A Refined Rotation Forest-Based Ensemble Classifier for Lithological Mapping with ZY1-02D Hyperspectral Remote Sensing Imagery

Hyperspectral remote sensing data provides distinct advantages for lithological classification in bedrock-exposed areas. Despite the superior performance of ensemble learning methods (e.g., Rotation Forest, ROF) in big data classification, their application in high-dimensional hyperspectral data is...

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Bibliografski detalji

Glavni autori:	Jing Xi, Hailiang Gao, Wenqian Zang, Xiaofei Zhao, Miao Liu, Bin Li
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2026-05-01
Serija:	Sensors
Teme:	hyperspectral data lithological mapping ensemble learning rotation forest
Online pristup:	https://www.mdpi.com/1424-8220/26/11/3340
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