Potential of Satellite Spectral Resolution Vegetation Indices for Estimation of Canopy Chlorophyll Content of Field Crops: Mitigating Effects of Leaf Angle Distribution

Accurate estimation of canopy chlorophyll content (CCC) is critically important for agricultural production management. However, vegetation indices derived from reflectance are influenced by structure, which limits their application across species and seasonality. For horizontally homogenous canopies such as field crops, LAI leaf inclination angle distribution or mean tilt (MTA) two biophysical characteristics determining structure. Since CCC relevant to LAI, MTA the only structural parameter affecting correlation between indices. To date, there few designed minimize effects estimation. Herein, in this study, CCC-sensitive MTA-insensitive satellite broadband developed crop The most efficient four sensors (Sentinel-2, RapidEye, WorldView-2 GaoFen-6) with red edge channels were identified (in context various index types) using simulated based on measurements validated PROSAIL model simulations. results indicate that present strong correlations weak MTA, overall R2 0.76–0.80 0.84–0.95 0.00 0.00–0.04 measured data simulations, respectively. best study soil-adjusted type SAI (B6, B7) Sentinel-2, Verrelts’s three-band spectral BSI-V (NIR1, Red, Red Edge) WorldView-2, Tian’s BSI-T (Red Edge, Green, NIR) RapidEye difference DI B4) GaoFen-6. can potentially be used real datasets more need tested further studies.