The final LOKI project report can be found online:
> Zahs, V., Kohns, J., Meyer, F., Schorlemmer, D., Anders, K., Klonner, C., Mey, H.,
Oostwegel, L., Zadeh, T. & Höfle, B. (2023): [LOKI – Luftgestützte Observation Kritischer Infrastrukturen](https://doi.org/10.2314/KXP:1885697937). Schlussbericht. Ruprecht-Karls-Universität Heidelberg, 120 S. DOI: 10.2314/KXP:1885697937.
# **Paper on automatic building damage classification**
# **Paper on automatic building damage classification**
As part of the [LOKI framework](https://git.gfz-potsdam.de/loki/loki_wiki/-/wikis/LOKI-Framework), we present a novel approach for the classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data.
As part of the [LOKI framework](https://git.gfz-potsdam.de/loki/loki_wiki/-/wikis/LOKI-Framework), we present a novel approach for the classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data.
