KJC Korea
Journal Central

In this study, a water footprint methodology that reflects the characteristics of domestic water resources, was developed and calculated the water footprint for expressway system as an infrastructure. Water footprint characterization factors were developed for groundwater and surface water in six representative watersheds which are Han River Basin, Nakdong River Basin, Geum River Basin, Seomjin River Basin, Youngsan River Basin, and Jejudo. Three different water footprint methodologies, Boulay’s methodology, Korea Ministry of Environment methodology, this study methodology were compared in an actual construction case of expressway. As the results, the water footprint of 1 km and 4 lane expressway with Boulay and MOE methodology showed 58,804 ㎥ H2Oeq, 42,036 ㎥ H2Oeq, respectively throughout whole life cycle. However, 9,478 ㎥ H2Oeq. of water footprint was calculated by using this study methodology. This difference is mainly due to a developed regional characterization factor, and its related water consumption coefficient of the construction materials.

The heat wave, which was first designated as a natural disaster in 2018 and causes casualties and property damage due to temperature rises above a certain standard, is becoming more serious at domestic and abroad. In particular, Busan faces the need to establish strategies to cope with the heat wave for its largest number of thermal disease among all metropolitan areas of the Korean Peninsula. This study aims to provide foundations for establishing heat wave strategies by using LSTM techniques, an artificial intelligence (AI) methodology, to reflect the urban-social characteristics of Busan. LSTM optimization analysis results show higher accuracy than conventional regression models and ensemble models, identified by MAE 0,139 and MSE 0.128. In addition, we perform a feature importance analysis to examine the effects of the utilized variables, and the results showed that the temperature-related variables had the highest impact. Significance of this study is found in predicting heat waves by reflecting the urban-social characteristics of Busan beyond simply utilizing climate data through AI methodology. It is expected that heat waves would be more accurately predicted by supplementing future data, adding variables, and improving models.

This study analyzed the geographic proximity between generations to support the generation-friendly housing support policy that solves the social problems of the low birth rate and aging age. A fixed-effect panel logit model has been developed with 2nd~6th KLoSA data for elderly parent households and adult children’s households. Analysis results indicate that common effects are as follows. The geographic proximity between generations is high during the physical decline period in the life cycle of elderly parents and rearing period in the family life cycle of adult children. The geographic proximity between generations is low when living with children in the elderly parent household. On the other hand, the discriminatory effects in urban areas were the economic constraints of elderly parents and the time constraints of adult children. Accordingly, the implication are as follows. First, it is confirmed that overseas studies findings are also applied in korea. Second, it is judged that the family function is performed despite of nuclear family society. Third, it can be used as basic data for the generation-friendly housing support policy plan.

Based on portfolio theory, this study derived an optimal portfolio including housing assets by investor characteristics. In particular, the study focused on classifying investor types into age, income, assets, home ownership, multiple homeowners and residential areas, and analyzing the differences between the risk aversion coefficient and optimal asset allocation for each characteristic. An analysis of the risk aversion coefficient in this study showed that Korean investors have relatively risk-taking behaviors with lower risk aversion coefficient than other countries’ investors. It was found that the lower the age, the more assets, the higher the income, and the lower the risk aversion coefficient. On average, the optimal portfolio include 33.46 percent risk-free assets, 60.34 percent apartments, and 6.21 percent stocks. An investor with lower risk aversion holds on average a much larger proportion of their wealth in risky-assets. Recently, low interest rates and ample liquidity have led to a rise in housing prices worldwide including in Korea. In terms of demand, it is believed that housing is a relatively less risky asset, and that risk-taking behavior has also affected the rise in housing prices in Korea.

In this study, the wind environment around architectural heritage (Hwanggungwoo) located in urban area was numerically investigated using Computational Fluid Dynamics (CFD) model and Geographic Information System (GIS) data. In the four experimental cases of different inflow directions, the horizontal and vertical wind vector fields, and also the wind speeds around architectural heritage were analyzed to assess wind flow characteristics. As a result, the various phenomena such as flow separation and vortex was represented in the vector fields of horizontal and vertical flow, depending on the location and arrangement of high-rise buildings rather than the direction of inflow. The effect of wind was analyzed to be relatively significant at the southeast side of Hwanggungwoo in the case of northerly inflow for the height of 2m Above Ground Level(AGL), and also at the northeast side of Hwanggungwoo in the case of southerly inflow for the height of 10 m AGL. Thus, it was suggested that the effect of urbanization on architectural heritage should be assessed for wind environment.

As the annual average temperature continues to rise due to climate change caused by global warming, the incidence of heat diseases and the number of deaths are also increasing, which is expected to require various alternatives and research. In this study, the average temperature rise-related variables are extracted through statistical analysis for Wonju City, where the average temperature increase rate and change are high, and the average temperature is predicted by utilizing deep learning-based LSTM and GRU based on the extracted variables. Three models were extracted through correlation and regression analysis for 26 variables collected based on prior research consideration, based on which LSTM and GRU analysis were conducted. The analysis showed the lowest MSE of LSTM – 0.4399(2.94°C), GRU – 0.4444(2.97°C) in the third model with 12 variables, with little MAE difference between validation and test data. This study is significant in that it extracted variables through statistical analysis and predicted average temperature rise using deep learning as a data acquisition method for adapting the annual average temperature rise problem. In addition, it is expected that urban space factors that affect the average temperature rise in Wonju City will be extracted along with predicting the trend of average temperature change, and appropriate measures will be prepared to take into account regional impact factors, not uniform climate change adaptation.

This study deals with the ambiguity of the design index among the 3Ds indices (Density, Design, and Diversity) of transit-oriented development (TOD). Unlike density and diversity, design is difficult to quantify arithmetically. We have thus developed a methodology in our study to replace existing 3Ds indices with “2Ds with D (Density with Design, Diversity with Design).” “2Ds with D” is a method that considers the accessibility of walkways at each point in calculating the density and diversity indices. We applied this analytical methodology to 287 station areas of the Seoul Metropolitan Railway. Furthermore, we compared and analyzed which index is better in reflecting the station user among “3Ds” and “2Ds with D” indices. The analysis found that in CBD, the analysis method presented in this study showed higher explanatory power than the existing method, but the difference was not large, and the explanatory power was rather low in other regions. This paper is the first to present the concept of 2Ds with D index to academia and confirm its applicability. It will have a great influence on the study of TOD in the future.