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Research Articles

Detection of alteration zones using the Dirichlet process Stick-Breaking model-based clustering algorithm to hyperion data: the case study of Kuh-Panj porphyry copper deposits, Southern Iran

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Pages 9788-9816 | Received 10 Jun 2021, Accepted 02 Jan 2022, Published online: 11 Jan 2022

References

  • Abubakar AJa, Hashim M, Pour AB. 2019. Remote sensing satellite imagery for prospecting geothermal systems in an aseismic geologic setting: Yankari Park. Nigeria. IJAEO. 80:157–172.
  • Alshabandar R, Hussain A, Keight R, Laws A, Baker T. 2018. The application of Gaussian mixture models for the identification of at-risk learners in massive open online courses. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), IEEE.
  • Askari G, Pour AB, Pradhan B, Sarfi M, Nazemnejad F. 2018. Band ratios matrix transformation (BRMT): a sedimentary lithology mapping approach using ASTER satellite sensor. Sensors. 18(10):3213.
  • Barbakh WA, Wu Y, Fyfe C. 2009. Review of clustering algorithms. In: Barbakh WA, Wu Y, Fyfe C, editors. Non-standard parameter adaptation for exploratory data analysis. Studies in computational intelligence. Vol. 249, Heidelberg: Springer; p. 7–28.
  • Baya AE, Granitto PM. 2013. How many clusters: a validation index for arbitrary-shaped clusters. IEEE/ACM Trans Comput Biol Bioinform. 10(2):401–414.
  • Beck R. 2003. EO-1 user guide v. 2.3. Ohio: Department of Geography University of Cincinnati.
  • Bedini E. 2011. Mineral mapping in the Kap Simpson complex, central East Greenland, using HyMap and ASTER remote sensing data. AdSpR. 47(1):60–73.
  • 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. IJRS. 33(4):939–961.
  • Bedini E. 2017. The use of hyperspectral remote sensing for mineral exploration: a review. J Hyperspect Remote Sensing. 7:189–211.
  • Bedini E, Van Der Meer F, Van Ruitenbeek F. 2009. Use of HyMap imaging spectrometer data to map mineralogy in the Rodalquilar caldera, southeast Spain. IJRS. 30(2):327–348.
  • Berkhin P. 2006. A survey of clustering data mining techniques. Grouping multidimensional data. Berlin, Heidelberg: Springer; p. 25–71.
  • Blei DM, Jordan MI. 2006. Variational inference for Dirichlet process mixtures. Bayesian Anal. 1(1):121–143.
  • Bolouki SM, Ramazi HR, Maghsoudi A, Beiranvand Pour A, Sohrabi G. 2019. A remote sensing-based application of Bayesian networks for epithermal gold potential mapping in Ahar-Arasbaran area, NW Iran. Rem Sensing. 12(1):105.
  • Bouveyron C, Girard S, Schmid C. 2007. High-dimensional data clustering. Comput Stat Data Anal. 52(1):502–519.
  • Chattoraj SL, Prasad G, Sharma RU, Champati Ray PK, van der Meer FD, Guha A, Pour AB. 2020. Integration of remote sensing, gravity and geochemical data for exploration of Cu-mineralization in Alwar basin, Rajasthan, India. IJAEO. 91:102162.
  • Chen G, Qian S-E. 2011. Denoising of hyperspectral imagery using principal component analysis and wavelet shrinkage. IEEE Trans Geosci Remote Sensing. 49(3):973–980.
  • Chen W-Y, Song Y, Bai H, Lin C-J, Chang E, 2011. Parallel spectral clustering in distributed systems. IEEE Trans Pattern Anal Mach Intell. 33(3):568–586.
  • Choi J, Kim G, Park N, Park H, Choi S. 2017. A hybrid pansharpening algorithm of VHR satellite images that employs injection gains based on NDVI to reduce computational costs. Rem Sensing. 9(10):976.
  • Cilibrasi R, Vitányi PM. 2005. Clustering by compression. IEEE Trans Inform Theory. 51(4):1523–1545.
  • Cohen-Addad V, Kanade V, Mallmann-Trenn F, Mathieu C. 2019. Hierarchical clustering. J Acm. 66(4):1–42.
  • Cugmas M, Ferligoj A, Kronegger L. 2016. The stability of co-authorship structures. SCIM. 106(1):163–186.
  • Datt B, Jupp D. 2004. Hyperion data processing workshop: hands-on processing instructions. Australia: CSIRO Earth Observation Centre.
