An investigation into the use of artificial neural networks and landsat thematic mapper imagery for vegetation classification in Southwestern British Columbia

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dc.contributor.authorWhite, Joanne Cherylen_US
dc.date.accessioned2024-08-15T20:15:10Z
dc.date.available2024-08-15T20:15:10Z
dc.date.copyright1998en_US
dc.date.issued1998
dc.degree.departmentDepartment of Geography
dc.degree.levelMaster of Science M.Sc.en
dc.description.abstractThe goal of this research was the experimentation with and characterization of neural networks for the classification of vegetation from multi-spectral remotely sensed imagery. A literature survey was undertaken to provide a theoretical context for the use of neural networks in remote sensing image classification and to determine the extent of previous research on this topic. The research described in this thesis combines the spatial analysis capabilities of a geographical information system with advanced multi­spectral image analysis procedures. Existing forest inventory information is utilized along with digital elevation data to provide training data and ancillary information useful to vegetation classification. Neural network classification algorithms were used to pre-stratify a Landsat Thematic Mapper image into categories corresponding to five levels of the new hierarchical vegetation inventory system being implemented in British Columbia. Emphasis was placed on the configuration of the neural network and on comparisons with conventional maximum likelihood estimates. Limitations to the success of this approach included the restricted availability of reliable training and reference data for all of the vegetation classes as well as the disparity between spectral classes found in the image data and the desired informational classes of the classification hierarchy.
dc.format.extent271 pages
dc.identifier.urihttps://hdl.handle.net/1828/20082
dc.rightsAvailable to the World Wide Weben_US
dc.titleAn investigation into the use of artificial neural networks and landsat thematic mapper imagery for vegetation classification in Southwestern British Columbiaen_US
dc.typeThesisen_US

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