Abstract
This study approaches the spatial stratification phenomenon through a data-based social stratification approach. In addition, by applying a dissimilarity-based clustering algorithm, this study analyzes how regions cluster as well as their disparities, thereby analyzing socio-spatial inequalities. Ultimately, through map visualization, this study seeks to visually identify spatial forms of social inequality and gain insight into the social structure for policy implications. The results determine how the regions are socioeconomically structured and identify the social inequalities between the spaces.
Highlights
As social inequality worsens worldwide, its manifestation in complex urban environments has become a key issue in policy research
This study proposes that data reflecting the multifaceted characteristics of spaces have a certain pattern to measure spatial stratification
As discussed in the previous section, this study proposes that multifaceted data have a certain pattern that can be utilized to measure spatial stratification
Summary
As social inequality worsens worldwide, its manifestation in complex urban environments has become a key issue in policy research. Current study proposes a dissimilarity-based clustering method by focusing on this similarity and dissimilarity as reflected in data in order to measure spatial stratification. This study proposes that multifaceted data have a certain pattern that can be utilized to measure spatial stratification According to this data-based social stratification approach, structural patterns can be elucidated. Considering the direct and indirect effects of the transportation infrastructure on the region and the parking problems in Korean metropolitan areas, public investment in roads and public parking spaces are essential factors for residents (Talley, 1996; Yi et al, 2012; Ahn et al, 2014) Cultural facilities such as public libraries, museums, and art galleries form cultural capital and are essential elements affecting the quality of life, vitality, and performance of individuals (Andersen and Hansen, 2012).
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