Introducing an Accuracy Indicator Based on Uncertainty Related Measures

Traditionally accuracy assessment of the classification results uses some collected reference data (ground truth). Ground truth collection is a time-consuming and money-swallowing activity and usually can not be done completely. Uncertainty is an important subject in remote sensing that can appear and be increased sequentially in a chain of remote sensing from data acquisition, geometric and radiometric processing to the information extraction. Conceptually the relation between uncertainty and accuracy is an inverse relation. This relation can aid us to construct a relation between accuracy measures and uncertainty related measures. In this paper we investigate this relation using the generated synthetic images (for the sake of the reliability of the obtained results) and try to find an uncertainty related measure that has a strong relationship with the accuracy parameters like overall accuracy.We have found that among the uncertainty measures the mean quadratic score has the strong and reliable relationship with the commonly used accuracy measures. This relationship can be a good basis for the future investigations that lead to the classification based accuracy measures and avoiding some problematic data related issued of ground truth data collection.