Taking Taizishan Forest Farm in Hubei Province as the study area and using GF-2 and SPOT-6 satellite images as the data source, texture features under different window sizes and spectral features were extracted. Using random forest algorithm and Taizishan forest data obtained by field investigation, we construct forest biomass inversion model. The results show that (1) although the spatial resolution of GF-2 and SPOT-6 are different, the correlation coefficients (0.75, 0.78, 0.73, 0.61) of the reflectance of different wavebands indicate that the waveband reflectance of the two images is relatively high. The high correlation indicates that the radiation performance of the two is similar. (2) By analyzing the influence of different texture features on the biomass model, it is found that the mean and contrast values have a good effect on biomass inversion. (3) High resolution remote sensing data has a good performance in biomass retrieval, and the accuracy of the GF-2 biomass model (R²=0.88, RMSE=27.11 Mg/hm²) and the SPOT-6 biomass model (R²=0.89, RMSE=23.93 Mg/hm²) is similar. (4) The two images have no significant differences in the biomass prediction values of different forest types, and both are suitable for predicting the biomass of different forest types.