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

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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 (SM) across spatial scales. In this study, the single channel algorithm (SCA) is first applied to Soil Moisture and Ocean Salinity (SMOS) brightness temperatures at vertical polarization ( ${\mathrm{ TB}}_{V}$ ) to estimate SM at coarse resolution (25 km) and develop a land cover-specific and incidence angle (32.5°, 42.5°, and 52.5°)-adaptive calibration of single scattering albedo ( $\omega$ ) and soil roughness ( $h_{s}$ ) parameters. These effective parameters are used together with fine-scale multiangular Sentinel-1 backscatter in a single-pass active–passive downscaling approach to estimate ${\mathrm{ TB}}_{V}$ at fine scale (1 km) for each SMOS incidence angle. These ${\mathrm{ TB}}_{V}\mathrm {s}$ are finally inverted to obtain the corresponding high-resolution SM maps. Results over the Iberian Peninsula for year 2018 show an increasing trend of $\omega $ and a decreasing trend of $h_{s}$ with SMOS incidence angle, with almost no variability of $\omega $ 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 ${\mathrm{ TB}}_{V}$ maps from the three SMOS incidence angles show similar distributions (mean differences below 0.38 K). Resulting high-resolution SM maps have maximum differences in mean and standard deviation of 0.016 and 0.015 m 3 /m 3 , respectively, and compare well with in situ measurements. Our results indicate that model-based microwave approaches to estimate SM can be adequately adapted to account for the incidence angle diversity of planned missions, such as Copernicus Microwave Imaging Radiometer (CIMR), Radar Observing System for Europe in L-band (ROSE-L), and Sentinel-1 next generation.
Funding Information
  • Ministerio de Ciencia e Innovaci?n (PID2020-114623RB-C32, MCIN/ AEI /10.13039/50110001)

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