Impact of Incidence Angle Diversity on SMOS and Sentinel-1 Soil Moisture Retrievals at Coarse and Fine Scales

Abstract

Incidence angle diversity of space-borne radiometer and radar systems operating at low microwave frequencies needs to be taken into consideration to accurately estimate soil moisture (<i>SM</i>) across spatial scales. In this study, the Single Channel Algorithm (SCA) is first applied to SMOS brightness temperatures at vertical polarization (<i>TB_V</i>) to estimate <i>SM</i> at coarse-resolution (25 km) and develop a land cover-specific and incidence angle (32.5&#x00B0;, 42.5&#x00B0; and 52.5&#x00B0;)-adaptive calibration of single scattering albedo (&#x03C9;) and soil roughness (<i>h_s</i>) parameters. These effective parameters are used together with fine-scale multi-angular Sentinel-1 backscatter in a single-pass active-passive downscaling approach to estimate <i>TB_V</i> at fine-scale (1 km) for each SMOS incidence angle. These <i>TB_V</i> are finally inverted to obtain the corresponding high-resolution <i>SM</i> maps. Results over the Iberian Peninsula for year 2018 show an increasing trend of &#x03C9; and a decreasing trend of <i>h_s</i> with SMOS incidence angle, with almost no variability of &#x03C9; across land cover types. The active-passive covariation parameter is shown to increase with SMOS incidence angle and decrease with Sentinel-1 incidence angle. Coarse and fine <i>TB_V</i> maps from the three SMOS incidence angles show similar distributions (mean differences below 0.38 K). Resulting high-resolution <i>SM</i> maps have maximum differences in mean and standard deviation of 0.016 and 0.015 m³/m³, respectively, and compare well with <i>in situ</i> measurements. Our results indicate that model-based microwave approaches to estimate <i>SM</i> can be adequately adapted to account for the incidence angle diversity of planned missions such as CIMR, ROSE-L and Sentinel-1 next generation.