Spatial Distribution Characteristics and Influencing Factors of Cultivated Land Productivity in a Large City: Case Study of Chengdu, Sichuan, China

Yuanli Liu, Qiang Liao, Zhouling Shao, Wenbo Gao, Jie Cao, Chunyan Chen, Guitang Liao, Peng He and Zhengyu Lin ()
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Yuanli Liu: Institute of Agricultural Information and Rural Economy, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China
Qiang Liao: Institute of Agricultural Information and Rural Economy, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China
Zhouling Shao: Institute of Agricultural Information and Rural Economy, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China
Wenbo Gao: Institute of Agricultural Information and Rural Economy, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China
Jie Cao: Institute of Agricultural Information and Rural Economy, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China
Chunyan Chen: Institute of Agricultural Information and Rural Economy, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China
Guitang Liao: College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225, China
Peng He: College of Resources, Sichuan Agriculture University, Chengdu 611130, China
Zhengyu Lin: Institute of Agricultural Information and Rural Economy, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China

Land, 2025, vol. 14, issue 2, 1-18

Abstract: Given the constraints of limited cultivated land resources, ensuring and enhancing crop productivity are crucial for food security. This study takes Chengdu as a case study. Using the cultivated land productivity (CLP) evaluation model, we calculated the cultivated land productivity index (CLPI) and analyzed its spatial distribution characteristics. The Geographical Detector model was employed to identify the main factors influencing CLP, and corresponding countermeasures and measures were proposed based on the limiting degrees of these factors. The findings reveal that Chengdu’s CLP index ranges from 1231 to 3053. Global spatial autocorrelation analysis indicates a spatial agglomeration pattern in Chengdu’s overall crop productivity distribution. The local spatial autocorrelation analysis demonstrates that township (street)-level crop productivity in Chengdu is primarily characterized by “high–high”, “low–low”, and “low–high” clusters. Key factors influencing the spatial differentiation of CLP in Chengdu include the agronomic management level, soil bulk density, irrigation guarantee rate, soil body configuration, field slope, and farmland flood control standard. Interaction detection shows that there are both double-factor and nonlinear enhancements among the factors. Specifically, the interaction between soil bulk density and the agronomic management level among other factors have the most explanatory power for the spatial differentiation of CLP. The CLP in Chengdu is highly restricted by its technical level, with the agronomic management level severely limiting CLP by more than 50%. These research results provide a theoretical reference for regional high-standard farmland construction and the protection and utilization of cultivated land resources.

Keywords: cultivated land productivity; spatial distribution characteristics; spatial autocorrelation; GeoDetector; limitation factor; Chengdu City (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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