Abstract:Leaf area index (LAI) is an important parameter to characterize the canopy characteristics. It has significant influence on ecosystem carbon cycle researches since its critical factor to determine ecosystem net primary productivity. The large scale leaf area index can be obtained by both remote sensing reversion and ecosystem modeling though uncertainties exist in the two methods. The atmosphere-vegetation interaction model (AVIM2) was used in this study to generate China-wide leaf area index at the resolution of 0.1 grid degree. The spatial distribution and seasonal cycles of model-generated LAI were compared with two datasets. One is satellite-derived LAI which was deduced by Myneni (1997) based on the physical principles of radiative transfer in vegetation and atmosphere. The other was deduced by Hagemann (2002) based on Advanced Very High Resoulution Radiometer (AVHRR) dataset by using heuristic corrective method. Hagemann′s dataset has being wildly used in general circulation models (GCMs). The comparison shows that the spatial distribution of China′s vegetation LAI is mainly restricted by water conditions, which appears an overall trend of high in southeast and low in northwest. The seasonal cycle of China′s LAI is closely correlated with the monsoon′s movement in a year. It is identical with seasonal variation trends of temperature and surface solar radiation. The seasonal cycle of LAI in China-wide appears a trend of high in summer, moderate in spring and autumn and low in winter.