Influence of classification errors on Intensity Analysis of land changes in southern Nigeria

This article presents the clearest description to date concerning how to compute the hypothetical classification errors that could explain deviations from uniform land changes in the context of Intensity Analysis. Intensity Analysis is an accounting framework that analyses a square contingency table to measure how the sizes of the changes compare to the sizes of the categories. Our case study analyses maps of a portion of southern Nigeria at 1987 and 2002 that show the categories: cultivation, forest, settlement, and water. The data reveal that the changes are not uniformly proportional to the sizes of the categories in terms of categorical gains, categorical losses, and transitions. The methods in this article show that hypothetical error in 9% of the 2002 map could explain all the deviations from uniform categorical gains, hypothetical error in 11% of the 1987 map could explain all the deviations from uniform categorical losses, and hypothetical error in 6% of the 1987 map could explain all deviations from uniform transitions. Larger hypothetical error indicates stronger evidence for a particular deviation from the relevant hypothesized uniform intensity. It is helpful to know the strength of evidence, even when the actual errors in the maps are unknown, which is frequently the case for historical time points.