Multi Model Integrated Simulation Of Microwave Surface Emissivity

Microwave surface emissivity is defined as the ratio of thermal radiation emitted by the surface under the same temperature to the energy of the black body radiation,one of the important parameters indicating land surface characteristics,one of the key parameters of the climate model and ecological mode,whose accuracy directly influences the star load or airborne microwave radiometer data utilization rate,the simulation accuracy of which has important significance in monitoring environment,improving weather forecast accuracy and ameliorating hydrological and ecological environment prediction model.Microwave surface emissivity is simulated through theoretical or experimental model.Although many researchers at home and abroad have done a lot of research on the calculation model of ground surface emissivity and many models have been developed to calculate ground surface emissivity with different characteristics,microwave surface emissivity simulation is still to be a problem.In recent years,some researchers in the field of remote sensing have applied the combination forecasting method to establish different ground emissivity simulation algorithm.Combination forecasting research method has significantly improved the most of the land surface of satellite microwave data use efficiency.However,the method's main characteristic is to choose different models according to different kinds of surface,which exists the following problems.Firstly,the method is a combination of a single emission rate model with different terrain features,which leads to that it does not give full play to the advantages of different prediction methods of the table features.Secondly,the structure's uncertainty factors of the model are not considered.The aim of this paper is to study the uncertainty of the ground surface emissivity model,especially the uncertainty of the model structure.The simulation accuracy and prediction technique by improving the surface emissivity of microwave is also studied in this paper.In this paper,the Bayesian model averaging method,which is widely used in the field of hydrology in recent years,is used to deal with the error introduced by the uncertainty.Based on the experimental analysis,the system error is further eliminated in the research,the improved algorithm is applied to the simulation of surface emissivity,the comparison and analysis of the global effective bare soil pixel is carried out taking the pixel of bare soil as an example.The results show that the simulation and prediction accuracy of surface emissivity are improved by the research.