Abstract
Hyperspectral and high spatial resolution sensors allow for better discrimination of geological features and combining the products of these two kinds of sensors hypothetically improves this task. We evaluated the synergies of WorldView-3 (WV-3) and Hyperion datasets by fusing them to get a spatially enhanced hyperspectral dataset for mapping hydrothermal alteration minerals of Chadormalu iron oxide-apatite deposit area, in Central Iran. Due to the fact that faults and hydrothermal alteration minerals are inseparable phenomena for mineral exploration, lineaments of the study area were extracted manually and automatically using ALOS World 3D—30 m (AW3D30) and WV-3 data respectively. Subsequently, the alteration minerals were mapped by the use of Mixture Tuned Matched Filtering (MTMF) partial unmixing method on the WV-3, Hyperion, and their fused dataset. Results revealed that fusion of Hyperion and WV-3 data provides higher model accuracies than using solely one sensor dataset. Hyperion and Hyperion- WV-3 fused datasets reached 59.15% and 66. 41% overall accuracies as comparing to WV-3 MTMF mineral map for concentrations greater than 50%. This study introduced two prospecting areas of iron ore by matching the lineaments and alteration mineral maps. Furthermore, it was revealed that WV-3 data can discriminate the rock units and their approximate geometry in messy and stripy active open-pit which are concordant with the 1:1000 lithological map. Importantly, ground truthing and field validation, reflectance spectroscopy, TSG analysis, and X-ray diffraction (XRD) supported the results of this research. Findings of this research stated the potential use of WV-3 and Hyperion data as well as their fusion for lineament and mineralogical discriminations to further develop new hyperspectral image processing approach and making synthetic high spatio-spectral dataset.
Similar content being viewed by others
Data availability
The datasets analysed during the current study are available from the corresponding author on reasonable request. All data generated during this study are included in this published article.
Notes
EO1H1610372005185110KW_1T.
Algorithm notations: B = band, float = floating point, ge = greater than or equal to, gt = greater than, le = less.
than or equal to, lt = less than.
References
Adams JW (1965) The visible region absorption spectra of rare-earth minerals. Am Mineral 50:356–366
Aghanabati A (1998) Major sedimentary and structural units of Iran (map). J Geosci 7:29–30
Alinia F (2014) Geochemical and economic geology studies of rare earth elements in Chadormalu iron deposit. Chadormalu mining and industrial company, internal report, unpublished. 127
Ashrafi A, Mahmoudi S, Rahimi R, Lotfi M (2016) Geological Map of the Chadormalu Iron Ore Mine, Chadormalu mining and industrial company, internal report, unpublished
Ayoobi I, Tangestani MH (2018) Evaluation of subpixel unmixing algorithms in mapping the porphyry copper alterations using EO-1 Hyperion data, a case study from SE Iran. Remote Sens Appl Soc Environ 10:120–127
Barry P (2001) EO-1/Hyperion Science Data User’s Guide. TRW Space, Defense & Information Systems, Redondo Beach, CA
Batson RM, Edwards K, Eliason EM (1975) Computer – generated shaded relief Images. J Res US Geol Surv 3(4):401–408
Beck R (2003) EO-1 User Guide, Version 2.3. University of Cincinnati, Ohio
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
Bedini E (2019) Application of WorldView-3 imagery and ASTER TIR data to map alteration minerals associated with the Rodalquilar gold deposits, southeast Spain. Adv Space Res 63:3346–3357
