地面光達可迅速獲得高精度且密佈於掃瞄場景內點雲資料，這些點雲資訊詳實地紀錄了掃瞄場景內地表或建物的三維空間資訊。當掃瞄場景無法以單一掃瞄站的資料涵蓋時，則須以多測站方式對整個場景進行掃瞄。然而各掃瞄站點雲雲資料所參考的座標並不相同，因此必須先將各掃瞄站點雲資料進行結合，才可進行後續的應用。也就是將所有點雲資料轉換到統一的參考座標系統，在許多測量的應用上，尚需統一於既有的地面座標系統。
　　本研究參考航空攝影測量學的獨立模型區域平差法，將各個掃瞄站點雲資料視為一個單元模型，同一區域(即掃瞄同一場景)內之模型之間須具有重疊區域，在模型重疊區域內尋找共軛點，視為模型之間的連結點，作為模型連結之約制。為使模型座標經平差轉換後能與其他地面資訊作結合應用，在區域內應佈設週邊控制點。接著觀測各模型內連結點與控制點座標，並將控制點地面座標值視為平差觀測值，加入平差系統中，進行整體平差，求解出各掃瞄站與地面座標之間的轉換參數以及待求點位的地面座標。利用解算出的各掃瞄站轉換參數，進行點雲資料座標轉換，將所有所有點雲資料轉換到同一個參考座標系統，完成點雲資料結合。藉由檢核點點位座標的計算，提出轉換後點位精度，視為點雲結合的精度指標。
　　本研究並提出地面光達與數位影像資料的結合方式，根據物空間與影像空間座標系統轉換關係，結合兩種不同類型儀器所取得的資料，以Pixel-Based方式進行場景材質敷貼，並配合點雲資料結合成果，完成成功大學總圖書館的場景建置，並就點雲資料結合成果進行分析與討論。經過實驗與分析，本研究所提出之點雲資料平差結合法，確實可進行場景掃瞄資料結合，並且提供客觀的點雲結合精度，供後續應用所參考。

　　Ground-based laser scanners can quickly obtain high density point cloud data of scanned object surface in high accuracy. Multiple scans are frequently required for a complete scan project of a large or complicated object. Because the data set of each scan is defined in a local coordinate system, data sets of multi-station must be merged into a unified coordinate system. For many surveying applications, transforming the scanned data coordinates into a previously defined ground coordinate system is also needed.
　　Based on the theory of independent model adjustment developed in the field of photogrammetry, a point cloud data merging adjustment is proposed. Each point cloud data set is treated as a single model. It is assumed that adjacent model should be overlapped. Identification of conjugate points in the overlap areas should be done in advance as tie points. Ground control points are also needed for the transformation of the merged data the ground coordinate system. The model coordinates of tie points and control points will be treated as observations in the adjustment calculation. The unknown parameters of the adjustment include : 1. the transformation parameters of each model coordinate system; 2.the ground coordinates of all tie points. After adjustment, the data sets can be merging using the transformation parameters, and the standard derivation of observation residuals indicates the quality of data merging.
　　This thesis also proposed a method to integrate ground-based LiDAR data sets and digital images. An image scene can be projected onto the LiDAR point cloud data as long as image orientation is solved. The experimental results demonstrate the proposed method can be successfully applied for merging point cloud data and reconstructed 3D-model from ground-based LiDAR.

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