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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.

At present, Korean one-person households have been continuously increased in 2014년 3월 8일 접수

A surprising aspect of the agglomeration economy is the lack of attention to the impact on the physical environment. Even in the field of spatial planning, road infrastructure has been built in situations where the consideration of the agglomeration economy is insufficient. The urban scaling proposed by theoretical physicists is an excellent tool to solve this problem but is only at the level of conceptually comparing the index values extracted by individually scaling socioeconomic indicators and urban infrastructure with the population. Accordingly, the frame model scales the urban infrastructure with the number of workers by industry sector and includes a density externality structure so that the agglomeration economy and urban infrastructure can be linked directly. Three experiments were conducted to verify the frame model: first, the Zipf distribution of economic activity found straight lines in large cities, peaks in medium cities and hills in small cities; the cities were categorised by urban size. The second experiment verified that linearisation was due to Jacobs externalities, while the third confirmed that the peak was due to Marshall–Arrow–Romer externalities. Moreover, in distinguishing traditional and modern industries, thresholds of 0.6 in agglomeration and 1.0 in economic interaction were found.