Abstract: This study focused on a Cunninghamia lanceolata (Chinese Fir) plantation within a state-owned forest farm in Shunchang County, Fujian Province. Utilizing multispectral and point cloud data acquired by a DJI Matrice 300 RTK UAV equipped with LiDAR and multispectral sensors, alongside ground-truth survey data, we extracted the Canopy Height Model (CHM) and treetop positions. An object-based approach integrating the Thiessen polygon method was employed to achieve individual tree crown delineation in stands with high canopy closure. The results indicated that by constructing the CHM from LiDAR point cloud data and applying a Local Maximum algorithm to the combined datasets, a treetop detection accuracy of 95.6% was achieved. The object-based Thiessen polygon segmentation method effectively delineated the crowns of Chinese Fir with an accuracy of 86%. The fusion of LiDAR-derived vertical structure information and multispectral texture features, coupled with Thiessen polygon segmentation, significantly enhanced the accuracy of crown delineation in high-density stands. This methodology provides a reliable technical pathway for dynamic biomass monitoring and carbon sink quantification in Chinese Fir plantations.