Accounting for Deciduous Forest Structure and Viewing Geometry Effects Improves Sentinel-1 Time Series Image Consistency.

Microwave scattering from forests generates pixel geolocation shifts in synthetic aperture radar (SAR) data that require an adequate representation within digital elevation models (DEMs) for preprocessing. We analyze the impact of DEM properties on the radiometry and geolocation of radiometric terrain corrected Copernicus Sentinel-1 imagery of forests to improve consistency in backscatter intensities for time series analyses. To account for the penetration depth of the C-band sensor, we approximate the structure of stands in a temperate deciduous forest using height percentiles from aerial laser scanning (ALS) point clouds in the Hainich National Park (HNP), Germany. Comparing the RTC results obtained using DEMs of SRTM, Copernicus, and ALS DEMs, the latter reduces topographically induced errors, resulting in visibly smaller effects from topography and spatially shifted information. Based on the P50 ALS vegetation elevation, the results show homogeneous intensities within the same orbit and reduce variance from 2.4 to 1.2 dB2 in the difference in mid-range data from ascending and descending azimuth directions. Over forest, we observe lower intensities on sensor-facing and increased intensities on away-facing slopes and correlations with the illuminated pixel area (IPA) and local incidence angle (LIA). We reduce this bias with linear regressions of intensity on IPA. ALS DEMs in RTC and the proposed regression correction increase the consistency of images across orbits, measured by the inter-orbit range (IOR), throughout the selected year at our study site. We suggest the proposed method applies to other areas, requiring further testing under different forest types and topography.