial framework for assessing multi-hazard threat on the
Bangladesh coast, integrating environmental hazards (EH), geo-environmental attributes …

Novel hybrid models by coupling support vector regression (SVR) with meta-heuristic algorithms (WOA and GWO) for flood susceptibility mapping

F Rezaie, M Panahi, SM Bateni, C Jun, CMU Neale… - Natural Hazards, 2022 - Springer
Schools as social bases and children's centers are among the most vulnerable areas to
flooding. Flood susceptibility mapping is very important for flood preparedness and adopting …

[HTML][HTML] Thematic and Bibliometric Review of Remote Sensing and Geographic Information System-Based Flood Disaster Studies in South Asia During 2004–2024

JAT Madushani, NC Withanage, PK Mishra, G Meraj… - Sustainability, 2024 - mdpi.com
Floods have catastrophic effects worldwide, particularly in monsoonal Asia. This systematic
review investigates the literature from the past two decades, focusing on the use of remote …

A machine learning-based approach for flash flood susceptibility mapping considering rainfall extremes in the northeast region of Bangladesh

ME Chowdhury, AKMS Islam, RU Zzaman… - Advances in Space …, 2024 - Elsevier
Flash floods are catastrophic global events, especially in northeast Bangladesh, and
assessing flash flood susceptibility is crucial for preparedness and mitigation. Traditional …