Automated Author ProfileQin, Dajun
Qin, Dajun
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
Metadata Description：(1) Carbon sequestration supply (NEP)The Carbon Sequestration Supply (NEP) data is produced based on the Carnegie-Ames-Stanford approach (CASA) model and Net Ecosystem Productivity (NEP) model, with a spatial resolution of 100 meters. The data content includes NEP datasets from Hainan Island, China in the years 2000, 2005, 2010, 2015 and 2020.(2) Carbon sequestration demand (CSD)The Carbon sequestration demand data is produced based on the emission factor assessment methods using energy consumption and population density, with a spatial resolution of 100 meters. The data content includes CSD datasets from Hainan Island, China in the years 2000, 2005, 2010, 2015 and 2020.(3) Spatial linked characteristics based on gravitational forceTo understand the degree of correlation and the extent of spatial correlation between the region's carbon sequestration supply and demand, we introduce the concept of regional supply and demand gravity. A higher gravitational force between two locations indicates that the transport corridor connecting them facilitates a greater flow of sequestered carbon streams, signifying its heightened importance.
Authors
- Xiao, Yang ;
- Ren, Bingnan ;
- Liu, Bin ;
- Geng, Jing ;
- Wu, Wenxiang ;
- Qin, Dajun
Metadata Description：(1) Carbon sequestration supply (NEP)The Carbon Sequestration Supply (NEP) data is produced based on the Carnegie-Ames-Stanford approach (CASA) model and Net Ecosystem Productivity (NEP) model, with a spatial resolution of 100 meters. The data content includes NEP datasets from Hainan Island, China in the years 2000, 2005, 2010, 2015 and 2020.(2) Carbon sequestration demand (CSD)The Carbon sequestration demand data is produced based on the emission factor assessment methods using energy consumption and population density, with a spatial resolution of 100 meters. The data content includes CSD datasets from Hainan Island, China in the years 2000, 2005, 2010, 2015 and 2020.(3) Spatial linked characteristics based on gravitational forceTo understand the degree of correlation and the extent of spatial correlation between the region's carbon sequestration supply and demand, we introduce the concept of regional supply and demand gravity. A higher gravitational force between two locations indicates that the transport corridor connecting them facilitates a greater flow of sequestered carbon streams, signifying its heightened importance.
Authors
- Xiao, Yang ;
- Ren, Bingnan ;
- Liu, Bin ;
- Geng, Jing ;
- Wu, Wenxiang ;
- Qin, Dajun