The Issue of Uncertainty Propagation in Spatial Decision Making

Abstract GISs give users facilities to integrate and analyze data from different sources with different scale, accuracy, resolution and quality of the original data which are the key aspects of GIS functionality, but it does raise the question as to what effects the combination of different levels of data uncertainty has on both the output maps and on the data derived from spatial query and analysis. In this paper, in addition to provide an overview of uncertainty propagation assessment in overlay analysis, an experiment using Monte Carlo simulation method has been performed and then the results were analyzed. Two polygons whose vertices have been perturbed by changing their coordinates randomly using Monte Carlo simulation method are overlaid so that their intersection defines the third polygons set which in turn were statistically analyzed using a developed program and some GPS data. Two mainly recommended indicators, i.e., area and perimeter of polygon, were used and ended up with consequence that the indices of these polygons whose vertices had error in position emerged less than those whose vertices were accurate.