A comparative study of regression methods to predict forest structure and canopy fuel variables from LiDAR full-waveform data

Regression methods are widely employed in forestry to predict and map structure and canopy fuel variables. We present a study where several regression models (linear, non-linear, regression trees and ensemble) were assessed. Independent variables were calculated using metrics extracted from full-wav...

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Bibliographic Details

Published in:	Revista de Teledetección
Main Authors:	P. Crespo-Peremarch, L.A. Ruiz, A. Balaguer-Beser
Format:	Article
Language:	English
Published:	Universitat Politècnica de València 2016-02-01
Subjects:	Regression models Random Forest CART M5 Wilcoxon Friedman forest structure canopy fuel LiDAR full-waveform
Online Access:	http://polipapers.upv.es/index.php/raet/article/view/4066