
This repository contains the fully labelled multimodal images cropped from the Sentinel-5P TROPOMI level-2 Carbon Monoxide data. This dataset was used in Wąsala et al. 2025 for carbon monoxide (CO) plume detection with AutoMergeNet. The training data is saved per image in .npy format.
This dataset was generated using the TROPOMI CO data. The Copernicus Datahub provides access to this data.
The dataset consists of 5207 images of the African content with 10 data layers. 24% of the images show plumes detected by Leguijt et al. 2024. The remaining images were selected randomly over the African content, using heuristics to discard potential plumes. Please see Wąsala et al. 2025 for a detailed description of how the dataset was compiled.
The images have 10 data layers: the CO data layer and 9 data layers that support the classification, making this dataset suitable for multimodal image classification or data fusion. These data layers are extracted from the operational (offline) TROPOMI CO product and are, therefore, already co-located.
The data layers are the following (see TROPOMI CO product for more detailed descriptions, variable name in the dataset indicated in brackets):
The annotations file contains the latitude and longitude of the top right corner of each image. Furthermore, Wąsala et al. defined a location-based test split. The images belonging to this test split are marked in the “test” column of the annotations file and “test” attribute in the NetCDFs (where 0=False and 1=True).
When using this dataset, please cite this repository and the following paper:
Wąsala, J., Maasakkers, J.D., Schuit, B.J., Leguijt, G., Aben, E.E.A., Schneider, R., Hoos, H.H., Baratchi, M.: AutoMergeNet: AutoML-based M-Source Satellite Data Fusion Evaluated with Atmospheric Case Studies, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, to appear.
Wąsala, J., Maasakkers, J.D., Schuit, B.J., Leguijt, G., Aben, E.E.A., Schneider, R., Hoos, H.H., Baratchi, M.: AutoMergeNet: AutoML-based M-Source Satellite Data Fusion Evaluated with Atmospheric Case Studies, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, ,doi.org, 2025.
Leguijt, G., Maasakkers, J. D., Denier van der Gon, H. A. C., Segers, A. J., Borsdorff, T., and Aben, I.: Quantification of carbon monoxide emissions from African cities using TROPOMI, Atmos. Chem. Phys., 23, 8899–8919, doi.org, 2023.
Landgraf, J., de Brugh, J., Scheepmaker, R., Borsdorff, T., Houweling, S., and Hasekamp, O.: Algorithm theoretical baseline document for sentinel-5 precursor: Carbon monoxide total column retrieval, Netherlands Institute for Space Research, the Netherlands, SRON-S5P-LEV2-RP-002, 2018.
Borsdorff, T., Hu, H., Hasekamp, O., Sussmann, R., Rettinger, M., Hase, F., ... & Landgraf, J. (2018). Mapping carbon monoxide pollution from space down to city scales with daily global coverage. Atmospheric Measurement Techniques, 11(10), 5507-5518.
Apituley, A., Pedergnana, M., Sneep, M., Veefkind, P.J., Loyola, D., Landgraf, J., and Borsdorff, T.: Sentinel-5 precursor/TROPOMI Level 2 Product User Manual Carbon Monoxide, Netherlands Institute for Space Research, the Netherlands, SRON-S5P-LEV2-MA-002, 2018.