geoai-datacubes: AI-ready multi-mission satellite data cubes for Earth-observation machine learning

Python Submitted 04 July 2026 • Published 13 November 2026
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Authors

Joachim Moortgat (0000-0002-0259-3597), Bhavika Jain (0009-0007-9606-2677), Aswathnarayan Radhakrishnan (0009-0001-1577-1946), Satyaki Roy Chowdhury (0009-0006-7035-3743), Hsiao Jou Hsu (0009-0008-5863-3229)

Citation

Moortgat et al., (2026). geoai-datacubes: AI-ready multi-mission satellite data cubes for Earth-observation machine learning. Journal of Open Source Software, 11(127), 11034, https://doi.org/10.21105/joss.11034

@article{Moortgat2026, doi = {10.21105/joss.11034}, url = {https://doi.org/10.21105/joss.11034}, year = {2026}, publisher = {The Open Journal}, volume = {11}, number = {127}, pages = {11034}, author = {Moortgat, Joachim and Jain, Bhavika and Radhakrishnan, Aswathnarayan and Chowdhury, Satyaki Roy and Hsu, Hsiao Jou}, title = {geoai-datacubes: AI-ready multi-mission satellite data cubes for Earth-observation machine learning}, journal = {Journal of Open Source Software} }
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remote sensing Earth observation satellite imagery Sentinel-2 Sentinel-1 Landsat PlanetScope data cubes machine learning deep learning geospatial

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Journal of Open Source Software is part of Open Journals, which is a NumFOCUS-sponsored project.

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