Assimilating Earth Observation Data into a Vegetation Model using an Ensemble Kalman Filter

机译：使用集成卡尔曼滤波器将地球观测数据吸收到植被模型中

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This paper describes the assimilation of data from Earth Observation satellites into a simple ecosystem model. An Ensemble Kalman Filter is used to assimilate both a satellite derived product (LAI) and NDVI measurements from the AVHRR FASIR time series. Results show that the assimilation of satellite data improves estimates of Net Ecosystem Productivity from the model.

机译：本文描述了将来自地球观测卫星的数据同化为简单的生态系统模型。集成卡尔曼滤波器用于同化来自AVHRR FASIR时间序列的卫星衍生产品（LAI）和NDVI测量。结果表明，对卫星数据的同化改进了该模型对净生态系统生产率的估计。

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《ISPRS vol.36 pt.7/W20; International Symposium on Physical Measurements and Signatures in Remote Sensing pt.1; 20051017-19; Beijing(CN)》|2005年|P.399-401|共3页
会议地点 Beijing(CN)
作者
T. Quaife; P. Lewis; M. Williams; M. Disney; M. De Kauwe;
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Centre for Terrestrial Carbon Dynamics, and UCL;

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原文格式 PDF
正文语种 eng
中图分类摄影测量学与测绘遥感;
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机译：将测高数据同化为HYCOM太平洋模型：集合最优插值与集合卡尔曼滤波器
2. Skill-assessments of statistical and Ensemble Kalman Filter data assimilative analyses using surface and deep observations in the Gulf of Mexico [J] . Zhibin SUN, Lie-Yauw OEY, Yi-Hui ZHOU Frontiers of earth science . 2013,第3期

机译：使用墨西哥湾的地表和深层观测进行统计和集合卡尔曼滤波数据同化分析的技能评估
3. Skill-assessments of statistical and Ensemble Kalman Filter data assimilative analyses using surface and deep observations in the Gulf of Mexico [J] . Zhibin SUN, Lie-Yauw OEY, Yi-Hui ZHOU 地球科学前沿：英文版 . 2013,第003期

机译：使用地面和深层观测在墨西哥湾进行统计和集合卡尔曼滤波数据同化分析的技能评估
4. Assimilating Earth Observation Data into a Vegetation Model using an Ensemble Kalman Filter [C] . . 2005

机译：使用集成卡尔曼滤波器将地球观测数据吸收到植被模型中
5. Assimilating satellite observations with a local ensemble Kalman filter. [D] . Fertig, Elana Judith. 2007

机译：用局部集合卡尔曼滤波器将卫星观测同化。
6. Ensemble Learning Approach via a Kalman Filtered Markov Model for a Passive Wearable Respiratory Monitor [O] . Sayandeep Acharya, William M. Mongan, Ilhaan Rasheed, -1

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7. Using Ensemble Kalman Filters to Assimilate Dynamic Ocean Topography Data into a Global Ocean Model [O] . Nerger Lars 2013

机译：利用集合卡尔曼滤波器将动态海洋地形数据同化为全球海洋模型

Assimilating Earth Observation Data into a Vegetation Model using an Ensemble Kalman Filter

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