Many environmental scientists are analysing spatial data by geostatistical methods and
interpolating from sparse sample data by kriging to make maps. They recognize its merits in …

Geostatistics is essential for environmental scientists. Weather and climate vary from place
to place, soil varies at every scale at which it is examined, and even man-made attributes …

This fully revised third edition introduces geostatistics by emphasising the multivariate
aspects for scientists, engineers and statisticians. Geostatistics offers a variety of models …

Understanding spatial statistics requires tools from applied and mathematical statistics,
linear model theory, regression, time series, and stochastic processes. It also requires a …

Absolute principal component score/multiple linear regression (APCS/MLR) and positive
matrix factorization (PMF) were applied to a dataset consisting of 10 heavy metals in 300 …

This Brief takes readers, in particular environmental scientists, through the important steps of
a geostatistical analysis. Most properties of the environment, such as rainfall, plant nutrients …

With new chapters addressing spatial patterning in single variables and spatial relations,
this second edition provides guidance to a wide variety of real-world problems. Focusing on …

The variogram is a critical input to geostatistical studies:(1) it is a tool to investigate and
quantify the spatial variability of the phenomenon under study, and (2) most geostatistical …

Geostatistics involves the fitting of spatially continuous models to spatially discrete data.
Preferential sampling arises when the process that determines the data locations and the …

The series aims to: present current and emerging innovations in GIScience; describe new
and robust GIScience methods for use in transdisciplinary problem solving and decision …