本研究采用的树高信息来源于无人机高分辨率影像，数据容易获取，且随机性和

Tree height information used in this study comes from the drone of high resolution images, easy data acquisition, and the randomness and strong applicability, can accurately reflect the fir and poplar plantation in each age stage growth conditions, and the relationship between the dominant tree height growth and stand productivity [35-36]. Preliminary evaluation of the feasibility of this study divided opposition to the drone by the quality of images and point clouds single tree, future research may expand the area of ​​data collection, and increase the sample size, the preparation of site index table for the use of unmanned aerial vehicles and single-image wood extraction evaluate site conditions, to achieve precise foster forest research more deep-seated.

The tree height information used in this study is derived from the high-resolution image of the drone, the data is easy to obtain, and the randomness and applicability is strong, can accurately reflect the growth status of the sequoia and poplar artificial forest in each age scale, as well as the relationship between the high growth of the superior wood tree and the forest productivity. This study first explores the feasibility of quality evaluation of the opposite area through the image point cloud and the single wood division of the drone, and in the future the research can expand the area of data collection, increase the sample size, compile the status index table, evaluate the land conditions by using the drone image and single wood extraction technology, and carry out a deeper research on the precise cultivation of forest.

The tree height information used in this study comes from UAV high-resolution image, the data is easy to obtain, and has strong randomness and applicability. It can accurately reflect the growth status of Metasequoia and poplar plantation in each age stage, as well as the relationship between the growth of dominant tree height and stand productivity [35-36]. In this study, the feasibility of site quality evaluation by UAV image point cloud and single tree segmentation is explored. In the future, the research can expand the data collection area, increase the sample size, prepare the status index table, and carry out a deeper research on using UAV image and single tree extraction technology to evaluate site conditions and achieve accurate forest cultivation.<br>