Cultivated Land Suitability Prediction in Southern Xinjiang Typical Areas Based on Optimized MaxEnt Model

Yilong Tian, Xiaohuang Liu (), Hongyu Li, Run Liu, Ping Zhu, Chaozhu Li, Xinping Luo, Chao Wang and Honghui Zhao
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Yilong Tian: Key Laboratory of Coupling Processes and Effects of Natural Resources Elements, Ministry of Natural Resources, Beijing 100055, China
Xiaohuang Liu: Key Laboratory of Coupling Processes and Effects of Natural Resources Elements, Ministry of Natural Resources, Beijing 100055, China
Hongyu Li: Key Laboratory of Coupling Processes and Effects of Natural Resources Elements, Ministry of Natural Resources, Beijing 100055, China
Run Liu: Key Laboratory of Coupling Processes and Effects of Natural Resources Elements, Ministry of Natural Resources, Beijing 100055, China
Ping Zhu: Key Laboratory of Coupling Processes and Effects of Natural Resources Elements, Ministry of Natural Resources, Beijing 100055, China
Chaozhu Li: Key Laboratory of Coupling Processes and Effects of Natural Resources Elements, Ministry of Natural Resources, Beijing 100055, China
Xinping Luo: Key Laboratory of Coupling Processes and Effects of Natural Resources Elements, Ministry of Natural Resources, Beijing 100055, China
Chao Wang: Key Laboratory of Coupling Processes and Effects of Natural Resources Elements, Ministry of Natural Resources, Beijing 100055, China
Honghui Zhao: Key Laboratory of Coupling Processes and Effects of Natural Resources Elements, Ministry of Natural Resources, Beijing 100055, China

Agriculture, 2025, vol. 15, issue 14, 1-19

Abstract: To ensure food security in Xinjiang, scientifically conducting land suitability evaluation is of significant importance. This paper takes an arid and ecologically fragile region of southern Xinjiang—Qiemu County—as an example. Based on the optimized Maximum Entropy (MaxEnt) model, 14 multi-source environmental variables including climate, soil, hydrology, and topography are integrated. The ENMeval package is used to optimize the model parameters, and Spearman’s rank correlation analysis is employed to screen key variables. The spatial distribution of land suitability and the dominant factors are systematically assessed. The results show that the model AUC values for the mountainous and plain areas are 0.987 and 0.940, respectively, indicating high accuracy. In the plain area, land suitability is primarily influenced by the soil sand content, while in the mountainous region, the annual accumulated temperature plays a leading role. The highly suitable areas are mainly distributed in the northern plains and parts of the southern mountains. This study clarifies the suitable areas for land development and environmental thresholds, providing a scientific basis for the development of land resources in arid regions and the implementation of the “store grain in the land” strategy.

Keywords: optimized MaxEnt model; suitable zones; arable land in Qiemo County (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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