A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect-Reference-Cited by-同舟云学术

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A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect

Published:2023-05-29 Issue:5 Volume:24 Page:2098-2125
ISSN:1385-2256
Container-title:Precision Agriculture
language:en
Short-container-title:Precision Agric

Author:

Pan Yuanyuan,Zhou Ruiheng,Zhang Jiayi,Guo Wanting,Yu Minglei,Guo Caili,Yao Xia,Cheng Tao,Zhu Yan,Cao Weixing,Tian Yongchao

Funder

Innovative Research Group Project of the National Natural Science Foundation of China

the Priority Academic Program Development of Jiangsu Higher Education Institutions

Jiangsu Agricultural Science and Technology Innovation Fund

Publisher

Springer Science and Business Media LLC

Subject

General Agricultural and Biological Sciences

Link

https://link.springer.com/content/pdf/10.1007/s11119-023-10032-w.pdf

Reference51 articles.

1. Chen, M. (2014). Chlorophyll modification and their spectral extension in oxygenic photosynthesis. Annual Review of Biochemistry, 83, 317–340. https://doi.org/10.1146/annurev-biochem-072711-162943

2. Croft, H., Chen, J. M., Wang, R., Mo, G., Luo, S., Luo, X., He, L., Gonsamo, A., Arabian, J., Zhang, Y., & Simic-Milas, A. (2020). The global distribution of leaf chlorophyll content. Remote Sensing of Environment, 236, 111479. https://doi.org/10.1016/j.rse.2019.111479

3. Dash, J., & Curran, P. J. (2004). The meris terrestrial chlorophyll index. International Journal of Remote Sensing, 25(23), 5403–5413. https://doi.org/10.1080/0143116042000274015

4. Datt, B. (1999). Visible/near infrared reflectance and chlorophyll content in eucalyptus leaves. International Journal of Remote Sensing, 20(14), 2741–2759. https://doi.org/10.1080/014311699211778

5. Féret, J. B., Gitelson, A. A., Noble, S. D., & Jacquemoud, S. (2017). Prospect-d: Towards modeling leaf optical properties throμgh a complete lifecycle. Remote Sensing of Environment, 193, 204–215. https://doi.org/10.1016/j.rse.2017.03.004

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