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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.