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http://dx.doi.org/10.12652/Ksce.2014.34.4.1317

A study on the Spatial Sampling Method to Minimize Spatial Autocorrelation of Spatial and Geographical Data  

Lee, Youn Soo (Hongik University)
Lee, Man Choul (Hongik University)
Lah, Kyung Beom (Hongik University)
Kang, Jun Mo (Hongik University)
Publication Information
KSCE Journal of Civil and Environmental Engineering Research / v.34, no.4, 2014 , pp. 1317-1325 More about this Journal
Abstract
The study focused on analyzing spatial sampling by minimizing autocorrelation of spatial based on spatial and geographical data. The study concluded two different ways of minimizing autocorrelation. First, it was important to use suitable spatial sampling method to alienate spatial autocorrelation from spatial or geographical data. The shear distribution rate of public transportation in Seoul resulted in high rate of autocorrelation. However, the study showed samples eliminated autocorrelation when samples were extracted with reasonable distance(above 400m) apart. Without spatial sampling the distortion of spatial data leads to false results; therefore, spatial sampling is indispensable. Second, factors which fluctuates shear distribution of public transportation spatial sampling changed before and after spatial sampling. This was caused by incapable of controling inherent spatial autocorrelation of the data.
Keywords
Spatial sampling; Spatial autocorrelation; Urban spatial structure; Public transportation use modal share;
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Times Cited By KSCI : 3  (Citation Analysis)
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