In the operation of robotic telescopes, ensuring equipment protection from adverse weather conditions and avoiding unproductive observations during heavy cloud cover are essential. Traditional methods of monitoring the sky for cloud typically involve IR cloud sensors that are prone to degradation and require regular calibration to provide reliable data. To address this, we propose a more sophisticated and reliable approach: comparing real-time zero-point values from astrometrically and photometrically calibrated all-sky images, provided by the ATLAS project, with a master reference zero-point map captured by the same system under ideal cloudless conditions to conduct a spatially resolved assessment of cloud cover across the entire visible sky. Currently, this method guides a basic decision of whether to observe or not. However, in the future, a more sophisticated approach could determine which sections of the sky are suitable for observation and limit observation requests to those specific areas.
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