Combining Microwave and Optical Remote Sensing to Characterize Global Vegetation Water Status

Vegetation water status, an important physiological characteristic of vegetation, lacked a global-scale estimate method. In this study, a global vegetation moisture relative index (VMRI) was established based on the vegetation optical depth (VOD) and leaf area index and compared to live fuel moisture content (LFMC) in-situ measurements and environmental factors (soil moisture from different depths, precipitation, vapor pressure deficit, ratio of actual to potential evapotranspiration, and self-calibrating Palmer drought severity index). Validation using LFMC measurements indicated that VMRI could characterize vegetation water status (R _median = 0.37) and that the VMRI establishment method could eliminate the influence of aboveground biomass in VOD. The results of the correlated comparison between VMRI and environmental factors showed positive significant correlations in most regions. Besides, the VMRI was more correlated with environmental factors in shrublands and grasslands (e.g., R _mean = 0.38 in multi-depth soil moisture) than in forests and savannas (R _mean = 0.15), and the correlations between the VMRI and environmental factors in water-limited regions (R _mean = 0.33) were higher than those in non-water-limited regions (R _mean = 0.18). Moreover, deeper soil moisture provided more information to the VMRI in regions above 60°N. Furthermore, comparison of soil moisture trends and VMRI trends displayed more synchronization, with about 60% of pixels showing the same trend and about 85% of the same-trend pixels showing decreasing trends Particularly, interannual variations in forests showed time-lagged responses to environmental drought. Overall, VMRI provides a new in-situ measurement-independent estimation for vegetation water status affected by multiple environmental factors at the global scale.