| Deep learning based 3D point cloud regression for estimating forest biomass S Oehmcke, L Li, JC Revenga, T Nord-Larsen, K Trepekli, F Gieseke, ... Proceedings of the 30th International Conference on Advances in Geographic …, 2022 | 25 | 2022 |
| Multiple-line identification of socio-ecological stressors affecting aquatic ecosystems in semi-arid countries: implications for sustainable management of fisheries in sub … VP Sanon, P Toé, J Caballer Revenga, H El Bilali, LJ Hundscheid, ... Water 12 (6), 1518, 2020 | 20 | 2020 |
| Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods JC Revenga, K Trepekli, S Oehmcke, R Jensen, L Li, C Igel, FC Gieseke, ... Remote Sensing 14 (16), 3912, 2022 | 19 | 2022 |
| Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR S Oehmcke, L Li, K Trepekli, JC Revenga, T Nord-Larsen, F Gieseke, ... Remote Sensing of Environment 302 (113968), 2024 | 6 | 2024 |
| Prediction of above ground biomass and C-stocks based on UAV-LiDAR, multispectral imagery and machine learning methods. J Caballer Revenga, K Trepekli, S Oehmcke, F Gieseke, C Igel, R Jensen, ... EGU General Assembly Conference Abstracts, EGU21-15708, 2021 | 2 | 2021 |
| Independent estimates of carbon stocks in croplands: UAV-LiDAR and machine learning vs. eddy-covariance JC Revenga, K Trepekli, R Jensen, PS Rummel, T Friborg EarthArxiv (preprint), 2023 | | 2023 |
| Contextual learning improves forest above-ground biomass estimates from UAV-LiDAR: use of tree trait associations JC Revenga, S Oehmcke, M Gharun, F Sutter, K Trepekli, F Gieseke, ... www.eartharxiv.org, 2023 | | 2023 |
| Forest structure analysis and above-ground biomass prediction in a European temperate forest via UAV-LiDAR, DL methods and spatial statistics. JC Revenga, S Oehmcke, M Gharun, K Trepekli, FC Gieseke, ... American Geoscience Union Fall Meeting 2022, 2022 | | 2022 |
| Plant Structure and Carbon Storage Assessment Utilizing Drone-Borne Lidar and Deep Learning Technologies in a Danish Agricultural Expanse. K Trepekli, JC Revenga, S Oehmcke, F Gieseke, R Jensen, T Friborg Authorea Preprints, 2022 | | 2022 |
| Linking UAV-LiDAR derived C-stocks and C uptake at the ecosystem level JC Revenga, K Trepekli, AS vby, SN rtoft, EF Giraldi, T Friborg ICOS Science Conference 2022, 2022 | | 2022 |
| Plant Structure and Carbon Storage Assessment Utilizing Drone-Borne Lidar and Deep Learning Technologies in a Danish Agricultural Expanse. JC Revenga, K Trepekli, S Oehmcke, FC Gieseke, R Jensen, T Friborg AGU Fall Meeting Abstracts 2020, B081-0013, 2020 | | 2020 |
Stefan OehmckeUniversity of CopenhagenVerified email at di.ku.dk
