无人机高分辨率影像的森林株数密度制图

本文以大兴安岭无人机遥感数据为基础进行森林密度制图，并提出了一种局部阈值算法，通过与传统的Otsu方法去除背景噪声相比，得出了该方法在中等或较低森林株数密度地区能很好地去除噪声背景。结合局部最大值法取得很好的单木提取精度，其查全率达到了100%。传统的Otsu去除背景方法在较高森林株数密度地区具有较好的识别效果，但对非林分的空地信息存在错提取的现象。通过对以上两种方法的对比研究，得到大兴安岭森林株数密度制图结果，该研究可为稀疏森林区域的株数密度制图提供参考。

Forest density mapping based on UAV high-resolution image

Based on the UAV remote sensing data of Daxing'anling Mountains, this paper proposes a local threshold algorithm for forest density mapping. Compared with the traditional Otsu method to remove the background noise, it is concluded that this method can remove the noise background well in the areas with medium or low forest density. Combined with the local maximum method, it has good single tree extraction accuracy, and its recall rate reaches 100%. The traditional Otsu background removal method has a good recognition effect in high forest density area, but its disadvantage is the wrong information extraction of non-forest open space. Through the comparative study of the above two methods, the mapping results of forest plant density in Daxing'an Mountains are obtained, which can provide a reference for the mapping of forest plant density in sparse forest areas.