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>Limited inventory plots and infrequent remeasurement periods, particularly in tropical forests but also in many temperate forests, make it difficult to estimate the timing and location of biomass recovery after disturbance
>Yet projecting forest growth is fundamental to our understanding of the global forest carbon sink
>Combining inventory plots, Earth Observation data and machine learning models can help
> Research on this topic is emerging rapidly, with various groups exploring these methods for different regions and scales.
Our assets are
1. Global forest inventory data and the network of data owners;
2. Our experience in coordinating and harmonizing global forest inventory data;
3. Prototype AI-based forest carbon dynamics model is ready;
4. Purdue’s new Anvil Cluster meets our needs for high-performance computing
5. Science-i facilitates real-time large-team collaboration.