Flood Extent Mapping During Hurricane Florence With Repeat‐Pass L‐Band UAVSAR Images

Abstract

Extreme precipitation events are intensifying due to a warming climate, which, in some cases, is leading to increases in flooding. Detection of flood extent is essential for flood disaster response, management, and prevention. 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. In 2018, Hurricane Florence produced heavy rainfall and subsequent record‐setting riverine flooding in North Carolina, USA. NASA/JPL collected daily high‐resolution 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 methods and a Random Forest classifier. 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. We show that floods receded faster near the upper reaches of the Neuse, Cape Fear, and Lumbee Rivers. 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. 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.

Flood Detection with SAR: A Review of Techniques and Datasets

“…For these reasons, only few papers utilizing these platforms have been produced. The interested reader can refer to [148,206,207] for airborne SAR applications and to [208,209] for UAV SAR ones. The joint exploitation of UAV SAR data and spaceborne ones has been discussed in [210,211].…”

Ten simple rules for working with high resolution remote sensing data

“…Hydrologic processes can occur very fast at a small scale. Mapping flood extents often require high-spatial and high-temporal resolutions (sub-daily) as well as advanced sensors, such as Synthetic Aperture Radar (SAR) (C. Wang et al 2021).…”

Inundated Vegetation Mapping Using SAR Data: A Comparison of Polarization Configurations of UAVSAR L-Band and Sentinel C-Band

“…As climate change continues to rise, many urban and rural areas will be prone to frequent floods, especially in low-elevated coastal areas [4]. Rapid flood extent mapping helps flood relief programs and emergency management agencies to direct their resources to the most affected areas [5][6][7][8].…”

“…These SAR systems monitor the earth's surface using various wavelengths, including X, C, and L-bands. A longer wavelength is more suitable for detecting inundated vegetation because longer wavelengths can penetrate vegetation canopy better than shorter wavelengths [5]. High temporal and spatial resolution SAR images are being used by many organizations around the world to produce nearreal-time floodwater extent maps.…”

“…Analyzing the contemporaneous data of various SAR systems acquired for the same area and comparing their results to ground reference data allows the identification of the suitable SAR system, in terms of cost and accuracy, for the particular environmental condition. Airborne SAR imagery, such as UAVSAR, can provide high spatial and temporal resolution data to monitor flooded areas in detail [5].…”