Assimilation of ground measured wheat leaf area index into CERES-Wheat model based on Kalman Filter

被引：0
|
作者：
Liu X. [1 ]
Liu C. [1 ]
Wang P. [1 ]
Xing Y. [1 ]
机构：
[1] College of Information and Electrical Engineering, China Agricultural University
来源：
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | 2010年 / 26卷 / SUPPL. 1期
关键词：
Assimilation algorithm; Kalman Filter; Models; Monitoring; Remote sensing;
D O I：
10.3969/j.issn.1002-6819.2010.z1.033
中图分类号：
学科分类号：
摘要：
An approach of assimilating ground measured leaf area index (LAI) into the CERES-Wheat model was developed in this paper. The CERES-Wheat model was used to simulate LAI under the Decision Support System for Agro-Technology Transfer (DSSAT) shell. Interpolation methods were used to solve the matching problem of the time scale between dynamic LAI simulated by the CERES-Wheat model and discrete LAI observed on ground. By comparisons, the interpolated LAIs by using cubic interpolation method based on measured LAI data were better than those of using the nearest neighbor interpolation, linear interpolation and cubic spline interpolation methods, respectively, which were assimilated by using Kalman Filter later. The experimental results showed that combination of the interpolation method and the Kalman Filter algorithm had stable and usable results. Assimilation results of LAI are close to their simulated and measured ones, which are better than the LAI data simulated by the model alone.
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收藏
页码：176 / 181
页数：5
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