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Research interests

Taking scientific data and spatial information and making it more useable, accessible, and effective for planning and community engagement. This work is primarily, but not exclusively, focused on supporting fire management in Northern Australia through three main research areas.

The use of Projection Augmented Physical Landscape technology for bringing science and local Indigenous knowledge together in a way that facilitates two-way learning about environmental history and science in the very diverse, cross-cultural, cross-linguistic space of northern Australia. The approach developed by Rohan, uses simulation games of landscape process projected onto 3D printed landscapes or sand that is shaped to fit the terrain. The use of this technology has successfully addressed the issue of supporting the integration of western scientific data with traditional indigenous knowledge in Australia, Cameroon and Mexico. This work was awarded the national AFR Higher Education, education technology award in 2018. Education More information here: landscapemodels.net

Developing fire behaviour simulation models. This work is developing a stochastic cellular automata fire behaviour simulation through a participatory modelling process that makes explicit the key variables affecting fire behaviour at a landscape scale in northern Australia This work aims to fill a gap in fire behaviour modelling tools by focusing on learning and participatory planning outcomes through fire behaviour simulation and explores the role of gamification for building a shared understanding of complex landscape processes. Operational applications of the Northern Australian Fire simulations have been applied to remote land management contexts throughout the Top-End of Northern Australia. More information here:  https://incendiarysim.wordpress.com/

Developing fire spread analysis tools for understanding assisting evidence-based fire management in northern Australia. This study seeks to support the application of this strategic fire management by providing a more detailed understanding of the landscape features that impede fire spread in Australia’s Tropical Savannas using long-term satellite-derived fire histories. The high frequency of fire in northern Australia provides a unique opportunity to investigate fire extinction in a way that supports on ground wildfire management planning. By combining long fire history data (> 25 years) in high fire frequency landscapes, it is possible to develop spatial datasets of fire extinction probability based on combining fire edges

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