TY - JOUR
T1 - GIS-based prospectivity-mapping based on geochemical multivariate analysis technology
T2 - A case study of MVT Pb–Zn deposits in the Huanyuan-Fenghuang district, northwestern Hunan Province, China
AU - Wang, Kun
AU - Li, Nan
AU - Bagas, Leon
AU - Li, Shengmiao
AU - Song, Xianglong
AU - Cong, Yuan
PY - 2017/12/1
Y1 - 2017/12/1
N2 - 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.
AB - 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.
KW - Boost Weights-of-Evidence
KW - Mineral potential maps
KW - Mineral systems
KW - Partial least squares regression
KW - Singularity mapping
UR - http://www.scopus.com/inward/record.url?scp=85031126281&partnerID=8YFLogxK
U2 - 10.1016/j.oregeorev.2017.09.015
DO - 10.1016/j.oregeorev.2017.09.015
M3 - Article
AN - SCOPUS:85031126281
VL - 91
SP - 1130
EP - 1146
JO - Ore Geology Reviews
JF - Ore Geology Reviews
SN - 0169-1368
ER -