Cited by Assessment of urban flood susceptibility based on a novel integrated machine learning method

Assessment of Urban Flood Disaster Responses and Causal Analysis at Different Temporal Scales Based on Social Media Data and Machine Learning Algorithms DOI

Qichen Guo,

Sheng Jiao, Yuchen Yang

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2025, Volume and Issue: 117, P. 105170 - 105170

Published: Jan. 5, 2025

Language: Английский

Citations

Building resilient urban drainage systems by integrated flood risk index for evidence-based planning DOI

Shakeel Ahmad, X. Peng, Anam Ashraf

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 374, P. 124130 - 124130

Published: Jan. 14, 2025

Language: Английский

Citations

Flood Monitoring Based on Multi-Source Remote Sensing Data Fusion Driven by HIS-NSCT Model DOI

P. F. Ding, Rong Li, Chenfei Duan

et al.

Water, Journal Year: 2025, Volume and Issue: 17(3), P. 396 - 396

Published: Jan. 31, 2025

Floods have significant impacts on economic development and cause the loss of both lives property, posing a serious threat to social stability. Effectively identifying evolution patterns floods could enhance role flood monitoring in disaster prevention mitigation. Firstly, this study, we utilized low-cost multi-source multi-temporal remote sensing construct an HIS-NSCT fusion model based SAR optical order obtain best image. Secondly, constructed regional growth accurately identify floods. Finally, extracted analyzed extent, depth, area farmland submerged by flood. The results indicated that maintained spatial characteristics spectral information images well, as determined through subjective objective multi-index evaluations. Moreover, preserve detailed features water body edges, eliminate misclassifications caused terrain shadows, enable effective extraction bodies. Based Poyang Lake, incorporating precipitation, elevation, cultivated land, other data, accurate identification inundation range, inundated land can be achieved. This study provides data technical support for identification, control, relief decision-making, among aspects.

Language: Английский

Citations

A Systematic Review of Urban Flood Susceptibility Mapping: Remote Sensing, Machine Learning, and Other Modeling Approaches DOI

Tania Islam, Ethiopia Bisrat Zeleke,

Mahmud Afroz

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(3), P. 524 - 524

Published: Feb. 3, 2025

Climate change has led to an increase in global temperature and frequent intense precipitation, resulting a rise severe urban flooding worldwide. This growing threat is exacerbated by rapid urbanization, impervious surface expansion, overwhelmed drainage systems, particularly regions. As becomes more catastrophic causes significant environmental property damage, there urgent need understand address flood susceptibility mitigate future damage. review aims evaluate remote sensing datasets key parameters influencing provide comprehensive overview of the causative factors utilized mapping. also highlights evolution traditional, data-driven, big data, GISs (geographic information systems), machine learning approaches discusses advantages limitations different mapping approaches. By evaluating challenges associated with current practices, this paper offers insights into directions for improving management strategies. Understanding identifying foundation developing effective resilient practices will be beneficial mitigating

Language: Английский

Citations

Disaster Management Systems: Utilizing YOLOv9 for Precise Monitoring of River Flood Flow Levels Using Video Surveillance DOI

G. Shankar,

M. Kalaiselvi Geetha,

P. Ezhumalai

et al.

SN Computer Science, Journal Year: 2025, Volume and Issue: 6(3)

Published: March 14, 2025

Language: Английский

Citations

Adaptive ranking of specific tree species for targeted green infrastructure intervention in response to urban hazards DOI

Xinyu Dong,

Yanmei Ye, Dan Su

et al.

Urban forestry & urban greening, Journal Year: 2025, Volume and Issue: unknown, P. 128776 - 128776

Published: March 1, 2025

Language: Английский

Citations

Integrating river channel flood diversion strategies into dynamic urban flood risk assessment and multi-objective optimization of emergency shelters DOI

Kunlun Chen, Haitao Wang,

Hao Jia

et al.

Physics of Fluids, Journal Year: 2025, Volume and Issue: 37(3)

Published: March 1, 2025

With the continuous advancement of urbanization, risk urban flooding is increasing, making establishment emergency shelters crucial for mitigating flood disasters. This study uses Jinshui River diversion pipeline project in Zhengzhou as a case to systematically investigate effect measures on reducing risks and optimize site selection based assessments. First, InfoWorks integrated catchment management model used simulate under different rainfall scenarios. Second, integrating multi-source data, technique order preference by similarity an ideal solution with four weighting methods applied identify high-risk areas. Finally, results assessment are weights multi-objective model, which solved particle swarm optimization algorithm determine optimal shelter locations. The show that: (1) In 10, 50, 200-years scenarios, significantly reduce depth inundated areas; however, limited extreme “7·20” event. (2) High-risk areas primarily concentrated highly urbanized northeast, although alleviates risk, overall remains high events. (3) Under scenario after diversion, 13 locations identified, average evacuation distance 471.9 meters, covering 97.3% population area. These findings provide scientific evidence management.

Language: Английский

Citations

Urban Flood Risk Analysis Using the SWAGU-Coupled Model and a Cloud-Enhanced Fuzzy Comprehensive Evaluation Method DOI

Jinhui Hu,

Chunyuan Deng,

Xinyu Chang

et al.

Environmental Modelling & Software, Journal Year: 2025, Volume and Issue: unknown, P. 106461 - 106461

Published: April 1, 2025

Language: Английский

Citations

Flood susceptibility assessment using deep neural networks and open-source spatial datasets in transboundary river basin DOI

Huu Duy Nguyen, Dinh Kha Dang,

H Truong

et al.

VIETNAM JOURNAL OF EARTH SCIENCES, Journal Year: 2025, Volume and Issue: unknown

Published: April 16, 2025

The Mekong Basin is the most critical transboundary river basin in Asia. This provides an abundant source of fresh water essential for development agriculture, domestic consumption, and industry, as well production hydroelectricity, it also contributes to ensuring food security worldwide. region often subject floods that cause significant damage human life, society, economy. However, flood risk management challenges this are increasingly substantial due conflicting objectives between several countries data sharing. study integrates deep learning with optimization algorithms, namely Grasshopper Optimisation Algorithm (GOA), Adam Stochastic Gradient Descent (SGD), open-source datasets identify probably occurring basin, covering Vietnam Cambodia. Various statistical indices, Area Under Curve (AUC), root mean square error (RMSE), absolute (MAE), coefficient determination (R²), were used evaluate susceptibility models. results show proposed models performed AUC values above 0.8, specifying DNN-Adam model achieved 0.98, outperforming DNN-GOA (AUC = 0.89), DNN-SGD 0.87), XGB 0.82. Regions very high concentrated Delta along River findings supporting decision-makers or planners proposing appropriate mitigation strategies, planning policies, particularly watershed.

Language: Английский

Citations

Machine learning-supported quantification and characterization of sediment plastic debris in an Anthropized Mfoundi River in Cameroon: Implications for the incidence of flood events DOI

Desmond N. Shiwomeh, Sameh A. Kantoush, Mohamed Saber

et al.

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 980, P. 179529 - 179529

Published: April 29, 2025

Language: Английский

Citations