Envisioning the Urban Past: GIS Reconstruction of a Lost Denver District

Abstract

Large areas within the old urban core of American cities were destroyed in the postwar era as city leaders sought to counteract metropolitan decentralization by implementing urban renewal programs. For the most part, these places were deemed not worthy of documentation; indeed, areas declared as "blighted" were widely viewed as ugly, cancerous threats to the future health of the city and were enthusiastically demolished. For this reason, they have rarely been the object of study. This paper attempts to address the neglect of such lost landscapes by using GIS to provide a means to envision the urban past. Focusing on the case of the old Auraria district in downtown Denver, the paper pursues three aims. The first aim is to develop and test a new method for reconstructing urban landscapes at the district scale using GIS methods and data derived from historic Sanborn fire insurance maps. The second aim is to conduct preliminary analysis of this historic district-scale GIS, focusing on land use, spatial connectivity, and building massing, in order to evaluate its utility in generating new insight into the form, character, and functioning of the historic city core. The third aim is to assess the degree to which historic urban reconstructions of this kind can become valuable tools in contemporary urban planning efforts.

Advancing the historical geography of late Ottoman and British Mandate Palestine using GIScience: A review

“…Such 2D or 3D GIScience‐based models can provide lots of virtual options to view and examine the data, such as rotation of scenes and views from almost any angle or aspect. More importantly, they may enable a new look at the past and consequently make significant theoretical contributions to urban development and human activity at the time (Page & Ross, 2015; Tobiáš, Cajthaml, & Krejčí, 2018).…”

Understanding Cumulative Hazards in a Rustbelt City: Integrating GIS, Archaeology, and Spatial History

“…Each of these individual risk-weighted results were then summed to establish a total risk-weighted release for each facility, and all facilities within a sector were summed to create the final sectoral totals [41] (pp. [22][23].…”

“…The application of digital, spatial technologies has further enhanced the value of historical maps for such activities [17][18][19]. Archaeologists, geographers, and other disciplines with a historical focus have increasingly also used fire insurance plans as the basis for digital reconstructions of past environments [20][21][22][23].…”

Creating building-level, three-dimensional digital models of historic urban neighborhoods from Sanborn Fire Insurance maps using machine learning

“…By analyzing the changes in key physical elements that shape the urban environment, such as streets, public spaces, and buildings, Sanborn maps can provide insights into the shifting patterns of urban development, demolition, and redevelopment experienced by many U.S. cities. Sanborn maps are also useful in evaluating the impact of various factors such as natural disasters [ 50 ], depopulation [ 51 ], urban renewal [ 52 ], and railroad abandonment [ 53 ] on urban morphology and the physical, social, and economic dimensions of urban change across different historical periods. Due to the level of effort required to extract features and attributes manually from the maps, such analyses are often limited to small geographic study areas and limited sets of attributes.…”

“…Creating immersive and interactive 3D digital models using information from Sanborn maps can be highly beneficial in the applications of these maps within the humanities and social sciences. These models offer realistic 3D representations of past urban environments that can be compared across different time periods, and even contrasted with present-day urban landscapes, which can provide scholars and planners with an intuitive and comprehensive understanding of what has been lost or gained during urban development and its lasting implications [ 52 , 57 ]. In addition, these 3D models enable 3D analytics of past built environments, such as visibility analysis of historic buildings [ 58 ], which reveals how the evolution of cities and towns affects quality of life and uncover important patterns and relationships that may not be readily apparent in non-spatial data or 2D maps.…”