TEMPORAL VARIABILITY OF SOIL AND VEGETATION BACKSCATTERING OBSERVED IN DENSE L-BAND TIME-SERIES

We study the temporal variability of soil and vegetation backscatter at L-band using a dense airborne time-series. Backscatter is assumed to change over time due to diurnal variations in soil and canopy water content as well as precipitations. A two-layer SAR backscatter model traditionally used for above-ground biomass retrieval is augmented here with the time dimension in order to guide the data analysis. The model is informed by examining a 5-year time-series of 32 L-band polarimetric UAVSAR images acquired over a vegetated area near the Sacramento Delta in California. Our initial results reported in this paper show that the temporal variability of soil and vegetation backscatter in absence of precipitation events fits well a lognormal probability distribution with mean and standard deviation related to each other. Characterizing the diurnal, seasonal and interannual variability of L-band backscatter may be critical for the successful estimation of ecosystem variables from dense time-series to be acquired globally by the NISAR mission.