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遥感技术与应用  2016, Vol. 31 Issue (5): 939-949    DOI: 10.11873/j.issn.1004-0323.2016.5.0939
数据与图像处理     
东中国海遥感叶绿素数据重构方法研究
郭俊如1,5,宋军2,6,鲍献文3,李静2,4
(1.国家海洋局海洋减灾中心,北京 100194;2.国家海洋信息中心,天津 300171;
3.中国海洋大学,海洋与大气学院,山东 青岛 266100;4.上海海洋大学,海洋科学学院,上海 201306;
5.国家海洋局空间海洋遥感与应用研究重点实验室,北京 10081;
6.中国海洋大学 教育部物理海洋学重点实验室,山东 青岛 266100)
The Method Study of Remote Sensing Data Reconstruction in Multi-scale Variations of Chlorophyll in East China Sea
Guo Junru1,5,Song Jun2,6,Bao Xianwen3,Li Jing4,2
(1.National Marine Hazard Mitigation Service,Beijing 100194,China;
2.National Marine Data & Information Service,Tianjin 300171,China;
3.Ocean University of China,college of Marine and Atmospheric Sciences 266100,China;
4.Shanghai Ocean University,college of Marine Sciences,Shanghai 201306,China;
5.Key Laboratory of Space Ocean Remote Sensing and Applications,Beijing 100081,China;
6.Ocean University of China,Key Laboratory of Physical Oceanography,Qingdao 266100,China)
 全文: PDF(6522 KB)  
摘要:

由于天气等各种因素,卫星遥感叶绿素数据中的大面积无规律缺失问题一直是遥感数据领域的研究热点,阻碍了卫星数据的应用。因此,卫星遥感数据的重构和再分析成为一个重要课题,在关注海域获得时空连续的完整数据对于扩展遥感数据的应用范围,提高其数据利用效率有着重要意义。针对这一系列问题,基于对东中国海叶绿素时空多尺度(包括天气过程时间尺度)变化机制研究的需要,结合多变量DINEOF方法和最优插值等数学方法的优点,成功构建和发展了多尺度最优插值、二次订正的多变量DINEOF方法,简称DINEOF-OI方法。对于目标缺测数据点重构过程中,如何有效分配时间序列上与空间场中的观测数据对重构数据的影响权重,取决于研究的具体目标问题,是研究的重要思路创新。基于这一方法对东中国海近10 a的卫星遥感叶绿素数据成功进行了重构试验,并较成功地刻画了东中国海海表面叶绿素的包括天气尺度在内的多尺度变化特征。


 

关键词: 卫星遥感;DINEOF\OI;叶绿素;生态动力学;东中国海    
Abstract:

Due to the aerosol and other reasons,large area of remote-sensing chlorophyll data are often missing,which hinders its development,and also becomes a hot topic in this field.Therefore,to retrieve the long\|term synchronous data,the re\|constructure and re\|analysis of remote-sensing data is called for.This can extend the application of remote-sensing data,and improve its utilization efficiency.In this study,combining the advantages of the DINEOF method and the Optimal Interpolation (OI),an algorithm (DINEOF-OI) with multi\|variables and second\|order\|correction has been developed to study the variable chlorophyll distribution in multi scales including weather-process scales in the East China Sea (ECS).This paper introduces how to locate the influencing weights of observed data on re-constructed data in temporal and spatial series.based on the algorithm developed in this paper,the recent decadal chlorophyll data in the ECS has been re-constructed and analysed.It indicates the re-constructed database can describe the primary characteristics of chlorophyll distribution in the ECS in multi\|scale processes.

 

Key words: Satellite-oceanic remote sensing;DINEOF\    OI;Chlorophyll;Marine ecosystem dynamics;East China sea
收稿日期: 2015-11-05 出版日期: 2016-11-25
:  TP 75  
基金资助:

国家海洋局空间海洋遥感与应用研究重点实验室开放基金重点课题(201601003),国家自然科学基金项目(41206013、41376014、41430963、41206004),教育部物理海洋重点实验室开放基金,2011年度高等学校博士学科点专项科研基金(20110132130001),海洋公益性行业科研专项(201205018、201005019),国家科技支撑计划项目(2014BAB12B02),天津市科技支撑计划项目(14ZCZDSF00012),国家海洋局青年科学基金重点项目(2012202、2013203、2012223),国家建设高水平大学公派研究生项目(留金出-2008-3019、2012-2013)资助。

通讯作者: 宋军(1983-),男,山东滨州人,博士研究生,主要从事近海动力学、业务化海洋学方面的研究。Email:thunder098@hotmail.com。   
作者简介: 郭俊如(1986-),女,辽宁营口人,博士研究生,主要从事近海动力学、海洋灾害方面的研究。Email:447907545@qq.com。
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引用本文:

郭俊如,宋军,鲍献文,李静. 东中国海遥感叶绿素数据重构方法研究[J]. 遥感技术与应用, 2016, 31(5): 939-949.

Guo Junru,Song Jun,Bao Xianwen,Li Jing. The Method Study of Remote Sensing Data Reconstruction in Multi-scale Variations of Chlorophyll in East China Sea. Remote Sensing Technology and Application, 2016, 31(5): 939-949.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2016.5.0939        http://www.rsta.ac.cn/CN/Y2016/V31/I5/939

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