Flood Extent Mapping in the Caprivi Floodplain Using Sentinel-1 Time Series

Deployment of Sentinel-1 (S1) satellite constellation carrying a C-band synthetic aperture radar (SAR) enables regular and timely monitoring floods from their onset until returning to nonflooded (NF) conditions. The major constraint on using SAR for near-real-time (NRT) flood mapping has been the inability rapidly process obtained imagery into reliable maps. This study evaluates efficacy S1 time series quantifying characterizing inundation extents in vegetated environments. A novel algorithm based statistical time-series modeling flooded (F) NF pixels is proposed NRT monitoring. For each new available image, probability temporarily F conditions tested against that by means likelihood ratio tests. likelihoods two are derived early acquisitions series. calibration consists adjusting thresholds match reference area extent during single season. applied Caprivi region, resulting maps were compared cloud-free Landsat-8 (LS8) captured events. good spatial agreement (85-87%) between LS8 was observed peak both 2017 2018 seasons. Significant discrepancies noted expansion recession phases, mainly due different sensitivities data sources emerging vegetation. Overall, analysis shows can stand as an effective standalone or gap-filling alternative optical event.