ORIGINAL PAPER
Application of satellite remote sensing methods in mineral prospecting in Kosovo, area of Selac
 
More details
Hide details
1
AGH University of Science and Technology
 
 
Submission date: 2019-11-27
 
 
Final revision date: 2020-01-30
 
 
Acceptance date: 2020-03-26
 
 
Publication date: 2020-03-26
 
 
Corresponding author
Katarzyna Adamek   

AGH University of Science and Technology
 
 
Gospodarka Surowcami Mineralnymi – Mineral Resources Management 2020;36(1):5-22
 
KEYWORDS
TOPICS
ABSTRACT
Introduction: Traditional methods of mineral exploration are mainly based on very expensive drilling and seismic methods. The proposed approach assumes the preliminary recognition of prospecting areas using satellite remote sensing methods. Maps of mineral groups created using Landsat 8 images can narrow the search area, thereby reducing the costs of geological exploration during mineral prospecting. This study focuses on the identification of mineralized zones located in the southeastern part of Europe (Kosovo, area of Selac) where hydrothermal mineralization and alterations can be found. The article describes all the stages of research, from collecting in-situ rock samples, obtaining spectral characteristics with laboratory measurements, preprocessing and analysis of satellite images, to the validation of results through field reconnaissance in detail. The authors introduce a curve-index fitting technique to determine the degree of similarity of a rock sample to a given pixel of satellite imagery. A comparison of the reflectance of rock samples against surface reflectance obtained from satellite images allows the places where the related type of rock can be found to be determined. Finally, the results were compared with geological and mineral maps to confirm the effectiveness of the method. It was shown that the free multispectral data obtained by the Landsat 8 satellite, even with a resolution of 30 meters, can be considered as a valuable source of information that helps narrow down the exploration areas.
METADATA IN OTHER LANGUAGES:
Polish
Wykorzystanie metod teledetekcji satelitarnej w poszukiwaniu złóż surowców mineralnych w rejonie Selac, Kosowo
GIS, teledetekcja, geologia, Landsat 8, geologiczne poszukiwania surowców mineralnych
Wstęp
Tradycyjne metody poszukiwania surowców mineralnych opierają się głównie na bardzo kosztownych metodach, takich jak wiercenia oraz metody sejsmiczne. Proponowane przez autorów podejście zakłada wstępne rozpoznanie obszarów perspektywicznych z wykorzystaniem metod teledetekcji satelitarnej. Mapy grup minerałów stworzone przy użyciu zobrazowań dostarczonych przez satelitę Landsat 8 mogą zawęzić obszar poszukiwań, a przez to doprowadzić do redukcji kosztów rozpoznania geologicznego podczas poszukiwania surowców mineralnych. Niniejsze badanie skupia się na identyfikacji stref zmineralizowanych znajdujących się w południowo-wschodniej Europie (Kosowo, rejon Selac) gdzie znajdują się mineralizacje hydrotermalne oraz strefy alteracji. Artykuł opisuje szczegółowo wszystkie etapy badań, od pozyskania próbek terenowych, badań laboratoryjnych mających na celu pozyskanie charakterystyk spektralnych, przez wstępne przetwarzanie oraz analizę zobrazowań satelitarnych do walidacji wyników poprzez rozpoznanie terenowe. Autorzy przedstawili technikę wykorzystującą wskaźnik dopasowania krzywej pozwalający na określenie stopnia podobieństwa próbki do piksela zobrazowania satelitarnego. Porównanie współczynnika odbicia dla próbek względem współczynnika odbicia zarejestrowanego przez satelitę pozwala na określenie miejsc, gdzie mogą występować określone typy skał. W celu określenia skuteczności metody wyniki zostały porównane z mapami geologicznymi. Wykazano, że darmowe dane multispektralne dostarczone przez satelitę Landsat 8, nawet z rozdzielczością 30 m, mogą stanowić cenne źródło informacji, które pozwala na zawężenie obszaru poszukiwań.
Materiał i metody
Wyniki
Wnioski
 
REFERENCES (40)
1.
Ahmadirouhani, R. and Samiee, S. 2014. Mapping glauconite unites with using remote sensing techniques in north east of Iran. 1st Isprs International Conference on Geospatial Information Research 40, pp. 7–11.
 
2.
Bedini, E., van der Meer, F. and van Ruitenbeek, F. 2009. Use of HyMap imaging spectrometer data to map mineralogy in the Rodalquilar caldera, southeast Spain. International Journal of Remote Sensing 30, pp. 327–348.
 
