Abstract: In order to solve the problems such as single feature, low calculation efficiency, and poor effect of vegetation coverage of the current airborne light detection and ranging(LiDAR) point cloud filtering algorithm, an adaptive double filtering method for point cloud in densely-vegetated areas was proposed. Firstly, the single and last echo of point cloud were extracted respectively and processed by coarse filtering by using the echo separation method. Then, the skewness balance theory was used to determine the intensity threshold of the single echo, and the maximum inter-class variance method was used to calculate the height difference between the first echo and the last echo, so as to realize the automation of the height difference threshold of the last echo. And the point cloud data of the single echo and the last echo after rough filtering were integrated. Finally, the incremental encryption filtering algorithm of triangulated irregular network was used to carry out the fine filtering processing on the fused point cloud data, and the experimental verification had been done. The results show that the type Ⅱ errors of the three data sets are relatively low of 1.06%, 1.64%, and 1.34% respectively. The dual filtering method that combines echo information and height difference information can not only eliminate vegetation, but also retain terrain details.