黄土高原地区矿产资源型城市脆弱性及其人口响应

doi:10.12118/j.issn.1000-6060.2020.06.29

摘要/Abstract

摘要： 资源型城市脆弱性研究对于当前我国落实新型城镇化战略，推动城市高质量发展具有重要意义。通过以黄土高原地区 25 个矿产资源型城市为研究对象，从经济、社会、生态环境和资源 4 个维度构建指标体系，采用 TOPSIS 法、灰色关联法和地理探测器等方法研究了 2000—2015 年的城市脆弱性格局及时空演化，并以人口这一流动性最强的社会资源为切入点，分析其脆弱性演变的区域效应。结果表明：（1）2000—2015 年，黄土高原地区资源型城市以中低脆弱性为主，总体呈上升趋势，城市间极差化显著，但不平衡性趋缓；（2）该区域资源型城市脆弱性主要问题呈“生态环境-经济＋社会－经济＋资源”的转变特征，其中成熟型、衰退型城市的问题尤为突出；社会及生态环境脆弱性总体上均得以改善，资源脆弱性上升区集中在东部、南部；（3）综合脆弱性的人口响应程度呈下降趋势。城镇人口比重的响应程度最强，人口老龄化、社会总抚养比和流动人口比重的响应具有阶段性特征。（4）分维度脆弱性的人口响应呈现维度差异。经济和社会脆弱性的人口响应具有一致性，社会总抚养比是关键解释因子，生态环境脆弱性中流动人口比重的解释力较强且增幅显著，而资源脆弱性中城镇人口比重的响应程度最高。

关键词: 矿产资源型城市, 脆弱性, 人口响应, 黄土高原

Abstract: It is of great significance to study the vulnerability of resource-based cities, which can implement a new urbanization strategy and promote the sustainable development of cities. Taking 25 mineral resource-based cities in the Loess Plateau, China as research objects, this study built an index system from four dimensions (economic, social, ecological environment, and resources). The vulnerability from 2000 to 2015 was evaluated to analyze the spatio-temporal pattern of vulnerability through grey correlation and geographic detector methods. Meanwhile, taking the population, the most mobile social resource, as the starting point, this paper analyzed the regional effect of the evolution of vulnerability of resource-based cities. It probed into the relationship between population factors and vulnerability of resource-based cities, which is helpful to reveal the internal mechanism of the population factors’response to vulnerability. The research findings are as follows: (1) The resource-based cities in the research area mainly exhibits medium and low vulnerability, and the overall trend was risen from 2000 to 2015. The polarization between cities was significant, but the imbalance was decreased. On the spatial pattern, the comprehensive vulnerability of resource- based cities had spatial heterogeneity in the Loess Plateau. Generally, it shows a decreasing pattern characteristic from southeast to northwest. Among them, the high vulnerable areas were concentrated in Loess Plateau gully region and the agricultural irrigation. (2) The vulnerability of resource- based cities in this region is characterized by the transformation of“ecological environment-economy+society-economy+ resources”. Among them, the economic-social vulnerability of mature-type and the economic-resources vulnerability of decline- type cities’ problem should be emphasized. In addition, the social vulnerability and ecological vulnerability of most cities had improved, while the resource vulnerability had increased significantly in the east and south. For the dimension of economic vulnerability, the range of change in the eastern and southern regions was relatively small. (3) The population response degree of comprehensive vulnerability was decreased. From the response of population aging, the total social dependency ratio and proportion of floating population were characterized by stages. The response of the proportion of urban population was found to be the strongest. The population of cities with low vulnerability expanded rapidly, while cities with high vulnerability, such as Baiyin and Weinan, faced population contraction. (4) The population response of sub- dimensional vulnerability presented dimensional differences, while the economic and social vulnerability was observed to be consistent. The total social dependency ratio was the key explanatory factor. In the ecological environment vulnerability, the proportion of floating population had a strong explanatory power and increased significantly, while the proportion of urban population had the highest degree of response in the resource vulnerability.

Key words: mineral resource-based city, vulnerability, population response, Loess Plateau

王佳宁, 薛东前, 马蓓蓓, 董朝阳. 黄土高原地区矿产资源型城市脆弱性及其人口响应[J]. 干旱区地理, 2020, 43(6): 1679-1690.

WANG Jia-ning, XUE Dong-qian, MA Bei-bei, DONG Chao-yang. Vulnerability and population response of mineral resource-based cities in the Loess Plateau[J]. Arid Land Geography, 2020, 43(6): 1679-1690.

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