TII-19-5199.pdf (5.11 MB)
Aerial visual perception in smart farming: field study of wheat yellow rust monitoring
journal contribution
posted on 2021-02-18, 09:16 authored by Jinya Su, Dewei Yi, Baofeng Su, Zhiwen Mi, Cunjia LiuCunjia Liu, Xiaoping Hu, Xiangming Xu, Lei Guo, Wen-Hua ChenWen-Hua ChenAgriculture is facing severe challenges from crop stresses, threatening its sustainable development and food security. This article exploits aerial visual perception for yellow rust disease monitoring, which seamlessly integrates state-of-the-art techniques and algorithms, including unmanned aerial vehicle sensing, multispectral imaging, vegetation segmentation, and deep learning U-Net. A field experiment is designed by infecting winter wheat with yellow rust inoculum, on top of which multispectral aerial images are captured by DJI Matrice 100 equipped with RedEdge camera. After image calibration and stitching, multispectral orthomosaic is labeled for system evaluation by inspecting high-resolution RGB images taken by Parrot Anafi Drone. The merits of the developed framework drawing spectral-spatial information concurrently are demonstrated by showing improved performance over purely spectral-based classifier by the classical random forest algorithm. Moreover, various network input band combinations are tested, including three RGB bands and five selected spectral vegetation indices, by sequential forward selection strategy of wrapper algorithm.
Funding
Enabling wide area persistent remote sensing for agriculture applications by developing and coordinating multiple heterogeneous platforms
Department for Business, Energy and Industrial Strategy
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School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
IEEE Transactions on Industrial InformaticsVolume
17Issue
3Pages
2242 - 2249Publisher
Institute of Electrical and Electronics Engineers (IEEE)Version
- AM (Accepted Manuscript)
Rights holder
© IEEEPublisher statement
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acceptance date
2020-02-27Publication date
2020-03-09Copyright date
2020ISSN
1551-3203eISSN
1941-0050Publisher version
Language
- en
Depositor
Prof Wen-Hua Chen. Deposit date: 17 February 2021Usage metrics
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