The 2021 European summer season has been one of the most intense for Mediterranean regions that experienced a heatwave in August, determining the onset of several fire events across regions in southern Europe. According to preliminary reports, most of the fires occurred in forest and in protected areas (Natura 2000, https://ec.europa.eu/environment/nature/natura2000/index_en.htm (accessed on 4 August 2022)) thus affecting system particularly sensitive. Moreover, fire have been increasingly affecting areas of Central and northern Europe as an effect of climate change (https://ec.europa.eu/commission/presscorner/detail/en/ip_21_5627 (access date 4 August 2022)).
In this work, we wanted to compare the area mapped as burned by an automated algorithm, developed by the research group and already applied to Mediterranean regions [1], to official map products provided by two operative systems: (i) European Forest Fire Information System and (ii) the Copernicus Emergency Management Service (CEMS).
We perform such inter-comparison by selecting three major fires in Italy and Greece to estimate the area affected by fire (burned area) from classification of Sentinel-2 pre- and post-fire images. The algorithm maps burned areas using an automated approach built on fuzzy set theory and region growing. Independent validation has been carried out over all datasets to provide reference for comparison of the quantitative assessment of the extent of the area burned.
Additional analysis has been carried out on burn severity estimated from NBR difference and Copernicus fire damage level that is the CEMS grading product. Preliminary results on the test site in the Sardinia Island (Montiferru region), Italy, revealed that more than 40% of the area affected by the fire has severely been damaged.
Author Contributions
Conceptualization, D.S., M.B. and M.S. (Matteo Sali); Methodology, D.S., M.B. and M.S. (Matteo Sali); Formal Analysis, M.S. (Matteo Sali); Investigation, D.S., M.B., M.S. (Michele Salis), B.A., G.P., G.C., S.F. and F.G.; Data Curation, D.S. and M.S. (Matteo Sali); Writing—Original Draft Preparation, M.S. (Matteo Sali) and D.S.; Supervision, D.S, M.B., M.S. (Michele Salis) and P.D. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
Reference
- Sali, M.; Piaser, E.; Boschetti, M.; Brivio, P.A.; Sona, G.; Bordogna, G.; Stroppiana, D. A Burned Area Mapping Algorithm for Sentinel-2 Data Based on Approximate Reasoning and Region Growing. Remote Sens. 2021, 13, 2214. [Google Scholar] [CrossRef]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).