  • Dellaportas P, Smith AF. 1993. Bayesian inference for generalized linear and proportional hazards models via Gibbs sampling. Appl Stat. 42(3):443–459.
  • Ding S, Jia H, Du M, Xue YJIS. 2018. A semi-supervised approximate spectral clustering algorithm based on HMRF model. Information Sci. 429:215–228.
  • dos Reis Salles R, de Souza Filho CR, Cudahy T, Vicente LE, Monteiro LVS. 2017. Hyperspectral remote sensing applied to uranium exploration: a case study at the Mary Kathleen metamorphic-hydrothermal U-REE deposit, NW, Queensland, Australia. J Geochem Explor. 179:36–50.
  • Du Q, Fowler JE. 2007. Hyperspectral image compression using JPEG2000 and principal component analysis. IEEE Geosci Remote Sensing Lett. 4(2):201–205.
  • Eberle DG, Paasche H. 2012. Integrated data analysis for mineral exploration: a case study of clustering satellite imagery, airborne gamma-ray, and regional geochemical data suites. GEOP. 77(4):B167–B176.
  • Ferguson TS. 1973. A Bayesian analysis of some nonparametric problems. Ann Statist. 1(2)
  • Fernandez-Manso A, Quintano C, Roberts D, Sensing R. 2019. Burn severity analysis in Mediterranean forests using maximum entropy model trained with EO-1 hyperion and LiDAR data. ISPRS J Photogrammetry Remote. 155:102–118.
  • 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.
  • Gelfand AE, Smith A. 1990. Sampling-based approaches to calculating marginal densities. J Am Stat Assoc. 85(410):398–409.
  • George R, Padalia H, Kushwaha S. 2014. Forest tree species discrimination in western Himalaya using EO-1 hyperion. IJAEO. 28:140–149.
  • Gersman R, Ben‐Dor E, Beyth M, Avigad D, Abraha M, Kibreab A. 2008. Mapping of hydrothermally altered rocks by the EO‐1 hyperion sensor, Northern Danakil Depression, Eritrea. IJRS. 29(13):3911–3936.
  • Gill PS, Swartz TB. 2007. Bayesian analysis of dyadic data. Am J Math Manage Sci. 27(1–2):73–92.
  • Gonbadi AM, Tabatabaei SH, Carranza EJM. 2015. Supervised geochemical anomaly detection by pattern recognition. J Geochem Explor. 157:81–91.
  • Green RO, Eastwood ML, Sarture CM, Chrien TG, Aronsson M, Chippendale BJ, Faust JA, Pavri BE, Chovit CJ, Solis M, et al. 1998. Imaging spectroscopy and the airborne visible/infrared imaging spectrometer (AVIRIS). RSEnv. 65(3):227–248.
  • Guha A, Kumar Ghosh U, Sinha J, Pour AB, Bhaisal R, Chatterjee S, Kumar Baranval N, Rani N, Kumar KV, Rao PV. 2021. Potentials of airborne hyperspectral AVIRIS-NG data in the exploration of base metal deposit—a study in the parts of Bhilwara, Rajasthan. Remote Sensing. 13(11):2101.
  • Guha A, Yamaguchi Y, Chatterjee S, Rani K, Vinod Kumar K. 2019. Emittance spectroscopy and broadband thermal remote sensing applied to phosphorite and its utility in geoexploration: a study in the parts of Rajasthan, India. Remote Sensing. 11(9):1003.
  • Halkidi M, Batistakis Y, Vazirgiannis M. 2001. On clustering validation techniques. J Intell Informat Systems. 17(2/3):107–145.
  • Hantson S, Chuvieco E. 2011. Evaluation of different topographic correction methods for Landsat imagery. IJAEO. 13(5):691–700.
  • Hubert L, Arabie P. 1985. Comparing partitions. J Classificat 2(1):193–218.
  • Ishidoshiro N, Yamaguchi Y, Noda S, Asano Y, Kondo T, Kawakami Y, Mitsuishi M, Nakamura H. 2016. Geological mapping by combining spectral unmixing and cluster analysis for hyperspectral data. Int Arch Photogramm Remote Sens Spatial Inf Sci. XLI-B8, 431435,
  • Jain A, Murty M, Flynn PJ. 2011. Data clustering: a review. ACM Comput Surv. 31, 264–323.
  • Kaufman L, Rousseeuw P. 2005. Wiley series in probability and statistics. Hoboken (NJ): John Wiley & Sons, Inc.
  • Kaufman L, Rousseeuw PJ. 2009. Finding groups in data: an introduction to cluster analysis. Vol. 344. New York (NY): John Wiley & Sons.
