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Algorithm for sea fog monitoring with the use of information technologies.

Authors :
Heo, Ki‐Young
Park, Suhyun
Ha, Kyung‐Ja
Shim, Jae‐Seol
Source :
Meteorological Applications. Apr2014, Vol. 21 Issue 2, p350-359. 10p.
Publication Year :
2014

Abstract

Sea fog occurs frequently around the Korean Peninsula during April to July and is considered a major marine meteorological disaster, causing serious transport accidents and socioeconomic losses. Fog-related marine accidents represent 29.5% of the total marine accidents in Korea, which mainly occur along domestic ship routes during night time. In this study, an algorithm for sea fog monitoring using information technologies was developed to reduce fog-related marine accidents and to manage marine transportation, offshore and coastal fisheries, and naval operations. A dual channel difference (DCD) method using the 3.9 and 10.8 µm channels and texture-related measurements from the Multi-functional Transport Satellite (MTSAT) is applied to detect sea fog. To delineate the probable area of sea fog, the threshold value of − 2.0 K on the DCD is regarded as an indication of areas of sea fog and low cloud. A Laplacian calculation of the 10.8 µm brightness temperature is proposed as the texture-related measurement for sea fog. The threshold value of the Laplacian calculation is 0.1. An algorithm based on a combination of information technology (IT)-based navigation and sea fog detection technologies was developed to provide warnings to sea-going ships that may encounter fog-related danger. The algorithm checks the geometric relationship between the detected sea fog area and parameters related to the ship, such as its current position, sailing direction and speed, and sailing route. If the algorithm determines that the ship may be in danger, a warning is provided to the ship and a change of route is recommended. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13504827
Volume :
21
Issue :
2
Database :
Academic Search Index
Journal :
Meteorological Applications
Publication Type :
Academic Journal
Accession number :
95663134
Full Text :
https://doi.org/10.1002/met.1344