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Coupling coordination and spatio-temporal evolution of land-use benefits under the dual carbon goal: A case study in
Li Qian1, Huimin Yi1, Mengyuan Shen1
1School of Public Administration, Anhui Jianzhu University, No. 856, Jinzhai South Road, Hefei, Anhui, China.
Abstract:
According to the dual carbon goal, urban development should adhere to the principle of low-carbon sustainable development in order to reach the "carbon peak" in 2030 and "carbon neutrality" in 2060. To achieve the dual carbon goal and sustainable land resource utilization, it is necessary to seek ways to improve land-use benefits and promote the coordinated development of economic, social, and ecological benefits. Therefore, the study analysed the coupling coordination and spatio-temporal evolution of land-use benefits in Anhui province, aiming to provide a reference for improving the level of regional land-use benefits. First, we developed a land-use benefit evaluation indicator system that took into account the dual carbon goal from three perspectives: economic benefits, social benefits, and ecological benefits or economic, social, and ecological benefits. Following that, we evaluated the spatial-temporal characteristics of land-use benefits using the coupling coordination model and coupling coordination gravity model. The results showed: (1) From the time scale, the comprehensive land-use benefits showed an increasing trend from 2011 to 2020, the coordination state changed from "moderately uncoordinated" to "on the verge of uncoordinated". (2) From the perspective of spatial differences, the coupling coordination level of land-use benefits in 16 prefecture-level cities increased year by year, but no prefecture-level cities reached the coordination stage. (3) As for the spatial linkage strength of coupling coordination of land-use benefits, 16 prefecture-level cities in 2011, 2015 and 2020 presented a similar spatial linkage pattern, and the coupling coordination of prefecture-level cities in southeast Anhui province was strongly influenced by regional factors.
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