A data-based mechanistic approach to time-series LAI modeling and estimation
采用DBM方法的时间序列LAI建模与估算

A data-based mechanistic (DBM) modeling approach is used to model the statistical relationship between time-series reflectance and leaf area index (LAI). This relationship model is referred to as LAI_DBM model. Moderate Resolution Imaging Spectroradiometer (MODIS) data products are utilized as example data to implement DBM modeling and validation. LAI field measurements from the Bigfoot project were used to further validate LAI_DBM model. The results show that LAI_DBM model provid a very good explanation of the relationship between time-series refl ectance and LAI. The LAI estimated by LAI_DBM model is better than MODIS LAI in terms of data quality and continuity.