The objective of this work was to determine the influence of stand age on the automatic detection of Eucalyptus sp. trees using LIDAR datasets. Three different stands 3, 5 and 7 years old were analyzed. The LIDAR cloud point data of the first return was split into two datasets: Class 1 (points for all vegetation), Class 2 (points for vegetation above 10m). Results for obtaining the number of stems for each dataset were compared to the census of the area, which was done by visual interpretation using an auxiliary high spatial resolution remote sensing image, and to forest inventory estimates. In comparison to the census data, tree counting using Class 1 dataset agreed well for all considered ages, with best results achieved in 3 and 5 year old stands. On the other hand, Class 2 biased toward underestimated values. The best results for this class were verified in 7 year old stands. When compared to the forest inventory data, this methodology proved to be more efficient. The number of stems derived from the forest inventory was biased towards overestimation. In order to achieve better estimates using forest inventory data, an intensification of the sampling procedure would be necessary.
Forest inventory; LIDAR; Individual-tree detection; Local maxima
