Hierarchical GML Modeling of Transportation Networks

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Hierarchical GML Modeling of Transportation
Networks

• Knut-Erik Johnsen
• knut.e.johnsen_at_hiof.no
• Veileder Gunnar Misund

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Project description

• There are vast amounts of geodata available.
• This project will try to find a smart way to
  organize and store this data with two goals in
  mind, visualization and analysis.
• The main case will be transportation networks.
  Different algorithms for transportation planning
  and shortest path will be investigated.
• All results and publications are part of the
  OneMap project.

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TigerLine Data
US Highways, resolution ca. 11 km
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Grid Approximation
Overlay the grid representing your wanted level
detail (resolution)
Snap points to nearest grid point
Discard redundant points
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Network Generalization
Clustering
Selection/deletion
Stroke ordering (Thomson)
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Road Class Grouping
Most road data incorporates some kind of
classification
US Census Tiger Line Files CFCC codes
Class A3 (green) "Secondary and Connecting
Road".
A1 (red) and A2 (blue) A1 "Primary Highway With
Limited Access" A2 "Primary Road Without
Limited Access".
A4 (purple, "Local, Neighborhood, and Rural
Road"), A6 (brown, "Road with Special
Characteristics") and A7 (cyan, "Road as Other
Thoroughfare").
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Stroke Extent Grouping
Strokes are constructed by joining consequtive
segments with same road name
657 to 1314 meter
164 to 328 meter
Larger than 10.5 km