  • Khosravi A. 2007. Statistical geological and alteration map of Kuh Panj copper deposit. Sar Cheshmeh, Kerman, Iran: Exploration Department.
  • Krapu C, Borsuk M. 2019. Probabilistic programming: a review for environmental modellers. Environ Model Softw. 114:40–48.
  • Kruse FA, Boardman JW, Huntington JF. 2003. Comparison of airborne hyperspectral data and EO-1 Hyperion for mineral mapping. IEEE Trans Geosci Remote Sensing. 41(6):1388–1400.
  • Kumar C, Chatterjee S, Oommen T, Guha A. 2020. Automated lithological mapping by integrating spectral enhancement techniques and machine learning algorithms using AVIRIS-NG hyperspectral data in Gold-bearing granite-greenstone rocks in Hutti, India. IJAEO. 86:102006.
  • Kusuma K, Chaitanya S, Guru B. 2019. Frequency ratio modelling using geospatial data to predict Kimberlite Clan of rock emplacement zones in Dharwar Craton, India. IJAEO. 74:191–208.
  • Le Cam L. 1986. The central limit theorem around 1935. Stat Sci. 1(1):78–91.
  • Li N, Huang X, Zhao H, Qiu X, Geng R, Jia X, Wang D. 2018. Multiparameter optimization for mineral mapping using hyperspectral imagery. IEEE J Sel Top Appl Earth Observat Remote Sensing. 11(4):1348–1357.
  • Li S, Sari YA, Kumral M. 2020. Optimization of mining–mineral processing integration using unsupervised machine learning algorithms. Nat Res Res. 29(5):3035–3012.
  • Liu Y, Li Z, Xiong H, Gao X, Wu J, Wu S. 2013. Understanding and enhancement of internal clustering validation measures. IEEE Trans Cybern. 43(3):982–994.
  • Lugrin T. 2013. Bayesian semiparametrics for modelling the clustering of extreme values. Switzerland: EPFL.
  • Lunn D, Jackson C, Best N, Spiegelhalter D, Thomas A. 2012. The BUGS book: A practical introduction to Bayesian analysis. Boca Raton (FL): Chapman and Hall/CRC.
  • Mathieu L. 2018. Quantifying hydrothermal alteration: a review of methods. Geosciences. 8(7):245.
  • Neal RM. 2000. Markov chain sampling methods for Dirichlet process mixture models. J Computat Graph Stat. 9(2):249–265.
  • Nerurkar P, Pavate A, Shah M, Jacob S. 2019. Performance of internal cluster validations measures for evolutionary clustering. In Computing, communication and signal processing. Springer; p. 305–312.
  • Noori L, Pour AB, Askari G, Taghipour N, Pradhan B, Lee C-W, Honarmand M. 2019. Comparison of different algorithms to map hydrothermal alteration zones using ASTER remote sensing data for polymetallic vein-type ore exploration: Toroud–Chahshirin Magmatic Belt (TCMB), North Iran. Remote Sensing. 11(5):495.
  • Pande-Chhetri R, Abd-Elrahman A. 2011. De-striping hyperspectral imagery using wavelet transform and adaptive frequency domain filtering. ISPRS J Photogramm Remote Sens. 66(5):620–636.
  • Pirajno F. 1992. Porphyry systems and skarns. In Hydrothermal mineral deposits. Springer; p. 325–374.
  • Pour AB, Hashim M. 2012a. The application of ASTER remote sensing data to porphyry copper and epithermal gold deposits. Ore Geol Rev. 44:1–9.
  • Pour AB, Hashim M. 2012b. Identifying areas of high economic-potential copper mineralization using ASTER data in the Urumieh–Dokhtar Volcanic Belt, Iran. AdSpR. 49(4):753–769.
  • Pour AB, Hashim M. 2014. ASTER, ALI and Hyperion sensors data for lithological mapping and ore minerals exploration. SpringerPlus. 3(1):1–19.
  • Pour AB, Hashim M. 2015. Integrating PALSAR and ASTER data for mineral deposits exploration in tropical environments: a case study from Central Belt, Peninsular Malaysia. Int J Image Data Fusion. 6(2):170–188.
  • Pour AB, Hashim M, Hong JK, Park Y. 2019. Lithological and alteration mineral mapping in poorly exposed lithologies using Landsat-8 and ASTER satellite data: North-eastern Graham Land, Antarctic Peninsula. Ore Geol Rev. 108:112–133.
  • Pour AB, Hashim M, van Genderen J. 2013. Detection of hydrothermal alteration zones in a tropical region using satellite remote sensing data: Bau goldfield, Sarawak, Malaysia. Ore Geol Rev. 54:181–196.
