Study On Soil Moisture Inversion Of Bare Random Surface Based On IEM Model

In the earth system, the surface soil moisture is the important factors in the process of terrestrial and atmospheric energy exchange; it also has a strong control effect on land surface evapotranspiration, moisture migration, the carbon cycle. As an important component of the terrestrial ecosystems water cycle, soil moisture is the basic condition for plant growth and development, but also an important objective of the studies in plant water stress, drought monitoring, crop yield estimation, etc. Therefore, the large-scale monitoring of soil moisture in hydrological, meteorological and agricultural sciences have greater significance, the soil moisture monitoring has been of great concern. A wide range of real-time soil moisture monitoring is recognized worldwide problem. The traditional measurement methods, optical remote sensing and passive microwave remote sensing in large-scale dynamics monitoring of soil moisture have certain limitations. Studies have shown that active microwave can make up for the lack of soil moisture monitoring in other ways and provide new ways and means for large-scale real-time monitoring of soil moisture.Studies have shown that the surface backscattering coefficient gotten from the spaceborne synthetic aperture radar has a direct correlativity with the dielectric constant, so we can extract the surface soil moisture information effectively within the required accuracy of the hydrological model. SAR system is currently being multi-polar, multi-angle. Multi-polarization, multi-angle SAR data have great potential in the dynamics monitoring of soil moisture. In this study, we make use of IEM model for simulation and analysis of microwave scattering properties of the surface and propose the empirical model to invert soil surface moisture by using multi-polarization SAR data.In this study, at first we use the IEM model to simulate the response relationship between the backscattering coefficient and radar system parameters,surface parameters at different frequencies and different polarization modes to reveal the discipline of radar backscattering coefficients variation with change in these parameters, taking the discipline as foundation to selected the ideal optimal radar system parameters of soil moisture inversion. Base on analysis of the relationship between radar backscattering coefficient and soil moisture, surface roughness parameters (RMS height, correlation length, combined roughness) we use least squares method and non-linear regression method to establish the empirical model to invert the soil moisture of smooth surface by using radar backscatter coefficient.Finally, we use the data obtained by RADAR-SAT2 to make an application and validation of the established empirical model in Weigan - Kuqa River delta oasis. The results showed that in this study there is a good correlation between the value of established empirical inversion model and measured values of soil moisture, the coefficient of determination reached 0.886, indicating that the application of empirical inversion models of soil moisture established in this study have a better result in the bare soil and sparse vegetation coverage area.