Propagation of Dem Uncertainty: an Interval Arithmetic Approach

In several GIS applications it is necessary to classify the topographic surface represented by a Digital Elevation Model (DEM) into specific slope classes. However, the computation of these classes from a DEM is influenced by the uncertainty in the elevations of those models. Monte-Carlo method has been used to study the effect of DEM uncertainty on topographic parameters. This method requires intensive computation, which turns the implementation very hard in most GIS software packages. Interval Arithmetic (IA) has been used as a successfully alternative to the Monte-Carlo method. Intervals of variation are used instead of a significant number of simulations. In this paper, we will show that the use of the IA constitutes a valid alternative to study the propagation of the uncertainty. Comparing the results from both methods, we conclude that the propagation of DEM uncertainty to the calculation of slope classes using IA is preferable to Monte-Carlo method, since it does not require so intensive computations, which turns the implementation easier in GIS analyses.