{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T07:02:26Z","timestamp":1780988546943,"version":"3.54.1"},"reference-count":40,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,21]],"date-time":"2022-11-21T00:00:00Z","timestamp":1668988800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The aim of this study was to develop a robust methodology for evaluating the spatiotemporal dynamics of the inundation status in tropical wetlands with the currently available Global Navigation Satellite System-Reflectometry (GNSS-R) data by proposing a new quality control technique called the \u201cprecision index\u201d. The methodology was applied over the Mekong Delta, one of the most important rice-production systems comprising aquaculture areas and natural wetlands (e.g., mangrove forests, peatlands). Cyclone Global Navigation Satellite System (CyGNSS) constellation data (August 2018\u2013December 2021) were used to evaluate the spatiotemporal dynamics of the reflectivity \u0393 over the delta. First, the reflectivity \u0393, shape and size of each specular footprint and the precision index were calibrated at each specular point and reprojected to a 0.0045\u00b0 resolution (approximately equivalent to 500 m) grid at a daily temporal resolution (Lv. 2 product); then, the results were obtained considering bias-causing factors (e.g., the velocity\/effective scattering area\/incidence angle). The Lv. 2 product was temporally integrated every 15 days with a Kalman smoother (+\/\u2212 14 days temporal localization with Gaussian kernel: 1\u03c3 = 5 days). By applying the smoother, the regional-annual dynamics over the delta could be clearly visualized. The behaviors of the GNSS-R reflectivity and the Advanced Land Observing Satellite-2 Phased-Array type L-band Synthetic Aperture Radar-2 quadruple polarimetric scatter signals were compared and found to be nonlinearly correlated due to the influence of the incidence angle and the effective scattering area.<\/jats:p>","DOI":"10.3390\/rs14225903","type":"journal-article","created":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T03:13:41Z","timestamp":1669086821000},"page":"5903","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Quality Control of CyGNSS Reflectivity for Robust Spatiotemporal Detection of Tropical Wetlands"],"prefix":"10.3390","volume":"14","author":[{"given":"Hironori","family":"Arai","sequence":"first","affiliation":[{"name":"CESBIO (CNRS\/CNES\/UPS\/IRD), 18 av. Edouard Belin, bpi 2801, CEDEX 9, 31401 Toulouse, France"},{"name":"Japan Society for the Promotion of Science, Chiyoda, Tokyo 102-0083, Japan"},{"name":"International Rice Research Institute (IRRI), Km 2 Pham Van Dong str., Tu Liem District, Hanoi 100000, Vietnam"},{"name":"Graduate School of Information Science and Technology, Osaka University, Osaka 565-0871, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6141-8222","authenticated-orcid":false,"given":"Mehrez","family":"Zribi","sequence":"additional","affiliation":[{"name":"CESBIO (CNRS\/CNES\/UPS\/IRD), 18 av. Edouard Belin, bpi 2801, CEDEX 9, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kei","family":"Oyoshi","sequence":"additional","affiliation":[{"name":"Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba 305-8505, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karin","family":"Dassas","sequence":"additional","affiliation":[{"name":"CESBIO (CNRS\/CNES\/UPS\/IRD), 18 av. Edouard Belin, bpi 2801, CEDEX 9, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mireille","family":"Huc","sequence":"additional","affiliation":[{"name":"CESBIO (CNRS\/CNES\/UPS\/IRD), 18 av. Edouard Belin, bpi 2801, CEDEX 9, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shinichi","family":"Sobue","sequence":"additional","affiliation":[{"name":"Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba 305-8505, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thuy Le","family":"Toan","sequence":"additional","affiliation":[{"name":"CESBIO (CNRS\/CNES\/UPS\/IRD), 18 av. Edouard Belin, bpi 2801, CEDEX 9, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,21]]},"reference":[{"key":"ref_1","unstructured":"Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., P\u00e9an, C., Berger, S., Huang, M., Yelekci, O., Yu, R., and Zhou, B. (2021). Climate change 2021: The physical science basis. 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