Resilient urban expansion: Identifying critical conflict patches by integrating flood risk and land use predictions: A case study of Min Delta Urban Agglomerations in China
被引:11
作者:
Wang, Qianwen
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机构:
Tianjin Normal Univ, Tianjin 300387, Peoples R China
393 Binshui West Rd, Tianjin 300387, Peoples R ChinaTianjin Normal Univ, Tianjin 300387, Peoples R China
Wang, Qianwen
[1
,5
]
Zhao, Guangyu
论文数: 0引用数: 0
h-index: 0
机构:
Tianjin Univ, Res Inst Architectural Design, Tianjin 300072, Peoples R China
Urban Planning Co Ltd, Tianjin 300072, Peoples R ChinaTianjin Normal Univ, Tianjin 300387, Peoples R China
Zhao, Guangyu
[2
,3
]
Zhao, Runze
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h-index: 0
机构:
North China Univ Water Resources & Elect Power, Zhengzhou 450045, Peoples R ChinaTianjin Normal Univ, Tianjin 300387, Peoples R China
Zhao, Runze
[4
]
机构:
[1] Tianjin Normal Univ, Tianjin 300387, Peoples R China
[2] Tianjin Univ, Res Inst Architectural Design, Tianjin 300072, Peoples R China
[3] Urban Planning Co Ltd, Tianjin 300072, Peoples R China
[4] North China Univ Water Resources & Elect Power, Zhengzhou 450045, Peoples R China
[5] 393 Binshui West Rd, Tianjin 300387, Peoples R China
The increasing occurrence of floods due to global climate change is a challenge to the growth of urban resilience. However, few studies have investigated strategies to avoid flood risks during long-term and comprehensive land use and development. To address this issue, this study proposes a method that integrates flood risk and land use predictions to identify critical conflict patches that impact urban resilience. Further strategies for differential development based on the attributes of these critical conflict patches were formulated. Taking the Min Delta Urban Agglomeration (MDUA) in China as a case study, critical conflict patches for expanded urban resilience were identified based on a multi-source data set, a random forest (RF) algorithm, and a patch generating land use simulation model (PLUS) combined with cellular automata (CA). These patches were categorized into three levels of risk prediction-low, medium, and high risk-based on flood risk attributes. These risk forecast levels were further divided into seven categories. The best land use approach was determined by assessing the quantity, spatial distribution, and risk based priority ranking of these conflict patches. The results demonstrated that most conflicting patches were located in bare land within built-up areas, urban-rural intersection zones, and remote suburban areas with high traffic accessibility. The identified conflicting patches were applied to three different land use patterns: intra-city renewal, urban edge expansion, and the creation of derived cities. The total number of conflicting patches for land use decisions in the MDUA was 122 (170.82 km2) in 2025 and 685 (1205.81 km2) in 2035. Approximately 108 km2 of urban land was added for resilience expansion following optimization. In all development scenarios, the optimized land use pattern facilitated resilient growth of urban development while maintaining the stability of the flood disaster environment. Based on our methodology and case study, we proposed a decision-making framework to assist cities or potential urban regions to avoid water-related problems and related issues. This approach could also contribute to decisions involving different geographical areas for resilient land use.
机构:
Penn State Univ, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USAPenn State Univ, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USA
Ceres, Robert L.
;
Forest, Chris E.
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机构:
Penn State Univ, Earth & Environm Syst Inst, Dept Geosci, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USAPenn State Univ, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USA
Forest, Chris E.
;
Keller, Klaus
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h-index: 0
机构:
Penn State Univ, Dept Geosci, University Pk, PA 16802 USA
Penn State Univ, Earth & Environm Syst Inst, University Pk, PA 16802 USA
Dartmouth Coll, Thayer Sch Engn, Hanover, NH 03755 USAPenn State Univ, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USA
机构:
Penn State Univ, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USAPenn State Univ, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USA
Ceres, Robert L.
;
Forest, Chris E.
论文数: 0引用数: 0
h-index: 0
机构:
Penn State Univ, Earth & Environm Syst Inst, Dept Geosci, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USAPenn State Univ, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USA
Forest, Chris E.
;
Keller, Klaus
论文数: 0引用数: 0
h-index: 0
机构:
Penn State Univ, Dept Geosci, University Pk, PA 16802 USA
Penn State Univ, Earth & Environm Syst Inst, University Pk, PA 16802 USA
Dartmouth Coll, Thayer Sch Engn, Hanover, NH 03755 USAPenn State Univ, Dept Meteorol & Atmospher Sci, University Pk, PA 16802 USA