Linking small- and large-scale Digital Twins: A concept

A Digital Twin (DT) is a data-driven model of a physical entity with two-information flows that enables the direct interaction between both. DTs of the natural environment are typically constructed by fusing multi-modal measurements of some physical phenomena using Artificial Intelligence (AI) methods. The physical entity interacts with the DT through natural changes whilst the DT interacts with the physical entity through automated changes in sensing systems and through decision-making processes. Large-scale DTs of the Earth system are currently in development through initiatives such as Destination Earth (DestinE) whilst small-scale DTs for local monitoring are in development for numerous applications such as hazard warning, agriculture and eco-hydrology. Currently these systems are being developed independently yet combining them offers opportunities for calibrating large-scale DTs and improving the resolution of large-scale DTs by replicating the dynamics of smaller systems using AI methods. In this contribution, we develop a new concept through which to link small- and large-scale DTs in order to automate an agile sensing system that can respond to natural environmental variability and directly measure changes of interest. Large-scale DTs are built primarily through Earth Observation (EO) data and describe regional to global scale changes in the Earth system whilst small-scale DTs simulate local variability using in situ sensors such as Terrestrial Laser Scanners (TLS). Linking the two means the large-scale DT can inform small-scale DTs by adapting their measurements (e.g. spatial and temporal resolution, focus area of interest, specific physical measurements) in response to regional changes in, for example, weather patterns. We focus on the following components: 1) using the small-scale DT to downscale the large-scale DT and ‘zoom’ into areas of interest; 2) using both the small- and large-scale DT to automatically detect changes in the environment and acquire new measurements without human intervention; and 3) using the small-scale DTs to calibrate large-scale DTs. With the increasing development of digital twin technology in the environmental sciences, our new concept will enable better integration of DTs and improve monitoring performance, which can improve decision-making.