Land cover classification using polarimetric SAR data

In this paper we demonstrate and validate the benefit of polarimetry for land cover classification. The performance of supervised and unsupervised algorithms are presented. Two data sources are used: DLR -ESAR L-Band data of Alling, Germany and JPL AIRSAR L and C Band data of Flevoland, The Netherlands. Both datasets have comprehensive ground truth and this is used as validation. Confusion matrices are presented and conclusions about the best frequency and polarisation combinations to use are drawn.

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