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Abstract The statistical method of visibility graph (VG) has been becoming widely employed for analyzing the topological properties of signals in various scientific fields. The VG method is based on transforming time series into graphs or networks, whose nodes are the series values linked between each other by edges drawn on the basis of specific ‘visibility’ criteria. The number of the edges departing from each node is the degree of that particular node. In this paper, the VG is utilized to analyze the topological properties of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite evapotranspiration time series of pixels covering olive orchards in various areas of southern Italy, some of which are affected by Xylella fastidiosa infection. Xylella fastidiosa is a very dangerous phytobacterium that causes desiccation and then death of olive trees. By converting the investigated MODIS time series in networks by using the VG, we focused on evaluating the discrimination capability between infected and uninfected sites by analyzing two informational quantities: the fisher information measure (FIM) and the Shannon entropy of the connection degree distribution. The results of the receiver operating characteristic analysis indicate that the Shannon entropy of the degree distribution demonstrates strong discrimination capability between infected and healthy pixels, while the FIM show a much less discrimination power. These findings suggest that the VG method combined with information theory is highly effective in identifying satellite pixels covering infected vegetated areas and holds significant potential as a valuable tool for infection detection of large-scale areas.
Telesca et al. (Mon,) studied this question.