Recognition of the regional lineaments of Iran: Using geospatial data and their implications for exploration of metallic ore deposits

SA Meshkani, B Mehrabi, A Yaghubpur, M Sadeghi - Ore Geology Reviews, 2013 - Elsevier
The relationship between major structural lineaments and locations of ore deposits in Iran
has been investigated using geospatial data. In the course of lineament extraction, satellite …

[HTML][HTML] Discovering hidden spatial patterns and their associations with controlling factors for potentially toxic elements in topsoil using hot spot analysis and K-means …

H Xu, P Croot, C Zhang - Environment International, 2021 - Elsevier
The understanding of sources and controlling factors of potentially toxic elements (PTEs) in
soils plays an important role in the improvement of environmental management. With the …

Tectono-magmatic evolution of porphyry belts in the central Tethys region of Turkey, the Caucasus, Iran, western Pakistan, and southern Afghanistan

L Zürcher, AA Bookstrom, JM Hammarstrom… - Ore Geology …, 2019 - Elsevier
Exploration in the central Tethys region of Turkey, Armenia, Azerbaijan, Georgia, Iran, and
western Pakistan has led to the identification of the giant Reko Diq (24 Mt Cu and 1300 t Au) …

Sedimentary response to the paleogeographic and tectonic evolution of the southern North China Craton during the late Paleozoic and Mesozoic

DB Yang, HT Yang, JP Shi, WL Xu, F Wang - Gondwana Research, 2017 - Elsevier
With the aim of constraining the influence of the surrounding plates on the Late Paleozoic–
Mesozoic paleogeographic and tectonic evolution of the southern North China Craton …

[HTML][HTML] Geochemical behavior investigation based on k-means and artificial neural network prediction for titanium and zinc, Kivi region, Iran

S Adel, Z Mansour, H Ardeshir - Известия Томского …, 2021 - cyberleninka.ru
The relevance. These are the first studies in the Kivi region. Due to the presence of titanium
and zinc in the area, these studies are necessary. Artificial Neural Network and K-means …

Spatio-geologically informed fuzzy classification: an innovative method for recognition of mineralization-related patterns by integration of elemental, 3D spatial, and …

S Esmaeiloghli, SH Tabatabaei… - Natural Resources …, 2021 - Springer
Recognition and mapping of mineralization-related patterns in geochemical data is a key
computational analysis to achieve a predictive model of prospectivity for mineral deposit …

[HTML][HTML] Geochemical and geostatistical studies for estimating gold grade in tarq prospect area by k-means clustering method

A Shirazy, A Shirazi, MH Ferdossi, M Ziaii - Open Journal of Geology, 2019 - scirp.org
Tarq geochemical 1: 100,000 Sheet is located in Isfahan province which is investigated by
Iran's Geological and Explorations Organization using stream sediment analyzes. This area …

Geochemical Behavior Investigation Based on K-means and Artificial Neural Network Prediction for Copper, in Kivi region, Ardabil province, IRAN

A Shirazy, M Ziaii, A Hezarkhani - Journal of Mining Engineering, 2020 - ijme.iranjournals.ir
Kivi region is located in Ardabil province of Iran. This research is on kivi geochemical sheet
(on scale 1: 100000) which is investigated by geological survey & mineral explorations of …

Assessment of metal contamination in groundwater and soils in the Ahangaran mining district, west of Iran

B Mehrabi, S Mehrabani, B Rafiei… - … monitoring and assessment, 2015 - Springer
In this study, 28 groundwater and 13 soil samples from Ahangaran mining district in
Hamedan Province, west of Iran were collected to evaluate the level of contamination …

Composite soil-geochemical halos delineating carbonate-hosted zinc–lead–barium mineralization in the Irankuh district, Isfahan, west-central Iran

H Hosseini-Dinani, A Aftabi, A Esmaeili… - Journal of Geochemical …, 2015 - Elsevier
The Irankuh district in west-central Iran hosts several largely unexposed Lower Cretaceous
carbonate-hosted Zn–Pb deposits whose host rocks are overlain by soil cover. This paper …