Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science

BURNED AREA RECOGNITION BY CHANGE DETECTION ANALYSIS USING IMAGES DERIVED FROM SENTINEL-2 SATELLITE: THE CASE STUDY OF SORRENTO PENINSULA, ITALY


DOI: 10.5937/jaes16-17249
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions. 
Creative Commons License

Volume 16 article 522 pages: 225 - 232

Massimiliano Pepe
University of Naples “Parthenope”, Department of Sciences and Technologies, Italy

Claudio Parente
University of Naples “Parthenope”, Department of Sciences and Technologies, Italy


The purpose of this paper is to identify the burned areas that occurred in Italy during the summer of 2017 using change detection analysis techniques. This task is possible thanks to continuous, free and open availability of the multispectral images obtained by Sentinel-2 satellites. Indeed, comparing the satellite images of the same scene recorded at different times, it was possible to evaluate the landscape change. In this paper, the Direct Comparison change detection technique was applied to the analysis and identification of burned area using several Remote Sensing indexes. In particular, in order to achieve this aim, NBR (Normalized Burn Ratio) and NDVI (Normalized Difference Vegetation Index) were used. By case study in South Italy region (Sorrento peninsula), using images derived from Sentinel-2A imagery, it was possible to identify the burned areas in a specifi c period and evaluate the performance of the two indexes. In fact, after having constructed the confusion matrix for the two tested indexes, through the use of methods that indicate the quality of a thematic map (User’s Accuracy, Producer’s Accuracy, Overall Accuracy and Kappa coefficient), the percentage values for each remote sensing index analyzed were compared. The analysis of the different methods revealed, from one side the high quality of the results achievable by NBR index, on the other side, it was shown how, in some areas, the NDVI was inadequate for the recognition of burned areas.

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This research was part of the “Change detection techniques applied to satellite images for the identification of expansions of the built territory”, a research project supported by University of Naples “Parthenope”. In addition, we want to thank the anonymous reviewers for constructive comments concerning our manuscript.

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