天山北坡城市群城市韧性时空演变特征及发展趋势预测

doi:10.12118/j.issn.1000-6060.2024.428

Abstract

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

HUANG Siyuan, ZHOU Shuhang, DONG Ye. Spatio-temporal evolution characteristics and development trend prediction of urban resilience of urban agglomeration on the northern slope of Tianshan Mountains[J].Arid Land Geography, 2025, 48(4): 559-570.

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References 25

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目标层	维度	子维度	具体指标	单位	属性	权重
城市韧性	驱动力	经济动力	城镇人均可支配收入（X₁）	元	正	0.032
			地区生产总值增长率（X₂）	%	正	0.013
			人均GDP（X₃）	元	正	0.047
			规模以上工业企业总生产值（X₄）	10⁴元	正	0.188
		社会动力	城镇化率（X₅）	%	正	0.041
	压力	生态压力	PM_2.5（X₆）	μm	负	0.021
			近地表SO₂含量（X₇）	ug·m^-3	负	0.016
			逐年平均降水量（X₈）	mm	负	0.007
		人口压力	建成区人口密度（X₉）	人·km^-2	负	0.017
		人口压力	人口自然增长率（X₁₀）	%	负	0.007
		资源压力	人均日生活用水量（X₁₁）	L	负	0.005
		资源压力	CO₂排放量（X₁₂）	t	负	0.010
	状态	产业发展	产业高级化指数（X₁₃）	-	正	0.053
		产业发展	产业结构（X₁₄）	-	正	0.028
		社会现状	人均道路面积（X₁₅）	m²	正	0.018
			建成区供水管道密度（X₁₆）	km·km^-2	正	0.019
			每万人拥有卫生技术人数（X₁₇）	人	正	0.051
			燃气普及率（X₁₈）	%	正	0.007
			每万人中学在校学生数量（X₁₉）	人	正	0.033
			每万人第三产业单位从业人员（X₂₀）	人	正	0.039
		生态现状	人均公园绿地面积（X₂₁）	m²	正	0.300
			建成区绿化覆盖率（X₂₂）	%	正	0.008
			归一化植被指数（X₂₃）	-	正	0.027
	响应	污染治理	污水处理厂集中处理率（X₂₄）	%	正	0.006
			生活垃圾无害化处理率（X₂₅）	%	正	0.005
			建成区排水管道密度（X₂₆）	km·km^-2	正	0.025
		社会治理	实用新型专利数量（X₂₇）	个	正	0.237
			数字普惠金融指数（X₂₈）	-	正	0.036
			一般公共预算支出（X₂₉）	10⁴元	正	0.158
			交通运输、仓储和邮政业地区生产总值（X₃₀）	10⁴元	正	0.320
			每万人医院床位数（X₃₁）	个	正	0.037
			人均城镇固定资产投资（X₃₂）	10⁴元	正	0.052

影响力排名	2010年	2014年	2018年	2022年
1	X₁₄（0.95）	X₂₇（0.96）	X₂₉（0.99）	X₇（0.96）
2	X₂₉（0.84）	X₂₉（0.94）	X₂₈（0.96）	X₁₁（0.94）
3	X₁₂（0.81）	X₄（0.94）	X₄（0.96）	X₂₄（0.94）
4	X₄（0.80）	X₂₈（0.93）	X₂₇（0.96）	X₂₇（0.93）
5	X₉（0.77）	X₃₀（0.91）	X₃₁（0.95）	X₁₂（0.92）
6	X₃（0.74）	X₁₄（0.86）	X₃₀（0.95）	X₂₈（0.91）
7	X₃₀（0.73）	X₆（0.82）	X₁₄（0.91）	X₄（0.90）
8	X₂₈（0.72）	X₂₅（0.82）	X₆（0.90）	X₂₉（0.89）
9	X₂₂（0.66）	X₁₅（0.81）	X₁₆（0.88）	X₃₁（0.88）
10	X₂₇（0.66）	X₁₂（0.80）	X₁₂（0.88）	X₁₃（0.88）

县市	后验差比C值	平均相对误差	城市韧性预测值
县市	后验差比C值	平均相对误差	2023年	2024年	2025年	2026年	2027年
天山北坡城市群	0.136	0.04635	6.220	6.433	6.653	6.880	7.115
昌吉市	0.092	0.03857	0.449	0.467	0.487	0.507	0.528
阜康市	0.260	0.06489	0.326	0.336	0.346	0.357	0.367
呼图壁县	0.117	0.04991	0.343	0.356	0.371	0.386	0.401
吉木萨尔县	0.233	0.06713	0.327	0.336	0.346	0.355	0.365
克拉玛依市	0.128	0.05438	0.504	0.512	0.519	0.527	0.534
奎屯市	0.349	0.05847	0.399	0.408	0.416	0.425	0.434
玛纳斯县	0.369	0.06236	0.269	0.275	0.280	0.286	0.291
木垒哈萨克自治县	0.114	0.04081	0.351	0.364	0.378	0.392	0.407
奇台县	0.117	0.03556	0.302	0.312	0.322	0.332	0.343
沙湾市	0.362	0.10177	0.395	0.413	0.431	0.449	0.467
石河子市	0.418	0.07310	0.435	0.445	0.455	0.465	0.474
吐鲁番市	0.066	0.04078	0.218	0.369	0.385	0.400	0.432
乌鲁木齐市	0.213	0.08194	1.099	1.143	1.188	1.223	1.278
乌苏市	0.406	0.06612	0.204	0.209	0.213	0.218	0.223
五家渠市	0.197	0.02981	0.356	0.363	0.370	0.377	0.384

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

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