• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.15-22
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• 2009

There exist some limits when we forecast urban railway demand by traditional 4 step model. The first reason is that the model based on socioeconomic data by an administrative unit, 'Dong', yields a 'Dong' unit trip matrix. But a 'Dong' often has two or more stations. The second reason is that urban railway demand by station would be affected rather by station access area on foot than by a 'Dong' unit. So the model based on 'Dong' characteristic data have some inaccuracies in itself. Owing to the limits of the model based on 'Dong' unit data, there exits some difficulty in forecasting urban railway demand by station. So this paper studied two alternatives. The first is to forecast the demand by using the data of station access area on foot rather than 'Dong' unit data. This needs too much time and effort to collect data and analyse them, while the accuracy of the model didn't improve a lot. The second is to adjust the location of 'Dong' centroid and the length of centroid connector link. By this way we can reflect the characteristics of station access area on foot under traditional 4 step model. Comparing the expected demand to the observed data for each station, the result looks like very similar.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.94-104
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• 2016

In this study, factor and cluster analysis are used to classify characteristics of the administrative basic unit, "Dong", of the Incheon Metropolitan City. Travel characteristics of the classified groups are then analyzed through databases to provide directions of urban transportation planning. First, industrially developed administrative-dong show a high commuting volume by using cars. Thus the analysis indicated the need to staggering work-hour system and signal operating system policy. Second, commercially developed administrative-dong show heavy use of public transportation and long distance commute as well as high volume of shoppers. The analysis indicated the need to improve road infrastructure. Third, densely populated administrative-dong show a high rate of commute to work and school as well as long hours of commuting. Thus the analysis indicated the need to improve road transportation policies during rush hours. Fourth, administrative-dong with multiple characteristics feature heavy pedestrian traffic thus the study analyzed the need to improve pedestrian environment policies. Lastly, administrative-dong in close proximity to train stations feature extensive use of biking as well as high volume of shoppers and students commuting. Thus the study analyzed the necessity to have plans to enhance accessibility.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.110-110
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• 2022

2011~2019년 평균 강수량은 100년 전(1912~1920) 보다 861mm 증가(7.4%)하였으며, 2020년 서울, 부산, 대전 등 대도시 지역에서 침수로 인한 인명피해가 발생하는 등 기후변화로 인한 강우량, 집중호우의 발생 빈도와 강우강도 증가 및 지속적인 도시침수로 인한 인명·재산 피해를 지속적으로 발생하고 있다. 이와 같이 도시침수는 단기간 집중호우에 의해 발생하고 좁은 범위에 발생하지만 건물, 인구 등 밀집도가 높은 지역에 발생하여 피해가 크게 발생한다. 또한 우수관 개선, 배수 펌프장 등 구조적인 대책만으로는 한계가 있으며, 예 경보 등 비구조적인 대책과 합께 이루어져야 한다. 이에 본 연구에서는 과거침수피해이력자료와 강우자료를 이용하여 해당 행정동에 대해 침수발생 한계강우량을 추정하였으며, 침수피해이력이 없는 행정동에 대해서는 유역특성과 한계강우량과의 관계를 이용하여 한계강우량을 예측하는 모델을 개발하였다. 3,344개 행정동에 대해 한계강우량을 추정하였으며, 이를 활용하여 2021년 침수 예·경보에 시범적용하였다. 6월~9월 까지 운영한 결과를 대상으로 강우자료와 비교하여 정확성을 검토하고 오차가 10% 이상인 행정동에 대해서는 개선하고자 한다.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.152-161
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• 2013

This study attempted to test the causal effect of structural characteristics of metropolitan neighborhoods on crime, based on the ecological model of crime explanation. To this end, a Negative Binomial Regression analysis was performed for Seoul's 424 Dong Districts. Results showed that the incidence of homicide increases as much as the scales of economic disadvantage, family disruption, and commercial land use go worse. It suggested that family integrity is one of the most strong and consistent factors that could deter crime in neighborhood's contexts. Economic disadvantage and commercial land use were also critical targets as crime-generating factors. Reasoning with the results of past studies implied that neighborhood-specific approaches need to be developed for effective crime prevention. Although a few limitations could raise a caveat against such interpretation of the results, the value of this research would not be simply denied as the first attempt to utilize all Dong districts of Seoul. It is expected that this study contributes to activating Dong level research and developing effective crime control policy.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.821-834
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• 2017

