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Improvement of LiDAR Data Accuracy Using 12 Parameter Affine Transformation

By Chien-Ting Wu, Cheng-Yang Hsiao and Chun-Sung Chen

Abstract

LiDAR data in a local coordinate system may need to be georeferenced and converted into a geographic or projected system. In coordinate transformation, the 7-parameter Helmet transformation method is usually used in measurements to eliminate the systematic errors made by a laser scanner. However, 7-parameter coordinate transformation assumes that there is only one scale error in all of the systematic errors. This study used 12 parameter affine transformation for coordinate transformation of airborne LiDAR data and terrestrial LiDAR data. The LiDAR data accuracy results upon 6-parameter similarity transformation, 7-parameter similarity transformation, and 12-parameter affine transformation were compared. The results showed that using 12-parameter affine transformation the airborne LiDAR and terrestrial LiDAR data have 2-3 times greater accuracy than do 7-parameter or 6-parameter transformations

Topics: LiDAR, coordinate transformation, 12-parameter, affine transformation
Publisher: 台北市:中華水土保持學會
Year: 2014
OAI identifier: oai:ir.lib.nchu.edu.tw:11455/84777

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