Journal of Plant Diseases and Protection

, Volume 126, Issue 4, pp 307–318 | Cite as

UAV-based multispectral imagery for fast Citrus Greening detection

  • Farzaneh DadrasJavanEmail author
  • Farhad Samadzadegan
  • Seyed Hossein Seyed Pourazar
  • Haidar Fazeli
Original Article


Considering the variation in spectral response of plants due to unhealthiness effects, this study utilizes multispectral imaging to detect Greening disease of citrus trees. Low altitude multispectral images acquired in five discrete bands of R, G, B, Red Edge, and NIR by an imaging camera embedded on an unmanned aerial vehicle. Image features including 16 vegetation indices and 5 bands from spectral images are extracted. Support vector machine (SVM) used to classify the images using generated features in two steps. First, for determining trees from non-trees objects and then based on the output, healthy and diseased trees are classified. The obtained overall classification results based on check samples are 81.75% for SVM model which demonstrates that low altitude multispectral imagery has the potential to be applied for fast detection of Greening infected trees in citrus orchards.


Citrus Greening Multispectral imagery UAV Support vector machine Vegetation indices 


Compliance with ethical standards

Conflict of interest

The author declares that they have no conflict of interest.


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Copyright information

© Deutsche Phytomedizinische Gesellschaft 2019

Authors and Affiliations

  • Farzaneh DadrasJavan
    • 1
    Email author
  • Farhad Samadzadegan
    • 1
  • Seyed Hossein Seyed Pourazar
    • 1
  • Haidar Fazeli
    • 1
  1. 1.School of Surveying and Geospatial Engineering, College of EngineeringUniversity of TehranTehranIran

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