Fangming Li

Historic gardens represent living heritage systems in which spatial configuration evolves through the interaction among vegetation dynamics, environmental conditions, and ongoing management. However, current 3D documentation approaches often treat these landscapes as static entities, limiting their ability to capture and interpret temporal transformations. This study proposes a multi-sensor, multi-temporal approach for the systematic documentation and monitoring of historic gardens, integrating UAV photogrammetry and mobile laser scanning (MLS) to enhance spatial completeness and analytical reliability.Two survey campaigns conducted at Villa Burba (Italy) in 2023 and 2025 produced multi-temporal datasets acquired under different environmental conditions. Following multi-sensor integration and temporal harmonisation, point cloud comparison was performed using the Cloud-to-cloud (C2C) distances and Multiscale Model-to-Model Cloud Comparison (M3C2) methods to quantify spatial differences. The results demonstrate centimetre-level geometric consistency and improved ground coverage by integrating UAV and MLS data, ensuring reliable comparability between epochs. Based on this, spatial changes were identified, including variations in vegetation structure, tree-removal events, terrain modifications, and changes to the internal watercourse. These findings were validated against botanical surveys and maintenance records, confirming their consistency with documented management activities and environmental conditions. To support interpretation and accessibility, the multi-temporal datasets were further deployed in GIS and on the Cesium platform using 3D Tiles, enabling interactive exploration and long-term data use. This proposed approach demonstrates how integrating photogrammetry with complementary surveying techniques can support multi-temporal analysis, contributing to more informed monitoring and interpretation of historic gardens as evolving landscapes.

The First Songhua River Bridge of the Chinese Eastern Railway (CER) entered service in 1901 and was protected by three military blockhouses constructed between 1915 and 1917. As the first metal bridge in the country exceeding one kilometre in length, the bridge represents a major achievement in the engineering history of the CER. Although the bridge preserves a substantial and diverse collection of historical archives, these materials have not been systematically organised, while archival records for the blockhouses remain scarce. In 1961, the original curved-chord through trusses and deck trusses were replaced and upgraded. To address these issues, this study proposes an Infrastructure HBIM (InfraHBIM) and HBIM–GIS integration methodology for this transport infrastructure heritage to support archival management, documentation, phase-based three-dimensional reconstruction and web-based remote access. The InfraHBIM model of the bridge representing its state between 1901 and 1961 was reconstructed using a forward modelling strategy based on historical archives, while the HBIM models of the blockhouses were developed through reverse modelling driven by point-cloud data acquired by drone photogrammetry. During the integration phase, heterogeneous datasets were organised within a GIS database derived from historical records and field investigations, and the integrated models were published via ArcGIS ^® Online to enable interactive visualisation, attribute query and remote access. The proposed approach provides a reusable reference for the digital management of large-scale linear heritage systems such as railways, canals and defensive networks, while supporting professional decision making as well as public interpretation and engagement.

Terrestrial laser scanning (TLS) enables the detailed three-dimensional characterization of forest stands, capturing structural elements from stems to individual branches in an objective and reproducible way. This high-resolution structural information is valuable for a wide range of applications, including precision forestry, forest management, and ecological and biodiversity monitoring. In addition, TLS-derived forest structure can serve as reference data for the calibration of area-wide remote sensing products, such as airborne laser scanning (ALS) point clouds, and for identifying the structural contributions to synthetic aperture radar (SAR) backscatter signals.Recent technological developments, particularly devices becoming lighter, easier to operate, and capable of functioning in both static and kinematic modes, have considerably broadened the applicability of TLS in forest environments. While multi-scan static TLS acquisitions still represent the gold standard in terms of geometric accuracy, kinematic laser scanning setups are increasingly able to provide point clouds suitable for many forest-related applications and offer advantages with respect to acquisition time and field logistics. In addition, improved usability and increasingly automated processing workflows have expanded the user base of TLS beyond remote sensing and surveying experts. As a result, TLS is now frequently integrated into applied forestry as well as inter- and transdisciplinary forestry research and academic education and training.Within the Earth Sensing Summer School 2025 in San Vito di Cadore (Italy), a student project group conducted forest point cloud acquisitions using multiple terrestrial laser scanning systems operated in both static and kinematic modes, complemented by UAV-based laser scanning (ULS) data. In the presented study, we show results derived from the data of this campaign, focusing on data acquired with a RIEGL VZ-600i terrestrial laser scanner operated in both static and kinematic acquisition setups. Both data acquisitions are performed with long-baseline RTK GNSS to provide absolute georeferencing, although GNSS accuracy is severely degraded within the forest. The analysis is based on a representative forest plot of approximately 2500 m², including around 150 trees. The plot is dominated by coniferous species, primarily Picea abies (Norway spruce), and is located on sloped terrain with sparse understory vegetation.We systematically compare the static and kinematic TLS acquisitions and the resulting point clouds with respect to acquisition time, data processing, point cloud completeness and occlusion effects. Furthermore, the point clouds are analyzed at the individual tree level, including semantic segmentation of individual trees and the derivation of key tree metrics. ULS data are used as a reference for the assessment of tree heights and the representation of upper canopy elements.The data acquisition was performed by students unexperienced with TLS after giving a 30 min introduction to the device and TLS in forest environments. Comparing data acquisitions, the two kinematic acquisitions took ~10 min each, the static acquisition resulted in 22 scan positions and an acquisition time of 1 h 35 min. Preliminary results of the initial data inspection indicate that the kinematic point clouds provide a more complete representation of tree tops than static point clouds.

