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Surface-based Geometric Registration of Aerial Images and LIDAR Data
Lee, Impyeong,Kim, Seong-Joon,Choi, Yunsoo Korean Society of Surveying 2005 Korean journal of geomatics Vol.5 No.1
Precise geometric registration is required in multi-source data fusion process to obtain synergistic results successfully. However, most of the previous studies focus on the assumption of perfect registration or registration in a limited local area with intuitively derived simple geometric model. In this study, therefore, we developed a robust method for geometric registration based on a systematic model that is derived from the geometry associated with the data acquisition processes. The key concept of the proposed approach is to utilize smooth planar patches extracted from LIDAR data as control surfaces to adjust exterior orientation parameters of the aerial images. Registration of the simulated LIDAR data and aerial images was performed. The experimental results show that the RMS value of the geometric discrepancies between two data sets is decreased to less than ${\pm}0.30\;m$ after applying suggested registration method.
A Framework for Building Reconstruction Based on Data Fusion of Terrestrial Sensory Data
Lee, Impyeong,Choi, Yunsoo Korean Society of Surveying 2004 Korean journal of geomatics Vol.4 No.2
Building reconstruction attempts to generate geometric and radiometric models of existing buildings usually from sensory data, which have been traditionally aerial or satellite images, more recently airborne LIDAR data, or the combination of these data. Extensive studies on building reconstruction from these data have developed some competitive algorithms with reasonable performance and some degree of automation. Nevertheless, the level of details and completeness of the reconstructed building models often cannot reach the high standards that is now or will be required by various applications in future. Hence, the use of terrestrial sensory data that can provide higher resolution and more complete coverage has been intensively emphasized. We developed a fusion framework for building reconstruction from terrestrial sensory data, that is, points from a laser scanner, images from digital camera, and absolute coordinates from a total station. The proposed approach was then applied to reconstructing a building model from real data sets acquired from a large complex existing building. Based on the experimental results, we assured that the proposed approach cam achieve high resolution and accuracy in building reconstruction. The proposed approach can effectively contribute in developing an operational system producing large urban models for 3D GIS with reasonable resources.
항공라이다데이터를 이용한 히스토그램 기반의 평균수목고도 추정
이미진(Lee, Mijin),황세란(Hwang, Seran),이임평(Lee, Impyeong) 한국측량학회 2012 한국측량학회 학술대회자료집 Vol.2012 No.4
As the necessity of forest conservation and management has been increased, various studies on measuring forest biomass have been actively performed. In this study, for forest biomass measurement, we estimated mean tree heights from airborne LIDAR data. We grouped the LIDAR data into a grid, and generated a histogram of point heights for each cell. By analyzing the histogram, we estimated the maximum and mean tree heights, and the mean crown height. We applied this method to the LIDAR data acquired from a mixed forest area and compared the results with field measurements. The estimated mean tree heights were underestimated by about 0.6 m and the mean crown height showed the RMSE of 2m. The proposed method will be effectively utilized for the accurate determination of forest biomass.