Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Refined lunar global chemistry mapping using farside ground truth information gathered by Chang’e-6

Nature Sensors (2026)Cite this article

Subjects

Abstract

Global mapping of lunar surface chemistry is crucial for revealing the geological characteristics and evolutionary history of the Moon. However, existing estimates of elemental abundances rely primarily on remote sensing data calibrated with sample-based ground truth information from the lunar nearside, leaving the farside largely unconstrained and limiting the accuracy of global chemical models. Here we integrate farside ground truth data from the Chang’e-6 sampling site, together with pre-existing nearside sample data and orbital spectral datasets from the Kaguya multiband imager, to refine global chemical maps. We apply a residual convolutional neural network with a fine-tuning strategy to optimally calibrate elemental abundances across the surface. The resulting global maps constrain the extent and composition of farside terranes and reveal deep-seated materials exposed in the South Pole–Aitken basin and highlands. These refined maps offer quantitative guidance for landing site selection and future lunar exploration missions.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Refined global lunar chemistry maps incorporating Chang’e-6 farside sample constraints.
Fig. 2: Refined lunar terranes based on the new Mg# map.
Fig. 3: Multi-scale geological implications from updated elemental maps of the farside, SPA and Chang’e-6 site.

Similar content being viewed by others

Data availability

The maps generated in this study and the LROC WAC global 100 m mosaic are available from Figshare50. The SELENE (Kaguya) multiband imager data with a resolution of ~59 m px−1 after topography shadow correction used in this study are available at https://astrogology.usgs.gov/search/map/lunar-kaguya-multiband-imager-mosaics. The previous multiband imager chemistry maps are available from https://doi.org/10.1038/s41467-023-43358-0 (ref. 14), https://doi.org/10.1016/j.icarus.2023.115505 (ref. 8) and https://doi.org/10.1016/j.pss.2021.105360 (ref. 7). The LRO Diviner chemistry maps are available from the Harvard Dataverse at https://doi.org/10.7910/DVN/ADSUJD; the M3–GRS map is available from https://doi.org/10.1051/0004-6361/201935773 (ref. 12); the LPGRS elemental maps are accessible from https://pds-geosciences.wustl.edu/lunar/lp-l-grs-5-elem-abundance-v1/; and the LRO LOLA global shaded relief map is available at https://doi.org/10.6084/m9.figshare.31044286.

Code availability

Python implementation of the methodology developed and used in the present study is available at https://github.com/zyyan-cc/RLCM-DL.

References

  1. He, H. et al. Water abundance in the lunar farside mantle. Nature 643, 366–370 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Lu, X. et al. Mature lunar soils from Fe-rich and young mare basalts in the Chang’e-5 regolith samples. Nat. Astron. 7, 142–151 (2023).

    Google Scholar 

  3. Lucey, P. G., Blewett, D. T. & Hawke, B. R. Mapping the FeO and TiO2 content of the lunar surface with multispectral imagery. J. Geophys. Res. Planets 103, 3679–3699 (1998).

    Article  CAS  Google Scholar 

  4. Liu, S. et al. In-situ mapping of iron and titanium with the visible and near-infrared image spectrometer (VNIS) along the Yutu-2 rover traverse on the farside of the moon. Icarus 412, 116003 (2024).

    Article  CAS  Google Scholar 

  5. Korotev, R. L., Jolliff, B. L., Zeigler, R. A., Gillis, J. J. & Haskin, L. A. Feldspathic lunar meteorites and their implications for compositional remote sensing of the lunar surface and the composition of the lunar crust. Geochim. Cosmochim. Acta 67, 4895–4923 (2003).

    Article  CAS  Google Scholar 

  6. Ma, M. et al. Global estimates of lunar surface chemistry derived from LRO Diviner data. Icarus 371, 114697 (2022).

    Article  CAS  Google Scholar 

  7. Wang, X., Zhang, J. & Ren, H. Lunar surface chemistry observed by the KAGUYA multiband imager. Planet. Space Sci. 209, 105360 (2021).

    Article  CAS  Google Scholar 

  8. Zhang, L. et al. New maps of major oxides and Mg # of the lunar surface from additional geochemical data of Chang’e-5 samples and KAGUYA multiband imager data. Icarus 397, 115505 (2023).

    Article  CAS  Google Scholar 

  9. Ohtake, M. et al. Asymmetric crustal growth on the Moon indicated by primitive farside highland materials. Nat. Geosci. 5, 384–388 (2012).

