Identification of Significative LiDAR Metrics and Comparison of Machine Learning Approaches for Estimating Stand and Diversity Variables in Heterogeneous Brazilian Atlantic Forest

Data collection and estimation of variables that describe the structure of tropical forests, diversity, and richness of tree species are challenging tasks. Light detection and ranging (LiDAR) is a powerful technique due to its ability to penetrate small openings and cracks in the forest canopy, enab...

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Hauptverfasser:	Rorai Pereira Martins-Neto, Antonio Maria Garcia Tommaselli, Nilton Nobuhiro Imai, Hassan Camil David, Milto Miltiadou, Eija Honkavaara
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2021-06-01
Schriftenreihe:	Remote Sensing
Schlagworte:	tropical forests airborne laser scanning forest structure forest attributes artificial intelligence machine learning
Online-Zugang:	https://www.mdpi.com/2072-4292/13/13/2444
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