The interpretation of geochemical survey data

Grunsky, Eric

doi:10.1144/1467-7873/09-210

Cited by 217 publications

(91 citation statements)

References 104 publications

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“…Many of those now involved in mapping the chemical elements of the urban environment, they have brought with them the interpretative techniques that are used for the interpretation of geochemical survey data, particularly that for mineral exploration purposes (Grunsky, 2010). In particular, many of the case studies in this volume have used principal component Because of the nature of geochemical data some authors (e.g., Lax and Andersson -Chapter 14) express a preference for using non-parametric methods.…”

Section: Discussionmentioning

confidence: 99%

Urban Geochemical Mapping: A Review of Case Studies in this Volume

Johnson

Demetriades

2011

Mapping the Chemical Environment of Urban Areas

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The development and history of geochemical mapping in urban areas is summarised. Urban geochemical surveys are generally classified as being systematic or targeted. A summary of the case studies presented in this book considers the sampling strategies, the chemical and data analytical methods applied. The use of the terms urban area, baseline, background and guideline values is explored. Important issues such as legislative drivers, communicating the results and future trends are also discussed.

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Section: Discussionmentioning

confidence: 99%

Urban Geochemical Mapping: A Review of Case Studies in this Volume

Johnson

Demetriades

2011

Mapping the Chemical Environment of Urban Areas

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“…Log-ratio transformation of compositional data is recommended due to the problem with closure (Grunsky, 2010). Data normalization is also important due to the skewed nature of most geochemical data, the assumption with most statistical analyses that the population is normally distributed and to compensate for possible differences in median values between populations (e.g., datasets from different years).…”

Section: Multivariate Analysismentioning

confidence: 99%

“…R-mode (Cattell, 1966b;Akbarpour, Azizi, and Torab, 2013), Q-mode (Cattell, 1966b) and RQ-mode (Gabriel, 1971;Zhou, Chang, and Davis, 1983;Grunsky, 2010).…”

Section: High Dimensional Low Sample Size Datamentioning

confidence: 99%

“…This analysis is based on the guidelines in Grunsky (2010). EDA is an important step to ensure the quality of the data as it is the foundation of this research.…”

Section: Exploratory Data Analysismentioning

confidence: 99%

“…Geochemical leveling is the adjustment of the element concentrations of one dataset to similar values within a second dataset to account for non-geologically-based heterogeneity (Grunsky, 2007). The heterogeneity in a dataset may be cause by variation in the field sampling methods, lab protocols, and changes in lab instrumentation which would interfere with interpreting natural variations.…”

Section: Leveling Geochemical Datamentioning

confidence: 99%

See 2 more Smart Citations

Multivariate statistical analysis of lodgepole pine outer bark samples for metallic mineral exploration within the southern Nechako Plateau, British Columbia, Canada

Benz¹

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Dike distribution density: Method for quantitative mine targets prediction in the South Alatao Mountains area, NW China

Jing

Luo

et al. 2017

Geological Journal

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The correlation between dike density and regional‐scale mineralization indicates a fundamental criterion for ore‐forming process. Here, a novel dike distribution density method is formulated for evaluating this correlation and exploring mine targets quantitatively. Three parameters (dike density, dike orientation scatter degree and dike fractal dimension) are proposed to express the degree of irregularity and complexity of dike distribution patterns. This method is applied to the South Alatao Mountains area (China), where the dike swarms show regionally well‐developed density gradients and the mineral deposits are spatially associated with abundant dike swarms. On the basis of this quantitative dike distribution density method, 60% of the deposit targets are delineated in this area. This result indicates that the method is an effective quantification tool for prospecting mine targets. The dike distribution density method is applicable for areas where abundant regional‐scale dike swarms and mineralization occur. It should be considered as an effective and complimentary technique for the common mine prospectivity analysis.

show abstract

The interpretation of geochemical survey data

Cited by 217 publications

References 104 publications

Urban Geochemical Mapping: A Review of Case Studies in this Volume

Urban Geochemical Mapping: A Review of Case Studies in this Volume

Multivariate statistical analysis of lodgepole pine outer bark samples for metallic mineral exploration within the southern Nechako Plateau, British Columbia, Canada

Dike distribution density: Method for quantitative mine targets prediction in the South Alatao Mountains area, NW China

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