Changes and Driving Forces of Urban–Agricultural–Ecological Space in the Yangtze River Economic Belt from 2000 to 2020

Junnan Xia, Mengyao Hong and Wei Wei ()
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Junnan Xia: School of Urban Design, Wuhan University, Wuhan 430072, China
Mengyao Hong: School of Urban Design, Wuhan University, Wuhan 430072, China
Wei Wei: School of Urban Design, Wuhan University, Wuhan 430072, China

Land, 2023, vol. 12, issue 5, 1-17

Abstract: Optimizing the urban–agricultural–ecological space in the Yangtze River Economic Belt is integral to China’s sustainable land development and protection. Based on land use data from 2000 to 2020, this study identified the urban-agricultural-ecological space in the Yangtze River Economic Belt. It analyzed its changes and driving forces using the land use transfer matrix, the Dagum Gini coefficient, and GeoDetector. The results show that urban space has increased significantly over the past 20 years, agricultural space has decreased dramatically, and ecological space has remained stable. The transformation of agricultural space into urban space was the dominant type of space transformation, followed by a mutual transformation between agricultural and ecological spaces. Each transformation type exhibited significant spatial inequality within and between regions. Socioeconomic and natural conditions significantly impacted the spatial transformation, and all factors have an apparently interactive reinforcing effect. The research has enhanced the identification accuracy of urban–agricultural–ecological spaces, precisely illustrating the changes and driving forces of the land spatial pattern in the Yangtze River Economic Belt over the last two decades. It holds vital theoretical and practical implications for the optimization of China’s land spatial pattern.

Keywords: urban–agricultural–ecological space; land cover; LUCC; Dagum Gini coefficient; optimal parameters-based geographical detector model (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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