Application of remote sensing for detecting plant disease using color and morphological features

Arkadi Zilberman, Jiftah Ben Asher, Natan S. Kopeika, Yaniv Reshef

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Remote sensing provides the ability for relatively rapid and early detection of the spatial distribution of a plant disease using methods based on thermography and canopy reflectance in visual and near-infrared wavebands. By remote mapping using color imaging and subsequent data analysis routines, it is possible to realize early detection, identification, and quantification of different relevant plant diseases. In the present work, an applicability of remote sensing with digital color imaging for detecting plant disease is demonstrated. The color and morphological features are used for analysis and classification purposes. As a case study, the image processing is applied to the color photos of banana fields obtained by a manned aerial vehicle equipped with a high resolution camera. Major banana diseases (e.g. Panama etc.) exhibit symptoms on leaf area in their earlier stage of infection. Change of color and morphology features act as criteria used to identify and classify the disease. The results of plant disease recognition and identification are demonstrated.

Original languageEnglish
Title of host publicationRemote Sensing for Agriculture, Ecosystems, and Hydrology XXI
EditorsChristopher M. U. Neale, Antonino Maltese
PublisherSPIE
ISBN (Electronic)9781510630017
DOIs
StatePublished - 1 Jan 2019
EventRemote Sensing for Agriculture, Ecosystems, and Hydrology XXI 2019 - Strasbourg, France
Duration: 9 Sep 201911 Sep 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11149
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceRemote Sensing for Agriculture, Ecosystems, and Hydrology XXI 2019
Country/TerritoryFrance
CityStrasbourg
Period9/09/1911/09/19

Keywords

  • Color features
  • Digital color imaging
  • Image segmentation
  • Panama wilt
  • Plant disease

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