Automated Author ProfileSumalika Biswas
Sumalika Biswas
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: 5.5 (sum of 8 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset provides information on tree cover for the country of Myanmar for the year 2018. The spatial resolution of the dataset is 30m. Each pixel represents percent tree cover value. The percent tree cover values range from 0-100%. The dataset is derived by calibrating uncalibrated tree-cover estimates from Landsat Vegetation Continuous Fields (VCF) tree cover layer against high-resolution estimates derived from drone imagery and other sources. The product is the result of collaboration between Smithsonian Conservation Biology Institute and terraPulse.
Authors
- Panshi Wang ;
- Sexton, Joseph O. ;
- Qiongyu Huang ;
- Sumalika Biswas ;
- Leimgruber, Peter
This dataset provides information on tree cover for the country of Myanmar for the year 2018. The spatial resolution of the dataset is 30m. Each pixel represents percent tree cover value. The percent tree cover values range from 0-100%. The dataset is derived by calibrating uncalibrated tree-cover estimates from Landsat Vegetation Continuous Fields (VCF) tree cover layer against high-resolution estimates derived from drone imagery and other sources. The product is the result of collaboration between Smithsonian Conservation Biology Institute and terraPulse.
Authors
- Sexton, Joseph O. ;
- Panshi Wang ;
- Qiongyu Huang ;
- Sumalika Biswas ;
- Leimgruber, Peter
Orthomosaic of drone image collected in 12 locations in Myanmar in 2018 and 2019
Authors
- Sumalika Biswas ;
- Qiongyu Huang ;
- Leimgruber, Peter
Orthomosaic of drone image collected in 12 locations in Myanmar in 2018 and 2019
Authors
- Sumalika Biswas ;
- Qiongyu Huang ;
- Leimgruber, Peter
Orthomosaic of drone image collected in 12 locations in Myanmar in 2018 and 2019
Authors
- Sumalika Biswas ;
- Qiongyu Huang ;
- Leimgruber, Peter
This dataset provides information on tree cover for the country of Myanmar for the year 2018. The spatial resolution of the dataset is 30m. Each pixel represents percent tree cover value. The percent tree cover values range from 0-100%. The dataset is derived by calibrating uncalibrated tree-cover estimates from Landsat Vegetation Continuous Fields (VCF) tree cover layer against high-resolution estimates derived from drone imagery and other sources. The product is the result of collaboration between Smithsonian Conservation Biology Institute and terraPulse.
Authors
- Panshi Wang ;
- Sexton, Joseph O. ;
- Qiongyu Huang ;
- Sumalika Biswas ;
- Leimgruber, Peter
Orthomosaic of drone image collected in 12 locations in Myanmar in 2018 and 2019
Authors
- Sumalika Biswas ;
- Qiongyu Huang ;
- Leimgruber, Peter