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  • 2025年7月23日 星期三

干旱区地理 ›› 2025, Vol. 48 ›› Issue (4): 559-570.doi: 10.12118/j.issn.1000-6060.2024.428 cstr: 32274.14.ALG2024428

• 第三次新疆综合科学考察 • 上一篇    下一篇

天山北坡城市群城市韧性时空演变特征及发展趋势预测

黄思源1(), 周书航2, 董晔2()   

  1. 1.新疆师范大学地理科学与旅游学院,新疆 乌鲁木齐 830017
    2.新疆师范大学商学院,新疆 乌鲁木齐 830017
  • 收稿日期:2024-07-16 修回日期:2024-08-30 出版日期:2025-04-25 发布日期:2025-04-18
  • 通讯作者: 董晔(1974-),女,教授,主要从事城市经济学、经济地理学方面的研究. E-mail: xj.dongye@163.com
  • 作者简介:黄思源(1999-),男,硕士研究生,主要从事人文地理学方面的研究. E-mail: huangsiyuan0918@163.com
  • 基金资助:
    国家自然科学基金重点项目(42330510)

Spatio-temporal evolution characteristics and development trend prediction of urban resilience of urban agglomeration on the northern slope of Tianshan Mountains

HUANG Siyuan1(), ZHOU Shuhang2, DONG Ye2()   

  1. 1. College of Geographic Science and Tourism, Xinjiang Normal University, Urumqi 830017, Xinjiang, China
    2. College of Business, Xinjiang Normal University, Urumqi 830017, Xinjiang, China
  • Received:2024-07-16 Revised:2024-08-30 Published:2025-04-25 Online:2025-04-18

摘要:

城市群城市韧性建设已成为城市风险治理研究的热点话题。选取2010—2022年天山北坡城市群15个城市面板数据,基于DPSR模型从动态视角出发,从“驱动力-压力-状态-响应”4个维度,构建城市韧性评价指标体系,利用熵值法、核密度分析城市韧性的时空演化特征、借助地理探测器探索主要影响因子、运用灰色预测模型预测未来发展趋势。结果表明:(1) 2010—2022年天山北坡城市群城市韧性有明显提升,当前形成以乌鲁木齐市西部地区为高韧性区、城市群边缘为低韧性区的“核心-边缘”空间格局。(2) 扰动响应能力对城市韧性影响最为显著,随着时间推移,环境管制和生态污染方面影响力开始逐渐增强。(3) 2023—2027年天山北坡城市群城市韧性“核心-边缘”的空间分布格局将会进一步得到巩固,地区间不平衡发展将会进一步加剧。研究结果可为天山北坡城市群发展规划、城市群韧性提升提供理论参考,从而增强城市在面对各种扰动时的适应能力、恢复能力和持续发展的能力。

关键词: 城市韧性, DPSR模型, 时空演化, 灰色预测模型, 天山北坡城市群

Abstract:

Building resilience in urban agglomerations has become a key focus in urban risk governance research. This study utilizes panel data from 15 cities in the urban agglomeration on the northern slope of Tianshan Mountains, Xinjiang, China from 2010 to 2022. Based on the DPSR model, an urban resilience evaluation index system is constructed, encompassing four dimensions (driving force, pressure, state, and response) analyzed from a dynamic perspective. The spatial and temporal evolution of urban resilience is assessed using the entropy method and kernel density estimation. Furthermore, the primary influencing factors are identified through geographical detectors, and future development trends are predicted using a grey prediction model. The results indicate that: (1) From 2010 to 2022, the resilience of the urban agglomeration on the northern slope of Tianshan Mountains has significantly improved, forming a spatial pattern characterized by a “core-edge” structure. The western part of Urumqi City has emerged as a high-resilience area, whereas the periphery of the urban agglomeration exhibits lower resilience. (2) When analyzing the factors influencing urban resilience, the response system has consistently exerted a strong impact. Over time, the influence of environmental regulation and ecological pollution indicators has increased. Specifically, the total production value of large-scale industrial enterprises, carbon dioxide emissions, the number of utility model patents, the digital financial inclusion index, and general public budget expenditures have demonstrated a strong long-term effect on urban resilience in this region. (3) For the period 2023—2027, dynamic predictions suggest that the resilience of the urban agglomeration will improve significantly, with cities in the urban agglomeration exhibiting steady growth. Spatially, Urumqi City will continue to lead in resilience levels, further widening interregional disparities. Consequently, the “core-edge” spatial pattern within the region will become more pronounced. These findings provide a theoretical reference for the development planning of urban agglomeration on the northern slope of Tianshan Mountains and the enhancement of urban resilience, thereby strengthening cities’ ability to adapt to, recover from, and sustainably develop in response to various disturbances.

Key words: urban resilience, DPSR model, spatio-temporal evolution, grey prediction models, urban agglomeration on the northern slope of Tianshan Mountains