9 papers
TerraMind: Large-Scale Generative Multimodality for Earth Observation
Johannes Jakubik, Felix Yang, Benedikt Blumenstiel +13
We present TerraMind, the first any-to-any generative, multimodal foundation model for Earth observation (EO). Unlike other multimodal models, TerraMind is pretrained on dual-scale…
HeatMat: Simulation of City Material Impact on Urban Heat Island Effect
Marie Reinbigler, Romain Rouffet, Peter Naylor +5
The Urban Heat Island (UHI) effect, defined as a significant increase in temperature in urban environments compared to surrounding areas, is difficult to study in real cities using…
Scaling Laws for Geospatial Foundation Models: A case study on PhilEO Bench
Nikolaos Dionelis, Riccardo Musto, Jente Bosmans +7
Foundation Models (FMs) have achieved state-of-the-art performance across domains by leveraging large-scale pretraining. In Earth Observation (EO), the availability of petabyte-sca…
Building Age Estimation: A New Multi-Modal Benchmark Dataset and Community Challenge
Nikolaos Dionelis, Alessandra Feliciotti, Mattia Marconcini +8
Estimating the construction year of buildings is critical for advancing sustainability, as older structures often lack energy-efficient features. Sustainable urban planning relies…
CARE: Confidence-Aware Regression Estimation of building density fine-tuning EO Foundation Models
Nikolaos Dionelis, Jente Bosmans, Nicolas Longépé
Performing accurate confidence quantification and assessment in pixel-wise regression tasks, which are downstream applications of AI Foundation Models for Earth Observation (EO), i…
Improving EO Foundation Models with Confidence Assessment for enhanced Semantic segmentation
Nikolaos Dionelis, Nicolas Longepe
Confidence assessments of semantic segmentation algorithms are important. Ideally, deep learning models should have the ability to predict in advance whether their output is likely…