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An ultrametric interpretation of building related event data

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  • Patrick Erik Bradley

Abstract

The long-term behaviour of the built environment is relevant to practising architects and engineers as well as to investors and policy makers. In contrast to this, the size, structure and dynamics of that important capital of society are not well established. As a first step towards assessing the dynamics of new constructions, refurbishments, demolitions and other building related event variables in urban building stocks in Southwest Germany, a first random sample of event data is examined using the more efficient ultrametric hierarchical classification in order to compare their dynamics. To this end, different ways of binary encodings of the multivariate data are carried out, and their ultrametric classification results compared. It turns out that municipalities of comparable sizes show similar behaviour in contrast to those of differing sizes, which corresponds to previous findings. Consequently, ultrametric methods can be applied to the study of building stock dynamics by revealing inherent hierarchical structure in data.

Suggested Citation

  • Patrick Erik Bradley, 2010. "An ultrametric interpretation of building related event data," Construction Management and Economics, Taylor & Francis Journals, vol. 28(3), pages 311-326.
    • Handle: RePEc:taf:conmgt:v:28:y:2010:i:3:p:311-326
    DOI: 10.1080/01446190903473790
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    References listed on IDEAS

    as
    1. Patrick Bradley, 2008. "Degenerating Families of Dendrograms," Journal of Classification, Springer;The Classification Society, vol. 25(1), pages 27-42, June.
    2. M E Gleeson, 1985. "Estimating Housing Mortality from Loss Records," Environment and Planning A, , vol. 17(5), pages 647-659, May.
    3. Fionn Murtagh, 2004. "On Ultrametricity, Data Coding, and Computation," Journal of Classification, Springer;The Classification Society, vol. 21(2), pages 167-184, September.
    4. M E Gleeson, 1986. "Estimating Housing Mortality with Standard Loss Curves," Environment and Planning A, , vol. 18(11), pages 1521-1530, November.
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    Citations

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    Cited by:

    1. Patrick Erik Bradley & Martin Behnisch, 2019. "Heavy-tailed distributions for building stock data," Environment and Planning B, , vol. 46(7), pages 1281-1296, September.

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