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Journal of Applied Remote Sensing • Open Access

Geostationary Operational Environmental Satellite Imager infrared channel-to-channel co-registration characterization algorithm and its implementation in the ground system
Author(s): Zhenping Li; Michael G. Grotenhuis; Xiangqian Wu; Timothy J. Schmit; Christopher C. Schmidt; Anthony J. Schreiner; James P. Nelson; Fangfang Yu; Hyre Bysal

Paper Abstract

Channel-to-channel co-registration is an important performance metric for the Geostationary Operational Environmental Satellite (GOES) Imager, and large co-registration errors can have a significant impact on the reliability of derived products that rely on combinations of multiple infrared (IR) channels. Affected products include the cloud mask, fog and fire detection. This is especially the case for GOES-13, in which the co-registration error between channels 2 (3.9  μm) and 4 (10.7  μm) can be as large as 1 pixel (or ∼4  km) in the east-west direction. The GOES Imager IR channel-to-channel co-registration characterization (GII4C) algorithm is presented, which allows a systematic calculation of the co-registration error between GOES IR channel image pairs. The procedure for determining the co-registration error as a function of time is presented. The algorithm characterizes the co-registration error between corresponding images from two channels by spatially transforming one image using the fast Fourier transformation resampling algorithm and determining the distance of the transformation that yields the maximum correlation in brightness temperature. The GII4C algorithm is an area-based approach which does not depend on a fixed set of control points that may be impacted by the presence of clouds. In fact, clouds are a feature that enhances the correlations. The results presented show very large correlations over the majority of Earth-viewing pixels, with stable algorithm results. Verification of the algorithm output is discussed, and a global spatial-spectral gradient asymmetry parameter is defined. The results show that the spatial-spectral gradient asymmetry is strongly correlated to the co-registration error and can be an effective global metric for the quality of the channel-to-channel co-registration characterization algorithm. Implementation of the algorithm in the GOES ground system is presented. This includes an offline component to determine the time dependence of the co-registration errors and a real-time component to correct the co-registration errors based on the inputs from the offline component.

Paper Details

Date Published: 6 November 2014
PDF: 17 pages
J. Appl. Remote Sens. 8(1) 083530 doi: 10.1117/1.JRS.8.083530
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Zhenping Li, ASRC Federal Holding, Co. (United States)
Michael G. Grotenhuis, National Oceanic and Atmospheric Administration (United States)
Xiangqian Wu, National Oceanic and Atmospheric Administration (United States)
Timothy J. Schmit, NOAA National Environmental Satellite, Data, and Information Service (United States)
Christopher C. Schmidt, Univ. of Wisconsin-Madison (United States)
Anthony J. Schreiner, Univ. of Wisconsin-Madison (United States)
James P. Nelson, Univ. of Wisconsin-Madison (United States)
Fangfang Yu, ERT, Inc. (United States)
Hyre Bysal, National Environmental Satellite, Data, and Information Service (United States)


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