Automated Author ProfileHainzl, Sebastian
GFZ German Research Centre for Geosciences0000-0002-2875-0933
Hainzl, Sebastian
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 5.2 (sum of 5 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
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Datasets
This repository includes the code and data used in the paper " Algorithmic identification of the precursory scale increase (PSI) phenomenon in earthquake catalogues". There are four folders, two for the data, and one each for the "Circular algorithm" and for the "Rectangular algorithm", respectively. Each folder has a Readme.txt file explaining its content.
Authors
- Christophersen, Annemarie ;
- Rhoades, David A ;
- Hainzl, Sebastian
This repository includes the code and data used in the paper " Algorithmic identification of the precursory scale increase (PSI) phenomenon in earthquake catalogues". There are four folders, two for the data, and one each for the "Circular algorithm" and for the "Rectangular algorithm", respectively. Each folder has a Readme.txt file explaining its content.
Authors
- Christophersen, Annemarie ;
- Rhoades, David A ;
- Hainzl, Sebastian
A seismic station installed in the vicinity of a volcano can provide an overview of the state of the volcano. Different observable parameters can be extracted from the seismic time series to help monitor the temporal changes that preceding and accompanying a volcanic eruption. We calculated five seismic parameters which are Permutation Entropy (PE), Phase Permutation Entropy (PPE), Instantaneous Frequency (IF), Root-Mean-Square and Root-Median-Square (RMeS) of the seismic amplitude to detect changes prior and during the 2014-2015 Holuhraun eruption in Iceland.
Authors
- Sudibyo, Maria R.P. ;
- Eibl, Eva P.S. ;
- Hainzl, Sebastian ;
- Ohrnberger, Matthias
Contains two global earthquake-rate forecasts developed by Bayona et al. (2021) to be prospectively evaluated by the Collaboratory for the Study of Earthquake Predictability (CSEP). The Tectonic Earthquake Activity Model (TEAM) is a geodetic-based model using Version 2.1 of the Global Strain Rate Map (GSRM2.1; Kreemer et al., 2014), while the World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) is a model obtained from a multiplicative log-linear combination of TEAM with the Smoothed Seismicity (KJSS) model of Kagan and Jackson (2011). Earthquake densities are expressed as number of M5.95+ events per unit 0.1o cell per year. The forecasts are stored in tab separated value files, with the following fields (the first row of data is shown as an example): lon_min lon_max lat_min lat_max depth_min depth_max 5.95 6.05 ... -180.0 -179.9 -90.0 -89.9 0.0 70.0 4.95e-11 3.97e-11 ... Data and forecasts are described in detail in the following publications: Bayona, J.A., Savran, W., Strader, A., Hainzl, S., Cotton, F. and Schorlemmer, D., 2021. Two global ensemble seismicity models obtained from the combination of interseismic strain measurements and earthquake-catalogue information. Geophysical Journal International, 224(3), pp.1945-1955. Kreemer, C., Blewitt, G. and Klein, E.C., 2014. A geodetic plate motion and Global Strain Rate Model. Geochemistry, Geophysics, Geosystems, 15(10), pp.3849-3889. Kagan, Y.Y. and Jackson, D.D., 2011. Global earthquake forecasts. Geophysical Journal International, 184(2), pp.759-776.
Authors
- Schorlemmer, Danijel ;
- Bayona, José A. ;
- Savran, William H. ;
- Strader, Anne E. ;
- Hainzl, Sebastian ;
- Cotton, Fabrice
Contains two global earthquake-rate forecasts developed by Bayona et al. (2021) to be prospectively evaluated by the Collaboratory for the Study of Earthquake Predictability (CSEP). The Tectonic Earthquake Activity Model (TEAM) is a geodetic-based model using Version 2.1 of the Global Strain Rate Map (GSRM2.1; Kreemer et al., 2014), while the World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) is a model obtained from a multiplicative log-linear combination of TEAM with the Smoothed Seismicity (KJSS) model of Kagan and Jackson (2011). Earthquake densities are expressed as number of M5.95+ events per unit 0.1o cell per year. The forecasts are stored in tab separated value files, with the following fields (the first row of data is shown as an example): lon_min lon_max lat_min lat_max depth_min depth_max 5.95 6.05 ... -180.0 -179.9 -90.0 -89.9 0.0 70.0 4.95e-11 3.97e-11 ... Data and forecasts are described in detail in the following publications: Bayona, J.A., Savran, W., Strader, A., Hainzl, S., Cotton, F. and Schorlemmer, D., 2021. Two global ensemble seismicity models obtained from the combination of interseismic strain measurements and earthquake-catalogue information. Geophysical Journal International, 224(3), pp.1945-1955. Kreemer, C., Blewitt, G. and Klein, E.C., 2014. A geodetic plate motion and Global Strain Rate Model. Geochemistry, Geophysics, Geosystems, 15(10), pp.3849-3889. Kagan, Y.Y. and Jackson, D.D., 2011. Global earthquake forecasts. Geophysical Journal International, 184(2), pp.759-776.
Authors
- Bayona, José A. ;
- Savran, William H. ;
- Strader, Anne E. ;
- Hainzl, Sebastian ;
- Cotton, Fabrice ;
- Schorlemmer, Danijel