ORIGINAL RESEARCH
Temporal and Spatial Characteristics
of the Coupled Coordination Degree
of the ‘Three Life’ Functions of Arable Land
in Xinjiang and its Driving Factors
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College of Economics and Management, Xinjiang Agricultural University, Urumqi, China
These authors had equal contribution to this work
Submission date: 2025-05-16
Final revision date: 2025-06-23
Acceptance date: 2025-07-18
Online publication date: 2025-10-20
Corresponding author
Guoyong Liu
College of Economics and Management, Xinjiang Agricultural University, Urumqi, China
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ABSTRACT
Exploring the multifunctionality of arable land and identifying the spatiotemporal characteristics
of its various functions are essential for promoting the coordinated and sustainable use of farmland in
Xinjiang. Based on socio-economic data from 14 prefectures in Xinjiang from 2009 to 2020, this study
employs a coupling coordination degree model, spatial autocorrelation analysis, and the geographical
detector method to measure the coupling coordination degree of the “production-living-ecological”
functions of arable land and to analyze its spatiotemporal evolution and driving factors. The results
indicate that: (1) From 2009 to 2020, the production, living, and ecological functions of arable land
in Xinjiang exhibited varying degrees of spatial and temporal differentiation. The production and
living functions showed an upward trend, while the ecological function demonstrated a downward
trend. (2) During the study period, the coupling coordination degree of the three functions increased
slightly, though no prefecture reached a state of high coordination. Most prefectures remained
in a state of imbalance. Spatially, the coordination degree was generally higher in northern Xinjiang
than in the southern region, shifting from a monocentric to a polycentric agglomeration pattern.
(3) The primary driving factors of the coupling coordination degree were regional policy implementation
level, agricultural development level, and industrial development level. The interactions among these
factors manifested as both bivariate enhancement and nonlinear enhancement, with a notable transition
trend from bivariate to nonlinear enhancement over time.