孔祥斌, 李翠珍, 王红雨, 马 嵩, 焦晋升, 李 涛, 张青璞, 李 靖. 京冀平原区地块尺度农户耕地集约利用差异对比[J]. 农业工程学报, 2010, 26(14): 331-337.
    引用本文: 孔祥斌, 李翠珍, 王红雨, 马 嵩, 焦晋升, 李 涛, 张青璞, 李 靖. 京冀平原区地块尺度农户耕地集约利用差异对比[J]. 农业工程学报, 2010, 26(14): 331-337.
    Kong Xiangbin, Li Cuizhen, Wang Hongyu, Ma Song, Jiao Jinsheng, Li Tao, Zhang Qingpu, Li Jing. Analysis on arable land intensity difference at plot scale in Jingji Plain[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(14): 331-337.
    Citation: Kong Xiangbin, Li Cuizhen, Wang Hongyu, Ma Song, Jiao Jinsheng, Li Tao, Zhang Qingpu, Li Jing. Analysis on arable land intensity difference at plot scale in Jingji Plain[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(14): 331-337.

    京冀平原区地块尺度农户耕地集约利用差异对比

    Analysis on arable land intensity difference at plot scale in Jingji Plain

    • 摘要: 为进行地块尺度耕地集约度的定量分析,该文选取北京市大兴区和河北省曲周县为对比研究区域,以全区域范围内的地块对应农户调研数据为基础,采取价值和实物2种形态的耕地利用集约度进行比较。研究结果表明:对于耕地利用集约度的价值形态,大兴区显著高于曲周县。大兴区地块的资本集约度平均值为9 797.30元hm2,曲周县为5 025.18元/ hm2;就价值集约度的构成来看,如果将农户家庭用工计入生产成本,劳动集约度所占比例较高,大兴区平均为67.03%,曲周县大于70%。对于实物形态的耕地利用集约度,大兴区也高于曲周县,同时大兴区农户相对更关注有机肥的使用;且对比分析亦显示出大兴区地块尺度的耕地利用集约度空间变异大于曲周县,表明大兴区域农户土地利用的个体差异较大。研究认为,城市郊区的农户相对更偏好资本和劳动集约的利用方式,关注有机肥的使用。因农户土地利用目标的差异,农户对资源环境,社会政策等因素变化做出响应进而形成不同的农户土地利用行为特征,这是导致地块尺度耕地利用集约度差异的重要微观动因,区域经济发展水平则是其中观尺度的重要影响因素。

       

      Abstract: In order to analyze the difference of arable land use intensity at plot level,Daxing in Beijing and Quzhou in Hebei province, which located in Jingji plain, were taken as comparative study areas in the paper. On the basis of farm household survey data at the plots level with GPS positioning on the whole county, the two areas were compared by arable land use intensity both in monetary and physical form. The results showed that: the economic development level was one of the most important factor impacting on the arable land use intensity, and the capital intensity for arable land use at plot level in Daxing was higher than that in Quzhou, which was 9 797.30 yuan/ha on average in Daxing, and 5 025.18 yuan/ha in Quzhou. From the composition of the arable land use intensity in monetary form, the arable land use labor intensity took a great share of the total, which the percentage was 67.03% on average in Daxing, and above 70% in Quzhou, while taking in the cost of the family labor in agriculture production. The arable land intensity in physical form showed that fertilizer input amount per ha in Daxing was greater than that in Quzhou, and farmers in Daxing had paid more attention to organic fertilizer adopt. The arable land use intensity at plot level in Daxing had much more spatial and temporal divergence than that in Quzhou, which showed that there were larger individual differences in land use behaviors between Daxing and Quzhou. The spatial variation of the arable land use intensity at pot level mainly came from the diversification of farm household land use objectives, which indicated that we should put emphasis on the spatial variation of farm household land use intensity to understand the driving force of the arable land in the future.

       

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