**5. Conclusions**

For the operational use of GNSS-R data for sustainable tropical wetland management, a simple quality control method was proposed in this study. Even without ad hoc parameter tuning, the proposed simple model comprising the "precision index" and DDM 3D statistics showed a fine performance in visualizing the spatiotemporal dynamics of wetlands at a fine spatiotemporal resolution (500 m spatial resolution, 15-day temporal resolution). Even without using a common change detection algorithm, the precision-index-model-based approach showed temporal dynamics similar to those obtained using a change detection algorithm. By considering the incidence angle difference, we also succeeded in improving the sensitivity and dynamic range of the change detection results. As a result, we now are able to detect two annual inundation peaks over the Mekong Delta, indicating that the multicropping rice system dominating this region plays a major role in controlling the inundation status of the delta. The DDM 3D statistics approach was applied to successfully denoise the locally abnormal specular points by adaptively detecting specular points collected over rough land surfaces. The comparison with L-band microwave SAR data based on the precision index showed a reasonable mutual correlation and provided knowledge of how the microwave scattering pattern is affected by the incidence angle over tropical wetlands. Further study is required with a shorter-integration-time coherence product or a polarimetric decomposition product (e.g., stokes vector) containing GNSS-R data with 1st-/2nd-order specular point velocity (e.g., acceleration) derivatives to enable more precise comparisons with L-band SAR data.

**Supplementary Materials:** The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/rs14225903/s1.

**Author Contributions:** H.A., M.Z., K.O., S.S. and T.L.T. conceived and designed the experiments; H.A., K.D. and M.H. performed the experiments; H.A., M.Z. and K.D. analyzed the data; H.A., M.Z. and M.H. preprocessed the base datasets; all authors supported the data interpretation and model design; H.A., M.Z. and T.L.T. wrote the paper; and all authors read the paper and provided revision suggestions. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** A portion of the field survey activities described in this work was supported by the Japan Society for the Promotion of Science (JSPS) Grants-in-aid for Scientific Research & Scholarship received from JSPS as research execution expenses and by JSPS KAKENHI Grant Numbers 15J00001 and 16J02509. The remote sensing study was financially supported by the Japan Aerospace Exploration Agency (JAXA) and by the JSPS KAKENHI Project (Area No. 16J02509) and JSPS Overseas Research Fellowships (No. 201960100). ALOS-2/PALSAR-2 data are provided under the "Agreement between ESA and JAXA on the cooperation for the use of synthetic aperture radar satellites in Earth science and applications".

**Conflicts of Interest:** The authors declare no conflict of interest.
