Towards robust vegetation indices: The multi-correlation matrix strategy. - Helge Aasen; Martin Leon Gnyp; Yuxin Miao; Georg Bareth (WHISPERS, 2014)

Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley. - Juliane Bendig; Kang Yu; Helge Aasen; Andreas Bolten; Simon Bennertz; Janis Broscheit; Martin L. Gnyp; Georg Bareth (Int. J. Appl. Earth Obs. Geoinformation, 2015)

Angular Dependency of Hyperspectral Measurements over Wheat Characterized by a Novel UAV Based Goniometer. - Andreas Burkart; Helge Aasen; Luis Alonso 002; Gunter Menz; Georg Bareth; Uwe Rascher (Remote. Sens., 2015)

Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass. - Nora Tilly; Helge Aasen; Georg Bareth (Remote. Sens., 2015)

Correction: Tilly, N. et al. Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass. Remote Sens. 2015, 7, 11449-11480. - Nora Tilly; Helge Aasen; Georg Bareth (Remote. Sens., 2015)

The acquisition of Hyperspectral Digital Surface Models of crops from UAV snapshot cameras - Helge Aasen (2016)

Soybean Leaf Coverage Estimation for Field-Phenotyping. - Kevin Keller; Raghav Khanna; Norbert Kirchgeßner; Roland Siegwart; Achim Walter; Helge Aasen (BMVC, 2018)

UAV Spectroscopy: Current Sensors, Processing Techniques and Theoretical Concepts for Data Interpretation. - Helge Aasen (IGARSS, 2018)

Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows. - Helge Aasen; Eija Honkavaara; Arko Lucieer; Pablo J. Zarco-Tejada (Remote. Sens., 2018)

Sun-Induced Chlorophyll Fluorescence II: Review of Passive Measurement Setups, Protocols, and Their Application at the Leaf to Canopy Level. - Helge Aasen; Shari Van Wittenberghe; Neus Sabater; Alexander Damm; Yves Goulas; Sebastian Wieneke; Andreas Hueni; Zbynek Malenovský; Luis Alonso 002; Javier Pacheco-Labrador; Maria Pilar Cendrero Mateo; Enrico Tomelleri; et al. (Remote. Sens., 2019)

Sun-Induced Chlorophyll Fluorescence III: Benchmarking Retrieval Methods and Sensor Characteristics for Proximal Sensing. - Maria Pilar Cendrero Mateo; Sebastian Wieneke; Alexander Damm; Luis Alonso 002; Francisco Pinto; José F. Moreno; Luis Guanter; Marco Celesti; Micol Rossini; Neus Sabater; Sergio Cogliati; Tommaso Julitta; et al. (Remote. Sens., 2019)

Sun-Induced Chlorophyll Fluorescence I: Instrumental Considerations for Proximal Spectroradiometers. - Javier Pacheco-Labrador; Andreas Hueni; Laura Mihai; Karolina Sakowska; Tommaso Julitta; Joel Kuusk; Dan Sporea; Luis Alonso 002; Andreas Burkart; Maria Pilar Cendrero Mateo; Helge Aasen; Yves Goulas; et al. (Remote. Sens., 2019)

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. - Etienne David; Simon Madec; Pouria Sadeghi-Tehran; Helge Aasen; B. Zheng; Shouyang Liu; Norbert Kirchgeßner; Goro Ishikawa; Koichi Nagasawa; Minhajul A. Badhon; Curtis Pozniak; Benoit de Solan; et al. (CoRR, 2020)

Current Practices in UAS-based Environmental Monitoring. - Goran Tmusic; Salvatore Manfreda; Helge Aasen; Mike R. James; Gil Gonçalves 001; Eyal Ben-Dor; Anna Brook; Maria Polinova; José Juan Arranz; János Mészáros; Ruodan Zhuang; Kasper Johansen; et al. (Remote. Sens., 2020)

Global Wheat Head Dataset 2021: an update to improve the benchmarking wheat head localization with more diversity. - Etienne David; Mario Serouart; Daniel Smith; Simon Madec; Kaaviya Velumani; Shouyang Liu; Xu Wang; Francisco Pinto Espinosa; Shahameh Shafiee; Izzat S. A. Tahir; Hisashi Tsujimoto; Shuhei Nasuda; et al. (CoRR, 2021)

Crop Nitrogen Retrieval Methods for Simulated Sentinel-2 Data Using In-Field Spectrometer Data. - Gregor Perich; Helge Aasen; Jochem Verrelst; Francesco Argento; Achim Walter; Frank Liebisch (Remote. Sens., 2021)

Using high-resolution drone data to assess apparent agricultural field heterogeneity at different spatial resolutions. - Quirina Noëmi Merz; Achim Walter; Helge Aasen (GIL Jahrestagung, 2022)

EOdal: An open-source Python package for large-scale agroecological research using Earth Observation and gridded environmental data. - Lukas Graf 002; Gregor Perich; Helge Aasen (Comput. Electron. Agric., 2022)

Propagating Sentinel-2 Top-of-Atmosphere Radiometric Uncertainty Into Land Surface Phenology Metrics Using a Monte Carlo Framework. - Lukas Valentin Graf; Javier Gorroño; Andreas Hueni; Achim Walter; Helge Aasen (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023)

LoRA-Ensemble: Efficient Uncertainty Modelling for Self-attention Networks. - Michelle Halbheer; Dominik J. Mühlematter; Alexander Becker; Dominik Narnhofer; Helge Aasen; Konrad Schindler; Mehmet Ozgur Turkoglu (CoRR, 2024)

In-season forecasting of within-field grain yield from Sentinel-2 time series data. - Eatidal Amin; Luca Pipia; Santiago Belda; Gregor Perich; Lukas Valentin Graf; Helge Aasen; Shari Van Wittenberghe; José F. Moreno; Jochem Verrelst (Int. J. Appl. Earth Obs. Geoinformation, 2024)

Model-Agnostic, Temperature-Informed Sampling Enhances Cross-Year Crop Mapping with Deep Learning. - Mehmet Ozgur Turkoglu; Selene Ledain; Helge Aasen (CoRR, 2025)