关中平原城市群韧性空间关联网络及其影响因素研究

doi:10.12118/j.issn.1000－6060.2023.104

Abstract

Abstract:

This study constructed an urban resilience evaluation index system that included four dimensions: economy, society, ecological environment, and infrastructure. Based on the entropy method, the resilience comprehensive evaluation index of 11 cities in the Guanzhong Plain urban agglomeration, northwest China from 2011 to 2020 was measured, and the spatiotemporal evolution characteristics of their resilience were analyzed, and moreover, the social network analysis method was used to analyze the structural and functional connections between cities in the resilience network of the Guanzhong Plain urban agglomeration. Furthermore, the quadratic assignment procedure was used to explore the comprehensive factors that affected the resilience network structure of the Guanzhong Plain urban agglomeration. The results indicated the following. (1) The overall resilience of each city in the Guanzhong Plain urban agglomeration was on the rise, and the resilience level showed a decreasing trend from provincial capital to the periphery. (2) The resilience network structure of urban agglomerations had become more complex and robust; however, the resilience connections between regions exhibited strong hierarchical characteristics and cities had not yet fully achieved interconnectivity. (3) Xi’an, Xianyang, and Tongchuan had strong centrality and could generate significant resource spillovers to surrounding or peripheral cities. The “core-edge” structure of urban agglomerations was obvious. (4) The level of economic development, openness, government financial support, scientific and technological development, differences in transport infrastructure, and geographical proximity all significantly affected changes in the resilient spatial network structure of the urban agglomeration. Therefore, to enhance the resilience of the Guanzhong Plain urban agglomeration and the connection between cities, one must first build an intercity digital management and exchange platform and promote the diffusion of resource elements from high- to low-agglomeration areas. Second, the construction of transportation networks must be strengthened, investment in scientific and technological innovation must be increased, and foreign trade and economic cooperation must be strengthened in the construction of “the Belt and Road”. This study reveals the position and role of each city in the resilience development process in the spatial association network of the Guanzhong Plain urban agglomeration, analyzes the spatial spillover effect of resilience development in the Guanzhong Plain urban agglomeration, and provides a new perspective on the study of urban resilience development from a geographically spatial perspective.

Key words: urban resilience, spatial correlation network, social network analysis, Guanzhong Plain urban agglomeration

SHI Yufang, NIU Yu. Resilience spatial correlation network and its influencing factors in Guanzhong Plain urban agglomeration[J].Arid Land Geography, 2024, 47(2): 270-280.

Figures/Tables 7

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References 23

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目标层	准则层	指标层	指标属性	权重
城市韧性	经济韧性	人均GDP/元	正	0.034
		第三产业GDP占比/%	正	0.025
		城镇居民人均可支配收入/农村居民人均可支配收入/%	负	0.017
		人均固定资产投资额/元	正	0.054
		人均社会消费品零售总额/元	正	0.051
		职工平均工资/元	正	0.031
		进出口贸易额占GDP比重/%	正	0.138
	社会韧性	人口自然增长率/%	正	0.025
		社会保障和就业支出占财政支出比重/%	正	0.015
		城市教育支出占财政支出比重/%	正	0.022
		公共管理、社会保障和社会组织从业人员占比/%	正	0.025
		每万人普通高校在校生人数/人	正	0.119
		每万人卫生技术人员人数/人	正	0.034
		失业率/%	负	0.025
	生态环境韧性	建成区绿地覆盖率/%	正	0.009
		人均园林绿地面积/m²	正	0.012
		工业废水排放量/GDP/t·(10⁴元)^-1	负	0.003
		工业SO₂排放量/GDP/t·(10⁸元)^-1	负	0.004
		生活垃圾无害化处理率/%	正	0.006
		城市污水处理率/%	正	0.014
		固体废弃物综合利用率/%	正	0.046
	基础设施韧性	公路线网密度/km·km^-2	正	0.024
		每万人公共汽车数/辆	正	0.080
		每万人拥有公共厕所/座	正	0.093
		每万人医院病床数/张	正	0.024
		燃气普及率/%	正	0.009
		建成区排水管道密度/km·km^-2	正	0.024
		互联网普及率/%	正	0.038

