New insight into the composition of the lunar surface from SiO2 map
The distribution of FeO and TiO 2 reveals mantle source characteristics and basaltic diversity, whereas SiO 2 distribution is closely related to magma evolution and crustal differentiation. However, global studies on SiO 2 remain limited. To address this gap, we combined the latest lunar sample data, Kaguya Multiband Imager spectra, and Christiansen Feature to develop a One-Dimensional Convolutional Neural Network (1D-CNN) for mapping lunar SiO 2 . The results reveal a clear spatial asymmetry in SiO 2 : high-latitude regions on the nearside show higher SiO 2 , while low-latitude regions exhibit lower values. Mare Tranquillitatis and Oceanus Procellarum have low SiO 2 but distinct TiO 2 variations, indicating different basaltic types and magmatic sources. The highlands are dominated by ferroan anorthosite, whereas the maria mainly consist of mafic to ultramafic rocks. Incorporating Chang’E-6 samples and Christiansen Feature data improved model accuracy. Future work on silicic volcanic rocks will further refine the global SiO 2 map and deepen understanding of lunar crustal evolution.
Authors
- Wencong Chen
- Jianguo Yan (ORCID: https://orcid.org/0000-0003-2612-4776)
- Denggao Qiu (ORCID: https://orcid.org/0000-0002-4388-9634)
- Sihai Yi
Institutions
- North China Institute of Science and Technology (CN)
- Chinese Academy of Sciences (CN)
- Xinjiang Astronomical Observatory (CN)
- Wuhan University (CN)
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN)
Publication Details
- Journal
- Frontiers in Astronomy and Space Sciences
- Published
- 2025-11-14
- DOI
- https://doi.org/10.3389/fspas.2025.1696995
- Primary Topic
- Planetary Science and Exploration
- Type
- article
- Field-Weighted Citation Impact
- 0.00