ABSTRACT
In this chapter, we review progress toward the measuring of vegetation water content by means of remotely sensed data collected at the leaf, ground, aircraft, and satellite level.
The main parameters describing the amount of water in vegetation that are usually investigated by remote sensing are gravimetric water content (%, i.e., fuel moisture content [FMC] in forest fire literature) and leaf equivalent water thickness (EWT, g/cm2). The possibility of estimating FMC and EWT by means of remotely sensed data derives from the fact that water absorbs radiant energy throughout the near-infrared (750–300 nm) and short-infrared (1300–2500 nm) spectral regions.
The methods for retrieval of vegetation water content from optical remote sensing have made much progress in the last decades. In particular, the increasing availability of high-resolution field spectrometers and hyperspectral imaging offer the possibility of exploiting several techniques to accurately estimate vegetation water content and evaluate its spatial and temporal variability for different ecosystems. Numerous methods have been developed to estimate water content from reflectance data collected at different scales; they mainly rely on empirical or physical approaches that use regression techniques with hyperspectral indices, and leaf and canopy radiative transfer models.
In summary, remote sensing is a powerful tool that provides accurate estimations of vegetation water content and offers the only possibility of generating maps at different spatial and temporal scales that can be assimilated in ecological studies that include vegetation as a dynamic component.