城市	2011年	2012年	2013年	2014年	2015年	2016年	2017年	2018年	2019年	2020年	平均值
西安市	0.5346	0.5525	0.5905	0.6251	0.6491	0.6536	0.6488	0.6995	0.7115	0.7002	0.6365
宝鸡市	0.2005	0.2216	0.2490	0.2673	0.3051	0.3379	0.3678	0.4010	0.4282	0.4449	0.3219
铜川市	0.2311	0.2558	0.2709	0.2955	0.3183	0.3652	0.3447	0.3807	0.4436	0.4801	0.3386
渭南市	0.1440	0.1721	0.1769	0.1888	0.2066	0.2452	0.2664	0.2984	0.3303	0.3451	0.2374
商洛市	0.1334	0.1423	0.1399	0.1609	0.1706	0.1698	0.2150	0.2317	0.2639	0.2872	0.1915
咸阳市	0.2125	0.2389	0.2507	0.2688	0.2928	0.3195	0.3515	0.3714	0.3937	0.4199	0.3120
天水市	0.1608	0.1618	0.1769	0.1845	0.2031	0.2242	0.2410	0.2536	0.2624	0.2903	0.2159
平凉市	0.1397	0.1550	0.1682	0.1772	0.1934	0.2069	0.2225	0.2485	0.2658	0.3026	0.2080
庆阳市	0.1436	0.1644	0.1780	0.1957	0.2122	0.2333	0.2223	0.2372	0.2357	0.2422	0.2064
运城市	0.2128	0.2174	0.2613	0.2557	0.2510	0.2669	0.2816	0.2737	0.3000	0.2929	0.2613
临汾市	0.1875	0.1980	0.2060	0.2107	0.2260	0.2342	0.2400	0.2527	0.2689	0.2779	0.2302
平均值	0.2091	0.2254	0.2426	0.2573	0.2753	0.2961	0.3092	0.3317	0.3549	0.3712	0.2873

城市	点度中心度				接近中心度				中介中心度
城市	2011年	2014年	2017年	2020年	2011年	2014年	2017年	2020年	2011年	2014年	2017年	2020年
西安市	10	10	10	10	100.00	100.00	100.00	100.00	19.81	19.81	17.78	17.78
宝鸡市	6	6	6	6	71.43	71.43	71.43	71.43	1.11	1.11	1.11	1.11
铜川市	9	9	9	9	90.91	90.91	90.91	90.91	13.15	13.15	11.11	11.11
渭南市	5	5	6	6	66.67	66.67	71.43	71.43	0.56	0.56	1.11	1.11
商洛市	4	4	5	5	62.50	62.50	66.67	66.67	0.00	0.00	0.00	0.00
咸阳市	9	9	9	9	90.91	90.91	90.91	90.91	11.67	11.67	11.11	11.11
天水市	4	4	4	4	62.50	62.50	62.50	62.50	0.00	0.00	0.00	0.00
平凉市	6	6	6	6	71.43	71.43	71.43	71.43	1.11	1.11	1.11	1.11
庆阳市	5	5	5	5	66.67	66.67	66.67	66.67	0.00	0.00	0.00	0.00
运城市	5	5	6	6	66.67	66.67	71.43	71.43	1.48	1.48	1.11	1.11
临汾市	3	3	4	4	58.82	58.82	62.50	62.50	0.00	0.00	0.00	0.00

变量名称	非标准化回归系数	标准化回归系数	显著性概率	概率1	概率2
地理空间邻近差异矩阵	0.424	0.406^***	0.000	0.000	1.000
经济发展水平差异矩阵	-0.498	-0.320^**	0.017	0.984	0.017
人口增速差异矩阵	-0.182	-0.093	0.102	0.898	0.102
对外开放度差异矩阵	0.308	0.214^**	0.026	0.026	0.974
政府财政支持差异矩阵	0.482	0.249^**	0.049	0.049	0.951
环境规制差异矩阵	-0.111	-0.055	0.207	0.793	0.207
交通基础设施差异矩阵	-0.239	-0.128^*	0.066	0.934	0.066
科学技术水平差异矩阵	-0.319	-0.105^*	0.053	0.947	0.053

Resilience spatial correlation network and its influencing factors in Guanzhong Plain urban agglomeration

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