The increase in the rate of industrialization due to urbanization has caused the Urban Heat Island phenomenon where the temperature of the city is higher than the surrounding area, and its intensity is increasing with climate change. Among the cities where heat island phenomenon occurs, Seoul city has different degree of urbanization, green area ratio, energy consumption, and population density in each administrative district, and as a result, the strength of heat island is also different. So It is necessary to analyze the difference of Urban Heat Island Intensity by administrative district and the cause. In this study, the UHI intensity of the administrative gu and the administrative dong were extracted from the Seoul metropolitan area and the differences among the administrative districts were examined. and linear regression analysis were conducted with The variables included in the three categories(weather condition, anthropogenic heat generation, and land use characteristics) to investigate the cause of the difference in heat UHI intensity in each administrative district. As a result of analysis, UHI Intensity was found to be different according to the characteristics of administrative gu, administrative dong, and surrounding environment. The difference in administrative dong was larger than gu unit, and the UHI Intensity of gu and the UHI Intensity distribution of dongs belonging to the gu were also different. Linear regression analysis showed that there was a difference in heat island development intensity according to the average wind speed, development degree, Soil Adjusted Vegetation Index (SAVI), Normalized Difference Built-up Index (NDBI) value. Among them, the SAVI and NDBI showed a difference in value up to the dong unit and The creation of a wind route environment for the mitigation of the heat island phenomenon is necessary for the administrative dong unit level. Therefore, it is considered that projects for mitigating heat island phenomenon such as land cover improvement plan, wind route improvement plan, and green wall surface plan for development area need to consider administrative dongs belonging to the gu rather than just considering the difference of administrative gu units. The results of this study are expected to provide the directions for urban thermal environment design and policy development in the future by deriving the necessity of analysis unit and the factors to be considered for the administrative city unit to mitigate the urban heat island phenomenon.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.93-93
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• 2018

최근 기후변화에 따라 우리나라 해수면 상승률은 평균 2.48mm/yr로 가파르게 상승하고 있다. 동해의 해수면 상승률은 2.69mm/yr 로 전세계 평균 해수면 상승률인 2.0mm/yr 보다 높게 나타나 해수면 상승에 의한 해수침투 피해가 증가할 것으로 예상된다. 해수침투로 인해 1차적으로 연안지역의 해수침투 영역이 증가하고, 지하수의 오염, 농작물의 염수 피해, 산업활동의 제약 등 피해 범위가 지역 사회 범위로 점차 증가한다. 한정된 자원에서 해수침투를 예방하고 피해지역을 줄이는 것에는 많은 어려움이 있다. 이를 위해 동해 연안지역의 행정구역을 대상으로 정량적인 분석을 통하여 해수침투에 취약한 지역을 선정하고 대비하는 것이 가장 효율적인 방법이라고 볼 수 있다. 본 연구에서는 해수침투에 영향을 미치는 인자들을 수집하고, 취약지역을 평가하여 분석하였다. 동해 연안의 11개 시 군 행정구역을 대상으로 해수침투에 영향을 미칠 수 있는 인자를 선택하고 자료를 수집하였다. 수집된 자료는 Re-scale 방법을 이용하여 표준화 하고 엔트로피 방법을 이용하여 산정된 가중치를 각각의 인자에 적용하였다. 산정된 해수침투 취약성 지수는 동해안을 대상으로 하여 각 행정구역에 대한 상대적인 취약성을 나타낸다. 최종적으로 산정된 취약성 지수를 동해안의 행정구역이 도시되어 있는 지도에 나타내어 취약한 지역에 대하여 해수침투 방지 대책 및 시설 보강 계획을 세운다면 해수침투 피해에 효율적인 대처가 가능할 것으로 예상된다.

