Enhancing Subsurface Imaging: Optimization of Data Acquisition and Processing Parameters in Passive Roadside MASW Surveys

This study presents an in-depth analysis of optimal data acquisition and processing parameters for passive roadside multi-channel analysis of surface waves (MASW) surveys in urban settings. Passive MASW surveys utilize ambient noise from traffic and natural seismicity, making them a non-invasive and cost-effective method for subsurface investigation. Key parameters such as receiver array length, receiver spacing, offline distance, sampling frequency and acquisition time were systematically varied in controlled experiments and field studies conducted at NIT Arunachal Pradesh, India. Advanced data processing techniques including filtering, muting and dispersion image stitching, were employed to enhance the resolution and reliability of subsurface images. The results demonstrate that a 23-m array length with 1-m receiver spacing, a sampling frequency of 4000 Hz and a 10-m offline distance yield the highest quality shear wave velocity profiles. Validation against active MASW and Standard Penetration Test (SPT) data confirms the consistency and reliability of the passive MASW method. Additionally, the soil type is categorized using the National Earthquake Hazards Reduction Program (NEHRP) site classification based on Vs30 values from both active and passive MASW surveys. This classification is further compared with the Unified Soil Classification System (USCS). This research offers actionable insights for geotechnical engineers and urban planners, emphasizing the efficacy of passive MASW surveys for detailed urban subsurface characterization.