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Full unmixing hydrothermal alteration minerals mapping by integration of pattern recognition network and directed matched filtering algorithm

Abstract

Partial unmixing categorizes each pixel based on a particular mineral while a pixel may contain several minerals. Hence, it seems that the full unmixing procedure is essential to make real results. In this study, at first, the hydrothermal alteration minerals have been mapped by directed matched filtering (DMF) algorithm as a partial unmixing method on the most important porphyry copper deposit in the Kerman province in Iran, then the full unmixing procedure was performed based on a pattern recognition network. In fact, the pattern recognition network uses results of the DMF algorithm to measure the amount of each alteration mineral in each pixel. According to the achieved results, the pure pixels of alteration minerals show high mixing with each other so that the average purity of kaolinite, muscovite, chlorite and alunite pixels are 80%, 70%, 95%, and 92%, respectively. Moreover, the spectral results of 30 samples and 212 chemical analysis of field samples by other research in this area validated those obtained by the full unmixing procedure.

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References

  1. Abrams M (2000) The advanced spaceborne thermal emission and reflection radiometer (ASTER): data products for the high spatial resolution imager on NASA’s Terra platform. Int J Remote Sens 21:847–859

  2. Abrams M, Hook S, Ramachandran B (2004) ASTER user handbook, version 2. Jet Propulsion Laboratory, California Institute of Technology. Online https://asterweb.jpl.nasa.gov/content/03_data/04_Documents/aster_user_guide_v2.pdf

  3. Adams JB, Smith MO, Johnson PE (1986) Spectral mixture modeling: a new analysis of rock and soil types at the Viking Lander 1 site. J Geophys Res 91:8098–8112

  4. Ayoobi I, Tangestani M (2018) Evaluation of subpixel unmixing algorithms in mapping the porphyry copper alterations using EO-1 Hyperion data, a case study from SE Iran. Int J Appl Earth Obs Geoinf 10:120–127

  5. Barzegar H (2007) Geology, petrology and geochemical characteristics of alteration zones within the Seridune prospect, Kerman, Iran. Geo resources and material technology of the Rheinisch Westfäli Technical University Aachen, Aachen, Germany, 180 p

  6. Benediktsson JA, Palmason JA, Sveinsson JR (2005) Classification of hyperspectral data from urban areas based on extended morphological profiles. IEEE Trans Geosci Remote Sens 43(3):480–491. https://doi.org/10.1109/TGRS.2004.842478

  7. Bishop CA, Liu JG, Mason PJ (2011) Hyperspectral remote sensing for mineral exploration in Pulang, Yunnan province, China. Int J Remote Sens 32(9):2409–2426

  8. Boardman JW (1993) Automated spectral unmixing of AVIRIS data using convex geometry concepts. In: Summaries of the 4th Annual JPL Airborne Geoscience Workshop, JPL Publication 93–26, vol 1. Jet Propulsion Laboratory, Pasadena, CA, 11–14

  9. Boardman JW, Kruse FA (2011) Analysis of imaging spectrometer data using N-dimensional geometry and a mixture-tuned matched filtering approach. Geosci Remote Sens IEEE Trans 49:4138–4152

  10. Boardman JW, Kruse FA, Green RO (1995) Mapping target signatures via partial unmixing of AVIRIS data. In: Summaries, Fifth JPL Airborne Earth Science Workshop. JPL Publication 95–1, 23–26

  11. Chang CI, Liu JM, Chieu BC, Ren H, Wang CM, Lo CS, Chung PC, Yang CW, Ma DJ (2000) Generalized constrained energy minimization approach to subpixel target detection for multispectral imagery. Opt Eng 39:1275–1281

  12. Chen F, Wang K, Van de Voorde T, Tang TF (2017) Mapping urban land cover from high spatial resolution hyperspectral data: an approach based on simultaneously unmixing similar pixels with jointly sparse spectral mixture analysis. Remote Sens Environ 196:324–442

  13. Fereydooni H, Mojeddifar S (2017) A directed matched filtering algorithm (DMF) for discriminating hydrothermal alteration zones using the ASTER remote sensing data. Int J Appl Earth Obs Geoinf 61:1–13

  14. Gabr S, Ghulam A, Kusky T (2010) Detecting areas of high-potential gold mineralization using ASTER data. Ore Geol Rev 38(1–2):59–69

  15. Green AA, Berman M, Switzer P, Craig MD (1988) A transformation for ordering multispectral data in terms of image quality with implications for noise removal. IEEE Trans Geosci Remote Sens 26(1):65–74

  16. Hassanzadeh J (1993) Metallogenic and tectonomagmatic events in the SE sector of the Cenozoic active continental margin of central Iran (Shahr e Babak area, Kerman Province). Ph.D. dissertation, University of California, Los Angeles, 204 p

  17. Honarmand M, Ranjbar H, Shahabpour J (2011) Application of spectral analysis in mapping hydrothermal alteration of the northwestern part of the Kerman Cenozoic magmatic arc, Iran. J Sci 22:221–238

  18. Kraut S, Scharf LL, Butler RW (2005) The adaptive coherence estimator: a uniformly most-powerful-invariant adaptive detection statistic. IEEE Trans Signal Process 53:427–438

  19. Kruse FA (1997) Regional geological mapping along the Colorado Front Range from Fort Collins to Denver using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). In: Proceedings of the 12th international conference on applied geologic remote sensing, vol. II, Denver, Colorado, 17–19 November. ERIM, Ann Arbor, MI, 91–98

