.Soil properties are very absent and sorely needed for many models. Conventional measurements are expensive and many samples are required. Hence it is difficult to quantitatively analysis them at a large-scale region. Hyperspectral methods are now used for the rapid characterization of a wide range of soil. In this paper, it was used to estimate organic matter content in soil of Heihe River basin. A total of 84 samples were collected and their reflected spectral were measured with ASD spectrometers. Then the organic matter were predicted using four forms of spectra and PLS method. The results show:1) the hyperspectral remote sensing can be used to predict soil organic matter content, and the precision can meet the requirement; 2) the best region of spectrum is 400~800nm in R, 1/R and Log (1/R) formation, and the FDR and FD(Log (1/R)) centered in 800nm based on the correlation coefficient and Variable Importance in Projection.