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.