Assimilation of Remote Sensing and Crop Model for LAI Estimation Based on Ensemble Kalman Filter

作者：Li Rui; Li Cun-jun^*; Dong Ying-ying; Liu Feng; Wang Ji-hua; Yang Xiao-dong; Pan Yu-chun

来源：Agricultural Sciences in China, 2011, 10(10): 1595-1602.

DOI：10.1016/S1671-2927(11)60156-9

• crop model
• assimilation
• Ensemble Kalman Filter algorithm
• leaf area index

Data assimilation in agricultural remote sensing research is of great significance to integrate with remote sensing observations and model simulations for parameters estimation. The present investigation not only designed and realized the Ensemble Kalman Filtering algorithm (EnKF) assimilation by combing the crop growth model (CERES-Wheat) with remote sensing data, but also optimized and updated the key parameters (LAI) of winter wheat by using remote sensing data. Results showed that the assimilation LAI and the observation ones agreed with each other, and the R-2 reached 0.8315. So assimilation remote sensing and crop model could provide reference data for the agricultural production.

• 出版日期2011-10-20
• 单位首都师范大学; 中国人民解放军信息工程大学