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Complexity-based metrics for discerning Xylella fastidiosa-infected olive groves in MODIS evapotranspiration satellite data

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  • Telesca, Luciano
  • Lasaponara, Rosa

Abstract

This study investigates the dynamic degradation of Evapotranspiration (ET) time series induced by Xylella fastidiosa (X.f.) infection using the Complexity-Entropy Causality Plane (CECP). By evaluating MODIS ET datasets from infected sites (X2015, X2016, and X2017) against a healthy one (Matera), we characterize the “infection” signature as a fundamental transition from structured, deterministic dynamics toward stochastic disorder. Our findings reveal that infected signals undergo a simultaneous increase in permutation entropy (H) and a significant decrease in statistical complexity (C). This “loss of complexity” serves as a robust marker of ecosystem disturbance, overshadowing the underlying deterministic components of the ET signal.

Suggested Citation

  • Telesca, Luciano & Lasaponara, Rosa, 2026. "Complexity-based metrics for discerning Xylella fastidiosa-infected olive groves in MODIS evapotranspiration satellite data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 691(C).
    • Handle: RePEc:eee:phsmap:v:691:y:2026:i:c:s0378437126002153
    DOI: 10.1016/j.physa.2026.131479
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