Comparison of Information Extracted from High Resolution Satellite Images for Update of a GIS

The aim of this study is to compare the information extracted from high and very high resolution satellite images in terms of information content and reliability to update thematic layers in a geographical information system (GIS). For the extraction of information from the selected remote sensing (RS) data sets, a knowledge-based classification technique based on a rule-based approach has been constructed. The method uses an initial image segmentation procedure based on a Mahalanobis distance classifier (or spectral parameters) as well as the constraints on spectral and spatial thresholds. Overall, the study indicated that unlike the information extracted from high resolution RS images which contains large uncertainty in terms of delineation of individual objects, the information extracted from very high resolution satellite images are very reliable and can be successfully used for update of a GIS layer specifically in urban context.