Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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Fundamental Research on Spring Season Daytime Sea Fog Detection Using MODIS in the Yellow Sea

  • Jeon, Joo-Young (Department of Convergence Study on the Ocean Science and Technology, Ocean Science and Technology School (OST)) ;
  • Kim, Sun-Hwa (Marine Safety Research Center, Korea Institution of Ocean Science and Technology (KIOST)) ;
  • Yang, Chan-Su (Department of Convergence Study on the Ocean Science and Technology, Ocean Science and Technology School (OST))
  • Received : 2016.05.04
  • Accepted : 2016.06.14
  • Published : 2016.08.31
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Abstract

For the safety of sea, it is important to monitor sea fog, one of the dangerous meteorological phenomena which cause marine accidents. To detect and monitor sea fog, Moderate Resolution Imaging Spectroradiometer (MODIS) data which is capable to provide spatial distribution of sea fog has been used. The previous automatic sea fog detection algorithms were focused on detecting sea fog using Terra/MODIS only. The improved algorithm is based on the sea fog detection algorithm by Wu and Li (2014) and it is applicable to both Terra and Aqua MODIS data. We have focused on detecting spring season sea fog events in the Yellow Sea. The algorithm includes application of cloud mask product, the Normalized Difference Snow Index (NDSI), the STandard Deviation test using infrared channel ($STD_{IR}$) with various window size, Temperature Difference Index(TDI) in the algorithm (BTCT - SST) and Normalized Water Vapor Index (NWVI). Through the calculation of the Hanssen-Kuiper Skill Score (KSS) using sea fog manual detection result, we derived more suitable threshold for each index. The adjusted threshold is expected to bring higher accuracy of sea fog detection for spring season daytime sea fog detection using MODIS in the Yellow Sea.

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