In this study, we aimed to implement information obtained and refined from garden elements in heritage conservation, monitoring, and management to precisely construct an information model of classical Chinese gardens, including information on the garden entity, garden space, and garden attributes, etc., and to improve the management efficiency of classical Chinese royal gardens. Three-dimensional laser scanning technology and point cloud information were used to accurately collect and process digital information from classical Chinese royal gardens. After classifying and processing the point cloud data, correlations therein could be further assessed and used to greatly improve the accuracy and management efficiency of spatial information. To provide a more convenient solution for the subsequent conservation and management of landscape heritage, a method for establishing a three-dimensional digital information database and a full life-cycle application management platform for classical Chinese royal gardens is proposed in this research. This method has broad applications for the digital conservation and management of cultural heritage.

Historic gardens contain a greater number and variety of ancient trees, which are older, have unique forms, and larger volumes. These trees hold significant value in both natural ecosystems and cultural heritage. However, current research on the carbon sequestration value of ancient and non-ancient trees in historical gardens is relatively lacking. Based on the unique morphology and carbon storage estimation needs of ancient trees in historic gardens, this paper proposes a morphology-based point cloud single-tree segmentation method. This method can precisely extract the morphological structures of various tree species and accurately estimate their carbon storage. From the perspective of carbon sequestration, it evaluates the correlation between the structural characteristics and carbon storage of trees in historic gardens, as well as the potential changes in their carbon storage capacity.Using the Jing Yi Park’s Jian Xin Pavilions in Fragrant Hills Park as a case study, this method was applied to extract structural indicators of 116 ancient and non-ancient trees. The total carbon storage was found to be 19,171.13 kg, with an average carbon storage of 165.27 kg per tree. Among these, ancient trees accounted for 13,178.32 kg, or 68.74% of the total carbon storage. The study revealed that the correlation between tree age and carbon storage varied by species, and there were significant positive correlations between carbon storage and tree height, DBH, and canopy volume. Notably, there was a significant linear growth trend between DBH, canopy volume, and carbon storage. By 2030, the total carbon storage is projected to increase to 21,924.96 kg, with an annual average increase of 393.40 kg, representing a growth rate of 14.4%.The results indicate that studying the correlation between structural characteristics and carbon storage of aged trees in historical gardens can shed light on the important role of trees in sustainable carbon sequestration. The precise extraction of tree information through 3D digital technology and the prediction of carbon storage potential not only offer new perspectives for the conservation of cultural heritage in historical gardens, urban microclimate planning and design, and spatial management of carbon sinks and emissions but also have significant value for promoting the scientific management and protection of urban green spaces.

With advancements in technology, virtual restoration of garden heritage has gained significant attention, yet the restoration of stone settings remains underexplored. Stone setting, small and naturally flexible, are vital elements in Chinese classical gardens. This paper introduces a comprehensive method for their virtual restoration, encompassing evidence verification, data acquisition, model creation, evaluation, and utilization of results. The approach aims to achieve high-precision restoration of complex stone settings using 3D digital technology. Applied to the Lingfeng stone in Wenyuan Pavilion of Yuanmingyuan, the method involves 3D digitization for existing parts and photo perspective reversion, grid positioning, and informed speculation for missing sections. The model’s accuracy is scientifically assessed, and the restoration results are effectively utilized. This case study confirms the method’s efficacy in high-precision virtual restoration, supporting the preservation and promotion of stone elements in classical gardens and enhancing the dissemination of garden heritage restoration achievements.