A spatio-temporal deformation model for laser scanning point clouds

被引:19
作者
Harmening, Corinna [1 ]
Neuner, Hans [1 ]
机构
[1] TU Wien, Dept Geodesy & Geoinformat, Vienna, Austria
基金
奥地利科学基金会;
关键词
B-spline surfaces; Deformation modelling; Laser scanning; Locally homogeneous stochastic processes; Prediction;
D O I
10.1007/s00190-020-01352-0
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The establishment of the terrestrial laser scanner changed the analysis strategies in engineering geodesy from point-wise approaches to areal ones. During recent years, a multitude of developments regarding a laser scanner-based geometric state description were made. However, the areal deformation analysis still represents a challenge. In this paper, a spatio-temporal deformation model is developed, combining the estimation of B-spline surfaces with the stochastic modelling of deformations. The approach's main idea is to model the acquired measuring object by means of three parts, similar to a least squares collocation: a deterministic trend, representing the undistorted object, a stochastic signal, describing a locally homogeneous deformation process, and the measuring noise, accounting for uncertainties caused by the measuring process. Due to the stochastic modelling of the deformations in the form of distance-depending variograms, the challenge of defining identical points within two measuring epochs is overcome. Based on the geodetic datum defined by the initial trend surface, a point-to-surface- and a point-to-point-comparison of the acquired data sets is possible, resulting in interpretable and meaningful deformation metrics. Furthermore, following the basic ideas of a least squares collocation, the deformation model allows a time-related space-continuous description as well as a space- and time-continuous prediction of the deformation. The developed approach is validated using simulated data sets, and the respective results are analysed and compared with respect to nominal surfaces.
引用
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页数:25
相关论文
共 52 条
[41]  
Schlittgen R, 2013, ZEITREIHENANALYSE LE
[42]   Deformation analysis of the Lake Urmia causeway (LUC) embankments in northwest Iran: insights from multi-sensor interferometry synthetic aperture radar (InSAR) data and finite element modeling (FEM) [J].
Shamshiri, Roghayeh ;
Motagh, Mahdi ;
Baes, Marzieh ;
Sharifi, Mohammad Ali .
JOURNAL OF GEODESY, 2014, 88 (12) :1171-1185
[43]   LOCALLY STATIONARY RANDOM-PROCESSES [J].
SILVERMAN, RA .
IRE TRANSACTIONS ON INFORMATION THEORY, 1957, 3 (03) :182-187
[44]  
Smith T.E., 2016, Notebook on Spatial Data Analysis
[45]   Soil water content interpolation using spatio-temporal kriging with external drift [J].
Snepvangers, JJJC ;
Heuvelink, GBM ;
Huisman, JA .
GEODERMA, 2003, 112 (3-4) :253-271
[46]  
Tang L., 2006, SMUTR337
[47]   A spatio-temporal hybrid neural network-Kriging model for groundwater level simulation [J].
Tapoglou, Evdokia ;
Karatzas, George P. ;
Trichakis, Ioannis C. ;
Varouchakis, Emmanouil A. .
JOURNAL OF HYDROLOGY, 2014, 519 :3193-3203
[48]   On the deformation analysis of point fields [J].
Velsink, Hiddo .
JOURNAL OF GEODESY, 2015, 89 (11) :1071-1087
[49]   Use of Terrestrial Laser Scanning Technology for Long Term High Precision Deformation Monitoring [J].
Vezocnik, Rok ;
Ambrozic, Tomaz ;
Sterle, Oskar ;
Bilban, Gregor ;
Pfeifer, Norbert ;
Stopar, Bojan .
SENSORS, 2009, 9 (12) :9873-9895
[50]  
Wujanz D, 2018, PHOTOGRAMMETRIE LASE