The purpose of this paper is to evaluate the potential of GF-5 satellite hyperspectral image for estimating soil organic matter(SOM)content in cultivated land，and the effect of different soil types on the estimation accuracy.Taking Jiansanjiang reclamation area of Heilongjiang province as the research object，we obtained GF-5 hyperspectral image covering the study area and collected 188 soil samples.The reflectance data were preprocessed by 9 kinds of mathematical transformation，and the spectral sensitive band of SOM content was determined by correlation coefficient method.Partial least squares regression(PLSR)model was established for SOM content estimation of all soil types，meadow soil，swamp soil and black soil，respectively，and the accuracy of models were evaluated.The results showed that the estimation accuracy of SOM content of all types of soil in the study area did not perform well. The determination coefficient(R2)of the best validation accuracy was 0.265，the root mean square error(RMSE)was 4.647%，and residual predictive deviation(RPD)was 1.135.The estimation accuracy of SOM content of different soil types was quite different.The estimation accuracy of meadow soil and swamp soil was not high，but that of black soil performed well，especially the accuracy of SOM content estimation based on log first-order derivative(LnR)′ was the highest，R2 was 0.729，RMSE was 1.065% and RPD was 1.850.SOM content estimation model based on different soil types can further inrestigate the potential of GF-5hyperspectral remote sensing to estimate SOM content.