Abstract
We present a method for determining 3-dimensional, local ground displacements caused by an earthquake. The technique requires pre- and post-earthquake point cloud datasets, such as those collected using airborne Light Detection and Ranging (Lidar). This problem is formulated as a point cloud registration problem in which the full point cloud is divided into smaller windows, for which the local displacement that best restores the post-earthquake point cloud onto its pre-earthquake equivalent must be found. We investigate how to identify the size of window to be considered for registration. We then present an information theoretic approach that classifies whether a region contains an earthquake fault. These methods are first validated on simulated earthquake datasets, for which the input displacement field is known, and then tested on a real earthquake. We show results and error analyses for a variety of different window sizes, as well as results for our fault detection algorithm.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Besl, P.J., McKay, N.D.: A method for registration of 3-d shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14, 239–256 (1992)
Bevis, M., Hudnut, K., Sanchez, R., Toth, C., Grejner-Brzezinska, D., Kendrick, E., Caccamise, D., Raleigh, D., Zhou, H., Shan, S., Shindle, W., Yong, A., Harvey, J., Borsa, A., Ayoub, F., Shrestha, R., Carter, B., Sartori, M., Phillips, D., Coloma, F.: The B4 Project: Scanning the San Andreas and San Jacinto Fault Zones. In: AGU Fall Meeting Abstracts, pp. H34–B01 (December 2005)
Crum, T., Hartkens, W.R., Hill, D.L.G.: Non rigid Image Registration: theory and practice. British Journal of Radiology (2004)
England, P., Jackson, J.: Uncharted seismic risk. Nature Geoscience 4, 348–349 (2011)
Low, K.-L.: Linear least squares optimization for point-to-plane ICP surface registration. Technical Report TR04-004
Oskin, M.E., Arrowsmith, J.R., Hinojosa-Corona, A., Elliott, A.J., Fletcher, J.M., Fielding, E.J., Gold, P.O., Garcia, J.J.G., Hudnut, K.W., Liu-Zeng, J., Teran, O.J.: Near-Field Deformation from the El Mayor-Cucapah Earthquake Revealed by Differential LIDAR. Science 335, 702–705 (2012)
Prentice, C.S., Crosby, C.J., Whitehill, C.S., Arrowsmith, J.R., Furlong, K.P., Phillips, D.A.: Illuminating Northern California’s Active Faults. Eos Trans. AGU 90, 55–55 (2009)
Rusinkiewicz, S., Levoy, M.: Efficient variants of the ICP algorithm. In: International Conference on 3-D Digital Imaging and Modeling (2001)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Krishnan, A.K., Nissen, E., Saripalli, S., Arrowsmith, R., Corona, A.H. (2013). Change Detection Using Airborne LiDAR: Applications to Earthquakes. In: Desai, J., Dudek, G., Khatib, O., Kumar, V. (eds) Experimental Robotics. Springer Tracts in Advanced Robotics, vol 88. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00065-7_49
Download citation
DOI: https://doi.org/10.1007/978-3-319-00065-7_49
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00064-0
Online ISBN: 978-3-319-00065-7
eBook Packages: EngineeringEngineering (R0)