• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.181-195
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• 2019

This study aims to analyze the spatial context by analyzing the flow characteristics of the walking tour course and visualizing effectively using the floating population data constructed through the communication data. The floating population data refinement algorithm was developed for estimation flow population along the road and the floating population data for each walking tour courses was constructed. In order to adopt the algorithm for forming suitable for the analysis of the walking tour courses, the estimation of floating population considering the area of the road and the estimation of floating population considering the value of floating population around the road were compared. As a result, the estimation of floating population considering ambient the values of flow population was adopted, which is more appropriate to apply analysis method due to the relatively consistent data. Then, a datamining algorithm for walking tour course was constructed according to the characteristics of the floating population data, the absence of missing values. Finally, this study analyzed the flow characteristics and spatial patterns of 18 walking trails in Seoul through the floating population data according to walking tour course. To do this, the kernel density analysis and the Getis-Ord $G^*_i$ statistical hotspot analysis were applied to visualize the main characteristics of each walking tour course.

• Survey Research
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• v.12 no.2
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• pp.27-50
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• 2011

It is increasingly important to estimate daytime population for the sake of urban administration and urban economy. The estimation of daytime population using a census data on commute, however, has its own limits, particularly when applying to the metropolis such as Seoul which is dominated by the service industry. This study suggests a pedestrian flow as another estimate of daytime population and presents a methodology of Seoul Pedestrian Flow Survey. The data of pedestrian flow gives us a view into hourly and spatial distribution of daytime population, which cannot be provided by the use of census data. In addition, comparing with a census-based daytime population on the borough level show some features of a pedestrian flow as another estimate of daytime population.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.301-304
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• 2021

COVID-19 가 장기간 지속됨에 따라 시민들의 생활패턴, 생계 등에 큰 영향을 미치고 있다. 본 논문에서는 서울시의 유동인구 및 카드 소비데이터를 이용하여 COVID-19 가 어떤 영향을 미쳤는지 알아보려 한다. 이를 분석하기 위하여 대용량 데이터인 2019 년 1 월 ~6 월 그리고 2020 년 1 월 ~ 6월 서울시 유동인구 및 카드 소비 데이터를 이용하였다. 서울시를 각 행정구로 나누어 이에 관련한 유동인구의 변화, 유동인구의 증감의 변화를 추정하고 마찬가지로 카드소비데이터의 증감의 변화를 추정하여 서울시 여러 행정구의 유동인구, 카드데이터 두 데이터 간의 연관 관계를 다방면으로 분석하여 엄밀한 인구 밀집도 분석으로 COVID-19 가 서울 지역경제에 미친 영향에 대하여 실증분석을 진행하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.1-10
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• 2016

Seoul, a mega city, contains many features of the modern city. When the disaster or emergency occurs in Seoul, the place for shelter is required for evacuation urgently. There are currently the numbers of shelters in Seoul City, which can hold the twice more capacity of population of Seoul. However, the population distribution fluctuation in the day and the night needs to be considered. Therefore, in order to analyze the actual capacity of shelter, it is necessary to consider the dynamic characteristics of population distribution in the metropolitan area. In the study, the substantial accessibility and the capacity of shelters in Seoul were analyzed by the floating population data of the metropolitan area. The accessibility of shelter was investigated through a network analysis that includes the pedestrian road data, while the capacity of shelter was analyzed by the local differences of daytime population distributions. Finally it was possible to identify the vulnerable areas on the basis of the distribution of shelter in the region.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.613-614
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• 2019

유동인구의 정확한 분석은 현대 사회의 중요한 과제이다. 현존하는 population counting 의 방법으로는 인력을 동원하여 수기를 하거나, 센서를 설치하여 지나가는 사람을 감지하여 수를 세는 등의 방식이 있다. 하지만 현재의 유동인구 분석 방법에는 문제점이 존재한다. 따라서 이런 문제점들을 해결하고자 새로운 Population Counting Solution 을 제시하여 좀 더 정확하고 자동화된 유동인구 분석 시스템을 개발하고자 한다. Deep learning 기반의 객체 검출 알고리즘을 이용하여 실시간 영상 내의 사람들의 고유 객체 좌표 값을 추출해 객체의 이동을 정보를 이용하여 유동 인구를 분석한다. 이러한 유동인구 분석 시스템을 다양한 방면에 응용하여 경제효과와 편리함을 사회에 제공하고자 한다.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.12-28
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• 2024

