Woollands, R.; Rossi, F.; Stegun Vaquero, T.; Sanchez Net, M.; Bae, S. S.; Bickel, V.; Vander Hook, J.: Maximizing Dust Devil Follow-Up Observations on Mars Using Cubesats and On-Board Scheduling. Journal of the Astronautical Sciences 69, pp. 918 - 940 (2022)
Bickel, V. T.; Aaron, J.; Manconi, A.; Loew, S.: Global Drivers and Transport Mechanisms of Lunar Rockfalls. Journal of Geophysical Research: Planets 126 (10), e2021JE006824 (2021)
Bickel, V. T.; Mandrake, L.; Doran, G.: A Labeled Image Dataset for Deep Learning-Driven Rockfall Detection on the Moon and Mars. Frontiers in Remote Sensing 2, 640034 (2021)
Bickel, V. T.; Mandrake, L.; Doran, G.: Analyzing multi–domain learning for enhanced rockfall mapping in known and unknown planetary domains. ISPRS Journal of Photogrammetry and Remote Sensing 182, pp. 1 - 13 (2021)
Bickel, V. T.; Moseley, B.; Lopez-Francos, I.; Shirley, M.: Peering into lunar permanently shadowed regions with deep learning. Nature Communications 12, 5607 (2021)
Czaplinski, E. C.; Harrington, E. M.; Bell, S. K.; Tolometti, G. D.; Farrant, B. E.; Bickel, V. T.; Honniball, C. I.; Martinez, S. N.; Rogaski, A.; Sargeant, H. M.et al.; Kring, D. A.: Human-assisted Sample Return Mission at the Schrödinger Basin, Lunar Far Side, Using a New Geologic Map and Rover Traverses. The Planetary Science Journal 2 (2), 51 (2021)
Bickel, V. T.; Conway, S. J.; Tesson, P.-A.; Manconi, A.; Loew, S.; Mall, U.: Deep Learning-driven Detection and Mapping of Rockfalls on Mars. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13, pp. 2831 - 2841 (2020)
Moseley, B.; Bickel, V. T.; Burelbach, J.; Relatores, N.: Unsupervised Learning for Thermophysical Analysis on the Lunar Surface. The Planetary Science Journal 1, 32 (2020)
Sargeant, H. M.; Bickel, V. T.; Honniball, C. I.; Martinez, S. N.; Rogaski, A.; Bell, S. K.; Czaplinski, E. C.; Farrant, B. E.; Harrington, E. M.; Tolometti, G. D.et al.; Kring, D. A.: Using Boulder Tracks as a Tool to Understand the Bearing Capacity of Permanently Shadowed Regions of the Moon. Journal of Geophysical Research: Planets 125 (2), e2019JE006157 (2020)
Bickel, V. T.; Lanaras, C.; Manconi, A.; Loew, S.; Mall, U.: Automated Detection of Lunar Rockfalls Using a Convolutional Neural Network. IEEE Transactions on Geoscience and Remote Sensing 57 (6), pp. 3501 - 3511 (2019)
Bickel, V. T.; Manconi, A.; Amann, F.: Quantitative Assessment of Digital Image Correlation Methods to Detect and Monitor Surface Displacements of Large Slope Instabilities. Remote Sensing 10 (6), 865 (2018)
Moseley, B.; Bickel, V. T.; Lopez-Francos, I. G.; Rana, L.: Extreme Low-Light Environment-Driven Image Denoising Over Permanently Shadowed Lunar Regions With a Physical Noise Model. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6317 - 6327. (2021)
Burelbach, J.; Bickel, V. T.; Moseley, B.; Relatores, N. C.: NASA Frontier Development Lab: Lunar Resource Mapping - Data Fusion and AI-driven Anomaly Detection. Mining Space Summit 2019, Luxembourg, Luxembourg (2019)
Bickel, V. T.; Kring, D.A.: Lunar South Pole Boulders and Boulder Tracks: Implications for Crew and Rover Traverses. NASA Exploration Science Forum 2019, Mountain View, CA, USA (2019)
Takala, M.; Bickel, V. T.; Bambach, P.; Braun, H. M.; Pursiainen, S.: The Stepped Frequency GPR: A Proposal to investigate the Lunar Subsurface. EGU General Assembly 2019, Vienna, Austria (2019)
Application deadline 1 October 2024. PhD projects in planetary science, solar and stellar physics, solar magnetism, heliophysics, helioseismology, asteroseismology, ...
In analyzing solar observations from the 19th century, scientists are turning to amateur researchers for help. The project will allow to better understand the history of our star.
Astronomical teamwork: By combining data from Solar Orbiter and SDO, a group of researchers has unambiguously determined the magnetic field at the solar surface.
Application deadline 1 October 2023. PhD projects in planetary science, solar and stellar physics, solar magnetism, heliophysics, helioseismology, asteroseismology, ...
Philipp Löschl has co-authored an excellent publication on Solar Orbiter data which has been awarded best Solar Physics paper of 2022 (Gherardo Valori et al. 2022)