海面連續影像序列提供了時間域以及空間域的海表面特徵資訊，是極具發展潛力的海洋環境資料，本研究討論利用空拍機影像所拍攝得到的海面影像時序列作為解析海表面特徵之可行性。本文透過影像分析技術對空拍機拍攝之海面影像時序列做三維傅立葉轉換，再利用頻散關係式(dispersion relation)對影像譜進行濾波，疊代計算得表面海流。本研究在探討觀測準確性之前對空拍機觀測海流遭遇之參數設定與環境因子問題進行探討，包含空間對位校正控制點所需之數量與擺放位置、控制點座標精準度、飛行高度以及風速和光線等因子，結果顯示控制點的佈設位置比數量影響更大，本文建議將控制點均勻佈設在陸域範圍，控制點數量至少四處以上，兩控制點間距建議大於五十公尺，另外本研究証實手機GPS定位座標即可滿足空拍機從事海流觀測之需要。本研究另發現當風速大於8m/s時，太陽仰角過高時，觀測結果不佳。本研究規劃空拍機和微波雷達及ADCP同步觀測來做定性和定量驗證，結果顯示空拍機觀測結果和雷達觀測結果一致，和ADCP量測結果之比對顯示流速均方根誤差為0.0985m/s，流向誤差為12.9º。由定量和定性上的結果顯示，以空拍機影像反算表面流場技術可實際應用於現場觀測，需要更多的實驗來獲得定量驗證結果以提高使用信心。

The images sequence provides information on the sea surface characteristics in the time and spatial domain. In this study, UAV had been used to capture the images sequence. An image analysis method based on the three-dimensional Fourier transform was also developed for obtain the sea surface current information which could be calculated iteratively by dropper shift from wavenumber-frequency spectrum. The influence factors and observation setting of the UAV, including the quantity and position of the ground control points, the coordinate accuracy, the flight altitude, the wind speed and light, were also tested. The results show that the position of the ground control points is more affected than the quantity. We recommended that the ground control points be evenly distributed around the land area. In addition, GPS position from mobile phone (iPhone XR) can meet the needs of the UAV for ocean current observation. This study also found that the observation results are not good under the conditions of wind speed greater than 8m/s or sun elevation angle too high. For verification and validation of sea surface current calculated from UAVs images, X-band radar and ADCP had been deploy and compare with. The results show that the UAV observation results are consistent with the radar, and the comparison with ADCP shows that the RMSE of the current speed is 0.0985 m/s and the direction error is 12.9º.

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