HR: 14:10h
AN: H53K-03    [Abstracts]
TI: Terrain: Slope and Aspect Influence on QuikSCAT Backscatter
AU: * Mladenova, I E
EM: maldenoi@mailbox.sc.edu
AF: USC Department of Geological Sciences, 701 Sumter St, Columbia, SC 29208, United States
AU: Lakshmi, V
EM: Lakshmi@mailbox.sc.edu
AF: USC Department of Geological Sciences, 701 Sumter St, Columbia, SC 29208, United States
AB: The importance of better understanding of the nature of the backscattering signal is driven by the need to derive global soil moisture products at a fine resolution applicable to small scale, i.e. watershed studies, where the application of the currently-available low spatial resolution products might be limited. Furthermore, most of the model studies and disaggregation techniques using active observations assume flat terrain. However due to the strong dependence of the radar backscatter to slope and aspect we need to take into account topography variations when using radar data. Active radar backscatter observations derived from the QuikSCAT sensor were analyzed to investigate the effect of sloping terrain for the North American Monsoon Experiment (NAME) region located in south-western United States, Arizona and northern Mexico. The test area considered for this study is characterized by a complex heterogeneous terrain mainly covered by shrub- and grasslands and forested areas. The combined effect of topography and slope was categorized and evaluated for eight main vegetation classes spread over varying elevation and slope angle. Together with the local incidence angle, the slope was used to investigate the backscatter dependence on topography variation. The variability of QuikSCAT backscatter was evaluated using different statistical methods. Pearson Product-Moment Correlation Analysis showed strong backscatter dependence on the local incidence angle. The backscatter - local incidence angle correlation was used as an indication for backscatter variations induced by changes in slope. Further analysis showed that the total backscatter variability in the area is mainly controlled by the combined effect of vegetation and slope variations. A polynomial correction procedure was further applied to the data to explore the overall reduction of variances under the NAME conditions.
DE: 3360 Remote sensing
DE: 9900 CORRECTIONS
SC: Hydrology [H]
MN: 2007 Fall Meeting