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.