Determining the Deformation Monitorable Indicator of Point Cloud Using Error Ellipsoid

作者:Xuan, W (Xuan, Wei)^{[ 1 ]} ; Hua, XH (Hua, Xianghong)^{[ 1,2 ]} ; Zou, JG (Zou, Jingui)^{[ 1,2 ]} ; He, XX (He, Xiaoxing)^{[ 1,3 ]}

JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING

DOI: 10.1007/s12524-016-0580-7

出版年: FEB 2017

摘要

As the development of the terrestrial laser scanning (TLS) technique, deformation monitoring using TLS has attracted increasing attention in the field. To distinguish the deformation from the error of TLS point cloud and evaluate the deformation monitorable capacity of the point cloud, a deformation monitorable indicator (DMI) should be determined. In this paper, a new method for determining the DMI of point cloud is proposed. The kernel procedure of the method is the establishment of point error ellipsoid and point cloud error ellipsoid and is described firstly in the paper. Then the computation of the actual point error ellipsoid is derived considering the intersection between the neighboring error ellipsoids. The determination of DMI comes in the next by calculating the point position error of the deformation orientation based on the actual point error ellipsoid. Furthermore, the performance of proposed approach is illustrated with validation experiments of planar board displacement where deformations with different sampling intervals, different scanning distances and different incidence angles were simulated. From the analysis of the experiments, the results show the validation of the feasibility of determining the DMI by the proposed method. This technique was also applied to a monitoring event of bridge pylon, and the results confirm the feasibility of the DMI in a real case, as well.

作者关键词:Error ellipsoid; Position error; Deformation detection; Deformation monitorable indicator

通讯作者地址: Hua, XH (通讯作者)

通讯作者地址: Hua, XH (通讯作者)

地址:

电子邮件地址:xhhua@sgg.whu.edu.cn

基金资助机构授权号

SPRINGER, 233 SPRING ST, NEW YORK, NY 10013 USA

研究方向:Environmental Sciences & Ecology; Remote Sensing

Web of Science 类别:Environmental Sciences; Remote Sensing

文献类型:Article

语种:English

入藏号: WOS:000394243200004

ISSN: 0255-660X

eISSN: 0974-3006

Impact Factor (影响因子): 0.676