Philipp Koyan, M.Sc.
Dr. Philipp Koyan
Applied Geophysics
Scientific Staff
Campus Golm
Building 27, Room 0.35
Karl-Liebknecht-Str. 24-25
14476 Potsdam-Golm
CV
2012-2015 | B.Sc., Geosciences (Universität Potsdam) |
2015-2018 | M.Sc., Geosciences (Universität Potsdam) |
2018-2023 | Doctoral Student, Applied Geophysics (Universität Potsdam) |
2023-present | Scientific Staff, Applied Geophysics (Universität Potsdam) |
Research
In my research, I focus on the analysis of both synthetic and field 2D/3D ground-penetrating radar (GPR) data aquired across sedimentary systems. Typically, such data are interpreted in a manual and thus time-consuming and barely reproducible manner. Hence, the scope of this project is to analyze and classify data attributes in order to interpret the data by generating 2D/3D GPR facies models of sedimentary systems.
Publications
https://orcid.org/0000-0002-3647-7260
Peer-reviewed Journal Articles
Koyan, P., Tronicke, J., 2024: 3D ground-penetrating radar data analysis and interpretation using attributes based on the gradient structure tensor. Geophysics. doi: https://doi.org/10.1190/geo2023-0670.1.
Allroggen, N., Heincke, B.H., Koyan, P., Wheeler, W., Rønning, J.S., 2022: 3D ground-penetrating radar attribute classification: A case study from a paleokarst breccia pipe in the Billefjorden area on Spitsbergen, Svalbard. Geophysics. doi: https://doi.org/10.1190/geo2021-0651.1
Koyan, P., Tronicke, J., Allroggen, N, 2021: 3D ground-penetrating radar attributes to generate classified facies models: A case study from a dune island. Geophysics. doi: https://doi.org/10.1190/geo2021-0204.1. Featured in: Behura, J., 2022: Geophysics Bright Spots. The Leading Edge. doi: https://doi.org/10.1190/tle41010062.1.
Koyan, P., Tronicke, J., 2020: 3D modeling of ground-penetrating radar data across a realistic sedimentary model. Computers and Geosciences. doi: https://doi.org/10.1016/j.cageo.2020.104422.
Conference Proceedings
Koyan, P., Guillemoteau, J., Klose, T., and Tronicke, J., 2024: 3D ground-penetrating radar to characterize near-surface environments: Advances in data analysis and integrated geophysical interpretation. In: EGU General Assembly 2024, Vienna. doi: https://doi.org/10.5194/egusphere-egu24-3588
Rulff, P., Castillo-Reyes, O., Koyan, P., Martin, T., Deleersnyder, W., and Carrizo Mascarell, M., 2024: Geoelectrical and electromagnetic imaging methods applied to groundwater systems: recent advances and future potentials. In: EGU General Assembly 2024, Vienna. doi: https://doi.org/10.5194/egusphere-egu24-654
Koyan, P., Tronicke, J., Klose, T., Guillemoteau, J., 2023: 3D GPR to explore peat deposits: Strategies for data acquisition, processing, and interpretation. In: 12th International Workshop on Advanced Ground Penetrating Radar, Lisbon. doi: 10.1109/IWAGPR57138.2023.10329077.
Klose, T., Guillemoteau, J., Vignoli, G., Koyan, P., Walter, J., Herrmann, A., Tronicke, J., 2023: Structurally-constrained FD-EMI data inversion using a Minimum Gradient Support (MGS) regularization. In: EGU General Assembly 2023, Vienna. doi: https://doi.org/10.5194/egusphere-egu23-7067.
Koyan, P., Tronicke, J., 2023: The gradient structure tensor (GST): An efficient tool to analyze 3D GPR data for archaeological prospection. In: 15th International Conference of Archaeological Prospection, Kiel. doi: 10.38072/978-3-928794-83-1/p86.
Koyan, P., Tronicke, J., 2022: 3D Classified GPR Facies Models from Multi-frequency Data Volumes: A Synthetic Study. In: 19th International Conference On Ground Penetrating Radar (GPR), Golden, Colorado. doi: https://doi.org/10.1190/gpr2022-042.1.
Koyan, P., Tronicke, J., 2020: Analyzing 3D multi-frequency ground-penetrating radar (GPR) data simulated across a realistic sedimentary model. In: 18th International Conference On Ground Penetrating Radar (GPR), Golden, Colorado. doi: https://doi.org/10.1190/gpr2020-073.1.
J. Tronicke, Koyan, P., Allroggen, N., 2020. The redundant wavelet transform to process and interpret GPR data. In: 18th International Conference On Ground Penetrating Radar (GPR), Golden, Colorado. doi: https://doi.org/10.1190/gpr2020-104.1.
Koyan, P., Tronicke, J., Allroggen, N., Kathage, A., Willmes, M., 2018. Estimating moisture changes in concrete using GPR velocity analysis: potential and limitations. In: 17th International Conference On Ground Penetrating Radar (GPR), Rapperswil (CH). doi: 10.1109/ICGPR.2018.8441572.
Guillemoteau, J., Koyan, P., Tronicke, J., 2017: Processing of Densely Sampled Electromagnetic Induction Data Collected across Peat Deposits. In: 23rd European Meeting of Environmental and Engineering Geophysics, Malmö (Sweden). doi: https://doi.org/10.3997/2214-4609.201701983.
Data sets
Koyan, P., Tronicke, J., 2019. A synthetic 3D ground-penetrating radar (GPR) data set across a realistic sedimentary model. Mendeley Data. doi: http://dx.doi.org/10.17632/by3yh79hx4.1.
Invited Talks
Koyan, P., 2020. 3D GPR data simulated across a realistic sedimentary model: Modelling, analyses and applications. (Online Workshop on Ground-Penetrating Radar modelling using gprMax, Newcastle upon Tyne 2020). link: https://www.youtube.com/watch?v=sw5zncmyKU0
Teaching
- GEW-B-WP05/7 - Vertiefung Geophysik I/III - Angewandte Geophysik für Fortgeschrittene, B. Sc.
- GEW-B-P14 - Grundlagen der Angewandten Geophysik (Feldpraktikum), B. Sc
- GEW-MC07 - Geophysical Laboratory, M. Sc.
- GEW-MF14 - Applied Geophysics Field Course, M. Sc.
Supervised Theses
Julia Berger: Potential und Limitationen des GPR-Verfahrens bei bodenkundlichen Fragestellungen anhand eines ausgewählten Feldstandortes in Groß Kreutz (Brandenburg), M.Sc. Thesis, 2024