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Sub-pixel mapping of iron-bearing minerals using ALI data and MTMF algorithm, Masahim volcano, SE Iran

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Abstract

The Advanced Land Imager (ALI) data were applied to sub-pixel mapping of iron-bearing minerals at the Masahim composite volcano, SE Iran. Key minerals including goethite, jarosite, and hematite were distinguished via the analysis of spectral reflectances of field samples. The imagery endmembers were extracted using field and laboratory spectra as references; then, the target minerals were mapped using mixture-tuned matched filtering (MTMF) algorithm. Iron-bearing minerals were mainly enhanced at the central facies, generally associated with argillic and phyllic alteration units. In addition, goethite and hematite were mapped in the proximal facies. The coefficient of determination (R 2) was calculated to assess the accuracy of sub-pixel maps. The R 2 coefficient was 0.67 for goethite, 0.54 for jarosite, and 0.49 for hematite. It is concluded that ALI data are useful for mapping and detecting iron-bearing minerals. However, misclassification of goethite and hematite could be the main source of errors.

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References

  • Ahmadipour H (1994) Dynamism of volcanic activities in Mosahim volcano (Shahr-e-Babak). Dissertation. Department of Geology, Shahid Bahonar University.

  • Atapour H, Aftabi A (2007) The geochemistry of gossans associated with Sarcheshmeh porphyry copper deposit, Rafsanjan, Kerman, Iran: implications for exploration and the environment. J Geochem Explor 93:47–65. doi:10.1016/j.gexplo.2006.07.007

    Article  Google Scholar 

  • Baron D, Palmer CD (1996) Solubility of jarosite at 4–35°C. Geochim Cosmochim Acta 60:185–195

    Article  Google Scholar 

  • Bedini E (2011) Mineral mapping in the Kap Simpson complex, central East Greenland, using HyMap and ASTER remote sensing data. Adv Space Res 47:60–73. doi:10.1016/j.asr.2010.08.021

    Article  Google Scholar 

  • Bedini E (2012) Mapping alteration minerals at Malmbjerg molybdenum deposit, central East Greenland, by Kohonen self-organizing maps and matched filter analysis of HyMap data. Int J Remote Sens 33:939–961. doi:10.1080/01431161.2010.542202

    Article  Google Scholar 

  • Bigham JM, Schwertmann U, Carlson L (1992) Mineralogy of precipitates formed by the biogeochemical oxidation of Fe(II) in mine drainage. In: Biomineralization: processes of iron and manganese, Skinner HCW, Fitzpatrick RW (eds) Catena Supplement 21: Cremlingen-Destedt, Germany, pp 219-232.

  • Bishop JL, Murad E (2005) The visible and infrared spectral properties of jarosite and alunite. Am Mineral 90:1100–1107. doi:10.2138/am.2005.1700

    Article  Google Scholar 

  • Boardman JW (1998) Leveraging the high dimensionality of AVIRIS data for improved subpixel target unmixing and rejection of false positives: mixture tuned matched filtering. Summaries of the seventh JPL airborne Geoscience workshop, 12-16 January, Pasadena, CA: JPL Publication 97-1, NASA Jet Propulsion Lab: pp 55-56.

  • Boardman JW, Kruse FA, Green RO (1995) Mapping target signatures via partial unmixing of AVIRIS data. In: Summaries, fifth JPL airborne earth science workshop, Pasadena: JPL Publication, 95-1 (1).

  • Clark RN (1999) Spectroscopy of rocks and minerals, and principles of spectroscopy. In: Rencz A (ed) Manual of remote sensing, vol. 3. Wiley and Sons Inc, New York, pp 3–58

    Google Scholar 

  • Clark RN, Swayze GA, Wise R et al (2003) USGS digital spectral library splib05a, USGS Open File Report 03–395.

  • Dimitrijevic M (1973) Geology of Kerman region. (Iran Geological Survey Report No. Yu/52.) Institute for Geological and Mining Exploration and Institution of Nuclear and Other Mineral Raw Materials, Beograd Yugoslavia, p334.

  • Farrand WH, Harsanyi JC (1997) Mapping the distribution of mine tailings in the Coeur D’Alene River Valley, Idaho area through the use of a constrained energy minimization technique. Remote Sens Environ 59:64–76. doi:10.1016/S0034-4257(96)00080-6

    Article  Google Scholar 

  • Hubbard BE, Crowley JK (2005) Mineral mapping on the Chilean-Bolivian Altiplano using co-orbital ALI, ASTER and Hyperion imagery: data dimensionality issues and solutions. Remote Sens Environ 99:173–186. doi:10.1016/j.rse.2005.04.027

    Article  Google Scholar 

  • Hu X, Weng Q (2009) Estimating impervious surfaces from medium spatial resolution imagery using the self-organizing map and multi-layer perceptron neural networks. Remote Sens Environ 113:2089–2102. doi:10.1016/j.rse.2009.05.014

