Automated processing for map generalization using web services
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In map generalization various operators are applied to the features of a map in order to maintain and improve the legibility of the map after the scale has been changed. These operators must be applied in the proper sequence and the quality of the results must be continuously evaluated. Cartographic constraints can be used to define the conditions that have to be met in order to make a map legible and compliant to the user needs. The combinatorial optimization approaches shown in this paper use cartographic constraints to control and restrict the selection and application of a variety of different independent generalization operators into an optimal sequence. Different optimization techniques including hill climbing, simulated annealing and genetic deep search are presented and evaluated experimentally by the example of the generalization of buildings in blocks. All algorithms used in this paper have been implemented in a web services framework. This allows the use of distributed and parallel processing in order to speed up the search for optimized generalization operator sequences.
KeywordsMap generalization Data enrichment Cartographic constraints Combinatorial optimization Parallel processing Web services Service oriented architecture
This research was partially funded by the Swiss National Science Foundation (grant 20-101798, project DEGEN). Thanks go to Ingo Petzold, Stefan Steiniger and three anonymous reviewers for helpful comments.
- 1.AGENT Consortium. “Deliverable D1—Specification of Basic Algorithms”. University of Zurich: Department of Geography, 1999.Google Scholar
- 4.M. Barrault, N. Regnauld, C. Duchêne, K. Haire, C. Baeijs, Y. Demazeau, P. Hardy, W. Mackaness, A. Ruas, and R. Weibel. “Integrating multi-agent, object-oriented and algorithmic techniques for improved automated map generalization,” in Proceedings of the 20th International Cartographic Conference, Beijing, China, pp. 2110–2116, 2001.Google Scholar
- 5.K. Beard. “Multiple representations from a detailed database: a scheme for automated generalization”, Ph.D. thesis, University of Wisconsin, Madison, 1988.Google Scholar
- 6.K. Beard. “Constraints on rule formation,” in B. Buttenfield and R. McMaster (Eds.), Map Generalization: Making Rules for Knowledge Representation. Longman: London, 121–135, 1991.Google Scholar
- 7.D. Burghardt and S. Meier. “Cartographic displacement using the snakes concept,” in W. Foerstner and L. Pluemer (Eds.), Semantic Modeling for the Acquisition of Topographic Information from Images and Maps. Birkhaeuser: Basel, 59–71, 1997.Google Scholar
- 9.D. Burghardt and S. Steiniger. “Usage of principal component analysis in the process of automated generalisation,” in Proceedings of 22nd International Cartographic Conference La Coruña, Spain, 2005.Google Scholar
- 10.D. Burghardt and M. Neun. “Automated sequencing of generalisation services based on collaborative filtering,” in M. Raubal, H.J. Miller, A.U. Frank, and M. Goodchild (Eds.), Geographic information science, 4th International Conference on Geographical Information Science (GIScience), IfGIprints 28, pp 41–46, 2006.Google Scholar
- 12.D. Burghardt, S. Schmid, and J. Stoter. “Investigatios on cartographic constraint formalisation,” in 10th ICA Workshop on Generalization and Multiple Representation, Moscow, 2007.Google Scholar
- 13.B. Buttenfield and R. McMaster. Map Generalization: Making Rules for Knowledge Representation. London: Longman, 1991.Google Scholar
- 14.P. Gray, L. Painton, C. Phillips, M. Trahan, J. Wagner. “A survey of global optimization methods,” Technical report, http://www.cs.sandia.gov/opt/survey/main.html (accessed 02/2007), 1997.
- 18.JUMP. “The JUMP Unified Mapping Platform,” http://www.jump-project.org, 2007.
- 20.G. Langran. “Generalization and parallel computation,” in B. Buttenfield and R. McMaster (Eds.), Map Generalization: Making Rules for Knowledge Representation. Longman: London, 204–216, 1991.Google Scholar
- 22.R. McMaster and S. Shea. Generalization in Digital Cartography. Association of American Geographers: Washington, USA, 1992.Google Scholar
- 24.S. Mustière, J.-D. Zucker, L. Saitta. “An abstraction-based machine learning approach to cartographic generalization,” in 9th International Symposium on Spatial Data Handling (SDH 2000), Beijing, China, 50–63, 2000.Google Scholar
- 26.I. Petzold, D. Burghardt, and M. Bobzien. “Workflow management and generalisation services,” in 9th ICA Workshop on Generalization and Multiple Representation, Portland, 2006.Google Scholar
- 27.N. Regnauld. “Constraint based mechanism to achieve automatic generalization using agent model,” in Proceedings of the GIS Research UK (GISRUK 2001), pp. 329–332, University of Glamorgan, 2001.Google Scholar
- 28.N. Regnauld. “Spatial Structures to Support Automatic Generalisation,” in Proceedings of the XXII International Cartographic Conference, A Coruña, Spain, 2005.Google Scholar
- 29.D. Richardson and J.-C. Muller. “Rule selection for small-scale map generalization”, in B. Buttenfield and R. McMaster (Eds.), Map Generalization: Making Rules for Knowledge Representation. Longman: London, 136–149, 1991.Google Scholar
- 30.A. Ruas and C. Plazanet. “Strategies for automated generalization,” in Proceedings of the 7th International Symposium on Spatial Data Handling (SDH 1996), pp. 319–336, Delft, the Netherlands, 1996.Google Scholar
- 31.A. Ruas. “Modèle de généralisation de données géographiques à base de contraintes et d’autonomie,” Ph.D. thesis, IGN France and Université de Marne La Vallée, 1999.Google Scholar
- 33.M. Sester. “Generalization based on least-squares adjustment,” International Archives of Photogrammetry and Remote Sensing, Vol. XXXIII:931–938, 2000 Part B4, Amsterdam.Google Scholar
- 34.Swiss Society of Cartography. Topographic Maps—Map Graphics and Generalisation. Swiss Society of Cartography: Wabern, Switzerland, 1995.Google Scholar
- 35.W. Staufenbiel. “Zur Automation der Generalisierung topographischer Karten mit besonderer Berücksichtigung großmaßstäbiger Gebäudedarstellungen,” Institute of Cartography and Geoinformatics, University of Hannover, No. 51, 1973.Google Scholar
- 37.S. Timpf. “Hierarchical structures in map series,” Ph.D. thesis, Technical University Vienna, 1998.Google Scholar
- 41.R. Weibel, S. Keller, and T. Reichenbacher. “Overcoming the knowledge acquisition bottleneck in map generalization: the role of interactive systems and computational intelligence,” in Proceedings of 2nd International Configuration on Spatial Information Theory (COSIT 95), pp. 139–156, 1995.Google Scholar
- 42.R. Weibel and G. Dutton. “Constraint-based automated map generalization,” in Proceedings of the 8th International Symposium on Spatial Data Handling, pp. 214–224, 1998.Google Scholar