Northeast China is one of the regions most sensitive to global changes. This paper uses Net Primary Productivity (NPP)to monitor environment changes of this area. Three typical study areas located in east, middle and west of the Northeast China were chosen. Based on the Carnegie-Ames-Stanford Approach(CASA)model, the Landsat TM data in two phases(2007 and 2010)and the meteorological observation data were employed to retrieve NPP. Consequently, the spatial distribution of NPP was analyzed. The results show that the NPP of three study areas fluctuates in two phases. As farmland and meadow area are larger in the western and central regions, NPP is significantly affected by seasons and human activities. On the other hand, as forests in the eastern area have a wide coverage, NPP is mainly influenced by seasons and hydrothermal conditions. Compare to the central and southern, the NPP of eastern area is higher. This paper combined multi-temporal remote sensing data with models, providing scientific bases for estimating regional NPP and researches on the dynamic changes of carbon storage.