Sustainability assessment of station-city integration based on DPSIR-SDGs framework: a case study of Chengdu in China

DPSIR公司 可持续发展 持续性 蚁群优化算法 可持续城市 层次分析法 计算机科学 环境经济学 城市规划 运筹学 环境资源管理 土木工程 工程类 环境科学 经济 算法 生态学 政治学 法学 生物
作者
Zhenhua Luo,Zijing Chen,Xiaoqing Wu,Haize Pan,Fanglin Wang,Rui Tu,Zongquan Yao,Yue Wang,Shou-Chi Chen
出处
期刊:Environment, Development and Sustainability [Springer Science+Business Media]
标识
DOI:10.1007/s10668-024-05902-w
摘要

The integrated station-city urban space development model based on public transportation-oriented development solves problems such as chaotic traffic order and provides new ideas for promoting sustainable urban development. Evaluating the sustainability of station-city integration at the station-city integration planning and development stage can solve the current problems of station-city integration development, such as low efficiency of transportation synergy and lack of coordination and organization of land development. This paper constructs a sustainability evaluation index system for station-city integration based on the Driving Force-Pressure-State-Impact-Response-Sustainable Development Goals (SDGs) framework, which effectively integrates the resource, economic, and environmental factors of station-city integration and solves the problem of the SDGs model's broad designation. The influence relationship among the indicators was analyzed using network hierarchy analysis (ANP), and the weights of the indicators were determined. A genetically improved Ant Colony Optimization (ACO) algorithm establishes a sustainability evaluation model for station-city integration. The genetically improved ACO algorithm effectively overcomes the shortcomings of the ACO algorithm, such as the tendency of the ACO algorithm to fall into the local optimum, and the model is easy to calculate and operate. Taking the Chengdu X station project in China as an example for empirical research, the results show that the overall sustainability level of this station-city integration project is IV (good), and 18 out of 33 third-level indicators are Higher Sensitivity indicators. Finally, combining the indicator weights and sensitivity, the study proposes targeted sustainable development planning suggestions for the three types of indicators: Higher Weight–Higher Sensitivity, Higher Weight–Low Sensitivity, and Low Weight–Higher Sensitivity. The evaluation system and evaluation model of station-city integration sustainable development proposed in this study provide a theoretical basis for decision-makers to carry out station-city integration sustainable development planning.

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