  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.

Atmospheric and Oceanic Physics;Geophysics