Use of a discrete electromagnetic model for simulating Aquarius L-band active/passive observations and soil moisture retrieval

Qiang Wang (Corresponding Author), R. van der Velde, Zhongbo Su

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In this paper, the discrete electromagnetic model developed at the Tor Vergata University of Rome (hereafter, TV-DEM) is used to simulate both active and passive L-band signals using a single set of input parameters. The simulations are compared to Aquarius observations collected from a view angle of 28.7° over the Maqu study area located near the north-eastern edge of the Tibetan Plateau. The TV-DEM parameters litter biomass, litter moisture factor, plant moisture and standard deviation of height variations are calibrated for Aquarius observations collected during the 2012 and 2013 warm seasons. The calibrated parameters are used to reproduce the brightness temperature (T b) and backscattering coefficient (σ o) for the 2014 and 2015 warm season as an independent assessment. The results show that the calibrated TV-DEM simulations capture Aquarius observations reasonably well with coefficients of determination (R 2's) varying from 0.75 to 0.86 for the T b's and from 0.36 to 0.68 (−) for the σ o's depending on the polarization and adopted matchup set (e.g. calibration or validation). The simulations, however, systematically overestimate the H polarized Aquarius observation and underestimate the V polarized observations. The calibrated TV-DEM is also utilized for soil moisture retrieval from three combinations of Aquarius data, including a set of both active and passive microwave observations. The obtained error metrics indicate that the soil moisture estimates from the active/passive data have the smallest bias (− 0.008 m 3 m − 3) and the lowest unbiased root mean squared difference (0.021 m 3 m − 3), while soil moisture retrieved using a calibrated τ (optical depth)-ω (single scattering albedo) model based algorithm provided the best R 2. These results warrant further investigation of the synergistic use of active/passive data for soil moisture retrieval as well as the use of complex physically radiative transfer model as part of well-established algorithms.

Original languageEnglish
Pages (from-to)434-452
Number of pages19
JournalRemote sensing of environment
Early online date28 Nov 2017
Publication statusPublished - 1 Feb 2018


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