**3.1. Data availability of SARAL/AltiKa-retracked SLA over the coastal region**

**Figures 3**–**8** show the percentage of data availability over the regions. In general, the AltiKa shows an outstanding data recovery with ≥80% of data availability for all retrackers (see **Figures 1**–**3**). The spatial plot around the Strait of Malacca shows that the data availability is considerably high (≥70%) for most all passes of all retrackers, considering the complexity of the region with its narrow strait. However, several passes on the Andaman Sea show data availability of ≤70%. The percentage of data also degrades significantly over the eastern part of the Southeast Asia, around the Sulu Sea, near the Philippines coastal water. The data availability is ≤50% for several passes.

The close-up of the most complex area around Singapore, near the Riau Archipelago, and the Sulu Sea near the Philippines, are shown in **Figures 6**–**8**. The percentage of data around the Riau Archipelago is considerably high (≥70%) even though it is located in shallow water and surrounded by small islands. On the other hand, data over the Philippines coastal water degrades significantly with the percentage of data availability ≤50% for several passes.

**Figure 9** indicates the mean percentage of retracked SLA data availability within 30 km of the coastline for the five tested regions. Of all regions, the South China Sea has the highest (≥88%) percentage, with the MLE-4, Ice-1, and Ice-2 retrackers providing 88, 90, and 89% of data, respectively. The South China Sea has less complex coastal topography when compared to the other regions. Hence, the contamination of land within the altimeter footprint may not be severe in this region, making the retracking of sea level work efficiently and producing outstanding data coverage.

**Figure 3.** (a) The data availability (in unit %) for MLE-4 retracked SLAs over the Southeast Asia. Close up for (b) the Andaman Sea, (c) the Gulf of Thailand, (d) the Strait of Malacca, (e) the South China Sea, and (f) the Sulu Sea.

Validation and Quality Assessment of Sea Levels from SARAL/AltiKa Satellite Altimetry over the…

http://dx.doi.org/10.5772/intechopen.74399

51

Validation and Quality Assessment of Sea Levels from SARAL/AltiKa Satellite Altimetry over the… http://dx.doi.org/10.5772/intechopen.74399 51

changes in sea level over time relative to a datum, which is mean sea surface height (MSSH).

The tide gauge is designed to estimate tides. In order to find the non-tidal sea level, highfrequency tidal effects on the tide gauge data need to be removed. Tidal signals from the tide gauge are removed using a harmonic analysis method [37, 38]. Harmonic analysis is a mathematical process which separates the observed tide into basic harmonic constituents. This method can determine the amplitude and phase of tidal constituents from a long-time series observation. It models the tidal signals as the sum of a finite set of sinusoids at specific frequencies related to astronomical parameters. If the amplitude and phase of each constitu-

This section investigates the quantity of retracked SLAs from the three retrackers (i.e., MLE-4, Ice-1, and Ice-2) that are available from the AVISO SGDR product. The quantity is computed in terms of the percentage of data availability over the region (Section 3.1) and the minimum distance to the coastline (Section 3.2). These assessments are conducted to evaluate the

**Figures 3**–**8** show the percentage of data availability over the regions. In general, the AltiKa shows an outstanding data recovery with ≥80% of data availability for all retrackers (see **Figures 1**–**3**). The spatial plot around the Strait of Malacca shows that the data availability is considerably high (≥70%) for most all passes of all retrackers, considering the complexity of the region with its narrow strait. However, several passes on the Andaman Sea show data availability of ≤70%. The percentage of data also degrades significantly over the eastern part of the Southeast Asia, around the Sulu Sea, near the Philippines coastal water. The data availability is ≤50% for

The close-up of the most complex area around Singapore, near the Riau Archipelago, and the Sulu Sea near the Philippines, are shown in **Figures 6**–**8**. The percentage of data around the Riau Archipelago is considerably high (≥70%) even though it is located in shallow water and surrounded by small islands. On the other hand, data over the Philippines coastal water degrades

**Figure 9** indicates the mean percentage of retracked SLA data availability within 30 km of the coastline for the five tested regions. Of all regions, the South China Sea has the highest (≥88%) percentage, with the MLE-4, Ice-1, and Ice-2 retrackers providing 88, 90, and 89% of data, respectively. The South China Sea has less complex coastal topography when compared to the other regions. Hence, the contamination of land within the altimeter footprint may not be severe in this region, making the retracking of sea level work efficiently and producing outstanding data coverage.

amount of data that can be recovered through those three retracking algorithms.

**3.1. Data availability of SARAL/AltiKa-retracked SLA over the coastal region**

significantly with the percentage of data availability ≤50% for several passes.

Meanwhile, the altimeter measures the sea level above the reference ellipsoid.

ent is known, it can be removed from the sea level measurement [37].

**3. Qualitative assessment**

50 Multi-purposeful Application of Geospatial Data

several passes.

**Figure 3.** (a) The data availability (in unit %) for MLE-4 retracked SLAs over the Southeast Asia. Close up for (b) the Andaman Sea, (c) the Gulf of Thailand, (d) the Strait of Malacca, (e) the South China Sea, and (f) the Sulu Sea.

**Figure 4.** (a) The data availability (in unit %) for Ice-1 retracked SLAs over the Southeast Asia. Close up for (b) the Andaman Sea, (c) the Gulf of Thailand, (d) the Strait of Malacca, (e) the South China Sea, and (f) the Sulu Sea.

