Vegetation Optical Depth and Scattering Albedo Retrieval Using Time Series of Dual-Polarized L-Band Radiometer Observations
[11-Apr-2016] Konings, A., Entekhabi, D., Piles, M., and McColl, K.
Presented at the 14th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment
Passive microwave measurements have the potential to estimate vegetation optical depth (VOD), an indicator of aboveground vegetation water content. They are also sensitive to the vegetation scattering albedo and soil moisture. In this work, we propose a novel algorithm to retrieve VOD and soil moisture from timeseries of dualpolarized L-band radiometric observations along with time-invariant scattering albedo. The method takes advantage of the relatively slow temporal dynamics of early morning vegetation water content and combines a number of consecutive observations to estimate a single VOD. It is termed the multi-temporal dual channel algorithm (MT-DCA). The soil dielectric constant (directly related to soil moisture) of each observation is also retrieved simultaneously. Additionally, the method retrieves a constant albedo, thereby providing for the first time information on global single-scattering albedo variations. The algorithm is tested using three years of L-band passive observations from the NASA Aquarius sensor. The global VOD distribution follows expected gradients of climate and canopy biomass conditions. Its seasonal dynamics follow expected behavior based on precipitation and land cover. The retrieved VOD is closely related to coincident cross-polarized backscatter coefficients. The VOD and dielectric retrievals from MT-DCA are also compared to those obtained from implementing the commonly used Land Parameter Retrieval Model (LPRM) algorithm and shown to have less high-frequency noise. There is almost as much variation in MT-DCA retrieved albedo between pixels of a given land cover class than between land cover classes, suggesting the common approach of assigning albedo based on land cover class may not capture its spatial variability. Globally, albedo appears to be primarily sensitive to woody biomass. The proposed algorithm allows for a more accurate accounting of the effects of vegetation on radiometric soil moisture retrievals, and generates new observations of L-band VOD and effective single-scattering albedo. These new datasets are complementary to existing remotely sensed vegetation measurements such as fluorescence and optical-infrared indices.