Automated Author ProfileYan, Eugene
Yan, Eugene
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: 0.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset supports the analysis conducted in the study "Did Official Flood Maps Work in Hurricane Helene? Systematic Evaluation of Official Flood Maps with Ground-truth Observations." It includes: (1) camera-based ground-truth flood extent data from Hurricane Helene in Pinellas County, Florida; (2) official flood maps from FEMA, FDEM, and Fathom; (3) population exposure and flood map performance metrics at the census block group level; (4) auxiliary datasets such as land cover and high-resolution population grids; and (5) Python scripts for calculating the Social Vulnerability Index (SoVI). The data enable spatial validation of flood risk models and investigation of socio-spatial disparities in flood map accuracy.
Authors
- Salim, Md Zakaria ;
- Qiang, Yi ;
- Dixon, Barnali ;
- Yan, Eugene ;
- Sahagún-Covarrubias, Sofía
This dataset supports the analysis conducted in the study "Did Official Flood Maps Work in Hurricane Helene? Systematic Evaluation of Official Flood Maps with Ground-truth Observations." It includes: (1) camera-based ground-truth flood extent data from Hurricane Helene in Pinellas County, Florida; (2) official flood maps from FEMA, FDEM, and Fathom; (3) population exposure and flood map performance metrics at the census block group level; (4) auxiliary datasets such as land cover and high-resolution population grids; and (5) Python scripts for calculating the Social Vulnerability Index (SoVI). The data enable spatial validation of flood risk models and investigation of socio-spatial disparities in flood map accuracy.
Authors
- Salim, Md Zakaria ;
- Qiang, Yi ;
- Dixon, Barnali ;
- Yan, Eugene ;
- Sahagún-Covarrubias, Sofía