Spatiotemporal Patterns and Driving Factors of Cropland Abandonment in Metropolitan Suburbs: A Case Study of Chengdu Directly Administered Zone, Tianfu New Area, Sichuan Province, China

Mingyong Zuo, Guoxiang Liu (), Chuangli Jing, Rui Zhang, Xiaowen Wang, Wenfei Mao, Li Shen, Keren Dai and Xiaodan Wu
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Mingyong Zuo: Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 610097, China
Guoxiang Liu: Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 610097, China
Chuangli Jing: Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 610097, China
Rui Zhang: Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 610097, China
Xiaowen Wang: Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 610097, China
Wenfei Mao: Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 610097, China
Li Shen: Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 610097, China
Keren Dai: The State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China
Xiaodan Wu: Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 610097, China

Land, 2025, vol. 14, issue 6, 1-24

Abstract: Cropland abandonment (CA) has become a significant threat to agricultural sustainability, particularly in metropolitan suburbs where urban expansion and cropland preservation often conflict. This study examines the Chengdu Directly Administered Zone of the Tianfu New Area in Sichuan Province, China, as a case study, utilizing high-precision vector data from China’s 2019–2023 National Land Survey to identify abandoned croplands through land use change trajectory analysis. By integrating kernel density estimation, spatial autocorrelation analysis, and geographically weighted regression modeling, we quantitatively analyzed the spatiotemporal patterns of CA and the spatial heterogeneity of driving factors in the study area. The results demonstrate an average annual abandonment rate of approximately 8%, exhibiting minor fluctuations but significant spatial clustering characteristics, with abandonment hotspots concentrated in peri-urban areas that gradually expanded toward urban cores over time, while exurban regions showed lower abandonment rates. Cropland quality and the aggregation index were identified as key restraining factors, whereas increasing slope and land development intensity were found to elevate abandonment risks. Notably, distance to roads displayed a negative effect, contrary to conventional understanding, revealing that policy feedback mechanisms induced by anticipated land expropriation along transportation corridors serve as important drivers of suburban abandonment. This study provides a scientific basis for optimizing resilient urban–rural land allocation, curbing speculative abandonment, and exploring integrated “agriculture + ecology + cultural tourism” utilization models for abandoned lands. The findings offer valuable insights for balancing food security and sustainable development in rapidly urbanizing regions worldwide, particularly providing empirical references for developing countries addressing the dilemma between urban expansion and cropland preservation.

Keywords: cropland abandonment; spatiotemporal patterns; driving factors; metropolitan suburbs; Tianfu New Area; China (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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