Abstract
Building patterns are important settlement structures in applications like automated generalization and spatial data mining. Previous investigations have focused on a few types of building patterns (e.g. collinear building alignments); while many other types are less discussed. In order to get better known of the building patterns available in geography, this paper studies existing topographic maps at large to medium scales, and proposes and discusses a comprehensive typology of building patterns, their distinctions and characteristics. The proposed typology includes linear alignments (i.e. collinear, curvilinear, align-along-road alignments) and nonlinear clusters (grid-like and unstructured patterns). We concentrate in this paper on two specific building structures: align-along-road alignment and unstructured clusters. Two graph-theoretic algorithms are presented to detect these two types of building patterns. The approach bases itself on auxiliary data structures such as Delaunay triangulation and minimum spanning trees for clustering; several rules are used to refine the clusters into specific building patterns. Finally, the proposed algorithms are tested against a real topographic dataset of the Netherlands, which shows the potential of the two algorithms.
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References
AGENT (1999) Selection of basic measures, deliverablec1. Technical Report
Anders KH (2006) Grid typification. In: Riedl A, Kainz W, Elmes GA (eds) Progress in spatial data handling, Springer, Vienna, pp 633–642
Boffet A, Rocca Serra S (2001) Identification of spatial structures within urban block for town qualification. In: ICC, vol 3, Beijing, pp 1974–1983
Christophe S, Ruas A (2002) Detecting building alignments for generalisation purposes. In: Richardson DE, van Oosterom P (eds) Advances in spatial data handling (SDH 2002). Springer, Ottawa, pp 419–432
Duchêne C, Bard S, Barillot X, Ruas A, Trévisan J, Holzapfel F (2003) Quantitative and qualitative description of building orientation. In: 5th workshop on progress in automated map generalization, Pairs
Lüscher P, Weibel R, Burghardt D (2009) Integrating ontological modelling and bayesian inference for pattern classification in topographic vector data. Comput Environ Urban Syst 33(5):363–374
Prim RC (1957) Shortest connection networks and some generalizations. Bell Syst Tech J 36:1389–1401
Regnauld N (1996) Recognition of building clusters for generalization. In: Kraak MJ, Molenaar M (eds) Advances in GIS research II (Proceedings of 6th SDH’96, Delft), Taylor & Francis, London, pp 4B.1–4B.14
Ruas A, Holzapfel F (2003) Automatic characterisation of building alignments by means of expert knowledge. In: ICC, Durban, pp 1604–1515
Stoter J, Burghardt D, Duchene C, Baella B, Bakker N, Blok C, Pla M, Regnauld N, Touya G, Schmid S (2009a) Methodology for evaluating automated map generalization in commercial software. Comput Environ Urban Syst 33(5):311–324
Stoter J, van Smaalen J, Bakker N, Hardy P (2009b) Specifying map requirements for automated generalization of topographic data. Cartogr J 46(3):214–227
Wertheimer M (1923) Laws of organization in perceptual forms. In: Ellis WD (ed) A source book of gestalt psychology. Routledge & Kegan Paul, London, pp 71–88
Zahn CT (1971) Graph-theoretical methods for detecting and describing gestalt clusters. Comput IEEE Trans C20(1):68–86
Zhang X, Stoter J, Ai T, Kraak MJ (2010) Formalization and data enrichment for automated evaluation of building pattern preservation. In: Joint international conference on theory, data handling and modelling in geoSpatial information science, Hong Kong, vol XXXVIII, Part 2, pp 267–272
Acknowledgements
The work was partly supported by the 863 Program (Grant No. 2009AA121404). Faculty of Geo-Information Science and Earth Observation (ITC) of the University of Twente, which funds the first author as a PhD student, is gratefully acknowledged.
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Zhang, X., Ai, T., Stoter, J. (2012). Characterization and Detection of Building Patterns in Cartographic Data: Two Algorithms. In: Yeh, A., Shi, W., Leung, Y., Zhou, C. (eds) Advances in Spatial Data Handling and GIS. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25926-5_8
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