Cloud Mask Intercomparison eXercise (CMIX): An evaluation of cloud masking algorithms for Landsat 8 and Sentinel-2

Cloud cover is a major limiting factor in exploiting time-series data acquired by optical spaceborne remote sensing sensors. Multiple methods have been developed to address the problem of cloud detection in satellite imagery and a number of cloud masking algorithms have been developed for optical sensors but very few studies have carried out quantitative intercomparison of state-of-the-art methods in this domain. This paper summarizes results of the first Cloud Masking Intercomparison eXercise (CMIX) conducted within the Committee Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV). CEOS is the forum for space agency coordination and cooperation on Earth observations, with…

• NA
  National Aeronautics and Space Administration

  Award: 80NSSC19M0222
• UD
  Universitat de València
• NS
  Nuclear Safety and Security Commission
• MD
  Ministerio de Ciencia e Innovación

  Awards: PID2019, PID2019-109026RB-I00
• GS
  Goddard Space Flight Center
• ER
  European Regional Development Fund