Polarimetric SAR observables for land cover classification: analyses and comparisons
Conference Paper
Publication Date:
2006
abstract:
In this contribution, we present a study on a series of representations of polarimetric synthetic aperture radar
(SAR) data, testing and comparing them with respect to their utility for land cover classification. Different
classification algorithms are also compared.
Part of this work is dedicated to the study of the dependence of the classification results on the varying
size of averaging windows of pixels. Such an analysis will permit to prove if the polarimetric parameters under
consideration describe only point-like physical properties of the targets or if they also contain "extended", local
information. The final goal is to provide an objective estimate of the usefulness of these parameters.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Image classification; neural networks; synthetic aperture radar (SAR) polarimetry
List of contributors:
Satalino, Giuseppe
Book title:
Proceedings of SPIE - The International Society for Optical Engineering
Published in: