Effect of Category Aggregation on Map Comparison
This paper investigates the influence of category aggregation on measurement of land-use and land-cover change. To date, research concerning data aggregation has examined primarily the effects of modifying the unit of observation (i.e., the modifiable areal unit problem and the ecological inference problem); here, we examine the effects of changing the categorical definition, such as the conversion from many, detailed Anderson Level II classes to fewer, broader Anderson Level I classes. Cross-tabulation matrices are used to analyze the change between two times for aggregated and unaggregated versions of identical landscapes. A mathematical technique partitions the Total change as the sum of Net (i.e., quantity change) and Swap (i.e., location change). This paper shows that the Total and Net exhibited by maps between two points in time can be substantially reduced through land-use category aggregation, but cannot be increased. Swap, however, can be reduced or increased by the aggregation of categories. We derive five principles that dictate the effect of aggregation and illustrate the principles using both simplified examples and empirical data. The empirical data are from three Human Environment Regional Observatory sites. The principles are mathematical facts that apply to the analysis of any categorical variable.
KeywordsModifiable Areal Unit Problem Identical Landscape Category Aggregation Barren Category Warm Season Crop
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