sentinel-2

Engage in a semantic segmentation challenge for land cover description using multimodal remote sensing earth observation data, delving into real-world scenarios with a dataset comprising 70,000+ aerial imagery patches and 50,000 Sentinel-2 satellite acquisitions.

Landcover classification on sentinel-2 data with Prithvi, EfficientNet-Unet and OSM / CNES Landcover labels.

Google Earth Engine tool to generate multi-modal and multi-temporal datasets, including spatially and temporally aligned Sentinel-1 SAR data, Sentinel-2 multispectral data, weather and DEM-based data. A supplementary material for Paluba et al. 2024: "Identification of Optimal Sentinel-1 SAR Polarimetric Parameters for Forest Monitoring in Czechia