8 papers
OSMGraphCLIP: Learning Global Location Representations from OpenStreetMap Graphs
Dimitrios Michail, Eleni Saka, Ioannis Giannopoulos +1
We present OSMGraphCLIP, a CLIP-style geospatial representation model that learns global location embeddings from freely available OpenStreetMap (OSM) data. OSMGraphCLIP represents…
GAIA: A Global, Multi-modal, Multi-scale Vision-Language Dataset for Remote Sensing Image Analysis
Angelos Zavras, Dimitrios Michail, Xiao Xiang Zhu +2
Existing Vision-Language Models (VLMs) are predominantly trained on web-scraped, noisy image-text data, exhibiting limited exposure to the specialized domain of RS. This deficiency…
Magnifying change: Rapid burn scar mapping with multi-resolution, multi-source satellite imagery
Maria Sdraka, Dimitrios Michail, Ioannis Papoutsis
Delineating wildfire affected areas using satellite imagery remains challenging due to irregular and spatially heterogeneous spectral changes across the electromagnetic spectrum. W…
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…
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…
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…