與有人機相比，利用無人機(Unmanned Aerial Vehicle, UAV)進行空中拍照獲取地面影像，其成本較低廉、機動性與彈性也相對較高。然而無人機受到載重、飛行時間與穩定性之限制，所能攜帶的感測器也相對必須較小、較輕，因此影像涵蓋之地面範圍比傳統大像幅航照影像小很多，在相同面積與重疊百分比要求下，拍攝的影像數量將大幅增加，會增加空三平差之時間與困難度。此外，在山區拍攝時，可能整張影像的內容皆為樹林，會導致重複性紋理、陰影與均調區域等問題，容易造成連結點自動匹配失敗或不可靠，進而無法以傳統空中三角測量求解影像之外方位參數。由於台灣山區每逢豪雨就會造成地質災害，因此本研究提出在定翼型無人機上裝載戰術級慣性導航儀(Inertial Measurement Unit, IMU)與雙頻全球定位系統(Global Postioning System, GPS)接收器，透過直接地理定位(Direct Georeferencing, DG)迅速解算影像之外方位參數，以便在災後快速提供災情空間資訊給災防單位。本研究在AL-40 UAV上裝載NovAtel SPAN-CPT和Canon EOS 5D Mark II數位相機分別作為定位定向與影像感測器。系統率定包括使用室內率定場相機內方位參數之率定，以及使用地面控制場與二階段率定法解算IMU與相機之軸角與固定臂參數。本文將說明整個率定作業程序與誤差分析成果，研究成果顯示在1200公尺航高，以直接地理定位解算相片外方位參數，再以前方交會檢驗其定位準確度，可得到小於1公尺之水平方向誤差與小於4公尺之高程誤差。而有/無利用地面控制點進行空三平差產製數值表面模型(Digital Surface Model, DSM)後其高程誤差分別約40公分與1公尺。成果顯示本系統之絕對定位精度可應用在災後快速提供災情範圍之數化與測量，若有地面控制點及災害前後之影像，甚至可推估崩塌地之土石流失與堆積量。

Comparing with manned airplane, an Unmanned Aerial Vehicle (UAV) is a more flexible with lower cost platform for aerial photo acquisition. However, its payload, endurance time, and flight height is comparably lower and generally only small format consumer grade digital camera can be carried out. That means, its footprint coverage will be smaller and more images are necessary to cover the same area, and may contain only forest within one image when flying over the mountainous area. Thus, it is a difficult to utilize the conventional aerial triangulation (AT) procedure to obtain the images’ exterior orientation parameters (EOPs) that requires uniform distributed tie-points within the images. Because, it is difficult to match tie-points automatically due to the image context has repetitive pattern, shadow, and homogeneous area. Since the geological hazard happened frequently after heavy rainfall in Taiwan mountainous area, it is thus suggested to utilize a tactical grade IMU together with a dual-frequency GPS antenna for direct georeferencing (DG) particularly when fast response for hazard investigation is required. In this paper, a fixed-wing UAV equipped with a SPAN-CPT and a Canon EOS 5D Mark II camera are used for image acquisition. An in-door camera calibration field is designed for the calibration of interior orientation parameters (IOPs) and an outdoor calibration field with two-step boresight and lever-arm calibration procedure is applied for the purpose of DG. Detail about the system calibration procedure and accuracy analyses will be provided in the paper. Experimental results show that for flying height at 1200-m after DG and checking with GCPs using space intersection, the RMSE in planimetric and vertical directions are less than 1-m and 4-m, respectively. In the meantime, the RMSE of the generated DSMs through ground controlled and non-ground controlled but GPS-supported aerial triangulation are 0.4-m and 1-m, respectively. It is estimated that the positing accuracy is high for the purpose of fast hazard investigation, e.g. digitization and measurement. If two image datasets can be acquired before and after disaster, the landslide loss and deposit volume can also be estimated.

李育華 (2010)，車載移動式製圖系統之系統率定及其直接地理定位之效能分析，國立成功大學測量及空間資訊學系碩士論文。
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