## 4 Applications of InSAR in Landslide Monitoring
### Recent Advances in Landslide Monitoring with InSAR
#### 4.2.5 Advancements in Integrated Approaches Combining InSAR and Other Techniques  
The integration of InSAR and the global navigation satellite system (GNSS) has garnered significant attention in landslide monitoring over the past years. Several methods have been employed in the integration process. One approach involves the fusion of InSAR and GNSS data to improve the spatial and temporal resolution of deformation measurements [106]. GNSS provides high temporal resolution and precise 3D positional data at specific points, while InSAR offers high spatial resolution over broad areas. By combining these datasets, more comprehensive monitoring of landslide dynamics can be achieved. Also, GNSS data can be used to correct and calibrate InSAR-derived deformation measurements. This correction helps to mitigate residual atmospheric delay phase error, residual topographic phase error, and orbital errors in InSAR data, enhancing the accuracy of the displacement maps [107; 108]. Another significant advancement in the integration of InSAR and GNSS is the capability to achieve 3D deformation monitoring. By integrating GNSS data, which provides precise 3D positional information, vertical and horizontal deformation components can be decomposed from the LOS observations, thus obtaining a full 3D deformation vector [109; 110]. Finally, InSAR observations can be validated by the truth deformation provided by GNSS stations. This validation is crucial for confirming the reliability of InSAR data in various terrains and conditions [111; 112; 113]. In addition to the aforementioned combination with GNSS, spaceborne InSAR can also be integrated with other technologies, such as optical remote sensing [114; 115], light detection and ranging (LiDAR) [116; 117], and UAVs [118; 119], in landslide studies. These approaches provide a more comprehensive and accurate understanding of landslide behavior. Although InSAR technology is capable of providing extensive surface deformation information, it still faces challenges in understanding failure mechanisms and potential controls of landslides. Therefore, in some studies, InSAR results are combined with geotechnical analysis (physical models) to delineate the landslide behavior and explain the physical processes, thereby guiding mitigation strategies. Especially for urban slopes, utilizing physical models makes more practical sense due to their proximity to urban areas, indicating higher landslide risk and potential serious consequences. For instance, [PERSON] et al. [120] employed a combination of MT-InSAR and numerical modeling to assess urban landslide dynamics in eastern Romania, identifying the active deformation sectors and the underlying mechanisms. [PERSON] et al. [121] applied the limit equilibrium method (LEM) to model a landslide under various soil saturation levels and embankment scenarios, revealing the connections between InSAR-monitored instability, rainfall, and embankment construction. A key point to note is that in the construction of physical models, soil properties such as shear strength are often challenging to measure directly in the field or laboratory. Due to the study areas' location, the abovementioned studies are more accessible for fieldwork and have historical monitoring datasets, including borehole information. Nevertheless, the data availability for physical modeling is still a challenge in some situations. To address this, missing parameters can be estimated through back analysis [122]. Some scholars argue that InSAR data can also be utilized to calibrate geotechnical models by adjusting model parameters until the simulated outcomes correspond with the observed deformations [123]. This method ensures that the models accurately represent the actual conditions and behaviors of landslides. In addition, physical models may also make reasonable assumptions to reduce the need for soil and rock parameters, such as assuming homogeneous soil properties in depth and laterally.