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TitleAchieving subpixel georeferencing accuracy in the canadian AVHRR processing system
AuthorKhlopenkov, K V; Trishchenko, A PORCID logo; Luo, Y
SourceIEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers) vol. 48, no. 4, 2010 p. 2150-2161,
Alt SeriesEarth Sciences Sector, Contribution Series 20090140
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Mediapaper; on-line; digital
File formatpdf
Subjectsgeophysics; remote sensing; satellites; satellite imagery; satellite geodesy
Illustrationsplots; images; satellite images
ProgramRemote Sensing Science
Released2010 04 01
AbstractPrecise 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 highquality 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 fromModerate 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 × 4800 km2), covering the entire Canada, the Northern U.S., Alaska, Greenland, and surrounding oceans.

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