Optimizing Intermodal Freight Flow Under Extreme Weather Disruptions

Опубликована: Янв. 1, 2025

Язык: Английский

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A GIS-based multi-criteria decision analysis of urban flood risk

International Journal of Building Pathology and Adaptation, Год журнала: 2025, Номер unknown

Опубликована: Март 4, 2025

Purpose Flooding is China’s most frequent and catastrophic natural hazard, causing extensive damage. The aim of this study to develop a comprehensive assessment urban flood risk in the Hubei Province China, focusing on following three issues: (1) What are factors that cause floods? (2) To what extent do these affect management? (3) How build an effective system can be used reduce risk? Design/methodology/approach This combines expert opinion evidence from literature identify indicators across four dimensions: disaster risk, susceptibility, exposure prevention mitigation. Criteria Importance Through Intercriteria Correlation (CRITIC) Grey Relational Analysis (RA)-based Technique for Order Preference by Similarity Ideal Solution (TOPSIS) decision-making approach were applied calculate weighting model risk. Then, ArcGIS software visualizes levels spatial distribution cities Province; uncertainty analysis verified method accuracy. Findings results show there significant differences level Province, with such as Tianmen, Qianjiang, Xiantao Ezhou being at high while Shiyan, Xiangyang, Shennongjia, Yichang, Wuhan Huanggang lower Originality/value innovative combining CRITIC-GRA-TOPSIS reduces presence subjective bias found many other frameworks. Regional data extraction enhance result reliability, supporting long-term planning. Overall, methodological developed provides advanced, highly efficient visualization deepens understanding mechanisms more broadly supports development resilient cities.

Язык: Английский

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A study of the temporal and spatial evolution trends of urban flood resilience in the Pearl River Delta, China

International Journal of Building Pathology and Adaptation, Год журнала: 2025, Номер unknown

Опубликована: Март 28, 2025

Purpose In view of the increasing threat flooding across world and specifically vulnerability Pearl River Delta region to these risks, this study undertakes a spatial temporal evolution flood risk in region, including an assessment urban resilience. Design/methodology/approach By combining pressure-state-response (PSR) model nature-economy-society-infrastructure (NESI) framework, resilience index system is constructed. The order relation analysis method, Criteria Importance Through Intercriteria Correlation method VlseKriterijumska Optimizacija Kompromisno Resenje evaluation they were then combined quantify reveal hierarchical relationships that exist between key factors. Using ArcGIS software, levels each city are dynamically tracked compared trends over three-year period. Findings results show annual precipitation impervious areas factors impacting environmental pressure, while sewage treatment rate found be response measure. cities Guangzhou Shenzhen shown have maintained high indexes (FRI), Zhaoqing City was weakest. Flood vary significantly, with central southern having higher than those eastern western regions. Originality/value This constructs new for assessing resilience, which suitable quickly accurately short-term trend

Язык: Английский

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Integrating Remote Sensing and Machine Learning for Actionable Flood Risk Assessment: Multi-Scenario Projection in the Ili River Basin in China Under Climate Change

Remote Sensing, Год журнала: 2025, Номер 17(7), С. 1189 - 1189

Опубликована: Март 27, 2025

Climate change is leading to an increase in the frequency and intensity of flooding, making it necessary consider future changes flood risk management. In regions where ground-based observations are significantly restricted, implementation conventional assessment methodologies always challenging. This study proposes integrated remote sensing machine learning approach for data-scarce regions. We extracted historical inundation using Sentinel-1 SAR Landsat imagery from 2001 2023 predicted susceptibility XGBoost, Random Forest (RF), LightGBM models. The framework systematically integrates hazard components (flood frequency) with vulnerability factors (population, GDP, land use) two SSP-RCP scenarios. results indicate that SSP2-RCP4.5 SSP5-RCP8.5 scenarios, combined high- very-high-flood-risk areas Ili River Basin China (IRBC) projected reach 29.1% 29.7% basin by 2050, respectively. short term, contribution predominant, while factors, particularly population, contribute increasingly long term. demonstrates integrating open geospatial data enables actionable assessment, quantitatively supporting climate-resilient planning.

Язык: Английский

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Integrating the Pressure-State-Response Model with the Extension Catastrophe Progression for Flood Risk and Resilience Assessment

Environmental and Sustainability Indicators, Год журнала: 2025, Номер unknown, С. 100727 - 100727

Опубликована: Май 1, 2025

Язык: Английский

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