[HTML][HTML] Flood susceptibility map**: integrating machine learning and GIS for enhanced risk assessment

Z Demissie, P Rimal, WM Seyoum, A Dutta… - Applied Computing and …, 2024‏ - Elsevier
Flooding presents a formidable challenge in the United States, endangering lives and
causing substantial economic damage, averaging around $5 billion annually. Addressing …

Flood susceptible prediction through the use of geospatial variables and machine learning methods

NM Gharakhanlou, L Perez - Journal of hydrology, 2023‏ - Elsevier
Floods are one of the most perilous natural calamities that cause property destruction and
endanger human life. The spatial patterns of flood susceptibility were assessed in this study …

[HTML][HTML] Flood prediction with time series data mining: Systematic review

DK Hakim, R Gernowo, AW Nirwansyah - Natural Hazards Research, 2024‏ - Elsevier
The global community is continuously working to minimize the impact of disasters through
various actions, including earth surveying. For example, flood-prone areas must be …

Modelling flood susceptibility based on deep learning coupling with ensemble learning models

Y Li, H Hong - Journal of Environmental Management, 2023‏ - Elsevier
Modelling flood susceptibility is an indirect way to reduce the loss from flood disaster. Now,
flood susceptibility modelling based on data driven model is state-of-the-art method such as …

[HTML][HTML] A novel framework for addressing uncertainties in machine learning-based geospatial approaches for flood prediction

MSG Adnan, ZS Siam, I Kabir, Z Kabir… - Journal of …, 2023‏ - Elsevier
Globally, many studies on machine learning (ML)-based flood susceptibility modeling have
been carried out in recent years. While majority of those models produce reasonably …

Urban flood vulnerability assessment in a densely urbanized city using multi-factor analysis and machine learning algorithms

F Parvin, SA Ali, B Calka, E Bielecka, NTT Linh… - Theoretical and Applied …, 2022‏ - Springer
Flood is considered as the most devastating natural hazards that cause the death of many
lives worldwide. The present study aimed to predict flood vulnerability for Warsaw, Poland …

Living with floods using state-of-the-art and geospatial techniques: flood mitigation alternatives, management measures, and policy recommendations

R Chakrabortty, SC Pal, D Ruidas, P Roy, A Saha… - Water, 2023‏ - mdpi.com
Flood, a distinctive natural calamity, has occurred more frequently in the last few decades all
over the world, which is often an unexpected and inevitable natural hazard, but the losses …

GIS-based hybrid machine learning for flood susceptibility prediction in the Nhat Le–Kien Giang watershed, Vietnam

HD Nguyen - Earth Science Informatics, 2022‏ - Springer
Floods is a natural hazard that occurs over a short time with a high transmission speed.
Flood risk management in many countries employs flood susceptibility modeling to mitigate …

Spatial modeling of flood hazard using machine learning and GIS in Ha Tinh province, Vietnam

HD Nguyen - Journal of Water and Climate Change, 2023‏ - iwaponline.com
The objective of this study was the development of an approach based on machine learning
and GIS, namely Adaptive Neuro-Fuzzy Inference System (ANFIS), Gradient-Based …

Flood susceptibility map** leveraging open-source remote-sensing data and machine learning approaches in Nam Ngum River Basin (NNRB), Lao PDR

S Mangkhaseum, Y Bhattarai, S Duwal… - … , Natural Hazards and …, 2024‏ - Taylor & Francis
Frequent floods caused by monsoons and rainstorms have significantly affected the
resilience of human and natural ecosystems in the Nam Ngum River Basin, Lao PDR. A cost …