首页|GIS-based prospectivity-mapping based on geochemical multivariate analysis technology: A case study of MVT Pb–Zn deposits in the Huanyuan-Fenghuang district, northwestern Hunan Province, China
GIS-based prospectivity-mapping based on geochemical multivariate analysis technology: A case study of MVT Pb–Zn deposits in the Huanyuan-Fenghuang district, northwestern Hunan Province, China
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NSTL
Elsevier
<![CDATA[<ce:abstract xmlns:ce="http://www.elsevier.com/xml/common/dtd" xmlns="http://www.elsevier.com/xml/ja/dtd" class="graphical" xml:lang="en" id="ab005" view="all"><ce:section-title id="st005">Graphical abstract</ce:section-title><ce:abstract-sec id="as005" view="all"><ce:simple-para>Display Omitted</ce:simple-para></ce:abstract-sec></ce:abstract><ce:abstract xmlns:ce="http://www.elsevier.com/xml/common/dtd" xmlns="http://www.elsevier.com/xml/ja/dtd" class="author-highlights" xml:lang="en" id="ab010" view="all"><ce:section-title id="st010">Highlights</ce:section-title><ce:abstract-sec id="as010" view="all"><ce:simple-para id="sp0010" view="all"><ce:list id="l0005"><ce:list-item id="o0005"><ce:label>?</ce:label><ce:para id="p0005" view="all">Geochemical modelling using partial least-squares regression (PLS) method.</ce:para></ce:list-item><ce:list-item id="o0010"><ce:label>?</ce:label><ce:para id="p0010" view="all">Proxy predictors were established by PLS, singularity mapping, entropy process, and fault density.</ce:para></ce:list-item><ce:list-item id="o0015"><ce:label>?</ce:label><ce:para id="p0015" view="all">The geochemical models presented in Section are here geologically interpreted, and compared using the PLS and PCA methods.</ce:para></ce:list-item></ce:list></ce:simple-para></ce:abstract-sec></ce:abstract><ce:abstract xmlns:ce="http://www.elsevier.com/xml/common/dtd" xmlns="http://www.elsevier.com/xml/ja/dtd" class="author" xml:lang="en" id="ab015" view="all"><ce:section-title id="st015">Abstract</ce:section-title><ce:abstract-sec id="as015" view="all"><ce:simple-para id="sp0015" view="all">This paper demonstrates a partial least-squares regression (PLS) method for geochemical modelling, and then uses the models and geological favourable features to obtain mineral potential maps. The PLS is one of multivariate analysis technologies, which can identify variations in associations and correlations among geochemical elements and mineralisation. The method is here used to calculate principal components as well as to identify correlations between Pb–Zn (mineralization) and 25 stream sediment elements for constructing geochemical models in the Huayuan-Fenghuang district of northwestern Hunan Province, China. The models showing the distribution of geochemical anomaly are useful in interpreting the distribution of faults and the Cambrian Qingxudong Formation (ore-bearing formation), and to better define the architecture on mineralisation in the study area. In addition, the models and other favourable features (proxies) are easily integrated into single possibility map by Boost Weights-of-Evidence (Boost WofE) approach for targets.</ce:simple-para></ce:abstract-sec></ce:abstract>]]>
Mineral potential mapsPartial least squares regressionSingularity mappingBoost Weights-of-EvidenceMineral systems
Leon Bagas、Shengmiao Li、Xianglong Song、Yuan Cong、Kun Wang、Nan Li
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MLR Laboratory of Metallogeny and Mineral Resource Assessment, Institute of Mineral Resources, Chinese Academy of Geological Sciences
Mineral Branch of Hunan Institute of Geological Survey
NSTL
Elsevier
