Multi-satellite sea fog detection algorithm using COMS/GOCI and Himawari-8/AHI

Title
Multi-satellite sea fog detection algorithm using COMS/GOCI and Himawari-8/AHI
Author(s)
박명숙; 박영제; 김원국
KIOST Author(s)
Park, Myung Sook(박명숙)Park, Young Je(박영제)
Alternative Author(s)
박명숙; 박영제; 김원국
Publication Year
2018-02-11
Abstract
Sea fog is one of the most dangerous weather hazards that threaten coastal and marine areas. Since in situ observation of visibility is very limited on the sea, sea fog is more difficult to monitor its variability than land fog. Accordingly, sea fog retrieval from satellite has been considered a valuable information for monitoring the variability of the sea fog.
So far, lots of research have been done to develop an effective sea fog detection algorithm using satellite data. Dual channel difference (DCD) of infrared (IR) and near-infrared (NIR) channels is widely used in fog retrieval and IR channel is very useful in removing high-level clouds. However, DCD and IR tend to have large variability depending on surface temperature, while reflectance of visible channel is hypothesized to be relatively stable. In this study, therefore, VIS channel of GOCI and IR and NIR channels of Himawari-8 are used together to complement each other and maximize their own benefits. In addition, SST was used to compensate for variabilities of DCD and IR.
The most challenging part of the satellite-based sea fog detection is to separate fog from low-level cloud because both of them have very similar optical properties. To solve this problem, normalized local standard deviation (NLSD) of GOCI Rayleigh corrected reflectance (Rrc) is used as a pattern index because fog and cloud have different roughness pattern in the satellite image.
In t
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/23487
Bibliographic Citation
OSM 2018, pp.1, 2018
Publisher
AGU
Type
Conference
Language
English
Publisher
AGU
Related Researcher
Research Interests

Ocean Color Remote Sensing,Satellite Applications,Ocean color Algorithm,해양원격탐사,위성활용,해색 알고리즘

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