Automated Author ProfileFu, Yongshuo
Beijing Normal UniversityUniversity of Antwerp
Fu, Yongshuo
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: 1.2 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
A vegetation phenology dataset for the Northern Hemisphere( the latitude ranging from 30°N to 90°N, the longitude ranging from -180°E to 180°E), including start of season (SOS_merge), SOS uncertainty range (SOS_merge_r), end of season (EOS_merge), and EOS uncertainty range (EOS_merge_r). This dataset is generated by merging four vegetation phenology datasets including MODIS MCD12Q2(https://lpdaac.usgs.gov/products/mcd12q2v061/), MEaSUREs VIPPHEN(https://lpdaac.usgs.gov/products/vipphen_ndviv004/), GIMMS NDVI3g(http://data.globalecology.unh.edu/data/GIMMS_NDVI3g_Phenology/), GIMMS NDVI4g(https://doi.org/10.5281/zenodo.7649107) using the reliability ensemble averaging method. The uncertainty range is calculated based on the weight of each dataset and the deviation between REA result and data sources, the upper and lower uncertainty limits are measured by REA result and the uncertainty range.The spatial resolution of the new dataset is 0.05° and its temporal scale spans 1982–2022. The new dataset was validated using data from the ground-based PhenoCam dataset from 280 sites over the period 2000–2018, which provided 1410 site–year combinations.The dataset is stored in TIFF format, the unit of “SOS_merge” and “EOS_merge” is day of year (DOY), and the unit of “SOS_merge_r” and “EOS_merge_r” is day.
Authors
- Cui, Yishuo ;
- Fu, Yongshuo
A vegetation phenology dataset for the Northern Hemisphere( the latitude ranging from 30°N to 90°N, the longitude ranging from -180°E to 180°E), including start of season (SOS_merge), SOS uncertainty range (SOS_merge_r), end of season (EOS_merge), and EOS uncertainty range (EOS_merge_r). This dataset is generated by merging four vegetation phenology datasets including MODIS MCD12Q2(https://lpdaac.usgs.gov/products/mcd12q2v061/), MEaSUREs VIPPHEN(https://lpdaac.usgs.gov/products/vipphen_ndviv004/), GIMMS NDVI3g(http://data.globalecology.unh.edu/data/GIMMS_NDVI3g_Phenology/), GIMMS NDVI4g(https://doi.org/10.5281/zenodo.7649107) using the reliability ensemble averaging method. The uncertainty range is calculated based on the weight of each dataset and the deviation between REA result and data sources, the upper and lower uncertainty limits are measured by REA result and the uncertainty range.The spatial resolution of the new dataset is 0.05° and its temporal scale spans 1982–2022. The new dataset was validated using data from the ground-based PhenoCam dataset from 280 sites over the period 2000–2018, which provided 1410 site–year combinations.The dataset is stored in TIFF format, the unit of “SOS_merge” and “EOS_merge” is day of year (DOY), and the unit of “SOS_merge_r” and “EOS_merge_r” is day.
Authors
- Cui, Yishuo ;
- Fu, Yongshuo
A vegetation phenology dataset for the Northern Hemisphere( the latitude ranging from 30°N to 90°N, the longitude ranging from -180°E to 180°E), including start of season (SOS_merge), SOS uncertainty range (SOS_merge_r), end of season (EOS_merge), and EOS uncertainty range (EOS_merge_r). This dataset is generated by merging four vegetation phenology datasets including MODIS MCD12Q2(https://lpdaac.usgs.gov/products/mcd12q2v061/), MEaSUREs VIPPHEN(https://lpdaac.usgs.gov/products/vipphen_ndviv004/), GIMMS NDVI3g(http://data.globalecology.unh.edu/data/GIMMS_NDVI3g_Phenology/), GIMMS NDVI4g(https://doi.org/10.5281/zenodo.7649107) using the reliability ensemble averaging method. The uncertainty range is calculated based on the weight of each dataset and the deviation between REA result and data sources, the upper and lower uncertainty limits are measured by REA result and the uncertainty range.The spatial resolution of the new dataset is 0.05° and its temporal scale spans 1982–2022. The new dataset was validated using data from the ground-based PhenoCam dataset from 280 sites over the period 2000–2018, which provided 1410 site–year combinations.The dataset is stored in TIFF format, the unit of “SOS_merge” and “EOS_merge” is day of year (DOY), and the unit of “SOS_merge_r” and “EOS_merge_r” is day.
Authors
- Cui, Yishuo ;
- Fu, Yongshuo