• Journal of the Economic Geographical Society of Korea
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• v.22 no.3
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• pp.351-365
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• 2019

This study aims to predict the changes in population distribution in Korea by considering spatio-temporal characteristics of major migration reasons. For the purpose, we analyze the spatio-temporal characteristics of each major migration reason(such as job, family, housing, and education) and estimate the transition probability, respectively. By appling Markov chain model processes with the ChapmanKolmogorov equation based on the transition probability, we predict the changes in the population distribution for the next six years. As the results, we found that there were differences of population changes by regions, while there were geographic movements into metropolitan areas and cities in general. The methodologies and the results presented in this study can be utilized for the provision of customized planning policies. In the long run, it can be used as a basis for planning and enforcing regionally tailored policies that strengthen inflow factors and improve outflow factors based on the trends of population inflow and outflow by region by movement factors as well as identify the patterns of population inflow and outflow in each region and predict future population volatility.

• Journal of the Korean association of regional geographers
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• v.22 no.1
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• pp.251-266
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• 2016

Intelligent interpolation methods such as dasymetric mapping are considered to be the best way to disaggregate zone-based population data by observing and utilizing the internal variation within each source zone. This research reviews the advantages and problems of the dasymetric mapping method, and presents a geographically weighted regression (GWR) based method to take into consideration the spatial heterogeneity of population density - land cover relationship. The locally adaptive intelligent interpolation method is able to make use of readily available ancillary information in the public domain without the need for additional data processing. In the case study, we use the preclassified National Land Cover Dataset 2011 to test the performance of the proposed method (i.e. the GWR-based multi-class dasymetric method) compared to four other popular population estimation methods (i.e. areal weighting interpolation, pycnophylactic interpolation, binary dasymetric method, and globally fitted ordinary least squares (OLS) based multi-class dasymetric method). The GWR-based multi-class dasymetric method outperforms all other methods. It is attributed to the fact that spatial heterogeneity is accounted for in the process of determining density parameters for land cover classes.

• 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.

• Journal of the Korean Geographical Society
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• v.46 no.1
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• pp.67-80
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• 2011

Choropleth mapping of population distribution is based on the assumption that people are uniformly distributed throughout each enumeration unit. Dasymetric mapping technique improves choropleth mapping by refining spatially aggregated data with residential information. Further, pycnophylactic interpolation can upgrade dasymetric mapping by considering population distribution of neighboring areas, while preserving the volumes of original units. This study proposed a combined solution of dasymetric mapping and pycnophylactic interpolation to improve the accuracy of population density distribution. Specifically, the dasymetric method accounts for the spatial distribution of population within each census unit, while pycnophylactic interpolation considers population distribution of neighboring area. This technique is demonstrated with 1990 census data of the Athens, GA. with land use land cover information derived from remotely-sensed imagery for the areal extent of populated areas. The results are evaluated by comparison between original population counts of smaller census units (census block groups) and population counts of the grid map built from larger units (census tracts) aggregated to the same areal units. The estimated populations indicate a satisfactory level of accuracy. Population distribution acquired by the suggested method can be re-aggregated to any type of geographic boundaries such as electoral boundaries, school districts, and even watershed for a variety of applications.

• Spatial Information Research
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• v.22 no.3
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• pp.89-99
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• 2014

The aim of this study is to represent the residential population distribution in Seoul, Korea more precisely through the dasymetric mapping method. Dasymetric mapping can be defined as a mapping method to calculate details from truncated spatial distribution of main statistical data by using ancillary data which is spatial data related to the main data. In this research, there are two types of data used for dasymetric mapping: the population data (2010) based on a output area survey in Seoul as the main data and the building footprint data including register information as ancillary spatial data. Using the binary method, it extracts residential buildings as actual areas where residents do live in. After that, the regression method is used for calculating the weights on population density by considering the building types and their gross floor areas. Finally, it can be reproduced three-dimensional density of residential population and drew a detailed dasymetric map. As a result, this allows to extract a more realistic calculating model of population distribution and draw a more accurate map of population distribution in Seoul. Therefore, this study has an important meaning as a source which can be applied in various researches concerning regional population in the future.

