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遥感技术与应用  2015, Vol. 30 Issue (4): 694-699    DOI: 10.11873/j.issn.1004-0323.2015.4.0694
图像与数据处理     
利用共线方程的ALOS DEM制作误差分析
范兴旺1,2,刘元波1
(1.中国科学院南京地理与湖泊研究所,江苏 南京 210008;
2.中国科学院大学,北京 100049)
A Study of Spatiotemporal Outlier Detection of Automatic Observing Data based on Time Series Similarity
Fan Xingwang1,2,Liu Yuanbo1
(1.Remote Sensing and Geographic Information Science Laboratory,Cold and Arid Regions
Environmental and Engineering Research Institute CAS,Lanzhou 730000,China;
2.University of Chinese Academy of Sciences,Beijing 100049,China;
3.Heihe Remote Sensing Experimental Research Station,Cold and Arid Region Enrironmental and
Engineering Research Institute,Chinese Academy of Sciences,Lanzou 730000,China)
 全文: PDF(1542 KB)  
摘要:

卫星遥感是获取DEM数据的重要手段,定量化和降低DEM数据误差是应用DEM数据的前提。在共线方程理论的基础上,模拟分析了DEM数据精度与内外方位元素之间的定量关系,以覆盖鄱阳湖地区的ALOS PRISM立体像对为研究数据,根据SRTM数据计算DEM误差,并求解影像内外方位元素误差。研究表明:影像角度误差是影响DEM误差的主要因素。消除角度元素误差后,DEM数据误差的均值由4.4 m降为0.2 m,标准差由7.7 m降为2.7 m。

关键词: DEMSRTMALOS PRISM内方位元素外方位元素    
Abstract:

According to the characteristics of the spatiotemporal data collected by Field Wireless Sensor Network,common spatiotemporal outlier detection methods were summarized,an method regarding time series similarity as spatiotemporal neighborhood was proposed to gain precisely mine outlier information of those spatiotemporal data .This method is verified by observation data acquired by 13 sites of Heihe Watershed Ecological and Hydrological Wireless Sensor Network on July 5th,2012,and the result indicates that anomaly of spatiotemporal data of the wireless sensor network was effectively identified,and several fake anomaly which caused by artificial irrigation and rainstorm were also identified,and this method  is of certain guidance significance for other data processing exploratory studies.

Key words: Spatio-temporal outlier detection    Time series similarity    Spatiotemporal neighborhood    Wireless Sensors Network(WSN)
收稿日期: 2014-03-06 出版日期: 2015-09-22
:  P 236  
基金资助:

国家自然科学基金项目(41430855),国家973计划项目(2012CB417003),中国科学院南京地理与湖泊研究所“一三五”重点项目(NIGLAS2012135001)。

通讯作者: 刘元波(1969-),男,山东济宁人,研究员,主要从事水文遥感研究。Email: ybliu@niglas.ac.cn。    
作者简介: 范兴旺(1989-),男,安徽芜湖人,博士研究生,主要从事水文遥感研究。Email:xwfan1989@163.com。
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引用本文:

范兴旺,刘元波. 利用共线方程的ALOS DEM制作误差分析[J]. 遥感技术与应用, 2015, 30(4): 694-699.

Fan Xingwang,Liu Yuanbo. A Study of Spatiotemporal Outlier Detection of Automatic Observing Data based on Time Series Similarity. Remote Sensing Technology and Application, 2015, 30(4): 694-699.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.4.0694        http://www.rsta.ac.cn/CN/Y2015/V30/I4/694

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