Based on the simulated data produced by PROSAIL model and field test data, the authors respectively analyzed many kinds of factors which affect some representative inversion methods, such as VI, second derivative, model inversion and the directional second derivative The factors taken into account include background, directional variation of canopy reflectance and random errors and so on The results demonstrate that under various conditions, there are huge differences araong the inversion results resulted from these methods Vegetation index NDVI has the lowest accuracy, could not avoid those influences The accuracy of model inversion is better than that of VI method, but is still influenced by the variety of backgrounds The second derivative can partly remove the influence of backgrounds, but it is also limited by the anisotropy of canopy reflectance By comparison, the directional second derivative can improve inversion accuracy through removing the influences from the soil background and directional variation of canopy reflectance simultaneously As second derivative is sensitive to noise, the elimination of noise is crucial to the inversion result