Computational Modelling and Human Use of Space

Inferring dynamic past behaviours from the static archaeological record is always a challenge, but computational and quantitative approaches to the human use of space can be helpful.

Our research in this field builds upon a long tradition at the Institute of teaching and research using computers, Geographic Information Systems and numerical methods.

It emphasises approaches that:

• are sensitive to human sensory behaviour and/or mobility patterns,
• foreground issues of spatial interaction, scale and process,
• leverage the flexibility of Monte Carlo simulation,
• address the kinds of complex and uncertain processes that are common in the archaeological record, and
• are perhaps best pursued via very 'open' approaches to software, data-sharing and analytical workflow.

In this regard we have a strong interest in point-process models, spatially-explicit regression, spatio-temporal uncertainty, viewsheds and wider sensory perception, cost surfaces, networks, spatial interaction models and agent-based simulation. In several instances, we, along with colleagues and graduate students, have pioneered the use of particular approaches in archaeology as well as developing appropriate bodies of archaeological theory to accompany them

Related outputs

• Bevan, A. and Conolly, J. 2011. Terraced fields and Mediterranean landscape structure: an analytical case study from Antikythera, Greece, Ecological Modelling 222: 1303-1314.
• Bevan, A. and Conolly, J. 2009. Modelling Spatial Heterogeneity and Nonstationarity in Artifact-Rich Landscapes, Journal of Archaeological Science 36.4: 956-964.
• Bevan, A. 2011. Computational Models for Understanding Movement and Territory, in Mayoral, V. and S. Celestino (eds.) Sistemas de Información Geográfica y Análisis Arquelógico del Territorio. V Simposio Internacional de Arqueología de Mérida, Anejos de Archivo Español de Arqueología. (pp. 383-394). Mérida: Consejo Superior de Investigaciones Científicas.
• Crema, E., Bevan, A., Lake, M. 2010. A Probabilistic Framework for Assessing Spatio-temporal Point Patterns in the Archaeological Record, Journal of Archaeological Science 37.5: 1118-1130
• Costopoulos, A. & Lake, M. W., ed. 2010. Simulating Change: Archaeology Into the Twenty-First Century, University of Utah Press, Salt Lake City
• Zhang, H., Bevan, A., Fuller, D., Fang, Y. 2010. Archaeobotanical and GIS-based Approaches to Prehistoric Agriculture in the Upper Ying Valley, Henan, China. Journal of Archaeological Science 37.7: 1480-1489.

• MSc in Computational Archaeology: GIS, Data Science and Complexity

Funding

• Arts and Humanities Research Council
• AHRC and UCL Graduate Studentships