Estimation of Leaf Water Content of Different Leaves from Different Species Using Hyperspectral Reflectance Data

Abstract

Water content of individual leaves or vegetation canopies is a significant variable in plant physiological processes. The water content of the vegetation leaves plays a very significant role. The ability of hyperspectral advanced technology to accurately evaluate leaf and canopy water content has improved large-scale measures. Due to the presence of water absorption band in near and SWIR wavelength range, electromagnetic spectrum will allow us to correctly measure the leaf water content. Three different parameters were used to describe the water status: Equivalent Water Thickness (EWT), Gravimetric Water Content (GWC), and Plant Water Concentration (PWC), with leaf multi angular reflectance spectrum, to find sensitive spectral indices, to correctly assess water content of leaves in a wide range of plant species. Using spectral indices derived from multi angular reflectance spectra, we looked into the possibility for predicting leaf water content of six species in the study area. To analyze the status of leaf water, three different forms of hyperspectral indices were evaluated, including the Simple Ratio (SR), Normalized ratio wavelength (ND) and Double Difference ratio (DDn). To look over the possibility of predicting the leaf water status of the species in the study field, we proposed four new indices. The results showed that EWT is comparatively more sensitive to trace leaf water status than GWC and PWC. The best-established EWT indices were (R905-R1795)/(R1905-R1935), R1350/R1390, (R840-R1565)/(R840+R1565) and (R925-R1625)/ (R925+R1625) and the performance of the proposed hyper-spectral indices surpassed the performance of other indices in this study. The mentioned indices were then further analyzed on LOPEX and ANGERS databases for validation of our suggested indices and we come up with better results. This study indicates that spectral indices can be used and could be more reliable to predict leaf water content, but future studies will need to include more plant species and field data. The newly developed indices can be used to estimate EWT using simple laboratory measurements, making them helpful for agricultural environmental sciences and ecology related studies.