Achieving Subpixel Georeferencing Accuracy in the Canadian AVHRR Processing System

被引:48
作者
Khlopenkov, Konstantin V. [1 ]
Trishchenko, Alexander P. [1 ]
Luo, Yi [2 ]
机构
[1] Nat Resources Canada, Canada Ctr Remote Sensing, Earth Sci Sector, Ottawa, ON K1A 0Y7, Canada
[2] Environm Canada, Canadian Ice Serv, Ottawa, ON K1A 0H3, Canada
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2010年 / 48卷 / 04期
关键词
Advanced Very High Resolution Radiometer (AVHRR); climate data records; image matching; image registration; orthorectification; satellite applications; IMAGE NAVIGATION; ARTIFICIAL SATELLITE; AUTOMATIC NAVIGATION; MODIS; RESOLUTION; SCHEME; ARGOS; CLOUD;
D O I
10.1109/TGRS.2009.2034974
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Precise geolocation is one of the fundamental requirements for satellite imagery to be suitable for climate applications. The Global Climate Observing System and the Committee on Earth Observing Satellites identified the requirement for the accuracy of geolocation of satellite data for climate applications as 1/3 field of view (FOV). This requirement for the series of the Advanced Very High Resolution Radiometer (AVHRR) on the National Oceanic and Atmospheric Administration platforms cannot be met without implementing the ground control point (GCP) correction, particularly for historical data, because of limited accuracy of orbit modeling and knowledge of satellite attitude angles. This paper presents a new method for precise georeferencing of the AVHRR imagery developed as part of the new Canadian AVHRR processing system (CAPS) designed for generating high-quality AVHRR satellite climate data record at 1-km spatial resolution. The method works in swath projection and uses the following: 1) the reference monthly images from Moderate Resolution Imaging Spectroradiometer at 250-m resolution; 2) orthorectification to correct for surface elevation; and 3) a novel image matching technique in swath projection to achieve the subpixel resolution. The method is designed for processing daytime data as it intensively employs observations from optical solar bands, the near-infrared channel in particular. The application of the developed processing system showed that the algorithm achieved better than 1/3 FOV geolocation accuracy for AVHRR 1-km scenes. It has very high efficiency rate (> 97%) due to the dense and uniform GCP coverage of the study area (5700 x 4800 km(2)), covering the entire Canada, the Northern U.S., Alaska, Greenland, and surrounding oceans.
引用
收藏
页码:2150 / 2161
页数:12
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