Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in <i>Eucalyptus</i> spp. Forest Plantations Using Field and LiDAR Data

Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in <i>Eucalyptus</i> spp. Forest Plantations Using Field and LiDAR Data

Light Detection and Ranging (LiDAR) remote sensing has been established as one of the most promising tools for large-scale forest monitoring and mapping. Continuous advances in computational techniques, such as machine learning algorithms, have been increasingly improving our capability to model for...

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Bibliographic Details
Main Authors: Vanessa Sousa da Silva, Carlos Alberto Silva, Midhun Mohan, Adrián Cardil, Franciel Eduardo Rex, Gabrielle Hambrecht Loureiro, Danilo Roberti Alves de Almeida, Eben North Broadbent, Eric Bastos Gorgens, Ana Paula Dalla Corte, Emanuel Araújo Silva, Rubén Valbuena, Carine Klauberg
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
LiDAR
eucalyptus
forest attributes
machine learning
variable selection
Online Access:https://www.mdpi.com/2072-4292/12/9/1438

Internet

https://www.mdpi.com/2072-4292/12/9/1438

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