Further references#

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

  • The first BigEarthNet (S2) paper Sumbul et al. [2]

  • The BigEarthNet-MM publication + the recommended 19-class nomenclature Sumbul et al. [3]

Pretrained models#

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

BigEarthNet Tools#



Karen Fletcher. Sentinel-2 : ESA's optical high-resolution mission for GMES operational services. ESA Communications, 2012. ISBN 9789292214197. URL: http://esamultimedia.esa.int/multimedia/publications/SP-1322_2/offline/download.pdf.


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.


European Space Agency. Heritage. 2021. URL: https://sentinel.esa.int/web/sentinel/missions/sentinel-2/heritage.