NDLI: Change Detection From Differential Airborne LiDAR Using a Weighted Anisotropic Iterative Closest Point Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Xiao Zhang Glennie, C. Kusari, A.
Copyright Year	2008
Abstract	Differential light detection and ranging (LiDAR) from repeated surveys has recently emerged as an effective tool to measure the three-dimensional (3-D) change. Currently, the primary method for determining 3-D change from LiDAR is through the use of the iterative closest point (ICP) algorithm and its variants, with a simplistic assumption of a uniform accuracy for the entire LiDAR point cloud. This common practice ignores the localization anisotropy and results in local convergence and spurious error estimation. To rigorously determine spatial change, this paper introduces an anisotropic-weighted ICP (A-ICP) algorithm, and proposes to model the random error for every LiDAR observation in the differential point cloud, and use this as a priori weights in the ICP algorithm. The implementation is evaluated by qualitatively and quantitatively comparing the estimation performance on point clouds with synthetic fault ruptures between standard ICP and A-ICP algorithm. As a further enhancement, we also present a moving window technique to improve A-ICP. Practical application of the combined moving window A-ICP technique is evaluated by estimating post-earthquake slip for the 2010 El Mayor-Cucapah Earthquake (EMC) using pre- and post-event LiDAR. Based on the analysis, moving window A-ICP is able to better estimate the synthetic surface ruptures, and provides a smoother estimate of actual displacement for the EMC earthquake.
Starting Page	3338
Ending Page	3346
Page Count	9
File Size	1282920
File Format	PDF
ISSN	19391404
Volume Number	8
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Iterative closest point algorithm Laser radar Accuracy Three-dimensional displays Laser beams Estimation Convergence moving window A-ICP Change detection earthquake iterative closest point (ICP) light detection and ranging (LiDAR)
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science Computers in Earth Sciences

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