Assessing effects of input uncertainty in structural landscape classification

This paper presents the results of a study aimed at assessing the eŒects of input uncertainty on the outcome of a raster-based model for structural landscape classiŽ cation. The model uses a DEM and a land-cover map as input, and calculates four structural indices from these data. The Ž rst two indices determine the openness of the landscape, the other two determine the degree of landscape homogeneity. By combining both aspects, nine diŒerent landscape types are deŽ ned. Applying Monte Carlo simulation, the eŒect of DEM error, uncertainty in land-cover classiŽ cation, and the combined eŒect of both sources of uncertainty on the outcome of the landscape model are assessed. Special attention is paid to the spatial structure of uncertainty in both data sources.