In the last decades new remote sensing and proximal sensing techniques have been
developed for forest monitoring and vegetation mapping application. In this context LiDAR …

Tree modeling and visualization still represent a challenge in the light detecting and ranging
area. Starting from the segmented tree point clouds, this article presents an innovative tree …

The vertical structure of forest ecosystems influences and reflects ecosystem functioning.
Terrestrial laser scanning (TLS) enables the rapid acquisition of 3D forest information and …

Deep learning techniques have been widely applied to classify tree species and segment
tree structures. However, most recent studies have focused on the canopy and trunk …

Wood-leaf separation from terrestrial laser scanning (TLS) is a crucial prerequisite for
quantifying many biophysical properties and understanding ecological functions. In this …

Successfully separating wood and leaves in forest plots is a prerequisite for measuring
structural parameters and reconstructing 3D forest models. Terrestrial laser scanning (TLS) …

The accurate leaf-wood separation of individual trees from point clouds is an important yet
challenging task. Many existing methods rely on manual features that are time-consuming …

Tree species classification is a ubiquitous task in the forest inventory field. Only directly
measured feature vectors have been applied to most existing methods that use LiDAR …

Predictive accuracy in wildland fire behavior is contingent on a thorough understanding of
the 3D fuel distribution. However, this task is complicated by the complex nature of fuel forms …

Leaf-wood separation plays an important role in estimating aboveground biomass (AGB) of
trees from terrestrial laser scanning (TLS) point clouds. Yet, leaf-wood separation studies …