Combination of Spectral Angle Cosine and Band Depth Can Reduce the Specular Reflection Effects in Leaf Biochemical Parameters Estimation From Multiangular Hyperspectral Data

Leaf chlorophyll content (LCC) and equivalent water thickness (EWT) are critical indicators of plant physiological state and photosynthetic capacity. Hyperspectral measurements provide technical support for the efficient estimation of these leaf biochemical parameters. However, most current studies ignored the influence of leaf surface specular reflection, which reduces estimation accuracy, in the multiangular (MA) measurements. This study proposed the spectral angle cosine-band depth indices (SACI_BD), a method that transforms additive specular reflection into multiplicative differences using band depth (BD) and eliminates them via spectral angle cosine (SAC). Based on an MA calibration dataset, the optimal spectral intervals (OSIs) for SACI_BD were identified. Then, SACI_BD was validated across five independent leaf datasets and canopy imaging datasets obtained through close-range camera and LESS simulated scene. Results demonstrated that SACI_BD efficiently captured biochemical-sensitive spectral absorption shape features (OSI_LCC: 658–748 nm and OSI_EWT: 1872–2026 nm) and eliminated the specular reflection influence on biochemical estimation. Strong linear relationships with both LCC ( $R^{\mathrm {2}}=0.9$ ) and EWT ( $R^{\mathrm {2}}=0.94$ ), as well as validation results of five leaf datasets (LCC: RMSE $= 5.98~\mu $ g/cm², $n = 2143$ ; EWT: RMSE = 0.0031 g/cm², $n = 1919$ ), confirmed the applicability of SACI_BD for various measurement strategies and plant species in the estimation of leaf biochemical parameters. When the study was extended to the canopy level, SACI_BD achieved similarly good accuracy (LCC: RMSE $= 6.98~\mu $ g/cm², $n = 104$ ; EWT: RMSE = 0.0044 g/cm², $n = 34$ ). Thus, the novel combination of SAC and BD provides an effective tool for quantitative plant biochemistry research.