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PI2009230 INFLUENCE OF MACROSCALE AND MICROSCALE SURFACE ROUGHNESS ON MULTI-BEAM RADARSAT-1 DATA

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ABSTRACT

The dependence of the radar backscatter on macro and microtopography was examined through a collection of multi-beam RADARSAT-1 imagery acquired under ascending and descending passes over the Curaçá Valley, Northeastern Brazil. Firstly, the influence of both surface roughness regimes on the images was qualitatively evaluated through the use of Principal Component Analysis (PCA). The backscatter variability was emphasized using PCA since the components are linear combinations of all input radar target contributions within the original scenes. Secondly, the research addressed the quantitative influence of the microtopography on RADARSAT-1 s0 values through the use of statistical parameters derived from surface roughness profiles of distinct rock alteration products. The investigation has shown that the use of PCA on RADARSAT-1 imagery with distinct look-direction and incidence angles is a suitable technique for highlighting backscattering variability from distinct targets within each scene expressed by tonal and textural patterns. These image patterns reflected a combination of effects related to large-scale surface slope (scarps, crests, positive and negative topographic breaks, etc.) and to ground cover (surface roughness of rock outcrops, residual soils and vegetation cover). The topographic enhancement provided by the RADARSAT-1 PC2, PC3 and PC4 showed to be excellent for structural mapping. In addition, variation in look-azimuth was more important than incidence changes in the enhancement of subtle geomorphic features, often an expression of geological structures and underlying lithology. Finally, the quantitative evaluation of the dependence of s0 on microscale surface roughness confirmed that the SAR backscattering was not controlled in a predominant manner by the microtopographic variations of the geological surfaces.

KEYWORDS

RADARSAT-1, Macro and microtopography, Geological mapping, Principal Component Analysis, Brazilian semi-arid environment.

9782747217194
Nouveau

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