This article is a new assessment of damaged roads after the Kumamoto earthquake in southern Japan (2016) using remotely sensed synthetic aperture radar (SAR) data, field data and deep learning. Three SAR images from descending orbits of Sentinel-1 in vertical-vertical polarizations are considered for radiometric calibration, geocoding and interferometric analyses. Field data in terms of the international roughness index (IRI) were gathered over more than 530 km using a smartphone accelerometer and the BumpRecorder application. The relationship between SAR data and IRI data was investigated in a binary (0 and 1) mode to establish a multilayer perceptron model of damaged and intact roads. We found the remote sensing SAR datasets suitable, not only for the detection of damaged roads, but also as an indicator of road roughness changes. The classification results for damaged and intact roads indicated that our datasets (SAR and field measurements), together with a deep learning model, yielded acceptable overall accuracy (87.1%).

Tabriz is located in the northwest of Iran. Two huge earthquakes with magnitudes of 7.4 and 7.3 occurred there in 1780 and 1721. These earthquakes caused considerable damage and casualties in Tabriz. Using the method of scenario building, we aim to investigate what would happen if such earthquakes occurred in 2021. This scenario building was carried out using deterministic and GIS-oriented techniques to find the levels of damage and casualties that would occur. This procedure included two steps. In the first step, a database of factors affecting the destructive power of earthquakes was prepared. In the next step, hierarchical analysis was used to weigh the data, and then the weighted data were combined with an earthquake intensity map. The obtained results were used to predict the earthquake intensity in Tabriz. According to our results, the earthquake with a magnitude of 7.3 that occurred in 1721 caused huge destruction in the north of Tabriz, as this earthquake occurred inside the site. However, this earthquake caused minimal damage to the south of the city owing to the geological situation of this area of Tabriz. The earthquake with a magnitude of 7.3 that occurred in 1780 caused less damage because of its distance from the site. In the third step of this analysis, the vulnerability of buildings and the population were examined. According to the estimates, District 4 would experience the highest damage rate in the earthquake of 1721, with 15,477 buildings destroyed, while this area would have a lower damage rate in the earthquake that occurred in 1780. The total casualties in Tabriz would number 152,092 and 505 people in the earthquakes of 1721 and 1780, respectively.

On 28 March 2025, a devastating M 7.7 earthquake struck Myanmar along the right-lateral strike-slip Sagaing fault, followed by an M 6.7 aftershock twelve minutes later. This study presents a comprehensive assessment of the earthquake’s effects through recorded strong ground motions, macroseismic intensity observations, secondary hazards including liquefaction, and remote sensing-based damage detection. The supershear rupture spanned ∼460 km, with pronounced fault directivity effects resulting in high peak ground acceleration values of up to 0.57g recorded for the horizontal components and macroseismic intensities reaching modified Mercalli intensity = X in nearby cities. Analysis of acceleration time series and Fourier amplitude spectra at nearby recording stations revealed significant near-field effects and spectral exceedances over Myanmar National building code design levels, particularly in the short-period range, affecting mostly low-rise structures. Secondary hazard evaluation indicates widespread liquefaction, especially near the Irrawaddy River, supported by correlations between cumulative absolute velocity and liquefaction probability maps. Remote sensing analysis using multitemporal Advanced Land Observation Satellite-2 Synthetic Aperture Radar (SAR) coherence data identified severe building and road damage in urban centers. A differential coherence method, coupled with urban masking and OpenStreetMap road data, enabled spatial quantification of damage, revealing over 39,000 km of roads and 306 km2 of buildings with moderate-to-heavy damage. The results provide critical insight into the earthquake’s impact and demonstrate the joint evaluation of ground-motion analysis and SAR-based damage mapping for rapid seismic response.