Assessing geochemical anomalies using geographically weighted lasso

被引:21
|
作者
Wang, Jian [1 ]
Zuo, Renguang [2 ]
机构
[1] Chengdu Univ Technol, Coll Earth Sci, Chengdu 610059, Peoples R China
[2] China Univ Geosci, State Key Lab Geol Proc & Mineral Resources, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Geochemical exploration; Geochemical anomalies; Geographically weighted lasso; Uncertainty; UNDISCOVERED MINERAL-DEPOSITS; PORPHYRY COPPER-DEPOSITS; STAGED FACTOR-ANALYSIS; STREAM SEDIMENT DATA; POLYMETALLIC MINERALIZATION; REGIONAL EXPLORATION; PROSPECTIVITY; REGRESSION; IDENTIFICATION; MACHINE;
D O I
10.1016/j.apgeochem.2020.104668
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Geochemical patterns in the surficial media are complex because of the various processes involved in their formation. These processes may or may not relate to mineralization. Therefore, geochemical anomalies identified are usually subject to uncertainty. Geographically weighted lasso (GWL) was adopted in this study to model the non-stationary relationships between the geological/geographical features and geochemical patterns in the surficial media. The sparsity and reliability of regression coefficients in the GWL modeling renders it suitable for quantifying the controls that geological/geographical features have on geochemical patterns. This information can improve current knowledge about the complexity of geochemical patterns. A case study in which the GWL model was established between geological/geographical variables and the geochemical patterns of Cu observed in stream sediments in the Southwestern Fujian province of China was presented. The following findings were obtained: (1) geological features show a major control on the geochemical patterns of Cu in the studied area. However, the geochemical patterns of Cu have been modified to some extent by secondary processes, resulting in the relationships between geochemical signatures and mineralization becoming more complex and uncertain, and (2) the GWL modeling can provide useful information for evaluating geochemical anomalies, which can help reduce the uncertainty and benefit geochemical exploration at a later stage.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Quantifying the spatial characteristics of geochemical patterns via GIS-based geographically weighted statistics
    Wang, Haicheng
    Cheng, Qiuming
    Zuo, Renguang
    JOURNAL OF GEOCHEMICAL EXPLORATION, 2015, 157 : 110 - 119
  • [2] Identification of Geochemical Anomalies Using an End-to-End Transformer
    Yu, Shuyan
    Deng, Hao
    Liu, Zhankun
    Chen, Jin
    Xiao, Keyan
    Mao, Xiancheng
    NATURAL RESOURCES RESEARCH, 2024, 33 (03) : 973 - 994
  • [3] Recognition of geochemical anomalies based on geographically weighted regression: A case study across the boundary areas of China and Mongolia
    Tian, Mi
    Wang, Xueqiu
    Nie, Lanshi
    Zhang, Chaosheng
    JOURNAL OF GEOCHEMICAL EXPLORATION, 2018, 190 : 381 - 389
  • [4] Application of geographically weighted regression (GWR) and singularity analysis to identify stream sediment geochemical anomalies, case study, Takab Area, NW Iran
    Nazarpour, Ahad
    Paydar, Ghodratollah Rostami
    Mehregan, Fatemeh
    Hejazi, Seyed Jafar
    Jafari, Mohammad Amin
    JOURNAL OF GEOCHEMICAL EXPLORATION, 2022, 235
  • [5] Mapping geochemical anomalies related to Fe-polymetallic mineralization using the maximum margin metric learning method
    Wang, Ziye
    Dong, Yanni
    Zuo, Renguang
    ORE GEOLOGY REVIEWS, 2019, 107 : 258 - 265
  • [6] Recognition of geochemical anomalies using a deep variational autoencoder network
    Luo, Zijing
    Xiong, Yihui
    Zuo, Renguang
    APPLIED GEOCHEMISTRY, 2020, 122
  • [7] Implementations of Geographically Weighted Lasso in Spatial Data with Multicollinearity (Case Study: Poverty Modeling of Java']Java Island)
    Setiyorini, Anis
    Suprijadi, Jadi
    Handoko, Budhi
    STATISTICS AND ITS APPLICATIONS, 2017, 1827
  • [8] An adapted geographically weighted LASSO (Ada-GWL) model for predicting subway ridership
    He, Yuxin
    Zhao, Yang
    Tsui, Kwok Leung
    TRANSPORTATION, 2021, 48 (03) : 1185 - 1216
  • [9] Mineral Exploration Using Subtle or Negative Geochemical Anomalies
    Zuo, Renguang
    JOURNAL OF EARTH SCIENCE, 2021, 32 (02) : 439 - 454
  • [10] Recognition of geochemical anomalies using a deep autoencoder network
    Xiong, Yihui
    Zuo, Renguang
    COMPUTERS & GEOSCIENCES, 2016, 86 : 75 - 82