Evaluating Variable Selection and Machine Learning Algorithms for Estimating Forest Heights by Combining Lidar and Hyperspectral Data

Machine learning has been employed for various mapping and modeling tasks using input variables from different sources of remote sensing data. For feature selection involving high- spatial and spectral dimensionality data, various methods have been developed and incorporated into the machine learnin...

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Detalles Bibliográficos

Principais autores:	Sanjiwana Arjasakusuma, Sandiaga Swahyu Kusuma, Stuart Phinn
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2020-08-01
Series:	ISPRS International Journal of Geo-Information
Assuntos:	forest height feature selection dimensionality reduction lidar AISA hyperspectral
Acceso en liña:	https://www.mdpi.com/2220-9964/9/9/507
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