A complete succession of the Shah Kuh Formation with the age of Early Cretaceous is exposed in southwest of Khur, in Central Iran. In order to study and describe calcareous algae the Shah Kuh Formation a stratigraphic section was selected, sampled and studied in Kuh- e More
A complete succession of the Shah Kuh Formation with the age of Early Cretaceous is exposed in southwest of Khur, in Central Iran. In order to study and describe calcareous algae the Shah Kuh Formation a stratigraphic section was selected, sampled and studied in Kuh- e Tangal- e Bala, 80 Km southwest of Khur city. Association of calcareous algae consist of Delloffrella quercifoliipora belongs to Triploporellaceae, Montiella elitzae, Neomeris cretacea, Salpingoporella sp. and Terquemella sp. related to Dasycladacea and Permocalculus cf. minutus belongs to Gymnocodiacea. Also 2 genera of Udoteaceae (Arabicodium and Boueina) and 1 species of Solenoporaceae (Marinella Lugeoni) were identified. A species of algae ascribed to uncertain affinities (Lithocodium aggregatum) accompanied by skeletal fragments of colonial octocorals were identified in this research. In studied microfacies, calcareous algae were observed in sediments of lagoon and bar environments. Based on calcareous algae and benthic foraminifera association, the age of Late Barremian- Early Aptian was assigned for the succession of the Shah Kuh Formation in studied section.
Manuscript profile
Separation of alteration units has an important role in exploration of ore deposits. In the past, classical methods were used for this purpose. Recently, the support vector machine (SVM), one of the most important data driven models, has been applied for geological purp More
Separation of alteration units has an important role in exploration of ore deposits. In the past, classical methods were used for this purpose. Recently, the support vector machine (SVM), one of the most important data driven models, has been applied for geological purpose. This algorithm is a useful learning system based on constrained optimization theory. In this study, the SVM algorithm with various kernels and maximum likelihood method were used to separate the alteration units of the Takht-e-Gonbad district situated in Chahar Gonbad sheet by using satellite images of the ASTER sensor. The results were analyzed and evaluated according to the field studies. Based on the achieved results and field studies, the SVM method with the RBF kernel function compared to other kernels and the maximum likelihood method had the highest accuracy (89.17%) and kappa coefficient (0.83). Thus, the SVM method for classification of alteration is more accurate compared to other discussed methods.
Manuscript profile