Impact of error on landscape pattern analyses performed on land-cover change maps

Researchers have emphasized the value of linking observed patterns of land-cover change to the processes driving changes in land-use to explain the dynamics of a land change system. The association of pattern and process requires an accurate quantification of the spatial characteristics of land-cover change. The objective of this research is to assess the impact of error on the accuracy of landscape pattern analyses performed on maps of change. Simulation was used to develop of a series of error-free and error-perturbed change maps, which varied with respect to the pattern of change occurring between the time-1 and time-2 land-cover maps and the patterns of error associated with the time-1 and time-2 land-cover maps. A variety of change and error patterns were examined. The error-free and error-perturbed change maps were compared by calculating landscape pattern metrics, which revealed the degree to which error altered the pattern of change. The introduction of error notably changed the structure of the persistent and transitioning classes, with metrics indicating a more fragmented and variable landscape under error. Agreement between the error-free and error-perturbed maps improved when a greater amount of change occurred within the time-series, change was concentrated at the boundaries of land-cover classes and when time-2 errors were increasingly correlated to their time-1 counterparts. These results have several implications for change pattern analyses given the fundamental nature of land-cover change.