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Temporal variations in synthetic aperture radar (SAR) backscatter over forests are of concern for any SAR mission with the goal of estimating forest parameters from SAR data. In this article, a densely sampled, two-year long time series of P-band (420 to 450 MHz) boreal forest backscatter, acquired by a tower-based radar, is analyzed. The experiment setup provides time series data at multiple polarizations. Tomographic capabilities allow the separation of backscatter at different heights within the forest. Temporal variations of these multipolarized, tomographic radar observations are characterized and quantified. The mechanisms studied are seasonal variations, effects of freezing conditions, diurnal variations, effects of wind, and the effects of rainfall on backscatter. An emphasis is placed on upper-canopy backscatter, which has been shown to be a robust proxy for forest biomass. The canopy backscatter was more stable than ground-level backscatter during nonfrozen conditions, supporting forest parameter retrieval approaches based on tomography or interferometric ground notching. Large backscatter variations during frozen conditions, which may be detected using cross-polarized backscatter observations, can result in large errors in forest parameter estimates. Diurnal backscatter variations observed during hot periods were likely connected to tree water transport and storage mechanisms. Backscatter changes were also observed during strong winds. These variations were small in comparison to the variations due to freeze-thaw and soil moisture changes and should not result in significant forest parameter estimation errors. The presented results are useful for designing physically based and semiempirical scattering models that account for temporal changes in scattering characteristics.

Temporal Characteristics of P-Band Tomographic Radar Backscatter of a Boreal Forest