Real Time Fire Monitoring Using Semantic Web and Linked Data Technologies

Fire monitoring and management in Mediterranean countries such as Greece is of paramount importance. Almost every summer massive forest fires break out, causing severe destruction and even human life losses. Thus, European initiatives in the area of Earth Observation (EO), such as GMES SAFER, have supported the development of relevant operational infrastructures. In the context of the European project TELEIOS, we aim at developing a fire monitoring service, that goes beyond operational systems currently deployed in various EO data centers, by building on Semantic Web and Linked Data technologies. In this demonstration we present the fire monitoring service that we have implemented using TELEIOS technologies focusing on its Semantic Web related functionality. The service implements a processing chain where raw satellite images are analyzed and hotspots (pixels of the image corresponding to geographic regions possibly on fire) are detected. The products of this analysis are encoded in RDF, so they can be combined with auxiliary linked geospatial data (e.g., GeoNames, OpenStreetMap). By comparing detected hotspots with auxiliary data their accuracy can be determined. For example, hotspots lying in the sea are retrieved and marked as invalid. Additionally, we can combine diverse information sources and generate added-value thematic maps which are very useful to civil protection agencies and firefighting teams during emergency situations.