Turkish Journal of Earth Sciences
Abstract
This study investigates the effects of adaptive filtering, based on the least mean square algorithm, on the quality of multichannel analysis of surface waves (MASW) data and frequency-phase velocity (f-c) images. Specifically, the adaptive filtering method aims to decrease the noise and improve the determination of fundamental modes in f-c images. Both sample and field seismic data with varying noise levels were evaluated using adaptive filtering, resulting in significant improvements in f-c image quality. The filtered data displayed a wider frequency range of f-c images, and reduced noise compared to the original noisy data. Based on these findings, adaptive filtering can be considered an effective tool for enhancing the MASW data, particularly in environments with nonstationary noise, by improving the reliability of dispersion curve extraction from f-c images.
Author ORCID Identifier
DOĞUKAN DURDAĞ: 0000-0002-9995-9865
DOI
10.55730/1300-0985.1999
Keywords
Adaptive filter, f-c images, MASW, noise reduction
First Page
875
Last Page
885
Publisher
The Scientific and Technological Research Council of Türkiye (TÜBİTAK)
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
DURDAĞ, D (2025). Impact of adaptive filtering-based noise reduction on the quality of f-c images in MASW. Turkish Journal of Earth Sciences 34 (7): 875-885. https://doi.org/10.55730/1300-0985.1999
