Global navigation satellite systems-reflectometry (GNSS-R) is an emerging remote sensing technique that makes use of navigation signals as signals of opportunity in a multistatic radar configuration, with as many transmitters as navigation satellites are in view. GNSS-R sensitivity to soil moisture has already been proven from ground-based and airborne experiments, but studies using space-borne data are still preliminary due to the limited amount of data, collocation, footprint heterogeneity, etc. This study presents a sensitivity study of TechDemoSat-1 GNSS-R data to soil moisture over different types of surfaces (i.e., vegetation covers) and for a wide range of soil moisture and normalized difference vegetation index (NDVI) values. Despite the scattering in the data, which can be largely attributed to the delay-Doppler maps peak variance, the temporal and spatial (footprint size) collocation mismatch with the SMOS soil moisture, and MODIS NDVI vegetation data, and land use data, experimental results for low NDVI values show a large sensitivity to soil moisture and a relatively good Pearson correlation coefficient. As the vegetation cover increases (NDVI increases) the reflectivity, the sensitivity to soil moisture and the Pearson correlation coefficient decreases, but it is still significant.

After the successful launching of the Soil Moisture and Ocean Salinity satellite in November 2009, continuous streams of data started to be regularly downloaded and made available to be processed. The first six months of operation were fully dedicated to the In-Orbit Commissioning Phase, with an intense activity aimed at bringing the satellite and instrument into a fully operational condition. Concerning the payload Microwave Imaging Radiometer with Aperture Synthesis, it was fully characterized using specific orbits dedicated to check all instrument modes. The procedures, already defined during the on-ground characterization, were repeated so as to obtain realistic temperature characterization and updated internal calibration parameters. External calibration maneuvers were tested for the first time and provided absolute instrument calibration, as well as corrections to internal calibration data. Overall, performance parameters, such as stability, radiometric sensitivity and radiometric accuracy were evaluated. The main results of this activity are presented in this paper, showing that the instrument delivers stable and well-calibrated data thanks to the combination of external and internal calibration and to an accurate thermal characterization. Finally, the quality of the visibility calibration is demonstrated by producing brightness temperature images in the alias-free field of view using standard inversion techniques. Images of ocean, ice, and land are given as examples.

During the last decade, a variety of agricultural drought indices have been developed using soil moisture (SM), or any of its surrogates, as the primary drought indicator. In this study, a comprehensive study of four innovative SM-based indices, the Soil Water Deficit Index (SWDI), the Soil Moisture Agricultural Drought Index (SMADI), the Soil Moisture Deficit Index (SMDI) and the Soil Wetness Deficit Index (SWetDI), is conducted over a large semi-arid crop region in northwest Spain. The indices were computed on a weekly basis from June 2010 to December 2016 using 1-km satellite SM estimations from Soil Moisture and Ocean Salinity (SMOS) and/or Moderate Resolution Imaging Spectroradiometer (MODIS) data. The temporal dynamics of the indices were compared to two well-known agricultural drought indices, the atmospheric water deficit (AWD) and the crop moisture index (CMI), to analyze the levels of similarity, correlation, seasonality and number of weeks with drought. In addition, the spatial distribution and intensities of the indices were assessed under dry and wet SM conditions at the beginning of the growing season. The results showed that the SWDI and SMADI were the appropriate indices for developing an efficient drought monitoring system, with higher significant correlation coefficients (R ≈ 0.5–0.8) when comparing with the AWD and CMI, whereas lower values (R ≤ 0.3) were obtained for the SMDI and SWetDI.

Soil moisture (SM) is an important component of the Earth’s surface water balance and by extension the energy balance, regulating the land surface temperature (LST) and evapotranspiration (ET). Nowadays, there are two missions dedicated to monitoring the Earth’s surface SM using L-band radiometers: ESA’s Soil Moisture and Ocean Salinity (SMOS) and NASA’s Soil Moisture Active Passive (SMAP). LST is remotely sensed using thermal infrared (TIR) sensors on-board satellites, such as NASA’s Terra/Aqua MODIS or ESA & EUMETSAT’s MSG SEVIRI. This study provides an assessment of SM and LST dynamics at daily and seasonal scales, using 4 years (2011–2014) of in situ and satellite observations over the central part of the river Duero basin in Spain. Specifically, the agreement of instantaneous SM with a variety of LST-derived parameters is analyzed to better understand the fundamental link of the SM–LST relationship through ET and thermal inertia. Ground-based SM and LST measurements from the REMEDHUS network are compared to SMOS SM and MODIS LST spaceborne observations. ET is obtained from the HidroMORE regional hydrological model. At the daily scale, a strong anticorrelation is observed between in situ SM and maximum LST (R $\approx -$ 0.6 to −0.8), and between SMOS SM and MODIS LST Terra/Aqua day (R $\approx -$ 0.7). At the seasonal scale, results show a stronger anticorrelation in autumn, spring and summer (in situ R $\approx -$ 0.5 to −0.7; satellite R $\approx -$ 0.4 to −0.7) indicating SM–LST coupling, than in winter (in situ R ≈ +0.3; satellite R $\approx -$ 0.3) indicating SM–LST decoupling. These different behaviors evidence changes from water-limited to energy-limited moisture flux across seasons, which are confirmed by the observed ET evolution. In water-limited periods, SM is extracted from the soil through ET until critical SM is reached. A method to estimate the soil critical SM is proposed. For REMEDHUS, the critical SM is estimated to be ∼0.12 m ${}^3$ /m ${}^3$ , stable over the study period and consistent between in situ and satellite observations. A better understanding of the SM–LST link could not only help improving the representation of LST in current hydrological and climate prediction models, but also refining SM retrieval or microwave-optical disaggregation algorithms, related to ET and vegetation status.