基于模糊ISODATA聚类方法的农用地定级研究

    Agricultural land gradation based on the fuzzy ISODATA clustering method

    • 摘要: 针对经典模糊聚类分析中采用传递闭包法在改造模糊相似矩阵过程中存在的传递偏差问题,本文尝试采用具有动态修正聚类中心,进行局部优化算法的模糊ISODATA聚类方法,结合GIS技术,进行农用地定级研究,并以江苏省金坛市为例进行定级评价实证分析。研究结果表明,金坛市农用地划分为四个级别,Ⅰ~Ⅳ级之面积比例为42.20%:22.41%:20.35%:15.04%。与传统的采用多因素综合法计算评价单元总分值,以数轴法或总分频率曲线法进行土地级别划分的定级结果相比较,实验结果与江苏省农用地分等成果联系较为紧密,体现了较好的等、级承接关系。

       

      Abstract: The Fuzzy Clustering Method(FCM) is widely used in agricultural land gradation (ALG). However, the FCM may usually bring into an accumulated information bias during the evolution of fuzzy similar matrix. The Fuzzy ISODATA Clustering Method(FISOCM), which can refine the clustering center dynamically, is researched in the present paper. Integrated with GIS, the FISOCM is applied to make the land gradation in Jintan city, Jiangsu Province. The area proportion of gradation from grade I to grade IV is 42.20%, 22.41%, 20.35% and 15.04% respectively. The result shows that the improved method FISOCM is better than the traditional agricultural land gradation method, which valued by weighted sum of indices, and gradation is classified by axis based method or sum frequency curve method. The test result can relate the existent result of agricultural land classification hierarchy more closely.

       

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