Beltrão N, Teodoro A (2018) Evaluating the potential of Sentinel-2 MSI and Landsat-8 OLI data fusion for land cover mapping in Brazilian Amazon. Proc. SPIE 10783, Remote Sensing for Agriculture, Ecosystems, and Hydrology XX, 107830H (10 October 2018). https://doi.org/10.1117/12.2325576
Bernstein LS, Adler-Golden SM, Sundberg RL et al (2005) Validation of the Quick Atmospheric Correction (QUAC) algorithm for VNIR-SWIR multi- and hyperspectral imagery. SPIE Proceedings, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI 5806:668–678
Boardman JW, Kruse FA (2011) Analysis of imaging spectrometer data using N-Dimensional geometry and a mixture-tuned matched filtering approach. IEEE Trans Geosci Remote Sens 49:4138–4152
Boardman JW (1998) Leveraging the high dimensionality of AVIRIS data for improved sub-pixel target unmixing and rejection of false positives: mixture tuned matched filtering, in: Summaries of the Seventh Annual JPL Airborne Geoscience Workshop, Pasadena, CA, p. 55
Cardoso-Fernandes J, Teodoro AC, Lima A (2019) Remote sensing data in lithium (Li) exploration: A new approach for the detection of Li-bearing pegmatites. Int J Appl Earth Obs Geoinf 76:10–25
Cetin M, Musaoglu N (2009) Merging hyperspectral and panchromatic image data: qualitative and quantitative analysis. Int J Remote Sens 30(7):1779–1804
Chakravortty S, Subramaniam P (2014) Fusion of hyperspectral and multispectral image data for enhancement of spectral and spatial resolution. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-8, 2014 ISPRS Technical Commission VIII Symposium, 09 – 12 December 2014, Hyderabad, India, 1099-1103
Chavez PS, Guptill SC, Bowell JA (1984)Image processing techniques for Thematic Mapper data. Proceedings, ASPRS Technical Papers 2:728–742
Chen W, Li X, Wang L (2019) Fine Land Cover Classification in an Open-pit Mining Area Using Optimized Support Vector Machine and WorldView-3 Imagery. Remote Sens 12:82
Clark RN, Swayze GA, Wise RA, Live KE, Hoefen TM, Kokaly RF, Sutley SJ (2007) USGS Digital Spectral Library splib06a: U.S. Geological Survey Data Series 231
Coulter DW, Harris PD, Wickert LM, Zhou X (2017) Advances in Spectral Geology and Remote Sensing: 2008 – 2017. In “Proceedings of Exploration 17: Sixth Decennial International Conference on Mineral Exploration” edited by Tschirhart V and Thomas MD, pp. 23–50
Cudahy TJ (2016) Mineral mapping for exploration: An Australian journey of evolving spectral sensing technologies and industry collaboration. Geosciences 6:52
Dadon A, Ben-Dor E, Karnieli A (2010) Use of derivative calculations and minimum noise fraction transform for detecting and correcting the spectral curvature effect (smile) in Hyperion images. IEEE Trans Geosci Remote Sens 48(6):2603–2612
Datt B, McVicar TR, Van Niel TG, Jupp DLB, Pearlmann JS (2003) Processing EO-1 Hyperion Hyperspectral Data to Support the Application of Agricultural Indexes. IEEE Trans Geosci Remote Sens 41(6):1246–1259
Digital Globe Inc., 2014. WorldView-3 data sheet. https://www.spaceimagingme.com/downloads/sensors/datasheets/DG_WorldView3_DS_2014.pdf
Ducart DF, Crosta AP, Filho CRS, Coniglio J (2006) Alteration mineralogy at the Cerro La Mina epithermal prospect, Patagonia, Argentina: Field mapping, short-wave infrared spectroscopy, and ASTER images. Econ Geol 101:981–996
Duke EF (1994) Near infrared spectra of muscovite, Tschermak substitution, and metamorphic reaction progress: Implications for remote sensing. Geology 22(7):621–624
Evans D (1998) Data fusion applied to geologic mapping and natural hazards. In: T. Ranchin & L. Wald (Eds.): Proceedings of the second conference “Fusion of Earth data: merging point measurements, raster maps and remotely sensed images”, Sophia Antipolis, France, January 28–30, 1998, published by SEE/URISCA, Nice, France, 117–122
Felde GW, Anderson GP, Cooley TW, Matthew MW, Adler-Golden SM, Berk A, Lee J (2003) Analysis of Hyperion Data with the FLAASH Atmospheric Correction Algorithm. IEEE Trans Geosci Remote Sens 90–92
FLAASH Module (2005) ENVI Manual User’s Guide, Research Systems Inc
Förster H, Jafarzadeh A (1994) The Bafq mining district in Central Iran: a highly mineralized Infracambrian volcanic field. Econ Geol 89:1697–1721
Fossi DH, Djomo HD, Takodjou Wambo JD, Ganno S, Pour AB, Kankeu B, Nzenti JP (2021) Structural lineament mapping in a sub–tropical region using Landsat–8/SRTM data: a case study of Deng-Deng area in Eastern Cameroon. Arab J Geosci 14:2651
Frutuoso R, Lima A, Teodoro AC (2021) Application of remote sensing data in gold exploration: targeting hydrothermal alteration using Landsat 8 imagery in northern Portugal. Arab J Geosci 14:459
Geological survey of Iran (2000) Geological map of Ariz. Scale 1:100000
Geological survey of Iran (2006) Geological map of Chadormalu. Scale 1:100000
Ghamisi P, Rasti B, Yokoya N, Wang Q, Hofle B, Bruzzone L, Bovolo F, Chi M, Anders K, Gloaguen R, Atkinson PM, Benediktsson JA (2019) Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art. IEEE Geosci Remote Sens Mag 7(1):6–39
Ghazi Thannoun R (2013) Automatic Extraction and Geospatial Analysis of Lineaments and their Tectonic Significance in some areas of Northern Iraq using Remote Sensing Techniques and GIS. Int J Enhanc Res Sci Technol Eng 2(2):11
Ghoneim SM, Yehia MA, Salem SM, Ali HF (2022) Integrating remote sensing data, GIS analysis and field studies for mapping alteration zones at Wadi Saqia area, central Eastern Desert, Egypt. Egypt J Remote Sens Space Sci 25(1):323–336
Goodenough DG, Dyk A, Niemann KO, Pearlman JS, Chen H, Murdoch M, West C (2003) Processsng Hyperion and ALI for Forest Classification. IEEE Trans Geosci Remote Sens 41(6):1321–1331
Green AA, Berman M, Switzer P, Craig MD (1998) A transformation for ordering multispectral data in terms of image quality with implications for noise removal. IEEE Trans Geosci Remote Sens 26:65–74
Heidarian H, Alirezaei S, Lentz DR (2017) Chadormalu Kiruna-type magnetite-apatite deposit, Bafq district, Iran: Insights into hydrothermal alteration and petrogenesis from geochemical, fluid inclusion, and sulfur isotope data. Ore Geol Rev 83:43–62
Hung LQ, Batelaan O, De Smedt F (2005) Lineament extraction and analysis, comparison of Landsat ETM and Aster imagery. Case study: Suoimuoi tropical karst catchment, Vietnam. Proc of SPIE 5983, 59830T:1–12
Hunt GR (1977) Spectral signatures of particulate minerals in the visible and near infrared. Geophysics 42:501–513
Hunt GR, Ashley RP (1979) Spectra of altered rocks in the visible and near infrared. Econ Geol 74:1613–1629
Hunt GR, Salisbury JW (1970) Visible and near- infrared spectra of minerals and rock: I silicate minerals. Mod Geol 1:283–300
Javhar A, Chen X, Bao A, Jamshed A, Yunus M, Jovid A, Latipa T (2019) Comparison of Multi-Resolution Optical Landsat-8, Sentinel-2 and Radar Sentinel-1 Data for Automatic Lineament Extraction: A Case Study of Alichur Area, SE Pamir. Remote Sens 11(778):29
Karimzadeh Z, Tangestani MH (2018) Identification of hydrothermal alteration mineralogy from Chadormalu Iron deposit area, Yazd province, Iran, through reflectance spectroscopy and petrographic data. The first national conference of Iranian Geological Remote Sensing Society (IGRSS), 12–14th Dec. 2018, Kerman-Iran (in Persian with English abstract). http://www.civilica.com/Paper-IGRSS01-IGRSS01_004.html
Karimzadeh Z, Tangestani MH (2019) Application of WorldView-3 data in alteration mineral mapping in chadormalu area, Central Iran, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-4/W18, 2019 GeoSpatial Conference 2019 – Joint Conferences of SMPR and GI Research, 12–14 October 2019, Karaj, Iran, p. 589–596
Karimzadeh S, Endo S, Modabberi S, Tangestani MH (2023) Geochemistry of color-zoned apatite from the Chadormalu iron oxide-apatite deposit, Central Iran: Insights into REE mobility during hydrothermal alteration. Phys Chem Earth, Parts A/B/C, 103402
Karimzadeh S, Tangestani MH (2021) Evaluating the VNIR-SWIR datasets of WorldView-3 for lithological mapping of a metamorphic-igneous terrain using Support Vector Machine algorithm; a case study of Central Iran. Adv Space Res 68(6):2421–2440
Karimzadeh S, Tangestani MH (2022) Potential of Sentinel-2 MSI data in targeting rare earth element (Nd3+) bearing minerals in Esfordi phosphate deposit, Iran. Egypt J Remote Sens Space Sci 25:697–710
Kattenborn T, Maack J, Faßnacht F, Enßle F, Ermert J, Koch B (2015) Mapping forest biomass from space – Fusion of hyperspectral EO1-hyperion data and Tandem-X and WorldView-2 canopy height models. Int J Appl Earth Obs Geoinformation 35:359–367
Knödel K, Toloczyki M, Bohn A, Abel T, Lange G, Tejedo A (2007) Data Fusion. In: Environmental Geology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74671-3_19
Kruse FA, Perry SL (2013) Mineral mapping using simulated WorldView-3 short-wave infrared imagery. Remote Sens 5(6):2688–2703
Kruse FA, Baugh WM, Perry SL (2015) Validation of Digital Globe WorldView-3 Earth imaging satellite shortwave infrared bands for mineral mapping. J Appl Remote Sens 9:17
Kruse FA (2003) Mineral Mapping with AVIRIS and EO-1 Hyperion. 11th JPL Airborne Geoscience Workshop, 4–8 March 2003, Pasadena, California
Laben CA, Brower BV (2000) Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening. US Patent 6,011,875
Li C, Liu L, Wang J, Zhao C, Wang R (2004) Comparison of two methods of the fusion of remote sensing images with fidelity of spectral information. Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS 2004), 20–24 September, Anchorage, Alaska, pp. 2561–2564
Lu H, Qiao D, Li Y, Wu S, Deng L (2021) Fusion of China ZY-1 02D Hyperspectral Data and Multispectral Data: Which Methods Should Be Used? Remote Sens 13:2354
Maaji UM, Maina MB, Sarki MU (2019) Lineaments Analysis and Interpretation for Assessment of Groundwater Potential of Lafia and Environs, North Central Nigeria. IOSR J Appl Geol Geophys (IOSR-JAGG) 7.1:22–28
Mars JC (2018) Mineral and Lithologic Mapping Capability of WorldView 3 Data at Mountain Pass, California, Using True- and False-Color Composite Images, Band Ratios, and Logical Operator Algorithms. Econ Geol 113:1587–1601
Mayumi N, Iwasaki A (2011) Image sharpening using hyperspectral and multispectral data. IEEE Int Geosci Remote Sens Symp, pp. 519–522
Mbianya GN, Ngnotue T, Takodjou Wambo JD, Ganno S, Pour AB, Kenne PA, Fossi DH, Wolf ID (2021) Remote sensing satellite-based structural/ alteration mapping for gold exploration in the Ketté goldfield, Eastern Cameroon. J Afr Earth Sc 184:104386
Pande H, Tiwari PS (2013)High-Resolution and Hyperspectral Data Fusion for Classification. New Advances in Image Fusion, Chapter 4:57-77
Pirajno F (1992) Hydrothermal Alteration. In: Hydrothermal Mineral Deposits. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-75671-9_5
Pour AB, Hashim M (2013) Fusing ASTER, ALI and Hyperion data for enhanced mineral mapping. Int J Image Data Fusion 4:126–145
Ramezani J, Tucker RD (2003) The Saghand region, central Iran: U-Pb geochronology, petrogenesis and implications for Gondwana tectonics. Am J Sci 303:622–665
