Building Damage Assessment in the 2015 Gorkha, Nepal, Earthquake Using Only Post‐Event Dual Polarization Synthetic Aperture Radar Imagery

This paper takes the 2015 Nepal earthquake as a case study to explore the use of post‐event dual polarimetric synthetic aperture radar images for earthquake damage assessment. The radar scattering characteristics of damaged and undamaged urban areas were compared by using polarimetric features derived from PALSAR‐2 and Sentinel‐1 images, and the results showed that distinguishing between damaged and undamaged urban areas with a single polarimetric feature is challenging. A split‐based image analysis, feature selection, and supervised classification were employed on a PALSAR‐2 image. The texture features derived from the intensity of cross‐polarization show higher correlations with the damage class. Additionally, feature selection revealed a positive influence on the overall performance. Employing 70% of the data for training and 30% data for testing, the support vector machine classifier achieved an accuracy of 80.5% compared with the reference data generated from the damage map that was provided by the United Nations Operational Satellite Applications Programme.