Department of Social Sciences
We combine the Historical Spatial Data Infrastructure (HSDI) concept developed within spatial history with elements of archaeological predictive modeling to demonstrate a novel GIS-based landscape model for identifying the persistence of historically-generated industrial hazards in postindustrial cities. This historical big data approach draws on over a century of both historical and modern spatial big data to project the presence of specific persistent historical hazards across a city. This research improves on previous attempts to understand the origins and persistence of historical pollution hazards, and our final model augments traditional archaeological approaches to site prospection and analysis. This study also demonstrates how models based on the historical record, such as the HSDI, complement existing approaches to identifying postindustrial sites that require remediation. Our approach links the work of archaeologists more closely to other researchers and to municipal decision makers, permitting closer cooperation between those involved in archaeology, heritage, urban redevelopment, and environmental sustainability activities in postindustrial cities.
Understanding cumulative hazards in a rustbelt city: Integrating GIS, archaeology, and spatial history.
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/558
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