Geostatistics
Definition
Geostatistics is the broader discipline that underpins geostatistical analysis, uniting theory and practice around spatial random fields. It addresses sampling design, de‑trending, covariance modeling, and spatial simulation, informing how we collect, analyze, and present spatial data. The field balances mathematical rigor with practical constraints in real‑world sampling and computation.
Application
Beyond mining, geostatistics powers hydrogeology, soil mapping, epidemiology, and urban analytics. It helps determine where to measure next and how to combine disparate sources into coherent surfaces with quantified uncertainty.
FAQ
How is de‑trending different from normalization?
De‑trending removes large‑scale gradients so local spatial structure is modeled cleanly; normalization rescales values for comparability. Both may be used together.
Why simulate instead of only kriging the mean?
Simulations create ensembles capturing possible realities. They’re invaluable for risk metrics—exceedance probabilities or worst‑case planning.
How much data is enough?
Enough to resolve the variogram reliably. Pilot studies and adaptive sampling improve efficiency when budgets are tight.
Can multiple variables be modeled jointly?
Yes—co‑kriging or Bayesian hierarchical models leverage correlated variables like elevation or soil moisture to improve predictions.
SUPPORT
© 2025 GISCARTA