粮食产销平衡区耕地非粮化动态演变及分区管控——以陕西省为例

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Dynamic evolution and zoning control of cultivated land non-grain in grain production and marketing balance area: A case of Shaanxi Province

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doi:10.12118/j.issn.1000-6060.2024.121

Abstract:

Exploring the spatial and temporal evolution characteristics and driving factors of cultivated land non-grain in grain production and marketing balance areas is crucial for providing references for differentiated control measures and long-term management strategies. This study employs spatial autocorrelation models, spatio-temporal geographically weighted regression models, K-means algorithms, and other methods to investigate the spatio-temporal evolution of cultivated land non-grain and its driving factors in Shaanxi Province, China, from 2000 to 2020. The results reveal the following: (1) The non-grain rate of cultivated land in Shaanxi Province increased from 16.11% in 2000 to 27.87% in 2020, representing a 73.00% rise. (2) The spatial distribution of non-grain in the province followed a pattern of “high in the north-south and low in the center.” The center of “high-high agglomeration” shifted gradually from the junction of the Guanzhong region and the northern region to the southern region of Shaanxi Province. Meanwhile, the “low-low agglomeration” was primarily concentrated in the Guanzhong region, exhibiting a diffusion trend from the center to surrounding areas. (3) The influence and scope of driving factors for cultivated land non-grain display significant spatio-temporal heterogeneity. The added value of the primary industry showed an increasing influence on cultivated land non-grain, while factors such as per capita cultivated land area, per capita mechanical labor force, average land slope, and annual precipitation demonstrated a decreasing influence. (4) The non-grain driving type of cultivated land in Shaanxi Province is mainly economic-driven, which is mainly distributed in Guanzhong region. Promoting the cost reduction and income increase of grain farmers and reducing the loss of rural population are the key points of control strategies. The types of production support are mainly distributed in the northern region, and the control strategies are mainly to improve the grain planting conditions and promote the development of the agricultural economy. The environmental restriction types are mainly distributed in the southern region of Shaanxi Province, and the combination measure of policy guidance and control strategies is the governance mode.

Key words: cultivated land protection, non-grain of cultivated land, grain production and marketing balance area, spatio-temporal geographically weighted regression model

WU Yifan, XING Peixue, ZHENG Weiwei, XIA Xianli, ZHANG Chaozheng. Dynamic evolution and zoning control of cultivated land non-grain in grain production and marketing balance area: A case of Shaanxi Province[J].Arid Land Geography, 2025, 48(1): 153-167.

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维度	因子	单位	预期符号
社会经济	一产增加值（X₁）	10⁸元	+
	农村居民可支配收入（X₂）	元	±
	乡村人口数（X₃）	10⁴人	+
生产条件	人均耕地面积（X₄）	hm²·人^-1	±
	人均机械劳动力（X₅）	kW·人^-1	+
	路网密度（X₆）	km·km^-2	+
自然禀赋	平均坡度（X₇）	（°）	+
	年降水量（X₈）	mm	±
	年均气温（X₉）	°C	+

年份	全局莫兰指数	P值
2000	0.283	0.001
2005	0.224	0.001
2010	0.144	0.025
2015	0.090	0.078
2020	0.123	0.021

维度	自变量	回归系数	标准误	P值	方差膨胀因子（VIF）
社会经济	一产增加值（X₁）	0.160	0.032	0.000^***	1.967
	农村居民可支配收入（X₂）	0.483	0.058	0.000^***	1.578
	乡村人口数（X₃）	-0.095	0.020	0.000^***	1.808
生产条件	人均耕地面积（X₄）	0.380	0.043	0.000^***	1.917
	人均机械劳动力（X₅）	-0.472	0.084	0.000^***	1.522
	路网密度（X₆）	0.245	0.029	0.000^***	1.698
自然禀赋	平均坡度（X₇）	0.132	0.012	0.000^***	2.010
	年降水量（X₈）	-0.072	0.021	0.001^***	1.635
	年均气温（X₉）	-0.063	0.022	0.005^***	1.804

影响因子	第一主成分	第二主成分	第三主成分
一产增加值（X₁）	0.346	-0.153	0.277
农村居民可支配收入（X₂）	-0.369	0.065	0.253
乡村人口数（X₃）	0.368	-0.237	0.226
人均耕地面积（X₄）	0.223	0.374	-0.049
人均机械劳动力（X₅）	0.063	0.353	0.046
路网密度（X₆）	-0.486	-0.049	0.222
平均坡度（X₇）	-0.042	-0.113	-0.337
年降水量（X₈）	-0.089	-0.309	-0.189
年均气温（X₉）	0.025	0.105	-0.037

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