We focus on the aspect of combining frontier science with high-density ground and building measurements and large open data pools to better predict ground-shaking and building behavior but also to better quantify and visualize the potential impact of earthquakes.
The aim of this session is to give an up-to-date view of new ideas and methods using dense seismological networks, the latest generation of ground-motion databases, data-mining analyses, crowd-sourcing data, and smart-city technologies to evaluate ground-shaking and assess earthquake hazard and risk.
We invite papers related to:
(1) Site-specific and ultra-high-density earthquake ground-motion prediction (e.g. non-ergodic ground-motion models, use of machine learning in engineering seismology, high-resolution site conditions)
(2) Scenario-based or probabilistic earthquake hazard and risk assessment
(3) Exposure models from open data (e.g. use of OpenStreetMap data)
(4) Structural health monitoring of buildings for dynamic vulnerability modeling during earthquake sequences or dynamic exposure modeling
(5) Transparent and innovative hazard/risk visualization methods