近年來衛星測高已成為提供高精度海水面的重要觀測工具之一，然而將其應用在近岸0~5 km仍舊有精度不佳的問題。香山濕地為許多瀕臨絕種生物的棲息地，也是東亞太水鳥保護網之一，極具保護價值，正受到海水面上升所威脅。因此，本研究將改善此區域的Envisat測高資料精度，以提供正確的海水面高度資料。本研究利用18Hz Envisat RA-2 Cycle 10 ~ Cycle 90 SGDR波形資料，結合線性判別分析（Linear Discriminant Analysis, LDA）與最近鄰居分類器（k-Nearest Neighbors Classifier, k-NN）進行波形分類，然後將分類出之海洋反射波形以不同波形重定演算法（包含Cruve Fit、Ice-1、Ocean、Threshold和 Modified Threshold演算法）重定來求得海水面高度，最後以新竹驗潮站和EGM2008大地起伏模型評估成果精度。本研究發現使用LDA搭配k-NN比起單獨使用k-NN的波形分類，近岸0~5km Ice-1波形重定後Envisat高度與驗潮站差值之標準偏差（Standard Deviation, STD），由0.26 m減少至0.17 m；然而，使用LDA於波形分類在5~10 km的差值STD卻是沒有明顯改善的，其原因為開闊海域下多屬於海洋波形，單獨使用k-NN即能獲得良好的分類效果。而使用LDA搭配k-NN分類後，能大幅改善於近岸0~5 km區域的精度，表現最好的波形重定為Ice-1演算法，與新竹驗潮站差值之STD由1.14 m提升至0.17 m，與未使用波形重定比較，其改善率（Improvement Percentage , IMP）為77.4%。與EGM2008差值之STD由1.26 m減少至0.20 m，IMP為82.2%。在開闊海域5~10 km的部分，其波形大多屬於海洋反射波形，經過波形重定重定後的STD即小於0.3 m以下，使用LDA搭配k-NN分類後只能些微改進精度，同樣也是Ice-1演算法表現最佳，與新竹驗潮站差值之STD由0.27 m減少至0.21 m，IMP為51.4%。與EGM2008差值之STD由0.30 m減少至0.22 m，IMP為58.6%。

Satellite radar altimetry becomes an irreplaceable tool to provide accurate surface height measurements over open oceans. However, the accuracy decreases when altimeters approach coastlines or non-ocean surfaces due to the improper geophysical corrections and complex returned waveforms. Many waveform retracking algorithms have been developed for improving the accuracy of non-ocean reflected altimetry data; however, the performance still cannot achieve the same accuracy as that in open oceans. In coastal regions, some waveforms reflected from non-ocean surfaces lead to the worse retracking results. Therefore, waveform classification methods are needed to distinguish if waveforms are truly reflected from oceans. Waveform classification used in this study includes two steps. The first step is applying Linear Discriminant Analysis (LDA) to reduce the dimensionality of original features’ spaces for classification. The second step is using k-Nearest Neighbors Classifier (k-NN) to separate waveforms into two groups: ocean and non-ocean waveforms. Afterward, we remove the non-ocean waveform before doing retracking. In this study, we use Envisat altimetry data over Hsiang-Shan wetland in Hsin-Chu, which is located in Northwestern Taiwan. The satellite-derived results are then evaluated using Hsin-Chu tide gauge data. In the case of distance from coastline 0~5 km, after waveform classification, the best performance retracker is ice-1 and standard deviation of the difference between tide gauge and ice-1 improve from 1.140 m to 0.173 m. Finally, we expect building an effective classification method and figuring out the most appropriate retracking algorithm applied for this study area.

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