JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Analysis of Eunpyeong New Town Land Price Using Geographically Weighted Regression
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Analysis of Eunpyeong New Town Land Price Using Geographically Weighted Regression
Jung, Hyo-jin; Lee, Jiyeong;
  PDF(new window)
 Abstract
Newtown Business of Seoul had been performed to reduce deterioration of Gangbuk and economic inequality between Gangnam and Gangbuk. According to this, Eunpyeong-gu was set as test-bed for Newtown business and Newtown business had been completed until 2013. This study aims to analyze the influence of social and economical factors which affect land price using GWR (Geographically Weighted Regression) considered spatial effect. As a result of analysis, GWR model demonstrated a better goodness-of-fit than OLS (Ordinary least square) model typically used in most study. Furthermore, AIC value and Moran's I of residual prove that GWR model is more suitable than OLS model. GWR model enable to explain more detailed than global regression model as coefficient and sign show different value locally. In future, this research will be helpful to develop Eunpyeong-gu considering spatial characters and strength effectiveness of development.
 Keywords
Eunpyeong Newtown;Newtown Projects;Land Value;Geographically Weighted Regression;
 Language
Korean
 Cited by
1.
An Analysis on the Spatio-temporal Heterogeneity of Real Transaction Price of Apartment in Seoul Using the Geostatistical Methods, Journal of Korean Society for Geospatial Information System, 2016, 24, 4, 75  crossref(new windwow)
2.
Performance evaluation of OCO-2 XCO2 signatures in exploring casual relationship between CO2 emission and land cover, Spatial Information Research, 2016, 24, 4, 451  crossref(new windwow)
 References
1.
Lee, C. M; Kim, M. K. 2009, A Critical Review on New-Town Projects in Seoul, Korean Association For Housing Policy Studies, 17(2):283-308.

2.
Min, W. K. 2007, An Analysis on the Urban Spatial Structure by Land Price Fluctuation, Jeonju University.

3.
Lee, H. Y; Noh, S. C. 2013, Statistics Analysis, Moonwoo-sa.

4.
Wang, Y. H. 2005, Land value fluctuation caused by the designation fo the Kangbuk Newtown area: Case study focused on kilum and Wangshimri Newtown, Sungkyunkwan University.

5.
Hong, J. H. 2005, The Hedonic Impacts on the Apartment Prices of the Newtown Projects in the River-North Area; The Case of Gil-Eum Newtown, Hongik University.

6.
Ham, J. S. 2010, An Analysis of Land Price Changes by Designation of Urban Renewal District, Hanbat University.

7.
Shonkwiler, J. S; Reynolds, J. E. 1986, A Note on the Use of Hedonic Price Models in the Analysis of Land Prices at the Urban Fringe, Land Economics, 62(1):58-63. crossref(new window)

8.
Basu, S; Thibodeau, T. G. 1998, Analysis of Spatial Autocorrelation in House Prices, Journal of Real Estate Finance and Economics, 17(1):61-85. crossref(new window)

9.
Tsutsumi, M; Seya, H. 2008, Measuring the Impact of Large-scale Transportation Projects on Land Price using Spatial Statistical Models, Papers in Regional Science, 87(3):385-401. crossref(new window)

10.
Kim, S. W; Chung, K. S. 2010, The Appraisal of Hedonic Price Models to the Housing Policy; Focused on the Spatial Econometrics Models, Korean Journal of Policy Analysis and Evaluation, 20(3):115-134.

11.
Kang, Y. I; Kim, H, C. 2012, The Impact of Transit Facilities on Land Prices : Experiences at Seoul Station and Cheongnyangni Station, Korean Urban Management Association, 25(3):139-159.

12.
Gao, X; Asami, Y. 2005, Influence of Spatial Features on Land and Housing Prices, Tsinghua Science and Technology, 10(3):344-353. crossref(new window)

13.
Du, H; Mulley, C. 2006, Relationship between Transport Accessibility and Land Value; Local Model Approach with Geographically Weighted Regression, Transportation Research Record, 1977 (2006):197-205 crossref(new window)

14.
Kim, H. Y; Jun, C. M. 2012, Land Values Analysis Using Space Syntax and GWR, Journal of the Korean Association of Geographic Information Studies, 15(2):35-45. crossref(new window)

15.
Oh, Y. K; Kang, J. K; Kim, J. M. 2014, Analysis of Regional Characteristics that Affect Housing Prices using a GWR Model, Korean Association of Tax & Accounting, 40(2014):1-17.

16.
Kim, J. S. 2013, Analysis on Policy Network of Urban Reorganization Project in Seoul: Case Study on Eunpyeong New Town, Kyunghee University.

17.
Heo, C. M. 2010, A Study on Characteristics of a Changes of Neighboring Commercial Land Price caused by the Multi-Complex Station; Focused on Wangsimni Private-invested Station, University of Seoul.

18.
Jo, Y. J. 2008, A Study on Location Factor of the Vicinity of Station Land Price Considering Pedestrian Assess Characteristics, Hanyang University.

19.
Fotheringham, A. S; Brunsdon, C; Charlton, M. 2002, Geographically Weighted Regression; the analysis of spatially varying relationships, Wiley.