• Journal of the Korean association of regional geographers
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• v.22 no.4
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• pp.856-874
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• 2016

This study aims to figure out the weather and climate environment of Seoul area in S. Korea during 1623~1800, which has not been studied so far, by using daily records of weather conditions and meteorological phenomena in the Daily Records of Royal Secretariat of Joseon Dynasty(承政院日記) together with records of abnormal weather conditions and natural disasters in the Annals of the Joseon Dynasty(朝鮮王朝實錄). During 1500~1760 as a period of the Little Ice Age it was generally cold and dry, particularly cool summers of Seoul area. Changes in weather conditions and meteorological phenomena and climate changes appeared prominently at around 1650, 1710, 1770. The annual numbers of rain days and of snow days began to change largely in the 1640s. The rain(and snow) days reduced significantly in the 1710s~1650s, but increased sharply in the 1710s and later. The rain days in summer rapidly increased after the late 1710s, while the snow days greatly reduced after the mid 1770s. The cloudy days around the 1710s greatly reduced in summer, while slightly increased in winter. The hail days increased significantly in the late 1720s and lasted until the 1760s. The fog days began to reduce after 1770 to the fewer days than the climatic normals of 1981~2010. These times are overall consistent with findings of historical climatological cross-checking data and geophysical biological proxy data, accompanied by a trend of relatively enhanced colder and drier of Seoul area.

• Journal of Environmental Impact Assessment
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• v.13 no.4
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• pp.197-211
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• 2004

Visibility impairment was known as an indicator of the increased air pollution. In many previous studies, it is known that both directly emitted fine particles mainly from vehicles and secondary aerosols from photochemical reactions could contribute to this visibility impairment in addition to the meteorological condition. Furthermore, the visibility showed different change patterns according to the geographical condition. In order to research into the influence of these factors on visibility, this study analyzed the visibility at 15:00, observed from 1990 to 2001 in Seoul, Ganghwa, Susan, Gwangju, Jeju. As a result, the visibility was increased in Seoul except the rainfall period, but in Susan, Gwangju, Jeju, it decreased with the relative humidity (RH). Especially, in Seoul, the number of low visibility days was larger than other sites and variations of the visibility were sensitive to the concentration of air pollutants, such as TSP, $NO_2$, $O_3$. The visibility impairment was mainly observed in meteorological condition of RH<50% and relatively stationary front. Therefore it is inferred that photochemical smog could lead to the low visibility in Seoul. On the other hands, in Ganghwa and Susan, when RH was 60~70%, the low visibility observed under the influence of the transports of air pollutants from nearby cities as well as humid air mass from coastal region. And in Jeju, sea fog and humid air mass caused the visibility impairment when the RH was larger than 80%. Finally, during the observational period, some cases of low visibility phenomena were simultaneously observed in the vast region including Seoul, Susan, Ganghwa. It not only includes the visibility aggravation by Asian Dust, but also could be caused by the movement and diffusion of flying dust or secondary aerosols. Moreover, the result shows that these phenomena could be mainly influenced by meteorological factors covering the wide regions.

• Journal of Environmental Science International
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• v.27 no.11
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• pp.1129-1140
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• 2018

Temporal and spatial characteristics of the frequency of several weather types and the change in air pollutant concentrations according to these weather types were analyzed over a decade (2007-2016) in seven major cities and a remote area in Korea. This analysis was performed using hourly (or daily) observed data of weather types (e.g., mist, haze, fog, precipitation, dust, and thunder and lighting) and air pollutant criteria ($PM_{10}$, $PM_{2.5}$, $O_3$, $NO_2$, CO, and $SO_2$). Overall, the most frequent weather type across all areas during the study period was found to be mist (39%), followed by precipitation (35%), haze (17%), and the other types (${\leq}4%$). In terms of regional frequency distributions, the highest frequency of haze (26%) was in Seoul (especially during winter and May-June), possibly due to the high population and air pollutant emission sources, while that of precipitation (47%) was in Jeju (summer and winter), due to its geographic location with the sea on four sides and a very high mountain. $PM_{10}$ concentrations for dust and haze were significantly higher in three cities (up to $250{\mu}g/m^3$ for dust in Incheon), whereas those for the other four types were relatively lower. The concentrations of $PM_{2.5}$ and its major precursor gases ($NO_2$ and $SO_2$) were higher (up to $69{\mu}g/m^3$, 48 ppb, and 16 ppb, respectively, for haze in Incheon) for haze and/or dust than for the other weather types. On the other hand, there were no distinct differences in the concentrations of $O_3$ and CO for the weather types. The overall results of this study confirm that the frequency of weather types and the related air quality depend on the geographic and environmental characteristics of the target areas.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1415-1425
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• 2018

