Automatic Flood Extent and Depth Estimation Using Alos-2 and Flood Simulation Data

The all-weather, day-and-night imaging capability of synthetic aperture radar (SAR) has become essential for flood disaster monitoring. This study developed a SAR-based flood monitoring method that automatically estimates flood extent, floodwater depth, and their changes. The flood extent was estima...

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Bibliographic Details
Main Authors: Ohki, Masato, Yamamoto, Kosuke, Tadono, Takeo
Format: Conference Proceeding
Language:English
Subjects:
Data models
disaster monitoring
Estimation
Geoscience and remote sensing
hydrodynamic simulation
Hydrodynamics
Imaging
inundation
PALSAR-2
Probabilistic logic
Radar imaging
synthetic aperture radar
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Summary:The all-weather, day-and-night imaging capability of synthetic aperture radar (SAR) has become essential for flood disaster monitoring. This study developed a SAR-based flood monitoring method that automatically estimates flood extent, floodwater depth, and their changes. The flood extent was estimated from a Bayesian probabilistic model using ALOS-2 SAR data (amplitude and coherence) and hydrodynamic simulation data provided by Today's Earth (TE). The floodwater depth was calculated using the SAR-derived flood extent and high-resolution digital elevation model (DEM). We examined our methods using ALOS-2 data for the 2015 flood in Japan.
ISSN:2153-7003
DOI:10.1109/IGARSS47720.2021.9553901