• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.567-573
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• 2020

This study was done to develop indicators for cities that can be used in the long term and in a sustainable manner. Activation indicators were developed to improve the resilience in the downtown area of Seo-gu, Incheon. Preliminary indicators were derived from prior studies on similar indicators of resilience for urban regeneration, and an expert opinion survey was conducted to analyze the suitability and importance of the indicators. Activation indicators were established for improving urban resilience in six areas: population stability, social inclusion, industrial diversity, local productivity, environmental sustainability, and social-based convenience. From 60 preliminary indicators, 42 indicators were selected through the expert opinion surveys for securing an economically active population, establishing a living infrastructure, improving the settlement environment, and upgrading industry to reflect the characteristics of the West, including industrial complexes. It was found that diversification is necessary. Further study is still necessary to improve the objectivity of the indicators and calculate a resilience index. The significance of this study is that it looks at quantitative indicators, complements other studies on regional decline diagnosis, and presents realistic alternatives suitable for domestic situations based on the concept of resilience.

• Spatial Information Research
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• v.22 no.3
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• pp.35-46
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• 2014

Population data are usually provided at administrative spatial units in Korea, so areal interpolation is needed for fine-grained analysis. This study aims to compare various methods of areal interpolation for population subgroups rather than the total population. We estimated the number of elderly people and single-person households for small areal units from Dong data by the different interpolation methods using 2010 census data of Seoul, and compared the estimates to actual values. As a result, the performance of areal interpolation methods varied between the total population and subgroup populations as well as between different population subgroups. It turned out that the method using GWR (geographically weighted regression) and building type data outperformed other methods for the total population and households. However, the OLS regression method using building type data performed better for the elderly population, and the OLS regression method based on land use data was the most effective for single-person households. Based on these results, spatial distribution of the single elderly was represented at small areal units, and we believe that this approach can contribute to effective implementation of urban policies.

• Spatial Information Research
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• v.23 no.5
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• pp.31-40
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• 2015

The purpose of this paper is to propose a data transformation method for visualizing the statistical information based on the grid system which has regular shape and size. Grid is better solution than administrator boundary or census block to check the distribution of the statistical information and be able to use as a spatial unit on the map flexibly. On the other hand, we need the additional process to convert the various statistical information to grid if we use the current method which is areal interpolation. Therefore, this paper proposes the 3 steps to convert the various statistical information to grid. 1)Geocoding the statistical information, 2)Converting the spatial information through the defining the spatial relationship, 3)Attribute transformation considering the data scale measurement. This method applies to the population density of Seoul to convert to the grid. Especially, spatial autocorrelation is performed to check the consistency of grid display if the reference data is different for same statistic information. As a result, both distribution of grid are similar to each other when the population density data which is represented by census block and building is converted to grid. Through the result of implementation, it is demonstrated to be able to perform the consistent data conversion based on the proposed method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.40-53
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• 2021

Recently, shared dockless e-scooter usage has rapidly increased, rather than the station-based shared mobility service, because of convenience. This transition leads to new social problems in urban areas such as increased traffic accidents and hindrance of pedestrian environments. In this study, we analyze the usage characteristics of shared e-scooters in Seoul, and identify factors influencing demand for shared e-scooters by developing a negative binomial regression model. As a result, the usage characteristics show that the average trip distance, the average trip duration, and the average trip speed were 1.5km, 9.4min, and 10.3km/h, respectively. Demographic factor, transport facility factors, land use factors, and weather factors have statistically significant impacts on demand for shared e-scooters. The results of this study will be used as basic data for suggesting effective operation strategies for areas with higher shared e-scooter demand and for establishing transport policies for facilitating shared e-scooter usage.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.118-129
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• 2016

Many epidemiological studies, relying on administrative air pollution monitoring data, have reported the association between particulate matter ($PM_{10}$) air pollution and human health. These monitoring data were collected at a limited number of fixed sites, whereas government-generated health data are aggregated at the area level. To link these two data types for assessing health effects, it is necessary to estimate area-level concentrations of $PM_{10}$. In this study, we estimated district (Gu)-level $PM_{10}$ concentrations using a previously developed pointwise exposure prediction model for $PM_{10}$ and three types of point locations in Seoul, Korea. These points included 16,230 centroids of the largest census output residential areas, 422 community service centers, and 610 centroids on the 1km grid. After creating three types of points, we predicted $PM_{10}$ annual average concentrations at all locations and calculated Gu averages of predicted $PM_{10}$ concentrations as representative Gu-estimates. Then, we compared estimates to each other and to measurements. Prediction-based Gu-level estimates showed higher correlations with measurement-based estimates as prediction locations became more population representative ($R^2=0.06-0.59$). Among the three estimates, grid-based estimates gave lowest correlations compared to the other two(0.35-0.47). This study provides an approach for estimating area-level air pollution concentrations and assesses air pollution health effects using national-scale administrative health data.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.25-25
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• 2015

