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Using high spatial resolution satellite imagery for mapping powdery mildew at a regional scale

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Abstract

Efficient crop protection management requires timely detection of diseases. The rapid development of remote sensing technology provides a possibility of spatial continuous monitoring of crop diseases over a large area. In this study, to monitor powdery mildew in winter wheat in an area where a severe disease infection occurred, the capability of high resolution (6 m) multi-spectral satellite imagery, SPOT-6, in disease mapping was assessed and validated using field survey data. Based on a rigorous feature selection process, five disease sensitive spectral features: green band, red band, normalized difference vegetation index, triangular vegetation index, and atmospherically-resistant vegetation index were selected from a group of candidate spectral features/variables. A spectral correction was processed on the selected features to eliminate possible baseline effect across different regions. Then, the disease mapping method was developed based on a spectral angle mapping technique. By validating against a set of field survey data, an overall mapping accuracy of 78 % and kappa coefficient of 0.55 were achieved. Such a moderate but practically acceptable accuracy suggests that the high resolution multi-spectral satellite image data would be of great potential in crop disease monitoring.

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Acknowledgments

This work was subsidized by National Natural Science Foundation of China (41301476), Beijing Nova Programme, China (Z151100000315059), and UK Newton project entitled “A system to improve the rational use of pesticides against locusts”. The authors are grateful to Mr. Weiguo Li, Ms. Hong Chang for their helps in field data collection.

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Authors and Affiliations

  1. School of Information Engineering and Art and Design, Zhejiang University of Water Resources and Electric Power, Hangzhou, 310018, China

    Lin Yuan

  2. College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou, 310018, China

    Jingcheng Zhang

  3. Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China

    Jihua Wang & Hao Yang

  4. School of Geosciences, University of South Florida, Tampa, FL, 33620, USA

    Ruiliang Pu

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  1. Lin Yuan
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  2. Ruiliang Pu
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  3. Jingcheng Zhang
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  4. Jihua Wang
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  5. Hao Yang
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Correspondence to Jingcheng Zhang.

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Yuan, L., Pu, R., Zhang, J. et al. Using high spatial resolution satellite imagery for mapping powdery mildew at a regional scale. Precision Agric 17, 332–348 (2016). https://doi.org/10.1007/s11119-015-9421-x

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  • DOI: https://doi.org/10.1007/s11119-015-9421-x

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