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Automatic Extraction of Faults and Fractal Analysis from Remote Sensing Data : Volume 14, Issue 2 (22/03/2007)

By Gloaguen, R.

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Book Id: WPLBN0004019811
Format Type: PDF Article :
File Size: Pages 8
Reproduction Date: 2015

Title: Automatic Extraction of Faults and Fractal Analysis from Remote Sensing Data : Volume 14, Issue 2 (22/03/2007)  
Author: Gloaguen, R.
Volume: Vol. 14, Issue 2
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2007
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Niemeyer, I., Marpu, P. R., & Gloaguen, R. (2007). Automatic Extraction of Faults and Fractal Analysis from Remote Sensing Data : Volume 14, Issue 2 (22/03/2007). Retrieved from http://hawaiilibrary.net/


Description
Description: Institute for Geology, Freiberg University of Mining and Technology, 09599 Freiberg, Germany. Object-based classification is a promising technique for image classification. Unlike pixel-based methods, which only use the measured radiometric values, the object-based techniques can also use shape and context information of scene textures. These extra degrees of freedom provided by the objects allow the automatic identification of geological structures. In this article, we present an evaluation of object-based classification in the context of extraction of geological faults. Digital elevation models and radar data of an area near Lake Magadi (Kenya) have been processed. We then determine the statistics of the fault populations. The fractal dimensions of fault dimensions are similar to fractal dimensions directly measured on remote sensing images of the study area using power spectra (PSD) and variograms. These methods allow unbiased statistics of faults and help us to understand the evolution of the fault systems in extensional domains. Furthermore, the direct analysis of image texture is a good indicator of the fault statistics and allows us to classify the intensity and type of deformation. We propose that extensional fault networks can be modeled by iterative function system (IFS).

Summary
Automatic extraction of faults and fractal analysis from remote sensing data

Excerpt
Baker, B. H.: Geology of the Magadi area., Geol. Surv. Kenya Rep., 42, 82 p., 1958.; Baker, B. H., Mitchell, J. G., and Williams L. A. J.: Stratigraphy, geochronology and volcano-tectonic evolution of the Kedong-Naivasha-Kinangop region, Gregory Rift Valley, Kenya, J. Geol. Soc., London, 145, 107–116, 1988.; Barnsley, M.: Fractals everywhere, Academic Press, San Diego, pp 1–117, 1988.; Benz, U. C., Hoffmann, P., Willhauck, G., Lingenfelder, I., and Heynen, M.: Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information, ISPRS Journal of Photogrammetry and Remote sensing, 58, 239–258, 2004.; Birt, C. S., Maguire, P. K. H., Khan, M. A., Thybo, H., Keller, G. R., and Patel, J.: The influence of pre-existing structures on the evolution of the southern Kenya Rift Valley-evidence from seismic and gravity studies, Tectonophysics, 248, 211–242, 1997.; Cardon, H.: Mécanisme de propagation des r�seaux de failles: l'exemple du Rift Gregory (Kenya), Unpublished PhD thesis, Univ. Claude Bernard., 1999.; Carr, J. R.: Numerical Analysis for the Geological Sciences, Prentice Hall, Inc, NJ, 1995.; Castaing, C., Bourgine, B., Chiles, J. P., Genter, A., Ouilon, G., and Sornette, D.: Multiscale organization of joints and faults revealed by geostatistical, multifractal and wavelet techniques, in: EUG8. Terra Abstracts, Strasbourg, 1995.; Chu, D. and Gordon, G. R.: Evidence for motion between Nubia and Somalia along the Southwest Indian Ridge, Nature, 398, 64–67, 1999.; Cowie, P. and Scholz, C. H.: Displacement-length scaling relationship for faults: data synthesis and discussion, J. Struc. Geol., 14(10), 1149–1156, 1992.; Cowie, P., Scholz, C. H., Edwards, M., and Malinverno, A.: Fault strain and seismic coupling on mid-ocean ridges, J. Geophys. Res., 98, 17 911–17 920, 1993.; Davy, P.: On the frequency-length distribution of the San Andreas fault system, J. Geophys. Res., 98(B7), 12 141–12 151, 1993.; Gloaguen, R., Rolet, J., Mouchot, M.-C., and Le Gall, B.: Geometry and role of transverse structures on the segmentation of the East African Rift System: Examples from the Kenya Rift, EOS, Trans. AGU, 80(46), 1024, 1999.; Velde, B., Dubois, J., Touchard, G., and Badri, A.: Fractal analysis of fracture in rocks: The Cantor's Dust Method, Tectonophysics, 179, 345–352, 1990.; Gloaguen, R.: Analyse quantitative de l'extension continentale par imagerie satellitale et optique et radar. Application au rift sud-kenyan, Unpublished PhD thesis, Univ. Bretagne Occidentale., 2000.; Henderson, F. M. and Lewis, A. J.: Principles and Applications of imaging Radar, manual of Remote sensing, 3rd edition, vol. 2., John Wiley and sons, 1998.; Keir, D., Stuart, G. W., Jackson, A., and Ayele, A.: Local Earthquake Magnitude Scale and Seismicity Rate for the Ethiopian Rift, Bulletin of the Seismological Society of America, vol. 96, no. 6, pp. 2221–2230, doi:10.1785/0120060051., 2006.; Marpu, P. R., Niemeyer, I., and Gloaguen, R.: A procedure for automatic object-based classification, Proceedings of the 1st International Conference on Object-based Image Analysis, 2006.; Marrett, R. and Allmendinger, R. W.: Estimates of strain due to brittle faulting: sampling of fault populations, J. Struct. Geol., 13, 735–738, 1991.; Mechie, J., Keller, G. R., Prodehl, C., Gaciri, S. J., Braile, L. W., Mooney, W. D., Gajewski, D. J., and Sandmeier, K. J.: Crustal structure beneath the Kenya Rift from axial profile data, Tectonophysics, 236, 179–199, 1994.; Nussbaum, S., Niemeyer, I., and Canty, M. J.: Feature Recognition in the Context of automated Object-Oriented Analysis of Remote Sensing Data monitoring the Iranian Nuclear Sites, Proceedings of Optics/Photonics in Security & Defence, SPIE, 2005.; Pentland, A. P.: Fractal-Based Description of Natural Scenes, IEEE Trans. Pattern Anal. Machine Intell., 6, 661–674, 1984

 

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