湖北农业科学 ›› 2025, Vol. 64 ›› Issue (6): 72-80.doi: 10.14088/j.cnki.issn0439-8114.2025.06.013

• 资源·环境 • 上一篇    下一篇

贵州省耕地“非粮化”空间分异特征及影响因素

廖艳梅1,2, 尹林江3, 蒙友波1,2, 韩敏1,2, 张慧1,2, 罗洁琼4   

  1. 1.贵州省自然资源勘测规划研究院,贵阳 550004;
    2.自然资源部贵州喀斯特山地国土生态与土地利用野外科学观测研究站,贵阳 550001;
    3.贵州科学院贵州省山地资源研究所,贵阳 550001;
    4.南通大学交通与土木工程学院,江苏 南通 226019
  • 收稿日期:2025-03-25 出版日期:2025-06-25 发布日期:2025-07-18
  • 通讯作者: 张 慧(1980-),女,贵州贵阳人,主要从事自然资源调查监测和耕地保护研究,(电子信箱)438649469@qq.com。
  • 作者简介:廖艳梅(1995-),女(仡佬族),贵州遵义人,硕士,主要从事自然资源调查、监测、评价研究,(电子信箱)yliaoyanmei@163.com
  • 基金资助:
    国家自然科学基金项目(42001239); 部省合作项目(2024ZRBSHZ042); 黔科合重大专项([2022]001-TZ2022-001)

Spatial differentiation characteristics and influencing factors of “non-grain conversion” of cultivated land in Guizhou Province

LIAO Yan-mei1,2, YIN Lin-jiang3, MENG You-bo1,2, HAN Min1,2, ZHANG Hui1,2, LUO Jie-qiong4   

  1. 1. Guizhou Institute of Natural Resources Survey and Planning, Guiyang 550004, China;
    2. Guizhou Karst Mountain Land Ecosystem and Land Use Field Scientific Observation and Research Station, Ministry of Natural Resources, Guiyang 550001, China;
    3. Institute of Mountain Resources, Guizhou Academy of Sciences, Guiyang 550001, China;
    4. School of Transportation and Civil Engineering, Nantong University, Nantong 226019, Jiangsu, China
  • Received:2025-03-25 Published:2025-06-25 Online:2025-07-18

摘要: 以市州、县域为研究单元,运用空间自相关分析贵州省2020年耕地“非粮化”空间分异特征,并借助普通最小二乘法、地理加权回归方法探讨其空间分异的影响因素。结果表明,2020年贵州省耕地“非粮化”面积达9 331.88 km2。贵阳市、铜仁市、遵义市、黔西南布依族苗族自治州和黔南布依族苗族自治州的耕地“非粮化”率较高,黔东南苗族侗族自治州最低;从耕地“非粮化”面积看,各市州整体呈北高南低的趋势。县域耕地“非粮化”率的热点区主要分布在贵州省中部县域,冷点区主要分布在黔东南苗族侗族自治州台江县和榕江县;耕地“非粮化”面积的热点区主要分布在贵州省东北部、西部县域,冷点区主要分布在贵州省中部、东部县域。人均GDP、规模以上工业增加值增速、乡村从业人员数量、喀斯特面积占比的抑制效应以及交通用地占比、海拔的正向驱动效应在空间上均呈现梯度变化的特征。受农户主体属性、自然资源、社会经济因素影响,贵州省耕地“非粮化”空间分异明显,影响因子空间异质性显著,可根据各地差异性,因地制宜采取措施抑制耕地“非粮化”。

关键词: 耕地, “非粮化”, 空间分异特征, 影响因素, 贵州省

Abstract: Taking prefecture-level cities and counties as research units, spatial autocorrelation analysis was used to analyze the spatial differentiation characteristics of “non-grain conversion” of cultivated land in Guizhou Province in 2020, and ordinary least squares (OLS) and geographically weighted regression (GWR) methods were applied to explore its influencing factors.The results showed that the area of “non-grain conversion” of cultivated land in Guizhou Province reached 9 331.88 km2 in 2020.The “non-grain conversion” rates of cultivated land were higher in Guiyang City, Tongren City, Zunyi City, Qianxinan Buyi and Miao Autonomous Prefecture, and Qiannan Buyi and Miao Autonomous Prefecture, while the lowest rate was observed in Qiandongnan Miao and Dong Autonomous Prefecture.In terms of the “non-grain conversion” area of cultivated land, all prefecture-level cities generally showed a spatial pattern of high in the north and low in the south.The hotspot areas of “non-grain conversion” rates at the county level were mainly distributed in central Guizhou Province, while the coldspot areas were concentrated in Taijiang County and Rongjiang County of Qiandongnan Miao and Dong Autonomous Prefecture.The hotspot areas of “non-grain conversion” area were predominantly located in northeastern and western counties of Guizhou Province, whereas the coldspot areas were mainly distributed in central and eastern counties.The inhibitory effects of per capita GDP, growth rate of industrial added value above designated size, number of rural employed persons, and karst area proportion, as well as the positive driving effects of transportation land proportion and altitude, all exhibited gradient spatial variations.Influenced by farmer household attributes, natural resources, and socio-economic factors, the spatial differentiation of “non-grain conversion” of cultivated land in Guizhou Province was significant, with notable spatial heterogeneity of influencing factors. Region-specific measures should be adopted to curb “non-grain conversion” based on local conditions.

Key words: cultivated land, “non-grain conversion”, spatial differentiation characteristics, influencing factors, Guizhou Province

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