Abstract
Remote sensing (RS) estimation of chlorophyll density serves as an effective measure to assess crop nitrogen (N) nutrition status and guide precision N fertilizer management. Throμgh multi-angular RS, this study aims to improve the estimation accuracy of chlorophyll density by reducing the disturbance of mixed background (soil and non-photosynthetic vegetation), and to explore the solutions to minimizing the influence of view zenith angles (VZAs). Wheat canopy multi-angular hyperspectral data (− 60°, − 45°, − 30°, 0°, 30°, 45°, 60°) were systematically collected throμgh three-years of field experiments. A soil non-photosynthetic background and angle insensitive vegetation index \(\left({\text{SAIVI}} = \frac{\Big({\left({\rho }_{750}\right)}^{-1} -{\left({\rho }_{860}\right)}^{-1}\Big)- \Big({\left({\rho }_{765}\right)}^{-1} -{\left({\rho }_{860}\right)}^{-1}\Big)}{\Big({\left({\rho }_{750}\right)}^{-1} -{\left({\rho }_{860}\right)}^{-1}\Big)+\Big({\left({\rho }_{765}\right)}^{-1} -{\left({\rho }_{860}\right)}^{-1}\Big)}\right)\) was proposed for inversion of chlorophyll density. Furthermore, SAIVI, along with another 11 vegetation indices (VIs), were evaluated for their performance in estimating three chlorophyll parameters, namely chlorophyll concentration (CC), canopy chlorophyll density based on leaf area (CCCL) and canopy chlorophyll density based on fresh weight (CCCW). The results indicated that SAIVI had strong stability in restraining distractor (mixed background of soil and non-photosynthetic vegetation). For inversion of CC, CCCL and CCCW, backward VZAs showed higher accuracy than vertical angle. The new proposed SAIVI performed best for estimating CCCL and CCCW with an optimal VZA of − 30°, and the corresponding R2 and RRMSE of 0.76 and 0.77, 14.5% and 26.6%, respectively.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (31971784), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), the earmarked fund for Jiangsu Agricultural Industry Technology System JATS[2022]168). The authors would like to thank Tiancheng Yang, Jie Zhu, Yining Tang, and Yangyang Gu for their help with the field data collection.
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YP: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Resources, Visualization, Writing—Original Draft, Writing—Review & Editing. RZ: Methodology, Supervision, Writing—Original Draft, Writing—Review & Editing. JZ: Supervision, Formal analysis, Writing—Original Draft, Writing—Review & Editing. WG, MY, CG: Data curation, Investigation, Writing—Original Draft. XY, TC, YZ, WC: Conceptualization, Methodology, Supervision, Writing—Original Draft. YT: Conceptualization, Resources, Writing—Original Draft, Writing—Review & Editing, Supervision, Project administration, Funding acquisition.
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Pan, Y., Zhou, R., Zhang, J. et al. A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect. Precision Agric 24, 2098–2125 (2023). https://doi.org/10.1007/s11119-023-10032-w
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DOI: https://doi.org/10.1007/s11119-023-10032-w