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Satellite_Detection

This is the repository for the analysis of satellite trails in Hubble images in the ESA summer project "The impact of megaconstellations on space astronomy".

  1. Zooniverse_Data.ipynb: Transforms the results from Zooniverse into training data for the machine learning algorithms.
  2. Hubble_Image_Download.ipynb: Downloads all the raw Hubble Archive Images that make up the composite images for the three instruments ACS/WFC, WFC3/UVIS and WFC3/IR and saves them in the format 600x600px.
  3. Image_Classifier.ipynb (Machine Learning algorithm 1): Makes binary predictions "satellite"/"no_satellite" on a given Hubble image.
  4. Mask_R-CNN_Satellites.ipynb (Machine Learning algorithm 2): Detects start/end point and the angle of a satellite trail on a given Hubble image with a satellite trail.
  5. Analysis.ipynb: Resulting analysis script for the raw images. Creates plots showing the time evolution of the fraction and the chance for a satellite trail as well as the fraction for the different filters.