Quality control of the GNSS-IR sea level measurements by using K-means clustering

Hatipoglu C. B., TANIR KAYIKÇI E.

SURVEY REVIEW, vol.57, no.404, pp.438-451, 2025 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 57 Issue: 404
  • Publication Date: 2025
  • Doi Number: 10.1080/00396265.2025.2455374
  • Journal Name: SURVEY REVIEW
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Environment Index, Geobase
  • Page Numbers: pp.438-451
  • Karadeniz Technical University Affiliated: Yes

Abstract

Quality control is a crucial step in GNSS-IR data processing and is performed in this study using two methods: the peak-to-noise ratio and K-means clustering. Both quality control methods are applied to the SNR data at the MERS, TRBZ, and SNOP sites. K-means clustering shows better performance for the MERS GPS L1, Galileo L1, and SNOP GPS L2, while the peak-to-noise ratio shows better performance for the TRBZ GPS L1. The correlation coefficient between the GNSS-IR sea levels from the L1 signal and tide gauge is greater than 85%. These results demonstrate that K-means clustering is promising for quality control.