Borncamp David

Abstract Reference: 31061
Identifier: P6.3
Presentation: Poster presentation
Key Theme: 6 Python in Astronomy

Satellite Detection in Advanced Camera for Surveys/Wide Field Channel Images

Authors:
Borncamp David, Lim Pey Lian

We present a novel process by which satellite trails can be detected and accurately masked within individual chips of an Advanced Camera for Surveys (ACS) Wide Field Channel (WFC) image using Python. Since satellites are transient and sporadic events, we used the Hubble Frontier Fields (HFF) dataset which is manually checked for satellite trails has been used as a truth set to verify that the method in this document does a complete job without a high false positive rate.  We also present the process of producing a mask that will update data quality information to inform users where the trail traverses the image and properly account for the affected pixels.  This code is now publicly available through the acstools (https://acstools.readthedocs.io/en/latest/) package and can be installed through the astroconda (http://astroconda.readthedocs.io/en/latest/) anaconda channel.