Temporal and Spatial Analysis of Deformation Monitoring of the Ming Great Wall in Shanxi Province through InSAR  
[PERSON]  
1 School of Information Science and Engineering, Shandong Agricultural University, Tian 271018, China; liuqi20025190163.com (Q.L. ); [EMAIL_ADDRESS] (X.W. ); 131818296990163.com (J.Z. ); [EMAIL_ADDRESS] (Z.Y)  
[PERSON]  
1 School of Information Science and Engineering, Shandong Agricultural University, Tian 271018, China; liuqi20025190163.com (Q.L. ); [EMAIL_ADDRESS] (X.W. ); 131818296990163.com (J.Z. ); [EMAIL_ADDRESS] (Z.Y)  
the Great Wall has been exposed to the influences of natural and human factors, leading to an increasing stability risk. In recent years, the Great Wall in China has experienced destruction, damage, and improper repairs, with occasional incidents of wall collapse. These challenges have significantly impacted the preservation and management of the Great Wall in China [15; 16]. The Ming Great Wall in Shanxi Province is an integral part of the Ming dynasty's Great Wall and faces extremely challenging circumstances due to limitations imposed by the surrounding natural environment when conducting large-scale field observations of the Ming Great Wall. Synthetic aperture radar (SAR) is a satellite-based technology that enables the collection of extensive ground information without physical contact with the target [17; 18; 19]. Since the 1980s, researchers have utilized SAR imagery to monitor cultural heritage and have demonstrated its reliability in sustainability and stability studies [20; 21; 22; 23; 24]. Among the studies utilizing SAR imagery for cultural heritage monitoring, those using interferometry synthetic aperture radar (InSAR) displayed marked advantages in deformation monitoring, owing to its wide coverage, high precision, high resolution, and all-weather capabilities [25; 26]. However, conventional differential InSAR (D-InSAR) techniques provide unsatisfactory results when monitoring the deformation of large-scale linear features due to factors like temporal and spatial decorrelation and atmospheric phase delay. Recent research has concentrated on the study of linear features, with particular attention from scholars both domestically and internationally being given to the small baseline subset InSAR (SBAS-InSAR) and persistent scatterer InSAR (PS-InSAR) techniques, owing to their high accuracy and noise resistance [27; 28; 29; 30; 31]. Studies using SBAS-InSAR and PS-InSAR techniques have already been applied to various linear features such as subways [32; 33; 34], bridges [35; 36], and high-speed railways [37; 38], producing positive outcomes. In recent years, scholars both domestically and internationally have utilized InSAR technology to monitor the surface deformation of several significant cultural heritage sites. For example, [PERSON] et al. applied SBAS-InSAR technology to monitor the surface deformation of the Zhangjiakou section of the Ming Great Wall in Hebei Province [39]. Similarly, [PERSON] et al. employed D-InSAR techniques to assess the surface deformation caused by the Made earthquake in Qinghai Province, focusing on the analysis of Zhalang Temple, a cultural heritage site associated with Tibetan Buddhism in Qinghai [40]. [PERSON] et al., on the other hand, conducted the surface deformation monitoring of the ancient pagodas in Bagan, Myanmar, using SBAS-InSAR and PS-InSAR technologies [41]. Additionally, [PERSON] et al. proposed a specialized algorithm suitable for complex terrains in mountainous areas to monitor surface deformation of the Shanhaiguan section of the Ming Great Wall in Hebei Province and produced a stability risk map for this section [42]. Building upon the studies conducted by scholars both domestically and internationally, this research combines Sentinel-1A ascending orbit data with the SBAS-InSAR technique to obtain a deformation velocity field of the Great Wall corridor in Shanxi.