Articles | Volume 11, issue 4
https://doi.org/10.5194/se-11-1597-2020
https://doi.org/10.5194/se-11-1597-2020
Method article
 | 
28 Aug 2020
Method article |  | 28 Aug 2020

Introducing noisi: a Python tool for ambient noise cross-correlation modeling and noise source inversion

Laura Ermert, Jonas Igel, Korbinian Sager, Eléonore Stutzmann, Tarje Nissen-Meyer, and Andreas Fichtner

Viewed

Total article views: 4,485 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,661 1,740 84 4,485 396 82 75
  • HTML: 2,661
  • PDF: 1,740
  • XML: 84
  • Total: 4,485
  • Supplement: 396
  • BibTeX: 82
  • EndNote: 75
Views and downloads (calculated since 13 May 2020)
Cumulative views and downloads (calculated since 13 May 2020)

Viewed (geographical distribution)

Total article views: 4,485 (including HTML, PDF, and XML) Thereof 3,920 with geography defined and 565 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 24 Apr 2024
Download
Short summary
We present an open-source tool to model ambient seismic auto- and cross-correlations with spatially varying source spectra. The modeling is based on pre-computed databases of seismic wave propagation, which can be obtained from public data providers. The aim of this tool is to facilitate the modeling of ambient noise correlations, which are an important seismologic observable, with realistic wave propagation physics. We present a description and benchmark along with example use cases.