In the past years, the scientific community has placed a special interest in remotely sensing soil moisture and vegetation parameters. Radiometry and radar techniques have been widely used for years. Global Navigation Satellite Systems opportunity signals Reflected (GNSS-R) over the earth's surface are younger, but they have already shown their potential to perform these observations. This paper presents a GNSS-R technique, based on Global Positioning System (GPS) measurements, that allows the retrieval of several geophysical parameters from land surfaces. This technique measures the power of the interference signal between the direct GPS signal and the reflected one after scattering over the land, so it is called Interference Pattern Technique (IPT). This paper presents the results obtained after applying the IPT for topography, soil moisture, and vegetation height retrievals over vegetation-covered soils.

Global Navigation Satellite Systems (GNSS) opportunity signals reflected at or near the Earth's surface have already shown their potential to perform retrievals of a number of geophysical parameters. Radio occultations using GNSS signals are also used for atmospheric sensing. This letter presents a GNSS technique to retrieve vegetation water content (VWC). This technique measures the received powers of the GPS signals in open sky and under the vegetation layer. From these two powers, the attenuation due to the vegetation is computed, which is related to the VWC. This letter presents the results obtained after deploying the instrument in a walnut-tree stand for 11 months.

UAV (unmanned Aerial Vehicle) platforms represent a challenging opportunity for the deployment of a number of remote sensors. These vehicles are a cost-effective option in front of manned aerial vehicles (planes and helicopters), are easy to deploy due to the short runways needed, and they allow users to meet the critical requirements of the spatial and temporal resolutions imposed by the instruments. L-band radiometers are an interesting option for obtaining soil moisture maps over local areas with relatively high spatial resolution for precision agriculture, coastal monitoring, estimation of the risk of fires, flood prevention, etc. This paper presents the design of a light-weight, airborne L-band radiometer for deployment in a small UAV, including the hardware and specific software developed for calibration, geo-referencing, and soil moisture retrieval. First results and soil moisture retrievals from different field experiments are presented.

The spaceborne synthetic aperture radar (SAR) technique based on a combination of P-band Signals of Opportunity (SoOp) reflectometry with a sparse array of receivers at low earth orbits (LEO) and transmit signals from the United States Navy's Mobile User Objective System (MUOS) operating on a geosynchronous altitude has been analyzed. The design focuses on the forward-looking geometry near the specular direction, which allows a high surface reflectivity, in order to obtain adequate signal to noise ratio (SNR) with a moderate receiving antenna gain. The sparse array is utilized to sharpen the across-track resolution and reduce the iso-range ambiguity. The formulation for match-filtering and illustrations of point target response are presented. This work shows that an array of 5 to 7 receivers is able to achieve an across-track resolution of about 200 m in the outer portion of swath and about 1 km in the center part of swath. The along-track resolution can reach 10 meters or better due to the feasibility of a long dwell time for Doppler filtering. We find that the sparse array allows the reduction of the iso-range ambiguity to a level of lower than 5% for a major portion of swath, ~70% or greater depending on the number of receivers and spacing. We have completed an SNR formulation, which can consistently account for both coherent and incoherent scattering regardless the spatial resolution. Our study suggests the promise of the SoOpSAR concept for high resolution remote sensing of land surfaces

Global Navigation Satellite System-Reflectometry (GNSS-R) is a promising field with a diverse set of applications. Polarimetric GNSS-R has been shown to be sensitive to different land parameters, such as freeze/thaw, crop growth, or soil moisture. In this article, the polarimetric scenario of a GNSS reflection is defined, and the theoretical basis and the algorithm to retrieve the Stokes parameters of a GNSS-R signal are proposed. The presented algorithms are validated using data collected by the two linear orthogonal polarization channels of the Soil Moisture Active Passive (SMAP) radar antenna working as GNSS-R, known as SMAP-Reflectometry (SMAP- $R$ ). The Stokes parameter retrieval is presented for the SMAP- $R$ case, and the receiver phase offset and intensity are calibrated. The same calibration procedure proposed by the CYclone GNSS (CYGNSS) mission is applied to the SMAP- $R$ first Stokes parameter, allowing the retrieval of the normalized bistatic radar cross Section (NBRCS) of such measurement. Finally, the SMAP- $R$ data are compared to the CYGNSS NBRCS over the ocean, showing an unbiased root-mean-square error of 3.3 dB and a small bias.