UAV Multispectral Remote Sensing for Yellow Rust Mapping: Opportunities and Challenges

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

7 Citations (Scopus)

Abstract

Wheat is threatened by various crop stresses in its life-cycle, where yellow rust is a severe disease significantly impacting wheat yield. This work aims to investigate the use of Unmanned Aerial Vehicle based multispectral remote sensing for winter wheat stress mapping caused by yellow rust disease. A simple unsupervised wheat yellow rust mapping framework is initially proposed by integrating Spectral Vegetation Indices generation, mutual information analysis and Otsu’s thresholding. A field experiment is carefully designed by infecting winter wheat with different levels of yellow rust inoculum, where UAV multispectral images are collected at the diseased stage with visible symptoms. Experimental results on the labelled dataset initially show the effectiveness of the proposed unsupervised framework for yellow rust disease mapping. Limitations of the proposed algorithm and challenges of yellow rust detection for real-life applications are also discussed.

Original languageEnglish
Title of host publicationSmart Agriculture (Singapore)
PublisherSpringer
Pages107-122
Number of pages16
Volume2
ISBN (Electronic)978-981-19-2027-1
ISBN (Print)978-981-19-2026-4
DOIs
Publication statusPublished - May 2022
Externally publishedYes

Publication series

NameSmart Agriculture (Singapore)
Volume2
ISSN (Print)2731-3476
ISSN (Electronic)2731-3484

Keywords

  • Precision agriculture
  • Remote sensing
  • Unmanned Aerial Vehicle (UAV)
  • Unsupervised learning

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Control and Systems Engineering

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