**Geostatistics and archaeology: a review**

C. D. Lloyd

School of Geography, Queen's University, BELFAST BT7 1NN

Most archaeological data have a spatial component. As such, the way
archaeological data vary in space is often a crucial part of their
interpretation. One set of tools that have been developed for the
analysis of spatial data is Geostatistics. At the present time, the
potential of Geostatistics in archaeology has not been realised. This
paper seeks to provide a basic outside of some key geostatistical
techniques and to illustrate how these techniques may be useful to
archaeologists. Geostatistics makes use of spatial dependence (or
autocorrelation) in one or more variables distributed in space.

Geostatistics is used to widely to

(i) characterise spatial variation;

(ii) estimate at locations for which no samples are available and

(iii)
design sampling strategies.

Clearly, all of these objectives have direct
relevance to archaeology and associated disciplines such as
palaeoecology. The core tool of most geostatistical analyses is the
variogram. In simple terms, the variogram is a plot of the average
distance separating paired data values (x axis, where data are divided
into classes such as a separating distance of 1 to 2 m, 2 to 3 m and so
on) against half their average squared difference (y axis, where again
the average is obtained for all pairs of data in each class). A
mathematical model may be fitted to the variogram and the coefficients
of the model can then be used to inform an interpolation procedure
called kriging. That is, the form of spatial variation, as characterised
by the variogram, is used to determine the influence the available data
have in an estimate at some location for which no observation is
available. A by-product of kriging is the kriging standard error. This
is a function of the form of the model fitted to the variogram and the
spatial configuration of the data with respect to (i) the location of
the estimate and (ii) the locations of other data. The kriging standard
error is guide to uncertainty in estimates but it may also be used in
the design of sampling strategies, as shown in one of the case studies
presented at the end of the paper. In the paper, some published
applications of geostatistics and palaeoecology were outlined and
reviewed. Following this, two case studies using published data were
presented to clarify some of the relevant concepts and to illustrate how
geostatistics may be useful to archaeologists. The case studies focused
on (i) the characterisation of the spatial distribution of early Bronze
age spearheads and (ii) the mapping of soil phosphates and assessment of
optimal sampling strategies. The review of published work and the case
studies demonstrated that geostatistics has much potential in
archaeological research and the work of archaeologists would benefit
from some knowledge of its capabilities as well as its limitations.

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