Abstract
Monitoring aboveground biomass carbon (AGC) stocks and their changes is crucial for understanding the global carbon cycle and the impact of climate change. Among remotely sensed methods, the use of the L-band (1.4 GHz) vegetation optical depth (L-VOD) derived from passive microwave satellite observations, offers rapid updates for timely monitoring of interannual AGC changes. L-VOD is sensitive to changes in the total water content of vegetation, which is determined by both AGC (the biomass of vegetation) and vegetation moisture content. While several methods have been used to understand and correct for the influence of the latter parameter when inferring AGC from L-VOD, there is still a lack of quantified corrections for its impact. Moreover, varying benchmark biomass datasets and fitting functions are currently used for converting L-VOD to AGC, making it difficult to harmonize or compare AGC estimates at regional and global scales. To address these issues, we first corrected the L-VOD time series for changes in the vegetation moisture content and then implemented a systematic global-scale calibration, resulting in annual AGC data set (called INRAE-BORDEAUX AGC, hereafter IB AGC) from 2010 to 2020 at a 25 km resolution. The accuracy assessments showed that IB AGC had a reasonably good spatial agreement with LiDAR referenced AGC data (R(2) = 0.60). Moreover, when aggregated at the national level, IB AGC exhibited stronger consistency with long-term net changes from country-level forest inventory data (R(2) = 0.62) than other mainstream satellite products. It is expected that IB AGC will provide an independent means for better monitoring the global vegetation carbon stocks and their variability in response to climate change.