Marrit Leenstra, Diego Marcos, Francesca Bovolo, Devis Tuia,
While annotated images for change detection using satellite imagery are scarce and costly to obtain, there is a wealth of unlabeled images being generated every day. In order to leverage these data to learn an image representation more adequate for change detection, we explore methods that exploit the temporal consistency of Sentinel-2 times series to obtain a usable self-supervised learning signal. For this, we build and make publicly available (https://zenodo.org/record/4280482) the Sentinel-2 ...
Tópico(s): Remote Sensing in Agriculture
2021 - Springer Science+Business Media | Lecture notes in computer science