Leaf Area Index（ LAI） is an important land surface parameter in global carbon cycle studies. Over the past decades

v arious of algorithms for retrieving LAI from satellite data have been developed. However

the continuity of LAI time series is still need to be improved. In this study

we present an algorithm for retrieving LAI dynamics based on the framework of Dual ensemble Kalman Filter（ Dual EnKF）

which updates the estimation of LAI and its sensitive parameters in a dynamic model

and gets optimal results simultaneously. The Dual EnKF algorithm can get better estimation results of the dynamic model

and assimilates remote sensing data into the dynamic model to get optimal estimation results of LAI. Three sites with the land cover of cropland

grassland

and forest are employed to validate this algorithm. The validation results show that the LAI temporal profile estimated by D ual EnKF method is very continuous with less fluctuations and abrupt change points; the estimation results of temporal dynamic model is improved

even when high quality remote sensing data is not available. LAI time series is in good agreement with the r ealistic LAI climatology.