Abstract
ABSTRACTSurvey data play a fundamental role in studies of social complexity. Integrating the results from multiple projects into large-scale analyses encourages the reconsideration of existing interpretations. This approach is essential to understanding changes in the Indus Civilization’s settlement distributions (ca. 2600–1600 b.c.), which shift from numerous small-scale settlements and a small number of larger urban centers to a de-nucleated pattern of settlement. This paper examines the interpretation that northwest India’s settlement density increased as Indus cities declined by developing an integrated site location database and using this pilot database to conduct large-scale geographical information systems (GIS) analyses. It finds that settlement density in northwestern India may have increased in particular areas after ca. 1900 b.c., and that the resulting landscape of de-urbanization may have emerged at the expense of other processes. Investigating the Indus Civilization’s landscapes has the potential to reveal broader dynamics of social complexity across extensive and varied environments.
Highlights
Investigating transformations in the distribution and density of past settlements is crucial to the identification of “signature landscapes,” which are those generated by specific social, cultural, and economic processes within specific physical environments (Wilkinson 2003: 4–9)
Identifying the signature landscapes that materialized the prevailing social processes that underpinned these dynamics requires large scale analysis that exceed the boundaries of most individual field survey projects
By integrating site location data from multiple projects, this paper offers new support for the interpretation that northwestern India comprised one or more of the Indus Civilization’s signature landscapes, where settlement densities chart trajectories of urbanization and de-urbanization, involving agglomeration and dispersal into areas with suitably favorable environmental conditions
Summary
Investigating transformations in the distribution and density of past settlements is crucial to the identification of “signature landscapes,” which are those generated by specific social, cultural, and economic processes within specific physical environments (Wilkinson 2003: 4–9). The identification and analysis of such landscapes contribute a large-scale dimension to models of social change, revealing interactions between societies and their dynamic and transforming environments. These investigations have the potential to transform these models, casting into high relief social processes that are dispersed across a broader landscape and may be hidden or obscured at the level of an archaeological excavation at a single site. Integrating datasets requires recognizing the limitations and errors incumbent to the production of each constituent survey project
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