| Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley J Bendig, K Yu, H Aasen, A Bolten, S Bennertz, J Broscheit, ML Gnyp, ... International Journal of Applied Earth Observation and Geoinformation 39, 79-87, 2015 | 906 | 2015 |
| Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: From camera calibration to quality assurance H Aasen, A Burkart, A Bolten, G Bareth ISPRS Journal of Photogrammetry and Remote Sensing 108, 245-259, 2015 | 451 | 2015 |
| Quantitative remote sensing at ultra-high resolution with UAV spectroscopy: a review of sensor technology, measurement procedures, and data correction workflows H Aasen, E Honkavaara, A Lucieer, PJ Zarco-Tejada Remote Sensing 10 (7), 1091, 2018 | 423 | 2018 |
| Fusion of plant height and vegetation indices for the estimation of barley biomass N Tilly, H Aasen, G Bareth Remote Sensing 7 (9), 11449-11480, 2015 | 189 | 2015 |
| low-weight and UAV-based hyperspectral full-frame cameras for monitor-ing crops: spectral comparison with portable spectroradiometer measure-ments G Bareth, H Aasen, J Bendig, ML Gnyp, A Bolten, A Jung, R Michels, ... Unmanned aerial vehicles (UAVs) for multi-temporal crop surface modelling …, 2015 | 158 | 2015 |
| Current practices in UAS-based environmental monitoring G Tmušić, S Manfreda, H Aasen, MR James, G Gonçalves, E Ben-Dor, ... Remote Sensing 12 (6), 1001, 2020 | 143 | 2020 |
| Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high-resolution RGB-labelled images to develop and benchmark wheat head detection methods E David, S Madec, P Sadeghi-Tehran, H Aasen, B Zheng, S Liu, ... Plant Phenomics, 2020 | 138 | 2020 |
| Angular dependency of hyperspectral measurements over wheat characterized by a novel UAV based goniometer A Burkart, H Aasen, L Alonso, G Menz, G Bareth, U Rascher Remote sensing 7 (1), 725-746, 2015 | 122 | 2015 |
| Multi-temporal high-resolution imaging spectroscopy with hyperspectral 2D imagers–From theory to application H Aasen, A Bolten Remote sensing of environment 205, 374-389, 2018 | 87 | 2018 |
| Extracting leaf area index using viewing geometry effects—A new perspective on high-resolution unmanned aerial system photography L Roth, H Aasen, A Walter, F Liebisch ISPRS Journal of Photogrammetry and Remote Sensing 141, 161-175, 2018 | 76 | 2018 |
| A comparison of UAV-and TLS-derived plant height for crop monitoring: using polygon grids for the analysis of crop surface models (CSMs) G Bareth, J Bendig, N Tilly, D Hoffmeister, H Aasen, A Bolten Photogramm. Fernerkund. Geoinf 2016, 85-94, 2016 | 75 | 2016 |
| Spectral vegetation indices to track senescence dynamics in diverse wheat germplasm J Anderegg, K Yu, H Aasen, A Walter, F Liebisch, A Hund Frontiers in plant science 10, 1749, 2020 | 71 | 2020 |
| Sun-induced chlorophyll fluorescence II: review of passive measurement setups, protocols, and their application at the leaf to canopy level H Aasen, S Van Wittenberghe, N Sabater Medina, A Damm, Y Goulas, ... Remote Sensing 11 (8), 927, 2019 | 62 | 2019 |
| Sun-induced chlorophyll fluorescence III: Benchmarking retrieval methods and sensor characteristics for proximal sensing MP Cendrero-Mateo, S Wieneke, A Damm, L Alonso, F Pinto, J Moreno, ... Remote sensing 11 (8), 962, 2019 | 59 | 2019 |
| Global wheat head detection 2021: An improved dataset for benchmarking wheat head detection methods E David, M Serouart, D Smith, S Madec, K Velumani, S Liu, X Wang, ... Plant Phenomics, 2021 | 47 | 2021 |
| PhenoFly Planning Tool: flight planning for high-resolution optical remote sensing with unmanned areal systems L Roth, A Hund, H Aasen Plant methods 14 (1), 1-21, 2018 | 47 | 2018 |
| Assessment of multi-image unmanned aerial vehicle based high-throughput field phenotyping of canopy temperature G Perich, A Hund, J Anderegg, L Roth, MP Boer, A Walter, F Liebisch, ... Frontiers in plant science 11, 150, 2020 | 45 | 2020 |
| Introduction and preliminary results of a calibration for full-frame hyperspectral cameras to monitor agricultural crops with UAVs H Aasen, J Bendig, A Bolten, S Bennertz, M Willkomm, G Bareth ISPRS Technical Commission VII Symposium 40, 1-8, 2014 | 37 | 2014 |
| PhenoCams for field phenotyping: using very high temporal resolution digital repeated photography to investigate interactions of growth, phenology, and harvest traits H Aasen, N Kirchgessner, A Walter, F Liebisch Frontiers in plant science 11, 593, 2020 | 36 | 2020 |
| Feasibility study of using non-calibrated UAV-based RGB imagery for grassland monitoring: Case study at the Rengen Long-term Grassland Experiment (RGE), Germany G Bareth, A Bolten, J Hollberg, H Aasen, A Burkart, J Schellberg DGPF Tagungsband 24 (2015), 1-7, 2015 | 35 | 2015 |
