One-dimensional deep learning driven geospatial analysis for flash flood susceptibility mapping: a case study in North Central Vietnam

PV Hoa, NA Binh, PV Hong, NN An, GTP Thao… - Earth Science …, 2024 - Springer
Flash floods rank among the most catastrophic natural disasters worldwide, inflicting severe
socio-economic, environmental, and human impacts. Consequently, accurately identifying …

Integration of machine learning and hydrodynamic modeling to solve the extrapolation problem in flood depth estimation

HD Nguyen, DK Dang, NY Nguyen… - Journal of Water and …, 2024 - iwaponline.com
Flood prediction is an important task, which helps local decision-makers in taking effective
measures to reduce damage to the people and economy. Currently, most studies use …

Morphometric analysis and prioritization of sub-watersheds of the Inaouene River upstream of the Idris I dam using the GIS techniques

S El Boute, M Agssura, A Hilali, A Hili, J Gartet - Applied Geomatics, 2024 - Springer
The prioritization of watersheds has increasingly become an optimal and relevant approach
for the management and planning against natural hazards. This approach is based on the …

Modelling on assessment of flood risk susceptibility at the Jia Bharali River basin in Eastern Himalayas by integrating multicollinearity tests and geospatial techniques

J Debnath, D Sahariah, N Nath, A Saikia… - Modeling Earth Systems …, 2024 - Springer
Climate change and anthropogenic factors have exacerbated flood risks in many regions
across the globe, including the Himalayan foothill region in India. The Jia Bharali River …

Urban land suitability analysis using geospatial techniques and combined weighting approach in Gabes zone, Southeastern Tunisia

D Souissi, L Zouhri, A Sebei, A Zghibi… - … , Natural Hazards and …, 2023 - Taylor & Francis
Abstract Urban Land Suitability analysis is necessary in any development project in order to
ensure rational urban planning and sustainable development. In this study, a novel …

Futuristic flood risks assessment, in the Upper Vellar Basin, integrating AHP and bivariate analysis

M Subbulakshmi, S Nanda - Advances in Space Research, 2024 - Elsevier
Flood susceptibility maps provide invaluable information for assessing and managing flood-
prone areas, aiding in proactive planning, risk reduction strategies, and safeguarding …

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 …

Assessing GLOF Hazards in the Himalayas: A Hybrid FR-AHP Approach to Susceptibility Mapping

D Gaikwad, A Tyagi, RK Tiwari - Remote Sensing Applications: Society and …, 2024 - Elsevier
Glacial lakes in the Himalayan region have triggered numerous glacial lake outburst floods
(GLOFs), leading to extreme flash floods and extensive destruction. Therefore, identifying …

SAR-driven flood inventory and multi-factor ensemble susceptibility modelling using machine learning frameworks

K Halder, A Ghosh, AK Srivastava, SC Pal… - … , Natural Hazards and …, 2024 - Taylor & Francis
Climate change has substantially increased both the occurrence and intensity of flood
events, particularly in the Indian subcontinent, exacerbating threats to human populations …

Enhancing flood-prone area mapping: fine-tuning the K-nearest neighbors (KNN) algorithm for spatial modelling

SV Razavi-Termeh, A Sadeghi-Niaraki… - … Journal of Digital …, 2024 - Taylor & Francis
This study focuses on determining the optimal distance metric in the K-Nearest Neighbors
(KNN) algorithm for spatial modelling of floods. Four distance metrics of the KNN algorithm …