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.

Polarimetric SAR observables for land cover classification: analyses and comparisons

G Satalino;
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.
2006
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
0819464589
Image classification
neural networks
synthetic aperture radar (SAR) polarimetry
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/66729
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