Remote sensing data from GOSAT (Greenhouse gases Observing SATellite) and GOSAT-2 in the future ameliorate inversion analysis of greenhouse gas (GHG) emissions, . Meso-scale atmospheric transport model AIST-MM (National Institute of Advanced Industrial Science and Technology-Mesoscale Model),  and global-scale transport model NICAM-TM (Nonhydrostatic ICosahedral Atmospheric Model-Transport Model) have been coupled for data assimilation in order to estimate CO2 emission from mega-city Tokyo. However, forests west and north of Tokyo Metropolis in the Kantō plain generate significant biogenic CO2 fluxes and such atmosphere-biosphere gas exchange remains to be properly calculated during the modeling processes. In this study, we use MODIS products,  to simulate regional gross primary production (GPP), vegetational and soil respirations based on Biosphere model integrating Eco-physiological And Mechanistic approaches using Satellite data (BEAMS) algorithms, . By integrating this atmosphere-terrestrial ecosystem carbon balance module to our regional inversion analysis, we aim at more precise estimation of CO2 emission from Tokyo.