Assessing Natural Disaster Impacts and Recovery Using Multifrequency, Fully-polarimetric Synthetic Aperture Radar (sar)

Many natural disasters involving landslides, volcanic eruptions, fires, or floods entail terrain resurfacing, followed by subsequent recovery. Modern satellite and airborne remote sensing technologies, which combine broad spatial coverage and high spatial resolution with time-sequential site revisit capability, can provide important information on the extent and duration of major landscape disturbance. In humid climate settings, these hazards temporarily remove or replace a natural vegetation cover and in doing so, modify the physical properties of the land surface. In optical remote sensing, removal of vegetation alters surface albedo in the visible near infrared (V-NIR) waveband, particularly the high reflectance from vegetation in the NIR. For SAR remote sensing, removal of vegetation cover causes a change in dominant microwave scattering mechanism for the areas affected. SAR has operational advantages over optical sensors for rapid disaster assessment because of its day/night acquisition capability, the ability to “see through” smoke, clouds and dust, and the side-looking viewing geometry, which is an advantage whenever data collection directly above the site would prove dangerous. We show how multifrequency, fully-polarimetric airborne SAR data can be “inverted” for parameters that reflect scattering mechanism signatures diagnostic of different surface cover types. We apply a uniform approach to map landslides resulting from the 1999 Mw 7.6 Chi-Chi earthquake in Taiwan and volcanic flows from the major 1996 eruption of Manam volcano in Papua New Guinea. In addition, earlier work has shown that multifrequency SAR polarimetric backscatter is sensitive to total above-ground biomass. This attribute can be exploited to calculate vegetation loss during a disaster and for assessment of regrowth during the recovery phase.