摘要
城市群是城市发展较高层次的空间组成形式,其城市韧性的提升对建设韧性城市、促进城市群持续健康发展具有重要意义。为全面测度城市群城市韧性水平并识别其障碍因子,构建了城市群城市韧性评价指标体系,采用熵值法和BP神经网络模型对关中平原城市群2011—2020年各城市分系统韧性和复合系统进行分析,进一步使用障碍度模型对影响关中平原城市群城市韧性的障碍因子进行识别。研究发现,关中平原城市群城市韧性位于中等韧性水平,但总体呈上升趋势,其空间分布格局呈现出“东西低,中间高”的倒V形。具体而言,经济系统韧性以较低韧性水平和中等韧性水平为主,社会系统韧性以中等韧性水平和较高韧性水平为主,生态系统韧性以较高韧性水平为主,而基础设施系统韧性则主要分布在较低至较高韧性水平之间;建成区绿化覆盖率和全社会用电量因子是影响关中平原城市群城市韧性提升的主要障碍因子;从分系统来看,社会系统始终是影响关中平原城市群城市韧性提升的关键系统。研究表明,城市群应进一步加强城市之间的合作,共享信息资源,提高人们生活水平,加大城市基础设施建设力度,不断促进城市群协调发展。
Urban agglomeration represents the pinnacle of urban development spatially.Enhancing urban resilience is paramount for fostering resilient cities and nurturing sustainable,healthy urban agglomerations.This paper endeavors to comprehensively gauge the urban resilience level of urban agglomerations and pinpoint obstacle factors.To this end,an urban agglomeration urban resilience evaluation index system was constructed,employing the entropy method and the BP neural network model to assess the resilience and composite performance of each city subsystem within the Guanzhong Plain urban agglomeration from 2011 to 2020.Through systematic analysis,the obstacle degree model was utilized to identify factors impeding urban resilience in the Guanzhong Plain urban agglomeration.The study reveals that the urban resilience of the Guanzhong Plain urban agglomeration rests at a medium level,with a general upward trajectory.Spatially,its distribution pattern exhibits an inverted V-shape,with lower resilience in the east and west,and higher resilience in the middle.Economic system resilience leans towards lower and medium levels,while social system resilience tends to be medium to higher.Ecosystem resilience predominantly falls within higher levels,while infrastructure system resilience spans between lower and higher levels.Notably,the primary obstacles hampering urban resilience improvement in the Guanzhong Plain urban agglomeration are the green coverage rate of built-up areas and society-wide electricity consumption.From a subsystem perspective,the social system consistently emerges as the key constraint on urban resilience improvement in this agglomeration.To address these challenges,urban agglomerations should intensify inter-city cooperation,facilitate information sharing,uplift living standards,bolster urban infrastructure construction,and perpetually drive coordinated development across urban agglomerations.
作者
马飞
张东伟
陈龙
刘擎
委笑琳
MA Fei;ZHANG Dongwei;CHEN Long;LIU Qing;WEI Xiaolin(School of Economics and Management,Chang'an University,Xi'an 710064,Shaanxi,China)
出处
《长安大学学报（社会科学版）》
2024年第2期112-124,共13页
Journal of Chang'an University(Social Science Edition)
基金
陕西省自然科学基础研究计划项目(2022JM-423)。
关键词
城市韧性
BP神经网络模型
关中平原城市群
障碍因子
社会系统
数据壁垒
中心城市
urban resilience
BP neural network model
Guanzhong Plain urban agglomeration
obstacle factor
social system
data barriers
central city
