Waveform re-tracking analyses with Fuzzy Logic on altimetry satellite data in Natuna Waters

Permana, R. D.; Nababan, Bisman; Panjaitan, James P.

doi:10.1088/1755-1315/429/1/012042

Cited by 1 publication

(6 citation statements)

References 27 publications

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“…They were found in near bay and small islands that had shallow waters (<200 m) and were close to the coastline (<17 km). Several studies in other regions reported similar findings, in which the peaky waveforms were found near to the coastline [8,25,29,46,47]. [8] also found that the highest percentage of peaky waveform was onshore, 5-6 km from the coastline.…”

Section: Waveform Classes In Halmahera Seasupporting

confidence: 59%

“…Over the Indonesian seas, previous studies (e.g., [23,25,28,29]) reported the performance of several retrackers using the geoidal height data, which highlighting the precision of retracked SSHs. While the accuracy of the retrackers is also valuable, such studies are yet to be done, thus becoming the motivation of this study.…”

Section: Introductionmentioning

confidence: 84%

“…However, it seemed that the percentage of Brown class over the study site was extremely lower when compared to other study regions in Southeast Asia. For example, the percentage of Brown waveforms >90% [24] over the South China Sea, ~94% [25] over Java Sea, and 95% [29] over Natuna Sea. Furthermore, [45] found 91% non-ocean like waveforms of Sentinel-3A Synthetic Aperture Radar (SAR) altimetry over the marginal seas at Southeast Asia.…”

Section: Waveform Classes In Halmahera Seamentioning

confidence: 99%

“…This was because the small threshold was the recommended algorithm for waveforms not dominated by surface scattering [35] while OCOG was only based on a statistical approach by calculating the gate width and the amplitude of waveform [17]. In the other regions of Indonesia e.g., Java Sea [23,25] and Natuna Sea [29], OCOG also showed poor performance and was estimated to be less accurate.…”

Section: Evaluation Of Waveform Retracking Performance Against Geoid Heightmentioning

confidence: 99%

“…Across Southeast Asia, several studies have been conducted to assess the retracking performance over the marginal seas [11,20,23,24,25,26,27,28,29]. The performance can be determined by comparing with geoidal height data and tide gauge data.…”

Section: Introductionmentioning

confidence: 99%

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Waveform Classification and Retracking of Jason-2 and Jason-3 in Halmahera Sea

et al. 2021

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The accuracy of sea surface heights (SSHs) estimation from satellite altimeters is strongly influenced by the microwave reflected signals (or waveforms). Waveforms in open oceans generally have ideal shapes following the Brown (1977) model. However, in coastal and shallow waters, the signals are disturbed by lands, thus resulting in complicated waveforms (non-Brown). Non-Brown waveforms produce inaccurate SSH estimations; therefore, specialized protocols such as waveform classification and retracking are crucial when attempting to produce accurate estimations. In this study, waveforms of Jason-2 and Jason-3 satellite altimeters in the Halmahera were classified and retracked using several algorithms, such as Offset Centre of Gravity (OCOG), Ice, Threshold, and Improved Threshold. The results showed that waveforms in the Halmahera Sea had ten generic classes with dominant class of the Browns. The validation results showed that all retrackers (except OCOG) had the value of correlations exceeding 0.75, and Root Mean Square Error (RMSE) smaller than 25 cm at a distance of 5-20 km from the land. The Threshold 10% was the most common retracker that appeared with the highest improvement percentage (IMP), meanwhile the Ice retracker consistently produced the best correlation (0.86) and the lowest RMSE (16cm). The retracking results showed that waveform retracking generally can improve SSH estimation accuracy from ocean (standard) retracker.

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