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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 meth od to alienate spatial autocorrelation from spatial or geographical data. The shear distribution rate of public transportation in Seo ul 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; therefor e, spatial sampling is indispensable. Second, factors which fluctuates shear distribution of public transportation spatial sampling change d before and after spatial sampling. This was caused by incapable of controling inherent spatial autocorrelation of the data.Key words : Spatial sampling, Spatial autocorrelation, Urban spatial structure, Public transportation use modal share???             ???      .     . ,               .          ???     .   (400m)     ???   .   ,       ,           . ,           .           . : , , ,  Regional and Urban Planning

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