Monitoring Forest Health Using Hyperspectral Imagery: Does Feature Selection Improve the Performance of Machine-Learning Techniques?

Monitoring Forest Health Using Hyperspectral Imagery: Does Feature Selection Improve the Performance of Machine-Learning Techniques?

This study analyzed highly correlated, feature-rich datasets from hyperspectral remote sensing data using multiple statistical and machine-learning methods. The effect of filter-based feature selection methods on predictive performance was compared. In addition, the effect of multiple expert-based a...

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Bibliographic Details
Main Authors: Patrick Schratz, Jannes Muenchow, Eugenia Iturritxa, José Cortés, Bernd Bischl, Alexander Brenning
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Remote Sensing
Subjects:
hyperspectral imagery
forest health monitoring
machine learning
feature selection
model comparison
Online Access:https://www.mdpi.com/2072-4292/13/23/4832

Internet

https://www.mdpi.com/2072-4292/13/23/4832

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