Landscape quality is a crucial factor for the heritage attractiveness of tourism, allowing tourists to experience both natural and cultural aspects along railway journeys. Moreover, railway landscape is a comprehensive system that defines the landscape observed and perceived by passengers and is characterized by the diversity and continuity of the train’s movement. Yunnan-Vietnam railway (YVR) heritage is the research object of this research, whose area encompasses various landscape types and heritage sites, providing great landscape enjoyment. Currently, the assessment methods specifically for railway landscape have been discussed less than for other landscape types, especially for a series of large linear sites like the YVR. To evaluate the value of railway heritage landscape along the railway, this paper proposes a methodology combining the Analytic Hierarchy Process (AHP), Delphi method, and GIS as an integrated spatial assessment. Creatively, this paper seeks to: (1) discuss the relationship between railway and landscape; (2) build a comprehensive evaluation system for the railway heritage landscape, covering the topics of history, tourism, ecology, heritage, social-culture, and visual quality; (3) quantify the landscape value of the YVR areas. Thus, the results of this research can be useful to future urban planning, development, and policymaking.

Historic buildings hold significant cultural value and their repair and protection require diverse approaches. With the advent of 3D digitalization, drones have gained significance in heritage studies. This research focuses on applying digital methods for restoring architectural heritage. It utilizes non-contact measurement technology, specifically unmanned aerial vehicles (UAVs), for data collection, creating 3D point cloud models using heritage building information modeling (HBIM), and employing virtual reality (VR) for architectural heritage restoration. Employing the “close + surround” oblique photography technique combined with image matching, computer vision, and other technologies, a detailed and comprehensive 3D model of the real scene can be constructed. It provides crucial data support for subsequent protection research and transformation efforts. Using the case of the Santo Stefano Church in Volterra, Italy, an idealized reconstructed 3D model database was established after data collection to preserve essential resources such as the original spatial data and relationships of architectural sites. Through the analysis of relevant historical data and the implementation of VR, the idealized and original appearance of the case was authentically restored. As a result, in the virtual simulation space, the building’s style was realistically displayed with an immersive experience. This approach not only safeguards cultural heritage but also enhances the city’s image and promotes tourism resources, catering to the diverse needs of tourists.

Historical villages bear historical, cultural, architectural, aesthetic, and landscape values, but they are facing a series of dangers and problems during the process of urbanization. Digital survey for traditional villages plays a crucial role in the preservation, planning, and development of this kind of heritage. The introduction of the terrestrial laser scanning technique is essential for heritage surveying, mapping, and modeling due to its advantages of noncontact measurement, accurate sensing of complex objects, and efficient operation. In recent years, TLS and related processing software (“SCENE”) have been widely presented as effective techniques for dealing with the management and protection of historical buildings in Fenghuang village. Thus, this paper highlights the process of using laser scanning to obtain architectural data, process point clouds, and compare the characteristics of historical buildings in Fenghuang village. The cloud-to-cloud registration technique is applied to build point clouds. As a result of model construction, some architectural patterns are summarized in this village, such as the spatial sequence of ancestral halls, the dominant position of memorial halls, and the character of building decorations and roof slopes. Furthermore, a BIM model is also explained to fulfill the statistical function for architectural components. In the future, more research can be fulfilled based on the built point cloud model, which will be beneficial for the development of the whole village.

The construction industry faces persistent challenges, including labor shortages and safety hazards, while traditional construction methods are increasingly strained by the complexity and sustainability demands of modern projects. The integration of robotics shows significant potential for mitigating labor shortages and enhancing safety on construction sites. The current adoption of robotics technologies is driven by both the maturity of robotics technology and the potential for cost reduction compared with manual labor. This review synthesizes recent advancements and trends in construction robotics through a bibliometric analysis of 212 publications indexed in Web of Science from 2002 to 2024. Key findings indicate a 320% increase in research output from 2015 to 2022, with dominant clusters focusing on autonomous navigation, human–robot collaboration, and sustainability-driven automation. Geographically, China and the United States lead in number of publications, with 67 and 65 articles, respectively; however, cross-border collaborations remain sparse, constituting fewer than 5% of co-authored papers. Keyword co-occurrence analysis reveals evolving priorities, including artificial intelligence (AI)-driven adaptive control, modular prefabrication, and the ethical implications of automation. Despite technological advancements, critical gaps remain in terms of interoperability, workforce retraining, and regulatory frameworks. This study emphasizes the need for interdisciplinary integration, standardized protocols, and policy alignment to bridge the divide between academic innovation and industry adoption, ultimately facilitating the global transition toward Construction 4.0.

The visual aesthetics of villages are remarkably affected by the exterior quality of traditional residences, influencing the impression and assessment of local culture. A proper scientific assessment of exterior quality can protect traditional cultures and improve the development of villages. This research was conducted in a village consisting of 115 residences (Mengjinglai village, which is on the border between China and Myanmar). The backpropagation (BP) neural network model with genetic algorithm (GA) was applied to evaluate the quality of the dwellings. All the evaluation values of the dwellings were defined by scores. Meanwhile, the score of each residence was affected by three main factors: architectural spatial elements, architectural construction elements, and historical and cultural elements. The results show that the village’s dwellings are well preserved and clearly express the traditional Dai style. Moreover, the GA–BP approach is more suitable than the traditional BP method for the assessment of the exterior quality. The quantitative machine learning model would be useful for other aspects of the assessment of similar villages in the future.

Scenic railway refers to the trains that operate for tourism purposes, which are mainly maintained for facilitating leisure activities, scenic tours, and heritage experiences. As both an extension of railway heritage and an important redevelopment method, this concept is meaningful for the touristic development of historical railways but has received less attention in academia. To understand the tourism and landscape values of scenic railways from a geo-historical perspective and discuss the recent techniques and methods for railway tourism, this article first introduces the relationship between railway and landscape and the concept of scenic railway in French literature. Secondly, it analyzes the current distribution of French scenic railways based on geographic information system (GIS) tools. Through georeferencing, mapping, data relating and joining, calculating, and classifying, different groups of scenic railways are systemized and published online. Following statistical treatment, the pattern of distribution of scenic railways in comparison with the standard-gauge railway system in France is revealed. Based on the discussions on scenic railways, further study should focus more on the landscape evaluation of scenic railways and its integration with other spatial technologies for deeper geo-analysis. Moreover, the research results can serve as a reference for the development of relative railway heritage and tourist activities.