Abstract
Numerical agglomerative hierarchical classification is fundamentally an unsupervised method of grouping individuals on which there are multivariate data so as to identify natural groups in them and perhaps in the populations from which they are drawn and where no prior classification exists or is assumed. We have used the technique to make a tectonic regionalization of the Zagros region and to see whether it can increase our understanding of the regional tectonics. We first identified 137 sub-areas as units for each of which we had recorded 18 quantitative variables; these formed our data, which we held in a data matrix of n = 137 rows and p = 18 columns. After data standardization, we computed the relationships among all pairs of sub-areas as Euclidean distances and then grouped them hierarchically using Ward’s method to form a dendrogram. Cutting the dendrogram at several levels of dissimilarity provided a series of tectonic zoning maps which matched the trends in tectonic evolution of the region. This sequence, obtained automatically, agrees well with our general understanding of the geology. However, in the present study some new findings about the tectonic nature of the region were obtained. For example, the role of the Kazerun-Qatar and Oman lines as two major structural features has been clearly demonstrated. In addition, a striking difference between the Minab zone and the other parts of the Zagros region has been observed. This study simply presents the necessity and usefulness of hierarchical cluster analysis, as an appropriate statistical pattern recognition technique, for increasing the degree of the objectivity of the regionalization researches in the Earth sciences.
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References
Agard P, Omrani J, Jolivet L, Whitechurch H, Vrielynck B, Spakman W, Monie P, Meyer B, Wortel R (2011) Zagros orogeny: a subduction-dominated process. In: Lacombe O, Grasemann B, Simpson G (eds) Geodynamic evolution of the Zagros. Geological Magazine, 692–725
Ahmed BYM (1997) Climatic classification of Saudi Arabia: an application of factor-cluster analysis. J Geol 41:69–84
Alavi M (1980) Tectonostratigraphic evolution of the Zagrosides of Iran. Geology 8:144–149
Alavi M (1994) Tectonics of the Zagros orogenic belt of Iran: new data and interpretations. Tectonophysics 229:211–238
Anderberg MR (1973) Cluster analysis for applications. Academic, New York
Ansari A, Noorzad A, Zafarani H (2009) Clustering analysis of the seismic catalog of Iran. Comput Geosci 35:475–486
Anyadike RNC (1987) A multivariate classification and regionalization of West African climates. Int J Climatol 7:157–164
Berberian M (1976) Contribution to the seismotectonics of Iran (Part II). Geology Survey of Iran, Tehran
Berberian M (1995) Master “blind” thrust fault hidden under the Zagros folds: active basement tectonics and surface morphotectonics. Tectonophysics 241:193–224
Blanc EJP, Allen MB, Inger S, Hassani H (2003) Structural styles in the Zagros Simple Folded Zone, Iran. J Geol Soc Lond 160:401–412
Collyer PL, Merriam DF (1973) An application of cluster analysis in mineral exploration. Math Geol 5:213–223
Davis JC (2002) Statistics and data analysis in geology, 3rd edn. John Wiley & Sons, New York
De Rubeis V, Casparini C, Solipaca A, Tosi P (1992) Seismotectonic characterization of Italy, using statistical analysis of geophysical variables. J Geodyn 16:103–122
Duda RO, Hart PE, Stork DG (2001) Pattern classification. Wiley, New York
Everitt BS, Landau S, Leese M, Stahl D (2011) Cluster analysis, 5th edn. John Wiley & Sons Ltd, West Sussex
Falcon NL (1974) Southern Iran: Zagros Mountains. In: Spenser A (ed) Mesozoic–Cenozoic Orogenic belts. Geological Society London Special Publication 4:199–211
Ghasemi A, Talbot CJ (2005) A new tectonic scenario for the Sanandaj–Sirjan Zone (Iran). J Asian Earth Sci 26:683–693
Gordon AD (1996) Hierarchical classification. In: Arabie P, Hubert LJ, De Soete G (eds) Clustering and classification. World Scientific Publishers, River Edge, pp 65–121
Gordon AD (1999) Classification, 2nd edn. Chapman and Hall/CRC Publication, London
Gower JC (1971) A general coefficient of similarity and some of its properties. Biometrics 27:857–874
Hair JF Jr, Anderson RE, Tatham RL, Black WC (1998) Multivariate data analysis. Prentice Hall, Englewood Cliffs
Härdle WK, Simar L (2012) Applied multivariate statistical analysis, 3rd edn. Springer, Berlin
Harff J, Davis JC (1990) Regionalization in geology by multivariate classification. Math Geol 22:573–588
