Abstract
A light loving invasive shrub, Austroeupatorium inulifolium has been spreading many land use types in the Knuckles Forest Reserve (KFR) in Sri Lanka, including man-made grasslands. In developing countries, there are limitations of using novel technologies to quantify and track the distribution of invasive species due to high costs and lack of facilities. This is a setback for their early detection and to introduce effective control measures. This pilot study attempted to map the distribution of A. inulifolium in man-made grasslands in KFR using high spatial multispectral images. Unsupervised, supervised and knowledge-based classifications were performed to quantify the spatial distribution of A. inulifolium in ERDAS Imagine. The results generated comparable results of the extent of area under A. inulifolium by using the unsupervised (108 ha), supervised (94 ha) and knowledge-based classifications (93 ha). They were 18, 15 and 15% from the total area selected for the study (622 - 646 ha), respectively. The results indicated the suitability of high spatial multispectral imageries in quantifying the spatial distribution of A. inulifolium. Further studies are recommended to investigate long-term changes in invasive plant population using multi temporal satellite data.