The Alan Turing Institute (GB)
Policy makers at local, national, and international level are increasingly being required to make decisions that mitigate the effects of climate change on society and the economy. Earth Observations (EO) are already a very important source of data to support such decisions, but making reliable predictions from this data is very difficult, particularly for more decentralised and polycentric decision-making processes, which are prevalent in the European context.
Therefore, the aim of this project is to pioneer the development of scenario-planning digital twins (SPDT), that can support decentralised and polycentric decision-making processes. The new SPDT will demonstrate how Earth observation (EO) datasets can be integrated with multilevel agent-based models (MABMs). The MABMs will enable specific scenarios to be explored. To demonstrate the concept, the focus will be on energy use in buildings and the wider built environments as this relates to several priority areas from the European Union’s Green Deal initiative.
The SPDT will be delivered in the form of a web application (with underlying web service) that works in standard web browsers (which is the user interface). The SPDT web app for energy use will be built from a specification that is informed by a Use Case co-developed with stakeholders and potential users. This engagement with key stakeholders and users will ensure maximum relevance and impact of the SPDT web app.
