Modeling spatial uncertainty with random sets for edge detection from satellite images

Random sets are common spatial statistical concepts that allow to quantify uncertainty in spatial objects. For objects extracted from remote sensing images, quantification of the uncertainty is important, as many objects are relatively small with respect to the pixel size and are sometimes poorly defined. Remote Sensing (RS) data, however, are attractive for land cover identification, classification and estimation. In this presentation we aim to address the presence of edges. Such edges occur on images in different shapes, for example as geological lineaments and as borders between agricultural parcels.