TerraMesh: A Planetary Mosaic of Multimodal Earth Observation Data

• URL: http://arxiv.org/abs/2504.11172v2
• Date: Fri, 01 Aug 2025 15:02:03 GMT
• Title: TerraMesh: A Planetary Mosaic of Multimodal Earth Observation Data
• Authors: Benedikt Blumenstiel, Paolo Fraccaro, Valerio Marsocci, Johannes Jakubik, Stefano Maurogiovanni, Mikolaj Czerkawski, Rocco Sedona, Gabriele Cavallaro, Thomas Brunschwiler, Juan Bernabe-Moreno, Nicolas Longépé,
• Abstract summary: TerraMesh is a new globally diverse, multimodal dataset combining optical, radar, elevation, aperture and land-ready modalities in a Data-Ready format.<n>We provide detailed data processing steps, comprehensive statistics, and empirical evidence demonstrating improved model performance when pre-trained on TerraMesh.
• Score: 3.674991996196602
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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. We provide detailed data processing steps, comprehensive statistics, and empirical evidence demonstrating improved model performance when pre-trained on TerraMesh. The dataset is hosted at https://huggingface.co/datasets/ibm-esa-geospatial/TerraMesh.

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