Coupling analysis of multi-systems urbanization: Evidence from China

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2025-01-01 DOI:10.1016/j.ecolind.2024.112977
Junqiang Luo , Weijing Ma , Shuang An , Zining Zhang , Yanchuan Fu , Hejun Huang , Genying Chang
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Abstract

China’s urbanization rate has reached 66.16 %, indicating its transition to a more complex mid-to-late stage, which makes multi-systems research on urbanization essential. However, studies on urbanization from multiple perspectives are still limited, hindering a full understanding of its multifaceted nature. This study focuses for the first time on 295 prefecture-level cities and above in China from 2000 to 2020, developing an evaluation system for multi-systems urbanization to assess coupling and coordination. Utilizing methods such as the entropy method, coupling coordination model, Theil index, and Geodetector, this study explores the spatiotemporal differentiation and driving factors of urbanization coupling coordination. The results indicate: (1) The coupling coordination degree of urbanization shows a steady upward trend. Highly coordinated cities are primarily distributed in the core city’s radiation circles, coastal economic belts, provincial capitals in the central and western regions, and northern industrial city zones. Low-coordination cities are mainly found in the Qinghai-Tibet Plateau, Yunnan-Guizhou Plateau, the border areas of Gansu, Shaanxi, Sichuan, Chongqing, and Hubei, the Hetao area of the Yellow River Basin, the agricultural regions of the Huanghuaihai Plain, and the southeastern hilly and mountainous areas. (2) The degree of uneven urbanization development initially expands and then contracts, with intra-regional imbalances following the pattern: “Eastern Coastal Area > Northeast Area > Middle Reaches of the Yangtze River Area > Northern Coastal Area > Middle Reaches of the Yellow River Area > Southwest Area > Southern Coastal Area > Northwest Area.” (3) The coupling and coordinated development of urbanization is closely related to the economic foundation and production energy usage. This study provides decision-making support for promoting the multi-systems coupling and coordinated development of urbanization in China, as well as in other developing nations and globally.
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多系统城市化的耦合分析:来自中国的证据
中国城镇化率已经达到66.16%,进入了更为复杂的中后期阶段,这使得对城镇化进行多系统研究变得十分必要。然而,从多个角度对城市化的研究仍然有限,阻碍了对城市化的多面性的充分认识。本研究首次以2000 - 2020年中国295个地级市及以上城市为研究对象,构建了多系统城镇化耦合与协调评价体系。利用熵值法、耦合协调模型、Theil指数和Geodetector等方法,探讨了中国城市化耦合协调的时空分异及其驱动因素。结果表明:(1)城镇化的耦合协调度呈稳步上升趋势。高度协同的城市主要分布在核心城市辐射圈、沿海经济带、中西部省会城市和北部工业城区。低协调城市主要分布在青藏高原、云贵高原、甘肃、陕西、四川、重庆、湖北边境地区、黄河流域河套地区、黄淮海平原农业区和东南部丘陵山区。(2)城镇化发展不平衡程度先扩大后缩小,区域内不平衡表现为“东部沿海地区;东北地区>;长江中游地区;北部沿海地区;黄河中游地区>;西南地区>;南部沿海地区;西北地区。(3)城镇化的耦合协调发展与经济基础和生产能源利用密切相关。本研究为促进中国乃至其他发展中国家乃至全球城市化多系统耦合与协调发展提供决策支持。
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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
期刊介绍: The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.
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