Fire Risk Analysis By Using Sentinel-2 Data: The Case Study Of The Vesuvius In Campania, Italy

TL;DR

This study evaluates the use of Sentinel-2 satellite data and the NDWI index to monitor forest fires at Vesuvius, Italy, demonstrating the potential of open-access remote sensing for fire risk analysis.

Contribution

It introduces a method using Sentinel-2 multispectral images and NDWI to effectively monitor forest fires in a specific volcanic region, enhancing fire detection capabilities.

Findings

NDWI effectively highlights burned areas.

Sentinel-2 data provides high-resolution, accessible fire monitoring.

The approach supports timely fire risk assessment.

Abstract

As sadly known, forest fires are part of a set of natural disasters that have always affected regions of the world typically characterized by a tropical climate with long periods of drought. However, due to climate changes of the recent years, other regions of our planet that were not affected by this plague have also had to deal with this phenomenon. One of them is certainly the Italian peninsula, and especially the regions of southern Italy. For this reason, the scientific community, and in particular that one of the remote sensing, plays an important role in the development of reliable techniques to provide useful support to the competent authorities. Therefore, in this work, the capability of the Normalized Differential Water Index (NDWI), derived from spaceborne remote sensing (RS) data, is assessed to monitor the forest fires occurred on a specific study area during the summer of 2017: the volcano Vesuvius, near Naples (in Campania, Italy). In particular, the index is obtained from Sentinel-2 multispectral images of the European Space Agency (ESA), which are free of charge and open accessible. Moreover, the twin Sentinel-2 (S-2) sensors allows to overcome some restrictions on time delivery and high frequency observation. These requirements are goodly matched by other spaceborne sensors, such as MODIS and VIIRS satellites, but at the expense of a lower spatial resolution.