Study On Soil Moisture Monitoring Method In Grassland Area With Multi-Source Data

Soil moisture,as an important component of surface water storage,directly affects the exchange of matter and energy between the land and the atmosphere,and has become one of the research hotspots in hydrology,meteorology,agriculture and ecological environment.The amount of moisture in the soil is expressed as the soil moisture content(exact quantitative data measured by the instrument).Quantitatively obtaining soil moisture content in this dissertation is an important part of the study.Therefore,soil moisture content is used instead of soil moisture.PolSAR(Polarimetric Synthetic Aperture Radar)has become one of the most effective methods for soil moisture monitoring with high spatial resolution due to the polarization characteristics of its data and the sensitivity of backscatter intensity to soil moisture content.The spatial resolution of optical remote sensing is high and there are many available satellite sensors,and optical data(normalized vegetation index NDVI,leaf area index LAI,etc.)can be provided for quantitative estimation of vegetation water content.The effective use of optical and microwave data in conjunction with each other can accurately invert soil moisture and maximize the use of these remote sensing satellites.The main research results of this dissertation include the following aspects:(1)This dissertation proposes a multi-source remote sensing data fusion classification.In environments where multiple scattering mechanisms coexist and are densely intercrossed,compared to single-polarization SAR data classification,Using the multi-source remote sensing data fusion classification method proposed in this dissertation to improve the classification accuracy of the land area in the study area,better classification support for soil moisture monitoring is provided.(2)Analysis of water content inversion model Shi model and Dubois model.The effects of water content inversion in vegetation cover areas were compared.The Shi model was found to be inapplicable in this type of vegetation coverage and the inversion accuracy was low.At the same time,the study also showed that compared with the Shi model,the Dubois model's water content inversion effect in the vegetation cover area is also relatively good.However,in the process of inversion of water content,there is a problem of high values,and a large part of this is due to the influence of vegetation on the scattering and absorption of electromagnetic waves in the study area.Therefore,a method for eliminating the effects of vegetation needs to be found.Through practical data and analysis experiments,the applicability of the water cloud model to the warm desertification steppe with relatively low vegetation coverage was verified.Eliminates the influence of vegetation scattering and absorption on the radar backscatter coefficient,which reduces the error of the Dubois model.This dissertation proposes a new method for large-scale inversion of water content in warm desertification steppe areas.