• Monika Sester
Living reference work entry


In this chapter, the scientific background of geoinformatics is reflected and research issues are described, together with examples and an extensive list of references.


Object Class Iterative Close Point Spatial Object Iterative Close Point Spatial Data Mining 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. AdV (2008) Dokumentation zur Modellierung der Geoinformationen des amtlichen Vermessungswesens (GeoInfoDok), Technical report, Arbeitsgemeinschaft der Vermessungsverwaltungen der Bundesrepublik DeutschlandGoogle Scholar
  2. Andrienko N, Andrienko G (2005) Exploratory analysis of spatial and temporal data-a systematic approach. Springer, BerlinGoogle Scholar
  3. Antoniou G, van Harmelen F (2004) Semantic web primer. MIT, CambridgeGoogle Scholar
  4. Bard S, Ruas A (2004) Why and how evaluating generalized data? In: Proceedings of 11th international symposium on progress in spatial data handling, Leicester. Springer, Berlin, pp 327–342Google Scholar
  5. Becker S, Haala N (2007) Refinement of building facades by integrated processing of Lidar and image data. In: Proceedings of PIA07: photogrammetrie image analysis, Munich, 19–21 Sept 2007, pp 7–12Google Scholar
  6. Besl PJ, McKay ND (1992) A method for registration of 3-D shapes. IEEE Trans Pattern Anal Mach Intell 14(2):239–256CrossRefGoogle Scholar
  7. Brenner C, Ripperda N (2006) Extraction of facades using RJMCMC and constraint equations. In: Frstner W, Steffen R (eds) ISPRS Commission III symposium (IAPRS), Bonn, vol XXXVI, Part 3, pp 155–160Google Scholar
  8. Cecconi A, Weibel R, Barrault M (2002) Improving automated generalisation for on-demand Web mapping by multiscale databases. In: Symposium on geospatial theory, processing and applications-spatial data handling. ISPRS, IGU, CIG, Ottawa. CD-RomGoogle Scholar
  9. de Berg M, van Kreveld M, Overmars M, Schwarzkopf O (2000) Computational geometry-algorithms and applications. Springer, HeidelbergzbMATHGoogle Scholar
  10. Douglas D, Peucker T (1973) Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Can Cartogr 10(2):112–122CrossRefGoogle Scholar
  11. Doytsher Y, Filin S, Ezra E (2001) Transformation of datasets in a linear-based map conflation framework. Surv Land Inf Syst 61(3):165–175Google Scholar
  12. Duckham M, Reitsma F (2009) Decentralized environmental simulation and feedback in robust geosensor networks. Comput Environ Urban Syst 33(4):256–268CrossRefGoogle Scholar
  13. Duckham M, Worboys M (2005) An algebraic approach to automated geospatial information fusion. Int J Geogr Inf Sci 19:537–557CrossRefGoogle Scholar
  14. Duckham M (2013) Decentralized spatial computing – foundations of geosensor networks. SpringerGoogle Scholar
  15. Fischler M, Bolles R (1981) Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun ACM 24(6):381–395MathSciNetCrossRefGoogle Scholar
  16. Frank R, Ester M (2006) A quantitative similarity measure for maps. In: Proceedings of 12th international symposium on progress in spatial data handling, Wien. Springer, Berlin, pp 435–450Google Scholar
  17. Gomory R (1958) Outline of an algorithm for integer solutions to linear programms. Bull Am Math Soc 64(5):274–278MathSciNetCrossRefGoogle Scholar
  18. Goodchild M (2007) Citizens as voluntary sensors: spatial data infrastructure in the World of Web 2.0. Int J Spat Data Infrastruct Res 2:24–32Google Scholar
  19. Green P (1995) Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82:711–732MathSciNetCrossRefzbMATHGoogle Scholar
  20. Gründig L, Gielsdorf F, Aschoff B (2007) Merging different data sets based on matching and adjustment techniques. In: Proceedings of XXX FIG working week, Hong Kong, p 100ffGoogle Scholar
  21. Gruber TR (1993) A translation approach to portable ontologies. Knowl Acquis 5(2):199–220CrossRefGoogle Scholar
  22. Gösseln Gv, Sester M (2005) Change detection and integration of topographic updates from ATKIS to geoscientific data sets. In: Agouris P, Croitoru A (eds) Next generation geospatial information. ISPRS book series, Taylor & Francis, London, pp 69–80Google Scholar
  23. Han J, Kamber M (2006) Data mining: concepts and techniques, 2nd edn. In: Gray J (series editor) The Morgan Kaufmann series in data management systems. Morgan Kaufmann, San FranciscoGoogle Scholar
