【Objective】 Actual measurements of the relationship between the distribution direction of branch heights and the intensity of spatial competition have highlighted the downside to three-dimensional (3D) forest models construction based on traditional forestry research survey data. Such models are unable to directly express differences in branch height distribution in varying directions. This results in the insufficient performance of the forest tree 3D model polymorphism. 【Method】 This study used eight temporary sample plots of Chinese fir in the Shanxia Forest Farm of Fenyi County, Xinyu City, Jiangxi Province, China to supply data. The existing undershoot height model was used alongside establishing the buffer zone of the geological analysis method combined with the forest stand spatial structure unit. The horizontal and vertical spatial structure parameters that directly affect the forest trees were established, and the high correlation between the spatial structure parameters and the undershoot was analyzed. This analysis provided the basis for the calculation of the spatial competition intensity in each direction, and the established relationship between spatial competition intensity and the measured undershoot height distribution. The under-branch height model was used to calculate the remaining-direction under-branch height. Finally, the branch and trunk model was loaded according to the measured data and analysis and calculation structure to construct a 3D forest model. 【Result】 The selected basic model variables included forest attributes and spatial structure parameters; the original model coefficient of determination was 0.720, the horizontal spatial structure and the adjusted branch height correlation coefficient was 0.410 to eliminate the influence of tree height. The vertical spatial structure correlation coefficient was 0.782, and positively correlated with the branch height. The respective correlation coefficients were weights to calculate spatial competition intensity in the corresponding direction. The minimum competition intensity direction spatial structure parameter was used to achieve the basic model fitting coefficient of determination of 0.790; this was an improvement compared with the original model. The measured branch height was allocated to competition intensity in the smallest direction and to quantify the lower height of branches in remaining directions. 【Conclusion】 Chinese fir was used as an example of utilizing spatial competition intensity to discriminate the high distribution under branches to improve the utilization of existing data and reducing field work intensity. This approach intuitively expresses differences in the high distribution under the branches of the forest and enhances the polymorphism of the 3D forest model expression.