    Article  CAS  Google Scholar 

  10. Crites, S. T. & Lucey, P. G. Revised mineral and Mg# maps of the Moon from integrating results from the Lunar Prospector neutron and gamma-ray spectrometers with Clementine spectroscopy. Am. Mineral. 100, 973–982 (2015).

    Article  Google Scholar 

  11. Lucey, P. G., Blewett, D. T. & Jolliff, B. L. Lunar iron and titanium abundance algorithms based on final processing of Clementine ultraviolet-visible images. J. Geophys. Res. Planets 105, 20297–20305 (2000).

    Article  CAS  Google Scholar 

  12. Bhatt, M., Wöhler, C., Grumpe, A., Hasebe, N. & Naito, M. Global mapping of lunar refractory elements: multivariate regression vs. machine learning. Astron. Astrophys. 627, A155 (2019).

    Article  CAS  Google Scholar 

  13. Fu, X.-H. et al. Data processing for the Active Particle-induced X-ray Spectrometer and initial scientific results from Chang'e-3 mission. Res. Astron. Astrophys. 14, 1595 (2014).

    Article  CAS  Google Scholar 

  14. Yang, C. et al. Comprehensive mapping of lunar surface chemistry by adding Chang’e-5 samples with deep learning. Nat. Commun. 14, 7554 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Li, C. et al. Nature of the lunar far-side samples returned by the Chang’e-6 mission. Natl Sci. Rev. 11, nwae328 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Yue, Z. et al. Geological context of the Chang’e-6 landing area and implications for sample analysis. Innovation 5, 100663 (2024).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Zeng, X. et al. Landing site of the Chang’e-6 lunar farside sample return mission from the Apollo basin. Nat. Astron. 7, 1188–1197 (2023).

    Article  Google Scholar 

  18. Melosh, H. J. et al. South Pole–Aitken basin ejecta reveal the Moon’s upper mantle. Geology 45, 1063–1066 (2017).

    Article  Google Scholar 

  19. Moriarty, D. P., Dygert, N., Valencia, S. N., Watkins, R. N. & Petro, N. E. The search for lunar mantle rocks exposed on the surface of the Moon. Nat. Commun. 12, 4659 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Jolliff, B. L., Gillis, J. J., Haskin, L. A., Korotev, R. L. & Wieczorek, M. A. Major lunar crustal terranes: surface expressions and crust-mantle origins. J. Geophys. Res. Planets 105, 4197–4216 (2000).

    Article  CAS  Google Scholar 

  21. Wieczorek, M. A. & Zuber, M. T. The composition and origin of the lunar crust: constraints from central peaks and crustal thickness modeling. Geophys. Res. Lett. 28, 4023–4026 (2001).

    Article  Google Scholar 

  22. Wieczorek, M. A. & Phillips, R. J. Potential anomalies on a sphere: applications to the thickness of the lunar crust. J. Geophys. Res. Planets 103, 1715–1724 (1998).

    Article  Google Scholar 

  23. Yingst, R. A. & Head, J. W. Volumes of lunar lava ponds in South Pole-Aitken and Orientale Basins: implications for eruption conditions, transport mechanisms, and magma source regions. J. Geophys. Res. Planets 102, 10909–10931 (1997).

    Article  Google Scholar 

  24. Sun, L. & Lucey, P. G. Lunar mantle composition and timing of overturn indicated by Mg# and mineralogy distributions across the South Pole-Aitken basin. Earth Planet. Sci. Lett. 643, 118931 (2024).

    Article  CAS  Google Scholar 

  25. Hapke, B. Theory of Reflectance and Emittance Spectroscopy (Cambridge Univ. Press, 1993).

  26. Pieters, C. Statistical analysis of the links among lunar mare soil mineralogy, chemistry, and reflectance spectra. Icarus 155, 285–298 (2002).

    Article  CAS  Google Scholar 

  27. Kodikara, G. R. L. & McHenry, L. J. Machine learning approaches for classifying lunar soils. Icarus 345, 113719 (2020).

    Article  CAS  Google Scholar 

  28. Li, S., Li, L., Milliken, R. & Song, K. Hybridization of partial least squares and neural network models for quantifying lunar surface minerals. Icarus 221, 208–225 (2012).

    Article  Google Scholar 

  29. Ohtake, M. et al. One moon, many measurements 3: spectral reflectance. Icarus 226, 364–374 (2013).

    Article  Google Scholar 

  30. Takeda, H. et al. Magnesian anorthosites and a deep crustal rock from the farside crust of the moon. Earth Planet. Sci. Lett. 247, 171–184 (2006).

