Landscape engineering plays a crucial role in urban construction and the development of ecological civilization in China. It actively designs and modifies natural elements, such as water and mountains, acting as the primary living infrastructure. This field continually receives great recognition and praise. Recent academic research has prioritized the use of extended reality (XR) technology to create a real-time interactive visual environment to tackle the issues presented by the dynamic nature of landscape engineering. This paper utilizes the PRISMA method to filter out 68 research documents related to XR in landscape engineering construction and management for bibliometric analysis. A comprehensive review is conducted on the precise and efficient utilization of XR to solve various issues in the field of landscape engineering. Using Cite Space 6.2.R6 (a visual bibliometric software) to visualize knowledge structures and research topics, the analysis includes temporal and spatial examination, application scenario analysis, and technological hierarchy analysis. The paper summarizes the current challenges that XR still faces in the landscape engineering field and envisions extensible application scenarios for XR, providing a reference roadmap for the implementation of XR in landscape engineering.

Intelligent construction, as a crucial driving force for the transformation and upgrading of the construction industry, is currently reshaping the production processes and management models throughout the entire life cycle of buildings. Nevertheless, construction enterprises are confronted with issues, such as great difficulties in system integration, complexity in multi-field collaboration, mismatch of technological requirements, and disharmony between standards and management processes during the process of promoting intelligent construction, which have restricted its in-depth application. This paper adopts a combination of questionnaire surveys and text mining methods to accurately gain insights into the actual situation of the application of intelligent construction in Chinese corporations. Cite Space is utilized to conduct keyword co-occurrence and clustering analyses and to construct the correlation atlas of the intelligent construction system, which are used to conduct in-depth analyses of its development trends and internal correlations. The research results demonstrate that aspects, such as building information modeling (BIM), smart construction sites, intelligent equipment, and prefabricated construction, exhibit significant development trends in the field of intelligent construction. Moreover, the precise matching between technology and the business needs of enterprises is of vital importance for the efficient implementation of intelligent construction. This research provides clear technological and management paths for intelligent construction in Chinese corporations, aiming to promote the standardization process of intelligent construction for enterprises and the industry and to facilitate the digital transformation and upgrading of the construction industry.

Building Information Modeling (BIM) is a very effective technology for supporting lean construction. However, the current application of BIM during the construction phase does not incorporate all necessary elements of the construction site in a comprehensive manner. Additionally, the depiction of the construction process lacks the desired level of detail. These limitations impede the application of BIM-based lean construction. In this paper, we propose a full-element and multi-time-scale modeling approach to BIM during the construction phase. Our method first establishes a full-element model by reconstructing the main body of the building based on construction subdivision dimensions, construction technology, and management objectives. We then create a three-dimensional model that includes a process elements model of circulating materials, temporary facilities, construction machinery, and surrounding environmental elements. The integrated model of these elements provides a comprehensive representation of BIM at any static time point. Second, we conduct multi-time-scale simulations based on the full-element model. Our approach divides the entire time, local time, and special time points into three scales to simulate project progress, local structure construction technology, and working conditions. A case study of the Daxing International Airport construction project verifies that our method can achieve lean management of construction resources. Full-element modeling provides a comprehensive BIM representation at any static time point, thereby supporting lean construction by improving construction resource management, reducing costs, and enhancing efficiency.

Regular on-site inspection is crucial for promptly detecting faults in water supply networks (WSNs) and auxiliary facilities, significantly reducing leakage risks. However, the fragmentation of information and the separation between virtual and physical networks pose challenges, increasing the cognitive load on inspectors. Furthermore, due to the lack of real-time computation in current research, the effectiveness in detecting anomalies, such as leaks, is limited, hindering its ability to provide immediate and direct-decision support for inspectors. To address these issues, this research proposes a mixed reality (MR) inspection method that integrates multi-source information, combining building information modeling (BIM), Internet of Things (IoT), monitoring data, and numerical simulation technologies. This approach aims to achieve in situ visualization and real-time computational capabilities. The effectiveness of the proposed method is demonstrated through case studies, with user feedback confirming its feasibility. The results indicate improvements in inspection task performance, work efficiency, and standardization compared to traditional mobile terminal-based methods.