2000—2020年粤港澳大湾区耕地非农化时空特征和影响因素

doi:10.14088/j.cnki.issn0439-8114.2026.07.010

摘要/Abstract

摘要： 在快速城市化背景下,揭示粤港澳大湾区耕地非农化的时空分异特征及其影响因素,对协调高度城镇化地区经济发展与耕地保护具有重要现实意义。基于2000—2020年多期土地利用数据,融合自然地理与社会经济因子,综合运用耕地数量变化指标、空间自相关分析及可解释机器学习方法（XGBoost-SHAP-PDP）,系统分析粤港澳大湾区耕地非农化的时空格局及其影响因素。结果表明,研究期内粤港澳大湾区耕地面积持续净减少27万hm²,非农化率在时间上呈现快速增长—波动下降—缓慢回升的阶段性演变特征,在空间上表现为显著的“核心-外围”梯度分异格局;全局莫兰指数为0.24~0.53,耕地非农化存在显著的空间集聚性,耕地非农化高值区由广佛惠核心区逐步向东部沿海扩展;耕地非农化重心迁移方向整体表现为“东偏南—北偏西—北偏东”的趋势,迁移距离逐期增大,由2005—2010年的4.24 km增至2010—2015年的18.99 km,并在2015—2020年进一步扩大至20.72 km,空间分布方向性整体呈先减弱后增强的变化趋势;影响因素分析表明,人口与经济因素为重要影响因素,但其影响程度随时间推移有所减弱,而农业机械化与粮食产量的抑制作用显著增强,各因素之间存在复杂的非线性协同效应。

关键词: 耕地非农化, 时空演变, 影响因素, 空间自相关, 可解释机器学习, 粤港澳大湾区

Abstract: Under the background of rapid urbanization, it is of great practical significance to reveal the spatio-temporal differentiation characteristics and influencing factors of non-agriculturalization of cultivated land in the Guangdong-Hong Kong-Macao Greater Bay Area for coordinating economic development and cultivated land protection in highly urbanized areas. Based on the multi-period land use data from 2000 to 2020, the spatial-temporal pattern and influencing factors of non-agriculturalization of cultivated land in the Guangdong-Hong Kong-Macao Greater Bay Area were systematically analyzed by integrating natural geography and socio-economic factors, and using the change index of cultivated land quantity, spatial autocorrelation analysis and interpretable machine learning method (XGBoost-SHAP-PDP). The results showed that the area of cultivated land in the Guangdong-Hong Kong-Macao Greater Bay Area continued to decrease by 270 000 hm² during the study period. The non-agriculturalization rate showed a stage evolution characteristic of rapid growth-fluctuating decline-slow recovery over time, and showed a significant “core-periphery” gradient differentiation pattern in space. The global Moran's I was 0.24-0.53, and the non-agriculturalization of cultivated land had significant spatial agglomeration. The high-value areas gradually expanded from the core region of Guangzhou, Foshan and Huizhou to the eastern coastal zones. The overall migration trend of the gravity center of cultivated land non-agricultural conversion followed the sequence of “southeastward-northwestward-northeastward”, and the migration distance increased from 4.24 km in 2005-2010 to 18.99 km in 2010-2015, and further expanded to 20.72 km in 2015-2020. The directional characteristic of its spatial distribution first weakened and then strengthened. In terms of influencing factors, population and economic conditions served as major drivers, while their impacts gradually declined over time. By contrast, agricultural mechanization and grain output exerted an increasingly prominent restraining effect. Complex non-linear synergistic relationships existed among various influencing factors.

Key words: cultivated land non-agriculturalization, spatio-temporal evolution, influencing factors, spatial autocorrelation, interpretable machine learning, Guangdong-Hong Kong-Macao Greater Bay Area

中图分类号:

F301.21

郭婧超, 张国壮. 2000—2020年粤港澳大湾区耕地非农化时空特征和影响因素[J]. 湖北农业科学, 2026, 65(7): 60-69.

GUO Jing-chao, ZHANG Guo-zhuang. Spatio-temporal characteristics and influencing factors of cultivated land non-agriculturalization in the Guangdong-Hong Kong-Macao Greater Bay Area from 2000 to 2020[J]. HUBEI AGRICULTURAL SCIENCES, 2026, 65(7): 60-69.

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