    Article  CAS  Google Scholar 

  31. Arai, T., Takeda, H., Yamaguchi, A. & Ohtake, M. A new model of lunar crust: asymmetry in crustal composition and evolution. Earth Planets Space 60, 433–444 (2008).

    Article  Google Scholar 

  32. Charlier, B., Grove, T. L., Namur, O. & Holtz, F. Crystallization of the lunar magma ocean and the primordial mantle-crust differentiation of the Moon. Geochim. Cosmochim. Acta 234, 50–69 (2018).

    Article  CAS  Google Scholar 

  33. Prettyman, T. H. et al. Elemental composition of the lunar surface: analysis of gamma ray spectroscopy data from Lunar Prospector. J. Geophys. Res. Planets 111, E12007 (2006).

    Article  Google Scholar 

  34. Chen, S. et al. Analysis of a large buried impact crater and vertical mineral composition at the Chang’e-4 landing site by multi-source remote sensing data. Icarus 422, 116256 (2024).

    Article  CAS  Google Scholar 

  35. Pieters, C. M., Head, J. W., Gaddis, L., Jolliff, B. & Duke, M. Rock types of South Pole-Aitken basin and extent of basaltic volcanism. J. Geophys. Res. Planets 106, 28001–28022 (2001).

    Article  CAS  Google Scholar 

  36. Joy, K. H. et al. Evidence of a 4.33 billion year age for the Moon’s South Pole–Aitken basin. Nat. Astron. 9, 55–65 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Dowty, E., Prinz, M. & Keil, K. Ferroan anorthosite: a widespread and distinctive lunar rock type. Earth Planet. Sci. Lett. 24, 15–25 (1974).

    Article  CAS  Google Scholar 

  38. Elardo, S. M. et al. The evolution of the lunar crust. Rev. Mineral. Geochem. 89, 293–338 (2023).

    Article  Google Scholar 

  39. Xu, X. et al. Formation of lunar highlands anorthosites. Earth Planet. Sci. Lett. 536, 116138 (2020).

    Article  CAS  Google Scholar 

  40. Shearer, C. K., Elardo, S. M., Petro, N. E., Borg, L. E. & McCubbin, F. M. Origin of the lunar highlands Mg-suite: an integrated petrology, geochemistry, chronology, and remote sensing perspective. Am. Mineral. 100, 294–325 (2015).

    Article  Google Scholar 

  41. Sheng, S.-Z. et al. Lunar primitive mantle olivine returned by Chang’e-6. Nat. Commun. 16, 3759 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Zhang, Q. W. L. et al. Lunar farside volcanism 2.8 billion years ago from Chang’e-6 basalts. Nature 643, 356–360 (2025).

    Article  CAS  PubMed  Google Scholar 

  43. Uemoto, K. et al. Evidence of impact melt sheet differentiation of the lunar South Pole-Aitken basin. J. Geophys. Res. Planets 122, 1672–1686 (2017).

    Article  CAS  Google Scholar 

  44. Blewett, D. T., Lucey, P. G., Hawke, B. R. & Jolliff, B. L. Clementine images of the lunar sample-return stations: refinement of FeO and TiO2 mapping techniques. J. Geophys. Res. Planets 102, 16319–16325 (1997).

    Article  CAS  Google Scholar 

  45. Lucey, P. G., Taylor, G. J. & Malaret, E. Abundance and distribution of iron on the moon. Science 268, 1150–1153 (1995).

    Article  CAS  PubMed  Google Scholar 

  46. Lucey, P. G., Blewett, D. T., Taylor, G. J. & Hawke, B. R. Imaging of lunar surface maturity. J. Geophys. Res. Planets 105, 20377–20386 (2000).

    Article  CAS  Google Scholar 

  47. He, K., Zhang, X., Ren, S. & Sun, J. Deep residual learning for image recognition. In Proc. 2016 IEEE Conference on Computer Vision and Pattern Recognition 770–778 (IEEE, 2016).

  48. Wortsman, M., et al. Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. In Proc. 39th International Conference on Machine Learning (eds Chaudhuri, K. et al.) 23965–23998 (2022).

  49. Hu, J., Shen, L. & Sun, G. Squeeze-and-excitation networks. In Proc. IEEE Conference on Computer Vision and Pattern Recognition 7132–7141 (IEEE, 2018).

