Geostatistics emerged from the South African mining industry in the 1950s when Danie Krige noticed that simple averaging systematically overestimated ore grades. Georges Matheron formalized Krige's insights into a rigorous mathematical framework, creating kriging — the best linear unbiased predictor for spatially correlated data. Today geostatistics underpins resource estimation in mining, petroleum reservoir modeling, environmental remediation, precision agriculture, and epidemiological mapping.
These simulations let you explore the core geostatistical workflow: model spatial correlation with variograms, interpolate with kriging, map probabilities with indicator kriging, detect spatial clusters with Moran's I and LISA, and estimate block grades for mine planning. Each technique builds on the fundamental insight that nearby things are more alike than distant things — Tobler's First Law of Geography made mathematically precise.