Use of finite mixture model to analyze the variability of heavy metal pollution characteristics in peitou guandu area

Statistical method is a tool with which we can use to explain and employ the sample data. In recent years, the development of GIS has made the improvement of combination of statistical methods and spatial relationship. Finite Mixture Model (FMM) has the ability to classify objectively the data by unsupervised learning. Then cooperating with spatial analysis, we can get implicit causes and characteristics of data to increase efficiently the data value. In this paper, Finite Mixture Model was used to classify heavy metal pollution source characteristics in the Peitou Guandu Area.