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Multispectral system analysis through modeling and simulationThe design and development of multispectral remote sensor systems and associated information extraction techniques should be optimized under the physical and economic constraints encountered and yet be effective over a wide range of scene and environmental conditions. Direct measurement of the full range of conditions to be encountered can be difficult, time consuming, and costly. Simulation of multispectral data by modeling scene, atmosphere, sensor, and data classifier characteristics is set forth as a viable alternative, particularly when coupled with limited sets of empirical measurements. A multispectral system modeling capability is described. Use of the model is illustrated for several applications - interpretation of remotely sensed data from agricultural and forest scenes, evaluating atmospheric effects in Landsat data, examining system design and operational configuration, and development of information extraction techniques.
Document ID
19780030975
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Malila, W. A.
(Environmental Research Inst. of Michigan Ann Arbor, MI, United States)
Gleason, J. M.
(Environmental Research Inst. of Michigan Ann Arbor, MI, United States)
Cicone, R. C.
(Michigan, Environmental Research Institute, Ann Arbor Mich., United States)
Date Acquired
August 9, 2013
Publication Date
January 1, 1977
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: International Symposium on Remote Sensing of Environment
Location: Ann Arbor, MI
Start Date: April 25, 1977
End Date: April 29, 1977
Accession Number
78A14884
Funding Number(s)
CONTRACT_GRANT: NAS9-14988
Distribution Limits
Public
Copyright
Other

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