Abstract: Pinus densata, the endemic tree species in high altitude area of Southwest China, was chosen as the test cultivar, and the spectral reflectance of foliage was measured by ASD Field Spec 3 Spectrometer. The spectral characteristic parameters highly significantly correlated with the foliar spectral reflectance and foliar nitrogen content were selected by Pearson Correlation Analysis, combined with the results of laboratory analysis of foliar nitrogen content. Parametric and nonparametric models for estimation of foliar nitrogen content of P.densata were established by employing regression analysis and KNN, the precision of the models were tested and compared by the independent sample. The results indicated that the best parametric model was the quadratic model using S_Dr/S_Db as a variable, in which the values of R², RMSE and RE were 0.627, 0.12 g/100 g and 4.75% respectively, and that the non-parametric model constructed by KNN had better effect, and the values of its R², RMSE and RE were 0.856, 0.12 g/100 g and 5.43% respectively. These results suggested that the nonparametric model established by KNN showed better predictive ability than the traditional parametric models for nitrogen content estimation of P.densata.