An assessment of the National Aeronautics and Space Administration NASA’s Cyclone Global Navigation Satellite System (CyGNSS) mission for biomass studies is presented in this work on rain, coniferous, dry, and moist tropical forests. The main objective is to investigate the capability of Global Navigation Satellite Systems Reflectometry (GNSS-R) for biomass retrieval over dense forest canopies from a space-borne platform. The potential advantage of CyGNSS, as compared to monostatic Synthetic Aperture Radar (SAR) missions, relies on the increasing signal attenuation by the vegetation cover, which gradually reduces the coherent scattering component ${\mathsf{\sigma }}^{\mathrm{coh},0}$ . This term can only be collected in a bistatic radar geometry. This point motivates the study of the relationship between several observables derived from Delay Doppler Maps (DDMs) with Above-Ground Biomass (AGB). This assessment is performed at different elevation angles ${\mathsf{\theta }}_{\mathrm{e}}$ as a function of Canopy Height (CH). The selected biomass products are obtained from data collected by the Geoscience Laser Altimeter System (GLAS) instrument on-board the Ice, Cloud, and land Elevation Satellite (ICESat-1). An analysis based on the first derivative of the experimentally derived polynomial fitting functions shows that the sensitivity requirements of the Trailing Edge $\mathrm{TE}$ and the reflectivity $\Gamma$ reduce with increasing biomass up to ~ 350 and ~ 250 ton/ha over the Congo and Amazon rainforests, respectively. The empirical relationship between $\mathrm{TE}$ and $\Gamma$ with AGB is further evaluated at optimum angular ranges using Soil Moisture Active Passive (SMAP)-derived Vegetation Optical Depth ( $\mathrm{VOD}$ ), and the Polarization Index ( $\mathrm{PI}$ ). Additionally, the potential influence of Soil Moisture Content (SMC) is investigated over forests with low AGB.

This work describes the first global scale assessment of a Global Navigation Satellite Systems Reflectometry (GNSS-R) experiment performed on-board the Soil Moisture Active Passive (SMAP) mission for soil moisture and biomass determination. Scattered GPS L2 signals (1227.6 MHz) were collected by the SMAP’s dual-polarization (Horizontal H and Vertical V) radar receiver and then processed on-ground using a known replica of the GPS L2C code. The scattering properties over land are evaluated using the Signal-to-Noise Ratio (SNR), the Polarimetric Ratio (PR), and the width of the waveforms’ trailing and leading edges. These parameters show sensitivity to the effects of the Earth’s topography and Above Ground Biomass (ABG) even over Amazonian and Boreal forests. These effects are shown to be an important factor in precise soil moisture and biomass determination. Additionally, it is found that PR shows sensitivity to soil moisture content over different land cover types. In particular, the following values of the PR are found over: (a) tropical forests ~−1.2 dB; (b) boreal forests ~0.8 dB; (c) Greenland ~2.8 dB; and (d) the Sahara Desert ~3.2 dB.

This paper presents an assessment of the correlation between CyGNSS-derived global navigation satellite systems reflectometry (GNSS-R) bistatic reflectivity, ${\Gamma _{rl}}$ , and soil moisture active passive (SMAP) derived brightness temperature, $T{}_I/2$ , over land surfaces. This parametric study is performed as a function of soil moisture content (SMC), vegetation opacity $\tau $ , and albedo $\omega $ . Several target areas, classified according to the International Geosphere-Biosphere Program (IGBP) land cover types, are selected to evaluate potential differentiated geophysical effects on “active” (as many transmitters as navigation satellites are in view) and passive approaches. Although microwave radiometry has potentially a better sensitivity to SMC, the spatial resolution achievable from a spaceborne platform is poor, ∼40 km. On the other hand, GNSS-R bistatic coherent radar pixel-size is limited by half of the first Fresnel zone, which provides about ∼150 m of spatial resolution (depending on the geometry). The main objective of this “active”/passive combination is twofold: a) downscaling the SMC, b) complement the information of microwave radiometry with GNSS-R data to improve the accuracy in SMC determination. The Pearson linear correlation coefficient of ${\Gamma _{rl}}$ and $T{}_I/2$ obtained over Thailand, Argentinian Pampas, and Amazon is ∼−0.87, ∼−0.7, and ∼−0.26, respectively, while the so-called tau–omega model is used to fit the data. Results over croplands are quite promising and deserve special attention since the use of GNSS-R could benefit agricultural and hydrological applications because of: a) the high spatio-temporal sampling properties, b) the high spatial resolution, and c) the potential combination with microwave radiometry to improve the accuracy of the measurements.

Global navigation satellite system reflectometry is a multistatic radar using navigation signals as signals of opportunity. It provides wide-swath and improved spatiotemporal sampling over current space-borne missions. The lack of experimental datasets from space covering signals from multiple constellations (GPS, GLONASS, Galileo, and Beidou) at dual-band (L1 and L2) and dual-polarization (right- and left-hand circular polarization), over the ocean, land, and cryosphere remains a bottleneck to further develop these techniques. ³ Cat-2 is a 6-unit (3 × 2 elementary blocks of 10 × 10 × 10 cm ³ ) CubeSat mission designed and implemented at the Universitat Politècnica de Catalunya-BarcelonaTech to explore fundamental issues toward an improvement in the understanding of the bistatic scattering properties of different targets. Since geolocalization of the specific reflection points is determined by the geometry only, a moderate pointing accuracy is only required to correct the antenna pattern in scatterometry measurements. This paper describes the mission analysis and the current status of the assembly, integration, and verification activities of both the engineering model and the flight model performed at Universitat Politècnica de Catalunya NanoSatLab premises. 3Cat-2 launch is foreseen for the second quarter of 2016 into a Sun-Synchronous orbit of 510-km height.

The empirical results of a global navigation satellite systems reflectometry (GNSS-R) experiment onboard the Balloon EXperiments for University Students (BEXUS) 17 stratospheric balloon performed north of Sweden over boreal forests show that the power of the reflected signals is nearly independent of the platform height for a high coherent integration time T _c = 20 ms. This experimental evidence shows a strong coherent component in the forward scattered signal, as compared with the incoherent component, that allows to be tracked. The bistatic coherent reflectivity is also evaluated as a function of the elevation angle, showing a decrease of ~6 dB when the elevation angle increases from 35° to 70°. The received power presents a clearly multimodal behavior, which also suggests that the coherent scattering component may be taking place in different forest elements, i.e., soil, canopy, and through multiple reflections canopy-soil and soil-trunk. This experiment has provided the first GNSS-R data set over boreal forests. The evaluation of these results can be useful for the feasibility study of this technique to perform biomass monitoring that is a key factor to analyze the carbon cycle.

Freeze/Thaw (F/T) surface state retrieval is important to further understand hydrological patterns and climate change. This article investigates the use of Earth-reflected Global Positioning System (GPS) L-band signals as collected by the National Aeronautics and Space Administration NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission for F/T surface state retrieval over a target area in South America, covering the Andes Mountains and the Argentinian Pampas. In the study, CYGNSS responsiveness to changes in surface permittivity is leveraged to detect transitions of F/T surface state, at an improved spatio-temporal sampling as compared to traditional Remote Sensing missions. A Seasonal-Threshold Algorithm (STA) is developed and validated using surface temperature data as provided by the European Centre for Medium-Range Weather Forecast (ECMWF) ERA5-Land numerical reanalysis model. Then, the monthly evolution of CYGNSS-derived F/T surface state maps is evaluated and an inter-comparison with the Soil Moisture Active Passive (SMAP) F/T data product is performed.