## 5 Discussion  
Conducting MT surveys in areas with significant noise sources presents a considerable challenge and requires meticulous data selection and processing. To begin with, it is important to evaluate the raw data and identify time segments with the least noise. This is where spectral analysis becomes crucial, as it provides insights into the noise characteristics present in the data, as presented in Section 4.1. Through time series and spectral analysis, the nighttime data were selected, as they were observed to have comparatively lower noise levels than daytime data. However, despite this, it is not possible to entirely eliminate noise, even during the night. In addition, if the correlated noise is present, using the remote reference method only would not suffice as it works to minimize noises on the basis that the noise in the observed sites and the local sites is uncorrelated. Consequently, the use of the remote reference method may still yield scatter shown in the transfer function curves, as shown in Figure 3. Thus, in highly populated areas where man-made noise is abundant, the conventional remote reference method might not suffice and calls for a better processing technique suited for such conditions. Despite this, we still managed to obtain adequate results from our survey. While the 1D inversion yields similar results between the TE and TM modes, this is not the case for the 2D inversion. This discrepancy is expected, as real field subsurface conditions are inherently heterogeneous. The 1D inversion cannot resolve 2D or 3D structures as effectively as higher-dimensional inversion methods. Nevertheless, the 1D inversion provides a clear view of the estimated boundaries, making it easier to identify these features. Even in conditions where a multidimensional inversion is applied, 1D inversion can still be valuable as a preliminary tool, offering a quick overview of the subsurface structure. The 2D inversion results demonstrate the sensitivity differences between both MT decomposition modes, as discussed in Section 1. The TE mode inversion effectively identifies the conductive bottom structure, suggesting deeper conductive features in the subsurface. On the other hand, the TM mode points to a possible vertical structure, which does not appear in the TE mode. However, it is crucial to note that the TM mode results may be influenced by certain artifacts. Specifically, noise from nearby infrastructure, such as the railway south of the study area, and roads and highways running parallel to the east-west \(E\) (\(Ey\)), may affect the inversion. A study by in Ilan, northeastern Taiwan demonstrates how electric trains have a stronger impact on the \(E\) in the direction parallel to the railway and on the \(H\) perpendicular to it [44]. Additionally, the absence of observation sites in areas where vertical structures are observed may result in inversion artifacts, potentially distorting the true subsurface structure. Given the possibility of external noise and inversion artifacts affecting the inversion results, interpretation should be made with caution when an MT survey is carried out in regions with significant noise interference. Noting the noise source location and orientation might be helpful in evaluating the noise-affected mode, which can minimize the possibility of misinterpretation. If one mode (either TE or TM) exhibits significantly lower data quality due to noise or 3D effects, including it in a joint inversion can degrade the overall result. In such cases, using only single-mode inversion may lead to a more reliable subsurface model [10; 52; 53]. Therefore, one should evaluate each inversion model before relying solely on the bimodal inversion as it may not always be the optimal approach. Comparing our results to the available geology and geophysical study results, we infer that our inversion results are still reasonable in representing the subsurface features below the study area.