Document Type : Original Research Paper

Authors

1 School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran

2 School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran

Abstract

Hyperspectral remote sensing records reflectance or emittance data in a large sum of contiguous and narrow spectral bands, and thus has many information in detecting and mapping the mineral zones. On the other hand, the geological and geophysical data gives us some other fruitful information about the physical characteristics of soil and minerals that have been recorded from the surface. The Sarcheshmeh mining area located in the NW-trending Uromieh-Dokhtar magmatic belt within Central Iran is mainly of porphyry type, and is associated with extensive hydrothermal alterations. Due to the semi-arid type of climate with abundant rock exposure, this area is suitable for application of remote sensing techniques. In this work, we focus on generating the alteration maps around Cu porphyry copper deposits using the spectral angle mapper algorithm on Hyperion data by applying two filters named reduction to pole and analytical signal on a total magnetic intensity map and generating the Kd map from radiometry data. What is clear is the high importance of applying the adequate pre-processing on Hyperion data because of low signal-to-noise ratio. By comparing the known deposits in the region with the results obtained by applying the mentioned methods, it is revealed that not all the higher K radiometric values are entirely associated with the hydrothermal alteration zones, and in contrast, the potassic alteration map extracted from Hyperion imagery successfully corresponds to the alteration zones around the Sarcheshmeh mining area. Finally, the results particularly obtained from processing the Hyperion data are confirmed by indices of Cu porphyry deposits in the region.

