Home // IARIA Congress 2025, The 2025 IARIA Annual Congress on Frontiers in Science, Technology, Services, and Applications // View article
Authors:
Luciano Telesca
Nicodemo Abate
Michele Lovallo
Rosa Lasaponara
Keywords: Sentinel-1; statistics; vegetation; pests.
Abstract:
In this study, we examine Sentinel 1 (S1) Synthetic Aperture Radar (SAR) time series to detect and assess pest-induced vegetation anomalies. The S1 time series was analysed using multiple SAR-based data as vegetation indices. The analyses were performed on a case study located in Castel Porziano (central Italy), chosen due to its significant impact from Toumeyella Parvicornis (TP) in recent years. The area of Follonica, which is not yet affected by TP, was used as a comparison. Our goal is to identify patterns associated with TP in the statistical features of S1 data. The methodology employed is the well-established Fisher-Shannon analysis, which characterizes the temporal dynamics of complex time series using two informational measures: the Fisher Information Measure (FIM) and the Shannon Entropy Power (SEP). Analysis of the Receiver Operating Characteristic (ROC) curve indicates that these two measures are highly effective in distinguishing between infected and healthy sites.
Pages: 10 to 16
Copyright: Copyright (c) IARIA, 2025
Publication date: July 6, 2025
Published in: conference
ISBN: 978-1-68558-284-5
Location: Venice, Italy
Dates: from July 6, 2025 to July 10, 2025