• Journal of the Korean association of regional geographers
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• v.19 no.4
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• pp.615-626
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• 2013

In this study, spatial patterns of the urban flood vulnerability index in Seoul are examined by considering climate exposure, sensitivity, and adaptability associated with floodings for recent 5 year (2006~2010) period by the smallest administrative unit called Dong. According to the results of correlation analyses based on the IPCC(Intergovernmental Panel on Climate Change)'s vulnerability model, among many variables associated with urban flooding, rainwater tank capacity, 1-day maximum precipitation and flood pumping station capacity have statistically-significant, and relatively-high correlations with the number of flood damage in Seoul. The flood vulnerability map demonstrates that the extensive areas along Anyang and Joongnang streams show relatively high flood vulnerability in Seoul due to high sensitivity. Especially in case of Joongnang stream areas, climatic factors also contribute to the increase of flood vulnerability. At local scales, several Dong areas in Gangdong-gu and Songpa-gu also show high flood vulnerability due to low adaptability, while those in Gangnam-gu do due to high sensibility and climate factor such as extreme rainfall events. These results derived from the flood vulnerability map by Dong unit can be utilized as primary data in establishing the adaptation, management and proactive policies for flooding prevention within the urban areas in more detail.

• Journal of the Korean Regional Science Association
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• v.38 no.4
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• pp.3-17
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• 2022

This study aims to empirically analyze the impacts of the topographic characteristics of residential areas and the characteristics of land use and transportation on average trip distance of the senior citizens in Busan Metropolitan city. Multiple regression is conducted to accomplish the purpose of this study, and the conclusions and policy implications of the analysis are as follows. First, the average and standard deviation of the residential areas are significantly related to average trip distance of the senior citizens. Thus, urban transportation policies need to take account of the topographic characteristics of the residential areas. Second, average distance from the nearest subway station and density of bus stops have positive and negative association respectively. Mobility improvement polices for senior citizens should consider urban spatial structure and different approach processes to transportation facilities by modes. Third, mobility and residential environment improvement policies for senior citizens should take into account different sociodemographic characteristics by locations. This shows that the mobility convenience policy for senior citizens is more necessary than any other policy for administrative dong, where traffic access is relatively low and the single senior citizen population is concentrated.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.136-139
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• 2010

우리나라 주소는 우편번호를 기준으로 한 주소체계, 법정동을 기준으로 한 주소체계, 행정동을 기준으로 한 주소체계, KT 에서 관리하는 KT 주소체계 등 주소관리가 통합되어 있지 않고, 각 기관, 기업별로 주소 관리를 별도로 하고 있다. 이에 따라 기관과 기업들간의 상이한 주소체계 관리문제로 인해 서로간의 주소체계의 의미가 일치하지 않는 문제가 발생하여 다양한 문제가 유발되고 있다. 본 논문에서는 이러한 문제점들을 해결하기 위해 주소 명칭에 대한 보다 자동화된 맵핑이 가능하도록 KT 주소, 우편번호주소, 행정동/법정동코드를 대상으로 온톨로지를 사용한 모델을 제안하였다. 제안된 모델은 주소정보간의 의미관계성을 유지하여 이기종 주소체계의 의미 불일치를 해결할 수 있으며, 보다 자동화된 데이터관리와 장기적인 비용절감이 가능하다.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.375-388
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• 2021

This paper aims to help prevent the spread of COVID-19 by analyzing confirmed cases of COVID-19 in Daejeon. A high volume of visitors, downtown areas, and psychological fatigue with prolonged social distancing were considered as risk factors associated with the spread of COVID-19. We considered the weekly confirmed cases in each administrative district as a response variable. Explanatory variables were the number of passengers getting off at a bus station in each administrative district and the elapsed time since the Korean government had imposed distancing in daily life. We employed a mixed-effects zero-inflated Poisson regression model because the number of cases was repeatedly measured with excess zero-count data. We conducted k-means clustering to identify three groups of administrative districts having different characteristics in terms of the number of bars, the population size, and the distance to the closest college. Considering that the number of confirmed cases might vary depending on districts' characteristics, the clustering information was incorporated as a categorical explanatory variable. We found that Covid-19 was more prevalent as population size increased and a district is downtown. As the number of passengers getting off at a downtown district increased, the confirmed cases significantly increased.