Automated Author ProfileLijing Wang
0000-0001-8121-5465
Lijing Wang
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: 0.5 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
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Datasets
This data release documents seismic data collected immediately adjacent to beaver ponds and in their surrounding floodplain environments using active and passive seismic measurements at three sites. These sites are located in the University of Connecticut (UConn) Forest in Storrs, Connecticut; Fenton-Ruby Park in Willington, Connecticut; and in Gunnison County, Colorado. Horizontal-to-vertical spectral ratio (HVSR) measurements were acquired using three-component Tromino seismometers (MoHo, S.R.L.) at non-inundated locations during late summer 2025 (51 total HVSR points). Resonance frequencies were identified from Fourier spectra using GRILLA software (MoHo, S.R.L.). Active 1D Multichannel Analysis of Surface Waves (MASW) test data were collected to estimate 1D seismic shear-wave velocity (Vs) structure at the UConn Forest and Fenton-Ruby Park sites using GRILLA (2 total MASW points). We used literature estimates of Vs for the Gunnison County site. We then converted the resonance frequencies to sediment thickness (depth to bedrock) using a range of plausible sediment shear-wave velocities to demonstrate potential uses of the geophysical data. The average inferred bedrock depth for the UConn Forest was 10.6 +/- 0.8 m; Fenton-Ruby Park was 5.3 +/- 0.9 m; and Gunnison County was 18 +/- 1.9 m. The uncertainty of these example calculations is based on how distinct the HVSR resonance frequency response was, as evaluated automatically with GRILLA software.
Authors
- Annie E Tucker ;
- Yeonju Kim ;
- Lijing Wang ;
- Eric A White ;
- David M Rey ;
- Fritz J Jean ;
- Samuel Pierce ;
- Martin Briggs
Using the horizontal-to-vertical spectral-ratio (HVSR) method, we inferred the depth to bedrock at the Slate River Floodplain, CO, USA. The point-scale passive seismic data were collected using Model TEP-3C Tromino seismometers over 20 min or less intervals with the instruments coupled directly to the floodplain ground surface at 42 non-flooded locations during June 2021. The ratio of horizontal-to-vertical Fourier spectra (HVSR), determined using Grilla software (MOHO, S.R.L.), along with the estimated sediment shear-wave velocity, was used to calculate the depth to the bedrock contact. This passive seismic dataset indicates that the deepest bedrock is 16 m below the surface, while the bedrock reaches the surface at the hillslope. This release contains the inferred bedrock depths based on likely shear wave velocities (Vs) intrinsic to the underlying sediment, ranging from 300 m/s to 400 m/s, listed in the processed_data subdirectory in the file 'SLAC_HVSR_June2021.csv.' The range of possible depth to bedrock interpretations is included for demonstration purposes only.
Authors
- Martin Briggs ;
- Lijing Wang