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Multispectral scanner imagery for plant community classificationAuthor(s): R. S. Driscoll; M. M. Spencer
Source: In: Proceedings of Int. Symp. Remote Sensing Environ; Ann Arbor, Michigan; October 1972. Ann Arbor, MI: Environmental Research Institute of Michigan. p. 1259-1278.
Publication Series: Paper (invited, offered, keynote)
Station: Rocky Mountain Research Station
PDF: Download Publication (927.0 KB)
DescriptionOptimum channel selection among 12 channels of multispectral scanner imagery identified six as providing the best information for computerized classification of 11 plant communities and. two nonvegetation classes. Intensive preprocessing of the spectral data was required to eliminate bidirectional reflectance effects of the spectral imagery caused by scanner view angle and varying geometry of the plant canopy. Generalized plant community types -- forest, grassland, and hydrophytic systems--were acceptably classified based on ecological analysis. Serious, but soluble, errors. occurred with attempts to classify specific community types within the grassland system. However, special clustering analyses provided for improved classification of specific grassland communities.
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CitationDriscoll, R. S.; Spencer, M. M. 1972. Multispectral scanner imagery for plant community classification. In: Proceedings of Int. Symp. Remote Sensing Environ; Ann Arbor, Michigan; October 1972. Ann Arbor, MI: Environmental Research Institute of Michigan. p. 1259-1278.
Keywordsmultispectral scanner imagery, plant community classification, spectral data
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