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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Autori principali:	Rorai Pereira Martins-Neto, Antonio Maria Garcia Tommaselli, Nilton Nobuhiro Imai, Hassan Camil David, Milto Miltiadou, Eija Honkavaara
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2021-06-01
Serie:	Remote Sensing
Soggetti:	tropical forests airborne laser scanning forest structure forest attributes artificial intelligence machine learning
Accesso online:	https://www.mdpi.com/2072-4292/13/13/2444
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