Interactive and visual fuzzy classification of remotely sensed imagery for exploration of uncertainty |
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| Authors: | Arko Lucieer Menno-Jan Kraak |
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| Institution: | International Institute for Geo-Information Science and Earth Observation (ITC) , Department of Geo-Information Processing (GIP) , PO Box 6, 7500 AA Enschede, The Netherlands E-mail: lucieer@itc.nl, kraak@itc.nl |
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| Abstract: | In this study, we propose, describe, and demonstrate a new geovisualization tool to demonstrate the use of exploratory and interactive visualization techniques for a visual fuzzy classification of remotely sensed imagery. The proposed tool uses dynamically linked views, consisting of an image display, a parallel coordinate plot, a 3D feature space plot, and a classified map with an uncertainty map. It allows a geoscientist to interact with the parameters of a fuzzy classification algorithm by visually adjusting fuzzy membership functions and fuzzy transition zones of land-cover classes. The purpose of this tool is to improve insight into fuzzy classification of remotely sensed imagery and related uncertainty. We tested our tool with a visual fuzzy land-cover classification of a Landsat 7 ETM+ image of an area in southern France characterized by objects with indeterminate boundaries. Good results were obtained with the visual classifier. Additionally, a focus-group user test of the tool showed that insight into a fuzzy classification algorithm and classification uncertainty improved considerably. |
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| Keywords: | Object‐based models Field‐based models GIS |
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