3.
Berger et al. 2012 – Berger, M., Moreno, J., Johannessen, J.A., Levelt, P.F. and Hanssen, R.F. 2012. ESA’s sentinel missions in support of Earth system science. Remote Sensing of Environment 120, pp. 84–90.
 
4.
Bielecka et al. 2014 – Bielecka, M., Porzycka-Strzelczyk, S. and Strzelczyk, J. 2014. SAR images analysis based on polarimetric signatures. Applied Soft Computing 23, pp. 259–269.
 
5.
Bilotti et al. 2000 – Bilotti, F., Shaw, J.H. and Brennan, P. A. 2000. Quantitative structural analysis with stereoscopic remote sensing imagery. AAPG Bulletin 84, pp. 727–740.
 
6.
Chavez, P.S. 1996. Image-based atmospheric corrections-revisited and improved. Photogrammetric engineering and remote sensing 62, pp. 1025–1035.
 
7.
Cloutis, E.A. 1996. Review article hyperspectral geological remote sensing: evaluation of analytical techniques. International Journal of Remote Sensing 17, pp. 2215–2242.
 
8.
Congedo, L. 2016. Semi-automatic classification plugin documentation. Release, 4, p. 29.
 
9.
Dasgupta, S. and Mukherjee, S. 2019. Remote sensing in lineament identification: examples from western India. Developments in Structural Geology and Tectonics. Elsevier.
 
10.
Elrakaiby, M. L. 1995. The use of enhanced landsat-tm image in the characterization of uraniferous granitic-rocks in the central eastern desert of Egypt. International Journal of Remote Sensing 16, pp. 1063–1074.
 
11.
Fraser et al. 1997 – Fraser, A., Huggins, P., Rees, J. and Cleverly, P. 1997. A satellite remote sensing technique for geological structure horizon mapping. International Journal of Remote Sensing 18, pp. 1607–1615.
 
12.
Goetz et al. 1985 – Goetz, A.F.H., Vane, G., Solomon, J.E. and Rock, B.N. 1985. Imaging spectrometry for earth remote-sensing. Science 228, pp. 1147–1153.
 
13.
Hyseni et al. 2010 – Hyseni, S., Durmishaj, B., Fetahaj, B., Shala, F., Berisha, A. and Large, D. 2010. Trepça Ore Belt and Stan Terg mine-Geological overview and interpretation, Kosovo (SE Europe). Geologija 53, pp. 87–92.
 
14.
Joyce et al. 2014 – Joyce, K.E., Samsonov, S.V., Levick, S.R., Engelbrecht, J. and Belliss, S. 2014. Mapping and monitoring geological hazards using optical, LiDAR, and synthetic aperture RADAR image data. Natural Hazards 73, pp. 137–163.
 
15.
Kavak, K. and Inan, S. 2002. Enhancement facilities of SPOT XS imagery in remote sensing geology: an example from the Sivas Tertiary Basin (central Anatolia/Turkey). International Journal of Remote Sensing 23, pp. 701–710.7.
 
16.
Kereszturi et al. 2018 – Kereszturi, G., Pullanagari, R., Mead, S., Schaefer, L., Procter, J., Schleiffarth, W. and Kennedy, B. 2018. Geological Mapping of Hydrothermal Alteration on Volcanoes from Multi-Sensor Platforms. IGARSS 2018–2018 IEEE International Geoscience and Remote Sensing Symposium, 2018. IEEE, pp. 220–223.
 
17.
Loughlin, W.P. 1991. Principal component analysis for alteration mapping. Photogrammetric Engineering and Remote Sensing 57, pp. 1163–1169.
 
18.
Madani, A. and Emam, A. 2011. SWIR ASTER band ratios for lithological mapping and mineral exploration: a case study from El Hudi area, southeastern desert, Egypt. Arabian journal of Geosciences 4, pp. 45–52.
 
19.
Mars, J.C. and 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, pp. 161–186.
 
20.
Mars, J.C. and Rowan, L.C. 2010. Spectral assessment of new ASTER SWIR surface reflectance data products for spectroscopic mapping of rocks and minerals. Remote Sensing of Environment 114, pp. 2011–2025.
 
21.
Mierczyk et al. 2016 – Mierczyk, M., Zagajewski, B., Jarocinska, A. and Knapik, R. 2016. Assessment of Imaging Spectroscopy for rock identification in the Karkonosze Mountains, Poland. Miscellanea Geographica 20, pp. 34–40.
 
