Spatializing an Artist-Resident Community Area at a Building-Level: A Case Study of Garosu-Gil, South Korea
Jiman Park,
Jihang Kim and
Byungyun Yang
Additional contact information
Jiman Park: Smart Mobility Research Center, Myongji University, 116 Myongji-ro, Cheoin-gu, Yongin-si 17058, Gyeonggi-do, Korea
Jihang Kim: Land Geospatial Informatics Education Institute, Korea Land and Geospatial Informatics Corporation, 182 Yeonsudanji-gil, Sagok-myeon, Gongju 32522, Chungcheongnam-do, Korea
Byungyun Yang: Department of Geography Education, Dongguk University, Jung-gu, Seoul 04620, Korea
Sustainability, 2020, vol. 12, issue 15, 1-21
Abstract:
This study integrated a focus on geographical, physical, and commercial characteristics to explore the commercial gentrification phenomenon and its related statistical summaries in the area of Garosu-gil in Seoul’s Sinsa-dong ward. In particular, this study first collected parcel and building data and corresponding attribute information and mapped the resulting datasets in a geographic information system (GIS) environment. We then examined gentrification issues per building and conducted statistical analyses to investigate spatial patterns of commercial gentrification, which were used to develop criteria for determining degrees of gentrification. Third, this study conducted correlation and regression analyses to quantify the strength of the linear relationship between pairs of variables associated with primary factors contributing to commercial gentrification, and used a geographically weighted regression model (GWR) to help understand and predict spatial relationships between significant variables. The results showed positive correlations between several variables and commercial gentrification in the study area, namely neighborhood-convenience facilities, building ages, store rents, new franchise and restaurant businesses, distance to subways, and the presence of multiple roads. Based on its finding, there are key contributions of this study as follows. The first significant contribution of this study is developing measurement of gentrification levels that can be used by policy makers at each of four stages of the gentrification process. Furthermore, this paper develops a comprehensive approach for spatially identifying gentrifying neighborhoods across multiple time periods in 2- and 3-dimensions. It eventually helps urban planners implement preventative or supportive programs to protect lower-income residents and small businesses and thereby engender more sustainable community development.
Keywords: GIS mapping; spatial analysis; building levels; geographically weighted regression model; artist-resident community area (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:15:p:6116-:d:391674
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