N. Sánchez

Soil moisture downscaling activities at the REMEDHUS Cal/Val site and its application to SMOS

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission will provide accurate global surface soil moisture estimates. However, due to technological limitations, the spatial resolution of SMOS observations is limited to 40-km. This resolution is adequate for many global applications, but restricts the use of the data in regional studies over land, where a resolution of 1–10 km is needed. Different downscaling experiments have been carried out at the REMEDHUS Cal/Val site within the GPS and RAdiometric Joint Observations one-year field experiment (GRAJO) to explore the possibility of enhancing the spatial resolution of SMOS-derived soil moisture estimates. This paper investigates the use of visible/infrared remote sensing data to improve the spatial resolution of passive microwave soil moisture estimates, and presents an approach to down-scale airborne observations acquired with the UPC Airborne RadIomEter at L-band (ARIEL) using LANDSAT imagery. Although a full validation of the method was not possible, preliminary results indicate that with this approach it is feasible to improve the spatial and radiometric resolution of the soil moisture estimates. The comparison with ground-based soil moisture demonstrates the strength of the link between visible/infrared satellite data and soil moisture status, and the potential of adapting this downscaling technique to SMOS-derived soil moisture estimates.

Comparison of SMOS, modelled and in situ long-term soil moisture series in the northwest of Spain

ABSTRACT This work aimed to evaluate the capability of modelled vs in situ soil moisture observations in the northwest of Spain for a period of four years (2010–2013) in order to validate the SMOS L2 product. Comparisons were performed for a set of representative stations of the Soil Moisture Measurement Stations network of the University of Salamanca (REMEDHUS) at both point and area scales. The SMOS series showed good correlation with the modelled series, better than that obtained with the in situ observations (0.77 vs 0.68 average correlation coefficients). However, some underestimation or overestimation of the SMOS series, related to the soil characteristics, was observed with respect to both the in situ and the modelled series. The SMOS data normalization produced a notable improvement in the results, highlighting the capability of the modelled data to validate the SMOS soil moisture series. This research provides a solid foundation for the future validation of SMOS at large scales, overcoming the spatial representativeness issues arising from the use of in situ point measurements. Editor M.C. Acreman; Associate editor N. Verhoest

A sensitivity study of land surface temperature to soil moisture using in-situ and spaceborne observations

Surface Soil Moisture (SSM) affects the soil surface energy balance and thus affects the Land Surface Temperature (LST), and viceversa. Currently, LST and SSM are remotely sensed using TIR sensors and L-band radiometers, respectively. The NASAs Terra/Aqua missions provide full coverage of LST measurements under clear sky conditions using MODIS. The ESAs SMOS mission is the first satellite providing frequent SSM and ocean salinity observations at global scale. In this paper, a sensitivity study about the relationship of the LST and SSM is performed using in-situ measurements from the REMEDHUS network and spaceborne observations from MODIS and SMOS. Results show that the correlation between SSM and LST (both in-situ and remotely sensed) is highest using the daily maximum LST. This could help improving SSM algorithms and deriving new SSM products at higher resolution from the synergy of microwave and TIR observations.

Learning to Detect Deception from Evasive Answers and Inconsistencies across Repeated Interviews: A Study with Lay Respondents and Police Officers

Previous research has shown that inconsistencies across repeated interviews do not indicate deception because liars deliberately tend to repeat the same story. However, when a strategic interview approach that makes it difficult for liars to use the repeat strategy is used, both consistency and evasive answers differ significantly between truth tellers and liars, and statistical software (binary logistic regression analyses) can reach high classification rates (Masip et al., 2016b). Yet, if the interview procedure is to be used in applied settings the decision process will be made by humans, not statistical software. To address this issue, in the current study, 475 college students (Experiment 1) and 142 police officers (Experiment 2) were instructed to code and use consistency, evasive answers, or a combination or both before judging the veracity of Masip et al.s (2016b) interview transcripts. Accuracy rates were high (60% to over 90%). Evasive answers yielded higher rates than consistency, and the combination of both these cues produced the highest accuracy rates in identifying both truthful and deceptive statements. Uninstructed participants performed fairly well (around 75% accuracy), apparently because they spontaneously used consistency and evasive answers. The pattern of results was the same among students, all officers, and veteran officers only, and shows that inconsistencies between interviews and evasive answers reveal deception when a strategic interview approach that hinders the repeat strategy is used.

An airborne GNSS-R field experiment over a vineyard for soil moisture estimation and monitoring

The Light Airborne Reflectometer for GNSS-R Observations (LARGO) is an airborne instrument designed for measuring the coherent reflectivity from different soils. In this work, an improved version of LARGO has been used in a field campaign together with other conventional remote sensing instruments. All the corrections made to the raw coherent reflectivity including the antenna pattern compensation, and a topographic correction are presented. The correlation between corrected coherent reflectivity and in situ soil moisture was not high enough due to the dry conditions of the field campaign.

Airborne GNSS-R, thermal and optical data relationships for soil moisture retrievals

New remote sensing techniques based on the analysis of the Earths surface-reflected signal from the Global Navigation Satellite Systems (GNSS-Reflectometry, or GNSS-R in short) are emerging. Soil moisture and vegetation status are some of the potential parameters that could be also retrieved from these sources. However, the complex interactions between the soil-vegetation interface can lead to spurious effects on the reflected signal. In order to study these effects, an airborne campaign was developed in an experimental area in Spain in August, 2014. A new GNSS-R-based instrument was flown together with thermal and optical cameras mounted on a paramotor. Ground measurements of soil moisture were taken during the flight. Maps at very high spatial resolution of reflectivity, Land Surface Temperature (LST) and the Digital Surface Model (DSM) were jointly analyzed, together with the ground observations. The results showed an important influence of the topography (i.e., the local incidence angle) on the GNSS-R reflectivity, and promising patterns relating reflectivity with soil moisture and LST were found. However, owing the dry soil and weather conditions during the experiment, further tests are needed over different environment and climatic conditions.

Preparatory activities at the remedhus SMOS cal/val site: Characterisation of bare soils and effect of surface roughness

Soil roughness is known to be one important factor affecting the observations of the microwave emission from land surfaces. Natural surfaces show a random roughness profile but many agricultural fields show a tilled row structure with a predominant row direction. To quantify the significance of tillage direction on the emission from soils a series of measurements were carried out with an L-band radiometer over three bare fields with different tillage. These activities are part of the GRAJO (GPS and RAdiometric Joint Observations) experiment which is being conducted at the REMEDHUS site in Zamora, Spain, in preparation for SMOS cal/val. Preliminary results show that tillage orientation affects the emission. The increase in emissivity due to roughness was found to be higher for transverse than for longitudinal orientation (approximately 0.1 in emissivity).