A new remote sensing benchmark dataset for machine learning applications : MultiSenGE

[UPDATE] You can now access MultiSen (GE and NA) collection though this portal : https://doi.theia.data-terra.org/ai4lcc/?lang=en

MultiSenGE is a new large-scale multimodal and multitemporal benchmark dataset covering one of the biggest administrative region located in the Eastern part of France. It contains 8,157 patches of 256 * 256 pixels for Sentinel-2 L2A, Sentinel-1 GRD and a regional LULC topographic regional database. 

Every file has a specific nomenclature :

Sentinel-1 patches: {tile}_{date}_S1_{x-pixel-coordinate}_{y-pixel-coordinate}.tif

Sentinel-2 patches: {tile}_{date}_S2_{x-pixel-coordinate}_{y-pixel-coordinate}.tif

Ground reference patches: {tile}_GR_{x-pixel-coordinate}_{y-pixel-coordinate}.tif

JSON Labels: {tile}_{x-pixel-coordinate}_{y-pixel-coordinate}.json

where tile is the Sentinel-2 tile number, date the date of acquisition of the patch, x-pixel-coordinate and y-pixel-coordinate are the coordinates of the patch in the tile.

In addition, you can find a set of useful python tools for extracting information about the dataset on Github : https://github.com/r-wenger/MultiSenGE-Tools

First experiments based on this dataset is in press in ISPRS Annals : Wenger, R., Puissant, A., Weber, J., Idoumghar, L., and Forestier, G.: MULTISENGE: A MULTIMODAL AND MULTITEMPORAL BENCHMARK DATASET FOR LAND USE/LAND COVER REMOTE SENSING APPLICATIONS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 635–640, https://doi.org/10.5194/isprs-annals-V-3-2022-635-2022, 2022.

Due to the large size of the dataset, you will only find the associated JSON files on this Zenodo repository. To download the Sentinel-1, Sentinel-2 patches and the reference data, please do so via these links: 

Sentinel-1 temporal serie patches: https://s3.unistra.fr/a2s_datasets/MultiSenGE/s1.tgz

Sentinel-2 temporal serie patches: https://s3.unistra.fr/a2s_datasets/MultiSenGE/s2.tgz

Ground reference patches: https://s3.unistra.fr/a2s_datasets/MultiSenGE/ground_reference.tgz

JSON files for each patch: https://s3.unistra.fr/a2s_datasets/MultiSenGE/labels.tgz