Nowadays, the space missions employing the GNSS-Reflectometry (GNSS-R) are UK TDS-1, NASA CYGNSS, and the Chinese BuFeng-1A/B twin satellites, part of the first Chinese global navigation satellite system reflectometry (GNSS-R) satellite mission. They provide Delay-Doppler Map (DDM) measurements reflected from the land as well as the ocean. Using land reflected DDMs, several studies have been conducted to retrieve land geophysical parameters, such as soil moisture and biomass. Despite the clear dependence on these parameters, many other parameters impact the DDMs as well, such as topography, surface roughness, etc. The impact of these perturbing factors must be analyzed, and modeled in various conditions. This work presents a comprehensive end-to-end simulator that can generate synthetic DDMs reflected over land. It is an extension of a previously developed simulator validated for ocean applications. This simulator is very generic, and it includes numerous configurable parameters such as arbitrary scattering geometry (transmitter and receiver positions and speeds), arbitrary GPS and Galileo transmitted signals and frequencies, GNSS-R instrument antenna and receiver errors, as well as surface topography, roughness, soil moisture, vegetation cover, etc. The sensitivities of GNSS-R observables with respect to soil moisture and vegetation are obtained and compared to previous experimental results, and synthetic DDMs are compared and validated against TDS-1 ones.

In this paper, an algorithm to retrieve surface soil moisture from GNSS-R (Global Navigaton Satellite System Reflectometry) observations is presented. Surface roughness and vegetation effects are found to be the most critical ones to be corrected. On one side, the NASA SMAP (Soil Moisture Active and Passive) correction for vegetation opacity (multiplied by two to account for the descending and ascending passes) seems too high. Surface roughness effects cannot be compensated using in situ measurements, as they are not representative. An ad hoc correction for surface roughness, including the dependence with the incidence angle, and the actual reflectivity value is needed. With this correction, reasonable surface soil moisture values are obtained up to approximately a 30° incidence angle, beyond which the GNSS-R retrieved surface soil moisture spreads significantly.

The 3Cat-3/MOTS (3: Cube, Cat: Catalunya, 3: 3rd CubeSat mission/Missió Observació Terra Satèl·lit) mission is a joint initiative between the Institut Cartogràfic i Geològic de Catalunya (ICGC) and the Universitat Politècnica de Catalunya-BarcelonaTech (UPC) to foster innovative Earth Observation (EO) techniques based on data fusion of Global Navigation Satellite Systems Reflectometry (GNSS-R) and optical payloads. It is based on a 6U CubeSat platform, roughly a 10 cm × 20 cm × 30 cm parallelepiped. Since 2012, there has been a fast growing trend to use small satellites, especially nanosatellites, and in particular those following the CubeSat form factor. Small satellites possess intrinsic advantages over larger platforms in terms of cost, flexibility, and scalability, and may also enable constellations, trains, federations, or fractionated satellites or payloads based on a large number of individual satellites at an affordable cost. This work summarizes the mission analysis of 3Cat-3/MOTS, including its payload results, power budget (PB), thermal budget (TB), and data budget (DB). This mission analysis is addressed to transform EO data into territorial climate variables (soil moisture and land cover change) at the best possible achievable spatio-temporal resolution.