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Detection of changes in spatial processes has long been of interest to quantitative geographers seeking to test models, validate theories, and anticipate change. Given the current “data‐rich” environment of today, it may be time to reconsider the methodological approaches used for quantifying change in spatial processes. New tools emerging from computer vision research may hold particular potential...
Model assessment is one of the most important aspects of statistical analysis. In geographical analysis, models represent spatial processes, where variability in mapped output results from uncertainty in parameter estimates. Slight spatial misalignments can cause inflated error scores when comparing maps of observed and predicted variables using traditional error metrics at the level of individual...
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