Automated Author ProfileGopalakrishna, Trisha
University of Exeter
Gopalakrishna, Trisha
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: 3.2 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The datasets in this repository are the results of the study titled "Optimizing Forest Restoration: a holistic spatial approach to deliver Nature's Contributions to People (NCP) with minimal trade-offs and maximal equity". The study shows that forest restoration plans aimed at joint achievement of multiple NCP have minimal trade-offs between the NCP, optimize areas evenly across the potential restoration area considered and have maximal equity considering socioeconomically disadvantaged people in India, when compared to single NCP forest restoration plans. There are 3 NCP considered- climate change mitigation (MtC), biodiversity value NCP (number of forest depenend mamm species of 56 forest mammals considered, who restoration area target will be met)) and people NCP (number of people to whom livelihoods, energy and housing contruction material will be delivered). Single NCP forest restoration plans aim at only one of the three NCP considered at a time while the integrated plan is aimed at joint achievement of all three NCP. The peer-reviewed publication will be linked here after the peer-review process. There are 5 datasets in this repository. The first titled opportunearea_10km_resample.tif is the potential forest restoration area considered in this study. The pixel values indicate the amount of potential forest restoration area within that pixel in sqm. The remaining 4 datasets are zipped files indicating each of the forest restoration plans considered. In each zipped file there are 100 raster files (.tif format). Each of the rasters provide the forest restoration area (first dataset) optimized for the respective type of forest restoration plan in 1% increments of the total potential restoration area. The naming format followed for each of these rasters is Y_NCPtype_optimality.tif, where Y is 1-100 and NCPType is either Biodiveristy, People, Carbon or Integrated. The pixel values in each of the rasters have a range of 0-1, where 0 means that restoration area (pixel) is not optimized for delivery of the respective NCP for that increment of total potential restoration area and 1 means the entire restoration area (pixel) has been optimized for delivery of the respective NCP. Proportional pixel values indicate that the respective proportion of the restoration area is optimal. All rasters have pixel dimensions of 10 km x 10k (333, 325, 1 (nrow, ncol, nlyr)) with raster extent 7590450, 10840450, 902100, 4232100 (xmin, xmax, ymin, ymax) and WGS 1984 Psuedo Mercator (EPSG: 3857) coordinate reference system.
Authors
- Gopalakrishna, Trisha ;
- Visconti, Piero ;
- Lomax, Guy ;
- Boere, Esther ;
- Malhi, Yadvinder ;
- Sarathi, Parth ;
- Joshi, Pawan ;
- Fedele, Giacomo ;
- Yowargana, Ping
The datasets in this repository are the results of the study titled "Optimizing Forest Restoration: a holistic spatial approach to deliver Nature's Contributions to People (NCP) with minimal trade-offs and maximal equity". The study shows that forest restoration plans aimed at joint achievement of multiple NCP have minimal trade-offs between the NCP, optimize areas evenly across the potential restoration area considered and have maximal equity considering socioeconomically disadvantaged people in India, when compared to single NCP forest restoration plans. There are 3 NCP considered- climate change mitigation (MtC), biodiversity value NCP (number of forest depenend mamm species of 56 forest mammals considered, who restoration area target will be met)) and people NCP (number of people to whom livelihoods, energy and housing contruction material will be delivered). Single NCP forest restoration plans aim at only one of the three NCP considered at a time while the integrated plan is aimed at joint achievement of all three NCP. The peer-reviewed publication will be linked here after the peer-review process. There are 5 datasets in this repository. The first titled opportunearea_10km_resample.tif is the potential forest restoration area considered in this study. The pixel values indicate the amount of potential forest restoration area within that pixel in sqm. The remaining 4 datasets are zipped files indicating each of the forest restoration plans considered. In each zipped file there are 100 raster files (.tif format). Each of the rasters provide the forest restoration area (first dataset) optimized for the respective type of forest restoration plan in 1% increments of the total potential restoration area. The naming format followed for each of these rasters is Y_NCPtype_optimality.tif, where Y is 1-100 and NCPType is either Biodiveristy, People, Carbon or Integrated. The pixel values in each of the rasters have a range of 0-1, where 0 means that restoration area (pixel) is not optimized for delivery of the respective NCP for that increment of total potential restoration area and 1 means the entire restoration area (pixel) has been optimized for delivery of the respective NCP. Proportional pixel values indicate that the respective proportion of the restoration area is optimal. All rasters have pixel dimensions of 10 km x 10k (333, 325, 1 (nrow, ncol, nlyr)) with raster extent 7590450, 10840450, 902100, 4232100 (xmin, xmax, ymin, ymax) and WGS 1984 Psuedo Mercator (EPSG: 3857) coordinate reference system.
Authors
- Gopalakrishna, Trisha ;
- Visconti, Piero ;
- Lomax, Guy ;
- Boere, Esther ;
- Malhi, Yadvinder ;
- Sarathi, Parth ;
- Joshi, Pawan ;
- Fedele, Giacomo ;
- Yowargana, Ping