A partially supervised change-detection technique

In this paper, a partially supervised approach to change detection is proposed. It allows the identification of one or few land-cover transitions of interest by using exclusively training samples belonging to the land covers involved. This represents a significant advantage, as avoids the need to label samples for all the land covers present in the area of interest at the two considered dates.