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A Footprint-Aware, High-Resolution Approach for Carbon Flux Prediction Across Diverse Ecosystems

Searcy, Jacob et al.
arXiv (All) · Papers
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machine-learning
Eddy-covariance (EC) flux towers provide in situ measurements of $CO_2$ flux and serve as the ground-truth data for predictive `upscaling' models derived from satellite products. However, many satellites now resolve spatial scales smaller than an EC tower's footprint. We show theoretically that upsc
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