On the Use of Satellite Sentinel 2 Data for Automatic Mapping of Burnt Areas and Burn Severity

Rosa Lasaponara,Luciana Ghermandi,Biagio Tucci

doi:10.3390/su10113889

Abstract

In this paper, we present and discuss the preliminary tools we devised for the automatic recognition of burnt areas and burn severity developed in the framework of the EU-funded SERV_FORFIRE project. The project is focused on the set up of operational services for fire monitoring and mitigation specifically devised for decision-makers and planning authorities. The main objectives of SERV_FORFIRE are: (i) to create a bridge between observations, model development, operational products, information translation and user uptake; and (ii) to contribute to creating an international collaborative 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 of Italy 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 map different burnt areas and burn severity levels. Local Index for Statistical Analyses LISA were used to overcome the limits of fixed threshold values and to devise an automatic approach that is easier to re-apply to diverse ecosystems and geographic regions. The validation was assessed using 15 random plots selected from in situ analyses performed extensively in the investigated burnt area. The field survey showed a success rate of around 95%, whereas the commission and omission errors were around 3% of and 2%, respectively. Overall, our findings indicate that the use of Sentinel 2 data allows the development of standardized burn severity maps to evaluate fire effects and address post-fire management activities that support planning, decision-making, and mitigation strategies.

Highlights

Rural and urban development remains a key priority area in the growth process oriented at sustainable economic development to improve quality of life and preserve the environment
For the purpose of our investigation, we first analyzed a satellite-based ∆normalized burn ratio (NBR) map obtained from the difference between the pre- and post-fire index
The approach devised was based on the joint use of: (i) satellite Sentinel 2 data, from which the spectral indices ∆NBR were computed to enhance fire-affected areas; (ii) statistical analysis based on LISA indices (Moran’s I, Geary’s C, and the Getis–Ord Local Gi index); and (iii) automatic unsupervised classification

Summary

Introduction

Rural and urban development remains a key priority area in the growth process oriented at sustainable economic development to improve quality of life and preserve the environment. The links and interactions between ‘rural’ and ‘urban’ are an increasingly important component of livelihoods and production systems and the promotion of a better management of urban–rural interactions is mandatory in order to: (i) support and encourage sustainable resource management; (ii) develop better practices in agriculture and forest management; and (iii) preserve our natural resources for future generations. For these reasons, forest fires are today recognized as a global ecological and social problem with expected potential increasing trends due to land abandonment and climate change. Fires are one of the most important causes of land degradation, as they induce significant alterations in the vegetation cover and in the fauna, soil, and atmosphere, producing high direct and indirect losses, including economic losses

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