• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.1
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• pp.173-185
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• 2015

This study aims to investigate the characteristics and types of car accidents and establish a prediction model by analyzing 456 car accidents having occurred in the 11 tunnels in Busan, through statistical analysis techniques. The results of this study can be summarized as below. As a result of analyzing the characteristics of car accidents, it was found that 64.9% of all the car accidents took place in the tunnels between 08:00 and 18:00, which was higher than 45.8 to 46.1% of the car accidents in common roads. As a result of analyzing the types of car accidents, the car-to-car accident type was the majority, and the sole-car accident type in the tunnels was relatively high, compared to that in common roads. Besides, people at the age between 21 and 40 were most involved in car accidents, and in the vehicle type of the first party to car accidents, trucks showed a high proportion, and in the cloud cover, rainy days or cloudy days showed a high proportion unlike clear days. As a result of analyzing the principal components of car accident influence factors, it was found that the first principal components were road, tunnel structure and traffic flow-related factors, the second principal components lighting facility and road structure-related factors, the third principal factors stand-by and lighting facility-related factors, the fourth principal components human and time series-related factors, the fifth principal components human-related factors, the sixth principal components vehicle and traffic flow-related factors, and the seventh principal components meteorological factors. As a result of classifying car accident spots, there were 5 optimized groups classified, and as a result of analyzing each group based on Quantification Theory Type I, it was found that the first group showed low explanation power for the prediction model, while the fourth group showed a middle explanation power and the second, third and fifth groups showed high explanation power for the prediction model. Out of all the items(principal components) over 0.2(a weak correlation) in the partial correlation coefficient absolute value of the prediction model, this study analyzed variables including road environment variables. As a result, main examination items were summarized as proper traffic flow processing, cross-section composition(the width of a road), tunnel structure(the length of a tunnel), the lineal of a road, ventilation facilities and lighting facilities.

• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.186-193
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• 2014

This study aimed to analyze spatio-temporal trends of phenological characteristics in South Korea by using MODIS EVI. For the phenology analysis, we had applied double logistic function to MODIS time-series data. Our results showed that starting date of phenology seems to have a tendency along with latitudinal trends. Starting date of phenology of Jeju Island and Mt. Sobeak went back for 0.38, 0.174 days per year, respectively whereas, Mt. Jiri and Mt. Seolak went forward for 0.32 days, 0.239 days and 0.119 days, respectively. Our results exhibited the fluctuation of plant phonological season rather than the change of phonological timing and season. Starting date of plant phenology by spatial distribution revealed tendency that starting date of mountain area was late, and basin and south foot of mountain was fast. In urban ares such as Seoul metropolitan, Masan, Changwon, Milyang, Daegu and Jeju, the phonological starting date went forward quickly. Pheonoligcal attributes such as starting date and leaf fall in urban areas likely being affected from heat island effect and related warming. Our study expressed that local and regional monitoring on phonological events and changes in Korea would be possible through MODIS data.

• The Journal of Engineering Geology
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• v.34 no.2
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• pp.229-248
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• 2024

This investigated the hydrogeochemical and isotopic characteristics of geothermal waters, groundwaters, and surface waters in Dongrae-gu, Busan, South Korea, in order to determine the origins of the salinity components in the geothermal waters, and their formation mechanisms and heat sources The geothermal waters are Na-Cl-type, distinct from surrounding groundwaters (Na-HCO₃^- and, Ca-HCO₃^- (SO₄, Cl)-type) and surface waters (Ca-HCO₃(SO₄, Cl)-type). This indicates the geothermal waters formed at depth as compared with the groundwaters. δ¹⁸O and δD values of the geothermal waters are relatively depleted as compared with the groundwaters, due to altitude effects and deep circulation of the geothermal waters. Helium and neon isotope ratios (³ He/⁴He and, ⁴He/²⁰Ne) of the geothermal waters plot on a single mixing line between mantle (³He = 3.76~4.01%) and crust (⁴He = 95.99~96.24 %), indirectly suggesting that the heat source is due to the decay of radioactive elements in rocks. The geothermal reservoir temperatures were calculated using the silica-enthalpy and Giggenbach models, yielding values of 82~130℃, and the depth of the geothermal reservoir is estimated to be 1.7~2.9 km below the surface. The correlation between Cl/Na and Cl/HCO₃ for the Dongrae geothermal waters requires the input of salty water. The supply of saline composition is interpreted due to the dissolution of residual paleo-seawater.