## 1 Introduction
Despite the high accuracy of passive instruments, such as total stations, it is almost impossible to measure the behavior of civil structures in real time due to variations in the site's conditions. Furthermore, conventional photogrammetry requires time-consuming analyses of the measured data because it involves taking pictures, drawing, and analyzing the data. Accordingly, many studies have recently been conducted on the application of digital monitoring methods and automatic measurement methods in various industries [19; 20; 21; 22]. The monitoring of MSE walls is mostly based on manual and visual field inspections using basic devices such as inclinometers. This leads to irregularities in the reliability of the results, depending on the expertise of the person performing the measurement [12; 23; 24; 25; 26]. Various devices such as global positioning systems and total stations are widely used to measure the deformation and inclination of MSE walls, but they have many limitations in terms of time and physical accessibility [27; 28; 29; 30]. Researchers have extensively studied the use of scanning techniques in conjunction with digital image photogrammetry. In particular, remote sensing techniques are becoming popular for monitoring infrastructures such as MSE walls [23; 31; 32; 33]. Typical remote sensing techniques for monitoring structures include light detection and ranging (LiDAR), laser scanning (terrestrial), and synthetic aperture radar [23]. However, these techniques always have limitations, such as atmospheric conditions, the acquisition of measurement targets, and satellite access [34; 35; 36; 37]. [PERSON] and [PERSON] [38] investigated the use of terrestrial laser scanning to monitor retaining walls with precast concrete panels. They concluded that the deformation of the MSE wall facing can be identified by analyzing multi-temporal scans. [PERSON] et al. [10]used terrestrial laser scanning to obtain the point clouds of MSE walls. They then checked the monitoring potential using a flat model from which extraneous objects had been removed. The random sample consensus (RANSAC) algorithm [39] was used in the study. [PERSON] et al. [40] evaluated the tilts and movements of MSE walls with panels using terrestrial laser scanning. [PERSON] et al. [41] proposed a practical monitoring approach using a mobile mapping system for monitoring earth walls, but their results were limited to the transversal tilt angle. [PERSON] et al. [13] proposed a monitoring method for MSE walls with panels using mobile LiDAR. Digital image photogrammetry has the advantage of being able to obtain three-dimensional coordinates, which makes it possible to automatically determine the behavior of measurement points. In particular, the stability assessment of large civil engineering structures increasingly employs automated measurement systems based on digital image photogrammetry. The digital image photogrammetry procedure involves image acquisition, image processing, and analyses of the target object. Traditionally, photogrammetry has been analyzed using film-based image acquisition, but CCD and CMOS cameras have been recently applied. The scale and pixel size of the images based on CCD and CMOS cameras are important factors in image analysis for digital image photogrammetry, i.e., improving the accuracy of the image has a significant effect on the measurement results [42]. Therefore, the distortion correction of the camera lens may be necessary for improving the accuracy of geometric variables in digital images [42]. The continuous development of optical cameras, image processing, and 3D modeling technologies has made it easy to implement 3D models from 2D images based on digital image photogrammetry [43; 44; 45; 46]. This implies that 3D models constructed from 2D images can yield quantitative localization information. Thus, many physical constraints in the monitoring of the deformation of MSE walls can be solved.