## 1 Introduction  
In many different scientific fields, the utmost significance of Soil Moisture Content (SMC) has been pointed out as an environmental factor for land surface dynamics monitoring [1; 2; 3; 4; 5; 6; 7; 8], such as evapotranspiration, droughts, floods, etc., while it simultaneously regulates energy and water exchange between the land and the atmosphere and other hydrological processes. SMC also enables the regulation of infiltration rate due to precipitation and thus controlling water runoff and surface erosion. Over a large scale, SMC is a key parameter for climate change studies [9]. In addition, SMC coupled with other environmental variables, such as land surface temperature, land cover, and precipitation, among others, are commonly used as input of climate models [10; 11; 12]. Moreover, in agriculture, SMC is a crucial indicator of plant growth and crop yield, as well as for drought prediction. Therefore, since all these variables are strongly linked to social and economic impacts on human activity [11], SMC is being employed for planning and managing irrigation strategies [4]. SMC can be estimated from a wide variety of methods and techniques. For instance, for local observations, direct procedures include, e.g., TDR (Time Domain Reflectometry) electric permittivity [2]. However, these local methods are only suitable for small areas (\(\sim\)km\({}^{2}\)) and the time needed for surveying is unacceptable for practical application on regional and meso-scales. Fortunately, in these last decades, near-Earth satellites have provided an unprecedented opportunity to sense SMC from space and with a wide diversity of techniques and sensors (e.g., [5; 13]). Although remote sensing observing activities began in the 1970s, technological development has evolved exponentially to get benefit from advances on electromagnetic (EE.MM.) radiation through different spectrum intervals [11]. Two main spectral domains for assessment of SMC can be devised, usually referred to optical and microwave spectrum, each of them with particular advantages and limitations [5; 14; 15]. In this study, we work in the microwave domain, where the wavelength varies from some few centimeters to meters, commonly employed in the ranges of \(\lambda\) = 2.5-3.75 cm (band X at 8.0-12 GHz), \(\lambda\) = 3.75-7.5 cm (band C at 4-8 GHz), and \(\lambda\) = 15-30 cm (band L at 1-2 GHz). In this domain, measurements can either be passive or active. With the passive instruments, soil dielectric properties and soil brightness temperatures can be retrieved for SMC assessment. With the active devices, only soil dielectric properties can be assessed by the means of measuring the scattering coefficient, usually denoted as the bistatic or back-scattering coefficient [16; 17]. Namely, a bistatic system holds when the transmitting and the receiving antennas are separately placed or included as independent instruments. In a mono-static system, the antenna alternates between transmitting and receiving signals, so only one instrument is required. Most of Earth observing systems belongs to the mono-static configuration. Unfortunately, SMC cannot be directly retrieved from active or passive microwave remote sensors, and different physical models based on geometrical and/or physical and optical properties have to be built [16; 17]. Active or passive signals have the advantage of moderately penetrating soil surfaces when they are not severely limited by atmospheric conditions. However, in both cases, the signals are strongly conditioned by geophysical and biophysical variables such as Bare Soil Roughness (BSR) and the different constituents of the vegetation canopy [18]. A complete description of active and passive systems for SMC estimation, including frequency bands and spatial resolutions, is given in [13].