應用空載光達資料自動化萃取建物邊界線

建物邊界線乃二維與三維圖資中重要的地物空間資訊，目前仍以航測立體測繪方式產製為主，產製效率不高。空載光達提供地物表面密佈的三維取樣點雲，隱含豐富的地物幾何特徵及三維空間資訊。理論上可從光達點雲萃取出屋頂面與牆面特徵，取其交會線特徵獲得建物邊界線，但空載光達點雲分佈於牆面的點通常較稀疏，不易萃取牆面特徵，以獲得建物邊界線。此外，由於屋頂面的附屬結構使得點雲分佈更雜亂，常使萃取得的邊界線特徵不連貫。本文針對上述課題提出自動化萃取建物邊界線之程序，演算法包含兩步驟，第一步驟是萃取三維平面點雲與邊界點偵測，結合多重回訊點，先獲得邊界線的候選點雲；第二步驟是透過Hough transform、直線擬合與線段分割等步驟萃取邊界線段。本研究選出十棟不同類型的建物進行測試，檢視邊界線萃取方法的成功率及效能，與現有地形圖比較之量化評估成果顯示，約70%的建物邊界線可被正確萃取出來，對屋頂結構線的正確萃取率也約可達85%，顯示出本研究所提出之演算法，對於從空載光達點雲資料萃取建物邊界線及結構線是有成效的。所萃取之建物邊界線及結構線乃三維建物模型重建的基本資料元素。

關鍵字

空載光達；點雲；建物邊界萃取；建物模型重建

並列摘要

Building boundary is one of the important components for the mapping of 2D digital topographic maps and the modeling of 3D city buildings. Photogrammetry is currently the common technique applied for building boundary generation,which are labor intensive. Airborne LiDAR data provides abundant3Dinformation of the scanned objects.The characteristics of objects are implicitly contained in the data set. Usually top surfaces, such as roofs, may have densely distributed points, but vertical surfaces, such as walls, usually have sparsely distributed points or even no points. Building boundaries, referring to the intersections of roof and wall planes are, therefore, not clearly defined in point clouds.To overcome this problem, this paper develops an algorithm to acquire building boundary from airborne LiDAR data. Threemajor process steps are included in the algorithm. Firstly the point clouds are classified as building points and non-building points. Then, octree-based split-and-merge segmentation is implemented to extract plane features.Second, those building points and coplanar points are used to trace the boundary points by concave-hull algorithm. Boundary points of coplanar point group and building points and the first and intermediate echo points of multi-return scan are selected as candidates of building boundary points. Finally, methods of the Hough transform, line fitting and line segmentation are applied to find line segments belonging to building boundaries. The experiment results show the effectiveness of the proposed method for automatic building boundary extraction from airborne LiDAR data, and that combining the information of the first and intermediate echo points of multi-return and the boundary points increases the completeness of boundaries. And, it is promising to use the extracted boundaries for 3D building modeling in the future.

並列關鍵字

airborne LiDAR ； point cloud ； building boundary extraction ； 3D building reconstruction

國際替代計量

應用空載光達資料自動化萃取建物邊界線

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