Historic gardens are living forms of Cultural Heritage whose spatial identity is inseparable from continuous processes of growth, decay, and maintenance. Although recent advances in laser scanning, photogrammetry, and mobile mapping systems enable highly accurate three-dimensional documentation, most digital models remain limited to static representations. The temporal dimension, essential for understanding and managing garden heritage, is rarely integrated as an intrinsic component of spatial data. This paper explores an experimental four-dimensional integration framework for historic gardens that combines point cloud data, semantic and multi-source data fusion based on GIS, and web-based 4D visualization. Rather than aiming at a complete temporal reconstruction, the approach investigates how a single-epoch 3D survey can act as a temporal anchor for integrating historical documentation and future-oriented scenarios within a unified spatial environment. The framework is tested on the historic garden of Villa Burba (Rho, Milan, Italy). Using open-source tools, point clouds from mobile laser scanning are processed using machine learning and semantically structured in a GIS environment, where time is modelled as a relational property describing transformation processes. The integrated model is visualized in the Cesium web platform, enabling interactive exploration of spatial-temporal relationships. The results demonstrate the feasibility of a scalable and interpretable 4D framework for living landscape heritage.

This paper presents a comparative evaluation of six cloud-based platforms including ArcGIS Online, Cintoo, Flai, Pointly, Cesium ion, and Atis.cloud for historic garden conservation, applied to two contrasting case studies: the complex, large-scale Naxos Archaeological Park and the compact, formal Villa Burba in Italy. Results show that Cesium ion and Cintoo performed strongly in point cloud visualization, with Cesium ion offering responsive large-scale rendering and Cintoo supporting high-precision geometry and version control. Flai demonstrated effective AI-driven element classification, particularly in heterogeneous landscapes, while Pointly required manual refinement and showed limited adaptability to organic features. ArcGIS Online excelled in stakeholder usability and layered documentation but lacked native 3D analytics. Collaborative functions were best addressed by Cintoo and Atis.cloud. Temporal functionality, such as phase comparison or seasonal tracking, remained limited, with no platform providing fully integrated support. The study highlights the fragmented nature of current solutions and argues for a modular, garden-oriented CDE model, integrating semantic intelligence, temporal awareness, and stakeholder-specific interfaces to support adaptive, sustainability-sensitive historic garden conservation in the cloud.

This paper presents a comprehensive scoping review of the application of 3D digital technologies in the documentation, conservation, and management of historic gardens and related cultural heritage. By analyzing a curated selection of literature, this study assessed the current state of research, highlighting trends in publications, the geographic distribution of contributors, and the key technologies employed. Using bibliometric methods and visualization tools, followed by a case study review, this review identified significant research hotspots and technical methodologies, particularly focusing on advanced techniques such as mobile laser scanning, UAV photogrammetry, and point cloud processing and their relationships with end users. The findings emphasize the importance of integrating multiple technologies to capture the diverse elements of historic gardens, including architectural features, vegetation, and topography. This review also underscores the significance of dynamic landscapes facing challenges posed by environmental degradation and urban development pressures. Moreover, it discusses the limitations of existing research and outlines future opportunities, such as the development of 4D documentation systems and the incorporation of AI for improving heritage management. This paper concludes by recommending interdisciplinary collaboration and public engagement to enhance the accessibility, understanding, and sustainable management of historic gardens through innovative technological applications.

This paper presents a comprehensive scoping review of the application of 3D digital technologies in the documentation, conservation, and management of historic gardens and related cultural heritage. By analyzing a curated selection of literature, the study assesses the current state of research, highlighting trends in publication, geographic distribution of contributors, and the key technologies employed. Using bibliometric methods and visualization tools, followed by case study review, the review identifies significant research hotspots, technical methodologies, particularly focusing on advanced techniques such as mobile laser scanning, UAV photogrammetry, point cloud processing, and their relationships with end users. The findings emphasize the importance of integrating multiple technologies to capture the diverse elements of historic gardens, including architectural features, vegetation, and topography. The review also underscores the significance of dynamic landscapes facing challenges posed by environmental degradation and urban development pressures. Moreover, it discusses the limitations of existing research and outlines future opportunities, such as the development of 4D documentation systems and the incorporation of AI for improving heritage management. The paper concludes by recommending interdisciplinary collaboration and public engagement to enhance the accessibility, understanding, and sustainable management of historic gardens through innovative technological applications.

Large archaeological areas or archaeological parks located within urbanized areas suffer more than other sites from anthropic pressure (urbanization and tourism), to which are added all the problems related to their conservation, safeguarding, fruition, management, maintenance, etc. Effective management strategies are essential. The use of Web Platforms in the management of 3D data is emerging as an effective solution for balancing conservation and development within large archaeological sites. This paper presents a case study of the Naxos Archaeological Park, Sicily, Italy. This case study highlights the role of advanced survey techniques, such as Mobile Mapping Systems and UAV-based photogrammetry, in generating extensive and comprehensive 3D datasets. It explores the possible contribution given by commercial web platforms for 3D data management in supporting design and development projects with reality capture data. Web platforms offer significant advantages by providing a shared environment for visualizing, interacting with, and processing large datasets. These platforms enable real-time collaboration among professionals with varying levels of expertise, fostering data sharing and reducing the need for local computing resources. This article provides a comparison methodology by testing and evaluating four commercial platforms: FlyVast, ATIS.cloud, Flai, and Cintoo, testing their functionalities and performances. It is then presented the adopted platform, Cintoo, and explained the reasons of the choice and its suitability for the project goal. Finally, it is provided an overview of the principal reasons that support the adoption of web platforms for sharing and collaboration supported by accurate 3D data, focusing on the potential cost reduction and efficiency.