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 ability of very high frequency (VHF) (∼50 MHz) windprofilers to measure backscatter, winds and turbulence in the troposphere and the lower stratosphere gives them a unique perspective not available with many other remote sounding radar techniques. This capability has been utilized to study the environment of 31 tornadoes generated in the provinces of Ontario and Quebec in Canada over an 11-year period. Tornadoes were mostly of Enhanced Fujita (EF) types EF0 to EF2, with one being EF3. Focus is on events which produced visible damage.

Changes in the abundance and area of mountain lakes in the Djungarskiy (Jetysu) Alatau between 2002 and 2014 were investigated using Landsat imagery. The number of lakes increased by 6.2 % from 599 to 636 with a growth rate of 0.51 % a−1. The combined areas were 16.26 ± 0.85 to 17.35 ± 0.92 km2 respectively and the overall change was within the uncertainty of measurements. Fifty lakes, whose potential outburst can damage existing infrastructure, were identified.

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.