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http://dx.doi.org/10.12672/ksis.2014.22.1.009

A Study on Estimation of the Greenhouse Gas Emission from the Road Transportation Infrastructure Using the Geostatistical Analysis -A Case of the Daegu-  

Lee, Sang Woo (Department of Spatial Information, Kyungpook National University)
Lee, Seung Wook (Department of Spatial Information, Kyungpook National University)
Lee, Seung Yeob (School of Architecture, Gyeongju University)
Hong, Won Hwa (School of Architecture and Civil Engineering, Kyungpook National University)
Publication Information
Spatial Information Research / v.22, no.1, 2014 , pp. 9-17 More about this Journal
Abstract
This study was intended to reliably predict the traffic green house gas emission in Daegu with the use of spatial statistical technique and calculate the traffic green house gas emission of each administrative district on the basis of the accurately predicted emission. First, with the use of the traffic actually surveyed at a traffic observation point, and traffic green house gas emission was calculated. Secondly, on the basis of the calculation, and with the use of Universal Kriging technique, this researcher set a suitable variogram modeling to accurately and reliably predict the green house gas emission at non-observation point suitable through spatial correlation, and then performed cross validation to prove the validity of the proper variogram modeling and Kriging technique. Thirdly, with the use of the validated kriging technique, traffic green gas emission was visualized, and its distribution features were analyzed to predict and calculate the traffic green house gas emission of each administrative district. As a result, regarding the traffic green house gas emission of each administration, it was found that Bukgu had the highest green house gas emission of $291,878,020kgCO_2eq/yr$.
Keywords
Traffic Greenhouse Gas Emission; Geostatistical; Universal-Kriging; Variogram Modeling;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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