ANALYSIS ON REGIONAL LAND USE ZONING BASED ON FUZZY C-MEANS ALGORITHM OF PRINCIPAL COMPONENTS ——A CASE STUDY OF DAPU COUNTY IN GUANGDONG PROVINCE
提出一种结合因子分析和模糊C均值算法的定量方法，用于确定土地利用最优分区数量，并以广东大埔县为例验证该方法在小样本数据集上的有效性，同时可为大数据集的多分类效果提供后评估支持。
Land use zoning is essentially a classification problem,so how to apply the idea of fuzzy classification to discuss the optimal regionalization number strategy of land use shall be valuable for providing decision assistance for regional land use optimal zoning.But current research on land use zoning is usually conducted by adoption of traditional hard classification clustering method,of which the classification number is of a strong subjectivity,ignoring the existence of the objectivity of optimal zoning number.This study proposed a quantitative calculation method for land use optimal regionalization number by applying factor analysis,c-means and fuzzy c-means algorithm complying with the efficient maximum membership principle.After a case study of Dapu County in Guangdong Province,the results showed that the method was a better solution in solving the puzzle of optimal classification number determination in land utilization zoning with small sample dataset,meanwhile a post-assessment support could be provided for the multi-classification effect of massive sample dataset by this method.