Kompsat-5 is the first Earth Observation Satellite which is equipped with an SAR in Korea. SAR images are generated by receiving signals reflected from an object by microwaves emitted from a SAR antenna. Because the wavelengths of microwaves are longer than the size of particles in the atmosphere, it can penetrate clouds and fog, and high-resolution images can be obtained without distinction between day and night. However, there is no color information in SAR images. To overcome these limitations of SAR images, colorization of SAR images using Cycle GAN, a deep learning model developed for domain translation, was conducted. Training of Cycle GAN is unstable due to the unsupervised learning based on unpaired dataset. Therefore, we proposed MS Cycle GAN applying multi-scale discriminator to solve the training instability of Cycle GAN and to improve the performance of colorization in this paper. To compare colorization performance of MS Cycle GAN and Cycle GAN, generated images by both models were compared qualitatively and quantitatively. Training Cycle GAN with multi-scale discriminator shows the losses of generators and discriminators are significantly reduced compared to the conventional Cycle GAN, and we identified that generated images by MS Cycle GAN are well-matched with the characteristics of regions such as leaves, rivers, and land.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.156-172
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• 2020

The purpose of this study was to predict road surface temperature using high-resolution solar radiation data. The road surface temperature prediction model (RSTPM) was applied to predict road surface temperature; this model was developed based on the heat-balance method. In addition, using SOLWEIG (SOlar and LongWave Environmental Irradiance Geometry-model), the shadow patterns caused by the terrain effects were analyzed, and high-resolution solar radiation data with 10 m spatial resolution were calculated. To increase the accuracy of the shadow patterns and solar radiation, the day that was modeled had minimal effects from fog, clouds, and precipitation. As a result, shadow areas lasted for a long time at the entrance and exit of a tunnel, and in a high-altitude area. Furthermore, solar radiation clearly decreased in areas affected by shadows, which was reflected in the predicted road surface temperatures. It was confirmed that the road surface temperature should be high at topographically open points and relatively low at higher altitude points. The results of this study could be used to forecast the freezing of sections of road surfaces in winter, and to inform decision making by road managers and drivers.

• Atmosphere
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• v.31 no.2
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• pp.241-249
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• 2021

A smart city utilizes data collected from various sensors through the internet of things (IoT) and improves city operations across the urban area. Recently substantial research is underway to examine all aspects of data that requires for the smart city operation. Atmospheric data are an essential component for successful smart city implementation, including Urban Air Mobility (UAM), infrastructure planning, safety and convenience, and traffic management. Unfortunately, the current level of conventional atmospheric data does not meet the needs of the new city concept. New and innovative approaches to developing high spatiotemporal resolution of observational and modeling data, resolving the complex urban structure, are expected to support the future needs. The geographic information system (GIS) integrates the atmospheric data with the urban structure and offers information system enhancement. In this study we proposed the necessity and applicability of the high resolution urban meteorological dataset based on heavy fog cases in the smart city region (e.g., Sejong and Pusan) in Korea.

• Journal of the Korean Orthopaedic Association
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• v.54 no.3
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• pp.211-218
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• 2019

Herniation of the intervertebral disc is a medical disease manifesting as a bulging out of the nucleus pulposus or annulus fibrosis beyond the normal position. Most lumbar disc herniation cases have a favorable natural course. On the other hand, surgical intervention is reserved for patients with severe neurological symptoms or signs, progressive neurological symptoms, cauda equina syndrome, and those who are non-responsive to conservative treatment. Numerous surgical methods have been introduced, ranging from conventional open, microscope assisted, tubular retractor assisted, and endoscopic surgery. Among them, microscopic discectomy is currently the standard method. Biportal endoscopic spinal surgery (BESS) has several merits over other surgical techniques, including separate and free handling of endoscopy and surgical instruments, wide view of the surgical field with small skin incisions, absence of the procedure of removing fog from the endoscope, and lower infection rate by continuous saline irrigation. In addition, existing arthroscopic instruments for the extremities and conventional spinal instruments can be used for this technique and surgery for recurred disc herniation is applicable because delicate surgical procedures are performed under a brightness of 2,700 to 6,700 lux and a magnification of 28 to 35 times. Therefore, due to such advantages, BESS is a novel technique for the surgical treatment of lumbar disc herniation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.635-644
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• 2009

