Optimizing Sentinel-2 feature space for improved crop biophysical and biochemical variables retrieval using the novel spectral triad feature selection algorithm

Optimizing Sentinel-2 feature space for improved crop biophysical and biochemical variables retrieval using the novel spectral triad feature selection algorithm

AbstractThis study presents a novel Spectral Triad feature selection (STfs) technique based on music theory and compares it to the entire Sentinel-2 feature space and Random Forest-Recursive Feature Elimination (RF-RFE). The optimal subsets were evaluated with Random Forest for retrieving Leaf Area...

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Bibliographic Details
Main Authors: Mahlatse Kganyago, Clement Adjorlolo, Paidamwoyo Mhangara
Format: Article
Language:English
Published: Taylor & Francis Group 2024-01-01
Series:Geocarto International
Subjects:
Remote sensing
feature selection
chlorophyll content
leaf area index
sentinel-2
random forest
Online Access:https://www.tandfonline.com/doi/10.1080/10106049.2024.2309174

Internet

https://www.tandfonline.com/doi/10.1080/10106049.2024.2309174

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