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A Study on Scale Effects of the MAUP According to the Degree of Spatial Autocorrelation - Focused on LBSNS Data -
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 Title & Authors
A Study on Scale Effects of the MAUP According to the Degree of Spatial Autocorrelation - Focused on LBSNS Data -
Lee, Young Min; Kwon, Pil; Yu, Ki Yun; Huh, Yong;
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 Abstract
In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.
 Keywords
LBSNS;MAUP;Moran's I;spatial autocorrelation;spatial error model;
 Language
Korean
 Cited by
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