Automated schematization using open standards, by Nottingham Uni
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This document discusses automated schematization and its application to creating schematic maps from geospatial data. It provides background on map generalization techniques like simplification, amalgamation, elimination, typification, exaggeration and displacement. The document then describes an optimization framework developed by the Centre for Geospatial Science to automate schematization using techniques like hillclimbing, simulated annealing and genetic algorithms. It demonstrates how this framework can simplify geospatial features while enforcing topological and geometric constraints to produce schematic maps from original geospatial datasets.
Automated schematization using open standards, by Nottingham Uni
- 1. AUTOMATED SCHEMATIZATION CASESTUDY Suchith Anand Jerry Swan Mike Jackson Mark Ware
- 2. Presentation Overview Introduction Generalization background Automated Schematization Conclusions
- 3. The Centre for Geospatial Science (CGS) Th C t f G ti l S i Established November 2005 as a cross- faculty post-graduate research centre. Research focus: – spatial data infrastructures (SDI), – geospatial intelligence, – geospatial interoperability – location-based services. location based
- 4. Creating Intelligent Applications Goal: Make it easier for geospatial researchers to incorporate proven geospatial techniques into their workflow. The idea is to create generic frameworks that are customized with the problem-specific details. problem specific Initial efforts have concentrated on an object-level object level optimization framework using state-space search.
- 5. Bigger picture Maturity of open Geospatial Standards source software (for (for ex. OGC spec.) ex. OSGeo stack)
- 6. OS Geo Product development statistics 2008 http://wiki.osgeo.org/wiki/Project_Stats
- 7. CGS Optimization Framework • Currently implemented: – Hillclimbing, Simulated Annealing – (Reactive) Tabu Search – Simple Genetic Algorithm • Implementation targets JVM and hence easily integrated with Geotools52North WPS etc ith etc.
- 8. Why – G h Generalization ? li i The process of simplifying the form or shape of map features, usually carried out when the map is changed from a large scale to a small scale, is referred to as generalisation. Map g p generalisation is a pprocess of extracting the important g p and relevant spatial information from reality.
- 9. Map Generalization operators M G li ti t Simplification Amalgamation l Elimination Typification Exaggeration Displacement
- 10. Simplification Si lifi ti Douglas-Peucker algorithm (1973)
- 11. Amalgamation DeLucia and Black (1987) - triangulation-based area amalgamation procedures. These ideas are taken up and advanced in Jones et al (1995) Su et al (1997) - A raster-based aggregation method (forms the basis of ESRI's AreaAggregate function) Ai and van Oosterom (2002) - displacement vectors p o to a a ga at o a d a Ooste o ( 00 ) d sp ace e t ecto s prior amalgamation
- 12. Elimination Regnauld (2001) – area features (includes deletion and aggregation of features)
- 13. Typification f Feature clusturing - (Mackaness 1994, Ormsby and Mackaness 1999, Mackaness and Mackechnie 1999) Sester (2003) and Moulin (2003) -Kohonen Self Organizing Maps Regnauld (1996) - Minimum Spanning Trees
- 14. Exaggeration gg Mackaness (1995) - alpha analysis for classifying urban road ac a ess ( 995) a p a a a ys s o c ass y g u ba oad networks hierarchically, providing a means for removing roads at smaller scale while still conveying essential characteristics of the network
- 15. Displacement Lonergan and Jones (2001) - map quality is measured in terms of minimum distance violations, and polygon displacement achieved by calculating displacement vectors in an iterative fashion Li et al (2002) - polygon displacement using a two-level agent-based architecture.
- 16. Harry Beck’s Schematic Tube Map Source: London Transport Museum
- 17. Schematic Map - Characteristics •Topologically consistent. T l i ll i t t •Simplified lines (Douglas-Peucker). •May be desirable to re-orient lines so that they are horizontal, vertical or diagonal. •Scale in congested areas expanded at the expense of scale in areas that are less so so.
- 18. Graphic manipulations for producing a schematic map Lines are simplified and re-oriented to conform to a regular grid. Congested areas are increased in scale at the expense of scale in areas of lesser node density
- 20. Topological Original network and derived schematic map should be topologically consistent Topological – original (Left), topological error (Middle) and acceptable solution (Right)
- 21. Orientation If possible, network edges should lie in horizontal, vertical or diagonal direction Orientation – original (L) and schematized (R)
- 22. Angle If possible, the angle between a pair of connected edges should be greater than some minimum angle Angle – edges re-oriented but Angle constraint violated (L) and acceptable solution
- 23. Rotation An edge’s orientation should remain as close to its starting orientation as possible :Rotation – original (L), acceptable solution (M) and better solution (R)
- 24. Clearance If possible, the distance between disjoint features should be g greater than some minimum distance Clearance – constraint violated (L) and resolved (R)
- 25. Displacement Vertices should remain as close to their starting positions as possible possible. Displacement – original (L), acceptable solution (M) and better solution (R)
- 26. Length Length – original (L) and congestion reduced by enforcing Length constraint (R)
- 27. Core Process •Evaluate – For each vertex: Count topological errors Measure constraint violations Heuristic l i th H i ti value is the sum of the above f th b Modify Displace vertices
- 28. Demo – Original Featureset
- 29. Demo – Schematized Featureset
- 30. Conclusions •Implements a usecase for automatic production of schematic maps •Proof-of-concept implemented for WFS, using schematization as transformation exemplar. p
- 32. Thank You