dc.contributor | 地政系 | |
dc.creator (作者) | 邱式鴻;詹立丞 | |
dc.creator (作者) | Chio, Shih-hong;Chan, Li-cheng | |
dc.date (日期) | 2020-03 | |
dc.date.accessioned | 2024-07-17 | - |
dc.date.available | 2024-07-17 | - |
dc.date.issued (上傳時間) | 2024-07-17 | - |
dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/152327 | - |
dc.description.abstract (摘要) | 以空載光達校正場矩形平屋頂作為標的物執行點雲精度評估時,需先萃取平屋頂面上之點雲,為避免萃取成果受雜訊影響,本研究引入粗差偵測理論,發展最小一乘法[1]結合李德仁所發展以後驗變方估計原理導出的選擇權迭代法(稱李德仁法)[2]將非屋頂點視為粗差排除。研究中使用校正場6組點雲資料,經由測試提出半自動化點雲精度評估之程序。實驗結果顯示本研究所提之程序,其成果可避免因人而異,達一致性之點雲精度評估結果;而實驗結果亦顯示,本研究所提最小一乘法結合李德仁法的改良李德仁法,可將非屋頂點視為粗差排除,於含有大量牆面點雲的資料中,比原李德仁法提升約10%的偵測粗差數量。 | |
dc.description.abstract (摘要) | This study attempts to establish a semi-automatic procedure for the accuracy assessment of point clouds from airborne LiDAR system. Least Absolute Deviation (LAD) [1] combined with the Iteration using selected weights presented by Li (Li method) [2] is developed to exclude the non-roof points that are regarded as gross errors and eliminate their influences. In this study, six datasets in calibration field were used to develop a semi-automatic procedure based on several tests. Even different operators employ this semi-automatic procedure, consistent results were obtained and the reliability can be achieved in this study. In additional, about 10% gross errors can be detected by our proposed improved Li method than original Li method. | |
dc.format.extent | 134 bytes | - |
dc.format.mimetype | text/html | - |
dc.relation (關聯) | 中國土木水利工程學刊, Vol.32, No.1, pp.43-61 | |
dc.subject (關鍵詞) | 點雲精度評估; 最小二乘平面擬合; 粗差偵測; 最小一乘法; 選擇權迭代法 | |
dc.subject (關鍵詞) | Point clouds accuracy assessment; Least squares plane fitting; Gross error detection; Least absolute deviation; Iteration with the selected weights | |
dc.title (題名) | 以空載光達校正場矩形平屋頂半自動評估點雲精度之程序研究 | |
dc.title (題名) | The Study of Semi-automatic Accuracy Assessment Procedure on Point Clouds Using Rectangular Planar Roofs from Airborne LiDAR Calibration Field | |
dc.type (資料類型) | article | |
dc.identifier.doi (DOI) | 10.6652/JoCICHE.202003_32(1).0005 | |
dc.doi.uri (DOI) | https://doi.org/10.6652/JoCICHE.202003_32(1).0005 | |