JOURNAL OF NATURAL RESOURCES ›› 2020, Vol. 35 ›› Issue (12): 2875-2887.doi: 10.31497/zrzyxb.20201205

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Vulnerability assessment of urban agglomeration based on neural network model: A case study of Central Yunnan Urban Agglomeration

FAN Jun-kai(), XU Jian-gang()   

  1. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China
  • Received:2019-05-10 Revised:2019-09-06 Online:2020-12-28 Published:2021-02-28
  • Contact: Jian-gang XU E-mail:8931210@qq.com;xjg129@sina.com

Abstract:

Urban vulnerability is an effective measure to evaluate urban development resilience. At present, most studies on urban vulnerability focus on the special city and use the statistical method in China, and there is no urban vulnerability assessment method that is applicable to all the regional urban agglomerations. Taking the Central Yunnan Urban Agglomeration as an example, this paper develops an assessment system of urban vulnerability from three aspects of environmental system, economic system and social system. Entropy method and back propagation neural network model are used to evaluate the urban vulnerability of the study area from 2007 to 2016. The evaluation shows that the vulnerability of this urban agglomeration has a declining trend on the whole, but there is a big difference between the urban groups, which shows an unbalanced development. The evaluation results have reference significance for the planning and resilience development of the Central Yunnan Urban Agglomeration, and provide a scientific evaluation method for the study on the comprehensive development vulnerability of urban agglomeration.

Key words: urban resilience, urban vulnerability, complex system, back propagation neural network, entropy method, Central Yunnan Urban Agglomeration