Discrimination different lithological units using a remote sensing application: A case study in the Dokan Area, Kurdistan Region - Iraq

• Autorzy: Bety Azhar Kh. S.

Identyfikatory

DOI

10.24425/jwld.2022.142312

• Języki publikacji: EN

Abstrakty

EN

This study discriminates different lithological units of the Dokan Area, Kurdistan Region, NE-Iraq, using rapid-eye satellite data by image enhancement techniques, namely the false colour composite (FCC), optimum index factor (OIF), minimum noise fraction (MNF), principal component analysis (PCA) and band ratio (BR). Results of analyses show that the FCC (R: 5; G: 4: B: 1); MNF (R: 2, G: 3, B: 5); PCA (R: 5, G: 2, B: 1), and band ratio (R: 5/4, G: 2/1, B: 5/3) are the best to different geological formations. The results are confirmed in the field support with the geological maps available for the area. Geological formations appeared as a result of the collision process between the Arabian plate and the Iranian plate. In general, the study area is mountainous, which is usually represented by anticline folds with the main NW - SE trend in the study area, with very a rugged relief mainly due to the continuous collision between the Arabian plate and Iranian plate. The digital image processing of satellite data has demonstrated the sensor’s capability and efficiency of the image processing methods in identifying and mapping geological units in the study area.

Słowa kluczowe

EN

Dokan Area; image enhancement; image transformation; lithological units; rapid eye; remote sensing

• Wydawca: Wydawnictwo ITP
• Czasopismo: Journal of Water and Land Development
• Rocznik: 2022
• Tom: no. 55
• Strony: 109--114
• Opis fizyczny: Bibliogr. 23 poz., rys., tab.

Twórcy

autor

Bety Azhar Kh. S.

• University of Sulaimani, College of Science, Department of Geology, Tasluja Str. 1, Zone 501 Sulaimania, As Sulaymaniyah, Kurdistan Region, Iraq

• https://orcid.org/0000-0001-6191-1789

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).