Dataset for Evaluating Sentinel-2 Super-Resolution Algorithms for Automated Building Delineation

When using these images, retain their spatial attributes. Images are processed and annotated with STAC metadata, with each folder containing its own collection. The following datasets are available: main datasets: hr_masks: 2.5m resolution cadastral masks with building footprints hr_orthophoto: 2.5m resolution orthophotos of Austria lr_s2: 10m resolution Sentinel-2 images of Austria (temporally and spatially aligned with the other data sources) image_samples: samples dataset representing the structure of this data repository building_delineation_inference: building delineation masks extracted from super-resolved or interpolated Sentinel-2 and orthophoto images metric_results: results from the conducted experiments on presented metrics stratification_tables: train/validation/test splits for different dataset configurations super_resolved: super-resolved Sentinel-2 images (from lr_s2) output from all used SR models tracasa_evaluation: dataset to achieve evaluation on a small subset for proprietary SR models thesis_figures: figures and plots featured in the written thesis This dataset contains only the image data and results, code repositories are available on the linked GitHub repository.