Figure 6. (a) Radarsat-1 image acquired on September 2, 2005, over New Orleans, Louisiana, USA. (b) The extent of flooding 
(blue) for September 2, 2005, mapped by combining the Radarsat-1 image with a pre-flood Landsat Enhanced Thematic Mapper 
Plus (ETM+) image mosaic (Rykhus et al., 2005). Several possible oil slicks (red) are identified. Calm water acts as a specular 
reflector (or forward scatterer) of the SAR signal, resulting in very low backscatter values for flooded areas. However, flooding in 
areas with tall vegetation or buildings can result in a very high, “double-bounce” backscattering and is important for identifying 
flooding in forests and urban areas. Further, the tendency of oil slicks on water is to dampen the roughness of the water, which 
allows for the discrimination of oil slicks in open water with moderate to light wind conditions. 
Both L-band and C-band InSAR imagery can be effective in 
accurately measuring water-level changes in river valleys and 
wetlands (Alsdorf et al., 2000; Lu et al., 2005c). InSAR images 
suggest that water-level changes in wetlands can be dynamic 
and spatially heterogeneous and may not be represented by 
readings from sparsely distributed gauge stations (Figure 4). 
Calibrated by in-situ measurements, the InSAR-derived water- 
level changes within wetlands allow precise estimation of 
volumetric changes in water storage, which can improve 
hydrological modeling predictions and enhance the assessment 
of future flood events over wetlands (Lu and Kwoun, 2007). 
2.6 Constructing DEMs 
hindered by inclement weather conditions. For example, repeat- 
pass InSAR can be used to generate ice surface topography, 
which can determine the magnitude and direction of the 
gravitational force that drives ice flow and ice dynamics. In 
addition, volcano surface topography measurements from 
before and after an eruption can be used to estimate the volume 
of extruded material (Figure 5). There are many sources of error 
in DEM construction from repeat-pass InSAR images: 
inaccurate determination of the InSAR baseline, atmospheric 
delay anomalies, possible surface deformation due to tectonic, 
volcanic, or other loading sources over the time interval 
spanned by repeat-pass interferograms, etc. To generate a high- 
quality DEM from repeat-pass InSAR images, these errors must 
be corrected (Lu et al., 2003c). 
InSAR can be used to construct DEMs over areas where the 2.7 Characterizing land cover and changes 
photogrammetric approach to DEM generation has been