Abstract
On 29 December 2020, an earthquake with a magnitude of M 6.4 hit the central part of Croatia. The earthquake resulted in casualties and damaged buildings in the town of Petrinja (~6 km away from the epicenter) and surrounding areas. This study aims to characterize ground displacement and to estimate the location of damaged areas following the Petrinja earthquake using six synthetic aperture radar (SAR) images (C-band) acquired from both ascending and descending orbits of the Sentinel-1 mission. Phase information from both the ascending (Sentinel-1A) and descending (Sentinel-1B) datasets, acquired from SAR interferometry (InSAR), is used for estimation of ground displacement. For damage mapping, we use histogram information along with the RGB method to visualize the affected areas. In sparsely damaged areas, we also propose a method based on multivariate alteration detection (MAD) and naive Bayes (NB), in which pre-seismic and co-seismic coherence maps and geocoded intensity maps are the main independent variables, together with elevation and displacement maps. For training, approximately 70% of the data are employed and the rest of the data are used for validation. The results show that, despite the limitations of C-band SAR images in densely vegetated areas, the overall accuracy of MAD+NB is ~68% compared with the results from the Copernicus Emergency Management Service (CEMS).
Highlights
Earthquakes are among the most destructive natural disasters on Earth
4g shows the damage distribution in Petrinja based on auxiliary information gathered by the Copernicus emergency management service (EMS)
Once the multivariate alteration detection (MAD) map is extracted from multivariate analysis (Figure 8a–c), the naive Bayes (NB)
Summary
Earthquakes are among the most destructive natural disasters on Earth. They are mainly unpredictable in terms of time and location. People located near seismically active areas are one of the most vulnerable elements during catastrophic earthquakes, and disaster prevention plans implemented by organizations and construction companies can increase the resiliency of a society. Resilience includes both pre-disaster and post-disaster actions. Along with innovative damage assessment techniques in terms of loss/consequences [12,13], remote sensing techniques can provide efficient damage
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