Complete Control of an Observed Confusion Matrix

Abstract

The error matrix has been adopted as a standard way to report on the thematic accuracy of any remotely sensed data product. A very usual way to perform the thematic accuracy analysis of an error matrix is by means of global indexes (e.g. overall accuracy, Kappa coefficient). But global indices do not allow for a category-wise control. This work proposes a new method for accuracy control of thematic classification based on an application of the chi-square goodness of fit test. By this way we can stablish our preferences of accuracy for each category but also we can consider some degree of misclassification between some categories. A practical example is provided for a 4×4 matrix (16 class combinations). In this example, a total of 13 quality levels (specifications) are imposed for certain class combinations. In this way, much more is controlled than by means of global indexes. In addition, the method allows to be more demanding or flexible in the quality levels of certain classes, according to convenience.