Farmland consolidation partitioning by clustering analysis of density graph based on dimension reduction processing

Abstract: For the factors affecting cultivated land quality vary with regions, classifying of land consolidation regions is the groundwork for farmland consolidation, which has great significance to improve the pertinence and effectiveness of the consolidation project. However, there exists some problems with the classification of large sample with multidimensional variable space, such as the classifying parameters being difficult to give and the result lacking visualization. In this paper, a new method called the graphical method of density diagram was put forward based on principal component analysis to improve the objectivity, visibility and interpretation of the classification. The processes were as follows: At the first, the method of principal component analysis was used to get the principal components from multiple factors, and then the values of first principal component (F1) and the second one (F2) of all the samples of Xinzheng City, Henan Province were calculated. Secondly, land consolidation regions were classified using cluster analysis method by making a scatter diagram of the samples in a two-dimensional plane of F1-F2 to create a scatter density figure. Finally, the types of land consolidation regions were subdivided by the method of parsing with the qualitative factors, such as landform type and soil texture. The study was performed in Xinzheng City, and the results showed that: 1) F1 and F2 contained 85.55% of the total information of the original factors including organic matter, total nitrogen, available phosphorus, available potassium of soil and irrigation rate, which could take the place of all of the original factors to classify land consolidation regions. 2) In the scatter density diagram of F1-F2, the obvious cluster feature was presented, by which different types of land consolidation regions could be classified effectively and objectively, and the types had clear connotations for F1 and F2 were well correlated with grain yield. 3) By cluster and analysis, the 315 administrative villages in Xinzheng City were divided into 6 types of land consolidation regions: the comprehensive factors limiting region, the available phosphorus-irrigation rate limiting region, and the available potassium and organic matter-irrigation rate limiting region with low grain yields; the potassium and organic matter-irrigation rate limiting region with medium grain yields; irrigation rate limiting region, and the unlimited region with a medium-high grain yield. The grain yield and factors features of the different types differed from each other. The conclusion can be given that the classification method put forward in this paper is suitable for farmland consolidation partition of large sample with multidimensional variable space, and the classification can be used in farmland consolidation in Xinzheng City.