# The CYGNSS Mission: On-Going Science Team Investigations
## 2 Methodology, Results, and Discussions
### Land Surfaces  
The use of GNSS-R for land-surface applications requires additional considerations because the dielectric properties of this scattering medium have significantly more variability than that of the ocean surface. Here, we provide some of the latest findings of the CYGNSS mission, including key-results, discussions, and on-going research activities. At present, a significant number of researchers within the CYGNSS Science Team are working on land surface applications, which remain less explored than ocean products. Session 3: Land Processes I  
The first Land Processes Session consists of a series of presentations and discussions focusing on the use of CYGNSS data and observations related to (a) surface SMC estimation, (b) creation of dynamic inland water body masks, and (c) advancements in forward GNSS-R-related electromagnetic scattering and forward models. GNSS-R-like observations have been shown to be sensitive to changes in surface SMC [27; 28; 29; 30; 31] as well as the presence (or absence) of inland water bodies [32; 33]. More recently, a 3 km CYGNSS Signal-to-Noise SNR-based surface SMC estimation approach was developed in [30], with results comparable to those by the NASA SMAP mission [34] and unbiased Root-Mean-Squared (ubRMSE) on the order of 0.045 m\({}^{3}\)/m\({}^{3}\). Given this background, the following briefly summarizes the key finding from each of the session's presentations. Forward scattering properties of Earth-reflected GNSS signals were evaluated over land surfaces. The CYGNSS End-to-End Simulator (E2 ES) was updated. A GNSS-R model capable of evaluating both the incoherent and the coherent scattering terms was developed based on the Huygens-Kirchhoff principle [35]. Results demonstrated the impact of higher order Fresnel zones on the spatial resolution of GNSS-R over heterogeneous areas, showing \"ringing\" fluctuations in the reflected power near high-contrast boundaries. An inland water body detection method was also presented during this session. The method [36] demonstrates the utility of ~2 years CYGNSS Level-1 Delay-Doppler Maps (DDM) to create [1; 3] km water masks (Figure 6). Inland water surfaces at L-band are presumed smooth enough such that specular scattering is the dominant features in the observed DDM. Therefore, by deploying a DMM coherence persistence and detection method [30], mapping inlands becomes possible. The derived inland water body masks were qualitatively and quantitively compared to, and validated against, historical (30 years) water body occurrence maps by [PERSON] et al. [37]. False-positive areas were identified and removed via comparison to the Pekel occurrence maps, and examination of high-quality Digital Elevation Maps (DEM). Areas with persistent coherence, unknown water bodies, and exceptionally flat surfaces were also removed. The current analysis was based on ~2 years of CYGNSS observations. Additional investigation to identify false-positive and improve the overall detection method is required. [PERSON] et al. [38] outlined an entropy-based CYGNSS coherence detector--via eigenvalue decomposition of the DDMs--which, overall showed good agreement with wetland maps derived from Advanced Land Observing Satellite-2 (ALOS-2). However, the current method does not discriminate between open water and flooded vegetation and merits further investigation. Additionally, [PERSON] et al. outlined a newly initiated research project with the ultimate goal of fusing CYGNSS-derived wetland with future wetland products from the NASA-ISRO Synthetic Aperture Radar (NISAR) mission. The primary motivation of this work was to develop the GNSS-R/SAR framework for future CYGNSS/NASA-ISRO (NISAR) activities. [PERSON] et al. [39; 40] presented a series of Artificial Neural Network (ANN) implementations to use CYGNSS SNR observations to estimate various geophysical properties.