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dc.contributor.advisorFranklin, Steven E.
dc.contributor.authorWilliams, Joan A.
dc.coverage.spatial2000002101en
dc.date.accessioned2005-08-05T16:52:31Z
dc.date.available2005-08-05T16:52:31Z
dc.date.issued1992
dc.identifier.citationWilliams, J. A. (1992). Vegetation classification using Landsat TM and SPOT-HRV imagery in mountainous terrain, Kananaskis Country, southwestern Alberta (Unpublished master's thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/15410en_US
dc.identifier.isbn031579108Xen
dc.identifier.urihttp://hdl.handle.net/1880/31095
dc.descriptionBibliography: p. 126-135.en
dc.description.abstractLandsat-5 Thematic Mapper (TM) 7-band data and SPOT-HRV 3-band data, and topographic measures derived from a digital elevation model (DEM) were used to determine the best set of classification variables for mapping vegetation communities in a mountainous region in southwestern Alberta. Ground and topographic data were gathered for 765 pixels sampled in the field. Discriminant analysis of an integrated TM+DEM data set resulted in overall accuracy of 72.77% for twenty-eight landcover classes, an improvement_ of 10.81 % over TM data alone. Discriminant analysis of a SPOT +DEM data set resulted in a similar accuracy of 73.44% for twenty-three classes, an improvement of 10.23% over SPOT data alone. Individual classes showed considerable variability in accuracy, which was reduced significantly with the addition of elevation, slope and incidence from the DEM. Most accuracy improvement occurred in poplar slope (by 60.7%), herb avalanche slope (40.9%), fen (by 28.5%) and Cassiope alpine meadow heath (by 25%) classes. Most spectrally distinct vegetated classes included mixedwood forest, herb- and pine-dominated rock outcrop complexes, several shrub-dominated communities, and burned and logged areas. Herb-dominated wetlands (fen, marsh, floating bog) were least distinct. Higher spatial resolution data (SPOT) is important in the separation of non­forested wetlands, particularly herb-dominated communities. In turn, higher spectral resolution data (TM) is important in the separation of non-forested upland classes. Integration of best classification accuracies from the two satellite data sets improved overall accuracy to 88.31 % and shows the need for further research in this area. A maximum likelihood classification and mapping of the TM data set illustrates the spatial distribution of the classes, and provides further support for statistical evidence that topographic data is necessary for landcover classification of high relief environments.
dc.format.extentx, 172 leaves : ill. ; 30 cm.en
dc.language.isoeng
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subject.lccQK 203 A4 W55 1992en
dc.subject.lcshVegetation classification - Alberta - Kananaskis Country
dc.subject.lcshEcology - Alberta - Kananaskis Country
dc.titleVegetation classification using Landsat TM and SPOT-HRV imagery in mountainous terrain, Kananaskis Country, southwestern Alberta
dc.typemaster thesis
dc.publisher.institutionUniversity of Calgaryen
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/15410
thesis.degree.nameMaster of Science
thesis.degree.nameMS
thesis.degree.nameMSc
thesis.degree.disciplineResources and the Environment
thesis.degree.grantorUniversity of Calgary
dc.identifier.lccQK 203 A4 W55 1992en
dc.publisher.placeCalgaryen
ucalgary.thesis.notesoffsiteen
ucalgary.thesis.uarcreleaseyen
ucalgary.item.requestcopytrue


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University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.