| Soil moisture content is a vital parameter in the study field of hydrology, meteorology and agriculture science. It is indispensable factor for indicating soil drought and development of plants, conducting the management of water resource, studying the processes of land surface. It is difficult to indicate spatial variability of soil moisture content at large area by conventional methods. But it is possible to monitor soil moisture content in timing and dynamic at large area as the development of remote sensing technology. At present, most methods to monitor soil moisture content by thermal infrared remote sensing are based on the relationship of land surface temperature and soil moisture content. The search to the relationship between emissivity and soil moisture content is considered less.This paper takes paddy soil in Kunshan as study object. Through imitating nature soil samples, the spectrum of emissivity and soil moisture are measured in order to expound the characteristic of emissivity in the thermal infrared part of the spectrum with different soil moisture content. A model of estimating the moisture content in soil is attempted to make based on Moisture Diagnostic Index (MDI). The bands in the thermal infrared part of ASTER satellite are imitated by the data of emissivity which we measured. Through analyzing the characteristic of spectrum which is imitated, we also try to construct a model to estimate soil moisture content using the stimulant bands in the thermal infrared part of ASTER satellite. The dissertation concentrates on the following aspects:1. In general, the spectral characteristic of soil emissivity in laboratory includes the following aspects. First, in the region of 8～9.5μm, along with the increase of soil moisture content, the emissivity of soil has varying degree increases. The spectral curves are parallel relatively and have a tendency to become horizontal and the absorbed characteristic of reststrahlen is also weakened relatively with the increase of soil moisture in this region. Secondly, in the region of 9.5～11μm, the emissivity of soil has a tendency of increasing, but there is no obvious relationship with the increase of soil moisture. And thirdly, in the region of 11～14μm, along with the increase of soil moisture content, the emissivity of soil has varying degree decreases. There is an absorption vale near about 12.7μm. As along with the soil moisture content increases, the depth of absorption also increases. This phenomenon may be coursed by soil moisture absorption.2. Methods as derivative, difference and standardized ratio transformation may weaken the background noise effectively to the spectrum data. Especially using the ratio of the emissivity to the average of 8～14μm may obviously enhance the correlation between soil moisture and soil emissivity. According to the result of the correlation analysis, the 8.237μm is regarded as the best detecting band for soil moisture content. Moreover, based on the Moisture Diagnostic Index (MDI) in the 8.194～ 8.279μm the logarithmic model of estimating soil moisture is made.3. Bands in the thermal infrared part of ASTER satellite are imitated. The simulation results show that B10, B11 and B12 have the characteristic of vale-peak-vale. B10 and B12 correspond to one of absorption reststrahlen vales respectively. And it is obvious.4. According to the result of the correlation analysis between each band and soil moisture, the results suggest that B10, B11 and B12 have positive correlation with soil moisture content, while B14 has negative correlation with soil moisture content. As far as each band is concerned, B10 is most sensitive to soil moisture content. Moisture Diagnostic Index B10 / B14 weaken the background noise effectively to the spectrum data, is more sensitive than B40. At last, the logarithmic model of estimating soil moisture is made based on Moisture Diagnostic Index B10 / B14.
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