Point Pattern Analysis as Tool for Digital Geoarchaeology: A Case Study of Megalithic Graves in Schleswig-Holstein, Germany

Abstract

In this contribution we apply different methods of spatial and geomorphometric analysis in order to present a general approach of data exploration in areas where detailed local information is absent. Our data are based on locations of megalithic graves from Funnel Beaker societies (3700-2800 BCE) in the area of Schleswig-Holstein, Germany. Using these locations, we apply methods of point pattern analysis in order to reconstruct the spatial processes that created the sample: We use density based measures to show the influence of first order effects on the dataset. While first order effects are related to the underlying areal characteristics of the point locations and hence are determinant of their intensity, second-order effects are the result of interactions between points. We conduct distance related approaches, e.g. focusing on nearest neighbor characteristics, in order to investigate the interaction between the points. The point pattern analyses is complemented by integrating geomorphometric measures that are indirectly indicative for some general environmental conditions, even in prehistoric times. This helps (a) to relate first-order effects to societal or environmental features and (b) to understand the specific pattern of interactions between the points. The necessary raw data in form of digital elevation models are freely available for large parts of the globe. All analyses are conducted using free and open source software in order to provide their limitless application.

Creating the funerary landscape of Eastern Sudan

“…settlements [51,52] and monuments patterns [53][54][55]. A point pattern corresponds to a set of locations of spatial events generated by a stochastic process within a bounded region [56].…”

“…The smoothing bandwidth can be specified in the function with the argument sigma. The kernel bandwidth sigma controls the degree of smoothing: a small value may omit a potential general trend, while a large value may omit local details [53,61]. In this research the sigma was automatically estimated with the likelihood cross-validation method in spatstat (bw.ppl) and manually adjusted through the function argument adjust.…”

Visibility of the Gask Ridge road from simulated Watchtowers: A Monte Carlo testing approach

“…second-order effects) which result in the distribution of sample points not reflecting the true conditions of site selection (e.g. Illian, 2008, p. 83;Knitter and Nakoinz, 2018). Although the potential to include distance preferences and constraints when simulating sample points has been noted (e.g.…”

Location Modeling of Final Palaeolithic Sites in Northern Germany

“…Three functions-G, F, and K-were used to compare the simulated points based on the hypotheses with the actual find spots regarding effects of the first and second order [15] (p. 9). First, the nearest-neighbor distance distribution function (G(r), following [45] (p. 262)), was used.…”

“…In the archaeological context, this method is used, on the one hand, for landscape reconstruction (as used by [10,11]) and, on the other hand, for modeling settlement preferences (as used by [12][13][14]). Nevertheless, many of these approaches do not specifically address second-order spatial effects, that is, the interaction of locations with each other, as examined in [15]. These effects are more likely to be considered in the description and analysis of existing finds [16] (p. 314) rather than in predictive modeling.…”