Soil moisture is a very important variable in hydrologic cycle and exchange of matter and energy near ground boundary. It was investigated by the means of remote sensing due to a number of reasons. In this study

under experimental conditions

relationship between hyperspectral data and soil surface moisture has been investigated. Correlation between soil surface moisture for nine soil samples and four sets of spectral data of them （prototype reflectance

absorbance

the first-order derivative of reflectance and the first-order derivative of absorbance） was analyzed. We found that it has no obvious correlation between soil surface moisture and prototype reflectance and absorbance for all samples

while absorbance has higher correlation than reflectance. The first-order derivative of reflectance and the first-order derivative of absorbance have the obvious correlation near wavebands 1844 nm

and the first-order derivative of absorbance reflectance has more obvious correlation than the first-order derivative of reflectance. We choose these bands with high square of correlation coefficient to creat liner regression forecasting equation. Another nine soil samples were used to verify the precision of estimation equation. Results show that the first-order derivative of absorbance has the capability to estimate soil surface moisture of the four sets of data. It shows the great potential to estimate soil surface moisture within a large area for different soil types.