# Recent Progress on Vegetation Remote Sensing Using Spaceborne GNSS-Reflectometry
## 5 Conclusions  
GNSS-R technology is an emerging method of Earth observation that uses the reflected signals of navigation satellites for remotely sensing terrestrial objects. Compared with the ocean applications, the research in the field of terrestrial remote sensing using GNSS-R is relatively lagging. The research on vegetation parameters using spaceborne GNSS-R technology is still in the exploratory research stage. Existing research is mostly based on a qualitative analysis and the analysis is dependent on the spaceborne observation data. In this paper, we reviewed the current research status, and then the microwave scattering model was employed to analyze the effects of coherent and incoherent scattering, polarization, different vegetation parameters, and observation geometry on the final scattering characteristics. It points out the potential research direction of this technology and the technical bottleneck that urgently needs to be broken through. How to use the scattering characteristics under different observation geometries and polarizations to determine the optimal observation combination (observation geometry and polarization) and develop the quantitative retrieval methods will be the key research directions for future development. The specific prospects that can improve the vegetation retrieval using GNSS-R should be paid attention to and can be summarized into two items.  
The first one is how to fully dig the observation geometry information in DDM. As we know, several works have pointed out that the noncoherent scattering properties should not be ignored and the information outside the specular direction can be employed to get more information on the vegetation parameters. However, the main difficulty for this is that the angle information is all integrated and the information from different angles is coupled in a DDM waveform. Then, how to use the DDM information from different scattering azimuth angles and zenith angles can be studied in the near future.  
The second item is that the polarization information of vegetation should be paid extra attention, since most of the present works lack the mining of polarization information. However, the vegetation will show specific different properties at various polarizations. Therefore, in the future, how to fully use the polarization information to get the vegetation properties should be one key direction that needs to be solved.  
X.W.: idea proposal, conceptualization, and original draft; P.G., X.Z., H.L. and W.B.: conceptualization suggestions and review; Y.S.: suggestions and funding. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (No. 42061057, No.42074042, 41971377,and 72004017) and the innovative Teams of Studying Environmental Evolution and Disaster Emergency Management of Chiefing University (cfxykycxtd202006) and Chiefing University, Laboratory of National Land Space Planning and Disaster Emergency Management of Inner Mongolia (CFXYZD202006).  
**Institutional Review Board Statement:** Not Applicable.  
**Informed Consent Statement:** Not Applicable.  
**Data Availability Statement:** The data used in this paper are already given in the corresponding reference.  
**Acknowledgments:** We are very grateful for the anonymous reviewers' comments, which have greatly improved the quality and content of the manuscript. We also thank [PERSON] in Nanjing University of Information Science and Technology for his wonderful work as for the abstract graphic figure.  
**Conflicts of Interest:** The authors declare no conflict of interest.