We are interested in the general question of how to augment the viewed landscape with representations of its otherwise invisible aspects and using these to prompt visitors to reveal previously unidentified aspects of that same landscape. We take a participatory, grassroots perspective, where expert and local knowledge are made available, but emphasis lies in the collection of new or explanatory information from the broadest feasible range of participants. This paper proposes a process for capturing not just individual experience of place, but collective experience built upon the individual. Crowd-sourced imagery and sound “bites” populate an augmented reality (AR) environment and prompts visitors to the AR to consider and respond to those originating experiences with their own. We provide and project additional environmental data to prompt embellishments, corrections or additions. In our prototype, the goal is to locate as-yet-unidentified valued highway landscapes, but the general approach has application in numerous other settings where understanding collective grassroots experiences in the landscape is essential for its protection and preservation.
Autor / Author: | Orland, Brian; Taylor, Micah; Mazurczyk, Tara; Welch-Devine, Meredith; Goldberg, Lacey; Candler Scales, Mary; Murtha, Timothy; Calabria, Jon |
Institution / Institution: | The University of Georgia, USA; The University of Georgia, USA; The Pennsylvania State University, USA; The University of Georgia, USA; The Pennsylvania State University, USA; The University of Georgia, USA; The University of Florida, USA; The University of Georgia, USA |
Seitenzahl / Pages: | 10 |
Sprache / Language: | Englisch |
Veröffentlichung / Publication: | JoDLA − Journal of Digital Landscape Architecture, 3-2018 |
Tagung / Conference: | Digital Landscape Architecture 2018 – Expanding the Boundaries: Landscape Architecture in a Big Data World |
Veranstaltungsort, -datum / Venue, Date: | Munich-Freising, Germany 30-05-18 - 02-06-18 |
Schlüsselwörter (de): | |
Keywords (en): | Augmented reality, cultural landscape, social media, crowd-sourced data |
Paper review type: | Full Paper Review |
DOI: | doi:10.14627/537642015 |
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