Increasing human and economic losses from urban disasters demand synthetic aperture radar (SAR), which has allweather, day-and-night observation capability. The Japan Aerospace Exploration Agency (JAXA) has been operating the Advanced Land Observing Satellite-2 (ALOS-2), carrying PALSAR-2, an L-band SAR, for monitoring disasters and environmental changes. We developed the first fully automated algorithms for detecting flood extents and earthquakeinduced building damage from ALOS-2 data. The algorithms rapidly process ALOS-2 and ancillary data (flood simulation, hazard map, and other geographical information) and provide damage information less than an hour after the input data are entered. The validation results showed that the accuracy of the estimated flood extent was 60 to 94%, depending on the observation conditions, especially the incidence angle of ALOS-2 observation. The accuracy of the damaged building detection was 72% for buildings with a footprint larger than 200 m2 in the area. We implemented these algorithms in an operational disaster response system. We launched a one-stop operation that automatically processes ALOS-2 data after emergency observation and provides the damage maps rapidly via email for disaster response workers.
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