Accuracy assessment on multi-temporal land-cover change detection using a trajectory error matrix

This study develops a practical methodology to assess the accuracy of multi-temporal change detection using a trajectory error matrix (TEM). In this error matrix one axis represents the land-cover change trajectory categories derived from single-date classified images, and the other represents the land-cover change trajectories identified from reference data. The overall accuracies of change trajectories and states of change/no-change are used as indices for accuracy assessment. As the number of possible land-cover change trajectories can be enormous, a practical processing flow for computing accuracy assessment indices has also been developed to avoid listing all possible change trajectories in the error matrix. A case study using this method was conducted to assess the accuracy of land-cover change over a period with five observations in a study area in China's arid zone. This method simplifies the process of estimating overall accuracy in the change trajectory analysis, and provides a more realistic and detailed assessment of the results of multi-temporal change detection using post-classification comparison methods.