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Characteristic vector analysis as a technique for signature extraction of remote ocean color dataCharacteristic vector analysis is being used to extract spectral signatures of suspended matter in the ocean from remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor), a multispectral scanner. Spectral signatures appear to be obtainable either directly from characteristic vectors or through a transformation of these eigenvectors. Quantification of the suspended matter associated with each resulting signature seems feasible using associated coefficients generated by the technique. This paper presents eigenvectors associated with algae, 'sediment', acid waste, sewage sludge, and oil. The results suggest an efficient method of transmitting from satellites multispectral data of pollution in our oceans.
Document ID
19780050950
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Grew, G. W.
(NASA Langley Research Center Hampton, Va., United States)
Date Acquired
August 9, 2013
Publication Date
January 1, 1977
Subject Category
Environment Pollution
Meeting Information
Meeting: Annual Remote Sensing of Earth Resources Conference
Location: Tullahoma, TN
Start Date: March 29, 1977
End Date: March 31, 1977
Accession Number
78A34859
Distribution Limits
Public
Copyright
Other

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