Species composition related to spectral classification in an Australian spinifex hummock grassland

Abstract

This paper demonstrates a methodology for relating objective vegetation classifications to spectral classifications in order to map variation in species composition within natural vegetation. Landsat MSS data was used to map spinifex-dominated vegetation units for an island conservation reserve and oil production field on the north-western shelf of Western Australia. A significant relationship was established between an agglomerative hierarchical classification of ground samples, characterized by percentage cover of plant species and physical cover components, and a similar classification of spectral means for sample pixels. Assignment of spectral means to mapping classes was guided by both ground and spectral sample clustering. The strong relationship between the spectral classification and vegetation groups meant that cover classes mapped on the basis of spectral properties could be characterized by quantitative ground data meaningful to vegetation ecology. The resultant groups were differentiated largely on the basis of percentage cover of the three major spinifex species and the proportion of plant litter and exposed soil and surface rock. The study confirms the utility of ground cover as a quantitative variable for developing relationships with spectral classifications, and demonstrates a methodology which may have a wider application for mapping natural vegetation communities.