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Inter-correlation of hydrothermal mineral alteration zone in the vicinity of lineaments


Affiliations
1 Department of Applied Geology, National Institute of Technology, Raipur 492 010, India
 

There are significant and effective roles of geological structures such as lineaments in mineral zone identification and interpretation, exploration and mapping of rock units, litho-boundaries, local tectonic zones and fractures, and hydrothermal alteration facies. The aim of this study was to extract lineaments of Jahajpur region of Bhilwara district, Rajashtan automatically and digitally using Sentinel 2A optical data. The automatic lineament extraction by ‘LINE’ algorithms tool with involvement of several processing steps and parameters of PCI Geomatica evaluated digitally extracted lineaments, geospatial analyses such as length of lineaments, lineament density and lineament orientation. The obtained results were validated through assessment of geomorphic and structural features interpretation by numerical, analogical, and geospatial analysis and field survey for a better understanding and correlation. The vicinity of extracted lineament and lineament densities show the various alteration minerals such as clay, talc, mica, dolomite and goethite. Thus, we can conclude that lineaments have excellent inter-relation­ship with hydrothermal alteration and weathering zones in the western Jahajpur belt, Rajasthan.

Keywords

Geospatial analysis, hydrothermal alteration, lineaments, optical data, weathering zones
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  • Baghdad, B., Structural interpretation of lineaments by remote sensing and GIS using Landsat 8 data: a case study of akreuch area (Morocco). Eur. J. Sci. Res., 2016, 138(3), 216–224.

  • Mwaniki, M. W., Moeller, M. S. and Schellmann, G., A comparison of Landsat 8 (OLI) and Landsat 7 (ETM+) in mapping geology and visualising lineaments: a case study of central region Kenya. Int. Arch. Photogramm., Remote Sensing Spat. Inf. Sci. – ISPRS Arch., 2015, 40(7W3), 897–903; doi:10.5194/isprsarchivesXL-7-W3-897-2015.

  • Hung, L. Q., Batelaan, O. and de Smedt, F., Lineament extraction and analysis, comparison of LANDSAT ETM and ASTER imagery. Case study: Suoimuoi tropical karst catchment, Vietnam. In Proc. SPIE 5983, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology V, 59830T, 2005; https:// doi.org/10.1117/12.627699.

  • O’Leary, D. W., Friedman, J. D. and Pohn, H. A., Lineament, linear, lineation: some proposed new standards for old terms. Geol. Soc. Am. Bull., 1976, 87, 1463–1469.

  • Thannoun, R. G., 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. Enhance. Res. Sci. Technol. Eng., 2013, 2(2), 1–11.

  • Ibrahim, M., El-Bastawesy, M. A. and El-Saud, W. A., Automated, manual lineaments extraction and geospatial analysis for Cairo–Suez district (northeastern Cairo–Egypt), using remote sensing and GIS. Int. J. Innov. Sci. Eng. Technol., 2016, 3(5), 491–500.

  • Hashim, A. M. S., Johari, M. A. M. and Pour, A., Automatic lineament extraction in a heavily vegetated region using landsat enhanced thematic mapper (ETM+) imagery. Adv. Space Res., 2013, 51, 874–890.

  • Abarca, M. A. A., Lineament extraction from digital terrain models. Case study, Lineament Extraction from Digital Terrain Models, San Antonio del Sur area, south-eastern Cuba, 2006.

  • Neawsuparp, K. and Charusiri, P., Lineaments analysis determined from Landsat data implication for tectonic features and mineral occurrences in Northern Loei Area, NE Thailand. Sci. Asia, 2004, 30, 269–278.

  • Masoud, A. A. and Koike, K., Auto-detection and integration of tectonically significant lineaments from SRTM DEM and remotely-sensed geophysical data. ISPRS J. Photogramm. Remote Sensing, 2011, 66, 818–832.

  • Alshayef, M. S., Mohammed, A. M., Javed, A. and Albaischolar_main, M. A., Manual and automatic extraction of lineaments from multispectral image in part of Al-Rawdah, Shabwah, Yemen by using remote sensing and GIS technology. Comput. Geosci., 2017, 2, 67–73.

  • Casas, A. M., Cortes, A. L., Maestro, A., Soriano, M. A., Riaguas, A. and Bernal, J., A program for lineament length and density analysis. Comput. Geosci., 2000, 26(9/10), 1011–1022.

  • Kruse, F. A., Advances in hyperspectral remote sensing for geologic mapping and exploration. What is imaging spectrometry (hyperspectral sensing)? Atmospheric corrections are required for most hyperspectral analyses. In 9th Australasian Remote Sensing Conference, Sydney, Australia, 1998, vol. 1; http://www.hgimaging.com/PDF/Kruse_9th_australasian_rs_98.pdf

  • Corgne, S., Magagi, R., Yergeau, M. and Sylla, D., An integrated approach to hydro-geological lineament mapping of a semi-arid region of West Africa using Radarsat-1 and GIS. Remote Sensing Environ., 2010, 114(9), 1863–1875; doi:10.1016/j.rse.2010.03.004.

  • Ramasamy, S. M., Bakliwal, P. C. and Rao, K. L. V. R., Use of remote sensing tectonic evolution and resources study of a part of Vindhychal basin, Jhalawar area, India. J. Indian Soc. Remote Sensing, 1988, 16(1), 63–71.

  • Middleton, M., Schnur, T. and Sorjonen-Ward, P., Geological lineaments interpretation using the object-based image analysis approach: results of semi-automated analysis versus visual interpretation. Geol. Surv. Finland, Spec. Paper, 2015, 67, 135–154.

  • Mavrantza, O. and Argialas, D., An object-oriented image analysis approach for the identification of geologic lineaments in a sedimentary geotectonic environment. In Object-Based Image Analysis (eds Blaschke, T., Lang, S. and Hay, G. J.), Lecture Notes in Geoinformation and Cartography, Springer, Berlin, Heidelbarg, 2008; https://doi.org/10.1007/978-3-540-77058-9_21.

  • Tripathi, M. K., Govil, H. and Chattoraj, S. L., Identification of hydrothermal altered/weathered and clay minerals through airborne AVIRIS-NG hyperspectral data in Jahajpur, India. Heliyon, 2020, 6, e03487; doi:10.1016/j.heliyon.2020.e03487.

  • Tripathi, M. K. and Govil, H., Evaluation of AVIRIS-NG hyperspectral images for mineral identification and mapping. Heliyon, 2019, 5(11), 1–10; doi:10.1016/j.heliyon.2019.e02931.

  • Meer, F. D. V. D. et al., Multi- and hyperspectral geologic remote sensing: a review. Int. J. Appl. Earth Obs. Geoinf., 2012, 14(1), 112–128; doi:10.1016/j.jag.2011.08.002.

  • Nouri, T. and Oskouei, M. M., Detection of the geothermal alterations and thermal anomalies by processing of remote sensing data. In XXXIII Asian Conference on Remote Sensing, Sabalan, Iran, 2010.

  • Skinner, B. J., Introduction to Ore-Forming Processes, Laurence Robb., Blackwell Publishing, USA, Oxford, Australia, 2005; ISBN 0-632-06378-5.

  • Tripathi, M. K. and Govil, H., Evaluation of analogical analysis techniques in interpretation of lineaments and litho-boundaries using Landsat 7 ETM+ imagery of western Jahajpur. In 4th International Conference on Information Systems and Computer Networks, Calcutta, 2019.

  • Gupta, S. N. et al., The precambrian geology of the Aravalli region, southern Rajasthan and north-eastern Gujarat. Mem. Geol. Surv. India, 1997, 123, 262.

  • Sinha-Roy, S., Neotectonically controlled catchment capture: an example from the Banas and Chambal drainage basins, Rajasthan. Curr. Sci., 2001, 80(2), 293–298.

  • Tripathi, M. K., Govil, H. and Prabhat, D., Lithological mapping using digital image processing techniques on landsat 8 OLI remote sensing data in Jahajpur, Bhilwara, Rajasthan. In 2nd International Conference on Intelligent Communication and Computational Techniques, Manipal University, Jaipur, 28 and 29 September 2019, pp. 43–48.

  • Tripathi, M. K., Govil, H. and Diwan, P., Petrography, XRD analysis and identification of Talc minerals near Chhabadiya village of Jahajpur Region, Bhilwara, India through Hyperion Hyperspectral Remote Sensing Data. In 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT), 2019, pp. 75–78; doi:10.1109/ICCT46177. 2019.8969008.

