Use of data assimilation technique for improveing the retrieval of leaf area index in time-series in alpine wetlands

Leaf area index (LAI) is one of the key vegetation indices for many biological and physical processes in plant canopies. In this study, an assimilation technique was used to simulate the LAI´s varying in time series in an alpine wetland located in western China. The Terra MODIS 16 day composite surface reflectance products at 250 m resolution in 2010 with high quality were used. LAI was retrieved based on the ACRM canopy reflectance model and LUT algorithm. An experiential LOGISTIC model was fitted using the retrieved LAI, and the ensemble Kalman filter algorithm was introduced to assimilate the estimated LAI into the LOGISTIC model to update the model state.