Towards a Sentinel-2 Based Human Settlement Layer

Patrick Helber, Benjamin Bischke, Jörn Hees, Andreas Dengel

In: Urban Land Use and Land Cover Change. IEEE International Geoscience and Remote Sensing Symposium (IGARSS) June 28-August 2 Yokohama Japan IEEE 2019.


In this paper, we present how multi-spectral Sentinel-2 satellite images can be used in a machine learning approach based on an encoder-decoder semantic segmentation network to map human settlements. We show the effectiveness of the proposed CNN approach for the mapping of settlements in experiments with 785 European cities. The proposed approach to learn a settlement mapping with noisy ground truth data results in an effective settlement segmentation network with a mean intersection over union of 80.55% and a pixel accuracy of 87.40%.


Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence