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Evolutionary feature selection to estimate forest stand variablesusing LiDAR

 

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Opened Access Evolutionary feature selection to estimate forest stand variablesusing LiDAR
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Author: García Gutiérrez, Jorge
González Ferreiro, Eduardo
Riquelme Santos, José Cristóbal
Miranda, David
Diéguez Aranda, Ulises
Navarro Cerrillo, Rafael M.
Department: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Date: 2014
Published in: International Journal of Applied Earth Observation and Geoinformation, 26, 119-131.
Document type: Article
Abstract: Light detection and ranging (LiDAR) has become an important tool in forestry. LiDAR-derived models are mostly developed by means of multiple linear regression (MLR) after stepwise selection of predictors. An increasing interest in machine learning a...
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Cite: García Gutiérrez, J., González Ferreiro, E., Riquelme Santos, J.C., Miranda, D., Diéguez Aranda, U. y Navarro Cerrillo, R.M. (2014). Evolutionary feature selection to estimate forest stand variablesusing LiDAR. International Journal of Applied Earth Observation and Geoinformation, 26, 119-131.
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Format: PDF

URI: http://hdl.handle.net/11441/43570

DOI: 10.1016/j.jag.2013.06.005

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