近年來，隨著全球暖化加劇，全球海水面持續上升，其中又以極區與沿岸地區影響最為嚴峻。臺灣作為四面環海的國家，亦面臨沿岸海水面上升的威脅，故能精確且持續地監測沿岸及極區海水面的長短期變化顯得至關重要。本研究利用全球導航衛星系統干涉反射技術(Global Navigation Satellite System Interferometric Reflectometry, GNSS-IR)，並透過既有之GNSS連續站資料進行沿岸及極區監測工作。本研究重點包含以下三個方面：(1)評估不同GNSS-IR反射訊號萃取技術於沿岸海水面精度提升之效益、(2)整合多星系多頻之GNSS-IR資料提升觀測量時間解析度並進行極區沿岸海水面與海冰面變化之評估、(3)利用長期GNSS-IR資料計算臺灣西南部海水面變化趨勢，結合精密單點定位技術計算橢球海水面及深度基準之潮位面，並評估該結果是否能作為臺灣垂直與深度基準之同化資料。
研究結果顯示，經比較四種訊號萃取方法：傳統二階擬合(Quadratic Fitting, QF)、經驗模態分解(Empirical Mode Decomposition, EMD)、總體經驗模態分解(Ensembled EMD, EEMD)及奇異譜分析(Singular Spectrum Analysis, SSA)，發現SSA於不同測站高度及監測環境中均能提供穩定和準確的海水面觀測量，且均方根誤差(root-mean-square-error, RMSE )最多可降低59%(Onsala測站)，加入調和分析輔助後可提供最高精度之海水面觀測量為5.7公分(Onsala測站)。此外，SSA能有效集中頻譜功率，提高訊號萃取的可靠度。相比之下，傳統的訊號萃取方法通常導致顯著的頻譜多峰問題，特別是當SNR數據不來自設計優化的觀測站時，將影響海水面觀測量的準確性。
另外，本研究展示GNSS-IR技術於極地環境下進行沿岸海水面監測和海冰特徵識別的可行性。透過K-means聚類方法，以Lomb-Scargle Periodogram (LSP)所求得之振幅和峰噪比(Peak-to-Noise Ratio)特徵，成功區分了海水、海水+海冰(過渡期)和海冰表面條件，改善GNSS-IR於極區應用易受海冰影響之缺點。本研究亦使用共站之GNSS-IR成果進行比較，其相關係數超過0.95，RMSE大多低於14 cm，證實了不同硬體平台和不同衛星系統下GNSS-IR結果的一致性。與鄰近潮位站的比較進一步表明，GPS-L5和GPS-L2C頻率提供了最穩定和準確的結果，RMSE最小為13.3公分，相關係數最高為0.98。而多星系多頻率整合顯著降低了潮汐分潮振福及相位角因僅使用單一衛星系統所產生的偏差，振幅誤差最多降低68%。此外，本研究提出的加權方式保持了GNSS-IR觀測值的整體準確性不受偏差較大的觀測量影響，可提供觀測量之RMSE約為20公分(包含所有觀測時期)。總結來說，本研究證實GNSS-IR技術為一種自主、長期且高頻率監測極端環境下海水面和海冰動態的可行方法。在理想條件(如夏季開闊水域)，GNSS-IR技術可達到公分級的精度，證明GNSS-IR技術有效補充傳統技術在觀測能力有限區域的不足，並在極地海水面及海冰動態監測中具有重要的應用前景。
最後，本研究評估使用GNSS-IR技術應用於建立垂直和深度基準面的可行性。研究結果顯示，從潮位站和GNSS-IR計算得之平均海水面(Mean Sea Surface, MSS)，平均基準偏移為11.6公分。至於長期海水面變化，GNSS-IR求得之海水面趨勢與衛星測高結果相比，與潮位站計算得之趨勢更為一致。具體來說，高雄測站觀測到的海水面上升約為3-4 mm/yr。關於建立深度基準之潮汐面，尤其是最低天文潮(Lowest Astronomical Tide, LAT)，潮位站和GNSS-IR觀測值之差異僅為幾毫米，這表明GNSS-IR技術能有效偵測大部分潮汐特徵和模式，達到與傳統潮位站相當的精度。
總體而言，本研究成功展示了GNSS-IR技術在不同地區應用的潛力，並在不同研究課題上皆有豐碩的成果，本研究成果可為大地測量、地球科學、極地研究及全球氣候變遷做出十足貢獻。

In recent years, the intensification of global warming has led to a continuous rise in global sea levels, with polar and coastal regions being particularly vulnerable. As an island nation, Taiwan is especially susceptible to the impacts of coastal sea level rise. Therefore, it is crucial to accurately and continuously monitor both long-term and short-term sea level variations in these sensitive regions. This study utilizes Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technology, leveraging existing continuous GNSS station data, to monitor the coastal and polar regions. The focus of this study includes the following three aspects: (1) to evaluate the effectiveness of different GNSS-IR signal extraction techniques in improving the accuracy of coastal sea level measurements; (2) to integrate multi-constellation and multi-frequency GNSS-IR data to enhance temporal resolution and assess polar coastal sea level and sea ice freeboard changes, and (3) to utilize long-term GNSS-IR data to calculate the sea level trend in the southwestern part of Taiwan, and to combine precise point positioning (PPP) to determine ellipsoidal sea surface heights and tidal surfaces for potential application in establishing Taiwan vertical and depth datums.
