## 6 Conclusions  
This study highlights the essential importance of the InSAR remote sensing approach for monitoring subsidence in railways and their surrounding environment, thanks to its very accurate millimeter precision and independence from weather conditions. In order to demonstrate the efficiency of the InSAR approach, three separate time-series datasets from S-1 and CSK radar satellites were utilized across three specific places along a 30 km length of the railway section. The vertical velocities derived from both S-1 and CSK data analysis demonstrate a strong internal agreement with each other and a strong exterior consistency with measurements acquired from the diagnostic train, thus confirming the reliability of the used methodologies. This investigation further confirms that subsidence in two out of the  
Figure 13: Specialized workflow model. three test regions in the Konya basin is principally caused by the geological composition of the region, which consists predominantly of clay, and excessive groundwater extraction by the agricultural sector. The soil type significantly influences the railway line's geometry over time, leading to issues like subsidence and deterioration. The planning of the route should consider this circumstance and make efforts to minimize the presence of uneven and weak ground. Otherwise, the condition would result in ongoing costs due to deterioration and a rise in the frequency of maintenance or repairs for the railway component. However, constant and long-term ground subsidence in any location can cause significant damage to underground facilities, buildings and highways, with the exception of railways. This condition would greatly benefit the municipalities and other relevant authorities and should be taken into consideration. The cumulative subsidence charts in Figure 11, which were created for study areas #1 and #2, demonstrate that InSAR data are a reliable method for detecting vertical levelling issues in railway lines. For instance, if the data obtained from the diagnostic train indicate any changes in the line's movement, such as a sudden decrease or increase, it might potentially affect the entire or a significant portion of that region. However, it is impossible to figure out this impact using only the diagnostic train, as the train operates on a single track and the track width has a standard gauge width of 1435 mm, which is common typical in Turkiye and also in many other countries. Performing maintenance work by removing all the rails and consistently adding ballast reinforcement is ineffective in this scenario, as the ground would persistently shift. The primary source of this information is derived almost entirely from InSAR data. The technology is crucial for monitoring railway lines due to its significant advantages in this context. In a different scenario, similar to the third location, the diagnostic train encounters obstacles and challenges that hinder its ability to effectively conduct measurements within a station. These restrictions include the station being used as a parking lot and the presence of several switches, among other issues. An advanced InSAR remote sensing method plays a crucial role in such places. Since these measurement systems are fundamentally different in their nature and purpose, they cannot replace each other, but they can support one another in order to extend the observation of deformation over a larger area and increase the frequency of observations. Given the range of possibilities it provides and the strong correlation between SAR analyses and diagnostic train measurements, with an average correlation coefficient of 0.8 and a maximum of 0.93, along with an average standard deviation of the datasets of less than 3.4 mm/year, it should be considered as an additional observation technique. Furthermore, the broad observation required before the construction of the line is exceedingly challenging and nearly unattainable using alternative terrestrial measuring methods. This technique also yields substantial cost and time advantages.