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SSL4EO-EU-Forest

_{Sentinel-2 winter scene}

_{tree (green) segmentation}

_{Sentinel-2 summer scene}

_{tree (green) segmentation}

Introduction

The dataset is an add-on to the globally sampled SSL4EO-S12 pre-training dataset (https://doi.org/10.1109/MGRS.2023.3281651) where v1.1 is available at https://huggingface.co/datasets/embed2scale/SSL4EO-S12-v1.1 with downstream tasks in https://huggingface.co/datasets/embed2scale/SSL4EO-S12-downstream .

Data Characteristics

SSL4EO-EU-Forest assembles an additional downstream task (85 GB) for binary semantic segmentation of forest land cover as follows:

images/ sub-directory: It curates 16K spatial patches (264x264 pixels) of Sentinel-2 L2A imagery (UInt16 GeoTIFF, 12 bands upsampled to 10m pixel resolution) over European forests. Each geolocation contains four Sentinel-2 timestamps from all seasons of year 2018 (winter, spring, summer, fall). The cloud cover in each scene is below 10%.
masks/ sub-directory: Binary forest masks (1: tree, 0: background, Byte GeoTIFF) have been derived from the 2018 HRL dataset (https://doi.org/10.2909/486f77da-d605-423e-93a9-680760ab6791) available through the Copernicus Land Monitoring Service, cf. https://land.copernicus.eu/en/products/high-resolution-layer-forests-and-tree-cover/dominant-leaf-type-2018-raster-10-m-europe-yearly .
Data of a geolocation are placed in numbered sub-directories (e.g. 0017618) of images/ and masks/, respectively. Each of those for the images/ directory contains four directories indicating the four seasons as per convention by Sentinel-2. For example, 20180520T094031_20180520T094033_T35VMH denotes the sensing start time as approx. May 20, 2018 at 9.41am UTC (spring scene) for geolocation defined by tile ID T35VMH (from which the patch was cropped from). Additional details in https://sentiwiki.copernicus.eu/web/s2-products .

Spatial Coverage

Spatial Distribution of SSL4EO-EU-Forest

Funding

This work was carried under the EvoLand project, cf. https://www.evo-land.eu . This project has received funding from the European Union's Horizon Europe research and innovation programme under grant agreement No. 101082130.