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Spatial Pattern Analysis of CO2 Emission in Seoul Metropolitan City Based on a Geographically Weighted Regression
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 Title & Authors
Spatial Pattern Analysis of CO2 Emission in Seoul Metropolitan City Based on a Geographically Weighted Regression
Kim, Dong Ha; Kang, Ki Yeon; Sohn, So Young;
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 Abstract
Effort to reduce energy consumptions or CO2 emissions is global trend. To follow this trend, spatial studies related to characteristics affecting energy consumptions or CO2 emissions have been conducted, but only with the focus on spatial dependence, not on spatial heterogeneity. The aim of this study is to investigate spatial heterogeneity patterns of CO2 emission based on socio-economic factors, land-use characteristics and traffic infrastructure of Seoul city. Geographically Weighted Regression (GWR) analysis was performed with 423 administrative district data in Seoul. The results suggest that population and employment densities, road density and railway length in most districts are found to have positive impact on the CO2 emissions. Residential and green area densities also have the highest positive impact on CO2 emissions in most districts of Gangnam-gu. The resulting model can be used to identify the spatial patterns of CO2 emissions at district level in Seoul. Eventually it can contribute to local energy policy and planning of metropolitan area.
 Keywords
CO2 Emission;Energy Consumptions;Seoul Metropolitan City;Spatial Heterogeneity;Geographically Weighted Regression;
 Language
Korean
 Cited by
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