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Change detection using NALC MSS triplicates to set forest planning contextAuthor(s): D. R. Grey; P. E. Gessler; M. Hoppus; S. L. Boudreau
Source: In: Hansen, Mark; Burk, Tom, eds. Integrated tools for natural resources inventories in the 21st century. Gen. Tech. Rep. NC-212. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 623-630.
Publication Series: General Technical Report (GTR)
Station: North Central Research Station
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DescriptionThe USDA Forest Service has purchased the North American Landscape Characterization (NALC) Landsat Multispectral Scanner (MSS) triplicates (70's, 80's, and 90's) for every national forest in the United States. To encourage analysis and use of these data for forest planning, a change-detection training course was developed. The course covers basic methods and options for developing change detection maps including visual, post-classification comparison, image algebra, principal components analysis, and unsupervised techniques. The broad spatial and spectral resolutions of the MSS data preclude use of these data for detailed tree species and forest habitat mapping. However, the broad synoptic nature of these data sets, available over a 25-year time period, provides a useful context within which more detailed analyses and management planning can take place.
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CitationGrey, D. R.; Gessler, P. E.; Hoppus, M.; Boudreau, S. L. 2000. Change detection using NALC MSS triplicates to set forest planning context. In: Hansen, Mark; Burk, Tom, eds. Integrated tools for natural resources inventories in the 21st century. Gen. Tech. Rep. NC-212. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 623-630.
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