Development of algorithms to automatically identify and spatialize all the trees in complex one-hectare 3D point cloud stands.


  • Philippe Nolet Université du Québec


The development of the mobile LiDAR technology for mapping forest ecosystems is rapidly advancing and has great potential in many ways. However, to date, the use of this technology remains marginal both in conducting inventories and in research in forest ecology. This is probably due to the difficulty of translating LiDAR point clouds into usable information. While the identification and spatialization of trees is certainly one of the most important pieces of information to provide, the algorithms for this identification remain poorly performing, especially in complex structured stands. In this study, we developed a series of algorithms adapted to complex data clouds. We then used these algorithms in 10 stands (1 ha) showing a dense shrub layer. Our results show that nearly 95% of trees over 10 cm DBH are automatically identified by our algorithms; a fast visual inspection subsequently allows us to identify missed trees. Our algorithms also allow us to identify trees less than 10 cm in DBH, but some of these may have been missed by the LiDAR due to the obstruction created by the foliage. These algorithms, along with the extremely accurate algorithm developed for estimating DBH (Nolet et al, under revision), represent an important step in deploying the mobile LiDAR technology on a larger scale. 

Author Biography

Philippe Nolet, Université du Québec

Philippe Nolet has been a researcher at ISFORT (Institute of Temperate Forest Sciences) and a professor at UQO (Université du Québec en Outaouais) since 2015. As a forest ecologist, Dr. Nolet has been interested in a wide range of subjects related to the silviculture of tolerant hardwood stands, including the regeneration of shade mid-tolerant species and the adaptation of silvicultural treatments in the context of global change. One of his favorite topics, however, remains the dynamics of American beech invasion in sugar maple stands. In recent years, he has been particularly focused on developing a high-resolution inventory approach based on terrestrial mobile LiDAR. His goal is to develop this approach so that it can be used by forest managers and other researchers to conduct more precise forest inventories and study spatial phenomena that could not be studied otherwise.