• Journal of the Korean Geographical Society
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• v.46 no.2
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• pp.197-211
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• 2011

Due to the complexity of spatial interaction and the necessity of spatial representation and modeling, aggregation of spatial interaction data is indispensible. Given this, the purpose of this paper is to evaluate the effects of modifiable areal unit problem (MAUP) on a spatial interaction model. Four aggregation schemes are utilized at eight different scales: 1) randomly select seeds of district and then allocate basic spatial units to them, 2) minimize the sum of population weighted distance within a district, 3) maximize the proportion of flow within a district, and 4) minimize the proportion of flow within a district. A simple Poisson regression model with origin and destination constraints is utilized. Analysis results demonstrate that spatial characteristics of residuals, parameter values, and goodness-of-fit of the model were influenced by aggregation scale and schemes. Overall, the model responded more sensitively to aggregation scale than aggregation schemes and the scale effect on the model was varied according to aggregation schemes.

• Journal of Welding and Joining
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• v.25 no.4
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• pp.1-3
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• 2007

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.277-292
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• 2017

The development impact fee (DIF) zoning is a very beneficial public tool to provide the pre-planned urban infrastructures in those areas where significant urban sprawl had already taken place. In order to guarantee its benefit, however, it is required to designate the zone boundaries accurately and consistently. This study, in this context, tries to test the validity of the 50m-grid suggested in the official DIF manual, and to compare an alternative Hot Spot Analysis tool with the existing Spatial Aggregation method in configuring the zone boundaries. The results indicate that, unlike the case of population growth rate, current 50m grid size could not be much adequate in the case of using the development-permit increase rate to configure the primary DIF zones. Also, the optimal grid sizes seem to differ in the cases of Spatial Aggregation and Hot Spot Analysis. Further extended studies, in this regard, seem necessary to check the validity of the existing grid-size criteria as well as the boundary configuration methods.

• Journal of the Korean association of regional geographers
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• v.16 no.6
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• pp.673-688
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• 2010

The purpose of this study is to develop an optimization model for reconstructing local administrative districts using spatial analysis and modeling. For this, literature related to reorganization of local administrative systems was critically reviewed and criteria for redistricting were extracted. An optimization model for reconstructing administrative districts was formulated based on these criteria. The model considered three criteria; homogeneity within a reconstructed district, equity among reconstructed districts, and spatial arrangement. Homogeneity for relieving spatial mismatch between administrative and living(economic) boundaries is measured by spatial interaction within a district. Equity among districts is evaluated using population, area, and financial independence. Finally, spatial arrangement is measured by compactness and contiguity. The developed optimization model was implemented using Automated Zoning Procedure(AZP) in GIS environment and applied to a problem aggregating Si-Gun administrative units into broader districts. Application results demonstrate that the model can provide optimal districts according to alternative objective functions.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.150-159
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• 2015

This study attempted to test the scale effect of MAUP, particularly focusing on the spatial autocorrelation of sex crime, correlations among neighborhood structural variables, and causal mechanism leading to sex crime. Analysis results of nation-wide Eup-Myon-Dong and Si-Gun-Gu data discovered that the spatial autocorrelation, correlations among independent variables, and determinant coefficient of multiple regression of Si-Gun-Gu level were generally bigger and stronger than those of Eup-Myon-Dong, which appeared to be due to the averaging effect. Regarding the causal effect to sex crime, two interesting results were found: First, the ratio of non-apartment residency lowered sex crime at both levels contrary to the hypothesis. Second, the ratio of food and lodging increased sex crime only at Eup-Myon-Dong level. These suggested that future research need to perform more detailed analyses dividing data into subsets such as urban vs. rural and/or economically advantaged vs. disadvantaged areas.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.25-33
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• 2016

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.