• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• Journal of Environmental Science International
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• v.22 no.6
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• pp.745-759
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• 2013

The characteristics of meteorological conditions and air pollution were investigated in a valley city (Yangsan) on bad visibility days (from 05:00 to 09:00 LST) of the cold half year (November 2008 to April 2009). This analysis was performed using the hourly observed data of meteorological variables (temperature, wind speed and direction, relative humidity, and 2 m and 10 m temperature) and air pollutants ($NO_2$, $SO_2$, $PM_{10}$, and $O_3$). In addition, visibility data based on visual measurements and a visibility meter were used. The bad visibility days were classified into four types: fog, mist, haze, and the mixture (mist+haze). The results showed that the bad visibility days of the four types in the valley city were observed to be more frequently (about 50% of the total study period (99 days except for missing data)) than (27%) those near coastal metropolitan city (Busan). The misty days (39%) in the valley city were the most dominant followed by the hazy (37%), mixture (14%), and foggy days (10%). The visibility degradation on the misty days in Yangsan was closely related to the combined effect of high-level relative humidity due to the accumulation of water vapor from various sources (e.g. river, stream, and vegetation) and strong inversion due to the development of surface radiative cooling within the valley. On the hazy days, the visibility was mainly reduced by the increase in air pollutant (except for $O_3$) concentrations from the dense emission sources under local conditions of weaker winds from the day before and stronger inversion than the misty days. The concentrations of $NO_2$, $PM_{10}$, and $SO_2$ (up to +36 ppb, $+25{\mu}g/m^3$, and +7 ppb) on the hazy days were a factor of 1.4-2.3 higher than those (+25 ppb, $+14{\mu}g/m^3$, and +3 ppb) on the misty days.