InundationExtent_Hurricane_Florence_UAVSAR_V2.0.zip

The 2018 Hurricane Florence produced heavy rainfall and subsequent record-setting riverine flooding in North Carolina, USA. NASA/JPL collected daily high-resolution (about 5 meters) full-polarized L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data between September 18th and 23rd. Here, we use UAVSAR data to construct a flood inundation detection framework through a combination of polarimetric decomposition method and a Random Forest classifier. Validation of the established model 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. This data set contains inundation extent information of four UAVSAR flight lines (i.e., 13510, 31509, 32023 and 35303) with at least four days’ observations from Sep 18 to Sep 23, corresponding to the area covering the Neuse, Cape Fear, and Lumbee Rivers as well as their tributaries in Eastern North Carolina