Automated Author ProfileBellat, Mathias
Bellat, Mathias
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: 3.0 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The prediction map for soil depth in cm (0 - 100 cm) and soil properties (0 - 10 - 30 - 50 - 70 - 100 cm) is based on a quantile random forest (QRF) model. The uncertainty was computed based on the lower and higher quantile from the QRF model (Uncertainty = (Qp0.95 - Qp0.05) / (Qp0.5)). Soil depth is expressed in cm, pH is expressed in absolute value, MWD in mm, Nt, Ct, Corg, Sand, Silt and Clay in %, and EC in µS/cm. The pixel size is 30 x 30 m, and the projected coordinate system is WGS84 (epsg:4326).
Authors
- Bellat, Mathias ;
- Zebari, Mjahid ;
- Glissmann, Benjamin ;
- Rentschler, Tobias ;
- Sconzo, Paola ;
- Kakhani, Nafiseh ;
- Kohsravani, Pegah ;
- Taghizadeh-Mehrjardi, Ruhollah ;
- Brifkany, Bekas ;
- Pfälzner, Peter ;
- Scholten, Thomas
The prediction map for soil depth in cm (0 - 100 cm) and soil properties (0 - 10 - 30 - 50 - 70 - 100 cm) is based on a quantile random forest (QRF) model. The uncertainty was computed based on the lower and higher quantile from the QRF model (Uncertainty = (Qp0.95 - Qp0.05) / (Qp0.5)). Soil depth is expressed in cm, pH is expressed in absolute value, MWD in mm, Nt, Ct, Corg, Sand, Silt and Clay in %, and EC in µS/cm. The pixel size is 30 x 30 m, and the projected coordinate system is WGS84 (epsg:4326).
Authors
- Bellat, Mathias
The prediction map for soil depth in cm (0 - 100 cm) and soil properties (0 - 10 - 30 - 50 - 70 - 100 cm) is based on a quantile random forest (QRF) model. The uncertainty was computed based on the lower and higher quantile from the QRF model (Uncertainty = (Qp0.95 - Qp0.05) / (Qp0.5)). Soil depth is expressed in cm, pH is expressed in absolute value, MWD in mm, Nt, Ct, Corg, Sand, Silt and Clay in %, and EC in µS/cm. The pixel size is 30 x 30 m, and the projected coordinate system is WGS84 (epsg:4326).
Authors
- Bellat, Mathias ;
- Zebari, Mjahid ;
- Glissmann, Benjamin ;
- Rentschler, Tobias ;
- Sconzo, Paola ;
- Kakhani, Nafiseh ;
- Kohsravani, Pegah ;
- Taghizadeh-Mehrjardi, Ruhollah ;
- Brifkany, Bekas ;
- Pfälzner, Peter ;
- Scholten, Thomas