Advances in estimation methods of vegetation water content based on optical remote sensing techniques

Abstract

Quantitative estimation of vegetation water content (VWC) using optical remote sensing techniques is helpful in forest fire assessment, agricultural drought monitoring and crop yield estimation. This paper reviews the research advances of VWC retrieval using spectral reflectance, spectral water index and radiative transfer model (RTM) methods. It also evaluates the reliability of VWC estimation using spectral water index from the observation data and the RTM. Focusing on two main definitions of VWC-the fuel moisture content (FMC) and the equivalent water thickness (EWT), the retrieval accuracies of FMC and EWT using vegetation water indices are analyzed. Moreover, the measured information and the dataset are used to estimate VWC, the results show there are significant correlations among three kinds of vegetation water indices (i.e., WSI, NDII, NDWI 1640 , WI/NDVI) and canopy FMC of winter wheat (n=45). Finally, the future development directions of VWC detection based on optical remote sensing techniques are also summarized. optical remote sensing, vegetation water content, estimation method, water index, FMC, EWT, radiative transfer model Citation: Zhang J H, Xu Y, Yao F M, et al. Advances in estimation methods of vegetation water content based on optical remote sensing techniques.

Remotely sensed vegetation moisture as explanatory variable of Lyme borreliosis incidence

“…The sensitivity of the short wave infrared (SWIR) region to changes in vegetation moisture has been widely documented (Ceccato et al, 2001;Gao, 1996;Zhang et al, 2010) and has been implemented in the form of a number of spectral indices. The most well known moisture related vegetation indices are computed as normalized differences between the near-infrared (NIR) reflectance and the SWIR and are commonly referred to in literature as Normalized Difference Water Index (NDWI).…”

Leaf Equivalent Water Thickness assessment using reflectance at optimum wavelengths

“…To estimate leaf EWT, stepwise regression and leaf reflectance model inversion can also be used ( Jacquemoud et al 2000). Many indexes have been introduced and most of them are empirical (Ceccato et al 2002), mostly in the form of the ratio of two reflectance values or a combination of two or more reflectance values (Zhang et al 2010). Zhang et al (2010) have reported five absorption bands for water in 400-2,500 nm spectral region: 970; 1,200; 1,450; 1,930 and 2,500 nm.…”

“…Many indexes have been introduced and most of them are empirical (Ceccato et al 2002), mostly in the form of the ratio of two reflectance values or a combination of two or more reflectance values (Zhang et al 2010). Zhang et al (2010) have reported five absorption bands for water in 400-2,500 nm spectral region: 970; 1,200; 1,450; 1,930 and 2,500 nm. Riaño et al (2005b) specified that 1,400-2,500 nm range provides the highest correlation with EWT.…”

“…Full Moisture Content (FMC) and Equivalent Water Thickness (EWT) are more often addressed. FMC is the ratio of leaf water mass to either dry or wet mass of leaf and is shown by Equation 1 (Zhang et al 2010 …”

Evaluation of the visible and shortwave infrared drought index in China

“…Wang and Qu (2009) comprehensively reviewed progress in soil moisture monitoring using optical, thermal, passive microwave, and active microwave remote sensing techniques. Zhang et al (2010) also reviewed advances in research of vegetation water content retrieval using optical remote sensing, including various vegetation moisture indices and the radiative transfer model (RTM) methods.…”