Classification of merged AVHRR and SMMR Arctic data with neural networks

A forward-feed back-propagation neural network is used to classify merged AVHRR and SMMR summer Arctic data. Four surface and eight cloud classes are identified. Partial memberships of each pixel to each class are examined for spectral ambiguities. Classification results are compared to manual inter...

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Bibliographic Details
Main Authors: Key, J., Maslanik, J. A., Schweiger, A. J.
Format: Other/Unknown Material
Language:unknown
Published: 1989
Subjects:
42
Arctic
Online Access:http://ntrs.nasa.gov/search.jsp?R=19890066417
Description
Summary:A forward-feed back-propagation neural network is used to classify merged AVHRR and SMMR summer Arctic data. Four surface and eight cloud classes are identified. Partial memberships of each pixel to each class are examined for spectral ambiguities. Classification results are compared to manual interpretations and to those determined by a supervised maximum likelihood procedure. Results indicate that a neural network approach offers advantages in ease of use, interpretability, and utility for indistinct and time-variant spectral classes.

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