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Analysis of the Evolution of Non-Agriculturization Arable Land Use Pattern and Its Driving Mechanisms

Author

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  • Ying Zhang

    (College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
    Tangshan Vocational and Technical College, Tangshan 063000, China
    Yanshan Late-Maturing Peach Technology Innovation Center, Tangshan 063000, China)

  • Qiang Wang

    (Aerospace Wanyuan Cloud Data Hebei Co., Ltd., Tangshan 063000, China)

  • Yueming Hu

    (College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
    College of Tropical Crops, Hainan University, Haikou 570208, China)

  • Wei Wang

    (College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China)

  • Xiaoyun Mao

    (College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China)

Abstract

Arable land is a crucial natural resource for human survival and development, which supports food production, ecological services, and material–energy cycling. It is not only an important production resource for agriculture but also a key guarantee for ensuring food security and sustainable agricultural development. Understanding the current utilization of arable land, exploring the spatial–temporal evolution characteristics, and analyzing the driving mechanisms behind its pattern changes are essential for the rational allocation and sustainable utilization of arable land resources. This study focuses on the utilization of arable land in Guangzhou from 2005 to 2018, employing methods such as statistical analysis and spatial econometrics to provide an in-depth analysis of the spatial–temporal distribution characteristics and driving mechanisms of arable land changes. The results show that from 2005 to 2018, the issue of the conversion of arable land to non-agricultural uses was quite severe in Guangzhou, with the primary form being the conversion of arable land into urban residential construction land. Kernel density analysis revealed that non-agriculturization in Guangzhou exhibited spatial clustering, mainly concentrated in areas with lower elevation. Using standard deviation ellipses and centroid migration analysis, it was found that the center of gravity of non-agriculturization in Guangzhou was generally distributed in a southwest–northeast direction, with a more distinct dispersion compared to the northwest–southeast direction. From 2005 to 2010, the rapid increase in the non-agriculturization rate of arable land in Guangzhou was mainly driven by population density and per capita income, both having a positive impact. From 2010 to 2015, the main driving factor shifted to regional GDP. From 2015 to 2018, regional GDP and the value of the tertiary industry became the main driving factors, but unlike the impact of GDP, the tertiary industry exerted a negative influence on non-agriculturization.

Suggested Citation

  • Ying Zhang & Qiang Wang & Yueming Hu & Wei Wang & Xiaoyun Mao, 2025. "Analysis of the Evolution of Non-Agriculturization Arable Land Use Pattern and Its Driving Mechanisms," Land, MDPI, vol. 14(5), pages 1-21, April.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:5:p:968-:d:1646775
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    References listed on IDEAS

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    1. Yan Sun & Yuanyuan Chang & Junna Liu & Xiaoping Ge & Gang-Jun Liu & Fu Chen, 2021. "Spatial Differentiation of Non-Grain Production on Cultivated Land and Its Driving Factors in Coastal China," Sustainability, MDPI, vol. 13(23), pages 1-18, November.
    2. Yan Ma & Xingyu Wang & Chuanliang Zhong, 2024. "Spatial and Temporal Differences and Influencing Factors of Eco-Efficiency of Cultivated Land Use in Main Grain-Producing Areas of China," Sustainability, MDPI, vol. 16(13), pages 1-20, July.
    3. Zhengxiang Wu & Qingbin Fan & Wen Li & Yong Zhou, 2024. "The Spatial–Temporal Evolution and Impact Mechanism of Cultivated Land Use in the Mountainous Areas of Southwest Hubei Province, China," Land, MDPI, vol. 13(11), pages 1-23, November.
    4. Huiting Yan & Hao Chen & Fei Wang & Linjing Qiu, 2025. "Dynamics of Cropland Non-Agriculturalization in Shaanxi Province of China and Its Attribution Using a Machine Learning Approach," Land, MDPI, vol. 14(1), pages 1-18, January.
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