• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.638-650
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• 2014

The objective of this study is to identify the causes of pedestrian volume path to the destination by investigating the influential levels of regional and planning features in the central area of Seoul. Regional characteristics can be classified from the result of the analysis and through the spatial characteristics of pedestrian volume. For global scale analysis, Ordinary Least Squares (OLS) regression is used for the degree of influence of each characteristics to pedestrian volume. For the local scale, Geographically Weighted Regression (GWR) is used to identify regional influential factors with consideration for spatial differences. The results of OLS indicate that boroughs with transportation facilities, commercial business districts, universities, and planning features with education research facilities and planning facilities have a positive effect on pedestrian volume path to the destination. Correspondingly, transportation hubs and congested areas, commercial and business centers, and university towns and research facilities in the Seoul central area can be identified through the results of GWR. The results of this study can provide information with relevance to existing plans and policies about the importance of regional characteristics and spatial heterogeneity effects on pedestrian volume, as well as significance in the establishment of regional development plans.

• Korean Journal of Ecology and Environment
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• v.52 no.2
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• pp.94-104
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• 2019

In this study, we investigated the spatial variation in land use and topographic effects on water quality at the Geum river watershed in South Korea, using the ordinary least squares(OLS) and geographically weighted regression (GWR) models. Understanding the complex interactions between land use, slope, elevation, and water quality is essential for water pollution control and watershed management. We monitored four water quality indicators -total phosphorus, total nitrogen, biochemical oxygen demand, and dissolved oxygen levels - across three land use types (urban, agricultural, and forested) and two topographic features (elevation and mean slope). Results from GWR modeling revealed that land use and topography did not affect water quality consistently through space, but instead exhibited substantial spatial non-stationarity. The GWR model performed better than the OLS model as it produced a higher adjusted $R^2$ value. Spatial variation in interactions among variables could be visualized by mapping $R^2$ values from the GWR model at fine spatial resolution. Using the GWR model, we were able to identify local pollution sources, determine habitat status, and recommend appropriate land-use planning policies for watershed management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.51-66
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• 2022

SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.

• Korean Journal of Community Nutrition
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• v.29 no.3
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• pp.234-252
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• 2024

Objectives: This study examined the intake of energy and macronutrients among elementary, middle, and high school students according to household income before the COVID-19 pandemic (2016-2019), during the social distancing period (2020-2021), and after the social distancing measures were lifted (2022). Methods: We included 5,217 students aged 5-18 from the Korea National Health and Nutrition Examination Survey (KNHANES) conducted between 2016 and 2022. Dietary intake was assessed using one-day 24-hour dietary recalls. We estimated the least squares means (LS-means) of intake according to household income for each period using a weighted linear regression model, adjusted for age and sex. Differences in LS-means between the periods were analyzed using the t-test. Results: During the social distancing period, the LS-means of energy intake among students decreased significantly by 143.2 kcal/day compared to pre-pandemic levels (P < 0.001). Students from low-income households experienced a more pronounced decrease in energy intake (-379.1 kcal/day, P < 0.001) and macronutrient intake compared to those from other income groups. Energy intake at school significantly declined for all income groups during the social distancing period compared to before the pandemic. No significant changes in home energy intake were observed among low-income students, whereas there was an increase for students from higher-income groups. Before the pandemic, 8.5% of students from low-income households reported insufficient food due to economic difficulties; this figure rose to 21.3% during the pandemic. Conclusions: During the pandemic, students from low-income families experienced significantly lower intake of energy and macronutrients compared to pre-pandemic levels. The most substantial reductions were noted among low-income students, largely due to the lack of compensation for decreased school-based intake with increased intake at home.