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Developing the Cloud Detection Algorithm for COMS Meteorolgical Data Processing System

  • Chung, Chu-Yong (Remote Sensing Research Laboratory/Meteorological Research Institute, KMA) ;
  • Lee, Hee-Kyo (Remote Sensing Research Laboratory/Meteorological Research Institute, KMA) ;
  • Ahn, Hyun-Jung (Remote Sensing Research Laboratory/Meteorological Research Institute, KMA) ;
  • Ahn, Myoung-Hwan (Remote Sensing Research Laboratory/Meteorological Research Institute, KMA) ;
  • Oh, Sung-Nam (Remote Sensing Research Laboratory/Meteorological Research Institute, KMA)
  • Published : 2006.10.31

Abstract

Cloud detection algorithm is being developed as primary one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-IR and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithms and preliminary test results of both algorithms.

Keywords

References

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