a b s t r a c tAdvances in remote sensing technologies have allowed us to send an ever-increasing number of satellites in orbit around Earth. As a result, Earth Observation data archives have been constantly increasing in size in the last few years, and have become a valuable source of data for many scientific and application domains. When Earth Observation data is coupled with other data sources many pioneering applications can be developed. In this paper we show how Earth Observation data, ontologies, and linked geospatial data can be combined for the development of a wildfire monitoring service that goes beyond applications currently deployed in various Earth Observation data centers. The service has been developed in the context of European project TELEIOS that faces the challenges of extracting knowledge from Earth Observation data head-on, capturing this knowledge by semantic annotation encoded using Earth Observation ontologies, and combining these annotations with linked geospatial data to allow the development of interesting applications. (K. Kyzirakos). processing of satellite images and outputs validated fire-related products (e.g., hotspot and burnt area maps) for Southern Europe (Spain, France, Italy, Portugal, and Greece).In this work, we discuss how NOA has redeveloped its real-time fire monitoring service using linked geospatial data and semantic web technologies developed in the research projects TELEIOS and SWeFS. TELEIOS 1 is a European research project that addresses the need for scalable access to petabytes of EO data and the effective discovery of knowledge hidden in them. SWeFS (Sensor Web Fire Shield) is a recent Greek research project that investigates the use of sensor networks in fire monitoring. TELEIOS and SWeFS pioneer the use of the following state-of-the-art technologies upon which the wildfire monitoring service has been built:• Publicly available linked geospatial data 2 for use in emergency response situations, such as OpenStreetMap 3 and GeoNames. 4 • The data model stRDF, an extension of the W3C standard RDF that allows the representation of geospatial data that changes over time [1,2]. stRDF is accompanied by stSPARQL, an 1