GLOS, M. Pokročilý systém pro identifikaci podpovrchových lunárních dutin [online]. Brno: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. 2025.
Mr. Glos’s thesis focuses on the identification of potential locations of subsurface cavities on the Moon. At the core of his work is the development of a Python-based software framework designed for retrieving and re-projecting raw data collected by various space missions, utilizing SPICE kernels. The resulting tool is well-automated, supports parallel processing, and significantly reduces data acquisition time. The code achieves a professional level of quality and has been published on the GitHub platform, including comprehensive documentation. This framework was applied to acquire and process data for approximately 400 known lunar pits, using observations from three scientific missions spanning the period from July 2009 to December 2024. Specifically, data from DIVINER (radiometric thermal measurements), LOLA (Lunar Orbiter Laser Altimeter for meter-scale topography), and Mini-RF (dual-band synthetic aperture radar) were retrieved and analyzed. While the relatively low resolution of the DIVINER and LOLA instruments limits their effectiveness for detecting subsurface anomalies, the radar-based Mini-RF data analysis yielded promising results. The thesis is written to a high stylistic and formal standard, with appropriate citation of all relevant sources. Mr. Glos regularly consulted with his supervisor in weekly meetings and addressed arising challenges with independence and innovative thinking. The thesis fully meets the objectives of a technically demanding and ambitious assignment, and I confidently recommend it for defense.
The provided thesis, titled “Advanced System for Identification of Subsurface Cavities in Lunar Pits,” focuses on the detection of potential subsurface cavities in the vicinity of lunar pits. For this purpose, the student developed a custom Python-based framework built on NASA’s SPICE kernels. Both the conceptual design and the implementation quality of the code is on very high level. The student demonstrates a deep understanding of several interdisciplinary fields, including planetary science, remote sensing, and modern software engineering. In particular, the quality of the provided code is something I would like to point out. Student uses a huge variety of tools (Docker, Celery, Redis..) as well as modern design patterns, proving his high skills in the software development. I have several comments on the work, mainly formally ones : - The list of abbreviations is missing. The thesis contains a large number of acronyms (where some of them are not explained at all. which can make the text harder to follow for readers. - The text itself of the thesis is quite long and some of the theoretical chapters (i.e 2.6) could be reduced or deleted completely. - The description of the instruments and used datasets should be done in the early chapters rather than being introduced close to the Summary. - In Chapter 6.2, the student focuses on describing the detection of lunar pits rather than discussing anomaly detection strategies. It's unclear why this shift in focus was made since the location of the lunar pits, are known. - It is unclear why student replaced the gravitational data by altimeter data obtained by LOLA instrument. Despite the stated shortcomings, student proved extensive skills and knowledge across different disciplines as well as an ability to develop a professional software therefore I recommend this thesis for a defence with 98/A.
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