Work

Evaluating the impact of canopy spatial heterogeneity on Solar-Induced chlorophyll fluorescence and Model-Based quantification

Year: 2025

Type: article

Abstract: Solar-induced chlorophyll fluorescence (SIF) is a powerful proxy for vegetation photosynthesis. However, its broader application remains constrained by the insufficient understanding and quantification of canopy spatial heterogeneity. We used the 3D discrete anisotropic radiative transfer (DART) model to simulate SIF. Heterogeneous and homogeneous canopies were compared to quantify the impact of canopy spatial configuration on total leaf-emitted SIF (SIF total ) and hemispherically integrated top-of-canopy SIF (SIF hemi ). Angular effects were examined by comparing top-of-canopy SIF (SIF toc ) with SIF total estimated at different viewing angles. We also compared the relationships of simulated SIF total and SIF toc with fraction of absorbed photosynthetically active radiation ( f APAR) and vegetation indices (VIs). In addition, we evaluated the relationships between the coefficient of variation (CV) of VIs and SIF, and developed a correction function for estimating heterogeneous-canopy SIF using homogeneous-canopy SIF. The results reveal that (1) both SIF total and SIF hemi are significantly higher in homogeneous than in heterogeneous canopies; (2) estimating SIF total from SIF toc effectively reduces angular dependency; (3) SIF total exhibits the strongest correlation with f APAR, while SIF toc aligns better with NIRv and EVI; and (4) VI-derived CVs are negatively correlated with SIF, with CV NIRv and CV EVI at 10 m resolution demonstrating robust performance in fitting the ratio of heterogeneous-to-homogeneous canopy SIF, validating the proposed correction function. This study highlights the critical role of canopy structural heterogeneity in shaping SIF and presents an approach to convert homogeneous-canopy SIF to heterogeneous-canopy conditions, offering a novel pathway toward more accurate SIF estimation and application.

Source: International Journal of Applied Earth Observation and Geoinformation

DOI: 10.1016/j.jag.2025.104971

Authors: Liang Zhao, Rui Sun

Institutions: Beijing Normal University, Beijing Normal University, Zhuhai

Language: English

Topic: Remote Sensing in Agriculture

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDG: Climate action

Open Access status: gold

Estimated APC paid: $3,550