Opening Gated Communities and Neighborhood Accessibility Benefits: The Case of Seoul, Korea
Abstract
:1. Introduction
2. Literature Review
3. Materials and Methods
3.1. Study Area
3.2. Data Sources
3.3. Methodology
3.4. Pedestrian Efficiency
4. Analysis Results
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Krizek, K.J.; Handy, S.L.; Forsyth, A. Explaining changes in walking and bicycling behavior: Challenges for transportation research. Environ. Plan. B Plan. Des. 2009, 36, 725–740. [Google Scholar] [CrossRef]
- Frank, L.D.; Sallis, J.F.; Conway, T.L.; Chapman, J.E.; Saelens, B.E.; Bachman, W. Many pathways from land use to health: Associations between neighborhood walkability and active transportation, body mass index, and air quality. J. Am. Plan. Assoc. 2006, 72, 75–87. [Google Scholar] [CrossRef]
- Yang, S.; Tan, W.; Yan, L. Evaluating accessibility benefits of opening gated communities for pedestrians and cyclists in China: A case study of Shanghai. Sustainability 2013, 13, 598. [Google Scholar] [CrossRef]
- Korean Statistical Information Service, 2018 Modal Share Data. 2018. Available online: https://kosis.kr/statHtml/statHtml.do?orgId=201&tblId=DT_201_00250_1996&vw_cd=&list_id=00000070&scrId=&s-qNo=&lang_mode=ko&obj_var_id=&itm_id=&conn_path=R1&path= (accessed on 11 January 2021).
- Dogan, O.; Han, J.; Lee, S. Analysis of large-scale residential development on walking environments in surrounding neighborhoods: A before-and-after comparison of apartment complex developments in Seoul, Korea. Sustainability 2020, 12, 7335. [Google Scholar] [CrossRef]
- McDonald, N.C.; Aalborg, A.E. Why parents drive children to school: Implications for safe routes to school programs. J. Am. Plan. Assoc. 2009, 75, 331–342. [Google Scholar] [CrossRef]
- Department for Transport. Manual for Streets; Thomas Telford Publishing: London, UK, 2017. Available online: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/341513/pdfmanforstreets.pdf (accessed on 12 January 2021).
- Fishman, R. The Open and The Enclosed: Shifting Paradigms in Modern Urban Design. In Companion to Urban Design; Routledge: Abingdon-on-Thames, UK, 2011; pp. 50–60. [Google Scholar]
- Jacobs, J. The Death and Life of Great American Cities; Random House: New York, NY, USA, 1961; pp. 55–74. [Google Scholar]
- Congress for the New Urbanism. 2001. Available online: https://www.cnu.org/sites/default/files/charter_english.pdf (accessed on 31 December 2020).
- Gehl, J. Life between Buildings: Using Public Space; Island Press: Washington, DC, USA, 2011. [Google Scholar]
- Järv, O.; Tenkanen, H.; Salonen, M.; Ahas, R.; Toivonen, T. Dynamic cities: Location-based accessibility modelling as a function of time. Appl. Geogr. 2018, 95, 101–110. [Google Scholar] [CrossRef]
- Yoon, T.; Lee, D.; Park, H. A study on basic analysis of the correlation between pedestrian environments of local community and apartment complex type—In case of increased length of pedestrian route by closed complex of apartment. J. Korean Inst. Cult. Archit. 2016, 64, 212–219. [Google Scholar]
- Sun, G.; Wallace, D.; Webster, C. Unravelling the impact of street network structure and gated community layout in development-oriented transit design. Land Use Policy 2020, 90, 104328. [Google Scholar] [CrossRef]
- Yang, D.; Yu, S. Assessing efficiency in physical layouts of pedestrian paths in apartment complexes. J. Korea Plan. Assoc. 2020, 55, 5–21. [Google Scholar] [CrossRef]
