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遥感技术与应用
数据同化专栏     
关键物候期遥感数据缺失条件下的数据同化研究
王一明1,2,蒙继华1,程志强1
(1.中国科学院遥感与数字地球研究所数字地球重点实验室,北京 100101 2.中国科学院大学,北京 100049;).
Data Assimilation Experiment ofPoor Quality of RemoteSensing Image in Critical Phenology
Wang Yiming1,2,Meng Jihua1,Cheng Zhiqiang1
(1.Key Laboratory of Digital Earth Science,Institute of Remote Sensing and DigitalEarth Chinese Academy of Sciences,Beijing 100101,China; 2.University of Chinese Academy of Sciences,Beijing 100049,China)
 全文: PDF(7004 KB)  
摘要: 随着数据同化方法的不断发展,数据同化已被广泛应用于遥感数据与作物生长模型的结合之中,但在关键物候期遥感数据缺失条件下的同化方法还有待加强研究。以黑龙江省红星农场为研究区,以玉米为研究对象,利用遥感数据与WOFOST模型开展同化方法研究。结果表明:经改进后的集合卡尔曼滤波算法同化,明显改善了误差较大的遥感影像对叶面积指数时序曲线的影响,同时减弱了曲线的锯齿状波动;在田块尺度上,和原始算法同化产量结果相比,R2提高到0.67,RMSE减少到92.23  kg/hm2;在农场尺度上,R2提高至0.61,RMSE减少至122.44  kg/hm2。
关键词: 遥感数据缺失调节因子膨胀系数作物生长模型集合卡尔曼滤波同化    
Abstract: In the process of data assimilation,influenced by the water vapor and cloud cover in the study area,the qualities of remote sensing images are poor in the key crop phenological phases.This will cause not to get the perfect remote sensing images for a long time.So we try to solve this problem by using an improved EnKF method to assimilate the WOFOST crop growth model and the terrible quality of remote sensing images to forecast the maize’s yield in the Red Star Farm in Heilongjiang province.In order to improve the accuracy of simulated time series curve of the LAI and yield production results,the consideration on quality evaluation of the remote sensing images is introduced by using expansion coefficient and adjustable factor.The results shows based on the improved EnKF method,time series curve of the LAI keeps a normal tendency of LAI rather than negative fluctuations,and it also avoids the serrated fluctuation to a certain extent.In addition,compared with the original EnKF method,in the field level R2 can increased to 0.67 from 0.59,RMSE is reduced to 92.23 kg/hm2 from 240.57 kg/hm2 and in the farm level R2 can increased to 0.61 from 0.52,RMSE is reduced to 122.44 kg/hm2 from 310.94 kg/hm2 between simulated yield and measured yield.
Key words: Lack of remote sensing data    Coefficient of Expansion    Adjustable factor    Crop growth model    Assimilation by EnKF
收稿日期: 2016-10-24 出版日期: 2017-09-13
:  TP 75  
基金资助: 国家863计划项目“典型应用领域全球定量遥感产品生产体系”(2013AA12A302),中国科学院科技服务网络计划(STS)项目(KFJ\|EW\|STS\|069)。

作者简介: 王一明(1992-),男,吉林大安人,硕士研究生,主要从事遥感数据同化研究。Email:wangyiming19920404@163.com。
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引用本文:

王一明,蒙继华,程志强. 关键物候期遥感数据缺失条件下的数据同化研究[J]. 遥感技术与应用, 10.11873/j.issn.1004-0323.2017.4.0615.

Wang Yiming,Meng Jihua,Cheng Zhiqiang. Data Assimilation Experiment ofPoor Quality of RemoteSensing Image in Critical Phenology. Remote Sensing Technology and Application, 10.11873/j.issn.1004-0323.2017.4.0615.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2017.4.0615        http://www.rsta.ac.cn/CN/Y2017/V32/I4/615

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