remote sensing

Kuro Siwo: 12.1 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping
Global floods, exacerbated by climate change, pose severe threats to human life, infrastructure, and the environment. This urgency is …
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Kuro Siwo: 12.1 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping
Burnt area mapping with aerial data
The aim of this thesis is to leverage aerial data for the automatic mapping of areas burnt by wildfires. The data were captured by a Light Manned Aircraft (LMA) during 3 separate flights over Delfi, Domokos, Yliki and Prodromos.
Burnt area mapping with aerial data
Burnt area mapping with MODIS data
Orion Lab has assembled a novel benchmark dataset, namely FLOGA [1], for the mapping of burnt areas in the Greek region. The dataset comprises bitemporal image acquisitions from Sentinel-2 and MODIS satellites and the ground truth labels are photointerpretation mappings produced by Hellenic Fire Brigade experts.
Burnt area mapping with MODIS data
Data curation and model finetuning for burnt area mapping
Orion Lab has assembled a novel benchmark dataset, namely FLOGA [1], for the mapping of burnt areas in the Greek region. The dataset comprises bitemporal image acquisitions from Sentinel-2 and MODIS satellites and the ground truth labels are photointerpretation mappings produced by Hellenic Fire Brigade experts.
Data curation and model finetuning for burnt area mapping
A sentinel-2 multiyear, multicountry benchmark dataset for crop classification and segmentation with deep learning
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Deep learning for downscaling remote sensing images: Fusion and super-resolution
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