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Siamese Networks with Transfer Learning for Change Detection in Sentinel-2 Images

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Book cover AIxIA 2021 – Advances in Artificial Intelligence (AIxIA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13196))

Abstract

The Earth’s surface is constantly changing due to various anthropogenic and natural causes. Leveraging machine learning to monitor land cover changes over time may provide valuable information on the transformation of the Earth’s environment. This study focuses on the discovery of land cover changes in bi-temporal, Sentinel-2 images. In particular, we rely on a Siamese network trained with labelled, imagery data of the same Earth’s scene acquired with Sentinel-2 at different times. Subsequently, we adopt a transfer learning strategy to adapt the Siamese network to Sentinel-2 data acquired in any new unlabeled scene. To deal with the lack of change labels in the new scene, transfer learning is performed with change pseudo-labels estimated in the new scene in unsupervised manner. We assess the effectiveness of the proposed change detection method in two couples of images acquired with Sentinel-2, at different times, in the urban areas of Cupertino and Las Vegas.

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Notes

  1. 1.

    In Sentinel-2, the optical camera covers 13 bands.

  2. 2.

    https://scikit-image.org/docs/dev/api/skimage.filters.html#skimage.filters.threshold_otsu.

  3. 3.

    https://rcdaudt.github.io/oscd/.

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Acknowledgements

This work fulfills the research objectives of the PON “Ricerca e Innovazione” 2014–2020 project “CLOSE – Close to the Earth” (ARS01_00141), funded by the Italian Ministry for Universities and Research (MIUR).

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Authors and Affiliations

  1. Department of Computer Science, University of Bari “Aldo Moro”, Bari, Italy

    Giuseppina Andresini, Annalisa Appice, Domenico Dell’Olio & Donato Malerba

  2. CINI - Consorzio Interuniversitario Nazionale per l’Informatica, Bari, Italy

    Annalisa Appice & Donato Malerba

Authors
  1. Giuseppina Andresini
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  2. Annalisa Appice
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  3. Domenico Dell’Olio
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  4. Donato Malerba
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Corresponding author

Correspondence to Giuseppina Andresini .

Editor information

Editors and Affiliations

  1. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Stefania Bandini

  2. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Francesca Gasparini

  3. Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genova, Italy

    Viviana Mascardi

  4. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Matteo Palmonari

  5. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Giuseppe Vizzari

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Andresini, G., Appice, A., Dell’Olio, D., Malerba, D. (2022). Siamese Networks with Transfer Learning for Change Detection in Sentinel-2 Images. In: Bandini, S., Gasparini, F., Mascardi, V., Palmonari, M., Vizzari, G. (eds) AIxIA 2021 – Advances in Artificial Intelligence. AIxIA 2021. Lecture Notes in Computer Science(), vol 13196. Springer, Cham. https://doi.org/10.1007/978-3-031-08421-8_33

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  • DOI: https://doi.org/10.1007/978-3-031-08421-8_33

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