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A method to rapidly construct 3D canopy scenes for maize and their spectral response evaluation

文献类型： 外文期刊

作者： Zhao, Dan 1 ; Xu, Tongyu 1 ; Henke, Michael 3 ; Yang, Hao 2 ; Zhang, Chengjian 2 ; Cheng, Jinpeng 2 ; Yang, Guijun 2 ;

作者机构： 1.Shenyang Agr Univ, Coll Informat & Elect Engn, Shenyang 110866, Peoples R China

2.Beijing Acad Agr & Forestry Sci, Informat Technol Res Ctr, Key Lab Quantitat Remote Sensing Agr, Minist Agr & Rural Affairs, Beijing 100097, Peoples R China

3.Hunan Agr Univ, Sch Agron, Changsha 410128, Peoples R China

关键词： 3D maize canopy scene; Functional-structural model; Canopy structure; 3D radiative transfer; Spectral response

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：7.7； 五年影响因子：8.4 ）

ISSN： 0168-1699

年卷期： 2024 年 224 卷

页码：

收录情况： SCI

摘要： Three-dimensional (3D) scenes of a maize canopy can be utilized to depict its vertical structure and serve as the foundation for a 3D radiative transfer model. Given the inherent heterogeneity of canopy structures, evaluating their spectral response is crucial for remote-sensing inversion algorithms. Yet existing methods to model 3D canopy scenes of crops lack the high efficiency required for large-scale breeding applications. Hence, this study aims to develop a method to rapidly construct 3D canopy scenes of maize based on key structural parameters -namely, leaf area, base angle, and inclination angle -across multiple cultivars and growth stages. The accuracy of this canopy scenes modeling method was validated by comparison with a fine-scale 3D model and a multi-growth stage reflectance dataset. The root mean square error (RMSE) and normalized root mean square error (NRMSE) between the fine-scale 3D model and the constructed 3D model were less than 0.021 and 6.4%, respectively. Moreover, the RMSE and NRMSE between the simulated reflectance and measured reflectance were less than 0.042 and 11.1%, respectively. Next, we integrated the 3D radiative transfer model with 3D scenes to analyze the spectral response of maize canopy structure. The findings revealed that the near-infrared band was affected more by leaf area than leaf base angle, while the opposite is observed for the red-edge band. Furthermore, the middle layer contributed more to the canopy reflectance than either the upper or lower layers. Notably, two maize scenes where two structural parameters simultaneously change could elicit the same canopy spectra. The proposed method thus offers the dual advantages of rapid modeling and high efficiency, making it highly applicable for maize and other similar crops.

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