Scale, aggregation, and the modifiable areal unit problem

Abstract

The modifiable areal unit problem (MAUP) is a serious analytical issue for analysts using spatial data. The MAUP manifests itself through the instability of a wide range of statistical results derived from analysis on spatially organized data. When spatial data are aggregated, the results are conditional on the spatial scale at which they are conducted, and the configuration of the areal units that are employed to represent the data. Such uncertainty means that the results of spatial data where the MAUP has not been considered explicitly should be treated with caution. Although solutions have been proposed, none have been applicable in more than a couple of specific cases. As such, it is likely that the MAUP will never be truly solved. This chapter charts the two related aspects of the MAUP, the scale and zonation effects, and details the role of spatial autocorrelation in understanding the processes in the data that lead to the statistical nonstationarity. The role of zone design as a tool to enhance analysis is explored and reference made to analyses that have adopted explicit spatial frameworks.