Automated Author ProfileBusey, Robert C
Busey, Robert C
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: 1.0 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Ice-wedge polygons are perhaps the most dominant permafrost related features in the Arctic landscape. The microtopography of these features, including rims, troughs, and high and low polygon centers, alter the local hydrology, as water tends to collect in the low areas. During winter, wind redistribution of snow leads to an increased snowpack depth in the low areas, while the slightly higher areas often have thinner snow cover, also leading to differences across the landscape in vegetation communities and soil moisture between higher and lower areas. These differences in local surface conditions lead to spatial variability of the ground thermal regime in the different microtopographic areas and between different types of ice-wedge polygons. We studied four different ice-wedge polygon developmental stages using intensive two-dimensional subsurface temperature measurements.Published here are videos that depict the two-dimensional temperature field cross-section from each polygon, created using the temperature data from five vertical temperature profiles of 16 temperatures for each polygon. The daily average temperature values were interpolated, linearly, onto a grid using the depths converted to elevation and the horizontal distance between temperature profiles. Movies using the daily cross-sections were created to aid in the initial data interpretation and quickly get a sense of the two-dimensional ground thermal dynamics within each polygon.The mean daily ground temperature is shown for the period 15 Sept. 2012 to 30 Oct. 2015 as a cross-section through each polygon (Incipient Polygon starts in 1 Sept. 2013). The magenta bars show the daily snow depth and the location of the snow depth sensors are indicated by the *, black if data is available and red if not. The black line, when present shows the location of the thawing or freezing front. The temperature measurement profiles are shown as black dots for each measurement point.
Authors
- Cable, William L ;
- Romanovsky, Vladimir E ;
- Busey, Robert C