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Revealing traits of phytopathogenic status induced by Xylella Fastidiosa in olive trees by analysing multifractal and informational patterns of MODIS satellite evapotranspiration data

Luciano Telesca, Nicodemo Abate, Farid Faridani, Michele Lovallo and Rosa Lasaponara

Physica A: Statistical Mechanics and its Applications, 2023, vol. 629, issue C

Abstract: In this work the time variability of MODIS satellite evapotranspiration data was investigated by using the informational Fisher–Shannon analysis and the multifractal detrended fluctuation analysis to reveal the presence of Xylella Fastidiosa in olive trees, a very dangerous phytobacterium capable to induce a severe disease in olive trees, known as olive quick decline syndrome. Several hundred pixels of infected and healthy sites located in southeastern Italy were analysed. Our results suggest that the informational (Fisher Information Measure and Shannon entropy) and multifractal (hq-range, multifractal width W and maximum α0) parameters allow a good discrimination between infected and healthy sites, envisaging the use of the combination of this two methods as an operational tool for early diagnosis of plant deterioration due to the bacterium.

Keywords: Satellite data; Vegetation; Xylella Fastidiosa; Fisher–Shannon analysis; Multifractal detrended fluctuation analysis (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:629:y:2023:i:c:s0378437123007185

DOI: 10.1016/j.physa.2023.129163

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Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

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