- Ai, T.; Yin, H.; Shen, Y.; Yang, M.; Wang, L. A formal model of neighborhood representation and applications in urban building aggregation supported by Delaunay triangulation. PLoS ONE 2019, 14, e0218877. [Google Scholar] [CrossRef] [Green Version]
- Kim, J.E.; Choi, M.J. Empirical analyses of physical exclusiveness of multi-family housing estates in Seoul and its socioeconomic effects. J. Korean Hous. Assoc. 2012, 23, 103–111. [Google Scholar] [CrossRef]
- Seo, M.; Choi, Y. A study on the effect of walking environment (characteristics) on apartment housing rental prices using multi-level model. J. Korean Soc. Civ. Eng. 2017, 37, 905–914. [Google Scholar]
- Cortright, J. Walking the Walk: How Walkability Raises Home Values in US Cities; CEOs for Cities: Washington, DC, USA, 2009. [Google Scholar]
- Pivo, G.; Fisher, J.D. The walkability premium in commercial real estate investments. Real Estate Econ. 2011, 39, 185–219. [Google Scholar] [CrossRef]
- Boyle, A.; Barrilleaux, C.; Scheller, D. Does walkability influence housing prices? Soc. Sci. Q. 2014, 95, 852–867. [Google Scholar] [CrossRef]
- Lucchesi, S.T.; Larranaga, A.M.; Cybis, H.B.B.; de Abreu e Silva, A.; Arellana, J.A. Are people willing to pay more to live in a walking environment? A multigroup analysis of the impact of walkability on real estate values and their moderation effects in two Global South cities. Res. Transp. Econ. 2020, 100976. [Google Scholar] [CrossRef]
- Sun, G.; Webster, C.; Chiaradia, A. Ungating the city: A permeability perspective. Urban Stud. 2018, 55, 2586–2602. [Google Scholar] [CrossRef]
- Southworth, M.; Owens, P.M. The evolving metropolis: Studies of community, neighborhood, and street form at the urban edge. J. Am. Plan. Assoc. 1993, 59, 271–287. [Google Scholar] [CrossRef]
- Schlossberg, M.; Johnson-Shelton, D.; Evers, C.; Moreno-Black, G. Refining the grain: Using resident-based walkability audits to better understand walkable urban form. J. Urban. Int. Res. Placemaking Urban Sustain. 2015, 8, 260–278. [Google Scholar] [CrossRef]
- Dekker, A. Conceptual distance in social network analysis. J. Soc. Struct. 2005, 6, 31. [Google Scholar]
- Liu, Y.; Wei, X.; Jiao, L.; Wang, H. Relationships between street centrality and land use intensity in Wuhan, China. J. Urban Plan. Dev. 2016, 142, 05015001. [Google Scholar] [CrossRef]
- Yue, H.; Zhu, X. Exploring the relationship between urban vitality and street centrality based on social network review data in Wuhan, China. Sustainability 2019, 11, 4356. [Google Scholar] [CrossRef] [Green Version]
- Kang, C.D. Effects of spatial access to neighborhood land-use density on housing prices: Evidence from a multilevel hedonic analysis in Seoul, South Korea. Environ. Plan. B Urban Anal. City Sci. 2019, 46, 603–625. [Google Scholar] [CrossRef]
- Dong, L.; Rinoshika, A.; Tang, Z. Dynamic evaluation on the traffic state of an urban gated community by opening the micro-inter-road network. Technologies 2018, 6, 71. [Google Scholar] [CrossRef] [Green Version]
- Yang, R.; Yan, H.; Xiong, W.; Liu, T. The study of pedestrian accessibility to rail transit stations based on KLP model. Procedia-Soc. Behav. Sci. 2013, 96, 714–722. [Google Scholar] [CrossRef] [Green Version]
- Sevtsuk, A.; Mekonnen, M. Urban network analysis toolbox. Int. J. Geomat. Spat. Anal. 2012, 22, 287–305. [Google Scholar] [CrossRef]
- Walker, J. Basics: Walking Distance to Transit. 2011. Available online: https://humantransit.org/2011/04/basics-walking-distance-to-transit.html (accessed on 24 September 2020).
