無人機攝影測量與直接地理定位之精度分析

利用無人機（Unmanned Aerial Vehicle，UAV）進行空中攝影獲取地面影像，與有人機相比其成本較低廉、機動性與彈性也相對較高。然而無人機受到載重、空間與續航時間之限制，所能攜帶的感測器也相對必須較小、較輕，因此只能使用消費型數位相機，而其內方位較不穩定且像幅涵蓋之地面範圍也比專業航測相機小很多，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，會增加空三平差之處理時間、複雜度與困難度。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、陰影與均調區等問題，容易造成連結點自動匹配失敗或錯誤，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NovAtel SPAN-CPT戰術級慣性導航儀（Inertial Measurement Unit，IMU）、雙頻GPS接收儀與Canon 5D Mark II數位相機，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，同時評估應用本系統於航測製圖之可能性。本研究在系統率定上包括使用室內率定場率定相機之內方位參數，以及使用戶外地面控制場與二階段率定法解算IMU與相機之軸角（Boresight Angles）。研究成果顯示在1,200公尺航高下，以直接地理定位解算得相片外方位參數，再以前方交會檢驗其定位精度，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。顯示本系統直接地理定位之準確度可應用在災後快速提供災情空間資訊。而在地形圖測製部分，有／無利用地面控制點進行空三平差產製DSM後其高程內部精度可達1公尺，立體製圖水平方向絕對定位誤差則在50公分以內。因此，若有災害前後之UAV影像，甚至可推估崩塌地之土石流失與堆積量。

關鍵字

系統率定；直接地理定位；無人機；數值地表模型

並列摘要

Comparing with manned aircraft, an Unmanned Aerial Vehicle (UAV) is a more flexible with lower cost platform for aerial photo acquisition. However, its payload, space, and endurance time is comparably lower and generally only light and 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 fixed-wing UAV equipped with a tactical grade SPAN-CPT IMU together with a dual-frequency GPS antenna, and a Canon EOS 5D Mark II digital camera for direct georeferencing (DG) particularly when fast response for hazard investigation is required. In this paper, 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 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 with 1200 m after DG and performing accuracy assessment using space intersection through check points, the RMSE in planimetric and vertical directions are less than 1 m and 4 m, respectively. It demonstrates that the positing accuracy after DG is enough for the purpose of fast hazard area investigation. On the test of topographic mapping, the internal precision of the generated DSM through ground controlled and non-ground controlled aerial triangulation are all about 1 m, while the planimetric accuracy in stereo-mapping is within 0.5 m. If two UAV image datasets can be acquired before and after disaster, the landslide loss and deposit volume could also be estimated.

並列關鍵字

System Calibration ； Direct Georeferencing ； Unmanned Aerial Vehicle ； Digital Surface Model

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