  20. Levenberg K (1994) A method for the solution of certain non-linear problems in least squares. Q Appl Math 2:164–168

  21. Lourakis MIA (2005) A brief description of the Levenberg-Marquardt algorithm implemented by levmar, Technical report, Institute of Computer Science, Foundation for Research and Technology – Hella

  22. Lowell JD, Guilbert JM (1970) Lateral and vertical alteration-mineralization zoning in porphyry ore deposits. Econ Geol 65(4):373–408

  23. Madani AA, Emam AA (2011) SWIR ASTER band ratios for lithological mapping and mineral exploration: a case study from El Hudi area, southeastern desert, Egypt. Arab J Geosci 4(11):45–52. https://doi.org/10.1007/s12517-009-0059-8

  24. Mojedifar S, Ranjbar H, Nezamabadi H (2013) Adaptive neuro-fuzzy inference system application for hydrothermal alteration mapping using ASTER data. J Min Environ 4(2):83–96

  25. Molan YE, Refahi D, Tarashti AH (2014) Mineral mapping in the Maherabad area, eastern Iran, using the HyMap remote sensing data. Int J Appl Earth Obs Geoinf 27:117–127

  26. Parsapoor A, Khalili M, Tepley F, Maghami M (2015) Mineral chemistry and isotopic composition of magmatic, re-equilibrated and hydrothermal biotites from Darreh-Zar porphyry copper deposit, Kerman (Southeast of Iran). Ore Geol Rev 66:200–218

  27. Pour BA, Hashim M (2012) The application of ASTER remote sensing data to porphyry copper and epithermal gold deposits. Ore Geol Rev 44:1–9

  28. Pour AB, Park TS, Park Y, Hong JK, Zoheir B, Pradhan B, Ayoobi I, Hashim M (2018a) Application of multi-sensor satellite data for exploration of Zn-Pb sulfide mineralization in the Franklinian Basin, North Greenland. Remote Sens 10(8):1186

  29. Pour AB, Hashim M, Park Y, Hong JK (2018b) Mapping alteration mineral zones and lithological units in Antarctic regions using spectral bands of ASTER. Remote sensing data. Geocarto Int 33(12):1281–1306

  30. Qiu F, Abdelsalam M, Thakka P (2006) Spectral analysis of ASTER data covering part of the Neoproterozoic Allaqi-Heiani suture, Southern Egypt. J Afr Earth Sci 44(2):169–180

  31. Rajendran S, Nasir S (2017) Characterization of ASTER spectral bands for mapping of alteration zones of volcanogenic massive sulphide deposits. Ore Geol Rev 88:317–335

  32. Rowan LC, Mars JC (2003) Lithologic mapping in the Mountain Pass, California area using advanced spaceborne thermal emission and reflection radiometer (ASTER) data. Remote Sens Environ 84(3):350–366

  33. Rowan LC, Mars JC, Simpson CJ (2005) Lithologic mapping of the mordor, NT, Australia ultramafic complex by using the advanced spaceborne thermal emission and reflection radiometer (ASTER). Remote Sens Environ 99:105–126

  34. Shi C, Wang L (2014) Incorporating spatial information in spectral unmixing: a review. Remote Sens Environ 149:70–87

  35. Smith MO, Ustin SL, Adams JB, Gillespie AR (1990) Vegetation in deserts: I. A regional measure of abundance for multispectral images. Remote Sens Environ 31:1–26

  36. Soheili M (1981) Geological map of Anar, 1:250 000 map. Geological Survey of Iran Publication, Tehran

  37. Stocklin J (1968) Structural history and tectonics of Iran: a review. AAPG Bull 52(7):1229–1258

  38. Talesh Hosseini S, Asghari O, Ghavami Riabi SR (2018) Spatial modelling of zonality elements based on compositional nature of geochemical data using geostatistical approach: a case study of Baghqloom area, Iran. J Min Environ 9(1):153–167

  39. Van der Meer FD, Jia X (2012) Collinearity and orthogonality of endmembers in linear spectral unmixing. Int J Appl Earth Obs Geoinf 18:491–507

  40. Wang Q, Shi W, Atkinson PM (2018) Enhancing spectral unmixing by considering the point spread function effect. Spat Stat 28:271–283

  41. Watts DR, Harris NBW (2005) Mapping granite and gneiss in domes along the North Himalayan antiform with ASTER SWIR band ratios. Geol Soc Am Bull 117:879–886

  42. Whiteside TG, Boggs GS, Maier SW (2011) Comparing object-based and pixel-based classifications for mapping savannas. Int J Appl Earth Obs Geoinf 13(6):884–893

  43. Yang J, He Y, Takash O (2014) An endmember optimization approach for linear spectral unmixing of fine-scale urban imagery. Int J Appl Earth Obs Geoinf 27:137–146

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Correspondence to Ali Moradzadeh.

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Communicated by: H. Babaie

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Fereydooni, H., Moradzadeh, A., Pahlavani, P. et al. Full unmixing hydrothermal alteration minerals mapping by integration of pattern recognition network and directed matched filtering algorithm. Earth Sci Inform (2020). https://doi.org/10.1007/s12145-019-00422-y

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Keywords

  • Directed matched filtering
  • Pattern recognition network
  • Alteration minerals
  • Full unmixing
  • Kerman Cenozoic magmatic arc