Abbak Ramazan Alpay2024-12-022024-12-0220232791-86372791-8637http://193.255.128.114/index.php/geomatics/article/view/751https://hdl.handle.net/20.500.13091/8154Tide gauge observations are samples of geodetic time series realized depending on the time. These observations like other experimental time series might have trends, short gaps, datum shifts and unequally spaced data which usually make disturbing effects to the analysis. In other methods (e. g. classical Fourier Transform), trend is removed before the analysis, the others (i.e. short gap and unequally spaced data) are taken over by filling any interpolation techniques. In this case the editing may produce well-composed time series, but it may obliterate the useful information in the series or even introduce artificial signals. This means that unwanted results take place during the process. There is an alternative method, called the Least-Squares Spectral Analysis (LSSA) which can bypass these problems without editing or pre-processing. In the present study, hourly sea level observations obtained from the Antalya tide gauge in Turkey were analyzed by using the LSSA method. Consequently, five hidden periodicities were successfully determined from the sea level observations containing difficulties mentioned above.Elektronikeninfo:eu-repo/semantics/openAccessLeast-SquaresMühendislik Temel Alanı>Harita Mühendisliği>Jeodezi>Ölçme Tekniği>KartografyaPeriodPeriodicitySpectral analysisTide gauge dataArticle