Interactive Visualisation Techniques for Data Mining of Satellite Imagery

This study presents a new visualisation tool for classification of satellite imagery. Visualisation of feature space allows exploration of patterns in the image data and insight into the classification process and related uncertainty. Visual Data Mining provides added value to image classifications as the user can be involved in the classification process providing increased confidence in and understanding of the results. In this study, we present a prototype visualisation tool for visual data mining (VDM) of satellite imagery. The visualisation tool is showcased in a classification study of high-resolution imagery of Heard Island. BIOGRAPHY OF PRESENTER Arko Lucieer is a lecturer in GIS and Remote Sensing at the Centre for Spatial Information Science (CenSIS), School of Geography and Environmental Studies, University of Tasmania. He is a member of the local SSI committee and the national SSI committee on remote sensing and photogrammetry. Arko moved to Tasmania from the Netherlands in 2004. He has a PhD in remote sensing from ITC and Utrecht University in the Netherlands and an MSc in Physical Geography from Utrecht University. Currently his research focus is on extracting information from satellite imagery for environmental mapping and monitoring with a particular interest in the application of pattern recognition algorithms and visualisation to remote sensing.