New Maps of Lunar Surface Oxide Abundances and Mg# Using an Optimized Ensemble Learning Algorithm

The oxide abundance and Mg# (Mg/(Mg + Fe)) of the lunar surface are critical for understanding the Moon's petrology and evolution. Previous studies primarily relied on a single remote sensing data source and traditional regression algorithms for lunar oxide abundance inversion, potentiall...

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Bibliographic Details
Main Authors: Chaofa Bian, Kefei Zhang, Yunzhao Wu, Suqin Wu, Yu Lu, Yabo Duan, Huajing Wu, Zhenxing Zhao, Wei Wu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Online Access:https://ieeexplore.ieee.org/document/10919024/
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