29 citations · 49 across the 14 of their papers we have counts for
15 papers
Hide and Seek: Investigating Redundancy in Earth Observation Imagery
Tasos Papazafeiropoulos, Nikolaos Ioannis Bountos, Nikolas Papadopoulos +1
The growing availability of Earth Observation (EO) data and recent advances in Computer Vision have driven rapid progress in machine learning for EO, producing domain-specific mode…
TIRAuxCloud: A Thermal Infrared Dataset for Day and Night Cloud Detection
Alexis Apostolakis, Vasileios Botsos, Niklas Wölki +4
Clouds are a major obstacle in Earth observation, limiting the usability and reliability of critical remote sensing applications such as fire disaster response, urban heat island m…
TeleViT1.0: Teleconnection-aware Vision Transformers for Subseasonal to Seasonal Wildfire Pattern Forecasts
Ioannis Prapas, Nikolaos Papadopoulos, Nikolaos-Ioannis Bountos +3
Forecasting wildfires weeks to months in advance is difficult, yet crucial for planning fuel treatments and allocating resources. While short-term predictions typically rely on loc…
Thalia: A Global, Multi-Modal Dataset for Volcanic Activity Monitoring
Nikolas Papadopoulos, Nikolaos Ioannis Bountos, Maria Sdraka +3
Monitoring volcanic activity is of paramount importance to safeguarding lives, infrastructure, and ecosystems. However, only a small fraction of known volcanoes are continuously mo…
Probabilistic Machine Learning for Noisy Labels in Earth Observation
Spyros Kondylatos, Nikolaos Ioannis Bountos, Ioannis Prapas +3
Label noise poses a significant challenge in Earth Observation (EO), often degrading the performance and reliability of supervised Machine Learning (ML) models. Yet, given the crit…
Towards a Unified Copernicus Foundation Model for Earth Vision
Yi Wang, Zhitong Xiong, Chenying Liu +8
Advances in Earth observation (EO) foundation models have unlocked the potential of big satellite data to learn generic representations from space, benefiting a wide range of downs…
On the Generalization of Representation Uncertainty in Earth Observation
Spyros Kondylatos, Nikolaos Ioannis Bountos, Dimitrios Michail +3
Recent advances in Computer Vision have introduced the concept of pretrained representation uncertainty, enabling zero-shot uncertainty estimation. This holds significant potential…
FireCastNet: Earth-as-a-Graph for Seasonal Fire Prediction
Dimitrios Michail, Charalampos Davalas, Konstantinos Chafis +5
With climate change intensifying fire weather conditions globally, accurate seasonal wildfire forecasting has become critical for disaster preparedness and ecosystem management. We…
Seasonal Fire Prediction using Spatio-Temporal Deep Neural Networks
Dimitrios Michail, Lefki-Ioanna Panagiotou, Charalampos Davalas +4
With climate change expected to exacerbate fire weather conditions, the accurate anticipation of wildfires on a global scale becomes increasingly crucial for disaster mitigation. I…
FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring
Nikolaos Ioannis Bountos, Arthur Ouaknine, Ioannis Papoutsis +1
Forests are vital to ecosystems, supporting biodiversity and essential services, but are rapidly changing due to land use and climate change. Understanding and mitigating negative…
Kuro Siwo: 33 billion under the water. A global multi-temporal satellite dataset for rapid flood mapping
Nikolaos Ioannis Bountos, Maria Sdraka, Angelos Zavras +6
Global floods, exacerbated by climate change, pose severe threats to human life, infrastructure, and the environment. Recent catastrophic events in Pakistan and New Zealand undersc…
TeleViT: Teleconnection-driven Transformers Improve Subseasonal to Seasonal Wildfire Forecasting
Ioannis Prapas, Nikolaos Ioannis Bountos, Spyros Kondylatos +3
Wildfires are increasingly exacerbated as a result of climate change, necessitating advanced proactive measures for effective mitigation. It is important to forecast wildfires week…
Hephaestus: A large scale multitask dataset towards InSAR understanding
Nikolaos Ioannis Bountos, Ioannis Papoutsis, Dimitrios Michail +3
Synthetic Aperture Radar (SAR) data and Interferometric SAR (InSAR) products in particular, are one of the largest sources of Earth Observation data. InSAR provides unique informat…
Self-supervised Contrastive Learning for Volcanic Unrest Detection
Nikolaos Ioannis Bountos, Ioannis Papoutsis, Dimitrios Michail +1
Ground deformation measured from Interferometric Synthetic Aperture Radar (InSAR) data is considered a sign of volcanic unrest, statistically linked to a volcanic eruption. Recent…
Learning from Synthetic InSAR with Vision Transformers: The case of volcanic unrest detection
Nikolaos Ioannis Bountos, Dimitrios Michail, Ioannis Papoutsis
The detection of early signs of volcanic unrest preceding an eruption, in the form of ground deformation in Interferometric Synthetic Aperture Radar (InSAR) data is critical for as…