MOBILE OUTDOOR AUGMENTED REALITY FOR LANDSCAPE SCENARIO VISUALIZATION

C.N. Feuerherdt¹, W. Cartwright², M. Black³

1 - Masters candidate, RMIT University, Melbourne, Australia

2 - RMIT University, School of Mathematical and Geospatial Sciences, Melbourne, Australia

3 - Spatial Vision, Melbourne, Australia

craigfeuerherdt@gmail.com

Many government departments are undertaking projects looking at the trade-offs between social, economic and environmental factors. These projects are heavily reliant on complex, computer-based models that generate potentially thousands of scenarios which provide land management alternatives to assist land managers determine the most appropriate solution for a given issue or set of issues. These modelling frameworks have become more robust with increased computing power and improved understanding of the natural systems being conceptualised, however scenarios are typically disseminated using static, thematic maps and abstract graphs requiring detailed explanation to fully be understood by their audience. This often results in land managers not fully understanding the long term implications of the land practice change being suggested.

There are a variety of alternate methods for disseminating the complexities of landscape scenarios. Virtual Reality (VR) is a common alternative to traditional static maps allowing users to view scenarios in a wholly virtual world. The implications of scenarios are often difficult to realistically interpret due to a variety of factors including lack of peripheral vision, distance and scale percpetions.

Augmented Reality (AR) provides an alternate method, capable of providing an interactive environment for viewing landuse scenarios while immersed in the physical world. The application of AR to catchment (landscape) management has not been explored.

This paper presents the findings from research evaluating the effectiveness of AR as interface between complex models and the dissemination of those scenarios to land managers.

This paper will provide a background to AR , outlines the research project and will provide results from evaluation of a proof-of-concept prototype.