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A method for local approximation of a planar deformation field Cover

A method for local approximation of a planar deformation field

Open Access
|Oct 2019

References

  1. Altiner, Y. (2013). Analytical surface deformation theory: for detection of the Earth’s crust movements Springer, Berlin, Heidelberg, doi:10.1007/978-3-662-03935-9
  2. Bayly, P. V., Cohen, T., Leister, E., Ajo, D., Leuthardt, E., and Genin, G. (2005). Deformation of the human brain induced by mild acceleration. Journal of Neurotrauma 22(8):845–856, doi:10.1089/neu.2005.22.845
  3. Berber, M., Kutoglu, H., Dare, P., and Vanícek, P. (2012). Combining surface deformation parameters referred to different terrestrial coordinate systems. Survey Review 44(324):23– 29, doi:10.1179/1752270611Y.0000000005
  4. Caspary, W., Haen, W., and Borutta, H. (1990). Deformation analysis by statistical methods. Technometrics 32(1):49–57.
  5. Chaves, E. W. V. (2013). Notes on continuum mechanics Springer, Dordrecht, doi:10.1007/978-94-007-5986-2
  6. Dermanis, A. and Kotsakis, C. (2006). Estimating crustal deformation parameters from geodetic data: Review of existing methodologies, open problems and new challenges. In Sansò, F. and Gil, A. J., editors, Geodetic deformation monitoring: from geophysical to engineering roles pages 7–18. Springer, Heidelberg, doi:10.1007/978-3-540-38596-7_2
  7. Dermanis, A. and Livieratos, E. (1983). Applications of deformation analysis in geodesy and geodynamics. Reviews of Geophysics 21(1):41–50, doi:10.1029/RG021i001p00041
  8. Gander, W. (1990). Algorithms for the polar decomposition. SIAM Journal on Scientific and Statistical Computing 11(6):1102– 1115, doi:10.1137/0911062
  9. Goudarzi, M. A., Cocard, M., and Santerre, R. (2015). Geostrain: An open source software for calculating crustal strain rates. Computers & Geosciences 82:1–12,doi:10.1016/j.cageo.2015.05.007
  10. Higham, N. J. (1986). Computing the polar decomposition—with applications. SIAM Journal on Scientific and Statistical Computing 7(4):1160–1174, doi:10.1137/0907079
  11. Markley, F. L. and Mortari, D. (1999). How to estimate attitude from vector observations. AIAA/AAS Paper pages 99–427.
  12. Osada, E. and Sergieieva, K. (2010). O badaniu zniekształcen modeli transformacji map na podstawie elipsy Tissota – długosci, pola lub katy. Magazyn geoinformacyjny Geodeta (1):176.
  13. Shoemake, K. and Duff, T. (1992). Matrix animation and polar decomposition. In Proceedings of the conference on Graphics interface volume 92, pages 258–264.
  14. Szafarczyk, A. and Gawalkiewicz, R. (2016). Case study of the tensor analysis of ground deformations evaluated from geodetic measurements in a landslide area. Acta Geodynamica et Geomaterialia 13(2):213–222, doi:10.13168/AGG.2015.0003
  15. Tanaka, M., Wada, S., and Nakamura, M. (2012). Computational biomechanics: theoretical background and biological/biomedical problems volume 3. Springer, Tokyo, doi:10.1007/978-4-431-54073-1
DOI: https://doi.org/10.2478/rgg-2019-0007 | Journal eISSN: 2391-8152 | Journal ISSN: 0867-3179
Language: English
Page range: 1 - 8
Submitted on: May 15, 2019
Accepted on: Aug 5, 2019
Published on: Oct 10, 2019
Published by: Warsaw University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2019 Marcin Ligas, Marek Banaś, Anna Szafarczyk, published by Warsaw University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.