Automated individual tree crown detection and delineation (ITCD) using remotely sensed
data plays an increasingly significant role in efficiently, accurately, and completely …

Efficient forest management demands detailed, timely information. As high spatial resolution
remotely sensed imagery becomes more available, there is a great potential for conducting …

Canopy height models (CHMs) derived from lidar data have been applied to extract forest
inventory parameters. However, variations in modeled height cause data pits, which form a …

The Pacific Equatorial dry forest of Northern Peru is recognised for its unique endemic
biodiversity. Although highly threatened the forest provides livelihoods and ecosystem …

A forest consists of multi-scale branches, tree crowns, and tree clusters. Similar to small tree
crowns in shape and scale, branches normally cause over-segmentation of imagery when a …

The retrieval of tree and forest structural attributes from Light Detection and Ranging
(LiDAR) data has focused largely on utilising canopy height models, but these have proved …

Adaptive single tree detection methods using airborne laser scanning (ALS) data were
investigated and validated on 40 large plots sampled from a structurally heterogeneous …

A canopy height model (CHM) derived from lidar data can be segmented to obtain individual
tree crowns. However, branches, tree crowns, and tree clusters usually have similar shapes …

This study investigated the effects of forest type, leaf area index (LAI), canopy cover (CC),
tree density (TD), and the coefficient of variation of tree height (CVTH) on the accuracy of …

Street trees interlaced with other objects in cluttered point clouds of urban scenes inhibit the
automatic extraction of individual trees. This paper proposes a method for the automatic …