UNIVERSITY OF BUCHAREST
FACULTY OF PHYSICS

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2024-11-23 2:09

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Conference: Bucharest University Faculty of Physics 2023 Meeting


Section: Atmosphere and Earth Science; Environment Protection


Title:
Satellite mega constellations: operational risks and impact on astronomic ground-based observation


Authors:
Cristian OMAT (1), Mirel BIRLAN (2)


*
Affiliation:
1) University of Bucharest, Faculty of Physics, 405 Atomistilor Street, 077125 Măgurele, Ilfov, Romania

2) Astronomical Institute of the Romanian Academy, 5 Cuțitul de Argint Street, 052034 Bucharest, Romania


E-mail
cristian.omat@astro.ro


Keywords:
Starlink, LEO, satellite, SpaceX, mega constellations, operational risks, astronomy, ground-based observations


Abstract:
More than half of the active satellites currently on Low Earth Orbits (LEO) belong to the Starlink mega-constellation. Many more satellites are to come, while just 10% of the scheduled Starlink satellites have been launched on their operational orbits, and more than 40,000 slots are reserved by the Starlink owner company. This unprecedented agglomeration of LEO is just at the beginning, the scientific community prediction is that until year 2030 up to 100,000 satellites are to be deployed in low Earth orbits, clustered in several mega-constellations. This will tremendously increase the orbital maneuvers, potential collisions on orbits and consequently the number of space debris. Beside this, problems for the worldwide astronomical community regarding ground-based observations should be immediately accounted. The presentation analyzes the stage of the configuration of the Starlink mega-constellation and refers the measures taken by the operator SpaceX in regards to one of the major concerns - reducing the harmful effects of the reflection of sunlight by satellites. A synthesis of several relevant scientific articles that present different methods of evaluating the impact of these satellites on astronomical observations and also their solutions is presented. These aspects will be treated in two Deep Learning methods for automatic classification of images affected by satellites, images from the Hubble Space Telescope archive. The presentation will focus also on the planed scientific activities on this subject in Romania and more specifically in the Astronomical Institute of the Romanian Academy.


Acknowledgement:
Astronomical Institute of the Romanian Academy