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FECHA LÍMITE/DEADLINE/SCADENZA: 28/10/2016
FECHA CONGRESO/CONGRESS DATE/DATA CONGRESSO: 14-15-16/03/2017
LUGAR/LOCATION/LUOGO: Georgia State University in Atlanta, (Atlanta, Georgia, USA)
ORGANIZADOR/ORGANIZER/ORGANIZZATORE: Eleftheria Paliou ; Adrian Chase
Over previous decades many advances in archaeology and contemporary urban geography have been made using computational and quantitative methods to study cities and their built environments at various stages of development. In recent years the proliferation of new approaches allowing for the documentation and analysis of built spaces have enabled the acquisition of large volumes of data on ancient settlements encouraging fresh lines of enquiry. Advances in data acquisition via geophysics and remote sensing methods have offered a more comprehensive picture of cities, towns, and villages in two, three, and sometimes four dimensions. These developments have contributed to better understanding of the form, size, and spatial configuration of past settlements, and have facilitated their interpretation through various forms of computational analysis. Methodologies such as Space Syntax, 2D and 3D GIS based analysis, spatial interaction models, network analysis, and urban scaling have been employed to explore socio-economic aspects of culturally diverse settlements at different spatial scales. These studies demonstrate the potential of computational methods to offer insights into the social organisation of past societies, often from a comparative and interdisciplinary perspective, as well as the challenges entailed in applying these methods to fragmented archaeological datasets. This session invites papers that discuss the use of computational methods for the acquisition and analysis of settlement data at the micro (building), meso (settlement) and macro (regional) scales. We especially welcome papers on the innovative applications of 2D and 3D spatial analyses to the built environment, works that adopt a comparative and diachronic perspective, and studies that seek to evaluate the theoretical contributions and challenges associated with the use of these computational approaches.