Gnss-R Soil Moisture Retrieval Within Consideration Of Vegetation Water Content Correction

Soil moisture is an important variable that characterizes soil characteristics,and is of great significance for studying the water cycle of ecosystems,crop growth,and weather prediction.The traditional soil moisture detection method has poor continuity and a long detection period,which cannot achieve large-scale soil moisture detection.The L-band electromagnetic wave signal transmitted by the GNSS satellite has the advantages of all-weather,strong penetration and cheap availability,and the reflected signal Humidity changes are very sensitive,so microwave remote sensing technology based on GNSS reflected signals has become one of the monitoring methods for inversion of land-based parameters such as surface vegetation and soil moisture.However,most of the current researches on soil moisture inversion using GNSS signals are based on the bare soil surface,without considering the influence of surface vegetation on soil moisture.Aiming at the problem of soil moisture monitoring under vegetation cover,this paper studies a GNSS-R soil moisture inversion model method that takes into account the correction of vegetation moisture content.The accuracy and effectiveness of the model are verified through experiments.The main research contents are as follows:(1)Summarize the basic principles and methods of GNSS-R inversion of soil moisture,including the electromagnetic wave reflection characteristics of the reflected signal,polarization mode,effective and maximum detection area,etc.,and analyze the physical characteristics of multi-path effects and signal-to-noise ratio observations A method for inversion of land surface parameters such as soil moisture and vegetation water content using characteristic parameters such as the phase and amplitude of the SNR value of the GNSS reflected signal is constructed.(2)The use of SNR observations to monitor changes in surface vegetation growth and water content was studied,and the relationship between vegetation water content and amplitude of GNSS signal-to-noise ratio observations was analyzed.The experimental results show that for desert grass and wheat low vegetation,and the vegetation moisture content is less than 1Kg?m~2,the amplitude A of the observed value of SNR and the vegetation moisture content VWC show a clear linear relationship;for alfalfa and other crops with higher vegetation moisture content,There is no linear relationship between the two.Therefore,the growth status of vegetation in the detection area can be approximated by the magnitude of the amplitude value.(3)For the surface environment covered by vegetation,a refined model of soil moisture that takes into account the correction of vegetation moisture content is studied.For the original SNR observations,combined with the vegetation type and vegetation water content,a soil moisture model that takes into account the correction of the VWC attenuation factor is proposed.The experimental results show that the calculated soil moisture value after adding VWC correction information is closer to the measured value,the correlation coefficient R is higher,and the linear relationship is more obvious;the root mean square error RMSE and the mean absolute error MAE are both better than those without VWC The bare soil model of the information is smaller.Therefore,it is very necessary to carry out research on soil moisture inversion under the condition of vegetation cover,and add vegetation disturbance factor correction.Using appropriate and reasonable models to remove vegetation influencing components can effectively improve the accuracy of soil moisture inversion.