[HTML][HTML] Flash flood susceptibility modelling using soft computing-based approaches: from bibliometric to meta-data analysis and future research directions

G Hinge, MA Hamouda, MM Mohamed - Water, 2024 - mdpi.com
In recent years, there has been a growing interest in flood susceptibility modeling. In this
study, we conducted a bibliometric analysis followed by a meta-data analysis to capture the …

[HTML][HTML] Flood susceptibility mapping using a novel integration of multi-temporal sentinel-1 data and eXtreme deep learning model

R Al-Ruzouq, A Shanableh, R Jena, MBA Gibril… - Geoscience …, 2024 - Elsevier
Flash floods (FFs) are amongst the most devastating hazards in arid regions in response to
climate change and can cause the loss of agricultural land, human lives and infrastructure …

[HTML][HTML] Uncertainty reduction in Flood susceptibility mapping using Random Forest and eXtreme Gradient Boosting algorithms in two Tropical Desert cities, Shibam …

AR Al-Aizari, H Alzahrani, OF AlThuwaynee… - Remote Sensing, 2024 - mdpi.com
Flooding is a natural disaster that coexists with human beings and causes severe loss of life
and property worldwide. Although numerous studies for flood susceptibility modelling have …

Climate change induced disasters and highly vulnerable infrastructure in Uttarakhand, India: current status and way forward towards resilience and long-term …

G Singh, A Pandey - Sustainable and Resilient Infrastructure, 2024 - Taylor & Francis
The mountain state of Uttarakhand constitutes a part of the North-western Indian Himalayan
region and is inherently vulnerable to natural disasters. It is witnessing faster melting of …

Forecasting of compound ocean-fluvial floods using machine learning

S Moradian, A AghaKouchak, S Gharbia… - Journal of …, 2024 - Elsevier
Flood modelling and forecasting can enhance our understanding of flood mechanisms and
facilitate effective management of flood risk. Conventional flood hazard and risk …

Flood susceptibility mapping through geoinformatics and ensemble learning methods, with an emphasis on the AdaBoost-Decision Tree algorithm, in Mazandaran …

M Jahanbani, MH Vahidnia, H Aghamohammadi… - Earth Science …, 2024 - Springer
Floods, as natural disasters, impose significant human and financial burdens, necessitating
stringent mitigation measures. The recurrent annual incidence of floods precipitates …

[HTML][HTML] Pluvial flood risk assessment for 2021–2050 under climate change scenarios in the Metropolitan City of Venice

E Allegri, M Zanetti, S Torresan, A Critto - Science of the Total Environment, 2024 - Elsevier
Pluvial flood is a natural hazard occurring from extreme rainfall events that affect millions of
people around the world, causing damages to their properties and lives. The magnitude of …

Application of Naive Bayes, kernel logistic regression and alternation decision tree for landslide susceptibility mapping in Pengyang County, China

H Shang, S Liu, J Zhong, P Tsangaratos, I Ilia, W Chen… - Natural Hazards, 2024 - Springer
The purpose of this research is to apply and compare the performance of the three machine
learning algorithms-Naive Bayes (NB), kernel logistic regression (KLR), and alternation …

[HTML][HTML] Flood risk assessment in arid and semi-arid regions using Multi-criteria approaches and remote sensing in a data-scarce region

MAS Almouctar, Y Wu, S An, X Yin, C Qin… - Journal of Hydrology …, 2024 - Elsevier
Flooding is a natural disaster that poses a threat to both people and the environment,
necessitating proactive assessment and mitigation strategies to protect vulnerable …

Flood subsidence susceptibility mapping using persistent scatterer SAR interferometry technique coupled with novel metaheuristic approaches from Jeddah, Saudi …

SI Abba, AM Al-Areeq, M Ghaleb, AQ Kawara… - Neural Computing and …, 2024 - Springer
Efficient flood risk management hinges on the precise mapping and assessment of areas
vulnerable to flooding. This research endeavors to advance the flood susceptibility mapping …