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Red-edge vegetation indices from GF-6 for mitigating LAI effect in leaf chlorophyll estimation
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DOI：10.1080/01431161.2026.2699967.png)
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Abstract
En 中文
Leaf chlorophyll content (LCC) is a critical biochemical parameter that reflects the photosynthetic capacity and physiological status of vegetation. Traditional remote sensing approaches for retrieving LCC based on vegetation indices (VIs) are often influenced by leaf area index (LAI), thereby limiting retrieval accuracy. The red-edge spectral region has emerged as a key area for improving LCC estimation due to its high sensitivity to chlorophyll variations and reduced susceptibility to LAI interference. In this study, Blue-adjusted Red-edge NDVI 1 (BNDRE1) and NIR-adjusted Chlorophyll-Sensitive Index (NCSI) were developed to enhance sensitivity to LCC while mitigating the effects of LAI based on red-edge multispectral information from China’s GaoFen-6 (GF-6) satellite data. Key spectral bands were identified through sensitivity analysis, and adjustment factors were integrated to optimize the formulation of the proposed indices. Their effectiveness was systematically validated using PROSAIL simulations, field observations, and MusyQ chlorophyll products. Simulation analysis showed that the correlation coefficients between BNDRE1 and NCSI with LCC were 0.901 and 0.904, respectively, representing improvements of at least 14.05% and 14.43% over traditional indices such as NDRE1. In field observations, their highest correlations with SPAD reached 0.740 and 0.736. Furthermore, BNDRE1 and NCSI achieved correlation coefficients of 0.640 and 0.665, respectively, in the cross-validation with MusyQ chlorophyll products, outperforming NDRE1. These findings demonstrate that incorporating red-edge characteristics and optimizing index structures can enhance the accuracy of LCC retrieval, thereby facilitating the application of GF-6 data for large-scale chlorophyll mapping to support agriculture, vegetation management, and ecological monitoring.
Keywords:
Winter wheat
PROSAIL model
chlorophyll retrieval
canopy structure effect
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