发表机构
CY Cergy Paris University; Musée national des châteaux de Versailles et de Trianon（塞吉-蓬图瓦兹大学; 凡尔赛宫国立博物馆）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对宫殿博物馆预防性保护，提出利用三维高光谱与LiDAR数据构建数字孪生，以增强EPICO方法在环境与文物状况关联分析中的决策支持能力。
AI 中文摘要
在当前能源与气候转型的背景下，历史建筑的预防性保护因其对建筑和艺术品的影响而尤为重要。建立环境变量与艺术品原位状况之间的相关性，需要进行全面且个体化的监测，从而理解因果机制。为应对这一挑战，EPICO方法提供了一个系统框架，通过多尺度监测以及环境参数与物体状况之间的相关性评估，来评估宫殿博物馆的劣化风险。本课题旨在通过创建数字孪生来增强这一决策支持工具，这些数字孪生由空间和物体的三维高光谱与LiDAR测绘数据驱动。
英文摘要
In the current context of energy and climate transition, the preventive conservation of historic buildings is particularly important due to their impact on architecture and works of art. Establishing the correlation between environmental variables and the condition of artworks in situ requires comprehensive and individualized monitoring, allowing for an understanding of cause-and-effect mechanisms. To address this challenge, the EPICO method provides a systematic framework for assessing deterioration risks in palace-museums through multi-scale monitoring and correlation between environmental parameters and object condition. The aim of the proposed topic is to enhance this decision-making tool with the creation of digital twins. These digital twins being fed with three-dimensional hyperspectral and LiDAR mapping of spaces and objects.
Journal refXXV ISPRS Congress : From Imagery to Understanding, ISPRS (International Society for Photogrammetry and Remote Sensing), Jul 2026, Toronto, Canada
