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In-Depth Information
measures, similarity and connectivity were employed to evaluate the selec-
tion results. The results show:
•
When the stroke-based selection approach is implemented, length
property performs best in distinguishing the different importance of all
the strokes, but performs worst in preserving the connectivity of the
retained network; Both betweenness and closeness perform best in pre-
serving the connectivity of the retained road network, and betweenenss
performs better than the other two topological properties in determining
the importance of strokes.
•
When the mesh density-based elimination approach is implemented,
length and three topological properties have similar performances in
determining the importance of strokes and degree property seems to per-
form a little better than others. Also, the connectivity of the retained
network can always be preserved by using this approach.
In future work, other possible properties will be investigated and also other
measures are needed to give a more reasonable evaluation of these proper-
ties
.
Acknowledgments
This research is supported by the Research Grants Council of Hong Kong (PolyU 5221/07E).
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