In disaster mitigation planning for future large earthquakes, seismic ground motion predictions are a crucial part of early warning systems. The way the ground moves depends on how the soil layers amplify the seismic waves (described in a mathematical site 'amplification factor'). However, geophysical explorations to understand soil conditions are costly, limiting characterization of site amplification factors to date. Using data on microtremors in Japan, a neural network model can estimate site-specific responses to earthquakes based on subsurface soil conditions.
