Date of this Version
Juckette, C. (2019). Using Virtual Reality and Remotely Sensed Data to Explore Object Identity and Embodiment in a Virtual Mayan City.
3D visualization, LiDAR (Light Detection and Ranging), and 3D modeling are not new concepts in archaeology, however when combined they represent a growing body of research that seeks to understand both how these tools can help us to study the people of the past, and the past itself. Recently, archaeologists have been creating large amounts of 3D digital assets because of new and more advanced technologies. Along with these digital assets has come a myriad of single object viewers—both web and desktop based. These platforms specifically focus on visualizing individual objects (i.e., artifacts or buildings). In contrast, 3DGIS and Virtual Reality (VR) software employ recreated landscapes with multiple 3D objects rather than single 3D models. The MayaCityBuilder Project (http://mayacitybuilder.org) employs Geographic Information Systems (GIS) and LIDAR data to simulate the ancient Maya city of Copan in a virtual space for immersive exploration. Using this environment as a virtual lattice, we embed object data into the actual simulated space of Copan, which users can explore using a virtual reality headset. I propose that such an environment allows us to explore the concept of object identity. Wherein the “objects” in the environment (i.e. 3D models of both remotely sensed extant objects and reconstructed buildings) are immersively evaluated by users who can better perceive the relationships between themselves and the “objects” with which they are interacting; resulting in insights that can push archaeological inquiry in new directions. Further, applying such an approach opens the door for 3D data reuse providing a platform that serves a unique database structure holding intuitive and perceptual data. In order to test these ideas, I embed multiple kinds of 3D models into the Copan VR platform and use the relationships between both the environment and the objects to explain object identity.
Advisor: Heather Richards-Rissetto