Quantifying the nonlinear and interactive effects of urban form on resilience to extreme precipitation: Evidence from 192 cities of Southern China DOI
Wenrui Wang, Yang Wang, Chen Shen

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106366 - 106366

Опубликована: Апрель 1, 2025

Язык: Английский

Post-Disaster Recovery Planning for Infrastructure Systems Based on Residents’ Needs: A Hypernetwork Approach DOI
Zeyu Zhao,

Zoe Li,

Tianyuan Wang

и другие.

International Journal of Disaster Risk Reduction, Год журнала: 2025, Номер unknown, С. 105258 - 105258

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
How do built environment characteristics influence metro-bus transfer patterns across metro station types in Shanghai? DOI
Yuji Shi,

Li Ai zeng

Journal of Transport Geography, Год журнала: 2025, Номер 123, С. 104137 - 104137

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
Mini-Review on Petroleum Molecular Geochemistry: Opportunities with Digitalization, Machine Learning, and Artificial Intelligence DOI
Kaiming Su,

Yaohui Xu,

Qingyong Luo

и другие.

Energy & Fuels, Год журнала: 2025, Номер unknown

Опубликована: Март 9, 2025

Язык: Английский

Процитировано

0
Global sensitivity analysis in a complex 1D-2D coupled hydrodynamic model: flood hazard and resilience perspectives over an urban catchment DOI
Kaustav Mondal, Mousumi Ghosh, Subhankar Karmakar

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106279 - 106279

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
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

и другие.

Physics of Fluids, Год журнала: 2025, Номер 37(3)

Опубликована: Март 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.

Язык: Английский

Процитировано

0
Investigating the Quantitative Impact of the Vegetation Indices on the Urban Thermal Comfort Based on Machine Learning: A Case Study of the Qinhuai River Basin, China DOI Creative Commons
Jianqing Zhao, Chunguang Hu, Zhuoqi Li

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106357 - 106357

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Quantifying the nonlinear and interactive effects of urban form on resilience to extreme precipitation: Evidence from 192 cities of Southern China DOI
Wenrui Wang, Yang Wang, Chen Shen

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106366 - 106366

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0