Abstract
ABSTRACT This study analyzes the ability of polarimetric Synthetic Aperture Radar (PolSAR) measurements to quantify post-earthquake damages. To achieve this goal, a twofold task is addressed: on one side a processing chain, which exploits multi-polarization SAR features, and a decision-tree classifier is proposed to quantify the levels of damage in earthquake-affected urbanized areas using dual-polarimetric (DP) SAR imagery. On the other side, a new damage index is developed that allows a fair spatial inter-comparison of building-by-building information, collected via ground surveys on the damaged areas, and SAR-derived damage maps. The proposed rationale is showcased using measurements related to the Central-Italy Earthquake occurred in 2016 where both Sentinel-1 DP imagery and ground-based information are available. Experimental results demonstrate the soundness of the proposed approach. The main outcomes can be summarized as follows: a) DP features perform better than single-polarization ones; b) DP features exhibit a larger sensitivity to lower damage grades if compared to the single polarization (SP) feature; c) the accuracy of the estimated damage levels depends on the requested granularity in the damage maps; d) the accuracy obtained using DP features spans from up to when five and two damage classes are considered, respectively.
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