Further references#

Here, we provide a collection of relevant links provided by our research group:

  • The first BigEarthNet (S2) paper Sumbul et al. [5]

  • The BigEarthNet-MM publication + the recommended 19-class nomenclature Sumbul et al. [6]

The BigEarthNet Guide#


The BigEarthNet Guide documentation introduces the multi-modal BigEarthNet v1.0 dataset and makes it more accessible to others by providing an interactive dataset website.

Pretrained models#

Every repository includes code to re-run the training procedure. These models are all trained with the TensorFlow library.

  • Pretrained models trained on BigEarthNet-S2 with 43-classes

    • https://git.tu-berlin.de/rsim/BigEarthNet-S2_43-classes_models

  • Pretrained models trained on BigEarthNet-S2 with 19-classes

    • https://git.tu-berlin.de/rsim/BigEarthNet-S2_19-classes_models

  • Pretrained multi-modal models trained on BigEarthNet-S1 and BigEarthNet-S2 simultaneously

    • https://git.tu-berlin.de/rsim/BigEarthNet-MM_19-classes_models

BigEarthNet Tools#

  • BigEarthNet-S1 Tools

    • https://git.tu-berlin.de/rsim/BigEarthNet-S1_tools

    • Read GeoTIFF patches from BigEarthNet-S1

    • Script to extract names and download links of the Sentinel-1 Level-1C GRD tiles

      • Requires the BigEarthNet-S1 dataset on disk

  • BigEarthNet-S2 Tools

    • https://git.tu-berlin.de/rsim/BigEarthNet-S2_tools

    • Read GeoTIFF patches from BigEarthNet-S2

      • While skipping cloudy/snowy patches

    • Script to extract names and download links of the Sentinel-2 Level-1C tiles

      • Requires the BigEarthNet-S2 archive on disk

  • Code to read pairs of Sentinel-1 and Sentinel-2 patches

    • https://git.tu-berlin.de/rsim/BigEarthNet-MM_tools



Kun Li, George Vosselman, and Michael Ying Yang. Hrvqa: a visual question answering benchmark for high-resolution aerial images. arXiv preprint arXiv:2301.09460, 2023.


Sylvain Lobry, Begüm Demir, and Devis Tuia. Rsvqa meets bigearthnet: a new, large-scale, visual question answering dataset for remote sensing. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 1218–1221. IEEE, 2021.


Sylvain Lobry, Diego Marcos, Jesse Murray, and Devis Tuia. Rsvqa: visual question answering for remote sensing data. IEEE Transactions on Geoscience and Remote Sensing, 58(12):8555–8566, 2020.


Mengye Ren, Ryan Kiros, and Richard Zemel. Exploring models and data for image question answering. Advances in neural information processing systems, 2015.


Gencer Sumbul, Marcela Charfuelan, Begüm Demir, and Volker Markl. Bigearthnet: A large-scale benchmark archive for remote sensing image understanding. In IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, July 2019. URL: https://doi.org/10.1109/igarss.2019.8900532, doi:10.1109/igarss.2019.8900532.


Gencer Sumbul, Arne de Wall, Tristan Kreuziger, Filipe Marcelino, Hugo Costa, Pedro Benevides, Mario Caetano, Begüm Demir, and Volker Markl. BigEarthNet-MM: A large-scale, multimodal, multilabel benchmark archive for remote sensing image classification and retrieval [Software and data sets]. IEEE Geosci. Remote Sens. Mag., 9(3):174–180, September 2021. URL: https://doi.org/10.1109/mgrs.2021.3089174, doi:10.1109/mgrs.2021.3089174.