Spatial Interpolation of Ground Motion Intensity Measures Based on Two-Step Gaussian Process Regression

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Key Points

This research aims to enhance the estimation accuracy of ground motion intensity measures through a two-step spatial interpolation method.
Proposed a two-step Gaussian process regression for spatial interpolation of ground motion intensity measures.
First step includes introducing artificial noise and interpolating ground motion values.
Second step addresses interpolation of error between the first step estimates and observed values.
The two-step Gaussian process regression significantly outperformed traditional methods like Simple Kriging in estimation accuracy.
Estimates derived from the proposed method demonstrated lower error rates compared to previous approaches.

Shows improved estimation accuracy in ground motion intensity measures, suggesting better disaster preparedness.

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Tsukioka et al. (2026) studied this question.

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