    Article  Google Scholar 

  • Hubbard BE, Crowley JK, Zimbelman DR (2003) Comparative alteration mineral mapping using visible to shortwave infrared (0.4–2.4 Am) hyperion, ALI and ASTER imagery. IEEE Trans Geosci Remote Sens 41:1401–1410. doi:10.1109/TGRS.2003.812906

    Article  Google Scholar 

  • Hunt GR, Ashley RP (1979) Spectra of altered rocks in the visible and near infrared. Econ Geol 74:1613–1629. doi:10.2113/gsecongeo.74.7.1613

    Article  Google Scholar 

  • Hunt GR, Salisbury JW (1970) Visible and near-infrared spectra of minerals and rocks, I. Silicate minerals. Mod Geol 1:283–300

    Google Scholar 

  • Integrated Spectronics (1999) Pima View v3.1, User Manual. In: Ltd. ISP (ed) Document Ref No ISPL-PV-31- 01. Baulkan Hills p102.

  • King TVV, Clark RN, Ager C et al (1995) Remote mineral mapping using AVIRIS data at Summitville, Colorado and the adjacent San Juan Mountains. In: Green RO (ed) Summaries of the Fifth Annual JPL Airborne Earth Science Workshop, 23-26 January, JPL Publication, 95–1:113–116.

  • Kruse FA, Hauff PL, Dietz J et al (1989) Characterization and mapping of mine waste at Leadville, Colorado, using imaging spectroscopy: Final Report Contract #412.DEN.63786.FM (CH2M HILL), Center for the Study of Earth from Space, University of Colorado, Boulder p79.

  • Mendenhall JA, Lencioni DE, Evans JB (2000) Earth observing-1 advanced land imager: radiometric response calibration, MIT/LL project report EO-1-3. Massachusetts Institute of Technology, Cambridge

    Google Scholar 

  • Mundt JT, Streutker DR, Glenn NF (2007) Partial unmixing of hyperspectral imagery: theory and methods, ASPRS 2007 Annual conference. American Society of Photogrammetry and Remote Sensing, Tampa, pp 7–11

    Google Scholar 

  • Research Systems Inc (2003) ENVI Tutorial, ENVI Software Package Version 4.0.

  • Riedmfiller G (1978) Neoformation and transformation of clay minerals in tectonic shear zones: Tschermaks Min. Petr Mitt 25:219–242

    Article  Google Scholar 

  • Rockwell B W (2004) Spectral variations in rocks and soils containing ferric iron hydroxide and(or) sulfate minerals as seen by AVIRIS and laboratory spectroscopy: U.S. Geological Survey Open-File Report 2004-1431 p 24.

  • Rowan LC, Schmidt RG, Mars JC (2006) Distribution of hydrothermally altered rocks in the Reko Diq, Pakistan mineralized area based on spectral analysis of ASTER data. Remote Sens Environ 104:74–87. doi:10.1016/j.rse.2006.05.014

    Article  Google Scholar 

  • Rowan LC, Vincent R (1971) Discrimination of iron-rich zones using visible and near-infrared spectral analysis (abst). Abstracts with Programs—Geological Society of America, Washington 3(7):691

    Google Scholar 

  • Sabine C (1999) Strategies for mineral exploration. In: Rencz A (ed) Manual of remote sensing, vol. 3. Wiley and Sons Inc, New York, pp 375–448

    Google Scholar 

  • Swayze GA, Smith KS et al (2000) Using imaging spectroscopy to map acidic mine waste. Environ Sci Technol 34:47–54

    Article  Google Scholar 

  • Vaughan RG, Calvin WM (2005) Mapping weathering and alteration minerals in the Comstock and Geiger Grade areas using visible to thermal infrared airborne remote sensing data. In: Rhoden HN, Steininger RC, Vikre PG, (eds) Geological Society of Nevada Symposium: Window to the World, May 2005, Reno, Nevada, 1035–1054.

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Acknowledgments

The ALI data were provided by the US Geological Survey (USGS). The authors thankfully acknowledge the constructive suggestions received from the AJGS’s editor, Abdullah M. Al-Amri, and two anonymous reviewers.

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Authors and Affiliations

  1. Department of Earth Sciences, Faculty of Sciences, Shiraz University, Shiraz, Iran

    Mohammad H. Tayebi & Majid H. Tangestani

  2. Department of Geology, Bowling Green State University, Bowling Green, USA

    Robert K. Vincent

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  1. Mohammad H. Tayebi
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  2. Majid H. Tangestani
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  3. Robert K. Vincent
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Correspondence to Mohammad H. Tayebi.

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Tayebi, M.H., Tangestani, M.H. & Vincent, R.K. Sub-pixel mapping of iron-bearing minerals using ALI data and MTMF algorithm, Masahim volcano, SE Iran. Arab J Geosci 8, 3799–3810 (2015). https://doi.org/10.1007/s12517-014-1400-4

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  • DOI: https://doi.org/10.1007/s12517-014-1400-4

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