• Journal of the Economic Geographical Society of Korea
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• v.12 no.4
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• pp.521-539
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• 2009

This study investigates the time-space characteristics of the road traffic flows in Seoul and the relationship with land use patterns. For the purpose, we analyze the road traffic data collected at 118 observation sites over Seoul City area since 1993. We examine the time-trend of the annual average traffic flows per day during the last fourteen years. Three different trends are revealed: rapid increase during the time period between 1993 and 1997, maintenance same level after sharp decrease between year 1997 and 1998, and gradual decrease after sharp decrease between year 2003 and 2004. The spatial distribution patterns of road traffic flows have also been changed significantly during the period. The traffic flows in the urban center have been declined gradually, while the traffic flows in the boundary area and southern CBDs have increased dramatically. In order to examine the relationship with the changes in the land-use patterns and road traffic flows, we analyze the changes in the spatial distribution patterns of population and industries. We developed three multiple linear regression models to test the relationships between the changes in the land-use variables and road traffic flows.

• Korean Journal of Hazardous Materials
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• v.3 no.1
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• pp.28-36
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• 2015

In early 2011, the Fukushima nuclear power plant had greater damage due to earthquake in Japan, and the awareness of safety has increased. In particular, special response systems should be required to handle disaster situations in plant sites which are likely to occur for large disasters. In this study, a program is designed to set up optimum escape routes, by a smart phone application, when a disaster situation occurs. This program could get information of the cumulative damage from sensors and display the escape route of the smallest damage in real-time on the screen. Utilizing our application in real-time evacuation has advantage in reducing cumulative damage. The optimal evacuation route, focusing on horizontal path, is calculated based on getting the data of fire, detected radioactivity and hazardous gas. Thus, using our application provides information of optimal evacuation to people who even can not hear sensor alarms or do not know geography, without requiring additional costs except fixed sensors or server network deployment cost. As a result, being informed of real-time escape route, the user could behave rapidly with suitable response to individual situation resulting in improved evacuation than simply reacting to existing warning alarms.

• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.632-647
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• 2007

Lots of geographic phenomena have dynamic spatial patterns with time changes, and there have been lots of researches on exploring these dynamic spatial patterns. However, most of these researches focused on the static pattern analysis in a given period, rather than dealing with dynamic changes in the spatial pattern over time with the continual or cumulative perspective. For this reason, investigation of the inertia of spatial process in terms of temporal changes is needed. From this background, the purpose of this paper is to propose the methodology to explore the changes in spatial pattern cumulatively by considering the inertia of the spatial statistics over time, and to apply it to the case study That is, we introduce the new spatial statistic, and produce the z-values of the statistic using Monte Carlo Simulation, and then to explore the changes in spatial patterns over time cumulatively. To do this, the method to combine the J statistic with CUSUM statistic for exploring spatial patterns, and to apply it to the changes in the commercial landuse in Erie County, New York State. Through the proposed method for spatio-temporal Patterns, we could explore continual changes effectively in the spatial patterns reflecting the statistics by temporal spot cumulatively.

• Journal of the Korean Geographical Society
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• v.48 no.2
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• pp.272-287
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• 2013

This paper describes the importance of selecting explanatory variables(e.g. land price determinants) in hedonic pricing models employed in predicting real estate price, and explores dynamics of the land price determinants over time. The City of Junju was chosen as the study area, and repeated measured price data of standard lots over 17 years were analyzed. We applied a three-level modeling approach to this data in consideration of its nested data structure and longitudinal characteristics. Main land price determinants we focused on are primarily based on items included in the standard comparison table of land price, which is an official hedonic pricing model used by Government to estimate land price for tax levy. Our result shows that the land price fluctuation over 17 years was not uniform over the whole study area with each neighborhood revealing different price trend, and as such warrants longitudinal model components. In addition, some of determinants previously recognized as important were proved insignificant. It was also found that significant determinants at a particular time point lost its power gradually over time and vice versa. It is expected that more accurate prediction of price would be possible when taken account for this dynamics of price determinants over time in applying hedonic pricing model method.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.231-245
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• 2020

The purpose of this study was to analyze the spatiotemporal characteristics of staying places by deriving the main staying places of the elderly population in Seoul using public transportation card data. For this reason, we used public transportation card data for 7 days from October 12, 2015 to October 18, 2015. As a result of the analysis, 14 places were extracted as the main staying places. It was divided into 5 groups based on the characteristics of the visiting users and concentration time. Most of the staying places showed that the elderly users who lived near the places visited, but in the case of the group where a large number of elderly users visited had relatively wide range of residential distribution. It was possible to confirm that there was a hierarchy. And the concentration time was displayed differently. Most of the staying places' concentration time was between 10 am and 5 pm. However, in the case of Jegi-dong group and Jamsil group had different concentration time. The results of this research provide necessary suggestions for establishing a public transport policy that considers the main stay spaces of the elderly population in Seoul and the stay characteristics of each stay space.

