2024
- Ecke S, Stehr F, Frey J, Tiede D, Dempewolf J, Klemmt H-J, Endres E, Seifert T (2024) Towards operational UAV-based forest health monitoring: Species identification and crown condition assessment by means of deep learning. Comput. Electron. Agric., 219: 108785. https://doi.org/10.1016/j.compag.2024.108785
- Morhart C, Schindler Z, Frey J, Sheppard JP, Calders K, Disney M, Morsdorf F, Raumonen P, Seifert, T (2024) Limitations of estimating branch volume from terrestrial laser scanning. European Journal of Forest Research. https://doi.org/10.1007/s10342-023-01651-z
- Mosig, C., Vajna-Jehle, J., Mahecha, M. D., Cheng, Y., Hartmann, H., Montero, D., Junttila, S., Horion, S., Adu-Bredu, S., Al-Halbouni, D., Allen, M., Altman, J., Angiolini, C., Astrup, R., Barrasso, C., Bartholomeus, H., Brede, B., Buras, A., Carrieri, E., Göritz, A., Gassilloud, M., Fabi, M., … Kattenborn, T. (2024). deadtrees.earth – An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics. bioRxiv. https://doi.org/10.1101/2024.10.18.619094
- Schiefer, F., Schmidtlein, S., Hartmann, H., Schnabel, F., Kattenborn, T. (2024) Large-scale remote sensing reveals that tree mortality in Germany appears to be greater than previously expected, Forestry: An International Journal of Forest Research, cpae062, https://doi.org/10.1093/forestry/cpae062
- Soltani, S., Ferlian, O., Eisenhauer, N., Feilhauer, H., & Kattenborn, T. (2024). From simple labels to semantic image segmentation: leveraging citizen science plant photographs for tree species mapping in drone imagery. Biogeosciences, 21(11), 2909-2935. doi: https://doi.org/10.5194/bg-21-2909-2024
2023
- Ouaknine, A., Kattenborn, T., Laliberté, E., & Rolnick, D. (2023). OpenForest: A data catalogue for machine learning in forest monitoring. arXiv preprint arXiv:2311.00277. doi: https://doi.org/10.48550/arXiv.2311.00277
- Schiefer, F., Schmidtlein, S., Frick, A., Frey, J., Klinke, R., Zielewska-Büttner, K., … & Kattenborn, T. (2023). UAV-based reference data for the prediction of fractional cover of standing deadwood from Sentinel time series. ISPRS Open Journal of Photogrammetry and Remote Sensing, 8, 100034. doi: https://doi.org/10.1016/j.ophoto.2023.100034