Remote Sensing Retrieval Of Fengyun-3 Soil Moisture

Soil Soil moisture affects the process of water exchange between landing surface and atmosphere,which is an important part of ecosystem.How to obtain soil moisture accurately has great significance to the study of soil moisture distribution,water cycle and water resources management.Soil moisture has become a key research parameter in agriculture,forestry,watershed hydrology,atmospheric science and other disciplines.It can be used in weather prediction,drought and flood monitoring and water resources management.The traditional method of obtaining soil moisture has a small observation area and can not obtain a large range of soil moisture.The measured data can only represent the current soil moisture in a certain area,and it is not representative in space.If a large range of soil moisture monitoring stations are established,it will not only consume resources,but also be difficult to build stations in areas with poor environment.Using remote sensing to obtain soil moisture has obvious advantages,which can obtain soil moisture for a long time and a large range.In this paper,passive microwave remote sensing is used to retrieve soil moisture.satellite borne sensor brightness temperature data and optical remote sensing data are used to improve the accuracy of soil moisture inversion.Firstly,we use the vegetation index data of optical remote sensing to study the climate averaging,and develop an average data set based on MODIS vegetation index.The spatial resolution of this data set is the same as that of the original data,and its temporal resolution is higher than that of the original data.The data set can well reflect the growth status of vegetable in each pixel and any period of the year.The water content of vegetation can be calculated by the data set,which is the basis of correcting vegetation impact in the process of soil moisture inversion.Secondly,the brightness temperature data of Fengyun No.3 scanning imaging microwave radiometer were used to retrieve the soil moisture in the study area,and the vegetation parameters were optimized using the measured data of the site.The results showed that the retrieved soil moisture was in good agreement with the measured values in time series,and the root mean square error was 0.04m3/m3,which met the corresponding accuracy requirements.Finally,the monthly average soil moisture products of Thailand from 2017 to 2018 are inverted.The results show that the seasonal variation of soil moisture is consistent with the local climate characteristics of Thailand.