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The spatial prediction model of forest soil organic matter was studied based on environmental factors and mixed interpolation methods. Firstly, digital terrain and remote sensing image analysis technologies were applied to get topographic factors and index of remote sensing. Then, the correlation of soil organic matter and environmental factors was analyzed. In the end, soil organic matter was predicted spatially according to the environmental factors. Aiming at the flaw of regression Kriging (RK) which needs to compute semi-variogram, a spatial interpolation method named regression-smoothing thin plate spline (R-STPS) was presented. This two interpolation methods were applied to predict soil organic matter of Shunchang county spatially. The results showed that the prediction accuracy and computation efficiency of RK and R-STPS were almost consistent. The overall trend of spatial prediction distribution of soil organic matter of study area was similar. However, R-STPS was not needed for calculation of semi-variogram and easy to use. Therefore, R-STPS has more advantages.