A novel red‐edge spectral index for retrieving the leaf chlorophyll content

The leaf chlorophyll content (Chlleaf) is a crucial vegetation parameter in carbon cycle modelling and agricultural monitoring at local, regional and global scales. The red-edge spectral region is sensitive to variations in Chlleaf. An increasing number of sensors are capable of sampling red-edge bands, providing opportunities to estimate Chlleaf. However, the contributions of canopy/foliar/soil factors are always combined in the reflectance signal, which limits the generalizability of vegetation index (VI)-based Chlleaf inversions. This study aims to propose a new red-edge chlorophyll index to decouple the effects of the canopy and soil background from the Chlleaf estimation.

The chlorophyll sensitive index (CSI) was proposed, and the regression equations between the CSI and Chlleaf were acquired using PROSAIL (PROSPECT + SAIL) and the 4-Scale-PROSPECT model.

Sensitivity analyses showed that the CSI is resistant to variations in the canopy structure and soil background. Validation results obtained using 308 ground-measured samples over nine sites world-wide revealed that CSI improves the Chlleaf retrieval accuracy (root mean square error (RMSE = 9.39 μg cm−2) compared with the existing Medium Resolution Imaging Spectrometer (MERIS) terrestrial chlorophyll index (MTCI; RMSE = 13.00 μg cm−2). Moreover, the CSI method steadily achieves a highly accurate inversion under different LAI and Chlleaf conditions. Based on the CSI regression method, a Chlleaf product with a 30-m/10-day resolution across China was generated.

The CSI is sensitive to Chlleaf but resistant to canopy structure and soil moisture parameters, and it has the potential to explicitly retrieve leaf-scale biochemistry in ecosystem modelling and ecological applications.