Research On The Remote Sensing Information Models Of Soil Moisture Based On MODIS Data In Beijing

The drought is one of the most principal factors that restrict agricultural production in CHINA. It's very favorable to detect Real-time soil moisture thus monitor the drought of farmland by using remote sensing. NOAA has been used to monitor soil moisture for a long time all over the world. With the blastoff of TERRA-MODIS, it has been very urgent for us to use the MODIS data to detect soil moisture.Based on the analysis of research progress of soil moisture remote sensing information models, this paper deals with the methods of monitoring soil moisture with Beijing plain as research base and energy balance as theoretical basis. The empirical models were established using two principal factors, VI and land surface temperature, which derived from MODIS data, and the data of soil moisture obtained from experiments.Because of different levels of vegetation in different growth period, we separated the models into 2 aspects. One approach was the model developed by using soil inertia for bare land and the region of low vegetation cover, the other was using land surface temperature and VI, which was developed for high vegetation coverage. The result indicated: In Beijing area, exponential empirical models developed by using soil inertia was suitable for bare land; the relationship between the linear combination of NDVI and brightness temperature of 31 band (T31) was significantly high in the region of high vegetation cover, and so did T31/NDVI, the performance of EVI and SAVI was not satisfactory; BP neural network could also be used to retrieve soil moisture from remote sensing.