Multitemporal classification of vegetation in the Oregon Coastal Range using landsat multispectral scanner data Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/vd66w2265

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  • The vegetation of a 420 square mile area of the Oregon Coastal Mountain Range was mapped using data from the multispectral scanner system aboard Landsat. Advantages of this mapping system include rapid synoptic coverage of the same geographic area at different periods in time at a reduced cost compared to photogrammetric mapping. The main disadvantages are the relatively poor resolution (1.1 acres) and classification accuracy for forest vegetation types. This project was designed to investigate the use of Principal Components Analysis (PCA) to combine data from two different dates (May and late July) in an attempt to improve classification accuracy. There were two significant results of this study. First, the overall classification accuracy was 7.7 percent (67.4 to 75.1 percent) higher for the July as compared to the May overpass when only single dates were used. This may be attributed to the stable phenological condition of July vegetation as compared to more variable condition in May. Spectral reflectance constantly changes over the spring growth period and varies greatly with changes in elevation. Second, it was found that combining data from the May and July overpasses using PCA resulted in an additional increase in overall classification accuracy by another 7.5 percent (75.1 to 82.6 percent) over the July single date classification.
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  • description.provenance : Approved for entry into archive by Linda Kathman(linda.kathman@oregonstate.edu) on 2009-02-05T15:03:42Z (GMT) No. of bitstreams: 1 Wang_Sen_1988.pdf: 607343 bytes, checksum: e65562d138a6156e0efc16c3f2677e1a (MD5)
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