Cluster B - B03



Deep learning for satellite-based land use and land cover reconstruction

Prof. Dr. Ribana Roscher
University of Bonn  |    +49 228 73-60854  |    This email address is being protected from spambots. You need JavaScript enabled to view it.



The goal of this project is the reconstruction of land use and land cover from optical satellite data using deep learning. To this end, we will develop spatio-temporal deep neural networks that consider the specific biogeographical characteristics of the regions of interest in order to ensure a high generalization capability across the study region. Furthermore, predictive uncertainties for the derived land use and land cover maps will be determined and the model’s capabilities in the context of multi-task learning will be studied. Lastly, we will also explore the potential of generated data to fill spatial and temporal data gaps.

Graphical Summary

B03 graphical abstract

Contribution to CRC

Land use and land cover maps generated in our project will be reused by other projects in DETECT for a variety of purposes: On the one hand, the A and B clusters will rely on these data to determine relevant regions for their own purposes, such as agricultural or water areas. The C and D clusters, on the other hand, will use the maps as inputs for terrestrial models or for subsequent analysis.


To train our model we will rely on openly available medium resolution, multispectral imagery from Sentinel-2 and the Landsat satellites. Observations from the LUCAS surveys will be used as reference data. As those data are distributed rather sparsely, special methods such as Neural Networks operating on images’ region adjacency graphs need be used. The above-described research ideas shall be implemented as amendments or extensions to this general model.

Main results in 2022

Conceptualization and start of implementation of the general model and approaches for improving its generalizability.

Collaborative Research Centre (SFB) 1502 - DETECT

Kekuléstr. 39a
53115 Bonn

+49 228 73 60585 / 60600

Coordination Office

logomosaik slim Universität Bonn Forschungszentrum Jülich Geomar Georg-August-Universität Göttingen Deutscher Wetterdienst