Radar Backscatter Modeling Based on Global TanDEM-X Mission Data

Radar backscatter knowledge is a valuable input for many remote sensing applications, which are based on synthetic aperture radar (SAR) systems. The amount of spaceborne data acquired within the TanDEM-X mission allows for the characterization of X-band backscatter on a global scale. The objective of this paper is to present a method for the characterization of radar backscatter behavior using a global statistical approach. The worldwide data set of images acquired within the TanDEM-X mission is taken into account, having the chance to exploit the unique high-quality topography information associated to it. The input measurements are differently assessed, by using a quality-based approach. A series of models can be derived, focusing on the backscatter dependence on polarization, incidence angle, ground classification, and seasonal time. The developed approach for the algorithm´s verification is presented as well, together with some preliminary results obtained from TanDEM-X mission data. The generation of up-to-date backscatter models for X-band will provide a useful database for the development of a large number of scientific applications and for the optimization of future radar systems.