SD4EO: AI-based synthetic satellite Sentinel-2 images of cities and building coverture (RGB+NIR bands)

This dataset has been created as part of the deliverables for ESA’s SD4EO project. It consists of synthetic versions of Sentinel-2 images in urban areas. These images were synthetically generated using schematic representations from Open Street Maps as a guide to create AI-based conditioned diffusion model images in the visible and near-infrared spectrum, along with coverage masks for non-residential buildings and the set of residential buildings combined with the former.

At least five synthetic variants were generated for each of the eleven cities:

• Paris (11 variants)
• Toulouse (9 variants)
• Poitiers (8 variants)
• Bordeaux (6 variants)
• Limoges (9 variants)
• Clermont-Ferrand (5 variants)
• Troyes (6 variants)
• Le Mans (14 variants)
• Angers (7 variants)
• Madrid (15 variants)
• Niort (6 variants)

The file names within the ZIP archives follow a very simple schema:

`assembled_` + city name + usage or band indicator + variant + PNG extension / NC extension

Each of the four types of images has a different indicator or band:

• `_RGB_` for images encoding visible spectrum signals
• `_NIR_` for images generated for the near-infrared band
• `_full_allbuildingmask` for the coverage pixel mask of all building types in floating point
• `_full_nonresidentialmask` for the coverage pixel mask of non-residential buildings in floating point
• if we have no indicator, then it is a netCDF file with a labelled xarray that merges RGB+NIR as the original Sentinel-2 spectral bands in full original range

NOTE: This 5th version corrects a minor bug in 3rd version of this dataset. If you want to access to version 4 (with non-already assembled patches), it is also available in the right side control version list.

The SD4EO Project is funded by the ESA’s FutureEO programme under contract no. 4000142334/23/I-DT and supervised by ESA Φ-lab.