• Journal of the Economic Geographical Society of Korea
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• v.23 no.1
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• pp.56-70
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• 2020

This study identifies the impact of social network service (SNS) on the spatial characteristics of retail stores locations in the hyper-connected society, which have been closely related to the everyday lives of urban residents. In particular, we focus on the changes in the spatial distribution of restaurants since the information retrieval process was added to the decision-making process of a consumer's restaurant selection. Empirically, we analyze restaurants in Seoul, Korea since the smart-phone was introduced. By applying the kernel density estimation and Moran's I index, we examine the changes in the spatial distribution pattern of restaurants during the last ten years for running, newly-open and closed restaurants as well as SNS popular ones. Finally, we develop a spatial regression model to identify geographic features affecting their locations. As the results, we identified geographical variables and online factors that influence the location of restaurants. The results of this study could provide important groundwork for food and beverage location planning and policy formulation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1004-1010
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• 2021

Ship-floating object accidents can lead not only to a delay in ship's operations, but also to large scale casualties. Hence, preventive measures are required to avoid them. This study analyzed the spatiotemporal aspects of such collisions based on the data on ship-floating object accidents in sea areas in the last five years, including the collisions in South Korea's territorial seas and exclusive economic zones. We also provide basic data for related research fields. To understand the distribution of the relative density of accidents involving floating objects, the sea area under analysis was visualized as a grid and a two-dimensional histogram was generated. A multinomial logistic regression model was used to analyze the effect of variables such as time of day and season on the collisions. The spatial analysis revealed that the collision density was highest for the areas extending from Geoje Island to Tongyeong, including Jinhae Bay, and that it was high near Jeongok Port in the West Sea and the northern part of Jeju Island. The temporal analysis revealed that the collisions occurred most frequently during the day (71.4%) and in autumn. Furthermore, the likelihood of collision with floating objects was much higher for professional fishing vessels, leisure vessels, and recreational fishing vessels than for cargo vessels during the day and in autumn. The results of this analysis can be used as primary data for the arrangement of Coast Guard vessels, rigid enforcement of regulations, removal of floating objects, and preparation of countermeasures involving preliminary removal of floating objects to prevent accidents by time and season.

• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.743-752
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• 2014

Delay time for groundwater recharge means the travel time from the bottom of soil layer to groundwater through vadose zone after infiltration from rainfall. As it is difficult to measure delay time, we suggested an empirical formula which is derived by using linear regression between altitude and delay time. For the regression analysis, 4 major gauging watersheds were chosen (Hancheon, Kangjeongcheon, Oedocheon, Cheonmicheon) with 18 measured groundwater level stations. To verify this empirical formula, derived equation from linear reservoir theory was applied to compute delay time and to compare estimated amounts of groundwater recharge using both methods. The result showed good agreement. Furthermore, if derived empirical formula would be linked with SWAT model, the spatial time delay effect in the watershed could be reflected properly.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.387-397
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• 2008

Recently many researches on data analysis using spatial statistics have been studied in various field and the studies on small area estimations using spatial statistics are in actively progress. In analysis of lattice data, defining the neighborhood information system is the most crucial procedure because it also determines the result of the analysis. However the used neighborhood informal ion system is generally defined by sharing the common border lines of small areas. In this paper the other neighborhood information systems are introduced and those systems are compared with Moran's I statistic and for the comparisons, Economic Active Population Survey (2001) is used.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.321-331
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• 2017

The objective of this study is to analyze the factors affecting the pedestrian accidents of roundabout near schools. To this end, this study has focus on the comparative analysis of pedestrian accidents across different school areas. The traffic accident data from 2007 to 2014 are collected from TAAS data set of Road Traffic Authority. To develop the pedestrian accident rate model, the linear regression model has been utilized in this study. 28 explanatory variables such as geometry and traffic volume factors are used. The main results are summarized as follows. First, the null hypotheses that the number of pedestrian accidents are the same are rejected. Second, 5 multiple linear regression accident models with higher statistical significance (adjusted $R^2$ of 0.651~0.788) have been developed. Third, while the common variables of 3 models (model I~III) related to school location are evaluated to be the pedestrian island, crosswalk, types of roundabout, elementary school and bus stop. Fourth, while the common variable of 3 models (model III~V) related to near school area or not is evaluated to be pedestrian island, type of roundabout, sidewalk, elementary school, speed hump, speed limit sign and number of entry lane. As a result, the installation of pedestrian islands and crosswalk might be expected to decrease the number of pedestrian accidents near schools.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.56-65
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• 2019

