The height of plant communities is an important parameter, which can be used to estimate biomass and is a functional trait of plant communities. Tree height and plant community height are commonly estimated by forest surveyors or measured through the use of a laser altimeter in traditional forest surveys. However, this traditional survey method is hard to apply to measure tree and plant community height in large areas. Recently, with the rapid development of unmanned aerial vehicle(UAV) technology, the development of low-altitude unmanned aerial photogrammetry and remote sensing technology has been stimulated. Previous studies have shown that UAV images can used to measure crops and orchard height, and to estimate biomass. However, obtaining the height of vegetation in rough mountain areas remains a big challenge. Chenggong campus of Yunnan University was chosen as an experimental area because of the small hill area. We also selected a plot in which 4203 m² was dominated by pine trees(Cedrus deodara[Roxb.] G. Don). Aerial images of the experimental area were acquired using the UAV equipped with a common digital camera platform(Sony ILCE-7R). We aligned these images to obtain point cloud data and to produce dense point cloud data. Then we built a digital surface model(DSM) using these point data. We extracted non-plant points according to the classification of cloud point. Some sections were removed because of edge fogs between the plant and non-plant parts, and a new height model(digital terrain model; DTM) was built by interpolation. For the height variation model of the cedar canopy in the study area(canopy height model; CHM), the height was obtained by overlaying the DSM and DTM. DTM was subtracted from DSM in order to obtain the height variation mode of the cedar canopy in the study area. The height variation model was the height of cedar individuals. Afterward, an accuracy assessment has been carried out using linear regression analysis. The heights of 100 cedar individuals, measured by a laser rangefinder were used as validation data. There are very greatly correlations(r² > 0.904) between the tree heights measured by laser range finder and quantified by CHM derived by overlaying DSM and DTM. Both the space model, which was based on the UAV images, and tree height which was subtracted from the space model were less affected by external environment factors. Additionally, this method is easy to be performed and can be widely used to investigate various plant communities and has prospects for use in ecological application.