Thanks for joining our project and welcome aboard! Please pay attention to the following items:
1. Please keep all contents in this project confidential;
2. Go to Docs for existing write-ups and documents;
3. Go to Documents for PDF files related to this project;
4. Go to Discussions to view existing discussion topics and/or create a new topic;
5. Go to Polls (if available) for ongoing polls and doodle schedulers.
Problem statement
>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.