This study empirically analyzes the effect of weather on pedestrian volume in an urban space. We used data from the 2009 Seoul Flow Population Survey and constructed a model with the pedestrian volume as a dependent variable and the weather and physical environment as independent variables. We constructed 28 models and compared the results to determine the effects of weather on pedestrian volume by season, land use, and time zone. A negative binomial regression model was used because the dependent variable did not have a normal distribution. The results show that weather affects the volume of walking. Rain reduced walking volume in most models, and snow and thunderstorms reduced the volume in a small number of models. The effects of the weather depended on the season and land use, and the effects of environmental factors depended on the season. The results have various policy implications. First, it is necessary to provide semi-outdoor urban spaces that can cope with snow or rain. Second, it is necessary to have different policies to encourage walking for each season.

• Journal of Wetlands Research
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• v.18 no.2
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• pp.148-153
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• 2016

Hydraulic and hydrological flood routing methods are commonly used to analyze temporal and spatial flood influences of flood wave through a river reach. Hydrological flood routing method has relatively more simple and reasonable performance accuracy compared to the hydraulic method. Storage constant used in Muskingum method widely applied in hydrological flood routing is very similar to the travel time. Focusing on this point, in this study, we estimate the travel time from HEC-RAS results to estimate storage constant, and develop a non-linear regression equation for the travel time using reach length, channel slope, and discharge. The estimated flow by Muskingum model with storage constant of nonlinear equation is compared with the flow calculated by applying the HEC-RAS 1-D unsteady flow simulation. In addition, this study examines the effect on the weighting factor changes and interval reach divisions; peak discharge increases with the bigger weighting factor, and RMSE decreases with the fragmented division.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.705-716
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• 2008

The objectives of this study are the detection and forecast of climate change signal in the annual mean of surface temperature data, which are generated by MRI/JMA CGCM over the Korean Peninsula. MRI/JMA CGCM outputs consist of control run data(experiment with no change of $CO_2$ concentration) and scenario run data($CO_2$ 1%/year increase experiment to quadrupling) during 142 years for surface temperature and precipitation. And ECMWF reanalysis data during 43 years are used as observations. All data have the same spatial structure which consists of 42 grid points. Two statistical models, the Bayesian fingerprint method and the regression model with autoregressive error(AUTOREG model), are separately applied to detect the climate change signal. The forecasts up to 2100 are generated by the estimated AUTOREG model only for detected grid points.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.96-104
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• 2001

Usage of ecosystem models has been extended to landscape scales for understanding the effects of environmental factors on natural and agro-ecosystems and for serving as their management decision tools. Accurate prediction of spatial variation in daily temperature is required for most ecosystem models to be applied to landscape scales. There are relatively few empirical evaluations of landscape-scale temperature prediction techniques in mountainous terrain such as Korean Peninsula. We derived a periodic function of seasonal lapse rate fluctuation from analysis of elevation effects on daily temperatures. Observed daily maximum and minimum temperature data at 63 standard stations in 1999 were regressed to the latitude, longitude, distance from the nearest coastline and altitude of the stations, and the optimum models with $r^2$ of 0.65 and above were selected. Partial regression coefficients for the altitude variable were plotted against day of year, and a numerical formula was determined for simulating the seasonal trend of daily lapse rate, i.e., partial regression coefficients. The formula in conjunction with an inverse distance weighted interpolation scheme was applied to predict daily temperatures at 267 sites, where observation data are available, on randomly selected dates for winter, spring and summer in 2000. The estimation errors were smaller and more consistent than the inverse distance weighting plus mean annual lapse rate scheme. We conclude that this method is simple and accurate enough to be used as an operational temperature interpolation scheme at landscape scale in Korea and should be applicable to elsewhere.

• 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.