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Detection of Rise Damage by Leaf Folder ( Cnaphalocrocis medinalis ) Using Unmanned Aerial Vehicle Based Hyperspectral Data

Author

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  • Tao Liu

    (College of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450002, China
    Key laboratory of New Materials and Facilities for Rural Renewable Energy (MOA of China), Henan Agricultural University, Zhengzhou 450002, China)

  • Tiezhu Shi

    (MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China
    School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China)

  • Huan Zhang

    (Key laboratory of New Materials and Facilities for Rural Renewable Energy (MOA of China), Henan Agricultural University, Zhengzhou 450002, China)

  • Chao Wu

    (School of Geographic and Biologic Information & Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

Abstract

Crop pests and diseases are key factors that damage crop production and threaten food security. Remote sensing techniques may provide an objective and effective alternative for automatic detection of crop pests and diseases. However, ground-based spectroscopic or imaging sensors may be limited in practically guiding the precision application and reduction of pesticide. Therefore, this study developed an unmanned aerial vehicle (UAV)-based remote sensing system to detect leaf folder ( Cnaphalocrocis medinalis ). Rice canopy reflectance spectra were obtained in the booting growth stage by using the UAV-based hyperspectral remote sensor. Newly developed and published multivariate spectral indices were initially calculated to estimate leaf-roll rates. The newly developed two-band spectral index (R490−R470), three-band spectral index (R400−R470)/(R400−R490), and published spectral index photochemical reflectance index (R550−R531)/(R550+R531) showed good applicability for estimating leaf-roll rates. The newly developed UAV-based micro hyperspectral system had potential in detecting rice stress induced by leaf folder. The newly developed spectral index (R490−R470) and (R400−R470)/(R400−R490) might be recommended as an indicator for estimating leaf-roll rates in the study area, and (R550−R531)/(R550+R531) might serve as a universal spectral index for monitoring leaf folder.

Suggested Citation

  • Tao Liu & Tiezhu Shi & Huan Zhang & Chao Wu, 2020. "Detection of Rise Damage by Leaf Folder ( Cnaphalocrocis medinalis ) Using Unmanned Aerial Vehicle Based Hyperspectral Data," Sustainability, MDPI, vol. 12(22), pages 1-14, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:22:p:9343-:d:442850
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    References listed on IDEAS

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    1. Shilong Piao & Philippe Ciais & Yao Huang & Zehao Shen & Shushi Peng & Junsheng Li & Liping Zhou & Hongyan Liu & Yuecun Ma & Yihui Ding & Pierre Friedlingstein & Chunzhen Liu & Kun Tan & Yongqiang Yu , 2010. "The impacts of climate change on water resources and agriculture in China," Nature, Nature, vol. 467(7311), pages 43-51, September.
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    Cited by:

    1. Meixuan Li & Xicun Zhu & Wei Li & Xiaoying Tang & Xinyang Yu & Yuanmao Jiang, 2022. "Retrieval of Nitrogen Content in Apple Canopy Based on Unmanned Aerial Vehicle Hyperspectral Images Using a Modified Correlation Coefficient Method," Sustainability, MDPI, vol. 14(4), pages 1-16, February.

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