Assessment of the coordinated relationship between blue-green space and urbanization in coastal mountain cities based on spatiotemporal evolution analysis: A case study in Qingdao, China

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Chao Li, Siyan Yue, Xin Liu, Huan Dai, Xingyu Li
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Abstract

Urban blue-green space is under great threat due to the huge impact of rapid urbanization. As representatives of high-density urban agglomerations, coastal mountain cities, while possessing a complex blue-green system, are also subject to great ecological vulnerability. To support the sustainable growth of cities, it is crucial to investigate the synergistic relationship between urbanization and blue-green space in coastal mountainous regions. Taking Qingdao, a typical fast-developing coastal mountainous city, as an example, the study analyzed the spatiotemporal evolution characteristics of blue-green space and urbanization in the study area from 2000 to 2020 on a grid-scale and explored the spatiotemporal dynamic trend of the coupling coordination degree of urbanization and blue-green space based on the coupling coordination model. The results showed: (1) From 2000 to 2020, land use in Qingdao experienced drastic changes. The main change was the encroachment of urban into the blue-green spaces, which led to the fragmentation and complexity of the landscape pattern of blue-green space, with the most significant change in the central coastal area. (2) The development levels of green space and blue space generally showed a downward and then upward trend, and the level of urbanization continued to rise. The development level between blue-green space and urbanization mainly showed a negative spatial correlation. (3) The coupling degree between composite systems showed a steady upward trend in time, but still lacked highly coordinated regions. Spatially, the coupling degree between the systems had a strong difference and agglomeration, showing the general characteristic of “High in the center, low in the north and south, and decreasing inward from the coast”, which was more spatially consistent with the level of urbanization. This study is of great significance to urban sustainable development planning of coastal mountain cities.
基于时空演化分析的沿海山地城市蓝绿空间与城市化协调关系评价——以青岛市为例
由于快速城市化的巨大影响,城市蓝绿空间面临着巨大的威胁。沿海山城作为高密度城市群的代表,在拥有复杂蓝绿系统的同时,也存在着巨大的生态脆弱性。为了支持城市的可持续发展,研究沿海山区城市化与蓝绿空间的协同关系至关重要。以典型的快速发展沿海山地城市青岛为例,在网格尺度上分析了研究区2000 - 2020年蓝绿空间与城市化的时空演化特征,并基于耦合协调模型探讨了城市化与蓝绿空间耦合协调度的时空动态趋势。结果表明:①2000 ~ 2020年青岛市土地利用变化剧烈;主要变化是城市对蓝绿空间的侵占,导致蓝绿空间景观格局的破碎化和复杂性,以中部沿海地区变化最为显著。(2)绿地和蓝色空间开发水平总体呈现先下降后上升的趋势,城市化水平持续上升。蓝绿空间发展水平与城市化之间主要呈现负空间相关关系。(3)复合系统间的耦合度随时间呈稳定上升趋势,但仍缺乏高度协调的区域。空间上,各系统之间的耦合度具有较强的差异性和集聚性,呈现出“中心高、南北低、沿海向内递减”的总体特征,与城市化水平在空间上更为一致。本研究对沿海山地城市可持续发展规划具有重要意义。
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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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