 The Tree Extraction Project conducted by Eurostr and ISPRS aimed to assess the accuracy and feasibility of automated tree extraction methods from laser scanning data. The final report by Cardinan and Hypa, 2008, found that there was significant variation in the quality of published methods depending on the forest type and laser point density. This paper further examined the results of the experiment and concluded that the most accurate methods were those which detected trees in the dominant, codominant and suppressed tree layers. These methods also had higher accuracy when it came to locating the tree's exact position compared to manual processing. Furthermore, the accuracy of tree height was greater than 0.5 meters in all tree heights, with the best methods achieving up to 1 meter in accuracy. Based on these results, the authors recommend that minimum curvature-based tree detection combined with point cloud-based cluster detection should be used for suppressed trees in order to achieve the highest level of accuracy in forest inventories. This article was authored by Baron Michael Wolfe, Ji Cheng Wu, Xiao Wei Yu, and others. We are article.tv, links in the description below.