Assessing Natural Disaster Impacts and Recovery Using Airborne, Multifrequency Synthetic Aperture Radar (SAR) Polarimetry
Lamont-Doherty Earth Observatory,
61 Route 9W,
Palisades, NY 10964,
(2) Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA 91109, United States
Many natural disasters involving landslides, volcanic eruptions, fires, or floods entail terrain resurfacing, followed by a period of 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 remove or replace a natural vegetation cover temporarily, 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 is an advantage whenever data collection directly above the site would prove dangerous. We show how parameters that reflect scattering mechanism signatures diagnostic of different surface cover types can be derived from multifrequency, fully-polarimetric airborne SAR data. We apply a uniform methodology to map landslides resulting from the 1999 Mw 7.6 Chi-Chi earthquake in Taiwan, volcanic flows from the major 1996 eruption of Manam volcano in Papua New Guinea, and the extent of damage from the summer 2002 Rodeo - Chediski wildfire in Arizona. 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.