Abstract: Fast and accurate quantification of biophysical parameters of trees is essential for forest management, assessment of carbon sequestration and evaluation of regional ecosystem services value. Unmanned aerial vehicle (UAV) is a promising tool to estimate biomass of individual trees due to its extremely high resolution. In this study, we used self-developed UAV to obtain shadow-free remote sensing images, taking Abies faxoniana in Wanglang Nature Reserve of Sichuan Province as an example. There were two plots, one for model training and the other for model validation. Crown area (CA) of individual trees was delineated through man-computer interpretation. Meanwhile, the field inventory was conducted to record the diameter at breast height (DBH) of individual trees, and to establish CA-DBH regression model. Based on the validity of CA-DBH model, the stem biomass (SB) of individual A. faxoniana trees in plot 2 was derived according to the existing empirical DBH-SB equation. There was a strong nonlinear correlation between CA extracted from the UAV remote sensing images and DBH documented in the field visit, with a coefficient of determination R2 = 0.752 (P<0.001, n = 94). Then prediction of DBH using the model in plot 2 was conducted, followed by a T-test. Verification results showed that the difference was not significant between the predicted DBH and observed DBH in the field (P>0.05), with a Pearson correlation coefficient of 0.879. This study indicates that it is practically feasible to estimate SB of individual trees through the CA extracted from UAV remote sensing images.