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The MinimumBreak algorithm applied to a series of road turns

  • 2nd CAJG 2019
  • Published:
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Abstract

Cartographic generalization is the process of small-scale map production from large-scale maps. When the size of the map is reduced, the objects present in the latter can conflict with each other. There may be overlapping of objects, coalesced roads, or imperceptibility problems. Generalization solves these problems through algorithms. However, the generalization is not yet automated due to the lack of algorithms. In this article, a new algorithm for processing turn series on a road to correct the coalescence is investigated. Tests as well as comparisons with existing algorithms are going to be conducted. This research has proven to be beneficial to the field of cartography as there is a lack of algorithms treating complex series of turns when producing a map. The samples used for the study are winding mountainous roads from Algeria, China, Norway, Switzerland, and France.

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Data availability

OpenStreetMap data is open source and available on www.openstreetmap.org.

References

  • Abam MA (2010) Streaming algorithms for line simplification. Discrete and Computational Geometry 43(3):497–515

    Article  Google Scholar 

  • Abbas I (1994) Vector databases and cartographic error. Problems posed by spot checks; an alternative method based on Hausdorff distance. Dissertation university of Paris Diderot, Paris

  • Balboa JLG, Lopez FJA (2005) Road line segmentation for cartographic generalization: a wavelet based procedure. 22nd International Cartographic Conference (ICC), Spain

  • Balboa JLG, Lopez FJA (2008) Generalization-oriented road line classification by means of an artificial neural network. Geoinformatica. 12:289–312. https://doi.org/10.1007/s10707-007-0026-z

    Article  Google Scholar 

  • Balboa JLG, Lopez FJA (2009) Sinuosity pattern recognition of road features for segmentation purposes in cartographic generalization. Pattern Recognition. 42(9):2150–2159

    Article  Google Scholar 

  • Balboa JLG, Lopez FJA, Luque RL (2005) Road line classification for cartographic generalization : a neural net approach. 22nd International Cartographic Conference (ICC), Spain

  • Cebrykow P (2017) Cartographic generalization yesterday and today. Polish Cartographical Review. 49(1):5–15. https://doi.org/10.1515/pcr-2017-0001

    Article  Google Scholar 

  • Douglas D, Peuker T (1973) Algorithms for the reduction of the number of pointsrequired to represent a digitised line or its caricature. The Canadian Cartographer. 10:112–122

    Article  Google Scholar 

  • Fritsch E (1997) Representations of geometry and cartographic constraints for the generalization of linear roads. Dissertation university of Gustave Eiffel, Paris

  • Gaffuri J (2008) Automatic generalization to take into account field themes: the GAEL model. Dissertaion university of Gustave Eiffel, Paris

  • Gao P, Liu Z, Han F, Tang L, Xie M (2015) Accelerating the computation of multi-scale visual curvature for simplifying a large set of polylines with Hadoop. GIScience & Remote Sensing. 52(3):315–331. https://doi.org/10.1080/15481603.2015.1035528

    Article  Google Scholar 

  • Goethem AV, Meulemans W, Speckmann B, Wood J (2014) Exploring curved schematization. IEEE Pacific Visualization Symposium, Yokohama. https://doi.org/10.1109/PacificVis

  • Jenks GF (1989) Geographic logic in line generalisation. Cartographica. 26(1):27–42

    Article  Google Scholar 

  • Lang T (1969) Rules for robot draughtsmen. Geographical Magazine. 42:50–51

    Google Scholar 

  • Lecordix F, Plazanet C, Lagrange JP (1997) A platform for research in generalization: application to caricature. GeoInformatica. 1(2):161–182

    Article  Google Scholar 

  • Legrand C, Duchene C, Lecordix F (2005) Propagation of displacements during a generalization process. Bulletin of the French cartography committee n°186 of december

  • Li ZL (2007) Essential operations and algorithms for geometric transformations in digital map generalization. International Cartographic Conference, Russia

  • Lopez FJA, Balboa JLG (2008) Generalization-oriented road line segmentation by means of an artificial neural network applied over a moving window. Pattern Recognition. 41(5):1593–1609

    Article  Google Scholar 

  • Lopez FJA, Balboa JLG, Gordo JFR (2005) Segmentation of lines by means of douglas peucker applied to effective areas of the visvalingam and whyatt algorithm. International cartographic conference, Spain

