The cultural landscape of the Zhangjiakou Ming Great Wall is susceptible to surface deformation, making the systematic conservation of cultural landscape in this corridor quite challenging. In order to fix the methodology and application gaps of Great Wall monitoring (large-scale linear heritage) systematically, the authors applied the SBAS-InSAR technology to the time-series deformation surveillance in this pilot case study. In the procedures of InSAR data processing, an external weather model (GACOS) was firstly used to reduce the atmospheric artifacts on interferograms; moreover, a 40 m Gauss and the Goldstein filters were sequentially applied for the phase noise suppression relevant to the natural landscape. In total 67 Sentinel-1 SAR images including 33 ascending and 34 descending data acquired from May 2017 to July 2018 were collected for the line of sight (LOS) deformation calculation using the SBAS-InSAR approach. The derived deformation rates were then projected onto vertical direction for the further analysis. Afterwards, motion rate profiles of ascending and descending datasets from a typical mountain and a flat area were selected for cross-validation, resulting in the maximum and averaged root mean square errors of 9.3 mm/a and 4.0 mm/a, respectively. With considering the significance level, the result demonstrates that 79.5% of the Great Wall corridor (85.1 km totally observed) is relatively stable (with deformation rates in the range of -10 mm/a to 10 mm/a) while remaining 20.5 % shows significant motions (the maximum subsidence rate up to -64.5 mm/a) using the 10 mm/a as the threshold. This pilot study implied the applicability of the applied SBAS-InSAR approach to the synoptic deformation monitoring of large-scale linear heritage sites.