Forest disturbances are key drivers of dynamic changes in the terrestrial carbon cycle, and the resulting changes in carbon sources and sinks have significant impacts on the global carbon budget. This paper provides a systematic review of methods for annual carbon accounting of forest disturbances, including both ground survey and remote sensing methods. It elaborates on recent technical advances in several key aspects such as forest disturbance classification, detection, intensity assessment, carbon loss estimation, restoration process simulation, and uncertainty analysis. The paper focuses on research that employs satellite remote sensing data to estimate the annual carbon budget associated with forest disturbances. This includes a grid-based carbon estimation model (GCA) developed using remote sensing data; annual assessment of wood product outputs and relevant carbon flow integrating ground survey and remote sensing data; and an improved grid carbon estimation model that incorporates annual wood product outputs. The continuous research efforts enable assessments of carbon sources or sinks resulted from forest disturbances at the grid scale by integrating remote sensing and ground survey data. Overall, the paper systematically reviews the progress in annual carbon accounting methods for forest disturbances based on remote sensing technology and highlights the collaborative innovation of remote sensing grid models and ground survey data as a key pathway to improving carbon measurement accuracy.
Gong et al. (Wed,) studied this question.