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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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Principais autores: P. Crespo-Peremarch, L.A. Ruiz, A. Balaguer-Beser
Format: Artigo
Sprog:Inglês
Udgivet: Universitat Politècnica de València 2016-02-01
Serier:Revista de Teledetección
Fag:
Regression models
Random Forest
CART
M5
Wilcoxon
Friedman
forest structure
canopy fuel
LiDAR full-waveform
Online adgang:http://polipapers.upv.es/index.php/raet/article/view/4066
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