| 英文摘要： |
Quantification of the spatial pattern of forest carbon (C) sinks in high resolution is helpful to reveal the factors that affect the C cycle and provides valuable information for developing sustainable forest management policies. Here we developed a method using the data of long-term forest inventories (1977-2018) and spatially-explicit remotely sensed information from land-use maps and the Normalized Difference Vegetation Index (NDVI) datasets, to estimate the spatial and temporal variation of forest biomass C in China. At first, we calculated forest biomass C stocks using the refined Continuous Biomass Expansion Factor (CBEF) model with parameters for each forest type based on eight national forest inventories. Secondly, based on multi-temporal land-use remote sensing and national forest inventory datasets, we obtained forest coverage datasets with high resolution (1 km*1 km). Thirdly, we downscaled the forest biomass C density using the calibrated forest coverage maps and the maximum NDVI values derived from GIMMS-NDVI3g imagery. Our results showed that China's forest functioned as a C sink of 3777.73 Tg C, and the C density of forest stands increased from 35.41 Mg C ha? 1 during 1977-1981 to 43.95 Mg C ha? 1 during 2014-2018. In addition, the validation results for most of the provinces based on published inventory estimates during the eight periods showed that the forest area at the pixel scale was successfully calibrated. From this, we produced the maps with a finer resolution for a series of spatially continuous forest biomass carbon density distribution and carbon sinks. Notably eight major forest projects have accounted for 44%-51% of the forest C stocks added in China from 1977 to 2018. Our research provides new insights for understanding and monitoring the spatiotemporal variations in of forest biomass and key information to support the development of new afforestation policies moving forward. |
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