The study of orbital dynamics and evolution of Solar system small-bodies like asteroids has been conducted regularly with the latest data to ensure and update our understanding of the object’s motion, especially the ones located nearby the Earth. One of its examples is asteroid 469219 Kamo’oalewa, which currently known as an Earth Quasi-satellite (QS). In this article, we investigate the orbital dynamics of 469219 Kamo’oalewa by running an N-body numerical integration. It was calculated from its latest orbital solution at epoch JD 2458600.5 using Gauss-Radau scheme provided by IAS15 integrator, which available on REBOUND code package. We found that the co-orbital motion of the asteroid towards Earth happens during time interval (–19.7,19.5) thousand years, with QS–HS transition happening at that period. The current QS motion started 15 years ago and will be transitioning to HS at around 50 years from now. After losing its current state, it will orbit the Sun near the Earth as an Apollo asteroid. We also investigated the secular evolution of this asteroid and found the result that support its QS–HS transition nature. On some occasions like a long period of HS, we found several orbital characteristics that resemble Kozai–Lidov resonance, but it doesn’t hold long before the transition to QS resumes.

Night sky brightness (NSB) research related to the artificial light pollution issues has been increasing all over the world, using various measurement techniques and tools. The research produces tens of thousands of data for each month such that proper handling, processing and analysing the data become challenging. In this article, we demonstrate an alternative method for processing the NSB data by utilising pattern recognition techniques: Canny edge detection and Hough transform. These techniques were applied to identify data and extract important parameter from the NSB density plot semi-automatically. Datasets collected from Bandung, Garut, Subang and Sumedang used as the test cases. Three time-segments (dusk, night and dawn) became the main focus of the analyses and our method successfully extracted following parameters: the rate of sky brightness change at dusk and dawn, the average NSB at night and the intersections which indicate transition time. This method, along with its many possible improvements, enables us to process data more effectively and encourage more observation campaigns to be conducted in the future.