  • Mackaness WA, Ruas A, Sarjakoski LT (2007) Generalisation of cartographic information: cartographic modelling and applications. Elsevier & ICA

  • McMaster RB (1987) Automated line generalization. Cartographica. 24(2):74–111

    Article  Google Scholar 

  • Muller JC (1987) Fractal and automated line generalization. The Cartographic Journal. 24(1):27–34. https://doi.org/10.1179/caj.1987.24.1.27

    Article  Google Scholar 

  • Muller JC (1990) The removal of spatial conflicts in line generalization. Cartography and Geographic Information Systems. 17(2):141–149. https://doi.org/10.1559/152304090783813817

    Article  Google Scholar 

  • Mustière S (2001) Supervised learning for cartographic generalization. Dissertation university of Pierre and Marie Curie, Paris

  • Perkal J (1958) An attempt at objective generalization. Geodezja I Kartografia 7(2):130–142

    Google Scholar 

  • Plazanet C (1996) Enrichment of geographic databases: analysis of the geometry of linear objects for cartographic generalization (application to roads). Dissertation university of Gustave Eiffel, Paris

  • Saux E (2003) B-spline functions and wavelets for cartographic line generalization. Cartography and Geographic Information Science. 30(1):33–50. https://doi.org/10.1559/152304003100010938

    Article  Google Scholar 

  • Skopeliti A, Tsoulos L (1999) On the parametric description of the shape of the cartographic line. Cartographica. 36(3):53–65

    Article  Google Scholar 

  • Stefanakis E (2015) SELF: Semantically enriched line simplification. International Journal of Geographical Information Science. 29(10):1826–1844

    Article  Google Scholar 

  • Tamilmani R, Stefanakis E (2017) Enriched geometric simplification of linear features. GEOMATICA. 71(1):3–19

    Article  Google Scholar 

  • Tienaah T, Stefanakis E, Coleman D (2015) Contextual Douglas-Peucker simplification. Geomatica. 69(3):327–338

    Article  Google Scholar 

  • Touya G (2011) Orchestration of a multi-model process of generalization of heterogeneous geographic spaces. Dissertation university of Gustave Eiffel, Paris

  • Van Horn E (1986) Generalizing cartographic data base. AUTO-CARTO. 7:532–540

    Google Scholar 

  • Visvalingam M, Whelan JC (2016) Implications of weighting metrics for line generalization with visvalingam’s algorithm. The Cartographic Journal. 53(3):253–267. https://doi.org/10.1080/00087041.2016.1149906

    Article  Google Scholar 

  • Visvalingam M, Whyatt JD (1993) Line generalisation by repeated elimination of points. The Cartographic Journal. 30(1):46–51. https://doi.org/10.1179/000870493786962263

    Article  Google Scholar 

  • Weibel R (1996) A typology of constraints to line simplification. 7th International Symposium on Spatial Data Processing, The Netherlands. 2(sec.9a): 1–14

  • White ER (1985) Assessment of line-generalization algorithms using characteristic points. The American Cartographer. 12(1):17–28. https://doi.org/10.1559/152304085783914703

    Article  Google Scholar 

  • Woojin P, Yu K (2011) Hybrid line simplification for cartographic generalization. Pattern Recognition Letters. 32(9):1267–1273

    Article  Google Scholar 

  • Zhilin L (1988) An algorithm for compressing digital contour data. The Cartographic Journal. 25:143–146

    Google Scholar 

Download references

Acknowledgments

I would like to thank Doctor Noureddine CHAIB for his expert advice and encouragement throughout this project, as well as Mrs. Meriem Ben Kattas for her brilliant contribution to the methodology of the research.

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Correspondence to Nardjes Hamini.

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Code availability

The software used for this study is QGIS which is also open source software.

Additional information

Responsible Editor: Biswajeet Pradhan

This paper was selected from the 2nd Conference of the Arabian Journal of Geosciences (CAJG), Tunisia 2019

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Hamini, N., Yagoubi, M.B. The MinimumBreak algorithm applied to a series of road turns. Arab J Geosci 14, 140 (2021). https://doi.org/10.1007/s12517-021-06471-2

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