Papers › CLOWN: The PASO cloud detection for optimization of automatic optical surveys
CLOWN: The PASO cloud detection for optimization of automatic optical surveys
Luís Gonçalves, Bruno Coelho, Domingos Barbosa, Miguel Bergano, Vitor Bonifácio, Dalmiro Maia
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
Orbiting space objects have become in the last decade a major nuisance impacting ground astronomy and orbiting space assets, from observatories to satellites and space stations. In particular with the rise of the satellite population in Low Earth Orbits (LEOs), space objects are becoming an even bigger threat and a strong problem to astronomical observations. To tackle these threats several coordinated surveillance networks composed of dedicated sensors (telescopes, radars and laser ranging facilities) track and survey space objects, from debris to active satellites. As part of the European Space Surveillance & Tracking (EU-SST) network, Portugal is developing the PAmpilhosa da Serra Space Observatory (PASO), with both radio and optical telescopes dedicated to the Space Situational Awareness (SSA) domain, deployed at a Dark Sky destination. To optimize telescope survey time, we developed {\tt{CLOWN}} (CLOud Watcher at Night), an application interface that automatically monitors clouds in real time. This software can correctly trace clouds positions in the sky, provides accurate pointing information to the observation planning of the optical telescope to avoid cloudy areas. {\tt{CLOWN}} only requires the use of an all-sky camera, which is already a norm in observatories with optical telescopes and can be used with any camera, including those for which no information about its model specification do exist. {\tt{CLOWN}} does not require great computing power and it does not require the installation of additional equipment. {\tt{CLOWN}} results are very promising and confirm that the app can correctly identify clouds in a variety of different conditions and cloud types.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections