Detecting olive quick decline syndrome: A satellite-based dataset for a case study in Apulia Region

Area of Science:

• Plant pathology
• Remote sensing applications
• Agricultural monitoring

Background:

• Xylella fastidiosa (Xf) is a bacterium causing olive quick decline syndrome (OQDS) in Europe.
• OQDS threatens olive tree health and regional economies, particularly in Italy.
• Accurate spatial data on Xf infections are crucial but scarce for effective monitoring.

Purpose of the Study:

• To create a detailed dataset of Xylella fastidiosa infected trees in Apulia, Italy.
• To support the development and validation of remote sensing techniques for OQDS detection.
• To provide data for spectral band analysis and species distribution modeling of Xf.

Main Methods:

• Acquisition and segmentation of three WorldView-2 satellite images covering a 25 km² hotspot.
• Visual interpretation of segmented images to identify 2340 olive trees affected by OQDS.
• Creation of a dataset of 76,637 individual olive trees for analysis.

Main Results:

• A dataset of 2340 olive trees identified as infected or removed due to OQDS was generated.
• The study focused on an area with documented Xf infections in 2019 and 2020.
• The dataset enhances the spatial understanding of Xf distribution in the Apulia region.

Conclusions:

• The generated dataset is a valuable resource for advancing remote sensing-based OQDS monitoring.
• This data can facilitate research into spectral signatures of Xf infection.
• The dataset will aid in broader ecological studies of Xf spread and impact.