Shahed Shahrestani , David R. Cohen , Ahmad Reza Mokhtari
{"title":"比较 PCA 和 ICA 在土壤数据地球化学模式识别中的应用:塞浦路斯案例","authors":"Shahed Shahrestani , David R. Cohen , Ahmad Reza Mokhtari","doi":"10.1016/j.gexplo.2024.107539","DOIUrl":null,"url":null,"abstract":"<div><p>Multivariate analysis of soil geochemistry is a powerful tool for differentiating lithological units and detecting geochemical dispersion halos related to mineralization or contamination. While univariate analysis can effectively identify lithological units with pronounced variations, it may fail to differentiate between subtler variations in lithologies. Traditional multivariate techniques such as principal component analysis (PCA) have limitations, including difficulties in understanding the individual contributions of each variable and an inability to work with non-Gaussian data. Independent component analysis (ICA) has emerged as a potential alternative, as it can effectively identify independent components of non-Gaussian data. In this study, we compared the effectiveness of PCA and ICA in relating multivariate soil geochemistry to parent lithology using the Soil Geochemical Atlas of Cyprus and associated digital geological maps. Both PCA and ICA were able to differentiate between the ultramafic units within the Troodos Ophiolite (TO) and the Circum-Troodos Sedimentary Succession (CTSS). However, ICA was more effective than PCA in identifying pillow lavas, providing a clear separation in the scores for IC4 and IC5. Furthermore, both PCA and ICA were able to separate the sheeted dykes from the cumulate mafic units within the TO. The gabbro unit is closely defined by IC2 scores. In contrast, PCA failed to provide factors that effectively delineated the Mamonia Terrane from other units, especially the TO, while ICA was able to provide a distinct separation in IC4 and IC5 scores. Separation between the CTSS and Quaternary units was weakly observed in IC2 scores. These findings demonstrate that there is a difference in the effectiveness of PCA and ICA in identifying different lithological units and emphasize the need for a careful selection of multivariate methods to differentiate between subtle differences in soil geochemistry relating to variations in parent lithology.</p></div>","PeriodicalId":16336,"journal":{"name":"Journal of Geochemical Exploration","volume":"264 ","pages":"Article 107539"},"PeriodicalIF":3.4000,"publicationDate":"2024-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A comparison of PCA and ICA in geochemical pattern recognition of soil data: The case of Cyprus\",\"authors\":\"Shahed Shahrestani , David R. Cohen , Ahmad Reza Mokhtari\",\"doi\":\"10.1016/j.gexplo.2024.107539\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Multivariate analysis of soil geochemistry is a powerful tool for differentiating lithological units and detecting geochemical dispersion halos related to mineralization or contamination. While univariate analysis can effectively identify lithological units with pronounced variations, it may fail to differentiate between subtler variations in lithologies. Traditional multivariate techniques such as principal component analysis (PCA) have limitations, including difficulties in understanding the individual contributions of each variable and an inability to work with non-Gaussian data. Independent component analysis (ICA) has emerged as a potential alternative, as it can effectively identify independent components of non-Gaussian data. In this study, we compared the effectiveness of PCA and ICA in relating multivariate soil geochemistry to parent lithology using the Soil Geochemical Atlas of Cyprus and associated digital geological maps. Both PCA and ICA were able to differentiate between the ultramafic units within the Troodos Ophiolite (TO) and the Circum-Troodos Sedimentary Succession (CTSS). However, ICA was more effective than PCA in identifying pillow lavas, providing a clear separation in the scores for IC4 and IC5. Furthermore, both PCA and ICA were able to separate the sheeted dykes from the cumulate mafic units within the TO. The gabbro unit is closely defined by IC2 scores. In contrast, PCA failed to provide factors that effectively delineated the Mamonia Terrane from other units, especially the TO, while ICA was able to provide a distinct separation in IC4 and IC5 scores. Separation between the CTSS and Quaternary units was weakly observed in IC2 scores. These findings demonstrate that there is a difference in the effectiveness of PCA and ICA in identifying different lithological units and emphasize the need for a careful selection of multivariate methods to differentiate between subtle differences in soil geochemistry relating to variations in parent lithology.</p></div>\",\"PeriodicalId\":16336,\"journal\":{\"name\":\"Journal of Geochemical Exploration\",\"volume\":\"264 \",\"pages\":\"Article 107539\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Geochemical Exploration\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0375674224001559\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOCHEMISTRY & GEOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geochemical Exploration","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0375674224001559","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
A comparison of PCA and ICA in geochemical pattern recognition of soil data: The case of Cyprus
Multivariate analysis of soil geochemistry is a powerful tool for differentiating lithological units and detecting geochemical dispersion halos related to mineralization or contamination. While univariate analysis can effectively identify lithological units with pronounced variations, it may fail to differentiate between subtler variations in lithologies. Traditional multivariate techniques such as principal component analysis (PCA) have limitations, including difficulties in understanding the individual contributions of each variable and an inability to work with non-Gaussian data. Independent component analysis (ICA) has emerged as a potential alternative, as it can effectively identify independent components of non-Gaussian data. In this study, we compared the effectiveness of PCA and ICA in relating multivariate soil geochemistry to parent lithology using the Soil Geochemical Atlas of Cyprus and associated digital geological maps. Both PCA and ICA were able to differentiate between the ultramafic units within the Troodos Ophiolite (TO) and the Circum-Troodos Sedimentary Succession (CTSS). However, ICA was more effective than PCA in identifying pillow lavas, providing a clear separation in the scores for IC4 and IC5. Furthermore, both PCA and ICA were able to separate the sheeted dykes from the cumulate mafic units within the TO. The gabbro unit is closely defined by IC2 scores. In contrast, PCA failed to provide factors that effectively delineated the Mamonia Terrane from other units, especially the TO, while ICA was able to provide a distinct separation in IC4 and IC5 scores. Separation between the CTSS and Quaternary units was weakly observed in IC2 scores. These findings demonstrate that there is a difference in the effectiveness of PCA and ICA in identifying different lithological units and emphasize the need for a careful selection of multivariate methods to differentiate between subtle differences in soil geochemistry relating to variations in parent lithology.
期刊介绍:
Journal of Geochemical Exploration is mostly dedicated to publication of original studies in exploration and environmental geochemistry and related topics.
Contributions considered of prevalent interest for the journal include researches based on the application of innovative methods to:
define the genesis and the evolution of mineral deposits including transfer of elements in large-scale mineralized areas.
analyze complex systems at the boundaries between bio-geochemistry, metal transport and mineral accumulation.
evaluate effects of historical mining activities on the surface environment.
trace pollutant sources and define their fate and transport models in the near-surface and surface environments involving solid, fluid and aerial matrices.
assess and quantify natural and technogenic radioactivity in the environment.
determine geochemical anomalies and set baseline reference values using compositional data analysis, multivariate statistics and geo-spatial analysis.
assess the impacts of anthropogenic contamination on ecosystems and human health at local and regional scale to prioritize and classify risks through deterministic and stochastic approaches.
Papers dedicated to the presentation of newly developed methods in analytical geochemistry to be applied in the field or in laboratory are also within the topics of interest for the journal.