Sensitivity of selected landscape pattern metrics to land-cover misclassification and differences in land-cover composition. Photogrammetric Engineering and Remote Sensing 63

Abstract investigation of the sensitivity of these measurements to clas-Calcuiation of landscape metrics from land-cover data is be- sification error (Hess, 1994). he objectives of this paper are coming increasingly common. Some studies have shown that two-fold: (1) to determine the sensitivity of landscape these measurements are sensitive to differences in land-cover metrics to land-cover misclassification, and (2) to determine composition, but none are known to have tested also their the sensitivity of landscape metrics to differences in land-to land-cover misc~ass~f icat~on ~ error sirnula- scape condition. These objectives are necessarily connected. tion model was written to test the sensitivity of selected land- Ideally, landscape pattern metrics would be insensitive to scape pattern metrics to misclassification, and regression misclassification but sensitive to differences in land cover. analysis was used to determine i f these metrics were signifi- Land-cover data, mapped from Landsat TM for the Ches-cantly related to differences in land-cover composition. Corn- apeake Bay Regional Watershed, were used for this study. parison of sensitivity and regression results suggests that The data were divided into 57 eight-digit U.S. Geological differences in land-cover composition need to be about 5 Survey (us~s) hydrologic units or watersheds. Sensitivity to percent greater than the misclassification rate to be confident misclassification is tested using a simulation model based on that differences in landscape metrjcs are not due to mjsclas- a published land-cover error matrix (Green et a]., 1993). Sen-sification. sitivity to differences in landscape condition is tested b