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http://dx.doi.org/10.5762/KAIS.2013.14.1.464

Characteristics for the Distribution of Elderly Population by Utilizing the Census Data  

Nam, Kwang-Woo (Department of Urban Design & Development, Kyungsung University)
Gwon, Il-Hwa (Department of Urban Design & Development, Kyungsung University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.14, no.1, 2013 , pp. 464-469 More about this Journal
Abstract
After city of Busan has been entered to the aging society in 2000, the city has the highest aging rate among 7 representative cities in 2011. Moreover, while entire population and number of average household are decreasing, over 65 years old of elderly population is rapidly increasing. So, it is possible to enter the super-aged society, where aging rate would be about 20% after 2020. The purpose of this study is that older housing-related analysis is consisted of dong-unit, and this led microscopic analysis has become necessary. Surveys from 2000 through 2010, census aggregate (output area) unit of spatial analysis was conducted. Take advantages of this, aging population and area, soaring area, high-density areas, such as the region of interest were primary extracted, and microscopic location and spatial distribution patterns were analyzed. Upon analysis, aging population is concentrated in the city and adjacent area, the highlands, and 10 years of increasing rate was more than 30 times in certain aggregate. Regarding the characteristic of these areas, the original city center, Busan, especially concentrated and intensified in aging population. Also, 2000 to 2010, the overall distribution pattern of Busan has identified aging population that is increasingly being distributed. This is the result, which is confronted with previous research result. Entering a super aged-society for the future is accordance with migration of social costs and improve the quality of life of elderly. And this could be the basic information to use the spatial dimension for the corresponding.
Keywords
Census Data; Output Data; Super-Aged Society; Hotspot Analysis; Cluster and Outlier Analysis;
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  • Reference
1 Anselin, 2007, Exploring spatial data with GeoDaTM: A workbook. Center for Spatially Integrated Socaial Science
2 Kyeong-Seok Jeong, Jae-Hee Jeong, Tae-Heon Moon, Heo Sun-Young. Analysis of Spatio-temporal Pattern of Urban Crime and Its Influencing Factors, Journal of the korean Association of Geographic Information Studies, Vol 12(1), pp.12-25, 2009
3 Getis, A. and Ord, J. 1996, Local spatial statistics: An overview, in Longly, P. and Batty, M.(eds), Spatial Analysis: Modeling in GIS Environment, Geoinformation International, Cambridge, 261-277.
4 Kam-Young Kim, Jee-Hye Park. Detecting Potential Urban Regeneration Districts GIS and Spatial Clustering Analysis, Journal of the Korean Urban Geography Society, Vol 15(2), pp.67-80, 2012
5 Eui-Taek Suh, Sung-Il Kim. A Study on the Change of the Population Distribution in Pusan, Journal of the Korean Planners Association, Vol 33(2), pp.29-49, 1998   과학기술학회마을
6 Su-Nam Kim, Young-Ho Park, Chang-Hwan Choi. Special Distribution Characteristics of Aging of Population in Busan, Korean Urban Management Association, Vol 18(3), pp.23-48, 2005