Interactive and visual fuzzy classification of remotely sensed imagery for exploration of uncertainty

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.

Acknowledgements

The authors gratefully acknowledge Freek van der Meer, Norman Kerle, Wietske Bijker, Raymond Nijmeijer, Harald van der Werff, Daniël van de Vlag and Arta Dilo for their participation and feedback in the focus group user test. We would like to thank Steven de Jong and Raymond Sluiter for providing the Landsat 7 imagery of the ‘La Peyne’ study area. We also thank the anonymous reviewers for their valuable comments.

Notes

¹A web supplement with colour figures and a demo version of the software can be found at http://parbat.lucieer.net