Improvement accuracy of terrestrial NPP estimation using ADEOS-II/GLI data

研究ノート(note)Ecosystem process model and remote sensing is useful for estimate Net Primary Production (NPP). This research will study to improve accuracy of terrestrial NPP estimation using ADEOS-II/GLI data as input towards Global Climate Observation Mission and carry Second generation Global Imager (GCOM-C/SGLI) that will be launched in near future. Fluxes data from FluxNet network were used to improve NPP estimation algorithms from stand scale up to regional and global estimates. Firstly, Gross Primary Production (GPP) was estimated from flux Net Ecosystem Exchange (NEE) data by analyze GPP and PAR relationship. GPP is expected to be a function of PAR. In this study the relation ship is exponential (rectangular hyperbola) the maximum GPP (Pmax) at light saturation and slope to understand the photosynthesis capability be found. In next step, ADEOS-II/GLI data vegetation condition and meteorological variable will be utilized for NPP estimation as well