Hargrove WW, Hoffman FM (2005) Potential of multivariate methods for delineation and visualization of ecoregions. Environ Manag 34:39–60
Hashemi SN (2004) Tectonic regionalization of Iran using multivariate geostatistical methods. unpublished doctoral dissertation, Shiraz University
Hashemi SN (2013) Seismicity characterization of Iran: a multivariate statistical approach. Math Geosci 45:705–725
Hassanzadeh J, Stockli DF, Horton BK, Axen GJ, Stockli LD, Grove M, Schmitt AK, Walker JD (2008) U-Pb zircon geochronology of late Neoproterozoic–Early Cambrian granitoids in Iran: implications for paleogeography, magmatism, and exhumation history of Iranian basement. Tectonophysics 451:71–96
Jain AK, Murty MN, Flynn PJ (1999) Data clustering: a review. ACM Comput Surv 31:264–323
Jung Y, Park H, Du D, Drake BL (2003) A decision criterion for the optimal number of clusters in hierarchical clustering. J Glob Optim 25:91–111
Kaufman L, Rousseeuw PJ (2005) Finding groups in data, an introduction to cluster analysis. Wiley, New York
Marques de Sa JP (2001) Pattern recognition: concepts, methods, and applications. Springer, New York
McQuarrie N (2004) Crustal scale geometry of the Zagros fold-thrust belt, Iran. J Struct Geol 26:519–535
Milligan GW, Cooper MC (1985) An examination of procedures for determining the number of clusters in a data set. Psychometrika 50:159–179
Mouthereau F, Tensi J, Bellahsen N, Lacombe O, De Boisgrollier T, Kargar S (2007) Tertiary sequence of deformation in a thin-skinned/thick-skinned collision belt: The Zagros Folded Belt (Fars, Iran). Tectonics 26:TC5006. doi:10.1029/2007TC002098, 28 p
Nowroozi AA (1976) Seismotectonic Provinces of Iran. Bull Seismol Soc Am 66:1249–1276
Parks JM (1966) Cluster analysis applied to multivariate geologic problems. J Geol 74:703–715
Puvaneswaran M (1990) Climatic classification for Queensland using multivariate statistical techniques. Int J Climatol 10:591–608
Romesburg HC (1984) Cluster analysis for researchers. Lifetime Learning Publications, Belmont
Sepehr M, Cosgrove JM (2004) Structural framework of the Zagros Fold-Thrust belt, Iran. Mar Pet Geol 21:829–843
Sneath PHA, Sokal RR (1973) Numerical taxonomy. W.H. Freeman, San Francisco
SPSS (2006) Statistical package for the social sciences, SPSS version 15.0. SPSS Inc, Chicago
Stöcklin J (1968) Structural history and tectonics of Iran: a review. Bull Am Assoc Pet Geol 52:1229–1258
Swan ARH, Sandilands M (1995) Introduction to geological data analysis. Blackwell Science, Oxford
Takin M (1972) Iranian geology and continental drift in the Middle East. Nature 235:147–150
Theodoridis S, Koutroumbas K (2006) Pattern recognition, 3rd edn. Academic Press
Thorndike RL (1953) Who belong in the family? Psychometrika 18:267–276
Tibshirani R, Walther G, Hastie T (2001) Estimating the number of clusters in a data set via the gap statistic. JRSS-B 63:411–423
Vernant P, Nilforoushan F, Hatzfeld D, Abbassi MR, Vigny C, Masson F, Nankali H, Martinod J, Ashtiani A, Bayer R, Tavakoli F, Chery J (2004) Present-day crustal deformation and plate kinematics in the Middle East constrained by GPS measurements in Iran and northern Oman. Geophys J Int 157:381–398
Webb AR, Copsey KD (2011) Statistical patterns recognition, 3rd edn. John Wiley & Sons, Ltd, Sussex
Webster R (1977) Quantitative and numerical methods in soil classification and survey. Oxford University Press, Oxford
Zamani A, Hashemi N (2004) Computer-based self organized tectonic zoning: a tentative pattern recognition for Iran. Comput Geosci 30:705–718
Zamani A, Sami A, Khalili M (2012) Multivariate rule-based seismicity map of Iran: a data-driven model. Bull Earthq Eng 10:1667–1683
Zhao Q, Hautamaki V, Franti P (2008) Knee Point Detection in BIC for Detecting the Number of Clusters. ACIVS 2008, LNCS 5259, 664–673
Acknowledgments
This research has been partially supported by the Damghan University Research Council. We thank Dr. Richard Webster (Rothamsted Research, Harpenden, UK) for his valuable help and guidance which resulted in an improvement of the earlier version of this manuscript. We also appreciate the comments of reviewers for constructive suggestions that improved the paper.
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Communicated by: H. A. Babaie
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Hashemi, S.N., Mehdizadeh, R. Application of hierarchical clustering technique for numerical tectonic regionalization of the Zagros region (Iran). Earth Sci Inform 8, 367–380 (2015). https://doi.org/10.1007/s12145-014-0163-5
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DOI: https://doi.org/10.1007/s12145-014-0163-5