Sentinel-1 Time-Series Analysis for Fires Monitoring using Google Earth Engine Tools

Abstract

Nowadays, the Earth remote-sensed observations are extensively used to manage risk, monitor forest, land cover/land use, and other applications. This work presents a Remote Sensing approach based on the Google Earth Engine (GEE) tools to monitor wildfires using Sentinel-1 data. In particular, we proposed a SAR Index using the Sentinel-1 SAR VV and VH backscatter. The SAR index (SI) effectiveness is tested on the Vesuvius area in a five-year time-series (2015–2020) analysis to determine useful information about the fire events occurrences in the presence of a pine forest. Further, the SAR index capability's advantages and disadvantages are considered in change detection analysis with a differential multi-temporal approach. The numerical and visual results encourage us to use the SI index in fires monitoring.