GeoColor: A Blending Technique for Satellite Imagery

Miller, Steven D.; Lindsey, Daniel T.; Seaman, Curtis J.; Solbrig, Jeremy E.

doi:10.1175/JTECH-D-19-0134.1

i

GeoColor: A Blending Technique for Satellite Imagery

2020
By Miller, Steven D. ; Lindsey, Daniel T. ; Seaman, Curtis J. ; ...

Details

Journal Title:

Journal of Atmospheric and Oceanic Technology
Personal Author:

Miller, Steven D. ; Lindsey, Daniel T. ; Seaman, Curtis J. ; Solbrig, Jeremy E.
NOAA Program & Office:

CIRA (Cooperative Institute for Research in the Atmosphere) ; NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research)
Description:

Value-added imagery is a useful means of communicating multispectral environmental satellite radiometer data to the human analyst. The most effective techniques strike a balance between science and art. The science side requires engineering physical algorithms capable of distilling the complex scene into a reduced set of key parameters. The artistic side involves design and construction of visually intuitive displays that maximize information content within the product image. The utility of such imagery to human analysts depends on the extent to which parameters or features of interest are conveyed unambiguously. Here, we detail and demonstrate a dynamic blended imagery technique, based on spatially variant transparency factors whose values are tied to algorithmically isolated parameters. The technique enables seamless display of multivariate information, and is applicable to any imaging system based on red–green–blue composites. We illustrate this technique in the context of GeoColor—an application of the Geostationary Operational Environmental Satellite R (GOES-R) series Advanced Baseline Imager (ABI) supporting operational forecasting and used widely in public communication of weather information.
Keywords:

Clouds Dust Storms Satellite Observations Dust Storms Satellite Observations
Source:

Journal of Atmospheric and Oceanic Technology, 37(3), 429-448.
DOI:

https://doi.org/10.1175/JTECH-D-19-0134.1
Document Type:

Journal Article
Rights Information:

CC BY
Compliance:

Submitted
Main Document Checksum:

urn:sha256:25eed56b634dc4d08592e565e0fae9ae2e093a2e001a044cd6ba19d64125e307
Download URL:

https://repository.library.noaa.gov/view/noaa/30693/noaa_30693_DS1.pdf
File Type:

[PDF - 3.40 MB ]

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