Hyperspectral Retrieval of Canopy Water Content Through Inversion of the Beer-Lambert Law

The retrieval of quantitative equivalent water thickness on canopy level $(\mathrm{EWT}_{\mathrm{c}})$ is an agriculturally important task for hyperspectral remote sensing. In this study the Beer-Lambert law is applied to inversely determine water content from measured winter wheat spectra collected in 2015 and 2017. The spectral model is calibrated using a look-up-table (LUT) of 50.000 PROSPECT spectra. Validation was performed using two leaf optical properties datasets (LOPEX93 and ANGERS) and in-situ data acquired in Southern Germany. After considering destructive in-situ water content measurements separately for leaves, stems, and fruits, results indicate optically active plant water by plant component in the 930 to 1060 nm range of canopy reflectance. Results for spectrally derived $\mathrm{EWT}_{\mathrm{c}}$ were most promising for leaves and ears reaching coefficients of determination up to 0.75 and a normalized RMSE (nRMSE) of 24% between measured and estimated canopy water content.