In contrast, the Sulu Sea has the lowest (≤68%) percentage of data coverage, with the MLE-4, Ice-1 and Ice-2 retrackers providing 64, 68, and 65% of data, respectively. The Sulu Sea is surrounded by many small islands, narrow straits, and shallow water with rough bottom topography. It is

**Figure 5.** (a) The data availability (in unit %) for Ice-2 retracked SLAs over the Southeast Asia. Close up for (b) the Andaman Sea, (c) the Gulf of Thailand, (d) the Strait of Malacca, (e) the South China Sea, and (f) the Sulu Sea.

Validation and Quality Assessment of Sea Levels from SARAL/AltiKa Satellite Altimetry over the…

http://dx.doi.org/10.5772/intechopen.74399

53

Validation and Quality Assessment of Sea Levels from SARAL/AltiKa Satellite Altimetry over the… http://dx.doi.org/10.5772/intechopen.74399 53

**Figure 5.** (a) The data availability (in unit %) for Ice-2 retracked SLAs over the Southeast Asia. Close up for (b) the Andaman Sea, (c) the Gulf of Thailand, (d) the Strait of Malacca, (e) the South China Sea, and (f) the Sulu Sea.

In contrast, the Sulu Sea has the lowest (≤68%) percentage of data coverage, with the MLE-4, Ice-1 and Ice-2 retrackers providing 64, 68, and 65% of data, respectively. The Sulu Sea is surrounded by many small islands, narrow straits, and shallow water with rough bottom topography. It is

**Figure 4.** (a) The data availability (in unit %) for Ice-1 retracked SLAs over the Southeast Asia. Close up for (b) the Andaman Sea, (c) the Gulf of Thailand, (d) the Strait of Malacca, (e) the South China Sea, and (f) the Sulu Sea.

52 Multi-purposeful Application of Geospatial Data

**Figure 6.** The data availability (in unit %) for MLE-4 retracked SLAs. Close up for area (a) near the Riau Archipelago and (b) over the Philippines coastal water.

**Figure 7.** The data availability (in unit %) for Ice-1 retracked SLAs. Close up for area (a) near the Riau Archipelago and (b) over the Philippines coastal water.

For the Andaman Sea, the Gulf of Thailand, and the Straits of Malacca, the AltiKa shows satisfactory results in data coverage with >72% data availability. Based on the result in **Figure 9**, 4 out of 5 regions have good data availability with more than 70% data coverage, thanks to the smaller AltiKa footprint size that has contributed to segregating the type of surface in

**Figure 9.** Mean percentage of AltiKa data availability over five experimental regions computed within 30 km of the coastline. It is computed from 18 passes for the Andaman Sea and the Strait of Malacca, 16 passes for the Gulf of Thailand,

**Figure 8.** The data availability (in unit %) for Ice-2 retracked SLAs. Close up for area (a) near the Riau Archipelago and

Validation and Quality Assessment of Sea Levels from SARAL/AltiKa Satellite Altimetry over the…

http://dx.doi.org/10.5772/intechopen.74399

55

(b) over the Philippines coastal water.

transition zones (from water to land and from land to water) over coastal regions.

30 passes for the South China Sea, and 17 passes for the Sulu Sea.

one of the most complex archipelagos in the world [39]. This area also suffers from rapid changes in sea-state and quasi periodic-variation of surface roughness [40]. The altimetric waveforms could be severely corrupted due to the high complexity of the coastal topography, thus producing invalid estimations of geophysical information [8], particularly SLAs.

**Figure 8.** The data availability (in unit %) for Ice-2 retracked SLAs. Close up for area (a) near the Riau Archipelago and (b) over the Philippines coastal water.

**Figure 9.** Mean percentage of AltiKa data availability over five experimental regions computed within 30 km of the coastline. It is computed from 18 passes for the Andaman Sea and the Strait of Malacca, 16 passes for the Gulf of Thailand, 30 passes for the South China Sea, and 17 passes for the Sulu Sea.

For the Andaman Sea, the Gulf of Thailand, and the Straits of Malacca, the AltiKa shows satisfactory results in data coverage with >72% data availability. Based on the result in **Figure 9**, 4 out of 5 regions have good data availability with more than 70% data coverage, thanks to the smaller AltiKa footprint size that has contributed to segregating the type of surface in transition zones (from water to land and from land to water) over coastal regions.

one of the most complex archipelagos in the world [39]. This area also suffers from rapid changes in sea-state and quasi periodic-variation of surface roughness [40]. The altimetric waveforms could be severely corrupted due to the high complexity of the coastal topography, thus produc-

**Figure 7.** The data availability (in unit %) for Ice-1 retracked SLAs. Close up for area (a) near the Riau Archipelago and

**Figure 6.** The data availability (in unit %) for MLE-4 retracked SLAs. Close up for area (a) near the Riau Archipelago and

ing invalid estimations of geophysical information [8], particularly SLAs.

(b) over the Philippines coastal water.

(b) over the Philippines coastal water.

54 Multi-purposeful Application of Geospatial Data

It is comprehended that the Ice-1 retracker always outperforms the MLE-4 and Ice-2 retrackers, except for the Andaman Sea where the performance of the Ice-1 and Ice-2 retrackers are similar. In contrast, the MLE-4 always underperforms compared to the other retrackers, except in the Andaman Sea where the percentage is slightly superior than those of other two retrackers.
