• Journal of the Korean Geographical Society
• /
• v.46 no.2
• /
• pp.197-211
• /
• 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 Korean Society for Geospatial Information Science
• /
• v.24 no.1
• /
• pp.25-33
• /
• 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.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.12 no.1
• /
• pp.80-87
• /
• 2009

The purpose of this study is to analyze the MAUP's effect in visibility analysis using GIS. MAUP normally occurs in the process in terrain spatial analysis including visibility analysis. There are two different types of grid data(based on digital map and Digital Terrain Elevation Data) and 10 different types of areal units are made for modeling, such as $5m{\times}5m,\;10m{\times}10m,\;15m{\times}15m,\;20m{\times}20m,\;25m{\times}25m,\;30m{\times}30m,\;35m{\times}35m,\;40m{\times}40m,\;45m{\times}45m,\;50m{\times}50$. By analyzing the result, it was possible to observe varying viewshed areas according to different grid cell sizes and the viewshed area did not varied linearly as expected. From a general point of view, smaller unit data map out the real world in more detail, but the results of modeling do not always reach a good conclusion when data are used in modeling for terrain analysis because of the MAUP' effect. The grid cell sizes of 30m or less seems to be adequate for visibility analysis, including terrain analysis considering vegetation heights.

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

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.11a
• /
• pp.3-8
• /
• 2003

Census data are usually provided at an aggregated level. However, the aggregated data are essentially arbitrary geographical areas. The areal units used to report census data have no natural or meaningful geographical identity. Unfortunately, this means that analyses of these area aggregations may be conditional upon the set of zones, which are presented. This effect is known as the modifiable areal unit problem (MAUP) and has two related aspects. First, scale effect is the variation in numerical results that occurs due to the number of zones used in an analysis. Second, results may also differ between different ways of aggregating exactly the same data to the same scale; this may be called the aggregation effect (Openshaw, 1984). This study aims to provide a practical tool for the study of MAUP. I have created a set of 91 areal units based on 280 basic units in Nonhyun-2 dong to solve zoning problem and scale problem. We can easily recognize the importance of areal classification as statistics were different according to areal classification.

• 한국지역지리학회:학술대회
• /
• 2009.08a
• /
• pp.81-81
• /
• 2009

• Journal of the Korean Association of Geographic Information Studies
• /
• v.16 no.3
• /
• pp.40-53
• /
• 2013

Most of the existing domestic studies to identify the distribution of longevity population and influencing factors oriented confirmatory approach. Furthermore, most of the studies in this research topic simply have used their own definition of spatial unit of analysis or employed arbitrary spatial units of analysis according to data availability. These research approaches can not sufficiently reflect the spatial characteristic of longevity phenomenon and exposed to the Modifiable Aerial Unit Problem(MAUP). This research performed the Exploratory Spatial Data Analysis(ESDA) to identify the spatial autocorrelation of the distribution of longevity population and investigated whether the modifiable areal unit problem in the aspect of scale effect using spatial population data in Korea. We used Si_Gun_Gu and Eup_Myeon_Dong as two different spatial units of regional longevity indicators measured. Then, we applied Getis-Ord Gi* to investigate the existence of spatial hot spots and cold spots. The results from our analysis show that there exist statistically significant spatial autocorrelation and spatial hot spots and cold spots of regional longevity at both Si_Gun_Gu and Eup_Myeon_Dong levels. This result implies that the modifiable areal unit problem does exist in the studies of spatial patterns of longevity population distribution. The demand for longevity researches would be increased inevitably. In addition, there were apparent differences for the global spatial autocorrelation and local spatial cluster which calculated different spatial units such as Si_Gun_Gu and Eup_Myeon_Dong and this can be seen as scale effect of MAUP. The findings from our analysis show that any study in this topic can mislead results when the modifiable areal unit problem and spatial autocorrelation are not explicitly considered.

• Spatial Information Research
• /
• v.10 no.2
• /
• pp.185-199
• /
• 2002

The objective of this study is to investigate the suitable spatio-temporal analysis method considering the zoning effect of spatial analysis termed the modifiable areal unit problem(MAUP). In former studies of spatio-temporal analysis, there were disagreement between attribute data with spatial data, because of variation of administrative district aggregating attribute data. It is need to consider how the analysis zone effects spatial characteristics and spatio-temporal variation of urban region through land price variation analysis. This study considers MAUP through basic mesh system, which is composed of micro grid. Mesh system can solve disagreement of resolution between spatial data and attribute data.

• Journal of the Korean Geographical Society
• /
• v.48 no.6
• /
• pp.879-896
• /
• 2013

The assessed land values and housing prices have been widely utilized as a basic information for the land and house trades and for evaluating governmental and local taxes. However, there exists a price difference in actual markets between the assessment level and assessed land values or housing prices. This paper emphasizes the spatial mismatch between the assessed land values and housing market prices and particularly addresses the following two aspects by focusing on spatial effects of the modifiable areal units, which would substantially affect the estimation of the assessed land values and housing prices. First, we examine the spatial distributions of the assessed land values and housing market prices, and the gap between those prices, on the basis of the aggregated spatial units(i.e., aggregation districts). Second, we explore the scale effect of the MAUP(modifiable areal unit problem) generally embedded in estimating the prices of the sampled standard lands and houses, and calibrating the correction index for the land values and housing prices for the individuals. For the application, we analysed the land values and housing prices in Seoul utilizing GIS and statistical software. As a result, some spatial clusters that the housing market prices are significantly higher than the assessed land values were identified at a finer geographic level. Also, it was empirically revealed that the statistical results from the regression of regional variables on the assessed land values for the individuals are significantly affected by the aggregation levels of the spatial units.

• Proceedings of the KGS Conference
• /
• 2006.06a
• /
• pp.29-30
• /
• 2006