Quality Control of CyGNSS Reflectivity for Robust Spatiotemporal Detection of Tropical Wetlands
2022
Hironori Arai | Mehrez Zribi | Kei Oyoshi | Karin Dassas | Mireille Huc | Shinichi Sobue | Thuy Le Toan
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 &ldquo:precision index&rdquo:. 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&ndash:December 2021) were used to evaluate the spatiotemporal dynamics of the reflectivity &Gamma: over the delta. First, the reflectivity &Gamma:, shape and size of each specular footprint and the precision index were calibrated at each specular point and reprojected to a 0.0045°: 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 (+/&minus: 14 days temporal localization with Gaussian kernel: 1&sigma: = 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.
Mostrar más [+] Menos [-]Palabras clave de AGROVOC
Información bibliográfica
Este registro bibliográfico ha sido proporcionado por Multidisciplinary Digital Publishing Institute