RSPECT: A PROSPECT-based model incorporating the real structure of rice leaves

IF 11.4 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES
Shuang Xiang , Shikuan Wang , Zhongyu Jin , Yi Xiao , Meihan Liu , Hao Yang , Shuai Feng , Ziyi Feng , Tan Liu , Fenghua Yu , Tongyu Xu
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引用次数: 0

Abstract

Radiative transfer models (RTMs) describe how light is absorbed, scattered, and transmitted within leaves by simulating mechanistic light propagation processes. The PROSPECT model is based on measurable parameters (the leaf biochemical content) and a non-measurable parameter (the leaf anatomical structure represented by the leaf structure parameter (N)). The effect of N on the optical properties of leaves has been investigated through a number of local and global sensitivity analyses. Other studies have directly evaluated the effect of the leaf anatomical structure on spectral reflectance, particularly in the near infrared region. However, the relationship between N and the anatomical structure is unclear. In this study, we leveraged eLeaf, a ray tracing-based 3D rice leaf simulator, to establish relationships between leaf anatomical features and spectral properties, enabling us to replace N in the PROSPECT-4 model with measurable leaf anatomical parameters and develop the RSPECT model. The leaf thickness at minor vein, leaf thickness at bulliform cells, mesophyll thickness at minor vein, and distance between two minor veins could be used to predict N effectively. The RSPECT model achieved spectral simulation accuracy comparable to PROSPECT-4 and was more suitable for parameter inversion of the physical and chemical properties of rice leaves, with relative root mean square errors of 7.4 % for chlorophyll content, 5.6 % for equivalent water thickness, and 7.5 % for dry matter content. In conclusion, RSPECT improves radiative transfer modeling by integrating measurable anatomical features and provides a framework for extending this approach to other vegetation types.
尊重:一个基于前景的模型,结合了水稻叶片的真实结构
辐射传输模型(RTMs)通过模拟光的机械传播过程来描述光是如何在叶片中被吸收、散射和传输的。PROSPECT模型基于可测量参数(叶片生化含量)和不可测量参数(叶片结构参数(N)表示的叶片解剖结构)。通过局部和全局敏感性分析,研究了氮对叶片光学特性的影响。其他研究直接评估了叶片解剖结构对光谱反射率的影响,特别是在近红外区域。然而,N与解剖结构的关系尚不清楚。在本研究中,我们利用基于光线跟踪的三维水稻叶片模拟器eLeaf建立了叶片解剖特征与光谱特性之间的关系,使我们能够用可测量的叶片解剖参数代替PROSPECT-4模型中的N,并建立了spect模型。小叶脉叶厚度、球状细胞叶厚度、小叶脉叶肉厚度、小叶脉间距可以有效地预测氮素。RSPECT模型的光谱模拟精度与PROSPECT-4相当,更适合于水稻叶片理化性质的参数反演,叶绿素含量的相对均方根误差为7.4%,等效水厚度的相对均方根误差为5.6%,干物质含量的相对均方根误差为7.5%。总之,RSPECT通过整合可测量的解剖特征来改进辐射传输建模,并为将该方法扩展到其他植被类型提供了一个框架。
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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