Texture-based classification of sub-Antarctic vegetation communities on Heard Island |
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Authors: | Humphrey Murray Arko Lucieer Raymond Williams |
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Institution: | 1. Datalive Software, 6 George St, Launceston, Tasmania 7250, Australia;2. School of Geography and Environmental Studies, University of Tasmania, Private Bag 76, Hobart, Tasmania 7001, Australia;3. School of Computing and Information Systems, University of Tasmania, Private Bag 100, Hobart, Tasmania 7001, Australia |
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Abstract: | This study was the first to use high-resolution IKONOS imagery to classify vegetation communities on sub-Antarctic Heard Island. We focused on the use of texture measures, in addition to standard multispectral information, to improve the classification of sub-Antarctic vegetation communities. Heard Island’s pristine and rapidly changing environment makes it a relevant and exciting location to study the regional effects of climate change. This study uses IKONOS imagery to provide automated, up-to-date, and non-invasive means to map vegetation as an important indicator for environmental change. Three classification techniques were compared: multispectral classification, texture based classification, and a combination of both. Texture features were calculated using the Grey Level Co-occurrence Matrix (GLCM). We investigated the effect of the texture window size on classification accuracy. The combined approach produced a higher accuracy than using multispectral bands alone. It was also found that the selection of GLCM texture features is critical. The highest accuracy (85%) was produced using all original spectral bands and three uncorrelated texture features. Incorporating texture improved classification accuracy by 6%. |
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Keywords: | Vegetation mapping Multispectral classification Grey level co-occurrence matrix (GLCM) Texture-based classification Sub-Antarctic Heard Island IKONOS imagery |
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