Application of Fractal Modelling for Cu Mineralisation Reconnaissance by ASTER Multispectral and Stream Sediment Data in
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RESEARCH ARTICLE
Application of Fractal Modelling for Cu Mineralisation Reconnaissance by ASTER Multispectral and Stream Sediment Data in Khoshname Area, NW Iran Peyman Afzal & Ramin Aramesh Asl & Ahmad Adib & Amir Bijan Yasrebi
Received: 4 January 2014 / Accepted: 15 April 2014 # Indian Society of Remote Sensing 2014
Abstract This study identifies the major Cu anomalous zones including iron oxide, argillic and phyllic alterations and lithology as the most important extractable layers from the satellite images in Khoshname area located in the western part of Tarom - Hashtjin belt as a main metallogenic belt in the NW of Iran by utilization of concentration-area (C-A) fractal model based on 216 collected stream sediment and remote sensing data. The C-A fractal model for ASTER image log-log plots indicate three Cu geochemical populations for alterations which means that the high intensity for iron oxides, argillic and phyllic commences with 199, 177 and 158, respectively, in terms of pixels’ values. With respect to the C-A log-log plot based on the stream sediment data, there are three Cu populations which indicate that Cu background and
P. Afzal (*) : R. A. Asl : A. Adib Department of Mining Engineering, Faculty of Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran e-mail: [email protected] R. A. Asl e-mail: [email protected] A. Adib e-mail: [email protected] P. Afzal : A. B. Yasrebi Camborne School of Mines, University of Exeter, Penryn, UK A. B. Yasrebi e-mail: [email protected]
high intensive anomalies are 56 ppm, respectively. The locations of high intensive Cu anomalies are situated in the SW parts of the area. To certify this, a correlation between remote sensing and geochemical data has been conducted to validate the C-A fractal model for Cu anomalies associated with alteration zones. Keywords C-A fractal model . PCA . Alteration . Multispectral . Hashtjin
Introduction Multispectral images have been increasingly utilised to characterise features on the earth’s surface for various purposes especially the mineral exploration. Remote sensing techniques are used for mineral exploration and geosciences in two applications: (1) Geological mapping of faults, fractures and lineaments; (2) Delineation of hydrothermally alteration zones (Sabins 1999; Ranjbar et al. 2004; Khan et al. 2007; Beiranvandpour and Hashim 2012; Sadeghi et al. 2013). The purpose of displaying the images should not be only practice to provide a visual interpretation to the variance of images, although this has been the primary objective of the most conventional methods, e.g., Crosta (Alberti et al. 1993) and band triples (Abrams et al. 1983). The colour palette should reflect realworld features on the ground which must be the primary objective of employing remote sensing data. One
J Indian Soc Remote Sens
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Fig. 1 Location and geological map of the Khoshname area
of the crucial tasks involved in image processing is to classify image values into components and to establish the relationships between thes
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