Estimation of Leaf Water Content in Cotton by Means of Hyperspectral Indices

The knowledge of vegetation water conditions can in fact contribute to detect vegetation physiological status, to provide useful information in agriculture for irrigation decisions and drought assessment. Remote sensing offers an important opportunity for quantitative assessment of vegetation properties at different scales.

Together with other parameters, vegetation water content is an important property that can be investigated by using remotely sensed data. The main parameters describing the amount of water in vegetation that are usually investigated by remote sensing are fuel moisture content (FMC, %) and leaf equivalent water thickness (EWT, cm). With the development of hyperspectral remote sensing technique, direct detection approaches of vegetation water content have been proposed and further used to evaluate crop drought condition.

To exploit the relationships between leaf water content (EWT and FMC) and all possible two-band combinations indices and evaluate the performance of various types of hyperspectral vegetation indices in characterizing leaf water content, YI Qiuxiang et al. from Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences conducted field experiment was in June–October 2010 at agricultural belts in Shihezi, Xinjiang, where cotton is the dominate crop.

In this study, all two-band combinations (350-2500 nm) in the ratio type of vegetation index (RVI) and the normalized difference type of vegetation index (NDVI) were performed on cotton leaf raw spectral reflectance (R) and the first derivative reflectance (DR). Researchers also determined the correlation coefficient (r) between all two-band combinations and two leaf water parameters (EWT and FMC).

The results shown that the new indices DR1647/DR1133 and DR1653/DR1687, proposed by two-band combinations, were considered as the optimal indices for EWT and FMC estimation, respectively. The models based on these two best combination indices could explain 58% and 67% variability in EWT and FMC, respectively. Besides, bands with center wavelengths in region from 950 nm to 1100 nm, and 1650 nm to 1750 nm were represented almost all selected bands.

The paper entitled “Estimation of Leaf Water Content in Cotton by Means of Hyperspectral Indices” was recently published in Computers and Electronics in Agriculture in 2013, 90: 144-151.