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

doi:10.1016/S1671-2927(11)60156-9

Journal of Integrative Agriculture ›› 2011, Vol. 10 ›› Issue (10): 1595-1602.DOI: 10.1016/S1671-2927(11)60156-9

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

LI Rui, LI Cun-jun, DONG Ying-ying, LIU Feng, WANG Ji-hua, YANG Xiao-dong , PAN Yu-chun

1.Beijing Research Center for Information Technology in Agriculture
2.Information Engineering Institute, Capital Normal University
3.Chengdu Dawan High School

收稿日期:2010-08-27 出版日期:2011-10-01 发布日期:2011-10-18
通讯作者: Correspondence LI Cun-jun, Associate Professor, Tel: +86-10-51503692, Fax: +86-10-51503750, E-mail: licj@nercita.org.cn
基金资助:
This research was supported by the National Natural Science Foundation of China (40701120), the Beijing Natural Science Foundation, China (4092016), and the Beijing Nova, China (2008B33).

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

LI Rui, LI Cun-jun, DONG Ying-ying, LIU Feng, WANG Ji-hua, YANG Xiao-dong , PAN Yu-chun

1.Beijing Research Center for Information Technology in Agriculture
2.Information Engineering Institute, Capital Normal University
3.Chengdu Dawan High School

Received:2010-08-27 Online:2011-10-01 Published:2011-10-18
Contact: Correspondence LI Cun-jun, Associate Professor, Tel: +86-10-51503692, Fax: +86-10-51503750, E-mail: licj@nercita.org.cn
Supported by:
This research was supported by the National Natural Science Foundation of China (40701120), the Beijing Natural Science Foundation, China (4092016), and the Beijing Nova, China (2008B33).

摘要/Abstract

摘要： 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 R2 reached 0.8315. So assimilation remote sensing and crop model could provide reference data for the agricultural production.

关键词: crop model, assimilation, Ensemble Kalman Filter algorithm, leaf area index

Abstract: 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 R2 reached 0.8315. So assimilation remote sensing and crop model could provide reference data for the agricultural production.

Key words: crop model, assimilation, Ensemble Kalman Filter algorithm, leaf area index

LI Rui, LI Cun-jun, DONG Ying-ying, LIU Feng, WANG Ji-hua, YANG Xiao-dong , PAN Yu-chun. Assimilation of Remote Sensing and Crop Model for LAI Estimation Based on Ensemble Kalman Filter[J]. Journal of Integrative Agriculture, 2011, 10(10): 1595-1602.

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

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

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