A case for natural colour imagery from geostationary satellites, and an approximation for the GOES-R ABI

‘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.

[1]  C. Yentsch The influence of phytoplankton pigments on the colour of sea water , 1960 .

[2]  D. Wark,et al.  TIROS I OBSERVATIONS OF ICE IN THE GULF OF ST. LAWRENCE , 1960 .

[3]  Gunther Wyszecki,et al.  Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd Edition , 2000 .

[4]  V. Suomi,et al.  a color view of planet Earth , 1968 .

[5]  the first color picture of the Earth taken from the ATS-3 satellite , 1968 .

[6]  G. Paltridge,et al.  Radiative processes in meteorology and climatology , 1976 .

[7]  F. Sabins Remote Sensing: Principles and Interpretation , 1987 .

[8]  H. Gordon,et al.  Clear water radiances for atmospheric correction of coastal zone color scanner imagery. , 1981, Applied optics.

[9]  G. Wyszecki,et al.  Color Science Concepts and Methods , 1982 .

[10]  F. Billmeyer Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed., by Gunter Wyszecki and W. S. Stiles, John Wiley and Sons, New York, 1982, 950 pp. Price: $75.00 , 1983 .

[11]  Peter V. Hobbs,et al.  Airborne measurements of particle and gas emissions from the 1990 volcanic eruptions of Mount Redoubt , 1991 .

[12]  W. Paul Menzel,et al.  Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS) , 1992, IEEE Trans. Geosci. Remote. Sens..

[13]  Y. Kaufman,et al.  Selection of the 1.375-µm MODIS Channel for Remote Sensing of Cirrus Clouds and Stratospheric Aerosols from Space , 1995 .

[14]  M. Kahru,et al.  Ocean Color Chlorophyll Algorithms for SEAWIFS , 1998 .

[15]  F. V. Van Dolah,et al.  Marine Algal Toxins : Origins , Health Effects , and Their Increased Occurrence , 2006 .

[16]  Van Dolah Fm Marine algal toxins: origins, health effects, and their increased occurrence. , 2000 .

[17]  J. Veefkind,et al.  Aerosol optical depth over Europe in August 1997 derived from ATSR‐2 data , 2000 .

[18]  James J. Gurka,et al.  The next generation GOES instruments: status and potential impact , 2001 .

[19]  R. Frouin,et al.  Influence of phytoplankton on the global radiation budget , 2002 .

[20]  A. Gitelson,et al.  Reflectance spectral features and non-destructive estimation of chlorophyll, carotenoid and anthocyanin content in apple fruit , 2003 .

[21]  K. Stamnes,et al.  Accurate and self-consistent ocean color algorithm: simultaneous retrieval of aerosol optical properties and chlorophyll concentrations. , 2003, Applied optics.

[22]  Dariusz Stramski,et al.  Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration , 2003 .

[23]  Mati Kahru,et al.  MODIS detects a devastating algal bloom in Paracas Bay, Peru , 2004 .

[24]  W. Paul Menzel,et al.  INTRODUCING THE NEXT-GENERATION ADVANCED BASELINE IMAGER ON GOES-R , 2005 .

[25]  Paul J. Curran,et al.  MERIS: the re‐branding of an ocean sensor , 2005 .

[26]  Jens Redemann,et al.  Retrieval of Aerosol Scattering and Absorption Properties from Photopolarimetric Observations over the Ocean during the CLAMS Experiment , 2005 .

[27]  David A. Siegel,et al.  Carbon‐based ocean productivity and phytoplankton physiology from space , 2005 .

[28]  R. Krishnan,et al.  A technique for generating natural colour images from false colour composite images , 2006 .

[29]  Arunas P. Kuciauskas,et al.  NexSat: Previewing NPOESS/VIIRS Imagery Capabilities , 2006 .

[30]  J. Ryu,et al.  Satellite detection of harmful algal bloom occurrences in Korean waters , 2006 .

[31]  W. von Hoyningen-Huene,et al.  Influence of land surface effects on MODIS aerosol retrieval using the BAER method over Korea , 2006 .

[32]  Nianzeng Che,et al.  A new method for retrieving band 6 of aqua MODIS , 2006, IEEE Geoscience and Remote Sensing Letters.

[33]  Steven D. Miller,et al.  MODIS provides a satellite focus on Operation Iraqi Freedom , 2006 .

[34]  Mahmood R. Azimi-Sadjadi,et al.  Dual-Satellite Cloud Product Generation Using Temporally Updated Canonical Coordinate Features , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[35]  Rasmus Fensholt,et al.  Remote Sensing , 2008, Encyclopedia of GIS.

[36]  H. John Caulfield,et al.  Hyperspectral image analysis using artificial color , 2010 .

[37]  Steven D. Miller,et al.  A dynamic global cloud layer for virtual globes , 2010 .