This document summarizes spatial analysis conducted on artifact distribution from an archaeological excavation site in the Czech Republic called Na Včelách. Three different interpolation methods - Inverse Distance Weighting, Kriging, and Spline - were used to map artifact elevations. Histograms of artifact depths and a trend analysis in 3D helped validate the interpolation maps. A Triangulated Irregular Network visualization in ArcScene further aided interpretation by allowing observation of artifact clusters from different perspectives. The analyses provide preliminary insights into how the site was occupied during the Great Moravian period, though the primary function remains unknown.

1. Figure 6: This map is displaying the artifacts
with the three interpolations superimposed
on top of the artifacts, with the IDW as
contour lines, the Kriging as filled contours,
and the Spline as a "heat map".
The artifact provenience during these excavations was collected using a Total Station, and it is the vector data that was
produced from this that was used in the spatial analysis of the artifacts.
The first step of the analyses was to look at a histogram of the artifacts by their Z value, as this would identify if the data is
skewed to a particular depth, in addition to identifying if any transformations will need to be done for later analysis. (Figure 3).
Therefore the Spline was converted into a Triangulated Irregular Network (TIN), and then viewed in ArcScene (Figure 7). The 3D view and ability to
look at the elevations from multiple perspectives, makes the identification of clusters of artifacts with unusually high or low elevations much easier.
When these areas are identified, the other data sets that were produced can then be looked at to see if there is any other outstanding features that
could aid int the interpretation of the site.
A special thanks goes out to: Dr. Dietz, Dr. Staeck, Dr. Dresler, and Dr. Hasenstab, as without their advice and guidance this project would not have
come to fruition. Also I would like to give thanks to the UIC Honors College, as without their research grants it is likely the project never would have
happened.
Works Cited:
∙Clarke, David 1972 Models and paradigms in contemporary archaeology. In Models in Archaeology. D. Clarke, ed. Pp. 60. London: Methuen & Co Ltd.
∙Hodder, Ian, and Clive Orton 1976 Introduction. In Spatial Analysis in Archaeology. D. Clarke, ed. Pp. 10.Cambridge London: Cambridge University Press.
∙Macháček, Jiří, et al. 2007 Raně středověká kovodělná výroba na Pohansku u Břeclavi. Památky Archeologické 98:56.
∙Shaw, Matt 2013 Pohansko 2013 Na včelách. Unpublished Field Notes Pp. 106.
∙Sláma, Jiří, and Vladimír Vavřínek 1996 Illustrated Czech History. Prague, Litera
In order to overcome the limitations of simple descriptive analysis, an Inverse Distance Weighting (IDW),
Kriging, and Spline map were produced from the elevations of the artifacts (Figure 6). While these maps do
aid in the interpretation of the data with regards to the elevation, they do not take full
Figure 3: This histogram is displaying the artifacts by their Z value, with each bin representing 1cm of variation.
Artifact Distribution Analysis at Na Včelách Pohansko
Figure 2: The greater research site of Pohansko a 9th
century Great Moravian Fortification. Na Včelách
can be seen to the north of the fortification
Figure 1: Site Location within the Czech Republic.
by James McGinty, University of Illinois at Chicago
Pohansko is a site located in the Southeastern region of the Czech Republic, on the confluence of the Dyje and Morava rivers. It was occupied during the 9th century AD as part of
the Great Moravian Empire, and represented a significant political and economic center for the region (Machaček et al. 2007: 131-135) (Figures 1&2).
The main enclosure and administrative center of the site that housed the church and court, had an industrial center for specialized craft production(Machaček et al. 2007: 131-135)
(Sláma 1996:36).
Na Včelách is located in the northern hinterlands of this enclosure (Figure 2) and only recently have researchers begun to turn their
focus away form the the enclosure and immediately surrounding area. These preliminary excavations have determined that the
hinterlands were in fact occupied by people during the Great Moravian period, yet the primary function of the site is still unknown
(Shaw, 2013)
The trend analysis function in the Geostatistical Analyst then was used to produce the initial 3D visualization of how the artifacts were
distributed through the site (Figure 4). This visualization was then used to cross validate the results of the interpolations that were
produced later in the analysis.
Figure 4: Two views from the trend analysis function looking at the artifact data by the Z value. The left image is a west to east
view, showing the general trend of increasing elevation from south to north. While the second image is looking at the data
from south to north, and not showing any clearly discernible trend from east to west.
The first series of analyses that were conducted were descriptive in nature, consisting of density distributions, and Nearest
Neighbor Hierarchical (NNH) cluster analyses (Figure 5). As these types of analysis have been used since the 70's (Hodder
1976: 1-4) they represent somewhat of baseline for the spatial analysis of artifacts. However as these descriptive methods
operate in a two dimensional universe, the information that can be deduced from such maps is then limited and does not
account for Z value. Therefore potentially producing a map that displays a higher degree of clustering than is actually
present (Clark 1972:15).
Figure 5: A general artifact density
distribution map, with a number of
NNH clusters superimposed.
advantage of the software's ability to render 3D data sets if only viewed in ArcMap.
Figure 7: The image above is a view of the TIN in ArcScene. It is useful as it allows for quick identification
of potential features or significant clusters of artifacts, such as the "hill" in the foreground of the image.
Source: National Geographic, Esri, DeLorme, HERE, UNEP-WCMC, USGS, NASA, ESA, METI,
NRCAN, GEBCO, NOAA, increment P Corp.