Multisource urban classification: joint processing of optical and SAR data for land cover mapping

In this paper we present and compare different techniques for the fusion of multitemporal SAR and multiband optical images. We consider both neuro-fuzzy and statistical approaches for the exploitation of the contextual information and the classification, and different schemes for the multisensor fusion. The proposed techniques are applied to a set of two multitemporal SAR and a Landsat multiband image of an urban area. Results show that it is possible to fully exploit the potentialities of the two sensors, by appropriately fusing their information. In particular, the proposed schemes are useful to retain at the same time the change detection capability and the best possible classification accuracy, thus they are of practical interest for civil protection applications.