In the previous study, Arakida et al. developed a data assimilation system with a dynamical global vegetation model known as the SEIB-DGVM (Spatially Explicit Individual-Based Dynamic Global Vegetation Model), and assimilated satellite-observed Leaf Area Index (LAI) successfully at one of the AsiaFlux sites in Siberia. In this study, we expand the study area to a large domain in Eastern Siberia to investigate the performance of the DA system. We estimated the state variables including carbon flux, water flux, heat flux, vegetation structure, and parameters related to the phenology of the deciduous needle leaved tree and grass. The results showed that the DA system performed well at the large domain.