ImpactMesh is a large-scale multimodal, multitemporal dataset for flood and wildfire mapping, released by IBM, DLR, and the ESA Φ-lab. It combines Sentinel-1 SAR, Sentinel-2 optical imagery, and Copernicus DEM with high-quality annotations from Copernicus EMS. The dataset covers over 400 events globally with four temporal observations per event.
Please find the wildfire subset at https://huggingface.co/datasets/ibm-esa-geospatial/ImpactMesh-Fire and the flood samples at https://huggingface.co/datasets/ibm-esa-geospatial/ImpactMesh-FLood. The following map gives an overview of events present in ImpactMesh:
This repository provides code to build the pytorch dataloader or directly fine-tune a model with TerraTorch.
Quick start from pypi:
pip install impactmeshAlternatively create a new environment and install TerraTorch and the package from source:
python -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install git+https://github.com/terrastackai/terratorch.git@multimodal
pip install zarr==2.18.0 numcodecs==0.15.1
pip install -e .ImpactMesh uses Zarr Version 2.
Run training using on of the configs provided in configs/.
terratorch fit --config configs/terramind_v1_tiny_impactmesh_fire.yamlRun the evaluation on the test split.
terratorch test --config configs/terramind_v1_tiny_impactmesh_fire.yaml -- ckpt output/terramind_tiny_impactmesh_fire/1e-4/best_val_loss.ckptRun prediction with the following command:
terratorch predict -c configs/terramind_v1_tiny_impactmesh_fire.yaml --ckpt path/to/ckeckpoint.pt --predict_output_dir output/impactmesh_fire_predictions
# TerraTorch automatically uses a tiled inference. It might still lead to OOM errors. In that case, you can use:
python impactmesh/run_inference.py -c configs/terramind_v1_tiny_impactmesh_fire.yaml --ckpt path/to/ckeckpoint.pt --output_dir output/impactmesh_fire_predictionsOur technical report is released soon!
ImpactMesh was developed as part of the FAST‑EO project funded by the European Space Agency Φ‑Lab (contract #4000143501/23/I‑DT).
Sentinel-2 Level-2A data were downloaded from Microsoft Planetary Computer and are provided under Copernicus Sentinel license conditions (© European Union 2015–2025, ESA) (https://planetarycomputer.microsoft.com/dataset/sentinel-2-l2a).
Sentinel-1 Radiometrically Terrain Corrected (RTC) SAR data were retrieved from Microsoft Planetary Computer (calibrated to GRD and terrain-corrected using PlanetDEM) under Copernicus Sentinel license terms (© European Union 2014–2025) (https://planetarycomputer.microsoft.com/dataset/sentinel-1-rtc).
The DEM data is produced using Copernicus WorldDEM-30 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014-2018 provided under COPERNICUS by the European Union and ESA; all rights reserved.
Annotations were sourced from the Copernicus Emergency Management Service (© European Union, 2012–2025), available at https://emergency.copernicus.eu/.
The code and models are release under Apache 2.0. The dataset is released under CC-BY 4.0.
