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Accurate Geometric Correction for Normalisation of PALSAR Radiometry

David Small(1), Michael Jehle(1), Adrian Schubert(1) and Erich Meier(1)

(1) University of Zurich, Winterthurerstrasse 190, CH-8057 Z├╝rich, Switzerland

Abstract

In contrast to earlier satellites with SAR instruments, the ENVISAT and ALOS platforms provide state vectors with sufficient accuracy to enable the ASAR and PALSAR sensors to support accurate tiepoint-free geolocation of their imagery. This enables not only map overlays and data fusion with other sources, but also normalisation for the systematic influence of terrain variations on individual image radiometry. Such normalisation is necessary to move away from dependency on single-track repeat passes for change-detection and interpretation.

We briefly describe our verifications of the geometric behaviour of PALSAR L1.1 products using available products with surveyed corner reflector targets present in reference images.

We model and evaluate the path delays induced by the troposphere and ionosphere on reference imagery, and compare Faraday rotation estimates produced using fully polarimetric PLR imagery with values derived from GNSS-network measurements. In the latter estimate, the total electron content (TEC) of the ionosphere at the time of the PALSAR acquisition is combined with a model of the Earth's magnetic field to estimate the Faraday rotation induced by the ionosphere along the line of sight from the satellite to each point on the ground.

Given accurate knowledge of the acquisition geometry of a SAR image from one of the above sensors together with a digital elevation model (DEM) of the area imaged, radiometric image simulation is applied to estimate the local illuminated area for each point in the image. Rather than a typical ellipsoid-based approximation that ignores topographic variation, terrain-based radiometric image simulation is used as the basis for converting from beta0 to sigma0 or gamma0 backscatter normalisation conventions.

The interpretability of PALSAR imagery with and without ellipsoid- vs. terrain-based normalisations is compared and evaluated.

 

Symposium presentation

 

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