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 | 1243 | 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 | 563 | 2018 |
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 | 536 | 2015 |
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 | 231 | 2015 |
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 | 222 | 2020 |
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 | 215 | 2020 |
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 | 176 | 2015 |
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 | 143 | 2015 |
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 | 114 | 2020 |
Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review K Berger, M Machwitz, M Kycko, SC Kefauver, S Van Wittenberghe, ... Remote sensing of environment 280, 113198, 2022 | 113 | 2022 |
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 | 111 | 2018 |
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 | 97 | 2021 |
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 | 97 | 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 | 95 | 2016 |
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 | 80 | 2019 |
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 | 76 | 2019 |
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 | 66 | 2020 |
PhenoFly Planning Tool: flight planning for high-resolution optical remote sensing with unmanned areal systems L Roth, A Hund, H Aasen Plant methods 14, 1-21, 2018 | 56 | 2018 |
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 | 43 | 2020 |
Sun-induced chlorophyll fluorescence I: Instrumental considerations for proximal spectroradiometers J Pacheco-Labrador, A Hueni, L Mihai, K Sakowska, T Julitta, J Kuusk, ... Remote Sensing 11 (8), 960, 2019 | 40 | 2019 |