Limitations and Improvements of the Leaf Optical Properties Model Leaf Incorporating Biochemistry Exhibiting Reflectance and Transmittance Yields (LIBERTY)

Wang, Jun; Ju, Weimin

doi:10.3390/rs9050431

Cited by 31 publications

(2 citation statements)

References 18 publications

(30 reference statements)

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“…In addition, OPM is the foundation for the study of particle radiation properties. Wang, B., & Ju, W. [5] proposed a particle string model based on Melamed theory and OPM, then based on the model, worked out the reflectance and transmittance of a particle string that is composed of a limited number of particles, with a result showing that the model can be used to simulate needle leaf optical properties. Luis F. González-Portillo et al [6] proposed an analytical model of the optical path to investigate the optical properties of particle curtains, then compared the model with the Monte Carlo Ray-Tracing (MCRT) model, showing similar calculation results, while the proposed model is simpler than the MCRT model.…”

Section: Introductionmentioning

confidence: 99%

Optical Path Model of Multi-Layer Media for Incoherent Light

Qi,

Zhang,

Liang

et al. 2024

Preprint

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Optical path model has been widely used in fields such as solar energy materials and optical constant calculation. Nevertheless, the accuracy and usability of models in recent studies are not satisfactory enough. In order to reduce the calculated error of the model in the application, the optical path model of multiple media and phases for incoherent light was proposed, which describes the optical path of continuous rays in the multi-layer system on two dimensions. In the paper, the optical properties of the optical cell were first calculated based on the single-layer model and genetic algorithm. Then, the proposed model was validated by a triple-phase system with multiple layers of media. Meanwhile, the main calculated error was analyzed. Finally, the models in existing studies were compared with the proposed model. The results show that the model can be used to accurately calculate the total transmittance, total reflectance, and total absorption of a multi-layer system with multiple phases and media when the optical properties of each layer are known. Meanwhile, the proposed model has good stability as well as internal coupling, and its accuracy is better than other models.

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Section: Introductionmentioning

confidence: 99%

Optical Path Model of Multi-Layer Media for Incoherent Light

Qi,

Zhang,

Liang

et al. 2024

Preprint

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“…Physical-based methods minimize the difference between the measured and modeled leaf optical properties using radiative transfer models. There are several radiative transfer models that could be used for this purpose, such as the PROSPECT [ 10 , 11 ], LIBERTY [ 12 , 13 ], and SLOPE [ 14 ] models. Among them, PROSPECT is the most widely used because of its relatively simple and satisfactory performances.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Methods for the Estimation of Leaf Water and Dry Matter Content: Performances, Potential and Limitations

Yang

Lin

2020

Sensors

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Leaf equivalent water thickness (EWT) and dry matter content (expressed as leaf mass per area (LMA)) are two critical traits for vegetation function monitoring, crop yield estimation, and precise agriculture management. Data-driven methods are widely used for remote sensing of leaf EWT and LMA because of their simplicity, satisfactory accuracy, and computation efficiency, such as the vegetation indices (VI)-based and machine learning (ML)-based methods. However, most of the data-driven methods are utilized at the canopy level, comparison of the performances of the data-driven methods at the leaf level has not been well documented. Moreover, the ML-based data-driven methods generally adopt leaf optical properties directly as their inputs, which may subsequently decrease their ability in remote sensing of leaf biochemical constituents. Performances of the ML-based methods cooperating with VI are rarely evaluated. Using the independent LOPEX and ANGERS datasets, we compared the performances of three data-driven methods: VI-based, ML-reflectance-based, and ML-VI-based methods, for the estimation of leaf EWT and LMA. Three sampling strategies were also utilized for evaluation of the generalization of these data-driven methods. Our results evidenced that ML-VI-based methods were the most accurate among these data-driven methods. Compared to the ML-reflectance-based and VI-based methods, the ML-VI-based model with support vector regression overall reduced errors by 5.7% (41.5%) and 1.8% (12.4%) for the estimation of leaf EWT (LMA), respectively. The ML-VI-based model inherits advantages of vegetation indices and ML techniques, which made it sensitive to changes of leaf biochemical constituents and capable of solving nonlinear tasks. It is thus recommended for the estimation of EWT and LMA at the leaf level. Moreover, its performance can further be enhanced by improving its generalization ability, such as adopting techniques on the selection of better wavelengths and definition of new vegetation indices. These results thus provided a prior knowledge of the data-driven methods and can be helpful for future studies on the remote sensing of leaf biochemical constituents.

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Optical path model of multi-layer media for incoherent light

Zhang,

Liang,

et al. 2024

J Opt

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Limitations and Improvements of the Leaf Optical Properties Model Leaf Incorporating Biochemistry Exhibiting Reflectance and Transmittance Yields (LIBERTY)

Cited by 31 publications

References 18 publications

Optical Path Model of Multi-Layer Media for Incoherent Light

Optical Path Model of Multi-Layer Media for Incoherent Light

Data-Driven Methods for the Estimation of Leaf Water and Dry Matter Content: Performances, Potential and Limitations

Optical path model of multi-layer media for incoherent light

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