Incorporating Spectral and Directional Leaf Reflectance into Virtual Plant Models via Phong Shader Parameter Fitting

Accurate light simulations using virtual plant models are essential for analyzing how plant structures influence the micro-light climate within canopies. Such simulations are increasingly important in applications including remote sensing, greenhouse optimization, and synthetic data generation for agricultural systems. However, many current models simplify leaf optical behavior by assuming purely diffuse reflectance, thereby neglecting the spectral and angular variability described by the bidirectional reflectance distribution function (BRDF). To address this limitation, the spectral BRDF of cucumber leaves was experimentally measured and corresponding Phong reflectance model parameters were determined for use in the GroIMP simulation environment. These parameters were optimized to replicate the angular and spectral reflectance distribution patterns and evaluated against a diffuse reflectance model. The Phong model successfully reproduced key features of the BRDF, particularly the increased diffuseness in the green and far-red spectral regions, although deviations in hemispherical reflectance emerged at high incidence angles. The resulting Phong parameters offer a practical method for incorporating wavelength- and direction-dependent reflectance into virtual plant simulations. These parameters can be adapted to other reflectance values of leaves with similar optical properties using hemispherical reflectance measurements, enabling more realistic light modeling in virtual canopies. Within a 30-60° incidence, the Phong BRDF reduced per-wavelength error relative to a diffuse baseline across all spectral regions.

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Publication Details

Journal
Plants
Published
2025-09-04
DOI
https://doi.org/10.3390/plants14172775
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.72

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article

Incorporating Spectral and Directional Leaf Reflectance into Virtual Plant Models via Phong Shader Parameter Fitting

Jens Balasus, Tran Quoc Khanh, Alexander Herzog, Felix Wirth
1 citations
Plants
Remote Sensing in Agriculture
1.72
article

Incorporating Spectral and Directional Leaf Reflectance into Virtual Plant Models via Phong Shader Parameter Fitting

Jens Balasus, Tran Quoc Khanh, Alexander Herzog, Felix Wirth
article en
1 citations

Abstract

Accurate light simulations using virtual plant models are essential for analyzing how plant structures influence the micro-light climate within canopies. Such simulations are increasingly important in applications including remote sensing, greenhouse optimization, and synthetic data generation for agricultural systems. However, many current models simplify leaf optical behavior by assuming purely diffuse reflectance, thereby neglecting the spectral and angular variability described by the bidirectional reflectance distribution function (BRDF). To address this limitation, the spectral BRDF of cucumber leaves was experimentally measured and corresponding Phong reflectance model parameters were determined for use in the GroIMP simulation environment. These parameters were optimized to replicate the angular and spectral reflectance distribution patterns and evaluated against a diffuse reflectance model. The Phong model successfully reproduced key features of the BRDF, particularly the increased diffuseness in the green and far-red spectral regions, although deviations in hemispherical reflectance emerged at high incidence angles. The resulting Phong parameters offer a practical method for incorporating wavelength- and direction-dependent reflectance into virtual plant simulations. These parameters can be adapted to other reflectance values of leaves with similar optical properties using hemispherical reflectance measurements, enabling more realistic light modeling in virtual canopies. Within a 30-60° incidence, the Phong BRDF reduced per-wavelength error relative to a diffuse baseline across all spectral regions.

PlantsVol. 14(17)
Technische Universität Darmstadt (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 14%
Remote Sensing in Agriculture
1.72
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Incorporating Spectral and Directional Leaf Reflectance into Virtual Plant Models via Phong Shader Parameter Fitting — Jens Balasus, Tran Quoc Khanh, et al. · Plants (2025) | TGRS Research Map | TGRS