The Tasseled Cap Transformation （TCT） is a widely used remote sensing image processing technique. For Landsat 8 satellite imagery， three TCT algorithms have been proposed by Baig et al.， Zhai et al.， and Liu et al.， respectively. However， the consistency among these three algorithms remains unclear， leaving users uncertain about which one to choose. Additionally， while Zhai et al. provided an algorithm based on Surface Reflectance （SR） data， the other two algorithms are only applicable to Top of Atmosphere （TOA） reflectance data. It is thus essential to verify whether the TOA-based algorithms can be applied to SR data. To address these issues， three Landsat 8 images with different land cover types were selected， and three TCT algorithms were applied. The inversion results were quantitatively compared to identify differences among the algorithms. The results show that the Baig and Zhai algorithms exhibit the highest consistency， with an average R² of 0.974 4 and an average RMSE of 0.025 for the three components. In contrast， the inversion results of the Liu algorithm exhibit significant differences compared to those of the Baig and Zhai algorithms. The average R² values between Liu and Baig， and between Liu and Zhai， are 0.803 1 and 0.865 2， respectively， while the average RMSE values are 0.077 6 and 0.065 5， respectively. Therefore， the inversion results of Baig and Zhai are more comparable. Furthermore， applying the TOA-based TCT algorithms of Baig and Liu to SR data reveals substantial differences between the components derived from SR and TOA reflectance， with RMSE reaching 0.053 5 and an average |PC| of 146.07%. Thus， it is not recommended to use the TOA-based algorithms of Baig and Liu for TCT on SR data. In conclusion， the algorithm proposed by Zhai et al.， which is applicable to both TOA and SR reflectance data， is recommended for Landsat 8 TCT applications.