ASTER-Based Remote Sensing Image Analysis for Prospection Criteria of Podiform Chromite at the Khoy Ophiolite (NW Iran)

Ali Imamalipour,Behnam Mehdikhani

doi:10.3390/min11090960

Abstract

A single chromite deposit occurrence is found in the serpentinized harzburgite unit of the Khoy ophiolite complex in northwest Iran, which is surrounded by dunite envelopes. This area has mountainous features and extremely rugged topography with difficult access, so prospecting for chromite deposits by conventional geological mapping is challenging. Therefore, using remote sensing techniques is very useful and effective, in terms of saving costs and time, to determine the chromite-bearing zones. This study evaluated the discrimination of chromite-bearing mineralized zones within the Khoy ophiolite complex by analyzing the capabilities of ASTER satellite data. Spectral transformation methods such as optimum index factor (OIF), band ratio (BR), spectral angle mapper (SAM), and principal component analysis (PCA) were applied on the ASTER bands for lithological mapping. Many chromitite lenses are scattered in this ophiolite, but only a few have been explored. ASTER bands contain improved spectral characteristics and higher spatial resolution for detecting serpentinized dunite in ophiolitic complexes. In this study, after the correction of ASTER data, many conventional techniques were used. A specialized optimum index factor RGB (8, 6, 3) was developed using ASTER bands to differentiate lithological units. The color composition of band ratios such as RGB ((4 + 2)/3, (7 + 5)/6, (9 + 7)/8), (4/1, 4/7, 4/5), and (4/3 × 2/3, 3/4, 4/7) produced the best results. The integration of information extracted from the image processing algorithms used in this study mapped most of the lithological units of the Khoy ophiolitic complex and new prospecting targets for chromite exploration were determined. Furthermore, the results were verified by comprehensive fieldwork and previous studies in the study area. The results of this study indicate that the integration of information extracted from the image processing algorithms could be a broadly applicable tool for chromite prospecting and lithological mapping in mountainous and inaccessible regions such as Iranian ophiolitic zones.

Highlights

The mapping of ophiolite sequences has become a research interest of scientists and exploration geologists in the world because they host economic minerals such as chromium, copper, manganese, gold, nickel, barium, lead, and zinc [1,2,3]
The results of this study indicate that the integration of information extracted from the image processing algorithms could be a broadly applicable tool for chromite prospecting and lithological mapping in mountainous and inaccessible regions such as Iranian ophiolitic zones
The present study evaluates the discrimination of chromite-bearing mineralized zones within the Khoy ophiolite complex by analyzing the capabilities of ASTER satellite data

Summary

Introduction

The mapping of ophiolite sequences has become a research interest of scientists and exploration geologists in the world because they host economic minerals such as chromium, copper, manganese, gold, nickel, barium, lead, and zinc [1,2,3]. Ophiolitic ultramafic rocks are the hosts of podiform chromite deposits. Podiform chromite deposits are small magmatic chromite bodies formed in the lower level of an ophiolite complex. Ophiolite zones in Iran are widespread and are often found in different locations with varying geologic and tectonic settings. The Khoy ophiolite complex is a part of the Tethyan ophiolite belt, and it is one of the largest Iranian ophiolite complexes, covering a widespread area in northwest Iran along the Iran–Turkey border and continuing toward western Turkey [5,6]

Objectives

Methods

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Conclusion