Eco-Urban Futures: A More-than-human Approach to Multi-Agent Simulation for the Digital Twin of Urban Forests

Abstract

Urban forests are now digitalized as smart green infrastructures to mitigate environmental change. Cities are proactively planting and replacing trees considering their future ecosystem benefits, such as carbon sequestration, urban heat reduction, and water retention. Digital twin simulation is a key technology enabling this particular mode of governance, which generates future scenarios under various management schemes. These data inform decisions on tree selection and placement, thereby shaping forests into uniquely efficient and responsive urban organisms. Despite its positive prospects, however, the underlying ontologies of these digital forests are rarely questioned, often lacking consideration for the flora and fauna inhabiting the forests. The models built upon anthropocentric biases and values pose a risk of selectively consolidating futures where the forests are optimized only for humans, which does not always guarantee the same good future for multi-species.
Acknowledging that humans coexist with other forms of life, Eco-Urban Futures takes a more-than-human approach in designing the computational model and a simulation platform. The notion of more-than-human bodies was constructed as a strong concept to explore alternative modes of making sense of and acting upon data toward more-than-human forest governance. The designed interface enables users to navigate the forest data across diverse temporal, spatial, and agential scales, thereby urging policymakers, urban planners, and citizens to reimagine healthier futures for us-with-the-forest.