A Digital Twin Framework for Biodiversity Risk Assessment in the Built Environment

The recent increase in the use of emerging technologies powered by artificial intelligence provides promising solutions to enhance biodiversity. However, there remains a gap in technology-driven frameworks that enable stakeholders to make real-time, risk-and biodiversity-informed decisions. To address this gap, the authors propose the concept of developing a Digital Twin (DT) of the biodiversity risk assessment process by incorporating multimodal data and interlinking environmental simulation outputs with risk evaluation mechanisms to provide stakeholders with actionable insights to prevent or mitigate adverse impacts on biodiversity. The risk assessment tool's ability to account for both positive and negative uncertainties, incorporate real-time data collection and analysis, and integrate expert input positions it as a practical enabler for biodiversity-aligned planning and development practices. This research has the potential to reshape how DTs are conceptualized and applied in sustainable construction, particularly by emphasizing the twinning of dynamic processes.