An Analysis of the Relationship Between Resettlement and Housing Redevelopment Characteristics

The reason that compulsory removals of a low-quality housing redevelopment such as involuntary or unintentional migration present a problem for urban communities is that whether involuntary movers adapt themselves to their new home has an influence on the urban communities that surround them. Moreover, involuntary emigrants have higher probability of choosing faulty residential areas than voluntary emigrants do. This gives rise to a problem of another residential migration for involuntary movers. In order to solve these problems, there is a need for a new housing policy that enables original residents to come back to their old community. However studies for resettlement had not conducted subjects about housing redevelopment characteristics which influences the involuntary movers directly. Instead personal microscopic characteristics such as statistics of resettlement, the moving distance, the reason of moving, improvement of living environment, had been main subjects of farmer studies. So the purpose of this study is to analyze an analysis of the relationship between resettlement and housing redevelopment characteristics. The data used in this study was obtained at 47 areas designated by Seoul (metropolis) since 1990 for redevelopment. Cluster Analysis Is used for dividing high rate of resettlement with low rate of resettlement and Regression Analysis is used for the analysis of the relationship between resettlement and housing redevelopment characteristics. The results of examining the effects of a redeveloped housing complex on returning residents at 47 areas designated by Seoul (metropolis) since 1990 fur redevelopment are as follows: First, A housing complex with a high returning rate (remove-in rate?) has no state/public land, unauthorized building owners who are in the low-income brackets, and few interested parties such as union members. This is the characteristic of a redeveloped housing complex with a short-period project span. On the contrary, a housing complex that has a low returning rate is crowded by state/public land, and numerous unauthorized building owners, and interested parties. Second, According to the linear regression analysis, among the factors that affect returning residents, 'physical properties(characteristics) of a region', 'population properties within a region', and 'properties of a project span' indicate a negative(-)influence whereas 'properties of a complex density' shows a positive(+) influence. In a nutshell, the more the physical properties, population properties, projectspan properties, the lower the returning rate and the more the complex density properties, the higher the returning rate. In detail, an area with many small land and new/large buildings, a high population, and a long project duration has a low returning rate of original residents while an area holding large capacity and buildings with many number of floors (multiple-storied building) has a high returning rate.

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