• Journal of Environmental Health Sciences
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• v.27 no.1
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• pp.44-50
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• 2001

This study was carried out to investigate characteristics of water quality and THMs formation in lake-waters at kunsan. Of the parameters examined for water quality, pH, alkalinity, SO$_4$$^{-2}$ and Co- reflected the characteristics according to the origin, geography and water source of lakes while COD, SS, T-P, T-N and chlorophyll-a corelatively reflected well the influence of pollution factors around factors around lakes. The result of water quality analysis showed that most lakes in Kunsan area have the severe eutropnication problem, especially in summer. In lake-waters, THMFP overally continued to increase until 48 hour with the reaction time and THMs formation was largely achieved within 24 hour of the reaction time. The average formation ratio were 68.2% for CHCl$_3$, 23.6% for CHCl$_2$Br, 7.6% for CHClBr$_3$ and 0.6% for CHBr$_3$respectively and much difference depending on the reaction time was not shown. Overally, 96h-THEFP levels in lakes were high during June~September and showed higher tencency in lakes where could be regarded more contaminated on the whole. These results suggest that THMFP may be available for the management of lake-water quality as one if the useful parameters for the general evaluation of contamination. 96h-THEMFP failed to show the strong corelation individually with pH, TOC, COD and chlorphyll-a.

• Journal of Environmental Impact Assessment
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• v.12 no.2
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• pp.109-120
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• 2003

This paper examined the impacts of dam construction on fog characteristics over surrounding areas. Juamdam which only supplies the water for use and Chungjudam which generates electricity were selected. The number of foggy days, fog occurrence and dissipation time and the differences of each lake water temperature and air temperature at Sunchun and Chungju were analyzed. After the construction of dam, the relative humidity and water vapor pressure were decreased at Sunchun and Chungju. The number of foggy days did not increase at Sunchun while largely increased at Chungju. Just because Juamdam were contained water, the water vapor pressure at surrounding areas of the weather station were largely decreased. It delayed the time of fog occurrence by bringing out the decrease of steam fog. The foggy days increased over the Chungju area due to the difference between air and cold outlet water temperature. The increase of foggy days mainly resulted from evaporation during colder seasons and from the temperature inversion over the water surface during warmer seasons.

• Journal of Environmental Science International
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• v.22 no.7
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• pp.885-893
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• 2013

The purpose of this study was to analyze the effects of partial solar eclipse on 21 May 2012 in Korea on meteorological variables in Busan. 0800 LST(Local Standard Time) solar radiation was similar or lower than 0700 LST solar radiation, and sunshine duration decreased by 0.2~0.5 hours in Busan and great cities under the influence of the partial solar eclipse. Temperature drop due to the partial solar eclipse was $0.2{\sim}2.0^{\circ}C$, time taken to arrive at maximum temperature after onset of eclipse was 8~62 minutes, and time taken to arrive at minimum temperature after maximum eclipse was -9~17 minutes in Busan. Change of wind speed was negligible as partial solar eclipse occurred in the morning. Soil temperature of 5 cm was minute as well, the increase of soil temperature due to sunset was delayed by more than 1 hour.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.147-147
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• 2018

In this article, we use an open source software library: TensorFlow, developed for the purposes of conducting very complex machine learning and deep neural network applications. However, the system is general enough to be applicable in a wide variety of other domains as well. The proposed model based on a deep neural network model, LSTM (Long Short-Term Memory) to predict the river water level at Okcheon Station of the Guem River without utilization of rainfall - forecast information. For LSTM modeling, the input data is hourly water level data for 15 years from 2002 to 2016 at 4 stations includes 3 upstream stations (Sutong, Hotan, and Songcheon) and the forecasting-target station (Okcheon). The data are subdivided into three purposes: a training data set, a testing data set and a validation data set. The model was formulated to predict Okcheon Station water level for many cases from 3 hours to 12 hours of lead time. Although the model does not require many input data such as climate, geography, land-use for rainfall-runoff simulation, the prediction is very stable and reliable up to 9 hours of lead time with the Nash - Sutcliffe efficiency (NSE) is higher than 0.90 and the root mean square error (RMSE) is lower than 12cm. The result indicated that the method is able to produce the river water level time series and be applicable to the practical flood forecasting instead of hydrologic modeling approaches.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.3
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• pp.319-331
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• 2007

Nowadays, urbanized area expands its boundary, and distribution of urbanized area is gradually transformed into more complicated pattern. In Korea, SMA(Seoul Metropolitan Area) has outstanding urbanized area since 1960. But it is ambiguous whether urban distribution is clustered or dispersed. That is to say, it is difficult to understand spatial distribution pattern of urbanized area, although urbanized area has grown gradually. This study aims to show the way in which expansions of urbanized area impact on spatial distribution pattern of urbanized area. We use GIS analysis based on raster dataset, quadrat analysis, and nearest neighbor analysis to know distribution pattern of urbanized area in time-series urban growth. Experiments show that cohesion of SMA's urbanized area had increased to the early 1980s, but has decreased from the middle 1980s. Also, urban growth of SMA has been characterized not by spillover growth but by leapfrogging growth and road-influenced growth since the middle 1980s.