采用DBM方法的时间序列LAI建模与估算

A data-based mechanistic approach to time-series LAI modeling and estimation

运用DBM(Data Based Mechanistic)方法,使用MODIS数据,建立了遥感观测反射率数据与叶面积指数(LAI)在时间序列上的统计关系模型(LAI_DBM模型),并结合部分Bigfoot站点实测LAI数据进行了模型检验。结果显示,LAI_DBM模型能够较好表达时间序列反射率与LAI的动态变化关系。LAI_DBM模型使用遥感观测数据实时估算得到的LAI,在数据质量和时间连续性上比MODISLAI有改进。

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 reflectance and LAI. The LAI estimated by LAI_DBM model is better than MODIS LAI in terms of data quality and continuity.