Articles | Volume 12, issue 2
Earth Syst. Sci. Data, 12, 789–804, 2020
https://doi.org/10.5194/essd-12-789-2020
Earth Syst. Sci. Data, 12, 789–804, 2020
https://doi.org/10.5194/essd-12-789-2020

Data description paper 02 Apr 2020

Data description paper | 02 Apr 2020

Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale

Wei Li et al.

Data sets

Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale W. Li https://doi.org/10.5281/zenodo.3274254

A global yield dataset for major lignocellulosic bioenergy crops based on field measurements W. Li, W. P. Ciais, D. Makowski, and S. Peng https://doi.org/10.1038/sdata.2018.169

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Short summary
We generated spatially explicit bioenergy crop yields based on field measurements with climate, soil condition and remote-sensing variables as explanatory variables and the machine-learning method. We further compared our yield maps with the maps from three integrated assessment models (IAMs; IMAGE, MAgPIE and GLOBIOM) and found that the median yields in our maps are > 50 % higher than those in the IAM maps.