Spatiotemporal Characteristics and Determinants of Rural Construction Land in China’s Developed Areas: A Case Study of the Yangtze River Delta

Fangqu Niu, Lan Wang and Wei Sun ()
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Fangqu Niu: Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Lan Wang: Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Wei Sun: Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Land, 2023, vol. 12, issue 10, 1-19

Abstract: Rural construction land (RCL) received less attention but played an important role to control rural land use. Studying the RCL of developed areas may provide valuable references for underdeveloped areas to optimize land use. The Yangtze River Delta (YRD) is the most economically developed region in China. The study is intended to explore the spatiotemporal characteristics and determinants of RCL in the YRD based on a period of data from 1990 to 2017. The results show that the RCL in the YRD increases at an average annual rate of 5.38% but the growth rate tends to decrease. There is a weak spatial linkage of the RCL growth between cities. Clear spatial differences exist in the effects of every determinant of RCL. The correlation between the rural population and the RCL is unstable, which proves the existence of hollow villages. There is no clear correlation between the RCL and the local economy and accessibility, as the rural population normally goes to few big cities for higher salary work but spends the money in their hometowns on building homes. These findings help optimize rural land use in the YRD and provide an important reference for planning land use in underdeveloped regions.

Keywords: rural construction land (RCL); land use; exploratory spatiotemporal data analysis (ESTDA); multiscale geographically weighted regression (MGWR) (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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