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

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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Bibliographic Details
Main Authors: Rui Xie, Roshanak Darvishzadeh, Andrew K. Skidmore, Marco Heurich, Stefanie Holzwarth, Tawanda W. Gara, Ils Reusen
Format: Article
Language:English
Published: Elsevier 2021-03-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Airborne hyperspectral data
Leaf area index
Gaussian processes regression
Uncertainty
Spectral subset
Temperate mixed forests
Online Access:http://www.sciencedirect.com/science/article/pii/S0303243420308850

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http://www.sciencedirect.com/science/article/pii/S0303243420308850

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