A case study for the integration of predictive mineral potential maps

A case study for the integration of predictive mineral potential maps

Bibliographic Details
Main Authors: Lee Saro, Oh Hyun-Joo, Heo Chul-Ho, Park Inhye
Format: Article
Language:English
Published: De Gruyter 2014-09-01
Series:Open Geosciences
Subjects:
gis
likelihood ratio
weight of evidence
logistic regression
artificial neural network
mineral potential mapping
Online Access:https://doi.org/10.2478/s13533-012-0183-y
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spelling doaj-8805028730514801a79f176a6d7ec2bb2021-09-05T21:03:21ZengDe GruyterOpen Geosciences2391-54472014-09-016337339210.2478/s13533-012-0183-ys13533-012-0183-yA case study for the integration of predictive mineral potential mapsLee Saro0Oh Hyun-Joo1Heo Chul-Ho2Park Inhye3Geological Mapping Department, Korea Institute of Geoscience Mineral Resources (KIGAM), 124 Gwahang-no, Yuseong-gu, Daejeon, 305-350, South KoreaMineral Resources Research Department, Korea Institute of Geoscience Mineral Resources (KIGAM), 124 Gwahang-no, Yuseong-gu, Daejeon, 305-350, South KoreaMineral Resources Research Department, Korea Institute of Geoscience Mineral Resources (KIGAM), 124 Gwahang-no, Yuseong-gu, Daejeon, 305-350, South KoreaGeological Mapping Department, Korea Institute of Geoscience Mineral Resources (KIGAM), 124 Gwahang-no, Yuseong-gu, Daejeon, 305-350, South Koreahttps://doi.org/10.2478/s13533-012-0183-ygislikelihood ratioweight of evidencelogistic regressionartificial neural networkmineral potential mapping
collection DOAJ
language English
format Article
sources DOAJ
author Lee Saro
Oh Hyun-Joo
Heo Chul-Ho
Park Inhye
spellingShingle Lee Saro
Oh Hyun-Joo
Heo Chul-Ho
Park Inhye
A case study for the integration of predictive mineral potential maps
Open Geosciences
gis
likelihood ratio
weight of evidence
logistic regression
artificial neural network
mineral potential mapping
author_facet Lee Saro
Oh Hyun-Joo
Heo Chul-Ho
Park Inhye
author_sort Lee Saro
title A case study for the integration of predictive mineral potential maps
title_short A case study for the integration of predictive mineral potential maps
title_full A case study for the integration of predictive mineral potential maps
title_fullStr A case study for the integration of predictive mineral potential maps
title_full_unstemmed A case study for the integration of predictive mineral potential maps
title_sort case study for the integration of predictive mineral potential maps
publisher De Gruyter
series Open Geosciences
issn 2391-5447
publishDate 2014-09-01
topic gis
likelihood ratio
weight of evidence
logistic regression
artificial neural network
mineral potential mapping
url https://doi.org/10.2478/s13533-012-0183-y
work_keys_str_mv AT leesaro acasestudyfortheintegrationofpredictivemineralpotentialmaps
AT ohhyunjoo acasestudyfortheintegrationofpredictivemineralpotentialmaps
AT heochulho acasestudyfortheintegrationofpredictivemineralpotentialmaps
AT parkinhye acasestudyfortheintegrationofpredictivemineralpotentialmaps
AT leesaro casestudyfortheintegrationofpredictivemineralpotentialmaps
AT ohhyunjoo casestudyfortheintegrationofpredictivemineralpotentialmaps
AT heochulho casestudyfortheintegrationofpredictivemineralpotentialmaps
AT parkinhye casestudyfortheintegrationofpredictivemineralpotentialmaps
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