22.
Palinkaš et al. 2013 – Palinkaš, S.S., Palinkaš, L.A., Renac, C., Spangenberg, J.E., Lüders, V., Molnar, F. and Maliqi, G. 2013. Metallogenic model of the Trepča Pb-Zn-Ag skarn deposit, Kosovo: evidence from fluid inclusions, rare earth elements, and stable isotope data. Economic Geology 108, pp. 135–162.
 
23.
Porzycka, S. and Leśniak, A. 3D GIS analysis of PSInSAR data as a source of information in monitoring of areas endangered by terrain deformations.
 
24.
Pour et al. 2018 – Pour, A.B., Hashim, M., Park, Y. and Hong, J.K. 2018. Mapping alteration mineral zones and lithological units in Antarctic regions using spectral bands of ASTER remote sensing data. Geocarto International 33, pp. 1281–1306.
 
25.
Pournamdari, M. and Hashim, M. 2014. Detection of chromite bearing mineralized zones in Abdasht ophiolite complex using ASTER and ETM+ remote sensing data. Arabian Journal of Geosciences 7, pp. 1973–1983.
 
26.
Rajendran et al. 2012 – Rajendran, S., Al-Khirbash, S., Pracejus, B., Nasir, S., Al-Abri, A.H., Kusky, T.M. and Ghulam, A. 2012. ASTER detection of chromite bearing mineralized zones in Semail Ophiolite Massifs of the northern Oman Mountains: Exploration strategy. Ore geology reviews 44, pp. 121–135.
 
27.
Rockwell, B.W. 2012. Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado. US Geological Survey.
 
28.
Rockwell, B.W. 2013. Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado. US Geological Survey Scientific Investigations Map, 3252.
 
29.
Rockwell, B.W. and Hofstra, A.H. 2008. Identification of quartz and carbonate minerals across northern Nevada using ASTER thermal infrared emissivity data-Implications for geologic mapping and mineral resource investigations in well-studied and frontier areas. Geosphere 4, pp. 992–992.
 
30.
Bennet et al. 1993 – Bennet, S.A., Atkinson Jr, W.W. and Kruse, F.A. 1993. Use of Thematic Mapper Imagery to Identify Mineralization in the Santa Teresa District, Sonora, Mexico. International Geology Review.
 
31.
Sabins, F.F. 1999. Remote sensing for mineral exploration. Ore Geology Reviews 14, pp. 157–183.
 
32.
Safari et al. 2018 – Safari, M., Maghsoudi, A. and Pour, A.B. 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. Geocarto international 33, pp. 1186–1201.
 
33.
Schowengerdt, R.A. 2006. Remote sensing: models and methods for image processing, Elsevier.
 
34.
Shalaby et al. 2010 – Shalaby, M., Bishta, A. and Roz, M. 2010. Integration of geologic and remote sensing studies for the discovery of uranium mineralization in some granite plutons, Eastern Desert, Egypt. Journal of King Abdulaziz University: Earth Sciences 150, pp. 1–50.
 
35.
Sultan et al. 1987 – Sultan, M., Arvidson, R.E., Sturchio, N.C. and Guinness, E.A. 1987. Lithologic mapping in arid regions with landsat thematic mapper data - meatiq dome, Egypt. Geological Society of America Bulletin 99, pp. 748–762.
 
36.
Tangestani, M.H. and Moore, F. 2002. Porphyry copper alteration mapping at the Meiduk area, Iran. International Journal of Remote Sensing 23, pp. 4815–4825.
 
37.
van der Meer et al. 2012 – 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. and Woldai, T. 2012. Multi- and hyperspectral geologic remote sensing: A review. International Journal of Applied Earth Observation and Geoinformation 14, pp. 112-128.
 
38.
van der Werff, H. and van der Meer, F. 2015. Sentinel-2 for mapping iron absorption feature parameters. Remote sensing 7, pp. 12635–12653.
 
39.
Yousefi et al. 2018 – Yousefi, S.J., Ranjbar, H., Alirezaei, S., Dargahi, S. and Lentz, D.R. 2018. Comparison of hydrothermal alteration patterns associated with porphyry Cu deposits hosted by granitoids and intermediate-mafic volcanic rocks, Kerman Magmatic Arc, Iran: Application of geological, mineralogical and remote sensing data. Journal of African Earth Sciences 142, pp. 112–123.
 
40.
Zagajewski, B., Tømmervik, H., Bjerke, J., Raczko, E., Bochenek, Z., Kłos, A., Jarocińska, A., Lavender, S. and Ziółkowski, D. 2017. Intraspecific differences in spectral reflectance curves as indicators of reduced vitality in high-arctic plants. Remote Sensing 9, p. 1289.
 
eISSN:2299-2324
ISSN:0860-0953
Journals System - logo
Scroll to top