Articles | Volume 7, issue 1
https://doi.org/10.5194/esurf-7-171-2019
https://doi.org/10.5194/esurf-7-171-2019
Research article
 | 
04 Feb 2019
Research article |  | 04 Feb 2019

Systematic identification of external influences in multi-year microseismic recordings using convolutional neural networks

Matthias Meyer, Samuel Weber, Jan Beutel, and Lothar Thiele

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Latest update: 27 Mar 2024
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Short summary
Monitoring rock slopes for a long time helps to understand the impact of climate change on the alpine environment. Measurements of seismic signals are often affected by external influences, e.g., unwanted anthropogenic noise. In the presented work, these influences are automatically identified and removed to enable proper geoscientific analysis. The methods presented are based on machine learning and intentionally kept generic so that they can be equally applied in other (more generic) settings.