Remote discrimination of clouds using a neural network

Stephen R. Yool; M. Brandley; C. Kern; Frank W. Gerlach; Ken L. Rhodes

doi:10.1117/12.130885

16 December 1992 Remote discrimination of clouds using a neural network

Stephen R. Yool, M. Brandley, C. Kern, Frank W. Gerlach, Ken L. Rhodes

Proceedings Volume 1766, Neural and Stochastic Methods in Image and Signal Processing; (1992) https://doi.org/10.1117/12.130885
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

Cloud classification is a key input to global climate models. Cloud spectra are typically mixed, however, thus difficult to classify using the maximum likelihood rule. In contrast to maximum likelihood, a densely interconnected, trained neural network can form powerful generalizations that distinguish unique statistical trends among otherwise ambiguous spectral response patterns. Accordingly, cloud classification accuracies produced by a neural network can exceed accuracies produced using the maximum likelihood criterion.

Citation Download Citation

Stephen R. Yool, M. Brandley, C. Kern, Frank W. Gerlach, and Ken L. Rhodes "Remote discrimination of clouds using a neural network", Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); https://doi.org/10.1117/12.130885

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