Yellow River Ice Decision Tree Classification Method Based on Polarimetric Sar Data

Abstract

According to the characteristic of different air bubbles and sediments content in the Yellow River ice (YRI), the YRI is classified into three types: thermal ice (TI), frazil ice (FI) and consolidated ice (CI). In this paper, we are modeling YRI firstly, and the backscattering coefficient of the ice cover based on this model is deduced on the basis of the integral equation model (IEM) and the vector radiation transfer theory (VRT). Due to the characteristics of different types of YRI corresponding to different microwave electromagnetic scattering, a method of classification of YRI based on decision tree is proposed. The method uses horizontal polarization backscattering coefficient, correlation coefficient and cross polarization power to classify different types of YRI. Finally, the classification accuracy is evaluated by using the confusion matrix (CM). The results show that the classifier is effective for the YRI classification.