Recent advances in three-dimensional (3D) scanning and reconstruction technologies based on light detection and ranging and digital imaging have greatly expanded the ability to capture and use 3D representations of real-world environments in engineering and environmental domains. High-performance laser scanners, mobile mapping systems, unmanned aerial vehicle-based sensing platforms, and image-based reconstruction techniques enable efficient acquisition of dense and accurate 3D data for large-scale structures and environments. These technologies have become essential for the development and maintenance of industrial facilities, civil infrastructure, construction sites, agricultural environments, and other physical assets. Furthermore, digital geometry data are increasingly recognized as a fundamental component of digital twins and cyber-physical systems that support monitoring, simulation, and decision making. In this context, 3D scanning and reconstruction technologies play a key role in bridging the gap between reality and virtual environments by transforming physical assets and environments into digital representations. Beyond advances in data acquisition, machine learning and data-driven approaches are enabling new possibilities for extracting semantic and structural information from acquired 3D data. As a result, increasing attention is being paid not only to data acquisition but also to the integration of sensing, understanding, modeling, and application technologies that facilitate the effective use of 3D data and digital representations of physical environments. Despite these advances, many challenges remain in acquiring, processing, interpreting, and using 3D data. Semantic understanding of complex environments, generation of structured digital models, integration with heterogeneous sensing data, and reliable data acquisition in challenging environments continue to be active research topics. This special issue presents recent advances in technologies that support the transition from reality to virtual environments, encompassing the acquisition, understanding, modeling, and application of 3D data. The selected papers cover a wide range of topics, including geometric fitting of industrial facilities, semantic segmentation and reconstruction of infrastructure point clouds, automated modeling of bridge structures, integration of point clouds and sensing data for digital twin-oriented construction management, evaluation of point cloud acquisition accuracy in agricultural environments, and dense 3D mapping in low-light conditions. We hope this special issue helps readers explore recent advances and share their knowledge and experiences in this rapidly evolving field. We sincerely thank all the authors for their valuable contributions and the reviewers for their careful and constructive reviews.
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