‘Natural’ (or ‘true’) colour imagery, so-called for its qualitative likeness to colour photography, is one of the most visually intuitive and readily communicable forms of satellite information. It is constructed by combining solar reflectance measurements from three narrow spectral bands defining the red, green and blue wavelengths of visible light. Natural colour facilitates the interpretation of multiple components in the complex earth/atmosphere scene and, therefore, it is widely used by experts and non-experts alike to visualize many forms of geophysical phenomena. Although sensors on board low-Earth-orbiting (LEO) satellites have long-demonstrated the superior quality of natural colour imagery over various other ‘false colour’ renditions, similar capabilities currently do not exist on sensors operating in geostationary orbits that offer distinct advantages over LEO in terms of high temporal refresh. The Advanced Baseline Imager (ABI) of the next-generation Geostationary Operational Environmental Satellite (GOES)-R series will include the blue and red bands, but is missing the 0.55 μm green band necessary for producing natural colour. The emphases of this article are twofold. First, we consider the merits of natural colour imagery from the standpoints of both science and operational users, and the philosophical roadblocks of a system definition process that seems inherently ill-equipped to consider qualitative user requirements. Second, we present a mitigation strategy for GOES-R ABI that entails synthesizing the missing ABI green band information via its correlation with spectrally adjacent available bands, with a first-order account for surface type dependencies. The technique is developed, demonstrated and evaluated here using Moderate-resolution Imaging Spectroradiometer (MODIS) data.
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Original Articles
A case for natural colour imagery from geostationary satellites, and an approximation for the GOES-R ABI
Steven D. Miller Cooperative Institute for Research in the Atmosphere (CIRA), Colorado State University , Fort Collins , CO , USA Correspondencemiller@cira.colostate.edu, Christopher C. Schmidt Cooperative Institute for Meteorological Satellite Studies (CIMSS), Space Science and Engineering Center (SSEC), University of Wisconsin-Madison , Madison , WI , USA , Timothy J. Schmit Advanced Satellite Products Branch (ASPB), NOAA/NESDIS-STAR , Madison , WI , USA & Donald W. Hillger Regional and Mesoscale Meteorology Branch (RAMMB), NOAA/NESDIS-STAR , Fort Collins , CO , USA
Pages 3999-4028
Received 15 Dec 2010
Accepted 28 Oct 2011
Published online: 13 Dec 2011