Journal of Research in Environmental and Earth Sciences, 04 (2016) 139-145 Print ISSN: 2356-5799; Online ISSN: 2356-5802 © Knowledge Journals www.knowledgejournals.com Research article Automatic extraction of lineaments from Landsat Etm+ images and their structural interpretation: Case Study in Nefza region (North West of Tunisia) Slimen Sedrette a,* , Noamen Rebaï b a UTM, Departement of Geology. Campus Universitaire, 2092 El Manar Tunisia. b UTM, Ecole Nationale d’Ingénieurs de Tunis, Departement de GC. BP. 37, le Belvédère 1002 Tunis, Tunisia. * Corresponding author. Tel.: +216 97419459. E-mail address: ssedrette@gmail.com (Slimen Sedrette) Article history: Received 22 March 2016; Received in revised form 6 June 2016. Accepted 8 June 2016; Available online 15 August 2016. Abstract The lineaments are linear or curvilinear discontinuities in direct connection with the faults and the composite fractures. Lineament analysis constitutes an interesting approach in the geological mapping and mineral exploration. In our study, various types of techniques to extract lineaments were applied to a panchromatic band of Landsat 7 ETM + image covering the Nefza mining district in the North West of Tunisia. In the first step, four derived images were generated from four Sobel directional filters in all possible directions (N-S, E-W, NE-SW and NW-SE). These filters increase contrast in the image and allowed mapping a larger number of lineaments. In the second step, the lineaments mapping was performed by using the Line module of PCI Geomatica. This will allow us an automatic extraction of lineaments. The next step is the superposition of the lineaments maps obtained in different directions to create a synthesis lineaments map. The result of this study show a positive correlation between structural geology (faulting, lineament, warping) and the dominant extracted lineament orientations. The highest densities obtained are oriented NE-SW, N-S and E-W, with the predominance of the first direction. Key words: Lineaments extraction, Satellite images, Nefza, Tunisia. © 2016 Knowledge Journals. All rights reserved. 1. Introduction The availability of high resolution multispectral data and the ability of digital image processing techniques to generate enhanced images have expanded the remote sensing potential of geological lineaments extraction with greater accuracy (Drury, 1987). Linear features on the earth surface have been a theme of study for geologists for many years, from the early years of the last century (Hobbs, 1904) up to now. Several approaches have already been used in numerous studies in the world (Bonn et Rochon, 1992; Yésou et al, 1993; Savané, 1997; Kouamé, 1999; Jourda, 2005). There are a variety of computer tools that can facilitate the interpretation of lineaments. Some even allow the automatic extraction of lineaments, using contrast- detection algorithms within an image. Abdullah et al., 2010 uses software PCI Geomatica with module LINE, which is used for extraction of linear features from raster images. Mallast et al., (2011) uses software ERDAS Imagine modules and PCI Geomatica. Argialas and Mavrantza on 2004 uses optimized Hough Transform method. Pinto et al., (2013) uses Hough Transform and software LESSA. The extraction of geological lineaments from remote sensing data can be grouped into at least three approaches: manual extraction (Jordan and Schott, 2005); semi-automatic extraction (Lim et al., 2001, Jourda et al., 2006) et finally the automatic extraction (Anwar et al., 2013; Rayan, 2013). In manual and semi-automatic approaches, the lineament extraction is influenced by the experience of the interpreter, whereas the automatic extraction depends mainly on the performance of the application and of the information in the image used (Al Dossary and Marfurt, 2007). The main objective of this work is to evaluate the results of automatic extraction of lineaments from