The results show that after comparing four signal extraction methods, including traditional quadratic fitting (QF), Empirical Mode Decomposition (EMD), Ensemble EMD (EEMD), and Singular Spectrum Analysis (SSA), it was found that SSA consistently provides stable and accurate sea level measurements across different station heights and monitoring environments. The root-mean-square-error (RMSE) can be reduced by up to 59%, and after incorporating harmonic analysis, the highest precision for sea level measurements reaches 5.7 cm at the Onsala station. Furthermore, SSA effectively concentrates spectral power, improving the reliability of signal extraction. In contrast, traditional signal extraction method (QF) often lead to significant spectral multi-peaks, especially when the SNR data is not derived from optimally designed GNSS-IR stations, which affects the accuracy of sea level measurements.
Additionally, this study demonstrates the feasibility of applying GNSS-IR technology for coastal sea level and sea ice monitoring in polar regions. Using the K-means clustering, along with the amplitude and Peak-to-Noise Ratio (PNR) features derived from the Lomb-Scargle Periodogram (LSP), we successfully distinguished sea water-only, sea water + sea ice, and sea ice-only, thereby improving GNSS-IR’s performance in polar regions, which is often affected by sea ice. A comparison of co-located GNSS-IR results shows a correlation coefficient greater than 0.95, with an RMSE generally below 14 cm, confirming the consistency of GNSS-IR results across different hardware platforms and satellite systems. Furthermore, comparisons with nearby tide stations further indicate that GPS-L5 and GPS-L2C frequencies provide the most stable and accurate results, with the smallest RMSE of 13.3 cm and the highest correlation coefficient of 0.98. Multi-constellation and multi-frequency integration significantly reduced errors in tidal harmonics and phase angles caused by using only a single satellite system, with amplitude errors reduced by 68%. Moreover, the proposed weighting method in this study maintained the overall accuracy of GNSS-IR measurements, ensuring that measurements with large deviations did not degrade the results, providing an RMSE of approximately 20 cm (for all observation periods).In summary, this study confirms that GNSS-IR technology is a viable method for autonomous, long-term, and high-frequency monitoring of sea level and sea ice dynamics in extreme environments. Under ideal conditions (such as in summer open water), GNSS-IR technology can achieve centimeter-level accuracy, demonstrating that it can effectively complement traditional technologies in regions with limited observational capabilities, offering significant progress in polar sea level and sea ice monitoring.
Finally, this study evaluates the feasibility of applying GNSS-IR technology to establish vertical and depth datums. The results show that the mean sea surface (MSS) derived from tide stations and GNSS-IR has an average datum offset of 11.6 cm. Regarding long-term sea level changes, the sea level trend obtained from GNSS-IR is more consistent with the trend derived from tide stations compared to satellite altimetry data. Specifically, the sea level rise observed at the Kaohsiung station was approximately 3-4 mm/yr. As for the establishment of depth reference tidal surfaces, particularly the Lowest Astronomical Tide (LAT), the difference between the tide station and GNSS-IR observations was only a few millimeters, indicating that GNSS-IR technology can effectively capture most tidal features and patterns, achieving accuracy comparable to that of conventional tide gauges.
Overall, this study successfully demonstrates the potential of GNSS-IR technology for applications in various regions and research topics, contributing significantly to geodesy, Earth sciences, polar research, and global climate change.

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