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Project ID: IST-1999-14189
Finanziato nell'ambito di: FP5-IST
Paese: Netherlands

Existential uncertainty of spatial objects segmented from satellite imagery

This research addresses quantification and visualization of existential uncertainty of spatial objects derived from remotely sensed imagery. A split-and-merge image segmentation technique is applied at various step sizes of splitting and merging parameters. We test the hypothesis that objects occurring at many step sizes have less existential uncertainty than those occurring at only a few step sizes. Segmentation accuracy is quantitatively assessed by comparing segmentation results with a topographic reference map. Seven objects are identified and their correspondence with mapped objects in terms of existence as expressed by content and extension are investigated. For that purpose we calculated the area fit index. Large, homogeneous objects in an isolated position like a lake have low existential uncertainty, whereas small or heterogeneous objects have a much higher existential uncertainty.

A second point addressed in this study is visualization of segmentation uncertainty. For that purpose we used the boundary stability image. We conclude that the boundary stability index (BSI) allows a quantification of existential uncertainty and is suitable for its visualization. The area fit index (AFI) is a measure for assessing the accuracy of individual objects. The boundary fit index (D(B)) is used to assess segmentation accuracy for the whole image.

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