Point Pattern

  • Oliver Nakoinz
  • Daniel Knitter
Part of the Quantitative Archaeology and Archaeological Modelling book series (QAAM)


In archaeology and geography, many data are available as sets of points. Hence, the analysis of point patterns is an important technique in both disciplines. To start with point processes are mentioned, as predefined rules of the formation of point patterns and hence theoretical models. First-order properties of point processes involve factors of point locations, which do not depend on other points. This part connects to regression and predictive modelling. Second-order properties deal with the dependence of the location on other points. Tests on complete spatial randomness (CSR) compare parameters of a random point distribution with the parameters of an empirical point distribution to establish whether CSR can be deduced. G-, F- and Ripley’s K-function are applied. These functions allow distinguishing regular point patterns, random point patterns and clustered point patterns. In the case of clustered point patterns, an attraction between the points is assumed. A new point prefers a location close to other points. In the case of regular patterns, a rejection is assumed where points tend to avoid other points. We present a systematisation of different functions of second-order point pattern analysis. For third-order properties, it is assumed that the location between points depends on the relationship of a triple of points.


Point processes Point pattern analysis Complete spatial randomness First-order properties Second-order properties Spatial dependencies 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Oliver Nakoinz
    • 1
  • Daniel Knitter
    • 2
  1. 1.University of KielKielGermany
  2. 2.Excellence Cluster TopoiFreie UniversitätBerlinGermany

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