  24. Harrie L, Weibel R (2007) Modelling the overall process of map generalization. In: Mackaness W, Ruas A, Sarjakoski T (eds) Generalization of geographic information: cartographic modelling and applications. Elsevier, OxfordGoogle Scholar
  25. Haunert J-H (2008) Aggregation in map generalization by combinatorial optimization. Volume 626 of Reihe C. Deutschen Geodätische Kommission, MünchenGoogle Scholar
  26. Haunert J-H, Sester M (2008) Assuring logical consistency and semantic accuracy in map generalization. Photogramm-Fernerkund-Geoinformation 2008(3):165–173Google Scholar
  27. Haunert J-H, Dilo A, van Oosterom P (2009) Constrained set-up of the tGAP structure for progressive vector data transfer. Comput Geosci 35(11):2191–2203CrossRefGoogle Scholar
  28. Heinzle F, Anders KH (2007) Characterising space via pattern recognition techniques: identifying patterns in road networks. In: Mackaness W, Ruas A, Sarjakoski T (eds) Generalization of geographic information: cartographic modelling and applications. Elsevier, Oxford, pp 233–253CrossRefGoogle Scholar
  29. Hettwer J, Benning, W (2000) Nachbarschaftstreue Koordinatenberechnung in der Kartenhomogenisierung. Allg Verm Nachr 107:194–197Google Scholar
  30. Hoppe H (1996) Progressive meshes. In: Proceedings of SIGGRAPH 96. ACM SIGGRAPH computer graphics proceedings annual conference series, New Orleans, pp 99–108Google Scholar
  31. Jin G, Nittel S (2008) Towards spatial window queries over continuous phenomena in sensor networks. IEEE Trans Parallel Distrib Syst 19(4):559–571CrossRefGoogle Scholar
  32. Jones C (1997) Geographical information systems and computer cartography. Addison Wesley/Longman, HarlowGoogle Scholar
  33. Jones CB, Purves R, Ruas A, Sanderson M, Sester M, van Kreveld M, Weibel R (2002) Spatial information retrieval and geographical ontologies: an overview of the SPIRIT project. In: Proceedings of the 25th annual international ACM SIGIR conference on research and development in information retrieval, Tampere, pp 387–388Google Scholar
  34. Kavouras M, Kokla M, Tomai E (2005) Comparing categories among geographic ontologies. Comput Geosci 31(2):145–154CrossRefGoogle Scholar
  35. Kiele C, Maué P (2009) GRID technologies for geospatial application-an overview. GIS Sci 3:65–67Google Scholar
  36. Kieler B, Sester M, Wang H, Jiang J (2007) Semantic data integration: data of similar and different scales. Photogramm Fernerkund Geoinformation 6:447–457Google Scholar
  37. Kirkpatrick SJ, Gelatt C, Vecci M (1983) Optimization by simulated annealing. Science 220(4598):671–680MathSciNetCrossRefzbMATHGoogle Scholar
  38. Koperski K, Han J (1995) Discovery of spatial association rules in geographic information databases. In: Egenhofer MJ, Herring JR (eds) Proceedings of the 4th international symposium on advances in spatial databases (SSD), Portland, vol 951. Springer, Berlin, pp 47–66CrossRefGoogle Scholar
  39. Kuhn W (2005) Geospatial semantics: why, of what, and how? J Data Semant III 3534:1–24. Lecture notes in computer science. Springer, BerlinGoogle Scholar
  40. Lamy S, Ruas A, Demazeau Y, Jackson M, Mackanes W, Weibel R (1999) The application of agents in automated map generalization. In: Proceedings of the 19th international cartographic conference of the ICA, OttawaGoogle Scholar
  41. Laube P, Duckham M (2009) Decentralized spatial data mining for geosensor networks. In: Miller HJ, Han J (eds) Geographic data mining and knowledge discovery, 2nd edn. CRC, Boca Raton, pp 409–430Google Scholar
  42. Leibe B, Leonardis A, Schiele B (2004) Combined object categorization and segmentation with an implicit shape model. In: ECCV workshop on statistical learning in computer vision, Prague, pp 17–32Google Scholar
  43. Lillesand TM, Kiefer RW (1999) Remote sensing and image interpretation, 4th edn. Wiley, New YorkGoogle Scholar
  44. Mackaness WA, Ruas A, Sarjakoski LT (2007) Generalisation of geographic information-cartographic modelling and applications. Elsevier, OxfordGoogle Scholar
  45. Marshall S (2005) Streets and patterns. S. Spon/Taylor & Francis, New YorkGoogle Scholar
  46. Müller P, Zeng G, Wonka P, Van Gool L (2007) Image based procedural modeling of facades. SIGGRAPH/ACM Trans Graph 26(3):85–109CrossRefGoogle Scholar
  47. Raubal M, Winter S, Teßmann S, Gaisbauer C (2007) Time geography for ad-hoc shared-ride trip planning in mobile geosensor networks. ISPRS J Photogram Remote Sens 62(5):366–381CrossRefGoogle Scholar