  • Saxena, Asha and Pandit, M. K., Geochemistry of Hindoli Group metasediments, SE Aravalli Craton, NW India: implications for palaeoweathering and provenance. J. Geol. Soc. India, 2012, 79, 267–278; http://mecl.gov.in/Reports/EXE_SUMM_BANERA.pdf

  • Yadav, O. P., Babu, T. B., Shrivastava, P. K., Pande, A. and Gupta, K. R., Short communications and its significance in west Jahajpur basin, Bhilwara district, Rajsthan. J. Geol. Soc. India, 2001, 58, 1–3.

  • Srivastava, R P., Systematic geological mapping in parts of Ajmer, Bhilwara and Udaipur districts, Rajsthan included in toposheet nos. 45 K/1&5 (Progress report for the field-season 1966– 67), Geological Survey of India, Jaipur, 1968.

  • Heron, A. and Heron, A. M., Synopsis of the pre-Vindhyan geology of Rajputana. Trans. Nat. Inst. Sci. India, 1935, I, 17–33.

  • Heron, A., The geology of Central Rajputana. In Memoirs of Geological Survey of India, Geological Survey of India, 1953, vol. 79, p. 389.

  • Drusch, M. et al., Sentinel-2: ESA’s optical high-resolution mission for GMES operational services. Remote Sensing Environ., 2012, 120, 25–36; doi:10.1080/014311600210092.

  • Abdullah, A., Akhir, J. M. and Abdullah, I., Automatic mapping of lineaments using shaded relief images derived from digital elevation model (DEMs) in the Maran–Sungi Lembing area, Malaysia. EJGE, 2010, 15, 949–957.

  • Adiri, Z. et al., Comparison of Landsat-8, ASTER and Sentinel 1 satellite remote sensing data in automatic lineaments extraction: a case study of Sidi Flah-Bouskour inlier, Moroccan Anti-Atlas. Adv. Space Res., 2017, 60(11), 2355–2367; doi:10.1016/j.asr.2017.09.006.

  • K. M. and Ová, K., Analysis of the relationship of automatically and manually extracted lineaments from DEM and geologically mapped tectonic faults around the main Ethopian rift and the Ehopian highlands. Ethopia, 2017, 1, 5–17.

  • Kocal, A., Duzgun, H. S. and Karpuz, C., An accuracy assessment methodology for the remotely sensed discontinuities: a case study in Andesite Quarry area, Turkey. Int. J. Remote Sensing, 2007, 17, 3915–3936; doi:https:// doi.org/10.1080/01431160601086001.

  • Baidder, L., Khanbari, K., Rhinane, H. and Hilali, A., Using remote sensing for lineament extraction in Al Maghrabah area. In The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 3rd International Geoadvances Workshop, Istanbul, Turkey, 16–17 October 2016, vol. XLII-2/w1; doi:10.5194/isprs-archives-XLII-2-W1-137-2016.

  • Tripathi, M. K., Govil, H., Champati Ray, P. K. and Das, I. C., Landslide hazard zonation mapping of Chamoli landslides in remote sensing and GIS environment, 2018; doi:10.5194/isprsarchives-XLII-5-475-2018.

  • Singh, C. P., Science results from Phase-1 airborne hyperspectral campaign with AVIRIS-NG over India, 2017; https://vedas.sac.gov.in/aviris/pdf/AVIRIS_NG_FIRST_PHASE_REPORT.pdf (accessed on 2 June 2018).

  • Ali, S. A. and Ali, U., Litho-structural mapping of sind catchment (Kashmir Basin), NW Himalaya, using remote sensing and GIS techniques. Int. J. Sci. Res., 2015, 4(7), 1325–1330.

  • Amri, K., Mahdjoub, Y. and Guergour, L., Use of Landsat 7 ETM + for lithological and structural mapping of Wadi Afara Heouine area (Tahifet–Central Hoggar, Algeria). Arabian J. Geosci., 2011, 4, 1273–1287; doi:10.1007/s12517-010-0180-8.

  • Pour, A. B., Hashim, M. and van Genderen, J., Detection of hydrothermal alteration zones in a tropical region using satellite remote sensing data: Bau goldfield, Sarawak, Malaysia. Ore Geol. Rev., 2013, 54, 181–196; doi:10.1016/j.oregeorev.2013.03.010.

