Chapter two focuses on the use of Local Digital Twins (LDT) in the physical living environment (PLE). It explores how LDTs fit into the current smart city and geospatial landscape and their ability to generate value for regions, cities and citizens. The chapter outlines what is unique about digital twins compared to other decision-making solutions and, through different use cases, examines the way in which LDTs close the gap between long-term policy and day-to-day decision-making. This chapter also focuses on how urban intelligence can be leveraged by LDTs to improve decision-making. By supporting evidence-informed decisions, LDTs can help drive better outcomes for urban communities. The decision-support function manifests itself on three analytical levels. The descriptive analysis is made possible thanks to data visualisation via 2D/3D maps and dashboards. The diagnostic analysis is achieved through the provision of aggregated insights. The prescriptive analysis, for its part, is grounded in simulation results that model future states based on desired parameters. The diverse analytical capabilities mean that LDTs have a role to play in various stages of a policy cycle, from design to implementation to evaluation. Given the complexity of translating urban dynamics into data and algorithms, all stakeholders must be involved in the co-interpretation process. This approach will ensure not only the accuracy of digital representations but also the ability of urban actors to benefit equally from LDT outcomes. In this regard, an important question to consider is whether and how LDTs can enable bottom-up, cross-sectoral engagement to make smart cities more inclusive. Engagement is not the only challenge facing LDTs. Technical limitations and barriers pertaining to data management, interoperability and the availability of adequate simulation models also abound. Addressing these issues is imperative to unlocking LDT’s potential to advance urban governance and making sure the technology resembles the real world it is designed to represent in form and substance.