  48. Reznik S, Mayer H (2008) Implicit shape models, self-diagnosis, and model selection for 3D facade interpretation. Photogramm Fernerkund Geoinformation 3:187–196Google Scholar
  49. Rodriguez MA, Egenhofer MJ (2004) Comparing geospatial entity classes: an asymmetric and context dependent similarity measure. Int J Geogr Inf Sci 18(3):229–256CrossRefGoogle Scholar
  50. Russell S, Norvig P (2002) Artificial intelligence: a modern approach. Prentice Hall series in artificial intelligence. Prentice Hall, Upper Saddle RiverGoogle Scholar
  51. Saalfeld A (1988) Automated map compilation. Int J Geogr Inf Syst 2(3):217–228CrossRefGoogle Scholar
  52. Schnabel R, Wahl R, Klein R (2007) Efficient RANSAC for point-cloud shape detection. Comput Graph Forum 26(2):214–226CrossRefGoogle Scholar
  53. Schwering A (2008) Approaches to semantic similarity measurement for geo-spatial data: a survey. Trans GIS 12(1):5–29CrossRefGoogle Scholar
  54. Sester M (2005) Optimizing approaches for generalization and data abstraction. Int J Geogr Inf Sci 19(8–9):871–897CrossRefGoogle Scholar
  55. Sester M (2009) Cooperative boundary detection in a geosensor network using a SOM. In: Proceedings of the international cartographic conference, Santiago. ICAGoogle Scholar
  56. Sester M, Brenner C (2009) A vocabulary for a multiscale process description for fast transmission and continuous visualization of spatial data. Comput Geosci 35(11):2177–2184CrossRefGoogle Scholar
  57. Stefanidis A, Nittel S (2004) Geosensor networks. CRC, Boca RatonCrossRefGoogle Scholar
  58. Stoter J, Burghardt D, Duchene C, Baella B, Bakker N, Blok C, Pla M, Regnauld N, Touya G, Schmid S (2009) Methodology for evaluating automated map generalization in commercial software. Comput Environ Urban Syst 33(5):311–324CrossRefGoogle Scholar
  59. Thiemann F (2002) Generalization of 3D building data. In: ISPRS commission IV symposium on geospatial theory, processing and applications (IAPRS), Ottawa, vol 34/4. CD-RomGoogle Scholar
  60. Thrun S, Burgard W, Fox D (2005) Probabilistic robotics. MIT, CambridgezbMATHGoogle Scholar
  61. van Kreveld M (2001) Smooth generalization for continuous zooming. In: Proceedings of the international cartographic conference (ICC’01), Beijing, pp 2180–2185Google Scholar
  62. van Oosterom P (1995) The GAP-tree, an approach to ‘on-the-fly’ map generalization of an area partitioning. In: Müller J-C, Lagrange J-P, Weibel R (eds) GIS and generalization-methodology and practice. Taylor & Francis, London, pp 120–132Google Scholar
  63. Veldhuis H, Vosselman G (1998) The 3D reconstruction of straight and curved pipes using digital line photogrammetry. ISPRS J Photogram Remote Sens 53(1):6–16CrossRefGoogle Scholar
  64. Volz S (2005) Shortest path search in multi-representation street databases. In: Gartner G (ed) Proceedings of the 3rd international symposium on location based services and TeleCartography, Vienna, 28–30 Nov 2005. Eigenverlag, Vienna, pp 1–10Google Scholar
  65. Volz S (2006) Management and conflation of multiple representations within an open federation platform. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, WadernGoogle Scholar
  66. Vosselman G (1992) Relational matching, vol 628. Springer, BerlinGoogle Scholar
  67. Vosselman G, Sester M, Mayer H (2004) Basic computer vision techniques. In: McGlone C (ed) Manual of photogrammetry. ASPRS, Bethesda, pp 455–504Google Scholar
  68. Walter V, Fritsch D (1999) Matching spatial data sets: a statistical approach. Int J Geogr Inf Sci 13(5):445–473CrossRefGoogle Scholar
  69. Ware J, Jones C (1998) Conflict reduction in map generalization using iterative improvement. GeoInformatica 2(4):383–407CrossRefGoogle Scholar
  70. Worboys MF, Duckham M (2004) GIS: a computing perspective, 2nd edn. CRC, Boca RatonGoogle Scholar
  71. Yang BS (2005) A multi-resolution model of vector map data for rapid transmission over the internet. Comput Geosci 31(5):569–578CrossRefGoogle Scholar
  72. Yaolin L, Molenaar M, Kraak M-J (2002) Semantic similarity evaluation model in categorical database generalization. In: Proceedings ISPRS commission IV symposium geospatial theory, processing and applications, Ottawa, 9–12 July 2002, Canada. International archives of photogrammetry, remote sensing and spatial information sciences, vol XXXIV (Part 4)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institute of Cartography and GeoinformaticsLeibniz Universitt HannoverHannoverGermany

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