  • Corgne, S., Magagi, R., Yergeau, M. and Sylla, D., An integrated approach to hydro-geological lineament mapping of a semi-arid region of West Africa using Radarsat-1 and GIS. Remote Sensing Environ., 2010, 114, 1863–1875.

  • Lesage, G., Distribution of district-scale hydrothermal alteration, vein orientations and white mica compositions in the Highland Valley Copper District, British Columbia, Canada: implications for the evolution of porphyry Cu–Mo systems. Thesis, University of British Columbia, 2020; doi:10.1017/CBO9781107415324.004.

  • Rakovan, J., Word to the wise: metasomatism. Rocks Miner., 2005, 80(1), 63–64; doi:10.3200/rmin.80.1.63-64.

  • Hausrath, E. M., Navarre-Sitchler, A. K., Sak, P. B., Steefel, C. I. and Brantley, S L., Basalt weathering rates on Earth and the duration of liquid water on the plains of Gusev Crater. Mars Geology, 2008, 36(1), 67–70; doi:10.1130/G24238A.1.

  • Greenberger, R. N. et al., Imaging spectroscopy of geological samples and outcrops: novel insights from microns to meters. GSA Today, 2015, 25(12), 4–10; doi:10.1130/GSATG252A.1.

  • Tripathi, M. K. and Govil, H., Regolith mapping and geochemistry of hydrothermally altered, weathered and clay minerals, Western Jahajpur Belt, Bhilwara, India. Geocarto Int., 2020; https://doi. org/10.1080/10106049.2020.1745302.

  • Govil, H., Tripathi, M. K., Diwan, P., Guha, S. and Monika, Identification of iron oxide minerals in western Jahajpur region, India using avirisng hyperspectral remote sensing. Int. Arch. Photogramm., Remote Sensing Spat. Infor. Sci. – ISPRS. 2018, 42, 233–237; doi:10.5194/isprs-archives-XLII-5-233-2018.

  • Govil, H., Tripathi, M. K., Diwan, P. and Monika, Comparative evaluation of AVIRIS-NG and hyperion hyperspectral image for talc mineral identification. In International Conference on Data Mangement Analytics and Innovation, Turkey, 2019, pp. 95–101.

  • Dey, B., Das, K., Dasgupta, N., Bose, S. and Ghatak, H., Zircon U–Pb SHRIMP dating of the Jahazpur granite and its implications on the stratigraphic status of the Hindoli–Jahazpur Group. In Seminar Abstract Volume: Developments in Geosciences in thePast Deca, 2016.

  • Pandit, M. K., Sial, A. N., Malhotra, G., Shekhawat, L. S. and Ferreira, V. P., C-, O-isotope and whole-rock geochemistry of Proterozoic Jahazpur carbonates, NW Indian Craton. Gondwana Res., 2003, 6(3), 513–522.


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  • Inter-correlation of hydrothermal mineral alteration zone in the vicinity of lineaments

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Authors

Mahesh Kumar Tripathi
Department of Applied Geology, National Institute of Technology, Raipur 492 010, India
H. Govil
Department of Applied Geology, National Institute of Technology, Raipur 492 010, India

Abstract


There are significant and effective roles of geological structures such as lineaments in mineral zone identification and interpretation, exploration and mapping of rock units, litho-boundaries, local tectonic zones and fractures, and hydrothermal alteration facies. The aim of this study was to extract lineaments of Jahajpur region of Bhilwara district, Rajashtan automatically and digitally using Sentinel 2A optical data. The automatic lineament extraction by ‘LINE’ algorithms tool with involvement of several processing steps and parameters of PCI Geomatica evaluated digitally extracted lineaments, geospatial analyses such as length of lineaments, lineament density and lineament orientation. The obtained results were validated through assessment of geomorphic and structural features interpretation by numerical, analogical, and geospatial analysis and field survey for a better understanding and correlation. The vicinity of extracted lineament and lineament densities show the various alteration minerals such as clay, talc, mica, dolomite and goethite. Thus, we can conclude that lineaments have excellent inter-relation­ship with hydrothermal alteration and weathering zones in the western Jahajpur belt, Rajasthan.

Keywords


Geospatial analysis, hydrothermal alteration, lineaments, optical data, weathering zones

References





DOI: https://doi.org/10.18520/cs%2Fv121%2Fi6%2F789-800