Joesan, Taqy Rahmawan (2026) Estimasi Sea Level Anomaly (SLA) Menggunakan High Frequency Altimetry Satelit 20 Hz Jason-3 Untuk Pemantauan Kenaikan Muka Air Laut Di Pantai Utara Pulau Jawa Tahun 2016-2024. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kenaikan muka air laut (sea level rise) merupakan salah satu indikator utama pemanasan global dan memberikan dampak yang signifikan terhadap wilayah pesisir padat penduduk serta bertopografi rendah, seperti pantai utara Pulau Jawa. Penelitian ini bertujuan mengestimasi Sea Level Anomaly (SLA) dan laju kenaikan muka laut menggunakan data altimetri satelit Jason-3 Geophysical Data Records (GDR) beresolusi tinggi (20 Hz) periode 2016–2024, serta mengevaluasi akurasinya melalui validasi terhadap data pasang surut. Parameter 1 Hz diinterpolasi ke resolusi 20 Hz menggunakan metode Inverse Distance Weighting (IDW), kemudian dikoreksi terhadap pengaruh geofisika untuk memperoleh Sea Surface Height (SSH) dan SLA. Data pasang surut dari sembilan stasiun Badan Informasi Geospasial (BIG) diolah menggunakan analisis harmonik least squares, proses de-tiding, dan Butterworth low-pass filter. Tren perubahan muka laut dianalisis menggunakan regresi Ordinary Least Squares (OLS), uji Mann–Kendall, dan estimator Theil–Sen, sedangkan variabilitas musiman dianalisis melalui dekomposisi Seasonal-Trend (STL) dan pengaruh ENSO dievaluasi menggunakan Oceanic Niño Index (ONI). Validasi dilakukan menggunakan koefisien korelasi Pearson, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), dan Mean Bias Error (MBE). Hasil penelitian menunjukkan rata-rata SLA bulanan sebesar 0,0143 m dengan standar deviasi 0,2069 m. Laju kenaikan muka laut diperoleh sebesar 4,42 mm/tahun berdasarkan estimator Theil–Sen dan 4,38 mm/tahun berdasarkan OLS. Nilai tersebut sebanding dengan laju kenaikan muka laut global terkini, namun belum signifikan secara statistik (p-value Mann–Kendall = 0,081; OLS = 0,066) karena periode observasi yang relatif singkat dan dominasi variabilitas ENSO. Hasil validasi menunjukkan nilai RMSE sebesar 0,134–0,440 m dan koefisien korelasi sebesar 0,067–0,515, dengan akurasi terbaik diperoleh di Jepara (r = 0,515) dan terendah di Tuban (r = 0,067). Bias negatif terbesar ditemukan di Semarang (MBE = −0,213 m) yang mengindikasikan pengaruh subsidensi tanah. Selain itu, SLA menunjukkan korelasi negatif terhadap ONI (r = −0,481), yang mengindikasikan pengaruh ENSO terhadap variabilitas muka laut di wilayah penelitian. Penelitian ini menunjukkan bahwa altimetri Jason-3 beresolusi 20 Hz mampu merekam dinamika muka laut di pesisir dangkal pantai utara Jawa dengan tingkat akurasi yang dipengaruhi kondisi lokal. Variabilitas muka laut selama periode 2016–2024 lebih didominasi oleh sinyal interannual ENSO dibandingkan tren kenaikan jangka panjang, sehingga estimasi tren yang lebih andal memerlukan rentang data altimetri yang lebih panjang.
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Sea level rise is one of the most integrative indicators of global warming and poses significant risks to densely populated, low-lying coastal regions such as the north coast of Java, where previous studies in Indonesian waters have generally relied on low-frequency altimetry with limited in-situ validation. This study aims to estimate Sea Level Anomaly (SLA) and the sea level rise rate using 20 Hz high-frequency altimetry from the Jason-3 Geophysical Data Records (GDR) over the 2016–2024 period along the north coast of Java and to evaluate its accuracy through validation against tide gauge observations. The 1 Hz parameters were interpolated to 20 Hz using Inverse Distance Weighting (IDW) and corrected for geophysical effects to derive Sea Surface Height (SSH) and SLA. Tide gauge data from nine stations of the Geospatial Information Agency (BIG) were processed using least-squares harmonic analysis, de-tiding, and a Butterworth low-pass filter. Sea level trends were analyzed using Ordinary Least Squares (OLS) regression, the Mann–Kendall test, and the Theil–Sen estimator, while Seasonal-Trend decomposition using Loess (STL) and the Oceanic Niño Index (ONI) were used to examine seasonal variability and the influence of ENSO. Validation was performed using the Pearson correlation coefficient, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Bias Error (MBE). The results show a mean monthly SLA of 0.0143 m with a standard deviation of 0.2069 m and a sea level rise rate of 4.42 mm/year based on the Theil–Sen estimator and 4.38 mm/year based on OLS regression. Although these values are consistent with recent global estimates, the trend is not statistically significant (Mann–Kendall, p = 0.081; OLS, p = 0.066), likely due to the relatively short observation period and the dominant influence of ENSO variability. Validation yielded RMSE values ranging from 0.134 to 0.440 m and correlation coefficients ranging from 0.067 to 0.515, with the highest agreement at Jepara (r = 0.515) and the lowest at Tuban (r = 0.067). The largest negative bias was observed at Semarang (MBE = −0.213 m), indicating the possible influence of land subsidence, while SLA exhibited a moderate negative correlation with ONI (r = −0.481). The study concludes that Jason-3 20 Hz altimetry is capable of capturing sea level dynamics along the shallow north coast of Java, although its accuracy varies according to local coastal conditions. Furthermore, sea level variability during 2016–2024 was dominated by interannual ENSO signals rather than a long-term trend, indicating that a more reliable estimate of sea level rise requires a longer altimetry observation record.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Sea Level Anomaly (SLA), Jason-3, frekuensi tinggi 20 Hz, validasi pasang surut, Pantai Utara Jawa, Sea Level Anomaly (SLA), Jason-3, 20 Hz high-frequency altimetry, tide gauge validation, north coast of Java |
| Subjects: | G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing G Geography. Anthropology. Recreation > GC Oceanography > GC89 Sea Level |
| Divisions: | Faculty of Civil, Environmental, and Geo Engineering > Geomatics Engineering > 29202-(S1) Undergraduate Theses |
| Depositing User: | Taqy Rahmawan Joesan |
| Date Deposited: | 08 Jul 2026 01:06 |
| Last Modified: | 08 Jul 2026 01:06 |
| URI: | http://repository.its.ac.id/id/eprint/134470 |
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