Monte Carlo simulation of false change in the overlay of misregistered forest vector maps

When an overlay of vector maps is performed, positional errors can cause a considerable overestimation of land cover change. When historical forest maps are used, this error can be high. It seems logical that the amount of false change is influenced by the degree of fragmentation of the landscape. This paper simulates positional error by using a rubbersheet procedure. Unlike in other studies, this approach does not perform a linear shift of the original map, but induced a positional error, heterogeneous in space. The spatial pattern of forest cover was quantified by means of pattern metrics and the relation between false change and spatial pattern was analyzed using a stepwise regression procedure. The results show that, when the positional error is kept constant, landscapes with a different degree of forest fragmentation contain diverging amounts of false change. False change was positively correlated with the mean nearest neighbour distance between forest fragments, the total forested area and the number of forest patches present. The results of this study also indicate that a coregistration with an RMSE inferior to 30 m is a real prerequisite in order to study change in a highly fragmented forest cover.