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遥感技术与应用  2014, Vol. 29 Issue (1): 155-163    DOI: 10.11873/j.issn.1004-0323.2014.1.0155
图像与数据处理     
低空间分辨率多源遥感数据的空间一致性分析和相对几何校正
赵涌泉1,2,单小军1,唐娉1
(1.中国科学院遥感与数字地球研究所遥感图像处理技术研究室,北京 100101;
2.中国科学院大学,北京 100049)
Spatial Consistency Analysis and Relative Geometric Correction of Low Spatial Resolution Multi\|source Remote Sensing Data
Zhao Yongquan1,2,Shan Xiaojun1,Tang Ping1
(1.Laboratory of Remote Sensing Image Processing Division,Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences,Beijing 100101,China;
2.University of Chinese Academy of Sciences,Beijing 10049,China)
 全文: PDF(1961 KB)  
摘要:

多源低空间分辨率遥感数据在空间上的一致性对于其在全球变化研究中的集成使用有非常重要的意义。对此,以公认几何精度较高的MODIS数据为基准,对NOAA/AVHRR、FY-3/VIRR、FY-3/MERSI、FY-2/VISSR这4类国内外常用的低空间分辨率传感器的L1B数据进行了一系列相对几何精度评价和多项式相对几何校正的实验。相对几何精度评价的结果表明:MODIS数据与这4类L1B数据在几何精度上的偏差都比较大。在此基础上,选取少量均匀分布的控制点并采用不同阶数的多项式几何校正模型对多源数据进行空间一致性校正。校正结果表明:低阶的多项式几何校正模型就能对各种待校正数据的几何精度有显著的提升,使其与基准数据在空间上达到一致,满足全球变化研究对低分辨率多源遥感数据在空间一致性上的需求。

关键词: 多源遥感数据几何精度评价几何校正空间一致    
Abstract:

Low-resolution remote sensing data are kinds of very important data source to global change research,which is with of high temporal resolution and large coverage.However,multi\|source low\|resolution data have their own characteristics,such as geographical coverage,data accumulated time,which could not satisfy the demands of global change research by single low\|resolution data.Therefore,it is necessary to combine multi\|source large\|scale low resolution remote sensing data together being mutually complementary to meet its requirement.It is very necessary to make the multi\|source remote sensing data be consistent with geo\|location firstly,so a series of analysis and experiments of geometric correction was carried out.MOD09A1,as a kind of standard data product with higher accuracy of geo\|location,is used as the base data.Relative geometric accuracy evaluation between the base data and L1B data of NOAA/AVHRR,FY\|3/VIRR,FY\|3/MERSI,FY\|2/VISSR was done respectively.The result shows that the difference in geo\|location between the base data and the L1B data mentioned is significant,which is not good for the combination of them.Meanwhile,multi\|order polynomial geometric correction based on sparse and evenly distributed Ground Control Points(GCPs) of the data mentioned was carried out,since the selection of GCPs on low spatial resolution data was difficult.The result indicates that low\|order polynomial geometric correction could make a remarkable improvement on geometric accuracy of the multi\|source remote sensing data and be consistent in geo\|location with the MODIS base data,which would meet the requirement of the combination of multi\|source remote sensing data in global change research.

Key words: Multi-source remote sensing data    Geometric accuracy evaluation    Geometric correction    Spatial consistency
收稿日期: 2012-12-25 出版日期: 2014-05-14
:  TP 751.1  
基金资助:

国家863计划“地球观测与导航技术领域”技术领域“星机地综合定量遥感系统与应用示范(一期)”项目“多尺度遥感数据按需快速处理与定量遥感产品生成关键技术”课题(2012AA12A304)。

作者简介: 赵涌泉(1988-),男,湖北巴东人,硕士研究生,主要从事遥感数字图像处理的研究。Email:yongquanzhao181@gmail.com
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引用本文:

赵涌泉,单小军,唐娉. 低空间分辨率多源遥感数据的空间一致性分析和相对几何校正[J]. 遥感技术与应用, 2014, 29(1): 155-163.

Zhao Yongquan,Shan Xiaojun,Tang Ping. Spatial Consistency Analysis and Relative Geometric Correction of Low Spatial Resolution Multi\|source Remote Sensing Data. Remote Sensing Technology and Application, 2014, 29(1): 155-163.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2014.1.0155        http://www.rsta.ac.cn/CN/Y2014/V29/I1/155

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