SVH-BD: Synthetic vegetation hyperspectral benchmark dataset derived from sentinel-2 tiles over France, Spain, Tanzania, and India during 1–6 May 2023
Chedly Ben Azizi, Claire Guilloteau, Gilles Roussel, Matthieu Puigt · 2026
Read SVH-BD: Synthetic vegetation hyperspectral benchmark dataset derived from sentinel-2 tiles over France, Spain, Tanzania, and India during 1–6 May 2023 by Chedly Ben Azizi, Claire Guilloteau, Gilles Roussel, Matthieu Puigt (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13264120.txt.
Description
Chedly Ben Azizi and colleagues release a synthetic hyperspectral dataset for vegetation research in a 2026 article. Each image cube records reflectance across hundreds of narrow bands, far beyond ordinary satellite color channels, for small land patches. Source scenes come from Sentinel-2 satellite tiles over parts of France, Spain, Tanzania and India during a short period in May 2023.
Plant traits were first estimated by inverting satellite reflectance with a canopy model, then fed back through the model to create physically consistent detailed spectra. Uncertainty maps and land cover classes accompany more than ten thousand cubes. Modelers can benchmark trait retrieval, train fast emulators of radiative transfer and study how spectra relate to plant properties under controlled variation.
Catalog record
| CREATOR | Chedly Ben Azizi, Claire Guilloteau, Gilles Roussel, Matthieu Puigt |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 22 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |