PRISMA hyperspectral imagery for mapping alteration zones associated with Kuhpanj porphyry copper deposit, Southern Iran

References

• Aali, A. A., Shirazy, A., Shirazi, A., Pour, A. B., Hezarkhani, A., Maghsoudi, A., Hashim, M., & Khakmardan, S. (2022). Fusion of remote sensing, magnetometric, and Geological Data to identify polymetallic mineral potential zones in Chakchak Region, Yazd, Iran. Remote Sensing, 14(23), 6018. https://doi.org/10.3390/rs14236018
   Web of Science ®Google Scholar
• Agard, P., Omrani, J., Jolivet, L., & Mouthereau, F. (2005). Convergence history across Zagros (Iran): Constraints from collisional and earlier deformation. International Journal of Earth Sciences, 94(3), 401–19. https://doi.org/10.1007/s00531-005-0481-4
   Web of Science ®Google Scholar
• Aghazadeh, M., Hou, Z., Badrzadeh, Z., & Zhou, L. (2015). Temporal–spatial distribution and tectonic setting of porphyry copper deposits in Iran: Constraints from zircon U–pb and molybdenite re–os geochronology. Ore Geology Reviews, 70, 385–406. https://doi.org/10.1016/j.oregeorev.2015.03.003
   Web of Science ®Google Scholar
• Alimohammadi, M., Alirezaei, S., & Kontak, D. J. (2015). Application of ASTER data for exploration of porphyry copper deposits: A case study of daraloo–sarmeshk area, southern part of the Kerman copper belt, Iran. Ore Geology Reviews, 70, 290–304. https://doi.org/10.1016/j.oregeorev.2015.04.010
   Web of Science ®Google Scholar
• Amer, R., Kusky, T., & Ghulam, A. (2010). Lithological mapping in the Central Eastern Desert of Egypt using ASTER data. Journal of African Earth Sciences, 56(2–3), 75–82. https://doi.org/10.1016/j.jafrearsci.2009.06.004
   Web of Science ®Google Scholar
• Atapour, H., & Aftabi, A. (2007). The geochemistry of gossans associated with sarcheshmeh porphyry copper deposit for exploration and the environment. Journal of geochemical exploration, 93, 47–65.
   Web of Science ®Google Scholar
• Atif, Y., Soulaimani, A., Ait Lamqadem, A., Pour, A. B., Pradhan, B., Nouamane, E. A., Abdelali, K., Muslim, A. M., & Hossain, M. S. (2022). Identifying hydrothermally altered rocks using ASTER satellite imageries in Eastern anti-atlas of Morocco: A case study from imiter silver mine. International Journal of Image and Data Fusion, 13(4), 337–361. https://doi.org/10.1080/19479832.2021.1958928
   Web of Science ®Google Scholar
• Ayoobi, I., & Tangestani, M. H. (2018). Evaluation of subpixel unmixing algorithms in mapping the porphyry copper alterations using EO-1 Hyperion data, a case study from SE Iran. Remote Sensing Applications: Society & Environment, 10, 120–127. https://doi.org/10.1016/j.rsase.2018.03.009
   Google Scholar
• Babae, M. (2009). Integration of Geochemical, geophysical and remote sensing data for uranium indices by using GIS [MSc Thesis]. Shahid Bahonar University of Kerman.
   Google Scholar
• Bedini, E., & and Chen, J. (2020). Application of PRISMA satellite hyperspectral imagery to mineral alteration mapping at cuprite. Journal of hyperspectral remote sensing v, 10, 87–94.
   Google Scholar
• Bedini, E., & Chen, J. (2022). Prospection for economic mineralization using PRISMA satellite hyperspectral remote sensing imagery: An example from central East Greenland. Journal of Hyperspectral Remote Sensing, V12(3), 124–130. https://doi.org/10.29150/2237-2202.2022.253484
   Google Scholar
• Beiranvand Pour, A. B., 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 Geology Reviews, 54, 181–196. https://doi.org/10.1016/j.oregeorev.2013.03.010
   Web of Science ®Google Scholar
• Beiranvand Pour, A. B., Sekandari, M., Rahmani, O., Crispini, L., Läufer, A., Park, Y., Hong, J. K., Pradhan, B., Hashim, M., Hossain, M. S., Muslim, A. M., & Mehranzamir, K. (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. https://doi.org/10.3390/rs13010038
   Web of Science ®Google Scholar
• Boardman, J. W. (1998). Leveraging the high dimensionality of AVIRIS data for improved sub-pixel target unmixing and rejection of false positives: Mixture tuned matched filtering, Summaries of the Seventh JPL Airborne Geoscience Workshop, USA (Vol. 97, pp. 55–56). JPL Publication.
   Google Scholar
• Carmona Juarez, L. (2022). Mapping mineralogy in the Rodalquilar caldera, Spain, using PRISMA satellite images [Msc Thesis, Faculty of Geosciences of Utrecht University]. The Netherlands.
   Google Scholar
• Chen, Q., Zhao, Z., Zhou, J., Zhu, R., Xia, J., Sun, T., Zhao, X., & Jiangqin, C. (2022). ASTER and GF-5 Satellite Data for Mapping Hydrothermal Alteration Minerals in the Longtoushan Pb-Zn Deposit, SW China. Remote Sensing, 14(5), 1253. 1253. https://doi.org/10.3390/rs14051253
   Web of Science ®Google Scholar
• Cooke, D. R., Baker, M., Hollings, P., Sweet, G., Chang, Z., Danyushevsky, L., Gilbert, S., Zhou, T., White, N. C., & Gemmell, J. B. (2014). New advances in detecting the distal geochemical footprints of porphyry systems—epidote mineral chemistry as a tool for vectoring and fertility assessments.
   Google Scholar
• Crosta, A. P., De Souza Filho, C. R., Azevedo, F., & Brodie, C. (2003). Targeting key alteration minerals in epithermal deposits in Patagonia, Argentina, using ASTER imagery and principal component analysis. International Journal of Remote Sensing, 24(21), 4233–4240. https://doi.org/10.1080/0143116031000152291
   Web of Science ®Google Scholar
• Eilu, P., & Groves, D. I. (2001). Primary alteration and geochemical dispersion haloes of Archaean orogenic gold deposits in the Yilgarn Craton: The pre-weathering scenario. Geochemistry: Exploration, Environment, Analysis, 1(3), 183–200. https://doi.org/10.1144/geochem.1.3.183
   Google Scholar
• Eismann, M. T., Stocker, A. D., & Nasrabadi, N. M.2009. Automated hyperspectral cueing for civilian search and rescue. Proceedings of the IEEE, USA (Vol. 97, pp. 1031–1055).
   Google Scholar
• Gabr, S., Ghulam, A., & Kusky, T. (2010). Detecting areas of high-potential gold mineralization using ASTER data. Ore Geology Reviews, 38(1–2), 59–69. https://doi.org/10.1016/j.oregeorev.2010.05.007
   Web of Science ®Google Scholar
• Green, A. A., Berman, M., Switzer, P., & Craig, M. D. (1988). A transformation for ordering multispectral data in terms of image quality with implications for noise removal. IEEE Transactions on Geoscience and Remote Sensing, 26(1), 65–74. https://doi.org/10.1109/36.3001
   Web of Science ®Google Scholar
• Hajaj, S., El Harti, A., Jellouli, A., Pour, A. B., Himyari, S. M., Hamzaoui, A., Bensalah, M. K., Benaouiss, N., & Hashim, M. (2023). HyMap imagery for copper and manganese prospecting in the east of Ameln Valley shear zone (kerdous inlier, western anti-atlas, Morocco). Journal of Spatial Science, 1–22. https://doi.org/10.1080/14498596.2023.2172085
   Web of Science ®Google Scholar
• Hosseinjanizadeh, M., & Tangestani, M. H. (2011). Mapping alteration minerals using sub-pixel unmixing of ASTER data in the Sarduiyeh area, SE Kerman, Iran. International Journal of Digital Earth, 4(6), 487–504. https://doi.org/10.1080/17538947.2010.550937
   Web of Science ®Google Scholar
• Hosseinjanizadeh, M., Tangestani, M. H., Roldan, F. V., & 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. https://doi.org/10.1016/j.asr.2013.11.029
   Web of Science ®Google Scholar
• Hosseinjanizadeh, M., Tangestani, M., Velasco Roldán, F., & Yusta, I.2014. Mineral exploration and alteration zone mapping using mixture tuned matched filtering approach on ASTER data at the central part of dehaj-sarduiyeh copper belt, SE Iran. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 7, 284–289. https://doi.org/10.1109/JSTARS.2013.2261800
   Google Scholar
• Inzana, J., Kusky, T., Higgs, G., & Tucker, R. (2003). Supervised classifications of landsat TM band ratio images and landsat TM band ratio image with radar for geological interpretations of central Madagascar. Journal of African Earth Sciences, 37(1), 59–72. https://doi.org/10.1016/S0899-5362(03)00071-X
   Web of Science ®Google Scholar
• Ishagh, M. M., Pour, A. B., Benali, H., Idriss, A. M., Reyoug, S. S., Muslim, A. M., & Hossain, M. S. (2021). Lithological and alteration mapping using landsat 8 and ASTER satellite data in the reguibat shield (West African Craton), north of Mauritania: Implications for uranium exploration. Arabian Journal of Geosciences, 14(23), 2576. https://doi.org/10.1007/s12517-021-08846-x
   Google Scholar
• 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. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 41, 431–435. https://doi.org/10.5194/isprsarchives-XLI-B8-431-2016
   Google Scholar
• Jong, S. M. D., Meer, F. D. V. D., & Clevers, J. G. (2004). Basics of remote sensing. In Remote sensing image analysis: including the spatial domain (pp. 1–15). Dordrecht: Springer Netherlands.
   Google Scholar
• Kamel, M., Youssef, M., Hassan, M., & Bagash, F. (2016). Utilization of ETM+ landsat data in geologic mapping of wadi ghadir-gabal zabara area, Central Eastern Desert, Egypt. The Egyptian Journal of Remote Sensing & Space Science, 19(2), 343–360. https://doi.org/10.1016/j.ejrs.2016.06.003
   Google Scholar
• Kokaly, R. F., Clark, R. N., Swayze, G. A., Livo, K. E., Hoefen, T. M., Pearson, N. C., Wise, R. A., Benzel, W. M., Lowers, H., & Driscoll, R. L. (2017). USGS spectral library version 7 data: Us geological survey data release. United States Geological Survey (USGS).
   Google Scholar
• Large, R. R., & McGoldrick, P. J. (1998). Lithogeochemical halos and geochemical vectors to stratiform sediment hosted zn–pb–ag deposits, 1. Lady Loretta Deposit, Queensland. Journal of Geochemical Exploration, 63(1), 37–56. https://doi.org/10.1016/S0375-6742(98)00013-2
   Web of Science ®Google Scholar
• Loizzo, R., Ananasso, C., Guarini, R., Lopinto, E., Candela, L., & Pisani, A. R. 2016, May. The Prisma hyperspectral mission. In Proceedings of the Living Planet Symposium, ague, Czech Republic (pp. 9–13).
   Google Scholar
• Loizzo, R., Guarini, R., Longo, F., Scopa, T., Formaro, R., Facchinetti, C., & Varacalli, G., 2018, July. PRISMA: The Italian hyperspectral mission. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain (pp. 175–178). IEEE.
   Google Scholar
• Lotfi, M., Arefi, H., & Bahroudi, A. (2020). Investigating alteration zone mapping using EO-1 hyperion imagery and Airborne Geophysics Data. Journal of Mining & Environment, 11(2), 405–417.
   Web of Science ®Google Scholar
• Loughlin, W. P. (1991). Principal component analysis for alteration mapping. Photogrammetric Engineering and Remote Sensing, 57(9), 1163–1169.
   Web of Science ®Google Scholar
• Lowell, J. D., & Gumbert, J. M. (1970). Lateral and vertical alteration-mineralization zoning in porphyry ore deposits: Econ. Geol, 65(4), 373–408. https://doi.org/10.2113/gsecongeo.65.4.373
   Google Scholar
• Maleki, M., Niroomand, S., Rajabpour, S., Beiranvand Pour, A., & Ebrahimpour, S. (2022). Targeting local orogenic gold mineralization zones using data-driven evidential belief functions: The godarsorkh area, Central Iran. All Earth, 34(1), 259–278. https://doi.org/10.1080/27669645.2022.2129132
   Google Scholar
• Mars, J. C., & Rowan, L. C. (2006). Regional mapping of phyllic and argillic altered rocks in the Zagros magmatic arc, Iran, using advanced spaceborne thermal emission and reflection radiometer (ASTER) data and logical operator algorithms. Geosphere, 2(3), 161–186. https://doi.org/10.1130/GES00044.1
   Web of Science ®Google Scholar
• Mathieu, L. (2018). Quantifying hydrothermal alteration: A review of methods. Geosciences, 8(7), 245. https://doi.org/10.3390/geosciences8070245
   Web of Science ®Google Scholar
• Melesse, A. M., Weng, Q., & Thenkabail S. P, & Senay, G. B. (2007). Remote sensing sensors and applications in environmental resources mapping and modelling. Sensors, 7(12), 3209–3241. https://doi.org/10.3390/s7123209
   PubMed Web of Science ®Google Scholar
• Mishra, G., Govil, H., Guha, A., Kumar, H., Kumar, S., & Mukherjee, S. (2022). Comparative evaluation of airborne AVIRIS-NG and spaceborne PRISMA hyperspectral data in identification and mapping of altered/weathered minerals in Jahazpur, Rajasthan. Advances in Space Research. https://doi.org/10.1016/j.asr.2022.09.047
   Google Scholar
• Mitchell, J. J., & Glenn, N. F. (2009). Subpixel abundance estimates in mixture-tuned matched filtering classifications of leafy spurge (Euphorbia esula L.). International Journal of Remote Sensing, 30(23), 6099–6119. https://doi.org/10.1080/01431160902810620
   Web of Science ®Google Scholar
• Mundt, J. T., Streutker, D. R., & Glenn, N. F.2007. Partial unmixing of hyperspectral imagery: Theory and methods. Proceedings of the American Society of Photogrammetry and Remote Sensing, 2007.
   Google Scholar
• Najafian, T. (2010). Discrimination and identification of hydrothermal alteration types related to porphyry copper deposits, Sarcheshmeh, Kerman Province. Shahid Bahonar University.
   Google Scholar
• Ninomiya, Y.2003. A stabilized vegetation index and several mineralogic indices defined for ASTER VNIR and SWIR data. IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings IEEE Cat, France. 1552–1554.
   Google Scholar
• Pellegrino, A., Fabbretto, A., Bresciani, M., Lima, T., Braga, F., Pahlevan, N., Brando, V., Kratzer, S., Gianinetto, M., & Giardino, C. (2023). Assessing the accuracy of PRISMA standard reflectance products in globally distributed aquatic sites. Remote Sensing, 15(8), 2163. https://doi.org/10.3390/rs15082163
   Web of Science ®Google Scholar
• Rajendran, S., & Nasir, S. (2019). ASTER capability in mapping of mineral resources of arid region: A review on mapping of mineral resources of the sultanate of Oman. Ore Geology Reviews, 108(March 2017), 33–53. https://doi.org/10.1016/j.oregeorev.2018.04.014
   Google Scholar
• Ranjbar, H., Masoumi, F., & Carranza, E. J. M. (2011). Evaluation of geophysics and spaceborne multispectral data for alteration mapping in the Sar Cheshmeh mining area, Iran. International Journal of Remote Sensing, 32(12), 3309–3327. https://doi.org/10.1080/01431161003745665
   Web of Science ®Google Scholar
• Roshani, P., Mokhtari, A. R., & Tabatabaei, S. H. (2013). Objective based geochemical anomaly detection—application of discriminant function analysis in anomaly delineation in the Kuh Panj porphyry cu mineralization (Iran). Journal of Geochemical Exploration, 130, 65–73. https://doi.org/10.1016/j.gexplo.2013.03.005
   Web of Science ®Google Scholar
• Rowan, L. C., Goetz, A. F. H., & Ashley, R. P. (1977). Discrimination of hydrothermally altered and unaltered rocks in visible and near infrared multispectral images. Geophysics, 42(3), 522–535. https://doi.org/10.1190/1.1440723
   Web of Science ®Google Scholar
• Rowan, L. C., & Mars, J. C. (2003). Lithologic mapping in the Mountain Pass, California area using advanced spaceborne thermal emission and reflection radiometer (ASTER) data. Remote Sensing of Environment, 84(3), 350–366. https://doi.org/10.1016/S0034-4257(02)00127-X
   Web of Science ®Google Scholar
• Sekandari, M., Masoumi, I., Pour, A. B., Muslim, A. M., Hossain, M. S., & Misra, A. (2022). ASTER and WorldView-3 satellite data for mapping lithology and alteration minerals associated with pb-zn mineralization. Geocarto International, 37(6), 1782–1812. https://doi.org/10.1080/10106049.2020.1790676
   Web of Science ®Google Scholar
• Shafiei, B.2008. Metallogenic Model of Kerman Porphyry Copper Belt and Its Exploratory Approaches. Ph. D. Thesis, Shaheed Bahonar University of Kerman.
