This work is part of a submission to Unearthed’s ExploreSA Gawler Challenge. The source code is posted at this link: Gawler Public Repository The ExploreSA Gawler Challenge is a contest to predict areas of potential mineralization in the Gawler region of South Australia. In this post I will lay some more of the groundwork for a computational approach to this mineral favorability mapping challenge. The SARIG data package contains a whole series of CSVs, sarig_md_*_exp.

This work is part of a submission to Unearthed’s ExploreSA Gawler Challenge. The source code is posted at this link: Gawler Public Repository The ExploreSA Gawler Challenge is a contest to predict areas of potential mineralization in the Gawler region of South Australia. In this post I will lay some of the groundwork for a computational approach to this mineral favorability mapping challenge. We’ll begin by loading some of the geochemistry data from the SARIG data package into Dask and extracting a smaller set of soil geochemistry records.

kRiging (Kriging in R) As a programmer, it is often frustrating to solve equations by hand, knowing that a clever implementation in software could solve an infinite variety of similar problems. This cannot be said for the paper-and-pen approach. As a <<Mastère spécialisé>> student in the Cycle de Formation Spécialisée en Géostatistique at Mines Paristech, I have spent the better part of these past few weeks building and solving kriging systems.