Methodology of UAV-based digital twins for smart environments

Smart environments represent an integrated system paradigm that enables continuous perception, dynamic analysis, and coordinated management of natural and built environments through multi-source sensing, information fusion, and system-level analysis. With the rapid advancement of unmanned aerial vehicle (UAV) technologies, their applications in smart environments have been increasingly expanded, providing high spatial–temporal resolution data to support environmental information acquisition. However, relying solely on UAV-based sensing and data processing remains insufficient for developing a systematic understanding of the overall structure and evolutionary processes of smart environments. As a theoretical and technological framework that connects physical and virtual systems, digital twins offer a promising pathway to address this challenge. Driven by the application requirements of smart environments, this paper focuses on the theoretical foundations of UAV-enabled digital twins and conducts a systematic methodological investigation from a systems perspective. We first analyse the core requirements of smart environments and UAV applications for digital twins. A theoretical architecture is then proposed, with digital twin modelling as the core, integrating the physical environment, virtual environment, and decision support. Based on this architecture, the key methodological elements of UAV-enabled digital twins are further synthesized, and application validation is conducted across multiple smart environment scenarios. This study aims to provide a unified methodological reference for the research and practice of UAV-enabled digital twins in smart environments.