A multivariate approach to vegetation mapping of Manitoba’s Hudson Bay Lowlands
Abstract. The Hudson Bay Lowlands of Manitoba contain a wide range of vegetation types that re ect local variations in climate, geological history, perma-frost, re, wildlife grazing and human use. This study, in Wapusk National Park and the Cape Churchill Wildlife Management Area, uses a Landsat-5 T...
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| Format: | Text |
| Language: | English |
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2002
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| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.588.385 http://www.umanitoba.ca/faculties/science/biological_sciences/botany_lab/pubs/2002b.pdf |
| Summary: | Abstract. The Hudson Bay Lowlands of Manitoba contain a wide range of vegetation types that re ect local variations in climate, geological history, perma-frost, re, wildlife grazing and human use. This study, in Wapusk National Park and the Cape Churchill Wildlife Management Area, uses a Landsat-5 TM image mosaic to examine landscape-level vegetation classes. Field data from 600 sites were rst classi ed into 14 vegetation classes and three unvegetated classes. Principal component analysis was used to examine the spectral properties of these classes and identify outliers. Multiple discriminant analysis was then applied to determine the statistical signi cance of the vegetation classes in spectral space. Finally, redundancy analysis was used to determine the amount of vegetation variance explained by the spectral re ectance data. We advocate this adaptive learning approach to vegetation mapping, by which the researcher employs an iterative strategy to carefully examine the relationship between ground and spec-tral data. This approach is labour intensive, but has the advantage of producing vegetation classes that are spectrally separable, decreasing the likelihood of errors in classi cation caused by overlap between classes. 1. |
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