The implementation of the forthcoming European Union’s Soil Monitoring Law (SML) is expected to generate extensive soil-related datasets, presenting a historic opportunity to investigate spatial heterogeneity. Meanwhile, medical geology, an interdisciplinary field examining the links between geological factors and health outcomes in humans, animals, and plants, exhibits pronounced spatial heterogeneity. The emergence of ‘big data’ introduces both challenges and opportunities for advancing research in medical geology.

This study evaluates several techniques for measuring spatial heterogeneity, based on pilot studies. These include local statistics used to assess spatial variability of nickel (Ni) concentrations in Northern Ireland soils; local Moran’s I, which identifies spatial clusters and outliers of lead (Pb) in Galway soils; Getis-Ord Gi* hot spot analysis, which detects high-value hot spots and low-value cool spots for total organic carbon (TOC) and pH across European soils; and local correlation coefficients, which reveal spatially varying relationships, such as between lead (Pb) and aluminum (Al) in London soils, and between soil organic carbon (SOC) and elevation in Ireland showing positive correlations in blanket peat regions and negative correlations in basin peat areas.

The EU SML opens new avenues for medical geology research. By acknowledging spatial heterogeneity as an inherent environmental characteristic, big data enables a more nuanced, localized analytical approach. A shift from global to local perspectives is essential for effective data analytics in medical geology.
 

Soil Monitoring Law, Medical Geology, Big data, Spatial Heterogeneity