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UAV multispectral remote sensing for yellow rust mapping: opportunities and challenges

chapter
posted on 10.05.2022, 13:09 authored by Jinya Su, Cunjia LiuCunjia Liu, Wen-Hua ChenWen-Hua Chen

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.

Funding

Space-enabled Crop disEase maNagement sErvice via Crop sprAying Drones (SCENE-CAD)

Science and Technology Facilities Council

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History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

Unmanned Aerial Systems in Precision Agriculture: Technological Progresses and Applications

Pages

107 - 122

Publisher

Springer

Version

AM (Accepted Manuscript)

Rights holder

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd

Publisher statement

This book chapter was accepted for publication in the book Unmanned Aerial Systems in Precision Agriculture: Technological Progresses and Applications. The definitive published version is available at https://doi.org/10.1007/978-981-19-2027-1_7

Publication date

2022-05-18

Copyright date

2022

ISBN

9789811920264; 9789811920271

ISSN

2731-3476

eISSN

2731-3484

Book series

Smart Agriculture (SA,volume 2)

Language

en

Editor(s)

Zhao Zhang; Hu Liu; Ce Yang; Yiannis Ampatzidis; Jianfeng Zhou; Yu Jiang

Depositor

Prof Wen-Hua Chen. Deposit date: 7 May 2022