Mapping leaf area index in a mixed temperate forest using Fenix airborne hyperspectral data and Gaussian processes regression

Machine learning algorithms, in particular, kernel-based machine learning methods such as Gaussian processes regression (GPR) have shown to be promising alternatives to traditional empirical methods for retrieving vegetation parameters from remotely sensed data. However, the performance of GPR in pr...

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Autors principals:	Rui Xie, Roshanak Darvishzadeh, Andrew K. Skidmore, Marco Heurich, Stefanie Holzwarth, Tawanda W. Gara, Ils Reusen
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2021-03-01
Col·lecció:	International Journal of Applied Earth Observations and Geoinformation
Matèries:	Airborne hyperspectral data Leaf area index Gaussian processes regression Uncertainty Spectral subset Temperate mixed forests
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S0303243420308850
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