A new ontology for semantic annotation of remotely sensed images

The remotely sensed images are considered as an important source of information which used in several domains such as environmental monitoring, disaster management and military intelligence. However, the appropriate information has to be extracted and represented to make efficient decision processes. This research presents an ontology based methodology for remote sensing imagery annotation and interpretation. We propose a fuzzy spatio-spectro-temporal ontology representing spatial knowledge about remote sensing images and natural risks domain. The proposed ontology takes into account the imperfection on spatial data, temporality of objects in natural scene and specificities of RS images. Besides, we propose to apply the developed ontology to annotate remote sensing images. The proposed process is validated using LANDSAT and SOPT images representing the kef area, situated in north-east of Tunisia.