본 논문의 목적은 전 세계적으로 기후변화로 인한 이상기후에 대한 관심이 높아지고 있으며 이로 인한 부정적 영향에 대한 우려가 증가되고 있다. 우리나라도 기후변화로 연평균 강수량이 1910년대 1,155mm에서 2000년대 1,375mm로 약 19% 증가했으며 21세기말에는 약 17%가 증가할 것으로 전망하고 있다. 정부간협의체(Intergovernmental Panel on Climate Change, IPCC)에 따르면 미래에는 지구의 연평균기온은 2050년은 $2.3^{\circ}C$ 2100년엔 $4.8^{\circ}C$가 증가할 것이라고 전망하였고, 우리나라의 경우 2050년에 $3.2^{\circ}C$ 2100년에 $6^{\circ}C$가 증가할 것으로 전망하였다. 따라서 본 연구에서는 최근 지구적인 문제로 대두되어 온 기후변화 대해 재해취약성 분석을 통하여 효과적인 대응방안을 모색하고자 하였다. 연구대상의 지역은 강원도의 18개 시, 군 지자체로 하였으며 계산의 평가단위는 각 지자체를 하나의 집계구로 정하였다. 재해취약성 분석 지표로는 현재(2000년)와 미래(2020년, 2050년)로 나누어서 분석하였다. 분석 결과 2000년에는 영동지역과 원주시가 가장 취약하였으며, 2020년에는 속초와 강릉, 춘천시가, 2050년에는 강원도 중부지역이 가장 취약할 것으로 전망되었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.257-257
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• 2016

현재 전 세계적으로 이상기후로 인해 자연재해가 증가하고 있으며, 우리나라 또한 집중호우, 태풍, 홍수 등의 자연재해로 인해 경제적 손실뿐만 아니라 인명피해도 증가하는 추세이다. 2014년도에만 약 2천억원의 재산피해가 발생 하였고, 5천억원 이상이 피해를 복구하는데 사용되었으며, 피해금액과 복구금액은 지속적으로 증가하고 있다. 최근 발생한 토사재해의 경우에는 인구가 밀집한 도심지에서 발생하여 매우 단기간에 치명적인 피해를 야기 시키고, 사회적 관심을 크게 일으키기도 했다. 이처럼 자연재해가 인구가 밀집되어있고, 사회적재화가 많은 도심에서 발생할 경우 그 피해규모는 더욱 커질 수 있으므로 이에 대한 적절한 대응방안이 마련되어야 한다. 본 연구에서는 대구지역에 대한 토사재해를 물리적 취약성과 사회적 취약성으로 구분하여 평가하고 이를 종합하여 평가하였다. 물리적 취약성은 Flow-R 모형을 사용하여 토사재해의 발생 가능성 및 정도를 평가하고, 발생지역의 건물 구분에 따라 그 취약성의 정도를 달리하였다. 사회적 취약성의 경우는 대구지역의 집계구 단위를 기준으로 하여, 다양한 사회적 지표에 계층분석법(Analytic Hierarchy Process, AHP)을 적용하여 지표에 대한 가중치를 산정하였다. 이후 물리적 취약성과 사회적 취약성의 값을 0에서 1사이로 정규화 시키고 정규화된 값을 다시 곱하여 0에서 1사이로 정규화 하여 취약성 정도로 나타내었다. 본 연구결과는 대구지역에 대한 토사재해의 취약성을 평가함으로써 대구 도심지에서 발생할 수 있는 토사재해 위험구역을 선정하고 방재시설을 준비하는데 있어서 기초자료로 활용될 수 있을 것으로 판단된다.

• Journal of the Korean Society for Railway
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• v.18 no.2
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• pp.166-174
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• 2015

A direct demand model requires relatively little analysis time and incurs a low cost. It is also known to be useful for the preliminary screening of promising configurations or concepts. This study reviews direct demand models of 12 existing urban railways using demographic data based on a block group level which is approximately 1/24 of a traditional zone area. However, direct demand models are limited. Therefore, a new approach is suggested. The proposed method is based on a field study and an empirical analysis. The study finds factors that affect ridership at the station level. As a case study, the proposed approach is tested using 54 light railway transit stations. The results of this empirical study demonstrate its applicability to improve the error rates of the predicted ridership at the station level.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.50-60
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• 2014

The purpose of this study is to identify characteristics and improvements of the climate change vulnerability analysis methods to build a safe city from disasters. For this, an empirical analysis on sea level rise disasters was performed focusing on Heaundae-gu in Busan. For the analysis, Census output areas and Dongs were set as analysis unit and their disaster vulnerability was analyzed. Improvements were reviewed through the comparison and review of analysis process and results. According to analysis results, Modifiable Areal Unit Problem(MAUP) which gives different results according to aggregate unit occurs. Improvements were induced by analysis process, and it was found that in spatial unit setting stage that becomes the base of analysis, analysis unit adjustment, score computation method adjustment, and clearer analysis method for each disaster type would be needed. In analysis execution stage, it was thought that weighting according to variables, diversification of variables, and exclusion of subjective analysis selection method would be needed. It is expected that accurate the total disaster vulnerability analysis will be the base for the improvement of efficiency in urban resilience responding to future weather changes.

• Journal of the Korean Society for Railway
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• v.19 no.5
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• pp.656-662
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• 2016

Based on time dependent location data of mobile phone users, users' ODs were produced after tracing their travel route and inducing their origins and destinations. System considered average signalizing frequency, which means that the longer the travel length is the more frequent the signal is. This is a home-based OD and is limited to the Seoul Metropolitan area. The OD matrix from the mobile phone data which was aggregated to the cell and transformed to the 'Dong' area, was compared to the KTDB OD. The results can be analyzed and it was determined that they are highly correlated because individual coefficients are 0.98 and 0.85, the former between the OD of this study and the KTDB Si/Gun/Gu unit area OD and the latter between the OD of this study and the Dong unit area KTDB OD.