   Google Scholar
• Shafiei, B., Haschke, M., & Shahabpour, J. (2009). Recycling of orogenic arc crust triggers porphyry cu mineralization in Kerman cenozoic arc rocks, southeastern Iran. Mineralium Deposita, 44(3), 265–283. https://doi.org/10.1007/s00126-008-0216-0
   Web of Science ®Google Scholar
• Shirazi, A., Hezarkhani, A., Beiranvand Pour, A., Shirazy, A., & Hashim, M. (2022). Neuro-fuzzy-AHP (NFAHP) technique for copper exploration using advanced spaceborne thermal emission and reflection radiometer (ASTER) and geological datasets in the sahlabad mining area, East Iran. Remote Sensing, 14(21), 5562. https://doi.org/10.3390/rs14215562
   Web of Science ®Google Scholar
• Siljestrom, P. A., Moreno, A., Vikgren, K., & Caceres, L. M. (1997). Technical note the application of selective principal components analysis (SPCA) to a thematic mapper (TM) image for the recognition of geomorphologic features configuration. International Journal of Remote Sensing, 18(18), 3843–3852. https://doi.org/10.1080/014311697216658
   Web of Science ®Google Scholar
• Sillitoe, R. H. (1995). Exploration of porphyry copper lithocaps. Pacrim Congress 1995, Australia (pp. 527–532). Australasian Institute of Mining and Metallurgy.
   Google Scholar
• Singh, A., & Harrison, A. (1985). Standardized principal components. International Journal of Remote Sensing, 6(6), 883–896. https://doi.org/10.1080/01431168508948511
   Web of Science ®Google Scholar
• Tabatabaei, S. H., Rodsari, P. R., & Mokhtari, A. R. (2015). Predicting Potential Mineralization Using Surface Geochemical Data and Multiple Linear Regression Model in the Kuh Panj Porphyry Cu Mineralization (Iran). The Arabian Journal for Science and Engineering, 40, 163–170.
   Web of Science ®Google Scholar
• Tangestani, M. H., & Moore, F. (2001). Comparison of three principal component analysis techniques to porphyry copper alteration mapping: A case study, meiduk area, kerman, iran). Canadian Journal of Remote Sensing, 27(2), 176–182. https://doi.org/10.1080/07038992.2001.10854931
   Web of Science ®Google Scholar
• Van der Meer, F. D., van der Werff, H. M. A., van Ruitenbeek, F. J. A., Hecker, C. A., Bakker, W. H., Noomen, M. F., van der Meijde, M., Carranza, E. J. M., de Smeth, J. B., & Woldai, T. (2012). Multi- and hyperspectral geologic remote sensing: A review. International Journal of Applied Earth Observation and Geoinformation, 14(1), 112–128. https://doi.org/10.1016/j.jag.2011.08.002
   Web of Science ®Google Scholar
• Vangi, E., D’Amico, G., Francini, S., Giannetti, F., Lasserre, B., Marchetti, M., & Chirici, G. (2021). The new hyperspectral satellite PRISMA: Imagery for forest types discrimination. Sensors, 21(Issue 4). https://doi.org/10.3390/s21041182
   PubMed Web of Science ®Google Scholar
• Volesky, J. C., Stern, R. J., & Johnson, P. R. (2003). Geological control of massive sulfide mineralization in the Neoproterozoic Wadi Bidah shear zone, southwestern Saudi Arabia, inferences from orbital remote sensing and field studies. Precambrian Research, 123(2–4), 235–247. https://doi.org/10.1016/S0301-9268(03)00070-6
   Web of Science ®Google Scholar
• Waske, B., Benediktsson, J. A., Arnason, K., & Sveinsson, J. R. (2009). Mapping of hyperspectral AVIRIS data using machine-learning algorithms. Canadian Journal of Remote Sensing, 35(sup1), S106–S116. https://doi.org/10.5589/m09-018
   Web of Science ®Google Scholar
• Yousefi, M., Tabatabaei, S. H., Rikhtehgaran, R., Pour, A. B., & Pradhan, B. (2022). 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. Geocarto International, 37(25), 9788–9816. https://doi.org/10.1080/10106049.2022.2025917
   Web of Science ®Google Scholar