TY  - CONF
AU  - Blumenstiel, Benedikt
AU  - Fraccaro, Paolo
AU  - Marsocci, Valerio
AU  - Jakubik, Johannes
AU  - Maurogiovanni, Stefano
AU  - Czerkawski, Mikolaj
AU  - Sedona, Rocco
AU  - Cavallaro, Gabriele
AU  - Brunschwiler, Thomas
AU  - Bernabe-Moreno, Juan
AU  - Longépé, Nicolas
TI  - Terramesh: A Planetary Mosaic of Multimodal Earth Observation Data
PB  - IEEE
M1  - FZJ-2025-03964
SP  - n/a
PY  - 2025
AB  - Large-scale foundation models in Earth Observation can learn versatile, label-efficient representations by leveraging massive amounts of unlabeled data. However, existing public datasets are often limited in scale, geographic coverage, or sensor variety. We introduce TerraMesh, a new globally diverse, multimodal dataset combining optical, synthetic aperture radar, elevation, and land-cover modalities in an Analysis-Ready Data format. TerraMesh includes over 9 million samples with eight spatiotemporal aligned modalities, enabling large-scale pre-training and fostering robust cross-modal correlation learning. The dataset spans nearly all terrestrial ecosystems and is stored with Zarr to facilitate efficient, HPC-friendly loading at scale. We provide detailed data processing steps, comprehensive statistics, and empirical evidence demonstrating improved model performance when pre-trained on TerraMesh. The dataset will be made publicly available with a permissive license.
T2  - 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
CY  - 11 Jun 2025 - 12 Jun 2025, Nashville (TN)
Y2  - 11 Jun 2025 - 12 Jun 2025
M2  - Nashville, TN
LB  - PUB:(DE-HGF)8
DO  - DOI:10.1109/CVPRW67362.2025.00225
UR  - https://juser.fz-juelich.de/record/1046797
ER  -