The article "KI-basierte Detektion von Gebäuden mittels Deep Learning und amtlichen Geodaten zur Baufallerkundung" (English: "AI-based detection of buildings using deep learning and official geodata for building case investigation") [paper], authored by Robert Roschlaub, Qingyu Li, Stefan Auer, Karin Möst, Clemens Glock, Michael Schmitt, Yilei Shi and Xiaoxiang Zhu, and published in zfv journal 3/2020, won the Geodesy Award of the Nico Rüpke foundation for the best paper of the year. 

Moreover, the proposed framework has been successfully implemented by the "Bavarian Agency for Digitization, High-Speed Internet and Surveying" as a routine strategy to detect undocumented building constructions in the state of Bavaria, Germany.

About the Geodesy Award: The DVW eV - Society for Geodesy, Geoinformation and Land Management, together with the Nico Rüpke Foundation Hamburg, awards an annual prize for an outstanding contribution in the specialist journal zfv - Journal for Geodesy, Geoinformation and Land Management. The prize money of 3,000 euros is provided by the Nico Rüpke Foundation.