IG-Mapper: A new ArcGIS® toolbox for the geostatistics-based automated geochemical mapping of igneous rocks

- A new ArcGIS® toolbox performing stochastic and deterministic statistical interpolation of geochemical data.
- Automated lithological mapping mirroring the main igneous rock classification diagrams by using Python scripting.
- Interpolation checking map tools investigating the effectiveness of the obtained results.

This work introduces a user-friendly, fast and effective tool for the automated geochemical mapping of igneous rocks, to provide a geospatial representation of petrological parameters through the application of either deterministic or stochastic interpolation techniques. The geostatistical approach allows mapping to be extended to areas where igneous rocks are hidden under sedimentary cover, also introducing an estimate of the interpolation reliability. This new GIS-based automated procedure, which is mostly constructed with the ArcGIS® Model-Builder as a graphical code designer, can generate three main types of outputs: 1) interpolation maps of major and trace elements, isotopic compositions, and derived parameters, to provide valuable geospatial information regarding the genetic and structural relationships between magmatic bodies; 2) lithological maps, that are based on the geostatistical interpolation of major element data and mirror the main geochemical classification diagrams of plutonic rocks; and 3) interpolation checking maps, which provide an estimate of the geostatistical interpolability for one specific parameter at a time. This last output is expressed in the form of an empirical index (Stochastic Interpolation Index), which highlights the randomness level of a specific value distribution. This automated lithological mapping function is an entirely new tool based on five original python scripts, which makes it possible to interpolate on a georeferenced map the compositions deriving from the most used geochemical classification diagrams. This new tool package is presented here by using a portion of the Serre Batholith in central Calabria (southern Italy), to illustrate the potential of this method to open new research perspectives in igneous petrology.

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