Automated Rain Detection by Dual-Polarization Sentinel-1 Data

Rain Signatures on C-band Synthetic Aperture Radar (SAR) images acquired over ocean are common and can dominate the backscattered signal from the ocean surface. In many cases, the inability to decipher between ocean and rain signatures can disturb the analysis of SAR scenes for maritime applications. This study relies on Sentinel-1 SAR acquisitions in the Interferometric Wide swath mode and high-resolution measurements from ground-based weather radar to document the rain impact on the radar backscattered signal in both co- and cross-polarization channels. The dark and bright rain signatures are found in connection with the timeliness of the rain cells. In particular, the bright patches are demonstrated by the hydrometeors (graupels, hails) in the melting layer. In general, the radar backscatter under rain increases with rain rate for a given sea state and decreases when the sea state strengthens. The rain also has a stronger impact on the radar signal in both polarizations when the incidence angle increases. The complementary sensitivity of the SAR signal of rain in both channels is then used to derive a filter to locate the areas in SAR scenes where the signal is not dominated by rain. The filter optimized to match the rain observed by the ground-based weather radar is more efficient when both polarization channels are considered. Case studies are presented to discuss the advantages and limitations of such a filtering approach


SAR, rain signatures, rain rate, sea surface winds

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1913 Mo
How to cite
Zhao Yuan, Longépé Nicolas, Mouche Alexis, Husson Romain (2021). Automated Rain Detection by Dual-Polarization Sentinel-1 Data. Remote Sensing. 13 (16). 3155 (19p.).,

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