In any type of geographic data analysis defining the primary unit has direct effect on the results. The key point in spatial studies is the exact definition of areal units. The necessity of defining the basic unit of study is that for instance if once we examine the rel More
In any type of geographic data analysis defining the primary unit has direct effect on the results. The key point in spatial studies is the exact definition of areal units. The necessity of defining the basic unit of study is that for instance if once we examine the relationship between income and crime rate in the neighborhood unit and again in the level of urban area, different results will be obtained. This problem originates from the fact that raw data (e.g. census) are shown in the census block format. So we have to aggregate this data into neighborhood units and urban areas or any other basic unit for our study. Since the choice of these basic units does not have any rule and is arbitrary, different results will be obtained. In fact results of statistical analysis are not independent of the scale at which analysis has been done. This problem was first identified by Gehlke and Biehlin as modifiable areal unit problem (MAUP).
The purpose of this study is to identify the basic areal units which make the least bias in raw data after data aggregation in the unit. We have applied a comparative research method and layers of census blocks are utilized for statistical analysis. In this article, we have selected three basic units based on urban network, urban locality and fishnet as well as using twenty demographic indicators and measures of central dispersion and correlation to examine the effect of MAUP. The results indicate that rectangular base unit is less affected by the MAUP.
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