世界建筑

以明代夯土长城为代表的大型线性遗产是世界文化遗产的重要组成部分，正面临着自然环境变化影响下快速侵蚀和消亡的危机，亟须完成对其病害调查的保护基础性工作。本文基于预防性保护视角，构建了“调查—量化—评估”三位一体的大型线性遗产数字化技术路径，系统解析夯土长城病害特征并实现风险评估。通过无人机低空摄影测量技术完成明长城全线高精度三维建模与多时相图像采集，建立动态演化的数字三维模型，揭示长城墙体底部掏蚀病害发育的底部掏蚀、局部坍塌、整体失稳劣化时序规律。结合形态特征量化指标与三维点云模型分析，提出病害劣化风险分级体系，实现单一区段病害风险的精准定位与动态监测。相较于传统保护模式，本文提出的技术框架通过“监测—评估—预警”闭环管理，使遗产保护资源的配置效率得到结构性优化，为文化遗产病害诊断建立基础的数据底座并提供科学的参考依据，以期推动不可移动文物建筑保护与修复工作的进一步发展。

Large-scale linear heritage sites， exemplified by the rammed-earth Ming Great Wall， constitute vital components of World Cultural Heritage. These sites face a crisis of rapid erosion and loss driven by environmental changes， necessitating urgent baseline conservation measures grounded in deterioration surveys. Adopting a preventive conservation framework， this paper constructs an integrated "investigation–quantification–evaluation" digital workflow for large-scale linear heritage. This framework systematically analyzes deterioration characteristics in the rammed-earth Great Wall and facilitates risk assessment. High-precision 3D modelling and multi-temporal image acquisition of the Ming Great Wall were completed using low-altitude UAV photogrammetry. By establishing dynamically evolving digital 3D models， the study reveals the sequential deterioration pattern of basal sapping in Great Wall segments: basal sapping， localized collapse， and overall instability. Combining quantitative morphological indicators with 3D point cloud analysis， this study proposes a risk classification system for deterioration. This enables the precise localization and dynamic monitoring of deterioration risks for individual sections. Compared to traditional conservation approaches， the framework presented here optimizes resource allocation efficiency through a "monitoring–evaluation–early warning" closed-loop management system. It establishes a fundamental data substrate and provides a scientific basis for deterioration diagnosis in cultural heritage. This work aims to advance conservation and restoration efforts for immovable cultural heritage.