Forests, Volume 14, Issue 8
2023 August - 180 articles
Cover Story: This study presents a method of tree species classification using individual tree metrics derived from a three-dimensional point cloud via unmanned aerial vehicle laser scanning (ULS). In this novel approach, we evaluated the metrics of 1045 trees using a generalized linear model (GLM) and random forest (RF) techniques to automatically assign individual trees into either a coniferous or broadleaf group. We evaluated several statistical descriptors, including a novel approach using the Clark–Evans spatial aggregation index (CE), which indicates the level of clustering in point clouds. A comparison of classifiers that included and excluded the CE indicator values demonstrated their importance for improved classification of the individual tree point clouds. The overall accuracy when including the CE index was 94.8% using a GLM approach and 95.1% using an RF approach. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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