Analysis of space–time variability in agriculture and the environment with geostatistics

This paper gives an overview of space–time variability in agriculture and the environment. Analysis is based upon geostatistics in the framework of linear regression theory. Common procedures for spatial data are extended towards the space–time domain. Several practical studies are presented. The first study describes the use of REML to estimate semi-variogram models within the presence of trends. The second study describes the use of probability maps in an environmental statistical study. The third study describes the use of geostatistics in modelling the development of a disease in cabbage. Studies are evaluated using quadratic scoring rules.