GeoColor: A Blending Technique for Satellite Imagery

Abstract

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 01, 2020
Source ID
10.1175/jtech-d-19-0134.1

Entities

People

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

Organizations

  • Colorado State University
  • National Oceanic and Atmospheric Administration
  • Office of Naval Research
  • United States Naval Research Laboratory

Tags

Fields of Study

  • Environmental science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.

Technology Areas

  • Space