# Stability Analysis of GNSS Stations Affected by Samos Earthquake
## 1 Introduction  
Stability analysis has a crucial role in deformation surveys for being sure of reliable and accurate measurements. In the context of GNSS deformation, monitoring stations measure the coordinates of stations on the Earth's surface with high accuracy. These stations are typically established at man-made structures or engineering projects as well as regions prone to seismic activities. Repeatability measurements involve the repeated measurement of the same GNSS station over multiple epochs to detect any changes or deformation in the monitored station or area [1, 2]. Reliable points away from deformation are needed to determine the deformation that occurs in an absolute measuring network [3, 4]. Reliable points or datum points should be selected delicately to conduct an analysis of deformation. These reference points are chosen to be fixed in deformation analysis. These points serve as stable references to detect changes in the monitoring area with repeated measurements; therefore, the stabilization of reference points directly affects the results [5, 6]. However, if a reference point is unstable or experiences deformation itself, utilizing this point as a reference can lead to distorted results. This will bias the results so that actual deformation cannot be detected. As a consequence, the selection of stable reference points is of importance to ensure the integrity and validity of deformation analysis. Therefore, reference points should be checked first, and any unstable points should be excluded. To determine single-point displacement, different approaches have been tried in the literature, such as the Gauss-Markov method, the implicit hypothesis method, robust estimation methods [7], the similarity transformation (S-transformation) method [8] and Msplit estimation [9, 10, 11]. Besides this, [PERSON] [12] studied the power of the global test in deformation analysis, [PERSON] [13] used a Bayesian approach in stability analysis of monitoring networks and [PERSON] [14] used squared Msplit estimation to identify unstable reference points. Among these research methods, S-transformation is a widely used approach for researchers and engineers because of the simplicity and independence of datum points. [PERSON] et al. [15] worked on a monitoring network comprising seven stations, with four IGS stations serving as reference points and three local CORS (Continuously OperatingReference Stations) from ISKANDARnet as test objects. They tested reference stations with iterative weighted similarity transformation (IWST) and subsequent deformation analysis using S-transformation, and concluded that no significant movements exceeding the threshold were observed at the reference stations. [PERSON] et al. [16] developed the \"threshold approach\" and \"statistical test approach\" based on a model of coordinate S-transformation to evaluate the stability of datum points in a first-order GNSS deformation monitoring network. The goal of the research is to assess the effectiveness and advantages of applied approaches in confirming the stability of the reference stations. The proposed method has the advantage of simplicity of calculation, and the results are insensitive to the choice of datum points. Furthermore, it ensures the unity of the reference framework and reference epoch; in other words, the proposed method is independent of the specific reference point or the time at which the measurements are taken. [PERSON] [17] suggested an algorithm based on sensitivity analysis of a network in the north of Israel, where the method is investigated against the Simple Transform Fault and the Locked Fault models. This shows that sensitivity analyses can be made not only on human-made objects but also on earthquake-related studies. In a tectonic sense, interseismic, coseismic and postseismic displacements on the crust alter due to strain accumulation on a fault or the magnitude of an earthquake. Active faults in Turkey can generate \(\mathrm{Mw}\geq 7\) earthquakes [18; 19].