Routh D, Seegmiller L, Bettigole C, Kuhn C, Oliver CD, Glick HB (2018) Improving the Reliability of Mixture Tuned Matched Filtering Remote Sensing Classification Results Using Supervised Learning Algorithms and Cross-Validation. Remote Sens 10:1675, 19
Sabins FF (1999) Remote sensing for mineral exploration. Ore Geol Rev 14:157–183
Salehi T, Tangestani MH (2020) Evaluation of WorldView-3 VNIR and SWIR Data for Hydrothermal Alteration Mapping for Mineral Exploration: Case Study from Northeastern Isfahan, Iran. Nat Resour Res 29:3479–3503
San BT, Suzen ML (2011) Evaluation of cross-track illumination in EO-1 Hyperion imagery for lithological mapping. Int J Remote Sens 32(22):7873–7889
Sarp G (2005) Lineament Analysis from Satellite Images, North-West of Ankara, Msc thesis, Middle East Technical University, p 76
Schmitt M, Zhu XX (2016) Data Fusion and Remote Sensing – An Ever-Growing Relationship. IEEE Geosci Remote Sens Mag 2561021
Suchitha K, Premananda BS, Singh AK (2017) High spatial resolution hyperspectral image using fusion technique. International Conference on Trends in Electronics and Informatics (ICEI), pp. 348–353
Taghipour S, Kananian A, Harlov D, Oberhänsli R (2015) Kiruna-type iron oxideapatite deposits, Bafq district, Central Iran: fluid-aided genesis of fluorapatitemonazite- xenotime assemblages. Can Miner 53:479–496
The Spectral Geologist support (2018) CSIRO website, https://research.csiro.au/thespectralgeologist/
Torab MF (2008) Geochemistry and metallogeny of magnetiteapatite deposits of the Bafq Mining District, Central Iran, PhD thesis. Clausthal University of Technology, p 144
Vaiopoulos AD, Nikolakopoulos KG (2012) Comparison of the mineral mapping performance of three fusion techniques in Hyperion hyperspectral imagery. 4th EARSeL Workshop on Remote Sensing and Geology, Mykonos, Greece, 24st 25th May, 2012
van der Meer F, Hecker C, van Ruitenbeek F, van der Werff H, de Wijkerslooth C, Wechsler C (2014) Geologic remote sensing for geothermal exploration: A review. Int J Appl Earth Obs Geoinformation 33:255–269
Wald L (1999) Some terms of reference in data fusion. IEEE Trans Geosci Remote Sens 37(3):1190–1193
Yang M, Kang L, Chen H, Zhou M, Zhang J (2018) Lithological mapping of East Tianshan area using integrated data fused by Chinese GF-1 PAN and ASTER multi-spectral data. Open Geosci 10:532–543
Ye B, Tian S, Ge J, Sun Y (2017) Assessment of WorldView-3 Data for Lithological Mapping. Remote Sens 9:1132
Zadeh MH, Tangestani MH, Roldan FV, Yusta I (2014) Sub-pixel mineral mapping of a porphyry copper belt using EO-1 Hyperion data. Adv Space Res 53:440–451
Funding
We would like to show our gratitude to the financial support of Iranian Mines and Mining Industries Development and Renovation Organization (IMIDRO) for XRD analyses.
Author information
Authors and Affiliations
Contributions
Sogand Karimzadeh: Conceptualization, Investigation, Methodology, Software, Field observation, Data Curation, Writing- Original draft preparation. Majid H. Tangestani: Supervision, Review & Editing. Anna Fonseca: Field observation, Spectrometry, TSG analysis.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Communicated by: H. Babaie
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Karimzadeh, S., Tangestani, M.H. & Fonseca, A. The synergistic use of WorldView-3 and EO1-Hyperion data for the identification of lineaments and hydrothermal alteration minerals in the Chadormalu iron oxide-apatite deposit area, Central Iran. Earth Sci Inform 16, 2573–2593 (2023). https://doi.org/10.1007/s12145-023-01048-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12145-023-01048-x