Estimating leaf chlorophyll content in sugar beet canopies using millimeter- to centimeter-scale reflectance imagery

For the eleven spatial resolutions, the four pixel selections and the five VI formats, similar band combinations are obtained when optimizing VI performances: the main bands of interest are generally located in the blue, red, red-edge and near-infrared domains. Overall, mNDblue[728, 850] defined as (R440 − R728)/(R440 + R850) and computed over the brightest green pixels obtains the best correlations with Cab for spatial resolutions finer than 8.8 cm with a root mean square error of prediction better than 2.6 μg/cm2. Conversely, mNDblue[728, 850] poorly correlates with variations in GF and GAI, thus reducing the risk of deriving non-causal relationships with Cab that would actually be due to the covariance between Cab and these canopy structure variables. As mNDblue[728, 850] can be calculated from most current multispectral sensors, it is therefore a promising VI to retrieve Cab from millimeter- to centimeter-scale reflectance imagery.