於近年空間資訊領域的發展中，三維城市的建置為相當重要的研究方向，其中又以房屋為主要的重建目標。因都市尺度中重建房屋模型需耗費大量的時間、人力與金錢等資源，且考慮後續時間變遷之效應，亦需更新變遷區域的三維房屋模型。因此本研究提出有效的房屋重建程序，並整合航空影像與空載光達資料更新既有之房屋模型。本計畫執行時間共計三年，第一年針對多元資料進行套合研究，多元資料包含有航照影像、光達點雲資料與房屋模型。由於多元資料獲取時間相異，各資料間彼此存在偏差量，為利於後續計畫進行，本研究擬提出一自動化套合程序來處理資料間之偏差量。其中包含參數分析與幾何距離分析兩種方式。於套合程序後，進行房屋模型之更新重建，房屋模型重建可分為兩個階段，偵測變遷區域與重建三維房屋模型。因此，第二年為偵測變遷區域，針對舊時期之房屋模型進行變遷偵測，藉此找出變遷的三維房屋模型，在藉由新時期之航照影像以及空載光達點雲，找出需要新建置模型之房屋區域。第三年為融合空載光達與航照影像，重建變遷區域三維房屋模型，藉此更新既有的三維房屋模型，同時加強屋頂結構細節之重建。 In recent years, 3D city modeling is one of the important topics in geoinformatics research. The most important reconstruction target in the research is building models. In the city scale, the 3D building models reconstruction needs plenty of time, human resources and cost. Considering the changes over a period of time, it also needs to reconstruct the buildings only for the change regions. Therefore, the main goal of this investigation is to propose an effective building modeling procedure by the fusion of aerial imagery and Lidar data to update the original building models. This project will perform for three years. In the first year, the multi-source data registration is the main objective. The data sets include aerial imagery, Lidar data and 3D building models. Because of the different acquisition time, it may exist geometric discrepancy among those data sets. We, thus, propose an automatic registration procedure. It includes two parts, one is to analyze the features in parameter space and the other is the geometric distance analysis. The reconstruction process then follows the registration. It has two stages, the first one is the change detection followed by the 3D building reconstruction. The task of the second year is to detect changed building regions using the latest aerial imagery and Lidar data. In the third year, we will integrate aerial imagery and Lidar data for 3D building reconstruction in changed regions. The step will reconstruct the details on the roof top of building models. 研究期間：10008 ~ 10107