This study aims to identify the trend of changes in tourist floating population before and after COVID-19 in major tourist destinations in Jeju Island through spatial analysis. Seongsan-eup and Andeok-myeon in Jeju Island were selected as the research area, and the research period was set at 1 year before and 2 years after the COVID-19 outbreak. For the analysis, mobile floating population data was refined and processed to calculate floating population distribution and floating population increase/decrease data. This was converted into spatial data and an overlay analysis was performed with location data of major tourist attractions. As a result of the analysis, it was confirmed that the floating population of indoor tourist attractions and small facilities decreased immediately after COVID-19, and that in open coastal areas or large facilities, the floating population decreased less or actually increased. In conclusion, in tourism development, it is necessary to identify changes in floating population according to the characteristics of tourist facilities, and it is necessary to develop tourism facilities and strategies that can respond to risk situations such as pandemics when developing tourist destinations.

• Journal of The Korean Society For Urban Railway
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• v.6 no.4
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• pp.373-381
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• 2018

The floating population that is index to figure out dynamic activities in urban area will be important in urban railway planning, but it is not useful because it is collected by posterior method. This study aims to investigate factors influencing floating population. The floating population data that was collected in Seoul for a month in December 2013 is used as dependent variable, and the negative binomial regression analysis is used in modelling. The number of households, number of employees, number of subway stations, and number of bus lines variables are statistically significant in predicting floating population.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.62-70
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• 2022

This study investigates the temporal structure and movement of floating people near university areas in Daegu metropolitan city, South Korea, before and after Covid-19. In order to determine Daegu's position, the current study compares Daegu and Seoul. The floating population is used as an index to reveal people's various activities in the area known as the local business district, which surrounds the university campus. The information was provided by mobile phone manufacturers. A municipal authority managed a public website where mobile data was made available. Several statistical and visualization techniques were used after the data pre-processing steps. As a result, the floating population fluctuation patterns in both cities in the first half of 2019 and 2020 were comparable. When the Covid-19 diffusion rate in Daegu stabilized in the second half of 2020, the floating population in Daegu increased slightly over the previous year, while the population in Seoul decreased due to the second wave of Covid-19.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.24-34
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• 2021

Estimation of the presence of people in real time is extremely useful for businesses in providing better services. Many companies and researchers have attempted various researches in order to count the number of floating population in specific space. Recently, as part of smart cities and digital twins, commercialization of measuring floating populations using Wi-Fi signals has become active in the public and private sectors. This paper explains the floating population measuring system from the perspective of general consumers(non-experts) who uses current population data. Specifically, it presents a method of estimating the floating population based on MAC-address values collected from smartphones. By distinguishing Real MAC-address and Random MAC-address values, we compare the estimated number of smartphone devices and the actual number of people caught on CCTV screens to evaluate the accuracy of the proposed method. And it appeared to have a similar correlation between the two datas. As a result, we present a method of estimating the floating population based on analyzing Wi-Fi Probe Requests

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.612-623
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• 2022

Estimation of the presence of people in real time is extremely useful for businesses in providing better services. Many companies and researchers have attempted various researches in order to count the number of floating population in a specific space. Recently, as part of smart cities and digital twins, commercialization of measuring floating populations using Wi-Fi signals has become active in the public and private sectors. In this paper we present a method of estimating the floating population based on MAC-address values collected from smartphones. By distinguishing Real MAC-address and Random MAC-address values, we compare the estimated number of smartphone devices and the actual number of people caught on CCTV screens to evaluate the accuracy of the proposed method. And it appeared to have a similar correlation between the two datas. As a result, we present a method of estimating the floating population based on analyzing Wi-Fi Probe Requests.