## 6 Conclusions  
Alpine forest regions, especially the eastern area of the Tibetan Plateau, are among the most landslide-prone areas owing to their complicated geological conditions and terrains. Understanding landslide development is a fundamental prerequisite for landslide susceptibility mapping and further landslide risk management. Incomplete landslide inventories may lead to underestimation of landslide risks and even lead to improper risk management strategies. Thus, for future landslide hazards risk management, a complete and precise landslide inventory is urgently required. However, in alpine forest regions, landslide identification through field surveying is a difficult and time-consuming task, and some landslides may not be detected. Thus, the current landslide inventory needs to be improved by incorporating objective and accurate observations. The InSAR technique is an efficient tool for this task owing to its ability to detect ground deformation with all-day and all-weather coverage. However, the role of the InSAR technique in understanding the development of potential landslides on the regional scale requires further clarification. Hence, aiming to promote the implementation of InSAR in landslide research in an alpine forest region, this study comparatively analyzed landslide inventories established using InSAR analysis and field investigation in Xiaojin County in the eastern area of the Tibetan Plateau. The results indicate that the InSAR technique is a feasible tool for identifying potential landslide sites as it can detect ground deformation with high accuracy and penetrate dense vegetation. It can not only improve the determination of the spatial distribution of landslides significantly but also contribute to the understanding of the historical deformation characteristics of landslides through continuous SAR observations. Moreover, InSAR analysis can not only facilitate the detection of the potential landslides but also provide deeper insight into landslide development at the regional scale. By establishing a complete landslide inventory using the InSAR technique, the understanding of landslide development with respect to the altitude, distance to roads, and distance to rivers is significantly improved at the regional scale. In addition, the joint analysis of InSAR results with geological conditions could improve understanding on the significance of the key factors controlling landslides at the regional scale, i.e., the stratigraphic occurrence and development of key joints. Therefore, when performing landslide risk assessment in alpine regions, a prior InSAR analysis is critical for obtaining a precise landslide inventory. For landslide identification, the InSAR analysis and field geological survey are complementary rather than competitive. On one hand, field geological surveys are more suitable for studying individual landslides and can provide detailed in situ landslide information, such as soil type, cracks, and failure mechanism. On the other hand, the InSAR analysis can be used to analyze landslides over a wider spatial dimension and to determine the regional development of landslides. Therefore, the combination of these two methods is of vital importance for the understanding of the distribution and development of landslides at the regional scale. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app132111851/s1](https://www.mdpi.com/article/10.3390/app132111851/s1)]([https://www.mdpi.com/article/10.3390/app132111851/s1](https://www.mdpi.com/article/10.3390/app132111851/s1)). Table S1. Sentinel-1 data used for the SBAS-InSAR analysis. Figure S1. Spatial coverage of SAR data used in this study. Figure S2. Baseline connections of the SAR images used in this study for ascending (left) and descending (right) orbit data sets. The red dots indicate the super reference images. Conceptualization, S.Z. and Z.G. ; methodology, S.Z. ; software, S.Z. ; validation, S.Z., Z.G., G.H. and K.L. ; formal analysis, S.Z. and Z.G. ; investigation, S.Z., G.H. and K.L.