Integrating Deep Mapping and Virtual Reality for Heritage Interpretation

Garand Spikberg, Michigan Technological University
Don Lafreniere, Michigan Technological University

With virtual reality experiences becoming an affordable entertainment option to the average consumer, there is a growing market ready to be tapped into in virtual heritage applications. Building on existing approaches to procedural modelling of historical landscapes using HGIS and ESRI’s CityEngine (Arnold and Lafreniere 2018) it is possible to rapidly produce representative 3D models of historical landscapes. The base built environment data used to produce the 3D models comes from the digitized Sanborn Fire Insurance Maps housed within the Copper Country Historical Spatial Data Infrastructure (CCHSDI), along with geocoded city directories, US census data, school records, historical disease tracking, and cumulative hazard maps. All of these datasets can be used to demonstrate things like socioeconomic status, air quality, and freedom from disease within the greater context of Michigan’s historical Keweenaw Peninsula. While CityEngine does support exporting some simple VR experiences they have limited functionality and scope, making it difficult to fully utilize these additional data sources. Using relatively new extensions and compatibility with Epic Games’s Unreal Engine, it is possible to develop VR applications with much greater scope and functionality. The introduction of this paper will outline the different modelling techniques, engine extensions/tools, and problems to overcome in importing an entire historical town into the Unreal Engine. We outline the development process of integrating data of the same town beyond the built environment to include virtual social environments such as neighborhoods with low socio-economic status, ethnic ghettos, and models of noxious industrial spaces. Our attempt at VR-as-deep-map may prove to be a powerful tool in expanding the interpretive capabilities of not just the CCHSDI but other HGIS datasets as well.

No extended abstract or paper available

 Presented in Session 118. Project Development