Automated Author Profile
Guerschman, Juan
CSIRO

Current S-Index

2.3

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.1

Average Dataset Index per dataset

Total Datasets

Total datasets for this author

Average FAIR Score

13.5%

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: 2.3 (sum of 2 datasets Dataset Index scores)

More information here.

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Fractional cover - MODIS, CSIRO algorithm

Vegetation fractional cover represents the exposed proportion of Photosynthetic Vegetation (PV), Non-Photosynthetic Vegetation (NPV) and Bare Soil (BS) within each pixel. In forested canopies the photosynthetic or non-photosynthetic portions of trees may obscure those of the grass layer and/or bare soil. The MODIS Fractional Cover product is derived from the MODIS Nadir BRDF-Adjusted Reflectance (NBAR) product (MCD43A4, collection 5). A suite of derivative products are also produced including monthly fractional cover, total vegetation cover (PV+NPV), and anomaly of total cover against the time series. Ground cover, as total cover minus an estimate of tree cover, is available as a separate product. MODIS fractional cover has been validated for Australia. A global product is also produced with the same algorithm using the global NBAR product MCD43C1 (collection 5, 0.05 degrees spatial resolution).

Authors

Guerschman, Juan

3 Citations0 Mentions13% FAIR2.0 Dataset Index

10.4225/08/5848a3f19a7b32014

Global Canopy Conductance (Gc)

This product provides estimates of canopy conductance at a global scale (0.05⁰) based on MODIS reflectance from MCD43C4 product and three vegetation indices (NDVI, EVI and Kc). The data is produced globally at 0.05⁰ and every 8 days. Monthly and anuual climatologies are also available.Base Period for Climatology: 2001-2011 Extra information about the pixel values:Units: mms-1Multiply by scale factor: 0.001Fill values: -9999The full reference for the algorithm is: Yebra, M., Van Dijk, A., Leuning, R., Huete, A., Guerschman, J.P., 2013. Evaluation of optical remote sensing to estimate actual evapotranspiration and canopy conductance. Remote Sensing of Environment. 129, 250-261