On the Use of Satellite Sentinel 2 Data for Automatic Mapping of Burnt Areas and Burn Severity
LASAPONARA R.; TUCCI B.; GHERMANDI L.
Abstract: In this paper, we present and discuss the preliminary tools we devised for the automaticrecognition of burnt areas and burn severity developed in the framework of the EU-fundedSERV_FORFIRE project. The project is focused on the set up of operational services for fire monitoringand mitigation specifically devised for decision-makers and planning authorities. The main objectivesof SERV_FORFIRE are: (i) to create a bridge between observations, model development, operationalproducts, information translation and user uptake; and (ii) to contribute to creating an internationalcollaborative community made up of researchers and decision-makers and planning authorities.For the purpose of this study, investigations into a fire burnt area were conducted in the south ofItaly from a fire that occurred on 10 August 2017, affecting both the protected natural site of Pignola(Potenza, South of Italy) and agricultural lands. Sentinel 2 data were processed to identify and mapdifferent burnt areas and burn severity levels. Local Index for Statistical Analyses LISA were used toovercome the limits of fixed threshold values and to devise an automatic approach that is easier tore-apply to diverse ecosystems and geographic regions. The validation was assessed using 15 randomplots selected from in situ analyses performed extensively in the investigated burnt area. The fieldsurvey showed a success rate of around 95%, whereas the commission and omission errors werearound 3% of and 2%, respectively. Overall, our findings indicate that the use of Sentinel 2 dataallows the development of standardized burn severity maps to evaluate fire effects and addresspost-fire management activities that support planning, decision-making, and mitigation strategies.