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.

Spectral indices for tracing leaf water status with hyperspectral reflectance data

“…The procedures described were applied to all possible wavelength combinations, and an iterative approach resulted in a wavelength interval of 5 nm. 28,38 The parameters of published indices were selected using the maximum coefficient of determination (R 2 ), and the least root mean square error (RMSE). The principal objective was to identify indices with minimum RMSE and the highest R 2 values.…”

“…EWT is the term used to describe how much water is present and how much energy is absorbed per unit of leaf area. 28,46 PWC relates to the dry weight ratio, and GWC determines the weight of the fresh and dry leaves. Below is the correspondence for EWT, PWC, and GWC…”

“…Reflectance and transmittance measurements of 275 leaf samples from 43 different species were collected along with associated biochemical and physical measurements. 28,53 Additional data from the LOPEX and ANGERS databases were considered to validate the indices provided in this work and determine their generalizability and reliability. As for both the databases reflectance curves with median spectrum have been measured, as shown in Fig.…”

“…The GWC, defined as the ratio of leaf water mass to leaf dry or fresh mass and given as a percentage, is a popular way to quantify leaf water content. 28 The vegetation fuel community prefers the GWC in dry mass form, but the ecological community prefers it in fresh mass form. The optical domain determination of GWC was based on the link between reflectance at 700 to 2500 nm and the amount of water present.…”