Mineral prospectivity mapping: a potential technique for sustainable mineral exploration and mining activities – a case study using the copper deposits of the Tagmout basin, Morocco

Mineral Prospectivity ◽

A COMPARATIVE ANALYSIS OF INDEX OVERLAY AND TOPSIS (BASED ON AHP WEIGHT) FOR IRON SKARN MINERAL PROSPECTIVITY MAPPING, A CASE STUDY IN SARVIAN AREA, MARKAZI PROVINCE, IRAN

Bulletin Of The Mineral Research and Exploration ◽

10.19111/bulletinofmre.305201 ◽

2017 ◽

pp. 1-1

Author(s):

Edris Mansouri ◽

Faranak Feizi ◽

Alireza Jafari Rad ◽

Mehran Arian

Keyword(s):

Comparative Analysis ◽

Mineral Prospectivity ◽

Index Overlay ◽

Prospectivity Mapping ◽

Skarn Mineral

A stable downward continuation of airborne magnetic data: A case study for mineral prospectivity mapping in Central Iran

Computers & Geosciences ◽

10.1016/j.cageo.2012.11.006 ◽

2013 ◽

Vol 52 ◽

pp. 269-280 ◽

Cited By ~ 36

Author(s):

Maysam Abedi ◽

Ali Gholami ◽

Gholam-Hossain Norouzi

Keyword(s):

Downward Continuation ◽

Central Iran ◽

Magnetic Data ◽

Mineral Prospectivity ◽

Prospectivity Mapping ◽

Airborne Magnetic

Evaluation of uncertainty in mineral prospectivity mapping due to missing evidence: A case study with skarn-type Fe deposits in Southwestern Fujian Province, China

Ore Geology Reviews ◽

10.1016/j.oregeorev.2014.09.024 ◽

2015 ◽

Vol 71 ◽

pp. 502-515 ◽

Cited By ~ 53

Author(s):

Renguang Zuo ◽

Zhenjie Zhang ◽

Daojun Zhang ◽

Emmanuel John M. Carranza ◽

Haicheng Wang

Keyword(s):

Fujian Province ◽

Mineral Prospectivity ◽

Southwestern Fujian ◽

A method for mineral prospectivity mapping integrating C4.5 decision tree, weights-of-evidence and m-branch smoothing techniques: a case study in the eastern Kunlun Mountains, China

Earth Science Informatics ◽

10.1007/s12145-013-0128-0 ◽

2013 ◽

Vol 7 (1) ◽

pp. 13-24 ◽

Cited By ~ 22

Author(s):

Cuihua Chen ◽

Binbin He ◽

Ze Zeng

Keyword(s):

Decision Tree ◽

Weights Of Evidence ◽

Smoothing Techniques ◽

Kunlun Mountains ◽

Eastern Kunlun Mountains ◽

C4.5 Decision Tree ◽

Mineral Prospectivity ◽

GIS-based Mineral Prospectivity Mapping of Seafloor Massive Sulfide on Ultraslow-spreading Ridges: A Case Study of Southwest Indian Ridge 48.7°–50.5° E

Natural Resources Research ◽

10.1007/s11053-020-09797-y ◽

2021 ◽

Author(s):

Lushi Liu ◽

Jilong Lu ◽

Chunhui Tao ◽

Shili Liao ◽

Shengbo Chen

Keyword(s):

Massive Sulfide ◽

Southwest Indian Ridge ◽

Spreading Ridges ◽

Mineral Prospectivity ◽

Indian Ridge ◽

Seafloor Massive Sulfide ◽

Application of fuzzy analytical hierarchy process (AHP) and prediction-area (P-A) plot for mineral prospectivity mapping: a case study from the Dananhu metallogenic belt, Xinjiang, NW China

Arabian Journal of Geosciences ◽

10.1007/s12517-016-2316-y ◽

2016 ◽

Vol 9 (4) ◽

Cited By ~ 9

Author(s):

Xishihui Du ◽

Kefa Zhou ◽

Yao Cui ◽

Jinlin Wang ◽

Nannan Zhang ◽

...

Keyword(s):

Analytical Hierarchy Process ◽

Fuzzy Analytical Hierarchy Process ◽

Nw China ◽

Metallogenic Belt ◽

Mineral Prospectivity ◽

Hierarchy Process ◽

A new linguistic quantifier knowledge-guided OWA approach for mineral prospectivity mapping: a case study of the Bavanat Region, Iran

Arabian Journal of Geosciences ◽

10.1007/s12517-018-3949-9 ◽

2018 ◽

Vol 11 (19) ◽

Cited By ~ 1

Author(s):

Reza Ghasemi ◽

Behzad Tokhmechi ◽

Gregor Borg

Keyword(s):

Linguistic Quantifier ◽

Mineral Prospectivity ◽

GIS-based mineral prospectivity mapping using machine learning methods: A case study from Tongling ore district, eastern China

Ore Geology Reviews ◽

10.1016/j.oregeorev.2019.04.003 ◽

2019 ◽

Vol 109 ◽

pp. 26-49 ◽

Cited By ~ 21

Author(s):

Tao Sun ◽

Fei Chen ◽

Lianxiang Zhong ◽

Weiming Liu ◽

Yun Wang

Keyword(s):

Machine Learning ◽

Eastern China ◽

Learning Methods ◽

Machine Learning Methods ◽

Mineral Prospectivity ◽

Prospectivity Mapping ◽

Ore District

3D Mineral Prospectivity Mapping Based on Deep Metallogenic Prediction Theory: A Case Study of the Lala Copper Mine, Sichuan, China

Journal of Earth Science ◽

10.1007/s12583-021-1437-8 ◽

2021 ◽

Vol 32 (2) ◽

pp. 348-357

Author(s):

Keyan Xiao ◽

Jie Xiang ◽

Mingjing Fan ◽

Yang Xu

Keyword(s):

Prediction Theory ◽

Copper Mine ◽

Mineral Prospectivity ◽

Metallogenic Prediction ◽

Comparison of the Data-Driven Random Forests Model and a Knowledge-Driven Method for Mineral Prospectivity Mapping: A Case Study for Gold Deposits Around the Huritz Group and Nueltin Suite, Nunavut, Canada

Natural Resources Research ◽

10.1007/s11053-015-9274-z ◽

2015 ◽

Vol 25 (2) ◽

pp. 125-143 ◽

Cited By ~ 48

Author(s):

G. McKay ◽

J. R. Harris

Keyword(s):

Random Forests ◽

Gold Deposits ◽

Data Driven ◽

Mineral Prospectivity ◽

Prospectivity Mapping ◽

Random Forests Model