• Journal of the Korean Regional Science Association
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• v.33 no.3
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• pp.79-100
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• 2017

This study provides the insight into the aged employment provision issue for the aged-low growth era. For the purpose, we analyze the national trend of the age demographic and occupational employment in first. And then we investigate the spatial characteristics of employment of the aged in the Seoul Metropolitan area which has the highest elderly population by utilizing location quotient, factor analysis, and K-means cluster analysis. As the result, we found that the spatial distribution patterns of the residence and workplace of the elderly were nearly coincided with each other. Furthermore, five clusters of the aged distribution have been determined according to the industrial-occupational-demographic attributes. The result revealed clear spatial segrmentation: Most of elderly population of the research area have been engaged in the low-level service jobs, while elderly population employed to the educated-knowledged based high-level jobs has been distributed at a few cores. The results could be applied to the practical use for regional employment planning for the aged.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.1
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• pp.20-33
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• 2018

Population distribution in urban space varies with transportation flow changing along time of day. Transportation flow is directly affected by the activities of urbanites and the distribution of related facilities, since the flow is the result of moving to the point where the facilities associated with their activities are located. It is thus necessary to analyze the spatio-temporal characteristics of the urban population distribution by integrating the distribution of activity spaces related to the daily life of urbanites and the flow of transportation. The purpose of this study is to analyze the population distribution in urban space with daily and weekly time bases using the building database and T-card database in the city of Seoul, which is rich in information on land use and transportation flow. For a time-based analysis that is difficult to grasp by general statistical techniques, a four-dimensional visualization method combining time and space using a Java program is devised. Dynamic visualization in the four-dimensional space and time allows intuitive analysis and makes it possible to understand more effectively the spatio-temporal characteristics of population distribution. For this purpose, buildings are classified into three activity groups: residential, working, and commercial according to their purpose, and the number of passengers traveling to and from each stop site of bus and subway networks in the T-card database for one week is calculated in one-minute increments, Visualizing these and integrating transportation and land use, we analyze spatio-temporal characteristics of the population distribution in Seoul. As a result, it is found that the population distribution of Seoul displays distinct spatio-temporal characteristics according to land use. In particular, there is a clear difference in the population distribution pattern along the time axis according to the mixed aspects of working, commercial, and residential activities. The results of this study can be very useful for transportation and location planning of city facilities.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.391-397
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• 2008

This paper analyzes the spatial patterns of population distribution in Seoul Metropolitan Area in terms of spatial association using spatial statistics and spatial exploratory technique. Our empirical analysis based on global index shows that, in Seoul Metropolitan Area, the population had been distributed with strong positive spatial association over the period of 1980-2005. It implies that the population of each region is affected by the population distribution of adjacent regions. In addition, the analysis using local index was conducted for detecting the local patterns of spatial association, and the result shows that the clusters of population had been moved in the direction of West(Incheon and Bucheon) and South(Anyang and Seongnam) of Seoul where a large scale of lands or towns were developed over the period. These results will be the preliminary data for establishing management and development plans of Seoul Metropolitan Area.

• Spatial Information Research
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• v.18 no.5
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• pp.107-117
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• 2010

Taking the East-Hwasung area as the case, this study first builds gridded population data based on the municipal population survey raw data, and then measures, by way of GIS tools, the major urban spatial variables that are thought to influence the composition of the regional population. For the purpose of comparison, the urban models based on the Genetic Algorithm technique and the regression technique are constructed using the same input variables. The findings indicate that the GA output performed better in differentiating the effective variables among the pilot model variables, and predicted as much consistent and meaningful coefficient estimates for the explanatory variables as the regression models. The study results indicate that GA technique could be a very useful and supplementary research tool in understanding the urban phenomena.

• Journal of the Korean Geographical Society
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• v.51 no.4
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• pp.525-539
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• 2016

This study attempts to predict the changes in the spatial distribution of occupational employment in Korea by applying Markov Chain Model. For the purpose we analyze the job-related migration pattern and estimate the transition probability with the last six years job-related migration data. By applying the Chapman-Kolmogorov equation based on the transition probability, we predict the changes in the spatial distribution of occupational employment for the next ten years. The result reveals that the employment of professional jobs is predicted to increase at every city and region except Seoul, while the employment of elementary labor jobs is predicted to increase slightly in Seoul. In particular, Gangwon-do and Chuncheongdo are predicted to increase in the employment of all occupational jobs.