Keywords

Main Subjects

[1]. Moon, C., Whateley, M. and Evans, A. (2000). Introduction to Mineral Exploration. Blackwell, Oxford 498 pp.
[2]. Van der Meer, F.D., Van der Werff, H.M., Van Ruitenbeek, F.J., Hecker, C.A., Bakker, W.H., Noomen, M.F. and Woldai, T. (2012). Multi-and hyperspectral geologic remote sensing: A review. International Journal of Applied Earth Observation and Geoinformation. 14 (1): 112-128.
[3]. Bedini, E. (2011). Mineral mapping in the Kap Simpson complex, central East Greenland, using HyMap and ASTER remote sensing data. Advances in Space Research. 47 (1): 60-73.‏‏
[4]. Kruse, F.A., Lefkoff, A.B. and Dietz, J.B. (1993). Expert system-based mineral mapping in northern Death Valley, California/Nevada, using the airborne visible/infrared imaging spectrometer (AVIRIS). Remote Sensing of Environment. 44 (2-3): 309-336.‏
[5]. Zadeh, M.H., Tangestani, M.H., Roldan, F.V. and Yusta, I. (2014). Sub-pixel mineral mapping of a porphyry copper belt using EO-1 Hyperion data. Advances in Space Research. 53 (3): 440-451.‏
[6]. Anderson, H. and Nash, C. (1997). Integrated lithostructural mapping of the Rössing area, Namibia using high resolution aeromagnetic, radiometric, Landsat data and aerial photographs. Exploration geophysics. 28 (2): 185-191.‏
[7]. Graham, D.F. and Bonham-Carter, G.F. (1993). Airborne radiometric data-A tool for reconnaissance geological mapping using a GIS. Photogrammetric Engineering and Remote Sensing. 59 (8): 1243-1249.‏
[8]. El Nabi, S.H.A. (2013). Role of γ-ray spectrometry in detecting potassic alteration associated with Um Ba’anib granitic gneiss and metasediments, G. Meatiq area, Central Eastern Desert, Egypt. Arabian Journal of Geosciences. 6 (4): 1249-1261.‏
[9]. Grasty, R.L. and Shives, R.B.K. (1997). Applications of gamma ray spectrometry to mineral exploration and geological mapping. In Workshop presented at Exploration (Vol. 97).‏
[10]. Lo, B.B. and Pitcher, D.H. (1996). A case history on the use of regional aeromagnetic and radiometric data sets for lode gold exploration in Ghana. In SEG Technical Program Expanded Abstracts 1996 (pp. 592-595). Society of Exploration Geophysicists.‏
[11]. Wilford, J.R., Bierwirth, P.E. and Craig, M.A. (1997). Application of airborne gamma-ray spectrometry in soil/regolith mapping and applied geomorphology. AGSO Journal of Australian Geology and Geophysics. 17 (2): 201-216.‏
[12]. Maden, N. and Akaryalı, E. (2015). Gamma ray spectrometry for recognition of hydrothermal alteration zones related to a low sulfidation epithermal gold mineralization (eastern Pontides, NE Türkiye). Journal of Applied Geophysics, 122, 74-85.‏
[13]. Shives, R.B., Charbonneau, B.W. and Ford, K.L. (2000). The detection of potassic alteration by gamma-ray spectrometry—Recognition of alteration related to mineralizationDetecting Ore Using GRS and K Alteration. Geophysics. 65 (6): 2001-2011.‏
[14]. Daneshfar, B. (1998). An evaluation of indicators of prospectivity and potential mapping of porphyry deposits in middle and southern British Columbia by a GIS study of regional geochemical and other geoscientific data (Doctoral dissertation, University of Ottawa).‏
[15]. Abedi, M., Gholami, A. and Norouzi, G.H. (2013). A stable downward continuation of airborne magnetic data: A case study for mineral prospectivity mapping in Central Iran. Computers & Geosciences, 52, 269-280.‏
[16]. Pazand, K., Hezarkhani, A. and Ataei, M. (2012). Using TOPSIS approaches for predictive porphyry Cu potential mapping: A case study in Ahar-Arasbaran area (NW, Iran). Computers & Geosciences, 49, 62-71.‏
[17]. Waterman, G.C. and Hamilton, R.L. (1975). The Sar Cheshmeh porphyry copper deposit. Economic Geology. 70 (3): 568-576.‏
[18]. Lowell, J.D. and Guilbert, J.M. (1970). Lateral and vertical alteration-mineralization zoning in porphyry ore deposits. Economic Geology. 65 (4): 373-408.‏
[19]. Hoover, D.B., Klein, D.P., Campbell, D.C. and du Bray, E. (1995). Geophysical methods in exploration and mineral environmental investigations. Preliminary compilation of descriptive geoenvironmental mineral deposit models. US Geological Survey Open-File Report, 95-831.‏
[20]. Nabighian, M.N. (1984). Toward a three-dimensional automatic interpretation of potential field data via generalized Hilbert transforms: Fundamental relations. Geophysics. 49 (6): 780-786.‏
[21]. Nabighian, M.N. (1972). The analytic signal of two-dimensional magnetic bodies with polygonal cross-section: its properties and use for automated anomaly interpretation. Geophysics. 37 (3): 507-517.
[22]. de Quadros, T.F., Koppe, J.C., Strieder, A.J. and Costa, J.F.C. (2003). Gamma-ray data processing and integration for lode-Au deposits exploration. Natural Resources Research. 12 (1): 57-65.‏
[23]. Van Ede, R. (2004). Destriping and geometric correction of an ASTER level 1a image. Department of Physical Geography, Utrecht University.‏
[24]. Darmawan, A. (2006). Mapping soil mineral using Hyperion imagery in relation to the level of structural damage in the Bam earthquake. University of Melbourne, Department of Geomatics.‏
[25]. Research Systems Inc. (2003). ENVI Tutorial, ENVI Software Package Version 4.0.
[26]. Matthew, M.W., Adler-Golden, S.M., Berk, A., Richtsmeier, S.C., Levine, R.Y., Bernstein, L.S. and Ratkowski, A.J. (2000). Status of atmospheric correction using a MODTRAN4-based algorithm. In Algorithms for multispectral, hyperspectral, and ultraspectral imagery VI (Vol. 4049, pp. 199-207). International Society for Optics and Photonics.‏‏
[27]. Plaza, A., Martínez, P., Pérez, R. and Plaza, J. (2004). A quantitative and comparative analysis of endmember extraction algorithms from hyperspectral data. IEEE transactions on geoscience and remote sensing. 42 (3): 650-663.‏
[28]. Boardman, J.W. (1994, August). Geometric mixture analysis of imaging spectrometry data. In Proceedings of IGARSS'94-1994 IEEE International Geoscience and Remote Sensing Symposium (Vol. 4, pp. 2369-2371). IEEE.‏
[29]. Chaudhry, F., Wu, C.C., Liu, W., Chang, C.I. and Plaza, A. (2006). Pixel purity index-based algorithms for endmember extraction from hyperspectral imagery. Recent advances in hyperspectral signal and image processing, 37 (2): 29-62.
[30]. Richards, J.A. and Richards, J.A. (1999). Remote sensing digital image analysis (Vol. 3, pp. 10-38). Berlin et al.: Springer.‏‏