Image processing technique in the outdoor environment is very sensitive, and it tends to lose a lot of accuracy when it rapidly changes by outdoor environment. Therefore, in order to calculate accurate traffic information using the traffic monitoring system, we must resolve removing shadow in transition time, Distortion by the vehicle headlights at night, noise of rain, snow, and fog, and occlusion. In the research, we developed a system to calibrate the amount of traffic, speed, and time occupancy by using image processing technique in a variety of outdoor environments change. This system were tested under outdoor environments at the Gonjiam test site, which is managed by Korea Institute of Construction Technology (www.kict.re.kr) for testing performance. We evaluated the performance of traffic information, volume counts, speed, and occupancy time, with 4 lanes (2 lanes are upstream and the rests are downstream) from the 16th to 18th December, 2008. The evaluation method performed as based on the standard data is a radar detection compared to calculated data using image processing technique. The System evaluation results showed that the amount of traffic, speed, and time occupancy in period (day, night, sunrise, sunset) are approximately 92-97% accuracy when these data compared to the standard data.

• Korean Journal of Hazardous Materials
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• v.2 no.1
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• pp.18-26
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• 2014

We analyzed the demand of competent authorities requiring adequate technical information for initial investigation of chemical accidents. Reflecting technical reports on chemical accident response by environmental agencies in the U.S. and Canada, we presented information on environmental diffusion and toxic effects available for the first chemical accident response. Hydrogen fluoride may have the risk potential to corrode metals and cause serious burns and eye damages. In case of inhalation or intake, it could have severe health effects. The substance itself is inflammable, but once heated, it decomposes producing corrosive and toxic fume. In case of contact with water, it can produce toxic, corrosive, flammable or explosive gases and its solution, a strong acid, may react fiercely with a base. In case of hydrogen fluoride leak, the preventive measures are to decrease steam generation in exposed sites, prevent the transfer of vapor cloud and promptly respond using inflammable substances including calcium carbonate, sodium bicarbonate, ground limestone, dried soil, dry sand, vermiculite, fly ash and powder cement. The method for fire fighting is to suppress fire with manless hose stanchions or monitor nozzles by wearing the whole body protective clothing equipped with over-pressure self-contained breathing apparatus from distance. In case of transport accident accompanied with fire, evacuation distance is 1,600m radius. In cae of fire, fire suppression needs to be performed using dry chemicals, CO₂, water spray, water fog, and alcohol-resistance foam, etc. The major symptoms by exposure route are dyspnoea, bronchitis, chemical pneumonia and pulmonary edema for respiration, skin laceration, dermatitis, burn, frostbite and erythema for eyes, and nausea, diarrhea, stomachache, and tissue destruction for digestive organs. In atmosphere, its persistency is low, and its bioaccumulation in aquatic organism is also low.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1451-1466
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• 2023

In the context of maritime emergencies, the utilization of drones has rapidly increased, with a particular focus on their application in search and rescue operations. Deep learning models utilizing drone images for the rapid detection of distressed vessels and other maritime drift objects are gaining attention. However, effective training of such models necessitates a substantial amount of diverse training data that considers various weather conditions and vessel states. The lack of such data can lead to a degradation in the performance of trained models. This study aims to enhance the performance of deep learning models for distress ship detection by developing a maritime environment simulator to augment the dataset. The simulator allows for the configuration of various weather conditions, vessel states such as sinking or capsizing, and specifications and characteristics of drones and sensors. Training the deep learning model with the dataset generated through simulation resulted in improved detection performance, including accuracy and recall, when compared to models trained solely on actual drone image datasets. In particular, the accuracy of distress ship detection in adverse weather conditions, such as rain or fog, increased by approximately 2-5%, with a significant reduction in the rate of undetected instances. These results demonstrate the practical and effective contribution of the developed simulator in simulating diverse scenarios for model training. Furthermore, the distress ship detection deep learning model based on this approach is expected to be efficiently applied in maritime search and rescue operations.