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A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables

 

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Opened Access A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables
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Author: García Gutiérrez, Jorge
Martínez Álvarez, Francisco
Troncoso Lora, Alicia
Riquelme Santos, José Cristóbal
Department: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Date: 2015
Published in: Neurocomputing, 167, 24-31.
Document type: Article
Abstract: Light Detection and Ranging (LiDAR) is a remote sensor able to extract three-dimensional information. Environmental models in forest areas have been benefited by the use of LiDAR-derived information in the last years. A multiple linear regression ...
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Cite: García Gutiérrez, J., Martínez Álvarez, F., Troncoso Lora, A. y Riquelme Santos, J.C. (2015). A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables. Neurocomputing, 167, 24-31.
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Format: PDF

URI: http://hdl.handle.net/11441/43592

DOI: http://dx.doi.org/10.1016/j.neucom.2014.09.091

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