Looking at the Big Picture: Using Geographic Information Systems to Explore Settlement Patterns in Kosova (15 min)

Presenters

Erina Baci, University of Michigan; Leela Anderson, University of Michigan; and Joana Hila, University of Michigan

Abstract

In this paper, we present the results of preliminary large-scale geospatial analyses conducted on archaeological sites in Kosova. This geospatial dataset was created by pulling site information and locations from volumes 1–3 of the archaeological maps of Kosova. The resulting gazetteer includes 700 sites, ranging from the Neolithic to the Medieval periods in Kosova. Attributes recorded for each site include site type, site size, time period, GPS coordinates, and short site descriptions. The sites were then divided into three temporal periods: prehistoric, antique and medieval. The data were imported into ArcGIS Pro, where the Nearest Neighbor, Ripley’s K and Kernel Density tools were used to measure the degree of spatial clustering of the sites across the three time periods. We had three broad goals in performing this analysis: research, preservation, and education. First, while it has been soundly argued that any meaningful geospatial analysis should operate at multiple scales, large-scale analyses such as that conducted here provide a crucial first step for any additional research by highlighting broad patterns and areas that need additional attention. Second, the dataset can serve as a valuable cultural heritage management resource. For example, the dataset can be used to identify sites that are at imminent threat of destruction due to resource extraction or expanding urbanization. And finally, the dataset has the potential to serve as a learning resource for students of Balkan archaeology, as geospatial data can be difficult to find for the region. Our preliminary analyses show that sites are spatially clustered throughout time, but that the location of these clusters change over time. The reason for this change is likely a mixture of geographical, environmental, and social processes.