Title | ||
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Interactive And Visual Fuzzy Classification Of Remotely Sensed Imagery For Exploration Of Uncertainty |
Abstract | ||
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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. |
Year | DOI | Venue |
---|---|---|
2004 | 10.1080/13658810410001658094 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE |
Keywords | Field | DocType |
transition zone,focus group,fuzzy classification,feature space,engineering,parallel coordinates,interactive visualization,geomatic engineering | Geovisualization,Data mining,Feature vector,Fuzzy classification,Computer science,Fuzzy logic,Interactive visualization,Parallel coordinates,Artificial intelligence,Classifier (linguistics),Machine learning,Image display | Journal |
Volume | Issue | ISSN |
18 | 5 | 1365-8816 |
Citations | PageRank | References |
12 | 1.25 | 6 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Arko Lucieer | 1 | 455 | 46.51 |
Menno-Jan Kraak | 2 | 386 | 33.93 |