USING SENTINEL-2 IMAGERY TO TRACK CHANGES PRODUCED BY XYLELLA FASTIDIOSA IN OLIVE TREES

This paper attempts to provide an understanding of the potential application of Sentinel-2 imagery for the monitoring and detection of disease symptoms caused by Xylella fastidiosa (Xf) in olive trees. A time series data of 188 Sentinel-2a images collected over the last two years was used to analyse the temporal trends in areas with Xf infected olive trees in Puglia, Southern Italy. The robustness of different physiological and structural hyperspectral indices was evaluated as an early indicator of Xf symptoms. Three validation sites for Sentinel-2a products were hence established over olive orchards in the Xf-infected zone in two different years (2016 and 2017) and overflown with a hyperspectral sensor to acquire high spatial resolution images (50 cm). Disease incidence and severity levels were recorded for more than 3300 olive trees in 18 orchards. Results demonstrate the capability of temporal Sentinel-2a was able to detect and discriminate between high and medium Xf incidence, reaching the maximum differences during the summer season. Among all the vegetation indices evaluated from Sentinel-2 imagery, OSAVI showed superior performance for detecting Xf incidence trends and OSAVI1510 for detecting changes in Xf severity levels