Study On Inversion Method Of Sandy Land Soil Moisture Based On Polarimetric SAR

Inner Mongolia grassland is an important ecological barrier of north China,and the ecological environment is extremely fragile.However,grassland desertification is more and more serious with human activities and climate changes.It not only has a serious impact on China's ecosystem,but also has influence on the economic development of China,so it is necessary to monitor the Inner Mongolia grassland desertification.Soil moisture plays an important role in hydrological,ecological and biological processes of grassland,therefore it is one of the most important factors for monitoring of grassland desertification.And sandy land in Inner Mongolia grassland is a typical example to observe grassland desertification.The SAR microwave remote sensing technology offers the opportunity to estimate the soil moisture of sandy land in a large scale,and it will have a positive influence on the monitoring of Inner Mongolia grassland desertification in China.The main work and research results of this dissertation are as follows:(1)In order to solve the problem of fuzzy classification of the method based on H-? and Wishart classifier,a polarimetric SAR image classification method based on decision tree and Wishart classifier is proposed.The polarimetric SAR data of the Hunshandake sandy land are classified by using this method.From the experimental results,this method improves the classification accuracy of the sandy land feature.(2)Based on the analysis of the Dubois model and the simulation of the backscattering characteristics of the natural surface with AIEM,a linear model for inversion of soil water content was proposed.The model does not need to consider the surface roughness,and only the VV and HH polarized backscattering coefficients can be used to invert the soil moisture of sandy land.The model solves the problem that the Dubois model overestimates sandy land soil moisture.Using this model to deal with polarimetric SAR data from Hunshandake sandy land,the experimental results demonstrate the effectiveness of the model.Finally,combining the classification method based on decision tree and Wishart classifier and the linear model of sandy land soil moisture inversion,this dissertation developed a soil moisture inversion algorithm.