长城作为典型的大型线性文化遗产，受到自然因素的多维度影响，尤其是风蚀和水蚀的影响最为广泛。长城文化遗产大部分位于野外，保存状况原始，其大量的自然损毁将严重影响整体价值。为有效应对这些自然环境因素的威胁，数字化保护途径成为当前长城文化遗产保护中的重要议题。本研究围绕长城文化遗产的自然损毁过程与数字化保护途径的科学问题展开，提出基于“认知-方法-实践”的研究框架，旨在为长城文化遗产的保护利用传承提供科学依据。从三条路径进行探讨：一是加深对长城文化遗产自然损毁过程的认知，二是基于数字孪生技术的长城文化遗产模拟预测的方法，三是赋能面向长城国家文化公园建设的保护规划实践。首先，通过田野调查和多源数据采集，分析风、水、地形等自然环境因素对长城文化遗产的影响。采用无人机遥感、激光扫描等技术，获取长城文化遗产的病害数据，探讨不同自然因素的作用过程，为后续的数字孪生模型构建奠定基础。其次，构建多尺度、多层次的长城文化遗产数字孪生建模方法。通过仿真模拟技术，动态预测长城文化遗产在强风、降水等环境条件下的损毁过程，并针对不同的病害特征进行保护优化。仿真模拟不仅能进行病害预测，还可以根据实时环境数据对保护策略进行动态调整，从而提高保护措施的精准性和灵活性。此外，结合数字孪生技术，提出赋能长城文化遗产保护实践的5条途径，包括遗产现状评估、保护规划优化、风险监测干预、展示利用传承、多元体系保障等。并在北京密云蟠龙山长城文化遗产和宁夏吴忠北岔口长城文化遗产的两个典型案例中验证这些保护途径的有效性。结果表明，数字孪生技术在长城文化遗产的保护中具有广泛应用价值。通过病害认知、模拟预测及动态优化等方面，可提升长城文化遗产保护的科学性与精确性。其优势在于其可不断更新并及时响应环境变化，确保保护工作与环境本底相匹配。研究的主要创新点包括：（1） 构建了城乡规划视角认知长城文化遗产病害过程的系统分类；（2） 构建了面向长城文化遗产数字孪生的数据采集与建模方法；（3） 构建了面向长城文化遗产自然损毁的侵蚀模拟及预测方法。通过数字孪生技术，认知长城文化遗产的自然损毁过程，探索多项技术方法集成的保护利用传承路径，为其他大型线性文化遗产的数字化保护实践提供参考。

The Great Wall, as a typical large-scale linear cultural heritage site, is subject to multi-dimensional impacts from natural factors, with wind erosion and water erosion being the most prevalent. The majority of The Great Wall Cultural Heritage is located in open and relatively untouched environments, where extensive natural degradation severely threatens its overall value. In response to these environmental threats, digital preservation approaches have emerged as a key focus in the protection of The Great Wall Cultural Heritage. This study addresses the scientific issues surrounding the natural degradation processes and digital preservation approaches for The Great Wall Cultural Heritage. It proposes a "Cognition-Method-Practice" research framework aimed at providing scientific foundations for the preservation, utilization, and transmission of the Great Wall’s heritage. The research explores three key pathways: first, deepening the understanding of the natural degradation processes of the Great Wall’s heritage; second, developing simulation and prediction methods based on digital twin technology; and third, empowering heritage protection planning practices for the construction of the Great Wall National Cultural Park. Initially, through field investigations and multi-source data collection, the study analyzes the effects of wind, water, and topography on The Great Wall Cultural Heritage. Technologies such as drone remote sensing and laser scanning were employed to collect data on the wall's degradation, exploring the processes of different natural factors and laying the foundation for subsequent digital twin model construction. Next, a multi-scale, multi-layered digital twin modeling approach for The Great Wall Cultural Heritage was developed. Using simulation technology, the dynamic prediction of the degradation process under conditions of strong winds and heavy rainfall was carried out, and protection strategies were optimized for different degradation characteristics. Simulation not only facilitates the prediction of damage but also enables real-time adjustments to protection strategies based on environmental data, thus enhancing the precision and flexibility of preservation measures. Additionally, the study proposed five pathways to empower the practical application of digital twin technology in the protection of The Great Wall Cultural Heritage. These include heritage condition assessment, protection planning optimization, risk monitoring and intervention, heritage display and transmission, and multi-system support. These pathways were validated through two typical case studies: the Great Wall heritage site in Panlongshan, Beijing, and the Beichakou section of the Great Wall in Wuzhong, Ningxia.The results indicate that digital twin technology has significant application value in the protection of The Great Wall Cultural Heritage. Through the recognition of degradation processes, predictive simulations, and dynamic optimization, the scientific rigor and precision of preservation efforts can be greatly enhanced. One of the technology's key advantages lies in its ability to continuously update and respond promptly to environmental changes, ensuring that preservation efforts remain aligned with environmental conditions. The main innovations of this study include:(1) Developing a classification system for the degradation processes of The Great Wall Cultural Heritage from an urban planning perspective, revealing the impacts of various natural factors on the heritage. (2) Creating data collection and modeling methods for the digital twin of The Great Wall Cultural Heritage, providing technical support for accurate digital preservation. (3) Establishing simulation and prediction methods for natural degradation, enabling dynamic adjustment of preservation strategies. Through the application of digital twin technology, this study advances the understanding of the natural degradation processes of the Great Wall's heritage, explores integrated pathways for preservation, utilization, and transmission, and offers valuable references for the digital preservation of other large-scale linear cultural heritage sites.