Classification of the Yellow River delta area using fully polarimetric SAR measurements. Issue 23 (2nd December 2017)

• Record Type: Journal Article
• Authors: Buono, A.; Nunziata, F.; Migliaccio, M.; Yang, X.; Li, X.
• Is Part Of: International journal of remote sensing. Volume 38:Issue 23(2017)
• Page Start: 6714
• Page End: 6734
• Publication Date: 2017-12-02
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2017.1363437
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: In this study, an analysis of the polarimetric synthetic aperture radar (SAR) capabilities to classify coastal areas is undertaken. The Yellow River delta (China) is selected as the test case since it represents an extraordinary environmental and economical area, which is characterized by a very heterogeneous scattering scenario, as witnessed by official reference data, provided by the Chinese government, that classified 12 different kinds of environment. Experimental results, obtained applying two well-known unsupervised classifiers, namely the H / α -based and the Freeman–Durden model-based algorithms, to a fully polarimetric SAR scene collected by Radarsat-2 in 2008 are compared and critically discussed. Both provide a satisfactory global accuracy (larger than 60% in average) with reference to the inland Yellow River delta area, but there are subareas that result in misclassifications and severe classification ambiguities. This study also suggests including single-polarization intensity information to improve the classification accuracy and to partly solve ambiguities.