Abstract
Space-based synthetic aperture radar (SAR) is a powerful tool for monitoring flood conditions over large areas without the influence of clouds and daylight. Permanent water surfaces can be excluded by comparing SAR images with pre-flood images, but fluctuating water surfaces, such as those found in flat wetlands, introduce uncertainty into flood mapping results. In order to reduce this uncertainty, a simple method called Normalized Backscatter Amplitude Difference Index (NoBADI) is proposed in this study. The NoBADI is calculated from a post-flood SAR image of backscatter amplitude and multiple images on non-flooding conditions. Preliminary analysis conducted in the US state of Florida, which was affected by Hurricane Irma in September 2017, shows that surfaces frequently covered by water (more than 20% of available data) have been successfully excluded by means of C-/L-band SAR (HH, HV, VV, and VH polarizations). Although a simple comparison of pre-flood and post-flood images is greatly affected by the spatial distribution of the water surface in the pre-flood image, the NoBADI method reduces the uncertainty of the reference water surface. This advantage will contribute in making quicker decisions during crisis management.
Original language | English |
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Article number | 4136 |
Journal | Remote Sensing |
Volume | 13 |
Issue number | 20 |
DOIs | |
Publication status | Published - 2021 Oct 1 |
Keywords
- ALOS-2
- Flood
- Florida
- Hurricane Irma
- NoBADI
- PALSAR-2
- SAR
- Sentinel-1
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)