刘彦文, 周霞, 何宗宜, 郝汉舟, 何国松. 基于Logistic回归的耕地数量演变及其空间要素边际效应分析[J]. 农业工程学报, 2020, 36(11): 267-276. DOI: 10.11975/j.issn.1002-6819.2020.11.032
    引用本文: 刘彦文, 周霞, 何宗宜, 郝汉舟, 何国松. 基于Logistic回归的耕地数量演变及其空间要素边际效应分析[J]. 农业工程学报, 2020, 36(11): 267-276. DOI: 10.11975/j.issn.1002-6819.2020.11.032
    Liu Yanwen, Zhou Xia, He Zongyi, Hao Hanzhou, He Guosong. Quantitative evolution and marginal effect analysis of spatial factors of cultivated land based on Logistic regression[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2020, 36(11): 267-276. DOI: 10.11975/j.issn.1002-6819.2020.11.032
    Citation: Liu Yanwen, Zhou Xia, He Zongyi, Hao Hanzhou, He Guosong. Quantitative evolution and marginal effect analysis of spatial factors of cultivated land based on Logistic regression[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2020, 36(11): 267-276. DOI: 10.11975/j.issn.1002-6819.2020.11.032

    基于Logistic回归的耕地数量演变及其空间要素边际效应分析

    Quantitative evolution and marginal effect analysis of spatial factors of cultivated land based on Logistic regression

    • 摘要: 厘清耕地演变的驱动机制对中国耕地资源可持续利用具有重要现实意义。该研究以鄂南地区为例,利用2000-2005、2005-2010和2010-2015年3期Landsat遥感影像解译成果、15类POI(Point of Interest)空间数据等,采用主成分分析、多元Logistic回归模型、边际效应分析等方法,系统分析了研究区近15 a以来耕地动态变化及其时空演变规律,并着重探讨了空间要素在驱动机制方面的双向边际效应。结果表明:1)耕地演变类型在空间上表现出相同类型的集聚性,转换类型受周边同类用地空间溢出效应影响明显。在时间上表现出不同转换类型的差异性,转换类型受土地利用政策宏观调控影响向建设用地单一转化趋势明显。2000-2015年间,耕地向建设用地的转换比例自28%过渡至44%后,迅速上升至96%,主要集中在城镇周边、主要道路沿线等区域。2)空间要素对不同时期耕地不同转化类型存在不同的边际效应,2000-2015年间耕地不同转化类型的边际效应变化幅度逐渐减小、不同转化类型边际效应曲线同类交点呈同向移动趋势。自然区位因素对耕地向建设用地转换和耕地向水域转换在POI空间要素不同取值时边际效应的变化较明显。3)空间要素边际效应曲线特征揭示其影响存在临界性,在临界值范围内,边际效应随着空间要素取值不同变化明显,但在临界值范围外,边际效应趋于稳定。耕地演变空间要素边际效应的定性定量分析对耕地布局优化与区域协调发展策略制定具有良好参考作用。

       

      Abstract: Abstract: Evolution of cultivated land needs to be clarified in the driving mechanism for the sustainable land use in China. Most studies generally focused on the relationship between the evolutionary data and the driving mechanism in the evolution of cultivated land use. However, research on the drivers of marginal impact is rare, such as the spatial factor density that represented by the POI points. There can be a tipping point of marginal impact, when the quantity reaches a specific region, in the distance to the main road represented by the human factors. In this paper, the marginal effect analysis was used to make a preliminary evaluation, taking Southern Hubei as an example. Landsat remote sensing images were selected for the interpretation data of three periods from the year of 2000-2005, 2005-2010 and 2010-2015, including 15 types of POI spatial data. Firstly, the evaluation system of spatial factors was constructed from three aspects, including Euclidean distance indices, POI kernel density indices and locational indices. The Spatio-temporal evolution of cultivated land was systematically analyzed, together with dynamic change in the area from 2000 to 2015. Secondly, the principal component analysis was used to integrate the driving factors for the change of cultivated land. The extracted principal components were selected to construct the multiple Logistic regression models, including interaction terms. Lastly, an emphasis was put on the bidirectional marginal effect of spatial elements in the driving mechanism, and the change rule that illustrated by the graph of marginal effect. The results indicated that: (1) The evolution types of cultivated land showed the agglomeration of the same type, while the specific conversion type strongly depended on the spillover effect of neighboring land use. There was obvious evolution trend from cultivated land to construction, but others were not, possibly due to the influence from the macro-control policy of land use. From 2000 to 2015, the proportion of cultivated land converted to construction land increased from 28% to 44%, and then jumped to 96%, mainly concentrated in areas around towns and along major roads. (2) Marginal effects of spatial factors depend on types of cultivated land and periods. From 2000 to 2015, there was a gradual decrease in the variation range of marginal effect for different conversion types of cultivated land, while the homogeneous intersection point moved in the same direction for marginal effect curves of different transformation types. The dominated marginal effect of natural location factors was on the conversion of cultivated land to construction land, and cultivated land to water area, when the spatial elements of POI were different values. (3) The curve of spatial factors implied that there was a critical value of marginal effect. In the range of critical values, marginal effect changed significantly with the spatial factors, but outside the range, marginal effect tended to be stable. The qualitative and quantitative analysis on the marginal effect of spatial factors can offer a theoretical reference for the optimization of cultivated land layout, and the formulation of regional coordinated development strategy.

       

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