  • Pour AB, Sekandari M, Rahmani O, Crispini L, Läufer A, Park Y, Hong JK, Pradhan B, Hashim M, Hossain MS, et al. 2020. Identification of phyllosilicates in the antarctic environment using aster satellite data: Case study from the mesa range, campbell and priestley glaciers, northern Victoria land. Remote Sensing. 13(1):38.
  • Rajan Girija R, Mayappan S, Fusion D. 2019. Mapping of mineral resources and lithological units: a review of remote sensing techniques. Int J Image Data Fusion. 10(2):79–106.
  • Renza D, Martinez E, Molina I, Ballesteros L DM. 2017. Unsupervised change detection in a particular vegetation land cover type using spectral angle mapper. AdSpR. 59(8):2019–2031.
  • Romano S, Bailey J, Nguyen V, Verspoor K. 2014. Standardized mutual information for clustering comparisons: one step further in adjustment for chance. PMLR 32(2), 1143–1151.
  • Roshani P, Mokhtari AR, Tabatabaei SH. 2013. Objective based geochemical anomaly detection—application of discriminant function analysis in anomaly delineation in the Kuh Panj porphyry Cu mineralization (Iran). J Geochem Explor. 130:65–73.
  • Safari M, Maghsoudi A, Pour AB. 2018. Application of Landsat-8 and ASTER satellite remote sensing data for porphyry copper exploration: a case study from Shahr-e-Babak, Kerman, south of Iran. GeoIn. 33(11):1186–1201.
  • Sekandari M, Masoumi I, Beiranvand Pour A, M Muslim A, Rahmani O, Hashim M, Zoheir B, Pradhan B, Misra A, Aminpour SM. 2020. Application of Landsat-8, Sentinel-2, ASTER and WorldView-3 spectral imagery for exploration of carbonate-hosted Pb-Zn deposits in the Central Iranian Terrane (CIT). Remote Sensing. 12(8):1239.
  • Sekandari M, Masoumi I, Pour AB, Muslim AM, Hossain MS, Misra A. 2020. ASTER and WorldView-3 satellite data for mapping lithology and alteration minerals associated with Pb-Zn mineralization. Geocarto Int. 1–31.
  • Shirmard H, Farahbakhsh E, Beiranvand Pour A, Muslim AM, Müller RD, Chandra R. 2020. Integration of selective dimensionality reduction techniques for mineral exploration using ASTER satellite data. Remote Sensing. 12(8):1261.
  • Sillitoe RH. 2010. Porphyry copper systems. Econ Geol. 105(1):3–41.
  • Spiegelhalter D, Thomas A, Best N, Gilks W. 1996. Bayesian inference using Gibbs sampling manual (version ii) BUGS 0.5. Cambridge: MRC Biostatistics Unit, Institute of Public Health; p. 59.
  • Teh Y, Jordan M, Beal M, Blei D. 2005. Sharing clusters among related groups: Hierarchical Dirichlet processes.
  • Vinh NX, 2010. Information theoretic methods for clustering with applications to microarray data.
  • Wambo JDT, Pour AB, Ganno S, Asimow PD, Zoheir B, dos Reis Salles R, Nzenti JP, Pradhan B, Muslim AM. 2020. Identifying high potential zones of gold mineralization in a sub-tropical region using Landsat-8 and ASTER remote sensing data: a case study of the Ngoura-Colomines goldfield, eastern Cameroon. Ore Geol Rev. 122:103530.
  • Zhang T, Yi G, Li H, Wang Z, Tang J, Zhong K, Li Y, Wang Q, Bie X. 2016. Integrating data of ASTER and Landsat-8 OLI (AO) for hydrothermal alteration mineral mapping in duolong porphyry cu-au deposit, Tibetan Plateau, China. Remote Sensing. 8(11):890.
  • Zhang Y, Zhang T. 2016. Structure-guided unidirectional variation de-striping in the infrared bands of MODIS and hyperspectral images. Infrared Phys Technol. 77:132–143.
  • Zoheir B, Emam A, Abdel-Wahed M, Soliman N. 2019a. Multispectral and radar data for the setting of gold mineralization in the South Eastern Desert, Egypt. Remote Sensing. 11(12):1450.
  • Zoheir B, El-Wahed MA, Pour AB, Abdelnasser A. 2019b. Orogenic gold in transpression and transtension zones: Field and remote sensing studies of the Barramiya-Mueilha sector. Egypt. Remote Sensing. 11(18):2122.

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