Behavior-based aggregation of land categories for temporal change analysis
Comparison between two time points of the same categorical variable for the same study extent can revealchanges among categories over time, such as transitions among land categories. If many categories exist, then analysis can be difficult to interpret. Category aggregation is the procedure that combines two ormore categories to create a single broader category. Aggregation can simplify interpretation, and canalso influence the sizes and types of changes. Some classifications have an a priori hierarchy to facilitateaggregation, but an a priori aggregation might make researchers blind to important category dynamics. We created an algorithm to aggregate categories in a sequence of steps based on the categories' behaviorsin terms of gross losses and gross gains. The behavior-based algorithm aggregates net gaining categorieswith net gaining categories and aggregates net losing categories with net losing categories, but neveraggregates a net gaining category with a net losing category. The behavior-based algorithm at each stepin the sequence maintains net change and maximizes swap change. We present a case study where datafrom 2001 and 2006 for 64 land categories indicate change on 17% of the study extent. The behavior-based algorithm produces a set of 10 categories that maintains nearly the original amount of change. Incontrast, an a priori aggregation produces 10 categories while reducing the change to 9%. We offer a freecomputer program to perform the behavior-based aggregation.
International Journal of Applied Earth Observation and Geoinformation
Aldwaik, Safaa Zakaria; Onsted, Jeffrey A.; and Pontius, Robert Gilmore, "Behavior-based aggregation of land categories for temporal change analysis" (2015). Geography. 736.