  Forests of the Earth are a vital carbon sink while providing an essential
habitat for biodiversity. Vegetation productivity (VP) is a critical indicator
of carbon uptake in the atmosphere. The leaf area index is a crucial vegetation
index used in VP estimation. This work proposes to predict the leaf area index
(LAI) using climate variables to better understand future productivity
dynamics; our approach leverages the capacities of the V-Net architecture for
spatiotemporal LAI prediction. Preliminary results are well-aligned with
established quality standards of LAI products estimated from Earth observation
data. We hope that this work serves as a robust foundation for subsequent
research endeavours, particularly for the incorporation of prediction
attribution methodologies, which hold promise for elucidating the underlying
climate change drivers of global vegetation productivity.
