Recent studies suggest that Antarctica has the potential to contribute up to ~15 m of sea-level rise over the next few centuries. The evolution of the Antarctic Ice Sheet is driven by a combination of climate forcing and non-climatic feedbacks.

Since the beginning of the 1980s, when Mandelbrot observed that earthquakes occur on ‘fractal’ self-similar sets, many studies have investigated the dynamical mechanisms that lead to self-similarities in the earthquake process. Interpreting seismicity as a self-similar process is undoubtedly convenient to bypass the physical complexities related to the actual process. Self-similar processes are indeed invariant under suitable scaling of space and time.

Original Source

The causative source of the first damaging earthquake instrumentally recorded in the Island of Ischia, occurred on 21 August 2017, has been studied through a multiparametric geophysical approach. In order to investigate the source geometry and kinematics we exploit seismological, Global Positioning System, and Sentinel‐1 and COSMO‐SkyMed differential interferometric synthetic aperture radar coseismic measurements.

In order to make a scientific emergency strategic decision after an earthquake, casualties need to be estimated rapidly. Asia is the most earthquake-prone continent in the world. In this paper, by spatial statistic and regressive analysis of historical Asian earthquake data from 1990 to 2012, vulnerability curves portraying the empirical relationship between the magnitude of an earthquake event and the casualty rate caused by it were created for countries of six-groups and the Quick Assessment Model of Earthquake Casualties for Asia (QAMECA) was developed.

Fault behavior during an earthquake is controlled by the state of stress on the fault. Complex coseismic fault slip on large earthquake faults has recently been observed by dense seismic networks, which complicates strong motion evaluations for potential faults. Here we show the three-dimensional prestress field related to the 2016 Kumamoto earthquake.

Landslide displacement prediction is one of the focuses of landslide research. In this paper, time series analysis was used to decompose the cumulative displacement of landslide into a trend component and a periodic component. Then LSSVM model and GA were used to predict landslide displacement. The results show that the GA-LSSVM model can be effectively used to predict landslide displacement and reflect the corresponding relationships between the major influencing factors and the displacement.

The rock avalanche that destroyed the village of Xinmo in Sichuan, China, on June 24th, 2017, brought the issue of landslide risk and disaster chain management in highly seismic regions back into the spotlight. The long-term post-seismic behaviour of mountain slopes is complex and hardly predictable. Nevertheless, the integrated use of field monitoring, remote sensing and real-time predictive modelling can help to set-up effective early warning systems, provide timely alarms, optimize rescue operations and perform secondary hazard assessments.