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河北省 167 个县城镇化与城市韧性耦合协调的时空演变及驱动因素

Spatial-Temporal Evolution and Driving Factors of the Coupling Coordination between Urbanization and Urban Resilience: A Case Study of the 167 Counties in Hebei Province.

机构信息

School of Architecture, Tianjin University, Tianjin 300072, China.

School of Applied Economics, Renmin University of China, Beijing 100872, China.

出版信息

Int J Environ Res Public Health. 2022 Oct 12;19(20):13128. doi: 10.3390/ijerph192013128.

DOI:10.3390/ijerph192013128
PMID:36293708
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9603727/
Abstract

Urban resilience, as an important ability to deal with disasters in the process of urbanization, has been paid more and more attention as the result of the increasing risks that are caused by rapid urbanization. China is taking the county level as the basic unit to promote new-type urbanization and constructing resilient cities has become one of the development strategies. However, to achieve this strategy researchers need to analyze the interaction between county urbanization and urban resilience and its driving mechanism, which have been paid little attention. Therefore, this paper selected 167 counties in Hebei Province as the investigation subject. Based on the statistical data from 2010 to 2020, a comprehensive index system was developed to quantify the degree of coupling coordination between urbanization and urban resilience, and the spatial Durbin model was used to analyze the driving mechanism of it. The study shows that: Firstly, the urbanization level of counties rose year after year, with there being a geographical distribution that was "lower from southeast to northwest". The level of urban resilience increased year after year, showing a geographical distribution that was "higher from south to north" and a "core-edge" feature that was localized. Secondly, the coupling coordination degree increased steadily, and the overall level changed from a basic imbalance to a mild imbalance. In space, it is bounded by "Pingquan City-Pingshan County", which showed the distribution of "high in the east and low in the west, high in the center and low on the outskirts". Thirdly, the coupling coordination degree has spatial spillover effect. Government financial expenditure, innovation level, industrial upgrading level and urban shape index all influence the coupling coordination degree positively, with a successively decreasing impact, while the urban compactness has significant negative impacts. This study indicates that the regional differences exist in the coupling coordination degree, and the counties in different development stages need to adopt different strategies to promote the coordinated development of urbanized and resilient cities. Inter-regional support is also necessary in this process. Meanwhile, it is necessary for the government to govern various urban elements, especially in terms of their urban form.

摘要

城市韧性作为城市化进程中应对灾害的重要能力,随着快速城市化带来的风险不断增加,受到了越来越多的关注。中国以县为基本单元推进新型城镇化,构建韧性城市已成为发展战略之一。然而,要实现这一战略,研究人员需要分析县域城镇化与城市韧性的相互作用及其驱动机制,而这方面的研究还很少。因此,本文选取河北省 167 个县作为调查对象,基于 2010-2020 年的统计数据,构建了城镇化与城市韧性耦合协调度的综合评价指标体系,并采用空间 Durbin 模型对其驱动机制进行了分析。研究表明:第一,县域城镇化水平逐年上升,呈现出由东南向西北逐渐降低的地理分布特征;城市韧性水平逐年提高,呈现出由南向北逐渐升高的地理分布特征和局部化的“核心-边缘”特征。第二,耦合协调度稳步提升,整体水平由基本失调向轻度失调转变。在空间上,以“平泉市-平山县”为界,呈“东高西低、中心高边缘低”的分布格局。第三,耦合协调度具有空间溢出效应。政府财政支出、创新水平、产业升级水平和城市形态指数均对耦合协调度有正向影响,且影响程度依次递减,而城市紧凑度则具有显著的负向影响。本研究表明,耦合协调度存在区域差异,不同发展阶段的县域需要采取不同的策略来促进城镇化和韧性城市的协调发展,区域间也需要相互支持。同时,政府需要治理好各种城市要素,特别是城市形态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/b44c587f38a1/ijerph-19-13128-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/2192d00b0d02/ijerph-19-13128-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/9128e06f1e8c/ijerph-19-13128-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/4805fb1b16d3/ijerph-19-13128-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/39a6994b23c1/ijerph-19-13128-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/4a1c3f62a8fc/ijerph-19-13128-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/4a338ea9d850/ijerph-19-13128-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/191b67460c88/ijerph-19-13128-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/b44c587f38a1/ijerph-19-13128-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/2192d00b0d02/ijerph-19-13128-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/9128e06f1e8c/ijerph-19-13128-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/4805fb1b16d3/ijerph-19-13128-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/39a6994b23c1/ijerph-19-13128-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/4a1c3f62a8fc/ijerph-19-13128-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/4a338ea9d850/ijerph-19-13128-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/191b67460c88/ijerph-19-13128-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a7d/9603727/b44c587f38a1/ijerph-19-13128-g008.jpg

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