Spatial distribution of forest aboveground biomass in China: Estimation through combination of spaceborne lidar, optical imagery, and forest inventory data

摘要: Abstract The global forest ecosystem, which acts as a large carbon sink, plays an important role in modeling the balance. An accurate estimation of total stock aboveground biomass (AGB) is therefore necessary for improving our understanding dynamics, especially against background climate change. area China among top five globally. However, because limitations AGB mapping methods and availability ground inventory data, there still lack nationwide wall-to-wall map China. In this study, we collected over 8000 records from published literatures, developed method using combination these Geoscience Laser Altimeter System (GLAS)/Ice, Cloud, Land Elevation Satellite (ICESat) optical imagery, surfaces, topographic data. uncertainty field model was introduced into procedure to minimize influence plot location uncertainty. Our results show that density 120 Mg/ha on average, with standard deviation 61 Mg/ha. Evaluation independent dataset showed proposed can accurately across landscape. adjusted coefficient determination (R2) root-mean-square error between predicted validation were 0.75 42.39 Mg/ha, respectively. This new resulting will help improve accuracy dynamic predictions