By now, humans have explored and measured the planet in a thousand different ways airplanes fly between all points of the map and the distances are well known. In addition to revealing flood inundation changes spatially, flood maps such as those produced here have great potential for assessing flood damages, supporting disaster relief, and assisting hydrodynamic modeling to achieve flood-resilience goals.It is the flat-earthers the ones who would have to refute the roundness of the Earth, because the current evidence shows that the planet is round. Meanwhile, along the flat terrain close to the lower reaches of the Cape Fear River, the flood wave traveled downstream during the observation period, resulting in the flood extent expanding 16.1% during the observation period. We show that floods receded faster near the upper reaches of the Neuse, Cape Fear, and Lumbee Rivers. Validation of the established models with compiled ground references shows that the incorporation of linear polarizations with polarimetric decomposition and terrain variables significantly enhances the accuracy of inundation classification, and the Kappa statistic increases to 91.4% from 64.3% with linear polarizations alone. Here, we use UAVSAR data to construct a flood inundation detection framework through a combination of polarimetric decomposition methods and a Random Forest classifier. NASA/JPL collected daily high-resolution full-polarized L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data between September 18th and 23rd. The 2018 Hurricane Florence produced heavy rainfall and subsequent record-setting riverine flooding in North Carolina, USA. However, it is challenging to delineate inundated areas through most publicly available optical and short-wavelength radar data, as neither can “see” through dense forest canopies. Detection of flood extent is essential for flood disaster management and prevention. Earth and Space Science Open Archive.ĪbstractExtreme precipitation events are intensifying due to a warming climate, which, in some cases, is leading to increases in flooding. Flood Extent Mapping during Hurricane Florence with Repeat-Pass L-Band UAVSAR Images. Sebastian, Antonia Frizzelle, Brian Frankenberg, Elizabeth & Clinton, Nicholas (Preprint). CitationWang, Chao Pavelsky, Tamlin M Yao, Fangfang Yang, Xiao Zhang, Shuai Chapman, Bruce Song, Conghe H.
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