- Park, J.; Ji, S.; Kim, E.; Jun, H. The application of Voronoi diagram into the space planning for urban design. In Proceedings of the 7th International Symposium on Architectural Interchanges in Asia (ISAIA 2008), Nicosia, Cyprus, 15–17 October 2008; pp. 524–528. [Google Scholar]
- Niu, H.; Lu, Y.; Savvaris, A.; Tsourdos, A. An energy-efficient path planning algorithm for unmanned surface vehicles. Ocean Eng. 2018, 161, 308–321. [Google Scholar] [CrossRef] [Green Version]
- Özcan, M.; Yaman, U. A continuous path planning approach on Voronoi diagrams for robotics and manufacturing applications. Procedia Manuf. 2019, 38, 1–8. [Google Scholar] [CrossRef]
- Wang, J.; Simacek, P.; Advani, S.G. Use of centroidal Voronoi diagram to find optimal gate locations to minimize mold filling time in resin transfer molding. Compos. Part A Appl. Sci. Manuf. 2016, 87, 243–255. [Google Scholar] [CrossRef] [Green Version]
- Ostrovsky-Berman, Y. Computing transportation Voronoi diagrams in optimal time. EuroCG 2005, 159–162. [Google Scholar]
- Lu, X.; Yan, H.; Li, W.; Li, X.; Wu, F. An algorithm based on the weighted network Voronoi Diagram for point cluster simplification. ISPRS Int. J. Geo-Inf. 2019, 8, 105. [Google Scholar] [CrossRef] [Green Version]
- Yu, W.; Chen, Y.; Chen, Z.; Xia, Z.; Zhou, Q. Service area delimitation of fire stations with fire risk analysis: Implementation and case study. Int. J. Environ. Res. Public Health 2020, 17, 2030. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Afyouni, I.; Ray, C.; Christophe, C. Spatial models for context-aware indoor navigation systems: A survey. J. Spat. Inf. Sci. 2012, 1, 85–123. [Google Scholar] [CrossRef] [Green Version]
- Al-Dahhan, M.R.H.; Schmidt, K.W. Voronoi boundary visibility for efficient path planning. IEEE Access 2020, 8, 134764–134781. [Google Scholar] [CrossRef]
- Okabe, A.; Satoh, T.; Furuta, T.; Suzuki, A.; Okano, K. Generalized network Voronoi diagrams: Concepts, computational methods, and applications. Int. J. Geogr. Inf. Sci. 2008, 22, 965–994. [Google Scholar] [CrossRef]
Measurement | Radius | Scenario 1 (Gated) | Scenario 2 (Partially Opened) | Scenario 3 (Fully Opened with Voronoi) | Pedestrian Efficiency (%) | ||
---|---|---|---|---|---|---|---|
Scenario 2 | Scenario 3 | ||||||
Reach | No. of benefitting building * | 400 m | - | 113 | 171 | 0.84% | 1.28% |
800 m | - | 464 | 830 | 3.46% | 6.19% | ||
Average index value | 400 m | 0.3549 | 0.3635 | 0.3678 | 2.42% | 3.61% | |
800 m | 1.4071 | 1.4432 | 1.4759 | 2.57% | 4.89% | ||
Gravity | No. of benefitting building * | 400 m | - | 174 | 356 | 1.30% | 2.66% |
800 m | - | 1645 | 2645 | 12.27% | 19.73% | ||
Average index value | 400 m | 0.1989 | 0.2037 | 0.2059 | 2.44% | 3.51% | |
800 m | 0.4814 | 0.4940 | 0.5035 | 2.62% | 4.59% | ||
Straightness | No. of benefitting building * | 400 m | - | 171 | 359 | 1.28% | 2.68% |
800 m | - | 1653 | 2657 | 12.33% | 19.82% | ||
Average index value | 400 m | 0.2628 | 0.2695 | 0.2733 | 2.54% | 3.99% | |
800 m | 1.0707 | 1.1050 | 1.1366 | 3.20% | 6.16% | ||
Betweenness | No. of benefitting building * | 400 m | - | 357 | 491 | 2.66% | 3.66% |
800 m | - | 1416 | 2063 | 10.56% | 15.39% | ||
Average index value | 400 m | 5.5168 | 5.6582 | 5.6718 | 2.56% | 2.81% | |
800 m | 38.4715 | 39.0389 | 39.6230 | 1.48% | 2.99% |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Dogan, O.; Han, J.; Lee, S. Opening Gated Communities and Neighborhood Accessibility Benefits: The Case of Seoul, Korea. Int. J. Environ. Res. Public Health 2021, 18, 4255. https://doi.org/10.3390/ijerph18084255
Dogan O, Han J, Lee S. Opening Gated Communities and Neighborhood Accessibility Benefits: The Case of Seoul, Korea. International Journal of Environmental Research and Public Health. 2021; 18(8):4255. https://doi.org/10.3390/ijerph18084255
Chicago/Turabian StyleDogan, Omer, Jaewon Han, and Sugie Lee. 2021. "Opening Gated Communities and Neighborhood Accessibility Benefits: The Case of Seoul, Korea" International Journal of Environmental Research and Public Health 18, no. 8: 4255. https://doi.org/10.3390/ijerph18084255
APA StyleDogan, O., Han, J., & Lee, S. (2021). Opening Gated Communities and Neighborhood Accessibility Benefits: The Case of Seoul, Korea. International Journal of Environmental Research and Public Health, 18(8), 4255. https://doi.org/10.3390/ijerph18084255