Inversion reflectance by apple tree canopy ground and unmanned aerial vehicle integrated remote sensing data

Yu, Ruiyang; Zhu, Xicun; Bai, Xueyuan; Tian, Zhongyu; Jiang, Yuanmao; Yang, Guijun

doi:10.1007/s10265-020-01249-1

JPR Symposium
Published: 15 February 2021

Inversion reflectance by apple tree canopy ground and unmanned aerial vehicle integrated remote sensing data

Ruiyang Yu¹,
Xicun Zhu^1,2,
Xueyuan Bai¹,
Zhongyu Tian¹,
Yuanmao Jiang³ &
Guijun Yang⁴

Journal of Plant Research volume 134, pages 729–736 (2021)Cite this article

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Abstract

To obtain accurate spatially continuous reflectance from Unmanned Aerial Vehicle (UAV) remote sensing, UAV data needs to be integrated with the data on the ground. Here, we tested accuracy of two methods to inverse reflectance, Ground-UAV-Linear Spectral Mixture Model (G-UAV-LSMM) and Minimum Noise Fraction-Pixel Purity Index-Linear Spectral Mixture Model (MNF-PPI-LSMM). At wavelengths of 550, 660, 735 and 790 nm, which were obtained by UAV multispectral observations, we calculated the canopy abundance based on the two methods to acquire the inversion reflectance. The correlation of the inversion and measured reflectance values was stronger in G-UAV-LSMM than MNF-PPI-LSMM. We conclude that G-UAV-LSMM is the better model to obtain the canopy inversion reflectance.

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Acknowledgements

This research was supported by the National Key Research and Development Program of China, 2017YFE0122500; National Natural Science Foundation of China, 41671346; Funds of Shandong “Double Tops” Program, SYL2017XTTD02; Shandong major scientific and technological innovation project: Research demonstration and extension of orchard irrigation and fertilization in accurate management, 2018CXGC0209; The Taishan Scholar Assistance Program from Shandong Provincial Government.

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Authors and Affiliations

College of Resources and Environment, Shandong Agricultural University, Tai’an, 271018, China
Ruiyang Yu, Xicun Zhu, Xueyuan Bai & Zhongyu Tian
National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources, College of Resources and Environment, Shandong Agricultural University, Tai’an, 271018, China
Xicun Zhu
College of Horticulture Science and Engineering, National Apple Engineering and Technology Research Center, Shandong Agricultural University, Tai’an, 271018, China
Yuanmao Jiang
National Engineering Research Center for Information Technology in Agriculture, Beijing, 100097, China
Guijun Yang

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Ruiyang Yu
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Xicun Zhu
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Xueyuan Bai
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Zhongyu Tian
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Yuanmao Jiang
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Guijun Yang
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Contributions

Conceptualization, R. Y. Y. and X. C. Z.; Data curation, R. Y. Y.; Investigation, R. Y. Y., X. C. Z., Z. Y. T. and X. Y. B.; Methodology, R. Y. Y.; Project administration, X. C. Z. and G. J. Y.; Resources, X. C. Z.; Software, R. Y. Y.; Supervision, Y. M. J. and G. J. Y.; Validation, X. C. Z., Z. Y. T. and X. Y. B.; Visualization, R. Y. Y.; Writing—original draft, R. Y. Y.; Writing—review and editing, R. Y. Y., X. C. Z. and Z. Y. T.

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Correspondence to Xicun Zhu.

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Yu, R., Zhu, X., Bai, X. et al. Inversion reflectance by apple tree canopy ground and unmanned aerial vehicle integrated remote sensing data. J Plant Res 134, 729–736 (2021). https://doi.org/10.1007/s10265-020-01249-1

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Received: 06 July 2020
Accepted: 24 December 2020
Published: 15 February 2021
Issue Date: July 2021
DOI: https://doi.org/10.1007/s10265-020-01249-1

Keywords

Apple tree canopy
Integrated
Inversion
Reflectance
Remote sensing