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Suitability of the MODIS-NDVI Time-Series for a Posteriori Evaluation of the Citrus Tristeza Virus Epidemic

Daniela Vanella, Simona Consoli, Juan Miguel Ramírez-Cuesta, M. Tessitori

2020Remote Sensing12 citationsDOIOpen Access PDF

Abstract

The technological advances of remote sensing (RS) have allowed its use in a number of fields of application including plant disease depiction. In this study, an RS approach based on an 18-year (i.e., 2001–2018) time-series analysis of Normalized Difference Vegetation Index (NDVI) data, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and processed with TIMESAT free software, was applied in Sicily (insular Italy). The RS approach was carried out in four orchards infected by Citrus tristeza virus (CTV) at different temporal stages and characterized by heterogeneous conditions (e.g., elevation, location, plant age). The temporal analysis allowed the identification of specific metrics of the NDVI time-series at the selected sites during the study period. The most reliable parameter which was able to identify the temporal evolution of CTV syndrome and the impact of operational management practices was the “Base value” (i.e., average NDVI during the growing seasons, which reached R2 values up to 0.88), showing good relationships with “Peak value”, “Small integrated value” and “Amplitude”, with R2 values of 0.63, 0.70 and 0.75, respectively. The approach herein developed is valid to be transferred to regional agencies involved in and/or in charge of the management of plant diseases, especially if it is integrated with ground-based early detection methods or high-resolution RS approaches, in the case of quarantine plant pathogens requiring control measures at large-scale level.

Topics & Concepts

Moderate-resolution imaging spectroradiometerNormalized Difference Vegetation IndexRemote sensingEnvironmental scienceTime seriesCitrus tristeza virusVegetation (pathology)GeographyStatisticsMathematicsClimate changeEcologyBiologyPlant virusVirologyVirusPathologyAerospace engineeringMedicineSatelliteEngineeringRemote Sensing in AgricultureSpecies Distribution and Climate ChangeLeaf Properties and Growth Measurement
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