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We investigated the vulnerability of Chinese forests to fires during the period 2001-2020 by integrating automatic machine learning with fire disturbance data and satellite products. The proposed methodology is purely data-driven and therefore reproducible, applicable at large scales, and in line with the measurement/reporting/verification process of UNFCCC.

Part of pre-processed data, codes of vulnerability models developed in the afore-mentioned work are made publicly available here and briefly described to facilitate reproducibility and applicability.


Study on the Forest Carbon Flux Process Mechanism at the Stand Scale

National Natural Science Foundation of China

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the National Natural Science Foundation of China (grant number 42071305)