  50. Shi, X. et al. Dataset title. Figshare https://doi.org/10.6084/m9.figshare.30022171 (2025).

  51. Moriarty, D. P. & Pieters, C. M. The character of South Pole-Aitken basin: patterns of surface and subsurface composition. J. Geophys. Res. Planets 123, 729–747 (2018).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank all of the staff of China’s Chang’e-6 lunar exploration project for providing precious sample truth. This work was supported by the National Natural Science Foundation of China (grants 42221002 (X.T.), T2521003 (W.H.), 42171432 (S.L.), W2511065 (F.W.), 62422410 (F.W.) and 62327812 (W.H.)); Strategic Priority Research Program of the Chinese Academy of Sciences (grant XDB0580000 (W.H.)); Shanghai Rising-Star Program (grant 24QA2711000 (F.W.)); CAS Pioneer Hundred Talents Program (F.W.) and Fundamental Research Funds for the Central Universities.

Author information

Author notes

  1. These authors contributed equally: Xuming Shi, Jian Chen, Juntao Wang.

Authors and Affiliations

  1. Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China

    Xuming Shi, Shijie Liu & Xiaohua Tong

  2. State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, China

    Xuming Shi, Junhao Chu, Weida Hu & Fang Wang

  3. Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, College of Surveying and Geo-Informatics, Tongji University, Shanghai, China

    Xuming Shi, Shijie Liu, Xiaohua Tong & Huan Xie

  4. Shandong Key Laboratory of Space Environment and Exploration Technology, Institute of Space Sciences, School of Space Science and Technology, Shandong University, Weihai, China

    Jian Chen

  5. Institute of Deep Space Sciences, Deep Space Exploration Laboratory, Hefei, China

    Juntao Wang

  6. National Key Laboratory of Deep Space Exploration, Hefei, China

    Juntao Wang

  7. Key Laboratory of Space Active Opto-electronics Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, China

    Jinning Li & Zhiping He

  8. College of Electronic Science and Engineering, Jilin University, Changchun, China

    Zeyi Yan & Shiji Wen

  9. University of Chinese Academy of Sciences, Beijing, China

    Junhao Chu, Weida Hu & Fang Wang

Authors
  1. Xuming Shi
    View author publications

    Search author on:PubMed Google Scholar

  2. Jian Chen
    View author publications

    Search author on:PubMed Google Scholar

  3. Juntao Wang
    View author publications

    Search author on:PubMed Google Scholar

  4. Shijie Liu
    View author publications

    Search author on:PubMed Google Scholar

  5. Xiaohua Tong
    View author publications

    Search author on:PubMed Google Scholar

  6. Jinning Li
    View author publications

    Search author on:PubMed Google Scholar

  7. Zeyi Yan
    View author publications

    Search author on:PubMed Google Scholar

  8. Shiji Wen
    View author publications

    Search author on:PubMed Google Scholar

  9. Huan Xie
    View author publications

    Search author on:PubMed Google Scholar

  10. Zhiping He
    View author publications

    Search author on:PubMed Google Scholar

  11. Junhao Chu
    View author publications

    Search author on:PubMed Google Scholar

  12. Weida Hu
    View author publications

    Search author on:PubMed Google Scholar

  13. Fang Wang
    View author publications

    Search author on:PubMed Google Scholar

Contributions

F.W., W.H., Z.H., X.T. and S.L. conceived of and supervised the project, proposed the idea and designed the experiments. J. Chu provided project planning and scientific background. X.S., J. Chen and J.W. contributed equally to the data analyses and geological interpretation and wrote the manuscript. J.L. helped with the global chemistry mapping. H.X. contributed to the reduction of remote sensing datasets. Z.Y. and S.W. contributed to data pre-processing and the inversion algorithm.

Corresponding authors

Correspondence to Shijie Liu, Xiaohua Tong, Zhiping He, Weida Hu or Fang Wang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Sensors thanks Gayantha Kodikara and the other, anonymous, reviewers for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary text, Tables 1–6 and Figs. 1–5.

Reporting Summary

Supplementary Data 1

Source Data for Supplementary Figs. 1–3.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shi, X., Chen, J., Wang, J. et al. Refined lunar global chemistry mapping using farside ground truth information gathered by Chang’e-6. Nat. Sens. (2026). https://doi.org/10.1038/s44460-025-00021-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • DOI: https://doi.org/10.1038/s44460-025-00021-z

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing