透過您的圖書館登入
IP:3.138.33.87
  • 期刊

利用拓樸約制條件協助LOD-2屋頂模型重建

LOD-2 Roof Models Reconstruction Assisted by Topological Constraints

摘要


隨著三維地理資訊系統的蓬勃發展,三維城市模型的需求與日俱增,而三維建物模型更是在其中扮演著非常重要的角色。本研究提出一套LOD-2三維屋頂模型之重建模式,利用無人機與空載雷射掃描產製點雲資料以提供三維坐標觀測量,並藉由二維多邊形資料以定義屋頂結構之平面邊界範圍,再透過最小二乘平差進行平面擬合,以取得各屋面在三維空間中的位置與分布狀態。此外,本研究藉由建立各多邊形之拓樸資訊,以提供平差計算中的附加約制條件與幾何改正條件,避免多邊形之間出現間隙、重疊等位相關係錯誤之情形,最後成功重建三維屋頂模型。

並列摘要


3D building model is one of the important elements in digital city analysis. It can be widely used in many geographic activities, such as smart city, urban planning, disaster management. The quality of 3D building models is related to their structure and geometry. CityGML, an international 3D city modeling standard, formulated the scale to express the detail of 3D building models in different Level-of-Details (LODs). From the roughest to the most detailed one is named LOD-0 to LOD-4. The main goal of our study is to reconstruct the LOD-2 3D building models which are configured by detailed roof structure with vertical facades. Since the 3D roof structure is the most important part of the LOD-2 model, we will focus on how to reconstruct the complete high-accuracy and topological error-free 3D roof models. We create point clouds and Object Height Model (OHM) from Unmanned Aerial Vehicle (UAV) images and Airborne Laser Scanning (ALS), extract 2D polygons of the roof structure by manual digitization, then perform least-squares adjustment to fit the 3D roof planes. Considering the geometry and relationship between adjacent polygons, we set some constraint conditions and conduct roof plane correction to avoid topological errors. Eventually, we reconstruct some typical roof models in Taiwan, and conduct accuracy analysis by manually measuring the 3D coordinates of roof corners. It has proved that the results can conform to the LOD-2 standard of CityGML, confirming that the proposed method of 3D roof models reconstruction is feasible to varied types of roofs with high accuracy.

參考文獻


Dorninger, P., and Pfeifer, N., 2008. A comprehensive automated 3D approach for building extraction, reconstruction, and regularization from airborne laser scanning point clouds, Sensors, 8: 7323- 7343.
dos Santos, R.C., Galo, M., and Habib, A.F., 2020. Regularization of building roof boundaries from airborne LiDAR data using an iterative CD-spline, Remote Sensing, 12: 1904.
Haines, E., 1994. Point in polygon strategies, In: Graphics Gems IV, Heckbert, P. (Ed.), Academic Press, Boston, MA, pp. 24-46
Malihi, S., Valadan Zoej, M.J., Hahn, M., Mokhtarzade, M., and Arefi, H., 2016. 3D building reconstruction using dense photogrammetric point cloud, Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLI-B3: 71-74.
Morgan, M., and Tempfli, K., 2000. Automatic building extraction from airborne laser scanning data, International Archives of Photogrammetry and Remote Sensing, 33: 616-623.

延伸閱讀